Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

Whole-body protein turnover and resting energy expenditure in obese, prepubertal children.

BACKGROUND: Obesity is becoming more frequent in children; understanding the extent to which this condition affects not only carbohydrate and lipid metabolism but also protein metabolism is of paramount importance. OBJECTIVE: We evaluated the kinetics of protein metabolism in obese, prepubertal children in the static phase of obesity. DESIGN: In this cross-sectional study, 9 obese children (x +/- SE: 44+/-4 kg, 30.9+/-1.5% body fat) were compared with 8 lean (28+/-2 kg ,16.8+/-1.2% body fat), age-matched (8.5+/-0.2 y) control children. Whole-body nitrogen flux, protein synthesis, and protein breakdown were calculated postprandially over 9 h from 15N abundance in urinary ammonia by using a single oral dose of [15N]glycine; resting energy expenditure (REE) was assessed by indirect calorimetry (canopy) and body composition by multiple skinfold-thickness measurements. RESULTS: Absolute rates of protein synthesis and breakdown were significantly greater in obese children than in control children (x +/- SE: 208+/-24 compared with 137+/-14 g/d, P < 0.05, and 149+/-20 compared with 89+/-13 g/d, P < 0.05, respectively). When these variables were adjusted for fat-free mass by analysis of covariance, however, the differences between groups disappeared. There was a significant relation between protein synthesis and fat-free mass (r = 0.83, P < 0.001) as well as between protein synthesis and REE (r = 0.79, P < 0.005). CONCLUSIONS: Obesity in prepubertal children is associated with an absolute increase in whole-body protein turnover that is consistent with an absolute increase in fat-free mass, both of which contribute to explaining the greater absolute REE in obese children than in control children.