The psychosis spectrum encompasses a heterogeneous range of clinical conditions associated with abnormal brain development. Detecting patterns of atypical neuroanatomical maturation across psychiatric disorders requires an interpretable metric standardized by age-, sex- and site-effect. The molecular and micro-architectural attributes that account for these deviations in brain structure from typical neurodevelopment are still unknown. Here, we aggregate structural magnetic resonance imaging data from 38,696 healthy controls (HC) and 1256 psychosis-related conditions, including first-degree relatives of schizophrenia (SCZ) and schizoaffective disorder (SAD) patients (n = 160), individuals who had psychotic experiences (n = 157), patients who experienced a first episode of psychosis (FEP, n = 352), and individuals with chronic SCZ or SAD (n = 587). Using a normative modeling approach, we generated centile scores for cortical gray matter (GM) phenotypes, identifying deviations in regional volumes below the expected trajectory for all conditions, with a greater impact on the clinically diagnosed ones, FEP and chronic. Additionally, we mapped 46 neurobiological features from healthy individuals (including neurotransmitters, cell types, layer thickness, microstructure, cortical expansion, and metabolism) to these abnormal centiles using a multivariate approach. Results revealed that neurobiological features were highly co-localized with centile deviations, where metabolism (e.g., cerebral metabolic rate of oxygen (CMRGlu) and cerebral blood flow (CBF)) and neurotransmitter concentrations (e.g., serotonin (5-HT) and acetylcholine (α₄β₂) receptors) showed the most consistent spatial overlap with abnormal GM trajectories. Taken together these findings shed light on the vulnerability factors that may underlie atypical brain maturation during different stages of psychosis.

精神病谱涵盖了与大脑发育异常相关的各种不同的临床病症。检测精神疾病的非典型神经解剖成熟模式需要一个按年龄、性别和部位效应标准化的可解释指标。造成大脑结构与典型神经发育的这些偏差的分子和微结构属性仍然未知。在这里，我们汇总了 38,696 名健康对照 (HC) 和 1256 名精神病相关疾病的结构磁共振成像数据，其中包括精神分裂症 (SCZ) 和分裂情感性障碍 (SAD) 患者的一级亲属 ( n = 160)、患有精神病的个体经历过的患者 ( n = 157)、经历过首次精神病发作的患者 (FEP, n = 352) 以及患有慢性 SCZ 或 SAD 的患者 ( n = 587)。使用规范建模方法，我们生成了皮质灰质 (GM) 表型的百分位评分，识别了所有条件下区域体积低于预期轨迹的偏差，对临床诊断的 FEP 和慢性影响更大。此外，我们使用多变量方法将健康个体的 46 个神经生物学特征（包括神经递质、细胞类型、神经层厚度、微观结构、皮质扩张和代谢）映射到这些异常百分位数。结果显示，神经生物学特征与百分位偏差高度共定位，其中代谢（例如脑氧代谢率（CMRGlu）和脑血流量（CBF））和神经递质浓度（例如、血清素（5-HT）和乙酰胆碱（α ₄ β ₂ ）受体）显示出与异常 GM 轨迹最一致的空间重叠。总而言之，这些发现揭示了精神病不同阶段可能导致非典型大脑成熟的脆弱因素。