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- Ramdas, S., et al.
(author)
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A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
- 2022
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In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 109:8, s. 1366-1387
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Journal article (peer-reviewed)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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- Adam, A, et al.
(author)
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Abstracts from Hydrocephalus 2016.
- 2017
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In: Fluids and Barriers of the CNS. - : Springer Science and Business Media LLC. - 2045-8118. ; 14:Suppl 1
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Journal article (peer-reviewed)
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- Kanoni, Stavroula, et al.
(author)
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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
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In: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
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Journal article (peer-reviewed)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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- Kerkhof, H. J. M., et al.
(author)
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Recommendations for standardization and phenotype definitions in genetic studies of osteoarthritis: the TREAT-OA consortium
- 2011
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In: Osteoarthritis and Cartilage. - : Elsevier BV. - 1063-4584. ; 19:3, s. 254-264
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Journal article (peer-reviewed)abstract
- Objective: To address the need for standardization of osteoarthritis (OA) phenotypes by examining the effect of heterogeneity among symptomatic (SOA) and radiographic osteoarthritis (ROA) phenotypes. Methods: Descriptions of OA phenotypes of the 28 studies involved in the TREAT-OA consortium were collected. We investigated whether different OA definitions result in different association results by creating various hip OA definitions in one large population based cohort (the Rotterdam Study I (RSI)) and testing those for association with gender, age and body mass index using one-way ANOVA. For ROA, we standardized the hip-, knee- and hand ROA definitions and calculated prevalence's of ROA before and after standardization in nine cohort studies. This procedure could only be performed in cohort studies and standardization of SOA definitions was not feasible at this moment. Results: In this consortium, all studies with SOA phenotypes (knee, hip and hand) used a different definition and/or assessment of OA status. For knee-, hip- and hand ROA five, four and seven different definitions were used, respectively. Different hip ROA definitions do lead to different association results. For example, we showed in the RSI that hip OA defined as "at least definite joint space narrowing (JSN) and one definite osteophyte" was not associated with gender (P=0.22), but defined as "at least one definite osteophyte" was significantly associated with gender (P=3 x 10(-9)). Therefore, a standardization process was undertaken for ROA definitions. Before standardization a wide range of ROA prevalence's was observed in the nine cohorts studied. After standardization the range in prevalence of knee- and hip ROA was small. Conclusion: Phenotype definitions influence the prevalence of OA and association with clinical variables. ROA phenotypes within the TREAT-OA consortium were standardized to reduce heterogeneity and improve power in future genetics studies. (C) 2010 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
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