Ministero dell'Istruzione,dell'Università e della
Ricerca
Università degliStudi di Palermo
Dottorato di Ricerca in
Medicina Sperimentale e Molecolare
XXIII ciclo
Metabolic Syndrome as putative independent associated/risk factor for Alzheimer’Disease and Mild Cognitive Impairment
Tesi di Dottorato della:
Dott.ssa Caterina Claudia Ventimiglia
Dipartimento di Biomedicina Sperimentale e Neuroscienze Cliniche
Tutor: Chiar.mo Prof. Cecilia Camarda
Settore scientifico-disciplinare MED/26
Coordinatore:
Chiar.mo Prof. Giovanni Zummo
INTRODUCTION
1
Metabolic syndrome (MetS) is a cluster of vascular risk factors
[1] that is well established to increase the risk of diabetes,
cardiovascular disease, and stroke [2, 3]. MetS also appears to
increase the risk of age-associated cognitive decline, overall dementia,
and vascular dementia (VaD) in particular [4], but the role of MetS in
Alzheimer’s disease (AD) remains inconclusive from the contrasting
findings reported so far [5–11].
Amnestic Mild Cognitive Impairment (aMCI) is presumably a
pathological-based prodromal stage of AD with an annual rate of
conversion to dementia of 5 to 10% in community-based populations
[12] and 10 to 15% among those in specialty clinics [13]. Only a few
studies have investigated the relationship between MetS and MCI [14–
16] and they provided very limited findings to form firm conclusions on
the role of MetS in aMCI and AD.
2
The Multiple Outcomes of Raloxifene Evaluation (MORE)
study showed an association between MetS and an increased risk of
developing cognitive impairment (defined as a composite outcome
comprising clinically adjudicated dementia or MCI or cognitive
impairment not clinically adjudicated) during a 4-year period in older
women [15]. The study showed that the number of MetS components
increased the risk of developing cognitive impairment with
hyperglycemia as the only MetS component associated with a higher
risk of cognitive impairment. Unfortunately, this study lacked the power
to analyze the effect of MetS on the risk of developing MCI or AD
alone. Subsequently, a cross-sectional, population-based study with
1,969 participants from Olmsted Country, MN, USA, found no
significant association of MetS with MCI overall or aMCI, and only the
combination of MetS and high levels of inflammation was significantly
associated with non-amnestic MCI (naMCI) [14].
3
More recently, the Italian Longitudinal Study of Ageing (ILSA)
reported no significant differences in overall risk of developing incident
MCI in non-cognitively impaired individuals with MetS compared with
those without MetS over 3.5-year follow-up [16].
APOE- 4 genotype has been found to be associated with an
increased risk of AD [17] and conversion from MCI to AD [18]. The
association of APOE-Σ4 with AD is reduced in older cases [19],
however, none of the abovementioned research has examined the
modifying effects of APOE-Σ4 and age on the association between
MetS and aMCI.
In the present dissertation, the association between MetS and
aMCI in a population sample of older adults from the CogItA study was
studied. I investigated whether MetS and its individual components,
were associated with aMCI. I also investigated the possible effects of
APOE-Σ4 genotype status and age in influencing the association
between MetS and aMCI and MetS and AD .
4
I hypothesized that among individuals carrying the APOE-Σ4
allele there would be an association between MetS and aMCI and AD.
5
MATERIAL AND METHODS
Population
Data from the Cognitive Impairment through Aging (CogItA)
study were used. The CogItA study is a large hospital-based
observational study including a cross-sectional and longitudinal
prospective begun in January 2000 and still ongoing. The main aim of
the project is to collect data from adult-to-elderly subjects aged 45
years or over with normal cognition, cognitive impairment and
cognitive disorders and to evaluate the determinants of individual
differences in cognitive ageing and/or the putative risk factors for the
conversion from normal cognition to cognitive impairment and/or
dementia at follow-up.
CogIta’s subjects were recruited from a large sample of
outpatients who enrolled voluntarily for health screening at the Centre
for Aging Brain and Dementia, the Movement Disorders Centre, the
Headache Centre and the Adult General Neurology Centre of the
6
Department of Experimental Biomedicine and Clinical Neurosciences
(BioNeC), Faculty of Medicine, University of Palermo. The study was
approved by the Medical Ethical Committee of the Faculty of Medicine
affiliated Hospital (AOUP “P.Giaccone”).
In the CogIta study, inclusion criteria were the presence of an
informant and age 45 years. Exclusion criteria were presence of
systemic diseases (cardiac, hepatic or renal failure, cancer or blood
diseases); history of significant head injury, severe sensory
impairment, mental retardation, severe psychiatric disorders, epilepsy
and metabolic, immunological, demyelinating and neoplastic brain’s
diseases. After a complete description of the study, and signing the
written informed consent subjects performed neurological,
neuropsychological and laboratory examinations. All subjects were
evaluated with the same examination procedures. Using a structured,
comprehensive and teasing questionnaire administered to the patient
by trained medical personnel, all possible medical information and
7
patient’s previous hospital records were collected in order to reach a
confident evaluation of subject’s health status. Collected data included
demographic characteristics, education (expressed as years of
schooling), occupational status, marital status, lifestyle habits (alcohol
and coffee consumption, smoking habits), family history of migraine,
epilepsy, psychiatric disturbances, stroke, dementia, diabetes mellitus,
hypertension and hyperlipidemias, osteoporosis, personal medical
history including thyroid diseases, head injuries, bladder disturbances,
gait and balance problems, falls in the last year, hip fractures, visual
and hearing impairment, vascular risk factors and vascular diseases,
actual and previous pharmacological treatments registered in a
structured way, evaluation of co-morbidity, body mass index (BMI),
metabolic syndrome. All these information were defined according to
the currently most widely accepted criteria, selected after a systematic
literature search.
