| 1. |
- Kanoni, Stavroula, et al.
(författare)
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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
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Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N=1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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| 2. |
- Mahajan, Anubha, et al.
(författare)
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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
- 2022
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:5, s. 560-572
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Tidskriftsartikel (refereegranskat)abstract
- We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
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| 3. |
- Gaziano, Liam, et al.
(författare)
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Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19
- 2021
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Ingår i: Nature Medicine. - : Springer Nature. - 1078-8956 .- 1546-170X. ; 27:4
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale Mendelian randomization and colocalization analyses using gene expression and soluble protein data for 1,263 actionable druggable genes, which encode protein targets for approved drugs or drugs in clinical development, identify IFNAR2 and ACE2 as the most promising therapeutic targets for early management of COVID-19. Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 x 10(-6); IFNAR2, P = 9.8 x 10(-11) and IL-10RB, P = 2.3 x 10(-14)) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.
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| 4. |
- Yuan, Shuai, et al.
(författare)
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Effects of metabolic traits, lifestyle factors, and pharmacological interventions on liver fat : mendelian randomisation study
- 2022
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Ingår i: BMJ medicine. - : BMJ Publishing Group Ltd. - 2754-0413. ; 1
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To investigate the effects of metabolic traits, lifestyle factors, and drug interventions on liver fat using the mendelian randomisation paradigm.Design: Mendelian randomisation study.Setting: Publicly available summary level data from genome-wide association studies.Participants: Genome-wide association studies of 32 974 to 1 407 282 individuals who were predominantly of European descent.Exposures: Genetic variants predicting nine metabolic traits, six lifestyle factors, four lipid lowering drug targets, three antihypertensive drug targets, and genetic association estimates formagnetic resonance imaging measured liver fat.Main Outcome Measures: Mendelian randomisation analysis was used to investigate the effects of these exposures on liver fat, incorporating sensitivity analyses that relaxed the requisite modelling assumptions.Results: Genetically predicted liability to obesity, type 2 diabetes, elevated blood pressure, elevated triglyceride levels, cigarette smoking, and sedentary time watching television were associated with higher levels of liver fat. Genetically predicted lipid lowering drug effects were not associated with liver fat; however, β blocker and calcium channel blocker antihypertensive drug effects were associated with lower levels of liver fat.Conclusion: These analyses provide evidence of a causal effect of various metabolic traits, lifestyle factors, and drug targets on liver fat. The findings complement existing epidemiological associations, further provide mechanistic insight, and potentially supports a role for drug interventions in reducing the burden of hepatic steatosis and related disease. Further clinical study is now warranted to investigate the relevance of these genetic analyses for patient care.
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