Individual-specific functional connectome biomarkers predict schizophrenia positive symptoms during adolescent brain maturation.
Individual-specific functional connectome biomarkers predict schizophrenia positive symptoms during adolescent brain maturation.
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DOI：
10.1002/hbm.25307
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发表时间：
2020-12-02
影响因子：
4.8
通讯作者：
Chen H
中科院分区：
文献类型：
--
作者：
Fan YS;Li L;Peng Y;Li H;Guo J;Li M;Yang S;Yao M;Zhao J;Liu H;Liao W;Guo X;Han S;Cui Q;Duan X;Xu Y;Zhang Y;Chen H
即使有青少年发作精神分裂症（AOS）的总体功能性连接障碍模型，也没有确定用于预测患者特定症状领域的功能性连接组（FC）生物标志物。青春期是大脑发育成熟的重要时期，个体间的大脑解剖结构存在很大差异。然而，现有的AOS组水平假设在神经解剖学边界方面缺乏精确性。本研究旨在确定青少年大脑成熟期间与精神分裂症症状表现相关的个体特异性FC生物标志物。我们使用了一种可靠的个体水平的皮质包裹方法来绘制每例受试者的功能性脑区，然后将其用于鉴定FC生物标志物，以预测30例抗精神病药物初治的首次发作AOS患者（招募样本39例）的维度特异性精神病症状。在这些患者和31名健康对照之间比较了生物标志物表达的年龄相关变化。此外，从另一个中心招募了29例抗精神病药物初治的首次发作AOS患者（分析样本为25例），以测试预测模型的普遍性。个体特异性FC生物标志物可以显著且更好地预测AOS阳性维度症状，其泛化能力比组水平相对更强。具体而言，积极的症状域估计的基础上之间的连接额顶控制网络（FPN）和显着性网络和FPN内。与精神分裂症的神经发育假说一致，FPN-SN连接在AOS中表现出异常的年龄相关改变。个体水平的研究结果揭示了与AOS阳性症状领域相关的可重现的基于FPN的FC生物标志物，并强调了在青少年发作性疾病研究中解释个体差异的重要性。可靠的基于额顶叶控制网络的功能性连接体生物标志物可以在个体水平上识别出阳性症状域，但不能在组水平上识别。重复性实验结果表明，与群体水平方法相比，基于个体的预测模型具有更好的泛化能力。
Even with an overarching functional dysconnectivity model of adolescent‐onset schizophrenia (AOS), there have been no functional connectome (FC) biomarkers identified for predicting patients' specific symptom domains. Adolescence is a period of dramatic brain maturation, with substantial interindividual variability in brain anatomy. However, existing group‐level hypotheses of AOS lack precision in terms of neuroanatomical boundaries. This study aimed to identify individual‐specific FC biomarkers associated with schizophrenic symptom manifestation during adolescent brain maturation. We used a reliable individual‐level cortical parcellation approach to map functional brain regions in each subject, that were then used to identify FC biomarkers for predicting dimension‐specific psychotic symptoms in 30 antipsychotic‐naïve first‐episode AOS patients (recruited sample of 39). Age‐related changes in biomarker expression were compared between these patients and 31 healthy controls. Moreover, 29 antipsychotic‐naïve first‐episode AOS patients (analyzed sample of 25) were recruited from another center to test the generalizability of the prediction model. Individual‐specific FC biomarkers could significantly and better predict AOS positive‐dimension symptoms with a relatively stronger generalizability than at the group level. Specifically, positive symptom domains were estimated based on connections between the frontoparietal control network (FPN) and salience network and within FPN. Consistent with the neurodevelopmental hypothesis of schizophrenia, the FPN–SN connection exhibited aberrant age‐associated alteration in AOS. The individual‐level findings reveal reproducible FPN‐based FC biomarkers associated with AOS positive symptom domains, and highlight the importance of accounting for individual variation in the study of adolescent‐onset disorders. Reliable frontoparietal control network‐based functional connectome biomarkers underlying positive symptom domains could be identified at the individual level, but not at the group level. Replication results indicated relatively better generalization ability of the prediction model by using individual‐based strategy compared with group‐level approach.
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