A multi-region single nucleus transcriptomic atlas of Parkinson's disease.

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-11-23 DOI:10.1038/s41597-024-04117-y

Prashant N M, John F Fullard, Tereza Clarence, Deepika Mathur, Clara Casey, Evelyn Hennigan, Marcela Alvia, Joana Krause-Massaguer, Ayled Barreda, David A Davis, Regina T Vontell, Susanna P Garamszegi, Jeffery M Vance, Lorelle Sang, Michael Chatigny, David Vismer, Barry Landin, David Burstein, Donghoon Lee, Georgios Voloudakis, Sabina Berretta, Vahram Haroutunian, William K Scott, Jaroslav Bendl, Panos Roussos

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Abstract

Parkinson's Disease (PD) is a debilitating neurodegenerative disorder, characterized by motor and cognitive impairments, that affects >1% of the population over the age of 60. The pathogenesis of PD is complex and remains largely unknown. Due to the cellular heterogeneity of the human brain and changes in cell type composition with disease progression, this complexity cannot be fully captured with bulk tissue studies. To address this, we generated single-nucleus RNA sequencing and whole-genome sequencing data from 100 postmortem cases and controls, carefully selected to represent the entire spectrum of PD neuropathological severity and diverse clinical symptoms. The single nucleus data were generated from five brain regions, capturing the subcortical and cortical spread of PD pathology. Rigorous preprocessing and quality control were applied to ensure data reliability. Committed to collaborative research and open science, this dataset is available on the AMP PD Knowledge Platform, offering researchers a valuable tool to explore the molecular bases of PD and accelerate advances in understanding and treating the disease.

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帕金森病的多区域单核转录组图谱。

帕金森病（Parkinson's Disease，PD）是一种使人衰弱的神经退行性疾病，以运动和认知功能障碍为特征，60 岁以上人群中发病率超过 1%。帕金森病的发病机理十分复杂，目前在很大程度上仍不为人所知。由于人脑细胞的异质性以及细胞类型组成随疾病进展而发生的变化，大块组织研究无法完全捕捉到这种复杂性。为了解决这个问题，我们从 100 例尸检病例和对照组中生成了单核 RNA 测序和全基因组测序数据，这些病例和对照组是经过精心挑选的，代表了帕金森病神经病理学严重程度的整个范围和各种临床症状。单核数据来自五个脑区，捕捉到了帕金森病病理在皮层下和皮层的分布。为确保数据的可靠性，我们进行了严格的预处理和质量控制。该数据集致力于合作研究和开放科学，可在 AMP PD 知识平台上获取，为研究人员提供了探索帕金森病分子基础的宝贵工具，加快了理解和治疗该疾病的进展。

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.