Pitfalls in performing genome-wide association studies on ratio traits.

Genome-wide association studies (GWAS) are often performed on ratios composed of a numerator trait divided by a denominator trait. Examples include body mass index (BMI) and the waist-to-hip ratio, among many others. Explicitly or implicitly, the goal of forming the ratio is typically to adjust for an association between the numerator and denominator.

Refinement of a Published Gene-Physical Activity Interaction Impacting HDL-Cholesterol: Role of Sex and Lipoprotein Subfractions.

Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C).

Differential stress responsiveness determines intraspecies virulence heterogeneity and host adaptation in Listeria monocytogenes.

Microbial pathogenesis is mediated by the expression of virulence genes. However, as microbes with identical virulence gene content can differ in their pathogenic potential, other virulence determinants must be involved. Here, by combining comparative genomics and transcriptomics of a large collection of isolates of the model pathogen Listeria monocytogenes, time-lapse microscopy, in vitro evolution and in vivo experiments, we show that the individual stress responsiveness of L.

Multitrait Analysis to Decipher the Intertwined Genetic Architecture of Neuroanatomical Phenotypes and Psychiatric Disorders.

Background: There is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven to be challenging, and new approaches are needed to infer the genetic structures that may underlie those phenotypes. Multivariate analyses are a meaningful approach to reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches.

Genome-wide discovery for biomarkers using quantile regression at biobank scale.

Genome-wide association studies (GWAS) for biomarkers important for clinical phenotypes can lead to clinically relevant discoveries. Conventional GWAS for quantitative traits are based on simplified regression models modeling the conditional mean of a phenotype as a linear function of genotype. We draw attention here to an alternative, lesser known approach, namely quantile regression that naturally extends linear regression to the analysis of the entire conditional distribution of a phenotype of interest.

A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations.

Although both short and long sleep duration are associated with elevated hypertension risk, our understanding of their interplay with biological pathways governing blood pressure remains limited. To address this, we carried out genome-wide cross-population gene-by-short-sleep and long-sleep duration interaction analyses for three blood pressure traits (systolic, diastolic, and pulse pressure) in 811,405 individuals from diverse population groups. We discover 22 novel gene-sleep duration interaction loci for blood pressure, mapped to 23 genes.

Trait selection strategy in multi-trait GWAS: Boosting SNP discoverability.

Since the first genome-wide association studies (GWASs), thousands of variant-trait associations have been discovered. However, comprehensively mapping the genetic determinant of complex traits through univariate testing can require prohibitive sample sizes. Multi-trait GWAS can circumvent this issue and improve statistical power by leveraging the joint genetic architecture of human phenotypes.

MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data.

Multivariate analysis is becoming central in studies investigating high-throughput molecular data, yet, some important features of these data are seldom explored. Here, we present MANOCCA (Multivariate Analysis of Conditional CovAriance), a powerful method to test for the effect of a predictor on the covariance matrix of a multivariate outcome. The proposed test is by construction orthogonal to tests based on the mean and variance and is able to capture effects that are missed by both approaches.

The Association of Urinary Sodium Excretion with Glaucoma and Related Traits in a Large United Kingdom Population.

Purpose: Excessive dietary sodium intake has known adverse effects on intravascular fluid volume and systemic blood pressure, which may influence intraocular pressure (IOP) and glaucoma risk. This study aimed to assess the association of urinary sodium excretion, a biomarker of dietary intake, with glaucoma and related traits, and determine whether this relationship is modified by genetic susceptibility to disease.

Design: Cross-sectional observational and gene-environment interaction analyses in the population-based UK Biobank study.

An approach to identify gene-environment interactions and reveal new biological insight in complex traits.

There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the Gene-Lifestyle Interactions Working Group within the Cohorts for Heart and Aging Research in Genetic Epidemiology Consortium has been spearheading efforts to investigate G × E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework.

Multi-trait GWAS for diverse ancestries: mapping the knowledge gap.

Background: Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores.

A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations.

