{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T07:00:03Z","timestamp":1791442803540,"version":"4.3.3"},"reference-count":101,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T00:00:00Z","timestamp":1722902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Takeda Farmac\u00e9utica Espa\u00f1a S.A."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Type 1 Gaucher disease (GD1) is a rare, autosomal recessive disorder caused by glucocerebrosidase deficiency. Skeletal manifestations represent one of the most debilitating and potentially irreversible complications of GD1. Although imaging studies are the gold standard, early diagnostic\/prognostic tools, such as molecular biomarkers, are needed for the rapid management of skeletal complications. This study aimed to identify potential protein biomarkers capable of predicting the early diagnosis of bone skeletal complications in GD1 patients using artificial intelligence. An in silico study was performed using the novel Therapeutic Performance Mapping System methodology to construct mathematical models of GD1-associated complications at the protein level. Pathophysiological characterization was performed before modeling, and a data science strategy was applied to the predicted protein activity for each protein in the models to identify classifiers. Statistical criteria were used to prioritize the most promising candidates, and 18 candidates were identified. Among them, PDGFB, IL1R2, PTH and CCL3 (MIP-1\u03b1) were highlighted due to their ease of measurement in blood. This study proposes a validated novel tool to discover new protein biomarkers to support clinician decision-making in an area where medical needs have not yet been met. However, confirming the results using in vitro and\/or in vivo studies is necessary.<\/jats:p>","DOI":"10.3390\/ijms25168586","type":"journal-article","created":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T15:24:16Z","timestamp":1722957856000},"page":"8586","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Machine Learning-Driven Biomarker Discovery for Skeletal Complications in Type 1 Gaucher Disease Patients"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8727-9179","authenticated-orcid":false,"given":"Jorge J.","family":"Cebolla","sequence":"first","affiliation":[{"name":"Takeda Farmac\u00e9utica Espa\u00f1a S.A., 28046 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8791-1901","authenticated-orcid":false,"given":"Pilar","family":"Giraldo","sequence":"additional","affiliation":[{"name":"FEETEG, 50006 Zaragoza, Spain"},{"name":"Hospital Quir\u00f3nSalud Zaragoza, 50012 Zaragoza, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica","family":"G\u00f3mez","sequence":"additional","affiliation":[{"name":"Anaxomics Biotech S.L., 08007 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3877-9462","authenticated-orcid":false,"given":"Carmen","family":"Montoto","sequence":"additional","affiliation":[{"name":"Takeda Farmac\u00e9utica Espa\u00f1a S.A., 28046 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5942-5669","authenticated-orcid":false,"given":"Javier","family":"Gervas-Arruga","sequence":"additional","affiliation":[{"name":"Takeda Development Center Americas Inc., Cambridge, MA 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"706","DOI":"10.1002\/jimd.12086","article-title":"Proposal for a simplified classification of IMD based on a pathophysiological approach: A practical guide for clinicians","volume":"42","author":"Saudubray","year":"2019","journal-title":"J. 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