UMEÅ UNIVERSITY MEDICAL DISSERTATIONSNew Series No 975 ISSN 0346-6612 ISBN 91-7305-909-9

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From Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden

Risk markers for a first myocardial infarction

Anna Margrethe Thøgersen

Umeå 2005

Copyright © 2005 by Anna Margrethe Thøgersen Department of Medicine, Public Health and Clinical Medicine, Umeå University,

Umeå, Sweden

Printed in SwedenPrint & Media, Umeå 2005:2001088

Fortune is not a terminus, but a continuous journey

Chinese proverb

Lykken er ikke en endestation, men en måde at rejse på.

Kinesisk ordsprog

To everybody

CONTENTS

ABSTRACT………………………………………………………………………4

ABBREVIATIONS…………………………………………….…………………5

ORIGINAL PAPERS………………………………………………………...…...6

INTRODUCTION………………………………………………………………...7

AIMS…………………………………………………………………………...…35

MATERIAL AND METHODS…………………………………………….....….36

RESULTS………………………………………………………………....………49

Study I

Study II

Study III

Study IV

DISCUSSION………………………………………………………………......…67

CONCLUSION…………………………………………………………...…..…..82

ACKNOWLEDGMENTS…………………………………………………..….....83

REFERENCES…………………………………………………………….…...…86

ABSTRACT

Risk markers for a first myocardial infarction

Anna Margrethe Thøgersen, Department of Public Health and Clinical Medicine, Umeå University, S-901 85 Umeå, Sweden.

The development of a first myocardial infarction is associated with a large number of contributing factors. Age, male sex, hypertension, smoking, diabetes, body mass index and hypercholesterolemia are considered as established risk factors. The primary aim of the present dissertation was to evaluate whether specific biomarkers could improve the prediction of subjects at risk for a first myocardial infarction when considered in addition to established cardiovascular risk factors. The biomarkers investigated include: tissue plasminogen activator (tPA), plasminogen activator inhibitor-1 (PAI-1), thrombomodulin (TM), von Willebrand factor (VWF), dehydroepiandrosterone sulfate (DHEAS), lipoprotein (a) (Lp(a)), leptin, apolipoproptein A1 (ApoA1), proinsulin, homocysteine and homozygosity for the 5,10-methylenetetrahydrofolate reductase (MTHFR) C>T genotype. A secondary objective was to determine whether a first myocardial infarction leads to increased plasma homocysteine concentrations and whether the association between homocysteine and myocardial infarction was greater at follow-up compared to baseline.

The study population consisted of 36 405 subjects screened and included in the Västerbotten Intervention Program and the Northern Sweden MONICA cohorts between January 1, 1985 and September 30, 1994. A nested incident case-referent study design was used. Seventy eight cases with a first myocardial infarction were identified, and from the same cohort twice as many sex and age matched referents were randomly selected. Moreover, a follow-up health survey (average 8.5 years between surveys) was conducted with 50 cases and 56 matched referents.

High plasma levels of tPA and PAI-1 mass concentration, VWF, proinsulin, leptin and Lp(a) and low plasma levels of ApoA1 were associated with subsequent development of a first myocardial infarction in univariate conditional logistic regression analysis. For PAI-1 and tPA, this relation was found in both men and women. For tPA, but not for PAI-1 and VWF, this association was independent of established risk factors. In women, high plasma concentrations of TM were associated with significant increases in risk of a first myocardial infarction. No predictive values of DHEAS, homocysteine or for the point mutation C677>T in the gene for MTHFR was found regarding the risk of a first myocardial infarction. The summarised importance of haemostatic and metabolic variables (proinsulin, lipids including Lp(a) and leptin) in predicting first myocardial infarction in men, as well as possible interactions among these variables, were studied. High tPA and Lp(a) and low ApoA1 remained significant risk markers in multivariate analysis independent of established risk factors. There were non-significant synergic interactions between high Lp(a) and leptin and tPA respectively, and between high Lp(a) and low ApoA1.

In the follow-up study plasma homocysteine and plasma creatinine increased significantly, and plasma albumin decreased significantly over time. Conditional univariate logistic regression indicated that high homocysteine at follow-up but not at baseline was associated with first myocardial infarction but the relation disappeared in multivariate analyses including plasma creatinine and plasma albumin. High plasma creatinine remained associated with first myocardial infarction at both baseline and follow-up.

In conclusion, the present results support the hypothesis that biomarkers, in addition to the traditional cardiovascular risk factors, carry predictive information on the risk of developing a first myocardial infarction.

Keywords: haemostatis, lipoprotein (a), MTHFR, homocysteine, proinsulin, leptin, apolipoprotein A1, DHEAS, myocardial infarction, risk factors.

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ABBREVIATIONS

ApoA1 apolipoprotein A1

CBS cystationine- -synthase

CI confidence interval

CV coefficient of variation

DHEAS dehydroepiandrosterone sulfate

DNA deoxyribonucleic acid

DBP diastolic blood pressure

EDTA ethylene diamine tetraacetate

ELISA enzyme-linked immunosorbent assay

GP glycoprotein

HDL high density lipoprotein

IL interleukin

LDL low density lipoprotein

Lp(a) lipoprotein (a)

MMP matrix metalloproteinase

MTHFR 5,10-methylenetetrahydrofolate reductase

MONICA Multinational Monitoring of Trends and Determinants in Cardiovascular Diseases

OR odds ratio

PAI-1 plasminogen activator inhibitor-1

SD standard deviation

SBP systolic blood pressure

TAFI thrombin-activatable fibrinolysis inhibitor

tHcy total plasma homocysteine

TNF tumor necrosis factor

TM thrombomodulin

tPA tissue plasminogen activator

uPA plasminogen activator urokinase

VIP Västerbotten Intervention Program

VWF von Willebrand factor

WHO World Health Organisation

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ORIGINAL PAPERS

This thesis is based on the following papers, which will be referred to by their Roman numerals.

Permission is granted to reprint all four papers in the thesis.

I. Thøgersen AM, Jansson JH, Boman K, Nilsson TK, Weinehall L, Huhtasaari F, Hallmans G.

High plasminogen activator inhibitor and tissue plasminogen activator levels in plasma precede a

first acute myocardial infarction in both men and women. Evidence for the fibrinolytic system as

an independent primary risk factor. Circulation 1998; 98: 2241-2247.

II. Thøgersen AM, Nilsson TK, Dahlén G, Jansson JH, Boman K, Huhtasaari F, Hallmans G.

Homozygosity for the C677 T mutation of 5,10-methylenetetrahydrofolate reductase and total

plasma homocyst(e)ine are not associated with greater than normal risk of a first myocardial

infarction in Northern Sweden. Coronary Artery Disease 2001; 12: 85-90.

III. Thøgersen AM, Søderberg S, Jansson J-H, Dahlén G, Boman K, Nilsson TK, Lindahl B,

Weinehall L, Stenlund H, Lundberg V, Johnson O, Ahrén B, Hallmans G. Interactions between

fibrinolysis, lipoproteins and leptin related to a first myocardial infarction. European Journal of

Cardiovascular Prevention and Rehabilitation 2004; 11: 33-40.

IV. Hultdin J, Thøgersen AM, Jansson J-H, Nilsson TK, Weinehall L, Hallmans G. Elevated plasma

homocysteine: cause or consequence of myocardial infarction? Journal of Internal Medicine 2004;

256: 491-498.

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INTRODUCTION

Epidemiology of myocardial infarction in Northern Sweden

Compared with the rest of Sweden, Northern Sweden has been characterized by a high incidence of

cardiovascular disease (1,2), and in an international 10-year comparison (3,4), Northern Sweden is

above the median rates of myocardial infarction for both men and women. The rate for a first

myocardial infarction among men aged 25-64 in Northern Sweden has been 250 per 100,000 during

1985-98, and the corresponding numbers for women have been about 66 per 100,000 in the same

age group (4). Cardiovascular diseases were identified as leading causes of morbidity and mortality

in northen Sweden during the 1970s and early 1980s (5).

Risk factor definition and cohort study

In Last´s Dictionary of Epidemiology (6), a risk factor is defined as “an aspect of personal behavior

or lifestyle, an environmental exposure, or an inborn or inherited characteristic, that, on the basis of

epidemiologic evidence, is known to be associated with health-related condition(s) considered

important to prevent”. This broad and rather loose definition leaves unanswered the issue of causal

role, strength of association, and modifiablility (7). Beck (8) has offered a more specific definition

of a risk factor as “an environmental, behavioral, or biologic factor confirmed by temporal

sequence, usually in longitudinal studies, which if present directly increases the probability of a

disease occurring, and if absent or removed reduces the probability”. Risk factors are part of the

causal chain, or expose the host to the causal chain. Once disease occurs, removal of a risk factor

may not result in a cure. Hill (9) have used different criteria for the probability of clinical causality

of which the most important are 1) temporality – the cause is present before the disease, 2) strength

of the relation – a stronger relationship means a greater probability of causality, 3) plausibility – the

relation has a biological rationale, 4) consistence – the relation is reproducible in different

populations and situations. Hill (9) suggested that the following aspects of an association can be

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considered in attempting to distinguish causal from non-causal associations: (1) strength, (2)

consistency, (3) specificity (4) temporality, (5) biologic gradient, (6) plausibility, (7) coherence, (8)

experimental evidence, and (9) analogy. A risk marker is an attribute or exposure that is associated

with an increased probability of disease, but is not necessarily a causal factor. A risk determinant is

an attribute or exposure that increases the probability of occurrence of disease or other specified

outcome. The relation could be causal, but this has not been proven. A modifiable risk factor is a

determinant that can be modified by intervention, thereby reducing the probability of disease (6).

Biologic interaction should be evaluated as departures from additivity of effect (10).

A cohort study is the analytical method of epidemiologic study in which subsets of a defined

population can be identified who are, have been, or in the future may be exposed or not exposed in

different degrees, to a factor or factors hypothesized to influence the probability of occurrence of a

given disease or other outcome (6). The main feature of cohort study is observation of large

numbers over a long period with comparison of incidence rates in groups that differ in exposure

levels (6). Generally, all the cases that are identified in the cohort are selected and included in a

nested case-referent study (11).

Myocardial infarction pathology: atherosclerotic plaques, platelet activation and the

fibrinolytic pathway

Virtually all-regional myocardial infarctions are caused by thrombosis developing on a culprit

coronary atherosclerotic plaque (12). The very rare exceptions to this are spontaneous coronary

artery dissection, coronary arteritis, coronary emboli, coronary spasm, and compression by

myocardial bridges (12).

The American Heart Association (AHA) has made a definition of advanced types of atherosclerotic

lesions and a histological classification of atherosclerosis (13). The initial (type I) atherosclerotic

lesion contains enough atherogenic lipoprotein to elicit an increase in macrophages and formation

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of scattered foam cells (13). The changes are more marked in locations of arteries with adaptive

intimal thickening. Type II lesions consist primarily of layers of macrophage foam cells and smooth

muscle with extracellular lipid deposits cells and include lesions grossly designated as fatty streaks

(13). Type III lesions consist of smooth muscle cells surrounded by extracellular lipid deposits. This

extracellular lipid is the immediate precursor of the larger, confluent, and more disruptive core of

extracellular lipid that characterizes type IV lesions (13). In type V lesions the lipid core contains a

thick layer of fibrous connective tissue. Some type V lesions are largely calcified (type Vb), and

some consist mainly of fibrous connective tissue and little or no accumulated lipid or calcium (type

Vc). Type VI lesions have fissure and/or hematoma, and thrombus (13). The lipid core in stage IV

is an extracellular mass of lipid containing cholesterol and its esters, some of which is in crystalline

form (12). The cholesterol ester composition of the atheromatous core is very similar to that of

circulating plasma-LDL, with a high fraction of cholesterol linoleate (14). Oxidized LDL and its

peroxide derivative, lysophosphatidylcholine, stimulate protein kinase C activity, phosphoinositide

turnover, and release of internal calcium. It also impairs endothelial cell replication and

angiogenesis, and induces apoptosis (15). The core is surrounded by numerous macrophages

derived from monocytes which cross the endothelium from the arterial lumen (12). They are highly

activated, producing procoagulant tissue factors and a host of inflammatory cell mediators. The

connective tissue capsule which surrounds this inflammatory mass is predominantly collagen

synthesised by smooth muscle cells (12). The current view of atherosclerosis is that the prime

stimulus for plaque inflammation is the reaction between oxidised LDL and the macrophage (12).

Thrombosis over plaques occurs because of two somewhat different processes. One is caused by an

extension of the process of endothelial denudation, while the second mechanism involves plaque

disruption (12). The fibrous cap is a dynamic structure within which the connective tissue matrix is

constantly being replaced and maintained by the smooth muscle cell (12). The inflammatory

process both reduces collagen synthesis by inhibiting the smooth muscle cell and causes its death by

apoptosis (12). Continued inflammation results in increased numbers of macrophages and

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lymphocytes emigrating from the blood into the lesion (14). Macrophages also produce a wide

range of metalloproteinases capable of degrading all the components of the connective tissue

matrix, including collagen (12). These metalloproteinases are secreted into the tissue in an inactive

form and then activated by plasmin (12). Metalloproteinase production by macrophages is

upregulated by inflammatory cytokines (12). Plaque disruption is therefore now seen as an auto-

destructive phenomenon associated with an enhanced inflammatory activation (12). When the

endothelium is physically disrupted or functionally perturbed, a prothrombotic and proinflammatory

state develops characterised by vasoconstriction, platelet and leukocyte activation and adhesion,

promotion of thrombin formation, coagulation and fibrin deposition at the vascular wall (16). Three

components need to interact to assure hemostasis: the vascular wall, the formed elements of the

blood and the plasmatic clotting and fibrinolytic systems.

The first event is platelet adhesion with a non-platelet surface, followed by platelet activation and

secretion. Adherent platelets release a varity of pro-inflammatory mediators and growth hormones

and have the potential to modify signaling cascades in vascular cells, inducing the expression of

endothelial adhesion receptors and the release of endothelial chemoattractants (17). In this manner

they might regulate the adhesion and infiltration of leukocytes, in particular that of monocytes, into

the vascular wall: a process which is thought to play a key role in acute and chronic inflammation

(17). von Willebrand factor (VWF) is secreted by platelets and facilitates adhesion of platelets to

vascular subendothelium. Also present is VWF that is secreted by the endothelium (17). A smaller

portion of VWF is secreted into the abluminal space where it adheres to collagen, while the

majority of VWF is released into the plasma compartment (17). Secondarily the reaction of the

plasma coagulation system results in fibrin formation (18) (Figure 1). Endothelial cells express

tissue factor procoagulant in response to inflammatory mediators and PAI-1 (19). Clot lysis and

vessel repair begin immediately after the formation of the definitive hemostatic plug (18). The

principal physiologic activators of the fibrinolytic system system, tissue plasminogen activator

(tPA) and plasminogen activator urokinase (uPA), diffuse from endothelial cells and convert

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plasminogen that is adsorbed to the fibrin clot into plasmin (18). Only a small quantity of each

coagulation enzyme is converted to its active form. Blood fluidity is maintained by the flow of

blood, the adsorption of coagulation factors to surfaces and their trapping in the emerging clot.

Multiple inhibitors in plasma also contribute such as antithrombin, protein C and S and tissue factor

pathway inhibitor (18). Protein C is converted to an active protease by thrombin after it is bound to

an endothelial cell protein called thrombomodulin (TM).

The fibrinolytic pathway

The main fibrinolytic components of plasma are plasminogen, t-PA, and urokinase-type

plasminogen activator (uPA) (20). tPA is the major plasminogen activator in plasma and uPA binds

to a cellular uPA receptor and is considered to participate in extravascular proteolysis (21).

Fibrinolysis involves the action of tPA and uPA on plasminogen, to produce plasmin, which in turn

degrades the cross-linked fibrin of a thrombus (22). The major inhibitors of fibrinolysis are PAI-1,

which inhibits tPA, 2-antiplasmin which neutralizes plasmin, and thrombin activatable fibrinolysis

inhibitor (TAFI) (23). In addition, tPA is inactivated by the slow inhibitors C1-inhibitor, 2-

antiplasmin and 2-macroglobulin (24,25). Expression of tPA, uPA, and PAI-1 is increased in the

atherosclerotic plaque, and these factors therefore may affect thrombotic events after plaque rupture

(23). Furthermore, the plasminogen system is involved in activation of matrix metalloproteinases

intimately involved in plaque stability and in tissue remodelling (23). Since fibrinolytic reactions

take place on the surface of the fibrin clot, fibrinolysis is locally restricted and does not become

systemic (20). The overall balance of tPA and PAI-1 in the circulation is such that PAI-1 is in

several-fold excess over tPA, so that most of the tPA circulates as tPA-PAI-1 complex (Figure 2)

(26). The balance can be changed subtly in normal individuals, for instance by the increase in tPA

concentration by virtue of release from endothelial cells in response to exercise or venous occlusion

(26). PAI-1, in particular, is variable within the normal population (26). Both tPA and

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Prothrombin

Extrinsic or Tissue-factor-dependent pathway Thrombomodulin

+ Thrombin

Xa Va Protein C

Protein S

Intrinsic or Activated contact system Protein C

Thrombin

Fibrinmonomer Cross-linked fibrin+

Plasminogen Plasmin

Fibrinogen

active tPA

PAI-1

Platelet

Platelet

von Willebrand factor Endothelial cells

Connective Connective tissue matrix

Lipidcore,LDL,Lp(a)

smooth muscle cell

Macro-phage

Figure 1. A simplified schematic diagram of the hemostatic and the fibrinolytic pathway and coronary artery disease.

PAI-1 show distinct circadian variations (26). In platelet-rich thrombi, PAI-1 provides an important

mechanism for controlling the activity of tPA (20).

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PAI-1 mass concentration

Active PAI-1

tPA/PAI-1 complex Active tPA

tPA mass concentration

PAI-1 PAI-1

tPA

Other

inhibitors

tPA tPA

Figure 2. Schematic presentation of the relation between tPA mass concentration and activity,

PAI-1 mass concentration and activity, and tPA/PAI-1 complex.

Tissue plasminogen activator

tPA is a serine protease synthesized in endothelial cells with gene expression mainly regulated at

the level of transcription (27). The release rate of tPA is subjected to a local regulation and the

systemic levels of tPA may not reflect the local profibrinolytic capacity in terms of availability of

active tPA at the organ level (28). The major determinant of how much active tPA is available in

the vascular bed of an organ, is proportional to the capacity of the endothelium to increase its

secretion of tPA when required (28). Ladenvall et al (29) recently identified a polymorphic Sp1

binding site in an enhancer at the tPA locus (tPA –7,351C/T), which was associated with vascular

tPA release. Subjects homozygous for the –7,351C allele had twice the tPA release rate compared

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to subjects carrying the –7,351T allele. However there was no significant correlation between

zygosity and systemic plasma tPA (29,30). The genes responsible for the genetic regulation of

plasma tPA remained to be determined and neither variation at the PLAT locus located on

chromosome eight nor the PAI-1 –675 4G>5G polymorphism are strong predictors of plasma tPA

levels (27). In healthy subjects, approximately 1/3 of plasma tPA is in an active, free form, and the

remaining part is complex bound (28). During basal conditions tPA is mainly released via a

constitutive secretory pathway, but a substantial amount of tPA can rapidly be released upon

stimulation (regulated release) (31). Substances released from activated platelets and products of the

coagulation process are potent triggers of stimulated tPA release (31). Release of tPA from vessel

wall is also stimulated by heparin, bradykinin, histamin, nicotinic acid, desmopressin, 1-desamino-

8-D-arginine-vasopressin (DDAVP), methacholine, doxazosin ( 1-inhibitor), prostacyclin,

epinephrine, stress, coffee, exercise, venous occlusion and ischemia (28,32,33). Circulating tPA is

cleared by the liver with a half-life of 3-5 minutes and clearance is proportional to liver blood flow

(34,35). Two receptors in the liver for tPA have been identified, the low-density lipoprotein

receptor-related protein and the mannose-dependent receptor (35,36,37). Active tPA is cleared by

both receptors and has a faster clearance than that of tPA/PAI-1 complex (37).

As free active tPA is difficult to measure in plasma (unless blood is collected into anticoagulants

specific for this purpose), most clinical studies have measured circulating tPA mass values (26,38).

tPA mass is mainly a marker of complex formation between tPA and its major plasma inhibitor

PAI-1, rather than a measure of free tPA (Figure 2).

PAI-1

PAI-1 is a glycoprotein that belongs to the serine protease inhibitor superfamily (serpins) (39). It

binds rapidly to tPA and to uPA, forming a stable complex with a ratio of 1:1 that is cleared from

the circulation by hepatic cells (20,39). The active form of PAI-1 is unstable, with a half-life of 30

minutes (20). Vitronectin has been identified as a protein that binds PAI-1 in plasma, stabilizes the

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active form and maintains a distribution between PAI-1 in plasma and in the extracellular matrix

(20, 40).

Although the principal source of plasma PAI-1 is unknown, available evidence indicates that

several cell types, including endothelial and vascular smooth muscle cells, platelets, macrophages,

hepatocytes, spleen cells, fibroblasts, and adipocytes, all have capacity to produce PAI-1 (39,41).

PAI-1 synthesis is stimulated by numerous agents, including thrombin, endotoxin, various

cytokines, Lp(a), insulin, oxidized LDL, and activation of the renin-angiotensin-aldosteron system,

among others (15,41). It is possible that different tissues are responsible for raised plasma PAI-1

depending on the actual condition (26). For instance, the acute-phase elevation of PAI-1 is

associated with hepatic synthesis, but the elevation that correlates with triglyceride levels may

reflect adipose tissue synthesis (26). The very marked elevation seen in sepsis is probably of

endothelial origin (26). Once produced, PAI-1 is generally secreted immediately, some of it binding

to proteins of the extracellular matrix, in particular vitronectin (26). The exposed reactive centre

loop in PAI-1 inserts spontaneously into the body of the molecule, generating a form known as

latent, because it can be re-activated in vitro by denaturation and subsequent refolding (26). This

loop insertion occurs much more slowly in the presence of vitronectin, which therefore stabilizes

PAI-1 activity (26). High local concentrations of PAI-1 mRNA have been demonstrated in

atherosclerotic plaques, in contrast to normal vessel walls, suggesting that local synthesis of PAI-1

in endothelial and smooth muscle cells is increased, as shown in cultured cells stimulated by

cytokines (26). Plasma levels of PAI-1 can be measured either as activity or as immunoreactive

PAI-1 mass. Both measurements require utmost care in blood collection and sample handling

because PAI-1 is a labile molecule (39). In addition, precautions must be taken to avoid release of

PAI-1 from platelets, which contain a large amount of mostly the inactive form (39). The PAI-1

activity assay detects free active PAI-1, whereas the PAI-1 mass assay measures free active PAI-1,

inactive latent PAI-1, and also inactive (complexed with tPA or uPA) PAI-1 (39) (figure 2).

