Immunohistochemical Detection of Potential Microbial Antigens in Granulomas in the Diagnosis of Sarcoidosis.
Tetsuo YamaguchiUlrich CostabelAndrew McDowellJosune GuzmanKeisuke UchidaKenichi OhashiYoshinobu EishiPublished in: Journal of clinical medicine (2021)
Sarcoidosis may have more than a single causative agent, including infectious and non-infectious agents. Among the potential infectious causes of sarcoidosis, Mycobacterium tuberculosis and Propionibacterium acnes are the most likely microorganisms. Potential latent infection by both microorganisms complicates the findings of molecular and immunologic studies. Immune responses to potential infectious agents of sarcoidosis should be considered together with the microorganisms detected in sarcoid granulomas, because immunologic reactivities to infectious agents reflect current and past infection, including latent infection unrelated to the cause of the granuloma formation. Histopathologic data more readily support P. acnes as a cause of sarcoidosis compared with M. tuberculosis, suggesting that normally symbiotic P. acnes leads to granuloma formation in some predisposed individuals with Th1 hypersensitivity against intracellular proliferation of latent P. acnes, which may be triggered by certain host or drug-induced conditions. Detection of bacterial nucleic acids in granulomas does not necessarily indicate co-localization of the bacterial proteins in the granulomas. In the histopathologic diagnosis of sarcoidosis, M. tuberculosis-associated and P. acnes-associated sarcoidosis will possibly be differentiated in some patients by immunohistochemistry with appropriate antibodies that specifically react with mycobacterial and propionibacterial antigens, respectively, for each etiology-based diagnosis and potential antimicrobial intervention against sarcoidosis.
Keyphrases
- mycobacterium tuberculosis
- drug induced
- liver injury
- immune response
- human health
- randomized controlled trial
- end stage renal disease
- staphylococcus aureus
- emergency department
- pulmonary tuberculosis
- chronic kidney disease
- microbial community
- dendritic cells
- inflammatory response
- newly diagnosed
- climate change
- machine learning
- hiv infected
- peritoneal dialysis
- hepatitis c virus
- prognostic factors
- deep learning
- patient reported
- sensitive detection