Multiple sclerosis and breast cancer

O'malley, P; Mulla, Zuber D.; Nešić, Olivera

doi:10.1016/j.jns.2015.06.033

Cited by 4 publications

(2 citation statements)

References 35 publications

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“…The etiology of MS is unclear, but it is currently thought to be an immune-mediated demyelinating disease involving the central nervous system ( Mariottini et al, 2022 ; Stampanoni Bassi et al, 2022 ). MS and breast cancer share some common features; most notably, the incidence of both diseases is much higher in women than in men ( O’Malley et al, 2015 ). Numerous studies have explored the relationship between them, but whether MS affects the incidence of breast cancer remains controversial ( Hajiebrahimi et al, 2016 ; Zecca et al, 2021 ; Groome et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies

Fang

Zhang

Zhou

et al. 2023

Front. Neuroinform.

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BackgroundSeveral observational studies have explored the relationships between multiple sclerosis (MS) and breast cancer; however, whether an association exists remains unknown.MethodsWe conducted a meta-analysis of observational studies and Mendelian randomization (MR) based on genetic variants to identify the relationship between MS and breast cancer. The observational studies were searched from PubMed, Embase, Web of Science, and Scopus to assess the relationship between MS and breast cancer from inception to 07 Nov 2022. Moreover, we explored the association between genetically pre-disposed MS and breast cancer risk based on an MR study. The summary analysis for MS from two separate databases [International Multiple Sclerosis Genetics Consortium (IMSGC), FinnGen] and the summary analysis for breast cancer from Breast Cancer Association Consortium.ResultsFifteen cohort studies involving 173,565 female MS patients were included in this meta-analysis. The correlation between MS and breast cancer was not statistically significant [relative ratio (RR) = 1.08, 95% confidence interval (CI) = 0.99–1.17]. In the MR analysis, we did not observe causal associations of genetically determined MS with breast cancer and its subtypes from both the IMSGC and FinnGen datasets.ConclusionThe meta-analysis of observational and MR based on genetic variants does not support the correlation between MS and breast cancer.

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Section: Discussionmentioning

confidence: 99%

Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies

Fang

Zhang

Zhou

et al. 2023

Front. Neuroinform.

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“…Again, opposite tendencies are described in the literature for this connection, where the order of appearance of the disease seems to drive the comorbidity pattern. It has been shown that breast cancer patients are 45% less likely to develop multiple sclerosis 51 . On the other hand, multiple sclerosis patients have been shown to have a significantly increased risk of breast cancer, presumably driven by immunosuppression derived from the associated treatment 52 .…”

Section: Discussionmentioning

confidence: 99%

Patient stratification reveals the molecular basis of disease comorbidities

Urda-García

Sánchez-Valle

Lepore

et al. 2021

Preprint

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Epidemiological evidence shows that some diseases tend to co-occur; more exactly, certain groups of patients with a given disease are at a higher risk of developing a specific secondary condition. Despite the considerable interest, only a small number of connections between comorbidities and molecular processes have been identified. Here we develop a new approach to generate a disease network that uses the accumulating RNA-seq data on human diseases to significantly match a large number of known comorbidities, providing plausible biological models for such co-occurrences. Furthermore, 64% of the known disease pairs can be explained by analysing groups of patients with similar expression profiles, highlighting the importance of patient stratification in the study of comorbidities. These results solidly support the existence of molecular mechanisms behind many of the known comorbidities. All the information can be explored on a large scale and in detail at http://disease-perception.bsc.es/rgenexcom/.

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