He Gao

Evidence of a Causal Relationship Between Adiponectin Levels and Insulin Sensitivity: A Mendelian Randomization Study

The adipocyte-secreted protein adiponectin is associated with insulin sensitivity in observational studies. We aimed to evaluate whether this relationship is causal using a Mendelian randomization approach. In a sample of Swedish men aged 71 years (n = 942) from the Uppsala Longitudinal Study of Adult Men (ULSAM), insulin sensitivity (M/I ratio) was measured by the euglycemic insulin clamp. We used three genetic variants in the ADIPOQ locus as instrumental variables (IVs) to estimate the potential causal effect of adiponectin on insulin sensitivity and compared these with results from conventional linear regression. The three ADIPOQ variants, rs17300539, rs3774261, and rs6444175, were strongly associated with serum adiponectin levels (all P ≤ 5.3 × 10−9) and were also significantly associated with M/I ratio in the expected direction (all P ≤ 0.022). IV analysis confirmed that genetically determined adiponectin increased insulin sensitivity (β = 0.47–0.81, all P ≤ 0.014) comparable with observational estimates (β = 0.50, all Pdifference ≥ 0.136). Adjustment for BMI and waist circumference partly explained the association of both genetically determined and observed adiponectin levels with insulin sensitivity. The observed association between higher adiponectin levels and increased insulin sensitivity is likely to represent a causal relationship partly mediated by reduced adiposity.

A meta-analysis of genome-wide association studies for adiponectin levels in East Asians identifies a novel locus near WDR11-FGFR2

Blood levels of adiponectin, an adipocyte-secreted protein correlated with metabolic and cardiovascular risks, are highly heritable. Genome-wide association (GWA) studies for adiponectin levels have identified 14 loci harboring variants associated with blood levels of adiponectin. To identify novel adiponectin-associated loci, particularly those of importance in East Asians, we conducted a meta-analysis of GWA studies for adiponectin in 7827 individuals, followed by two stages of replications in 4298 and 5954 additional individuals. We identified a novel adiponectin-associated locus on chromosome 10 near WDR11-FGFR2 (P = 3.0 × 10(-14)) and provided suggestive evidence for a locus on chromosome 12 near OR8S1-LALBA (P = 1.2 × 10(-7)). Of the adiponectin-associated loci previously described, we confirmed the association at CDH13 (P = 6.8 × 10(-165)), ADIPOQ (P = 1.8 × 10(-22)), PEPD (P = 3.6 × 10(-12)), CMIP (P = 2.1 × 10(-10)), ZNF664 (P = 2.3 × 10(-7)) and GPR109A (P = 7.4 × 10(-6)). Conditional analysis at ADIPOQ revealed a second signal with suggestive evidence of association only after conditioning on the lead SNP (Pinitial = 0.020; Pconditional = 7.0 × 10(-7)). We further confirmed the independence of two pairs of closely located loci (<2 Mb) on chromosome 16 at CMIP and CDH13, and on chromosome 12 at GPR109A and ZNF664. In addition, the newly identified signal near WDR11-FGFR2 exhibited evidence of association with triglycerides (P = 3.3 × 10(-4)), high density lipoprotein cholesterol (HDL-C, P = 4.9 × 10(-4)) and body mass index (BMI)-adjusted waist-hip ratio (P = 9.8 × 10(-3)). These findings improve our knowledge of the genetic basis of adiponectin variation, demonstrate the shared allelic architecture for adiponectin with lipids and central obesity and motivate further studies of underlying mechanisms.

Genetic Variation in CDH13 Is Associated With Lower Plasma Adiponectin Levels but Greater Adiponectin Sensitivity in East Asian Populations

