A Systems Approach to Uncover Novel Genes and Networks in Heart Failure

描述（由申请人提供）：心力衰竭的发病机制是复杂的，涉及异质性的遗传和环境因素。全基因组关联研究（GWAS）在心力衰竭方面取得了有限的成功，而导致人类心力衰竭的遗传因素仍然知之甚少。该领域的一个主要挑战是充分了解疾病的异质性，以便开发更有效和个性化的治疗方法。在本提案中，我们开发了一种新的方法，在明确定义的病理应激源下，通过杂交小鼠多样性面板（HMDP）使用GWAS系统地识别与心力衰竭有关的遗传因素和分子网络。我们相信这种新颖的方法有几个主要的优点。首先，HMDP由大约100个常见的自交系和重组自交系（RI）组成，这些菌株要么被完全测序，要么被密集地基因分型[超过14万个单核苷酸多态性（SNPs）]。其次，从小鼠心力衰竭模型中获得的见解应该为未来人类心力衰竭的机制、流行病学和遗传学研究提供相关指导。最后，慢性肾上腺素能过度驱动是公认的人类心力衰竭的主要原因，了解β - aar信号的遗传调节剂将产生重大影响。通过异丙肾上腺素（一种非选择性β受体激动剂）的精确慢性治疗，我们将能够以相对高通量的方式定量地造成病理损伤。因此，我们建议1)。通过定量分析HMDP小鼠对慢性异丙肾上腺素刺激的心功能和重塑，确定小鼠对慢性β -肾上腺素能刺激的心脏反应的遗传位点，并使用有效的混合模型算法进行关联分析，以确定与慢性β -肾上腺素能刺激心脏反应的不同特征相关的基因组区域和潜在候选基因。2）. 通过对异丙肾上腺素治疗前后心脏的全局表达阵列分析，建立有助于调节心脏功能和肥厚的途径，绘制与慢性β -肾上腺素能反应相关的基因表达差异的位点，并构建共表达网络，以确定与慢性β -肾上腺素能反应相关的子网络。简而言之，本提案中设计的系统方法将为基因及其相互作用网络带来新的见解，这些网络涉及β - aar信号和心力衰竭。

DESCRIPTION (provided by applicant): The pathogenesis of heart failure is complex, involving heterogeneous genetic and environmental factors. Genome-wide association studies (GWAS) have had limited success for heart failure and the genetic factors contributing to human heart failure remain poorly understood. A major challenge in the field is to fully understand the heterogeneity of the disease in order to develop more effective and personalized therapies. In this proposal, we have developed a novel approach by using GWAS across a hybrid mouse diversity panel (HMDP) under a well defined pathological stressor to systematically identify genetic factors and molecular networks implicated in heart failure. We believe this novel approach has several major advantages. First, the HMDP consists of ~100 common inbred and recombinant inbred (RI) strains which have been either entirely sequenced or densely genotyped [over 140,000 single nucleotide polymorphisms (SNPs)]. Second, the insights learnt from mouse models of heart failure should provide relevant guidance for future mechanistic, epidemiological and genetic studies in human. Lastly, Chronic excessive adrenergic overdrive is a well recognized major contributor to human heart failure and understanding the genetic modulators to betaAR signaling would have a major impact. With precisely administered chronic treatment of isoproterenol, a non-selective betaAR agonist, we will be able to quantitatively inflict a pathological insult in a relatively high-throughput manner. Accordingly, we propose to 1). Identify genetic loci in mouse contributing to cardiac responses to chronic beta-adrenergic stimulation by quantitative analysis of cardiac function and remodeling in the HMDP mice in response to chronic isoproterenol stimulation, and association analysis with an efficient mixed model algorithm to identify regions of the genome and potential candidate genes linking to the different features of cardiac response to chronic beta-adrenergic stimulation. 2). Model pathways contributing to regulation of heart function and hypertrophy by global expression array analyses of hearts before and after isoproterenol treatment to map loci contributing to differences in gene expression that are associated with chronic beta-adrenergic response, and construction co-expression networks to identify subnetworks associated with chronic beta-adrenergic response. In short, the systems approach designed in this proposal will bring novel insights to genes and their interacting networks implicated in betaAR signaling and heart failure.