Drögemöller Britt I, Emsley Robin, Chiliza Bonginkosi, van der Merwe Lize, Wright Galen E B, Daya Michelle, Hoal Eileen, Malhotra Anil K, Lencz Todd, Robinson Delbert G, Zhang Jian-Ping, Asmal Laila, Niehaus Dana J H, Warnich Louise
aDepartment of Genetics, Stellenbosch University, Stellenbosch Departments of bPsychiatry cMolecular Biology and Human Genetics, Stellenbosch University, Cape Town dDepartment of Statistics, University of the Western Cape, Bellville, South Africa eDepartment of Psychiatry, Zucker Hillside Hospital, North Shore-Long Island Jewish Health System, New York, New York, USA.
Pharmacogenet Genomics. 2016 May;26(5):235-42. doi: 10.1097/FPC.0000000000000213.
Although antipsychotics are integral to the treatment of schizophrenia, drug efficacy varies between patients. Although it has been shown that antipsychotic treatment response outcomes are heritable, our understanding of the genetic factors that are involved remains incomplete. Therefore, this study aims to use an unbiased scan of the genome to identify the genetic variants contributing toward antipsychotic treatment response outcomes.
This study utilized whole-exome sequencing of patients on extreme ends of the treatment response spectrum (n=11) in combination with results from previous antipsychotic studies to design a panel of variants that were genotyped in two well-characterized first-episode schizophrenia cohorts (n=103 and 87). Association analyses were carried out to determine whether these variants were significantly associated with antipsychotic treatment response outcomes.
Association analyses in the discovery cohort identified two nonsynonymous variants that were significantly associated with antipsychotic treatment response outcomes (P<2.7 × 10(-5)), which were also significantly associated with the corresponding treatment response outcome in an independent replication cohort. Computational approaches showed that both of these nonsynonymous variants--rs13025959 in MYO7B (E1647D) and rs10380 in MTRR (H622Y)--were predicted to impair the functioning of their corresponding protein products.
The use of whole-exome sequencing in a subset of patients from a well-characterized cohort of first-episode schizophrenia patients, for whom longitudinal depot treatment response data were available, allowed for (i) the removal of confounding factors related to treatment progression and compliance and (ii) the identification of two genetic variants that have not been associated previously with antipsychotic treatment response outcomes and whose results were applicable across different classes of antipsychotics. Although the genes that are affected by these variants are involved in pathways that have been related previously to antipsychotic treatment outcomes, the identification of these novel genes will play an important role in improving our understanding of the specific variants involved in antipsychotic treatment response outcomes.
尽管抗精神病药物是治疗精神分裂症不可或缺的药物，但不同患者对药物的疗效存在差异。虽然已有研究表明抗精神病药物治疗反应结果具有遗传性，但我们对其中涉及的遗传因素的理解仍不完整。因此，本研究旨在通过对基因组进行无偏扫描，以识别对抗精神病药物治疗反应结果有影响的基因变异。
本研究对治疗反应谱两端的患者（n = 11）进行全外显子组测序，并结合先前抗精神病药物研究的结果，设计了一组变异体，在两个特征明确的首发精神分裂症队列（n = 103和87）中进行基因分型。进行关联分析以确定这些变异体是否与抗精神病药物治疗反应结果显著相关。
在发现队列中的关联分析确定了两个非同义变异体，它们与抗精神病药物治疗反应结果显著相关（P < 2.7 × 10⁻⁵），并且在独立的复制队列中也与相应的治疗反应结果显著相关。计算方法表明，这两个非同义变异体——MYO7B中的rs13025959（E1647D）和MTRR中的rs10380（H622Y）——预计会损害其相应蛋白质产物的功能。
对来自特征明确的首发精神分裂症患者队列中的一部分患者进行全外显子组测序，这些患者有纵向长效治疗反应数据，这使得（i）能够消除与治疗进展和依从性相关的混杂因素，以及（ii）识别出两个先前未与抗精神病药物治疗反应结果相关的基因变异体，其结果适用于不同类别的抗精神病药物。尽管受这些变异体影响的基因参与了先前与抗精神病药物治疗结果相关的途径，但这些新基因的识别将在提高我们对抗精神病药物治疗反应结果中涉及的特定变异体的理解方面发挥重要作用。
