Department of Pharmacology and Systems Physiology, University of Cincinnati, Cincinnati, OH, USA.
Neuroscience Graduate Program, University of Cincinnati, Cincinnati, OH, USA.
Mol Psychiatry. 2022 Oct;27(10):4023-4034. doi: 10.1038/s41380-022-01657-w. Epub 2022 Jun 27.
In psychiatric disorders, mismatches between disease states and therapeutic strategies are highly pronounced, largely because of unanswered questions regarding specific vulnerabilities of different cell types and therapeutic responses. Which cellular events (housekeeping or salient) are most affected? Which cell types succumb first to challenges, and which exhibit the strongest response to drugs? Are these events coordinated between cell types? How does disease and drug effect this coordination? To address these questions, we analyzed single-nucleus-RNAseq (sn-RNAseq) data from the human anterior cingulate cortex-a region involved in many psychiatric disorders. Density index, a metric for quantifying similarities and dissimilarities across functional profiles, was employed to identify common or salient functional themes across cell types. Cell-specific signatures were integrated with existing disease and drug-specific signatures to determine cell-type-specific vulnerabilities, druggabilities, and responsiveness. Clustering of functional profiles revealed cell types jointly participating in these events. SST and VIP interneurons were found to be most vulnerable, whereas pyramidal neurons were least. Overall, the disease state is superficial layer-centric, influences cell-specific salient themes, strongly impacts disinhibitory neurons, and influences astrocyte interaction with a subset of deep-layer pyramidal neurons. In absence of disease, drugs profiles largely recapitulate disease profiles, offering a possible explanation for drug side effects. However, in presence of disease, drug activities, are deep layer-centric and involve activating a distinct subset of deep-layer pyramidal neurons to circumvent the disease state's disinhibitory circuit malfunction. These findings demonstrate a novel application of sn-RNAseq data to explain drug and disease action at a systems level.
在精神疾病中,疾病状态和治疗策略之间的不匹配非常明显,这主要是因为对于不同细胞类型的特定脆弱性和治疗反应仍存在许多未解决的问题。哪些细胞事件(基本的或显著的)受到的影响最大?哪些细胞类型首先受到挑战,哪些对药物的反应最强?这些事件在细胞类型之间是否协调?疾病和药物如何影响这种协调?为了解决这些问题,我们分析了人类前扣带回的单细胞 RNA 测序 (sn-RNAseq) 数据-该区域涉及许多精神疾病。密度指数是一种用于量化不同功能谱之间相似性和差异性的度量标准,用于识别跨细胞类型的常见或显著功能主题。将细胞特异性特征与现有的疾病和药物特异性特征相结合,以确定细胞类型特异性的脆弱性、可用药性和反应性。功能谱的聚类揭示了共同参与这些事件的细胞类型。发现 SST 和 VIP 中间神经元最脆弱,而锥体神经元最不脆弱。总的来说,疾病状态以浅层为中心,影响细胞特异性显著主题,强烈影响去抑制神经元,并影响星形胶质细胞与一部分深层锥体神经元的相互作用。在没有疾病的情况下,药物特征在很大程度上再现了疾病特征,这可能解释了药物的副作用。然而,在存在疾病的情况下,药物活性以深层为中心,涉及激活深层锥体神经元的一个不同子集,以规避疾病状态的去抑制回路功能障碍。这些发现展示了 sn-RNAseq 数据在系统水平上解释药物和疾病作用的新应用。