Role of the Gut Microbiome in Reward Network Alterations in Obesity

肠道微生物组在肥胖奖励网络改变中的作用

• 批准号: 9895068
• 负责人: ARPANA GUPTA
• 金额: $ 11.7万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2022-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9895068
• 关键词: Address; Adjuvant Therapy; Affect; Agonist; Amino Acids; Aromatic Amino Acids; Behavior; Behavioral; Biologic Characteristic; Biological; Body Weight decreased; Brain; Branched-Chain Amino Acids; Calories; Clinical; Cognitive Therapy; Cross-Sectional Studies; Cues; Data; Desire for food; Development; Diet; Dietary Intervention; Eating; Eating Behavior; Effectiveness; Feces; Feeding behaviors; Female; Fiber; Firmicutes Bacteroidetes ratio; Food; Frequencies; Functional disorder; Funding; Future; Glutamates; Goals; Grant; Health; Homeostasis; Hunger; Immune; Immune system; Individual; Ingestion; Insulin Resistance; Intervention; Intervention Studies; Kynurenic Acid; Kynurenine; Lead; Life Style Modification; Link; Longitudinal Studies; Magnetic Resonance Imaging; Measures; Metagenomics; Modeling; N-Methylaspartate; Obesity; Obesity Epidemic; Outcome; Pathway interactions; Patients; Pattern; Peripheral; Pharmacological Treatment; Pharmacology; Phenotype; Play; Prediction of Response to Therapy; Prevalence; Prevention; Public Health; Quinolinic Acid; Recurrence; Reporting; Research; Rewards; Risk; Role; Sampling; Serum; Sex Differences; Shotguns; Signal Transduction; Source; Substance abuse problem; Systems Biology; Techniques; Testing; Therapeutic Intervention; Thinness; Treatment Efficacy; Treatment outcome; Tryptophan; Volatile Fatty Acids; Weight; Weight Gain; Woman; addiction; base; blood glucose regulation; clinical predictors; comorbidity; craving; emotion regulation; food addiction; food craving; gut microbiome; host-microbe interactions; male; medical complication; metabolomics; microbial; microbiome; microbiome alteration; neuroimaging; novel therapeutics; obesity treatment; patient subsets; pleasure; post intervention; predictive marker; primary outcome; psychologic; recruit; response; secondary outcome; somatosensory; weight maintenance

ABSTRACT The already funded K23 is focused on investigating the brain-immune interactions associated with maladaptive eating behaviors (disinhibited ingestive behaviors [DIB]). DIB is an important factor in the underlying pathophysiology observed in 25-37% of obese individuals where eating for pleasure overrides eating for homeostatic needs. This R03 application builds on the investigative efforts of the K23 by aiming to identify the role of altered brain gut microbiome (BGM) signaling contributing to DIB in the same obese sample recruited for the K23. I propose to address this goal both in a cross-sectional study, as well as in a longitudinal study determining changes in the BGM axis in response to two interventions: cognitive behavioral therapy (CBT) and a diet intervention (high fiber hypocaloric diet). While the cross-sectional study will identify alterations in BGM interactions between obese females with DIB compared to those without DIB, the longitudinal intervention studies aim to identify biomarkers that predict treatment responses and to identify biologically based subgroups of patients. The CBT intervention is aimed to strengthen prefrontal inhibitory influences on reward networks, thereby reversing maladaptive ingestive behaviors. The CBT intervention will be compared to a control diet intervention which will target the gut microbiome. The primary outcome is the normalization of DIB with the secondary outcome being weight loss. Recruitment will be restricted to females due to the known sex differences in DIB, with higher cravings, poorer weight loss and maintenance outcomes in obese females compared to obese males. The presence of DIB will be based on the Yale Food Addiction Scale (YFAS), a validated measure of disinhibited ingestion. Stool and serum to determine microbial-related measures (16sRNA sequencing, shotgun metagenomics, and metabolomics), and MRI to assess brain alterations in the extended reward network will be collected pre-and post-intervention and will be used to examine disinhibited ingestion-related differences and as predictors of clinical response. Advanced multivariate analytic techniques will be used to integrate data from multiple neuroimaging sources, microbiome and metabolite profiles, and behavioral data. This analysis will determine the unique variance associated with DIB in moderating the altered BGM axis at baseline and after the interventions. Integrating information from multiple central, peripheral, and behavioral sources will help increase the validity of the proposed BGM model and will identify phenotypes at increased risk for DIB and obesity. The proposed studies will focus on: 1) Identifying mechanisms underlying maladaptive eating behaviors in DIB, 2) identifying targets that can be modified by brain and gut targeted interventions, and 3) to generate pilot data for a larger mechanistic R01 proposal. Identifying biological characteristics of a subset of obese patients is essential for the development of more effective, personalized non-surgical treatments, which may be used in conjunction with pharmacological treatments.

抽象的 已经获得资助的 K23 专注于研究与适应不良相关的大脑免疫相互作用 饮食行为（解除抑制的摄入行为[DIB]）。 DIB是底层的一个重要因素 在 25-37% 的肥胖者中观察到病理生理学，其中为了快乐而吃的东西超过了为了快乐而吃的东西 体内平衡的需要。该 R03 应用程序以 K23 的调查工作为基础，旨在识别 在招募的同一肥胖样本中，脑肠道微生物组 (BGM) 信号改变导致 DIB 的作用 对于K23。我建议通过横断面研究和纵向研究来实现这一目标 确定 BGM 轴响应两种干预措施的变化：认知行为疗法 (CBT) 和 饮食干预（高纤维低热量饮食）。虽然横断面研究将确定 BGM 的变化 患有 DIB 的肥胖女性与没有 DIB 的肥胖女性之间的相互作用，纵向干预 研究旨在确定预测治疗反应的生物标志物并确定基于生物学的亚组 的患者。 CBT 干预旨在加强前额叶对奖励网络的抑制影响， 从而扭转适应不良的摄入行为。 CBT 干预将与对照饮食进行比较 针对肠道微生物组的干预措施。主要结果是 DIB 正常化 次要结果是减肥。由于性别已知，招募仅限女性 DIB 的差异，肥胖女性的食欲更高，减肥和维持结果更差 与肥胖男性相比。 DIB 的存在将基于耶鲁大学食物成瘾量表 (YFAS)，这是一个 经验证的去抑制摄入测量。粪便和血清以确定微生物相关指标 （16sRNA 测序、鸟枪法宏基因组学和代谢组学）和 MRI 来评估大脑的变化 扩展奖励网络将在干预前后收集，并用于检查解除抑制 摄入相关的差异并作为临床反应的预测因子。先进的多元分析技术 将用于整合来自多个神经影像来源、微生物组和代谢物概况的数据，以及 行为数据。该分析将确定与 DIB 相关的独特方差，以调节改变的 基线时和干预后的 BGM 轴。整合多个中枢、外周、各系统的信息 行为来源将有助于提高所提出的 BGM 模型的有效性，并将识别表型 DIB 和肥胖的风险增加。拟议的研究将重点关注：1）确定潜在机制 DIB 中的适应不良饮食行为，2) 确定可以通过大脑和肠道靶向改变的目标 干预措施，以及 3) 为更大的机械 R01 提案生成试点数据。识别生物 肥胖患者子集的特征对于开发更有效、个性化的治疗方案至关重要 非手术治疗，可与药物治疗结合使用。