Multiple Sclerosis Subtypes Research Articles

Improvement in depressive symptoms is associated with sustained improvement in fatigue impact in adults with multiple sclerosis

BackgroundFatigue is one of the most common and disabling symptoms of multiple sclerosis (MS). Behavioral interventions that target one or more behaviors such as sleep hygiene, exercise, energy management, cognitive processes, as well as mood have been shown to reduce fatigue in people with MS. Yet, little is known about mechanisms of intervention effects on MS fatigue. Research suggests that depressive symptoms may be an important intervention target for improving MS fatigue. This study examined the association between pre- to post-intervention improvement in depressive symptoms and improvement in MS fatigue impact from pre-intervention through six months post-intervention. MethodsThis study is a secondary analysis of data from a randomized controlled trial comparing a fatigue self-management intervention to general MS education for improving fatigue in people with MS. Adults with MS (N = 218) were recruited for the parent trial from the Portland, Seattle, Baltimore, and North Florida/South Georgia VA Medical Centers, affiliated academic medical centers, and surrounding communities. Both study interventions showed similar efficacy, so participants were combined into one sample for this secondary analysis. Structural equation modeling was used to examine whether clinically significant change in depressive symptoms (a 17.5 % reduction in the total Beck Depression Inventory-II score) from pre- to post-intervention, was associated with improvement in fatigue impact on the physical, cognitive, and psychosocial subscales of the Modified Fatigue Impact Scale from pre-intervention through six-month follow-up. ResultsParticipants were predominantly female (72 %), middle-aged (M = 53.7 ± 10.1), and White (76 %) with a disease duration of 12.5 ± 8.4 years. Over half of the sample (58 %) had relapsing-remitting MS. Clinically significant improvement in depressive symptoms was associated with reduction in physical fatigue impact (β = -0.17, p = .004, 95 % CI [-0.28, -0.05]), cognitive fatigue impact (β = -0.20, p = .000, 95 % CI [-0.31, -0.10]), and psychosocial fatigue impact (β = -0.13, p = .03, 95 % CI [-0.25, -0.01]) through the six-month follow-up controlling for baseline depressive symptoms and fatigue impact, MS subtype (RRMS or Progressive MS), and income level. The model demonstrated adequate fit, χ2(6) = 12.747, p = .047, RMSEA = 0.072, CFI = 0.986, SRMR = 0.016, and accounted for 32 %, 39 %, and 28 % of the variance in physical, cognitive, and psychosocial fatigue impact respectively, which corresponded with large effect sizes. ConclusionThese findings, building on previous research, support the importance of reducing depressive symptoms for improving fatigue impact in people with MS. Future research should examine whether explicit focus on reducing depressive symptoms or related cognitive behavioral factors reduces fatigue in people with MS.

Multiple sclerosis subgroups: Data-driven clusters based on patient-reported outcomes and a large clinical sample

Background: While standard clinical assessments provide great value for people with multiple sclerosis (PwMS), they are limited in their ability to characterize patient perspectives and individual-level symptom heterogeneity. Objectives: To identify PwMS subgroups based on patient-reported outcomes (PROs) of physical, cognitive, and emotional symptoms. We also sought to connect PRO-based subgroups with demographic variables, functional impairment, hypertension and smoking status, traditional qualitative multiple sclerosis (MS) symptom groupings, and neuroperformance measurements. Methods: Using a cross-sectional design, we applied latent profile analysis (LPA) to a large database of PROs; analytic sample N = 6619). Results: We identified nine distinct MS subtypes based on PRO patterns. The subtypes were primarily categorized into low, moderate, and high mobility impairment clusters. Approximately 70% of participants were classified in a low mobility impairment group, 10% in a moderate mobility impairment group, and 20% in a high mobility impairment group. Within these subgroups, several unexpected patterns were observed, such as high mobility impairment clusters reporting low non-mobility impairment. Conclusions: The present study highlights an opportunity to advance precision medicine approaches in MS. Combining PROs with data-driven methodology allows for a cost-effective and personalized characterization of symptom presentations. that can inform clinical practice and future research designs.

Characterizing Fatigue by Multiple Sclerosis Subtype and Determining Validity of a Fatigue Scale Specific to Persons With Progressive Multiple Sclerosis.

