ArticleNature communications2024
Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Multidimensional GWAS analyses on longitudinal phenotypes reveal candidate genes regulating multi-stage egg production traits in Wannan yellow chicken.Poultry science · 2026Article
- Genetic drivers of protein changes over time: Findings, considerations, and approaches in TOPMed cohorts and UK Biobank.bioRxiv : the preprint server for biology · 2026Article
- Shared mechanisms of organ fibrosis.JCI insight · 2026Review
- Longitudinal Genome-Wide Association Study for Female Fertility Traits in German Holstein Cattle.Animal genetics · 2026Article
- Mendelian Randomization With Longitudinal Exposure Data: Simulation Study and Real Data Application.Statistics in medicine · 2026Article
- Novel approaches and applications in identifying DNA methylation markers of cardio-kidney-metabolic disease.Epigenomics · 2025Review
- Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study.Journal of translational medicine · 2025Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Understanding the genetics of kidney function decline, or trait change in general, is hampered by scarce longitudinal data for GWAS (longGWAS) and uncertainty about how to analyze such data. We use longitudinal UK Biobank data for creatinine-based estimated glomerular filtration rate from 348,275 individuals to search for genetic variants associated with eGFR-decline. This search was performed both among 595 variants previously associated with eGFR in cross-sectional GWAS and genome-wide. We use seven statistical approaches to analyze the UK Biobank data and simulated data, finding that a linear mixed model is a powerful approach with unbiased effect estimates which is viable for longGWAS. The linear mixed model identifies 13 independent genetic variants associated with eGFR-decline, including 6 novel variants, and links them to age-dependent eGFR-genetics. We demonstrate that age-dependent and age-independent eGFR-genetics exhibit a differential pattern regarding clinical progression traits and kidney-specific gene expression regulation. Overall, our results provide insights into kidney aging and linear mixed model-based longGWAS generally.
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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 Socratic graph.