A genome-wide association study implicates multiple mechanisms influencing raised urinary albumin–creatinine ratio. (20th October 2019)

• Record Type: Journal Article
• Authors: Casanova, Francesco; Tyrrell, Jessica; Beaumont, Robin N; Ji, Yingjie; Jones, Samuel E; Hattersley, Andrew T; Weedon, Michael N; Murray, Anna; Shore, Angela C; Frayling, Timothy M; Wood, Andrew R
• Is Part Of: Human molecular genetics. Volume 28:Number 24(2019)
• Page Start: 4197
• Page End: 4207
• Publication Date: 2019-10-20
• Subjects: Human molecular genetics -- Periodicals; Human chromosome abnormalities -- Periodicals; 572.8
• DOI: 10.1093/hmg/ddz243
• Languages: English
• ISSNs: 0964-6906

Abstract

Abstract: Raised albumin–creatinine ratio (ACR) is an indicator of microvascular damage and renal disease. We aimed to identify genetic variants associated with raised ACR and study the implications of carrying multiple ACR-raising alleles with metabolic and vascular-related disease. We performed a genome-wide association study of ACR using 437 027 individuals from the UK Biobank in the discovery phase, 54 527 more than previous studies, and followed up our findings in independent studies. We identified 62 independent associations with ACR across 56 loci ( P < 5 × 10 –8 ), of which 20 were not previously reported. Pathway analyses and the identification of 20 of the 62 variants (at r 2 > 0.8) coinciding with signals for at least 16 related metabolic and vascular traits, suggested multiple pathways leading to raised ACR levels. After excluding variants at the CUBN locus, known to alter ACR via effects on renal absorption, an ACR genetic risk score was associated with a higher risk of hypertension, and less strongly, type 2 diabetes and stroke. For some rare genotype combinations at the CUBN locus, most individuals had ACR levels above the microalbuminuria clinical threshold. Contrary to our hypothesis, individuals carrying more CUBN ACR-raising alleles, and above the clinical threshold, had a higher frequency of vascular disease. The CUBN allele effects on ACR were twice as strong in people with diabetes—a result robust to an optimization-algorithm approach to simulating interactions, validating previously reported gene–diabetes interactions ( P ≤ 4 × 10 –5 ). In conclusion, a variety of genetic mechanisms and traits contribute to variation in ACR.