Fatigue is a common and debilitating symptom of multiple sclerosis (MS). Prior work suggests that the prevalence of fatigue is higher in progressive MS (PMS) than relapsing MS (RRMS). No patient-reported outcomes of fatigue have been validated specifically for individuals with PMS, despite evidence that they characterize fatigue differently than individuals with RRMS. Therefore, the objective of this study was to characterize fatigue in both the RRMS and PMS subtypes and determine the convergent validity of the Fatigue Symptoms and Impacts Questionnaire (FSIQ) for individuals with PMS. A nationwide survey yielded 806 (637 RRMS, 169 PMS) complete responses. The survey collected demographic information and self-reported disease severity, as well as measures of fatigue, health-related quality of life, and self-reported functioning. People with PMS reported significantly more severe fatigue than those with RRMS (P < .001). The FSIQ subdomains of physical, cognitive/emotional, and coping demonstrated moderate (r = 0.5-0.75) to excellent (r > 0.75) validity (P < .001) with other measures of fatigue. More severe fatigue in people with PMS as compared to those with RRMS underscores the importance of using validated tools to capture fatigue in persons with PMS. The FSIQ is a valid and freely available tool to capture the physical, mental, and emotional fatigue of individuals with PMS.

Investigation of comparative Nonword repetition performance in multiple sclerosis: Group differences, subtype variations, and disability effects

This study investigated Nonword Repetition (NWR) tasks in individuals with Multiple Sclerosis (MS) compared to healthy controls (HC), focusing on phonological working memory (WMP). Significant differences were found in NWR acurracy (NWRacc) score between MS subgroups and HC (H = 48.2, p < 0.001). NWRacc decreased as the number of syllables increased in both groups, indicating increased cognitive load. All MS subtypes showed lower NWRacc compared to HC across varying syllable lengths (Mann Whitney U Test: two syllables U = 64.5, p < 0.001; three syllables U = 183, p < 0.001; four syllables U = 248, p < 0.001; five syllables U = 283.5, p < 0.001). However, no significant differences were found within MS subtypes based on syllable length. NWRacc did not differ between mild and severe MS groups. Overall, the NWR test effectively assessed WMP in MS, highlighting its utility in diagnosing and addressing language-cognitive challenges in individuals with MS. This underscores the importance of tailored intervention strategies to mitigate these challenges.

Brain hemodynamic responses and fall prediction in older adults with multiple sclerosis.

We examined whether brain hemodynamic responses, gait, and cognitive performances under single- and dual-task conditions predict falls during longitudinal follow-up in older adults with multiple sclerosis (OAMS) with relapsing-remitting and progressive subtypes. Participants with relapsing-remitting (n = 53, mean age = 65.02 ± 4.17 years, %female = 75.5) and progressive (n = 28, mean age = 64.64 ± 4.31 years, %female = 50) multiple sclerosis (MS) subtypes completed a dual-task-walking paradigm and reported falls during longitudinal follow-up using a monthly structured telephone interview. We used functional near-infrared spectroscopy (fNIRS) to assess oxygenated hemoglobin (HbO) in the prefrontal cortex during active walking and while performing a cognitive test under single- and dual-task conditions. Adjusted general estimating equations models indicated that higher HbO under dual-task walking was significantly associated with a reduction in the odds of reporting falls among participants with relapsing-remitting (odds ratio (OR) = 0.472, p = 0.004, 95% confidence interval (CI) = 0.284-0.785), but not progressive (OR = 1.056, p = 0.792, 95% CI = 0.703-1.588) MS. In contrast, faster stride velocity under dual-task walking was significantly associated with a reduction in the odds of reporting falls among progressive (OR = 0.658, p = 0.004, 95% CI = 0.495-0.874), but not relapsing-remitting (OR = 0.998, p = 0.995, 95% CI = 0.523-1.905) MS. Findings suggest that higher prefrontal cortex activation levels during dual-task walking, which may represent compensatory reallocation of brain resources, provide protection against falls for OAMS with relapsing-remitting subtype.

