Meta Analysis of Epigenomic and Metabolomic Signatures of APOA2 Gene by Saturated Fat
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 602
- 试验地点
- 1
- 主要终点
- Body mass index (BMI)
研究概览
简要总结
Obesity is driven by genetic and environmental factors. Among the latter, diet is a most important one. The investigators refer to these combinations of genetic and dietary factors as 'gene-diet interactions.' Higher consumption of saturated fats (found mostly in foods of animal origin) has been associated with higher weight in people who were homozygotes for the minor allele at a genetic variant known as APOA2 -265 T>C (rs5082). In the current study, the investigators will seek to gain an understanding of the biological mechanisms driving this interaction. The investigators will select participants in three cohorts according to this genetic factor and conduct a series of molecular analyses (epigenetics, transcriptomics, and metabolomics). The analyses will identify epigenetic marks that are associated with saturated fat intake exclusively in subjects who carry this genetic factor. Moreover, the investigators will examine the association between epigenetic status and genotype at APOA2 and mRNA expression of the gene, and concentrations of metabolites in the blood. This study will increase the understanding of how genetics and diet act together to promote weight gain, and may eventually have implications for dietary recommendations that make use of genetic information.
详细描述
Background: Apolipoprotein A-II (APOA2) is a significant constituent of high-density lipoproteins (HDL) with an undefined biological role. A putative functional variant, -265 T>C (rs5082) within the APOA2 promoter, has been shown consistently to interact with saturated fat (SFA) intake to influence the risk of obesity.
Objective: This study will implement an integrative approach to characterize the molecular basis of this interaction.
Design: The investigators will conduct an epigenome-wide scan on 80 participants carrying either the rs5082 less common genotype (CC) or the most common genotype (TT) and consuming either a low (<22 g/d) or high (≥22 g/d) SFA diet, matched for age, sex, BMI, and diabetes status in the Boston Puerto Rican Health Study (BPRHS). The investigators then will validate the findings in selected participants in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) (n=379) and the Framingham Heart Study (FHS) (n=243). Transcription and metabolomics analyses will be conducted to determine the relationship between epigenetic status, APOA2 mRNA expression, and blood metabolites.
Data sources. The Boston Puerto Rican Health Study (BPRHS), the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), and the Framingham Heart Study (FHS) Study selection: In BPRHS, 40 participants with CC genotype at APOA2 -265T>C (rs5082) will be selected, with 20 reporting a low SFA intake (<22 g/d) and 20 indicating a high SFA intake (≥22 g/d). By matching age, sex, SFA intake, type 2 diabetes status, and BMI for the 40 participants with CC genotype, the second set of 40 participants with TT genotype of APOA2 -265T>C will be selected from the same population. In GOLDN, 107 participants with CC genotype and 272 with TT genotype for APOA2 -265T>C, who were not taking medication for hypertension, dyslipidemia, or diabetes, will be selected to validate the findings from BPRHS. In FHS, the investigators will include 73 unrelated participants with CC genotype and 170 with TT genotype at APOA2 -265T>C, who did not take medication for hypertension, dyslipidemia, or diabetes. Participants of each genotype will be further divided into two subgroups based on SFA intake: low, <22 grams/day, high, ≥22 grams/day.
Data Extraction. Genome-wide DNA methylation of isolated DNA samples in BPRHS and GOLDN was quantified using Illumina Infinium® human methylation 450K arrays (Illumina, San Diego, CA, USA). The methylation signal at each methylation site will be estimated as a β score, the proportion of total methylation-specific signal, and the detection P-value as the probability that total intensity for a given probe falls within the background signal intensity after normalization and quantity control check. FHS methylome data from dbGaP, accession#:phg000492.v2, where methylation statuses of 2,741 participants were measured in samples taken from participants attending their exam 8 visit between 2005 and 2008, using Illumina Infinium® human methylation 450K array. Methylation signals will be processed and normalized as for BPRHS and GOLDN. The investigators will obtain FHS transcriptome data from dbGaP under accession phe00002.v6. Metabolic profiling of plasma samples from those 80 participants of BPRHS for whom the methylome analysis will be performed by Metabolon, Inc. (Durham, NC, USA) Outcomes: Body mass index will be the only outcome. Data Synthesis. (1) Epigenome-wide analysis of APOA2 genotype, by high and low SFA intake, will be conducted in 80 matched case/control participants of BPRHS, replicated in selected participants of GOLDN, and FHS using linear mixed models. (2) A meta-analysis of the results from the three populations will be conducted using the meta R package.The comparison of allelic effect (beta) of APOA2 -265T>C from the meta-analysis between low and high SFA intake will be conducted with SAS 9.4 using a t-test. (3) Associations between epigenetic variants and APOA2 genotypes with APOA2 mRNA expression will be tested in FHS. (4) Metabolome analysis will be conducted in the same 80 matched case/control participants of BPRHS, and metabolites will be correlated with epigenetic variants at APOA2 locus. (5) Enriched metabolic pathways will be examined in relation to identified epigenetic variants at APOA2 region.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 90 Years(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •subjects with the apoA2 genotype TT or CC
排除标准
- •all other genotypes
结局指标
主要结局
Body mass index (BMI)
时间窗: One time point taken during the first visit of the participants to the studies used for the meta-analyses.
BMI calculated based on weight (kg) and height (meters) information from each participant using the equation BMI=kg/m2
次要结局
未报告次要终点
研究者
Jose Ordovas
Senior Scientist, Lab Director JM-USDA-HNRCA
Tufts University
