Transcriptomic signatures of menopause across human tissues

项目总结 不幸的是，女性在绝经后增加了冠心病、中风和死亡的风险。这 可部分归因于许多女性经历的心血管疾病(CVD)风险因素的增加 绝经后，如血压、血脂水平和肥胖，但这些和背后的机制 人们对其他变化知之甚少。循环中雌激素水平的降低是与 更年期，雌激素可以转录调节许多基因，通常是以组织特有的方式。之前 关于绝经后基因表达变化的研究一直很有限，大多数都集中在 乳房、骨骼和女性生殖组织。我们假设转录检测 跨越更年期的心脏代谢组织将揭示分子过程 对增加的心血管疾病风险负责。尽管大多数人类缺少更年期状态信息 组织基因表达数据集，我们假设可以从基因表达推断绝经状态 数据。为了实现这一点，在目标1A中，我们将推断数百个女性基因组织的绝经状态 表达(GTEx)受试者基于其女性生殖组织的基因表达谱，使用 由已知生物学和更不可知的聚类法提供信息的降维方法的组合 以方法论为基础。由于GTEx受试者平均贡献了超过18个组织的样本，我们将有 还推断了非生殖组织的绝经状态信息。在子宫的初步分析中 基因表达数据(保留年龄作为协变量)，我们观察到明确的个体分类为 推论绝经前和推论绝经后组。在目标1B中，我们将使用推断的更年期 来自Aim 1A的状态信息，以识别在衍生组织中差异表达的基因和途径 根据推断的绝经前和绝经后妇女，重点关注与心脏代谢相关的组织 心血管疾病，如肝脏、脂肪和血管。最后，由于更年期状态是 在目标2中，我们将在心脏代谢的GTEx组织和其他组织中识别性别特异的衰老基因 现有的人类组织基因表达数据集，其中包含来自适当数量的年轻人的年龄和性别信息 (age&lt；50)和老年人(age&gt；50)，并检验基因表达与年龄的关系。 每个性爱子集。推断的绝经相关基因与时间序列没有表现出类似的相关性 男性组织中的年龄可能受更年期女性特有的荷尔蒙变化的影响 而不是更一般的老化过程。总体而言，这将是对 到目前为止，绝经对基因表达的影响，这一发现可以确定分子途径 绝经后妇女疾病负担增加的原因。

PROJECT SUMMARY Unfortunately, women have increased coronary heart disease, stroke, and mortality risk after menopause. This can be partially attributed to increases in cardiovascular disease (CVD) risk factors that many women experience after menopause, such as blood pressure, lipid levels, and adiposity, but the mechanisms behind these and other changes are poorly understood. A reduction in circulating estrogen levels is one of the major changes with menopause, and estrogen can transcriptionally regulate many genes, often in a tissue-specific manner. Prior studies of changes in gene expression with menopause have been limited, and most have been focused on breast, bone, and female reproductive tissues. We hypothesize that transcriptomic examination of cardiometabolic tissues across the menopause transition will reveal insight into the molecular processes responsible for the increased CVD risk. Though menopause status information is missing from most human tissue gene expression datasets, we hypothesize that menopausal status can be inferred from gene expression data. To accomplish this, in Aim 1A we will infer the menopausal status of hundreds of female Genotype-Tisssue Expression (GTEx) subjects based on the gene expression profiles of their female reproductive tissues, using a combination of dimensionality reduction approaches informed by known biology and more agnostic, clustering- based methodology. Since the average GTEx subject contributed samples from over 18 tissues, we will have inferred menopausal status information for non-reproductive tissues as well. In a preliminary analysis of uterus gene expression data (withholding age as a covariate), we observed clear classification of individuals into an inferred premenopausal and an inferred postmenopausal group. In Aim 1B, we will use the inferred menopausal status information from Aim 1A to identify genes and pathways that are differentially expressed in tissues derived from inferred premenopausal versus postmenopausal women, focusing on cardiometabolic tissues of relevance to cardiovascular disease, such as liver, adipose, and blood vessels. Finally, since menopause status is confounded by age, in Aim 2 we will identify sex-specific aging genes in cardiometabolic GTEx tissues and other existing human tissue gene expression datasets with age and sex information from suitable numbers of younger (age<50) and older (age >50) adults and examine the relationship of gene expression with chronological age in each sex subset. Inferred menopause-related genes that do not exhibit similar correlations with chronological age in male tissues are likely to be regulated by the female-specific hormonal changes during menopause rather than more general aging processes. Overall, this will be the most comprehensive evaluation of the effects of menopause on gene expression performed to date, and the findings could identify molecular pathways underlying the increased disease burden in post-menopausal women.