Understanding progression in multiple sclerosis: analysis of an in-patient admissions audit

Analysis of in-patient data is valuable to reduce avoidable admissions, which are disruptive to patients and costly to the NHS. The audit aimed to identify causes of in-patient admissions of people with multiple sclerosis at a district general hospital. The audit comprised a retrospective evaluation of secondary in-patient admissions data. Primary causes of admissions included chest infections, falls and urinary tract infections. Secondary progressive multiple sclerosis accounted for the largest number of admissions by multiple sclerosis sub-type, disproportionate to representation on the multiple sclerosis nurse caseload. In contrast, primary progressive multiple sclerosis was represented proportionally. Given the crossover between the two sub-types, this paper explores potential reasons for disproportionate representation by sub-type. Several factors may contribute to the admissions data by sub-type, including patient understandings of progression and information provided by clinicians. These findings have implications for the information and support provided by multiple sclerosis services.

Association of chronotype and timing of interferon injection with severity of IFNβ-induced flu-like syndrome in Multiple sclerosis (MS) patients

BackgroundAlthough Interferon-beta (IFNβ) has long been approved as a disease-modifying therapy (DMT) for Multiple sclerosis (MS), flu-like syndrome (FLS) persists as a common adverse effect of interferon therapy. Given the importance of circadian rhythm in regulating physiological processes, we aimed to assess the relationship between patient’s chronotype and time of interferon injection with FLS score in MS patients receiving IFNβ. MethodsA cross-sectional study was conducted on 118 MS patients who were referred to the clinic of neurology of Zanjan Vali-e-Asr Hospital for interferon injection. The included were invited to complete a morningness-eveningness questionnaire (MEQ) assessing patients’ chronotype. The following data were extracted from patients’ record: age, gender, duration of interferon treatment, type of interferon taken, time of interferon injection (morning/evening), FLS score, MS subtype, and usage of pain killers. All data found were imported and statistically analyzed in SPSS ver.26. ResultsAccording to the patients’ record, 114 (96.6%) patients had experienced post-interferon injection FLS with different severities. Statistical analysis revealed no significant relationship between the patient’s chronotype and FLS score. Nevertheless, the FLS score was significantly higher in those who had evening injections. ConclusionsTime of interferon injection was significantly associated with FLS score, with higher FLS score following evening injection. However, no significant relationship was found between the FLS score and the patient’s chronotype. It is recommended that further studies assessing circadian rhythm using laboratory tests such as melatonin measurement need to be undertaken to investigate the association of circadian rhythm with post-interferon injection FLS.

Multi-omics profiling reveals peripheral blood biomarkers of multiple sclerosis: implications for diagnosis and stratification.

Multiple sclerosis (MS), a chronic autoimmune disorder marked by demyelination in the central nervous system, is exceptionally uncommon in China, and remains poorly understood in terms of its peripheral blood manifestations. We conducted a cohort study comprising 39 MS patients and 40 normal controls (NC). High-dimensional mass cytometry, protein arrays, and targeted metabolomics were utilized to profile immune subsets, proteins, and metabolites in blood. Differences in multi-omics signatures were scrutinized across varying MS subtypes. Immune profiling demonstrated an elevation in various B cell subsets and monocytes, alongside a reduction in dendritic cells among MS patients. Proteomic data revealed a downregulation in neurotrophic and tissue repair proteins. Metabolomic assessment showed a noted decrease in anti-inflammatory molecules and sphingolipids. Integrated analysis identified distinct molecular patterns distinguishing MS from controls. Additionally, multi-omics differences among different MS subtypes were uncovered. Notably, hippuric acid levels was consistently lower in MS subgroups with greater disease severity. This study represents the pioneering exploration of multi-omics in Chinese MS patients, presenting a comprehensive view of the peripheral blood changes in MS. Our study underscores the robust capability of multi-omics assessments in identifying peripheral blood biomarkers that delineate the varied clinical presentation, and facilitates future development of biomarkers and targeted therapeutic interventions in MS.

Differential Expression of PACAP/VIP Receptors in the Post-Mortem CNS White Matter of Multiple Sclerosis Donors.

