Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
J Neurol Neurosurg Psychiatry. 2021 May;92(5):494-501. doi: 10.1136/jnnp-2020-323541. Epub 2021 Jan 15.
Progranulin-related frontotemporal dementia (FTD-) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-, in a data-driven way.
We included 56 presymptomatic and 35 symptomatic mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD- and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.
Language functioning and NfL were the earliest abnormal biomarkers in FTD-. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.
Degeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic mutation carriers at risk of conversion to the clinical stage.
颗粒蛋白前体相关性额颞叶痴呆（FTD-）是一种快速进展性疾病。对多模态生物标志物变化的建模有助于了解该疾病的病因，并能够监测个体突变携带者。在这项横断面研究中，我们以数据驱动的方式估计了 FTD-的生物标志物变化的时间级联。
我们纳入了 56 名无症状前症和 35 名有症状的突变携带者，以及 35 名健康的非携带者。选择的生物标志物为神经丝轻链（NfL）、灰质体积、白质微观结构和认知领域。我们使用基于事件的判别建模来推断 FTD-中的生物标志物变化级联，并通过交叉验证来估计个体疾病严重程度。我们推导出非流利型原发性进行性失语症（nfvPPA）和行为变异型额颞叶痴呆（bvFTD）的生物标志物级联，以了解这些表型之间的差异。
语言功能和 NfL 是 FTD-中最早出现异常的生物标志物。白质束在灰质体积之前受到影响，左半球在右半球之前退化。根据个体疾病严重程度，可将无症状携带者与有症状携带者区分开来，其敏感性为 100%，特异性为 96.1%。估计的疾病严重程度与 nfvPPA 的功能严重程度强烈相关，但与 bvFTD 不相关。此外，bvFTD 的生物标志物级联显示出比 nfvPPA 更多的不确定性。
轴突变性和语言缺陷被认为是 FTD-中最早的生物标志物，bvFTD 在疾病进展方面比 nfvPPA 更为异质。我们的数据驱动模型可以帮助识别有转化为临床阶段风险的无症状突变携带者。
