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Disease phenotype p...
Disease phenotype prediction in multiple sclerosis
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- Herman, Stephanie (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Klinisk kemi
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- Arvidsson McShane, Staffan (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap
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- Zhukovsky, Christina (author)
- Uppsala universitet,Experimentell neurologi
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- Emami, Payam (author)
- Uppsala universitet,Klinisk kemi,Cancerfarmakologi och beräkningsmedicin,Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm, Sweden
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- Svenningsson, Anders (author)
- Karolinska Institutet
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- Burman, Joachim, 1974- (author)
- Uppsala universitet,Experimentell neurologi
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- Spjuth, Ola, Docent, 1977- (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap
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- Kultima, Kim (author)
- Uppsala universitet,Klinisk kemi
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Zjukovskaja, C (author)
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(creator_code:org_t)
- Cell Press, 2023
- 2023
- English.
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In: iScience. - : Cell Press. - 2589-0042. ; 26:6
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Abstract
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- Progressive multiple sclerosis (PMS) is currently diagnosed retrospectively. Here, we work toward a set of biomarkers that could assist in early diagnosis of PMS. A selection of cerebrospinal fluid metabolites (n = 15) was shown to differentiate between PMS and its preceding phenotype in an independent cohort (AUC = 0.93). Complementing the classifier with conformal prediction showed that highly confident predictions could be made, and that three out of eight patients developing PMS within three years of sample collection were predicted as PMS at that time point. Finally, this methodology was applied to PMS patients as part of a clinical trial for intrathecal treatment with rituximab. The methodology showed that 68% of the patients decreased their similarity to the PMS phenotype one year after treatment. In conclusion, the inclusion of confidence predictors contributes with more information compared to traditional machine learning, and this information is relevant for disease monitoring.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Neurosciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Herman, Stephani ...
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Arvidsson McShan ...
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Zhukovsky, Chris ...
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Emami, Payam
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Svenningsson, An ...
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Burman, Joachim, ...
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Spjuth, Ola, Doc ...
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Kultima, Kim
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Zjukovskaja, C
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- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Basic Medicine
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and Neurosciences
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Bioinformatics
- Articles in the publication
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iScience
- By the university
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Uppsala University
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Karolinska Institutet