scholarly journals Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

10.1186/gm217 ◽  
2011 ◽  
Vol 3 (1) ◽  
pp. 3 ◽  
Author(s):  
Joanne H Wang ◽  
Derek Pappas ◽  
Philip L De Jager ◽  
Daniel Pelletier ◽  
Paul IW de Bakker ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Genetic Risk ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Association Data

scholarly journals What is Next for the Genetics of Multiple Sclerosis?

2011 ◽  
Vol 2011 ◽  
pp. 1-3 ◽  
Author(s):  
Sreeram V. Ramagopalan ◽  
David A. Dyment
Keyword(s):  
Multiple Sclerosis ◽  
Genetic Risk ◽  
Neurological Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
New Genes ◽  
Histocompatibility Complex ◽  
Genome Wide ◽  
The Common

We review here our current understanding of the genetic aetiology of the common complex neurological disease multiple sclerosis (MS). The strongest genetic risk factor for MS is the major histocompatibility complex which was identified in the 1970s. In 2011, after a number of genome-wide association studies have been completed and have identified approximately 20 new genes for MS, we ask the question—what is next for the genetics of MS?

scholarly journals A higher burden of multiple sclerosis genetic risk confers an earlier onset

2020 ◽  
Author(s):  
Elina Misicka ◽  
Mary F. Davis ◽  
Woori Kim ◽  
Steven W. Brugger ◽  
Jeremy Beales ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Association Analysis ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Age At Onset ◽  
Genome Wide Association ◽  
Multiple Sclerosis Risk ◽  
Risk Variants ◽  
Genome Wide

AbstractMultiple sclerosis is a neurodegenerative, autoimmune disease characterized by inrreversible neurological disability. The age at onset of multiple sclerosis is an objective and influential predictor of the evolution of multiple sclerosis independent of disease duration. Little is known about the mechanisms contributing to variation in onset age of multiple sclerosis, though HLA-DRB1*15:01, the predominant risk variant, confers an earlier onset. Here we present an age at onset genome-wide association analysis for 9.2 million variants, including gene-based and pathway enrichment analyses, for 3,495 cases who were non-Latinx white with onset ≥18 years. We investigated whether a higher burden of multiple sclerosis risk variants conferred an earlier age at onset for combinations of HLA-DRB1*15:01 alleles and quintiles of a genetic risk score for 200 risk variants that reside outside the major histocompatibility complex. The study population had a mean age at onset of 32 years, 29% was male, and 46% were HLA-DRB1*15:01 carriers. HLA-DRB1*15:01 carriers were on average one year younger at onset than non-carriers (p<0.001); a similar effect was observed for a 10-risk-allele increase in the genetic risk score (p<1×10-8). Those in the highest genetic risk score quintile (n=717) were on average 2.5 years younger at onset than those in the lowest quintile (n=698; p=1.2×10-7). For those with the greatest genetic risk burden (highest genetic risk score quintile with two HLA-DRB1*15:01 alleles) were on average five years younger at onset (p=0.002) than those with the lowest genetic risk burden (lowest genetic risk score quintile with no HLA-DRB1*15:01 alleles). There was an apparent inverse relationship between the genetic multiple sclerosis risk burden and age at onset of multiple sclerosis (p<5×10-8). We did not observe any individual variants reaching genome-wide significance in the genome-wide association analysis of age at onset. The most significantly associated independent genic loci (p<5×10-6) were located within HLA-DQB1, COL21A1, LINC01484, UBR3, and CSMD1. At the gene-level, the most significant associations (p<5×10-5) were for SSB, TRAFD1, HECTD2, MMP8, NAA25 and UBR3. There was an enrichment of genes involved in adaptive and innate immunity, specifically genes in the complement pathway, and genes involved in synapses and collagen biosynthesis. In summary, we demonstrated a significant gradient between elevated genetic risk burden and an earlier onset of multiple sclerosis.

scholarly journals Treatment- and population-specific genetic risk factors for anti-drug antibodies against interferon-beta: a GWAS

BMC Medicine ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Till F. M. Andlauer ◽  
◽  
Jenny Link ◽  
Dorothea Martin ◽  
Malin Ryner ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Sclerosis ◽  
Genetic Risk ◽  
Prediction Models ◽  
Genetic Risk Factors ◽  
Genome Wide Association ◽  
Risk Haplotype ◽  
Interferon Β ◽  
Genome Wide ◽  
Multiple Sclerosis Patients

