ArticleAmerican journal of human genetics2021
Efficient mixed model approach for large-scale genome-wide association studies of ordinal categorical phenotypes.
Article in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 of them syntheses that pooled it.
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Who cites it
34 citing papers in PubMed, 4 syntheses or guidelines pooled it.
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- Genome-wide association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures.Nature communications · 2025Pooled it
- Single nucleotide polymorphisms are associated with strain-specific virulence differences among clinical isolates of Cryptococcus neoformans.Nature communications · 2024Pooled it
- Genome-wide association study of image-based emphysema scoring in the Swedish CArdioPulmonary bioImage Study (SCAPIS) suggests two new risk loci in smokers.Respiratory research · 2026Article
- A fast method for breeding by design via G × E interactions detected in large-scale climatic, phenomic and genomic data.National science review · 2026Article
- Genome-wide association studies and QTL mapping for traits deviating from normal distribution.National science review · 2026Article
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- SPAmix: a scalable, accurate, and universal analysis framework for large-scale genetic association studies in admixed populations.Genome biology · 2025Article
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- A genome-wide association study of imaging-defined atherosclerosis.Nature communications · 2025Article
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- SPANature communications · 2025Article
- Sex-stratified Genomic Structural Equation Models of Posttraumatic Stress Inform PTSD Etiology: L'utilisation de la modélisation génomique par équations structurelles stratifiée par sexe du stress post-traumatique pour expliquer l'étiologie du TSPT.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2025Article
- Genome-wide association analysis of composite sleep health scores in 413,904 individuals.Communications biology · 2025Article
- Association between genetically predicted leisure and social activities and cardiovascular disease and other health outcomes.Nature cardiovascular research · 2025Article
- A phenome-wide association study of tandem repeat variation in 168,554 individuals from the UK Biobank.Nature communications · 2024Article
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- Genetically predicted dietary intake and risks of colorectal cancer: a Mendelian randomisation study.BMC cancer · 2024Article
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6 authors.
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Abstract
In genome-wide association studies, ordinal categorical phenotypes are widely used to measure human behaviors, satisfaction, and preferences. However, because of the lack of analysis tools, methods designed for binary or quantitative traits are commonly used inappropriately to analyze categorical phenotypes. To accurately model the dependence of an ordinal categorical phenotype on covariates, we propose an efficient mixed model association test, proportional odds logistic mixed model (POLMM). POLMM is computationally efficient to analyze large datasets with hundreds of thousands of samples, can control type I error rates at a stringent significance level regardless of the phenotypic distribution, and is more powerful than alternative methods. In contrast, the standard linear mixed model approaches cannot control type I error rates for rare variants when the phenotypic distribution is unbalanced, although they performed well when testing common variants. We applied POLMM to 258 ordinal categorical phenotypes on array genotypes and imputed samples from 408,961 individuals in UK Biobank. In total, we identified 5,885 genome-wide significant variants, of which, 424 variants (7.2%) are rare variants with MAF < 0.01.
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