8
An overnight fasting venous blood sample was taken to each
subject for laboratory blood tests including glucose, lipids levels,
triglyceride, homocysteine, and APOE genotyping. Diabetes mellitus
was defined as glucose ≥ 110 (7.0mmol/L), haemoglobin A1c of ≥
6,5% or use of oral antidiabetic drugs or insulin. Hyperlipidemia was
defined as a total cholesterol ≥ 240 mg/dL (> 5.0 mmol/L) or low-
density lipoprotein cholesterol (≥ 160 mg/dL) or high-density
lipoprotein cholesterol < 40 mmol/L in men and < 50 mmol/L in
women and/or the use of cholesterol lowering drugs.
Hypertriglyceridemia was defined as a plasma triglyceride ≥ 150
mg/dL. Hyperhomocysteinemia was defined as a plasma
homocysteine ≥ 13 micromol/L. [20]. Height was measured withouth
shoes and weight and waist circumference were measured withouth
heavy clothing, and the body mass index (BMI) was calculated
(Kg/m2). Blood pressure (mmHg) was measured twice with a
sphygmomanometer and the average of the two measures was
9
calculated. Hypertension was defined as a mean systolic blood
pressure ≥ 140 mmHg or a mean diastolic pressure ≥ 95 mmHg or use
of antihypertensive drugs. Smoking, coffee intake was categorized as
never or current. Lastly, all subjects were evaluated with a dedicated
neurological examination including a careful evaluation of the primitive
reflexes.
Functional, Neuropsychological and neuropsychiatric assessment
The CogItA protocol included a large assessment containing
several tests evaluating disability, cognition, behaviour and
comorbidity.
The functional status was assessed with the Basic Activities
of Daily Living (BADL) [21] and the Instrumental Activities of Daily
Living (IADL) [22] scales.
10
The neuropsychological assessment included the Mini Mental
State Examination (MMSE), as test of general cognition [23], and
specific tests to assess the following five cognitive domains: (1) verbal
memory [Story Recall Test] and the immediate and delayed recall of
Rey’s Auditory Verbal Learning Test; (2) executive functioning (Raven
Coloured Matrices, Letter Fluency and the Frontal Assessment
Battery; (3) language (Token Test for verbal comprehension and the
naming subtest of the Aachener Aphasie test; (4) selective and
divided attention (Visual Search Test,Trail Making Test part A and B ;
(5) and visuospatial and constructional abilities (Copy Drawing Test
and the position discrimination subtest of the Visual Object and Space
Perception test and construttive apraxia. Details on administration
procedures and Italian normative data for score adjustment based on
age and education as well as normality cut-off scores (>95% of the
lower tolerance limit of the normal population distribution) were
available [24-30]. The neuropsychiatric assessment included the
11
Neuropsychiatric Inventory [31] which evaluate the presence and
severity of 12 non-cognitive symptoms in the month previous the last
examination, as well as tests for the evaluation of depression ( Cornell
Depression Scale) [32] and Hospital Anxiety and Depression Scale,
depression subscore) [34]. Anxiety symptoms were evaluated through
the Hamilton Anxiety Rating Scale [33] and Hospital Anxiety and
Depression Scale, anxiety subscore) [34].
Assessment of comorbidity
Somatic comorbidity was quantified by the Cumulative Illness
Rating Scale (CIRS) [35], which evaluates a score to the total burden
of illness of 13 body systems (cardiac, hypertension, vascular,
respiratory disease, eye-nose-throat dysfunction, upper and lower
gastro-intestinal disease, hepatic, renal or genitor-urinary disease,
musculoskeletal disease, neurological disease and
endocrine/metabolic disease), ranging from no disease (score = 1) to
12
life-threatening disease (score = 5). The CIRS illness severity index
was also calculated, as summary score based on the average of all
CIRS items.
Furthermore, the following vascular risk factors and diseases
were evaluated:
(a) Vascular risk factors:
- Current smoking: included all subject with current smoking (any
amount at least in the last five years);
- Hypertension, diabetes mellitus, hypercholesterolaemia with low-
and high-density lipoprotein cholesterol, hypertrigliceridaemia,
hyperhomocysteinemia as previously defined,
- Obesity (body mass index ≥30)
- Carotid atherosclerosis (degree of stenosis ≥50% of the internal
carotid arteries assessed by colour Doppler ultrasound);
- Intima-media tickness ( assessed as a value ≥ 1,1 mm)
13
(b) Vascular diseases:
- Coronary ischaemic heart disease (as evidenced by medical history
of myocardial infarction, angina, coronary artery bypass graft or
angioplasty and/or detected by EKG),
- Atrial fibrillation (evidenced by medical history and/or detected by
EKG, and/or treatment with dipiridamole or warfarin)
- Cardiac Valvulopaties and Rythm disturbances (evidenced by
medical history and documented by cardiological records)
- TIA/Stroke (evidenced by medical history and/or detected by
significant lesion on CT or MRI brain or confirmed by neurological
examination)
In the present study, subjects with previous stroke documented
by clinical history or CT/MRI scan positive for stroke were excluded.
On the contrary, subjects showing silent strokes on CT/MRI done
during the investigation were not excluded.
14
For each subject, all data collected were recorded on a
computer by means of a dedicated data entry programme, and the
data acquired were processed for quality control and statistical
analysis.
APOE genotyping from blood samples was done using the
DNA PCR amplification and single nucleotide extension technique.
