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Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits.

ABSTRACT: Genome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account estimates of heritability, sample size variations and overlaps across the traits. Simulation studies show that the proposed method has correct type I error, robust to population stratification and leads to desired genome-wide enrichment of association signals. Application of the proposed method to publicly available data for three groups of genetically related traits, lipids (N = 188,577), psychiatric diseases (Ncase = 33,332, Ncontrol = 27,888) and social science traits (N ranging between 161,460 to 298,420 across individual traits) increased the number of genome-wide significant loci by 12%, 200% and 50%, respectively, compared to those found by analysis of individual traits. Evidence of replication is present for many of these loci in subsequent larger studies for individual traits. HIPO can potentially be extended to high-dimensional phenotypes as a way of dimension reduction to maximize power for subsequent genetic association testing.

SUBMITTER: Qi G

PROVIDER: S-EPMC6192650 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits.

Qi Guanghao G Chatterjee Nilanjan N

PLoS genetics 20181005 10

Genome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account ...[more]

PMID: 30289880

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Project description:BackgroundDepression and anxiety are commonly observed in people with multiple sclerosis (pwMS). There is a growing body of literature supporting the hypothesis that personality traits can influence the mood disorders. This study aimed to investigate the personality traits and their relationships with depression and anxiety among pwMS.Methods234 pwMS were involved in this cross-sectional study. Personality traits, depression, and anxiety were assessed using the NEO Five-Factor Inventory (NEO-FFI) and Hospital Anxiety and Depression Scale (HADS), respectively. Pearson's correlation coefficient and generalized linear model were employed to evaluate the relationships between demographic and clinical characteristics, NEO-FFI, and HADS subscales.ResultsIn pwMS, longer disease duration was significantly associated with lower level of conscientiousness (β = - 0.23, p = 0.008) and agreeableness (β = - 0.2, p = 0.01). Moreover, higher expanded disability status scale (EDSS) of pwMS had a significant relationship with higher level of neuroticism (β = 0.89, p = 0.01). Increased level of neuroticism was significantly correlated with lower level of extraversion (r = - 0.28, p < 0.001), openness (r = - 0.37, p < 0.001), agreeableness (r = - 0.31, p < 0.001), and conscientiousness (r = - 0.45, p < 0.001). PwMS with higher level of conscientiousness showed more extraversion (r = 0.23, p < 0.001), openness (r = 0.61, p < 0.001), and agreeableness (r = 0.41, p < 0.001). Elevated level of neuroticism was significantly associated with higher level of anxiety (β = 0.47, p < 0.001) and depression (β = 0.11, p < 0.001) among pwMS.ConclusionThe co-occurrence of depression and anxiety is probably associated with neuroticism among pwMS. Additionally, the impact of personality traits extends to influencing key disease aspects such as physical disability and disease duration in MS.

Dataset Information

Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits.

Publications

Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits.

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