{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T05:20:55Z","timestamp":1787721655087,"version":"build-2784847793"},"reference-count":55,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Tacrolimus is a core immunosuppressant in organ transplantation, but its narrow therapeutic window and significant pharmacokinetic variability hinder precision dosing. Although CYP3A5-guided strategies have established clinical relevance for tacrolimus initial dose adjustment, they do not fully account for the marked interindividual variability in tacrolimus exposure, highlighting the need for complementary models to decode more complex genetic regulation. This study aimed to identify candidate genetic modulators of tacrolimus metabolism and develop an integrated predictive framework for individualized therapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using 46 BXD recombinant inbred mouse strains, we characterized transcriptomics and machine learning, and validated key genes. We then constructed a clinical model using data from 168 renal transplant recipients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We identified 19 genomic loci associated with tacrolimus pharmacokinetic traits and supported DBP\/CYP2A6 as candidate modulators associated with tacrolimus disposition. The clinical prediction model, incorporating these genes and clinical variables, achieved robust AUROC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>These findings support a polygenic contribution to tacrolimus metabolism and provide an experimental and computational framework for identifying candidate modulators relevant to individualized dosing. The BXD mouse platform offers a systems-genetics approach for mechanistic discovery that may inform future translational studies on tacrolimus precision dosing.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1903968","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T04:50:22Z","timestamp":1787719822000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Advancing precision tacrolimus therapy: a systems genetics dissection in BXD platform"],"prefix":"10.3389","volume":"17","author":[{"given":"Wei","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Pharmacy, China-Japan Friendship Hospital","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin-Bo","family":"Wang","sequence":"additional","affiliation":[{"name":"China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, China"]},{"name":"Department of Pharmacy, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu-Wei","family":"Guo","sequence":"additional","affiliation":[{"name":"Maurice H. 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