A dysregulated endocannabinoid-eicosanoid network supports pathogenesis in a mouse model of Alzheimer's disease.
A dysregulated endocannabinoid-eicosanoid network supports pathogenesis in a mouse model of Alzheimer's disease.
复制标题
DOI:
10.1016/j.celrep.2012.05.001
复制
发表时间:
2012-06-28
期刊:
影响因子:
8.8
通讯作者:
Samad TA
中科院分区:
文献类型:
--
作者:
Piro JR;Benjamin DI;Duerr JM;Pi Y;Gonzales C;Wood KM;Schwartz JW;Nomura DK;Samad TA
Although inflammation in the brain is meant as a defense mechanism against neurotoxic stimuli, increasing evidence suggests that uncontrolled, chronic and persistent inflammation contributes to neurodegeneration. Most neurodegenerative diseases have now been associated with chronic inflammation, including Alzheimer’s disease (AD). Whether anti-inflammatory approaches can be used to treat AD, however, is a major unanswered question. We recently demonstrated that monoacylglycerol lipase (MAGL) hydrolyzes endocannabinoids to generate the primary arachidonic acid pool for neuroinflammatory prostaglandins. In this study, we show that genetic inactivation of MAGL attenuates neuroinflammation and lowers amyloid βlevels and plaques, in an AD mouse model. We also find that pharmacological blockade of MAGL recapitulates the cytokine lowering effects through reduced prostaglandin production, rather than enhanced endocannabinoid signaling. Our findings thus reveal a heretofore unrecognized role of MAGL in modulating neuroinflammation and amyloidosis in AD etiology, and put forth MAGL inhibitors as a potential next-generation strategy for combatting AD.
登录
查看更多内容
DOI:
10.18632/aging.100021
发表时间:
2009-02-11
期刊:
Aging
影响因子:
--
作者:
Choi SH;Bosetti F
通讯作者:
Bosetti F
DOI:
10.4049/jimmunol.1100620
发表时间:
2011-12-15
期刊:
Journal of immunology (Baltimore, Md. : 1950)
影响因子:
--
作者:
Kitazawa M;Cheng D;Tsukamoto MR;Koike MA;Wes PD;Vasilevko V;Cribbs DH;LaFerla FM
通讯作者:
LaFerla FM
影响因子:
4.4
作者:
Liu, Shirong;Liu, Yang;Fassbender, Klaus
通讯作者:
Fassbender, Klaus
影响因子:
9.3
作者:
Martín-Moreno AM;Brera B;Spuch C;Carro E;García-García L;Delgado M;Pozo MA;Innamorato NG;Cuadrado A;de Ceballos ML
通讯作者:
de Ceballos ML
影响因子:
3.6
作者:
Chanda, Pranab K.;Gao, Ying;Samad, Tarek A.
通讯作者:
Samad, Tarek A.