Search

Objective:Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.Subjects:Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102?514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200?000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.Results:We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.Conclusion:Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.

Validation studies of food frequency questionnaires (FFQs) describe the extent to which the FFQ reflects true diet and the relation between measured and true diet (calibration). Calibration data can be used to estimate the relation between disease and diet that would have been observed in the absence of error due to the FFQ. In this paper, the authors consider the optimal design of a validation study when the goal is precise calibration of an FFQ. The authors posed the following question: Under the constraint of a fixed total cost for a validation study, what is the optimal choice of number of subjects (n) and number of days (m) of diet records (or 24-hour recalls) per subject? The optimal n and m were found to depend upon 1) the ratio between the costs of the initial and subsequent 1-day diet records and 2) the ratio of the variance in day-to-day nutrient intake to the variance in true diet for a fixed FFQ value. Data for the two ratios and optimal values of n and m are given under a variety of realistic scenarios. The authors conclude that in most settings the optimal study design will rarely require more than four or five 1-day diet records per subject.

Associations of smoking habit with serum levels of total protein as well as protein fractions were studied in a population consisting of 4,739 atomic-bomb survivors and unexposed control subjects in Hiroshima, Japan who participated in the 1979-1981 period of the Adult Health Study, an ongoing health follow-up program of the Radiation Effects Research Foundation. Smoking was strongly related to serum protein concentration after correction for age, sex, and body mass index. Among current smokers, levels of total protein, beta globulin, and gamma globulin were significantly lower and levels of alpha-1 and alpha-2 globulin were significantly higher, when compared with nonsmokers. For serum albumin levels a decrease was also noted, but it failed to attain statistical significance. Ex-smokers were indistinguishable from nonsmokers in terms of the serum protein levels analyzed. With an increase of the amount of daily cigarette consumption, monotonic increases of serum levels were observed only in alpha-1 globulin. Duration of smoking was related to increased alpha-1 and alpha-2 globulin. Smoking duration was also associated with albumin level, but the trend was not monotonic. The radiation exposure effect on serum protein level was significant in several instances but was in general much smaller than the smoking effect, and its inclusion in the regression models did not noticeably affect the association between smoking and serum proteins.