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Background: Evidence for a role of human gut microbiota in multiple sclerosis (MS) risk is mounting, yet large variability is seen across studies. This is, in part, due to the lack of standardization of study protocols, sample collection methods, and sequencing approaches. Objective: This study aims to address the effect of a household experimental design, sample collection, and sequencing approaches in a gut microbiome study in MS subjects from a multi-city study population. Methods: We analyzed 128 MS patient and cohabiting healthy control pairs from the International MS Microbiome Study (iMSMS). A total of 1005 snap-frozen or desiccated Q-tip stool samples were collected and evaluated using 16S and shallow whole-metagenome shotgun sequencing. Results: The intra-individual variance observed by different collection strategies was dramatically lower than inter-individual variance. Shallow shotgun highly correlated with 16S sequencing. Participant house and recruitment site accounted for the two largest sources of microbial variance, while higher microbial similarity was seen in household-matched participants as hypothesized. A significant proportion of the variance in dietary intake was also dominated by geographic distance. Conclusion: A household pair study largely overcomes common inherent limitations and increases statistical power in population-based microbiome studies.

The human leukocyte antigen (HLA) genes are extremely polymorphic and are useful molecular markers to make inferences about human population history. However, the accuracy of the estimation of genetic diversity at HLA loci very much depends on the technology used to characterize HLA alleles; high-resolution genotyping of long-range HLA gene products improves the assessment of HLA population diversity as well as other population parameters compared to lower resolution typing methods. In this study we examined allelic and haplotype HLA diversity in a large healthy European American population sourced from the UCSF-DNA bank. A high-resolution next-generation sequencing method was applied to define non-ambiguous 3- and 4-field alleles at the HLA-A, HLA-C, HLA-B, HLA-DRB1, HLA-DRB3/4/5, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1 loci in samples provided by 2248 unrelated individuals. A number of population parameters were examined including balancing selection and various measurements of linkage disequilibrium were calculated. There were no detectable deviations from Hardy-Weinberg proportions at HLA-A, HLA-DRB1, HLA-DQA1 and HLA-DQB1. For the remaining loci moderate and significant deviations were detected at HLA-C, HLA-B, HLA-DRB3/4/5, HLA-DPA1 and HLA-DPB1 loci mostly from population substructures. Unique 4-field associations were observed among alleles at 2 loci and haplotypes extending large intervals that were not apparent in results obtained using testing methodologies with limited sequence coverage and phasing. The high diversity at HLA-DPA1 results from detection of intron variants of otherwise well conserved protein sequences. It may be speculated that divergence in exon sequences may be negatively selected. Our data provides a valuable reference source for future population studies that may allow for precise fine mapping of coding and non-coding sequences determining disease susceptibility and allo-immunogenicity.

Author(s): University of California, San Francisco MS-EPIC Team; Cree, Bruce AC; Hollenbach, Jill A; Bove, Riley; Kirkish, Gina; Sacco, Simone; Caverzasi, Eduardo; Bischof, Antje; Gundel, Tristan; Zhu, Alyssa H; Papinutto, Nico; Stern, William A; Bevan, Carolyn; Romeo, Andrew; Goodin, Douglas S; Gelfand, Jeffrey M; Graves, Jennifer; Green, Ari J; Wilson, Michael R; Zamvil, Scott S; Zhao, Chao; Gomez, Refujia; Ragan, Nicholas R; Rush, Gillian Q; Barba, Patrick; Santaniello, Adam; Baranzini, Sergio E; Oksenberg, Jorge R; Henry, Roland G; Hauser, Stephen L | Abstract: ObjectiveRates of worsening and evolution to secondary progressive multiple sclerosis (MS) may be substantially lower in actively treated patients compared to natural history studies from the pretreatment era. Nonetheless, in our recently reported prospective cohort, more than half of patients with relapsing MS accumulated significant new disability by the 10th year of follow-up. Notably, "no evidence of disease activity" at 2 years did not predict long-term stability. Here, we determined to what extent clinical relapses and radiographic evidence of disease activity contribute to long-term disability accumulation.MethodsDisability progression was defined as an increase in Expanded Disability Status Scale (EDSS) of 1.5, 1.0, or 0.5 (or greater) from baseline EDSS = 0, 1.0-5.0, and 5.5 or higher, respectively, assessed from baseline to year 5 (±1 year) and sustained to year 10 (±1 year). Longitudinal analysis of relative brain volume loss used a linear mixed model with sex, age, disease duration, and HLA-DRB1*15:01 as covariates.ResultsRelapses were associated with a transient increase in disability over 1-year intervals (p = 0.012) but not with confirmed disability progression (p = 0.551). Relative brain volume declined at a greater rate among individuals with disability progression compared to those who remained stable (p l 0.05).InterpretationLong-term worsening is common in relapsing MS patients, is largely independent of relapse activity, and is associated with accelerated brain atrophy. We propose the term silent progression to describe the insidious disability that accrues in many patients who satisfy traditional criteria for relapsing-remitting MS. Ann Neurol 2019;85:653-666.

