Association of caffeine and related analytes with resistance to Parkinson disease among <i>LRRK2</i> mutation carriers
Neurology(2020)
摘要
ObjectiveTo identify markers of resistance to developing Parkinson disease (PD) among LRRK2 mutation carriers (LRRK2+), we carried out metabolomic profiling in individuals with PD and unaffected controls (UC), with and without the LRRK2 mutation.MethodsPlasma from 368 patients with PD and UC in the LRRK2 Cohort Consortium (LCC), comprising 118 LRRK2+/PD+, 115 LRRK2+/UC, 70 LRRK2−/PD+, and 65 LRRK2−/UC, and CSF available from 68 of them, were analyzed by liquid chromatography with mass spectrometry. For 282 analytes quantified in plasma and CSF, we assessed differences among the 4 groups and interactions between LRRK2 and PD status, using analysis of covariance models adjusted by age, study site cohort, and sex, with p value corrections for multiple comparisons.ResultsPlasma caffeine concentration was lower in patients with PD vs UC (p < 0.001), more so among LRRK2+ carriers (by 76%) than among LRRK2− participants (by 31%), with significant interaction between LRRK2 and PD status (p = 0.005). Similar results were found for caffeine metabolites (paraxanthine, theophylline, 1-methylxanthine) and a nonxanthine marker of coffee consumption (trigonelline) in plasma, and in the subset of corresponding CSF samples. Dietary caffeine was also lower in LRRK2+/PD+ compared to LRRK2+/UC with significant interaction effect with the LRRK2+ mutation (p < 0.001).ConclusionsMetabolomic analyses of the LCC samples identified caffeine, its demethylation metabolites, and trigonelline as prominent markers of resistance to PD linked to pathogenic LRRK2 mutations, more so than to idiopathic PD. Because these analytes are known both as correlates of coffee consumption and as neuroprotectants in animal PD models, the findings may reflect their avoidance by those predisposed to develop PD or their protective effects among LRRK2 mutation carriers.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn