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Mitigating false-positive associations in rare disease gene discovery.

ABSTRACT: Clinical sequencing is expanding, but causal variants are still not identified in the majority of cases. These unsolved cases can aid in gene discovery when individuals with similar phenotypes are identified in systems such as the Matchmaker Exchange. We describe risks for gene discovery in this growing set of unsolved cases. In a set of rare disease cases with the same phenotype, it is not difficult to find two individuals with the same phenotype that carry variants in the same gene. We quantify the risk of false-positive association in a cohort of individuals with the same phenotype, using the prior probability of observing a variant in each gene from over 60,000 individuals (Exome Aggregation Consortium). Based on the number of individuals with a genic variant, cohort size, specific gene, and mode of inheritance, we calculate a P value that the match represents a true association. A match in two of 10 patients in MECP2 is statistically significant (P = 0.0014), whereas a match in TTN would not reach significance, as expected (P > 0.999). Finally, we analyze the probability of matching in clinical exome cases to estimate the number of cases needed to identify genes related to different disorders. We offer Rare Disease Match, an online tool to mitigate the uncertainty of false-positive associations.

SUBMITTER: Akle S

PROVIDER: S-EPMC4576452 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Mitigating false-positive associations in rare disease gene discovery.

Akle Sebastian S Chun Sung S Jordan Daniel M DM Cassa Christopher A CA

Human mutation 20151001 10

Clinical sequencing is expanding, but causal variants are still not identified in the majority of cases. These unsolved cases can aid in gene discovery when individuals with similar phenotypes are identified in systems such as the Matchmaker Exchange. We describe risks for gene discovery in this growing set of unsolved cases. In a set of rare disease cases with the same phenotype, it is not difficult to find two individuals with the same phenotype that carry variants in the same gene. We quantif ...[more]

PMID: 26378430

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Project description:BACKGROUND:There are several indications that malfunctions of the circadian clock contribute to depression. To search for particular circadian gene polymorphisms associated with depression, diverse polymorphisms were genotyped in two samples covering a range of depressed volunteers and participants with normal mood. METHODS:Depression mood self-ratings and DNA were collected independently from a sample of patients presenting to a sleep disorders center (1086 of European origin) and from a separate sample consisting of 399 participants claiming delayed sleep phase symptoms and 406 partly-matched controls. A custom Illumina Golden Gate array of 768 selected single nucleotide polymorphisms (SNPs) was assayed in both samples, supplemented by additional SNPlex and Taqman assays, including assay of 41 ancestry-associated markers (AIMs) to control stratification. RESULTS:In the Sleep Clinic sample, these assays yielded Bonferroni-significant association with depressed mood in three linked SNPs of the gene FMR1: rs25702 (nominal P=1.77E-05), rs25714 (P=1.83E-05), and rs28900 (P=5.24E-05). This FMR1 association was supported by 8 SNPs with nominal significance and a nominally-significant gene-wise set test. There was no association of depressed mood with FMR1 in the delayed sleep phase case-control sample or in downloaded GWAS data from the GenRED 2 sample contrasting an early-onset recurrent depression sample with controls. No replication was located in other GWAS studies of depression. Our data did weakly replicate a previously-reported association of depression with PPARGC1B rs7732671 (P=0.0235). Suggestive associations not meeting strict criteria for multiple testing and replication were found with GSK3B, NPAS2, RORA, PER3, CRY1, MTNR1A and NR1D1. Notably, 16 SNPs nominally associated with depressed mood (14 in GSK3B) were also nominally associated with delayed sleep phase syndrome (P=3E10-6). CONCLUSIONS:Considering the inconsistencies between samples and the likelihood that the significant three FMR1 SNPs might be linked to complex polymorphisms more functionally related to depression, large gene resequencing studies may be needed to clarify the import for depression of these circadian genes.

Dataset Information

Mitigating false-positive associations in rare disease gene discovery.

Publications

Mitigating false-positive associations in rare disease gene discovery.

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