Patients with either one or both 4 alleles were considered as 4 carriers
15
Neuroimaging
Carotid arteries duplex ultrasonography was
performed in all subjects to measure the intima-media
thickness (IMT) in the left and right common carotid arteries
by the mean value of six measurements [36]. IMT is a marker
for the extent of subclinical atherosclerosis. Stenosis of
internal carotid arteries was graded according to NASCET
trials [37] as low-degree stenosis (0% to 40%), moderate
stenosis (50% to 60%), and hemodinamically relevant
stenosis (≥ 70%).
All subjects underwent brain scans either CT or MRI.
Due to the prevalent epidemiological-clinical design of our
projects, and to the fact than in our country the number of
MRI scanners is limited whereas the less expensive CT
scanners are numerous and are the most used brain imaging
tool worldwide, we did not advise a common scanning
protocol and we allowed the use of different machineries.
The MRI equipment used operated from 0.5 to 1.5 T.
Axial T1- and T2-weighted images, axial fluid-attenuated
16
inversion recovery and proton density images were used.
Slice thickness was 5mm mm.
Findings on CT/MRI images were evaluated on the
computer screen by one experienced radiologist and two
trained neurologists who were blinded to subject’s clinical
data examined.
Brain atrophy
With the assumption that ventricular enlargement
basically reflects brain tissue loss either at cortical level as
well as at white matter axonal tracts, global brain atrophy
was determined within the axially acquired images on CT and
MRI using a multiplicity of linear distances measures using a
transparent metric ruler: a) the bifrontal span of the lateral
ventricle, b) the width of the lateral ventricles at the head of
the caudate nucleus, c) the minimum width of the bodies of
the lateral ventricles at the waist. For these three ventricular
measurements (a,b,c, above), ratios were determined by
dividing the values obtained by the maximum width of the
skull at the same level as the bifrontal span, caudate nuclei
17
an lateral ventricles measurement, resulting the following
ratios : bifrontal ratio, bicaudate ratio, lateral ventricular ratio.
Brain atrophy was evaluated semi-quantitatively using
the bicaudate ratio. Within the axially acquired images those
on which the two caudate nuclei produced the greatest
indentation on the lateral ventricles was selected, the
distance between the two caudate apices ie the ventricular
dimension, was measured in millimeters and divided by the
maximum width of the skull at the same level as the caudate
measurement. With this simple measurements, the highest
is the ventricular enlargement the highest is the distance
between the two caudate nuclei resulting in a higher
bicaudate ratio. Therefore, a larger value of bicaudate ratio
indicates a greater degree of atrophy.
Vascular lesions
Vascular lesions were classified according to size
(lacuna, defined as area of tissue destruction 3-10 mm in
diameter with their centre isointense to CFS on MRI and
18
hypodense on CT, or infarction), number (single or multiple)
and size of the vessels involved (large vessels, small vessels
or combined). Large-vessel cortical-subcortical infarcts were
considered as well-defined areas with an abnormal TC/MRI
signal in a specific vascular distribution territory with no mass
effect. Small-vessel lacunar infarcts were considered areas
with an abnormal TC/MRI signal sized ≥ 10 mm in diameter
(small subcortical infarcts) located in the subcortical white
matter, thalamus, nucleo-capsular region or basal ganglia.
The number of lacunes and small-vessel lacunar infarcts was
categorized into none =0, one=1 (1 lacuna/lacunar infarct),
few =2 (2 to 3 lacunes/lacunar infarcts), and many= 3 (4
lacunes/lacunar infarcts or more). For each hemisphere, the
brain areas used for rating the location of lacunes and lacunar
infarcts were the same rated for white matter lesion (WML)
by Wahlund et al [38] : frontal, parieto-occipital, temporal,
infratentorial (brainstem/cerebellum) and basal ganglia
(striatum,/globus pallidus, thalamus, internal/external
capsule). The region-specific scores of both hemispheres were
summed in order to use both the total categorized number
19
of lacunes (range 0 to 30) and the partial degree for brain
regions (range 0 to 24) and basal ganglia (range 0 to 6). The
same modalities of categorization and scoring were used for
small lacunar infarcts. For the following analyses, the
presence of ≥1 focal lesion in at least one brain region, it
was scored as “presence of lacuna/lacunar infarct”.
White Matter Lesion [WML].
WML involving the periventricular and deep sub-
cortical white matter were defined as areas of ill-defined
hypodensity on CT scans (leukoaraiosis) and areas with high
signal intensities on proton-density and T2-weighted MRI
scans. The presence, location, and severity of WML on MRI
were rated visually according to the Walhund scale [38]
applicable to both CT and MRI and to the a 4-point visual
scale of Fazekas et al. [39] applicable to MRI only. Using the
Fazekas scales [39], WML were assessed as periventricular
hyperintensities (WML-PV) or deep, subcortical, wither
matter hyperintensities (WML-SB). WML-PV were graded as
follow: Grade 0= no changes, Grade 1 = “caps” or pencil-thin
lining, Grade 2 = smooth “halo”, Grade 3 = irregular
20
periventricular WML extending into the deep with matter.
WML-SB were graded as follow: Grade 0 = no changes, Grade
1 = mild WML punctuate foci single or “grouped” WM lesions
below 10 and 20 mm respectively); grade 2= moderate WML
(single lesion between 10 and 20 mm; areas of “grouped”
lesions more than 20 mm in diameter; no “connecting
bridges” between individual lesions, grade 3= severe WML
(single lesion or confluent areas of WML 20 mm in diameter;
selective deep WML separate from periventricular regions).