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von Willebrand factor

Mature VWF is a multimeric glycoprotein composed of identical disulfide-linked subunits (42).

Plasma concentrations of VWF have a wide range, from 50 to 200% of normal. The two storage

organelles found in the cells that synthesize VWF are the Weibel-Palade body in endothelial cells

and the -granule in megakaryocytes and platelets (42). In megakaryocytes, only the regulated

pathway of VWF secretion is effectively operative in vivo. Thus, the VWF circulating in plasma is

essentially all of endothelial cell origin, as platelets release their -granule content only when

activated (42). The VWF secreted from endothelial cells, through either the constitutive or the

regulated pathway, is directed towards both the lumen and the subendothelial matrix (42).

Circulating VWF is cleared by the liver with a half-life of approximately 12 to 18 hours (43, 44).

Secretion is stimulated by a variety of agents, including histamine, thrombin and fibrin (45).

Vascular injury or stress increases VWF synthesis and VWF can fluctuate considerably in acute-

phase inflammatory responses (23,46,47). The VWF levels tend to increase with age and VWF

concentrations are also increased in patients with hypertension, diabetes, inflammatory vascular

disease, peripheral artery disease, exercise, pregnancy, malignancy, liver disease ande

hyperthyroidism (43,48-50).

Plasma VWF has three major activities: (1) mediating platelet adhesion to damaged arterial walls,

(2) mediating platelet aggregation at high shear stress, and (3) binding and stabilizing factor VIIIc

(23). Platelets adhere to VWF through IIb/IIIa glycoprotein receptors, which are usually available

for binding only after platelet activation (43). By serving as the carrier for factor VIII, VWF may

also coordinate formation of the fibrin (and platelet)- rich thrombus at the site of endothelial cell

injury. VWF may mediate initial platelet adhesion to the subendothelium by linking to specific

platelet membrane receptors (glycoprotein Ib-IX complex) and to constituents of subendothelial

connective tissue. Through multiple functional domains, each VWF subunit has binding sites for

collagen, heparin, glycoprotein (GP) Ib, GPIIb/IIIa and factor VIII (43).

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Thrombomodulin

Thrombomodulin is an endothelial cell surface receptor for thrombin that functions as an

anticoagulant by greatly accelerating thrombin-induced activation of protein C (51) (Figure 1). The

activity of activated protein C is enhanced by its co-factor protein S, which is synthesized by

endothelial cells, among other cell types (15). Binding of thrombin to thrombomodulin also

dampens the enzyme´s ability to activate platelets, factor V, factor XIII, and fibrinogen and

promotes endothelial cell fibrinolytic activity (15). Thrombomodulin also inhibits prothrombinase

activity indirectly by binding factor Xa (15). Binding of thrombin to thrombomodulin accelerates its

capacity to activate a protein known as thrombin-activatable fibrinolysis inhibitor (TAFI or

procarboxypeptidase B) (15,52). TAFI cleaves when activated by basic carboxyterminal residues

within fibrin and other proteins. This results in the loss of plasminogen/plasmin and tPA binding

sites on fibrin resulting in retarded fibrinolysis (15). Thus, through the regulated expression of

thrombomodulin, endothelial cells also serve as a potent template to decrease the rate of

intravascular fibrinolysis (15). Thrombomodulin has also been found to exhibit anti-inflammatory

properties. In part, this is mediated by protein C activation, but thrombin activation of endothelial

cells contributes to a variety of inflammatory events. This includes the expression of P selectin on

the endothelial cell surface and the formation of the neutrophil agonist, platelet-activating factor.

The ability of thrombomodulin to block these activities has an indirect antiinflammatory effect

(52,53). Various inflammatory cytokines downregulate thrombomodulin gene transcription and

accelerate thrombomodulin internalization, while at the same time promoting tissue factor

expression and shedding of endothelial cell protein C from the endothelium (15,52). Inflammation

leading to downregulation of thrombomodulin, decrease in TAFI activation and increased

complement activation could work together to injure the vessel wall and expose coagulant

phospholipid surfaces (53). A soluble, truncated form of thrombomodulin circulates in plasma, but

its significance is unknown (51).

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Dehydroepiandrosterone sulfate (DHEAS)

Dehydroepiandrosterone (DHEA) and its sulphated form (DHEAS) are produced in the adrenal

cortex and are converted to androgens and oestrogens in peripheral tissues (54). DHEAS

concentration is 100- to 500-fold higher than that of testosterone and 1000 to 10 000 times greater

than that of estradiol (55). DHEA and DHEAS, however, do not possess intrinsic estrogenic or

androgenic activity (55). DHEAS binds strongly to albumin (56). These inactive precursor steroids

are converted into active androgens and estrogens in peripheral target tissues, a process that

depends on the specific expression of the steroidogenic enzymes in each of these tissues (55). In

epidemiological studies, concentrations of DHEAS rather than DHEA have been used, as DHEAS

has been shown to have a longer half-time and little diurnal variation (57). DHEA inhibition of

mammalian glucose 6-phosphate dehydrogenase, which is the entry point into the pentose

phosphate pathway, might provide a plausible biological site of action for the various stages at

which DHEA might interfere with the atherogenic process (57,58). It may affect adherence of

platelets and macrophages, the release of chemoattractants and growth factors, the proliferation of

cellular elements or the uptake of cholesterol into the atheroma (57). DHEA may also reduce local

free radical generation by macrophages (57). In 1996, Beer et al (59) reported that 2 weeks of oral

DHEA administration reduces plasma PAI-1 and tPA mass concentration in men, however the

precise physiological functions of DHEAS are uncertain.

Lp(a)

Lp(a) is a complex serum lipoprotein composed of a LDL particle linked by its surface

apolipoprotein (apo) B-100 via a disulfide bond to an unique and highly polymorphic glycoprotein,

apo(a) (60). Apo(a) shares extensive structural homology with plasminogen, and consists of a non-

functional serine protease domain, a variable number of multiple repeats of kringle IV, and a single

copy of kringle V (51). The variable number of kringle IV repeats is due to varying number of

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copies within the apo(a) gene, and results in at least 35 different molecular weight isoforms (51).

Plasma Lp(a) levels are largely genetically determined (61), and vary inversely with apo(a) isoform

size. Levels increase in patients with renal disease (51). The presence of multiple interleukin-6

responsive elements may explain the transient increase in Lp(a) levels observed during acute

inflammatory states (62). In contrast to plasma LDL levels, Lp(a) levels are unaffected by diet,

physical activity, and most lipid-lowering agents (51). On the other hand, estrogen replacement

therapy and high-dose niacin can lower plasma Lp(a) levels (51). Lp(a) competes for the binding of

plasminogen to endothelial cells, which may contribute to the prothrombotic effects of this

lipoprotein (15). Lp(a) has been implicated in the regulation of PAI-1 expression in endothelial

cells, and shown to inhibit endothelial surface fibrinolysis, to attenuate plasminogen binding to

platelets, to be a possible attractant of macrophages in the atheromatous plaque, to be associated

with smooth muscle cell proliferation and to bind to plaque matrix components (63). Lp(a)

accumulates in atherosclerotic lesions, but it is not found in normal vessels (64). Lp(a) binds avidly

to the extracellular matrix and, once trapped, becomes susceptible to modifications by oxidative

processes and by the action of lipolytic and proteolytic enzymes (64). Hence, Lp(a) lipoprotein may

acquire a pathogenic profile on entering the arterial wall as a consequence of modifications effected

by factors operating in the inflammatory milieu of the atheromatous vessel (64).

Apolipoprotein A1

Apolipoprotein A1 is the major constituent of high density lipoprotein (HDL) and mediates efflux

of cholesterol from the peripheral cell membranes (65). In addition, ApoA1 activates lecithin-

cholesterol acetyl transferase, a key enzyme in the reverse transport of cholesterol from peripheral

tissues to the liver (65). ApoA1 concentration is mainly determined by genetic factors (65). Because

of the close association between apolipoproteins and serum lipids, measurement of ApoA1 has been

proposed as an important factor in predicting the risk of cardiovascular disease (65).

19

Homocysteine

Homocysteine is a sulfhydryl amino acid derived from the metabolic conversion of the essential

amino acid methionine (15,66 and Figure 3). The entry point of the pathway is the transport of

dietary methionine derived from protein food sources into the cellular space (67). It exists both in

free and protein-bound forms and is oxidized in plasma to the disulfides homocysteine-

homocysteine (homocystine) and homocysteine-cysteine (mixed disulfide). Free and protein-bound

homocysteine and its disulfides are globally referred to as total homocysteine (tHcy) or

homocyst(e)ine (66). About 70-80% of plasma homocysteine is bound to albumin, 20-30% is

oxidized to disulfides, and only approximately 1% is present as free homocysteine (66). The

intracellular metabolism of homocysteine occurs through enzymatic pathways that are dependent on

vitamins as cofactors or cosubstrates (Figure 3). There are two pathways of remethylation of

homocysteine to methionine and one pathway of trans-sulfuration to cysteine. In the remethylation

pathway catalyzed by methionine synthase, cobalamin acts as a cofactor and the methyl group is

donated by 5-methyl-tetrahydrofolate, the major form of folate in plasma, derived from the

reduction of 5,10-methylenetetrahydrofolate by methylenetetrahydrofolate reductase (MTHFR). In

the other remethylation pathway, which is active mainly in the liver, betaine is the methyl donor and

the reaction is catalyzed by betaine-homocysteine methyltransferase. In the trans-sulfuration

pathway, homocysteine is transformed by cystationine- -synthase (CBS) to cystathionine, with

pyridoxal-5`-phosphate, a vitamin B6 derivate, acting as a cofactor. Vitamin B6 is also necessary for

transformation of cystathionine to cysteine and alpha-ketobutyric acid (66). There are several

inherited disorders that lead to hyperhomocysteinemia (67). The most common is the 5-

methylenetetrahydrofolate reductase (MTHFR) polymorphism due to a point mutation on

chromosome 1, where folate-deficient individuals will develop hyperhomocysteinemia (67).

Cystathionine -synthase deficiency (homocystinuria), methionine synthase deficiency, and

MTHFR enzyme deficiency are rare autosomal recessive disorders that are associated with

20

hyperhomocysteinemia and vascular thrombosis (67). Moderate elevations of plasma tHcy levels

are not found in all subjects with genetic defects causing a 50% reduction of the corresponding

enzyme activities, indicating that their phenotypic expression can be influenced by other factors

(66). Major determinants of plasma homocysteine levels include diet (vitamin B12, B6 and folate

intake) and renal function (68,69). The plasma levels of homocysteine increase with age, are lower

in fertile women than in men and increase after menopause (66,69). Other, less well established

determinants of hyperhomocysteinemia are cigarette smoking, hypercholesterolemia, lack of

physical exercise, coffee and alcohol consumption (66). Drugs interfering with the metabolism of

folate (e.g. methotrexate and various anticonvulsants), cobolamin (e.g. nitrous oxide), and of

vitamin B6 (e.g.theophylline), can cause moderate hyperhomocysteinemia (66). Estrogens,

tamoxifen, penicillamine and acetylcysteine reduce plasma homocysteine levels (66). An enzyme

immunoassay has become commercially available, which allows homocysteine measurements in

non-specialized clinical laboratories (70).

The adverse effects of homocysteine include vascular endothelial injury, smooth muscle

proliferation, oxidation of low-density lipoprotein cholesterol, and induction of a prothrombotic

vascular endothelial microenvironment (71,72). Homocysteine has growth-promoting and collagen

production-stimulating effects on vascular smooth muscle cells and inhibitory effects on endothelial

cell growth (73-75). Homocysteine induces oxidative stress and activates matrix metalloproteinases

(76). Homocysteine alters the normal antithrombotic phenotype of the endothelium by enhancing

the activities of factor XII and factor V and depressing the activation of protein C (72).

Homocysteine also inhibits the expression of tissue factor, and suppresses the expression of heparan

sulfate by the endothelium (72). Homocysteine has been shown to reduce binding sites for tPA in

cultured endothelial cells and reduce tPA activity by as much as 60% (77). In vitro data report a

decrease in fibrinolytic activity in the presence of homocysteine due to increased binding of Lp(a)

to fibrin and stimulation of PAI-1 production in endothelial cells (78,79); in cultured cells, however,

homocysteine does not alter the secretion of PAI-1 (79). In vitro, homocysteine inhibits cell surface

21

expression of thrombomodulin (80). There are several possible biologic mechanisms whereby an

elevated homocysteine level might exert a deleterious effect on vascular function. Homocysteine

may have pro-oxidant effects, it can diminish nitric oxide-mediated vasodilatation, and it may

promote thrombosis or impede fibrinolysis (69). Less frequently discussed is the possibility that

elevated homocysteine may also diminish adenosine formation (81): adenosine being an important

cardiac vasodilator as well as a vasoconstrictor in the renal vascular bed (82).

The mechanism(s) by which hyperhomocysteinemia might contribute to atherogenesis and

thrombogenesis are incompletely understood. Recently, Jakubowski (83) proposed a mechanism of

cellular damage mediated by homocysteine that could lead to cardiovascular disease. Homocysteine

thiolactone, one of homocysteine´s metabolites, is chemically reactive and acylates free amino

groups of lysine residues, resulting in protein modification and cellular damage. Homocysteinylated

proteins loose their biologic activity, and homocysteine-thiolactone is known to be toxic to

endothelial cells, factors that may be involved in the early development of atherosclerosis. This

mechanism is very specific, because homocysteine-thiolactone can be produced only from

homocysteine, and does not require concentrations higher than the physiologic concentrations of

homocysteine (83).

22

Remethylation Remethylation

Methionine

THF Dimethylglycine

AdoMet

R

RCH3

Methylene-THF B12

AdoHcy

Methyl-THF Betaine Betaine

MS

Homocysteine

BHMT

MTHFR

Serine

CBSB6

Cystathionine

-cystathionaseB6

Cysteine

Trans-sulfuration

Figure 3. Schematic representation of homocysteine metabolism. THF: tetrahydrofolate; MTHFR: methylenetetrahydrofolate reductase; MS: methionine synthase; AdoMet: S-adenosylmethionine;AdoHcy: S-adenosylhomocysteine; BHMT: Betaine homocysteine methyltransferase; CBS: cystathionine- -synthase; B12: vitamin B12; B6: vitamin B6. Adapted from Reference 66 with permission.

23

MTHFR

5,10-methylenetetrahydrofolate reductase (MTHFR) is a folate-dependent enzyme and is essential

for the remethylation of homocysteine (84) (Figure 3). In 1988, Kang et al (85) described a

thermolabile variant of MTHFR that is associated with decreased enzyme activity and mildly

elevated plasma homocysteine levels. The responsible mutation in the MTHFR gene, a cytosine (C)

thymine (T) substitution at base pair 677 leading to the exchange of an alanine to a valine, was

identified by Frosst et al in 1995 (86). A modification of the effect of this mutation by plasma levels

of folate has been described, indicating that an increased level of total plasma homocysteine (tHcy)

as a consequence of the mutation occurs only if plasma levels of folate are low (87). Brattstrøm et al

(68) reported from a meta-analysis of 23 studies that the prevalence of the TT genotype varied

between 5.4% and 16% in the different groups of control subjects and between 6.5% and 29.7% in

the different groups of patients. In the meta-analysis by Klerk et al (88) the TT genotype varied

between 3.2 % and 30.2 % (mean 10.2 %) among control subjects.

The metabolic syndrome

There are 6 major components of the metabolic syndrome: abdominal obesity, atherogenic

dyslipidemia, elevated blood pressure, insulin resistance ± glucose intolerance, a proinflammatory

state, and a prothrombotic state (89) or low fibrinolytic activity (90). In addition, research shows

that other components not routinely measured commonly aggregate with the major components:

elevated apolipoprotein B, small LDL particles, elevated C-reactive protein, and variation in

coagulation factors (eg, elevated PAI-1, VWF and fibrinogen) (89,91). At least 3 organizations have

recommended clinical criteria for the diagnosis of the metabolic syndrome; the World Health

Organization (WHO), the American Association of Clinical Endocrinologists (AACE) and The

National Cholesterol Education Program´s Adult treatment Panel III (ATP III) (92). The clinical

criteria proposed by ATP III are abdominal obesity, elevated triglycerides, low HDL cholesterol,

24

high blood pressure and high fasting glucose (89). When 3 of 5 of the characteristics are present, a

diagnosis of metabolic syndrome can be made (92). Explicit demonstration of insulin resistance is

not required for diagnosis: however most persons meeting ATP III criteria will be insulin resistant

(92). Insulin resistance was defined as 1 of the following: type 2 diabetes, impaired fasting glucose

(IFG), impaired glucose tolerance (IGT), or for those with normal fasting glucose values (<110

mg/dL or < 6.1 mmol/L), a glucose uptake below the lowest quartile for background population

under hyperinsulinemic, euglycemic conditions. The conference on the definition of the metabolic

syndrome identified 3 potential etiologic categories: (1) obesity and disorders of adipose tissue, (2)

insulin resistance, and (3) a constellation of independent factors (eg, molecules of hepatic, vascular,

and immunologic origin) that mediate specific components of the syndrome (89). Adipose tissue is

recognized as a source of several molecules that are potentially pathogenic: excess non-esterified

fatty acids, cytokines (tumor necrosis factor- ), resistin, adiponectin, leptin, and PAI-1 (89).

Visceral adipose tissue may be particularly active in producing several of these factors (89).

However, the mechanisms underlying the association between abdominal obesity (particularly

visceral obesity) and the metabolic syndrome are not fully understoood and likely are complex (89).

The second pathogenic category, insulin resistance, is widely believed to be at the heart of the

metabolic syndrome, even though there is as yet little clinical trial evidence that a reduction in

insulin resistance will substantially improve any of the components of the metabolic syndrome

other than glucose intolerance (89). Thus, the mechanistic link between insulin resistance and most

of the components of the metabolic syndrome remains unclear (89). Although insulin resistance is

strongly associated with atherogenic dyslipidemia and a proinflammatory state, it is less tightly

associated with hypertension and the prothrombotic state (89). Much of the heterogeneity in the

manifestation of the metabolic syndrome may therefore be due to the fact that many of the

component factors are regulated independently of insulin resistance (89). Lipoprotein metabolism is

regulated by genetic factors as well as by diet composition, and both can worsen atherogenic

dyslipidemia (89). Blood pressure regulation is similar complex and affected by dietary factors,

25

physical activity, and renal/adrenal organ function (89). Other important modifiers also influence

clinical expression of the metabolic syndrome. For example, physical inactivity promotes the

development of obesity and modifies muscle insulin sensitivity (89). Aging is commonly

accompanied by a loss of muscle mass and by an increase in body fat, particularly accumulation of

fat in the abdomen; both changes can increase insulin resistance (89). Moreover, recent studies

suggest that aging is accompanied by specific defects in fatty acid oxidation in muscle, also

enhancing insulin resistance (89). Men with the metabolic syndrome are at increased risk for

coronary heart disease (93).

Insulin and proinsulin

Insulin, which is produced by cells in pancreatic islets of Langerhans, consists of 51 amino acids

contained within two peptide chains: an A chain with 21 amino acids and a B chain with 30 amino

acids (94 and Figure 4). A precursor molecule, preproinsulin, is produced in the endoplasmic

reticulum and cleaved by microsomal enzymes to yield proinsulin almost immediately after its

synthesis. Proinsulin is transported to the Golgi apparatus, where packaging into clathrin-coated

secretory granules takes place. Proinsulin consists of a single chain of 86 amino acids containing 3

disulphide bridges, and includes the A and B chains of the insulin molecule plus a connecting

segment of 35 amino acids. Maturation of the secretory granules is associated with loss of the

clathrin coating and conversion of proinsulin to insulin and C-peptide by proteolytic cleavage. Two

endoproteases, proconvertase 2 and 3, cleave proinsulin at the AC and BC junctions. Further

processing by carboxypeptidase H results in the removal of the two pairs of dibasic amino acids

located at the two cleaved junctions to give the des forms of partially processed proinsulin, as

shown in Figure 4 (94). C-peptide and insulin are produced when enzymatic cleavage is complete at

both junctions. As a small amount of proinsulin produced by the pancreas escapes cleavage partially

or totally, normal mature secretory granules contain insulin and C-peptide in equimolar quantities,

plus 2 to 6 % of intact and split proinsulins (94). Approximately 50 % of insulin is removed in a

26

Figure 4. Processing of pro-insulin to insulin and C-peptide.

Adapted from D. Chevenne et al (94) with permission.

27

single pass through the liver, while proinsulin is mainly eliminated by the kidneys (94). Therefore,

the half-live for proinsulin is longer (90 min versus 3-5 min for insulin) (94). This allows

proinsulins to accumulate in the blood where they account for 15-20 % of the total amount of

insulin and proinsulins in the basal state (94), whereas in noninsulin dependent diabetes mellitus

circulating proinsulin is known to be disproportionately elevated compared to insulin (95,96).

As proinsulin conversion has a preferred sequential route, with cleavage at the BC junction

occurring first, the two major proinsulins in plasma are intact proinsulin and des 31,32 proinsulin,

far exceeding other barely detectable 65,66 products (94). Proinsulins have 5-10 % of the

bioactivity of insulin (94).

Insulin is the master regulator of glucose and lipid metabolism (97,98). Insulin increases the uptake

of glucose in muscle and fat and inhibits hepatic glucose production, thus serving as the primary

regulator of blood glucose concentration (97,98). Insulin also stimulates cell growth and

differentation, and promotes the storage of substrates in fat, liver and muscle by stimulating

lipogenesis, glycogen and protein synthesis, and inhibiting lipolysis, glycogenolysis and protein

breakdown (98). Insulin has recently been shown to exert an anti-inflammatory effect on human

aortic endothelial cells in vitro and mononuclear cells in humans in vivo (99). These effects were

reflected in the suppression of the expression of intercellular adhesion molecule-1 and monocyte

chemoattractant protein-1 and in the intranuclear binding activity of nuclear factor- B (which

induces the transcription of proinflammatory genes like TNF- and IL-6) in human aortic

endothelial cells, with a concomitant fall in plasma concentration of PAI-1 (99). Moreover, insulin

has the ability to induce the release of nitric oxide (NO) and to enhance the expression of

constitutive nitric oxide synthase (NOS) (100). The ability of insulin to induce an acute release of

nitric oxide from endothelial cells and to increase the expression of nitric oxide synthase in these

cells is associated with an acute vasodilatory effect (100). Two other proinflammatory transcription

factors, activator protein-1 and early growth response gene-1 (Egr-1), were also suppressed, along

with their respectively regulated genes, matrix metalloproteinase (MMP)-2, MMP-9, and tissue

28

factor (99). Thus, the action of insulin may not only be anti-inflammatory in general; it may be

particularly relevant to atherosclerotic plaque rupture in which MMPs play an important role: in the

initiation of thrombosis, in which tissue factor is a major trigger; and fibrinolysis, which is inhibited

by PAI-1 (99).

