{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T16:53:49Z","timestamp":1793120029165,"version":"4.5.0"},"reference-count":67,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T00:00:00Z","timestamp":1670803200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T00:00:00Z","timestamp":1670803200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000002","name":"U.S. Department of Health & Human Services | National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Commun"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we searched for likely pathogenic mechanisms of multiple sclerosis (MS). We aggregated cerebrospinal fluid (CSF) biomarkers from 1305 proteins, measured blindly in the training dataset of untreated MS patients (N\u2009=\u2009129), into models that predict past and future speed of disability accumulation across all MS phenotypes. Healthy volunteers (N\u2009=\u200924) data differentiated natural aging and sex effects from MS-related mechanisms. Resulting models, validated (Rho 0.40-0.51, p\u2009&lt;\u20090.0001) in an independent longitudinal cohort (N\u2009=\u200998), uncovered intra-individual molecular heterogeneity. While candidate pathogenic processes must be validated in successful clinical trials, measuring them in living people will enable screening drugs for desired pharmacodynamic effects. This will facilitate drug development making, it hopefully more efficient and successful.<\/jats:p>","DOI":"10.1038\/s41467-022-35357-4","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T10:03:32Z","timestamp":1670839412000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms"],"prefix":"10.1038","volume":"13","author":[{"given":"Peter","family":"Kosa","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Barbour","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mihael","family":"Varosanec","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alison","family":"Wichman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary","family":"Sandford","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Greenwood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0959-9430","authenticated-orcid":false,"given":"Bibiana","family":"Bielekova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,12,12]]},"reference":[{"key":"35357_CR1","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1038\/s41586-018-0175-2","volume":"558","author":"BB Sun","year":"2018","unstructured":"Sun, B. B. et al. Genomic atlas of the human plasma proteome. Nature 558, 73\u201379 (2018).","journal-title":"Nature"},{"key":"35357_CR2","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1126\/science.aaq1327","volume":"361","author":"V Emilsson","year":"2018","unstructured":"Emilsson, V. et al. Co-regulatory networks of human serum proteins link genetics to disease. Science 361, 769\u2013773 (2018).","journal-title":"Science"},{"key":"35357_CR3","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1002\/ana.25083","volume":"82","author":"C Barbour","year":"2017","unstructured":"Barbour, C. et al. Molecular-based diagnosis of multiple sclerosis and its progressive stage. Ann. Neurol. 82, 795\u2013812 (2017).","journal-title":"Ann. Neurol."},{"key":"35357_CR4","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/S1474-4422(17)30469-6","volume":"17","author":"M Filippi","year":"2018","unstructured":"Filippi, M. et al. Prediction of a multiple sclerosis diagnosis in patients with clinically isolated syndrome using the 2016 MAGNIMS and 2010 McDonald criteria: a retrospective study. Lancet Neurol. 17, 133\u2013142 (2018).","journal-title":"Lancet Neurol."},{"key":"35357_CR5","unstructured":"Thompson, A.J. et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 17, 162\u2013173 (2017)."},{"key":"35357_CR6","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/ana.24408","volume":"78","author":"M Komori","year":"2015","unstructured":"Komori, M. et al. CSF markers reveal intrathecal inflammation in progressive multiple sclerosis. Ann. Neurol. 78, 3\u201320 (2015).","journal-title":"Ann. Neurol."