MHConstructor: A high-throughput, haplotype-informed solution to the MHC assembly challenge.

The extremely high levels of genetic polymorphism within the human major histocompatibility complex (MHC) limit the usefulness of reference-based alignment methods for sequence assembly. We incorporate a short read de novo assembly algorithm into a workflow for novel application to the MHC. MHConstructor is a containerized pipeline designed for high-throughput, haplotype-informed, reproducible assembly of both whole genome sequencing and target-capture short read data in large, population cohorts. To-date, no other self-contained tool exists for the generation of de novo MHC assemblies from short read data. MHConstructor facilitates wide-spread access to high quality, alignment-free MHC sequence analysis.

An autoantibody signature predictive for multiple sclerosis.

Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. In this study, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster in approximately 10% of PwMS who share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active preclinical period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically or radiologically isolated neuroinflammatory syndromes.

Predicting disease severity in multiple sclerosis using multimodal data and machine learning.

BACKGROUND: Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. METHODS: We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre. RESULTS: We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high-accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts. CONCLUSION: Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening.

High-resolution DNA methylation screening of the major histocompatibility complex in multiple sclerosis.

Background: The HLA-DRB1 gene in the major histocompatibility complex (MHC) region in chromosome 6p21 is the strongest genetic factor identified as influencing multiple sclerosis (MS) susceptibility. DNA methylation changes associated with MS have been consistently detected at the MHC region. However, understanding the full scope of epigenetic regulations of the MHC remains incomplete, due in part to the limited coverage of this region by standard whole genome bisulfite sequencing or array-based methods. Methods: We developed and validated an MHC capture protocol coupled with bisulfite sequencing and conducted a comprehensive analysis of the MHC methylation landscape in blood samples from 147 treatment naïve MS study participants and 129 healthy controls. Results: We identified 132 differentially methylated region (DMRs) within MHC region associated with disease status. The DMRs overlapped with established MS risk loci. Integration of the MHC methylome with human leukocyte antigen (HLA) genetic data indicate that the methylation changes are significantly associated with HLA genotypes. Using DNA methylation quantitative trait loci (mQTL) mapping and the causal inference test (CIT), we identified 643 cis-mQTL-DMRs paired associations, including 71 DMRs possibly mediating causal relationships between 55 single nucleotide polymorphisms (SNPs) and MS risk. Results: The results describe MS-associated methylation changes in MHC region and highlight the association between HLA genotypes and methylation changes. Results from the mQTL and CIT analyses provide evidence linking MHC region variations, methylation changes, and disease risk for MS.

Neurofilament Light Chain Elevation and Disability Progression in Multiple Sclerosis.

