Indo-Asian ethnicity is associated with an increased risk of type 2 diabetes and cardiovascular disease (CVD) that is not reconciled by conventional risk factors (1,2). In a recent study (3), we found that pregnant Indo-Asian women exhibited strikingly low serum levels of adiponectin, a protein with putative insulin-sensitizing and antiatherogenic activity. Hypoadiponectinemia has since been demonstrated in both Indo-Asian male and nonpregnant female subjects (4–6). Thus, hypoadiponectinemia may be a generalized phenomenon in people of Indo-Asian descent that could contribute to their increased risk of type 2 diabetes and CVD.
It has recently emerged that adiponectin circulates in oligomeric complexes, with its high–molecular weight (HMW) isoform mediating insulin-sensitizing and vasculature-protective effects (7,8). Accordingly, Scherer and colleagues (7) have proposed the ratio of the HMW isoform to total adiponectin (SA) (expressed as a percentage) as a measure of the biological activity of adiponectin. Given the risk of type 2 diabetes and CVD in Indo-Asians, we hypothesized that hypoadiponectinemia in this ethnic group may reflect selective deficiency of the HMW isoform (i.e., low SA). Therefore, to test this hypothesis, we sought to assess the relationship between SA and ethnicity within our earlier study of pregnant women.
RESEARCH DESIGN AND METHODS
Study protocol and methods have been described previously (9,10). The research ethics board at Mount Sinai Hospital approved the protocol, and all participants gave written informed consent. Briefly, participants consisted of 180 healthy pregnant women attending outpatient obstetrics clinics, who had been referred for a 3-h, 100-g oral glucose tolerance test (OGTT) following an abnormal result on a screening 50-g glucose challenge (plasma glucose ≥7.8 mmol/l at 1-h postchallenge). Demographic/historical information was obtained by the interviewer-administered questionnaire at the OGTT. Indo-Asians were defined as having ancestry from India, Pakistan, Sri Lanka, or Bangladesh. As described previously (9), the OGTT stratified participants into three glycemic tolerance groups: normal glucose tolerance, impaired glucose tolerance, and gestational diabetes mellitus (GDM). The current analysis was performed in 95 participants, in whom adiponectin isoform distribution was measured. These 95 participants consisted of 65 Caucasians and 30 Indo-Asians randomly selected in a 2:1 ratio within each glucose tolerance group (normal glucose tolerance: 27 Caucasians, 13 Indo-Asians; impaired glucose tolerance: 10 Caucasians, 4 Indo-Asians; and GDM: 28 Caucasians, 13 Indo-Asians).
Venous blood samples for measurement of glucose and insulin were drawn at fasting and hourly during the OGTT. Glucose, insulin, C-reactive protein (CRP) and total adiponectin were measured as previously described (9,10). Adiponectin isoform distribution was determined from fasting serum by modification of the method described by Pajvani et al. (7), adapted to use an SW60 rotor (Beckman Coulter, Mississauga, ON, Canada) and infrared Western blot analysis (Doc#988-07737; LI-COR, Lincoln, NE).
Statistical analyses were conducted using the Statistical Analysis System (SAS version 8.02; SAS Institute, Cary, NC). The area under the glucose curve (AUCglucose), insulin sensitivity index (ISOGTT), and SA were determined as previously described (7,9,11). The distributions of weeks’ gestation, prepregnancy BMI, fasting glucose, fasting insulin, ISOGTT, CRP, and total adiponectin were skewed, and thus natural logarithmic transformations of these variables were used in multivariate analyses. Ethnic variation in SA after adjustment for covariates was tested by ANCOVA. Univariate correlates of SA were assessed by Spearman correlation analysis. The following variables of known or potential biological relevance to adiponectin were considered in forward stepwise multiple linear regression analysis: age, ethnicity, prepregnancy BMI, weight gain in pregnancy, family history of diabetes, previous GDM, smoking history, AUCglucose, and ISOGTT.
RESULTS
Table 1 shows the demographic and metabolic characteristics of the study participants. Caucasians were more likely to report a history of smoking (P = 0.0439). Otherwise, there were no significant differences between the ethnic groups in age, weeks’ gestation, prepregnancy BMI, weight gain in pregnancy, previous GDM, family history of diabetes, parity, glucose tolerance status, AUCglucose, fasting glucose, fasting insulin, ISOGTT, or CRP. As expected, median total adiponectin concentration was substantially lower in Indo-Asians (9.7 μg/ml) than in Caucasians (15.8 μg/ml) (P < 0.0001). Mean SA was also significantly lower in Indo-Asians (29.9%) than in Caucasian women (35.6%) (P = 0.012). After adjustment for age, weeks’ gestation, prepregnancy BMI, weight gain in pregnancy, family history of diabetes, previous GDM, smoking history, and glucose intolerance, mean SA remained significantly lower in Indo-Asians (29.6%) than in Caucasians (35.7%) (P = 0.0049).
On Spearman correlation analysis, SA was inversely related to prepregnancy BMI in both Caucasians (r = −0.31, P = 0.011) and Indo-Asians (r = −0.46, P = 0.010). In Caucasians only, SA was positively correlated with ISOGTT (r = 0.32, P = 0.010) and CRP (r = 0.35, P = 0.0044). These relationships were not apparent in Indo-Asians (ISOGTT: r = 0.18, P = 0.33; CRP: r = 0.11, P = 0.55). In both ethnic groups, SA was unrelated to age, weeks’ gestation, and weight gain in pregnancy.
