The role of sex in genetic association studies of depression

项目摘要 抑郁症是美国最常见的精神疾病，影响着近4000万18岁的成年人， 老了女性比男性更容易受到抑郁症的影响。抑郁症既有遗传因素， 环境影响。抑郁症是一种多基因疾病（由于许多遗传因素的综合影响）。 抑郁症的发病率因性别而异。基因和抑郁症之间的关系是复杂的， 受性的影响。因此，了解抑郁症性别特异性差异的共同遗传基础， 很大的潜力，导致新的生物学理解的病因，抑郁症的女性相比， 并促进新的和更有效的药物治疗的发展。 这项建议的根本目标是发展和评估研究性别在遗传中作用的方法。 抑郁症的关联研究这些方法将应用于英国生物库。英国生物银行是 目前最大的生物库，代表了广泛的资源，既有遗传数据， 抑郁症表型（约474，000名参与者）。麻省总布里格姆生物银行 （约33，000名参与者）将用于验证和评估 接近。 该基金的重点是用于抑郁症的方法开发以及性别在遗传关联中的作用 抑郁症的研究;然而，我们的最终目标是开发适用于广泛范围的方法， 心理健康和成瘾表型的关系。我们还将创建公开可用的软件包， 实施这些新方法，使科学界能够广泛利用这些方法。

Project Abstract Depression is the most common mental illness in the U.S. affecting nearly 40 million adults age 18 years and older. Women are more likely to be affected by depression than men. Depression has both genetic and environmental influences. Depression is a polygenic disorder (due to the combined effects of many genetic variants) and depression rates differ by sex. The relationship between genes and depression is complex and influenced by sex. Thus, understanding the shared genetic basis of sex-specific differences for depression has great potential to lead to new biological understanding of the etiology of depression in females compared to males and to promote the development of novel and more effective pharmacotherapies. The underlying goal of this proposal is to develop and evaluate methods to examine the role of sex in genetic association studies of depression. These methods will be applied to the UK Biobank. The UK Biobank is one of the largest biobanks available at present and represents an extensive resource with both genetic data and depression phenotypes (approximately 474,000 participants). The Mass General Brigham Biobank (approximately 33,000 participants) will be used for validation and assessment of the robustness of the approaches. The grant focuses on methods development applied to depression and the role of sex in genetic association studies of depression; however, our ultimate goal is to develop approaches that are applicable to a broad range of mental health and addiction phenotypes. We will also create publicly available software packages to implement these new approaches, so that they will be broadly accessible to the scientific community.