Although both short and long sleep duration are associated with elevated hypertension risk, our understanding of their interplay with biological pathways governing blood pressure remains limited. To address this, we carried out genome-wide cross-population gene-by-short-sleep and long-sleep duration interaction analyses for three blood pressure traits (systolic, diastolic, and pulse pressure) in 811,405 individuals from diverse population groups. We discover 22 novel gene-sleep duration interaction loci for blood pressure, mapped to genes involved in neurological, thyroidal, bone metabolism, and hematopoietic pathways.

PaintorPipe: a pipeline for genetic variant fine-mapping using functional annotations.

Motivation: Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with common diseases. These results include a mix of causal and non-causal variants related through strong linkage disequilibrium (LD, i.e.

Trait selection strategy in multi-trait GWAS: Boosting SNPs discoverability.

Since the first Genome-Wide Association Studies (GWAS), thousands of variant-trait associations have been discovered. However, the sample size required to detect additional variants using standard univariate association screening is increasingly prohibitive. Multi-trait GWAS offers a relevant alternative: it can improve statistical power and lead to new insights about gene function and the joint genetic architecture of human phenotypes.

Polygenic risk scores identify heterogeneity in asthma and chronic obstructive pulmonary disease.

Background: Asthma and chronic obstructive pulmonary disease (COPD) have distinct and overlapping genetic and clinical features.

Objective: We sought to test the hypothesis that polygenic risk scores (PRSs) for asthma (PRS) and spirometry (FEV and FEV/forced vital capacity; PRS) would demonstrate differential associations with asthma, COPD, and asthma-COPD overlap (ACO).

Methods: We developed and tested 2 asthma PRSs and applied the higher performing PRS and a previously published PRS to research (Genetic Epidemiology of COPD study and Childhood Asthma Management Program, with spirometry) and electronic health record-based (Mass General Brigham Biobank and Genetic Epidemiology Research on Adult Health and Aging [GERA]) studies.

Quantile Regression for biomarkers in the UK Biobank.

Genome-wide association studies (GWAS) for biomarkers important for clinical phenotypes can lead to clinically relevant discoveries. GWAS for quantitative traits are based on simplified regression models modeling the conditional mean of a phenotype as a linear function of genotype. An alternative and easy to apply approach is quantile regression that naturally extends linear regression to the analysis of the entire conditional distribution of a phenotype of interest by modeling conditional quantiles within a regression framework.

The Association of Physical Activity with Glaucoma and Related Traits in the UK Biobank.

Purpose: To examine the association of physical activity (PA) with glaucoma and related traits, to assess whether genetic predisposition to glaucoma modified these associations, and to probe causal relationships using Mendelian randomization (MR).

Design: Cross-sectional observational and gene-environment interaction analyses in the UK Biobank. Two-sample MR experiments using summary statistics from large genetic consortia.

Enhancer/gene relationships: Need for more reliable genome-wide reference sets.

Differences in cells' functions arise from differential activity of regulatory elements, including enhancers. Enhancers are cis-regulatory elements that cooperate with promoters through transcription factors to activate the expression of one or several genes by getting physically close to them in the 3D space of the nucleus. There is increasing evidence that genetic variants associated with common diseases are enriched in enhancers active in cell types relevant to these diseases.

Identifying COPD subtypes using multi-trait genetics.

Chronic Obstructive Pulmonary Disease (COPD) has a simple physiological diagnostic criterion but a wide range of clinical characteristics. The mechanisms underlying this variability in COPD phenotypes are unclear. To investigate the potential contribution of genetic variants to phenotypic heterogeneity, we examined the association of genome-wide associated lung function, COPD, and asthma variants with other phenotypes using phenome-wide association results derived in the UK Biobank.

A high-throughput sequencing approach identifies immunotherapeutic targets for bacterial meningitis in neonates.

Background: Worldwide, Escherichia coli is the leading cause of neonatal Gram-negative bacterial meningitis, but full understanding of the pathogenesis of this disease is not yet achieved. Moreover, to date, no vaccine is available against bacterial neonatal meningitis.

Methods: Here, we used Transposon Sequencing of saturated banks of mutants (TnSeq) to evaluate E.