Importance: Mechanisms contributing to disability accumulation in multiple sclerosis (MS) are poorly understood. Blood neurofilament light chain (NfL) level, a marker of neuroaxonal injury, correlates robustly with disease activity in people with MS (MS); however, data on the association between NfL level and disability accumulation have been conflicting. Objective: To determine whether and when NfL levels are elevated in the context of confirmed disability worsening (CDW). Design, Setting, and Participants: This study included 2 observational cohorts: results from the Expression, Proteomics, Imaging, Clinical (EPIC) study at the University of California San Francisco (since 2004) were confirmed in the Swiss Multiple Sclerosis Cohort (SMSC), a multicenter study in 8 centers since 2012. Data were extracted from EPIC in April 2022 (sampling July 1, 2004, to December 20, 2016) and SMSC in December 2022 (sampling June 6, 2012, to September 2, 2021). The study included 2 observational cohorts in tertiary MS centers. All participants of both cohorts with available NfL results were included in the study, and no eligible participants were excluded or declined to participate. Exposure: Association between NfL z scores and CDW. Main Outcome Measures: CDW was defined as Expanded Disability Status Scale (EDSS) worsening that was confirmed after 6 or more months and classified into CDW associated with clinical relapses (CDW-R) or independent of clinical relapses (CDW-NR). Visits were classified in relation to the disability worsening events into CDW(-2) for 2 visits preceding event, CDW(-1) for directly preceding event, CDW(event) for first diagnosis of EDSS increase, and the confirmation visit. Mixed linear and Cox regression models were used to evaluate NfL dynamics and to assess the association of NfL with future CDW, respectively. Results: A total of 3906 EPIC visits (609 participants; median [IQR] age, 42.0 [35.0-50.0] years; 424 female [69.6%]) and 8901 SMSC visits (1290 participants; median [IQR] age, 41.2 [32.5-49.9] years; 850 female [65.9%]) were included. In CDW-R (EPIC, 36 events; SMSC, 93 events), NfL z scores were 0.71 (95% CI, 0.35-1.07; P < .001) units higher at CDW-R(-1) in EPIC and 0.32 (95% CI, 0.14-0.49; P < .001) in SMSC compared with stable MS samples. NfL elevation could be detected preceding CDW-NR (EPIC, 191 events; SMSC, 342 events) at CDW-NR(-2) (EPIC: 0.23; 95% CI, 0.01-0.45; P = .04; SMSC: 0.28; 95% CI, 0.18-0.37; P < .001) and at CDW-NR(-1) (EPIC: 0.27; 95% CI, 0.11-0.44; P < .001; SMSC: 0.09; 95% CI, 0-0.18; P = .06). Those findings were replicated in the subgroup with relapsing-remitting MS. Time-to-event analysis confirmed the association between NfL levels and future CDW-R within approximately 1 year and CDW-NR (in approximately 1-2 years). Conclusions and Relevance: This cohort study documents the occurrence of NfL elevation in advance of clinical worsening and may hint to a potential window of ongoing dynamic central nervous system pathology that precedes the diagnosis of CDW.

GWAS meta-analysis of psoriasis identifies new susceptibility alleles impacting disease mechanisms and therapeutic targets.

Psoriasis is a common, debilitating immune-mediated skin disease. Genetic studies have identified biological mechanisms of psoriasis risk, including those targeted by effective therapies. However, the genetic liability to psoriasis is not fully explained by variation at robustly identified risk loci. To move towards a saturation map of psoriasis susceptibility we meta-analysed 18 GWAS comprising 36,466 cases and 458,078 controls and identified 109 distinct psoriasis susceptibility loci, including 45 that have not been previously reported. These include susceptibility variants at loci in which the therapeutic targets IL17RA and AHR are encoded, and deleterious coding variants supporting potential new drug targets (including in STAP2, CPVL and POU2F3). We conducted a transcriptome-wide association study to identify regulatory effects of psoriasis susceptibility variants and cross-referenced these against single cell expression profiles in psoriasis-affected skin, highlighting roles for the transcriptional regulation of haematopoietic cell development and epigenetic modulation of interferon signalling in psoriasis pathobiology.

Shared Genetic Risk Factors for Multiple Sclerosis/Psoriasis Suggest Involvement of Interleukin-17 and Janus Kinase-Signal Transducers and Activators of Transcription Signaling.

