5 research outputs found
Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.
Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Variant annotation was supported by software resources provided via the Caché Campus program of the InterSystems GmbH to Alexander Teumer
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Association of obesity with 3-month mortality in kidney failure patients with COVID-19.
BackgroundIn the general population with coronavirus disease 2019 (COVID-19), obesity is associated with an increased risk of mortality. Given the typically observed obesity paradox among patients on kidney function replacement therapy (KFRT), especially dialysis patients, we examined the association of obesity with mortality among dialysis patients or living with a kidney transplant with COVID-19.MethodsData from the European Renal Association COVID-19 Database (ERACODA) were used. KFRT patients diagnosed with COVID-19 between 1 February 2020 and 31 January 2021 were included. The association of Quetelet's body mass index (BMI) (kg/m2), divided into: <18.5 (lean), 18.5-24.9 (normal weight), 25-29.9 (overweight), 30-34.9 (obese I) and ≥35 (obese II/III), with 3-month mortality was investigated using Cox proportional-hazards regression analyses.ResultsIn 3160 patients on KFRT (mean age: 65 years, male: 61%), 99 patients were lean, 1151 normal weight (reference), 1160 overweight, 525 obese I and 225 obese II/III. During follow-up of 3 months, 28, 20, 21, 23 and 27% of patients died in these categories, respectively. In the fully adjusted model, the hazard ratios (HRs) for 3-month mortality were 1.65 [95% confidence interval (CI): 1.10, 2.47], 1 (ref.), 1.07 (95% CI: 0.89, 1.28), 1.17 (95% CI: 0.93, 1.46) and 1.71 (95% CI: 1.27, 2.30), respectively. Results were similar among dialysis patients (N = 2343) and among those living with a kidney transplant (N = 817) (Pinteraction = 0.99), but differed by sex (Pinteraction = 0.019). In males, the HRs for the association of aforementioned BMI categories with 3-month mortality were 2.07 (95% CI: 1.22, 3.52), 1 (ref.), 0.97 (95% CI: 0.78. 1.21), 0.99 (95% CI: 0.74, 1.33) and 1.22 (95% CI: 0.78, 1.91), respectively, and in females corresponding HRs were 1.34 (95% CI: 0.70, 2.57), 1 (ref.), 1.31 (95% CI: 0.94, 1.85), 1.54 (95% CI: 1.05, 2.26) and 2.49 (95% CI: 1.62, 3.84), respectively.ConclusionIn KFRT patients with COVID-19, on dialysis or a kidney transplant, obesity is associated with an increased risk of mortality at 3 months. This is in contrast to the obesity paradox generally observed in dialysis patients. Additional studies are required to corroborate the sex difference in the association of obesity with mortality
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Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria.
Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria
Estimated GFR: time for a critical appraisal
Since 1957, over 70 equations based on creatinine and/or cystatin C levels have been developed to estimate glomerular filtration rate (GFR). However, whether these equations accurately reflect renal function is debated. In this Perspectives article, we discuss >70 studies that compared estimated GFR (eGFR) with measured GFR (mGFR), involving similar to 40,000 renal transplant recipients and patients with chronic kidney disease (CKD), type 2 diabetes mellitus or polycystic kidney disease. Their results show that eGFR often differed from mGFR by +/- 30% or more, that eGFR values incorrectly staged CKD in 30-60% of patients, and that eGFR and mGFR gave different rates of GFR decline. Errors were unpredictable, and comparable for equations based on creatinine and/or cystatin C. We argue, therefore, that the persistence of these errors (despite intensive research) suggests that the problem lies with using creatinine and/or cystatin C as markers of renal function, rather than with the mathematical methods used for GFR estimation.Nephrolog