{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T10:03:21Z","timestamp":1784887401806,"version":"3.55.0"},"reference-count":52,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:00:00Z","timestamp":1776902400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:00:00Z","timestamp":1776902400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J cachexia sarcopenia muscle"],"published-print":{"date-parts":[[2026,6]]},"abstract":"ABSTRACT<\/jats:title>\n \n Background<\/jats:title>\n Chronic obstructive pulmonary disease (COPD) is associated with musculoskeletal comorbidities, including cachexia. Weight loss (WL) is the major criterion for cachexia and increases risk for mortality in COPD. Risk factors for WL in COPD are incompletely understood. We performed this whole genome sequencing (WGS) analysis to identify genetic risk variants for WL in COPD.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n We studied 16\u2009972 participants from the Trans\u2010Omics for Precision Medicine (TOPMed) Initiative and All of Us Research Program. COPD was diagnosed using spirometry in TOPMed, while diagnosis codes were used in All of Us. WL was defined as WL \u2265\u20095% or a final body mass index (BMI)\u2009<\u200920\u2009kg\/m\n 2<\/jats:sup>\n . WGS data came from white blood cells in all cohorts. Single\u2010variant testing was conducted on both race\u2010 and study\u2010stratified cohorts and in a cosmopolitan, ancestry\u2010independent manner using GENESIS in TOPMed and SAIGE in All of Us. SAIGE\u2010GENE+ gene\u2010based analyses were performed on race\u2010stratified and cosmopolitan cohorts. Single variant meta\u2010analyses were conducted using METAL within (B\/AA and NHW analyses of Black\/African\u2013American and non\u2010Hispanic white participants, respectively) and across racial groups (COSMO). Rare variant gene\u2010based results were combined using Fisher's method. Transcriptomic effects were predicted using MetaXcan. We used the GWAS Catalogue to analyse for colocalization with other related traits.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Two single variants were associated with WL in COPD among All of Us participants: one intronic variant in\n HCN1<\/jats:italic>\n in Black\/African\u2013American participants (chr5:45271359:TACACAC:T, odds ratio with 95% confidence interval (OR (CI\n 95<\/jats:sub>\n ))\u2009=\u20092.43(1.78\u20133.31),\n p<\/jats:italic>\n \u2009=\u20091.95 \u00d7 10\n \u22128<\/jats:sup>\n ) and one intergenic variant between\n PPP4R2<\/jats:italic>\n and\n PDZRN3<\/jats:italic>\n in the cosmopolitan and NHW cohorts (chr3:73345901:A:G, OR (CI\n 95<\/jats:sub>\n )\u2009=\u20090.21(0.12\u20130.35),\n p<\/jats:italic>\n \u2009=\u20098.84 \u00d7 10\n \u22129<\/jats:sup>\n in cosmopolitan and OR (CI\n 95<\/jats:sub>\n )\u2009=\u20090.18(0.10\u20130.33),\n p<\/jats:italic>\n \u2009=\u20099.44 \u00d7 10\n \u22129<\/jats:sup>\n in NHW). Single\u2010variant meta\u2010analysis identified two loci associated with WL in COPD: five variants within\n DRAIC<\/jats:italic>\n in the B\/AA meta\u2010analysis (lead variant chr15:69571341:A:G, OR (CI\n 95<\/jats:sub>\n )\u2009=\u20091.37(1.23\u20131.51),\n p<\/jats:italic>\n \u2009=\u20091.29 \u00d7 10\n \u22129<\/jats:sup>\n ) and two intronic variants within\n RFX3<\/jats:italic>\n in the cosmopolitan meta\u2010analysis (lead variant chr9:3390983:T:C, OR (CI\n 95<\/jats:sub>\n )\u2009=\u20091.50(1.31\u20131.73),\n p<\/jats:italic>\n \u2009=\u20091.06 \u00d7 10\n \u22128<\/jats:sup>\n ). Rare variants within\n RNU6\u2010565P<\/jats:italic>\n (NHW analysis in All of Us;\n p<\/jats:italic>\n \u2009=\u20092.83 \u00d7 10\n \u22127<\/jats:sup>\n ) and\n LOC339298<\/jats:italic>\n (B\/AA analysis in All of Us,\n p<\/jats:italic>\n \u2009=\u20091.85 \u00d7 10\n \u22126<\/jats:sup>\n ) were associated with WL in COPD. The\n RNU\u2010565P<\/jats:italic>\n signal remained significant after combination with TOPMed results (p\n combined<\/jats:sub>\n \u2009=\u20091.23 \u00d7 10\n \u22126<\/jats:sup>\n ). MetaXcan predicted differential expression of\n LNC00959<\/jats:italic>\n in visceral adipose tissue (\n p<\/jats:italic>\n \u2009=\u20091.16 \u00d7 10\n \u22126<\/jats:sup>\n in COSMO analysis). Colocalization analyses identified genomic associations between BMI and variants in or near\n DRAIC<\/jats:italic>\n ,\n RFX3<\/jats:italic>\n ,\n PDZRN3<\/jats:italic>\n , and\n LINC00959<\/jats:italic>\n .\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n In the first WGS analysis of WL in COPD, we have identified seven novel loci. Further characterization of these loci will validate our findings and improve our understanding of the molecular pathophysiology of this condition.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/jcsm.70293","type":"journal-article","created":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T02:48:24Z","timestamp":1776998904000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Whole Genome Sequence Analysis of Weight Loss in 16\u2009972 Participants With COPD Reveals Novel Risk Loci in\n DRAIC<\/i>\n and\n RFX3<\/i>"],"prefix":"10.1002","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9935-6319","authenticated-orcid":false,"suffix":"III","given":"Joe\u00a0W.","family":"Chiles","sequence":"first","affiliation":[{"name":"Division of Pulmonary, Allergy, and Critical Care Medicine University of Alabama at Birmingham Birmingham Alabama 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