Chronic alcohol abuse has a detrimental effect on the brain and liver. There is no effective treatment for these patients, and the mechanism underlying alcohol addiction and consequent alcohol-induced damage of the liver/brain axis remains unresolved. We compared experimental models of alcoholic liver disease (ALD) and alcohol dependence in mice and demonstrated that genetic ablation of IL-17 receptor A (IL-17ra–/–) or pharmacological blockade of IL-17 signaling effectively suppressed the increased voluntary alcohol drinking in alcohol-dependent mice and blocked alcohol-induced hepatocellular and neurological damage. The level of circulating IL-17A positively correlated with the alcohol use in excessive drinkers and was further increased in patients with ALD as compared with healthy individuals. Our data suggest that IL-17A is a common mediator of excessive alcohol consumption and alcohol-induced liver/brain injury, and targeting IL-17A may provide a novel strategy for treatment of alcohol-induced pathology.
Jun Xu, Hsiao-Yen Ma, Xiao Liu, Sara Rosenthal, Jacopo Baglieri, Ryan McCubbin, Mengxi Sun, Yukinori Koyama, Cedric G. Geoffroy, Kaoru Saijo, Linshan Shang, Takahiro Nishio, Igor Maricic, Max Kreifeldt, Praveen Kusumanchi, Amanda Roberts, Binhai Zheng, Vipin Kumar, Karsten Zengler, Donald P. Pizzo, Mojgan Hosseini, Candice Contet, Christopher K. Glass, Suthat Liangpunsakul, Hidekazu Tsukamoto, Bin Gao, Michael Karin, David A. Brenner, George F. Koob, Tatiana Kisseleva
Usage data is cumulative from February 2020 through February 2020.
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.