Pituitary adenylate cyclase-activating polypeptide (PACAP) and vasoactive intestinal peptide (VIP) are two neuroprotective and anti-inflammatory molecules of the central nervous system (CNS). Both bind to three G protein-coupled receptors, namely PAC1, VPAC1 and VPAC2, to elicit their beneficial effects in various CNS diseases, including multiple sclerosis (MS). In this study, we assessed the expression and distribution of PACAP/VIP receptors in the normal-appearing white matter (NAWM) of MS donors with a clinical history of either relapsing-remitting MS (RRMS), primary MS (PPMS), secondary progressive MS (SPMS) or in aged-matched non-MS controls. Gene expression studies revealed MS-subtype specific changes in PACAP and VIP and in the receptors' levels in the NAWM, which were partly corroborated by immunohistochemical analyses. Most PAC1 immunoreactivity was restricted to myelin-producing cells, whereas VPAC1 reactivity was diffused within the neuropil and in axonal bundles, and VPAC2 in small vessel walls. Within and around lesioned areas, glial cells were the predominant populations showing reactivity for the different PACAP/VIP receptors, with distinctive patterns across MS subtypes. Together, these data identify the differential expression patterns of PACAP/VIP receptors among the different MS clinical entities. These results may offer opportunities for the development of personalized therapeutic approaches to treating MS and/or other demyelinating disorders.

SENSITIVITY OF PLATELET-LYMPHOCYTE RATIO, MONOCYTE-LYMPHOCYTE RATIO, NEUTROPHIL-LYMPHOCYTE RATIO, RED BLOOD CELL DISTRIBUTION WIDTH AND SYSTEMIC IMMUNE INFLAMMATORY INDEX IN MULTIPLE SCLEROSIS PATIENTS: RELATIONSHIP WITH DISEASE SUBTYPES AND DISABILITY

OBJECTIVE: Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS). Although it is not clear how autoimmune responses occur, it is known that peripheral blood cells may promote the initiation and exacerbation of the inflammatory response in MS. The aim of this study was to evaluate the sensitivity and specificity of neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), erythrocyte distribution width (RDW) and systemic immune inflammation index (SIII) in MS and to determine their relationship with disability. MATERIAL AND METHODS: In this single-center, retrospective case-control study, 104 patients with MS and 65 healthy individuals were included. Disability was assessed with the Expanded Disability Status Scale (EDSS) score, and patients were classified as mild (EDSS&amp;lt;3), moderate (3.5 ≤ EDSS ≥4.5), and severe (EDSS≥5) disabilities. NLR, MLR, PLR, RDW and SIII values were calculated according to the complete blood counts of the patients and the control group. Inflammation markers between the control group and MS patients, MS subtypes, and relapsing-remitting MS (RRMS) attack and remission periods were compared. the relationship between these markers and duration of illness, number of attacks and disability was examined. RESULTS: MLR and RDW were higher in MS than the controls. There was no significant difference in these values between MS subtypes. It was observed that RDW increased as the disease duration, number of attacks and EDSS increased. CONCLUSIONS: In our study, in evaluating inflammation it was seen that MLR and RDW were more determinative than PLR, NLR and SIII. The fact that RDW is higher in MS patients and is affected by disease disability indicates that RDW may have an important role in the follow-up of MS patients and in evaluating the degree of disability.

NMR-based metabolomics identification of potential serum biomarkers of disease progression in patients with multiple sclerosis

Multiple sclerosis (MS) is a chronic and progressive neurological disorder, characterized by neuroinflammation and demyelination within the central nervous system (CNS). The etiology and the pathogenesis of MS are still unknown. Till now, no satisfactory treatments, diagnostic and prognostic biomarkers are available for MS. Therefore, we aimed to investigate metabolic alterations in patients with MS compared to controls and across MS subtypes. Metabolic profiles of serum samples from patients with MS (n = 90) and healthy control (n = 30) were determined by Nuclear Magnetic Resonance (1H-NMR) Spectroscopy using cryogenic probe. This approach was also utilized to identify significant differences between the metabolite profiles of the MS groups (primary progressive, secondary progressive, and relapsing–remitting) and the healthy controls. Concentrations of nine serum metabolites (adenosine triphosphate (ATP), tryptophan, formate, succinate, glutathione, inosine, histidine, pantothenate, and nicotinamide adenine dinucleotide (NAD)) were significantly higher in patients with MS compared to control. SPMS serum exhibited increased pantothenate and tryptophan than in PPMS. In addition, lysine, myo-inositol, and glutamate exhibited the highest discriminatory power (0.93, 95% CI 0.869–0.981; 0.92, 95% CI 0.859–0.969; 0.91, 95% CI 0.843–0.968 respectively) between healthy control and MS. Using NMR- based metabolomics, we identified a set of metabolites capable of classifying MS patients and controls. These findings confirmed untargeted metabolomics as a useful approach for the discovery of possible novel biomarkers that could aid in the diagnosis of the disease.

