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，这主要是因为有关不同细胞类型和治疗反应的特定脆弱性的未解决问题。哪些细胞事件（管家或显着事件）受影响最大？哪些细胞类型首先屈服于挑战，哪些对药物表现出最强的反应？这些事件是否在细胞类型之间协调？疾病和药物如何影响这种协调？为了解决这些问题，我们分析了来自人类前扣带皮层的单核 RNAseq (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跨功能概况的相似性和不同性的指标，用于识别跨细胞类型的共同或显着功能主题。细胞特异性特征与现有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、成药性和反应性。功能配置文件的聚类揭示了共同参与这些事件的细胞类型。SST 和 VIP 中间神经元被发现最脆弱，而锥体神经元最少。总体而言，疾病状态以表层为中心，影响细胞特异性显着主题，强烈影响去抑制神经元，并影响星形胶质细胞与深层锥体神经元子集的相互作用。在没有疾病的情况下，药物概况在很大程度上概括了疾病概况，为药物副作用提供了可能的解释。然而，在存在疾病、药物活动的情况下，以深层为中心，涉及激活深层锥体神经元的一个独特子集，以规避疾病状态的去抑制回路故障。这些发现证明了 sn-RNAseq 数据在系统水平上解释药物和疾病作用的新应用。