Variants in the CDH13 gene have been identified as determinants of blood levels of adiponectin, an insulin-sensitizing adipokine. However, their association with other metabolic risk factors remains unclear. We examined variants at CDH13 in relation to total and high-molecular-weight (HMW) adiponectin using data from a genome-wide association study performed in 2,434 Singaporean Chinese with replication in up to 3,290 Japanese and 1,610 Koreans. The top signal rs4783244 in CDH13 showed strong associations with total adiponectin (standardized β [β] = −0.34, 95% CI −0.38 to −0.30, P = 2.0 × 10−70), HMW adiponectin (β = −0.40, 95% CI −0.43 to −0.36, P = 1.1 × 10−117), and the HMW-to-total adiponectin ratio (β = −0.44, 95% CI −0.49 to −0.40, P = 3.2 × 10−83). In the replication study, this single nucleotide polymorphism explained 4.1% of total and 6.5% of HMW adiponectin levels. No association was observed between rs4783244 and metabolic traits associated with insulin resistance before adjustment for HMW adiponectin levels. After adjustment for HMW adiponectin levels, the minor allele was associated with lower BMI (β = −0.15, 95% CI −0.19 to −0.11, P = 3.5 × 10−14), homeostasis model assessment-insulin resistance index (β = −0.16, 95% CI −0.20 to −0.12, P = 9.2 × 10−16), and triglycerides (β = −0.16, 95% CI −0.19 to −0.12, P = 1.3 × 10−16) and with higher HDL (β = 0.16, 95% CI 0.12 to 0.19, P = 2.1 × 10−17). CDH13 variants strongly influence plasma total and HMW adiponectin levels in East Asian populations but appear to alter adiponectin sensitivity, resulting in better metabolic health than expected based on circulating adiponectin levels.

Can body fat distribution, adiponectin levels and inflammation explain differences in insulin resistance between ethnic Chinese, Malays and Asian Indians?

Objective:Diabetes in Asia constitutes approximately half of the global burden. Although insulin resistance and incidence of type 2 diabetes differ substantially between ethnic groups within Asia, the reasons for these differences are poorly understood. We evaluated to what extent body fatness, adiponectin levels and inflammation mediate the relationship between ethnicity and insulin resistance in an Asian setting.Design:Cross-sectional population-based study.Subjects:In total, 4136 adult Chinese, Malays and Asian Indians residing in Singapore.Measurements:Insulin resistance was assessed using homeostasis model assessment (HOMA-IR) and systemic inflammation by C-reactive protein (CRP). Data were analyzed using path analysis.Results:HOMA-IR was highest in Asian Indians, intermediate in Malays and lowest in Chinese (P<0.001). The difference in HOMA-IR between Malays and Chinese disappeared after adjusting for body mass index (BMI). For the comparison of Asian Indians with Chinese, the association between ethnicity and HOMA-IR was mediated by BMI (men: 32.9%; women: 48.5%), BMI-adjusted waist circumference (men: 6.1%; women: 3.5%), and CRP (men: 5.1%; women: 5.6%), and unidentified factors (men: 47.2%; women: 26.5%). Part of the mediating effects of body fatness was indirect through effects of body fatness on CRP and adiponectin concentrations.Conclusion:Mediators of ethnic differences in insulin resistance differed markedly depending on the ethnic groups compared. General adiposity explained the difference in insulin resistance between Chinese and Malays, whereas abdominal fat distribution, inflammation and unexplained factors contributed to excess insulin resistance in Asian Indians as compared with Chinese and Malays. These findings suggest that interventions targeting excess weight gain can reduce ethnic disparities in insulin resistance among Asian Indians, Chinese and Malays.

Abnormal brain white matter microstructure is associated with both pre-hypertension and hypertension

Objectives To characterize effects of chronically elevated blood pressure on the brain, we tested for brain white matter microstructural differences associated with normotension, pre-hypertension and hypertension in recently available brain magnetic resonance imaging data from 4659 participants without known neurological or psychiatric disease (62.3±7.4 yrs, 47.0% male) in UK Biobank. Methods For assessment of white matter microstructure, we used measures derived from neurite orientation dispersion and density imaging (NODDI) including the intracellular volume fraction (an estimate of neurite density) and isotropic volume fraction (an index of the relative extra-cellular water diffusion). To estimate differences associated specifically with blood pressure, we applied propensity score matching based on age, sex, educational level, body mass index, and history of smoking, diabetes mellitus and cardiovascular disease to perform separate contrasts of non-hypertensive (normotensive or pre-hypertensive, N = 2332) and hypertensive (N = 2337) individuals and of normotensive (N = 741) and pre-hypertensive (N = 1581) individuals (p<0.05 after Bonferroni correction). Results The brain white matter intracellular volume fraction was significantly lower, and isotropic volume fraction was higher in hypertensive relative to non-hypertensive individuals (N = 1559, each). The white matter isotropic volume fraction also was higher in pre-hypertensive than in normotensive individuals (N = 694, each) in the right superior longitudinal fasciculus and the right superior thalamic radiation, where the lower intracellular volume fraction was observed in the hypertensives relative to the non-hypertensive group. Significance Pathological processes associated with chronically elevated blood pressure are associated with imaging differences suggesting chronic alterations of white matter axonal structure that may affect cognitive functions even with pre-hypertension.