Quantitative differences in gene expression are thought to contribute to phenotypic differences between individuals. We generated genome-wide transcriptional profiles of lymphocyte samples from 1,240 participants in the San Antonio Family Heart Study. The expression levels of 85% of the 19,648 detected autosomal transcripts were significantly heritable. Linkage analysis uncovered >1,000 cis-regulated transcripts at a false discovery rate of 5% and showed that the expression quantitative trait loci with the most significant linkage evidence are often located at the structural locus of a given transcript. To highlight the usefulness of this much-enlarged map of cis-regulated transcripts for the discovery of genes that influence complex traits in humans, as an example we selected high-density lipoprotein cholesterol concentration as a phenotype of clinical importance, and identified the cis-regulated vanin 1 (VNN1) gene as harboring sequence variants that influence high-density lipoprotein cholesterol concentrations.

Background Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically-derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here we describe the Endophenotype Ranking Value (ERV), a new objective index of the genetic utility of endophenotypes for any heritable illness. Methods Applying ERV analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individiauls (n=1122) from large randomly-selected extended pedigrees. Results Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (LOD=3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk. Conclusions The wider use of quantitative endophentpyes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression.

The data set simulated for Genetic Analysis Workshop 17 was designed to mimic a subset of data that might be produced in a full exome screen for a complex disorder and related risk factors in order to permit workshop participants to investigate issues of study design and statistical genetic analysis. Real sequence data from the 1000 Genomes Project formed the basis for simulating a common disease trait with a prevalence of 30% and three related quantitative risk factors in a sample of 697 unrelated individuals and a second sample of 697 individuals in large, extended pedigrees. Called genotypes for 24,487 autosomal markers assigned to 3,205 genes and simulated affection status, quantitative traits, age, sex, pedigree relationships, and cigarette smoking were provided to workshop participants. The simulating model included both common and rare variants with minor allele frequencies ranging from 0.07% to 25.8% and a wide range of effect sizes for these variants. Genotype-smoking interaction effects were included for variants in one gene. Functional variants were concentrated in genes selected from specific biological pathways and were selected on the basis of the predicted deleteriousness of the coding change. For each sample, unrelated individuals and family, 200 replicates of the phenotypes were simulated.

PURPOSE. Primary open-angle glaucoma (POAG) is a complex disease with a genetic architecture that can be simplified through the investigation of individual traits underlying disease risk. It has been well studied in twin models, and this study was undertaken to investigate the heritability of some of these key endophenotypes in extended pedigrees. METHODS. These data are derived from a large, multicenter study of extended, Caucasian POAG families from Australia and the United States. The study included 1181 people from 22 extended pedigrees. Variance components modeling was used to determine the heritabilities of maximum intraocular pressure (IOP), maximum vertical cup-to-disc ratio (VCDR), and mean central corneal thickness (CCT). Bivariate quantitative genetic analysis between these eye-related phenotypes and POAG itself was performed to determine whether any of these traits represent true endophenotypes. RESULTS. Heritability estimates for IOP, VCDR, and CCT (0.42, 0.66, and 0.72, respectively) were significant and show strong concordance with data in previous studies. Bivariate analysis revealed that both IOP (RhoG = 0.80; P = 9.6 x 10(-6)) and VCDR (RhoG = 0.76; P = 4.8 x 10(-10)) showed strong evidence of genetic correlation with POAG susceptibility. These two traits also correlated genetically with each other (RhoG = 0.45; P = 0.0012). Alternatively, CCT did not correlate genetically with risk of POAG. CONCLUSIONS. All the proposed POAG-related traits have genetic components. However, the significant genetic correlations observed between IOP, VCDR, and POAG itself suggest that they most likely represent true endophenotypes that could aid in the identification of genes underlying POAG susceptibility. CCT did not correlate genetically with disease and is unlikely to be a useful surrogate endophenotype for POAG.