Multimodal omics approach to identify health to cardiometabolic disease transitions

多模式组学方法确定健康状况向心脏代谢疾病的转变

• 批准号: 10753664
• 负责人: Paivi Pajukanta
• 金额: $ 70.75万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-10 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10753664
• 关键词: ATAC-seq; Address; Adipocytes; Adipose tissue; Aorta; Automobile Driving; Biological; Biological Assay; Biological Markers; Biomedical Research; Body mass index; Cardiometabolic Disease; Caring; Cell Nucleus; Cells; Chromatin; Clustered Regularly Interspaced Short Palindromic Repeats; Data; Deterioration; Diabetes Mellitus; Disease; Environment; Environmental Risk Factor; Epigenetic Process; Fatty acid glycerol esters; Female; Gene Expression; Genes; Genetic; Genetic Transcription; Genome; Genomics; Genotype; Health; Health Transition; High Fat Diet; High Prevalence; Human; Individual; Inflammation; Inflammatory; Insulin Resistance; Knowledge; Ligands; Link; Lipids; Liver; Maps; Mediating; Medical; Mendelian randomization; Metabolic; Mexican; Molecular; Mus; Non-Insulin-Dependent Diabetes Mellitus; Normal tissue morphology; Obesity; Obesity Epidemic; Overnutrition; Overweight; Phenotype; Population Heterogeneity; Prevention; Protein Secretion; Publishing; RNA Sequences; Regulatory Element; Reporter; Role; Running; Sampling; Serum; Sex Differences; Sex Factors; Site; Small Interfering RNA; Stimulus; TREM2 gene; Testing; Thinness; Time; Tissue Sample; Tissues; Variant; Visceral; Weight; biobank; candidate identification; cardiometabolism; cell type; cohort; disorder risk; epidemiology study; epigenomics; experience; follow-up; functional genomics; gene discovery; gene environment interaction; genetic linkage analysis; genome wide association study; genomic data; global health; inflammatory marker; lipid biosynthesis; male; multimodality; multiple omics; non-alcoholic fatty liver disease; personalized strategies; polygenic risk score; prevent; response; risk variant; sex; single nucleus RNA-sequencing; single-cell RNA sequencing; subcutaneous; trait; transcriptome sequencing; transcriptomics

Abstract: The global obesity epidemic drives the high prevalence of cardiometabolic disorders (CMDs), including type 2 diabetes (T2D), and non-alcoholic fatty liver disease (NAFLD). Epidemiological studies have also established strong sex differences in CMDs. Obesity-induced low-grade inflammation and insulin resistance in adipose tissue (AT), their deteriorating impacts on the efficacy of adipogenesis, and subsequent ectopic fat storage into other cardiometabolic tissues, particularly liver, have been proposed as the key drivers of the CMD risks related to obesity. However, the mechanisms promoting the transitions from health-to-disease states in human fat depots have remained largely elusive. We hypothesize that there are transcriptional inflammatory markers and cell-type-specific changes in open chromatin pertinent to health-to-CMD transitions that can be discovered using single cell level and bulk omics analyses in fat cell-types and tissue. We also hypothesize that by elucidating molecular responses to obesity-related stimuli during adipogenesis we can discover candidate variants and genes with functional priors for formal identification of gene-sex and gene-environment interactions (i.e. GxSs and GxEs) underlying obesity-induced health-to-CMD transitions in large biobanks. In Aim 1, we will generate sex- and context-specific bulk and single cell level transcriptomics (RNA-seq) and epigenomics (ATAC- seq) data in two obesity-relevant fat depots, i.e. subcutaneous and visceral AT, to identify epigenetic and transcriptional markers for health-to-CMD transitions in six health-to-CMD stages comprising lean, overweight, and obese males and females with and without prediabetes, T2D, and NAFLD. We will also use existing serum samples to discover health-to-CMD transition biomarkers among the genes that differ between the six health/disease states and encode secreted proteins. We will test the top results for replication in independent omics cohorts, including Mexicans. In Aim 2, we will use a new function-to-variants omics approach to discover GxSs and GxEs involved in early transitions from health to CMD in males and females. We will generate functional genomics data in CMD-relevant human primary preadipocytes, extracted from fresh AT of normal weight, metabolically healthy males and females. These preadipocytes will be differentiated with and without key inflammatory stimuli to discover stimuli-responsive adipogenesis genes and cis-regulatory elements (CREs) that harbor regulatory variants in diverse populations. Subsequently, these variants will be fine-mapped using massively parallel reporter assay in (pre)adipocytes and functionally characterized using extensive variant-to- gene-linkage analysis and genomic perturbations (CRISPR and siRNA). The identified candidate SNPs will be tested for GxE and GxS effects on health-to-CMD transitions in large biobanks to verify their role in these critical transitions. Our preliminary results and ample previous experience with integrative multiomics approaches of CMDs provide a strong prior scientific rigor for the proposed Aims, and overall, accomplishing our Aims has a great potential to develop personalized strategies that prevent or postpone the onset of obesity-related CMDs.

