Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
Mol Neurodegener. 2012 May 31;7:26. doi: 10.1186/1750-1326-7-26.
The search for biomarkers in Parkinson's disease (PD) is crucial to identify the disease early and monitor the effectiveness of neuroprotective therapies. We aim to assess whether a gene signature could be detected in blood from early/mild PD patients that could support the diagnosis of early PD, focusing on genes found particularly altered in the substantia nigra of sporadic PD.
The transcriptional expression of seven selected genes was examined in blood samples from 62 early stage PD patients and 64 healthy age-matched controls. Stepwise multivariate logistic regression analysis identified five genes as optimal predictors of PD: p19 S-phase kinase-associated protein 1A (odds ratio [OR] 0.73; 95% confidence interval [CI] 0.60-0.90), huntingtin interacting protein-2 (OR 1.32; CI 1.08-1.61), aldehyde dehydrogenase family 1 subfamily A1 (OR 0.86; 95% CI 0.75-0.99), 19 S proteasomal protein PSMC4 (OR 0.73; 95% CI 0.60-0.89) and heat shock 70-kDa protein 8 (OR 1.39; 95% CI 1.14-1.70). At a 0.5 cut-off the gene panel yielded a sensitivity and specificity in detecting PD of 90.3 and 89.1 respectively and the area under the receiving operating curve (ROC AUC) was 0.96. The performance of the five-gene classifier on the de novo PD individuals alone composing the early PD cohort (n = 38), resulted in a similar ROC with an AUC of 0.95, indicating the stability of the model and also, that patient medication had no significant effect on the predictive probability (PP) of the classifier for PD risk. The predictive ability of the model was validated in an independent cohort of 30 patients at advanced stage of PD, classifying correctly all cases as PD (100% sensitivity). Notably, the nominal average value of the PP for PD (0.95 (SD = 0.09)) in this cohort was higher than that of the early PD group (0.83 (SD = 0.22)), suggesting a potential for the model to assess disease severity. Lastly, the gene panel fully discriminated between PD and Alzheimer's disease (n = 29).
The findings provide evidence on the ability of a five-gene panel to diagnose early/mild PD, with a possible diagnostic value for detection of asymptomatic PD before overt expression of the disorder.
在帕金森病（PD）中寻找生物标志物对于早期识别疾病和监测神经保护治疗的效果至关重要。我们旨在评估早期/轻度 PD 患者的血液中是否可以检测到基因特征，以支持早期 PD 的诊断，重点关注在散发性 PD 的黑质中特别改变的基因。
在 62 名早期 PD 患者和 64 名年龄匹配的健康对照者的血液样本中，检查了七个选定基因的转录表达。逐步多元逻辑回归分析确定了五个基因是 PD 的最佳预测因子：p19 S 期激酶相关蛋白 1A（比值比[OR]0.73；95%置信区间[CI]0.60-0.90）、亨廷廷相互作用蛋白 2（OR1.32；CI1.08-1.61）、醛脱氢酶家族 1 亚家族 A1（OR0.86；95%CI0.75-0.99）、19S 蛋白酶体蛋白 PSMC4（OR0.73；95%CI0.60-0.89）和热休克 70kDa 蛋白 8（OR1.39；CI1.14-1.70）。在 0.5 截止值下，基因面板在检测 PD 方面的敏感性和特异性分别为 90.3%和 89.1%，接收操作曲线（ROC AUC）下面积为 0.96。在由 38 名早期 PD 患者组成的新诊断 PD 个体中，五个基因分类器的性能得到了类似的 ROC，AUC 为 0.95，表明模型的稳定性，并且患者的药物治疗对分类器的 PD 风险预测概率（PP）没有显著影响。该模型的预测能力在一个独立的 30 名晚期 PD 患者队列中得到了验证，正确地将所有病例归类为 PD（100%的敏感性）。值得注意的是，该队列中 PD 的 PP 的名义平均值（0.95（SD=0.09））高于早期 PD 组（0.83（SD=0.22）），这表明该模型有可能评估疾病的严重程度。最后，该基因面板完全区分了 PD 和阿尔茨海默病（n=29）。
研究结果为五个基因面板诊断早期/轻度 PD 的能力提供了证据，对检测疾病前无症状 PD 具有潜在的诊断价值。