On forward stepwise multiple linear regression analysis, Indo-Asian ethnicity emerged as an independent and negative determinant of SA (β = −6.21, F = 8.37, P = 0.0048), consistent with lower SA in this ethnic group after adjustment for covariates. Prepregnancy BMI was the only other independent and negative determinant of SA (β = −16.19, F = 7.51, P = 0.0074), in a model reconciling 20% of the variance in SA.
CONCLUSIONS
Women of Indo-Asian descent exhibit decreased SA compared with Caucasian women during pregnancy. Indeed, Indo-Asian ethnicity emerged as an independent and negative determinant of SA. These data document ethnic variation in adiponectin isoform distribution for the first time and raise the possibility that low serum levels of HMW adiponectin may contribute to the increased risk of type 2 diabetes and CVD in Indo-Asians.
. | Caucasians . | Indo-Asians . | . |
---|---|---|---|
. | (n = 65) . | (n = 30) . | P . |
Age (years) | 33.7 ± 3.8 | 34.2 ± 5.2 | 0.5970 |
Weeks’ gestation (weeks) | 29.0 (28–30) | 29.0 (28–31) | 0.9758 |
Prepregnancy BMI (kg/m2) | 24.5 (20.8–27.1) | 22.6 (20.4–24.9) | 0.0627 |
Weight gain in pregnancy (kg) | 12.0 ± 5.4 | 10.8 ± 4.8 | 0.2796 |
Previous GDM/macrosomia (%) | 10.8 | 10.0 | 0.9101 |
Family history of diabetes (%) | 58.5 | 46.7 | 0.2856 |
Parity | 0.6166 | ||
Nulliparous (%) | 58.5 | 53.3 | |
One (%) | 30.8 | 33.3 | |
More than one (%) | 10.8 | 13.3 | |
Smoking history | 0.0439 | ||
Never (%) | 63.1 | 86.7 | |
Remote (%) | 23.1 | 6.7 | |
Current (%) | 13.9 | 6.7 | |
Glucose tolerance status | 0.9401 | ||
Normal glucose tolerance (%) | 41.5 | 43.3 | |
Impaired glucose tolerance (%) | 15.4 | 13.3 | |
GDM (%) | 43.1 | 43.3 | |
AUCglucose | 24.1 ± 4.1 | 24.8 ± 4.2 | 0.4707 |
Fasting blood glucose (mmol/l) | 4.5 (4.2–4.9) | 4.7 (4.3–5.2) | 0.1963 |
Fasting insulin (pmol/l) | 63 (45–80) | 61 (48–100) | 0.3395 |
ISOGTT | 4.2 (3.2–6.7) | 4.0 (2.8–5.7) | 0.2780 |
CRP (mg/l) | 5.2 (2.3–9.2) | 4.5 (2.5–7.9) | 0.8088 |
Total adiponectin (ug/ml) | 15.8 (12.4–20.6) | 9.7 (7.9–13.3) | <0.0001 |
SA (%) | 35.6 ± 9.5 | 29.9 ± 11.5 | 0.0120 |
. | Caucasians . | Indo-Asians . | . |
---|---|---|---|
. | (n = 65) . | (n = 30) . | P . |
Age (years) | 33.7 ± 3.8 | 34.2 ± 5.2 | 0.5970 |
Weeks’ gestation (weeks) | 29.0 (28–30) | 29.0 (28–31) | 0.9758 |
Prepregnancy BMI (kg/m2) | 24.5 (20.8–27.1) | 22.6 (20.4–24.9) | 0.0627 |
Weight gain in pregnancy (kg) | 12.0 ± 5.4 | 10.8 ± 4.8 | 0.2796 |
Previous GDM/macrosomia (%) | 10.8 | 10.0 | 0.9101 |
Family history of diabetes (%) | 58.5 | 46.7 | 0.2856 |
Parity | 0.6166 | ||
Nulliparous (%) | 58.5 | 53.3 | |
One (%) | 30.8 | 33.3 | |
More than one (%) | 10.8 | 13.3 | |
Smoking history | 0.0439 | ||
Never (%) | 63.1 | 86.7 | |
Remote (%) | 23.1 | 6.7 | |
Current (%) | 13.9 | 6.7 | |
Glucose tolerance status | 0.9401 | ||
Normal glucose tolerance (%) | 41.5 | 43.3 | |
Impaired glucose tolerance (%) | 15.4 | 13.3 | |
GDM (%) | 43.1 | 43.3 | |
AUCglucose | 24.1 ± 4.1 | 24.8 ± 4.2 | 0.4707 |
Fasting blood glucose (mmol/l) | 4.5 (4.2–4.9) | 4.7 (4.3–5.2) | 0.1963 |
Fasting insulin (pmol/l) | 63 (45–80) | 61 (48–100) | 0.3395 |
ISOGTT | 4.2 (3.2–6.7) | 4.0 (2.8–5.7) | 0.2780 |
CRP (mg/l) | 5.2 (2.3–9.2) | 4.5 (2.5–7.9) | 0.8088 |
Total adiponectin (ug/ml) | 15.8 (12.4–20.6) | 9.7 (7.9–13.3) | <0.0001 |
SA (%) | 35.6 ± 9.5 | 29.9 ± 11.5 | 0.0120 |
Data are means ± SD or median (interquartile range) unless otherwise indicated. P values refer to overall differences between groups as derived from t test (for continuous variables) or χ2 tests (for categorical variables). Boldface indicates P < 0.05
Article Information
This study was supported by Canadian Institutes of Health Research.
We thank Dr. Philip Scherer and Pernille Keller for guidance in the measurement of HMW adiponectin.
References
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.
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