ArticleEuropean journal of human genetics : EJHG2021
An expanded analysis framework for multivariate GWAS connects inflammatory biomarkers to functional variants and disease.
Article in European journal of human genetics : EJHG, 2021. 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.
- Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk.International journal of molecular sciences · 2023Pooled it
- Two-sample Mendelian randomization study of gut microbiota and inflammatory proteins: Predictive, preventive, and personalized treatment for migraine.Neural regeneration research · 2026Article
- Wavelet Decomposition-Based Genomic Analysis of the Human Electrocardiogram.medRxiv : the preprint server for health sciences · 2026Article
- ReverseGWAS identifies combined phenotypes associated with a genotype in GWA studies.Bioinformatics (Oxford, England) · 2026Article
- A Time-to-Event Comparison of Immune and Endocrine Biomarkers and Latent Profiles in Hospitalisation: An Outcome-wide Approach.medRxiv : the preprint server for health sciences · 2026Article
- VEGF-A cis-located SNPs on human chromosome 6 associated with VEGF-A plasma levels and survival in a coronary disease cohort.BMC cardiovascular disorders · 2025Article
- Examining the link between 179 lipid species and 7 diseases using genetic predictors.EBioMedicine · 2025Article
- Exploring autism spectrum disorder and co-occurring trait associations to elucidate multivariate genetic mechanisms and insights.BMC psychiatry · 2024Article
- A linear weighted combination of polygenic scores for a broad range of traits improves prediction of coronary heart disease.European journal of human genetics : EJHG · 2024Article
- Genome-wide association analysis of plasma lipidome identifies 495 genetic associations.Nature communications · 2023Article
- Multivariate Genome-Wide Association Study of Concentrations of Seven Elements in Seeds Reveals Four New Loci in Russian Wheat Lines.Plants (Basel, Switzerland) · 2023Article
- Inflammatory and infectious upper respiratory diseases associate with 41 genomic loci and type 2 inflammation.Nature communications · 2023Article
- Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations.PloS one · 2023Article
- VEGF-A related SNPs: a cardiovascular context.Frontiers in cardiovascular medicine · 2023Review
- Article
- snpXplorer: a web application to explore human SNP-associations and annotate SNP-sets.Nucleic acids research · 2021Article
- Multi-Trait Genome-Wide Association Study of Atherosclerosis Detects Novel Pleiotropic Loci.Frontiers in genetics · 2021Article
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multivariate methods are known to increase the statistical power to detect associations in the case of shared genetic basis between phenotypes. They have, however, lacked essential analytic tools to follow-up and understand the biology underlying these associations. We developed a novel computational workflow for multivariate GWAS follow-up analyses, including fine-mapping and identification of the subset of traits driving associations (driver traits). Many follow-up tools require univariate regression coefficients which are lacking from multivariate results. Our method overcomes this problem by using Canonical Correlation Analysis to turn each multivariate association into its optimal univariate Linear Combination Phenotype (LCP). This enables an LCP-GWAS, which in turn generates the statistics required for follow-up analyses. We implemented our method on 12 highly correlated inflammatory biomarkers in a Finnish population-based study. Altogether, we identified 11 associations, four of which (F5, ABO, C1orf140 and PDGFRB) were not detected by biomarker-specific analyses. Fine-mapping identified 19 signals within the 11 loci and driver trait analysis determined the traits contributing to the associations. A phenome-wide association study on the 19 representative variants from the signals in 176,899 individuals from the FinnGen study revealed 53 disease associations (p < 1 × 10
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