García-San-Martín Natalia, Bethlehem Richard A I, Mihalik Agoston, Seidlitz Jakob, Sebenius Isaac, Alemán-Morillo Claudio, Dorfschmidt Lena, Shafiei Golia, Ortiz-García de la Foz Víctor, Merritt Kate, David Anthony, Morgan Sarah E, Ruiz-Veguilla Miguel, Ayesa-Arriola Rosa, Vázquez-Bourgon Javier, Alexander-Bloch Aaron, Misic Bratislav, Bullmore Edward T, Suckling John, Crespo-Facorro Benedicto, Romero-García Rafael
Department of Medical Physiology and Biophysics, University of Seville, Seville, Spain.
Department of Psychology, University of Cambridge, Cambridge, UK.
Mol Psychiatry. 2025 Apr;30(4):1287-1296. doi: 10.1038/s41380-024-02724-0. Epub 2024 Sep 12.
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 (αβ) 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.
精神病谱系包含一系列与大脑发育异常相关的异质性临床病症。检测跨精神疾病的非典型神经解剖学成熟模式需要一个由年龄、性别和部位效应标准化的可解释指标。导致大脑结构偏离典型神经发育的分子和微观结构属性仍然未知。在这里,我们汇总了来自38696名健康对照者(HC)和1256例与精神病相关病症的结构磁共振成像数据,这些病症包括精神分裂症(SCZ)和分裂情感性障碍(SAD)患者的一级亲属(n = 160)、有精神病体验的个体(n = 157)、首次发作精神病(FEP,n = 352)的患者以及患有慢性SCZ或SAD的个体(n = 587)。使用规范建模方法,我们生成了皮质灰质(GM)表型的百分位数分数,确定了所有病症中区域体积低于预期轨迹的偏差,对临床诊断的病症(FEP和慢性病症)影响更大。此外,我们使用多变量方法将来自健康个体的46种神经生物学特征(包括神经递质、细胞类型、层厚度、微观结构、皮质扩展和代谢)映射到这些异常百分位数上。结果显示,神经生物学特征与百分位数偏差高度共定位,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(αβ)受体)与异常GM轨迹显示出最一致的空间重叠。这些发现共同揭示了在精神病不同阶段可能构成非典型大脑成熟基础的脆弱因素。