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As functional effectors of genes, proteins provide direct insight into disease mechanisms. However, most proteomic alterations in postmortem human brains of AUD likely reflect a combination of inherited susceptibility (AUD-associated), the consequences of alcohol exposure (ethanol-responsive), other environmental and lifestyle factors, as well as sample preparation. Here, we profiled the proteome of human microglia-containing cortical organoids derived from human induced pluripotent stem cells from individuals with AUD (n=11) and without (n=5), paired with or without intermittent ethanol exposure. To maximize statistical power, donors were selected based on high or low genetic liability for AUD as measured by polygenic scores. Among 8,952 proteins that passed quality control, 1,038 were AUD-associated and 718 were ethanol-responsive. AUD-associated proteins were enriched for neuronal signaling, immune, mitochondrial, and extracellular matrix pathways, whereas ethanol-responsive proteins were enriched for RNA processing, ribosome biogenesis, protein translation, vesicle trafficking, and membrane transport pathways. Twenty ethanol-responsive proteins were replicated in a postmortem human prefrontal cortex proteomic dataset. Using UK Biobank plasma proteomics data, we identified 26 candidate AUD-associated biomarkers and 9 candidate ethanol-responsive biomarkers. We also found that major proteomic variation was significantly correlated with AUD polygenic scores. Together, these findings reveal distinct proteomic signatures of inherited susceptibility to AUD and ethanol exposure, providing new insights into mechanisms underlying AUD and identifying candidate circulating biomarkers for further investigation.<\/jats:p>","DOI":"10.64898\/2026.09.27.754852","type":"posted-content","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T20:55:18Z","timestamp":1790628918000},"source":"Crossref","is-referenced-by-count":0,"title":["Identification of alcohol use disorder-associated and ethanol-responsive proteins and candidate biomarkers using human cortical organoids"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-2467-7074","authenticated-orcid":false,"given":"Xindi","family":"Li","sequence":"first","affiliation":[{"name":"Center for NeuroMetabolism, Child Health Institute of New Jersey and Department of Neuroscience and Cell Biology, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, 08854, 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Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, U.S.A"},{"name":"Department of Biochemistry, Molecular Biology and Pharmacology, Indiana University School of Medicine, Indianapolis, IN, 46202, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tatiana","family":"Foroud","sequence":"additional","affiliation":[{"name":"Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2699-626X","authenticated-orcid":false,"given":"Yunlong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, U.S.A"},{"name":"Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, 46202, 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