Background: In persons with multiple sclerosis (MS), the Expanded Disability Status Scale (EDSS) is the criterion standard for assessing disability, but its in-person nature constrains patient participation in research and clinical assessments. Objective: The aim of this study was to develop and validate a scalable, electronic, unsupervised patient-reported EDSS (ePR-EDSS) that would capture MS-related disability across the spectrum of severity. Methods: We enrolled 136 adult MS patients, split into a preliminary testing Cohort 1 ( n = 50), and a validation Cohort 2 ( n = 86), which was evenly distributed across EDSS groups. Each patient completed an ePR-EDSS either immediately before or after a MS clinician’s Neurostatus EDSS evaluation. Results: In Cohort 2, mean age was 50.6 years (range = 26–80) and median EDSS was 3.5 (interquartile range (IQR) = [1.5, 5.5]). The ePR-EDSS and EDSS agreed within 1-point for 86% of examinations; kappa for agreement within 1-point was 0.85 ( p Discussion: The ePR-EDSS was highly correlated with EDSS, with good agreement even at lower EDSS levels. For clinical care, the ePR-EDSS could enable the longitudinal monitoring of a patient’s disability. For research, it provides a valid and rapid measure across the entire spectrum of disability and permits broader participation with fewer in-person assessments.

Multiple sclerosis (MS) susceptibility shows strong genetic associations with HLA alleles and haplotypes. We genotyped 11 HLA genes in 477 non-Hispanic European MS patients and their 954 unaffected parents using a validated next-generation sequencing (NGS) methodology. HLA haplotypes were assigned unequivocally by tracing HLA allele transmissions. We explored HLA haplotype/allele associations with MS using the genotypic transmission disequilibrium test (gTDT) and multiallelic TDT (mTDT). We also conducted a case-control (CC) study with all patients and 2029 healthy unrelated ethnically matched controls. We performed separate analyses of 54 extended multi-case families by reviewing transmission of haplotype blocks. The haplotype fragment including DRB5*01:01:01~DRB1*15:01:01:01 was significantly associated with predisposition (gTDT: p < 2.20e-16; mTDT: p =1.61e-07; CC: p < 2.22e-16) as reported previously. A second risk allele, DPB1*104:01 (gTDT: p = 3.69e-03; mTDT: p = 2.99e-03; CC: p = 1.00e-02), independent from the haplotype bearing DRB1*15:01 was newly identified. The allele DRB1*01:01:01 showed significant protection (gTDT: p = 8.68e-06; mTDT: p = 4.50e-03; CC: p = 1.96e-06). Two DQB1 alleles, DQB1*03:01 (gTDT: p = 2.86e-03; mTDT: p = 5.56e-02; CC: p = 4.08e-05) and DQB1*03:03 (gTDT: p = 1.17e-02; mTDT: p = 1.16e-02; CC: p = 1.21e-02), defined at two-field level also showed protective effects. The HLA class I block, A*02:01:01:01~C*03:04:01:01~B*40:01:02 (gTDT: p = 5.86e-03; mTDT: p = 3.65e-02; CC: p = 9.69e-03) and the alleles B*27:05 (gTDT: p = 6.28e-04; mTDT: p = 2.15e-03; CC: p = 1.47e-02) and B*38:01 (gTDT: p = 3.20e-03; mTDT: p = 6.14e-03; CC: p = 1.70e-02) showed moderately protective effects independently from each other and from the class II associated factors. By comparing statistical significance of 11 HLA loci and 19 haplotype segments with both untruncated and two-field allele names, we precisely mapped MS candidate alleles/haplotypes while eliminating false signals resulting from ‘hitchhiking’ alleles. We assessed genetic burden for the HLA allele/haplotype identified in this study. This family-based study including the highest-resolution of HLA alleles proved to be powerful and efficient for precise identification of HLA genotypes associated with both, susceptibility and protection to development of MS.

