Highlights
- •Predictive models for MS may identify patients at risk for worse disease.
- •Outcome prediction modestly improved by adding biomarker data.
- •Worse clinical outcomes were associated with higher sGFAP.
- •Worse MRI outcomes were associated with higher sNfL.
- •1-year follow-up values further improved prediction of MRI outcomes, not clinical outcomes.
Abstract
Background
Early risk-stratification in multiple sclerosis (MS) may impact treatment decisions.
Current predictive models have identified that clinical and imaging characteristics
of aggressive disease are associated with worse long-term outcomes. Serum biomarkers,
neurofilament (sNfL) and glial fibrillary acidic protein (sGFAP), reflect subclinical
disease activity through separate pathological processes and may contribute to predictive
models of clinical and MRI outcomes.
Methods
We conducted a retrospective analysis of the Comprehensive Longitudinal Investigation
of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB study), where patients
with multiple sclerosis are seen every 6 months and undergo Expanded Disability Status
Scale (EDSS) assessment, have annual brain MRI scans where volumetric analysis is
conducted to calculate T2-lesion volume (T2LV) and brain parenchymal fraction (BPF),
and donate a yearly blood sample for subsequent analysis. We included patients with
newly diagnosed relapsing-remitting MS and serum samples obtained at baseline visit
and 1-year follow-up (both within 3 years of onset), and were assessed at 10-year
follow-up. We measured sNfL and sGFAP by single molecule array at baseline visit and
at 1-year follow-up. A predictive clinical model was developed using age, sex, Expanded
Disability Status Scale (EDSS), pyramidal signs, relapse rate, and spinal cord lesions
at first visit. The main outcome was odds of developing of secondary progressive (SP)MS
at year 10. Secondary outcomes included 10-year EDSS, brain T2LV and BPF. We compared
the goodness-of-fit of the predictive clinical model with and without sNfL and sGFAP
at baseline and 1-year follow-up, for each outcome by area under the receiver operating
characteristic curve (AUC) or R-squared.
Results
A total 144 patients with median MS onset at age 37.4 years (interquartile range:
29.4–45.4), 64% female, were included. SPMS developed in 25 (17.4%) patients. The
AUC for the predictive clinical model without biomarker data was 0.73, which improved
to 0.77 when both sNfL and sGFAP were included in the model (P = 0.021). In this model, higher baseline sGFAP associated with developing SPMS (OR=3.3
[95%CI:1.1,10.6], P = 0.04). Adding 1-year follow-up biomarker levels further improved the model fit
(AUC = 0.79) but this change was not statistically significant (P = 0.15). Adding baseline biomarker data also improved the R-squared of clinical models
for 10-year EDSS from 0.24 to 0.28 (P = 0.032), while additional 1-year follow-up levels did not. Baseline sGFAP was associated
with 10-year EDSS (ß=0.58 [95%CI:0.00,1.16], P = 0.05). For MRI outcomes, baseline biomarker levels improved R-squared for T2LV
from 0.12 to 0.27 (P<0.001), and BPF from 0.15 to 0.20 (P = 0.042). Adding 1-year follow-up biomarker data further improved T2LV to 0.33 (P = 0.0065) and BPF to 0.23 (P = 0.048). Baseline sNfL was associated with T2LV (ß=0.34 [95%CI:0.21,0.48], P<0.001) and 1-year follow-up sNfL with BPF (ß=-2.53% [95%CI:-4.18,-0.89], P = 0.003).
Conclusions
Early biomarker levels modestly improve predictive models containing clinical and
MRI variables. Worse clinical outcomes, SPMS and EDSS, are associated with higher
sGFAP levels and worse MRI outcomes, T2LV and BPF, are associated with higher sNfL
levels. Prospective study implementing these predictive models into clinical practice
are needed to determine if early biomarker levels meaningfully impact clinical practice.
Graphical abstract
Graphical Abstract
Keywords
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Biography
Gauruv Bose has received an endMS PostDoctoral Fellowship award from the Multiple Sclerosis Society of Canada.
Biography
Brian C. Healy has received research support from Analysis Group, Celgene (Bristol-Myers Squibb), Verily Life Sciences, Merck-Serono, Novartis and Genzyme.
Biography
Shrishti Saxena reports no disclosures.
Biography
Fermisk Saleh reports no disclosures.
Biography
Anu Paul reports no disclosures.
Biography
Christian Barro has received a PostDoctoral Fellowship award from the Swiss National Science Foundation.
Biography
Hrishikesh A. Lokhande has received research support from Verily Life Sciences, Octave Bioscience, and the Department of Defense.
Biography
Mariann Polgar-Turcsanyi reports no disclosures.
Biography
Mark Anderson reports no disclosures.
Biography
Bonnie I. Glanz has received grant support from Merck Serono and Verily Life Sciences.
Biography
Charles R.G. Guttmann has received research funding from Sanofi, the National Multiple Sclerosis Society, the International Progressive Multiple Sclerosis Alliance, the National Institutes of Health, the U.S. Office for Naval Research, the Bright Focus Foundation, as well as travel support from Roche Pharmaceuticals; C.R.G.G. owns stock in Roche, Novartis, GSK, Alnylam, Protalix Biotherapeutics, Arrowhead Pharmaceuticals, Cocrystal Pharma, Sangamo Therapeutics, Alcon.
Biography
Rohit Bakshi has received consulting fees from Bristol-Myers Squibb and EMD Serono and research support from Bristol-Myers Squibb, EMD Serono, Novartis, the US Department of Defense, the National Institutes of Health, and the National Multiple Sclerosis Society.
Biography
Howard L. Weiner has received research support from Cure Alzheimer's Fund, EMD Serono, Inc., Genentech, Inc., National Institutes of Health, National Multiple Sclerosis Society, Sanofi Genzyme, and Verily Life Sciences. He has received payment for consulting from Genentech, Inc, MedDay Pharmaceuticals, Tiziana Life Sciences and vTv Therapeutics.
Biography
Tanuja Chitnis has received compensation for consulting from Biogen, Novartis Pharmaceuticals, Roche Genentech, and Sanofi Genzyme. She has received research support from the National Institutes of Health, National MS Society, US Department of Defense, EMD Serono, I-Mab Biopharma, Mallinckrodt ARD, Novartis Pharmaceuticals, Octave Bioscience, Roche Genentech, and Tiziana Life Sciences.
Article info
Publication history
Published online: April 02, 2023
Accepted:
March 31,
2023
Received in revised form:
March 8,
2023
Received:
December 14,
2022
Identification
Copyright
© 2023 Elsevier B.V. All rights reserved.
