Data for: Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis
SND-ID: 2023-165.
Access to data via
Citation
Creator/Principal investigator(s)
Mika Gustafsson - Linköping university, Department of Physics, Chemistry and Biology
Jan Ernerudh
- Linköping university, Department of Biomedical and Clinical Sciences
Tomas Olsson
- Karolinska Institute, Department of Clinical Neuroscience
Research principal
Description
Data contains personal data
Yes
Sensitive personal data
Yes
Type of personal data
The data is pseudonymised and contains information if samples are from persons with MS or healthy controls, and the age and sex of these persons.
Code key exists
Yes
Language
Population
Cerebrospinal fluid (CSF) samples and plasma samples were taken from 92 persons with CIS or RRMS at Linköping University Hospital, Sweden and 51 persons with CIS or RRMS at the Karolinska University Hospital, Sweden. Everyone fulfilled the revised McDonald criteria from 2010 and 2017 for CIS or Multiple sclerosis (MS). Age-matched healthy controls (HC) were recruited from healthy blood donors (23 at the Linköping University hospital and 20 at the Karolinska University Hospital).
Time Method
Study design
Observational study
Case-control study
Data format / data structure
Other research principals
Ethics Review
Linköping - Ref. 2017/288-31
Linköping - Ref. 2016/305-32
Stockholm - Ref. 2022-03650-02
Linköping - Ref. 2013/155-32
Linköping - Ref. 2016/304-32
... Show more..Linköping - Ref. 2017/288-31
Linköping - Ref. 2016/305-32
Stockholm - Ref. 2022-03650-02
Linköping - Ref. 2013/155-32
Linköping - Ref. 2016/304-32
Linköping - Ref. 2014/311-31
Show less..Research area
Bioinformatics (computational biology) (Standard för svensk indelning av forskningsämnen 2011)
Bioinformatics and systems biology (Standard för svensk indelning av forskningsämnen 2011)
Neurology (Standard för svensk indelning av forskningsämnen 2011)
Rheumatology and autoimmunity (Standard för svensk indelning av forskningsämnen 2011)
Specific diseases, disorders and medical conditions (CESSDA Topic Classification)
Keywords