OBJECTIVE: Psoriasis and multiple sclerosis (MS) are complex immune diseases that are mediated by T cells and share multiple comorbidities. Previous studies have suggested psoriatic patients are at higher risk of MS; however, causal relationships between the two conditions remain unclear. Through epidemiology and genetics, we provide a comprehensive understanding of the relationship, and share molecular factors between psoriasis and MS. METHODS: We used logistic regression, trans-disease meta-analysis and Mendelian randomization. Medical claims data were included from 30 million patients, including 141,544 with MS and 742,919 with psoriasis. We used genome-wide association study summary statistics from 11,024 psoriatic, 14,802 MS cases, and 43,039 controls for trans-disease meta-analysis, with additional summary statistics from 5 million individuals for Mendelian randomization. RESULTS: Psoriatic patients have a significantly higher risk of MS (4,637 patients with both diseases; odds ratio [OR] 1.07, p = 1.2 × 10-5 ) after controlling for potential confounders. Using inverse variance and equally weighted trans-disease meta-analysis, we revealed >20 shared and opposing (direction of effect) genetic loci outside the major histocompatibility complex that showed significant genetic colocalization (in COLOC and COLOC-SuSiE v5.1.0). Co-expression analysis of genes from these loci further identified distinct clusters that were enriched among pathways for interleukin-17/tumor necrosis factor-α (OR >39, p < 1.6 × 10-3 ) and Janus kinase-signal transducers and activators of transcription (OR 35, p = 1.1 × 10-5 ), including genes, such as TNFAIP3, TYK2, and TNFRSF1A. Mendelian randomization found psoriasis as an exposure has a significant causal effect on MS (OR 1.04, p = 5.8 × 10-3 ), independent of type 1 diabetes (OR 1.05, p = 4.3 × 10-7 ), type 2 diabetes (OR 1.08, p = 2.3 × 10-3 ), inflammatory bowel disease (OR 1.11, p = 1.6 × 10-11 ), and vitamin D level (OR 0.75, p = 9.4 × 10-3 ). INTERPRETATION: By investigating the shared genetics of psoriasis and MS, along with their modifiable risk factors, our findings will advance innovations in treatment for patients suffering from comorbidities. ANN NEUROL 2023;94:384-397.

A Predictive Autoantibody Signature in Multiple Sclerosis.

Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. Here, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster of PwMS that share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active prodromal period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid (CSF) and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically- or radiologically-isolated neuroinflammatory syndromes.

Integration of epigenetic and genetic profiles identifies multiple sclerosis disease-critical cell types and genes.

Genome-wide association studies (GWAS) successfully identified multiple sclerosis (MS) susceptibility variants. Despite this notable progress, understanding the biological context of these associations remains challenging, due in part to the complexity of linking GWAS results to causative genes and cell types. Here, we aimed to address this gap by integrating GWAS data with single-cell and bulk chromatin accessibility data and histone modification profiles from immune and nervous systems. MS-GWAS associations are significantly enriched in regulatory regions of microglia and peripheral immune cell subtypes, especially B cells and monocytes. Cell-specific polygenic risk scores were developed to examine the cumulative impact of the susceptibility genes on MS risk and clinical phenotypes, showing significant associations with risk and brain white matter volume. The findings reveal enrichment of GWAS signals in B cell and monocyte/microglial cell-types, consistent with the known pathology and presumed targets of effective MS therapeutics.

Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans.

Polygenic inheritance plays a pivotal role in driving multiple sclerosis susceptibility, an inflammatory demyelinating disease of the CNS. We developed polygenic risk scores (PRS) of multiple sclerosis and assessed associations with both disease status and severity in cohorts of European descent. The largest genome-wide association dataset for multiple sclerosis to date (n = 41 505) was leveraged to generate PRS scores, serving as an informative susceptibility marker, tested in two independent datasets, UK Biobank [area under the curve (AUC) = 0.73, 95% confidence interval (CI): 0.72-0.74, P = 6.41 × 10-146] and Kaiser Permanente in Northern California (KPNC, AUC = 0.8, 95% CI: 0.76-0.82, P = 1.5 × 10-53). Individuals within the top 10% of PRS were at higher than 5-fold increased risk in UK Biobank (95% CI: 4.7-6, P = 2.8 × 10-45) and 15-fold higher risk in KPNC (95% CI: 10.4-24, P = 3.7 × 10-11), relative to the median decile. The cumulative absolute risk of developing multiple sclerosis from age 20 onwards was significantly higher in genetically predisposed individuals according to PRS. Furthermore, inclusion of PRS in clinical risk models increased the risk discrimination by 13% to 26% over models based only on conventional risk factors in UK Biobank and KPNC, respectively. Stratifying disease risk by gene sets representative of curated cellular signalling cascades, nominated promising genetic candidate programmes for functional characterization. These pathways include inflammatory signalling mediation, response to viral infection, oxidative damage, RNA polymerase transcription, and epigenetic regulation of gene expression to be among significant contributors to multiple sclerosis susceptibility. This study also indicates that PRS is a useful measure for estimating susceptibility within related individuals in multicase families. We show a significant association of genetic predisposition with thalamic atrophy within 10 years of disease progression in the UCSF-EPIC cohort (P < 0.001), consistent with a partial overlap between the genetics of susceptibility and end-organ tissue injury. Mendelian randomization analysis suggested an effect of multiple sclerosis susceptibility on thalamic volume, which was further indicated to be through horizontal pleiotropy rather than a causal effect. In summary, this study indicates important, replicable associations of PRS with enhanced risk assessment and radiographic outcomes of tissue injury, potentially informing targeted screening and prevention strategies.

