{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T12:15:57Z","timestamp":1791375357836,"version":"4.3.1"},"reference-count":24,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T00:00:00Z","timestamp":1762905600000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["HemaSphere"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Hemoglobinopathies, such as sickle cell disease and thalassemias, impose a substantial global burden, particularly in endemic regions. Current diagnostic methods, such as high\u2010performance liquid chromatography (HPLC), capillary electrophoresis, and genetic testing, can be time\u2010consuming, expensive, or limited in detecting all variants. This study introduces a novel diagnostic framework that combines high\u2010throughput proteomics with machine learning to address these challenges. We processed red blood cells, whole blood, and plasma samples from 82 individuals (development cohort) and 45 individuals (validation cohort) with structural hemoglobin variants (hemoglobin S, hemoglobin C, hemoglobin D, and hemoglobin E) or \u03b2\u2010thalassemia trait, as confirmed by standard clinical testing. Tryptic peptides were analyzed using data\u2010independent acquisition mass spectrometry, and random forest classifiers were trained to identify structural variants or \u03b2\u2010thalassemia trait. Model performance was evaluated across 100 Monte Carlo cross\u2010validations. For structural variants, the classifier achieved an area under the receiver\u2010operating characteristic curve (AUC) of 1.000 and 99.9% prediction accuracy in the validation cohort, when comparing our proteomics\u2010based diagnostics to standard testing with HPLC and Sanger sequencing (gold standard). For \u03b2\u2010thalassemia trait, the mean AUC was 1.000, and the prediction accuracy was 96.9% in the validation cohort, and a single peptide alone yielded 92% accuracy in a simple decision tree. This high\u2010throughput proteomics approach offers a rapid, scalable, and potentially cost\u2010effective alternative to existing diagnostic workflows, requiring minimal sample preparation while reducing manual interpretation. By combining peptide\u2010level data with machine learning, it enables precise classification of hemoglobinopathies and demonstrates a compelling path for routine clinical evaluation of hereditary anemias.<\/jats:p>","DOI":"10.1002\/hem3.70227","type":"journal-article","created":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T09:20:34Z","timestamp":1762939234000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Accurate diagnosis of hemoglobinopathies with machine learning based on high\u2010throughput proteomics"],"prefix":"10.1002","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1261-0645","authenticated-orcid":false,"given":"Shaodong","family":"Wei","sequence":"first","affiliation":[{"name":"Department of Hematology, Danish Red Blood Cell Center Copenhagen University Hospital\u2010Rigshospitalet Copenhagen Denmark"},{"name":"Department of Clinical Biochemistry Copenhagen University Hospital, Bispebjerg and Frederiksberg Hospital Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2855-208X","authenticated-orcid":false,"given":"Annelaura Bach","family":"Nielsen","sequence":"additional","affiliation":[{"name":"Department of Clinical Biochemistry Copenhagen University Hospital, Bispebjerg and Frederiksberg Hospital Copenhagen Denmark"},{"name":"Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1876-8187","authenticated-orcid":false,"given":"Jens","family":"Helby","sequence":"additional","affiliation":[{"name":"Department of Hematology, Danish Red Blood Cell Center Copenhagen University Hospital\u2010Rigshospitalet Copenhagen Denmark"},{"name":"Department of Clinical Medicine University of Copenhagen Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6633-1721","authenticated-orcid":false,"given":"Lylia","family":"Drici","sequence":"additional","affiliation":[{"name":"Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christine","family":"Rasmussen","sequence":"additional","affiliation":[{"name":"Department of Clinical Biochemistry Copenhagen University Hospital, Bispebjerg and Frederiksberg Hospital Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juanjuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1292-4799","authenticated-orcid":false,"given":"Matthias","family":"Mann","sequence":"additional","affiliation":[{"name":"Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark"},{"name":"Department of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6116-5114","authenticated-orcid":false,"given":"Jesper","family":"Petersen","sequence":"additional","affiliation":[{"name":"Department of Hematology, Danish Red Blood Cell Center Copenhagen University Hospital\u2010Rigshospitalet Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4230-5753","authenticated-orcid":false,"given":"Nicolai J.","family":"Wewer Albrechtsen","sequence":"additional","affiliation":[{"name":"Department of Clinical Biochemistry Copenhagen University Hospital, Bispebjerg and Frederiksberg Hospital Copenhagen Denmark"},{"name":"Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark"},{"name":"Department of Clinical Medicine University of Copenhagen Copenhagen Denmark"},{"name":"Copenhagen Center for Translational Research Copenhagen University Hospital\u2010Bispebjerg and Frederiksberg Hospital Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2082-0738","authenticated-orcid":false,"given":"Andreas","family":"Glenth\u00f8j","sequence":"additional","affiliation":[{"name":"Department of Hematology, Danish Red Blood Cell Center Copenhagen University Hospital\u2010Rigshospitalet Copenhagen Denmark"},{"name":"Department of Clinical Medicine University of Copenhagen Copenhagen 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