Personalized medicine for schizophrenia: developing neuropsychological tests at first episode to predict treatment resistance

30%的精神分裂症患者对至少2种抗精神病药物没有反应[难治性精神分裂症（TRS），占NHS精神卫生总资金的25 - 50%]。氯氮平是TRS的金标准治疗，但最近的证据表明，当治疗延迟时，对氯氮平的反应概率降低，SLAM的平均延迟为4年。因此，TRS的早期识别至关重要，以便能够迅速提供个性化治疗。有新的证据表明，TRS可以确定从第一次发作使用神经化学成像，如PET和MRS。然而，这样的调查是昂贵的，对患者来说是沉重的负担，限制了他们在临床实践中的效用。神经心理学检查价格低廉，耐受性良好，单独或与血液生物标志物结合，将患者分为TRS和非TRS亚型，具有很大的潜力。拟议的博士学位将：（1）联合收割机现有的数据从首发精神病研究：i。MRC：精神分裂症和其他精神病的病因学和种族：ESOP（N = 402）; ii. NIHR BRC遗传学和精神病：GAP（N = 246）; iii. MRC MICA：精神分裂症治疗抵抗和治疗进展：（STRATA）（N = 492）（2）确定区分治疗反应性精神分裂症、早发性TRS和晚发性TRS的神经心理学预测因子，以便（3）为设计结合遗传和其他数据的多模式方法提供信息，以预测精神分裂症的治疗反应。

30% of patients with schizophrenia fail to respond to at least 2 antipsychotics [Treatment resistant schizophrenia (TRS), accounting for 25-50% of total NHS funding for mental health]. Clozapine is the gold-standard treatment for TRS, but recent evidence shows that the probability of response to clozapine diminishes when treatment is delayed, and that the mean delay in SLAM is 4 years. Early identification of TRS is therefore crucial, so that personalised treatment can be given quickly. There is emerging evidence that TRS can be identified from first episode using neurochemical imaging such as PET and MRS. However, such investigations are costly and burdensome for patients, limiting their utility in clinical practice. Neuropsychological investigations are inexpensive, well tolerated and have great potential, alone or in combination with blood biomarkers, to stratify patients into TRS and non-TRS subtypes. The proposed PhD will:(1) combine existing data from first episode psychosis studies:i. MRC: Aetiology and Ethnicity in Schizophrenia and Other Psychoses: ÆSOP (N=402);ii. NIHR BRC Genetics and Psychosis: GAP (N=246); iii. MRC MICA: Schizophrenia Treatment Resistance and Therapeutic Advances: (STRATA) (N=492) (2) identify neuropsychological predictors distinguishing between treatment-responsive schizophrenia, early-onset TRS and late-onset TRS, in order to(3) inform the design of a multi-modal approach combining genetic and other data to predict treatment response in schizophrenia.