Ancestral risk modification for multiple sclerosis susceptibility detected across the Major Histocompatibility Complex in a multi-ethnic population.

The Major Histocompatibility Complex (MHC) makes the largest genetic contribution to multiple sclerosis (MS) susceptibility, with 32 independent effects across the region explaining 20% of the heritability in European populations. Variation is high across populations with allele frequency differences and population-specific risk alleles identified. We sought to identify MHC-specific MS susceptibility variants and assess the effect of ancestral risk modification within 2652 Latinx and Hispanic individuals as well as 2435 Black and African American individuals. We have identified several novel susceptibility alleles which are rare in European populations including HLA-B*53:01, and we have utilized the differing linkage disequilibrium patterns inherent to these populations to identify an independent role for HLA-DRB1*15:01 and HLA-DQB1*06:02 on MS risk. We found a decrease in Native American ancestry in MS cases vs controls across the MHC, peaking near the previously identified MICB locus with a decrease of ~5.5% in Hispanics and ~0.4% in African Americans. We have identified several susceptibility variants, including within the MICB gene region, which show global ancestry risk modification and indicate ancestral differences which may be due in part to correlated environmental factors. We have also identified several susceptibility variants for which MS risk is modified by local ancestry and indicate true ancestral genetic differences; including HLA-DQB1*06:02 for which MS risk for European allele carriers is almost two times the risk for African allele carriers. These results validate the importance of investigating MS susceptibility at an ancestral level and offer insight into the epidemiology of MS phenotypic diversity.

Epigenetic control of ataxin-1 in multiple sclerosis.

OBJECTIVE: ATXN1 encodes the polyglutamine protein ataxin-1, which we have demonstrated exerting an immunomodulatory function in the context of central nervous system (CNS) autoimmunity, in addition to its classical role in the neurodegenerative disorder spinocerebellar ataxia type 1 (SCA1). In this study, we dissected the contribution of DNA methylation to the regulation of ATXN1 in multiple sclerosis (MS). METHODS: We interrogated a DNA methylation dataset previously generated via bisulfate DNA sequencing (BS-seq) in sorted peripheral immune cytotypes (CD4+ and CD8+ T cells, CD19+ B cells, and CD14+ monocytes) isolated from untreated MS patients at symptoms onset. RESULTS: Here, we report that ATXN1 undergoes hypo-methylation at four distinct regions upon MS, exclusively in B cells. We also highlight how these differentially methylated sites overlap with other regulatory epigenetic marks and MS risk variants. Lastly, we employ luciferase assays to assess the functionality of these regions, showing that the loss of methylation leads to an increase in ATXN1 expression. INTERPRETATION: Altogether, these findings provide biological insights into ataxin-1 regulation in the immune system as well as into the molecular mechanisms underlying MS risk.

Plasma neurofilament light chain levels suggest neuroaxonal stability following therapeutic remyelination in people with multiple sclerosis.