},{"key":"35357_CR7","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1002\/ana.22230","volume":"68","author":"R Magliozzi","year":"2010","unstructured":"Magliozzi, R. et al. A Gradient of neuronal loss and meningeal inflammation in multiple sclerosis. Ann. Neurol. 68, 477\u2013493 (2010).","journal-title":"Ann. Neurol."},{"key":"35357_CR8","doi-asserted-by":"publisher","first-page":"1232","DOI":"10.3389\/fneur.2019.01232","volume":"10","author":"JL Milstein","year":"2019","unstructured":"Milstein, J. L., Barbour, C. R., Jackson, K., Kosa, P. & Bielekova, B. Intrathecal, not systemic inflammation is correlated with multiple sclerosis severity, especially in progressive multiple sclerosis. Front. Neurol. 10, 1232 (2019).","journal-title":"Front. Neurol."},{"key":"35357_CR9","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.msard.2018.11.032","volume":"28","author":"R Masvekar","year":"2018","unstructured":"Masvekar, R. et al. Cerebrospinal fluid biomarkers link toxic astrogliosis and microglial activation to multiple sclerosis severity. Mult. Scler. Relat. Disord. 28, 34\u201343 (2018).","journal-title":"Mult. Scler. Relat. Disord."},{"key":"35357_CR10","doi-asserted-by":"crossref","unstructured":"Liddelow, S.A. et al. Neurotoxic reactive astrocytes are induced by activated microglia. Nature 541, 481\u2013487 (2017).","DOI":"10.1038\/nature21029"},{"key":"35357_CR11","doi-asserted-by":"publisher","first-page":"1550","DOI":"10.1177\/1352458515623365","volume":"22","author":"J Kuhle","year":"2016","unstructured":"Kuhle, J. et al. Serum neurofilament light chain in early relapsing remitting MS is increased and correlates with CSF levels and with MRI measures of disease severity. Mult. Scler. 22, 1550\u20131559 (2016).","journal-title":"Mult. Scler."},{"key":"35357_CR12","doi-asserted-by":"publisher","first-page":"e2457","DOI":"10.1212\/WNL.0000000000009571","volume":"94","author":"A Manouchehrinia","year":"2020","unstructured":"Manouchehrinia, A. et al. Plasma neurofilament light levels are associated with risk of disability in multiple sclerosis. Neurology 94, e2457\u2013e2467 (2020).","journal-title":"Neurology"},{"key":"35357_CR13","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-67504-6","volume":"10","author":"S Thebault","year":"2020","unstructured":"Thebault, S. et al. Serum neurofilament light chain predicts long term clinical outcomes in multiple sclerosis. Sci. Rep. 10, 10381 (2020).","journal-title":"Sci. Rep."},{"key":"35357_CR14","doi-asserted-by":"crossref","unstructured":"Kosa, P. et al. Enhancing the clinical value of serum neurofilament light chain measurement. JCI Insight 7, e161415(2022).","DOI":"10.1172\/jci.insight.161415"},{"key":"35357_CR15","doi-asserted-by":"publisher","first-page":"e2120","DOI":"10.1212\/WNL.0000000000200258","volume":"98","author":"D Leppert","year":"2022","unstructured":"Leppert, D. et al. Blood neurofilament light in progressive multiple sclerosis: post hoc analysis of 2 randomized controlled trials. Neurology 98, e2120\u2013e2131 (2022).","journal-title":"Neurology"},{"key":"35357_CR16","doi-asserted-by":"publisher","unstructured":"Williams, T.E. et al. Assessing neurofilaments as biomarkers of neuroprotection in progressive multiple sclerosis: from the MS-STAT randomized controlled trial. Neurol. Neuroimmunol. Neuroinflamm. 9 https:\/\/doi.org\/10.1212\/NXI.0000000000001130 (2022).","DOI":"10.1212\/NXI.0000000000001130"},{"key":"35357_CR17","doi-asserted-by":"publisher","first-page":"1444","DOI":"10.1212\/WNL.33.11.1444","volume":"33","author":"JF Kurtzke","year":"1983","unstructured":"Kurtzke, J. F. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33, 1444\u20131452 (1983).","journal-title":"Neurology"},{"key":"35357_CR18","doi-asserted-by":"publisher","first-page":"131","DOI":"10.3389\/fneur.2016.00131","volume":"7","author":"P Kosa","year":"2016","unstructured":"Kosa, P. et al. Development of a sensitive outcome for economical drug screening for progressive multiple sclerosis treatment. Front. Neurol. 7, 131 (2016).","journal-title":"Front. Neurol."