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表明抑郁症与心血管疾病发病率和死亡率增加之间存在关联，但其机制尚不清楚。了解抑郁症如何导致心血管疾病（CVD）将有助于阐明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。随着越来越多的证据表明表观遗传调节在免疫和炎症反应中的重要性，我们的基本假设是参与免疫系统调节的表观遗传机制在抑郁症和心血管疾病之间的联系中很重要。我们的初步研究为这一假设提供了强有力的支持，我们的目标是确定重度抑郁症（MDD）病例和对照组之间白细胞甲基化谱的差异，并进一步评估这些甲基化变异是否参与CVD的发病机制。具体来说，我们将在一个现有的双胞胎队列中进行全基因组甲基化筛查，该队列与MDD不一致，并在独立队列中进行复制。这将是第一个探索可能的表观遗传修饰将抑郁症与心血管疾病联系起来的研究。澄清这些表观遗传修饰将提高我们对脑-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，以识别和治疗心血管疾病高风险个体。

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.