The presence of caps on anterior and posterior horns of the
lateral ventricles and of pencil-thin lining of periventricular
WML corresponding to Fazekas’s WML-PV grade 1 was
defined as absence of WML. Fazekas’s WML-PV grade 2 and
Fazekas’s WML-SC grade 1 were defined as presence of
mild WML, whereas Fazekas’s WML-PV grade 3 and
Fazekas’s WML-SC grade 2 and 3 were defined as presence
of severe WML. Using the Whalund scale [38], WML were
defined as images of ≥ 5 mm hyperintense on T2,PD, or
FLAIR images and hypointense on CT and were rated
visually as follow: 0= no lesions (including symmetrical, well-
21
defined caps or bands); 1= focal lesions; 2= beginning
confluence of lesions; 3= diffuse involvement of the entire
region ,with or without involvement of U fibers. For each
hemisphere, the brain areas used for rating were: frontal,
parieto-occipital, temporal, infratentorial
(brainstem/cerebellum) and basal ganglia (striatum, globus
pallidus, thalamus, internal/external capsule, and insula). The
region-specific scores of both hemispheres were summed in
order to use both the total degree of WML (range 0 to 30)
and the partial degree of WML for brain regions (range 0 to
24) and basal ganglia (range 0 to 6). For the following
analyses when a score of ≥1 focal lesion in at least one
brain region was observed, it was scored as “presence of
WML”.
22
Diagnostic criteria for AD
NINDS-ADRDA Diagnostic criteria for Alzheimer's Disease
(AD) [40] were used to diagnostic AD subjects. Core diagnostic criteria
for AD subjects was the presence of an early and significant episodic
memory impairment that includes the following features:
- gradual and progressive change in memory function reported by
patients or informants over more than 6 months;
23
- objective evidence of significantly impaired episodic memory on
testing: this generally consists of recall deficit that does not improve
significantly or does not normalise with cueing or recognition testing
and after effective encoding of information has been previously
controlled;
- the episodic memory impairment can be isolated or associated with
other cognitive changes at the onset of AD or as AD advances
We did not have the opportunity of evaluate supportive
features for AD as the presence of medial temporal lobe atrophy and
of abnormal cerebrospinal fluid biomarkers (low amyloid β1–42
concentrations, increased total tau concentrations, or increased
phospho-tau concentrations, or combinations of the three)
Diagnostic criteria for amnestic mild cognitive impairment [aMCI]
aMCI was defined according to criteria recommended by the
MCI Working Group of the European Consortium on AD [41], which is
24
cognitive decline relative to previous abilities during the past year
reported by patient or informant; impairment in memory domain;
essentially normal functional activities; and absence of dementia.
The operational criteria included: 1) Subjective cognitive
complaints from a single question asking whether subject had more
problems with memory than most, or a single ‘yes or-no’ informant
report of memory decline, “Do you think your family member’s memory
or other mental abilities have declined?”; 2) Memory impairment was
defined as a score that was 1.5 SD below age education adjusted
norms of the Rey Auditory Verbal Learning Test (RAVLT) and delayed
recall or the Short story and delayed recall; 3) functional independence
was defined with respect to performing ten basic activities of daily
living (BADL) [31]: bowels, bladder, grooming, toilet use, feeding,
transferring, mobility, dressing, stairs, and bathing; 4) The absence of
dementia was defined by the presence of (i) Mini-Mental State
Examination (MMSE) [23] score more than 24, or (ii) Clinical Dementia
25
Rating (CDR) scale [42] global score of 0,5 and Sum of Boxes score
less than 3 [43].
Cognitively healthy controls
Cognitively healthy controls were identified from participants
with no subjective memory complaints, whose cognitive test
performance on delayed memory recall from the RAVLT and BVMT-R,
attention and executive function (RCPM, Phonemic Fluency, Attentive
Matrices), visual-spatial ability (Constructive Apraxia), and language
(Aachener denomination, Token Test) were above−1.5 SD of age-
education adjusted norms, were functionally independent on BADL,
and did not have dementia.
Metabolic syndrome
26
MetS was defined using the International Diabetes Federation
criteria [1]. Based on this definition, patients must have central obesity
(waist circumference ≥90 for male and ≥80 for female) plus at least
two of the following components: raised triglyceride level (≥150 mg/dL
(1.7 mmol/L) or specific treatment for this lipid abnormality); reduced
high density lipoprotein (HDL) cholesterol (<40 mg/dL (1.03 mmol/L) in
males, and <50 mg/dL (1.29 mmol/L) in females or specific treatment
for this lipid abnormality); raised blood pressure (BP) (systolic BP≥130
or diastolic BP≥85mm Hg, or treatment of previously diagnosed
hypertension), and raised fasting plasma glucose (FPG) (≥100 mg/dL
(5.6 mmol/L), or previously diagnosed type 2 diabetes).
Self-report of a physician diagnosis of diabetes, hypertension,
or treatment for these conditions was ascertained by interview.
Participants were asked to show all their current medications to the
research nurses during interviews, details of drugs use for diabetes,
hypertension,
27
Statistical analysis
Means among groups were analysed by one-way analisys of
variance (ANOVA), while contingency tables were evaluated by the -
test.
The association between cognitive status, MetS and putative risk
factors/diseases was investigated with binary multiple logistic
regression analyses, controlling for age, sex and education (model 1).
A subsequent model included other significant variables which resulted
significant from the model 1, and age, sex and education was added
(model 2). All tests were two-tailed; statistical significance was set at p
≥0.05. Results are presented as odds ratios (ORs) with 95%
confidence intervals (95% CIs). All analyses were performed using the
SPSS statistical package version 12.0 (SPSS Inc., Chicago, Ill., USA).