},{"key":"35357_CR19","doi-asserted-by":"publisher","first-page":"1144","DOI":"10.1212\/01.WNL.0000156155.19270.F8","volume":"64","author":"RH Roxburgh","year":"2005","unstructured":"Roxburgh, R. H. et al. Multiple sclerosis severity score: using disability and disease duration to rate disease severity. Neurology 64, 1144\u20131151 (2005).","journal-title":"Neurology"},{"key":"35357_CR20","doi-asserted-by":"crossref","unstructured":"Manouchehrinia, A. et al. Age related multiple sclerosis severity score: disability ranked by age. Mult. Scler. 23, 1938\u20131946 (2017).","DOI":"10.1177\/1352458517690618"},{"key":"35357_CR21","doi-asserted-by":"publisher","first-page":"598","DOI":"10.3389\/fneur.2017.00598","volume":"8","author":"AM Weideman","year":"2017","unstructured":"Weideman, A. M. et al. New Multiple Sclerosis Disease Severity Scale predicts future accumulation of disability. Front. Neurol. 8, 598 (2017).","journal-title":"Front. Neurol."},{"key":"35357_CR22","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1007\/s00415-016-8059-6","volume":"263","author":"MH Barnett","year":"2016","unstructured":"Barnett, M. H., McLeod, J. G., Hammond, S. R. & Kurtzke, J. F. Migration and multiple sclerosis in immigrants from United Kingdom and Ireland to Australia: a reassessment. III: risk of multiple sclerosis in UKI immigrants and Australian-born in Hobart, Tasmania. J. Neurol. 263, 792\u2013798 (2016).","journal-title":"J. Neurol."},{"key":"35357_CR23","doi-asserted-by":"publisher","first-page":"2038","DOI":"10.1093\/brain\/awab104","volume":"144","author":"CE Sabel","year":"2021","unstructured":"Sabel, C. E. et al. The latitude gradient for multiple sclerosis prevalence is established in the early life course. Brain 144, 2038\u20132046 (2021).","journal-title":"Brain"},{"key":"35357_CR24","doi-asserted-by":"publisher","first-page":"1241","DOI":"10.1002\/acn3.640","volume":"5","author":"P Kosa","year":"2018","unstructured":"Kosa, P. et al. NeurEx: digitalized neurological examination offers a novel high-resolution disability scale. Ann. Clin. Transl. Neurol. 5, 1241\u20131249 (2018).","journal-title":"Ann. Clin. Transl. Neurol."},{"key":"35357_CR25","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1016\/0921-8734(92)90030-S","volume":"275","author":"D Harman","year":"1992","unstructured":"Harman, D. Free radical theory of aging. Mutat. Res. 275, 257\u2013266 (1992).","journal-title":"Mutat. Res"},{"key":"35357_CR26","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1111\/jnc.14037","volume":"143","author":"A Grimm","year":"2017","unstructured":"Grimm, A. & Eckert, A. Brain aging and neurodegeneration: from a mitochondrial point of view. J. Neurochem. 143, 418\u2013431 (2017).","journal-title":"J. Neurochem."},{"key":"35357_CR27","doi-asserted-by":"publisher","first-page":"9175806","DOI":"10.1155\/2017\/9175806","volume":"2017","author":"A Guillaumet-Adkins","year":"2017","unstructured":"Guillaumet-Adkins, A. et al. Epigenetics and oxidative stress in aging. Oxid. Med. Cell Longev. 2017, 9175806 (2017).","journal-title":"Oxid. Med. Cell Longev."},{"key":"35357_CR28","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.arr.2007.09.002","volume":"7","author":"A Salminen","year":"2008","unstructured":"Salminen, A. et al. Activation of innate immunity system during aging: NF-kB signaling is the molecular culprit of inflamm-aging. Ageing Res. Rev. 7, 83\u2013105 (2008).","journal-title":"Ageing Res. Rev."},{"key":"35357_CR29","doi-asserted-by":"publisher","first-page":"102434","DOI":"10.1016\/j.msard.2020.102434","volume":"45","author":"P Kosa","year":"2020","unstructured":"Kosa, P. et al. Idebenone does not inhibit disability progression in primary progressive MS. Mult. Scler. Relat. Disord. 45, 102434 (2020).","journal-title":"Mult. Scler. Relat. Disord."},{"key":"35357_CR30","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1002\/ana.24506","volume":"78","author":"S Yatsuga","year":"2015","unstructured":"Yatsuga, S. et al. Growth differentiation factor 15 as a useful biomarker for mitochondrial disorders. Ann. Neurol. 78, 814\u2013823 (2015).","journal-title":"Ann. Neurol."