Stoessel Daniel, Stellmann Jan-Patrick, Willing Anne, Behrens Birte, Rosenkranz Sina C, Hodecker Sibylle C, Stürner Klarissa H, Reinhardt Stefanie, Fleischer Sabine, Deuschle Christian, Maetzler Walter, Berg Daniela, Heesen Christoph, Walther Dirk, Schauer Nicolas, Friese Manuel A, Pless Ole
Metabolomic Discoveries GmbH, Potsdam, Germany.
Institut für Biochemie und Biologie, Universität Potsdam, Potsdam, Germany.
Front Hum Neurosci. 2018 Jun 4;12:226. doi: 10.3389/fnhum.2018.00226. eCollection 2018.
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson's disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.
原发性进行性多发性硬化症（PPMS）的疾病进展高度可变，预后较差，患者会出现典型的残疾累积。PPMS的这些特征使其难以诊断，目前也无法有效治疗。本研究旨在确定血浆代谢物谱，以实现PPMS的诊断及其与复发缓解型亚型（RRMS）、原发性神经退行性疾病（帕金森病，PD）和健康对照（HC）的区分，并且这些代谢物谱在疾病过程中会发生显著变化，可作为随时间推移与多发性硬化症（MS）相关神经退行性变的替代标志物。我们对血浆样本应用非靶向高分辨率代谢组学来识别PPMS特异性特征，在独立的性别和年龄匹配的PPMS和HC队列中验证我们的发现，并通过偏最小二乘判别分析（PLS-DA）建立判别模型。将该特征与性别和年龄匹配的RRMS患者、PD患者及HC进行比较。最后，我们在一个为期24个月的PPMS患者纵向队列中研究了这些代谢物。PLS-DA产生了用于分类的预测模型以及一组20个PPMS特异性信息性代谢物标记物。这些代谢物表明甘油磷脂和亚油酸途径存在疾病特异性改变。值得注意的是，甘油磷脂溶血磷脂酰胆碱（LysoPC，20:0）在观察期内显著下降。这些发现显示了诊断和疾病进程监测的潜力，并可能作为生物标志物，在未来用于评估神经保护性MS疗法的临床试验中的治疗效果。
