DNA Diagnostics for Minimizing Metabolic Side-Effects of Antipsychotics

描述(申请人提供)：非典型抗精神病药物(AAP)用于治疗精神分裂症、双相情感障碍、精神病性抑郁和其他精神疾病。它们的缺点是药物引起的代谢紊乱，包括体重增加、高脂血症和糖尿病风险。这些糖尿病代谢症状(DIM)在不同药物和不同患者之间差异很大。我们建议开发一种名为“生理学”的新产品，为每个患者提供关于阿立哌唑、奥氮平、奎硫平、利培酮和齐拉西酮之间药物特定风险的个性化信息。生型由单核苷酸多态(SNPs)的多基因集合组成，通过生物数学算法解释，可以解释5个AAP之间DIM的大部分个体差异。专有的生理学组学技术和最先进的基因组实验室将通过分包分别与生活研究所(哈特福德CT)和肯塔基大学(列克星敦，肯塔基)的临床资源整合。我们在第二阶段的目标是发现能够预测这5种AAP之间的模糊副作用差异的SNPs，并将它们开发成精神科医生执业时的预测性诊断产品。我们将招募200名分别接受5个AAP治疗的患者，确定他们的体重和血脂特征，并获取他们的DNA，以建立临床登记和DNA储存库。我们将在100,000个SNPs上确定每个患者的基因型，覆盖所有~30,000个基因，并确定进化保守区域，以便在没有假设的情况下全面搜索DIMS的遗传标记。在第一阶段，合作者已经积累了374名接受AAP治疗的患者及其DNA的注册和DNA存储库。我们对接受奥氮平和利培酮治疗的患者的DNA进行了基因分型，在222个心血管、代谢和精神疾病候选基因的384个SNP阵列中进行了基因分型，并进行了生理基因组预测建模。我们发现了奥氮平和利培酮的新型药物特异性DIMS标志物，分别包括载脂蛋白E和瘦素受体基因。我们已经开发了一个原型生态型，并在一个独立的精神疾病人群中进行了测试。生理类型预测，约20%的患者体重与利培酮有关，~80%与奥氮平有关，这与已知的奥氮平平均疗效一致，也明确了许多人更大的利培酮特有风险。在第三阶段，作为FDA对生理型装置审查的一部分，计划对所有5个AAP进行前瞻性随机试验。生理型将帮助精神病学家避免副作用，根据每个患者的先天特征指导药物选择，这些特征直接从患者自己的DNA中解开和解释。拟议的计划将开发DNA诊断产品，以提高非典型抗精神病药物(AAP)的安全性，并改善精神分裂症和相关疾病的医疗管理，从而获得更好的结果。到目前为止，AAP副作用的发展是不可预测的，可能会使患者丧失能力，并阻碍患者的依从性。这些产品将使DNA引导医学成为可能：利用患者的个人基因组，确定哪种AAP最合适，并实施针对每个患者的临床保障措施。

DESCRIPTION (provided by applicant): Atypical antipsychotic drugs (AAPs) are indicated in the treatment for schizophrenia, bipolar disorder, psychotic depression and other psychiatric disorders. Their drawback is drug-induced metabolic derangements including weight gain, hyperlipidemia, and diabetic risks. These diabetic metabolic symptoms (DiMS) vary widely between drugs and from patient to patient. We propose to develop a novel product termed "Physiotype" to deliver personalized information for each patient on the drug- specific risks among aripiprazole, olanzapine, quetiapine, risperidone, and ziprasidone. The Physiotype consists of a multi-gene ensemble of single nucleotide polymorphisms (SNPs) that, interpreted with a biomathematical algorithm, may explain most of the inter-individual differences in DiMS among the 5 AAPs The proprietary physiogenomics technology and state-of-the-art genotyping laboratories of Genomas will be integrated with the clinical resources of the Institute of Living (Hartford CT) and of the University of Kentucky (Lexington KY), through subcontracts, respectively, to Dr. John Goethe and Dr. Jose de Leon. Our goal in Phase II is to discover SNPs predictive of differences in DiMS side effects between these 5 AAPs and to develop them into predictive diagnostic products for psychiatrists in their practice. We will recruit 200 patients treated by each of the 5 AAPs, characterize their weight and lipid profiles, and obtain their DNA for creation of a clinical registry and DNA repository. We will determine each patient's genotype at 100,000 SNPs covering all ~30,000 genes and also evolutionary conserved regions for a comprehensive, hypothesis-free search for genetic markers of DiMS. In Phase I, the collaborators have already accumulated a registry and DNA repository of 374 AAP-treated patients and their DNA. We have genotyped DNA from olanzapine- and risperidone-treated patients in the repository for an array of 384 SNPs in 222 cardiovascular, metabolic and psychiatric candidate genes and performed physiogenomic predictive modeling. We have discovered novel drug-specific DiMS markers for olanzapine and risperidone including the apolipoprotein E and leptin receptor genes, respectively. We have developed a prototype Physiotype and tested it in an independent psychiatric population. The Physiotype predicted that ~20% of patients have the most weight associated with risperidone and ~80% with olanzapine, which is consistent with known olanzapine average effects, and also pinpoints the greater risperidone-specific risk for many individuals. In Phase III, a prospective randomized trial of all 5 AAPs is planned as part of FDA review of a Physiotype device. The Physiotype will assist psychiatrists to avoid side effects by guiding drug selection for each patient according to innate characteristics unraveled and interpreted directly from the person's own DNA. The proposed program will develop DNA diagnostic products to enhance safety of atypical antipsychotic drugs (AAPs) and improve the medical management of schizophrenia and related disorders leading to better outcomes. As of now, the development of AAP side effects is unpredictable, potentially disabling to the patient, and discourages patient compliance. The products will enable DNA- guided medicine: the determination of which AAP is most suitable and the implementation of clinical safeguards, individualized to each patient, using his/her personal genome.