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Biochemical Markers of Insulin Sensitivity at 24-28 Weeks of
Gestation in Chinese American Population
Vanessa Sy1, So-Young Kim1, Takako Araki1, Diana Huang2, Anjit Khurana1, Emilia Liao1, Doris Tan2, George Liu1, Stephen Wan2,
Leonid Poretsky1, Donna Seto-Young1
1Division of Endocrinology and Friedman Diabetes Institute, Department of Medicine; 2Department of Obstetrics and Gynecology, Beth Israel Medical Center and Albert Einstein
College of Medicine, New York, NY 10003
Introduction
Pregnancy is a complex metabolic state that involves remarkable changes in hormone levels (1)
The first trimester is associated with increased insulin sensitivity that promotes adipose tissue accumulation. During this time, pregnant women are at increased risk for hypoglycemia.
Glycogen stores are depleted quickly during the fasting state due to high feto-placental glucose demand. This results in increased lipolysis and ketone production
On the other hand, the second and third trimesters are characterized
by insulin resistance. As levels of cortisol, progesterone, estrogen, prolactin, and human
placental lactogen rise, insulin resistance develops (2)
Introduction
Placenta-derived hormones are believed to be a major factor in reprogramming maternal physiology to achieve an insulin-resistant state.
Insulin resistance is the inability of a defined concentration of insulin to achieve a predictable biological response of nutrient metabolism at the level of the target tissue
Insulin resistance results in: decreased glucose uptake in skeletal muscle, white adipose tissue and liver decreased suppression of hepatic glucose production inability of insulin to suppress lipolysis decreased ability of insulin to suppress amino acid turnover
Pregravid insulin resistance coupled with inadequate insulin response are underlying factors leading to gestational diabetes (3)
Introduction
• Insulin resistance markers:
Insulin – increased insulin level is involved in developing insulin resistance and GDM(4)
Insulin-like Growth Factor-I (IGF-I)(4) promotes growth and differentiation has also been shown to mimic metabolic actions of insulin, including
stimulation of glucose and inhibition of gluconeogenesis circulating free IGF-1 has been shown to be elevated in increasing
BMI .
Insulin-like Growth Factor-Binding Protein 1 (IGFBP-1) hyperinsulinemia suppresses IBFBP-1 production and increases
free IGF-I (5)
The roles of IGF-I and IGFBP-I in GDM are not yet clearly understood
Introduction
• Fibroblast Growth Factor-21 (FGF-21)
protein that stimulates glucose uptake in adipocytes has previously been reported to be associated with markers of insulin
resistance (6-7)
A previous study showed that FGF-21 was significantly correlated with decreased adiponectin and dyslipidemia (increased triglycerides, decreased HDL) (6)
In another study, FGF-21 was found to be significantly greater in DM2
patients compared to control patients (7) The role of FGF-21 in GDM is still unknown
Introduction
• Inflammatory markers C-Reactive Protein (CRP), and pro-inflammatory cytokines Interleukin-6 (IL-6) and Tumor Necrosis Factor-alpha (TNF-) are elevated in individuals with DM2 (8)
CRP (9)
• Produced primarily in the liver under the stimulation of adipocyte-derived IL-6 and TNF-
• Studies have shown this to be correlated with parameters relevant to diabetes including obesity, lipogenesis and adiponectin.
• It has been consistently associated with the incidence of DM2
Introduction
IL-6(9)
• Produced by many cell types which include: endothelial cells, monocytes-macrophages, and fibroblasts
• 15-30% of circulating IL-6 are derived from adipose tissue production, to modulate adipocyte glucose and lipid metabolism
• Obesity causes IL-6 upregulation in adipocytes• Studies have shown IL-6 to be correlated with the extent of insulin
resistance
TNF- (9)
• Produced by activated mononuclear phagocytes, T-cells, Natural killer cells, and mast cells
• A previous study has shown a 2.5-fold increase in adipose tissue TNF- mRNA expression in obese subjects; there was also a strong correlation of TNF- mRNA expression with hyperinsulinemia
Introduction
• Monocyte Chemoattractant Protein-1 (MCP-1) (10)
– Produced by macrophages and endothelial cells, it is a chemokine with an agonistic effect for monocytes, memory T cells and basophils
– It is thought to be a key player in the recruitment of monocytes for atheroma formation
– Studies showed that MCP-1 may be released from adipocytes, with an increased secretion and expression in obesity
– Obesity being a constituent of the metabolic syndrome (along with DM2), has initiated several studies linking MCP-1 to insulin resistance
Introduction
• Leptin (11)
- An amino acid secreted by adipocytes proportionate to their total tissue mass
- A rise in leptin levels signals satiety to the brain through receptors in the hypothalamic and brainstem neurons
