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Kidney Int. 2019 Mar;95(3):624-635. doi: 10.1016/j.kint.2018.10.029.

Uncovering genetic mechanisms of kidney aging through transcriptomics, genomics, and epigenomics.

Author information

1
Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK.
2
Department of Cellular Pathology, University Hospitals of Leicester, Leicester, UK.
3
Division of Population Health, Health Services Research and Primary Care, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK.
4
Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.
5
Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.
6
Faculty of Health and Life Sciences, Federation University Australia, Ballarat, Victoria, Australia.
7
Department of Urology and Uro-oncology, Karol Marcinkowski University of Medical Sciences, Poznan, Poland.
8
Department of Treatment of Obesity, Metabolic Disorders and Clinical Dietetics, Poznan University of Medical Sciences, Poznan, Poland.
9
Department of Health Care, Silesian Medical College, Katowice, Poland; Department of Internal Medicine, Diabetology and Nephrology, Medical University of Silesia, Zabrze, Poland.
10
Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK; Department of Paediatric Nephrology, Royal Manchester Children's Hospital, Manchester University National Health Service Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
11
Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; Leicester National Institute for Health Research Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
12
Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; Faculty of Health and Life Sciences, Federation University Australia, Ballarat, Victoria, Australia; Department of Physiology, University of Melbourne, Parkville, Victoria, Australia.
13
Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK; Division of Medicine and Manchester Heart Centre, Manchester University National Health Service Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK. Electronic address: maciej.tomaszewski@manchester.ac.uk.

Abstract

Nephrons scar and involute during aging, increasing the risk of chronic kidney disease. Little is known, however, about genetic mechanisms of kidney aging. We sought to define the signatures of age on the renal transcriptome using 563 human kidneys. The initial discovery analysis of 260 kidney transcriptomes from the TRANScriptome of renaL humAn TissuE Study (TRANSLATE) and the Cancer Genome Atlas identified 37 age-associated genes. For 19 of those genes, the association with age was replicated in 303 kidney transcriptomes from the Nephroseq resource. Surveying 42 nonrenal tissues from the Genotype-Tissue Expression project revealed that, for approximately a fifth of the replicated genes, the association with age was kidney-specific. Seventy-three percent of the replicated genes were associated with functional or histological parameters of age-related decline in kidney health, including glomerular filtration rate, glomerulosclerosis, interstitial fibrosis, tubular atrophy, and arterial narrowing. Common genetic variants in four of the age-related genes, namely LYG1, PPP1R3C, LTF and TSPYL5, correlated with the trajectory of age-related changes in their renal expression. Integrative analysis of genomic, epigenomic, and transcriptomic information revealed that the observed age-related decline in renal TSPYL5 expression was determined both genetically and epigenetically. Thus, this study revealed robust molecular signatures of the aging kidney and new regulatory mechanisms of age-related change in the kidney transcriptome.

KEYWORDS:

aging; epigenome; genetics; kidney; transcriptome

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