Research overview
The text below is the source article’s original abstract under a verified reuse license. cc by
Human endogenous retroviruses (HERVs) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV-promoting pathological conditions, including the development of autoimmunity, neurodegenerative disease and cancer. What infections trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases, Crohn's disease, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis (RA) and autoimmune thyroiditis. MAP is also associated with Alzheimer's disease (AD) and Parkinson's disease (PD). Autoimmune diabetes, MS and RA are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation, including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via the un-silencing of HERV. We examine the link between the ever-increasing number of MAP-associated diseases and the MAP/HERV intersection with these diverse medical conditions, and propose treatment opportunities based upon this association.
Scientific assessment
Research question
Assess the question within the original study’s scope.
Methods & sample
Check the source article for study design and sample details.
Key findings
An editorially approved findings summary is not yet published for this record.
Limitations
Generalizability, bias and clinical meaning require separate assessment.
Methods, samples and clinical conclusions are not inferred from bibliographic metadata.