Genetically harmonized dietary intake and causal relationships with diabetes-related outcomes

遗传协调的饮食摄入量及其与糖尿病相关结果的因果关系

• 批准号: 10324581
• 负责人: Joanne Burnette Cole
• 金额: $ 8.8万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2022-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10324581
• 关键词: Address; Adherence; Alcohols; Biological Markers; Body mass index; Cardiometabolic Disease; Career Mobility; Clinical; Clinical Markers; Collaborations; Complex; Consumption; Data; Data Set; Diabetes Mellitus; Diet; Dietary Intervention; Dietary Practices; Dietary intake; Disease; Enzymes; Etiology; Faculty; Food; Food Patterns; Food Preferences; Foundations; Fruit; Genes; Genetic; Genetic Determinism; Genetic Markers; Genetic Variation; Genetic study; Genomics; Goals; Guidelines; Health; Heritability; Heterogeneity; Human; Human Genetics; Individual Differences; Intake; Intervention Studies; Intervention Trial; Life Style; Link; Maps; Mendelian randomization; Mentors; Meta-Analysis; Metabolic; Metabolic Diseases; Metabolism; Methodology; Methods; Milk; Nomenclature; Obesity; Obesity Epidemic; Observational Study; Outcome; Pathway Analysis; Phase; Phenotype; Population; Positioning Attribute; Recommendation; Research; Research Personnel; Risk Factors; Role; Series; Tea; Tissues; Training; Translations; Work; biobank; burden of illness; career; cohort; design; dietary; epidemiology study; experience; follow-up; food consumption; food environment; genetic analysis; genetic association; genetic epidemiology; genetic variant; genome wide association study; genome-wide; genomic locus; improved; mortality; multi-ethnic; novel; nutrition; nutritional epidemiology; nutritional genomics; olfactory receptor; phenome; preference; prevent; programs; skills; success; trait

ABSTRACT Unhealthful diet is a leading risk factor for diabetes and mortality worldwide. As the diabetes and obesity epidemics continue to rise, so does the contribution of dietary risk factors to global disease burden. There is an urgent need to identify which aspects of diet causally influence metabolic disease to guide more effective dietary recommendations. Teasing apart correlation from causation remains a challenge, and while numerous epidemiological studies have observationally linked diet to diabetes, there has been limited success with translation to intervention studies. Normal human genetic variation has both direct and indirect effects on dietary intake, with recent work establishing significant heritability and hundreds of genetic associations with numerous different foods and dietary patterns. However, combining dietary traits across studies for genetic analysis remains a challenge due to study differences in design, cultures, and preferences. We hypothesize shared genetic influences on dietary intake can act as the common reference to identify comparable diets across studies. In each of several cohorts, with both genetic and diet data, we will initiate new collaborations, derive quantitative food traits and dietary patterns, and conduct genome-wide association studies (GWAS) to create homologous GWAS datasets with study-specific dietary phenotypes and a common set of genetic markers. A series of genetic correlation analyses will be conducted to identify comparable foods and dietary patterns across diverse studies. Once identified, GWAS meta-analysis of comparable dietary phenotypes will improve power to detect novel and multi-ethnic genetic associations. To elucidate the direct and indirect genetic mechanisms of dietary intake at the locus and genome-wide levels we will conduct fine-mapping and gene prioritization, enrichment and pathway analysis, and genetic correlation and phenome-wide association studies (PheWAS). To address limitations with observational studies, Mendelian randomization (MR) causal inference will be performed using genetically predicted dietary intake and publicly available GWAS on diabetes-related outcomes to prioritize causal associations for intervention trials. Clustering of genetic loci by phenotypic correlations and causal effects will pinpoint genetic mechanisms of diet that causally influence metabolic disease. We will extend MR to all UK Biobank outcomes to map comprehensive causal bidirectional relationships with diet. Overall we will identify novel and multi-ethnic genetic associations with comparable dietary phenotypes across diverse studies to elucidate the mechanisms of dietary intake and uncover causal relationships between diet, diabetes, and overall human health. To achieve my goal of becoming an independent investigator in nutrigenomic and metabolic disease research, I have designed a detailed K99 plan with didactic coursework and co-mentoring by Drs. Florez, Hirschhorn, and Willett in metabolism, statistical genetics, and nutritional epidemiology. During the R00 phase, while conducting independent research and continuing to develop research skills, I will maintain and cultivate collaborations in nutrition and genetics and grow my research program.

