The Journal of investigative dermatology · 2021
Multi-Trait Genetic Analysis Identifies Autoimmune Loci Associated with Cutaneous Melanoma.
СтатьяМетаанализПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Liyanage Upekha E, MacGregor Stuart, Bishop D Timothy, Shi Jianxin, An Jiyuan, Ong Jue Sheng, Han Xikun, Scolyer Richard A, Martin Nicholas G, Medland Sarah E, Byrne Enda M, Green Adèle C, Saw Robyn P M, Thompson John F, Stretch Jonathan, Spillane Andrew, Jiang Yunxuan, Tian Chao, 23andMe Research Team, Gordon Scott G, Duffy David L, Olsen Catherine M, Whiteman David C, Long Georgina V, Iles Mark M, Landi Maria Teresa, Law Matthew H
Аннотация
Genome-wide association studies (GWAS) have identified a number of risk loci for cutaneous melanoma. Cutaneous melanoma shares overlapping genetic risk (genetic correlation) with a number of other traits, including its risk factors such as sunburn propensity. This genetic correlation can be exploited to identify additional cutaneous melanoma risk loci by multitrait analysis of GWAS (MTAG). We used bivariate linkage disequilibrium-score regression score regression to identify traits that are genetically correlated with clinically confirmed cutaneous melanoma and then used publicly available GWAS for these traits in a multitrait analysis of GWAS. Multitrait analysis of GWAS allows GWAS to be combined while accounting for sample overlap and incomplete genetic correlation. We identified a total of 74 genome-wide independent loci, 19 of them were not previously reported in the input cutaneous melanoma GWAS meta-analysis. Of these loci, 55 were replicated (P < 0.05/74, Bonferroni-corrected P-value in two independent cutaneous melanoma replication cohorts from Melanoma Institute Australia and 23andMe, Inc. Among the, to our knowledge, previously unreported cutaneous melanoma loci are ones that have also been associated with autoimmune traits including rs715199 near LPP and rs10858023 near AP4B1. Our analysis indicates genetic correlation between traits can be leveraged to identify new risk genes for cutaneous melanoma.