Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.</p

Genome-wide association study evaluating lipoprotein-associated phospholipase A2 mass and activity at baseline and after rosuvastatin therapy.

Background-Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) is a proinflammatory enzyme bound to low-density lipoprotein cholesterol and other circulating lipoproteins. Two measures of Lp-PLA(2), mass and activity, are associated with increased cardiovascular risk. Data are sparse regarding genetic determinants of Lp-PLA(2) mass and activity, and no prior data are available addressing genetic determinants of statin-induced changes for this proinflammatory biomarker. Methods and Results-We performed a genome-wide association study of Lp-PLA(2) mass and activity at baseline and after 12 months of rosuvastatin therapy (20 mg/d) among 6851 participants of European ancestry from the Justification for Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) and performed replication in a meta-analysis of 13 664 participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Novel associations were identified and replicated at MS4A4E and TMEM49 for baseline Lp-PLA(2) activity with genome-wide significant joint P values (P=2.0x10(-11) and P=2.9x10(-9), respectively). In addition, genome-wide associations (P&lt;5x10(-8)) were identified and replicated for baseline Lp-PLA(2) mass at CETP and for Lp-PLA(2) activity at the APOC1-APOE and PLA2G7 loci. Among 2673 statin-allocated participants, both Lp-PLA(2) mass and activity were reduced by &gt;30% and low-density lipoprotein cholesterol by 50% after 12 months of statin therapy (P&lt;0.001 for both). Variants in ABCG2 and LPA were associated with change in statin-induced Lp-PLA(2) activity at genome-wide significance but were substantially attenuated after adjustment for statin-induced changes in lipid levels. Conclusions-Genome-wide significant associations at MS4A4E and TMEM49 may reflect novel influences on circulating levels of Lp-PLA(2) activity. In addition, genome-wide significant associations with rosuvastatin-induced change in Lp-PLA(2) activity were observed in ABCG2 and LPA, likely because of their impact on statin-induced low-density lipoprotein cholesterol lowering. (Circ Cardiovasc Genet. 2012;5:676-685.

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (n(DM) = 178,691, n(noDM) = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease. Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (n(DM) = 178,691, n(noDM) = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM