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Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis.

Kazuyoshi IshigakiSaori SakaueChikashi C TeraoYang LuoKyuto SoneharaKensuke YamaguchiTiffany AmariutaChun Lai TooVincent A LauferIan C ScottSebastien ViatteMeiko TakahashiKoichiro OhmuraAkira MurasawaMotomu HashimotoHiromu ItoMohammed HammoudehSamar Al EmadiBasel K MasriHussein HalabiHumeira BadshaImad W UthmanXin WuLi LinTing LiDarren PlantRichard B WarrenGisela OrozcoSuzanne M M VerstappenJohn David BowesAlexander J MacGregorSuguru HondaMasaru KoidoKohei TomizukaYoichiro KamataniHiroaki TanakaEiichi TanakaAkari SuzukiYuichi MaedaKenichi YamamotoSatoru MiyawakiGang XieJinyi ZhangChristopher Ian AmosEdward KeystoneGertjan WolbinkIrene van der Horst-BruinsmaJing CuiKatherine P LiaoRobert J CarrollHye-Soon LeeSo-Young BangKatherine A SiminovitchNiek De VriesLars AlfredssonSolbritt Rantapää DahlqvistElizabeth W KarlsonSang-Cheol BaeRobert P KimberlyJeffrey C EdbergXavier MarietteThomas Wj HuizingaPhilippe DieudeMatthias SchneiderMartin KerickJoshua C Dennynull nullKoichi MatsudaKeitaro MatsuoTsuneyo MimoriFumihiko MatsudaKeishi FujioYoshiya TanakaAtsushi KumanogohMatthew TraylorCathryn M LewisStephen EyreHuji XuRicha SaxenaThurayya ArayssiYuta KochiKatsunori IkariMasayoshi HarigaiPeter K GregersenKazuhiko YamamotoS Louis BridgesLeonid PadyukovJavier MartínLars KlareskogYukinori OkadaSoumya Raychaudhuri
Published in: Nature genetics (2022)
Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10 -8 ), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.
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