Colocalization of Genetic Associations with Plasma and Urine Proteins Provide Insights into Renal Protein Handling and Related Clinical Outcomes

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Background: Genetic mechanisms underlying tubular handling of proteins in the kidney can provide valuable insights into the pathogenesis of kidney-related diseases. We generated urine proteomics data and integrated it with large-scale proteomics, genomics, and biobank data to test whether genetic influences on protein levels are shared between plasma and urine, hypothesizing that shared signals represent filtered or tissue-shared proteins secreted into the urinary tract. Methods: We employed genome-wide association study (GWAS) results of 364 plasma proteins measured in 35,559 Icelanders with significant (p<2e-9) associations in 2,279 genomic regions. We extracted respective regions from GWAS of 353 proteins measured in urine of 754 participants of the German Chronic Kidney Disease study and conducted genetic colocalization analyses for plasma-urine protein pairs. To link the results with clinical outcomes, we additionally incorporated genetic associations with 1,419 medical conditions from the UK Biobank (N=400,000). Results: Strong evidence for colocalization was detected for 105 of 2,371 plasmaurine pairs, suggesting a single causal genetic variant affecting both plasma and urine protein levels. The proportion of pairs consisting of the same protein was significantly higher among the colocalizing pairs (23/105, 21.9%) than among all pairs (54/2371, 2.3%; p=5e-13), and included known and emerging biomarkers such as GDF15 for adverse kidney outcomes. We further detected 3,001 colocalized pairs of plasma protein and clinical outcome (out of 37,030), entailing kidney diseases, of which 1,141 (38%) enlisted plasma proteins that also colocalized with urine proteins. Interesting examples encompassed a shared genetic basis for urine and plasma levels of Kidney Injury Molecule-1 (HAVCR1), hypertension and kidney stones, as well as for prostate-specific microseminoprotein beta in urine and plasma and prostate cancer. Conclusions: We report colocalizing proteins that share genetic architecture in plasma and urine, additionally linking them to medical conditions. The generated resource can reveal circulating biomarkers of diseases that are also informative when quantified in urine, and will facilitate a deeper understanding of renal protein handling and its link to kidney diseases. Funding: Government Support - Non-U.S.

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