| 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. |
- de las Fuentes, Lisa, et al.
(författare)
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Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci
- 2021
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Ingår i: Molecular Psychiatry. - : Springer Nature. - 1359-4184 .- 1476-5578. ; 26:6, s. 2111-2125
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Tidskriftsartikel (refereegranskat)abstract
- Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, “Some College” (yes/no) and “Graduated College” (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10-8). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
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| 3. |
- 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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| 4. |
- Murphy, Rachel A, et al.
(författare)
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Omega-3 and omega-6 polyunsaturated fatty acid biomarkers and sleep : a pooled analysis of cohort studies On behalf of the Fatty Acids and Outcomes Research Consortium (FORCE).
- 2022
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Ingår i: American Journal of Clinical Nutrition. - : Oxford University Press (OUP). - 0002-9165 .- 1938-3207. ; 115:3, s. 864-876
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: n-3 and n-6 polyunsaturated fatty acids (PUFAs) have physiologic roles in sleep processes, but little is known regarding circulating n-3 and n-6 PUFA and sleep parameters.OBJECTIVES: To assess associations between biomarkers of n-3 and n-6 PUFA intake with self-reported sleep duration and difficulty falling sleeping in the Fatty Acids and Outcome Research Consortium.METHODS: Harmonized, de novo, individual-level analyses were performed and pooled across 12 cohorts. Participants were between 35 to 96 years old and from 5 nations. Circulating measures included alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), EPA + DPA + DHA, linoleic acid and arachidonic acid. Sleep duration (10 cohorts, N = 18,791) was categorized as short (≤6 hours), 7-8 hours (reference) or long (9 + hours). Difficulty falling sleeping (8 cohorts, N = 12,500) was categorized as yes or no. Associations between PUFAs, sleep duration, and difficulty falling sleeping were assessed by cross-sectional multinomial logistic regression using standardized protocols and covariates. Cohort-specific multivariable-adjusted odds ratios (ORs) per quintile of PUFAs were pooled with inverse-variance weighted meta-analysis.RESULTS: In pooled analysis adjusted for sociodemographics and health status, participants with higher very long-chain n-3 PUFAs were less likely to have long sleep duration. Comparing top vs. bottom quintiles, the multivariable-adjusted OR (95% confidence interval, CI) for long-sleep was 0.78 (0.65, 0.95) for DHA and for EPA + DPA + DHA, 0.76 (0.63, 0.93). Significant associations were not identified for ALA and n-6 PUFA with short sleep duration, or difficulty falling sleeping.CONCLUSIONS: Participants with higher levels of very long-chain n-3 PUFAs were less likely to have long sleep duration. While objective biomarkers reduce recall bias and misclassification, the cross-sectional design limits assessment of the temporal nature of this relationship. These novel findings across 12 cohorts highlight the need for experimental and biological assessments of very long-chain n-3 PUFAs and sleep duration.
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| 5. |
- Xu, Yu, et al.
(författare)
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An atlas of genetic scores to predict multi-omic traits
- 2023
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Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 616:7955, s. 123-131
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Tidskriftsartikel (refereegranskat)abstract
- The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.
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