DNA Diagnostic System for Statin Safety and Efficacy

描述（由申请人提供）：他汀类药物是世界上处方最多的药物。它们在心血管疾病的一级和二级预防以及有益的多营养和抗炎作用方面的功效促进了越来越积极的使用和剂量。它们的主要临床相关安全风险是他汀类药物诱导的肌病（SIM），临床证明是一系列神经肌肉副作用（以下简称NMSEs）。NMSEs使3-20%的他汀类药物患者致残，需要改变治疗方法，降低依从性。NMSEs包括肌痛（肌肉疼痛、痉挛、无力）和肌炎（通过血清肌酸激酶（CK）活性升高监测）。NMSEs在不同药物和患者之间的程度不同。我们将开发一种名为SIM PhyzioType系统的新产品，为临床医生提供阿托伐他汀、辛伐他汀和瑞舒伐他汀这三种最常用的他汀类药物中最安全的他汀类药物的个性化信息。PhyzioType由一个多snp（单核苷酸多态性）集合组成，用生物数学算法进行解释，预测药物反应。作为我们前期工作的一部分，我们用222个心血管和神经肌肉候选基因的384个snp靶向阵列对242名接受他汀治疗的患者进行了基因分型，并进行了生理基因组关联。我们已经开发了一个原型PhyzioType系统，该系统结合了阿托伐他汀和辛伐他汀患者肌痛、血清CK活性和ldl降低的预测模型。我们已经发现了血管稳态和CK升高之间以及血清素受体和肌痛之间的机制联系。这些结果发表在《药物基因组学》和《肌肉与神经》杂志上。在这个SBIR项目中，Genomas的生理基因组学技术和最先进的基因分型实验室将与临床经验和博士资源相结合。Paul Thompson， Alan Wu和Bruce Gordon分别在Hartford医院，加州大学旧金山分校和Rogosin研究所，通过机构分包合同。我们将招募250名接受每种药物治疗的患者，并使用现有的临床记录来描述他们的NMSE和LDLc反应。我们将使用生理基因组学来识别3种他汀类药物中区分NMSEs风险的snp，并将其合并到SIM PhyzioType系统中。在第一阶段，我们将继续使用假设驱动的384个snp阵列进行基因分型。在第二阶段，我们将采用无假设的方法，对每位患者进行550,000个snp的基因分型，总基因组阵列覆盖所有染色体和线粒体上的所有~30,000个基因。这项工作也将有助于SIM的药理学和揭示新的药物靶点。我们将创建并验证SIM PhyzioType系统，该系统具有临床有用的NMSEs预测和3种他汀类药物的效力。在III期，一项前瞻性试验计划向FDA申请SIM PhyzioType产品的批准。

DESCRIPTION (provided by applicant): Statins are the most prescribed drugs in the world. Their efficacy in primary and secondary prevention of cardiovascular disease as well as beneficial pleiotrophic and anti-inflammatory effects have fostered increasingly aggressive usage and dosage. Their main clinically relevant safety risk is statin-induced myopathy (SIM) evidenced clinically as a constellation of neuromuscular side effects (hereinafter NMSEs). NMSEs are disabling to 3-20% of patients on statins, require alteration of therapy, and reduce compliance. NMSEs include myalgias (muscle aches, cramps, weakness) and myositis (monitored by elevation of serum creatine kinase [CK] activity). NMSEs vary in extent between drugs and from patient to patient. We will develop a novel product termed SIM PhyzioType" system to provide clinicians with individualized information for each patient on the safest statin drug among atorvastatin, simvastatin, and rosuvastatin, the 3 most prescribed statins. The PhyzioType consists of a multi-SNP (single nucleotide polymorphism) ensemble that, interpreted with a biomathematical algorithm, predicts drug response. As part of our preliminary work, we have genotyped 242 statin-treated patients with a targeted array of 384 SNPs from 222 cardiovascular and neuromuscular candidate genes, and performed physiogenomic associations. We have developed a prototype PhyzioType system incorporating predictive models for myalgia, serum CK activity, and LDLc reduction for atorvastatin and simvastatin patients. We have discovered a mechanistic link between vascular homeostasis and CK elevation, and between serotonin receptors and myalgia. These results have been published in Pharmacogenomics and Muscle & Nerve. For this SBIR Program, the physiogenomics technology and state-of-the-art genotyping laboratories of Genomas will be combined with the clinical experience and resources of Drs. Paul Thompson, Alan Wu, and Bruce Gordon, respectively, at Hartford Hospital, Univ. California San Francisco and Rogosin Institute, through institutional subcontracts. We will recruit to obtain 250 patients treated with each drug and use existing clinical records to characterize their NMSE and LDLc responses. We will use physiogenomics to identify those SNPs that differentiate the risk of NMSEs among the 3 statins and combine them into the SIM PhyzioType system. In Phase I, we will continue genotyping with the hypothesis-driven array of 384 SNPs. In Phase II, we will incorporate a hypothesis-free approach by genotyping each patient at 550,000 SNPs with a total genome array covering all ~30,000 genes on all chromosomes and the mitochondrion. This work will also contribute to the pharmacology of SIM and unravel new pharmaceutical targets. We will create and validate the SIM PhyzioType system with clinically useful prediction of NMSEs and potency for each of the 3 statins. In Phase III a prospective trial is planned for FDA approval of the SIM PhyzioType product.