Max Planck Institute of Psychiatry, Munich, Germany.
International Max Planck Research School for Translational Psychiatry, Munich, Germany.
Neuropsychopharmacology. 2021 Oct;46(11):1895-1905. doi: 10.1038/s41386-021-01051-0. Epub 2021 Jun 14.
Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.
精神障碍表现出异质的症状和轨迹，目前的分类法不能准确反映其分子病因，以及诊断类别内部和之间的变异性和症状重叠。这种异质性阻碍了及时和有针对性的治疗。我们的研究旨在确定具有相似临床和遗传特征的精神障碍患者群体，这些患者可能受益于类似的治疗方法。我们使用深度临床数据的高维数据聚类来识别发现样本（N=1250）中健康对照者和被诊断为抑郁症、双相情感障碍、精神分裂症、分裂情感障碍和其他精神障碍的患者的跨诊断组。我们观察到五个诊断上混合的簇，并根据严重程度对其进行排序。受影响最小的簇 0 包含大多数健康对照者，表现出普遍的健康。簇 1-3 主要在受虐待程度、抑郁、日常功能和父母养育方面存在差异。簇 4 包含大多数被诊断为精神病性障碍的患者，在许多维度上表现出最高的严重程度，包括药物负荷。所有簇中都有抑郁患者，表明我们捕获了不同的疾病阶段或亚型。我们在独立样本（N=622）中复制了除最小簇 1 之外的所有簇。接下来，我们使用多基因评分（PGS）和精神科家族史分析了簇之间的遗传差异。这些遗传变量主要在簇 0 和 4 之间存在差异（接受者操作特征曲线下的预测面积 AUC=81%；显著的 PGS：跨疾病精神风险、精神分裂症和受教育程度）。我们的结果证实，精神障碍由具有相似分子因素和症状的异质亚型组成。跨诊断簇的识别提高了我们对精神障碍异质性的理解，并可能支持个性化治疗的发展。
