Integrated Label Transfer for Oligodendrocyte Subpopulation Profiling in Parkinson's Disease and Multiple System Atrophy

E. Teeple, P. Joshi, R. Pande, Y. Huang, Akshat Karambe, M. Latta-Mahieu, S. Sardi, A. Cedazo-Mínguez, Katherine W. Klinger, A. Flores-Morales, S. Madden, D. Rajpal, Dinesh Kumar
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Abstract

Transfer of cell type labels as part of the comprehensive integration of multiple single nucleus RNA sequencing (snRNAseq) datasets offers a powerful tool for comparing cell populations and their activation states in normal versus disease conditions. Another potential use for these methods is annotation alignments between samples from different anatomic areas. This study describes and evaluates an integration analysis applied for profiling of oligodendrocyte lineage nuclei sequenced from human brain putamen region tissue samples for healthy Control (n = 3), Parkinson’s Disease (PD; n = 3) and Multiple System Atrophy (MSA; n = 3) subjects with label transfer to substantia nigra region tissue samples for healthy Control (n = 5) subjects. PD and MSA are both synucleinopathies, progressive neurodegenerative disorders characterized by nervous system aggregates of α-synuclein, a protein encoded by the SNCA gene. Histologic findings and genetic evidence suggest links between oligodendrocyte biology and synucleinopathy pathogenesis. In this work, we first identify disease-associated changes among transcriptionally distinct oligodendrocyte subpopulations in putamen. We then apply label transfer methods to generalize our findings from putamen to substantia nigra, a brain region characteristically impacted in PD and variably affected in MSA. Interestingly, our analysis predicts oligodendrocytes in substantia nigra include a significantly greater proportion of an oligodendrocyte subpopulation identified in putamen as most highly overexpressing SNCA in PD. Our results provide new insights into oligodendrocyte biology in PD and MSA and our workflow provides an example of label transfer methods applied for cross-dataset exploratory purpose.
帕金森病和多系统萎缩中少突胶质细胞亚群分析的集成标签转移
作为多个单核RNA测序(snRNAseq)数据集全面整合的一部分,细胞类型标签的转移为比较正常和疾病条件下的细胞群及其激活状态提供了一个强大的工具。这些方法的另一个潜在用途是来自不同解剖区域的样本之间的注释对齐。本研究描述并评估了一种整合分析,该分析应用于人类大脑壳核区组织样本的少突胶质细胞谱系核测序,用于健康对照(n = 3),帕金森病(PD;n = 3)和多系统萎缩(MSA;n = 3)受试者用标签转移到黑质区域组织样本作为健康对照(n = 5)受试者。PD和MSA都是突触核蛋白病,以神经系统α-突触核蛋白聚集为特征的进行性神经退行性疾病,α-突触核蛋白是SNCA基因编码的一种蛋白质。组织学发现和遗传证据表明少突胶质细胞生物学与突触核蛋白病发病机制之间存在联系。在这项工作中,我们首先确定了壳核中转录不同的少突胶质细胞亚群中疾病相关的变化。然后,我们应用标签转移方法将我们的发现从壳核推广到黑质,黑质是PD中典型的受影响的大脑区域,在MSA中受到不同的影响。有趣的是,我们的分析预测黑质中的少突胶质细胞包括在壳核中被鉴定为PD中SNCA高表达的少突胶质细胞亚群的比例显著更高。我们的结果为PD和MSA的少突胶质细胞生物学提供了新的见解,我们的工作流程提供了一个应用于跨数据集探索目的的标签转移方法的示例。
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