Characteristics of study participants^*.

<p>*Data are mean ± SD, median (interquartile range) or number (%); <i>P</i> value was calculated after adjusted for age and urban/rural residence (where appropriate).</p>‡<p>Self-reported CVD including stroke and coronary heart disease.</p>§<p>Parents or siblings had a history of diabetes or CVD.</p><p>|| This variable was log-transformed before analysis.</p

Associations of plasma ferritin and indices of body fat distribution.

<p>*Adjusted for age and residence (urban/rural).</p>†<p>Adjusted for age, residence (urban/rural), alcohol drinking, smoking, education attainment, physical activity, self-reported CVD, and family history of diabetes and CVD and menopause status (in women participants); plasma ferritin concentrations were nature log-transformed.</p>‡<p>Additionally adjusted for waist circumference or hip circumference (each other).</p>§<p>Additionally adjusted for trunk fat mass or leg fat mass (each other).</p

Associations of rs6902123 in <i>PPARD</i> with type 2 diabetes and combined phenotype of type 2 diabetes and impaired fasting glucose in Chinese Hans.

a<p>The <i>P</i> values were adjusted for age, sex, and BMI.</p>b<p>Dominant model was applied.</p>c<p>Fixed-effect model was used in the meta-analysis.</p

Characteristics of the study population.

<p>Data are n (%), means±SD or medians (interquartile range).</p><p>BMI, body mass index; HOMA-B, homeostasis model assessment of pancreatic beta-cell function; HOMA-S, homeostasis model assessment of insulin sensitivity; IFG, impaired fasting glucose.</p>a<p>Body fat percentage (%) was assessed using the dual-energy X-ray absorptiometry (DEXA) among 1,634 participants (711 men and 923 women) from Shanghai.</p

Case-control analyses of <i>PCSK1</i> rs6234 with obesity and overweight.

<p>The ORs are odds ratios that represent the effects of risk allele (G-allele) based on an additive model, in which individuals homozygous for CC were coded as 0, heterozygous individuals CG were coded as 1, and individuals homozygous for GG were coded as 2; The ORs and <i>P</i> values were adjusted for age, region and sex (where appropriate).</p><p>MAF, minor allele frequency.</p

Associations of Genetic Risk Score with Obesity and Related Traits and the Modifying Effect of Physical Activity in a Chinese Han Population

<div><p>Background/Objectives</p><p>Recent large-scale genome-wide association studies have identified multiple loci robustly associated with BMI, predominantly in European ancestry (EA) populations. However, associations of these loci with obesity and related traits have not been well described in Chinese Hans. This study aimed to investigate whether BMI-associated loci are, individually and collectively, associated with adiposity-related traits and obesity in Chinese Hans and whether these associations are modified by physical activity (PA).</p><p>Subjects/Methods</p><p>We genotyped 28 BMI-associated single nucleotide polymorphisms (SNPs) in a population-based cohort including 2,894 unrelated Han Chinese. Genetic risk score (GRS), EA and East Asian ancestry (EAA) GRSs were calculated by adding BMI-increasing alleles based on all, EA and EAA identified SNPs, respectively. Interactions of GRS and PA were examined by including the interaction-term in the regression model.</p><p>Results</p><p>Individually, 26 of 28 SNPs showed directionally consistent effects on BMI, and associations of four loci (<i>TMEM18</i>, <i>PCSK1</i>, <i>BDNF</i> and <i>MAP2K5</i>) reached nominal significance (<i>P</i><0.05). The GRS was associated with increased BMI, trunk fat and body fat percentages; and increased risk of obesity and overweight (all <i>P</i><0.05). Effect sizes (0.11 vs. 0.17 kg/m²) and explained variance (0.90% vs. 1.45%) of GRS for BMI tended to be lower in Chinese Hans than in Europeans. The EA GRS and EAA GRS were associated with 0.11 and 0.13 kg/m² higher BMI, respectively. In addition, we found that PA attenuated the effect of the GRS on BMI (<i>P</i>_interaction = 0.022).</p><p>Conclusions</p><p>Our observations suggest that the combined effect of obesity-susceptibility loci on BMI tended to be lower in Han Chinese than in EA. The overall, EA and EAA GRSs exert similar effects on adiposity traits. Genetic predisposition to increased BMI is attenuated by PA in this population of Han Chinese.</p></div

Associations of individual SNPs and GRSs with risk of obesity and overweight.

<p>Data are OR (95% CI) adjusted for sex, age, age², region and the first two principle components.</p

Effect of interaction between GRSs and PA on BMI.

<p>Interaction beta is the difference in trait of GRS with every increase in PA category, e.g., an interaction beta of −0.06 kg/m² for BMI represents a 0.06 kg/m² attenuation in per BMI-increasing effect of GRS with every increase in PA category. <i>P</i>_interaction was adjusted for age, age², sex, region and the first two principle components.</p

Associations of individual SNPs and GRSs with body fat percentage, trunk fat percentage and leg fat percentage.

<p>Data are beta (SE) per BMI-increasing allele, adjusted for age, age² and sex.</p

Correlation of BMI-related loci between European ancestry and Chinese Hans.

<p>The plots showed the effect size (kg/m²) of loci on BMI (A), BMI-increasing allele frequencies (B), and explained variance (%) of loci on BMI (C) in GIANT (Speliotes et al) and NHAPC (our data) studies. X-axis represents the data from our study (NHAPC) and Y-axis represents the data from European ancestry populations (GIANT).</p