Universal clinical Parkinson's disease axes identify a major influence of neuroinflammation.
Universal clinical Parkinson's disease axes identify a major influence of neuroinflammation.
复制标题
帕金森氏病的普遍临床轴线确定了神经炎症的主要影响。
DOI：
10.1186/s13073-022-01132-9
复制
发表时间：
2022-11-16
期刊：
影响因子：
12.3
通讯作者：
中科院分区：
文献类型：
--
作者：
帕金森病患者的临床表现和进展存在很大的个体差异。生成深度和纵向表型的患者队列具有识别疾病亚型以进行预后和治疗目标的巨大潜力。通过在三个大型帕金森氏症队列（牛津发现队列 (n = 842)/追踪英国帕金森氏症研究 (n = 1807) 和帕金森氏症进展标记计划 (n = 472)）中进行复制，并使用 5-10 年纵向收集的临床观察测量数据，我们开发了一种包含遗传关系的贝叶斯多重表型混合模型能够将许多不同的临床测量结果解释为较少数量的连续潜在因素（“表型轴”）的个体之间。当应用于诊断时的疾病严重程度时，三个表型轴“轴1”中影响最大的特征是诊断时严重的非震颤运动表型、焦虑和抑郁，伴随着认知功能测量的更快进展。轴 1 与阿尔茨海默病遗传风险增加和 CSF Aβ1-42 水平降低相关。正如之前在阿尔茨海默病遗传风险中观察到的那样，与帕金森病遗传风险相反，影响轴 1 的位点与涉及神经炎症的小胶质细胞表达基因相关。当应用于每个个体的疾病进展测量时，阿尔茨海默病基因位点单倍型的整合提高了进展建模的准确性，而帕金森病遗传学的整合却没有。我们确定了帕金森病表型变异的通用轴，表明具有阿尔茨海默氏病高伴随遗传风险的帕金森病患者更有可能在基线时出现严重的运动和非运动特征，并且更快地进展为早期痴呆。在线版本包含可在 10.1186/s13073-022-01132-9 获取的补充材料。
There is large individual variation in both clinical presentation and progression between Parkinson’s disease patients. Generation of deeply and longitudinally phenotyped patient cohorts has enormous potential to identify disease subtypes for prognosis and therapeutic targeting. Replicating across three large Parkinson’s cohorts (Oxford Discovery cohort (n = 842)/Tracking UK Parkinson’s study (n = 1807) and Parkinson’s Progression Markers Initiative (n = 472)) with clinical observational measures collected longitudinally over 5–10 years, we developed a Bayesian multiple phenotypes mixed model incorporating genetic relationships between individuals able to explain many diverse clinical measurements as a smaller number of continuous underlying factors (“phenotypic axes”). When applied to disease severity at diagnosis, the most influential of three phenotypic axes “Axis 1” was characterised by severe non-tremor motor phenotype, anxiety and depression at diagnosis, accompanied by faster progression in cognitive function measures. Axis 1 was associated with increased genetic risk of Alzheimer’s disease and reduced CSF Aβ1-42 levels. As observed previously for Alzheimer’s disease genetic risk, and in contrast to Parkinson’s disease genetic risk, the loci influencing Axis 1 were associated with microglia-expressed genes implicating neuroinflammation. When applied to measures of disease progression for each individual, integration of Alzheimer’s disease genetic loci haplotypes improved the accuracy of progression modelling, while integrating Parkinson’s disease genetics did not. We identify universal axes of Parkinson’s disease phenotypic variation which reveal that Parkinson’s patients with high concomitant genetic risk for Alzheimer’s disease are more likely to present with severe motor and non-motor features at baseline and progress more rapidly to early dementia. The online version contains supplementary material available at 10.1186/s13073-022-01132-9.
登录
查看更多内容
影响因子：
30.8
作者：
Dahl A;Iotchkova V;Baud A;Johansson Å;Gyllensten U;Soranzo N;Mott R;Kranis A;Marchini J
通讯作者：
Marchini J
DOI：
10.1002/mds.26374
发表时间：
2016-01
期刊：
Movement disorders : official journal of the Movement Disorder Society
影响因子：
--
作者：
Nalls MA;Keller MF;Hernandez DG;Chen L;Stone DJ;Singleton AB;Parkinson's Progression Marker Initiative (PPMI) investigators
通讯作者：
Parkinson's Progression Marker Initiative (PPMI) investigators
DOI：
10.3233/jpd-140523
发表时间：
2015
期刊：
Journal of Parkinson's disease
影响因子：
--
作者：
Lawton M;Baig F;Rolinski M;Ruffman C;Nithi K;May MT;Ben-Shlomo Y;Hu MT
通讯作者：
Hu MT
影响因子：
4.2
作者：
Nalls, Mike A.;Bras, Jose;Singleton, Andrew B.
通讯作者：
Singleton, Andrew B.
影响因子：
14.5
作者：
Fereshtehnejad, Seyed-Mohammad;Zeighami, Yashar;Postuma, Ronald B.
通讯作者：
Postuma, Ronald B.