Dataset Information

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma.

ABSTRACT: Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12,000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedigrees with increased risk for suicide completion. A number of medical conditions co-occur with suicide, including asthma, and this study was undertaken to identify genetic risk common to asthma and suicide. This study tests the hypothesis that a particular comorbid condition may identify a more homogeneous genetic subgroup, facilitating the identification of specific genetic risk factors in that group. From pedigrees at increased risk for suicide, we identified three pedigrees also at significantly increased familial risk for asthma. Five suicide decedents from each of these pedigrees, plus an additional three decedents not from these pedigrees with diagnosed asthma, and 10 decedents with close relatives with asthma were genotyped. Results were compared with 183 publicly available unaffected control exomes from 1000 Genomes and CEPH (Centre d'etude du polymorphisme humain) samples genotyped on the same platform. A further 432 suicide decedents were also genotyped as non-asthma suicide controls. Genotyping was done using the Infinium HumanExome BeadChip. For analysis, we used the pedigree extension of Variant Annotation, Analysis and Search Tool (pVAAST) to calculate the disease burden of each gene. The Phenotype Driven Variant Ontological Re-ranking tool (Phevor) then re-ranked our pVAAST results in context of the phenotype. Using asthma as a seed phenotype, Phevor traversed biomedical ontologies and identified genes with similar biological properties to those known to result in asthma. Our top associated genes included those related to neurodevelopment or neural signaling (brain-derived neurotrophic factor (BDNF), neutral sphingomyelinase 2 (SMPD2), homeobox b2 (HOXB2), neural cell adhesion molecule (NCAM2), heterogeneous nuclear ribonucleoprotein A0 (HNRNPA0)), inflammation (free fatty acid receptor 2 (FFAR2)) and inflammation with additional evidence of neuronal involvement (oxidized low density lipoprotein receptor 1 (OLR1), toll-like receptor 3 (TLR3)). Of particular interest, BDNF has been previously implicated in both psychiatric disorders and asthma. Our results demonstrate the utility of combining pedigree and co-occurring phenotypes to identify rare variants associated with suicide risk in conjunction with specific co-occurring conditions.

SUBMITTER: Darlington TM

PROVIDER: S-EPMC4350517 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma.

Darlington T M TM Pimentel R R Smith K K Bakian A V AV Jerominski L L Cardon J J Camp N J NJ Callor W B WB Grey T T Singleton M M Yandell M M Renshaw P F PF Yurgelun-Todd D A DA Gray D D Coon H H

Translational psychiatry 20141021

Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12,000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedi ...[more]

PMID: 25335167

Similar Datasets

Project description:BackgroundWith the advent of next-generation sequencing (NGS) technologies, researchers are now generating a deluge of data on high dimensional genomic variations, whose analysis is likely to reveal rare variants involved in the complex etiology of disease. Standing in the way of such discoveries, however, is the fact that statistics for rare variants are currently designed for use with population-based data. In this paper, we introduce a pedigree-based statistic specifically designed to test for rare variants in family-based data. The additional power of pedigree-based statistics stems from the fact that while rare variants related to diseases or traits of interest occur only infrequently in populations, in families with multiple affected individuals, such variants are enriched. Note that while the proposed statistic can be applied with and without statistical weighting, our simulations show that its power increases when weighting (WSS and VT) are applied.ResultsOur working hypothesis was that, since rare variants are concentrated in families with multiple affected individuals, pedigree-based statistics should detect rare variants more powerfully than population-based statistics. To evaluate how well our new pedigree-based statistics perform in association studies, we develop a general framework for sequence-based association studies capable of handling data from pedigrees of various types and also from unrelated individuals. In short, we developed a procedure for transforming population-based statistics into tests for family-based associations. Furthermore, we modify two existing tests, the weighted sum-square test and the variable-threshold test, and apply both to our family-based collapsing methods. We demonstrate that the new family-based tests are more powerful than corresponding population-based test and they generate a reasonable type I error rate.To demonstrate feasibility, we apply the newly developed tests to a pedigree-based GWAS data set from the Framingham Heart Study (FHS). FHS-GWAS data contain approximately 5000 uncommon variants with frequencies less than 0.05. Potential association findings in these data demonstrate the feasibility of the software PB-STAR (note, PB-STAR is now freely available to the public).ConclusionOur tests show that when analyzing for rare variants, a pedigree-based design is more powerful than a population-based case-control design. We further demonstrate that a pedigree-based statistic's power to detect rare variants increases in direct relation to the proportion of affected individuals within the pedigree.

Dataset Information

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma.

Publications

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets