rs10151563 - Y_RNA - Y_RNA

Magnitude 2.2 · 3 studies on file

Reported associations

• Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease. - Nature genetics (2022) · Liu H, Doke T, Guo D, Sheng X, Ma Z, Park J, Vy HMT, Nadkarni GN, Abedini A, Miao Z, Palmer M, Voight BF, Li H, Brown CD, Ritchie MD, Shu Y, Susztak K · PubMed 35710981

  More than 800 million people suffer from kidney disease, yet the mechanism of kidney dysfunction is poorly understood. In the present study, we define the genetic association with kidney function in 1.5 million individuals and identify 878 (126 new) loci. We map the genotype effect on the methylome in 443 kidneys, transcriptome in 686 samples and single-cell open chromatin in 57,229 kidney cells. Heritability analysis reveals that methylation variation explains a larger fraction of heritability than gene expression. We present a multi-stage prioritization strategy and prioritize target genes for 87% of kidney function loci. We highlight key roles of proximal tubules and metabolism in kidney function regulation. Furthermore, the causal role of SLC47A1 in kidney disease is defined in mice wi

• Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals - Unknown journal (n.d.) · Unknown authors · PubMed 34272381

  ABSTRACT: Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 lo

• Genetic analysis of elevated levels of creatinine and cystatin C biomarkers reveals novel genetic loci associated with kidney function - Unknown journal (n.d.) · Unknown authors · PubMed 39927731

  ABSTRACT: Abstract The rising prevalence of chronic kidney disease (CKD), affecting an estimated 37 million adults in the United States, presents a significant global health challenge. CKD is typically assessed using estimated Glomerular Filtration Rate (eGFR), which incorporates serum levels of biomarkers such as creatinine and cystatin C. However, these biomarkers do not directly measure kidney function; their elevation in CKD results from diminished glomerular filtration. Genome-wide association studies (GWAS) based on eGFR formulas using creatinine (eGFRcre) or cystatin C (eGFRcys) have identified distinct non-overlapping loci, raising questions about whether these loci govern kidney function or biomarker metabolism. In this study, we show that GWAS on creatinine and cystatin C levels

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