Leptin

Leptin circulates as a 16-kDa protein and is partially bound to plasma proteins (101). An additional

pool of leptin is bound to tissue-binding sites and is likely to contribute to the maintenance of

steady-state plasma leptin levels (101). Leptin is synthesized mainly by white adipose tissue, but

also in placenta, ovary, gastric fundic mucosa, skeletal muscle, bone marrow and mammary

epithelium, and is cleared by the kidneys (101,102). Structural analysis indicates that leptin is

similar to cytokines (101,102). The long form leptin receptor is present in hypothalamic regions,

whereas the short leptin receptor isoforms are expressed in choriod plexus, vascular endothelium,

platelets, macrophages, lymphocytes and peripheral tissues, such as kidney, liver, heart, lung, small

intestine, pancreas, adrenal gland, spleen, skeletal muscle and gonads (101,102,103). Leptin inhibits

appetite and weight gain by decreasing orexigenic and increasing anorexigenic peptide expression

in the hypothalamus (101). Plasma leptin levels correlate with fat stores and respond to changes in

energy balance (101). Leptin levels are regulated by insulin, glucocorticoids, testosterone,

oestrogens, endotoxin, cytokines, insulin-like growth factor-1 (IGF-1), growth hormone,

somatostatin, catecholamines, alcohol and smoking (102). Furthermore, it has been shown that

leptin is related to platelet aggregation (104), PAI-1 production (105), endothelial nitric oxide

release (106), vascular calcification (107), angiogenesis (102) and stimulates free fatty acid

oxidation (102). In lean persons, roughly 50% of leptin is present in the bound form, whereas

mostly free leptin is present in the circulation of obese people (103). Hyperleptinemia is thought to

be indicative of leptin resistance, which may play a role in the development of obesity (101). Leptin

29

levels increase acutely during inflammation and regulate T-cell responses, polarizing T-helper cells

towards a T-helper 1 phenotype (108). Thus increased leptin production, during obesity, may exert

a proinflammatory influence (108).

Overview of prospective studies

tPA

A meta-analysis on all seven available prospective cohort studies in general populations of tPA and

risk of myocardial infarction (2119 cases and 8832 controls in total) showed a combined odds ratio

of 2.18 (1.77-2.69) in the top third versus those in the bottom third of baseline tPA values after

adjustment for age and sex only, and this fell to 1.47 (1.19-1.81) after further adjustment for

smoking, blood pressure, blood lipids and body mass index (38). The mean weighted age at entry

was 54 years and mean weighted follow-up was 8 years (38). All studies used enzyme-linked

immunoassays, and all used plasma samples.

PAI-1

A meta-analysis of the five previous prospective studies of PAI including our own study (109 - 112)

involved a total of 833 coronary heart disease cases and 3122 controls (38). They had a mean

weighted age at entry of 58 years and mean weighted follow-up of 5 years. One study measured

latent and free, active PAI-1 (112), two measured PAI-1 mass (109 and our study I), one used

chromogenic assay of PAI-1 activity (110), and one did not specify the assay method used (111).

There was no significant heterogeneity among the five seperate studies, and a combined analysis

yielded an odds ratio of 0.98 (0.53-1.81) in individuals in the top third versus those in the bottom

third of baseline PAI-1 values (38).

30

von Willebrand Factor

Danesh et al (47) has updated an earlier meta-analysis of prospective studies of VWF (which adds

2445 cases of coronary heart disease to the previous total of 1524 cases) and found an odds ratio of

1.23 (95 percent confidence interval, 1.14 to 1.33), which is propably weaker than the previous

estimate of about 1.5 (95 percent confidence interval, 1.1 to 2.0) (46). In the recently published

PRIME study (113) including 296 cases and 563 controls, VWF was an independent risk factor for

fatal and nonfatal myocardial infarction. Individuals with plasma VWF levels in the highest quartile

showed a 3.04-fold increase in the risk of fatal and nonfatal myocardial infarction compared with

those in the lowest quartile (95% CI, 1.59 to 5.80) after adjustment for body mass index, total

cholesterol, HDL cholesterol, systolic blood pressure, smoking, alcohol, and diabetes. After further

adjustment for inflammatory variables (fibrinogen, C-reactive protein, tumor necrosis factor – and

interleukin –6) the odds ratio in the highest quartile increased to 3.40 (95% CI, 1.65 – 7.02).

Thrombomodulin

The ARIC study including 258 cases and 753 controls found a strong inverse association of soluble

thrombomodulin with incident coronary heart disease where rate ratio of the highest quintile of

soluble thrombomodulin compared with the lowest quintile was 0.29 (96% CI 0.15-0.57) after

adjustment for age, sex, etnic origin, study center, smoking, systolic blood pressure, total

cholesterol, HDL cholesterol, triglycerides, diabetes, and body mass index (114). However, in the

prospective PRIME study (113) there was no association between plasma thrombomodulin and

coronary heart disease.

Dehydroepiandrosterone sulfate (DHEAS)

Several prospective studies have examined the relationship between DHEAS levels and

cardiovascular disease, but results have been inconsistent and conflicting, generating much debate

and controversy on this issue (55 - 57,115,116).

31

Apolipoprotein A1

A number of prospective studies have shown the value of plasma ApoA1 in predicting coronary

heart disease (65,117-120).

Lp(a)

Prospective studies of Lp(a) as a cardiovascular risk factor have yielded conflicting results, but a

meta-analysis including 18 prospective cohort studies (4044 cases) showed that the relative risk of

coronary heart disease comparing top and bottom thirds of baseline measurements was 1.7

(p<0.0001), without significant heterogeneity (121). The interpretation of these data is however

complicated by the different methodologies used in measuring plasma Lp(a) and the lack of

standardization (122).

Insulin

A meta-analysis of 17 studies on hyperinsulinemia and risk of cardiovascular disease (1639 cases)

resulted in an estimated summary relative risk of 1.18 (95% CI 1.08 to 1.29) (123). The relationship

between hyperinsulinemia and cardiovascular disease was modified by ethnic background (stronger

longitudinal relationship in white than in non white populations) and by type of insulin assay

involved (123).

Proinsulin

Three prospective studies have found proinsulin to be an independent predictor of coronary heart

disease (124-126). Dunder et al (124) included 251 men cases and 1108 men control men during

28.7 years follow-up and found a hazard ratio of 1.46 (95% CI 1.20 – 1.76) for development of fatal

and nonfatal myocardial infarction. Zethelius et al (125) included a population based cohort of 874

men with a follow-up of 27 years. Intact proinsulin was an independent predictor of coronary heart

32

disease mortality with hazard ratio 1.31 (95% CI 1.12 to 1.53). Yudkin et al (126) reported that the

sum of proinsulin-like molecules predicted the incidence of coronary heart disease with a

standardised odds ratio 1.54 (95 % CI 1.07 to 2.20) after adjustment for age and body mass index in

a cohort of 1181 non-diabetic men 50-64 years old during 10-14 years follow-up.

Leptin

Only limited prospective data are available for leptin as a cardiovascular risk factor (127,128). In

our previous report (129), in which we used other sets of variables and statistical models, leptin was

found to be an independent risk marker for a first myocardial infarction. Couillard et al. (127) found

in a group of 86 non-diabetic men matched for age, body mass index, smoking, and alcohol intake,

that hyperleptinemia was not an independent risk factor for ischemic heart disease, defined as effort

angina, coronary insufficiency, nonfatal myocardial infarction, or coronary death. In the larger

prospective WOSCOP study (128) including 377 men cases, was plasma leptin a risk factor for

coronary heart disease independent of body mass index, age, lipids, systolic blood pressure, and

fasting glucose.

Homocysteine

Wald et al (130) reported on 16 prospective studies including 3144 cases with death from ischaemic

heart disease or non-fatal myocardial infarction a summary odds ratio of 1.23 (95% CI 1.14 to 1.32)

for a 5 µmol/L increase in serum homocysteine, adjusted for age, sex, smoking, cholesterol

concentration, and blood pressure. An individual patient data meta-analysis of observational studies

of tHcy up to January 1999 and cardiovascular disease by the Homocysteine Studies Collaboration

(131) reported on 12 prospective studies including 1968 cases with nonfatal or fatal myocardial

infarction or occlusive coronary artery disease. After adjustment for age, sex, smoking, total

cholesterol levels, systolic blood pressure and regression dilution in the prospective studies, a 25%

lower usual (corrected dilution bias) homocysteine level (about 3 µmol/L) was associated with an

33

11% (OR 0.89; 95% CI 0.83-0.96) lower risk of ischemic heart disease. However the variation in

the level of control for confounding factors in the studies included in these reviews raises the

possibility that the combined relative risk estimates from these meta-analyses may not be reliable.

O´Leary et al (132) also concluded that failure to adjust for creatinine in meta-analysis of

homocysteine and cardiovascular disease could result in an overestimate of risk.

MTHFR

Klerk et al (88) conducted a meta-analysis of individual participant data from all observational case-

control studies (retrospective or nested case-control) with data on the MTHFR 677 C>T genotype

and coronary heart disease as an endpoint. Data were obtained from 40 (34 published and 6

unpublished) observational studies, involving a total of 11162 cases and 12758 controls. Individuals

with the MTHFR 677 C>T genotype had a 16% (OR 1.16; 95% CI 1.05 to 1.28) higher risk of

coronary heart disease compared with individuals with the CC genotype. There was a significant

heterogeneity between the results obtained in European populations, compared with the North

American populations, which might largely be explained by interaction between MTHFR 677 C>T

polymorphism and folate status (88). There was also significant heterogeneity between the pooled

estimates of prospective and retrospective studies. The pooled OR for coronary heart disease for the

TT genotype compared with the CC genotype was 0.86 (95% CI 0.67 to 1.10) for prospective

studies (5 studies involving 1288 cases and 1749 controls), and 1.21 (95% CI 1.10 to 1.33) for

retrospective studies (35 studies involving 9874 cases and 11009 controls).

34

AIMS

The general aims of the present dissertation were:

- To evaluate whether the biomarkers: tPA, PAI-1, VWF, TM, DHEAS, ApoA1,

homocysteine and MTHFR could improve the prediction of subjects at increased risk for a

first myocardial infarction in addition to established cardiovascular risk factors (I-II).

- To investigate the summarised importance of haemostatic and metabolic variables (insulin,

lipids including lipoprotein (a) (Lp(a)) and leptin) in predicting first myocardial infarction,

and to explore potential synergistic interactions among these variables (III).

- To test the hypothesis that a first myocardial infarction leads to increased plasma

homocysteine concentrations and that the association between homocysteine and myocardial

infarction is greater at follow-up compared to baseline (IV).

35

MATERIAL AND METHODS

Study population

When Northern Sweden applied for membership in the WHO MONICA study in 1984, the high

prevalence of cardiovascular disease in the region had become a great concern in the population as

well as among policy makers and healthcare providers (5). A Västerbotten County Council task

force was selected, representing both preventive medicine and public health, in order to advise in

the planning and implementation process of a coming community-oriented cardiovascular disease

prevention programme. In early 1985 both the monitoring Northern Sweden MONICA Project and

the preventive Västerbotten Intervention Program (VIP) was launched (133). The VIP health survey

was designed to fit the MONICA criteria so that it would be possible to refer to MONICA data

when evaluating the community intervention programme (134).

The Västerbotten Intervention Program

In the Västerbotten Intervention Program (VIP) intended for health promotion of the population in

the county of Västerbotten (approx. 254,000 inhabitants), all men and women were invited to a

health survey at their local primary health care center the year they became 30, 40, 50, and 60 years

of age (135). Between January 1, 1985 and September 30, 1994, 31 680 persons participated in the

VIP health surveys. Selection bias in the VIP study was examined in 1992 and 1993 (136,137).

During those two years a total of 24 870 eligible persons were at the appropriate ages (30, 40, 50,

60 years). Of those, 14 188 took part in the health survey (57%). In order to get information about

age, employment, education level and socio-economic group of the non-participants of the VIP

survey, a record linkage was made between the data from all invited and the 1990 population and

housing census. Overall, the differences were small between participants and non-participants, with

marginal differences in socio-economic groups and educational levels. However, the youngest

group (30 years) and the unemployed were less prone to participate (46.0% and 42.5% participants,

respectively). To estimate the overall risk factor status among the VIP participants, a comparison

36

was made against a reference population. In the 1990 and 1994 MONICA surveys a random sample

of Västerbotten County population (aged 25-64 years) was screened. The participation rate was

more than 75%. Data from the two MONICA surveys were pooled and used as a reference group

for risk factor comparison. There were no significant differences between VIP and MONICA

participants in mean BMI and smoking status. The mean level of total cholesterol was lower among

the VIP participants. However, the MONICA participants had lower blood pressure (except for

diastolic blood pressure in men) (136,137).

The WHO MONICA study

The WHO MONICA Study started in the beginning of the 1980s in 26 countries (138). The

objective of the study was to measure trends in cardiovascular mortality and disease (3,138). To

allow comparison of rates between different populations, data collection should be done with

uniform diagnostic criteria and quality assurance procedures. The Northern Sweden MONICA

Study started 1985 in Västerbotten and Norrbotten counties, with a total population of 510 000 (291

000 aged 25-64 years) (136). Population surveys for cardiovascular risk factors were performed in

1986, 1990, 1994 and 1999. At each survey, a random sample (stratified for age and sex) of 2000

individuals aged 25-64 years was invited and more than 75% participated. Between January 1, 1985

and September 30, 1994, 4725 participated in three MONICA screening surveys.

Baseline examination

Baseline examination for cardiovascular risk factors was performed in the VIP and MONICA

surveys and included measurement of blood pressure, height, weight and cholesterol. Participants in

both surveys were requested to donate blood samples to be stored at the Northern Sweden Medical

Research Bank for future research purposes. More than 90% donated blood samples. Participants

were also asked to fill in a questionnaire with items on social background, lifestyle factors including

37

diet, smoking habits, medical history and intake of drugs among other. Informed consent was

collected from the start of the project and all projects were reviewed and approved by the local

research ethics committee (135).

Case definition and exclusion

A diagnosis of myocardial infarction was confirmed if the event met World Health Organisation

MONICA criteria, definition 1 (3) (for relevant section of MONICA Manual see URL:

www.ktl.fi/publications/monica/manual/part4/iv-1.htm). A definite myocardial infarction meets

one of the following criteria: definite serial ECG progression (defined by the Minnesota criteria) or

at least one cardiac enzyme level more than twice the upper limit of normal in the local laboratory

either with typical symptoms and abnormal ECG or with an ECG progression labelled probable and

atypical symptoms. For fatal myocardial infarctions we also accepted diagnoses based on

necropsies and on deaths confirmed by records as being due to coronary heart disease (ICD-9 411-

414). Silent myocardial infarctions found on routine examination were not included, as they could

not be assigned an accurate date of occurrence.

Case findings are based on reports from hospitals and general practitioners and on screening of

hospital discharge registers and all death certificates. Annually, computer-based lists of discharge

diagnoses from acute-care hospitals and nursing homes are screened for additional cases (138).

Only cases with a first definite myocardial infarction and no known cancer were included.

Accordingly, cases were excluded if they had been registered for a previous myocardial infarction

or stroke according to the MONICA registry or cancer according to the regional cancer registry. If

the questionnaires or patient records revealed information of a possible prior stroke, myocardial

infarction or cancer, the diagnosis was validated and if appropriate, the case was excluded.

38

Referent definition and exclusion

Two referents were randomly selected amongst the participants in the VIP or MONICA surveys

who had donated a blood sample to the Northern Sweden Medical Research Bank. They were

matched for sex, age (± 2 years), date of health survey (± 1 year), type of survey (VIP or MONICA)

and geographical region (same screening center). Referents were excluded if they had died or had

moved out of the MONICA region before September 30, 1994, if they had reported a prior

myocardial infarction or stroke according to the Northern Sweden MONICA Incidence Registry or

on the survey questionnaire, or if myocardial infarction or stroke might have occurred before the

health survey and could not definitely be excluded based on the case record (139).

Case and referent finding

All cases and referents were collected from the VIP and MONICA study base and fulfilled the

inclusion and exclusion criteria stated above. Two referents were identified and matched to each

case according to the principles described (see Figure 5 for a schematic overview).

Study I - III

According to the VIP health surveys and the three MONICA screening surveys during January 1

1985 and September 30, 1994, a total of 243 myocardial infarction cases were reported in the

MONICA incidence registry (139) (Figure 5). Ninety-two fulfilled the following two criteria: 1)

The cases were registered in the Northern Sweden MONICA Incidence registry during the period of

January 1, 1985 to September 30, 1994, and 2) The cases participated in the VIP or MONICA

health surveys prior to the myocardial infarction event, and on those occasions had donated blood

samples to the Northern Sweden Medical Research Bank. Individuals were excluded if they had a

cancer diagnosis according to the regional cancer registry or if the blood sample was inadequate for

analysis. For study I, 78 cases remained after exclusion. 156 matched referents were identified.

39

In study II the presence of the mutation C677>T in the MTHFR was determined for 69 of the 78

cases of myocardial and 129 of their referents, from which DNA for analysis was available.

In study III women were excluded due to few cases and because of significantly different leptin and

Lp(a) levels compared to men. Consequently, study III comprised of 62 men cases and 124 men

referents.

Study IV

This is a follow-up study of the 78 participants developing a first myocardial infarction and their

referents. The first health surveys for the participants in the present study occurred between April

1988 and November 1993, and the follow-up examinations were performed between July 1997 and

February 2001. The time interval between the two screening episodes had a mean of 8.4 1.8 years

(SD) for cases and 8.7 1.7 years (SD) for referents (unpaired t-test: p=0.5). Fifty cases had their

fasting total plasma homocysteine level repeated at follow-up. Of the 28 cases not participating in

the follow-up survey, 24 had died in the interim, 1 had severe dementia, 1 had terminal cancer, 1

had relocated outside the catchment area and 1 was lost to follow-up. Cases were matched with one

referent subject for age (± 2 years), sex, date (± 1 year), type (MONICA or VIP) of health survey,

and geographical region. Three cases had no matching control subjects in the follow-up

examination, and 7 cases had two matching referent subjects. Two additional referent subjects were

used without corresponding cases. Thus, for the conditional logistic regression analysis, 40 cases

with one referent and 7 cases with two referents were included in study IV.

40

Measurements of body mass index and blood pressure

Subjects were weighted without shoes in light indoor clothing. Height was measured without shoes.

Body mass index (BMI) was calculated as (weight in kg)/(height in m2). In the MONICA project

blood pressure was measured twice in every person after a five-minute rest with the subject in the

sitting position using the random zero method (Hawksley Gelman Ltd, Lancing UK) (140). The

mean value of the two measurements was used in the present study. In the VIP survey, blood

pressure was measured after 5 minutes rest in recumbent position. An adjustment was made to the

sitting posture based on comparison between sitting and recumbent position in 1850 subjects from

the VIP health survey (139)

41

Initialinclusion

Cases:- MI in MONICA registry Jan 1, 1985- Sep 30 1994

- Blood sample in the Northern Sweden Medical Bank

92

Referents: - 2 randomly selected referents/case, matched for sex, age (±2years) - No MI according to MONICA Jan 1, 1985 – Sep 30, 1994 - Blood sample in the Northern Sweden Medical Bank

Exclusion

Cases:

- MI according toMONICA, but inaddition, previous MIbefore Jan 1, 1985.

- Cancer according to theNational Cancer Register

- Missing blood samples

Referents:

- Dead before Sep 30, 1994- Cancer according to the regional

cancer registry- Moved out from the province

before Sep 30, 1994- If statement of “prior MI” in

survey questionnaire or if, frompatient file, a MI/stroke beforesurvey not could be excluded

- 6

- 6

- 2

86

80

78 156 Cases Referents

Study base: All participants in the Västerbotten Intervention Program or the Northern Sweden MONICA surveys

Figure 5. Adapted from reference 139 with permission.

42

Estimations of smoking status, presence of diabetes and hypertension

This information was obtained from the self-reported questionnaire answered at the health

screening. Smokers were defined as those who reported smoking cigarettes, cigars, or pipe on a

daily basis. Non-smokers were those who reported occasional smoking or never had smoked (139).

Presence or absence of diabetes was based on the self-reported data. Reported hypertension was

defined as having ever received information from a physician or nurse about having high blood

pressure. Anti-hypertensive medication was defined as treatment with blood pressure lowering

drugs within 14 days prior to screening. Hypertension was defined as systolic blood pressure 160

mmHg and/or diastolic blood pressure 95 mmHg and/or reported use of antihypertensive

medication during a period of 14 days before the health survey.

Blood sampling

The 20 ml whole blood sample was taken after four hours of fasting (20%) or on the morning after

overnight fasting (80%) in the VIP and MONICA cohorts. Subjects in the MONICA surveys, in

addition, had been instructed not to use tobacco and to avoid strenuous physical activity before the

examination. The blood sample is divided into 10 subsamples consisting of six plasma, two

leucocyte (buffy coat) and two erythrocyte samples, each containing 1.5 ml (135). Plasma was

obtained by centrifugation at 1500g for 15 minutes, aliquoted, and was initially stored frozen at -

20° C and then transferred to -80° C at the Medical Biobank at Umeå University Hospital until

analysis. In some instances, samples were stored at -20˚ C for up to 1 week and then transferred to -

80˚ C. Venous blood samples for hemostatic assays, DHEAS, insulin variables, apolipoprotein A1,

apolipoprotein B, Lp(a), leptin, homocysteine, MTHFR, creatinine and albumin were drawn, with a

minimum of stasis in sitting position, into evacuated glass tubes (Venoject) containing 1/100

volume of 0.5 mmol/L EDTA. The organization of the bank includes specially trained staff and an

organization of standardized transport, storage, and security facilities. For DNA handling a

43

specialized laboratory were established (135). Blood specimens from cases and referents were

analyzed in triplets of one case and two referents, the position was varied at random within each

triplet to avoid systemic bias and interassay variability. The investigators and laboratory staff had

no knowledge of case and referent status.

Measurement of serum cholesterol,

In the VIP survey serum cholesterol was measured by enzymatic methods using Reflotron bench-

top analyzers (Boehringer Mannheim GmbH Diagnostica, Germany) at each health survey center at

the time for the screening. The mean interassay coefficient of variation (CV) was 2.6%. An

enzymatic method (CHOD-PAP, Boehringer Mannheim GmbH Diagnostica, Germany) performed

at Umeå University hospital was used in the MONICA survey. To evaluate the two methods 180

subjects were analyzed with both benchtop analyzer and the enzymatic method. The mean value for

each method differed by 0.04 mmol/L and the correlation coefficient between the methods was

0.90. Total cholesterol values were adjusted based on these results, using the enzymatic method as

standard (137).

Laboratory procedures

Measurement of fibrinolytic factors

The mass concentration of tPA and PAI-1 in plasma were determined with an ELISA (25). Reagent

kits (Imulyse) were purchased from Biopool AB. For tPA mass concentration, the CV at 8 µg/L was

9.5% in our hands (n = 34) and 10% according to the manufacturer. For PAI-1 mass concentration,

the CV is 9% according to the manufacturer.