翻译后摘要：全球肥胖症的流行驱动心脏代谢疾病（CMD）的高患病率， 包括2型糖尿病（T2 D）和非酒精性脂肪肝（NAFLD）。流行病学研究 还建立了强烈的性别差异的CMD。肥胖引起的低度炎症和胰岛素抵抗 在脂肪组织（AT）中，它们对脂肪生成的功效和随后的异位脂肪的恶化影响 储存到其他心脏代谢组织，特别是肝脏，已被认为是CMD的关键驱动因素 与肥胖有关的风险。然而，促进从健康状态向疾病状态过渡的机制， 人体脂肪库在很大程度上仍然是难以捉摸的。我们假设转录炎性因子 与健康到CMD转变相关的开放染色质中的标志物和细胞类型特异性变化 在脂肪细胞类型和组织中使用单细胞水平和批量组学分析发现。我们还假设， 通过阐明脂肪形成期间对肥胖相关刺激的分子反应，我们可以发现候选者 具有功能先验的变异体和基因，用于正式鉴定基因-性别和基因-环境相互作用 (i.e. GxSs和GxEs）在大型生物库中潜在的肥胖诱导的健康到CMD的转变。在目标1中，我们 产生性别和背景特异性的批量和单细胞水平的转录组学（RNA-seq）和表观基因组学（ATAC- seq）两个肥胖相关脂肪库（即皮下和内脏AT）中的数据，以鉴定表观遗传和 在包括瘦，超重， 以及患有和不患有前驱糖尿病、T2 D和NAFLD的肥胖男性和女性。我们还将使用现有的血清 样本，以发现健康到CMD过渡的生物标志物之间的基因，不同的六个 健康/疾病状态和编码分泌蛋白质。我们将在独立环境中测试复制的最佳结果 包括墨西哥人在内的经济学群体。在目标2中，我们将使用一种新的功能到变体组学方法来发现 GxSs和GxEs参与男性和女性从健康到CMD的早期过渡。我们将产生 从正常人新鲜AT中提取的CMD相关人原代前脂肪细胞的功能基因组学数据 体重，代谢健康的男性和女性。这些前脂肪细胞将在有和没有关键的分化 炎症刺激，以发现刺激响应性脂肪生成基因和顺式调节元件（克雷斯）， 在不同人群中存在调节变异。随后，这些变体将使用 在（前）脂肪细胞中进行大规模平行报告基因测定，并使用广泛的变体- 基因连锁分析和基因组扰动（CRISPR和siRNA）。确定的候选SNP将是 在大型生物库中测试GxE和GxS对健康到CMD转变的影响，以验证它们在这些关键过程中的作用。 过渡。我们的初步结果和丰富的经验，与综合多组学方法， CMD为提出的目标提供了强有力的科学严谨性，总体而言，实现我们的目标具有 开发个性化策略以预防或推迟肥胖相关CMD发作的巨大潜力。