Parker David A, Trotti Rebekah L, McDowell Jennifer E, Keedy Sarah K, Keshavan Matcheri S, Pearlson Godfrey D, Gershon Elliot S, Ivleva Elena I, Huang Ling-Yu, Sauer Kodiak, Hill S Kristian, Sweeney John A, Tamminga Carol A, Clementz Brett A
Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA.
Department of Psychology, Emory University, Atlanta, GA, USA.
Transl Psychiatry. 2025 Aug 14;15(1):281. doi: 10.1038/s41398-025-03501-5.
Idiopathic psychosis shows considerable biological heterogeneity across cases. The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) used psychosis-relevant biomarkers to identify psychosis Biotypes, which will aid etiological and targeted treatment investigations. Here, our previous approach (Clementz et al. 2022) is updated, which supports the development of an efficient psychosis Biotype diagnostic procedure called ADEPT. Psychosis probands (n = 1907), their first-degree biological relatives (n = 705), and healthy participants (n = 895) completed a biomarker battery composed of cognitive performance, saccades, and auditory EEG/ERP measurements. EEG and ERP quantifications were modified from previous Biotypes iterations. Multivariate integration using multiple approaches reduced biomarker outcomes to 11 "bio-factors." Twenty-four different approaches indicated bio-factor data among probands were best described by three subgroups. Numerical taxonomy with k-means clustering yielded psychosis Biotypes; Rand Indices evaluated individual-case consistency of Biotype assignments. Psychosis subgroups, their non-psychotic first-degree relatives, and healthy individuals were compared across bio-factors. The three psychosis Biotypes differed significantly on all 11 bio-factors, especially prominent for general cognition, antisaccades, ERP magnitude, and intrinsic neural activity. Rand Indices showed excellent individual-case consistency of Biotype membership when samples included more than 1000 subjects. Canonical discriminant analysis described composite bio-factors that simplified group comparisons: "Pattern-2" (high antisaccade errors, low BACS, high ongoing EEG) captured Biotype-2, "Pattern-1" (low ERP amplitudes, low intrinsic EEG) captured Biotype-1, and "Pattern-3" (low frontal P3 complex, accentuated S2 ERP, faster saccadic reaction times) captured Biotype-3. First-degree relatives had patterns like their proband for general cognition, antisaccades, ERP magnitudes, and intrinsic brain activity. These outcomes refine and extend operations for characterizing biologically distinct psychosis Biotypes. They also show that over 1000 observations are useful for achieving consistent individual-case diagnostic assignments. First-degree relative data implicate specific bio-factors as familial within idiopathic psychosis which may inform genetic studies.
特发性精神病在不同病例中表现出相当大的生物学异质性。双相情感障碍-精神分裂症中间表型网络（B-SNIP）使用与精神病相关的生物标志物来识别精神病生物型，这将有助于病因学和靶向治疗研究。在此，我们更新了之前的方法（克莱门茨等人，2022年），该方法支持开发一种名为ADEPT的高效精神病生物型诊断程序。精神病先证者（n = 1907）、他们的一级生物学亲属（n = 705）和健康参与者（n = 895）完成了一组由认知表现、扫视和听觉脑电图/事件相关电位测量组成的生物标志物检测。脑电图和事件相关电位的量化方法是在前几代生物型的基础上修改的。使用多种方法进行多变量整合，将生物标志物结果简化为11个“生物因子”。24种不同的方法表明，先证者中的生物因子数据最好由三个亚组来描述。采用k均值聚类的数值分类法得出了精神病生物型；兰德指数评估了生物型分配的个体病例一致性。对精神病亚组、其非精神病一级亲属和健康个体的生物因子进行了比较。这三种精神病生物型在所有11个生物因子上均存在显著差异，在一般认知、反扫视、事件相关电位幅度和内在神经活动方面尤为突出。当样本数量超过1000名受试者时，兰德指数显示生物型成员的个体病例一致性极佳。典型判别分析描述了简化组间比较的复合生物因子：“模式2”（高反扫视错误、低BACS、高持续脑电图）代表生物型2，“模式1”（低事件相关电位幅度、低内在脑电图）代表生物型1，“模式3”（低额部P3复合波、增强的S2事件相关电位、更快的扫视反应时间）代表生物型3。一级亲属在一般认知、反扫视、事件相关电位幅度和内在脑活动方面的模式与其先证者相似。这些结果完善并扩展了表征生物学上不同的精神病生物型的操作。它们还表明，超过1000次观察对于实现一致的个体病例诊断分配是有用的。一级亲属的数据表明，在特发性精神病中，特定的生物因子具有家族性，这可能为基因研究提供信息。