},{"key":"35357_CR31","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.mito.2014.10.006","volume":"20","author":"Y Fujita","year":"2015","unstructured":"Fujita, Y. et al. GDF15 is a novel biomarker to evaluate efficacy of pyruvate therapy for mitochondrial diseases. Mitochondrion 20, 34\u201342 (2015).","journal-title":"Mitochondrion"},{"key":"35357_CR32","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1111\/ggi.12724","volume":"16","author":"Y Fujita","year":"2016","unstructured":"Fujita, Y., Taniguchi, Y., Shinkai, S., Tanaka, M. & Ito, M. Secreted growth differentiation factor 15 as a potential biomarker for mitochondrial dysfunctions in aging and age-related disorders. Geriatr. Gerontol. Int. 16, 17\u201329 (2016).","journal-title":"Geriatr. Gerontol. Int."},{"key":"35357_CR33","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1002\/1873-3468.13013","volume":"592","author":"G Campbell","year":"2018","unstructured":"Campbell, G. & Mahad, D. J. Mitochondrial dysfunction and axon degeneration in progressive multiple sclerosis. FEBS Lett. 592, 1113\u20131121 (2018).","journal-title":"FEBS Lett."},{"key":"35357_CR34","doi-asserted-by":"publisher","first-page":"2386","DOI":"10.1161\/ATVBAHA.119.312405","volume":"39","author":"JM Eales","year":"2019","unstructured":"Eales, J. M. et al. Human Y chromosome exerts pleiotropic effects on susceptibility to atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 39, 2386\u20132401 (2019).","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"35357_CR35","doi-asserted-by":"publisher","first-page":"450","DOI":"10.3389\/fneur.2019.00450","volume":"10","author":"EA Hogestol","year":"2019","unstructured":"Hogestol, E. A. et al. Cross-sectional and longitudinal MRI brain scans reveal accelerated brain aging in multiple sclerosis. Front. Neurol. 10, 450 (2019).","journal-title":"Front. Neurol."},{"key":"35357_CR36","doi-asserted-by":"publisher","first-page":"D607","DOI":"10.1093\/nar\/gky1131","volume":"47","author":"D Szklarczyk","year":"2019","unstructured":"Szklarczyk, D. et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607\u2013D613 (2019).","journal-title":"Nucleic Acids Res."},{"key":"35357_CR37","doi-asserted-by":"publisher","first-page":"W191","DOI":"10.1093\/nar\/gkz369","volume":"47","author":"U Raudvere","year":"2019","unstructured":"Raudvere, U. et al. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res. 47, W191\u2013W198 (2019).","journal-title":"Nucleic Acids Res"},{"key":"35357_CR38","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"Y Benjamini","year":"1995","unstructured":"Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol.) 57, 289\u2013300 (1995).","journal-title":"J. R. Stat. Soc. Ser. B (Methodol.)"},{"key":"35357_CR39","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L. Random Forests. Mach. Learn. 45, 5\u201332 (2001).","journal-title":"Mach. Learn."},{"key":"35357_CR40","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1159\/000330778","volume":"72","author":"ML Calle","year":"2011","unstructured":"Calle, M. L., Urrea, V., Boulesteix, A. L. & Malats, N. AUC-RF: a new strategy for genomic profiling with random forest. Hum. Hered. 72, 121\u2013132 (2011).","journal-title":"Hum. Hered."},{"key":"35357_CR41","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"J Friedman","year":"2001","unstructured":"Friedman, J. Greedy function approximation: the gradient boosting machine. Ann. Stat. 29, 1189\u20131232 (2001).","journal-title":"Ann. Stat."},{"key":"35357_CR42","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1155\/JBB.2005.215","volume":"2005","author":"DJ Hand","year":"2005","unstructured":"Hand, D. J. & Heard, N. A. Finding groups in gene expression data. J. Biomed. Biotechnol. 2005, 215\u2013225 (2005).","journal-title":"J. Biomed. Biotechnol."},{"key":"35357_CR43","unstructured":"Kaufman, L. & Rousseeuw, P. J. Finding Groups in Data: an Introduction to Cluster Analysis (Wiley, Hoboken, N.J., 2005)."},{"key":"35357_CR44","doi-asserted-by":"publisher","first-page":"1851","DOI":"10.1038\/s41591-019-0665-2","volume":"25","author":"SA Williams","year":"2019","unstructured":"Williams, S. A. et al. Plasma protein patterns as comprehensive indicators of health. Nat. Med. 25, 1851\u20131857 (2019).","journal-title":"Nat. Med."