ArticleEuropean journal of human genetics : EJHG2019
Comparison of methods for multivariate gene-based association tests for complex diseases using common variants.
Article in European journal of human genetics : EJHG, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Different genes may be involved in distal and local sensitization: A genome-wide gene-based association study and meta-analysis.European journal of pain (London, England) · 2022Pooled it
- A novel machine learning-based algorithm for eQTL identification reveals complex pleiotropic effects in the MHC region.Briefings in bioinformatics · 2026Article
- Rare-variant association studies: When are aggregation tests more powerful than single-variant tests?American journal of human genetics · 2025Article
- Modulatory Neurotransmitter Genotypes Shape Dynamic Functional Connectome Reconfigurations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- GbyE: an integrated tool for genome widely association study and genome selection based on genetic by environmental interaction.BMC genomics · 2024Article
- Identification of novel genes for triple-negative breast cancer with semiparametric gene-based analysis.Journal of applied statistics · 2023Article
- A computationally efficient clustering linear combination approach to jointly analyze multiple phenotypes for GWAS.PloS one · 2022Article
- A Comparison of Methods for Gene-Based Testing That Account for Linkage Disequilibrium.Frontiers in genetics · 2022Article
- Genetic association-based functional analysis detectsFrontiers in genetics · 2022Article
- Sweet Taste Preference: Relationships with Other Tastes, Liking for Sugary Foods and Exploratory Genome-Wide Association Analysis in Subjects with Metabolic Syndrome.Biomedicines · 2021Article
- Advances in Genetics and Epigenetic Alterations in Alzheimer's Disease: A Notion for Therapeutic Treatment.Genes · 2021Review
- Multivariate Analysis Identifies Eight Novel Loci Associated with Meat Productivity Traits in Sheep.Genes · 2021Article
- Integrating Genome-Wide Association Analysis With Transcriptome Sequencing to Identify Candidate Genes Related to Blooming Time inFrontiers in plant science · 2021Article
- Genetic Epidemiology of Complex Phenotypes.Methods in molecular biology (Clifton, N.J.) · 2021Review
- Multi-trait analysis of rare-variant association summary statistics using MTAR.Nature communications · 2020Article
- Article
- MetaPhat: Detecting and Decomposing Multivariate Associations From Univariate Genome-Wide Association Statistics.Frontiers in genetics · 2020Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Complex diseases are usually associated with multiple correlated phenotypes, and the analysis of composite scores or disease status may not fully capture the complexity (or multidimensionality). Joint analysis of multiple disease-related phenotypes in genetic tests could potentially increase power to detect association of a disease with common SNPs (or genes). Gene-based tests are designed to identify genes containing multiple risk variants that individually are weakly associated with a univariate trait. We combined three multivariate association tests (O'Brien method, TATES, and MultiPhen) with two gene-based association tests (GATES and VEGAS) and compared performance (type I error and power) of six multivariate gene-based methods using simulated data. Data (n = 2000) for genetic sequence and correlated phenotypes were simulated by varying causal variant proportions and phenotype correlations for various scenarios. These simulations showed that two multivariate association tests (TATES and MultiPhen, but not O'Brien) paired with VEGAS have inflated type I error in all scenarios, while the three multivariate association tests paired with GATES have correct type I error. MultiPhen paired with GATES has higher power than competing methods if the correlations among phenotypes are low (r < 0.57). We applied these gene-based association methods to a GWAS dataset from the Alzheimer's Disease Genetics Consortium containing three neuropathological traits related to Alzheimer disease (neuritic plaque, neurofibrillary tangles, and cerebral amyloid angiopathy) measured in 3500 autopsied brains. Gene-level significant evidence (P < 2.7 × 10
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.