Background: Electronic medical records (EMR) data are increasingly used in research, but no studies have yet evaluated similarity between EMR and research-quality data and between characteristics of an EMR multiple sclerosis (MS) population and known natural MS history. Objectives: To (1) identify MS patients in an EMR system and extract clinical data, (2) compare EMR-extracted data with gold-standard research data, and (3) compare EMR MS population characteristics to expected MS natural history. Methods: Algorithms were implemented to identify MS patients from the University of California San Francisco EMR, de-identify the data and extract clinical variables. EMR-extracted data were compared to research cohort data in a subset of patients. Results: We identified 4142 MS patients via search of the EMR and extracted their clinical data with good accuracy. EMR and research values showed good concordance for Expanded Disability Status Scale (EDSS), timed-25-foot walk, and subtype. We replicated several expected MS epidemiological features from MS natural history including higher EDSS for progressive versus relapsing–remitting patients and for male versus female patients and increased EDSS with age at examination and disease duration. Conclusion: Large real-world cohorts algorithmically extracted from the EMR can expand opportunities for MS clinical research.

Animal models are widely employed in basic research to test mechanistic hypotheses in a complex biological environment as well as to evaluate the therapeutic potential of candidate compounds in preclinical settings. Rodents, and in particular mice, represent the most common in vivo models for their small size, short lifespan and possibility to manipulate their genome. Over time, a typical laboratory will develop a substantial number of inbred strains and transgenic mouse lines, requiring a substantial effort, in both logistic and economic terms, to maintain an animal colony for research purposes and to safeguard the integrity of results. To meet this need, here we present TopoDB, a robust and extensible web-based platform for the rational management of laboratory animals. TopoDB allows an easy tracking of individual animals within the colony and breeding protocols as well as the convenient storage of both genetic and phenotypic data generated in the different experiments. Altogether, these features facilitate and enhance the design of in vivo research, thus reducing the number of necessary animals and the housing costs. In summary, TopoDB represents a novel valuable tool in modern biomedical research. Database URL: https://github.com/UCSF-MS-DCC/TopoDB

Background: Substantial progress has been made toward unraveling the genetic architecture of multiple sclerosis (MS) within populations of European ancestry, but few genetic studies have focused on Hispanic and African American populations within the United States. Objective: We sought to test the relevance of common European MS risk variants outside of the major histocompatibility complex ( n = 200) within these populations. Methods: Genotype data were available on 2652 Hispanics (1298 with MS, 1354 controls) and 2435 African Americans (1298 with MS, 1137 controls). We conducted single variant, pathway, and cumulative genetic risk score analyses. Results: We found less replication than statistical power suggested, particularly among African Americans. This could be due to limited correlation between the tested and causal variants within the sample or alternatively could indicate allelic and locus heterogeneity. Differences were observed between pathways enriched among the replicating versus all 200 variants. Although these differences should be examined in larger samples, a potential role exists for gene–environment or gene–gene interactions which alter phenotype differentially across racial and ethnic groups. Cumulative genetic risk scores were associated with MS within each study sample but showed limited diagnostic capability. Conclusion: These findings provide a framework for fine-mapping efforts in multi-ethnic populations of MS.

Background Patients with multiple sclerosis (MS) face several challenges in accessing clinical tools to help them monitor, understand, and make meaningful decisions about their disease course. The University of California San Francisco MS BioScreen is a web-based precision medicine tool initially designed to be clinician facing. We aimed to design a second, openly available tool, Open MS BioScreen, that would be accessible, understandable, and actionable by people with MS. Objective This study aimed to describe the human-centered design and development approach (inspiration, ideation, and implementation) for creating the Open MS BioScreen platform. Methods We planned an iterative and cyclical development process that included stakeholder engagement and iterative feedback from users. Stakeholders included patients with MS along with their caregivers and family members, MS experts, generalist clinicians, industry representatives, and advocacy experts. Users consisted of anyone who wants to track MS measurements over time and access openly available tools for people with MS. Phase I (inspiration) consisted of empathizing with users and defining the problem. We sought to understand the main challenges faced by patients and clinicians and what they would want to see in a web-based app. In phase II (ideation), our multidisciplinary team discussed approaches to capture, display, and make sense of user data. Then, we prototyped a series of mock-ups to solicit feedback from clinicians and people with MS. In phase III (implementation), we incorporated all concepts to test and iterate a minimally viable product. We then gathered feedback through an agile development process. The design and development were cyclical—many times throughout the process, we went back to the drawing board. Results This human-centered approach generated an openly available, web-based app through which patients with MS, their clinicians, and their caregivers can access the site and create an account. Users can enter information about their MS (basic level as well as more advanced concepts), visualize their data longitudinally, access a series of algorithms designed to empower them to make decisions about their treatments, and enter data from wearable devices to encourage realistic goal setting about their ambulatory activity. Agile development will allow us to continue to incorporate precision medicine tools, as these are validated in the clinical research arena. Conclusions After engaging intended users into the iterative human-centered design of the Open MS BioScreen, we will now monitor the adaptation and dissemination of the tool as we expand its functionality and reach. The insights generated from this approach can be applied to the development of a number of self-tracking, self-management, and user engagement tools for patients with chronic conditions.

