Decoding mechanisms underlying metabolic dysregulation in obesity and digestive cancer risk

肥胖和消化道癌症风险中代谢失调的解码机制

• 批准号: 10504203
• 负责人: EDWARD GIOVANNUCCI
• 金额: $ 134.29万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10504203
• 关键词: Address; Adipose tissue; Adult; Biological; Blood; Blood specimen; Body mass index; C-reactive protein; Chronic; Cocoa Powder; Cohort Studies; Colorectal; Colorectal Cancer; Communities; Data; Derivation procedure; Development; Diagnosis; Dual-Energy X-Ray Absorptiometry; Ensure; Ethnic Origin; Follow-Up Studies; Future; Gene Expression; General Population; Genotype-Tissue Expression Project; Glycosylated hemoglobin A; Goals; Health; Health Professional; Individual; Inflammation; Inflammation Process; Inflammatory; Insulin Resistance; Link; Lipoproteins; Liver; Logistics; Longitudinal cohort; Longterm Follow-up; Machine Learning; Malignant Neoplasms; Malignant neoplasm of liver; Measures; Mediating; Mediator of activation protein; Mendelian randomization; Metabolic; Modeling; Multivitamin; Nurses' Health Study; Obesity; Omega-3 Fatty Acids; Organ; Outcome Study; Pathway interactions; Pattern; Phenotype; Physicians; Play; Population Study; Prevention strategy; Preventive; Prospective cohort; Prospective cohort study; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; Proteins; Proteomics; Public Health; Recording of previous events; Regulator Genes; Regulatory Element; Research Personnel; Resources; Risk; Risk Factors; Role; Techniques; Tissues; Validation; Visceral; Vitamin D; Woman; Women' s Health; Work; base; biobank; cancer risk; case control; cohort; cost; epidemiology study; high risk; innovation; men; novel; novel strategies; prevent; programs; prospective; public database; risk prediction; success; therapeutic target; trait

PROJECT SUMMARY/ABSTRACT Obesity is associated with increased risk of at least 13 cancers. Of all cancers attributable to excess adiposity, colorectum and liver account for 55% of cancer among men and 48% among women, excluding reproductive cancers. Although most epidemiologic studies of obesity as a cancer risk factor evaluated body mass index (BMI), accumulating evidence for colorectal and liver cancers implicates viscerally located adiposity (and its closely related glycemic metabolic dysregulation) as the likely direct causal component. How visceral adiposity mechanistically predisposes its proximal organs to cancer is largely unknown. Inflammation undoubtedly plays a role in development and progression of malignancies, including colorectal and liver cancers; however, the large body of evidence for general inflammation processes and systemic markers like C-reactive protein (CRP) in relation to digestive cancers are underwhelming, possibly because most are non-specific to high-risk metabolically unhealthy obesity per se. Thus, distilling the inflammatory pathways and markers to identify those most reflective of the metabolically unhealthy obese state has immense potential to uncover key mechanisms and inform powerful broad-spectrum strategies for prevention. Techniques to obtain precise measures to characterize metabolically unhealthy obesity are often prohibitively costly and logistically infeasible in the context of large population-based studies. Therefore, we propose an innovative approach to address these gaps by (i) deriving novel proteomic-based inflammation signatures of metabolically unhealthy obesity (“Inflammotypes”) in cohorts with visceral adipose tissue quantified via dual-energy X-ray absorptiometry (DXA) and traits of glycemic metabolic function; then (ii) prospectively investigating these novel Inflammotypes in longitudinal cohorts with stored blood samples in relation to incident colorectal and liver cancer risk. We will characterize Inflammotypes via state-of-the-art Olink proteomic panel (384 inflammation-related proteins) to describe metabolically unhealthy obesity (i.e., higher visceral adiposity, with homeostatic model assessment for insulin resistance [HOMA-IR], hemoglobin A1c [HbA1c], or lipoprotein insulin resistance score [LPIR]). Machine learning analyses to identify the Inflammotypes will be replicated in an external cohort. We will then investigate the relationship between proteomic Inflammotypes with long-term risk of incident colorectal (1000 cases/1000 controls) and liver cancer (500 cases/500 controls), combining longitudinal cohorts with stored baseline bloods and long-term follow-up (median ranges 6.1-16.7 years). Based on compelling preliminary data, we hypothesize the combination of greater visceral adipose tissue and glycemic metabolic dysregulation are associated with abnormal profiles of circulating proteins, and that these novel Inflammotypes are independently predictive of long-term colorectal and liver cancer risks. These aims are closely aligned with the goals of the Metabolic Dysregulation and Cancer Risk Program, including enhancing identification of high-risk individuals, risk prediction, and elucidation of potential preventive and therapeutic targets.

项目摘要/摘要 肥胖与至少13种癌症的风险增加有关。在所有可归因于过度肥胖的癌症中， 男性癌症中55%是结直肠癌，女性中48%是结直肠癌，不包括生殖道。 癌症。尽管大多数将肥胖作为癌症危险因素的流行病学研究都评估了身体质量指数 (BMI)，不断积累的结直肠癌和肝癌的证据表明内脏部位肥胖(及其 密切相关的血糖代谢紊乱)可能是直接原因。内脏肥胖症 其近端器官易患癌症的机制在很大程度上是未知的。炎症无疑在起作用 在包括结直肠癌和肝癌在内的恶性肿瘤的发展和进展中发挥作用；然而， 关于一般炎症过程和C-反应蛋白(CRP)等系统标志物的大量证据 与消化系统癌症的关系平淡无奇，可能是因为大多数是非特异性的或高风险的 本身就是新陈代谢不健康的肥胖。因此，提取炎症途径和标记物来识别 最能反映代谢不健康的肥胖状态的人有巨大的潜力来揭示关键的机制 并为预防提供强大的广谱战略。获得精确措施的技术 描述代谢不健康的肥胖通常成本高得令人望而却步，在后勤上也不可行 大规模人口研究的背景。因此，我们提出了一种创新的方法来解决这些问题 代谢性不健康肥胖症的新的基于蛋白质组学的炎症特征 内脏脂肪组织通过双能X射线吸收法定量的队列(“炎症型”) (DXA)和血糖代谢功能的特点；然后(Ii)前瞻性地研究这些新的炎症类型 在储存血液样本的纵向队列中，研究与发生结直肠癌和肝癌风险的关系。我们会 通过最先进的Olink蛋白质组小组(384个炎症相关蛋白质)来表征炎症类型 描述代谢不健康的肥胖(即较高的内脏肥胖症，并进行体内平衡模型评估 胰岛素抵抗[HOMA-IR]、血红蛋白A1c[HbA1c]或脂蛋白胰岛素抵抗积分[LPIR])。 识别火焰类型的机器学习分析将在外部队列中复制。到时候我们会的 研究蛋白质组炎症类型与结直肠事件(1000)长期风险的关系 病例/1000对照)和肝癌(500病例/500对照)，结合纵向队列和存储 基线血样和长期随访(中位数为6.1-16.7年)。基于令人信服的初步调查 数据，我们假设更多的内脏脂肪组织和血糖代谢紊乱的组合 与循环蛋白的异常谱有关，这些新的炎症型是 独立预测结直肠癌和肝癌的长期风险。这些目标与 代谢失调和癌症风险计划的目标，包括加强对高危人群的识别 个人，风险预测，并阐明潜在的预防和治疗目标。