Genes Identified That Predispose People to Chronic Kidney Disease

Chronic kidney disease (CKD) affects 10% to 15% of the population worldwide and is now recognized as the most rapidly increasing contributor to global burden of disease. The costs related to CKD and end-stage renal disease (the terminal manifestation of CKD) are an enormous burden for all healthcare systems around the world.

The role of heritable factors in predisposition to CKD is well documented as earlier family-based studies revealed high narrow-sense heritability for estimated glomerular filtration rate (eGFR) in two independent collections of European families. Some of the risk variants identified in such studies also predispose their carriers to the development of CKD in prospective case–control investigations.


An international team of scientists led by the University of Manchester (Manchester, UK) studied two groups: The TRANSLATE cohort of 180 patients, age 61.7 ± 10.7, 55% male, eGFR: 76.2 ±20.1 mL/min/1.73m2; and the TCGA cohort of 100 patients, age 61.2 ±13.2, and 70% male. The TRANSLATE study recruited patients diagnosed with unilateral non-invasive renal cancer, eligible for elective nephrectomy and with no apparent history of primary nephropathy. A needle biopsy samples were collected within 6 to 28 hours since the extraction time (donation after brain death).

DNA was extracted from the frozen kidney samples (upon prior homogenization) using Qiagen DNeasyBlood and Tissue Kit. The extracted DNA was hybridized to Infinium HumanCoreExome-24 beadchip array, composed of 547,644 markers. Genotype calls were made using GenomeStudio. RNA was extracted from kidney samples immersed in RNAlater using Qiagen RNeasy Kits. Upon checking of RNA purity and integrity, a total of 1 μg of kidney RNA was subjected to Illumina TruSeq RNA Sample Preparation protocol with poly-A selection. Sequencing was performed using either 100 bp reads (on an Illumina HiSeq 2000) or 75 bp paired-end reads (on an Illumina NextSeq or HiSeq 4000).

The team used 280 kidney transcriptomes and 9,958 gene expression profiles from 44 non-renal tissues to uncover gene expression partners (eGenes) for 88.9% of CKD-dt GWAS loci. Through epigenomic chromatin segmentation analysis and variant effect prediction they annotated functional consequences to 74% of these loci. Their co-localization analysis and Mendelian randomization in >130,000 subjects demonstrate causal effects of three eGenes (NAT8B, CASP9 and MUC1) on estimated glomerular filtration rate. They identified a common alternative splice variant in MUC1 (a gene responsible for rare Mendelian form of kidney disease) and observe increased renal expression of a specific MUC1 mRNA isoform as a plausible molecular mechanism of the GWAS association signal.

Maciej Tomaszewski, MD, FRCP, FAHA. Professor of Cardiovascular Medicine and a leading author of the study, said, “Chronic kidney disease is known for its strong genetic component. Our limited knowledge of its exact genetic mechanisms partly explains why progress in the development of new diagnostic tests and treatments of chronic kidney disease has been so slow. The findings were made possible by using a state-of-the art technology known as "next-generation RNA sequencing" applied to one of the largest ever collections of human kidneys. We hope that some of the kidney genes we discovered may become attractive targets for the development of future diagnostics and treatment for patients with chronic kidney disease.” The study was published on November 22, 2018, in the journal Nature Communications.

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