Measurement of von Willebrand factor, soluble thrombomodulin and DHEAS

44

VWF was measured with an ELISA (141) by use of reagents purchased from DAKO. The values

are expressed as percent of the value obtained in a pool of normal subjects (n = 20). For VWF, the

CV at a level of 138% was 11.7% in our hands (n = 41). TM was measured with an ELISA method

(142) purchased from STAGO, France. The interassay CV was below 8.6% (143). Plasma DHEAS

was measured directly in diluted plasma with a radioimmunoassay with an antiserum obtained from

Endocrine Sciences and raised against DHEA-SO4-17-oxime-BSA. 7-3H-DHEAS was used as a

tracer, and free and bound radioactivities were separated by means of ammonium sulfate

precipitation.

Measurement of apolipoprotein A-1, apolipoprotein B, Lp(a) and leptin

Apolipoprotein A1 was measured at a hospital laboratory with a commercial radioimmunoassay

research kit (RIA-100, KABI Pharmacia, Uppsala, Sweden). The interassay CV was 5.7%

according to the manufacturer. Apolipoprotein B was determined with our own enzyme-linked

immunosorbent assay (ELISA) (144). The interassay CV was 6.8%. The results correlated well

(0.97) with those of a previously used commercial radioimmunoassay method (RIA-100, Kabi

Pharmacia, Uppsala, Sweden). Lipoprotein(a) was measured by the specific protein(a) content with

our own ELISA technique (144). A catching monospecific polyclonal (a) antibody was used. The

results were identical (r = 0.98) whether a detecting monospecific antibody against Apo(a) or

against Apo B-100 was used. The mean interassay CV was 6.6% and 7.7% at Lp(a) concentrations

of 40 mg L-1 and 300 mg L-1, respectively. Leptin analysis was performed using a double-antibody

RIA with rabbit antihuman leptin antibodies, 125I-labelled human leptin as tracer, and human leptin

as standard (Linco Res., St Louis, MO, USA) (129). Interassay CV was 1.9% at low levels (< 5ng

mL-1) and 3.2% at high levels (10 – 15 ng mL-1).

45

Measurement of insulin, proinsulin and specific insulin

Insulin was measured using a microparticle enzyme immunoassay (MEIA) (Abbott Laboratories,

IL, USA) (129). The CV was 6.7% at the level of 7.9 mU L –1. The insulin assay measures total

immunoreactive insulin, which is comprised primarily of proinsulin and its conversion

intermediates.

The proinsulin level was measured using a highly sensitive two-site sandwich ELISA (145,146).

The assay is based on two monoclonal antibodies, a mouse anti-human C-peptide antibody (PEP-

001) and a mouse anti-human insulin antibody (HUI-001). The detection limit in human serum is

0.25 pmol/L. There was no cross-reactivity with human insulin and human C-peptide. However, the

four major proinsulin conversion intermediates reacted in various proportions of 65% to 99%. The

specific insulin level was measured in a similar manner using another sensitive two-site sandwich

ELISA (147). The assay is based on one monoclonal antibody with its epitope near the C-terminal

end of the B-chain (OXI-005) and one monoclonal antibody with its epitope centered around the A-

chain loop (HUI-018). The detection limit is 5.0 pmol/L. The specificity of the assay excludes intact

proinsulin, split(32-33), and des(31.32) proinsulin. There was a cross-reactivity with the less

frequently occuring split(65-66) proinsulin (30%) and des(64,65) proinsulin (63%).

Measurement of homocysteine, creatinine and albumin

In study II total plasma homocysteine was measured by high-pressure liquid chromatography using

electrochemical detection. The preparation of samples included reduction of disulfide bonds with

dithiothreitol and deproteinization with trichloracetic acid. In the concentration range 10-50 µmol/L

the interassay CV was 3.6%. In study IV total plasma homocysteine was measured using a

fluorescence polarization immunoassay on an IMx (Abbott Laboratories, Abbott Park, Il, USA)

(148). Inter- and intraassay coefficients of variation (CV) were 1.31 % and 1.42 % at a mean plasma

homocysteine level of 12.8 mol/L, and 2.10 % and 1.00 %, respectively at a mean plasma

46

homocysteine level of 25.7 mol/L. Plasma creatinine and plasma albumin concentrations were

determined using the Vitros DT60 II dry chemistry system (Ortho-Clinical Diagnostics, NJ, USA).

Genotyping

DNA was extracted according to a method published by Ma et al (149) after lysis of cells,

deproteinization with perchlorate, and extraction with chloroform and resin, using the Nucleon

DNA extraction kit (Nucleon Biosciences, Coatbridge, UK). The DNA samples were subjected to

amplification by the polymerase chain reaction, and restriction enzyme HinfI was used to identify

those with the point mutation C677>T in the gene for MTHFR, as described by Frostt et al (86).

Statistics

Mean values and standard deviations (SD) or frequencies for baseline cardiovascular risk factors

were calculated for cases and referents by unpaired t tests, Fisher´s exact test and chi-square tests as

appropriate (Study I - IV). Prevalences of alleles and genotype among cases and referents were

counted and compared by chi-square test with Hardy-Weinberg prediction (150) (Study II). Possible

relations between study variables were explored by Spearman or Pearson correlation analysis

(Study II, III). To test the relation between increasing levels of risk factors and the risk of

myocardial infarction, the sample was categorized into quartiles, tertiles or dichotomized by the

distribution of the referent values, or based on clinically relevant levels (Study I, II, III). A chi-

square test for trends was employed to assess relationships between different levels of the respective

variables and risk of myocardial infarction (Study I, II, III). Conditional logistic regression analysis

was used when estimating odds ratios (OR) and 95% confidence interval (CI) (Study I-IV) to

account for the matching variables and potential confounding factors simultaneously (151). Missing

values for categorical variables were treated as a separate category (omitted from tables) in the

analysis (Study I-IV). In the conditional logistic regression analysis Apo B was excluded as a

traditional risk factor due to high correlation with serum cholesterol (r=0.74) (Study I, III). Based

47

on the results of the Spearman correlation analysis and the univariate logistic regression analysis,

the variable hypertension replaced systolic and diastolic blood pressure, and proinsulin replaced

insulin and specific insulin, in the multivariate conditional logistic regression analysis (Study I, III,

IV). The presence of interaction was assessed by conditional logistic regression between high and

low plasma levels of tPA, ApoAI, Lp(a), leptin and proinsulin in relation to the risk of a first

myocardial infarction (Study III). Cut-off values were selected according to the distribution of the

referent values, and missing values were considered unexposed and thus assigned to the lower

category for tPA, PAI-1, VWF, TM, Lp(a), leptin and proinsulin, and the higher category for

ApoA1 and DHEAS (Study I, III). The empirical criterion of interaction is a departure from

additivity of effects of each of the risk determinants (152). Synergy index scores (SI) were therefore

calculated, which give the ratio of the combined effects to the sum of the effects of two risk factors

(153). The mathematical formula is as follows: SI = (OR ”high-high”-1)/(OR ”high-low” + OR

”low-high” – 2). A Synergy index score exceeding 1.0 indicates the presence of synergistic

interaction. All calculations were performed using the SPSS statistical program (Chicago, Il, USA)

version 6.1 (Study I-III) and version 11.0 (study IV) and STATA (College Station, TX, USA)

version 5.0 (Study III) and 7.0 on a Macintosh computer (Study III) and the EGRET software

package (SERC, Seattle, Wasington, USA) (Study I-IV). With a total of 78 cases and 156 referents,

it is estimated that for a statistical power of 80%, OR > 3.0 will be significant at the 5% level when

exposure prevalence is 10% and OR > 2.3 will be significant at the 5% levels when exposure

prevalence is 30% (Study I). With a total of 69 cases and 129 referents and a 5% prevalence of the

MTHFR mutation, for a statistical power of 80%, odds ratios above 4.3 for +/+ versus –/– and

above 2.4 for +/– versus –/– would be significant at the 5% level (Study II). With a total of 50 cases

and 56 referents, it was estimated that for a statistical power of 80%, a difference in total plasma

homocysteine concentration of 1.5 mol/L between the two groups at the first and the second

examination would be significant at the 5% level (study IV).

48

RESULTS

Study I

In this study, haemostatic factors (PAI-1, tPA, VWF and TM) and DHEAS were investigated as

predictors for a first myocardial infarction. Acute myocardial infarction events for the 78 cases

occurred on average 18 months after their participation in the health survey (median, 15 months).

Baseline characteristics for the 16 women and 62 men who developed a myocardial infarction and

for the matched controls are shown in Table 1

Table 1. Mean Baseline Characteristics for Patients and Referent Subjects by Use of an Unpaired tTest and Fisher's Exact Test for Comparison

Men Women

Patients Referents P Patients Referents P

Age, y 54.7 54.5 NS 55.1 55.1 NS

Smokers, % 46.4 29.9 0.041 30.8 19.4 NS

Diabetes, % 5.2 0.8 NS 20.0 0 0.034

History of hypertension, % 43.1 30.3 NS 53.3 12.5 0.009

BMI, kg/m2 27.1 25.9 0.031 28.7 24.5 0.006

Cholesterol, mmol/L 6.60 6.37 NS 7.33 6.47 0.051

ApoA1, mg/L 1054 1135 0.002 1109 1232 0.029

DBP, mm Hg 89.6 86.9 NS 87.9 83.3 NS

SBP, mm Hg 142.0 138.3 NS 148.4 132.9 0.01

tPA, µg/L 12.2 9.3 <0.001 13.3 8.3 <0.001

PAI-1, µg/L 15.1 11.4 0.041 17.3 10.0 0.015

VWF, % of normal 142 131 NS 162 134 0.044

TM, µg/L 45.5 40.0 NS 28.6 29.9 NS

DHEAS, µmol/L 4.03 4.30 NS 2.88 2.61 NS

DBP indicates diastolic blood pressure; SBP, systolic blood pressure.

49

Established cardiovascular risk factors such as smoking, hypertension, and diabetes were more

common in the cases, as were higher mean levels of body mass index, systolic and diastolic blood

pressures, and serum cholesterol concentrations, but lower mean concentrations of ApoA1.

Moreover, in the group with myocardial infarction, the mass concentrations of PAI-1, tPA, and

VWF were significantly higher, whereas TM and DHEAS did not differ compared with the

reference group.

Data for the total study population and the probability value for the test for trends across the

stratification are shown in Tables 2 and 3. High plasma levels of PAI-1, tPA, and VWF mass

concentrations, obesity and high levels of cholesterol were all associated with significant increases

in the risk of myocardial infarction. High levels of ApoA1 were associated with a markedly reduced

risk, whereas only nonsignificant trends for increased risk were seen for high levels of TM and low

levels of DHEAS.

50

Table 2. Relative Risk of Myocardial Infarction From a Matched Analysis of 78 Case-Referent Triplets With Conditional Logistic Regression and Adjustment for Traditional Risk Factors

Relative Risk Matched forAge and Sex (95% CI)

P for Trend*

Relative Risk for Model Including Diabetes, Smoking, Hypertension, BMI, Cholesterol, ApoA1, and tPA

(95% CI)

No history of diabetes

1.00 0.002 1.00

History of diabetes 12.74 (1.52–106.6) † 7.90 (0.45–139.5)

Nonsmoker 1.00 0.021 1.00

Daily smoker 2.07 (1.12–3.82) † 1.98 (0.90–4.35)

Normotensive 1.00 0.013 1.00

Hypertensive 2.31 (1.23–4.33) † 1.71 (0.73–3.98)

BMI 26.9 kg/m2 1.00 0.043 1.00

BMI 27–29.9 kg/m2 1.26 (0.65–2.42) 0.68 (0.27–1.73)

BMI 30 kg/m2 2.23 (1.03–4.83) † 0.43 (0.12–1.47)

Cholesterol <6.5 mmol/L

1.00 0.002 1.00

Cholesterol 6.5–7.79 mmol/L

1.47 (0.78–2.78) 1.79 (0.79–4.02)

Cholesterol 7.8mmol/L

3.19 (1.47–6.89) † 5.66 (1.95–16.47) †

ApoA1 1047 mg/L 1.00 <0.001 1.00

ApoA1 1048–1148 mg/L

0.46 (0.22–0.97) † 0.35 (0.14–0.91) †

ApoA1 1149–1266 mg/L

0.29 (0.12–0.67) † 0.33 (0.11–0.96) †

ApoA1 1267 mg/L 0.21 (0.09–0.51) † 0.16 (0.05–0.50) †

* 2 test. † Significant relation.

51

Table 3. Relative Risk of Myocardial Infarction From a Matched Analysis of 78 Case-Referent Triplets With Conditional Logistic Regression and Adjustment for Traditional Risk Factors

Relative RiskMatched for Age and

Sex (95% CI) P for Trend*

Relative Risk for Model Including Diabetes, Smoking,

Hypertension, BMI, Cholesterol, ApoA1, and 1 of

the Variables Shown (95% CI)

tPA 6.0 µg/L 1.00 <0.001 1.00

tPA 6.1–8.4 µg/L 1.04 (0.42–2.59) 1.08 (0.37–3.16)

tPA 8.5–11.6 µg/L 1.79 (0.73–4.37) 1.32 (0.45–3.90)

tPA 11.7 µg/L 5.89 (2.38–14.57) † 5.42 (1.75–16.79) †

PAI-1 5.8 µg/L 1.00 0.002 1.00

PAI-1 5.9–7.9 µg/L 1.25 (0.50–3.13) 0.96 (0.34–2.73)

PAI-1 8.0–13.5 µg/L 2.37 (0.98–5.72) 1.77 (0.58–5.89)

PAI-1 13.6 µg/L 3.35 (1.38–8.14) † 1.83 (0.57–5.89)

VWF 102% 1.00 0.045 1.00

VWF 103–124% 1.49 (0.66–3.38) 1.40 (0.50–3.94)

VWF 125–154% 1.57 (0.69–3.57) 1.37 (0.50–3.76)

VWF 155% 2.39 (1.05–5.44) † 2.58 (0.87–7.63)

TM 26.7 µg/L 1.00 0.682 1.00

TM 26.8–36.9 µg/L 1.24 (0.57–2.73) 0.87 (0.32–2.35)

TM 37.0–45.2 µg/L 1.14 (0.50–2.63) 0.79 (0.27–2.29)

TM 45.3 µg/L 1.30 (0.53–3.16) 1.04 (0.35–3.05)

DHEAS 2.9 µmol/L 1.00 0.688 1.00

DHEAS 3.0–4.9 µmol/L 1.11 (0.58–2.15) 1.30 (0.55–3.10)

DHEAS 5.0 µmol/L 0.82 (0.38–1.77) 0.55 (0.20–3.10)

* 2 test. † Significant relations.

To visually illustrate the strength of these relationships, the ORs through quartiles 1 through 4 of the

distributions of mass concentrations of tPA, PAI-1, and VWF are shown in the Figure 6.

52

Figure 6. Relative risk of myocardial infarction in all subjects for quartiles 1 through 4 of massconcentrations in plasma of t-PA, PAI-1, and VWF.

Subgroup analysis on men showed that higher levels of cholesterol and mass concentrations of tPA

and PAI-1 and lower levels of apoA-I were associated with significant increases in the risk of

myocardial infarction, whereas no significant trend was found for BMI, VWF, TM, or DHEAS

(data not shown).

Variables for women were only dichotomized because of the small number of cases. In women,

high levels of TM and mass concentrations of tPA and PAI-1 and low levels of ApoA1 were

associated with significant increases in the risk of myocardial infarction (Table 4).

53

Table 4. Subgroup Analyses on 16 Women With First Myocardial Infarction and 32 Age- and Sex-Matched Referent Subjects on Relative Risk of Myocardial Infarction With Conditional Logistic Regression

Cut-off Level OR 95% CI

tPA mass concentration, µg/L 8.10 8.42 1.06–67.13

PAI-1 mass concentration,µg/L

7.30 10.00 1.23–81.47

VWF, % 126 3.42 0.68–17.15

TM, µg/L 23 5.62 1.14–27.79

ApoA1, mg/L 1232 0.19 0.04–0.92

Cut-off level was defined as the median level in the 32 female referent subjects.

In multivariate conditional logistic regression analysis on all cases of both sexes, when all the

traditional atherosclerotic risk factors available in this study were simultaneously controlled for, the

relative risk in the highest quartile of tPA mass concentration was only slightly reduced to 5.42

(95% CI, 1.75 to 16.79) compared with 5.89 (95% CI, 2.38 to 14.57) in univariate analysis (Table

3). Low levels of ApoA1 and high cholesterol levels also remained significantly associated with

myocardial infarction in this analysis with tPA (Table 2). When PAI-1, VWF, TM, and DHEAS

were included in the same multivariate analysis together with the established risk factors diabetes,

smoking, hypertension, body mass index, cholesterol, and ApoA1, the significant associations of

these former variables to myocardial infarction disappeared.

Subgroup analysis on men showed a significant association of tPA and diabetes, smoking,

hypertension, BMI, cholesterol, and ApoA1 in multivariate conditional logistic regression, whereas

no significant association could be shown when PAI-1, VWF, TM, or DHEAS was included in the

model (data not shown). Multivariate subgroup analysis on women was not done because the

statistical power was too small owing to the limited number of women.

54

Study II

In this study, the prevalences of the three possible genotypes of the C 677>T mutation of MTHFR,

namely –/– (no mutation), +/+ (both alleles have the mutation) and +/–, and plasma concentration of

total homocysteine were investigated as predictors of a first myocardial infarction. Prevalences of

genotypes did not deviate from the Hardy–Weinberg equilibrium for referent subjects ( 2 = 0.31, P

> 0.05), cases ( 2 = 0.63, P > 0.05), and the subjects overall ( 2 = 0.78, P > 0.05). The T prevalence

was greater for cases than referents (0.30 versus 0.25) but not significantly. The expected

prevalance of the TT mutation was 6.25%. There was no statistically significant difference between

cases and referents for any of these combinations. Neither were odds ratios for the +/– and +/+

groups significantly higher (Table 5).

Cases Referents Odds ratio Confidence interval (95%)

MTHFR /

MTHFR /+

MTHFR +/+

Prevalence of alleles

–

+

Total plasma homocysteine

First quartile ( 9.66 µmol/L)

Second quartile (9.67-11.43 µmol/L)

Third quartile (11.44-13.58 µmol/L)

Fourth Quartile ( 13.59 µmol/L)

32 (46)

32 (46)

5(7)

0.70

0.30

19

18

15

24

71 (55)

51(40)

7(5)

0.75

0.25

36

36

38

37

1.00

1.4

1.7

1.00

0.9

0.8

1.2

0.7-2.6

0.5-6.3

0.4-2.2

0.4-1.7

0.5-2.7

Table 5. Distributions of 5,10-methylenetetrahydrofolate reductase (MTHFR) genotype and level of

total plasma homocyst(e)ine for case subjects with myocardial infarction and age-matched and sex-

matched referents. Values are expressed as numbers (percentages). MTHFR, P -value for trend

0.249; total plasma homocysteine, P -value for trend 0.700. Conditional logistic regression was

used for comparisons.

Mean concentrations of homocysteine did not differ between the group with myocardial infarction

and the reference group and between men and women.

55

In Figure 7 we show the relative distributions of homocysteine for cases and controls. The

prevalence of hyperhomocysteinemia, whether defined as homocysteine >15.8 µmol/l (154), or the

95th (homocysteine >18.65 µmol/l) or the 90th (homocysteine >15.65 µmol/l) percentile of

concentration of homocysteine of the distribution for referents, corresponding to 16% of cases and

9.6% of referent subjects, 2.6% of cases and 4.8% of referent subjects, and 17.1% of cases and

10.9% of referent subjects, respectively, did not differ significantly between cases and referent

subjects. Univariate conditional logistic regression analysis of the quartiles for homocysteine

showed that there was no association with risk of myocardial infarction (Table 5).

Figure 7. Relative distribution of total plasma homocyst(e)ine (TPH) among cases and controls besides one control individual with a TPH of 55.13 µmol/l.

We observed no association between MTHFR genotype and homocysteine (Table 6) even after

stratification by age, for which 60% of the study population were aged more than 58 years.

56

Homocysteine was positively associated with age (r = 0.138, P = 0.039). The mean age of subjects

in the homozygous mutant group was lower than those of subjects in the other groups (Table 6).

MTHFR genotypes CC CT TT

Homocysteine in cases (µmol/L)

Homocysteine in referents (µmol/L)

Homocysteine in all subjects (µmol/L)

Homocysteine in all subjects 58 years

Homocysteine in all subjects > 58 years

Age (years)†

11.5±2.9

12.5±6.0

12.2±5.2

11.3±3.0

12.8±6.0

55.1±6.9

12.5±4.1

11.6±3.9

12.0±4.0

11.7±3.3

12.1±4.3

55.3±6.5

11.4±1.7

11.6±2.6

11.5±2.2

11.3±1.8

12.0±2.5

46.6±10.2

Table 6. Plasma concentrations of total plasma homocyst(e)ine in the study population by 5,10-

methylenetetrahydrolfate reductase (MTHFR) 677 C>T genotype and age. All values are means ±

SD. †P for age by analysis of variance < 0.001.

Study III

In this study, the summarised importance of haemostatic (tPA, PAI-1, VWF) and metabolic

variables (insulin, lipids including lipoprotein (a) (Lp(a)) and leptin) in predicting first myocardial

infarction, as well as possible interactions among these variables were investigated among the 62

men cases and 124 men referents. The insulin variables were, as expected, correlated to each other,

as well as to BMI, leptin, PAI-1, tPA, VWF, and systolic and diastolic blood pressure. Proinsulin

was also correlated to VWF. High levels of leptin were associated with BMI, blood pressure, and

high plasma levels of PAI-1, tPA, VWF, and apo B. Lp(a) correlated only positively to Apo B. tPA

and PAI-1 were correlated to each other. Partial correlations after adjustment for BMI resulted in r

0.30 for insulin in relation to proinsulin, specific insulin, and leptin; proinsulin to leptin and

specific insulin; leptin to PAI-1; cholesterol to ApoA1 and apo B; and systolic blood pressure to

diastolic pressure.

57

Table 7. Odds ratios for first myocardial infarction based on conditional logistic regression analysis of 62 male cases matched with double referents

BMI, body mass index; apo A-I, apolipoprotein A-I; tPA, tissue plasminogen activator; PAI-1, plasminogenactivator inhibitor-1; vWF, von Willebrand factor; Lp(a), lipoprotein (a). * Significant relation. † 2 test.

