Mental health conditions and cardiovascular diseases: association and risk stratification based on genetics, lifestyle, and biomarkers

关键词：精神健康；心血管疾病；风险分层；预测心血管疾病(CVD)的流行病学算法通常侧重于传统的风险因素(如吸烟)和生物标记物(如胆固醇)，尽管流行病学和孟德尔随机研究表明，包括严重抑郁障碍在内的精神健康状况是导致CVD的原因。然而，对于几个重要的遗留问题，这种关系还没有被很好地理解，例如，这种联系是动脉粥样硬化性心血管疾病特有的，还是延伸到其他心血管疾病，如心房颤动和心力衰竭？焦虑症，另一种常见的心理健康状况，也预示着心血管疾病吗？抑郁症、焦虑症和心血管疾病之间的潜在途径是什么？也许更重要的是，为什么一些有精神健康问题的人患上了心血管疾病，而另一些人没有，原因也是难以捉摸的。这为有心理健康状况的人进行心血管疾病的风险分层以及将心理健康纳入一般心血管疾病预测算法的可能性提供了独特的机会。目的：本博士的首要目标是使用现有的大数据(英国生物库和初级保健数据)调查心理健康和心血管疾病之间的关联，目标如下：1.研究焦虑障碍与心血管疾病类型(ASCVD、房颤、心力衰竭、PAD)的关联，以及在现有的心血管疾病预测模型(如AHA/ACC或SCORE)中加入焦虑的任何额外预测效用2.探索心理健康状况(包括抑郁和焦虑)与CVD3的联系的机制路径(中介)。确定风险因素(遗传、生活方式、生物标记物)与精神健康之间与心血管疾病风险之间的任何相互作用

Keywords: Mental health; cardiovascular; risk stratification; epidemiology Algorithms for predicting cardiovascular disease (CVD) often focus on traditional risk factors (e.g. smoking) and biomarkers (e.g. cholesterol) even though epidemiological and Mendelian randomisation studies have shown mental health conditions, including major depressive disorder, to be causal of CVD. However, the relationship is not well understood with several important remaining questions, e.g. Is the association specific to atherosclerotic CVD, or does it extend to other CVDs, such as atrial fibrillation and heart failure? Is anxiety disorder, another common mental health condition, also predictive of CVDs? What are the underlying pathways between depression, anxiety and CVD? Perhaps more importantly, the reasons why some people with mental health conditions developed CVD but some do not is also elusive. This presents a unique opportunity for risk stratifying people with mental health conditions for CVD, as well as to the potential inclusion of mental health in the general CVD prediction algorithms.Aims: The overarching aim of this PhD would be to investigate the association between mental health and CVD using existing big data (UK Biobank and primary care data) with the following objectives:1. To study the association between anxiety disorder and types of CVD (ASCVD, AF, HF, PAD), as well as any additional prediction utility of adding anxiety to existing CVD prediction models (e.g. AHA/ACC or SCORE)2. To explore the mechanistic pathways (mediators) connecting mental health conditions (including depression and anxiety) and CVD3. To identify any interactions between risk factors (genetics, lifestyle, biomarkers) and mental health in relation to the risk of CVD