Bipolar disorder (BD) and major depressive disorder (MDD) have both common and distinct clinical features, that pose both conceptual challenges in terms of their diagnostic boundaries and practical difficulties in optimizing treatment. Multivariate machine learning techniques offer new avenues for exploring these boundaries based on clinical neuroanatomical features. Brain structural data were obtained at 3 T from a sample of 90 patients with BD, 189 patients with MDD, and 162 healthy individuals. We applied sparse partial least squares discriminant analysis (s-PLS-DA) to identify clinical and brain structural features that may discriminate between the two clinical groups, and heterogeneity through discriminative analysis (HYDRA) to detect patient subgroups with reference to healthy individuals. Two clinical dimensions differentiated BD from MDD (area under the curve: 0.76, P < 0.001); one dimension emphasized disease severity as well as irritability, agitation, anxiety and flight of ideas and the other emphasized mostly elevated mood. Brain structural features could not distinguish between the two disorders. HYDRA classified patients in two clusters that differed in global and regional cortical thickness, the distribution proportion of BD and MDD and positive family history of psychiatric disorders. Clinical features remain the most reliable discriminant attributed of BD and MDD depression. The brain structural findings suggests that biological partitions of patients with mood disorders are likely to lead to the identification of subgroups, that transcend current diagnostic divisions into BD and MDD and are more likely to be aligned with underlying genetic variation. These results set the foundation for future studies to enhance our understanding of brain–behavior relationships in mood disorders.

躁郁症（BD）和重度抑郁症（MDD）具有共同和不同的临床特征，就其诊断范围和优化治疗的实际困难而言，既构成概念挑战。多元机器学习技术为基于临床神经解剖学特征探索这些边界提供了新途径。在3 T时从90例BD患者，189例MDD患者和162个健康个体的样本中获得了大脑结构数据。我们应用稀疏偏最小二乘判别分析（s-PLS-DA）来识别可能区分两个临床组的临床和大脑结构特征，并通过判别分析（HYDRA）进行异质性检测以健康个体为参考的患者亚组。P <0.001）; 一个方面强调疾病的严重性以及易怒性，躁动，焦虑和想法的流失，另一个方面则强调情绪的升高。脑部结构特征无法区分这两种疾病。HYDRA将患者分为两类，在整体和区域皮层厚度，BD和MDD的分布比例以及精神疾病的阳性家族史方面有所不同。临床特征仍然是归因于BD和MDD抑郁症的最可靠的判别方法。大脑结构的发现表明，情绪障碍患者的生物分区可能导致亚组的识别，这些亚组超越了目前的诊断部门，分为BD和MDD，并且更有可能与潜在的遗传变异保持一致。