Relative risk matched for age (95%

CI)

P for

trend†

Multivariate model including all the

variables with calculations (95% CI)No history of diabetes 1.00 0.11 1.00History of diabetes 6.00 (0.62-57.7) 0.42 (0.002-118)

Non-smoker 1.00 0.09 1.00Daily smoker 2.11 (1.08-4.12)* 2.10 (0.61-7.26)

Normotensive 1.00 0.2 1.00Hypertensive 1.76 (0.87-3.56) 0.86 (0.22-3.39)

BMI 26,9 kg/m2 1.00 0.3 1.00

BMI 27-29,9 kg/m2 1.15 (0.56-2.36) 0.59 (0.14-2.52)

BMI 30 kg/m2 2.18 (0.75-6.29) 0.57 (0.10-3.22)

Cholesterol <6,5 mmol/l 1.00 0.02 1.00Cholesterol 6,5-7,79 mmol/l 1.33 (0.68-2.61) 1.73 (0.49-6.04)Cholesterol 7,8 mmol/l 2.63 (1.09-6.37)* 2.33 (0.40-13.4)

ApoA1 1038 mg/L 1.00 0.002 1.00ApoA1 1038-1136 mg/L 0.40 (0.17-0.92)* 0.16 (0.03-0.89)*ApoA1 1136-1242 mg/L 0.28 (0.11-0.74)* 0.17 (0.03-0.96)*ApoA1 1223 mg/L 0.22 (0.08-0.62)* 0.15 (0.02-0.93)*

tPA 5.9 g/L 1.00 0.001 1.00tPA 5.9-8.5 g/L 2.22 (0.73-6.71) 2.51 (0.41-15.4)tPA 8.5-12.2 g/L 3.95 (1.24-12.55) 7.29 (0.79-67.2)tPA 12.2 g/L 7.53 (2.24-25.26)* 21.3 (2.04-222)*

PAI-1 5.8 g/L 1.00 0.03PAI-1 5.8-8.2 g/L 1.56 (0.59-4.14)PAI-1 8.2-14.0 g/L 2.18 (0.81-5.84)PAI-1 14.0 g/L 2.98 (1.09-8.16)*

VWF 102 % 1.00 0.2VWF 102-124 % 1.42 (0.56-3.61)VWF 124-151 % 1.28 (0.49-3.31)VWF 151 % 1.93 (0.79-4.70)

Proinsulin 4.5 pmol/L 1.00 0.02 1.00Proinsulin 4.5-6.8 pmol/L 4.97 (1.47-16.76) 4.55 (0.57-36.6)Proinsulin 6.8-11 pmol/L 3.33 (1.06-10.44) 2.66 (0.28-25.4)Proinsulin > 11 pmol/L 5.50 (1.64-18.44)* 6.47 (0.54-78.1)

Lp(a) 30 mg/L 1.00 0.002 1.00Lp(a) 30-65 mg/L 0.56 (0.21-1.54) 0.95 (0.15-5.93)Lp(a) 65-134 mg/L 0.67 (0.22-2.06) 0.91 (0.12-6.92)Lp(a) 134 mg/L 2.59 (1.14-5.90)* 7.21 (1.31-39.8)

Leptin 3.0 ng/mL 1.00 0.002 1.00Leptin 3.0 -4.1 ng/mL 1.00(0.34-2.90) 0.11(0.01-1.21)Leptin 4.1-6.4 ng/mL 2.25 (0.77-6.58) 0.14 (0.01-2.08)Leptin >6.4 ng/mL 4.89 (1.63-14.7)* 0.83 (0.04-19.59)

58

In conditional univariate logistic regression analysis, smoking, hypercholesterolemia, and high

plasma levels of tPA, PAI-1, proinsulin, Lp(a), and leptin, and low plasma levels of ApoA1 were all

associated with significant increases in the risk of first myocardial infarction (Table 7). Tests for

trends after categorization of the continuous variables were significant for cholesterol, ApoA1, tPA,

PAI-1, proinsulin, Lp(a), and leptin (Table 7). In multivariate conditional logistic regression

analysis, after simultaneously controlling for all traditional atherosclerotic risk factors available in

this study (diabetes, smoking, hypertension, BMI, and cholesterol) together with each of the

variables shown in Table 7, only high plasma levels of tPA, proinsulin, and Lp(a), and low plasma

levels of ApoA1 remained significant risk determinants for first myocardial infarction, though high

leptin was also borderline significant (p=0.06). Combining these variables with the traditional risk

factors, only tPA, Lp(a), and ApoA1 remained significant risk determinants for first myocardial

infarction (table 7). If a cut-off level of 200mg/L for Lp(a) was implemented according to our

previous report (144), then odds ratio for Lp(a) 200mg/L increased to 20.4 (95% CI, 3.2-129) in

the final model. If the categories for leptin were reduced by combining quartiles 1 and 2, a method

employed in a previous report (155), then the odds ratio for leptin levels 6.4 ng/mL increased to

8.4 (95% CI, 1.01-70) in the final model. Repeated analysis after exclusion of diabetic subjects (3

cases and their respective referents, and 1 referent subject) did not alter the results of the uni- and

multivariate analyses.

To explore possible interactions among plasma levels of tPA, ApoA1, Lp(a), leptin, and proinsulin,

these variables were dichotomized according to the median values of the controls and analysed in

pairs by conditional logistic regression (Tables 8 and 9). No significant synergistic interactions were

observed for any of these combinations (Tables 8 and 9 and Figure 8).

59

Table 8. Interaction analysis by conditional logistic regression on pairs of selected

dichotomized variables for 62 male cases of first myocardial infarction matched with double

referents

Relative risk matched

for age (95% CI)

P value for trend

chi-square test

Synergy index

(95%CI)

Leptin-ApoA1

low-high 1.00 0.001

low-high 1.08 (0.36-3.21)

high-high 1.13 (0.35-3.65)

high-low 3.93 (1.48-10.4)* 14.6†

Leptin-Lp(a)

low-low 1.00 0.001

low-high 1.66 (0.61-4.55)

high-low 1.72 (0.56-5.25)

high-high 6.02 (2.05-17.7)* 3.6 (0.7-17.9)

Leptin-proinsulin

low-low 1.00 0.01

low-high 1.06 (0.37-3.05)

high-low 2.32 (0.83-6.51)

high-high 2.84 (1.22-6.64)* 1.3 (0.2-7.4)

Leptin-tPA

low-low 1.00 0.003

low-high 1.50 (0.50-4.54)

high-low 1.69 (0.55-5.17)

high-high 4.59 (1.71-12.29)* 3.0 (0.4-19.0)

tPA-Lp(a)

low-low 1.00 <0.001

low-high 2.29 (0.80-6.59)

high-low 2.74 (0.88-8.57)

high-high 7.86 (2.60-23.80)* 2.3 (0.8-6.6)

ApoA1, apolipoprotein A1; Lp(a), lipoprotein (a); tPA, tissue plasminogen activator. * Denotes

significant relations. † Confidence interval not depicted because of too high standard error.

”Low” and ”high” are defined as values at or below the median, and above the median value,

respectively.

60

Table 9. Interaction analysis by conditional logistic regression on pairs of selected

dichotomized variables for 62 male cases of first myocardial infarction matched with double

referents

Relative risk matched

for age (95% CI)

P value for trend

chi-square test

Synergy index

(95% CI)

tPA-proinsulin

low-low 1.00 0.007

low-high 0.87 (0.31-2.46)

high-low 1.96 (0.73-5.28)

high-high 3.22 (1.30-7.95)* 2.7 (0.3-26.1)

Lp(a)-proinsulin

low-low 1.00 0.003

low-high 1.45 (0.48-4.42)

high-low 2.36 (0.81-6.85)

high-high 3.89 (1.37-11.0)* 1.6 (0.4-7.1)

Lp(a)-ApoA1

low-high 1.00 0.001

low-low 2.40 (0.75-7.68

high-high 1.86 (0.59-5.85)

high-low 6.53 (2.10-20.31)* 2.5 (0.7-8.7)

Proinsulin-ApoA1

low-high 1.00 0.02

low-low 1.92 (0.70-5.28)

high-high 1.17 (0.41-3.28)

high-low 3.33 (1.29-8.62)* 2.2 (0.3-13.5)

tPA-ApoA1

low-high 1.00 0.001

low-low 2.40 (0.77-7.47)

high-high 2.80 (0.85-9.22)

high-low 6.33 (2.07-19.34)* 1.7 (0.6-4.9)

tPA, tissue plasminogen activator; Lp(a), lipoprotein (a); ApoA1, apolipoprotein A1. * Denotes

significant relations.

“Low” and “high” are defined as values at or below the median, and above the median value,

respectively.

61

0

2

4

6

8

10

low-low low-high high-low high-high

Relative risk

Figure 8. Interaction analysis by conditional logistic regression of four different combinations oflow and high plasma concentrations of tPA and Lp(a) for 62 male cases of first myocardialinfarction matched with double referents.

Study IV

In this study comparison of plasma homocysteine, plasma creatinine and plasma albumin in 50

cases and 56 referent subjects were investigated before and after the development of a first

myocardial infarction. The first myocardial infarct events for the 50 cases occurred on average 20

months after participation in the first health survey (median, 18 months). The time interval between

the two screening episodes had a mean of 8.4 1.8 years (SD) for cases and 8.7 1.7 years (SD) for

referents (unpaired t-test: p=0.5). Baseline characteristics for the 50 cases and 56 referents are

shown in Table 10.

62

Table 10. Characteristics of variables in study subjects at baseline and follow-up.

Cases Referent Subjects

(n = 50) SD (n = 56) SD

Sex (male/female) 42/8 47/9

Age at first blood sampling, year 53.7 7.5 53.1 8.3

Smokers, % 19/44 (43%) 13/55 (24%)

Diabetes, yes/no, % 2/46 (4.4%) 0/56 (0%)

Systolic blood pressure (mmHg) 140 24 136 21

Diastolic blood pressure (mmHg) 86 9 83 10

History of hypertension, % 17/46 (37%) 14/56 (25%)

Body mass index, kg/m2 27.0 4.2 25.7 3.6

Cholesterol, baseline (mmol/L) 6.7 1.5 6.4 1.4

Homocysteine, baseline ( mol/L) 11.4 2.8 10.7 2.0

Homocysteine, follow-up ( mol/L) 12.4 3.2 11.9 3.2

Albumin, baseline (g/L) 43.0 2.0 42.9 2.5

Albumin, follow-up (g/L) 41.7 1.8 41.9 2.0

Creatinine, baseline ( mol/L) 95.8 13.1 92.2 13.1

Creatinine, follow-up ( mol/L) 100.7 14.6 95.8 15.3

SD, Standard deviation.

Established cardiovascular risk factors such as smoking, diabetes, and hypertension were more

common among cases than referents, whereas none of the continuous variables differed between the

groups. There was a significant increase in total plasma homocysteine concentrations during follow-

up among both cases and referents. The mean increase in tHcy among cases and referents were

comparable (1.0 2.8 mol/L versus 1.1 2.6 mol/L). The difference in homocysteine

concentration at follow-up and baseline was not correlated to the time interval between the two

health survey occasions (Spearman´s rho correlation coefficient – 0.064, p=0.5). There were

63

significant increases in plasma creatinine concentrations in cases (4.9 12.4 mol/L; p<0.01) and

referents (3.7 11.6 mol/L; p<0.05), and significant decreases in plasma albumin concentrations

in cases (-1.2 2.1 g/L; p<0.001) and referents (-1.0 2.9 g/L; p<0.05) during follow-up.

Significant correlations were observed between baseline plasma homocysteine concentration and

body mass index (r=0.25; p<0.05), creatinine (r=0.31; p<0.01) and plasma homocysteine

concentration at follow-up (r=0.633; p<0.001). For both creatinine and albumin in plasma, a

correlation was found between baseline and follow-up concentrations (r = 0.66; p<0.001 and r = –

0.25; p<0.05 respectively). Conditional univariate logistic regression analysis of all the continuous

variables showed no significant associations with first myocardial infarction (Table 11). High

plasma concentrations of homocysteine at follow-up and high plasma concentrations of creatinine at

baseline and follow-up were associated with first myocardial infarction (Table 11).

Multivariate analysis with conditional logistic regression in models including two variables

indicated that high homocysteine concentrations at follow-up remained associated to a first

myocardial infarction when combined with albumin at follow-up, whereas the same was true only

for high concentrations of creatinine in combination with tHcy at follow-up (Table 12). Multivariate

conditional logistic regression analysis with the three variables homocysteine, albumin and

creatinine showed that only creatinine at baseline (OR 2.94; 95% CI 1.05-8.21) and creatinine at

follow-up (OR 3.38; 95% CI 1.21-9.48) were significantly associated with outcome (Table 12).

64

Table 11. Odds ratios of myocardial infarction from a matched analysis of 47 case-

referent pairs/triplets with conditional logistic regression

Odds ratio matched for age with continuous variables (95% CI)

Odds ratio matched for age with variables dichotomised or as specified (95% CI)

Non-smokerSmoker

1.003.36 (1.07-10.55)*

Cholesterol< 6.5 mmol/L6.5-7.79mmol/L

7.8 mmol/L

1.04 (0.80-1.35)1.000.92 (0.38-2.23)1.79 (0.64-4.99)

NormotensiveHypertensive

1.001.82 (0.60-5.47)

Body mass index 26.9 kg/m2

27-29.9 kg/m2

30 kg/m2

1.08 (0.96-1.22)1.001.20 (0.45-3.35)2.66 (0.66-10.74)

Homocysteine, baseline 10.66 mol/L 10.67 mol/L

1.13 (0.93-1.38)1.001.34 (0.59-3.11)

Homocysteine, follow-up 10.88 mol/L 10.89 mol/L

1.08 (0.95-1.22)1.002.49 (1.03-6.02)*

Albumin, baseline 43 g/L 44 g/L

0.97 (0.81-1.16)1.000.61 (0.25-1.48)

Albumin, follow-up 41 g/L 42 g/L

0.93 (0.74-1.19)1.001.00 (0.41-2.44)

Creatinine, baseline 90 mol/L 91 mol/L

1.02 (0.98-1.05)1.002.72 (1.05-7.07)*

Creatinine, follow-up 93 mol/L 94 mol/L

1.03 (1.00-1.06)1.004.05 (1.49-11.0)*

* Significant relation

65

Table 12. Multivariate conditional logistic regression analyses on odds ratios of myocardial

infarction in models including two or three variables.

Odds ratio (95%CI)

with two variables

respectively

Odds ratio (95%CI)

with three variables

respectively

Homocysteine, baseline, median

Albumin, baseline, median

Creatinine, baseline, median

1.38 (0.56-3.24)

0.60 (0.24-1.48)

1.06 (0.43-2.61)

0.51 (0.19-1.39)

2.94 (1.05-8.21)*

Homocysteine, baseline, median

Creatinine, baseline, median

1.05 (0.44-2.54)

2.68 (0.99-7.20)

Homocysteine, follow-up, median

Albumin, follow-up, median

Creatinine, follow-up, median

2.50 (1.03-6.07)*

0.94 (0.37-2.33)

1.83 (0.70-4.78)

0.90 (0.35-2.36)

3.38 (1.21-9.48)*

Homocysteine, follow-up, median

Creatinine, follow-up, median

1.82 (0.70-4.75)

3.38 (1.20-9.47)*

* Significant relation

66

DISCUSSION

Current smoking, hypertension and diabetes in combination accounted for 53 % of the population

attributable risks of acute myocardial infarction in the Interheart case-control study (156).

Identification of other markers associated with an increased risk of atherosclerotic vascular disease

may allow better insight into the pathobiology of atherosclerosis and facilitate the development of

preventive and therapeutic measures (157).

Thrombus formation requires complex interactions involving injury to the vascular endothelium,

platelet adherence, aggregation and release, and clotting factor activation. This process eventually

leads to thrombin generation and fibrin formation (43). The availability of a useful index of

endothelial dysfunction may, therefore, have potential value as measurement of such a marker can

be a non-invasive way of assisting in diagnosis, as well as an indicator of disease progression or

prognosis (43).

Study base

The two surveys fulfil the criteria of a population-based study cohort and the observed prevalence

of traditional risk factors should be expected to be representative of a larger population. A total of

78 first myocardial infarctions were included between 1985 and 1994, which may appear

unexpectedly low considering the size of the study cohort. There are several explanations for this.

First, participants in the surveys are predominantly middle-aged with a low incidence of

cardiovascular disease. Second, only cases with a first myocardial infarction were included and

subjects with previous stroke were excluded. In addition, all cases with diagnosed cancer and cases

with no blood sample or blood sample not adequate for analysis were also excluded from the

studies. Finally, the VIP and MONICA surveys started in 1985 and the number of screened subjects

has a linear growth. During the first years of the VIP survey only a few screening centers were

performing health examinations. Consequently, years at risk for cardiovascular disease are therefore

relatively shorter for a majority of the participants (136).

67

Determinants of myocardial infarction

Study I showed that established cardiovascular risk factor such as smoking, hypertension, and

diabetes were more common in the cases, and they had higher mean levels of body mass index,

systolic and diastolic blood pressure, and serum cholesterol concentrations and lower mean

concentrations of ApoA1. The overall results are in concordance with previous prospective studies

on myocardial infarction and should be expected to be representative of the whole cohort.

Hemostatic factors and myocardial infarction

High PAI-1 and tPA mass concentrations are associated with increased risk of a first myocardial

infarction in both men and women (study I). For tPA, the association is strong, especially in women,

is independent of established cardiovascular risk factors, and is continuous across the tPA strata.

Increased levels of PAI-1 were also associated with first myocardial infarctions in both sexes in

univariate, but not multivariate analyses when adjusted for traditional risk factors. In multivariate

analysis high plasma levels of tPA remained significant risk markers for a first myocardial

infarction after adjustment for traditional risk factors (diabetes, smoking, hypertension, BMI, and

cholesterol) and proinsulin, ApoA1, Lp(a) and leptin (study III). Our study in men emphasizes the

position of tPA mass concentration as an independent risk determinant.

Although there is a statistically significant association between circulating concentrations of tPA

mass and subsequent coronary heart disease, additional studies are needed to determine to what

extent this is independent from other risk determinants like markers of systemic inflammation and

kidney function. It is not known how much of the residual association between tPA and coronary

heart disease would persist with more complete adjustment for these (and other) factors (38). At

present the pathophysiological relevance of circulating levels of tPA to plaque rupture remains

uncertain (38). Epidemiological studies of tPA consistently show strong correlations with PAI-1

activity or mass concentration (38). This association may reflect simultaneous release from

68

endothelial cells, delayed clearance of tPA-PAI-1 complexes, acute-phase reactions, or mutual

correlations with measures of insulin resistance (38).

Although PAI-1 poorly predicts coronary heart disease in healthy subjects, an underlying

association between PAI-1 levels and coronary disease may be hidden by the confounding effect of

the close correlation between levels of PAI-1 and other established cardiovascular risk factors,

particularly those that occur in association with insulin resistance (158).

It is evident that PAI-1 can play an ambivalent role, either by contributing to plaque stabilization by

reducing local plasmin activity and therefore the activation of matrix metallopeptidases (39), or by

enhancing the risk of thrombosis after plaque rupture with ensuing increased fibrin deposition (39).

In addition, as for other “players” acting locally as autocrine/paracrine factors, the relationship

between circulating (plasma) and local (tissue) levels of PAI-1 must be taken into consideration.

This has been neglected in most available studies (39). Thus, although it has been hypothesizes that

an increase in local levels of PAI-1 might contribute to the pathogenesis of atherosclerosis, it is still

unclear whether the increase in PAI-1 plasma levels observed in this pathological condition

represents cause, effect, or both (39). In our view, the cause-effect relationship must be

demonstrated in prospective studies of healthy populations before PAI-1 can be considered a risk

factor for coronary atherosclerosis. Whether PAI-1, per se, carries an increased risk of

cardiovascular disease remains to be determined, perhaps with the exception of late restenosis after

percutaneous coronary intervention (39).

Cases had higher mean VWF values than controls, and this difference was also significant in

subgroup analysis of women, but not in men (study I). VWF was predictive of a future myocardial

infarction, and its OR actually increased slightly after adjustment for traditional risk factors. The

predictive value of VWF may thus be real in the type of subjects studied here, although the

introduction of confounding variables in multivariate analyses resulted in too great a loss of

statistical power to achieve statistical significance. The precise mechanism by which VWF is

associated with cardiovascular risk is unclear (113). As well as having roles in haemostais and

69

thrombosis, circulating VWF values can increase markedly during acute phase responses to

systemic and/or local inflammation and to endothelial injury (46). However, in the PRIME study

(113), the contribution of VWF to coronary heart disease was independent of inflammatory markers

and traditional risk factors, suggesting different pathways through which VWF and inflammation

determine coronary heart disease risk.

No significant differences in the mean levels of plasma TM were found between the case and

control groups, although TM tended to be higher in subgroup analysis of male cases compared with

controls (study I). However, in a stratified subgroup analysis of women, high levels of TM were

predictive of future myocardial infarction. Results of prospective studies on TM and cardiovascular

end-points have been inconsistent (113,114), and more specially designed studies are therefore

necessary to confirm the possibility that TM may be a risk determinant, albeit a weak one, of a first

myocardial infarction. Both endothelial cell protein C receptor and thrombomodulin are severely

downregulated over atherosclerotic plaque, vein bypass grafts, in diabetes, and by acute

inflammmatory insults like bacterial infection, potentially contributing to both thrombosis and

plaque rupture through localized thrombin generation and subsequent metalloproteinase activation

(53). Since raised thrombomodulin concentrations indicate an increased risk of bleeding in patients

receiving oral anticoagulants (159), circulating thrombomodulin might reflect not only endothelial

cell damage, but also increased synthesis, which would therefore enhance the anticoagulant

property of the endothelial cell surface. The importance of circulating TM as an indicator of

anticoagulant or procoagulant activity on the surface of the endothelium is still unclear and data on

the relation between soluble TM and membrane bound TM are not available. Whether low levels of

soluble TM represent high amounts of membrane bound TM due to reduced shedding from the

endothelium or whether low levels reflect low amounts of membrane bound TM due to impaired

expression of TM to the endothelial surface is unknown. It thus remains to be determined whether

thrombosis or hemorrhage can be directly attributed to the plasma concentration of TM or whether

it is only a reflection of other pathophysiological processes (160).

70

DHEAS

No predictive value of DHEAS regarding the risk of a first myocardial infarction was found for

either men or women in Study I. The epidemiological and experimental data on the relationship

between DHEAS and coronary artery disease are inconsistent and unconvincing (115) and do not

support the hypothesis that DHEAS deficiency is a risk factor for coronary artery disease fatalities

or that DHEAS may confer an anti-atherogenic action in men or women (115). The age-related

decline in serum DHEA and DHEAS has suggested that a relative deficiency of these steroids may

be causally related to the development of chronic diseases generally associated with aging,

including insulin resistance, obesity, cardiovascular disease, cancer, reductions of the immune

defense, depression and a general deterioration in the sense of well-being (55). There is still a lack

of understanding of the basic biological effects of DHEAS and further data in both men and women

from prospective studies and randomized trials are needed (57).

