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Neurofilament levels, disease activity and brain volume during follow-up in multiple sclerosis

Overview of attention for article published in Journal of Neuroinflammation, July 2018
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Title
Neurofilament levels, disease activity and brain volume during follow-up in multiple sclerosis
Published in
Journal of Neuroinflammation, July 2018
DOI 10.1186/s12974-018-1249-7
Pubmed ID
Authors

Irene Håkansson, Anders Tisell, Petra Cassel, Kaj Blennow, Henrik Zetterberg, Peter Lundberg, Charlotte Dahle, Magnus Vrethem, Jan Ernerudh

Abstract

There is a need for clinically useful biomarkers of disease activity in clinically isolated syndrome (CIS) and relapsing remitting MS (RRMS). The aim of this study was to assess the correlation between neurofilament light chain (NFL) in cerebrospinal fluid (CSF) and serum and the relationship between NFL and other biomarkers, subsequent disease activity, and brain volume loss in CIS and RRMS. A panel of neurodegenerative and neuroinflammatory markers were analyzed in repeated CSF samples from 41 patients with CIS or RRMS in a prospective longitudinal cohort study and from 22 healthy controls. NFL in serum was analyzed using a single-molecule array (Simoa) method. "No evidence of disease activity-3" (NEDA-3) status and brain volume (brain parenchymal fraction calculated using SyMRI®) were recorded during 4 years of follow-up. NFL levels in CSF and serum correlated significantly (all samples, n = 63, r 0.74, p < 0.001), but CSF-NFL showed an overall stronger association profile with NEDA-3 status, new T2 lesions, and brain volume loss. CSF-NFL was associated with both new T2 lesions and brain volume loss during follow-up, whereas CSF-CHI3L1 was associated mainly with brain volume loss and CXCL1, CXCL10, CXCL13, CCL22, and MMP-9 were associated mainly with new T2 lesions. Serum and CSF levels of NFL correlate, but CSF-NFL predicts and reflects disease activity better than S-NFL. CSF-NFL levels are associated with both new T2 lesions and brain volume loss. Our findings further add to the accumulating evidence that CSF-NFL is a clinically useful biomarker in CIS and RRMS and should be considered in the expanding NEDA concept. CSF-CXCL10 and CSF-CSF-CHI3L1 are potential markers of disease activity and brain volume loss, respectively.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 147 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 20%
Researcher 25 17%
Student > Postgraduate 11 7%
Student > Master 11 7%
Student > Bachelor 10 7%
Other 29 20%
Unknown 32 22%
Readers by discipline Count As %
Medicine and Dentistry 46 31%
Neuroscience 32 22%
Biochemistry, Genetics and Molecular Biology 11 7%
Agricultural and Biological Sciences 5 3%
Nursing and Health Professions 3 2%
Other 11 7%
Unknown 39 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 26 September 2018.
All research outputs
#14,884,881
of 23,096,849 outputs
Outputs from Journal of Neuroinflammation
#1,672
of 2,663 outputs
Outputs of similar age
#195,649
of 329,174 outputs
Outputs of similar age from Journal of Neuroinflammation
#33
of 61 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,663 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
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 329,174 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.