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However, their clinical adoption is limited by the invasive nature of tissue sampling. Furthermore, transcriptomic datasets are often affected by batch effects and gene-level noise, which compromise model generalizability across platforms and clinical cohorts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We developed WBT-DC (Whole Blood Transcriptomics\u2013based Disease Classification), a computational pipeline designed to overcome these challenges. WBT-DC integrates rank-based feature extraction to mitigate batch effects with an ensemble machine-learning framework that incorporates cross-validation and hyperparameter optimization. Its performance was systematically evaluated across five independent cohorts involving 2,164 participants and three disease contexts: Crohn\u2019s disease (CD), ulcerative colitis (UC), and amyotrophic lateral sclerosis (ALS). We tested the model\u2019s robustness across RNA-sequencing and microarray platforms. Additionally, an internal rheumatoid arthritis (RA) cohort (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009165) was utilized for real-world prospective validation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>WBT-DC demonstrated high accuracy, achieving ROC\u2013AUC values of 0.90\u20130.94 in independent datasets when training and testing were conducted on the same platform. In cross-platform evaluations, the pipeline maintained robust performance with ROC\u2013AUC values ranging from 0.71 to 0.84, consistently outperforming conventional gene expression-based models. In the RA validation cohort, WBT-DC achieved an ROC\u2013AUC of 0.81, supporting its applicability in a real-world clinical setting.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>WBT-DC provides a robust, non-invasive, and platform-agnostic framework for disease classification using whole-blood transcriptomics. By effectively addressing batch effects and platform variability, this pipeline offers a scalable solution for translating systems-level transcriptomic insights into applications.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12967-026-08254-3","type":"journal-article","created":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T08:29:03Z","timestamp":1778488143000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["WBT-DC pipeline: a cross-cohort and cross-platform disease classification pipeline based on whole-blood transcriptomics"],"prefix":"10.1186","volume":"24","author":[{"given":"Mengzhen","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingqi","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ozlem","family":"Altay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bayram","family":"Yuksel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mathias","family":"Uhlen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hasan","family":"Turkez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4254-6090","authenticated-orcid":false,"given":"Adil","family":"Mardinoglu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,11]]},"reference":[{"key":"8254_CR1","doi-asserted-by":"crossref","unstructured":"He D, Guler SA, Shannon CP, Ryerson CJ, Tebbutt SJ. 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The study was conducted in accordance with the Declaration of Helsinki.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"All the authors reviewed and approved the final version of the manuscript for publication.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"AM is the cofounder of the SZA Longevity Inc and Trustlife Global Inc. The other authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"679"}}