28
RESULTS
Fig. 1 shows the flow diagram of the CogItA study at 30 July
2012. Among the 6948 selected participants, we excluded subjects
without imaging (n. 657), young (n.1372), partecipants with previous
stroke (n. 69), meaningful neurological examination (n. 56),
Parkinson’s disease (n. 441) and vascular parkinsonism (n. 60), VaD
29
(n. 146), and naMCI (n. 551). Therefore, the present study involved
3665 participants (n. 1748 controls, n. 1180 aMCI and n. 737 AD).
Demographics, comorbidity scores, vascular risk factors and
vascular imaging scores of our sample are reported in Tab 1.
The mean age of the controls participants was 61.9 (±10.7), the
mean (±SD) education score was 8.6 (±4.5) and the mean (±SD) mild
subcortical atrophy was 0.12 (±0.02).
About 64.7% (n = 1131) were female, 32.3% (n = 565) were
current smokers, 36.8% (n = 644) had hypercholesterolemia, 3.1% (n
= 54) had hyperuricemia, 58.3% (n = 256) had hyperhomocysteinemia,
39.6% (n = 692) had depression, 41.7% (n = 729) had anxiety, 3.7% (n
= 65) had atrial fibrillation, 8.2% (n = 144) had ischemic cardiopathy,
15.5% (n = 56) had cardiac valvulopaties, 28.5% (n = 434) had intima-
media tickness, 1.4% (n = 22) had carotid stenosis, 15.1% (n = 102)
had APOE-4, 5.9% (n = 104) had TIA, 11.5% (n = 201) had WML,
0.8% (n = 14) had stroke, and 16.2% (n = 284) had lacunae, 34.3 % (n
30
= 481) had MetS, 23.1 % (n = 319) had Hypertension, 20.6 % (n =
294) had diabetes, 22.1 % (n = 315) had hypertrygliceridemia, 64.4%
(n = 1112) had obesity and 29.0% (n = 375) raised high-density
lipoprotein.
The mean age of the aMCI participants was 69.8 (±9.5), the
mean (±SD) education score was 6.9 (±4.6)and the mean (±SD) mild
subcortical atrophy was 0.15 (±0.02).
About 53.9% (n = 636) were female, 37.2% (n = 439) were
current smokers, 39.3% (n = 464) had hypercholesterolemia, 7.5% (n
= 88) had hyperuricemia, 68.5% (n = 490) had hyperhomocysteinemia,
57.3% (n = 676) had depression, 45.5% (n = 537) had anxiety, 6.0% (n
= 71) had atrial fibrillation, 13.3% (n = 156) had ischemic cardiopathy,
30.9% (n = 68) had cardiac valvulopaties, 51.9% (n = 595) had intima
media tickness, 4.3% (n = 49) had carotid stenosis, 18.2% (n = 162)
had APOE-4, 7.8% (n = 92) had TIA, 27.0% (n = 319) had WML, 8.1%
(n = 96) had stroke, and 31.9% (n = 376) had lacunae, 38.3 % (n =
31
403) had MetS, 24.2% (n = 218) had hypertension, 25.2 % (n = 270)
had diabetes, 23.3% (n = 248) had hypertrygliceridemia, 59.2% (n =
682) had obesity and 30.1% (n = 304) raised high-density lipoprotein.
The mean age of the AD participants was 76.5 (±7.5), the
mean (±SD) education score was 4.7 (±3.5)and the mean (±SD) mild
subcortical atrophy was 0.17 (±0.02).
About 68.2% (n = 503) were female, 23.3% (n = 172) were
current smokers, 33.6% (n = 248) had hypercholesterolemia, 6.1% (n
= 45) had hyperuricemia, 76.1% (n = 322) had hyperhomocysteinemia,
53.5% (n = 333) had depression, 33.0% (n = 243) had anxiety, 9.0% (n
= 66) had atrial fibrillation, 15.5% (n = 113) had ischemic cardiopathy,
21.2% (n = 25) had cardiac valvulopaties, 70.2% (n = 482) had intima
media tickness, 4.4% (n = 30) had carotid stenosis, 28.6% (n = 152)
had APOE-4, 4.2% (n = 31) had TIA, 34.9% (n = 257) had WML, 1.6%
(n = 12) had stroke, and 24.8% (n = 183) had lacunae, 29.4% (n =
168) had hypertension, 25.5 % (n = 166) had diabetes, 25.9% (n =
32
169) had hypertrygliceridemia, 69.8% (n = 469) had obesity, and
38.1% (n = 235) raised high-density lipoprotein.
Cognitively healthy controls participants compared with aMCI
and AD were significantly younger, had higher education level and
lower percentage of comorbidity and lower levels of hyperuricemia
and hyperhomocystenemia. Furthermore, depression, atrial fibrillation,
ischemic cardiopathy, intima-media tickness, carotid stenosis, WML,
lacunae, higher mild subcortical atrophy level, MetS, diabetes, raised
high-density lipoprotein were more frequently present in aMCI and AD.
Healthy controls had lower percentage of smoking, and anxiety
than aMCI, and higher percentage than AD patients. Healthy controls
had higher percentage of obesity than aMCI and had lower percentage
than AD patients. Arterial hypertension and APOE-Σ4 were less
present in healthy controls than in AD subjects. Cardiac valvulopaties,
TIAs and stroke were less present in healthy controls than in aMCI
subjects.
33
Table 2 shows the multivariate associations of those vascular
risk factors, imaging scores and MetS components that at the
univariate analysis resulted positively associated in Controls versus
aMCI and in Controls versus AD.
