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- Ramdas, S., et al.
(författare)
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A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
- 2022
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 109:8, s. 1366-1387
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Tidskriftsartikel (refereegranskat)abstract
- A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
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| 5. |
- 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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| 6. |
- Dauber, A., et al.
(författare)
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A Genome-Wide Pharmacogenetic Study of Growth Hormone Responsiveness
- 2020
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Ingår i: The Journal of clinical endocrinology and metabolism. - : The Endocrine Society. - 1945-7197 .- 0021-972X. ; 105:10, s. 3203-3214
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Tidskriftsartikel (refereegranskat)abstract
- CONTEXT: Individual patients vary in their response to growth hormone (GH). No large-scale genome-wide studies have looked for genetic predictors of GH responsiveness. OBJECTIVE: To identify genetic variants associated with GH responsiveness. DESIGN: Genome-wide association study (GWAS). SETTING: Cohorts from multiple academic centers and a clinical trial. PATIENTS: A total of 614 individuals from 5 short stature cohorts receiving GH: 297 with idiopathic short stature, 276 with isolated GH deficiency, and 65 born small for gestational age. INTERVENTION: Association of more than 2 million variants was tested. MAIN OUTCOME MEASURES: Primary analysis: individual single nucleotide polymorphism (SNP) association with first-year change in height standard deviation scores. Secondary analyses: SNP associations in clinical subgroups adjusted for clinical variables; association of polygenic score calculated from 697 genome-wide significant height SNPs with GH responsiveness. RESULTS: No common variant associations reached genome-wide significance in the primary analysis. The strongest suggestive signals were found near the B4GALT4 and TBCE genes. After meta-analysis including replication data, signals at several loci reached or retained genome-wide significance in secondary analyses, including variants near ST3GAL6. There was no significant association with variants previously reported to be associated with GH response nor with a polygenic predicted height score. CONCLUSIONS: We performed the largest GWAS of GH responsiveness to date. We identified 2 loci with a suggestive effect on GH responsiveness in our primary analysis and several genome-wide significant associations in secondary analyses that require further replication. Our results are consistent with a polygenic component to GH responsiveness, likely distinct from the genetic regulators of adult height. © Endocrine Society 2020.
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