Abstract

Background: Multiple sclerosis is characterized by both neuroinflammation and accelerated brain atrophy. These two processes can be quantified by MRI, are at least partially independent, and have different underlying pathological mechanisms. MicroRNA (miRNA) have previously shown strong ties to various neurological disease processes, and have potential as biomarkers in MS.

Objectives: To classify and immunologically characterize persons with MS based on serum miRNA profiles in conjunction with MRI phenotypes, as defined by relative burden of cerebral T2-hyperintense lesion volume (T2LV) and brain parenchymal fraction (BPF).

Methods: Cerebral T2LV and BPF were retrospectively quantified from 1.5T MRI, and used to define the following MRI phenotypes. Type I: low T2LV, low atrophy; type II: high T2LV, low atrophy; type III: low T2LV, high atrophy; type IV: high T2LV, high atrophy, in a large cross-sectional cohort (n = 1,088) and a subset with 5-year longitudinal follow-up (n = 153). Serum miRNAs were assessed on a third MS cohort with 2-year MRI phenotype stability (n = 98). A proportional odds logistic regression model was used to determine significant associations been MRI features and miRNA expression.

Results: One-third of the patients showed dissociation between lesion burden and atrophy severity as defined by MRI phenotypes II or III. At 5-year follow-up, all phenotypes showed increased atrophy (p < 0.001), disproportionally in type II (BPF −2.28%). Only type IV experienced significantly worse neurological disability scores. Types I and II had a 5-year MRI phenotype conversion rate of 33% and 46%, whereas III and IV had >90% stability. Type II switched primarily to IV (91%); type I switched primarily to II (47%) or III (37%). Baseline higher age (p = 0.006) and lower BPF (p < 0.001) predicted 5-year phenotype conversion. MicroRNA analysis revealed sixteen miRNA differentially expressed (p < 0.05, uncorrected) between the four phenotypes. Each phenotype demonstrated a distinct miRNA signature. Biological interpretation of these miRNA suggest a role for blood-brain barrier pathology. miR-22-3p, miR-361-5p, and miR-345-5p were the most valid differentiators.

Conclusions: MRI-defined MS phenotypes show high conversion rates characterized by relentless brain atrophy with or without ongoing inflammation, and results support the partial independence of these two features. Differentially expressed serum microRNA for the MRI phenotypes implicates the blood-brain barrier as an important mechanism determining pathological course. MicroRNA are promising as biomarkers in MS but require significant further verification and methodological standardization.

Abstract

Background: Multiple sclerosis is characterized by both neuroinflammation and accelerated brain atrophy. These two processes can be quantified by MRI, are at least partially independent, and have different underlying pathological mechanisms. MicroRNA (miRNA) have previously shown strong ties to various neurological disease processes, and have potential as biomarkers in MS.

Objectives: To classify and immunologically characterize persons with MS based on serum miRNA profiles in conjunction with MRI phenotypes, as defined by relative burden of cerebral T2-hyperintense lesion volume (T2LV) and brain parenchymal fraction (BPF).

Methods: Cerebral T2LV and BPF were retrospectively quantified from 1.5T MRI, and used to define the following MRI phenotypes. Type I: low T2LV, low atrophy; type II: high T2LV, low atrophy; type III: low T2LV, high atrophy; type IV: high T2LV, high atrophy, in a large cross-sectional cohort (n = 1,088) and a subset with 5-year longitudinal follow-up (n = 153). Serum miRNAs were assessed on a third MS cohort with 2-year MRI phenotype stability (n = 98). A proportional odds logistic regression model was used to determine significant associations been MRI features and miRNA expression.

Results: One-third of the patients showed dissociation between lesion burden and atrophy severity as defined by MRI phenotypes II or III. At 5-year follow-up, all phenotypes showed increased atrophy (p < 0.001), disproportionally in type II (BPF −2.28%). Only type IV experienced significantly worse neurological disability scores. Types I and II had a 5-year MRI phenotype conversion rate of 33% and 46%, whereas III and IV had >90% stability. Type II switched primarily to IV (91%); type I switched primarily to II (47%) or III (37%). Baseline higher age (p = 0.006) and lower BPF (p < 0.001) predicted 5-year phenotype conversion. MicroRNA analysis revealed sixteen miRNA differentially expressed (p < 0.05, uncorrected) between the four phenotypes. Each phenotype demonstrated a distinct miRNA signature. Biological interpretation of these miRNA suggest a role for blood-brain barrier pathology. miR-22-3p, miR-361-5p, and miR-345-5p were the most valid differentiators.

Conclusions: MRI-defined MS phenotypes show high conversion rates characterized by relentless brain atrophy with or without ongoing inflammation, and results support the partial independence of these two features. Differentially expressed serum microRNA for the MRI phenotypes implicates the blood-brain barrier as an important mechanism determining pathological course. MicroRNA are promising as biomarkers in MS but require significant further verification and methodological standardization.

