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Propensity score-based nonparametric test revealing genetic variants underlying bipolar disorder.

ABSTRACT: Association analysis has led to the identification of many genetic variants for complex diseases. While assessing the association between genes and a disease, other factors can play an important role. The consequence of not considering covariates (such as population stratification and environmental factors) is well-documented in genetic studies. We introduce a nonparametric test of association that adjusts for covariate effects. Specifically, the adjustment is realized through weights that are constructed from genomic propensity scores that summarize the contribution of all covariates. The benefit of our test is demonstrated through an important data set on bipolar disorder (BD) collected by the Wellcome Trust Case Control Consortium. When compared to other tests, our test identified an unreported region with three single nucleotide polymorphisms (SNPs) on chromosome 16 that show strong evidence of association (P-value <5 × 10(-7)). This region is near the RPGRIP1L gene known to be associated with BD. A haplotype block including these three SNPs was further discovered to be strongly associated with BD. It is also interesting to note that our nonparametric test did not reveal strong signals at two SNPs that were detected by a covariate-adjusted parametric test. This suggests that different methods of covariate adjustment can complement each other. Thus, we recommend using both parametric and nonparametric testing. Additionally, we performed simulation studies to compare our proposed test with the unadjusted test and an adjusted parametric test. Our finding underscores the importance of accommodating and controlling for covariate effects in discovering genetic variants associated with complex disorders.

SUBMITTER: Jiang Y

PROVIDER: S-EPMC3077545 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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Propensity score-based nonparametric test revealing genetic variants underlying bipolar disorder.

Jiang Yuan Y Zhang Heping H

Genetic epidemiology 20110201 2

Association analysis has led to the identification of many genetic variants for complex diseases. While assessing the association between genes and a disease, other factors can play an important role. The consequence of not considering covariates (such as population stratification and environmental factors) is well-documented in genetic studies. We introduce a nonparametric test of association that adjusts for covariate effects. Specifically, the adjustment is realized through weights that are c ...[more]

PMID: 21254220

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Project description:OBJECTIVE:In this study, we performed a candidate genetic risk score (GRS) analysis of early-onset bipolar disorder (BD). METHODS:Treatment of Early Age Mania (TEAM) study enrollment and sample collection took place from 2003 to 2008. Mayo Clinic Bipolar Biobank samples were collected from 2009 to 2013. Genotyping and analyses for the present study took place from 2013 to 2014. The diagnosis of BD was based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria. Eight single-nucleotide polymorphisms (SNPs), previously reported in genome-wide association studies to be associated with BD, were chosen for GRS analysis in early-onset bipolar disease. These SNPs map to 3 genes: CACNA1C (calcium channel, voltage-dependent, L type, alpha 1C subunit), ANK3 (ankyrin-3, node of Ranvier [ankyrin G]), and ODZ4 (teneurin transmembrane protein 4 [formerly "odz, odd Oz/10-m homolog 4 {Drosophila}, ODZ4"]). The 8 candidate SNPs were genotyped in patients from the TEAM study (n = 69); adult patients with BD (n = 732), including a subset with early-onset illness (n = 192); and healthy controls (n = 776). GRS analyses were performed to compare early-onset cases with controls. In addition, associations of early-onset BD with individual SNPs and haplotypes were explored. RESULTS:GRS analysis revealed associations of the risk score with early-onset BD (P = .01). Gene-level haplotype analysis comparing TEAM patients with controls suggested association of early-onset BD with a CACNA1C haplotype (global test, P = .01). At the level of individual SNPs, comparison of TEAM cases with healthy controls provided nominally significant evidence for association of SNP rs10848632 in CACNA1C with early-onset BD (P = .017), which did not remain significant after correction for multiple comparisons. CONCLUSIONS:These preliminary analyses suggest that previously identified BD risk loci, especially CACNA1C, have a role in early-onset BD, possibly with stronger effects than for late-onset BD.

Project description:BACKGROUND:Lithium is a first-line treatment in bipolar disorder, but individual response is variable. Previous studies have suggested that lithium response is a heritable trait. However, no genetic markers of treatment response have been reproducibly identified. METHODS:Here, we report the results of a genome-wide association study of lithium response in 2563 patients collected by 22 participating sites from the International Consortium on Lithium Genetics (ConLiGen). Data from common single nucleotide polymorphisms (SNPs) were tested for association with categorical and continuous ratings of lithium response. Lithium response was measured using a well established scale (Alda scale). Genotyped SNPs were used to generate data at more than 6 million sites, using standard genomic imputation methods. Traits were regressed against genotype dosage. Results were combined across two batches by meta-analysis. FINDINGS:A single locus of four linked SNPs on chromosome 21 met genome-wide significance criteria for association with lithium response (rs79663003, p=1·37?×?10(-8); rs78015114, p=1·31?×?10(-8); rs74795342, p=3·31?×?10(-9); and rs75222709, p=3·50?×?10(-9)). In an independent, prospective study of 73 patients treated with lithium monotherapy for a period of up to 2 years, carriers of the response-associated alleles had a significantly lower rate of relapse than carriers of the alternate alleles (p=0·03268, hazard ratio 3·8, 95% CI 1·1-13·0). INTERPRETATION:The response-associated region contains two genes for long, non-coding RNAs (lncRNAs), AL157359.3 and AL157359.4. LncRNAs are increasingly appreciated as important regulators of gene expression, particularly in the CNS. Confirmed biomarkers of lithium response would constitute an important step forward in the clinical management of bipolar disorder. Further studies are needed to establish the biological context and potential clinical utility of these findings. FUNDING:Deutsche Forschungsgemeinschaft, National Institute of Mental Health Intramural Research Program.

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Propensity score-based nonparametric test revealing genetic variants underlying bipolar disorder.

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Propensity score-based nonparametric test revealing genetic variants underlying bipolar disorder.

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