MTHFR

Study II shows that homozygosity for the point mutation C677>T in the gene for MTHFR is not a

clinically useful predictor of a greater than normal risk of a first myocardial infarction for the

population of Northern Sweden. The low prevalence of the homozygous MTHFR mutant, 5% in the

present study or estimated 6.25%, compared with 10 % to 12% reported in the meta-analysis by

Klerk et al (88) might have been caused by the sampling strategy. We found that the homozygous

carriers of MTHFR mutation were younger than individuals with the mutation in the heterozygous

state and homozygous normal genotypes. The consequence of this could be a selection bias in

reports by authors using other than prospective designs for the evaluation of the importance of the

MTHFR mutation. However, studies comparing the allele frequency of the C677>T /MTHFR

genotypes in the newborn, young and elderly (161,162) could not demonstrate significant gene

mutations differences among the various age groups, suggesting that the point mutation C677>T in

71

the gene for MTHFR do not contribute significantly to longevity. Klerk et al (88) reported that

individuals with the MTHFR 677 TT genotype had a significantly higher risk of coronary heart

disease, particular in the setting of low folate status. However, the increased risk with the TT

genotype was shown only for retrospective studies, which are restricted to survivors, whereas

prospective studies can include fatal and non-fatal outcomes. In the face of a low prevalence of the

MTHFR mutation, we conclude that the MTHFR mutation does not explain any major part of the

risk of a first myocardial infarction in the area of Northern Sweden. Klerk et al (88) also concluded

that provided that folate status is adequate, there is little clinical value of screening for MTHFR 677

TT genotype in the general population for prediction of coronary heart disease. Epidemiologic

observations have led to the hypothesis that the risk of developing coronary artery disease in

adulthood is influenced not only by genetic and adult life-style factors but also by environmental

factors acting in early life (163). Thereby, also the folate intake by the mothers in early pregnancy

could be important as well as the type of feeding in the postnatal and infant phase.

Homocysteine

Study II and IV show that baseline plasma homocysteine concentration was not associated with a

first myocardial infarction. However, homocysteine concentrations at follow-up were significantly

associated with myocardial infarction when dichotomized with the median value as cut-off (study

IV). This association disappeared after adjustment for creatinine concentrations (study IV). Total

plasma homocysteine concentrations during eight and a half years of follow-up evolved similarly in

subjects who developed a first myocardial infarction compared to referents (study IV). These data

are not compatible with the hypothesis that homocysteine increases secondarily to a first myocardial

infarction. On the contrary, Nurk et al (164) reported from a population-based, prospective study in

7031 subjects from western Norway who constituted 2 age groups (41-42 and 65-67 years) at

baseline. Previously healthy subjects who developed cardiovascular disease or hypertension during

6 years of follow-up had a significantly higher mean increase in total plasma homocysteine than did

72

those who were free of cardiovascular disease or hypertension (164). The reason for the

discrepancies between our and the Hordaland study could be differences in the age groups studied

and the end points.

Prospective studies of the association of hyperhomocysteinemia and the risk of arterial disease in

otherwise healthy subjects at the time of randomization have given contrasting results. Among the

possible explanations for the different results, the effects of genetic and/or nutritional differences

and of different cardiovascular risk profiles among the populations studied could be considered

(66). The findings that hyperhomocysteinemia consistently proved to be predictive of

cardiovascular events in patients affected by pathologies associated with high cardiovascular risk

suggest that the basal cardiovascular risk profile of the population may be relevant (66). Renal

function is an important determinant of circulating homocysteine concentrations independent of B

vitamin status (72,165). Results of prospective studies of patients with renal disease suggest that

individuals with higher homocysteine levels are at increased risk of cardiovascular events and death

(166,167). In a recent report, Go et al (168) found an independent, graded association between a

reduced estimated glomerular filtration rate and the risk of death, cardiovascular events, and

hospitalization in a large, community-based population. Reduced kidney function was also

associated with increased levels of inflammatory factors, enhanced coagulability, abnormal

apolipoprotein levels, elevated plasma homocysteine, oxidative stress, anemia, left ventricular

hypertrophy, increased arterial calcification, derangement in calcium-phosphate homeostasis, and

arterial stiffness, all of which are associated with accelerated atherosclerosis and endothelial

dysfunction (168,169). Other non-conventional risks that progressively increase with renal decline

include albuminuria, proteinuria, and elevated uric acid levels (169). Whether and how these and

other factors interact to increase the risk of adverse outcomes remains unclear but are the focus of

ongoing investigations (168).

In a recent randomized clinical trial with high and low dose B-vitamin treatment there was no effect

on any clinical endpoint despite a significant decrease of homocysteine by 2 µmol/L in the high

73

dose group (170). Nevertheless, baseline homocysteine concentrations in that study were

significantly associated with new coronary events, indicating homocysteine as a marker and not a

causal factor for coronary disease. No adjustment for creatinine or albumin concentrations was

performed. Two coronary angioplasty studies (171,172) have shown contradictory results regarding

oral supplementation with a combination of folic acid and vitamins B6 and B12 and risk of

restenosis. The two studies differed regarding doses of vitamins and the patients differed regarding

smoking habits, diabetes mellitus, prior myocardial infarction, treatment with statins and

angiotensin-converting-enzyme inhibitors, coronary artery lesion size and use of balloon

angioplasty and stents (173). Studies are needed to clarify the optimal dose, route, and timing of

administration and the subgroups of patients who might benefit from this treatment. Burke et al

(174) reported that increased serum homocysteine was associated with coronary atherosclerosis

with fibrous plaques, a mechanism of atherogenesis separate from that induced by hyperlipidemia,

which is believed to be mediated largely by inflammatory cells, especially macrophages.

Homocysteine was not associated with acute or organized coronary thrombi (174). The issue of

whether mild elevation of homocysteine is a marker or a mediator of vascular disease is still

unresolved.

In the present study, significant decreases in plasma albumin concentrations in cases and referents

were observed during follow up. Prior epidemiologic studies have reported an inverse association

between serum albumin and coronary heart disease (175-177). In a meta-analysis (176), low

albumin was associated with a 50% increased risk of coronary heart disease, and the combined

relative risk for all-cause mortality associated with low albumin was 1.9 (95% CI: 1.6 to 2.3). In

contrast, several observational studies did not find an association between serum albumin and

coronary heart disease (178-181). Albumin is an acute phase protein, whose plasma concentration

decreases in response to inflammatory stimuli (182). Certain conditions, such as increasing age or

several renal or hepatic diseases, might reduce serum albumin, and thus produce spurious inverse

associations (183). Albumin has potent anti-oxidant properties inhibiting the production of free

74

radicals, lipid peroxidation and endothelial cell apoptosis (184-187), mechanisms who are

fundamentally involved in atherogenesis. It is not clear whether low serum albumin concentration is

a nonspecific, prognostic variable, a marker for subclinical disease, or a part of the causal

mechanism leading to coronary heart disease (188).

Apolipoprotein A1

In multivariate analysis low plasma levels of ApoA1 remained significant risk markers for a first

myocardial infarction in men after adjustment for traditional risk factors (diabetes, smoking,

hypertension, body mass index, and cholesterol) and proinsulin, tPA, Lp(a) and leptin (Study III).

ApoA1 was also found to be a risk determinant for first myocardial infarction in women, but

multivariate analyses were not done (Study I). Due to sampling conditions and missing data, it was

not possible to include HDL-cholesterol in the analysis. It can therefore not be concluded that

ApoA1 is a more powerful predictor than indices such as HDL, total/HDL and LDL/HDL

cholesterol ratios (65,120) and LDL-cholesterol (118). In the Interheart case-control study (156),

raised ApoB/ApoA1 ratio (odds ratio 3.25 for top versus lowest quintile, population attributable

risks 49.2% for top four quintiles versus lowest quintiles) was related to myocardial infarction. In

our study, was the mean ratio of ApoB/ApoA1 1.666 for 50 cases (0.298 SD) and 0.966 for 55

referents (0.298 SD) (unpaired student´s t-test for cases versus referents: p = 0.001). Conditional

logistic regression on 46 matched sets showed that the odds ratio of ApoB/ApoA1 was 5.66 (95%

CI 1.44 – 22.28). Odds ratio for the highest quartile of ApoB/ApoA1 versus the lowest quartile was

4.20 (95% CI 1.002 – 17.63). So, our data also support the importance of ApoB/ApoA1 as a risk

determinant for a first myocardial infarction.

Lp(a)

75

In multivariate analysis high plasma levels of Lp(a) remained significant risk markers for a first

myocardial infarction in men after adjustment for traditional risk factors (diabetes, smoking,

hypertension, BMI, and cholesterol) and proinsulin, tPA, leptin and ApoA1 (Study III). Our study

and a recent meta-analysis of prospective studies (121) demonstrate a clear association between

Lp(a) and coronary heart disease.

Non-significant synergistic interactions were noted for high plasma levels of Lp(a) in combination

with high plasma levels of leptin or tPA, and between high plasma levels of Lp(a) and low plasma

levels of ApoA1 in men who had two of these metabolic alterations (study III). We have previously

shown that Lp(a) and cholesterol levels act synergistically (144). Concentrations of plasma Lp(a)

and classic vascular risk factors have not been found to be strongly correlated. This suggests that

the influence of Lp(a) is unlikely to be accounted for by effects on, or confounding with, classic

vascular risk factors (121). Although the unique structural features of Lp(a) suggest both

thrombogenic and atherogenic potential, the precise mechanism of Lp(a) action is still uncertain

(63). Lp(a) may acquire a pathogenic profile on entering the arterial wall as a consequence of

modifications effected by factors operating in the inflammatory milieu of the atheromatous vessel

(64). Given this complex picture, it appears that the cardiovascular pathogenicity of Lp(a) is

influenced by both external factors and factors within the wall of the artery (64).

Leptin

In conditional univariate logistic regression analysis, a high plasma concentration of leptin was

associated with significant increase in the risk of first myocardial infarction in men (Study III),

whereas the association disappeared in multivariate analysis after adjustment for traditional risk

factors (diabetes, smoking, hypertension, BMI, and cholesterol) and proinsulin, tPA, Lp(a) and

ApoA1 (Study III). Considering the different designs of this and other studies, including sample

size, choice of primary endpoint, and variables in the multivariate analyses, especially markers of

76

insulin resistance, further epidemiologic and experimental studies are needed to evaluate the role of

leptin as an atherothrombotic factor. Leptin is undoubtly a major regulator of appetite and food

intake and by altering body mass influences insulin sensitivity profoundly (189). However, its

potential, direct peripheral effects on insulin sensitivity are inconsistent and unclear (189).

In a recent study in which the accumulation of subcutaneous and intra-abdominal fat was studied in

insulin-sensitive and insulin-resistant lean and obese individuals, it was concluded that intra-

abdominal fat correlates with insulin resistance, whereas subcutaneous fat deposition correlates with

circulating leptin levels (190). The investigators also concluded that the concurrent increase in these

two metabolically distinct fat compartments is a major explanation for the association between

insulin resistance and elevated circulating leptin concentrations in lean and obese individuals (190).

Proinsulin

In conditional univariate logistic regression analysis, high plasma concentrations of proinsulin was

associated with significant increase in the risk of first myocardial infarction in men (Study III), and

the association remained in multivariate analysis after adjustment for traditional risk factors

(diabetes, smoking, hypertension, BMI, and cholesterol), but disappeared after adjustment for tPA,

Lp(a) and ApoA1 (study III). Because hyperinsulinemia is a reflection of an insulin-resistant state,

it is now increasingly accepted that insulin resistance rather than hyperinsulinemia is proatherogenic

(99). One mechanism that might connect insulin resistance and atherosclerosis is the

antiinflammatory and potential anti-atherosclerotic effect of insulin, which in the presence of

resistance will lead to a proinflammatory state (191). Insulin resistance at the level of the fat cell is

the initiating insult, leading to increased intracellular hydrolysis of triglycerids and release of fatty

acids into the circulation (192). The inability of insulin-resistant fat cells to store triglycerids is very

likely the initial step in the development of the dyslipidemia characteristic of insulin resistance

(192). The findings by several groups that insulin resistance seems to spare the MAP kinase

(mitogen-activated protein kinase) component of the insulin signalling pathway suggest that insulin

77

could be atherogenic by stimulating division and migration of vascular smooth muscle cells (192).

Insulin´s effects on PAI-1 expression may be mediated by the MAP kinase pathway as well (192).

Indeed, thiazolidinediones and other peroxisome proliferator-activated receptor (PPAR ) ligands

inhibit insulin signalling downstream of MAP kinase, and these agents inhibit smooth muscle cell

proliferation and migration (192). Insulin seems to be one of the main regulators of the cytokine-

associated acute-phase reaction, and tumour necrosis factor- and interleukin-6 is increased in the

insulin resistant states of obesity and type II diabetes (191,193). Recent studies suggest that

adipocytokines are major regulators of insulin sensitivity potentially linking insulin resistance and

obesity (189). These effects indicate that hyperinsulinemia could have a key inhibitory role in the

regulation of factors which are central to atherogenesis, plaque rupture and thrombosis, the final

events which precipitate acute myocardial infarction (100).

Methodological considerations

Observational studies such as cohort and case-control studies, are more appropriate than

randomised trials to study certain cause-effect relationships, and are particular useful in the

evaluation of potential risk factors for cardiac disease (11). Although cohort studies are generally

the preferred approach for observational research, their size and complexity have recently given rise

to several alternatives such as the nested case-control study (11). The nested case-control study is a

relatively new observational design whereby a case-control approach is employed within an

established cohort (11). A major advantage of a cohort study over a case-control study is that

individuals who develop the outcome and individuals who do not develop the outcome derive from

the same source population (i.e., the cohort itself) (11). Another advantage is that, unlike the case-

control study, the cohort study allows for measurement of exposures before the outcome occurs, an

appropriate time sequence for a cause-effect relationship (11). There are different possible reasons

for the discrepant results of case-control and more recent nested case-control studies (11). First,

78

selection bias can be introduced in case-control studies because controls are not randomly selected

from the same predefined study cohort as they are in nested case-controls studies (11). Secondly,

case-control studies are susceptible to the problem of reverse causality, which would occur if the

plasma variable levels (measured after the occurrence of the outcome) become elevated as a result

of the outcome itself directly or indirectly (e.g., changes in therapy or renal function) (11).

The prospective design does not eliminate the influence of other determinants and risk factors for

myocardial infarction. Adjustments for known risk factors are usually made in multivariate

analyses, revealing whether the studied factor is independently associated with myocardial

infarction or not. However, prospective epidemiologic studies still may suffer from confounding of

apparent associations by other known risk factors. These intercorrelations probably argue that

studies of fibrinolytic markers and atherothrombosis should statistically control for other risk

factors as “confounding” variables, to determine the independent effect of fibrinolysis. On the other

hand, it might be that such statistical control is inappropriate because risk factors cluster,

particularly those related to insulin resistance, and may operate together to cause atherothrombosis.

Hence, it is propably inappropiate to adjust for some covariates since they may be mediators and

not true confounders. Therefore, both univariate and multivariate epidemiologic data need to be

considered, in conjunction with knowledege of the underlying biologic processes. However, the

question whether there is a causal relationship between the studied factors and myocardial

infarction cannot be answered with this study design.

Limitations of the study

The limited number of cases confers lower statistical power on the study to detect significant group

differences. This also restricted the number of covariates we were able to control for in order to

assess the independent predictive power of the variable of interest. Hence, residual effects of other

confounders might be present and not adjusted for in the statistical analyses. We had no data on

79

waist-to-hip ratio and physical activity, and did not include psychosocial factors, consumption of

fruits, vegetables, and alcohol in our analysis.

The observational natures of the studies do not allow conclusions about causality, but addresses

only indicators of cardiovascular risk.

A potential limitation in the study design was the single baseline examination and blood-sampling

occasion. Variations within-person of the hemostatic variables may therefore contribute to an

under- or overestimation of the risk due to fluctuations (194). Repeated measurements of the

hemostatic factors would admit calculation of the regression dilution bias and increase the precision

of the statistical analyses. However, investigations of the variability for tPA mass and PAI-1

activity show that the within-person variability is smaller than the between-person variability (195),

suggesting that only one blood sample occasion is sufficient in epidemiological studies.

Overview and future directions

Overall, these studies suggest that hemostatic factors, Lp(a), ApoA1 and proinsulin carry predictive

information about the risk of a first myocardial infarction in addition to traditional cardiovascular

risk factors. Neither leptin and MTHFR, nor homocysteine after adjustment for creatinine, were

clinically useful predictors of a greater than normal risk of a first myocardial infarction in the

population of Northern Sweden. Today, measurement of blood pressure, lipids, and glucose,

together with smoking cessation and weight reduction, guides the preventive treatment of ischemic

heart disease. In the Interheart study (156,196), raised ApoB/ApoA1 ratio, smoking, hypertension,

diabetes, abdominal obesity, psychosocial factors (depression, locus of control, perceived stress,

and life events), consumption of fruits, vegetables, and alcohol, and regular physical activity in

combination accounted for 90% of the population attributable risks in men and 94% in women. In a

previous report on our study population, Weinehall et al (139) found that self-reported perceived ill

health was a risk determinant for a first myocardial infarction and an interaction was found between

80

perceived ill health and smoking, hypertension and hypercholesterolemia. Psychosocial stressors

have been related to a hypercoagulable state reflected by increased procoagulant molecules and by

reduced fibrinolytic capacity (197). Understanding the mechanisms by which societal factors affect

the development of risk factors could lead to new approaches to prevent development of coronary

heart disease. Early detection of ongoing processes preceding cardiac events events by utilization of

a combination of biomarkers in the present studies may be useful.

Integration of knowledge involving novel hemostatic biomarkers at the genetic, biochemical, and

clinical-epidemiologic levels should lead to a significant development in understanding the

pathophysiology of arterial thrombotic disease, the assessment of cardiovascular risk, and the

targeting of specific antithrombotic therapies in high-risk individuals.

For instance, treatment with an ACE inhibitor has been shown to decrease not only PAI-1 levels

(198) and rate of cardiovascular events (199) but also the incidence of type 2 diabetes (200). In this

way, PAI-1 could represent a potential target for therapeutic intervention that aims to decrease the

risk of both cardiovascular disease and Type 2 diabetes (201,202). However, further research in this

area is needed before these biomarkers could be used in clinical practice. Furthermore, hemostatic

factors are genetically determined and future studies should be designed to identify key

combinations of polymorphisms of the hemostatic system and to investigate the extent to which

environmental cardiovascular risk factors interact with genetic factors. Future studies in this field

have to include sufficient numbers of women to make it possible to draw conclusions about

cardiovascular risk in females.

In our study 7 cases died within 24 hours and 3 cases within 28 days. Subgroup analysis on cases

developing sudden cardiac death could be valuable to identify individuals who would benefit for

treatment with a prophylactic implantable cardioverter in future research.

Preanalytical handling, precision in measurement, adequate standardization, intra-individual

variability, and finally costs may represent other issues which should be addressed in more detail

before introducing a new disease marker in clinical medicine (203).

81

CONCLUSIONS

High plasma concentrations of tPA and PAI-1 mass, VWF, Lp(a), leptin and proinsulin, and

low plasma concentrations of ApoA1 are associated with subsequent development of a first

myocardial infarction. This relation was also shown in men for tPA, PAI-1, Lp(a), leptin,

proinsulin and ApoA1 and in women for tPA, PAI-1, TM and ApoA1.

High tPA and Lp(a) and low ApoA1 are significant risk markers for a first myocardial

infarction in multivariate analysis with smoking habits, body mass index, hypertension,

cholesterol, and diabetes included as covariates. There are non-significant synergic

interactions between high Lp(a) and leptin and tPA respectively, and between high Lp(a)

and low ApoA1.

Neither homozygosity for the point mutation C677>T in the gene for MTHFR nor

homocysteine was related to a greater than normal risk of a first myocardial infarction.

High homocysteine at follow-up but not at baseline was associated with first myocardial

infarction, but the relation disappeared in multivariate analyses including plasma creatinine

and plasma albumin.

Total plasma homocysteine concentrations during eight and a half years of follow-up

evolved similarly in subjects who developed a first myocardial infarction compared to

referents.

82

ACKNOWLEDGMENTS

I wish to express my deep gratitude and appreciation to all those who, in different ways and during

different periods of time, have contributed to this thesis, and in particular to:

All the patients and referent subjects that participated in the studies.

Associate professor Jan-Håkan Jansson, my tutor, for introducing me to the field of fibrinolysis,

and for sharing his vast knowledge in this field. For never ending enthusiasm, encouragement and

endless support in a fantastic way. For being concise, prompt, honest and having a big humane

insight.

Professor Torbjörn K. Nilsson, my co-tutor, for sharing some of your profound knowledge in the

fields of hemostasis and genetics, for thorough work with manuscripts, for expert supervision of the

analysis of the biomarkers, and for great support.

Professor Per-Olav Wester, former head of the Department of Internal medicine, for introducing me

to research and sharing his profound knowledge in the fields of magnesium therapy in

cardiovascular disease. For encouragement and support.

Professor Göran Hallmans, co-author, for being a visionary and creating a friendly atmosphere, and

taking responsibility of the Medical Biobank at the University of Umeå. For valuable criticism of

manuscripts, and for support.

Professor Kurt Boman, co-author, for fruitful discussions and criticism of the manuscripts,

enthusiasm and encouragement.

83

Professor Kjell Asplund, for providing excellent research conditions and support.

Lars Weinehall Johan Hultdin, Stefan Söderberg, Vivan Lundberg, Owe Johnson and Gösta

Dahlén, co-authors for valuable contributions to the manuscripts, including statistical analyses.

Hans Stenlund for expert statistical assistance and valuable discussions.

Professor Anders Waldenström, for encouragement and kindness.

Professor Tommy Olsson, for encouragement and support.

Research assistant Åsa Ågren, for untiring performance in preparing data for this study.

The county Council of Västerbotten for its persistence in maintaining the community promotion

program care and thereby creating and guaranteeing the study base.

Steffen Helqvist my collegue and office partner. At moments when I was sad, he was the remedy.

For laughter and fun.

My family for love and support, especially my mother Kathrine who has taken care of my son

Christian whenever I needed it.

KUNDSKAB GØR SIG

Kundskab gør sig altid flot

og bør helligt fredes.

Husk i din begejstring blot:

Ku det ikke lissågodt

være anderledes.

GRUK/Piet Hein

84

Freely translated to English:

Knowledge always makes impression

and should holy be preserved.

Remember in your enthusiasm merely:

Couldn´t it just be otherwise.

This study was supported by grants from the Swedish Council for Planning and Coordination of

Research, the Swedish National Public Health Institute, the Swedish Medical Research Council

(27X-07192, -08267 and 6834), Joint Committee of the Northern Sweden Health Care Region,

Heart and Chest Region, Heart and Chest Fund, the Swedish Heart-Lung Foundation, King Gustaf

V´s 80th Anniversary Fund, the Kempe Foundations, the Swedish Council for Forestry and

Agriculture, Västerbotten County Council, Norrbotten County Council and Umeå University.

