认知基本症状的生物特征标志着通往精神分裂症的一条独特神经发育路径

摘要(中文译文)

利用生物学数据预测精神分裂症风险的努力，一直受到当前“临床高风险”（CHR-P）标准异质性的阻碍，这些标准将现象学和生物学上不同的综合征归集于单一标签之下。尤其是，该领域几乎仅关注“超高危”（UHR）症状，而认知基本症状——尽管其与精神分裂症的核心特征如形式思维障碍密切相关——仍未得到充分利用。迄今为止，尚无研究直接比较不同CHR-P定义下的大脑特征与精神分裂症的相似性及其诊断、生物心理社会和预后特征。我们对1425例患者（CHR-P亚组、近期起病精神病、抑郁症）和907名健康对照的结构MRI数据应用机器学习，以推导和比较诊断性大脑特征：认知障碍（COGDIS）、UHR、二者的重叠（MIXED）以及精神分裂症。MIXED和UHR特征缺乏诊断区分度及与精神分裂症的相似性。相反，COGDIS特征能够区分患者与对照（平衡准确率=69%，P<0.001），并与精神分裂症特征一致（r=0.60），涉及共同的额-顶-外侧裂周围体积缩小。UHR的特征为体积增大，而MIXED相对于健康对照则表现出体积缩小与增大的混合模式。基于多基因、认知和暴露组因素，COGDIS和精神分裂症特征表达可被预测，解释方差为12%-21%，在跨诊断患者队列和健康对照中均如此。其表达从健康状态到精神分裂症逐渐增加。MIXED特征表达也可从生物心理社会数据中预测，但患者样本中的解释方差（21%）高于健康对照（3%）。UHR特征表达在两组中均未显示出显著的生物心理社会可预测性。细胞富集的多基因风险谱在不同特征间存在差异，COGDIS和精神分裂症显示出与神经发育过程相关的富集模式，而MIXED则与免疫和血脑屏障相关的富集有关。在纵向研究中，COGDIS和精神分裂症大脑评分能够对功能残疾患者进行分层，而UHR评分则预测较好的结局。总之，这些发现表明，精神病风险综合征在其潜在大脑特征的诊断特异性、生物心理社会信息量和预后价值方面存在显著差异。UHR症状与一种微弱且诊断上非特异的大脑模式相关，而MIXED表型则以一种维度性、跨诊断的特征为特点，在早期精神病性和情感性疾病状态中均有富集。相比之下，COGDIS与一种具有神经发育基础的易感性模式一致，该模式与精神分裂症的认知-解体维度相汇聚。这些区别支持对精神病风险进行基于生物学的重新概念化，其中认知基本症状捕捉了精神分裂症的核心易患维度，而其他风险状态则反映了精神病症状表达背后更为短暂的过程。

Abstract

Efforts to predict schizophrenia risk using biological data have been hampered by the heterogeneity of current 'clinical high-risk' (CHR-P) criteria, which pool phenomenologically and biologically distinct syndromes under a single label. In particular, the field has focused almost exclusively on 'ultra high-risk' (UHR) symptoms, while cognitive basic symptoms-despite their close alignment with schizophrenia's core features such as formal thought disorder-have remained under-used. To date, no study has directly compared brain signatures of different CHR-P definitions with respect to their similarity to schizophrenia and their diagnostic, biopsychosocial and prognostic profiles. We applied machine learning to structural MRI data from 1425 patients (CHR-P subgroups, recent-onset psychosis, depression) and 907 healthy controls to derive and compare diagnostic brain signatures: cognitive disturbances (COGDIS), UHR, their overlap (MIXED), and schizophrenia. The MIXED and UHR signatures lacked diagnostic separability and similarity with schizophrenia. Contrarily, the COGDIS signature distinguished patients from controls (balanced accuracy = 69%, P < 0.001) and aligned with the schizophrenia signature (r = 0.60), involving shared fronto-parieto-perisylvian volume reductions. UHR was characterized by volume enlargements, whereas MIXED exhibited a mixed pattern of reductions and enlargements relative to healthy controls. COGDIS and schizophrenia signature expressions were predictable with 12%-21% variance explained, based on polygenic, cognitive and exposomal factors, both in a transdiagnostic patient cohort and healthy controls. Their expressions increased from health to schizophrenia. MIXED signature expression was also predictable from biopsychosocial data, but with higher explained variance in patient samples (21%) than in healthy controls (3%). UHR signature expression showed no significant biopsychosocial predictability in either group. Cell-enriched polygenic risk profiles differed across signatures, with COGDIS and schizophrenia showing enrichment patterns implicated in neurodevelopmental processes, while MIXED being associated with immune- and blood-brain barrier-related enrichments. Longitudinally, COGDIS and schizophrenia brain scores stratified patients with functional disability, while UHR scores predicted better outcomes. Together, these findings indicate that psychosis-risk syndromes differ markedly in the diagnostic specificity, biopsychosocial informativeness and prognostic value of their underlying brain signatures. UHR symptoms are linked to a weak and diagnostically unspecific brain pattern, whereas the MIXED phenotype is characterized by a dimensional, transdiagnostic signature enriched across early psychotic and affective disease states. In contrast, COGDIS aligns with a neurodevelopmentally grounded vulnerability pattern that converges with schizophrenia's cognitive-disorganization dimension. These distinctions support a biologically informed reconceptualization of psychosis risk, with cognitive basic symptoms capturing a core liability dimension of schizophrenia, while other risk states reflect more transient processes underlying psychotic symptom expression.

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