The original version of this Article contained an error in the spelling of the author Nikolaos A. Patsopoulos, which was incorrectly given as Niklaos A. Patsopoulos, and author Efthimios Dardiotis, which was incorrectly given as Dardiotis Efthimios. This has now been corrected in both the PDF and HTML versions of the Article.

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available., Genome-wide association studies (GWAS) have so far uncovered more than 200 loci for multiple sclerosis (MS). Here, the authors integrate data from various sources for a cell type-specific pathway analysis of MS GWAS results that specifically highlights the involvement of the immune system in disease pathogenesis.

Objective: Primary progressive multiple sclerosis (PPMS) causes accumulation of neurological disability from disease onset without clinical attacks typical of relapsing multiple sclerosis (RMS). However, whether genetic variation influences the disease course remains unclear. We aimed to determine whether mutations causative of neurological disorders that share features with multiple sclerosis (MS) contribute to risk for developing PPMS. Methods: We examined whole-genome sequencing (WGS) data from 38 PPMS and 81 healthy subjects of European ancestry. We selected pathogenic variants exclusively found in PPMS patients that cause monogenic neurological disorders and performed two rounds of replication genotyping in 746 PPMS, 3,049 RMS, and 1,000 healthy subjects. To refine our findings, we examined the burden of rare, potentially pathogenic mutations in 41 genes that cause hereditary spastic paraplegias (HSPs) in PPMS (n = 314), secondary progressive multiple sclerosis (SPMS; n = 587), RMS (n = 2,248), and healthy subjects (n = 987) genotyped using the MS replication chip. Results: WGS and replication studies identified three pathogenic variants in PPMS patients that cause neurological disorders sharing features with MS: KIF5A p.Ala361Val in spastic paraplegia 10; MLC1 p.Pro92Ser in megalencephalic leukodystrophy with subcortical cysts, and REEP1 c.606 + 43G>T in Spastic Paraplegia 31. Moreover, we detected a significant enrichment of HSP-related mutations in PPMS patients compared to controls (risk ratio [RR] = 1.95; 95% confidence interval [CI], 1.27–2.98; p = 0.002), as well as in SPMS patients compared to controls (RR = 1.57; 95% CI, 1.18–2.10; p = 0.002). Importantly, this enrichment was not detected in RMS. Interpretation: This study provides evidence to support the hypothesis that rare Mendelian genetic variants contribute to the risk for developing progressive forms of MS. Ann Neurol 2018;83:51–63.

Multiple sclerosis is a common, complex neurological disease, where almost 20% of risk heritability can be attributed to common genetic variants, including >230 identified by genome-wide association studies (Patsopoulos et al., 2017). Multiple strands of evidence suggest that the majority of the remaining heritability is also due to the additive effects of individual variants, rather than epistatic interactions between these variants, or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that as much as 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common variant signals, which highlight a key role for regulatory T cell homeostasis and regulation, IFNγ biology and NFκB signaling in MS pathogenesis. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

IMPORTANCE: Blood sample–based biomarkers that are associated with clinically meaningful outcomes for patients with multiple sclerosis (MS) have not been developed. OBJECTIVE: To evaluate the potential of serum neurofilament light chain (sNFL) measurements as a biomarker of disease activity and progression in a longitudinal MS data set. DESIGN, SETTING, AND PARTICIPANTS: Single-center, ongoing, prospective observational cohort study of 607 patients with MS from the longitudinal EPIC (Expression, Proteomics, Imaging, Clinical) study at the University of California, San Francisco from July 1, 2004, through August 31, 2017. Clinical evaluations and sample collection were performed annually for 5 years, then at different time points for up to 12 years, with a median follow-up duration of 10 (interquartile range, 7-11) years. Serum NFL levels were measured using a sensitive single molecule array platform and compared with clinical and magnetic resonance imaging variables with the use of univariable and multivariable analyses. MAIN OUTCOMES AND MEASURES: The main outcomes were disability progression defined as clinically significant worsening on the Expanded Disability Status Scale (EDSS) score and brain fraction atrophy. RESULTS: Mean (SD) age of the 607 study participants at study entry was 42.5 (9.8) years; 423 (69.7%) were women; and all participants were of non-Hispanic European descent. Of 3911 samples sequentially collected, 3904 passed quality control for quantification of sNFL. Baseline sNFL levels showed significant associations with EDSS score (β, 1.080; 95% CI, 1.047-1.114; P

