Yadav Ravi, Dey Saikat, Kumar Ravichandiran, Mohanan Athira P, Vasudevan Geethu T, Harish Manasi, Kamble Nitish, Holla Vikram V, Mahale Rohan R, Mailankody Pooja, Debnath Monojit, Saini Jitender, Kumar Keshav, Mahadevan Anita, Subramanian Sarada, Alladi Phalguni, Datta Indrani, Sreekumarannair Binu V, Thomas Priya, Mehta Anish, Stezin Albert, Ingalhalikar Madhura, Ramdas Sweta, Bathula Deepthi R, Pal Pramod Kumar
Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India.
Department of Human Genetics, National Institute of Mental Health and Neurosciences, Bangalore, India.
PLoS One. 2025 Jun 26;20(6):e0325624. doi: 10.1371/journal.pone.0325624. eCollection 2025.
Atypical Parkinsonian Syndromes (APS) form the third largest group of neurodegenerative disorders including Progressive Supranuclear Palsy (PSP), Multiple System Atrophy (MSA), and Corticobasal Syndrome (CBS). These conditions are characterized by rapid progression, poor prognosis, low survival rates, and limited treatment options. Few studies have suggested that genetic, environmental factors and inflammation contribute to the pathobiology of these complex disorders, however, the etiology of disease and progression remains unclear.
A multicenter prospective longitudinal (3-time point) study will be conducted with a total sample size of 400 across all the groups (PSP, MSA, CBS). Patients with APS will be recruited after a detailed evaluation by movement disorder specialists and obtaining valid informed consent. The socio-demographic data and whole exome sequencing will be performed only at the baseline. Non-invasive procedures such as neurological and cognitive assessments, sleep quality assessments including polysomnography, brain imaging, and retinal imaging will be conducted at each time point. In addition, gene expressions, methylation patterns, inflammatory cytokines, disease-associated pathological proteins (Tau, pTau-181, α-synuclein and β-amyloid), non-targeted proteomics, skin biopsy, and iPSC will be performed at each time point eventually. The statistical analysis will be performed, followed by the developing of machine learning (ML) models.
This unique native dataset in APS will enhance our understanding of the molecular mechanisms driving pathological protein aggregation and disease progression. Furthermore, the longitudinal design of the study enables a detailed examination of symptom development, progression, and management. The ML models combined with advanced imaging techniques will aid in early diagnosis, differentiation among APS types, and the development of future clinical trials and treatment strategies.
非典型帕金森综合征(APS)是第三大类神经退行性疾病,包括进行性核上性麻痹(PSP)、多系统萎缩(MSA)和皮质基底节综合征(CBS)。这些病症的特点是进展迅速、预后不良、生存率低且治疗选择有限。很少有研究表明遗传、环境因素和炎症与这些复杂疾病的病理生物学有关,然而,疾病的病因和进展仍不清楚。
将开展一项多中心前瞻性纵向(3个时间点)研究,所有组(PSP、MSA、CBS)的总样本量为400例。APS患者将在运动障碍专家进行详细评估并获得有效知情同意后招募。仅在基线时进行社会人口统计学数据和全外显子组测序。在每个时间点将进行非侵入性检查,如神经和认知评估、包括多导睡眠图的睡眠质量评估、脑成像和视网膜成像。此外,最终将在每个时间点进行基因表达、甲基化模式、炎性细胞因子、疾病相关病理蛋白(Tau、pTau-181、α-突触核蛋白和β-淀粉样蛋白)、非靶向蛋白质组学、皮肤活检和诱导多能干细胞研究。将进行统计分析,随后开发机器学习(ML)模型。
这个独特的APS原始数据集将增进我们对驱动病理蛋白聚集和疾病进展的分子机制的理解。此外,该研究的纵向设计能够详细检查症状的发展、进展和管理。结合先进成像技术的ML模型将有助于早期诊断、APS类型的鉴别以及未来临床试验和治疗策略的制定。