Division of Neurobiology, Faculty of Biology, LMU Munich, 82152, Martinsried, Germany.
Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.
Sci Rep. 2024 Sep 2;14(1):20314. doi: 10.1038/s41598-024-71316-3.
Cognitive deficits are prevalent in individuals with psychosis and are associated with neurobiological changes, potentially serving as an endophenotype for psychosis. Using the HCP-Early-Psychosis-dataset (n = 226), we aimed to investigate cognitive subtypes (deficit/intermediate/spared) through data-driven clustering in affective (AP) and non-affective psychosis patients (NAP) and controls (HC). We explored differences between three clusters in symptoms, cognition, medication, and grey matter volume. Applying principal component analysis, we selected features for clustering. Features that explained most variance were scores for intelligence, verbal recognition and comprehension, auditory attention, working memory, reasoning and executive functioning. Fuzzy K-Means clustering on those features revealed that the subgroups significantly varied in cognitive impairment, clinical symptoms, and, importantly, also in medication and grey matter volume in fronto-parietal and subcortical networks. The spared cluster (86%HC, 37%AP, 17%NAP) exhibited unimpaired cognition, lowest symptoms/medication, and grey matter comparable to controls. The deficit cluster (4%HC, 10%AP, 47%NAP) had impairments across all domains, highest symptoms scores/medication dosage, and pronounced grey matter alterations. The intermediate deficit cluster (11%HC, 54%AP, 36%NAP) showed fewer deficits than the second cluster, but similar symptoms/medication/grey matter to the spared cluster. Controlling for medication, cognitive scores correlated with grey matter changes and negative symptoms across all patients. Our findings generally emphasize the interplay between cognition, brain structure, symptoms, and medication in AP and NAP, and specifically suggest a possible mediating role of cognition, highlighting the potential of screening cognitive changes to aid tailoring treatments and interventions.
认知缺陷在精神病患者中很常见，与神经生物学变化有关，可能是精神病的一个内表型。我们使用 HCP-Early-Psychosis-dataset（n=226），旨在通过数据驱动聚类，在情感障碍（AP）和非情感障碍精神病（NAP）患者和对照组（HC）中研究认知亚型（缺陷/中等/正常）。我们探索了三个聚类之间在症状、认知、药物和灰质体积方面的差异。通过主成分分析，我们选择了聚类的特征。解释大部分方差的特征是智力、言语识别和理解、听觉注意力、工作记忆、推理和执行功能的分数。对这些特征进行模糊 K-Means 聚类，发现亚组在认知障碍、临床症状以及重要的药物和额顶叶和皮质下网络中的灰质体积方面存在显著差异。正常组（86%HC、37%AP、17%NAP）表现出认知不受影响、症状/药物最低，灰质与对照组相当。缺陷组（4%HC、10%AP、47%NAP）在所有领域都存在障碍，症状评分/药物剂量最高，灰质改变明显。中等缺陷组（11%HC、54%AP、36%NAP）的缺陷比第二组少，但与正常组的症状/药物/灰质相似。控制药物因素后，认知评分与所有患者的灰质变化和阴性症状相关。我们的发现总体上强调了 AP 和 NAP 中认知、大脑结构、症状和药物之间的相互作用，特别是表明认知可能起中介作用，强调了筛查认知变化以帮助调整治疗和干预的潜力。