In the adjusted model for sex, age and education (model 1), in
wich cognitively healthy controls were compared with aMCI, smoking
(OR = 1.3; 95% CI 1.1–1.6), hyperuricemia (OR = 1.8; 95% CI 1.1–
2.4), depression (OR = 2.5; 95% CI 2.1–3.0), anxiety (OR = 1.6; 95%
CI 1.3–1.9), cardiac valvulopathies (OR = 1.7; 95% CI 1.1–2.7), intima-
media tickness (OR = 1.6; 95% CI 1.3–1.9), carotid stenosis (OR =
2.0; 95% CI 1.2–3.4), WML (OR = 1.9; 95% CI 1.5–2.3), stroke (OR =
13.2; 95% CI 7.3–24.1), lacunae (OR = 1.6; 95% CI 1.4–2.0), mild
subcortical atrophy (OR = 1.9; 95% CI 5.8–6.4) and obesity (OR = 0.7;
95% CI 0.6–0.8) were significantly associated with increased odds of
aMCI. Adjustment for demographic and clinical covariates including
vascular risk factor and neuroimaging measurements (model 2)
34
reduced the estimate of the odd ratio for aMCI leaving statistically
significant depression (OR = 2.3; 95% CI 1.3–4.2), stroke (OR = 4.2;
95% CI 1.3–13.7), mild subcortical atrophy (OR = 2.5; 95% CI 2.4–2.6)
and obesity (OR = 0.5; 95% CI 0.3–0.8) only.
In the adjusted model for sex, age and education (model 1), in
wich cognitively healthy controls were compared with AD subjects,
depression (OR = 2.3; 95% CI 1.3–4.2), intima-media tickness (OR =
1.9; 95% CI 1.5–2.5), APOE-Σ4 (OR = 3.0; 95% CI 2.0–4.3), WML
(OR = 1.9; 95% CI 1.4–2.4), mild subcortical atrophy (OR = 1.1; 95%
CI 2.8–4.7) and obesity (OR = 0.7; 95% CI 0.5–0.8) were significantly
associated with increased odds of AD. Adjustment for demographic
and clinical covariates including vascular risk factor and neuroimaging
measurements modestly reduced the estimate of the odd ratio leaving
statistically significant depression (OR = 1.7; 95% CI 1.2–2.4), APOE-
4 (OR = 2.4; 95% CI 1.6–3.8) and mild subcortical atrophy (OR = 7.2;
95% CI 6.2–8.4) only.
35
Tab. 3 shows the association between MetS and aMCI
subjects stratified for age, APOE-Σ4 variously combinated. It appears
from the table that MetS was significantly associated with increased
odds in subjects aged ≤ 65 years.
Table 4 shows the association between MetS and AD subjects
stratified for age, APOE-Σ4 variously combinated.
It appears from the table that MetS was significantly
associated with increased odds in all subjects. Furthemore, MetS
was significantly associated with AD independently of the type of
APOE. When APOE-Σ4 carriers and age were associated, MetS was
significantly associated with increased odds in AD subjects aged ≥ 65
years. By the end, when non APOE-Σ4 carriers and age were
associated, MetS appeared not associated with AD.
36
DISCUSSION
We found that MetS is not associated with aMCI. Only one
component of MetS, central obesity, showed increased odds of
association with aMCI. The association of MetS with aMCI appeared
not to be influenced by APOE-Σ4 status. However, when subjects
37
were stratified for age, MetS was modestly associated with younger
age in aMCI subjects.
On the contrary, we found that MetS is associated with AD
independently of the age and of the APOE-Σ4 status since non APOE-
Σ4 carriers showed an increased odd [2.0 (1.1-3.6)] respects to APOE-
Σ4 carriers [1.4 (1.1- 1.9)]. However, when subjects were stratified for
age and APOE-Σ4 status, MetS was associated with a reasonable
odd [ 2.3 ( 1.1-4,9] in subjects APOE-Σ4 carriers aged ≥65 years.
This study failed to demonstrate directly a positive association
between MetS and aMCI, a precursor state of AD. This stands in
agreement with several recent studies that have failed to demonstrate
a positive relationship directly between MetS and MCI [14, 16].
In contrast, among studies of old-old cohorts, MetS have been
found be associated with either no increased odds of association with
MCI overall as in the relatively older Omsted county study of
individuals aged 70 to 89 [14], or decelerated decline in cognition from
38
follow up as in the Leiden 85 + study [44], or significantly better
cognitive function among elderly aged 75 + in Tuscania (Italy) [45].
We found that the principal component of MetS, central obesity,
was not associated with aMCI and AD. This finding is not consistent
with published findings that obesity in mid-life is a risk factor for late-
life dementia [46–48] Interestingly too, this finding is in agreement with
other published findings showing hat in old-old study populations, high
bodymass index was not found to be associated with AD [49, 50].
Together, the different ages at which MetS and its components were
measured in these studies, and the reverse causality underlying the
paradoxical relationship between MetS and dementia onset in very old
age [51, 52] are likely explanations for the variable findings across
studies.
We found in this study that the association between MetS and
aMCI was present, albeit not particularly strong, only among
39
individuals aged < 65 years. No association was found between MetS
and aMCI wathever was the APOE allele.
MetS was associated with 1.8 times increased odds for AD
aged <65 years and 1,3 times among subjects aged >65 years. MetS
was also associated with 1,4 times odds for APOE-Σ4 carriers AD and
2,0 times in AD non APOE-Σ4 carriers. However, when APOE status
and age were variously combined, MetS was associated with 2,3
times increased odds only for AD aged >65 years but not for AD aged
<65 years and AD non APOE-Σ4 carriers.
