| Title: | Multimodal predictions of end stage chronic kidney disease from asymptomatic individuals for discovery of genomic biomarkers |
| Journal: | BMC Nephrology |
| Published: | 12 May 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42120994/ |
| DOI: | https://doi.org/10.1186/s12882-026-05016-7 |
| URL: | http://dx.doi.org/10.1186/s12882-026-05016-7 |
Publication 20094
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Abstract
Chronic kidney disease (CKD) is a complex condition where the kidneys are damaged and progressively lose their ability to filter blood, 10% of the world population have the disease that often goes undetected until it is too late for intervention. Using the UK Biobank (UKBB) we constructed a CKD cohort of patients (n = 46,986) with genomic, clinical and demographic data available, a subset (n = 2,151) having also whole body Magnetic Resonance Imaging (MRI) scans. We used this multimodal cohort to successfully predict, from initially healthy patients, their 5-year outcomes for End-Stage Renal Disease (ESRD, n = 210, AUC = 0.804 $$\pm$$ 0.03 with 5 fold cross-validation) and the larger cohort for validation to predict time-to ESRD and perform Genome-wide association studies (GWAS). Extracting important clinical, phenotypic and genetic features from the models, we were able to stratify the cohorts based on a novel set of significant previously unreported SNPs related to mitochondria/cell death, kidney development and function. In particular, we show that the risk allele of SNP rs1383063 present in 30% of the population irrespective of ancestry and putatively regulating MAGI-1, a gene expressed in the podocyte slit diaphragm, is a strong predictor of ESRD and stratifies male populations of older age.</p>
11 Authors
- Simona Rabinovici-Cohen
- Daniel E. Platt
- Toshiya Iwamori
- Itai Guez
- Sanjoy Dey
- Aritra Bose
- Michiharu Kudo
- Laura Cosmai
- Camillo Porta
- Akira Koseki
- Pablo Meyer
1 Application
| Application ID | Title |
|---|---|
| 95318 | Multi-modal AI representation learning to accelerate discovery of composite biomarkers |
Enabling scientific discoveries that improve human health