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- Sampson, Joshua N., et al.
(författare)
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Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
- 2015
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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- Wang, Zhaoming, et al.
(författare)
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Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33
- 2014
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:24, s. 6616-6633
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
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- 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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- Schael, S, et al.
(författare)
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Precision electroweak measurements on the Z resonance
- 2006
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Ingår i: Physics Reports. - : Elsevier BV. - 0370-1573 .- 1873-6270. ; 427:5-6, s. 257-454
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Forskningsöversikt (refereegranskat)abstract
- We report on the final electroweak measurements performed with data taken at the Z resonance by the experiments operating at the electron-positron colliders SLC and LEP. The data consist of 17 million Z decays accumulated by the ALEPH, DELPHI, L3 and OPAL experiments at LEP, and 600 thousand Z decays by the SLID experiment using a polarised beam at SLC. The measurements include cross-sections, forward-backward asymmetries and polarised asymmetries. The mass and width of the Z boson, m(Z) and Gamma(Z), and its couplings to fermions, for example the p parameter and the effective electroweak mixing angle for leptons, are precisely measured: m(Z) = 91.1875 +/- 0.0021 GeV, Gamma(Z) = 2.4952 +/- 0.0023 GeV, rho(l) = 1.0050 +/- 0.0010, sin(2)theta(eff)(lept) = 0.23153 +/- 0.00016. The number of light neutrino species is determined to be 2.9840 +/- 0.0082, in agreement with the three observed generations of fundamental fermions. The results are compared to the predictions of the Standard Model (SM). At the Z-pole, electroweak radiative corrections beyond the running of the QED and QCD coupling constants are observed with a significance of five standard deviations, and in agreement with the Standard Model. Of the many Z-pole measurements, the forward-backward asymmetry in b-quark production shows the largest difference with respect to its SM expectation, at the level of 2.8 standard deviations. Through radiative corrections evaluated in the framework of the Standard Model, the Z-pole data are also used to predict the mass of the top quark, m(t) = 173(+10)(+13) GeV, and the mass of the W boson, m(W) = 80.363 +/- 0.032 GeV. These indirect constraints are compared to the direct measurements, providing a stringent test of the SM. Using in addition the direct measurements of m(t) and m(W), the mass of the as yet unobserved SM Higgs boson is predicted with a relative uncertainty of about 50% and found to be less than 285 GeV at 95% confidence level. (c) 2006 Elsevier B.V. All rights reserved.
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- 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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- Stanaway, Jeffrey D., et al.
(författare)
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Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - 1474-547X .- 0140-6736. ; 392:10159, s. 1923-1994
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Tidskriftsartikel (refereegranskat)abstract
- Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk- outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.
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