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- Winkler, TW, et al.
(author)
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Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals
- 2022
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In: Communications biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 5:1, s. 580-
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Journal article (peer-reviewed)abstract
- 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.
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- Gao, H, et al.
(author)
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Genetic variation in CDH13 is associated with lower plasma adiponectin levels but greater adiponectin sensitivity in East Asian populations
- 2013
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In: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 62:12, s. 4277-4283
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Journal article (peer-reviewed)abstract
- Variants in the CDH13 gene have been identified as determinants of blood levels of adiponectin, an insulin-sensitizing adipokine. However, their association with other metabolic risk factors remains unclear. We examined variants at CDH13 in relation to total and high-molecular-weight (HMW) adiponectin using data from a genome-wide association study performed in 2,434 Singaporean Chinese with replication in up to 3,290 Japanese and 1,610 Koreans. The top signal rs4783244 in CDH13 showed strong associations with total adiponectin (standardized β [β] = −0.34, 95% CI −0.38 to −0.30, P = 2.0 × 10−70), HMW adiponectin (β = −0.40, 95% CI −0.43 to −0.36, P = 1.1 × 10−117), and the HMW-to-total adiponectin ratio (β = −0.44, 95% CI −0.49 to −0.40, P = 3.2 × 10−83). In the replication study, this single nucleotide polymorphism explained 4.1% of total and 6.5% of HMW adiponectin levels. No association was observed between rs4783244 and metabolic traits associated with insulin resistance before adjustment for HMW adiponectin levels. After adjustment for HMW adiponectin levels, the minor allele was associated with lower BMI (β = −0.15, 95% CI −0.19 to −0.11, P = 3.5 × 10−14), homeostasis model assessment-insulin resistance index (β = −0.16, 95% CI −0.20 to −0.12, P = 9.2 × 10−16), and triglycerides (β = −0.16, 95% CI −0.19 to −0.12, P = 1.3 × 10−16) and with higher HDL (β = 0.16, 95% CI 0.12 to 0.19, P = 2.1 × 10−17). CDH13 variants strongly influence plasma total and HMW adiponectin levels in East Asian populations but appear to alter adiponectin sensitivity, resulting in better metabolic health than expected based on circulating adiponectin levels.
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- Kilpelainen, TO, et al.
(author)
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Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity
- 2019
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In: Nature communications. - London : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 376-
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Journal article (peer-reviewed)abstract
- Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.
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