Biomarkers of olanzapine-induced weight gain in mice

描述（由申请方提供）：三分之一服用抗精神病药奥氮平的患者出现重度体重增加和代谢综合征，包括内脏脂肪储存增加、胰岛素抵抗、糖耐量受损、血脂异常和高血压。在一项大型临床试验中，1,039名精神分裂症患者接受奥氮平治疗至少6个月，平均体重变化为+7.6 kg或接近初始体重的10%。然而，群体遵循正态分布，上四分位数体重增加>20 kg，下四分位数体重没有增加。这些数据与复杂的遗传性状一致，并表明有可能鉴定出对该ADR极端敏感的临床有用的生物标志物。最近的几篇出版物已经证明了在小鼠中建立奥氮平诱导体重增加模型的能力，并表明遗传背景影响对这种药物不良反应的易感性。在生物技术研究所，我们拥有下一代系统生物学平台，协作交叉（CC），旨在梳理调节复杂表型的机制，如药物反应。在第一年，我们在严格的实验条件下将100种遗传多样的CC小鼠品系暴露于类似人类浓度的奥氮平，并仔细测量体重，肥胖，血液化学和运动活动的变化。与人类数据一样，我们希望找到适合生物标志物发现的极端反应者。在第二年，我们专注于极端反应菌株（10个高和10个低），以确定调节体重增加易感性的基因网络。首先，我们将重新创建这20个细胞系并重新表型化，以测量药物反应表型的稳健性。其次，我们将使用下一代测序技术来评估药物和安慰剂治疗动物下丘脑的转录组和甲基化组。第三，我们将用一种独特的方法验证最有希望的转录本和甲基化变化。最后，我们将使用从极端小鼠的外周血中收集的RNA和DNA来评估这些生物标志物的预测有效性。然后可以在人类样本中测试出现的生物标志物，以确定跨物种的复制。我们期望为人类的此类工作确定一个可管理的高概率生物标志物列表，为药物基因组学领域提供典型候选基因或动力不足的全基因组搜索的替代方案。

DESCRIPTION (provided by applicant): One-third of patients taking the antipsychotic olanzapine experience severe weight gain and a metabolic syndrome consisting of increased visceral fat stores, insulin resistance, impaired glucose tolerance, dyslipidemia and hypertension. In a large clinical trial following 1,039 schizophrenia patients treated with olanzapine for at least 6 months, the average weight change was +7.6 kg or nearly 10 percent of initial body weight. The population, however, followed a normal distribution with the upper quartile gaining >20 kg and the lower quartile experiencing no weight gain. These data are consistent with a complex genetic trait and suggest that it may be possible to identify clinically-useful biomarkers of extreme sensitivity to this ADR. Several recent publications have demonstrated an ability to model olanzapine-induced weight gain in mice and suggest that genetic background influences susceptibility to this adverse drug reaction. At UNC, we have at our disposal a next-generation systems biology platform, the Collaborative Cross (CC), which was designed to tease out mechanisms regulating complex phenotypes, such as drug response. In year one, we expose 100 genetically diverse CC mouse strains to human-like concentrations of olanzapine under rigorous experimental conditions and carefully measure changes in body mass, adiposity, blood chemistry and locomotor activity. As with the human data, we expect to identify extreme responders ideal for biomarker discovery. In year two, we focus on the extreme responder strains (10 high and 10 low) to identify gene networks regulating susceptibility to weight gain. First, we will re-create these 20 lines and re-phenotype them to measure robustness of the drug response phenotype. Second, we will use next generation sequencing technologies to assess the transcriptome and methylome of the hypothalamus in drug and placebo treated animals. Third, we will validate the most promising transcript and methylation changes with a distinct methodology. Finally, we will evaluate the predictive validity of these biomarkers using RNA and DNA collected from the peripheral blood of the extreme mice. Biomarkers that emerge could then be tested in human samples to determine replication across species. We expect to identify a manageable list of high probability biomarkers for such work in humans, providing the pharmacogenomics field with an alternative to the typical Candidate gene or under-powered genome-wide search.