BACKGROUND: Chronic demyelination is a major contributor to axonal vulnerability in multiple sclerosis (MS). Therefore, remyelination could provide a potent neuroprotective strategy. The ReBUILD trial was the first study showing evidence for successful remyelination following treatment with clemastine in people with MS (pwMS) with no evidence of disease activity or progression (NEDAP). Whether remyelination was associated with neuroprotection remains unexplored. METHODS: Plasma neurofilament light chain (NfL) levels were measured from ReBUILD trial's participants. Mixed linear effect models were fit for individual patients, epoch and longitudinal measurements to compare NfL concentrations between samples collected during the active and placebo treatment period. RESULTS: NfL concentrations were 9.6% lower in samples collected during the active treatment with clemastine (n=53, geometric mean=6.33 pg/mL) compared to samples collected during treatment with placebo (n=73, 7.00 pg/mL) (B=-0.035 [-0.068 to -0.001], p=0.041). Applying age- and body mass index-standardised NfL Z-scores and percentiles revealed similar results (0.04 vs 0.35, and 27.5 vs 33.3, p=0.023 and 0.042, respectively). Higher NfL concentrations were associated with more delayed P100 latencies (B=1.33 [0.26 to 2.41], p=0.015). In addition, improvement of P100 latencies between visits was associated with a trend for lower NfL values (B=0.003 [-0.0004 to 0.007], p=0.081). Based on a Cohen's d of 0.248, a future 1:1 parallel-arm placebo-controlled study using a remyelinating agent with comparable effect as clemastine would need 202 subjects per group to achieve 80% power. CONCLUSIONS: In pwMS, treatment with the remyelinating agent clemastine was associated with a reduction of blood NfL, suggesting that neuroprotection is achievable and measurable with therapeutic remyelination. TRIAL REGISTRATION NUMBER: NCT02040298.

KIR+CD8+ T cells suppress pathogenic T cells and are active in autoimmune diseases and COVID-19.

In this work, we find that CD8+ T cells expressing inhibitory killer cell immunoglobulin-like receptors (KIRs) are the human equivalent of Ly49+CD8+ regulatory T cells in mice and are increased in the blood and inflamed tissues of patients with a variety of autoimmune diseases. Moreover, these CD8+ T cells efficiently eliminated pathogenic gliadin-specific CD4+ T cells from the leukocytes of celiac disease patients in vitro. We also find elevated levels of KIR+CD8+ T cells, but not CD4+ regulatory T cells, in COVID-19 patients, correlating with disease severity and vasculitis. Selective ablation of Ly49+CD8+ T cells in virus-infected mice led to autoimmunity after infection. Our results indicate that in both species, these regulatory CD8+ T cells act specifically to suppress pathogenic T cells in autoimmune and infectious diseases.

A short HLA-DRA isoform binds the HLA-DR2 heterodimer on the outer domain of the peptide-binding site.

The human leukocyte antigen (HLA) locus encodes a large group of proteins governing adaptive and innate immune responses. Among them, HLA class II proteins form α/ß heterodimers on the membrane of professional antigen-presenting cells (APCs), where they display both, self and pathogen-derived exogenous antigens to CD4+ T lymphocytes. We have previously shown that a shorter HLA-DRA isoform (sHLA-DRA) lacking 25 amino acids can be presented onto the cell membrane via binding to canonical HLA-DR2 heterodimers. Here, we employed atomistic molecular dynamics simulations to decipher the binding position of sHLA-DRA and its structural impact on functional regions of the HLA-DR2 molecule. We show that a loop region exposed only in the short isoform (residues R69 to G83) is responsible for binding to the outer domain of the HLA-DR2 peptide-binding site, and experimentally validated the critical role of F76 in mediating such interaction. Additionally, sHLA-DRA allosterically modifies the peptide-binding pocket conformation. In summary, this study unravels key molecular mechanisms underlying sHLA-DRA function, providing important insights into the role of full-length proteins in structural modulation of HLA class II receptors.

Serum neurofilament light chain for individual prognostication of disease activity in people with multiple sclerosis: a retrospective modelling and validation study.

