{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T04:17:33Z","timestamp":1774844253988,"version":"3.50.1"},"reference-count":34,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T00:00:00Z","timestamp":1657756800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100005646","name":"Actelion Pharmaceuticals","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005646","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000317","name":"Action Medical Research","doi-asserted-by":"publisher","award":["GN2465"],"award-info":[{"award-number":["GN2465"]}],"id":[{"id":"10.13039\/501100000317","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014461","name":"NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust\/Institute of Cancer Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014461","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Develop Med Child Neuro"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Aim<\/jats:title><jats:p>Using Niemann\u2013Pick type C disease (NPC) as a paradigm, we aimed to improve biomarker discovery in patients with neurometabolic disorders.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>Using a multiplexed liquid chromatography tandem mass spectrometry dried bloodspot assay, we developed a selective intelligent biomarker panel to monitor known biomarkers <jats:italic>N<\/jats:italic>\u2010palmitoyl\u2010<jats:italic>O<\/jats:italic>\u2010phosphocholineserine and 3\u03b2,5\u03b1,6\u03b2\u2010trihydroxy\u2010cholanoyl\u2010glycine as well as compounds predicted to be affected in NPC pathology. We applied this panel to a clinically relevant paediatric patient cohort (<jats:italic>n<\/jats:italic>\u00a0=\u00a075; 35 males, 40 females; mean age 7\u2009years 6\u2009months, range 4\u2009days\u201319\u2009years 8\u2009months) presenting with neurodevelopmental and\/or neurodegenerative pathology, similar to that observed in NPC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The panel had a far superior performance compared with individual biomarkers. Namely, NPC\u2010related established biomarkers used individually had 91% to 97% specificity but the combined panel had 100% specificity. Moreover, multivariate analysis revealed long\u2010chain isoforms of glucosylceramide were elevated and very specific for patients with NPC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Interpretation<\/jats:title><jats:p>Despite advancements in next\u2010generation sequencing and precision medicine, neurological non\u2010enzymatic disorders remain difficult to diagnose and lack robust biomarkers or routine functional testing for genetic variants of unknown significance. Biomarker panels may have better diagnostic accuracy than individual biomarkers in neurometabolic disorders, hence they can facilitate more prompt disease identification and implementation of emerging targeted, disease\u2010specific therapies.<\/jats:p><\/jats:sec><jats:sec><jats:title>What this paper adds<\/jats:title><jats:p>\n<jats:list list-type=\"bullet\">\n<jats:list-item><jats:p>Intelligent biomarker panel design can help expedite diagnosis in neurometabolic disorders.<\/jats:p><\/jats:list-item>\n<jats:list-item><jats:p>In Niemann\u2013Pick type C disease, such a panel performed better than individual biomarkers.<\/jats:p><\/jats:list-item>\n<jats:list-item><jats:p>Biomarker panels are easy to implement and widely applicable to neurometabolic conditions.<\/jats:p><\/jats:list-item>\n<\/jats:list><\/jats:p><\/jats:sec>","DOI":"10.1111\/dmcn.15334","type":"journal-article","created":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T08:45:45Z","timestamp":1657788345000},"page":"1539-1546","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Niemann\u2013Pick type C disease as proof\u2010of\u2010concept for intelligent biomarker panel selection in neurometabolic disorders"],"prefix":"10.1111","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5093-6075","authenticated-orcid":false,"given":"Apostolos","family":"Papandreou","sequence":"first","affiliation":[{"name":"Inborn Errors of Metabolism Section, Genetics &amp; Genomic Medicine Programme, Great Ormond Street Institute of Child Health University College London  London UK"},{"name":"Molecular Neurosciences, Developmental Neurosciences Programme, Great Ormond Street Institute of Child Health University College London  London UK"},{"name":"Department of Neurology, Great Ormond Street Hospital for Children  London UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4580-6396","authenticated-orcid":false,"given":"Ivan","family":"Doykov","sequence":"additional","affiliation":[{"name":"Inborn Errors of Metabolism Section, Genetics &amp; Genomic Medicine Programme, Great Ormond Street Institute of Child Health University College London  London UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Justyna","family":"Spiewak","sequence":"additional","affiliation":[{"name":"Inborn Errors of Metabolism Section, Genetics &amp; Genomic Medicine Programme, Great Ormond Street Institute of Child Health University College London  London UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikita","family":"Komarov","sequence":"additional","affiliation":[{"name":"Inborn Errors of Metabolism Section, Genetics &amp; 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