Potential biomarkers for multiple sclerosis stage from targeted proteomics and microRNA sequencing.

Multiple sclerosis is a chronic demyelinating disease of the central nervous system. There is a need for new circulating biomarkers for multiple sclerosis, in particular, markers that differentiate multiple sclerosis subtypes (relapsing-remitting, secondary progressive and primary progressive multiple sclerosis), as this can help in making treatment decisions. In this study, we explore two classes of potential multiple sclerosis biomarkers-proteins and microRNAs-circulating in the cerebrospinal fluid and serum. Targeted medium-throughput proteomics (92 proteins) and microRNA sequencing were performed on serum samples collected in a cross-sectional case-control cohort (cohort I, controls n = 30, multiple sclerosis n = 75) and a prospective multiple sclerosis cohort (cohort II, n = 93). For cohort I, we also made these measurements in paired cerebrospinal fluid samples. In the cohort I cerebrospinal fluid, we observed differences between multiple sclerosis and controls for 13 proteins, including some previously described to be markers for multiple sclerosis [e.g. CD27, C-X-C motif chemokine 13 (CXCL13) and interleukin-7 (IL7)]. No microRNAs were significantly differentially expressed between multiple sclerosis and controls in the cerebrospinal fluid. In serum, 10 proteins, including angiopoietin-1 receptor (TIE2), and 16 microRNAs were significantly different between relapsing-remitting multiple sclerosis and secondary progressive multiple sclerosis after performing a meta-analysis combining both cohorts. In the prospective part of the study, participants with relapsing-remitting multiple sclerosis were followed for around 3 years, during which time 12 participants converted to secondary progressive multiple sclerosis. In these longitudinally collected serum samples, we observed a peak in granzyme B, A and H proteins around the time of conversion. Single-sample enrichment analysis of serum microRNA profiles revealed that the peak in granzyme B levels around conversion coincides with enrichment for microRNAs that are enriched in CD4+, CD8+ and natural killer cells (e.g. miRNA-150). We identified several proteins and microRNAs in serum that represent potential biomarkers for relapsing-remitting and secondary progressive multiple sclerosis. Conversion to secondary progressive disease is marked by a peak in granzyme B levels and enrichment for immune-related microRNAs. This indicates that specific immune cell-driven processes may contribute to the conversion of relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis.

Investigating SNHG3 and BCYRN1 lncRnas expression in the peripheral blood cells of multiple sclerosis patients

ABSTRACT Background MS (Multiple sclerosis) is a progressive neurologic disorder often appearing in the third decade of life. MS is the most frequent demyelinating disease of the central nervous system. The development of MS is influenced by environmental, genetic, and epigenetic factors. The bulk of the human transcriptome comprises lncRNAs, which play crucial regulatory roles. We aimed to assess the SNHG3 and BCYRN1 lncRNA expression in blood samples from MS patients and how these lncRNAs and disease activity are related. Methods A total of 100 MS patients, including 8 primary progressive (PP), 82 relapsing-remitting (RR), and 10 secondary progressive (SP) MS, as well as 100 healthy controls, had their blood samples taken. Gene expression was assessed using quantitative real-time PCR. Recognizing the receiver operating characteristic (ROC) curve analysis, the diagnostic potential of lncRNA levels was evaluated. Results Expressions of SNHG3 and BCYRN1 were found to have significantly increased (p < 0.0001). SNHG3 expression level showed significant differences compared to age groups and MS subtypes (p value = 0.001 and p value = 0.02). Furthermore, patients with a family history showed elevated BCYRN1 expression with a p value of 0.01. Considering the age factor, BCYRN1 exhibits altered expression levels in patient groups compared to healthy controls (p value 0.04). Additionally, the novel biomarkers SNHG3 and BCYRN1 can be used to diagnose MS (AUC = 0.97 and AUC = 0.88, respectively). Discussion Increased levels of SNHG3 and BCYRN1 in the serum may serve as potential molecular biomarkers for the MS diagnosis.

