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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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- Justice, A. E., et al.
(author)
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Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits
- 2017
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
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Journal article (peer-reviewed)abstract
- Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
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- Graff, M., et al.
(author)
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Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults
- 2017
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In: PLoS Genet. - : Public Library of Science (PLoS). - 1553-7404 .- 1553-7390. ; 13:4
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Journal article (peer-reviewed)abstract
- Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by similar to 30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
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- Bryois, J., et al.
(author)
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Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease
- 2020
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 52:5, s. 482-493
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Journal article (peer-reviewed)abstract
- Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson’s disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson’s disease. © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
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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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- Locke, Adam E, et al.
(author)
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Genetic studies of body mass index yield new insights for obesity biology.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
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Journal article (peer-reviewed)abstract
- Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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- Silventoinen, K., et al.
(author)
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The CODATwins Project : The current status and recent findings of COllaborative Project of Development of Anthropometrical Measures in Twins
- 2019
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In: Twin Research and Human Genetics. - : Cambridge University Press. - 1832-4274 .- 1839-2628. ; 22:6, s. 800-808
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Journal article (peer-reviewed)abstract
- The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural-geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
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- Shungin, Dmitry, et al.
(author)
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New genetic loci link adipose and insulin biology to body fat distribution.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
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Journal article (peer-reviewed)abstract
- Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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- Palmer, Nicholette D, et al.
(author)
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A genome-wide association search for type 2 diabetes genes in African Americans.
- 2012
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In: PloS one. - San Francisco : Public Library of Science (PLoS). - 1932-6203. ; 7:1, s. e29202-
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Journal article (peer-reviewed)abstract
- African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.
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- Stolk, Lisette, et al.
(author)
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Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways
- 2012
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 44:3, s. 260-268
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Journal article (peer-reviewed)abstract
- To newly identify loci for age at natural menopause, we carried out a meta-analysis of 22 genome-wide association studies (GWAS) in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 loci newly associated with age at natural menopause (at P < 5 × 10(-8)). Candidate genes located at these newly associated loci include genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG and PRIM1) and immune function (IL11, NLRP11 and PRRC2A (also known as BAT2)). Gene-set enrichment pathway analyses using the full GWAS data set identified exoDNase, NF-κB signaling and mitochondrial dysfunction as biological processes related to timing of menopause.
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