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

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  1. New insights into the genetic etiology of Alzheimer's disease and related dementias

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  2. Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles

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  3. Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

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  4. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

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  1. Monocyte count and soluble markers of monocyte activation in people living with HIV and uninfected controls

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  2. Self-reported and genetically predicted coffee consumption and smoking in dementia: A Mendelian randomization study

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  3. New insights into the genetic etiology of Alzheimer's disease and related dementias

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  4. Risk of recurrence and long-term mortality following radical cystectomy for bladder cancer

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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 .

Original languageEnglish
JournalNature Genetics
Volume50
Pages (from-to)928-36
ISSN1061-4036
DOIs
Publication statusPublished - 11 Jun 2018

ID: 54774876