Epigenetics, a Potential Mechanism Linking Depression to Cardiovascular Disease

描述（由申请人提供）：流行病学和临床研究已经证明抑郁症与心血管发病率和死亡率风险增加之间存在关联，但机制尚不清楚。了解抑郁症如何导致心血管疾病（CVD）将有助于澄清CVD的病理生理学，并制定干预措施，以降低与抑郁症相关的心血管风险。以前的研究，包括我们自己的研究，已经提供了证据表明炎症可能是一个关键因素。然而，这种神经-心脏相互作用的详细机制尚不清楚。与免疫和炎症反应中表观遗传调节重要性的新证据相呼应，我们的基本假设是，免疫系统调节中涉及的表观遗传机制在抑郁症和CVD之间的联系中很重要。基于我们的初步研究，这提供了强有力的支持，这一假设，我们的目标是确定差异甲基化谱之间的重性抑郁症（MDD）的情况下，对照组和进一步评估这些甲基化变异是否参与了CVD的发病机制。具体而言，我们将在现有的MDD不一致的双胞胎队列中进行全基因组甲基化筛查，并在独立队列中进行复制。这将是第一项探索将抑郁症与CVD联系起来的可能的表观遗传修饰的研究。这些表观遗传修饰的澄清将提高我们对脑-心相互作用的关键机制的理解，并最终指出更有效的一级预防策略，用于识别和治疗CVD风险最高的个体。

DESCRIPTION (provided by applicant): Epidemiological and clinical studies have demonstrated an association between depression and increased risk of cardiovascular morbidity and mortality, but the mechanisms are unclear. Understanding how depression leads to cardiovascular disease (CVD) will help clarify the pathophysiology of CVD and develop interventions to decrease the cardiovascular risk associated with depression. Previous studies, including our own, have provided evidence that inflammation may be a key factor. However, detailed mechanisms underlying this neuro-cardiac interaction are unknown. In syntony with emerging evidence on the importance of epigenetic regulation in immune and inflammatory responses, our fundamental hypothesis is that epigenetic mechanisms involved in immune system regulation are important in the link between depression and CVD. Based on our preliminary study which provides strong support to this hypothesis, we aim to identify the differential methylation profiles in leukocytes between major depressive disorder (MDD) cases and controls and further evaluate whether these methylation variations are involved in the pathogenesis of CVD. Specifically, we will perform a genome-wide methylation screening in an existing twin cohort discordant for MDD and a replication in independent cohorts. This will be the first study to explore possible epigenetic modification linking depression to CVD. Clarification of these epigenetic modifications will improve our understanding of key mechanisms underlying brain-heart interactions, and ultimately point to more effective primary prevention strategies for the identification and treatment of individuals at highest risk of CVD.