ArticleNPJ systems biology and applications2024
Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease.
Article in NPJ systems biology and applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and frame theory: a systematic review.Frontiers in public health · 2025Pooled it
- Salt and chronic kidney disease.Nature reviews. Nephrology · 2026Review
- Advancing risk gene discovery across the allele frequency spectrum.HGG advances · 2026Review
- Article
- The Omics-Driven Machine Learning Path to Cost-Effective Precision Medicine in Chronic Kidney Disease.Proteomics · 2025Review
- Urea Transporters and Their Gene Mutations in Diseases.Sub-cellular biochemistry · 2025Review
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
Abstract
Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.
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Registered trials
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