BACKGROUND: Serum neurofilament light chain (sNfL) is a biomarker of neuronal damage that is used not only to monitor disease activity and response to drugs and to prognosticate disease course in people with multiple sclerosis on the group level. The absence of representative reference values to correct for physiological age-dependent increases in sNfL has limited the diagnostic use of this biomarker at an individual level. We aimed to assess the applicability of sNfL for identification of people at risk for future disease activity by establishing a reference database to derive reference values corrected for age and body-mass index (BMI). Furthermore, we used the reference database to test the suitability of sNfL as an endpoint for group-level comparison of effectiveness across disease-modifying therapies. METHODS: For derivation of a reference database of sNfL values, a control group was created, comprising participants with no evidence of CNS disease taking part in four cohort studies in Europe and North America. We modelled the distribution of sNfL concentrations in function of physiological age-related increase and BMI-dependent modulation, to derive percentile and Z score values from this reference database, via a generalised additive model for location, scale, and shape. We tested the reference database in participants with multiple sclerosis in the Swiss Multiple Sclerosis Cohort (SMSC). We compared the association of sNfL Z scores with clinical and MRI characteristics recorded longitudinally to ascertain their respective disease prognostic capacity. We validated these findings in an independent sample of individuals with multiple sclerosis who were followed up in the Swedish Multiple Sclerosis registry. FINDINGS: We obtained 10 133 blood samples from 5390 people (median samples per patient 1 [IQR 1-2] in the control group). In the control group, sNfL concentrations rose exponentially with age and at a steeper increased rate after approximately 50 years of age. We obtained 7769 samples from 1313 people (median samples per person 6·0 [IQR 3·0-8·0]). In people with multiple sclerosis from the SMSC, sNfL percentiles and Z scores indicated a gradually increased risk for future acute (eg, relapse and lesion formation) and chronic (disability worsening) disease activity. A sNfL Z score above 1·5 was associated with an increased risk of future clinical or MRI disease activity in all people with multiple sclerosis (odds ratio 3·15, 95% CI 2·35-4·23; p<0·0001) and in people considered stable with no evidence of disease activity (2·66, 1·08-6·55; p=0·034). Increased Z scores outperformed absolute raw sNfL cutoff values for diagnostic accuracy. At the group level, the longitudinal course of sNfL Z score values in people with multiple sclerosis from the SMSC decreased to those seen in the control group with use of monoclonal antibodies (ie, alemtuzumab, natalizumab, ocrelizumab, and rituximab) and, to a lesser extent, oral therapies (ie, dimethyl fumarate, fingolimod, siponimod, and teriflunomide). However, longitudinal sNfL Z scores remained elevated with platform compounds (interferons and glatiramer acetate; p<0·0001 for the interaction term between treatment category and treatment duration). Results were fully supported in the validation cohort (n=4341) from the Swedish Multiple Sclerosis registry. INTERPRETATION: The use of sNfL percentiles and Z scores allows for identification of individual people with multiple sclerosis at risk for a detrimental disease course and suboptimal therapy response beyond clinical and MRI measures, specifically in people with disease activity-free status. Additionally, sNfL might be used as an endpoint for comparing effectiveness across drug classes in pragmatic trials. FUNDING: Swiss National Science Foundation, Progressive Multiple Sclerosis Alliance, Biogen, Celgene, Novartis, Roche.

Spinal Cord Atrophy Predicts Progressive Disease in Relapsing Multiple Sclerosis.

OBJECTIVE: A major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS). METHODS: From a single-center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12-year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion. RESULTS: Patients who developed SPMS showed faster cord atrophy rates (-2.19%/yr) at least 4 years before conversion compared to their RRMS matches (-0.88%/yr, p < 0.001). Spinal cord atrophy rates decelerated after conversion (-1.63%/yr, p = 0.010) towards those of SPMS patients from study entry (-1.04%). Each 1% faster spinal cord atrophy rate was associated with 69% (p < 0.0001) and 53% (p < 0.0001) shorter time to silent progression and SPMS conversion, respectively. INTERPRETATION: Silent progression and conversion to secondary progressive disease are predominantly related to cervical cord atrophy. This atrophy is often present from the earliest disease stages and predicts the speed of silent progression and conversion to Progressive MS. Diagnosis of SPMS is rather a late recognition of this neurodegenerative process than a distinct disease phase. ANN NEUROL 2022;91:268-281.