摘要 不健康的饮食是世界范围内糖尿病和死亡率的主要风险因素。糖尿病和肥胖症 流行病继续上升，饮食危险因素对全球疾病负担的贡献也在继续上升。有一个 迫切需要确定饮食的哪些方面对代谢性疾病有因果影响，以指导更有效的饮食 建议。从因果关系中梳理出相关性仍然是一个挑战，尽管有许多 流行病学研究已经观察到饮食与糖尿病之间的联系，但在以下方面取得的成功有限 转化为干预研究。人类正常的遗传变异对饮食有直接和间接的影响 摄入量，最近的研究确定了显著的遗传力和数百种与许多 不同的食物和饮食模式。然而，将不同研究的饮食特征结合起来进行遗传分析 由于研究设计、文化和偏好的差异，这仍然是一个挑战。我们假设分享了 基因对饮食摄入量的影响可以作为确定研究中可比饮食的共同参考。 在几个队列中的每一个中，都有遗传和饮食数据，我们将启动新的合作，推导出定量的 食物特性和饮食模式，并进行全基因组关联研究(GWAS)以创建同源 具有研究特定饮食表型和一组共同遗传标记的GWAs数据集。一系列遗传基因 将进行相关性分析，以确定不同研究中的可比食物和饮食模式。 一旦确定，对可比饮食表型的GWAMeta分析将提高检测新的和 多种族遗传关联。阐明饮食摄入量的直接和间接遗传机制 在基因座和基因组水平上，我们将进行精细作图和基因优先排序、丰富和途径 分析，以及遗传相关性和表型全关联研究(Phewas)。要解决以下限制，请使用 观察性研究，孟德尔随机化(MR)因果推断将使用遗传 糖尿病相关结局的预测膳食摄入量和可公开获得的GWA，以确定原因的优先顺序 干预试验协会。通过表型相关性和因果效应对遗传基因座进行聚类 明确饮食对代谢性疾病产生影响的遗传机制。我们将把MR推广到整个英国 生物库结果，绘制全面的因果双向关系与饮食。 总体而言，我们将确定新的和多种族的遗传关联与可比的饮食表型 不同的研究来阐明饮食摄取的机制，并揭示饮食和饮食之间的因果关系， 糖尿病，以及整个人类健康。为了实现我成为一名独立调查员的目标 营养基因组学和代谢性疾病研究，我已经设计了一个详细的K99计划，教学课程和 由Florez博士、Hirschhorn博士和Willett博士共同指导新陈代谢、统计遗传学和营养学 流行病学。在R00阶段，同时进行独立研究并继续开发研究 技能，我将保持和培养在营养和遗传学方面的合作，并扩大我的研究计划。

项目成果

Genome-wide copy number variations in a large cohort of bantu African children.

• DOI: 10.1186/s12920-021-00978-z
• 发表时间: 2021-05-17
• 期刊: BMC medical genomics
• 影响因子: 2.7
• 作者: Yilmaz F;Null M;Astling D;Yu HC;Cole J;Santorico SA;Hallgrimsson B;Manyama M;Spritz RA;Hendricks AE;Shaikh TH
• 通讯作者: Shaikh TH

Genome-wide analysis of copy number variants and normal facial variation in a large cohort of Bantu Africans.

• DOI: 10.1016/j.xhgg.2021.100082
• 发表时间: 2022-01-13
• 期刊: HGG advances
• 作者: Null M;Yilmaz F;Astling D;Yu HC;Cole JB;Hallgrímsson B;Santorico SA;Spritz RA;Shaikh TH;Hendricks AE
• 通讯作者: Hendricks AE