MiR-24-3p and miR-484 are potential biomarkers for neurodegeneration in multiple sclerosis

Multiple sclerosis (MS) is a complex, neurodegenerative chronic disorder. Circulating diagnostic biomarkers for MS have remained elusive, and those proposed so far have limited sensitivity and specificity to MS. Plasma-circulating microRNAs (miRNAs) have advantageous biochemical and physiological attributes that can be utilized in clinical testing and disease monitoring. MS miRNA expression microarray datasets analysis resulted in four candidate miRNAs that were assessed for their expression in a separate MS case-control study. Only miR-24-3p was downregulated in all MS patients compared to healthy controls. MiR-484 was significantly upregulated in relapsing-remitting MS (RRMS) patients compared to healthy controls. Mir-146-5p and miR-484 were significantly downregulated in secondary-progressive MS (SPMS) compared to RRMS. MiR-484 downregulation was associated with worsening disability and increased lipocalin-2 levels. Mir-342-3p and miR-24-3p downregulation were associated with increased semaphorin-3A levels in MS and RRMS patients. In conclusion, mir-24-3p downregulation is diagnostic of MS, and mir-484 upregulation and downregulation are potential biomarkers for RRMS and SPMS conversion, respectively. The differential expression of miR-146a-3p in MS subtypes suggests its potential as an SPMS transition biomarker. The association of downregulated mir-24-3p and mir-484 with increased neurodegeneration biomarkers suggests they play a role in MS pathogenesis and neurodegeneration.

Soluble biomarkers for Neuromyelitis Optica Spectrum Disorders: a mini review.

The Neuromyelitis Optica Spectrum Disorders (NMOSD) constitute a spectrum of rare autoimmune diseases of the central nervous system characterized by episodes of transverse myelitis, optic neuritis, and other demyelinating attacks. Previously thought to be a subtype of multiple sclerosis, NMOSD is now known to be a distinct disease with unique pathophysiology, clinical course, and treatment options. Although there have been significant recent advances in the diagnosis and treatment of NMOSD, the field still lacks clinically validated biomarkers that can be used to stratify disease severity, monitor disease activity, and inform treatment decisions. Here we review many emerging NMOSD biomarkers including markers of cellular damage, neutrophil-to-lymphocyte ratio, complement, and cytokines, with a focus on how each biomarker can potentially be used for initial diagnosis, relapse surveillance, disability prediction, and treatment monitoring.

