Single nuclei RNA-sequencing to map adipose cellular populations and senescent cells in older subjects

衰老的特征是脂肪组织的扩张(即肥胖)，这在 许多老年性疾病的病理生理学，包括2型糖尿病，动脉粥样硬化性血管疾病， 阿尔茨海默氏症和一些癌症。脂肪组织由脂肪细胞、免疫细胞、内皮细胞组成 干细胞、干细胞/基质细胞，以及以前未描述的细胞群。脂肪组织还含有 经历了细胞衰老的细胞，一种以细胞周期停滞和 衰老相关分泌表型(SASP)，可引起炎症、细胞毒性和代谢 其他细胞和组织的功能障碍。最近的研究表明，衰老与 脂肪细胞群体和亚群体，这些变异可能参与了 衰老与衰老相关疾病的病因学。然而，脂肪组织细胞成分的精确轮廓 由于缺乏针对众多细胞亚群的强大的细胞表面标记，这一研究受到了限制。 单细胞(Sc)rna seq是一种新的高分辨率方法，能够在全球范围内鉴定细胞。 组织中的种群和亚群(已知的和新鉴定的)。我们已经开发出一种单核 (SN)基于RNA-seq的方法(scRNA-seq的变体)，允许出色的识别、分离和 脂肪细胞群体的聚集，包括成熟脂肪细胞、免疫细胞、内皮细胞和 间充质干细胞。尽管SnRNA-seq也是一种很有前途的鉴定和鉴定 对于正在经历衰老的细胞，它还没有被用来更充分地阐明这种细胞在 衰老生物学和衰老相关代谢性疾病的病因学。 在目标1中，我们将在基线的三个队列中通过SnRNA-seq进行脂肪组织分子图谱： 年轻的瘦人、年长的瘦人和年长的肥胖者。我们将在这些主题中开发分子图谱，以 测试这一假设，即衰老和衰老加肥胖都会有不同的脂肪组织分子图谱。 在老年肥胖受试者的子组中，我们还将测试生活方式干预是否改变了全球 脂肪组织中的分子图谱与年轻和年长瘦削个体的图谱更接近。 在目标2中，我们将重点研究脂肪组织的识别、量化和功能特征 衰老的细胞。次级目标2A将检验脂肪的数量和功能(即SASP)的假设 组织衰老细胞会随着年龄的增长而增加，肥胖症会进一步增强，而且这种生活方式 干预(来自目标1)将减少老年肥胖者的衰老细胞负担。在子目标2B中，我们将 对一组老年肥胖受试者(来自目标1)使用感觉剂，以确定是否清除 衰老细胞可以改善新陈代谢结果。这个子目标将直接测试细胞衰老理论 并将作为生活方式干预潜在的抗衰老作用的积极对照。

Aging is characterized by an expansion in adipose tissue (i.e. obesity), which plays a key role in the pathophysiology of many aging-diseases, including type 2 diabetes, atherosclerotic vascular disease, Alzheimer’s disease, and some cancers. Adipose tissue is composed of adipocytes, immune cells, endothelial cells, stem/stromal cells, and previously uncharacterized cellular populations. Adipose tissue also contains cells that have undergone cellular senescence, a state characterized by the arrest of the cell cycle and a senescence-associated secretory phenotype (SASP), which induces inflammation, cytotoxicity, and metabolic dysfunction in other cells and tissues. Recent research suggests that aging is associated with changes in adipose cellular populations and subpopulations, and that these variations may be involved in the biology of aging and etiology of aging-related diseases. Yet, the precise profiling of adipose tissue cellular composition has been limited due to a lack of robust cell surface markers for the numerous cellular subpopulations. Single-cell (sc) RNA seq is a novel high-resolution methodology that enables global identification of cellular populations and subpopulations (known and newly identified) in tissues. We have developed a single nuclei (sn)RNA-seq based method (a variation of scRNA-seq) that allows excellent identification, separation and clustering of adipose cellular populations, including mature adipocytes, immune cells, endothelial cells, and mesenchymal stem cells. Although snRNA-seq also is a promising tool for identification and characterization of cells undergoing senescence, it has not been used to more fully elucidate the importance of such cells in the biology of aging and the etiology of aging-related metabolic diseases. In Aim 1 we will conduct adipose tissue molecular profiling via snRNA-seq in three cohorts at baseline: younger lean, older lean, and older obese individuals. We will develop molecular atlases in these subjects to test the hypothesis that both aging and aging plus obesity will have distinct adipose tissue molecular profiles. In a subgroup of older obese subjects we will also test whether a lifestyle intervention changes the global molecular profile in adipose tissue to a profile closer to that in younger and older lean individuals. In Aim 2 we will focus on the identification, quantification, and functional characterization of adipose tissue senescent cells. Sub Aim 2A will test the hypotheses that the amount and function (i.e. SASP) of adipose tissue senescent cells will be elevated with aging and further enhanced by obesity, and that the lifestyle intervention (from Aim 1) will reduce senescent cell burden in older obese subjects. In Sub Aim 2B we will administer senolytic agents to a subgroup of older obese subjects (from Aim 1) to determine whether clearance of senescent cells improves metabolic outcomes. This Sub Aim will directly test the cellular senescence theory and will serve as a positive control for the lifestyle intervention regarding its potential anti-senescence effect.