85

REFERENCES

1. Nyström L, Rosén M, Wall S. Why are diabetes, stomach cancer and circulatory diseases

more common in Northern Sweden? Scand J Prim Health Care 1986; 4: 5-12.

2. Asplund K, Huhtasaari F, Wester PO. [Results from the WHO MONICA study: Northern

Sweden has the highest cardiovascular mortality rate]. Läkartidningen 1988; 85: 3182-3,

3186-7. Swedish.

3. Tunstall-Pedoe H, Kuulasmaa K, Mähönen M, Tolonen H, Ruokokoski E, Amouyel P, for the

WHO MONICA (monitoring trends and determinants in cardiocvascular disease) Project.

Contribution of trends in survival and coronary-event rates to changes in coronary heart

disease mortality: 10-year results from 37 WHO MONICA project populations. Lancet 1999;

353: 1547-57.

4. Messner T, Lundberg V, Boström S, Huhtasaari F, Wikström B. Trends in event rates of first

and recurrent, fatal and non-fatal acute myocardial infarction, and 28-day case fatality in the

Northern Sweden MONICA area 1985-98. Scand J Public Health 2003; 31(Suppl. 61): 51-59.

5. Weinehall L. The emerging epidemic of cardiovascular disease. History and background of

the Northern Sweden initiative on cardiovascular disease. Scand J Public Health 2003; 31

(Suppl. 61): 5-8.

6. Last JM, ed. A dictionary of epidemiology. 4th ed. New York: Oxford University Press, 2001.

7. Burt BA. Definitions of risk. J Dent Educ 2001; 65(10): 1007-8.

8. Beck JD. Risk revisited. Community Dent Oral Epidemiol 1998; 26: 220-5.

9. Hill AB. The environment and disease: association or causation? Proc R Soc Med 1965; 58:

295-300.

10. Rothman KJ & Greenland S. Modern Epidemiology. 1998. 2nd Edn. Lippincott-Raven,

Philadelphia.

11. Essebag V, Genest J Jr, Suissa S, Pilote L. The nested case-control study in cardiology. Am

Heart J 2003; 146: 581-90.

86

12. Davies MJ. The pathophysiology of acute coronary syndromes. Heart 2000; 83: 361-366.

13. Stary HC, Chandler AB, Dinsmore RE, Fuster V, Glagov S, Insull W Jr, Rosenfeld ME,

Schwartz CJ, Wagner WD, Wissler RW. A definition of advanced types of atherosclerotic

lesions and a histological classification of atherosclerosis. A report from the committee on

vascular lesions of the council on arteriosclerosis, American Heart Association. Circulation

1995; 92: 1355-1374.

14. Zaman AG, Helft G, Worthley SG, Badimon JJ. The role of plaque rupture and thrombosis in

coronary artery disease. Atherosclerosis 2000; 149: 251-266.

15. Cines DB, Pollak ES, Buck CA, Loscalzo J, Zimmerman GA, McEver RP, Pober JS, Wick

TM, Konkle BA, Schwartz BS, Barnathan ES, McCrae KR, Hug BA, Schmidt A-M, Stern

DM. Endothelial cells in physiology and in the pathophysiology of vascular disorders. Blood

1998; 91: 3527-3561.

16. Becker BF, Heindl B, Kupatt C, Zahler S. Endothelial function and hemostasis. Z Kardiol

2000; 89: 160-167.

17. Gawaz M. Role of platelets in coronary thrombosis and reperfusion of ischemic myocardium.

Cardiovasc Res 2004; 61: 498-511.

18. Harrison´s Principles of Internal Medicine. 15th Edition, Braunwald E, Fauci AS, Kasper DL,

Hauser SL, Longo DL, Jameson JL. London, McGraw-Hill, 2001. Bleeding and thrombosis:

354-358.

19. Stassen JM, Arnout J, Deckmyn H. The hemostatic system. Curr Med Chem 2004; 11: 2245-

60.

20. Kohler HP, Grant PJ. Plasminogen-activator inhibitor type 1 and coronary artery disease. N

Engl J Med 2000; 342: 1792-1801.

21. Collen D. The plasminogen (fibrinolytic) system. Thromb Haemost. 1999; 82: 259-70.

87

22. Nilsson TK, Wallén PB. The fibrinolytic system: biochemistry and assay methods. Clinical

Aspects of Fibrinolysis pp. 9-53. Edited by T.K. Nilsson, K. Boman and J. H. Jansson.

Almqvist & Wiksell International, Stockholm-Sweden 1991.

23. Folsom AR. Hemostatic risk factors for atherothrombotic disease: an epidemiologic view.

Thromb Haemost 2001; 86: 366-73.

24. Chandler WL, Jascur ML, Henderson PJ. Measurement of different forms of tissue

plasminogen activator in plasma. Clin Chem. 2000; 46: 38-46.

25. Declerk PJ, Alessi MC, Versterken M, Kruithof EK, Juhan-Vague I, Collen D. Measurement

of plasminogen activator inhibitor 1 in biologic fluids with a murine monoclonal antibody-

based enzyme-linked immunosorbent assay. Blood 1988; 71: 220-5.

26. Booth NA. Fibrinolysis and thrombosis. Baillière´s Best Pract Res Clin Haematol 1999; 12:

423-433.

27. Ladenvall P, Nilsson S, Jood K, Rosengren A, Blomstrand C, Jern C. Genetic variation at the

human tissue-type plasminogen activator (tPA) locus: haplotypes and analysis of association

to plasma levels of tPA. Eur J Hum Genet 2003; 11: 603-610.

28. Hrafnkelsdottir T, Gudnason T, Wall U, Jern C, Jern S. Regulation of local availability of

active tissue-type plasminogen activator in vivo in man. J Thromb Haemost 2004; 2: 1960-8.

29. Ladenvall P, Wall U, Jern S, Jern C. Identification of eight novel single-nucleotide

polymorphisms at human tissue-type plasminogen activator (t-PA) locus: association with

vascular t-PA release in vivo. Thromb Haemost 2000; 84: 150-5.

30. Ladenvall P, Johansson L, Jansson JH, Jern S, Nilsson TK, Tjärnlund A, Jern C, Boman K.

Tissue-type plasminogen activator –7,351C/T enhancer polymorophism is associated with a

first myocardial infarction. Thromb Haemost 202; 87: 105-9.

31. Emeis JJ. Regulation of the acute release of tissue-type plasminogen activator from the

endothelium by coagulation activation products. Ann N Y Acad Sci. 1992; 667: 249-58.

88

32. Jansson J-H, Teger-Nilsson A-C. Drug effects on the fibrinolytic system. Clinical Aspects of

Fibrinolysis pp. 111-129. Edited by T.K. Nilsson, K. Boman and J. H. Jansson. Almqvist &

Wiksell International, Stockholm 1991.

33. Boman K. Life style and fibrinolysis. Clinical Aspects of Fibrinolysis pp. 55-66. Edited by

T.K. Nilsson, K. Boman and J. H. Jansson. Almqvist & Wiksell International, Stockholm

1991.

34. Nilsson T, Wallen P, Mellbring G. In vivo metabolism of human tissue-type plasminogen

activator. Scand J Haematol. 1984; 33: 49-53.

35. Camani C, Kruithof EKO. Clearance receptors for tissue-type plasminogen activator. Int J

Hematol 1994; 60: 97-109.

36. Otter M, Kuiper J, van Berkel TJC, Rijken DC. Mechanisms of tissue-type plasminogen

activator (tPA) clearance by the liver. Ann N Y Acad Sci. 1992; 667: 431-42.

37. Chandler WL, Alessi MC, Aillaud MF, Henderson P, Vague P, Juhan-Vague I. Clearance of

tissue plasminogen activator (TPA) and TPA/plasminogen activator inhibitor type 1 (PAI-1)

complex: relationship to elevated TPA antigen in patients with high PAI-1 activity levels.

Circulation. 1997; 96: 761-8.

38. Lowe GDO, Danesh J, Lewington S, Walker M, Lennon L, Thomson A, Rumley A, Whincup

PH. Tissue plasminogen activator antigen and coronary heart disease. Prospective study and

meta-analysis. Eur Heart J 2004; 25: 252-259.

39. Cesari M, Rossi GP. Plasminogen activator inhibitor type 1 in ischemic cardiomyopathy.

Arterioscler Thromb Vasc Biol 1999; 19: 1378-1386.

40. Gils A, Declerck PJ. The structural basis for the pathophysiological relevance of PAI-1 in

cardiovascular diseases and the development of potential PAI-1 inhibitors. Thromb Haemost

2004; 91: 425-37.

41. Huber K, Christ G, Wojta J, Gulba D. Plasminogen activator inhibitor type-1 in

cardiovascular disease. Status report 2001. Thromb Res 2001; 103: S7-S19.

89

42. Ruggeri ZM. Von Willebrand factor, platelets and endothelial cell interactions. J Thromb

Haemost 2003; 1: 1335-42.

43. Lip GYH, Blann A. von Willebrand factor: a marker of endothelial dysfunction in vascular

disorders? Cardiovascular Research 1997; 34: 255-265.

44. Sadler JE. Biochemistry and genetics of von Willebrand factor. Annu Rev Biochem. 1998;

67: 395-424.

45. Wagner DD. Cell biology of von Willebrand factor. Annu Rev Cell Biol. 1990; 6: 217-46.

46. Whincup PH, Danesh J, Walker M, Lennon L, Thomson A, Appleby P, Rumley A, Lowe

GDO. von Willebrand factor and coronary heart disease. Prospective study and meta-analysis.

Eur Heart J 2002; 23: 1764-1770.

47. Danesh J, Wheeler JG, Hirschfiels GM, Eda S, Eiriksdottir G, Rumley A, Lowe GDO, Pepys

MB, Gudnason V. C-reactive protein and other circulating markers of inflammation in the

prediction of coronary heart disease. N Engl J Med 2004; 350: 1387-97.

48. Romani de Wit T, van Mourik JA. Biosynthesis, processing and secretion of von Willebrand

factor: biological implications. Best Prac Res Clin Haematol 2001; 14: 241-255.

49. Erem C, Ersoz HÖ, Karti SS, Ukinç K, Hacihasanoglu A, De ger O, Teletar M. Blood

coagulation and fibrinolysis in patients with hyperthyroidism. J Endocrinol Invest 2002; 25:

345-350.

50. Lo B, Fijnheer R, Castigliego D, Borst C, Kalkman CJ, Nierich AP. Activation of hemostasis

after coronary artery bypass grafting with or without cardiopulmonary bypass. Anesth Analg

2004; 99: 634-640.

51. Reiner AP, Siscovick DS, Rosendaal FR. Hemostatic risk factors and arterial thrombotic

disease. Thromb Haemost 2001; 85: 584-95.

52. Conway EM, Wouwer MVd, Pollefeyt S, Jurk K, Aken HV, Vriese AD, Weitz JI, Weiler H,

Hellings PW, Schaeffer P, Herbert J-M, Collen D, Theilmeier G. The lectin-like domain of

thrombomodulin confers protection from neutrophil-mediated tissue damage by suppressing

90

adhesion molecule expression via nuclear factor B and mitogen-activated protein kinase

pathways. J Exp Med 2002; 196: 565-77.

53. Esmon CT. Inflammation and thrombosis. J Thromb Haemost 2003; 1: 1343-8.

54. Tannenbaum C, Barrett-Connor E, Laughlin GA, Platt RW. A longitudinal study of

dehydroepiandrosterone sulphate (DHEAS) change in older men and women: the Rancho

Bernardo Study. Eur J Endocrin 2004; 151: 717-725.

55. Tchernof A, Labrie F. Dehydroepiandrosterone, obesity and cardiovascular disease risk: a

review of human studies. Eur J Endocrin 2004; 151: 1-14.

56. Muller M, van der Schouw YT, Thijssen JHH, Grobbee DE. Endogenous sex hormones and

cardiovascular disease in men. J Clin Endocrinol Metab 2003; 88: 5076-5086.

57. Khaw KT. Dehydroepiandrosterone, dehydroepiandrosterone sulphate and cardiovascular

disease. J Endocrinol 1996; 150: S149-53.

58. Schwartz AG, Pashko LL. Dehydroepiandrosterone, glucose-6-phosphate dehydrogenase, and

longevity. Ageing Res Rev 2004; 3: 171-187.

59. Beer NA, Jakubowicz DJ, Matt DW, Beer RM, Nestler JE. Dehydroepiandrosterone reduces

plasma plasminogen activator inhibitor type 1 and tissue plasminogen activator antigen in

men. Am J Med Sci 1996; 311: 205-210.

60. Hajjar KA, Nachman RL. The role of lipoprotein(a) in atherogenesis and thrombosis. Annu

Rev Med 1996; 47: 423-42.

61. Boerwinkle E, Leffert CC, Lin J, Lackner C, Chiesa G, Hobbs HH. Apolipoprotein(a) gene

accounts for greater than 90% of the variation in plasma lipoprotein(a) concentrations. J Clin

Invest 1992; 90: 52-60.

62. Maeda S, Abe A, Seishima M, Makino K, Noma A, Kawade M. Transient changes of serum

lipoprotein(a) as an acute phase protein. Atherosclerosis 1989; 78: 145-150.

91

63. Dangas G, Mehran R, Harpel PC, Sharma SK, Marcovina SM, Dube G, Ambrose JA, Fallon

JT. Lipoprotein(a) and inflammation in human coronary atheroma: association with the

severity of clinical presentation. JACC 1998; 32: 2035-42.

64. Scanu AM. Lp(a) lipoprotein – Coping with heterogeneity. N Engl J Med 2003; 349: 2089-

2090.

65. Rader DJ, Hoeg JM, Brewer HB Jr. Quantitation of plasma apolipoproteins in the primary and

secondary prevention of coronary artery disease. Ann Intern Med 1994; 120: 1012-1025.

66. Cattaneo M. Hyperhomocysteinemia, atherosclerosis and thrombosis. Thromb Haemost 1999;

81: 165-176.

67. Gauthier GM, Keevil JG, McBride PE. The association of homocysteine and coronary artery

disease. Clin Cardiol 2003; 26: 563-568.

68. Brattström L, Wilcken DEL, Ohrvik J, Brudin L. Common methylenetetrahydrofolate

reductase gene mutation leads to hyperhomocysteinemia but not to vascular disease: The

results of a meta-analysis. Circulation 1998; 98: 2520-6.

69. Francis ME, Eggers PW, Hostetter TH, Briggs JP. Association between serum homocysteine

and markers of impaired kidney function in adults in the United States. Kidney Int 2004; 66:

303-12.

70. Frantzen F, Faaren AL, Alfheim I, Nordhei AK. Enzyme conversion immunoassay for

determining total homocysteine in plasma or serum. Clin Chem 1998; 44: 311-316.

71. Moghadasian MH, McManus BM, Frohlich JJ. Homocyste(e)ine and coronary artery disease.

Clinical evidence and genetic and metabolic background. Arch Intern Med 1997; 157: 2299-

308.

72. Welch GN, Loscalzo J. Homocysteine and atherothrombosis. N Engl J Med 1998; 338: 1042-

1050.

92

73. Majors A, Ehrhart LA, Pezacka EH. Homocysteine as a risk factor for vascular disease:

enhanced collagen production and accumulation by smooth muscle cells. Arterioscler Thromb

Vasc Biol 1997; 17(10): 2074-81.

74. Tsai JC, Perrella MA, Yoshizumi M, Hsieh CM, Haber E, Schlegel R, Lee ME. Promotion of

vascular smooth muscle cell growth by homocysteine: A link to atherosclerosis. Proc Natl

Acad Sci USA 1994; 91(14): 6369-73.

75. Tyagi SC. Homocysteine redox receptor and regulation of extracellular matrix components in

vascular cells. Am J Physiol 1998; 274(2 Pt 1): C396-405.

76. Mujumdar VS, Aru GM, Tyagi SC. Induction of oxidative stress by homocyst(e)ine impairs

endothelial function. J Cell Biochem 2001; 82(3): 491-500.

77. Hajjar KA. Homocysteine-induced modulation of tissue plasminogen activator binding to its

endothelial cell membrane receptor. J Clin Invest 1993; 91: 2873-2879.

78. Harpel PC, Borth W. Identification of mechanisms that may modulate the role of

lipoprotein(a) in thrombosis and atherogenesis. Ann Epidemiol 1992; 2: 413-417.

79. Harpel PC, Chang VT, Borth W. Homocysteine and other sulfhydryl compounds enhance the

binding of lipoprotein(a) to fibrin: A potential biochemical link between thrombosis,

atherogenesis, and sulfhydryl compound metabolism. Proc Natl Acad Sci USA 1992; 89:

10193-10197.

80. Lentz SR, Sadler JE. Inhibition of thrombomodulin surface expression and protein C

activation by the thrombogenic agent homocysteine. J Clin Invest 1991; 88: 1906-1914.

81. Chen YF, Li PL, Zou AP. Effect of hyperhomocysteinemia on plasma or tissue adenosine

levels and renal function. Circulation 2002; 106: 1275-1281.

82. Inscho EW. Modulation of renal microvascular function by adenosine. Am J Physiol Regul

Integr Comp Physiol 2003; 285: R23-R25.

93

83. Jakubowski H, Zhang L, Bardeguez A, Aviv A. Homocysteine thiolactone and protein

homocysteinylation in human endothelial cells: Implications for atherosclerosis. Circ Res

2000; 87: 45-51.

84. Gallagher PM, Meleady R, Shields DC, Tan KS, McMaster D, Rozen R, Evans A, Graham

IM, Whitehead AS. Prevention of cardiovascular disease: homocysteine and risk of premature

coronary heart disease. Evidence for a common gene mutation. Circulation 1996; 94: 2154 –

2158.

85. Kang SS, Zhou J, Wong PWK, Kowalisyn J, Strokosch G. Intermediate homocysteinemia: a

thermolabile variant of methylenetetrahydrofolate reductase. Am J Hum Genet 1988; 43: 414-

421.

86. Frosst P, Blom HJ, Milos R, Goyette P, Sheppard CA, Matthews RG, Boers GJH, den Heijer

M, Kluijtmans LAJ, van den Heuvel LP, Rozen R. A candidate genetic risk factor for vascular

disease: a common mutation in methylenetetrahydrofolate reductase. Nat Genet 1995; 10:

111-113.

87. Jacques PF, Bostom AG, Williams RR, Ellison RC, Eckfeldt JH, Rosenberg IH, Selhub J,

Rozen R. Relation between folate status, a common mutation in methylenetetrahydrofolate

reductase, and plasma homocysteine concentrations. Circulation 1996; 93: 7 – 9.

88. Klerk M, Verhoef P, Clarke R, Blom HJ, Kok FJ, Schouten EG, and the MTHFR Studies

Collaboration Group. MTHFR 677C>T polymorphism and risk of coronary heart disease: A

meta-analysis. JAMA 2002; 288: 2023-2031.

89. Grundy SM, Hansen B, Smith SC Jr, Cleeman JI, Kahn RA; for Conference Participants.

Clinical management of metabolic syndrome. Report of the American Heart

Association/National Heart, Lung, and Blood Institute/American Diabetes Association

Conference on Scientific Issues Related to Management. Circulation 2004; 109:551-556.

90. Lindahl B, Asplund K, Eliasson M, Evrin P-E. Insulin resistance syndrome and fibrinolytic

activity: the Northern Sweden MONICA study. Int J Epidemiol 1996; 25: 291-299.

94

91. Isomaa B. A major health hazard: The metabolic syndrome. Life Sciences 2003; 73: 2395-

2411.

92. Grundy SM, Brewer HB, Cleeman JI, Smith SC Jr, Lenfant C; for Conference Participants.

Definition of metabolic syndrome. Report of the National Heart, Lung, and Blood

Institute/American Heart Association Conference on Scientific Issues Related to Definition.

Circulation 2004; 109: 433-438.

93. Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, Salonen

JT. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged

men. JAMA 2002; 288: 2709-2716.

94. Chevenne D, Trivin F, Porquet D. Insulin assays and reference values. Review. Diabetes

Metab. 1999; 25: 459-76.

95. Temple RC, Clark PMS, Nagi DK, Schneider AE, Yudkin JS, Hales CN. Radioimmunoassay

may overestimate insulin in non-insulin-dependent diabetics. Clin Endocrin 1990; 32: 689-93.

96. Sobey WJ, Beer SF, Carrington CA, Clark PMS, Frank BH, Gray IP, Luzio SD, Owens DR,

Schneider AE, Siddle K, Temple RC, Hales CN. Sensitive and specific two-site

immunoradiometric assays for human insulin, proinsulin, 65-66 split and 32-33 split

proinsulins. Biochem J 1989; 260: 535-541.

97. Saltiel AR. Putting the brakes on insulin signaling. N Engl J Med 2003; 349: 2560-2562.

98. Saltiel AR, Kahn CR. Insulin signaling and the regulation of glucose and lipid metabolism.

Nature 2001; 414: 799-806.

99. Dandona P, Aljada A, Chaudhuri A, Bandyopadhyay A. The potential influence of

inflammation and insulin resistance on the pathogenesis and treament of atherosclerosis-

related complications in type 2 diabetes. J Clin Endocrinol Metab 2003; 88: 2422-2429.

100. Dandona P, Aljada A, Mohanty P. The anti-inflammatory and potential anti-atherogenic effect

of insulin: a new paradigm. Diabetologia 2002; 45: 924-930.

101. Ahima RS, Flier JS. Leptin. Annu Rev Physiol 2000; 62: 413-437.

95

102. Margetic S, Gazzola C, Pegg GC, Hill RA. Leptin: a review of its peripheral actions and

interactions. Int J Obes 2002; 26: 1407-1433.

103. Fantuzzi G, Faggioni R. Leptin in the regulation of immunity, inflammation, and

hematopoiesis. J Leukoc Biol 2000; 68: 437-446.

104. Nakata M, Yada T, Soejima N, Maruyama I. Leptin promotes aggregation of human platelets

via the long form of its receptor. Diabetes 1999; 48: 426-9.

105. Hosoi M, Yamakawa K, Koyama H, Fukumoto S, Inaba M, Okuno Y, Nishizawa Y, Morii H.

Leptin increases plasminogen activator inhibitor-1 (PAI-1) production in human vascular

smooth muscle cell. Diabetes 1998; 47: A118 (463). Abstract.

106. Frühbeck G. Pivotal role of nitric oxide in the control of blood pressure after leptin

administration. Diabetes 1999; 48: 903-8.

107. Parhami F, Tintut Y, Ballard A, Fogelman AM, Demer LL. Leptin enhances the calcification

of vascular cell. Artery wall as a target of leptin. Circ Res 2001; 88: 954-960.

108. Grimble RF. Inflammatory status and insulin resistance. Curr Opin Clin Nutr Metab Care

2002; 5: 551-9.

109. Folsom AR, Aleksic N, Park E, Salomaa V, Juneja H, Wu KK. Prospective study of

fibrinolytic factors and incident coronary heart disease. The Atherosclerosis Risk in

Communities (ARIC) Study. Arterioscler Thromb Vasc Biol 2001; 21: 611-617.