Prevalence, treatment and correlates of depression in multiple sclerosis

BackgroundThe prevalence of depression in Multiple Sclerosis (MS) is often assessed by administering patient reported outcome measures (PROMs) examining depressive symptomatology to population cohorts; a recent review summarised 12 such studies, eight of which used the Hospital Anxiety and Depression Scale-Depression (HADS-D). In clinical practice, depression is diagnosed by an individual structured clinical interview; diagnosis often leads to treatment options including antidepressant medication. It follows that an MS population will include those whose current depressive symptoms meet threshold for depression diagnosis, plus those who previously met diagnostic criteria for depression and have been treated such that depressive symptoms have improved below that threshold. We examined a large MS population to establish a multi-attribute estimate of depression, taking into account probable depression on HADS-D, as well as anti-depressant medication use and co-morbidity data reporting current treatment for depression. We then studied associations with demographic and health status measures and the trajectories of depressive symptoms over time. MethodsParticipants were recruited into the UK-wide Trajectories of Outcome in Neurological Conditions-MS (TONiC-MS) study, with demographic and disease data from clinical records, PROMs collected at intervals of at least 9 months, as well as co-morbidities and medication. Interval level conversions of PROM data followed Rasch analysis. Logistic regression examined associations of demographic characteristics and symptoms with depression. Finally, a group-based trajectory model was applied to those with depression. ResultsBaseline data in 5633 participants showed the prevalence of depression to be 25.3 % (CI: 24.2–26.5). There were significant differences in prevalence by MS subtype: relapsing 23.2 % (CI: 21.8- 24.5), primary progressive 25.8 % (CI: 22.5–29.3), secondary progressive 31.5 % (CI: 29.0–34.0); disability: EDSS 0–4 19.2 % (CI: 17.8–20.6), EDSS ≥4.5 31.9 % (CI: 30.2–33.6); and age: 42–57 years 27.7 % (CI: 26.0–29.3), above or below this range 23.1 % (CI: 21.6–24.7). Fatigue, disability, self-efficacy and self esteem correlated with depression with a large effect size (>0.8) whereas sleep, spasticity pain, vision and bladder had an effect size >0.5. The logistic regression model (N = 4938) correctly classified 80 % with 93 % specificity: risk of depression was increased with disability, fatigue, anxiety, more comorbidities or current smoking. Higher self-efficacy or self esteem and marriage reduced depression. Trajectory analysis of depressive symptoms over 40 months in those with depression (N = 1096) showed three groups: 19.1 % with low symptoms, 49.2 % with greater symptoms between the threshold of possible and probable depression, and 31.7 % with high depressive symptoms. 29.9 % (CI: 27.6–32.3) of depressed subjects were untreated, conversely of those treated, 26.1 % still had a symptom level consistent with a probable case (CI: 23.5–28.9). ConclusionA multi-attribute estimate of depression in MS is essential because using only screening questionnaires, diagnoses or antidepressant medication all under-estimate the true prevalence.Depression affects 25.3 % of those with MS, almost half of those with depression were either untreated or still had symptoms indicating probable depression despite treatment. Services for depression in MS must be pro-active and flexible, recognising the heterogeneity of outcomes and reaching out to those with ongoing symptoms.

A rapid review of differences in cerebrospinal neurofilament light levels in clinical subtypes of progressive multiple sclerosis.

Multiple sclerosis (MS) is divided into three clinical phenotypes: relapsing-remitting MS (RRMS), secondary progressive MS (SPMS), and primary progressive MS (PPMS). It is unknown to what extent SPMS and PPMS pathophysiology share inflammatory or neurodegenerative pathological processes. Cerebrospinal (CSF) neurofilament light (NfL) has been broadly studied in different MS phenotypes and is a candidate biomarker for comparing MS subtypes. Are CSF NfL levels different among clinical subtypes of progressive MS? A search strategy identifying original research investigating fluid neurodegenerative biomarkers in progressive forms of MS between 2010 and 2022 was applied to Medline. Identified articles underwent title and abstract screen and full text review against pre-specified criteria. Data abstraction was limited to studies that measured NfL levels in the CSF. Reported statistical comparisons of NfL levels between clinical phenotypes were abstracted qualitatively. 18 studies that focused on investigating direct comparisons of CSF NfL from people with MS were included in the final report. We found NfL levels were typically reported to be higher in relapsing and progressive MS compared to healthy controls. Notably, higher NfL levels were not clearly associated with progressive MS subtypes when compared to relapsing MS, and there was no observed difference in NfL levels between PPMS and SPMS in articles that separately assessed these phenotypes. CSF NfL levels distinguish individuals with MS from healthy controls but do not differentiate MS subtypes. Broad biological phenotyping is needed to overcome limitations of current clinical phenotyping and improve biomarker translatability to decision-making in the clinic.

Exploring subtypes of multiple sclerosis through unsupervised machine learning of automated fiber quantification.

This study aimed to subtype multiple sclerosis (MS) patients using unsupervised machine learning on white matter (WM) fiber tracts and investigate the implications for cognitive function and disability outcomes. We utilized the automated fiber quantification (AFQ) method to extract 18 WM fiber tracts from the imaging data of 103 MS patients in total. Unsupervised machine learning techniques were applied to conduct cluster analysis and identify distinct subtypes. Clinical and diffusion tensor imaging (DTI) metrics were compared among the subtypes, and survival analysis was conducted to examine disability progression and cognitive impairment. The clustering analysis revealed three distinct subtypes with variations in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Significant differences were observed in clinical and DTI metrics among the subtypes. Subtype 3 showed the fastest disability progression and cognitive decline, while Subtype 2 exhibited a slower rate, and Subtype 1 fell in between. Subtyping MS based on WM fiber tracts using unsupervised machine learning identified distinct subtypes with significant cognitive and disability differences. WM abnormalities may serve as biomarkers for predicting disease outcomes, enabling personalized treatment strategies and prognostic predictions for MS patients.

