Genetic Analysis Workshop 16: Strategies for genome-wide association study analyses

National Institutes of Health (AR44422, N01-AR-7-2232); Genome Canada and Associations AFP; Polyarctique-Groupe Taitbout; Rhumatisme et Travail; Arthritis Research Campaign; National Institute of General Medical Sciences (R01 GM31575

Genetic Analysis Workshop 14: microsatellite and single-nucleotide polymorphism marker loci for genome-wide scans.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Genetic Analysis Workshop 14: microsatellite and single-nucleotide polymorphism marker loci for genome-wide scans

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Identifying Rare Variants from Exome Scans: The GAW17 Experience

Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the worksho

Identifying rare variants from exome scans: the GAW17 experience

Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop

Genetic Analysis Workshop 15: gene expression analysis and approaches to detecting multiple functional loci

National Institutes of Health (AR44422, N01-AR-7-2232, 5R01-HL049609-14, IR01-AG021917-01A1); Genome Canada and Associations AFP; Polyarctique-Groupe Taitbout; Rhumatisme et Travail; Arthritis Research Campaign; Unversity of Minnesota; Minnesota Supercomputing Institute; National Institute of General Medical Sciences (R01 GM31575

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Genome-wide association study identifies common loci influencing circulating glycated hemoglobin (HbA1c) levels in non-diabetic subjects:The Long Life Family Study (LLFS)

OBJECTIVE: Glycated hemoglobin (HbA(1c)) is a stable index of chronic glycemic status and hyperglycemia associated with progressive development of insulin resistance and frank diabetes. It is also associated with premature aging and increased mortality. To uncover novel loci for HbA(1c) that are associated with healthy aging, we conducted a genome-wide association study (GWAS) using non-diabetic participants in the Long Life Family Study (LLFS), a study with familial clustering of exceptional longevity in the US and Denmark. METHODS: A total of 4,088 non-diabetic subjects from the LLFS were used for GWAS discoveries, and a total of 8,231 non-diabetic subjects from the Atherosclerosis Risk in Communities Study (ARIC, in the MAGIC Consortium) and the Health, Aging, and Body Composition Study (HABC) were used for GWAS replications. HbA(1c) was adjusted for age, sex, centers, 20 principal components, without and with BMI. A linear mixed effects model was used for association testing. RESULTS: Two known loci at GCK rs730497 (or rs2908282) and HK1 rs17476364 were confirmed (p < 5e–8). Of 25 suggestive (5e–8 < p < 1e–5) loci, one known (G6PC2 rs560887, replication p = 5e–5) and one novel (OR10R3P/SPTA1- rs12041363, replication p = 1e–17) loci were replicated (p < 0.0019). Similar findings resulted when HbA(1c) was further adjusted for BMI. Further validations are crucial for the remaining suggestive loci including the emerged variant near OR10R3P/SPTA1. CONCLUSIONS: The analysis reconfirmed two known GWAS loci (GCK, HK1) and identified 25 suggestive loci including one reconfirmed variant in G6PC2 and one replicated variant near OR10R3P/SPTA1. Future focused survey of sequence elements containing mainly functional and regulatory variants may yield additional findings