Recent advances in sequencing technology have presented both opportunities and challenges, with limited statistical power to detect a single causal rare variant with practical sample sizes. To overcome this, the contributors to Group 1 of Genetic Analysis Workshop 17 sought to develop methods to detect the combined signal of multiple causal rare variants in a biologically meaningful way. The contributors used genes, genome location proximity, or genetic pathways as the basic unit in combining the information from multiple variants. Weaknesses of the exome sequence data and the relative strengths and weaknesses of the five approaches are discussed.

Purpose

To investigate whether the association between physical activity and serum 25-hydroxyvitamin D (25(OH)D) concentrations is independent of sun exposure, body size, and other potential explanatory variables.

Methods

Using data from a sample of 1,343 postmenopausal women, from the Women’s Health Initiative, linear regression was used to examine the associations of duration (minutes/week) of recreational activity and of yard work with 25(OH)D concentrations (nmol/L).

Results

In age-adjusted analyses, positive associations were observed between 25(OH)D concentrations and both duration of recreational physical activity (β=0.71, SE(0.09), P<0.001) and yard work (β=0.36, SE(0.10), P=0.004). After further adjustment for vitamin D intake, self-reported sunlight exposure, waist circumference, and season of blood draw, 25(OH)D was significantly associated with recreational activity (β=0.21, SE(0.09), P=0.014) but not with yard work (β=0.18, SE(0.09), P=0.061). Interactions were observed between season and both recreational activity (Pinteraction=0.082) and yard work (Pinteraction=0.038) such that these activity-25(OH)D associations were greater during summer/fall compared to winter/spring. Self-reported sunlight exposure and measures of body size did not modify the associations.

Conclusion

The observed age-adjusted activity-25(OH)D associations were attenuated after adjusting for explanatory variables and were modified by season of blood draw. Adopting a lifestyle that incorporates outdoor physical activity during summer/fall, consuming recommended amounts of vitamin D, and maintaining a healthy weight may improve or maintain vitamin D status in postmenopausal women.

Vitamin D deficiency is associated with many adverse health outcomes. There are several well established environmental predictors of vitamin D concentrations, yet studies of the genetic determinants of vitamin D concentrations are in their infancy. Our objective was to conduct a pilot genome-wide association (GWA) study of 25-hydroxyvitamin D (25[OH]D) and 1,25-dihydroxyvitamin D (1,25[OH]2D) concentrations in a subset of 229 Hispanic subjects, followed by replication genotyping of 50 single nucleotide polymorphisms (SNPs) in the entire sample of 1,190 Hispanics from San Antonio, Texas and San Luis Valley, Colorado. Of the 309,200 SNPs that met all quality control criteria, three SNPs in high linkage disequilibrium (LD) with each other were significantly associated with 1,25[OH]2D (rs6680429, rs9970802, and rs10889028) at a Bonferroni corrected P-value threshold of 1.62 × 10−7, however none met the threshold for 25[OH]D. Of the 50 SNPs selected for replication genotyping, five for 25[OH]D (rs2806508, rs10141935, rs4778359, rs1507023, and rs9937918) and eight for 1,25[OH]2D (rs6680429, rs1348864, rs4559029, rs12667374, rs7781309, rs10505337, rs2486443, and rs2154175) were replicated in the entire sample of Hispanics (P < 0.01). In conclusion, we identified several SNPs that were associated with vitamin D metabolite concentrations in Hispanics. These candidate polymorphisms merit further investigation in independent populations and other ethnicities.

Despite the importance of gene-environment (G×E) interactions in the etiology of common diseases, little work has been done to develop methods for detecting these types of interactions in genome-wide association study data. This was the focus of Genetic Analysis Workshop 16 Group 10 contributions, which introduced a variety of new methods for the detection of G×E interactions in both case-control and family-based data using both cross-sectional and longitudinal study designs. Many of these contributions detected significant G×E interactions. Although these interactions have not yet been confirmed, the results suggest the importance of testing for interactions. Issues of sample size, quantifying the environmental exposure, longitudinal data analysis, family-based analysis, selection of the most powerful analysis method, population stratification, and computational expense with respect to testing G×E interactions are discussed.