A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis

Abstract Background There exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules. Result We assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omic integration of 20 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor-associated genes from several independent cohorts. Our benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS genes. The multi-omic case study using MS data revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module were differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10− 47) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS. Conclusions We believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omic approaches for complex diseases.

Download Full-text

A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis

10.1101/2020.10.26.351783 ◽

2020 ◽

Author(s):

Tejaswi V.S. Badam ◽

Hendrik A. de Weerd ◽

David Martínez-Enguita ◽

Tomas Olsson ◽

Lars Alfredsson ◽

...

Keyword(s):

Risk Factors ◽

Multiple Sclerosis ◽

Enrichment Analysis ◽

Robust Identification ◽

Systematic Assessment ◽

Genome Wide ◽

Disease Module ◽

Practical Guidelines ◽

Disease Modules

ABSTRACTBackgroundThere are few (if any) practical guidelines for predictive and falsifiable multi-omics data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules.MethodsWe assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omics integration of 19 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor associated genes from several independent cohorts.ResultsOur benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS-genes. The multi-omics case study using MS revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module was differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10-47) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS.ConclusionWe believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omics approaches for complex diseases.

Download Full-text

Enrichment analysis of GWAS data in autoimmunity delineates the multiple sclerosis-Epstein Barr virus association

10.1101/2021.06.06.447253 ◽

2021 ◽

Author(s):

Rosella Mechelli ◽

Renato Umeton ◽

Virginia Rinaldi ◽

Gianmarco Bellucci ◽

Rachele Bigi ◽

...

Keyword(s):

Multiple Sclerosis ◽

Epstein Barr Virus ◽

Association Studies ◽

Enrichment Analysis ◽

Gwas Data ◽

Genome Wide Association Studies ◽

Barr Virus ◽

Genome Wide ◽

Gene Modules ◽

Epstein Barr

We exploited genetic information to assess non-genetic influences in autoimmunity. We isolated gene modules whose products physically interact with environmental exposures related to autoimmunity, and analyzed their nominal statistical evidence of association with autoimmune and non-autoimmune diseases in genome-wide association studies (GWAS) data. Epstein Barr virus (EBV) and other Herpesviruses interactomes emerged as specifically associated with multiple sclerosis (MS), possibly under common regulatory mechanisms. Analyses of MS blood and brain transcriptomes, cytofluorimetric studies of endogenous EBV-infected lymphoblastoid lines, and lesion immunohistochemistry, confirmed a dysregulation of MS-associated EBV interactors, suggesting their contribution to CD40 signaling alterations in MS. These interactors resulted enriched in modules from inherited axonopathies-causing genes, supporting a link between EBV and neurodegeneration in MS, in accord with the observed transcriptomic dysregulations in MS brains. They were also enriched with top-ranked pharmaceutical targets prioritized on a genetic basis. This study delineates a disease-specific influence of herpesviruses on MS biology.

Download Full-text

A genome-wide association study (GWAS) in the Japanese population reveals novel genetic risk factors for multiple sclerosis and neuromyelitis optica

Journal of the Neurological Sciences ◽

10.1016/j.jns.2015.08.1085 ◽

2015 ◽

Vol 357 ◽

pp. e308

Author(s):

J. Kira ◽

T. Matsushita ◽

S. Sato ◽

K. Yamamoto

Keyword(s):

Risk Factors ◽

Multiple Sclerosis ◽

Association Study ◽

Neuromyelitis Optica ◽

Genetic Risk ◽

Japanese Population ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide ◽

A Genome

Download Full-text

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

BMC Medicine ◽

10.1186/s12916-020-01769-6 ◽

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.

Download Full-text

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

10.1101/2020.05.01.20086033 ◽

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.

Download Full-text

The neurogenic bladder in multiple sclerosis: review of the literature and proposal of management guidelines

Multiple Sclerosis Journal ◽

10.1177/1352458506075651 ◽

2007 ◽

Vol 13 (7) ◽

pp. 915-928 ◽

Cited By ~ 240

Author(s):

Marianne de Sèze ◽

Alain Ruffion ◽

Pierre Denys ◽

Pierre-Alain Joseph ◽

Brigitte Perrouin-Verbe ◽

...