We assembled and analyzed genetic data of 47,351 multiple sclerosis (MS) subjects and 68,284 control subjects and establish a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 independent associations within the extended MHC. We used an ensemble of methods to prioritize up to 551 potentially associated MS susceptibility genes, that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we do find enrichment for MS genes in these brain - resident immune cells. Thus, while MS is most likely initially triggered by perturbation of peripheral immune responses the functional responses of microglia and other brain cells are also altered and may have a role in targeting an autoimmune process to the central nervous system.One Sentence Summary:We report a detailed genetic and genomic map of multiple sclerosis, and describe the role of putatively affected genes in the peripheral immune system and brain resident microglia.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.

Importance Although multiple HLA alleles associated with multiple sclerosis (MS) risk have been identified, genotype-phenotype studies in the HLA region remain scarce and inconclusive. Objectives To investigate whether MS risk-associated HLA alleles also affect disease phenotypes. Design, Setting, and Participants A cross-sectional, case-control study comprising 652 patients with MS who had comprehensive phenotypic information and 455 individuals of European origin serving as controls was conducted at a single academic research site. Patients evaluated at the Multiple Sclerosis Center at University of California, San Francisco between July 2004 and September 2005 were invited to participate. Spinal cord imaging in the data set was acquired between July 2013 and March 2014; analysis was performed between December 2014 and December 2015. Main Outcomes and Measures Cumulative HLA genetic burden (HLAGB) calculated using the most updated MS-associated HLA alleles vs clinical and magnetic resonance imaging outcomes, including age at onset, disease severity, conversion time from clinically isolated syndrome to clinically definite MS, fractions of cortical and subcortical gray matter and cerebral white matter, brain lesion volume, spinal cord gray and white matter areas, upper cervical cord area, and the ratio of gray matter to the upper cervical cord area. Multivariate modeling was applied separately for each sex data set. Results Of the 652 patients with MS, 586 had no missing genetic data and were included in the HLAGB analysis. In these 586 patients (404 women [68.9%]; mean [SD] age at disease onset, 33.6 [9.4] years), HLAGB was higher than in controls (median [IQR], 0.7 [0-1.4] and 0 [−0.3 to 0.5], respectively; P = 1.8 × 10 −27 ). A total of 619 (95.8%) had relapsing-onset MS and 27 (4.2%) had progressive-onset MS. No significant difference was observed between relapsing-onset MS and primary progressive MS. A higher HLAGB was associated with younger age at onset and the atrophy of subcortical gray matter fraction in women with relapsing-onset MS (standard β = −1.20 × 10 −1 ; P = 1.7 × 10 −2 and standard β = −1.67 × 10 −1 ; P = 2.3 × 10 −4 , respectively), which were driven mainly by the HLA-DRB1*15:01 haplotype. In addition, we observed the distinct role of the HLA-A*24:02 - B*07:02 - DRB1*15:01 haplotype among the other common DRB1*15:01 haplotypes and a nominally protective effect of HLA-B*44:02 to the subcortical gray atrophy (standard β = −1.28 × 10 −1 ; P = 5.1 × 10 −3 and standard β = 9.52 × 10 −2 ; P = 3.6 × 10 −2 , respectively). Conclusions and Relevance We confirm and extend previous observations linking HLA MS susceptibility alleles with disease progression and specific clinical and magnetic resonance imaging phenotypic traits.

iCTNet (integrated Complex Traits Networks) version 2 is a Cytoscape app and database that allows researchers to build heterogeneous networks by integrating a variety of biological interactions, thus offering a systems-level view of human complex traits. iCTNet2 is built from a variety of large-scale biological datasets, collected from public repositories to facilitate the building, visualization and analysis of heterogeneous biological networks in a comprehensive fashion via the Cytoscape platform. iCTNet2 is freely available at the Cytoscape app store.

Objective To characterize the accrual of long‐term disability in a cohort of actively treated multiple sclerosis (MS) patients and to assess whether clinical and magnetic resonance imaging (MRI) data used in clinical trials have long‐term prognostic value. Methods This is a prospective study of 517 actively managed MS patients enrolled at a single center. Results More than 91% of patients were retained, with data ascertained up to 10 years after the baseline visit. At this last assessment, neurologic disability as measured by the Expanded Disability Status Scale (EDSS) was stable or improved compared to baseline in 41% of patients. Subjects with no evidence of disease activity (NEDA) by clinical and MRI criteria during the first 2 years had long‐term outcomes that were no different from those of the cohort as a whole. 25‐OH vitamin D serum levels were inversely associated with short‐term MS disease activity; however, these levels had no association with long‐term disability. At a median time of 16.8 years after disease onset, 10.7% (95% confidence interval [CI] = 7.2–14%) of patients reached an EDSS ≥ 6, and 18.1% (95% CI = 13.5–22.5%) evolved from relapsing MS to secondary progressive MS (SPMS). Interpretation Rates of worsening and evolution to SPMS were substantially lower when compared to earlier natural history studies. Notably, the NEDA 2‐year endpoint was not a predictor of long‐term stability. Finally, the data call into question the utility of annual MRI assessments as a treat‐to‐target approach for MS care. Ann Neurol 2016;80:499–510

BackgroundIn Northern European descended populations, genetic susceptibility for multiple sclerosis (MS) is associated with alleles of the human leukocyte antigen (HLA) Class II gene DRB1. Whether other major histocompatibility complex (MHC) genes contribute to MS susceptibility is controversial.Methodology/principal findingsA case control analysis was performed using 958 single nucleotide polymorphisms (SNPs) spanning the MHC assayed in two independent datasets. The discovery dataset consisted of 1,018 cases and 1,795 controls and the replication dataset was composed of 1,343 cases and 1,379 controls. The most significantly MS-associated SNP in the discovery dataset was rs3135391, a Class II SNP known to tag the HLA-DRB1*15:01 allele, the primary MS susceptibility allele in the MHC (O.R. = 3.04, p < 1 x 10(-78)). To control for the effects of the HLA-DRB1*15:01 haplotype, case control analysis was performed adjusting for this HLA-DRB1*15:01 tagging SNP. After correction for multiple comparisons (false discovery rate = .05) 52 SNPs in the Class I, II and III regions were significantly associated with MS susceptibility in both datasets using the Cochran Armitage trend test. The discovery and replication datasets were merged and subjects carrying the HLA-DRB1*15:01 tagging SNP were excluded. Association tests showed that 48 of the 52 replicated SNPs retained significant associations with MS susceptibility independently of the HLA-DRB1*15:01 as defined by the tagging SNP. 20 Class I SNPs were associated with MS susceptibility with p-values < or = 1 x 10(-8). The most significantly associated SNP was rs4959039, a SNP in the downstream un-translated region of the non-classical HLA-G gene (Odds ratio 1.59, 95% CI 1.40, 1.81, p = 8.45 x 10(-13)) and is in linkage disequilibrium with several nearby SNPs. Logistic regression modeling showed that this SNP's contribution to MS susceptibility was independent of the Class II and Class III SNPs identified in this screen.ConclusionsA MHC Class I locus contributes to MS susceptibility independently of the HLA-DRB1*15:01 haplotype.

Background When selecting mates, many vertebrate species seek partners with major histocompatibility complex (MHC) genes different from their own, presumably in response to selective pressure against inbreeding and towards MHC diversity. Attempts at replication of these genetic results in human studies, however, have reached conflicting conclusions. Results Using a multi-analytical strategy, we report validated genome-wide relationships between genetic identity and human mate choice in 930 couples of European ancestry. We found significant similarity between spouses in the MHC at class I region in chromosome 6p21, and at the odorant receptor family 13 locus in chromosome 9. Conversely, there was significant dissimilarity in the MHC class II region, near the HLA-DQA1 and -DQB1 genes. We also found that genomic regions with significant similarity between spouses show excessive homozygosity in the general population (assessed in the HapMap CEU dataset). Conversely, loci that were significantly dissimilar among spouses were more likely to show excessive heterozygosity in the general population. Conclusions This study highlights complex patterns of genomic identity among partners in unrelated couples, consistent with a multi-faceted role for genetic factors in mate choice behavior in human populations.