Disparities in DMT treatment: Demographic and neurocognitive differences between MS patients currently treated versus not treated with disease-modifying therapies

BackgroundCurrent treatment guidelines recommend consideration of disease-modifying therapy (DMT) for all multiple sclerosis (MS) patients, but barriers to access have begun to be identified. In particular, prior studies have found that people with higher education have better access to DMTs, perhaps explained by the association of higher education with higher income. And while the majority of people with MS are women, being male is also associated with higher income. These factors argue for the need to better understand whether there are differences in DMT uptake based on sex and education. Finally, in addition to well-documented benefits of DMTs for slowing disease progression, there is growing evidence to suggest benefits of DMTs for cognitive functioning. ObjectiveDetermine whether rates of DMT treatment differ based on education and sex. Secondarily, we investigate whether neurocognitive test performance differs in treated versus not treated groups. MethodsIn cross-sectional data, mixed effects linear regression evaluated differences in education and sex of those treated versus not treated with DMTs. Models included the following predictors: age, disease duration, MS subtype, sex/education, disability, atrophy, and T2 lesion volume. Propensity score weights were extracted to obtain unbiased estimates of the relationship between DMT status and each outcome of interest. The same models evaluated performance differences between groups on an iPad-based processing speed test (PST) and manual dexterity test (MDT). ResultsControlling for covariates, individuals with less education (OR=1.09, 95 % CI=[1.03, 1.14], p = 0.003) and women (OR=0.80, 95 % CI=[0.72, 0.90], p < 0.001) were less likely to be currently treated with DMTs. Small effect size association was shown for DMT treatment with better performance on PST (beta=0.09, CI=[0.06, 0.13], p < 0.001) and MDT (beta=0.05, CI=[0.01,0.08], p = 0.011). ConclusionsWomen and people with lower education had a lower likelihood of being currently treated with DMTs. After controlling for all relevant variables, an independent (small) association of DMT treatment to better performance on tests of processing speed and fine motor dexterity was found. Reasons for disparities remain to be investigated in future work, and may include employment status, health insurance coverage, or sex differences in risk tolerance.

Domain-specific cognitive impairment in multiple sclerosis: A systematic review and meta-analysis.

Methods of cognitive measurements in multiple sclerosis (MS) are not standardized. We aimed to identify the prevalence of cognitive domain-specific impairment (DSI) in MS by using subtests of the Brief Repeatable Battery of Neuropsychological Tests (BRB-N) with analyzing different cutoff values. The systematic review and meta-analysis were registered on PROSPERO (ID: CRD42021287004). The systematic literature search was performed via PubMed, Embase, and CENTRAL on 24 October 2021. Inclusion criteria were adults of different MS subtypes (CIS, RRMS, PPMS, and SPMS) with the condition of distinct DSI measured by BRB-N. Pediatric MS, computerized versions of BRB-N, and patients receiving steroids were excluded. Primary outcome was pooled prevalence rates of impaired patients within each cutoff and MS subtype, with 95% confidence interval, I-squared statistics for heterogeneity, and chi-squared test for subgroup differences. Risk of bias was assessed using the "JBI Quality Assessment Tool for Prevalence Studies." In 48 eligible observational studies (n = 3431 patients), the three most prevalent thresholds were the 2.0 SD and 1.5 SD below the mean of normative values, and the score below the fifth percentile of the normative values. A progressively increasing worsening of the overall DSI was observed from CIS, moving toward RRMS, PPMS, and SPMS. Cognitive impairment is observed in all MS phenotypes, with varying degrees. Due to several potential influencing factors, our comprehensive literature review has not revealed consistent findings, and we, therefore, recommend considering a more sophisticated, "individual referencing" approach, acknowledging the diverse clinical and sociodemographic characteristics among populations and disparities in cognitive testing.