It is well known that APOE modulates susceptibility to both
atherosclerosis and AD through its pleiotropic and context-dependent
effects on plasma lipoprotein metabolism, coagulation, oxidative
processes, macrophage, glial cell and neuronal cell homeostasis,
central nervous system (CNS) physiology, inflammation, and cell
proliferation [53]. It also known that APOE plays direct roles in CNS
cholesterol transport and lipid homeostasis, amyloid-β (Aβ) clearance,
40
synaptic plasticity, and neuronal repair [54]. Carriers of the APOE-Σ4
allele are at increased risk of AD [55, 56] as well as an earlier age at
onset of AD [19].
Our results are in agreement with other reports of relevant
risks among APOE-Σ4 carriers of AD associated for components of
MetS, namely hypertension [57], diabetes [57–60], hypercholesterol
[60], and with atherosclerosis [59].
However, this study confirms that beside the APOE status,
age is another important risk factor for AD since MetS is not
associated with AD when APOE-Σ4 status and age <65 years are
taken into consideration.
The mechanisms underlying the association between MetS and
AD are still not fully understood. Several hypotheses have been
proposed to explain their relationship. First, macrovacular and
microvascular injury caused by diabetes could contribute to the
findings [61]. The presence of heart disease and stroke contributed in
41
part to the observed association in this study, but it is also likely that
subclinical vascular diseases such as lacunae and white matter
hyperintensities could possibly be an underlying factor. Some
researchers also reported that white matter lesions [WML], a
surrogate marker of small vessel disease, could partially mediate the
association [62].
The multiple-adjusted logistic regression analysis for the
association between vascular and metabolic risk factors for aMCI and
AD with MetS shows that stroke and subcortical atrophy increase the
risk of aMCI of 4,2 and 2,5 respectively, whereas for AD only cerebral
atrophy is strongly associated since the odd is equal to 7,2.
In conclusion, our data permit to affirm that MetS components
are cofactors of vascular cerebral damage with a consequent fiber
tracts lesions and cerebral atrophy. Both lesions, APOE-Σ4 status and
age >65 years greatly contribute to the AD onset.
42
Possible limitations to this study should be discussed. First, the
associations of MetS and its individual components with aMCI and AD
were estimated from cross-sectional analyses, hence precluding firm
causal inference. In general, bias from selective non participation by
subjects who are impaired by their exposure to the risk factor may
cause underestimation of effects. However, this did not appear to have
mitigated the observed relationship between MetS and cognitive
impairment. Furthermore, cases of non-amnestic MCI were not
included in the study because the number of cases was too small to
give meaningful results. This precludes us from a wider examination of
the associations between MetS and different MCI subtypes together.
This should be further investigated in future studies.
ACKNOWLEDGMENTS
43
Thanks are due for encouragment and support to Prof.
Rosolino Camarda former Director of the UOC di Neurologia e
Patologie Cognitive of the Policlinico P.Giaccone, Palermo.
I am deeply indebted also to Dr. Giusi D. Ventimigila, PhD, for
the assistance in the preparation of this thesis.
Appendix
Figure 1: flow diagram of the study population
Sample
44
N. 6948 No Imaging N. 657 ≤ 44 anni N. 1372 Stroke N. 69
Normali
Meaningful N. 56
Parkinson Desease
N. 441
Vascular
Park N. 60
VaD N. 146
naMCI ≥45 anni N. 551
Controls aMCI+ AD+ N. 1748 N. 1180 N. 737
aMCI N. 469 aMCImd N. 711
Table 1. Demographics, comorbidity scores, vascular risk factors and vascular imaging scores of controls, aMCI and AD
Controls
(n=1748)
aMCI
(n=1180)
AD
(n=738)
45
Female, n (%) 1131 (64.7) 636 (53.9)*** 503 (68.2)***
Age, years 61.9 (10.7) 69.8 (9.5)*** 76.5 (7.5)***
Education, years 8.6 (4.5) 6.9 (4.6) *** 4.7 (3.5)***
CIRS score 19.8 (3.1) 21.7 (3.6)*** 21.4 (3.1)
Smoking 565 (32,3) 439 (37,2)** 172 (23,3)***
Hypercolesterolemia 644 (36,8) 464 (39,3) 248 (33,6)
Hyperuricemia 54 (3,1) 88 (7,5)*** 45 (6,1)***
Hyperhomocystenemia 256 (58,3) 490 (68,5)*** 322 (76,1)***
Current depression 692 (39,6) 676 (57,3)*** 333 (53,5)***
Current anxiety 729 (41,7) 537 (45,5)* 243 (33) ***
Atrial Fibrillation 65 (3,7) 71 (6)** 66 (9)***
Ischemic Cardiopathy 144 (8,2) 156 (13,3)*** 113 (15,5)***
Cardiac Valvulopaties 56 (15,5) 68 (30,9)*** 25 (21,2)
Intima-media tickness 434 (28,5) 595 (51,9)*** 482 (70,2)***
Carotid stenosis 22 (1,4) 49 (4,3)*** 30 (4,4)***
ApoE4 allele 102 (15,1) 162 (18,2) 152 (28,6)***
TIA 104 (5,9) 92 (7,8)* 31 (4,2)
Neuro_Imaging
Whalund Total score 201 (11,5) 319 (27)*** 257 (34,9)***
Stroke Total score 14 (0,8) 96 (8,1)*** 12 (1,6)
Lacunae total score 284 (16,2) 376 (31,9)*** 183 (24,8)***
Mild subcortical atrophy (m±sd)
0,12 (0,02) 0,15 (0,02) *** 0,17 (0,02) ***
46
MetS
MetS 481 (34,3) 403 (38,3)* 308 (47.8)***
Raised blood pressure 319 (23,1) 218 (24,2) 168 (29.4)**
Raised fasting plasma glucose 294 (20,6) 270 (25.2)** 166 (25,5)*
Raised triglycerides 315 (22,1) 248 (23,3) 169 (25.9)
Obesity 1112 (64,4) 682 (59.2)** 469 (69,8)*
Raised high-density lipoprotein 375 (29,0) 304 (30,1) 235 (38,1)***
Abbreviations: aMCI+= amnestic mild cognitive impairment, AD= Alzheimer's disease; CIRS=
Comorbidity Inventory Rating Scale
Significant differences at pair comparison (one-way analysis of variance with
Scheffe’s post-hoc test) are starred (compared to PC-cn group) as follows: * p=
<0.05; **p= <0.01; ***p= <0.001.