110. Lowe GDO, Yarnell JWG, Sweetnam PM, Rumley A, Thomas HF, Elwood PC. Fibrin D-

dimer, tissue plasminogen activator, plasminogen activator inhibitor, and the risk of major

ischaemic heart disease in the Caerphilly Study. Thromb Haemost 1998; 79: 129-33.

111. Ridker PM, Vaughan DE, Stampfer MJ, Manson JE, Hennekens CH. A prospective study of

plasminogen activator inhibitor and the risk of future myocardial infarction. Circulation 1992;

85 [Suppl 1]; I-325 (abstr).

96

112. Cushman M, Lemaitre R, Kuller LH, Psaty BM, Macy EM, Sharrett AR, Tracy RP.

Fibrinolytic activation markers predict myocardial infarction in the elderly: The

Cardiovascular Health Study. Arterioscler Thromb Vasc Biol 1999; 19: 493-498.

113. Morange PE, Simon C, Alessi MC, Luc G, Arveiler D, Ferrieres J, Amouyel P, Evans A,

Ducimetiere P, Juhan-Vague I, on behalf of the PRIME study Group. Endothelial cell markers

and the risk of coronary heart disease. The prospective epidemiological study of myocardial

infarction (PRIME) study. Circulation 2004; 109: 1343-1348.

114. Salomaa V, Matei C, Aleksic N, Sansores-Garcia L, Folsom AR, Juneja H, Chambless LE,

Wu KK. Soluble thrombomodulin as a predictor of incident coronary heart disease and

symptomless carotid artery atherosclerosis in the Atherosclerosis Risk in Communities

(ARIC) Study: a case-cohort study. Lancet 1999; 353: 1729-34.

115. Wu FCW, von Eckardstein A. Androgens and coronary artery disease. Endocrine Reviews

2003; 24: 183-217.

116. Nilsson T, Mellbring G, Damber J-E. Relationships between tissue plasminogen activator,

steroid hormones and deep vein thrombosis. Acta Chir Scand 1985; 151: 515-519.

117. Luc G, Bard J-M, Ferriéres J, Evans A, Amouyel P, Arveiler D, Fruchart J-C, Ducimetière P,

on behalf of the PRIME Study Group. Value of HDL cholesterol, apolipoprotein A-1,

lipoprotein A-1, and lipoprotein A-1/A-II in prediction of coronary heart disease. The PRIME

study. Arterioscler Thromb Vasc Biol 2002; 22: 1155-1161.

118. Walldius G, Jungner I, Holme I, Aastveit AH, Kolar W, Steiner E. High apolipoprotein B,

low apolipoprotein A-I, and improvement in the prediction of fatal myocardial infarction

(AMORIS study): a prospective study. Lancet 2001; 358: 2026-33.

119. Qureshi AI, Giles WH, Croft JB, Guterman LR, Hopkins LN. Apolipoproteins A-1 and B and

the likelihood of non-fatal stroke and myocardial infarction – data from the Third National

Health and Nutrition Examination Survey. Med Sci Monit 2002; 8: CR311-316.

97

120. Lamarche B, Moorjani S, Lupien PJ, Cantin B, Bernard PM, Dagenais GR, Despres JP.

Apolipoprotein A-I and B levels and the risk of ischemic heart disease during a five-year

follow-up of men in the Québec Cardiovascular Study. Circulation 1996; 94: 273-278.

121. Danesh J, Collins R, Peto R. Lipoprotein(a) and coronary heart disease. Meta-analysis of

prospective studies. Circulation 2000; 102: 1082-1085.

122. Luc G, Bard J-M, Arveiler D, Ferrieres J, Evans A, Amouyel P, Fruchart J-C, Ducimetiere P,

on behalf of the PRIME Study Group. Lipoprotein(a) as a predictor of coronary heart disease:

the PRIME study. Atherosclerosis 2002; 163: 377-384.

123. Ruige JB, Assendelft WJJ, Dekker JM, Kostense PJ, Heine RJ, Bouter LM. Insulin and risk of

cardiovascular disease. A meta-analysis. Circulation 1998; 97: 996-1001.

124. Dunder K, Lind L, Zethelius B, Berglund L, Lithell H. Evalutation of a scoring scheme,

including proinsulin and the apolipoprotein B/apolipoprotein A1 ratio, for the risk of acute

coronary events in middle-aged men: Uppsala Longitudinal Study of Adult Men (ULSAM).

Am Heart J 2004; 148: 596-601.

125. Zethelius B, Byberg L, Hales CN, Lithell H, Berne C. Proinsulin is an independent predictor

of coronary heart disease. Report from a 27-year follow-up study. Circulation 2002; 105:

2153-2158.

126. Yudkin JS, May M, Elwood P, Yarnell JWG, Greenwoood R, Smith GD. Concentrations of

proinsulin like molecules predict coronary heart disease risk independently of insulin:

prospective data from the Caerphilly Study. Diabetologia 2002: 45: 327-336.

127. Couillard C, Lamarche B, Mauriège P, Cantin B, Dagenais GR, Moorjani S, Lupien PJ,

Després JP. Leptinemia is not a risk factor for ischemic heart disease in men. Prospective

results from the Quebeck Cardiovascular Study. Diabetes Care 1998; 21: 782-786.

128. Wallace AM, McMahon AD, Packard CJ, Kelly A, Sheperd J, Gaw A, Sattar N; on behalf of

the WOSCOPS Executive Committee. Plasma leptin and the risk of cardiovascular disease in

98

the west of Scotland coronary prevention study (WOSCOPS). Circulation 2001; 104: 3052-

3056.

129. Söderberg S, Ahrén B, Jansson J-H, Johnson O, Hallmans G, Asplund K, Olsson T. Leptin is

associated with increased risk of myocardial infarction. J Intern Med 1999; 246: 409-418.

130. Wald DS, Law M, Morris JK. Homocysteine and cardiovascular disease: evidence on

causality from a meta-analysis. BMJ 2002; 325: 1202-8.

131. The Homocysteine Studies Collaboration. Homocysteine and risk of ischemic heart disease

and stroke. A Meta-analysis. JAMA 2002; 288: 2015-2023.

132. O´Leary CM, Knuiman MW, Divitini ML. Homocysteine and cardiovascular disease: a 17-

year follow-up study in Busselton. Eur J Cardiovasc Prev Rehabil 2004; 11: 350-351.

133. Weinehall L. Partnership for health. On the role of primary health care in a community

intervention programme. PhD thesis. Umeå, Sweden, 1997.

134. Anon. [Västerbotten Intervention Program Manual.] Umeå, Sweden: Västerbotten County

Council, Department of Community Medicine, 1996 (In Swedish).

135. Hallmans G, Ågren Å, Johansson G, Johansson A, Stegmayr B, Jansson J-H, Lindahl B,

Rolandsson O, Söderberg S, Nilsson M, Johansson I, Weinehall L. Cardiovascular disease and

diabetes in the Northern Sweden Health and Disease Study Cohort – evaluation of risk factors

and their interactions. Scand J Public Health 2003; 31(Suppl. 61): 18-24.

136. Johansson L. Hemostatic factors in cardiovascular disease with special reference to stroke.

Medical dissertation. Umeå, Sweden, 2002.

137. Weinehall L, Hallgren CG, Westman G, Janlert U, Wall S. Reduction of selection bias in

primary prevention of cardiovascular disease through involvement of primary health care.

Scand J Prim Health Care 1998; 16: 171-6.

138. Stegmayr B, Lundberg V, Asplund K. The events registration and survey procedures in the

Northern Sweden MONICA Project. Scand J Public Health 2003; 31(Suppl. 61): 9-17.

99

139. Weinehall L, Johnson O, Jansson J-H, Boman K, Huhtasaari F, Hallmans G, Dahlén GH,

Wall S. Perceived health modifies the effect of biomedical risk factors in the prediction of

acute myocardial infarction. An incident case-control study from Northern Sweden. J Intern

Med 1998; 243: 99-107.

140. Wright BM, Dore CF. A random-zero sphygmanometer. Lancet 1970; i: 337-8.

141. Cejka J. Enzyme immunoassay for factor VIII-related antigen. Clin Chem 1982; 28: 1356-

1358.

142. Amiral J, Adam M, Mimilia F, Larrivaz I, Chambrette B, Boffa MC. A new assay for soluble

forms of thrombomodolin in plasma. Thromb Haemostas 1991; 947: 65. Abstract.

143. Amiral J, Adam M, Mimilla F, Larrivaz I, Chambrette B, Boffa MC. Design and validation of

a new immunoassay for soluble forms of thrombomodolin and studies on plasma. Hybridoma

1994; 13: 205-13.

144. Dahlén GH, Weinehall L, Stenlund H, Jansson J-H, Hallmans G, Huhtasaari F, Wall S.

Lipoprotein(a) and cholesterol levels act synergistically and apolipoprotein A-1 is protective

for the incidence of primary acute myocardial infarction in middle-aged males. An incident

case-control study from Sweden. J Intern Med 1998; 244: 425-430.

145. Lindahl B, Dinesen B, Eliasson M, Røder M, Jansson J-H, Huhtasaari F, Hallmans G. High

proinsulin concentration precedes acute myocardial infarction in a nondiabetec population.

Metabolism 1999; 48: 1197-1202.

146. Kjems LL, Røder ME, Dinesen B, Hartling SG, Jørgensen PN, Binder C. Higly sensitive

enzyme immunoassay of proinsulin immunoreactivity with use of two monoclonal antibodies.

Clin Chem 1993; 39: 2146-2150.

147. Andersen L, Dinesen B, Jørgensen PN, Poulsen F, Røder ME. Enzyme immunoassay for

intact human insulin in serum or plasma. Clin Chem 1993; 39: 578-582.

148. Shipchandler MT, Moore EG. Rapid, fully automated measurement of plasma homocyst(e)ine

with the Abbott Imx Analyzer. Clin Chem 1995; 41: 991-94.

100

149. Ma HW, Cheng J, Caddy B. Extraction of high quality genomic DNA from microsamples of

human blood. J Forensic Sci Soc 1994; 34: 231-235.

150. Emery AEH. Hardy-Weinberg equilibrium and the estimation of gene frequencies. In: Emery

AEH (editor): Methodology in medical genetics; an introduction to statistical methods.

Edinburgh: Churchill Livingstone, 1976. pp 3-9.

151. Breslow NE, Day NE. Statistical methods in cancer research. Volume 1 – The analysis of

case-control studies. International agency for research on cancer. Lyon, 1980 (IARC

Scientific Publications No.32).

152. Hallqvist J, Ahlbom A, Diderichsen F, Reuterwall C. How to evaluate interaction between

causes: a review of practices in cardiovascular epidemiology. J Intern Med 1996; 239: 377-

382.

153. Hosmer DW, Lemeshow S. Confidence interval estimation of interaction. Epidemiology

1992; 3: 452-456.

154. Stampfer MJ, Malinow MR, Willett WC, Newcomer LM, Upson B, Ullmann D, Tishler PV,

Hennekens CH. A prospective study of plasma homocyst(e)ine and risk of myocardial

infarction in US physicians . JAMA 1992; 268: 877 – 881.

155. Söderberg S, Jansson J-H, Ahren B, Jonsson O, Hallmans G, Asplund K, Olsson T. Leptin,

tPA and Lp(a) are associated with increased risk of myocardial infarction. Circulation 1999;

100: 3914. Abstract.

156. Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P,

Varigos J, Lisheng L, on behalf of the INTERHEART Study Investigators. Effect of

potentially modifiable risk factors associated with myocardial infarction in 52 countries (the

INTERHEART study): case-control study. Lancet 2004; 364: 937-52.

157. Kullo IJ, Gau GT, Tajik J. Novel risk factors for atherosclerosis. Mayo Clin Proc 2000; 75:

369-380.

101

158. Juhan-Vague I, Alessi MC, Vague P. Increased plasma plasminogen activator inhibitor 1

levels. A possible link between insulin resistance and atherothrombosis. Diabetologia 1991;

34: 457-462.

159. Jansson J-H, Boman K, Brännström M, Nilsson TK. High concentration of thrombomodulin

in plasma is associated with hemorrhage: a prospective study in patients receiving long-term

anticoagulant treatment. Circulation 1997; 96: 2938-43.

160. Fareed J, Messmore HL. Plasma thrombomodulin level as a predictor of hemorrhagic (and

thrombotic) events in patients on long-term anticoagulant treatment. Circulation. 1997; 96:

2765-8.

161. Bladbjerg EM, Andersen-Ranberg K, De Maat MP, Kristensen SR, Jeune B, Gram J,

Jespersen J. Longevity is independent of common variations in genes associated with

cardiovascular risk. Thromb Haemost 1999; 82: 1100-5.

162. Brattström L, Zhang Y, Hurtig M, Refsum H, Östensson S, Fransson L, Jonés K, Landgren F,

Brudin L, Ueland PM. A common methylenetetrahydrofolate reductase gene mutation and

longevity. Atherosclerosis 1998; 141: 315-319.

163. Gluckman PD, Hanson MA. Living with the past: evolution, development, and patterns of

disease. Science 2004; 305: 1733-1736.

164. Nurk E, Tell GS, Vollset SE, Nygård O, Refsum H, Nilsen RM, Ueland PM. Changes in

lifestyle and plasma total homocysteine: the Hordaland Homocysteine Study. Am J Clin Nutr

2004; 79: 812-9.

165. Clarke R, Lewington S, Landray M. Homocysteine, renal function, and risk of cardiovascular

disease. Kidney Int 2003: (84): S131-S133.

166. Moustapha A, Naso A, Nahlawi M, Gupta A, Arheart KL, Jacobsen DW, Robinson K, Dennis

VW. Prospective study of hyperhomocysteinemia as an adverse cardiovascular risk factor in

end-stage renal disease. Circulation 1998; 97: 138-141.

102

167. Jungers P, Massy ZA, Khoa TN, Fumeron C, Labrunie M, Lacour B, Descamps-Latscha B,

Man NK. Incidence and risk factors of atherosclerotic cardiovascular accidents in predialysis

chronic renal failure patients: A prospective study. Nephrol Dial Transplant 1997; 12: 2597-

2602.

168. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risk of

death, cardiovascular events, and hospitalization. N Engl J Med 2004; 351: 1296-305.

169. Anavekar NS, McMurray JJV, Velazquez EJ, Solomon SD, Kober L, Rouleau J-L, White HD,

Nordlander R, Maggioni A, Dickstein K, Zelenkofske S, Leimberger JD, Califf RM, Pfeffer

MA. Relation between renal dysfunction and cardiovascular outcomes after myocardial

infarction. N Engl J Med 2004; 351: 1285-95.

170. Toole JF, Malinow MR, Chambless LE, Spence JD, Pettigrew LC, Howard VJ, Sides EG,

Wang CH, Stampfer M. Lowering homocysteine in patients with ischemic stroke to prevent

recurrent stroke, myocardial infarction, and death. The vitamin intervention for stroke

prevention (VISP) randomized controlled trial. JAMA 2004; 291: 565-575.

171. Lange H, Suryapranata H, De Luca G, Börner C, Dille J, Kallmayeer K, Pasalary MN,

Scherer E, Dambrink J-H E. Folate therapy and in-stent restenosis after coronary stenting. N

Engl J Med 2004; 350: 2673-81.

172. Schnyder G, Roffi M, Pin R, Flammer Y, Lange H, Eberli FR, Meier B, Turi ZG, Hess OM.

Decreased rate of coronary restenosis after lowering of plasma homocysteine levels. N Engl J

Med 2001; 345: 1593-600.

173. Herrmann HC. Prevention of cardiovascular events after percutaneous coronary intervention.

N Engl J Med 2004; 350: 2708-10.

174. Burke AP, Fonseca V, Kolodgie F, Zieske A, Fink L, Virmani R. Increased serum

homocysteine and sudden death resulting from coronary atherosclerosis with fibrous plaques.

Arterioscler Thromb Vasc Biol 2002; 22: 1936-1941.

103

175. Kuller LH, Eichner JE, Orchard TJ, Grandits GA, McCallum L, Tracy RP, for the Multiple

Risk factor Intervention Trial Research Group. The relation between serum albumin levels

and risk of coronary heart disease in the Multiple Risk factor Intervention Trial. Am J

Epidemiol 1991; 134: 1266-1277.

176. Danesh J, Collins R, Appleby P, Peto R. Association of fibrinogen, C-reactive protein,

albumin, or leukocyte count with coronary heart disease. Meta-analyses of prospective

studies. JAMA 1998; 279: 1477-1482.

177. Djoussé L, Rothman KJ, Cupples A, Levy D, Ellison RC. Serum albumin and risk of

myocardial infarction and all-cause mortality in the Framingham Offspring Study. Circulation

2002; 106: 2919-2924.

178. Law MR, Morris JK, Wald NJ, Hale AK. Serum albumin and mortality in the BUPA study.

Int J Epidemiol 1994; 23: 38-41.

179. Corti MC, Salive ME, Guralnik JM. Serum albumin and physical function as predictors of

coronary heart disease mortality and incidence in older persons. J Clin Epidemiol 1996; 49:

519-526.

180. Kuller LH, Tracy RP, Shaten J, Meilahn EN for the MRFIT Research Group. Relation of C-

reactive protein and coronary heart disease in the MRFIT nested case-control study. Am J

Epidemiol 1996; 144: 537-547.

181. Tracy RP, Lemaitre RN, Psaty BM, et al. Relationship of C-reactive protein to risk of

cardiovascular disease in the elderly. Results from the Cardiovascular Health Study and the

Rural Health Promotion Project. Arterioscler Thromb Vasc Biol 1997; 17: 1121-1127.

182. Gabay C, Kushner I. Acute phase proteins and other systemic responses to inflammation. N

Engl J Med 1999; 340: 448-54.

183. Goldwasser P, Feldman J. Association of serum albumin and mortality risk. J Clin Epidemiol

1997; 50: 693-703.

104

184. Halliwell B. Albumin - an important extracellular antioxidant? Biochem Pharmacol 1988; 37:

569-71.

185. Wayner DDM, Burton GW, Ingold KU, Locke S. Quantitative measurement of the total,

peroxyl radical-trapping antioxidant capability of human blood plasma by controlled

peroxidation. The important contribution made by plasma proteins. FEBS Lett 1985; 187: 33-

7.

186. Luoma PV, Näyhä S, Sikkilä K, Hassi J. High serum alpha-tocopherol, albumin, selenium and

cholesterol, and low mortality from coronary heart disease in Northern Finland. J Intern Med

1995; 237: 49-54.

187. Zoellner H, Höfler M, Beckmann R, Hufnagl P, Vanyek E, Bielek E, Wojta J, Fabry A,

Lockie S, Binder BR. Serum albumin is a specific inhibitor of apoptosis in human endothelial

cells. J Cell Sci 1996; 109: 2571-80.

188. Gillum RF. Assessment of serum albumin concentration as a risk factor for stroke and

coronary disease in African Americans and whites. J Natl Med Assoc 2000; 92: 3-9.

189. Fasshauer M, Paschke R. Regulation of adipocytokines and insulin resistance. Diabetologia

2003; 46: 1594-1603.

190. Cnop M, Landchild MJ, Vidal J, Havel PJ, Knowles NG, Carr DR, Wang F, Hull RL, Boyko

EJ, Retzlaff BM, Walden CE, Knopp RH, Kahn SE. The concurrent accumulation of

intraabdominal and subcutaneous fat explains the association between insulin resistance and

plasma leptin concentrations: distinct metabolic effects of two fat compartments. Diabetes

2002; 51: 1005-1015.

191. Dandona P, Aljada A, Bandyopadhyay A. Inflammation: the link between insulin resistance,

obesity and diabetes. Trends Immunol 2004; 25: 4-7.

192. Ginsberg HN. Insulin resistance and cardiovascular disease. J Clin Invest 2000; 106: 453-458.

193. Fernández-Real JM, Ricart W. Insulin resistance and chronic cardiovascular inflammatory

syndrome. Endocrine Reviews 2003; 24 (3): 278-301.

105

194. Sakkinen PA, Macy EM, Callas PW, Cornell ES, Hayes TE, Kuller LH, Tracy RP. Analytical

and biologic variability in measures of hemostasis, fibrinolysis, and inflammation: assessment

and implications for epidemiology. Am J Epidemiol. 1999; 149: 261-7.

195. de Maat MP, de Bart ACW, Hennis BC, Meijer P, Havelaar AC, Mulder PGH, Kluft C.

Interindividual and intraindividual variability in plasma fibrinogen, TPA antigen, PAI

activity, and CRP in healthy, young volunteers and patients with angina pectoris. Arterioscler

Thromb Vasc Biol. 1996; 16: 1156-62.

196. Rosengren A, Hawken S, Ôunpuu S, Sliwa K, Zubaid M, Almahmeed WA, Blackett KN,

Sitthi-amorn C, Sato H, Yusuf S, for the Interheart investigators. Association of psychosocial

risk factors with risk of acute myocardial infarction in 11 119 cases and 13648 controls from

52 countries (the INTERHEART study): case-control study. Lancet 2004; 364: 953-62.

197. von Känel R, Mills PJ, Fainman C, Dimsdale JE. Effects of psychological stress and

psychiatric disorders on blood coagulation and fibrinolysis: a biobehavioral pathway to

coronary artery disease? Psychosom Med 2001; 63: 531-544.

198. Boman KOA, Jansson J-H, Nyhlén KA, Nilsson TK. Improved fibrinolysis after one year

treatment with enalapril in men and women with uncomplicated myocardial infarction.

Thromb Haemost 2002; 87: 311-6.

199. The Heart Outcome Prevention Evaluation Study Investigators. Effects of an angiotensin-

converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients. N Engl J

Med 2000: 342: 145-53.

200. Hansson L, Lindholm LH, Niskanen L, Lanke J, Hedner T, Niklason A, Luomanmæki K,

Dahløf B, de Faire U, Mørlin C, Karlberg BE, Wester PO, Bjørk J-E. Effect of angiotensin-

converting-enzyme inhibition compared with conventional therapy on cardiovascular

morbidity and mortality in hypertension: the Captopril Prevention Project (CAPPP)

randomized trial. Lancet 1999; 353: 611-6.

106

201. Juhan-Vague I, Alessi M-C, Mavri A, Morange PE. Plasminogen activator inhibitor-1,

inflammation, obesity, insulin resistance and vascular risk. J Thromb Haemost 2003; 1: 1575-

9.

202. Festa A, D´Agostino R Jr, Tracy RP, Haffner SM. Elevated levels of acute-phase proteins and

plasminogen activator inhibitor-1 predict the development of Type 2 diabetes. The Insulin

Resistance Atherosclerosis Study. Diabetes 2002; 51: 1131-7.

203. Koenig W. Is measuring endothelial function a good idea for prediction of coronary heart

disease complications? Eur Heart J 2002; 23: 1728-1730.

107