Linking genetic variants to kidney disease via the epigenome
Nature Genetics (IF41.307), Pub Date : 2022-06-23, DOI: 10.1038/s41588-022-01098-9
The largest GWAS for kidney function so far provided the starting point for integrated multi-stage annotation of genetic loci. Whole kidney and single-cell epigenomic information is crucial for translating GWAS information to the identification of causal genes and pathogenetic (and potentially targetable) cellular and molecular mechanisms of kidney disease.
Nature Genetics (IF41.307), Pub Date : 2022-06-23, DOI: 10.1038/s41588-022-01098-9
The largest GWAS for kidney function so far provided the starting point for integrated multi-stage annotation of genetic loci. Whole kidney and single-cell epigenomic information is crucial for translating GWAS information to the identification of causal genes and pathogenetic (and potentially targetable) cellular and molecular mechanisms of kidney disease.
