The kidneys act as the body’s waste disposal unit and fluid filter – so when dysfunction occurs, it’s important to move quickly to preserve the patient’s health. Although kidney disease is a serious health concern affecting over 13 percent of the world’s population (1), the mechanisms behind renal dysfunction remain surprisingly poorly understood.
New research, however, has started to elucidate the mysteries of kidney function and how specific genetic traits affect this all-important organ. A recent study that sought to observe genetic associations with kidney function has successfully identified 878 loci, 126 of which have not previously been associated with renal disease (2). Through analysis of 443 kidneys, 686 samples, and over 57,000 kidney cells, researchers revealed that variation in DNA methylation is responsible for a much larger difference between kidney outcomes than gene expression.
But that’s not to say that genes themselves don’t play a significant role. By analyzing phenotypes of mice with genetic loss of Slc47a1 and humans with rare SLC47A1 loss-of-function coding variants, the researchers established a causal role for the gene in the development of kidney disease. Crucially, the team were able to demonstrate that SLC47A1 is a kidney disease risk gene that likely influences toxin uptake and the secretion of tubule epithelial cells. Overall, the findings highlight the importance of epigenomic and transcriptomic analysis to accompany genome-wide association studies when seeking the origins of complex mechanisms.
Patients with chronic kidney disease (CKD) often face decreased quality of life or even early death. Accurate prediction and screening methods can help identify and treat these patients early, alleviating the health burden of CKD and improving health outcomes. Polygenic prediction, although previously used to this end, has yet to be used effectively in genetically diverse populations. A recent study sought to address this by establishing a genome-wide polygenic scope (GPS) for CKD. Using APOL1 risk genotypes and genome-wide association studies of kidney function, the team successfully demonstrated a genetic risk score across ancestry cohorts (3). The team’s new GPS was applied to 15 different cohorts – spanning European, African, Asian, and Latinx ancestry – and saw reproducible performance across all tested groups. One significant finding was that people in the top 2 percent of the GPS have triple the risk of the average person across ancestries – an equivalent risk increase to a family history of CKD.
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References
- J-C Lv et al., Adv Exp Med Biol, 1165, 3 (2019). PMID: 31399958.
- H Liu et al., Nat Genet, 54, 950 (2022). PMID: 35710981.
- A Khan et al., Nat Med, 28, 141 (2022). PMID: 35710995.
