Florian Hartig Theoretical Ecology & Ecological Data Science

← Publications

Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline

Simon Wiegrebe, Mathias Gorski, Janina M. Herold, Klaus J. Stark, Barbara Thorand, Christian Gieger, Carsten A. Böger, Johannes Schödel, Florian Hartig, Han Chen, Thomas W. Winkler, Helmut Küchenhoff, Iris M. Heid

Nature Communications, 15(1), 10061 (2024)
Cite this
@article{wiegrebe2024analyzing,
  author = {Simon Wiegrebe and Mathias Gorski and Janina M. Herold and Klaus J. Stark and Barbara Thorand and Christian Gieger and Carsten A. Böger and Johannes Schödel and Florian Hartig and Han Chen and Thomas W. Winkler and Helmut Küchenhoff and Iris M. Heid},
  title = {Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline},
  journal = {Nature Communications},
  volume = {15},
  number = {1},
  pages = {10061},
  year = {2024},
  doi = {10.1038/s41467-024-54483-9},
}

DOI: 10.1038/s41467-024-54483-9
Cited by 15 (Google Scholar) · 8 (OpenAlex), as of 07 September 2026

View article (DOI)

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, 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.

What the paper shows and why it matters (AI-generated)

Studying how a trait changes over time genetically needs longitudinal data that genome-wide association studies rarely have, and no settled method for analysing it once they do. Comparing seven statistical approaches on nearly 350,000 UK Biobank participants' kidney function measurements, this outside-the-usual-ecology paper identifies linear mixed models as the reliable choice and uses it to find six previously unknown genetic variants linked to kidney function decline — a concrete finding, not just a methods recommendation, and one already informing follow-up work on biobank-linked drug dosing and polygenic ageing scores.