The Role of Mitochondrial Mutations in Chronification of Inflammation: Hypothesis and Overview of Own Data.
Alexander N OrekhovNikita G NikiforovAndrey V OmelchenkoVasily V SinyovIgor A SobeninAndrey Y VinokurovVarvara A OrekhovaPublished in: Life (Basel, Switzerland) (2022)
Chronic human diseases, especially age-related disorders, are often associated with chronic inflammation. It is currently not entirely clear what factors are responsible for the sterile inflammatory process becoming chronic in affected tissues. This process implies impairment of the normal resolution of the inflammatory response, when pro-inflammatory cytokine production ceases and tissue repair process begins. The important role of the mitochondria in the correct functioning of innate immune cells is currently well recognized, with mitochondrial signals being an important component of the inflammatory response regulation. In this work, we propose a hypothesis according to which mitochondrial DNA (mtDNA) mutations may play a key role in rendering certain cells prone to prolonged pro-inflammatory activation, therefore contributing to chronification of inflammation. The affected cells become sites of constant pro-inflammatory stimulation. The study of the distribution of atherosclerotic lesions on the surface of the arterial wall samples obtained from deceased patients revealed a focal distribution of lesions corresponding to the distribution of cells with altered morphology that are affected by mtDNA mutations. These observations support the proposed hypothesis and encourage further studies.
Keyphrases
- oxidative stress
- mitochondrial dna
- induced apoptosis
- inflammatory response
- copy number
- cell cycle arrest
- immune response
- cell death
- gene expression
- end stage renal disease
- endothelial cells
- endoplasmic reticulum stress
- signaling pathway
- lipopolysaccharide induced
- newly diagnosed
- ejection fraction
- dna methylation
- electronic health record
- machine learning
- lps induced
- peritoneal dialysis
- drug induced
- toll like receptor
- big data
- deep learning
- patient reported outcomes
- genome wide
- reactive oxygen species