Abstract

Background: Multiple sclerosis is characterized by both neuroinflammation and accelerated brain atrophy. These two processes can be quantified by MRI, are at least partially independent, and have different underlying pathological mechanisms. MicroRNA (miRNA) have previously shown strong ties to various neurological disease processes, and have potential as biomarkers in MS.

Objectives: To classify and immunologically characterize persons with MS based on serum miRNA profiles in conjunction with MRI phenotypes, as defined by relative burden of cerebral T2-hyperintense lesion volume (T2LV) and brain parenchymal fraction (BPF).

Methods: Cerebral T2LV and BPF were retrospectively quantified from 1.5T MRI, and used to define the following MRI phenotypes. Type I: low T2LV, low atrophy; type II: high T2LV, low atrophy; type III: low T2LV, high atrophy; type IV: high T2LV, high atrophy, in a large cross-sectional cohort (n = 1,088) and a subset with 5-year longitudinal follow-up (n = 153). Serum miRNAs were assessed on a third MS cohort with 2-year MRI phenotype stability (n = 98). A proportional odds logistic regression model was used to determine significant associations been MRI features and miRNA expression.

Results: One-third of the patients showed dissociation between lesion burden and atrophy severity as defined by MRI phenotypes II or III. At 5-year follow-up, all phenotypes showed increased atrophy (p < 0.001), disproportionally in type II (BPF −2.28%). Only type IV experienced significantly worse neurological disability scores. Types I and II had a 5-year MRI phenotype conversion rate of 33% and 46%, whereas III and IV had >90% stability. Type II switched primarily to IV (91%); type I switched primarily to II (47%) or III (37%). Baseline higher age (p = 0.006) and lower BPF (p < 0.001) predicted 5-year phenotype conversion. MicroRNA analysis revealed sixteen miRNA differentially expressed (p < 0.05, uncorrected) between the four phenotypes. Each phenotype demonstrated a distinct miRNA signature. Biological interpretation of these miRNA suggest a role for blood-brain barrier pathology. miR-22-3p, miR-361-5p, and miR-345-5p were the most valid differentiators.

Conclusions: MRI-defined MS phenotypes show high conversion rates characterized by relentless brain atrophy with or without ongoing inflammation, and results support the partial independence of these two features. Differentially expressed serum microRNA for the MRI phenotypes implicates the blood-brain barrier as an important mechanism determining pathological course. MicroRNA are promising as biomarkers in MS but require significant further verification and methodological standardization.

Background

Psychiatric comorbidities are common in multiple sclerosis (MS) and are associated with diminished quality of life and non-adherence to disease-modifying therapy (DMT). Depression is linked to immune activation in inflammatory disorders. We hypothesized that persons with self-reported MS not receiving DMT and those on lower efficacy DMT (low [LED] and moderate [MED]) had more symptoms of anxiety, depression, and fatigue, as compared to those on DMT and on high efficacy DMT (HED).

Objectives

Our team sought to determine if symptoms of depression, anxiety, and fatigue in MS correlate with the use and efficacy of DMT.

Methods

We developed a web-based survey including the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder 7-item (GAD-7) scale, and the Modified Fatigue Impact Scale 5-item version (MFIS-5). Invitations to complete the survey were distributed electronically by MS organizations. DMTs were classified in LED (interferon beta-1a, interferon beta-1b, peginterferon beta-1a, glatiramer acetate), MED (teriflunomide, fingolimod, siponimod, dimethyl fumarate), and HED (alemtuzumab, ocrelizumab, rituximab, natalizumab, cladribine). Analyses were conducted using linear models adjusted for age, sex, ethnicity, disease duration, employment status, and whether the individual has an MS provider.

Results

2121 persons completed the survey (age 51.1±12.4 years, 18% male, and 52% have had MS for >10 years). 1650 were on DMT (465 LED, 546 MED, 624 HED, 15 other). MFIS-5 and GAD-7 scores were lower for those on DMT as compared to those not on DMT (for MFIS-5: 0.79 points lower, 95% CI -1.37, -0.21; p=0.007; for GAD-7: 0.68 points lower; 95% CI -1.29, -0.07, p=0.03). Those on LED had -1.18 (95% CI -1.97, -0.38; p=0.004) lower PHQ-9 scores compared to those on no DMT. Among individuals on a DMT, those on HED had higher MFIS-5 and PHQ-9 scores relative to those on LED (for MFIS-5: 1.78 points higher, 95% CI 1.13, 2.24, p<0.001; for PHQ-9: 1.00 points higher; 95% CI 0.25, 1.74, p=0.009).

Conclusions

In this cross-sectional study, untreated patients had more fatigue and anxiety than those on DMT and greater depression than those on LED. LED-treated patients had lower fatigue and depression scores compared to those on HED. Indication biases may have influenced our results; longitudinal studies taking into account prior DMT history and indicators for specific DMTs should evaluate whether certain DMT classes affect future depression, anxiety, or fatigue levels.