},{"key":"35357_CR45","doi-asserted-by":"publisher","first-page":"884089","DOI":"10.3389\/fneur.2022.884089","volume":"13","author":"J Liu","year":"2022","unstructured":"Liu, J., Kelly, E. & Bielekova, B. Current status and future opportunities in modeling clinical characteristics of multiple sclerosis. Front. Neurol. 13, 884089 (2022).","journal-title":"Front. Neurol."},{"key":"35357_CR46","doi-asserted-by":"publisher","first-page":"654942","DOI":"10.3389\/fnins.2021.654942","volume":"15","author":"S Thebault","year":"2021","unstructured":"Thebault, S., Booth, R. A., Rush, C. A., MacLean, H. & Freedman, M. S. Serum neurofilament light chain measurement in MS: hurdles to clinical translation. Front. Neurosci. 15, 654942 (2021).","journal-title":"Front. Neurosci."},{"key":"35357_CR47","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1038\/nrn3024","volume":"12","author":"JL Ables","year":"2011","unstructured":"Ables, J. L., Breunig, J. J., Eisch, A. J. & Rakic, P. Not(ch) just development: Notch signalling in the adult brain. Nat. Rev. Neurosci. 12, 269\u2013283 (2011).","journal-title":"Nat. Rev. Neurosci."},{"key":"35357_CR48","doi-asserted-by":"publisher","unstructured":"Vanderbeck, A. & Maillard, I. Notch signaling at the crossroads of innate and adaptive immunity. J. Leukoc. Biol. https:\/\/doi.org\/10.1002\/JLB.1RI0520-138R (2020).","DOI":"10.1002\/JLB.1RI0520-138R"},{"key":"35357_CR49","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1038\/nrn.2018.13","volume":"19","author":"MA Petersen","year":"2018","unstructured":"Petersen, M. A., Ryu, J. K. & Akassoglou, K. Fibrinogen in neurological diseases: mechanisms, imaging and therapeutics. Nat. Rev. Neurosci. 19, 283\u2013301 (2018).","journal-title":"Nat. Rev. Neurosci."},{"key":"35357_CR50","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1111\/ene.12696","volume":"22","author":"R Bergamaschi","year":"2015","unstructured":"Bergamaschi, R. et al. BREMSO: a simple score to predict early the natural course of multiple sclerosis. Eur. J. Neurol. 22, 981\u2013989 (2015).","journal-title":"Eur. J. Neurol."},{"key":"35357_CR51","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.msard.2014.11.002","volume":"4","author":"E Bernitsas","year":"2015","unstructured":"Bernitsas, E. et al. Spinal cord atrophy in multiple sclerosis and relationship with disability across clinical phenotypes. Mult. Scler. Relat. Disord. 4, 47\u201351 (2015).","journal-title":"Mult. Scler. Relat. Disord."},{"key":"35357_CR52","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1016\/j.msard.2015.08.009","volume":"4","author":"P Kosa","year":"2015","unstructured":"Kosa, P. et al. Novel composite MRI scale correlates highly with disability in multiple sclerosis patients. Mult. Scler. Relat. Disord. 4, 526\u2013535 (2015).","journal-title":"Mult. Scler. Relat. Disord."},{"key":"35357_CR53","doi-asserted-by":"crossref","unstructured":"Fitzgerald, K.C. et al. Early complement genes are associated with visual system degeneration in multiple sclerosis. Brain 142, 2722\u20132736 (2019).","DOI":"10.1093\/brain\/awz188"},{"key":"35357_CR54","doi-asserted-by":"crossref","unstructured":"Jackson, K.C. et al. Genetic model of MS severity predicts future accumulation of disability. Ann. Hum. Genet. 84, 1\u201310 (2019).","DOI":"10.1111\/ahg.12342"},{"key":"35357_CR55","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.msard.2018.11.032","volume":"28","author":"R Masvekar","year":"2019","unstructured":"Masvekar, R. et al. Cerebrospinal fluid biomarkers link toxic astrogliosis and microglial activation to multiple sclerosis severity. Mult. Scler. Relat. Disord. 28, 34\u201343 (2019).","journal-title":"Mult. Scler. Relat. Disord."},{"key":"35357_CR56","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1002\/1531-8249(200006)47:6<707::AID-ANA3>3.0.CO;2-Q","volume":"47","author":"C Lucchinetti","year":"2000","unstructured":"Lucchinetti, C. et al. Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination. Ann. Neurol. 47, 707\u2013717 (2000).","journal-title":"Ann. Neurol."},{"key":"35357_CR57","unstructured":"Bridel, C. et al. Diagnostic value of cerebrospinal fluid neurofilament light protein in neurology: a systematic review and meta-analysis. JAMA Neurol. 76, 1035\u20131048 (2019)."