- Aside from its action on the appetite-regulating center of the brain, previous studies have linked leptin to the CNS regulation of glucose metabolism which may relate to the pathogenesis of insulin resistance and DM2 associated with obesity
• Retinol Binding Protein 4 (RBP4) (12) - A transport protein for retinol secreted by adipocytes and the liver
- Previously published studies suggest that RBP4 may be one of the key components in explaining the association between obesity and insulin resistance
- Elevated RBP4 levels have been shown to increase hepatic glucose output and cause increased insulin resistance
Introduction
• Adiponectin– Secreted solely by adipocytes and has been linked to glucose, lipid, and
cardiovascular regulation (11)
– Reduced adiponectin levels have been associated with obesity, diabetes and, atherosclerosis (13 , 11)
– Adiponectin circulates in human plasma as a low molecular weight hexamer/monomer and a high molecular weight (HMW) multimer (11)
– Some studies suggest that the HMW adiponectin multimer may be an important biomarker for insulin resistance(14)
Introduction
• Resistin– an adipocyte-derived polypeptide whose role in obesity
and DM2 has been the subject of much controversy as different studies have shown contradictory findings (15)
Introduction
Some studies have shown an elevation of the following biomarkers in DM2 and GDM:• Insulin• IGF-I• CRP• Leptin • Retinol Binding Protein 4 (RBP4)
Adiponectin was found to be decreased in GDM & metabolic syndrome
Adiponectin multimer, and not the monomer, is a marker for evaluating DM2
The roles of the following remain unclear in GDM & DM2 as various contradicting findings have been reported:• Fibroblast Growth Factor-21 (FGF-21)• Resistin • Insulin Growth Factor Binding Protein-1 (IGFBP-1)
Introduction
A study found that at a lower BMI, Chinese Americans have: (16)
• Higher fasting insulin level• Increased chronic inflammatory markers• Altered circulating adipokines
Our previous studies (unpublished) showed that there were lower levels of adiponectin monomer and multimer in Chinese Americans with GDM
To our knowledge, there has not yet been a report that examined all of the above mentioned biomarkers in Chinese American pregnant women within a single study
Goals of the Study
To analyze the relationships among the following markers in Chinese Americans at 24-28 weeks of gestation
Insulin IGF-I IGFBP-1
Adipocytokines: adiponectin monomer, adiponectin multimer, RBP4,
and leptin CRP TNF- IL-6 MCP-1 Resistin FGF-21
Methods
Beth Israel Medical Center’s Institutional Review Broadapproval was obtained for this project and all consent forms were translated into Chinese.
Inclusion Criteria:
- 18 to 40 years of age - Pregnant (24-28 weeks of pregnancy) - Chinese ethnicity
Methods
Exclusion Criteria:
• Cognitive impairment• Prior established diagnosis of DM2• Hepatitis B or other infectious diseases• Thyroid dysfunction• Thalassemia • History of miscarriages• Infertility with use of In-Vitro Fertilization
Methods
Information collected:
• Family history of DM2 or previous GDM• Age• Height• Weight• Blood pressure• 1-hour Glucose Challenge Test (GCT, 50-gram) • 3-hour Glucose Tolerance Test (GTT, 100-gram)• HgA1C
Methods
For the ELISA procedures, blood samples were drawn 1 hour after the 50-gram oral glucose challenge.
Blood samples were centrifuged at 2000 rpm for 10 mins, and sera were collected and stored at -80 degrees Centigrade until ELISA was performed.
ELISA kits were obtained from the American Laboratory Products Company (ALPCO, Salem, NH), and included the following:
Insulin IGF-1 IGFBP-1 Leptin Adiponectin (monomer) Adiponectin (multimer) Resistin RBP4 FGF-21 CRP
TNF- MCP-1 IL-6
Statistical Analysis
• Data were analyzed using the SPSS system to calculate the Pearson correlation coefficients of glucose, HbA1C,Insulin, BMI and systolic blood pressure (SBP) against the different biomarkers
RESULTS
n = 136 mean age: 31.0+ 4.9 years mean glucose levels (1-hr GCT) : 117.5+ 25.9 mg/dL mean HbA1c: 5.3% + 0.4 mean BMI: 24.4 + 3.0
Glucose, HbA1c, Insulin, BMI and SBP were each correlated individually with leptin, adiponectin monomer/multimer, resistin, IGF-1, IGFBP-1, FGF-21, RBP4, CRP, TNF-, IL-6 and MCP-1
Statistically significant correlations are presented in the following figures
Study Population
RESULTSFigure 1
Glucose (mg/dL)
40 60 80 100 120 140 160 180 200
Syst
olic
blo
od p
ress
ure
(mm
Hg)
80
100
120
140
Glucose vs. Systolic Blood Pressure
Glucose (mg/dL)
40 60 80 100 120 140 160 180 200
Insu
lin (n
g/m
l)
0
100
200
300
Glucose vs. Insulin
R=0.19p<0.025
R=0.489p<0.001
Glucose (mg/dL)
40 60 80 100 120 140 160 180 200
Adi
pone
ctin
mon
omer
( g
/ml)
0
10
20
30 Adiponectin m
ultlimer (
g/m
l)
0
10
20
30
Glucose vs. Adiponectin Monomer Glucose vs Adiponectin Multimer
R= -0.291p<0.001
R= -0.287p<0.001
N=136
Results
Figure 1: Using the entire cohort, Pearson’s correlation analyses were performed.
