Alan Edwards Pain Management Unit, McGill University Health Centre, Montreal, QC, Canada.
Canadian Center for Computational Genomics, McGill University and Genome Quebec Innovation Center, Montreal, QC, Canada.
Pain. 2019 Nov;160(11):2589-2602. doi: 10.1097/j.pain.0000000000001640.
Fibromyalgia (FM) is a prevalent syndrome, characterised by chronic widespread pain, fatigue, and impaired sleep, that is challenging to diagnose and difficult to treat. The microbiomes of 77 women with FM and that of 79 control participants were compared using 16S rRNA gene amplification and whole-genome sequencing. When comparing FM patients with unrelated controls using differential abundance analysis, significant differences were revealed in several bacterial taxa. Variance in the composition of the microbiomes was explained by FM-related variables more than by any other innate or environmental variable and correlated with clinical indices of FM. In line with observed alteration in butyrate-metabolising species, targeted serum metabolite analysis verified differences in the serum levels of butyrate and propionate in FM patients. Using machine-learning algorithms, the microbiome composition alone allowed for the classification of patients and controls (receiver operating characteristic area under the curve 87.8%). To the best of our knowledge, this is the first demonstration of gut microbiome alteration in nonvisceral pain. This observation paves the way for further studies, elucidating the pathophysiology of FM, developing diagnostic aids and possibly allowing for new treatment modalities to be explored.
纤维肌痛(FM)是一种常见的综合征,其特征为慢性广泛性疼痛、疲劳和睡眠障碍,诊断具有挑战性,治疗也很困难。我们使用 16S rRNA 基因扩增和全基因组测序比较了 77 名 FM 患者和 79 名对照参与者的微生物组。使用差异丰度分析比较 FM 患者与无关联对照时,发现几个细菌分类群存在显著差异。微生物组组成的方差更多地由与 FM 相关的变量而不是任何其他内在或环境变量来解释,并与 FM 的临床指标相关。与观察到的丁酸盐代谢物种的改变一致,靶向血清代谢物分析验证了 FM 患者血清中丁酸盐和丙酸盐水平的差异。使用机器学习算法,仅微生物组组成就可以对患者和对照进行分类(受试者工作特征曲线下面积 87.8%)。据我们所知,这是首次在非内脏疼痛中观察到肠道微生物组的改变。这一观察为进一步研究奠定了基础,阐明 FM 的病理生理学,开发诊断辅助工具,并可能探索新的治疗方法。