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- Sawcer, Stephen, et al.
(author)
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Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
- 2011
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 476:7359, s. 214-219
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Journal article (peer-reviewed)abstract
- 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.
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- Benkert, P., et al.
(author)
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Serum neurofilament light chain for individual prognostication of disease activity in people with multiple sclerosis: a retrospective modelling and validation study
- 2022
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In: The Lancet Neurology. - 1474-4422 .- 1474-4465. ; 21:3, s. 246-257
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Journal article (peer-reviewed)abstract
- 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. © 2022 Elsevier Ltd
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- Din, Lennox, et al.
(author)
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Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes
- 2019
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In: Genetic Epidemiology. - : WILEY. - 0741-0395 .- 1098-2272. ; 43:7, s. 844-863
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Journal article (peer-reviewed)abstract
- Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p =.0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.
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- Hensiek, A E, et al.
(author)
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Familial effects on the clinical course of multiple sclerosis.
- 2007
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In: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 1526-632X .- 0028-3878. ; 68:5, s. 376-83
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Journal article (peer-reviewed)abstract
- BACKGROUND: Familial factors influence susceptibility to multiple sclerosis (MS) but it is unknown whether there are additional effects on the natural history of the disease. METHOD: We evaluated 1,083 families with > or =2 first-degree relatives with MS for concordance of age at onset, clinical course, and disease severity and investigated transmission patterns of these clinical features in affected parent-child pairs. RESULTS: There is concordance for age at onset for all families (correlation coefficient 0.14; p < 0.001), as well as for affected siblings (correlation coefficient 0.15; p < 0.001), and affected parent-child pairs (correlation coefficient 0.12; p = 0.03) when each is evaluated separately. Concordance for year of onset is present among affected siblings (correlation coefficient 0.18; p < 0.001) but not the parent-child group (correlation coefficient 0.08; p = 0.15). The clinical course is similar between siblings (kappa 0.12; p < 0.001) but not affected parents and their children (kappa -0.04; p = 0.09). This influence on the natural history is present in all clinical subgroups of relapsing-remitting, and primary and secondary progressive MS, reflecting a familial effect on episodic and progressive phases of the disease. There is no concordance for disease severity within any of the considered family groups (correlation coefficients: all families analyzed together, 0.02, p = 0.53; affected sibling group, 0.02, p = 0.61; affected parent-child group, 0.02, p = 0.69). Furthermore, there are no apparent transmission patterns of any of the investigated clinical features in affected parent-child pairs and no evidence for anticipation or effects of genetic loading. CONCLUSION: Familial factors do not significantly affect eventual disease severity. However, they increase the probability of a progressive clinical course, either from onset or after a phase of relapsing remitting disease. The familial effect is more likely to reflect genetic than environmental conditions. The results are relevant for counseling patients and have implications for the design of studies seeking to identify factors that influence the natural history of the disease.
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- Madireddy, L, et al.
(author)
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A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis
- 2019
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2236-
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Journal article (peer-reviewed)abstract
- 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.
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- Beecham, Ashley H, et al.
(author)
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Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis.
- 2013
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In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:11, s. 1353-60
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Journal article (peer-reviewed)abstract
- Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
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- Langefeld, Carl D., et al.
(author)
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Transancestral mapping and genetic load in systemic lupus erythematosus
- 2017
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 8
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Journal article (peer-reviewed)abstract
- Systemic lupus erythematosus (SLE) is an autoimmune disease with marked gender and ethnic disparities. We report a large transancestral association study of SLE using Immunochip genotype data from 27,574 individuals of European (EA), African (AA) and Hispanic Amerindian (HA) ancestry. We identify 58 distinct non-HLA regions in EA, 9 in AA and 16 in HA (similar to 50% of these regions have multiple independent associations); these include 24 novel SLE regions (P < 5 x 10(-8)), refined association signals in established regions, extended associations to additional ancestries, and a disentangled complex HLA multigenic effect. The risk allele count (genetic load) exhibits an accelerating pattern of SLE risk, leading us to posit a cumulative hit hypothesis for autoimmune disease. Comparing results across the three ancestries identifies both ancestry-dependent and ancestry-independent contributions to SLE risk. Our results are consistent with the unique and complex histories of the populations sampled, and collectively help clarify the genetic architecture and ethnic disparities in SLE.
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- Creary, Lisa E., et al.
(author)
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Next-Generation Sequencing Identifies Extended HLA Class I and II Haplotypes Associated With Early-Onset and Late-Onset Myasthenia Gravis in Italian, Norwegian, and Swedish Populations
- 2021
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In: Frontiers in Immunology. - : Frontiers Media S.A.. - 1664-3224. ; 12
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Journal article (peer-reviewed)abstract
- Genetic susceptibility to myasthenia gravis (MG) associates with specific HLA alleles and haplotypes at the class I and II regions in various populations. Previous studies have only examined alleles at a limited number of HLA loci that defined only broad serotypes or alleles defined at the protein sequence level. Consequently, genetic variants in noncoding and untranslated HLA gene segments have not been fully explored but could also be important determinants for MG. To gain further insight into the role of HLA in MG, we applied next-generation sequencing to analyze sequence variation at eleven HLA genes in early-onset (EO) and late-onset (LO) non-thymomatous MG patients positive for the acetylcholine receptor (AChR) antibodies and ethnically matched controls from Italy, Norway, and Sweden. For all three populations, alleles and haplotype blocks present on the ancestral haplotype AH8.1 were associated with risk in AChR-EOMG patients. HLA-B*08:01:01:01 was the dominant risk allele in Italians (OR = 3.28, P = 1.83E−05), Norwegians (OR = 3.52, P = 4.41E−16), and in Swedes HLA-B*08:01 was the primary risk allele (OR = 4.24, P <2.2E-16). Protective alleles and haplotype blocks were identified on the HLA-DRB7, and HLA-DRB13.1 class II haplotypes in Italians and Norwegians, whereas in Swedes HLA-DRB7 exhibited the main protective effect. For AChR-LOMG patients, the HLA-DRB15.1 haplotype and associated alleles were significantly associated with susceptibility in all groups. The HLA-DR13–HLA-DR–HLA-DQ haplotype was associated with protection in all AChR-LOMG groups. This study has confirmed and extended previous findings that the immunogenetic predisposition profiles for EOMG and LOMG are distinct. In addition, the results are consistent with a role for non-coding HLA genetic variants in the pathogenesis of MG.
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