Table n. 2 Odds Ratio (OR) and 95% Confidence Intervals (CIs) from simple-adjusted (Model 1) and multiple-adjusted (Model 2) logistic regression analysis for the association between vascular and metabolic risk factors and aMCI or AD with metabolic syndrome
47
Controls vs aMCI Controls vs AD
Variables Model 1 Model 2 Model 1 Model 2
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Smoking1.3 (1.1-1.6) 1.2 (0.7- 2.1) 1.1 (0.8-1.4)
Hyperuricemia1.8 (1.1-2.4) 1.7 (0.6- 4.7) 0.9 (0.6-1.5)
Hyperhomocystenemia1.2 (0.9-1.5) 1.3 (0.9-1.9)
Current depression2.5 (2.1-3.0) 2.3 (1.3-4.2) 1.7 (1.4-2.2) 1.7 (1.2-2.4)
Current anxiety1.6 (1.3-1.9) 0.8 (1.3- 4.2) 0.8 (0.6-1.0)
Atrial Fibrillation0.9 (0.7-1.4) 1.1 (0.7-1.7)
Ischemic Cardiopathy1.1 (0.8-1.4) 1.2 (0.9-1.7)
Cardiac Valvulopaties1.7 (1.1-2.7) 1.7 (0.9- 2.8)
Intima-media tickness1.6 (1.3-1.9) 1.2 (0.7-2.0) 1.9 (1.5-2.5) 1.3 (0.9-2.0)
Carotid stenosis2.0 (1.2-3.4) 1.6 (0.6-4.6) 1.5 (0.8-2.9)
ApoE4 allele3.0 (2.0-4.3) 2.4 (1.6-3.8)
TIA1.0 (0.7-1.4)
Neuro Imaging
Whalund Total score1.9 (1.5-2.3) 1.0 (0.6-1.8) 1.9 (1.4-2.4) 1.5 (0.9-2.2)
Stroke Total score13.2 (7.3-24.1) 4.2 (1.3-13.7)
Lacunae total score1.6 (1.4-2.0) 1.5 (0.9- 2.4) 0.8 (0.6-1.0)
Mild subcortical atrophy (m±sd) 1.9 (5.8-6.4) 2.5 (2.4-2.6) 1.1 (2.8-4.7) 7.2 (6.2-8.4)
MetS
MetS1.0 (0.8-1.2) 1.2 (0.9-1.5)
Raised blood pressure1.3 (0.9-1.7)
48
Raised fasting plasma glucose1.1 (0.9-1.4) 1.1 (0.9-1.5)
Obesity0.7 (0.6-0.8) 0.5 (0.3-0.8) 0.7 (0.5-0.8) 0.6 (0.4-1.0)
Raised high-density lipoprotein 1.2 (0.9-1.5)
Abbreviations: aMCI+= amnestic mild cognitive impairment, AD= Alzheimer's disease;Model 1: data are adjusted for age, sex and education; Model 2: data are adjusted for demographics and the other vascular/metabolic variables which significantly differs when comparing controls vs MCI and controls vs AD from chi-square analysis (Table 6)
Tab. 3 Association between MetS and aMCI after stratification for age, APOΣ4 status and various combination of age and APOE status
49
Subgroups n OR (95%CI) p
Age < 65 1357 1.3 (1.1-1.8) 0.041
Age>=65 1571 0.9 (0.7-1.1) 0.504
APOE4 carrier 264 1.2 (0.7-2.2) 0.506
Non APOE4 carrier 1300 1.1 (0.8-1.3) 0.572
APOE4 carrier and Age < 65
86 0.8 (0.3-2.4) 0.712
APOE4 carrier and Age>=65
178 1.4 (0.7-3.0) 0.370
Non APOE4 carrier and Age < 65
470 1.2 (0.8-1.8) 0.398
Non APOE4 carrier and Age>=65
830 0.9 (0.7-1.2) 0.438
Tab. 4 Association between MetS and AD after stratification for age, APOΣ4 status and various combination of age and APOE status
50
Subgroups n OR (95%CI) p
Age < 65 1099 1.8 (1.0-3.1) 0.041
Age>=65 1386 1.3 (1.1-1.7) 0.012
APOE4 carrier 254 1.4 (1.1-1.9) 0.015
Non APOE4 carrier 954 2.0 (1.1-3.6) 0.022
APOE4 carrier and Age < 65
69 0.8 (0.2-3.1) 0.768
APOE4 carrier and Age>=65
185 2.3 (1.1-4.9) 0.027
Non APOE4 carrier and Age < 65
317 1.9 (0.8-4.2) 0.130
Non APOE4 carrier and Age>=65
637 1.1 (0.8-1.5) 0.530
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