Person:

Zheng, Yan

Background: The pathogenesis of cardiovascular (CV) mortality, whose rate is increased in type 2 diabetes, is poorly understood. While high serum adiponectin is associated with increased CV mortality in the general population, no data are available in type 2 diabetes. We here investigated whether this counterintuitive association was observable also in diabetic patients and whether it was sex-specific. Methods: Three prospective cohorts were analyzed: 1) Gargano Heart Study (GHS; 359 patients, 58 events/1,934 person-years; py); 2) Health Professional Follow-up Study (HPFS; 833 men, 146 events/10,024 py); 3) Nurses’ Health Study (NHS; 902 women, 144 events/15,074 py). Results: In GHS serum adiponectin predicted CV mortality in men (hazard ratio, HR, and 95% CI per standard deviation, SD, increment = 1.54, 1.19-2.01), but not women (HR = 0.98, 0.48-2.01). Circulating adiponectin predicted CV mortality in men from HPFS (HR = 1.44, 1.21-1.72), but not in women from NHS (HR = 1.08, 0.86-1.35), used as replication samples. In a pooled analysis, HRs were 1.47 (1.27-1.70) in 1,075 men and 1.07 (0.86-1.33) in 1,019 women (p for HRs heterogeneity across sexes = 0.018). Conclusions: This is the first report showing that high circulating adiponectin predicts increased CV mortality in men, but not in women with type 2 diabetes. Further studies are necessary to unravel the mechanisms through which adiponectin influences CV mortality in a sex-specific manner. Electronic supplementary material The online version of this article (doi:10.1186/s12933-014-0130-y) contains supplementary material, which is available to authorized users.

Background: Whether habitual coffee consumption interacts with the genetic predisposition to obesity in relation to body mass index (BMI) and obesity is unknown. Methods: We analyzed the interactions between genetic predisposition and habitual coffee consumption in relation to BMI and obesity risk in 5116 men from the Health Professionals Follow-up Study (HPFS), in 9841 women from the Nurses’ Health Study (NHS), and in 5648 women from the Women’s Health Initiative (WHI). The genetic risk score was calculated based on 77 BMI-associated loci. Coffee consumption was examined prospectively in relation to BMI. Results: The genetic association with BMI was attenuated among participants with higher consumption of coffee than among those with lower consumption in the HPFS (P interaction = 0.023) and NHS (P interaction = 0.039); similar results were replicated in the WHI (P interaction = 0.044). In the combined data of all cohorts, differences in BMI per increment of 10-risk allele were 1.38 (standard error (SE), 0.28), 1.02 (SE, 0.10), and 0.95 (SE, 0.12) kg/m2 for coffee consumption of < 1, 1–3 and > 3 cup(s)/day, respectively (P interaction < 0.001). Such interaction was partly due to slightly higher BMI with higher coffee consumption among participants at lower genetic risk and slightly lower BMI with higher coffee consumption among those at higher genetic risk. Each increment of 10-risk allele was associated with 78% (95% confidence interval (CI), 59–99%), 48% (95% CI, 36–62%), and 43% (95% CI, 28–59%) increased risk for obesity across these subgroups of coffee consumption (P interaction = 0.008). From another perspective, differences in BMI per increment of 1 cup/day coffee consumption were 0.02 (SE, 0.09), –0.02 (SE, 0.04), and –0.14 (SE, 0.04) kg/m2 across tertiles of the genetic risk score. Conclusions: Higher coffee consumption might attenuate the genetic associations with BMI and obesity risk, and individuals with greater genetic predisposition to obesity appeared to have lower BMI associated with higher coffee consumption. Electronic supplementary material The online version of this article (doi:10.1186/s12916-017-0862-0) contains supplementary material, which is available to authorized users.

Sixty genetic loci associated with abdominal obesity, measured by waist circumference (WC) and waist-hip ratio (WHR), have been previously identified, primarily from studies conducted in European-ancestry populations. We conducted a meta-analysis of associations of abdominal obesity with approximately 2.5 million single nucleotide polymorphisms (SNPs) among 53,052 (for WC) and 48,312 (for WHR) individuals of Asian descent, and replicated 33 selected SNPs among 3,762 to 17,110 additional individuals. We identified four novel loci near the EFEMP1, ADAMTSL3 , CNPY2, and GNAS genes that were associated with WC after adjustment for body mass index (BMI); two loci near the NID2 and HLA-DRB5 genes associated with WHR after adjustment for BMI, and three loci near the CEP120, TSC22D2, and SLC22A2 genes associated with WC without adjustment for BMI. Functional enrichment analyses revealed enrichment of corticotropin-releasing hormone signaling, GNRH signaling, and/or CDK5 signaling pathways for those newly-identified loci. Our study provides additional insight on genetic contribution to abdominal obesity.

Objective: Weight loss intervention through diet modification has been widely used to improve obesity-related hyperglycemia; however, little is known about whether genetic variation modifies the intervention effect. We examined the interaction between weight-loss diets and genetic variation of fasting glucose on changes in glycemic traits in a dietary intervention trial. Research Design and Methods The Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial is a randomized, controlled 2-year weight-loss trial. We assessed overall genetic variation of fasting glucose by calculating a genetic risk score (GRS) based on 14 fasting glucose-associated single nucleotide polymorphisms, and examined the progression in fasting glucose and insulin levels, and insulin resistance and insulin sensitivity in 733 adults from this trial. Results: The GRS was associated with 6-month changes in fasting glucose (P<0.001), fasting insulin (P=0.042), homeostasis model assessment of insulin resistance (HOMA-IR, P=0.009) and insulin sensitivity (HOMA-S, P=0.043). We observed significant interaction between the GRS and dietary fat on 6-month changes in fasting glucose, HOMA-IR and HOMA-S after multivariable adjustment (P-interaction=0.007, 0.045, and 0.028, respectively). After further adjustment for weight loss, the interaction remained significant on change in fasting glucose (P=0.015). In the high-fat diet group, participants in the highest GRS tertile showed increased fasting glucose, whereas participants in the lowest tertile showed decreased fasting glucose (P-trend<0.001); in contrast, the genetic association was not significant in the low-fat diet group (P-trend=0.087). Conclusions: Our data suggest that participants with a higher genetic risk may benefit more by eating a low-fat diet to improve glucose metabolism.

The first epigenome-wide association study of BMI identified DNA methylation at an HIF3A locus associated with BMI. We tested the hypothesis that DNA methylation variants are associated with BMI according to intake of B vitamins. In two large cohorts, we found significant interactions between the DNA methylation–associated HIF3A single nucleotide polymorphism (SNP) rs3826795 and intake of B vitamins on 10-year changes in BMI. The association between rs3826795 and BMI changes consistently increased across the tertiles of total vitamin B2 and B12 intake (all P for interaction <0.01). The differences in the BMI changes per increment of minor allele were −0.10 (SE 0.06), −0.01 (SE 0.06), and 0.12 (SE 0.07) within subgroups defined by increasing tertiles of total vitamin B2 intake and −0.10 (SE 0.06), −0.01 (SE 0.06), and 0.10 (SE 0.07) within subgroups defined by increasing tertiles of total vitamin B12 intake. In two independent cohorts, a DNA methylation variant in HIF3A was associated with BMI changes through interactions with total or supplemental vitamin B2, vitamin B12, and folate. These findings suggest a potential causal relation between DNA methylation and adiposity.