• There is positive correlation between glucose level and:systolic blood pressure (SBP) (R=0.19, p<0.025) insulin (R=0.489, p<0.001).
• There is negative correlation between glucose level and:adiponectin monomer (R= -0.291, p<0.001) adiponectin multimer (R= - 0.287, p<0.001).
RESULTSFigure 2
N=136
Results
Figure 2:• There is positive correlation between HbA1c and
CRP (R=0.2, p<0.025)
• There is negative correlation between HbA1c and adiponectin monomer (R= -0.256, p<0.003) resistin (R= -0.176, p<0.042).
RESULTSFigure 3
Insulin (ng/mL)
0 50 100 150 200 250 300 350
IGF-
1 (n
g/m
L)
0
100
200
300
400
500
Insulin vs. IGF-I Insulin vs FGF-21
Insulin (ng/mL)
0 50 100 150 200 250 300 350
IGFB
P-1
(ng
/mL)
0
100
200
300
400
500
Insulin vs. IGFBP-1
Insulin (ng/mL)
0 50 100 150 200 250 300 350
Adi
pon
ectin
Mon
om
er (u
g/m
L)
0
10
20
30
Adip
onectin
Multim
er (ug/m
l)
0
10
20
30
Insulin vs. Adiponectin Monomer Insulin vs Adiponectin Multimer
R=0.346p<0.001
R= -0.318p<0.001
R= -0.23p<0.007
R=0.197p<0.023
R=0.304p<0.001
N=136
Results
Figure 3:
• There is positive correlation between insulin and IGF-1 (R= 0.346, p<0.001) FGF-21 (R=0.197, p<0.023)
• There is negative correlation between insulin and IGFBP-1 (R=-0.304, p<0.001), adiponectin monomer (R= -0.23, p<0.007) adiponectin multimer (R= -0.318, p<0.001)
RESULTSFigure 4
BMI (lbs/in2)
16 18 20 22 24 26 28 30 32 34 36
Sys
tolic
Blo
od
Pre
ssu
re (
mm
Hg
)
0
20
40
80
100
120
140
160
Res
istin
(ug
/mL
)
0
20
40
80
100
120
140
160
BMI vs. Systolic Blood Pressure BMI vs Resistin
BMI (lbs/in2)
16 18 20 22 24 26 28 30 32 34 36L
ep
tin
(n
g/m
L)
0
10
20
30
40
50
60
BMI vs. Leptin
BMI (lbs/in2)
16 18 20 22 24 26 28 30 32 34 36
CR
P (
ug
/mL
)
0
20
40
60
RB
P4 (
mg
/L)
0
20
40
60
BMI vs. CRP BMI vs RBP4
R=0.213p<0.014
R=0.216p<0.016
R=0.363p<0.001
R=0.433p<0.001
BMI (lbs/in2)
16 18 20 22 24 26 28 30 32 34 36
Ins
ulin
(n
g/m
L)
0
100
200
300
BMI vs. Insulin BMI vs FGF-21
BMI (lbs/in2)
16 18 20 22 24 26 28 30 32 34 36
IGF
BP
-1 (
ng
/mL
)
0
100
200
300
400
500
BMI vs. IGFBP-1
BMI (lbs/in2)
16 18 20 22 24 26 28 30 32 34 36
Ad
ipo
necti
n M
on
om
er
(ug
/mL
)0
10
20
30
Ad
ipo
nectin
Mo
no
mer (u
g/m
L)
0
10
20
30
BMI vs. Adiponectin Monomer BMI vs Adiponectin Mutimer
R=0.233p<0.007
R= -0.237p<0.008
R=0.266p<0.002
R= -0.181p<0.037
R=0.222p<0.022
R= -0.221p<0.01
N=136
Figure 4:
• There is positive correlation between BMI and the following:
SBP (R=0.363, p<0.001) resistin (R=0.213, p<0.014) leptin (R= 0.433, p<0.001) CRP (R=0.216, p<0.016) RBP4 (R=0.266, p<0.002) Insulin (R=0.233, p<0.007) FGF-21 (R=0.222, p<0.022)
• There is negative correlation between BMI and the following:
IGFBP-1 (R= -0.237, p<0.008), adiponectin monomer (R= -0.181, p<0.037) adiponectin multimer (R= -0.221, p<0.01)
Results
Conclusion
For most biomarkers that we examined, the findings in Chinese Americans are similar to those reported in the literature in other populations
The new findings in our study are:• Adiponectin monomer is consistently associated with glucose levels, HbA1c,
insulin and BMI• Resistin is positively correlated with BMI, but negatively correlated with HbA1c• IL-6, TNF-, and MCP-1 did not show any correlation with HbA1c and BMI. Only
CRP is correlated with both HbA1c and BMI
These findings suggest that the mechanisms underlying the development of diabetes in pregnant Chinese Americans may differ from other populations. Larger future studies are needed to confirm this conclusion
Limitation
Study was limited by:
• Sample size of 136 patients
• Lack of a control group
Acknowledgements
The Gerald J. Friedman Diabetes Institute
Chinese American Medical Society & Chinese American Independent Practice Association Research Fund
The Yen Family Foundation
References
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