Plasma Metabolite Signature Classifies Male LRRK2 Parkinson's Disease Patients.

Plasma Metabolite Signature Classifies Male LRRK2 Parkinson's Disease Patients.
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DOI:
10.3390/metabo12020149
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发表时间:
2022-02-05
期刊:
影响因子:
4.1
通讯作者:
O'Day EM
O'Day EM
中科院分区:
生物学3区
文献类型:
--
作者:
Dong C;Honrao C;Rodrigues LO;Wolf J;Sheehan KB;Surface M;Alcalay RN;O'Day EM

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帕金森病(Parkinson's disease,PD)是一种进行性神经退行性疾病,可导致运动和非运动功能的丧失。诊断是基于直到疾病进展后期才出现的临床症状,此时大多数患者的多巴胺能神经元已经被破坏。虽然许多PD病例是特发性的,但已经确定了可遗传的遗传风险,包括LRRK 2基因突变,LRRK 2是一种多结构域激酶,在自噬、线粒体功能、转录、分子结构完整性、内-溶酶体系统和免疫应答中发挥作用。明确的PD诊断只能在死后进行,目前还没有非侵入性或基于血液的疾病生物标志物。在PD患者中已经发现了代谢物的改变,这表明代谢组学可能为PD诊断工具带来希望。在这项研究中,我们试图确定血浆中PD的代谢标志物。使用1H-13 C杂原子单量子相干光谱(HSQC)NMR光谱代谢组学平台结合机器学习(ML),我们测量了年龄/性别匹配的G2019 S LRRK 2突变PD患者和非PD对照的血浆代谢物。基于已知和未知代谢物的差异水平,我们能够建立ML模型并开发生物标志物反应(BoR)评分,该评分对男性LRRK 2 PD患者进行分类,准确性为79.7%,灵敏度为81.3%,特异性为78.6%。BoR评分的高准确性表明,本文描述的代谢组学/ML工作流程可进一步用于开发更大患者队列中PD的确证性诊断。PD的诊断检测将帮助临床医生及其患者快速做出明确的诊断,并最终为未来的临床试验和治疗方案提供支持。
Parkinson’s disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients’ dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.
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发表时间: 2020-05-01
影响因子: 7
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帕金森氏病的遗传结构。
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