Keyword(s):

Risk Factors ◽

Multiple Sclerosis ◽

Urinary Tract ◽

Neurogenic Bladder ◽

High Amplitude ◽

Upper Urinary Tract ◽

Review Of The Literature ◽

Indwelling Catheter ◽

Practical Guidelines

Vesicourethral dysfunction is very frequent in multiple sclerosis (MS) and has functional consequences for patients' quality of life and also an organic impact following complications of the neurogenic bladder on the upper urinary tract. While the functional impact and its management are well documented in the literature, the organic impact remains underestimated and there are no consensual practical guidelines for the screening and prevention of MS neurogenic bladder complications. The aim of this review of the literature, focused on identifying the risk factors of urinary tract complications in MS, is to put forward well informed considerations to help in the definition of practical guidelines for the follow-up of the neurogenic bladder in MS in order to improve its prevention and patient management. Four main risk factors have been identified for upper urinary tract damage: the duration of MS, the presence of an indwelling catheter, high-amplitude neurogenic detrusor contractions and permanent high detrusor pressure. Detrusor-sphincter dyssynergia, age over 50 and male sex may form three additional risk factors. Recommendations for long-term urological follow-up, taking into account these specific risks are constructed according to the procedures recommended by the French Health Authorities. Multiple Sclerosis 2007; 13: 915-928. http://msj.sagepub.com

Download Full-text

Genome-wide analysis of DNA methylation and risk of cardiovascular disease in a Chinese population

BMC Cardiovascular Disorders ◽

10.1186/s12872-021-02001-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yan Gao ◽

Huifang Pang ◽

Bowang Chen ◽

ChaoQun Wu ◽

Yanping Wang ◽

...

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Dna Methylation ◽

High Risk ◽

Area Under The Curve ◽

Independent Set ◽

Enrichment Analysis ◽

Cardiac Risk ◽

Genome Wide ◽

Baseline Characteristics

Abstract Background Systemic studies of association of genome-wide DNA methylated sites with cardiovascular disease (CVD) in prospective cohorts are lacking. Our aim was to identify DNA methylation sites associated with the risk of CVD and further investigate their potential predictive value in CVD development for high-risk subjects. Methods We performed an epigenome-wide association study (EWAS) to identify CpGs related to CVD development in a Chinese population.We adopted a nested case–control design based on data from China PEACE Million Persons Project. A total of 83 cases who developed CVD events during follow-up and 83 controls who were matched with cases by age, sex, BMI, ethnicity, medications treatment and behavior risk factors were included in the discovery stage. Genome-wide DNA methylation from whole blood was detected using Infinium Human Methylation EPIC Beadchip (850 K). For significant CpGs [FDR(false discovery rate) < 0.005], we further validated in an independent cohort including 38 cases and 38 controls. Results In discovery set, we identified 8 significant CpGs (FDR < 0.005) associated with the risk of CVD after adjustment for cell components, demographic and cardiac risk factors and the first 5 principal components. Two of these identified CpGs (cg06901278 and cg09306458 in UACA) were replicated in another independent set (p < 0.05). Enrichment analysis in 787 individual genes from 1036 CpGs in discovery set revealed a significant enrichment for anatomical structure homeostasis as well as regulation of vesicle-mediated transport. Receiver operating characteristic (ROC) analysis showed that the model combined 8 CVD-related CpGs with baseline characteristics showed much better predictive effect for CVD occurrence compared with the model with baseline characteristics only [AUC (area under the curve) = 0.967, 95% CI (0.942 − 0.991); AUC = 0.621, 95% CI (0.536 − 0.706); p = 9.716E-15]. Conclusions Our study identified the novel CpGs associated with CVD development and revealed their additional predictive power in the risk of CVD for high-risk subjects.

Download Full-text