Aarskog-Scott syndrome: clinical update and report of nine novel mutations of the FGD1 gene.

Mutations in the FGD1 gene have been shown to cause Aarskog-Scott syndrome (AAS), or facio-digito-genital dysplasia (OMIM#305400), an X-linked disorder characterized by distinctive genital and skeletal developmental abnormalities with a broad spectrum of clinical phenotypes. To date, 20 distinct mutations have been reported, but little phenotypic data are available on patients with molecularly confirmed AAS. In the present study, we report on our experience of screening for mutations in the FGD1 gene in a cohort of 60 European patients with a clinically suspected diagnosis of AAS. We identified nine novel mutations in 11 patients (detection rate of 18.33%), including three missense mutations (p.R402Q; p.S558W; p.K748E), four truncating mutations (p.Y530X; p.R656X; c.806delC; c.1620delC), one in-frame deletion (c.2020_2022delGAG) and the first reported splice site mutation (c.1935+3A>C). A recurrent mutation (p.R656X) was detected in three independent families. We did not find any evidence for phenotype-genotype correlations between type and position of mutations and clinical features. In addition to the well-established phenotypic features of AAS, other clinical features are also reported and discussed.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.