{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T21:20:51Z","timestamp":1791667251164,"version":"4.3.4"},"reference-count":22,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,28]],"date-time":"2021-12-28T00:00:00Z","timestamp":1640649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel \u201camyloid signature\u201d proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.<\/jats:p>","DOI":"10.3390\/ijms23010319","type":"journal-article","created":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T02:31:27Z","timestamp":1640745087000},"page":"319","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Classification of Amyloidosis by Model-Assisted Mass Spectrometry-Based Proteomics"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1480-6550","authenticated-orcid":false,"given":"Nicolai Bj\u00f8dstrup","family":"Palstr\u00f8m","sequence":"first","affiliation":[{"name":"Odense Amyloidosis Center, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Centre for Clinical Proteomics, Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, 5000 Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aleksandra M.","family":"Rojek","sequence":"additional","affiliation":[{"name":"Odense Amyloidosis Center, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Department of Pathology, Odense University Hospital, 5000 Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanne E. H.","family":"M\u00f8ller","sequence":"additional","affiliation":[{"name":"Odense Amyloidosis Center, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Department of Pathology, Odense University Hospital, 5000 Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1080-6609","authenticated-orcid":false,"given":"Charlotte Toftmann","family":"Hansen","sequence":"additional","affiliation":[{"name":"Odense Amyloidosis Center, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Department of Hematology, Odense University Hospital, 5000 Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6353-2616","authenticated-orcid":false,"given":"Rune","family":"Matthiesen","sequence":"additional","affiliation":[{"name":"Computational and Experimental Biology Group, CEDOC, Chronic Diseases Research Centre, NOVA Medical School, Faculdade de Ci\u00eancias M\u00e9dicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lars Melholt","family":"Rasmussen","sequence":"additional","affiliation":[{"name":"Odense Amyloidosis Center, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Centre for Clinical Proteomics, Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Department of Clinical Research, Odense University Hospital, 5000 Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niels","family":"Abildgaard","sequence":"additional","affiliation":[{"name":"Odense Amyloidosis Center, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Department of Hematology, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Department of Clinical Research, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Haematology Pathology Research Laboratory, Department of Haematology, Odense University Hospital, 5000 Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7763-3637","authenticated-orcid":false,"given":"Hans Christian","family":"Beck","sequence":"additional","affiliation":[{"name":"Odense Amyloidosis Center, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Centre for Clinical Proteomics, Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, 5000 Odense, Denmark"},{"name":"Department of Clinical Research, Odense University Hospital, 5000 Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1080\/13506129.2018.1549825","article-title":"Amyloid nomenclature 2018: Recom-mendations by the international society of amyloidosis (isa) nomenclature committee","volume":"25","author":"Benson","year":"2018","journal-title":"Amyloid"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1111\/j.1742-1241.1988.tb08540.x","article-title":"Therapeutic focus. 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