Genetic screens of imaging-derived kidney volumes identify genes linked to kidney function.
Authors
Affiliations (7)
Affiliations (7)
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany University of Freiburg, Freiburg, Germany.
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany University of Freiburg, Freiburg, Germany; Core facility MRDAC, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany University of Freiburg, Freiburg, Germany.
- Department of Medicine IV, Faculty of Medicine, Medical Center-University of Freiburg, Freiburg, Germany.
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany University of Freiburg, Freiburg, Germany.
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA. Electronic address: [email protected].
Abstract
Chronic kidney disease (CKD) is defined as sustained abnormalities in kidney function or structure. Genetic studies of CKD have largely focused on kidney function markers such as estimated glomerular filtration rate (eGFR). We hypothesized that genome-wide association studies (GWAS) of magnetic resonance imaging (MRI)-based kidney sub-volumes could provide insights into CKD risk genes complementary to the study of eGFR. Total kidney volume (TKV) and sub-volumes for cortex, medulla, and sinus were derived from abdominal MRIs of 38,816 United Kingdom Biobank participants of European ancestry using a trained convolutional neural network. GWAS was performed for body surface area-normalized kidney volumes and eGFR for comparison. Potentially causal genes at each locus were prioritized using a developed annotation pipeline. We assessed locus overlap between volumes, biomarker-based kidney function, and clinical traits using colocalization analyses. Annotated genes were further characterized through enrichment analyses, molecular and clinical annotations, including a screen for rare, putative loss-of-function variants. GWAS for 9,803,932 common genetic variants identified 34 significant loci for TKV, 24 for medulla, 26 for cortex, and 71 for sinus, compared to 32 for eGFR. Prioritized genes for cortex and medulla volumes showed corresponding tissue-specific expression and were enriched for kidney development- and hypoxia-related pathways. Genetic effect sizes of significant index single nucleotide polymorphisms for TKV, cortex, and medulla volumes correlated positively with those for eGFR. Some loci such as PKHD1 and BICC1 were strongly associated with kidney volumes but not eGFR. Integration with disease information revealed that rare, putative loss-of-function variants in BICC1, and common variants with regulatory potential, are associated with increased risk for CKD and dialysis, which was not identified in a previous GWAS of eGFR CONCLUSIONS: Our investigation shows that genetic findings of kidney structure can complement kidney function studies and reveal previously unrecognized CKD risk genes in the population.