},{"key":"35357_CR58","doi-asserted-by":"publisher","first-page":"1368","DOI":"10.1212\/WNL.34.10.1368","volume":"34","author":"JC Sipe","year":"1984","unstructured":"Sipe, J. C. et al. A neurologic rating scale (NRS) for use in multiple sclerosis. Neurology 34, 1368\u20131372 (1984).","journal-title":"Neurology"},{"key":"35357_CR59","doi-asserted-by":"publisher","first-page":"577","DOI":"10.3389\/fneur.2017.00577","volume":"8","author":"AM Weideman","year":"2017","unstructured":"Weideman, A. M., Tapia-Maltos, M. A., Johnson, K., Greenwood, M. & Bielekova, B. Meta-analysis of the age-dependent efficacy of multiple sclerosis treatments. Front. Neurol. 8, 577 (2017).","journal-title":"Front. Neurol."},{"key":"35357_CR60","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.nbt.2011.11.016","volume":"29","author":"L Gold","year":"2012","unstructured":"Gold, L., Walker, J. J., Wilcox, S. K. & Williams, S. Advances in human proteomics at high scale with the SOMAscan proteomics platform. N. Biotechnol. 29, 543\u2013549 (2012).","journal-title":"N. Biotechnol."},{"key":"35357_CR61","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1016\/j.nicl.2013.03.002","volume":"2","author":"EM Sweeney","year":"2013","unstructured":"Sweeney, E. M. et al. OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI. Neuroimage Clin. 2, 402\u2013413 (2013).","journal-title":"Neuroimage Clin."},{"key":"35357_CR62","doi-asserted-by":"publisher","first-page":"e387","DOI":"10.1212\/NXI.0000000000000387","volume":"4","author":"AJ Solomon","year":"2017","unstructured":"Solomon, A. J., Watts, R., Dewey, B. E. & Reich, D. S. MRI evaluation of thalamic volume differentiates MS from common mimics. Neurol. Neuroimmunol. Neuroinflamm. 4, e387 (2017).","journal-title":"Neurol. Neuroimmunol. Neuroinflamm"},{"key":"35357_CR63","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1093\/gerona\/glu121","volume":"70","author":"C Menni","year":"2015","unstructured":"Menni, C. et al. Circulating proteomic signatures of chronological age. J. Gerontol. A Biol. Sci. Med. Sci. 70, 809\u2013816 (2015).","journal-title":"J. Gerontol. A Biol. Sci. Med. Sci."},{"key":"35357_CR64","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1161\/CIRCULATIONAHA.116.021803","volume":"134","author":"D Ngo","year":"2016","unstructured":"Ngo, D. et al. Aptamer-based proteomic profiling reveals novel candidate biomarkers and pathways in cardiovascular disease. Circulation 134, 270\u2013285 (2016).","journal-title":"Circulation"},{"key":"35357_CR65","unstructured":"R Core Team. R: A Language and Environment for Statistical Computing (ed. R.F.f.S. Computing) (R Core Team, Vienna, Austria; 2019)."},{"key":"35357_CR66","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v077.i01","volume":"77","author":"M Wright","year":"2017","unstructured":"Wright, M. & Ziegler, A. ranger: a fast implementation of random forests for high dimensional data in C++ and R. J. Stat. Softw. 77, 1\u201317 (2017).","journal-title":"J. Stat. Softw."},{"key":"35357_CR67","doi-asserted-by":"publisher","first-page":"2847","DOI":"10.1093\/bioinformatics\/btw313","volume":"32","author":"Z Gu","year":"2016","unstructured":"Gu, Z., Eils, R. & Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32, 2847\u20132849 (2016).","journal-title":"Bioinformatics"}],"container-title":["Nature Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41467-022-35357-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41467-022-35357-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41467-022-35357-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T06:25:54Z","timestamp":1728541554000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41467-022-35357-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,12]]},"references-count":67,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["35357"],"URL":"https:\/\/doi.org\/10.1038\/s41467-022-35357-4","relation":{},"ISSN":["2041-1723"],"issn-type":[{"value":"2041-1723","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,12]]},"assertion":[{"value":"8 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 November 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 December 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"7670"}}