Park Gilsoon, Ha Jongmok, Lee Jun Seok, Ahn Jong Hyeon, Cho Jin Whan, Seo Sang Won, Youn Jinyoung, Kim Hosung
Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA 90033, USA.
Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea; Department of Neurology, Emory School of Medicine, Atlanta, GA, USA.
Neurobiol Dis. 2025 Aug;212:106970. doi: 10.1016/j.nbd.2025.106970. Epub 2025 May 24.
Several subtyping methods have been proposed to characterize Parkinson's disease (PD) progression, yet the trajectory of subcortical and cortical neurodegeneration and its clinical implications remain unclear.
We aimed to conduct a strictly image-based, data-driven classification of PD progression through Subtype and Stage Inference (SuStaIn) algorithm.
Brain volumetric data from 565 patients with PD and 150 propensity-matched healthy controls were analyzed. 16 regions of interest, including 9 cortical and 7 deep grey matter structures, were segmented from T1-weighted magnetic resonance images. Clinical data, including REM sleep behavior disorder (RBD), levodopa equivalent daily dose (LEDD), and motor complications were collected. SuStaIn was trained and tested using a 10-folds cross-validation and identified two distinct PD progression subtypes, which were compared for differences in clinical and radiological characteristics.
We found two distinct neurodegenerative trajectories: deep grey matter (DG)-first and cortex (CO)-first. The CO-first subtype had a higher prevalence of RBD (p = 0.009) and levodopa-induced dyskinesia (p = 0.024) than the DG-first subtype. Disease progression was faster in the CO-first subtype (0.203 year/stage, LEDD increase 59.3 mg/year), than in the DG-first subtype (0.081 year/stage, LEDD increase 45.1 mg/year, respectively). Regardless of the subtypes, the sensorimotor and auditory cortices were the earliest affected cortical regions, while the amygdala was the first affected subcortically. A subset of participants (n = 186) showed no significant atrophy progression.
Our findings support the existence of two distinct subtypes of PD progression based on neuroimaging data. Longitudinal studies are warranted to track their evolution.
已经提出了几种亚型分类方法来描述帕金森病（PD）的进展情况，然而，皮层下和皮层神经退行性变的轨迹及其临床意义仍不明确。
我们旨在通过亚型和阶段推断（SuStaIn）算法对PD进展进行严格基于图像的数据驱动分类。
分析了565例PD患者和150例倾向匹配的健康对照的脑体积数据。从T1加权磁共振图像中分割出16个感兴趣区域，包括9个皮层和7个深部灰质结构。收集了临床数据，包括快速眼动睡眠行为障碍（RBD）、左旋多巴等效日剂量（LEDD）和运动并发症。使用10折交叉验证对SuStaIn进行训练和测试，并确定了两种不同的PD进展亚型，比较了它们在临床和放射学特征上的差异。
我们发现了两种不同的神经退行性轨迹：深部灰质（DG）优先和皮层（CO）优先。与DG优先亚型相比，CO优先亚型的RBD（p = 0.009）和左旋多巴诱导的异动症（p = 0.024）患病率更高。CO优先亚型的疾病进展（0.203年/阶段，LEDD每年增加59.3 mg）比DG优先亚型（分别为0.081年/阶段，LEDD每年增加45.1 mg）更快。无论亚型如何，感觉运动皮层和听觉皮层是最早受影响的皮层区域，而杏仁核是最早受皮层下影响的区域。一部分参与者（n = 186）没有显示出明显的萎缩进展。
我们的研究结果支持基于神经影像学数据存在两种不同的PD进展亚型。有必要进行纵向研究来追踪它们的演变。
