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Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

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  1. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

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  2. Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

  3. Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

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  4. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa

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  5. Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes

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  1. Reply to: Clinical impact of high platelet count and high hematocrit, by Marc Sorigue

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  2. Obesity as a Causal Risk Factor for Aortic Valve Stenosis

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  3. Lipoprotein(a) Reduction in Persons with Cardiovascular Disease

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Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa 1 .

OriginalsprogEngelsk
TidsskriftNature Genetics
Vol/bind50
Sider (fra-til)928-36
ISSN1061-4036
DOI
StatusUdgivet - 11 jun. 2018

ID: 54774876