PNPLA3 variation and kidney disease.
Alessandro MantovaniGiovanni TargherPublished in: Liver international : official journal of the International Association for the Study of the Liver (2024)
Accumulating epidemiological evidence shows that the patatin-like phospholipase domain-containing protein-3 (PNPLA3) rs738409 G allele, which is the most robust genetic variant associated with greater susceptibility to metabolic dysfunction-associated steatotic liver disease (MASLD), is significantly associated with impaired kidney function in both adults and children, regardless of the presence of common renal risk factors, MASLD severity, and other potential confounders. Although some prospective studies have reported a significant association between the PNPLA3 rs738409 G allele and the increased risk of developing chronic kidney disease (CKD), the epidemiological evidence about a possible direct effect of the PNPLA3 rs738409 G allele on the risk of developing CKD is still limited. Experimentally, PNPLA3 is expressed in renal podocytes, pericytes, and proximal tubule cells, thus supporting the notion that the mutant PNPLA3 protein may play a role in developing renal steatosis and fibrosis. However, it cannot be ruled out that a part of the adverse effect of the PNPLA3 rs738409 G allele on kidney function may be driven by a direct impact of this genetic variant on the development and progression of MASLD. It is possible to hypothesize that identifying the PNPLA3 genotype might help identify individuals at higher risk of CKD and those at greater risk of advanced MASLD. In this narrative minireview, we summarize the current epidemiological data about the association between the PNPLA3 rs738409 G allele and the risk of CKD and abnormal albuminuria. We also briefly discuss the putative biological mechanisms underpinning this association and its potential and future clinical implications.
Keyphrases
- chronic kidney disease
- end stage renal disease
- risk factors
- young adults
- type diabetes
- metabolic syndrome
- risk assessment
- oxidative stress
- machine learning
- genome wide
- small molecule
- dna methylation
- cell death
- amino acid
- cell proliferation
- climate change
- endothelial cells
- peritoneal dialysis
- human health
- deep learning
- drug induced