Biochemical Profiling of the Brain and Blood Metabolome in a Mouse Model of Prodromal Parkinson's Disease Reveals Distinct Metabolic Profiles.
Biochemical Profiling of the Brain and Blood Metabolome in a Mouse Model of Prodromal Parkinson's Disease Reveals Distinct Metabolic Profiles.
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DOI：
10.1021/acs.jproteome.8b00224
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发表时间：
2018-07-06
影响因子：
4.4
通讯作者：
Brundin P
中科院分区：
文献类型：
--
作者：
Graham SF;Rey NL;Yilmaz A;Kumar P;Madaj Z;Maddens M;Bahado-Singh RO;Becker K;Schulz E;Meyerdirk LK;Steiner JA;Ma J;Brundin P
帕金森氏症是第二常见的神经退行性疾病。尽管α-突触核蛋白聚集体的逐渐积累似乎是发病机制的核心，但在绝大多数病例中，起源不是遗传的，原因也不清楚。目前，缺乏减缓疾病进展的治疗方法，也没有强有力的生物标志物来促进这种治疗方法的发展，或作为早期诊断的辅助手段。因此，我们确定了前驱帕金森病动物模型中大脑和血清的代谢组学变化。我们对单侧在嗅球中注射预先形成的α-突触核蛋白原纤维引发的进行性突触核蛋白病在脑内传播的小鼠模型的脑组织和血清进行了生化分析。总共，我们分别使用1H NMR和靶向质谱技术准确地鉴定和定量了71种脑代谢物和182种血清代谢物。通过多变量分析，我们准确地确定了哪些代谢物在病例和对照组之间解释了最大的差异。通过途径富集分析，我们强调了大脑中显著受干扰的生化途径，并将这些途径与疾病的进展联系起来。此外，我们确定了前6个歧视性代谢物，并能够建立一个模型，能够以高精度(AUC （95% CI) = 0.861(0.755-0.968)）从健康对照中识别出发生病理的动物。我们的研究强调了代谢组学在识别帕金森病发病机制和开发疾病早期诊断生物标志物方面的效用。
Parkinson’s disease is the second most common neurodegenerative disease. In the vast majority of cases the origin is not genetic and the cause is not well understood, although progressive accumulation of α-synuclein aggregates appears central to the pathogenesis. Currently, treatments that slow disease progression are lacking and there are no robust biomarkers that can facilitate development of such treatments, or act as aids in early diagnosis. Therefore, we have defined metabolomic changes in the brain and serum in an animal model of prodromal Parkinson’s disease. We biochemically profiled the brain tissue and serum in a mouse model with progressive synucleinopathy propagation in the brain triggered by unilateral injection of preformed α-synuclein fibrils in the olfactory bulb. In total, we accurately identified and quantified 71 metabolites in brain and 182 in serum using 1H NMR and targeted mass spectrometry, respectively. Using multivariate analysis, we accurately identified which metabolites explain the most variation between cases and controls. Using pathway enrichment analysis, we highlight significantly perturbed biochemical pathways in the brain and correlate these with the progression of the disease. Further, we identified the top 6 discriminatory metabolites and were able to develop a model capable of identifying animals that developed the pathology from healthy controls with high accuracy (AUC (95% CI) = 0.861 (0.755–0.968)). Our study highlights the utility of metabolomics in identifying elements of Parkinson’s disease pathogenesis and for the development of early diagnostic biomarkers of the disease.
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影响因子：
14.8
作者：
Bosco, DA;Fowler, DM;Kelly, JW
通讯作者：
Kelly, JW
影响因子：
9.9
作者：
LeWitt, Peter A.;Li, Jia;Auinger, Peggy
通讯作者：
Auinger, Peggy
影响因子：
11.2
作者：
HATTORI, N;TANAKA, M;MIZUNO, Y
通讯作者：
MIZUNO, Y
影响因子：
14.5
作者：
Bogdanov, Mikhail;Matson, Wayne R.;Beal, M. Flint
通讯作者：
Beal, M. Flint
DOI：
10.1002/mds.26913
发表时间：
2017-03
期刊：
Movement disorders : official journal of the Movement Disorder Society
影响因子：
--
作者：
Espay AJ;Schwarzschild MA;Tanner CM;Fernandez HH;Simon DK;Leverenz JB;Merola A;Chen-Plotkin A;Brundin P;Kauffman MA;Erro R;Kieburtz K;Woo D;Macklin EA;Standaert DG;Lang AE
通讯作者：
Lang AE