Abstract
Genetic Analysis Workshop 18 (GAW18) focused on identification of genes and functional variants that influence complex phenotypes in human sequence data. Data for the workshop were donated by the T2D-GENES Consortium and included whole genome sequences for odd-numbered autosomes in 464 key individuals selected from 20 Mexican American families, a dense set of single-nucleotide polymorphisms in 959 individuals in these families, and longitudinal data on systolic and diastolic blood pressure measured at 1-4 examinations over a period of 20 years. Simulated phenotypes were generated based on the real sequence data and pedigree structures. In the design of the simulation model, gene expression measures from the San Antonio Family Heart Study (not distributed as part of the GAW18 data) were used to identify genes whose mRNA levels were correlated with blood pressure. Observed variants within these genes were designated as functional in the GAW18 simulation if they were nonsynonymous and predicted to have deleterious effects on protein function or if they were noncoding and associated with mRNA levels. Two simulated longitudinal phenotypes were modeled to have the same trait distributions as the real systolic and diastolic blood pressure data, with effects of age, sex, and medication use, including a genotype-medication interaction. For each phenotype, more than 1000 sequence variants in more than 200 genes present on the odd-numbered autosomes individually explained less than 0.01-2.78% of phenotypic variance. Cumulatively, variants in the most influential gene explained 7.79% of trait variance. An additional simulated phenotype, Q1, was designed to be correlated among family members but to not be associated with any sequence variants. Two hundred replicates of the phenotypes were simulated, with each including data for 849 individuals.
Highlights
The Genetic Analysis Workshop 18 (GAW18) data set consisted of whole genome sequence data in a pedigreebased sample, longitudinal phenotype data for hypertension and related traits, and 200 replicates of simulated longitudinal phenotype data that used the real genotypes, that could not be determined unambiguously
The GAW18 data set was drawn from T2D-GENES Project 2, a complex pedigree-based study designed to identify low-frequency or rare variants that influence susceptibility to type 2 diabetes using information from whole genome sequencing (WGS) of 1043 individuals from 20 Mexican American pedigrees enriched for type 2 diabetes from San Antonio, Texas
These family data were obtained from two studies: the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/ Gallbladder Study (SAFDGS), which are together referred to as the San Antonio Family Studies (SAFS)
Summary
The Genetic Analysis Workshop 18 (GAW18) data set consisted of whole genome sequence data in a pedigreebased sample, longitudinal phenotype data for hypertension and related traits, and 200 replicates of simulated longitudinal phenotype data that used the real genotypes,. Real phenotype data included sex, age, year of examination, systolic and diastolic blood pressure, use of antihypertensive medications, and tobacco smoking at up to four time points
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