{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T20:50:19Z","timestamp":1791406219639,"version":"4.3.3"},"reference-count":32,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T00:00:00Z","timestamp":1781654400000},"content-version":"vor","delay-in-days":16,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"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":["CNS Neurosci Ther"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Opioid\u2010induced delirium represents a major clinical challenge with substantial implications for patient safety and outcomes. An integrated evaluation combining pharmacovigilance and genetic evidence remains limited. This study aimed to systematically assess delirium risk across different opioids and to elucidate underlying molecular mechanisms by integrating real\u2010world safety data with Mendelian randomization (MR) analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) spanning 2004\u20132025, disproportionality analyses (reporting odds ratio, proportional reporting ratio, and empirical Bayes geometric mean) and multivariable logistic regression were conducted to quantify delirium risk associated with 12 commonly used opioids. Network pharmacology was subsequently applied to identify candidate pathways and targets, followed by MR analyses based on FinnGen data to investigate potential causal relationships between key target genes and delirium.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Substantial heterogeneity in delirium risk was observed across opioids. Methadone showed the strongest association with delirium (EBGM 25.98) and the highest independent risk after adjustment (adjusted odds ratio 29.79), followed by oxycodone. Stronger risk signals were consistently observed among older individuals (&gt;\u200955\u2009years) and females. Mechanistic analyses highlighted pathways related to xenobiotic metabolism and neuroinflammation, particularly the PI3K\u2010Akt signaling pathway. MR analyses identified\n                      <jats:italic>COMT<\/jats:italic>\n                      as a risk\u2010associated gene for delirium (OR 1.25), whereas\n                      <jats:italic>MYD88<\/jats:italic>\n                      and\n                      <jats:italic>CYP1B1<\/jats:italic>\n                      demonstrated potential protective effects.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      Marked differences in delirium risk exist among opioids.\n                      <jats:italic>COMT<\/jats:italic>\n                      ,\n                      <jats:italic>MYD88<\/jats:italic>\n                      , and\n                      <jats:italic>CYP1B1<\/jats:italic>\n                      were identified as key candidate genes underlying opioid\u2010associated delirium. These findings provide a genetic and mechanistic framework to support clinical risk stratification and the development of precision prevention and intervention strategies.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cns.70983","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T12:49:04Z","timestamp":1781700544000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Integrating Pharmacovigilance Data Mining and Mendelian Randomization to Identify Risk Profiles and Causal Targets of Opioid\u2010Induced Delirium"],"prefix":"10.1002","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1564-6392","authenticated-orcid":false,"given":"Xuetai","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Anesthesiology The Yancheng Clinical College of Xuzhou Medical University, the First People's Hospital of Yancheng  Yancheng 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