1.
Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index.
Wen, W, Zheng, W, Okada, Y, Takeuchi, F, Tabara, Y, Hwang, JY, Dorajoo, R, Li, H, Tsai, FJ, Yang, X, et al
Human molecular genetics. 2014;(20):5492-504
-
-
Free full text
-
Abstract
Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488-47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10(-13)), ALDH2/MYL2 (rs671, P = 3.40 × 10(-11); rs12229654, P = 4.56 × 10(-9)), ITIH4 (rs2535633, P = 1.77 × 10(-10)) and NT5C2 (rs11191580, P = 3.83 × 10(-8)) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10(-8)) and an additional 14 at P < 1.0 × 10(-3) with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity.
2.
A randomized trial of a tailored, self-help dietary intervention: the Puget Sound Eating Patterns study.
Kristal, AR, Curry, SJ, Shattuck, AL, Feng, Z, Li, S
Preventive medicine. 2000;(4):380-9
Abstract
BACKGROUND This study evaluated a tailored, multiple-component self-help intervention designed to promote lower fat and higher fruit and vegetable consumption. METHODS Participants were 1,459 adults selected at random, stratified by sex and age (18-34, 35-54, 55-69), from enrollees of a large health maintenance organization. After completing a baseline telephone survey, participants were randomized to receive the intervention (consisting of a computer-generated personalized letter, a motivational phone call, a self-help manual, a package of supplementary materials, computer-generated behavioral feedback based on a self-administered food frequency questionnaire, and newsletters) or to receive no materials. Evaluation was based on 1,205 (86.5%) participants who completed both a 3- and a 12-month follow up survey. RESULTS The intervention effect +/- SE for fat, based on a diet habits questionnaire, was -0.10 +/- 0.02 (P < 0.001), corresponding to a reduction of approximately 0.8 percentage points of percentage energy from fat. For fruits and vegetables, the intervention effect was 0.47 +/- 0.10 servings/day (P < 0.001). Intervention effects were similar across age and sex groups. CONCLUSIONS Tailored, self-help interventions can effectively promote dietary change among both men and women and among younger as well as older adults.