Computational protocol: NRXN3 Is a Novel Locus for Waist Circumference: A Genome-Wide Association Study from the CHARGE Consortium

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Protocol publication

[…] Common to all analyses were use of the raw WC measures and the assumption of an additive model; study specific details follow. Each study reported an effect allele which was meta-analyzed consistently across all studies. Results are currently presented relative to the minor G allele for the NRXN3 SNP. In all studies except CHS, MACH (version 1.0.15 in Family Heart, Framingham, EUROSPAN and RS; version 1.0.16 in ARIC, AGES, and OOA) was used to impute all autosomal SNPs on the HapMap, using the publicly available phased haplotypes (release 22, build 36, CEU population) as a reference panel. In CHS, the program BIMBAM was used . Details are provided in regarding covariates and trait creation.In ARIC, Framingham, and RS, sex- and either cohort-specific or study center-specific residuals were created after adjustment for age, age-squared, and smoking status. In CHS and Family Heart, linear regression models were used to adjust for age, age-squared, sex, smoking, and study center. In AGES, linear regression models using PLINK v1.04 were used to adjust for age, age-squared, sex, and smoking. In the OOA the measured genotype mixed effects model was used adjusting for age, age-squared, sex and family structure based on the complete 14-generation pedigree as implemented in ITSNBN . Framingham employed the linear mixed effect model for continuous traits and the generalized estimating equations for dichotomous traits in R to account for family relatedness. In RS, linear regression models were run using MACH2QTL . In ARIC and EUROSPAN, all regression models were run using the ProbABEL package from the ABEL set of programs and in EUROSPAN genomic control was used to correct standard errors of the effect estimates for relatedness among individuals. The Family Heart Study determined the effect of each SNP using linear mixed effects models to account for the siblings present in the data using SAS.Principal components calculated using EIGENSTRAT were adjusted for in the individual studies when significant in order to account for population substructure. […]

Pipeline specifications

Software tools BIMBAM, PLINK
Application GWAS
Organisms Homo sapiens
Diseases Cardiovascular Diseases, Diabetes Mellitus