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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring
|
|---|---|
| Published in |
Frontiers in Human Neuroscience, June 2018
|
| DOI | 10.3389/fnhum.2018.00226 |
| Pubmed ID | |
| Authors |
Daniel Stoessel, Jan-Patrick Stellmann, Anne Willing, Birte Behrens, Sina C. Rosenkranz, Sibylle C. Hodecker, Klarissa H. Stürner, Stefanie Reinhardt, Sabine Fleischer, Christian Deuschle, Walter Maetzler, Daniela Berg, Christoph Heesen, Dirk Walther, Nicolas Schauer, Manuel A. Friese, Ole Pless |
| Abstract |
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson's disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 13% |
| Switzerland | 1 | 13% |
| Germany | 1 | 13% |
| Unknown | 5 | 63% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
| Scientists | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 103 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 17% |
| Student > Ph. D. Student | 17 | 17% |
| Student > Master | 12 | 12% |
| Other | 10 | 10% |
| Student > Doctoral Student | 8 | 8% |
| Other | 14 | 14% |
| Unknown | 24 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 18 | 17% |
| Agricultural and Biological Sciences | 13 | 13% |
| Biochemistry, Genetics and Molecular Biology | 12 | 12% |
| Medicine and Dentistry | 10 | 10% |
| Chemistry | 7 | 7% |
| Other | 16 | 16% |
| Unknown | 27 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 December 2023.
All research outputs
#5,544,155
of 26,106,015 outputs
Outputs from Frontiers in Human Neuroscience
#2,275
of 7,794 outputs
Outputs of similar age
#96,228
of 345,644 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#51
of 142 outputs
Altmetric has tracked 26,106,015 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,794 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 345,644 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.