Abstract Background Upon treatment with biopharmaceuticals, the immune system may produce anti-drug antibodies (ADA) that inhibit the therapy. Up to 40% of multiple sclerosis patients treated with interferon β (IFNβ) develop ADA, for which a genetic predisposition exists. Here, we present a genome-wide association study on ADA and predict the occurrence of antibodies in multiple sclerosis patients treated with different interferon β preparations. Methods We analyzed a large sample of 2757 genotyped and imputed patients from two cohorts (Sweden and Germany), split between a discovery and a replication dataset. Binding ADA (bADA) levels were measured by capture-ELISA, neutralizing ADA (nADA) titers using a bioassay. Genome-wide association analyses were conducted stratified by cohort and treatment preparation, followed by fixed-effects meta-analysis. Results Binding ADA levels and nADA titers were correlated and showed a significant heritability (47% and 50%, respectively). The risk factors differed strongly by treatment preparation: The top-associated and replicated variants for nADA presence were the HLA-associated variants rs77278603 in IFNβ-1a s.c.- (odds ratio (OR) = 3.55 (95% confidence interval = 2.81–4.48), p = 2.1 × 10−26) and rs28366299 in IFNβ-1b s.c.-treated patients (OR = 3.56 (2.69–4.72), p = 6.6 × 10−19). The rs77278603-correlated HLA haplotype DR15-DQ6 conferred risk specifically for IFNβ-1a s.c. (OR = 2.88 (2.29–3.61), p = 7.4 × 10−20) while DR3-DQ2 was protective (OR = 0.37 (0.27–0.52), p = 3.7 × 10−09). The haplotype DR4-DQ3 was the major risk haplotype for IFNβ-1b s.c. (OR = 7.35 (4.33–12.47), p = 1.5 × 10−13). These haplotypes exhibit large population-specific frequency differences. The best prediction models were achieved for ADA in IFNβ-1a s.c.-treated patients. Here, the prediction in the Swedish cohort showed AUC = 0.91 (0.85–0.95), sensitivity = 0.78, and specificity = 0.90; patients with the top 30% of genetic risk had, compared to patients in the bottom 30%, an OR = 73.9 (11.8–463.6, p = 4.4 × 10−6) of developing nADA. In the German cohort, the AUC of the same model was 0.83 (0.71–0.92), sensitivity = 0.80, specificity = 0.76, with an OR = 13.8 (3.0–63.3, p = 7.5 × 10−4). Conclusions We identified several HLA-associated genetic risk factors for ADA against interferon β, which were specific for treatment preparations and population backgrounds. Genetic prediction models could robustly identify patients at risk for developing ADA and might be used for personalized therapy recommendations and stratified ADA screening in clinical practice. These analyses serve as a roadmap for genetic characterizations of ADA against other biopharmaceutical compounds.

scholarly journals Treatment- and population-specific genetic risk factors for anti-drug antibodies against interferon-beta

2020 ◽  
Author(s):  
Till F. M. Andlauer ◽  
Jenny Link ◽  
Dorothea Martin ◽  
Malin Ryner ◽  
Christina Hermanrud ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Sclerosis ◽  
Genetic Risk ◽  
Prediction Models ◽  
Genetic Risk Factors ◽  
Genome Wide Association ◽  
Risk Haplotype ◽  
Interferon Β ◽  
Genome Wide ◽  
Multiple Sclerosis Patients

Background: Upon treatment with biopharmaceuticals, the immune system may produce anti-drug antibodies (ADA) that inhibit the therapy. Up to 40% of multiple sclerosis patients treated with interferon β (IFNβ) develop ADA, for which a genetic predisposition exists. Here, we present a genome-wide association study on ADA and predict the occurrence of antibodies in multiple sclerosis patients treated with different interferon β preparations. Methods: We analyzed a large sample of 2,757 genotyped and imputed patients from two cohorts, split between a discovery and a replication dataset. Binding ADA (bADA) levels were measured by capture-ELISA, neutralizing ADA (nADA) titers using a bioassay. Genome-wide association analyses were conducted stratified by cohort and treatment preparation, followed by fixed-effects meta-analysis. Results: Binding ADA levels and nADA titers were correlated and showed a significant heritability (47% and 50%, respectively). The risk factors differed strongly by treatment preparation: The top-associated and replicated variants for nADA presence were the HLA-associated variants rs77278603 in IFNβ-1a s.c.- (odds ratio (OR)=3.55 (95% confidence interval=2.81-4.48), p=2.1x10-26) and rs28366299 in IFNβ-1b s.c.-treated patients (OR=3.56 (2.69-4.72), p=6.6x10-19). The rs77278603-correlated HLA haplotype DR15-DQ6 conferred risk specifically for IFNβ-1a s.c. (OR=2.88 (2.29-3.61), p=7.4x10-20) while DR3-DQ2 was protective (OR=0.37 (0.27-0.52), p=3.7x10-09). The haplotype DR4-DQ3 was the major risk haplotype for IFNβ-1b s.c. (OR=7.35 (4.33-12.47), p=1.5x10-13). These haplotypes exhibit large population-specific frequency differences. In a cohort of IFNβ-1a s.c.-treated patients, prediction models for nADA reached an AUC of 0.91 (0.85-0.95), a sensitivity of 0.78, and a specificity of 0.90. Patients with the top 30% of genetic risk had, compared to patients in the bottom 30%, an OR of 73.9 (11.8 463.6, p=4.4x10-06) of developing nADA. Conclusions: We identified several HLA-associated genetic risk factors for ADA against interferon β, which were specific for treatment preparations and population backgrounds. Genetic prediction models could robustly identify patients at risk for developing ADA and might be used for personalized therapy recommendations and stratified ADA screening in clinical practice. These analyses serve as a roadmap for genetic characterizations of ADA against other biopharmaceutical compounds.

scholarly journals A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e63300 ◽  
Author(s):  
Rosella Mechelli ◽  
Renato Umeton ◽  
Claudia Policano ◽  
Viviana Annibali ◽  
Giulia Coarelli ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Genome Wide Association ◽  
Aggregate Analysis ◽  
Genome Wide ◽  
Association Data
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