The migration of leukocytes into the CNS drives the neuropathology of multiple sclerosis (MS). It is likely that this penetration utilizes energy resources that remain to be defined. Using the experimental autoimmune encephalomyelitis (EAE) model of MS, we determined that macrophages within the perivascular cuff of postcapillary venules are highly glycolytic, as manifested by strong expression of lactate dehydrogenase A (LDHA), which converts pyruvate to lactate. These macrophages expressed prominent levels of monocarboxylate transporter-4 (MCT-4), which is specialized in the secretion of lactate from glycolytic cells. The functional relevance of glycolysis was confirmed by siRNA-mediated knockdown of LDHA and MCT-4, which decreased lactate secretion and macrophage transmigration. MCT-4 was in turn regulated by EMMPRIN (also known as CD147), as determined through coexpression and co-IP studies and siRNA-mediated EMMPRIN silencing. The functional relevance of MCT-4–EMMPRIN interaction was confirmed by lower macrophage transmigration in culture using the MCT-4 inhibitor α-cyano-4-hydroxy-cinnamic acid (CHCA), a cinnamon derivative. CHCA also reduced leukocyte infiltration and the clinical severity of EAE. Relevance to MS was corroborated by the strong expression of MCT-4, EMMPRIN, and LDHA in perivascular macrophages in MS brains. These results detail the metabolism of macrophages for transmigration from perivascular cuffs into the CNS parenchyma and identify CHCA and diet as potential modulators of neuroinflammation in MS.
Deepak Kumar Kaushik, Anindita Bhattacharya, Reza Mirzaei, Khalil S. Rawji, Younghee Ahn, Jong M. Rho, V. Wee Yong
Usage data is cumulative from January 2020 through January 2021.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.