Genetic burden of common variants in progressive and bout-onset multiple sclerosis

Sorosina, Melissa; Brambilla, Paola; Clarelli, Ferdinando; Barizzone, Nadia; Lupoli, Sara; Guaschino, Clara; Osiceanu, Ana Maria; Moiola, Lucia; Ghezzi, Angelo; Coniglio, Gabriella; Patti, Francesco; Mancardi, Gianluigi; Manunta, Paolo; Glorioso, Nicola; Guerini, Franca Rosa; Bergamaschi, Roberto; Perla, Franco; Martinelli, Vittorio; Cusi, Daniele; Leone, Maurizio; Comi, Giancarlo; D’Alfonso, Sandra; Boneschi, Filippo Martinelli

doi:10.1177/1352458513512707

Cited by 11 publications

(14 citation statements)

References 31 publications

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“…This is in agreement with previous studies based on a smaller number of risk loci in which no difference in MS risk was observed between BOMS and PPMS patients, 2,7-10 except for a difference between these disease course groups in male patients only in one study. 10 Our findings also correspond to what is seen in family studies, where it was shown that affected family members do not necessarily have the same clinical course, 22 but do present with similar genetic risk scores. 7,8 A pathological hallmark of MS is intrathecal IgG synthesis, which can be measured in a qualitative (OCB status) or quantitative (IgG index) way.…”

Section: Discussionsupporting

confidence: 93%

Burden of risk variants correlates with phenotype of multiple sclerosis

2015

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Section: Discussionsupporting

confidence: 93%

Burden of risk variants correlates with phenotype of multiple sclerosis

2015

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“…Quality controls were performed as described elsewhere. 5 , 12 Whenever a specific SNP was absent in one of the arrays, the best available proxy according to HapMap release 24 was considered for the analyses; in this case, the r 2 value between the original and proxy SNP was included in the wGRS calculation. The score was also calculated after the exclusion of the HLA polymorphism in order to evaluate the contribution of non-HLA risk variants (wGRS–non-HLA).…”

Section: Methodsmentioning

confidence: 99%

Impact of MS genetic loci on familial aggregation, clinical phenotype, and disease prediction

Esposito

Guaschino

Sorosina

et al. 2015

Neurol Neuroimmunol Neuroinflamm

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Objective:To investigate the role of known multiple sclerosis (MS)-associated genetic variants in MS familial aggregation, clinical expression, and accuracy of disease prediction in sporadic and familial cases.Methods:A total of 1,443 consecutive patients were screened for MS and familial autoimmune history in a hospital-based Italian cohort. Among them, 461 sporadic and 93 familial probands were genotyped for 107 MS-associated polymorphisms. Their effect sizes were combined to calculate the weighted genetic risk score (wGRS).Results:Family history of MS was reported by 17.2% of probands, and 33.8% reported a familial autoimmune disorder, with autoimmune thyroiditis and psoriasis being the most frequent. No difference in wGRS was observed between sporadic and familial MS cases. In contrast, a lower wGRS was observed in probands with greater familial aggregation (>1 first-degree relative or >2 relatives with MS) (p = 0.03). Also, female probands of familial cases with greater familial aggregation had a lower wGRS than sporadic cases (p = 0.0009) and male probands of familial cases (p = 0.04). An inverse correlation between wGRS and age at onset was observed (p = 0.05). The predictive performance of the genetic model including all known MS variants was modest but greater in sporadic vs familial cases (area under the curve = 0.63 and 0.57).Conclusions:Additional variants outside the known MS-associated loci, rare variants, and/or environmental factors may explain disease occurrence within families; in females, hormonal and epigenetic factors probably have a predominant role in explaining familial aggregation. The inclusion of these additional factors in future versions of aggregated genetic measures could improve their predictive ability.

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“…. Notably, no study has been able to identify consistently a significant difference in genetic burden or variants between relapsing and progressive‐onset MS …”

Section: Cause Versus Course – Are the Risk Factors Different?mentioning

confidence: 99%

Environmental and genetic risk factors for MS: an integrated review

Waubant

Lucas

Mowry

et al. 2019

Ann Clin Transl Neurol

217

184

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Recent findings have provided a molecular basis for the combined contributions of multifaceted risk factors for the onset of multiple sclerosis (MS). MS appears to start as a chronic dysregulation of immune homeostasis resulting from complex interactions between genetic predispositions, infectious exposures, and factors that lead to pro‐inflammatory states, including smoking, obesity, and low sun exposure. This is supported by the discovery of gene–environment (GxE) interactions and epigenetic alterations triggered by environmental exposures in individuals with particular genetic make‐ups. It is notable that several of these pro‐inflammatory factors have not emerged as strong prognostic indicators. Biological processes at play during the relapsing phase of the disease may result from initial inflammatory‐mediated injury, while risk factors for the later phase of MS, which is weighted toward neurodegeneration, are not yet well defined. This integrated review of current evidence guides recommendations for clinical practice and highlights research gaps.

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Genetic burden of common variants in progressive and bout-onset multiple sclerosis

Abstract: Our results suggest that the liability of disease is better captured by common genetic variants in BOMS than PrMS cases. The absence of inflammatory activity and male gender further raise the difference between clinical courses.

Cited by 11 publications

References 31 publications

Burden of risk variants correlates with phenotype of multiple sclerosis

Burden of risk variants correlates with phenotype of multiple sclerosis

Impact of MS genetic loci on familial aggregation, clinical phenotype, and disease prediction

Environmental and genetic risk factors for MS: an integrated review

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