Genetic and Environmental Determinants of Triglycerides (GOLDN)
研究概览
详细说明
BACKGROUND:
Hypertriglyceridemia is emerging as an important predictor of atherosclerosis, and recent evidence suggests related phenotypes of triglycerides (TGs), such as TG remnant particles and small lactate dehydrogenase (LDL) particles, are particularly atherogenic. There is considerable variation in the response of TGs and related phenotypes to the environment.
The study is in response to a Request for Applications (RFA) entitled " Interaction of Genes and Environment in Shaping Risk Factors for Heart, Lung, Blood, and Sleep Disorders". The RFA was released in October, 2001.
DESIGN NARRATIVE:
Measurements will be collected before and after a dietary fat challenge to assess postprandial TGs and related atherogenic phenotypes (VLDL TGs, chylomicron TGs, TG remnant particles, high-density lipoprotein(HDL) and low density lipids (LDL) particle sizes, total cholesterol, LDL-C, and HDL-C). In families with 2 or more members in a sibship with high TGs (>= 130 mg/dl), the authors will conduct a short-term, placebo-controlled, randomized trial of fenofibrate in all willing and eligible family members (anticipated sample size = 1,200). A two-period crossover design will be executed with a 2-week washout between two 3-week treatment periods (placebo or micronized fenofibrate, 160 mg). About 1,000 family members have a Marshfield genome marker set available as part of national Heart Lung and Blood (NHLBI) FHS; the remaining 1,400 will be typed using the same marker set. They will conduct genome-wide linkage analyses using state-of-the-art methods to localize novel genetic loci contributing to TG response in the context of fat loading and fenofibrate treatment. They will type 15 single nucleotide polymorphisms (SNPs) in ten candidate genes known to contribute to the response of TGs to dietary fat and fenofibrate, and create haplotypes for association studies. They will use combinatorial partitioning methods and neural networks to test association of the individual SNPs and haplotypes with response to the two environmental interventions. The identification of genetic loci that predict TG response in the presence of two disparate contexts, fat loading and fibrate therapy, may provide insights into genetic pathways (a) predisposing to hypertriglyceridemia, ultimately leading to avenues for primary prevention, and (b) predicting response to TG lowering, leading to new drug targets for hypertriglyceridemia.
研究类型
注册 (实际的)
参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
取样方法
研究人群
描述
Inclusion criteria:
- ≥18 years of age
- fasting TGs <1,500 mg/dl
- willingness to participate in the study and attend the scheduled clinic exams
- member of a family with at least two members in a sibship
- aspartate aminotransferase (AST) and alanine aminotransferase (ALT) results within normal range
- creatinine ≤2.0 mg/dl
Exclusion criteria:
- history of liver, kidney, pancreas, or gall bladder disease or malabsorption
- current pregnancy
- insulin use
- use of lipid-lowering drugs (including prescription, over the counter, and nutriceuticals; volunteers taking these agents were withdrawn from them at least 4 weeks prior to the study with physician's approval)
- use of warfarin
- women of childbearing potential not using an acceptable form of contraception
- known hyper-sensitivity to fenofibrate
- history of pancreatitis within 12 months prior to enrollment
学习计划
研究是如何设计的?
设计细节
研究衡量的是什么?
主要结果指标
结果测量 |
措施说明 |
大体时间 |
---|---|---|
describe the association between blood lipids and gene variants
大体时间:3 weeks after start of fenofibrate intervention // 3 weeks after start of fenofibrate intervention
|
Blood lipids were measured by the following: triglyceride, high-density cholesterol, low-density cholesterol concentrations.
We will describe the association between blood lipids and gene variants.
|
3 weeks after start of fenofibrate intervention // 3 weeks after start of fenofibrate intervention
|
合作者和调查者
调查人员
- 首席研究员:Donna Arnett、University of Alabama at Birmingham
出版物和有用的链接
一般刊物
- Fretts AM, Follis JL, Nettleton JA, Lemaitre RN, Ngwa JS, Wojczynski MK, Kalafati IP, Varga TV, Frazier-Wood AC, Houston DK, Lahti J, Ericson U, van den Hooven EH, Mikkila V, Kiefte-de Jong JC, Mozaffarian D, Rice K, Renstrom F, North KE, McKeown NM, Feitosa MF, Kanoni S, Smith CE, Garcia ME, Tiainen AM, Sonestedt E, Manichaikul A, van Rooij FJ, Dimitriou M, Raitakari O, Pankow JS, Djousse L, Province MA, Hu FB, Lai CQ, Keller MF, Perala MM, Rotter JI, Hofman A, Graff M, Kahonen M, Mukamal K, Johansson I, Ordovas JM, Liu Y, Mannisto S, Uitterlinden AG, Deloukas P, Seppala I, Psaty BM, Cupples LA, Borecki IB, Franks PW, Arnett DK, Nalls MA, Eriksson JG, Orho-Melander M, Franco OH, Lehtimaki T, Dedoussis GV, Meigs JB, Siscovick DS. Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians. Am J Clin Nutr. 2015 Nov;102(5):1266-78. doi: 10.3945/ajcn.114.101238. Epub 2015 Sep 9.
- Tanaka T, Ngwa JS, van Rooij FJ, Zillikens MC, Wojczynski MK, Frazier-Wood AC, Houston DK, Kanoni S, Lemaitre RN, Luan J, Mikkila V, Renstrom F, Sonestedt E, Zhao JH, Chu AY, Qi L, Chasman DI, de Oliveira Otto MC, Dhurandhar EJ, Feitosa MF, Johansson I, Khaw KT, Lohman KK, Manichaikul A, McKeown NM, Mozaffarian D, Singleton A, Stirrups K, Viikari J, Ye Z, Bandinelli S, Barroso I, Deloukas P, Forouhi NG, Hofman A, Liu Y, Lyytikainen LP, North KE, Dimitriou M, Hallmans G, Kahonen M, Langenberg C, Ordovas JM, Uitterlinden AG, Hu FB, Kalafati IP, Raitakari O, Franco OH, Johnson A, Emilsson V, Schrack JA, Semba RD, Siscovick DS, Arnett DK, Borecki IB, Franks PW, Kritchevsky SB, Lehtimaki T, Loos RJ, Orho-Melander M, Rotter JI, Wareham NJ, Witteman JC, Ferrucci L, Dedoussis G, Cupples LA, Nettleton JA. Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. Am J Clin Nutr. 2013 Jun;97(6):1395-402. doi: 10.3945/ajcn.112.052183. Epub 2013 May 1.
- Blanco-Rojo R, Delgado-Lista J, Lee YC, Lai CQ, Perez-Martinez P, Rangel-Zuniga O, Smith CE, Hidalgo B, Alcala-Diaz JF, Gomez-Delgado F, Parnell LD, Arnett DK, Tucker KL, Lopez-Miranda J, Ordovas JM. Interaction of an S100A9 gene variant with saturated fat and carbohydrates to modulate insulin resistance in 3 populations of different ancestries. Am J Clin Nutr. 2016 Aug;104(2):508-17. doi: 10.3945/ajcn.116.130898. Epub 2016 Jul 20.
- Slade E, Irvin MR, Xie K, Arnett DK, Claas SA, Kind T, Fardo DW, Graf GA. Age and sex are associated with the plasma lipidome: findings from the GOLDN study. Lipids Health Dis. 2021 Apr 3;20(1):30. doi: 10.1186/s12944-021-01456-2.
- Aslibekyan S, Almasy L, Province MA, Absher DM, Arnett DK. Data for GAW20: genome-wide DNA sequence variation and epigenome-wide DNA methylation before and after fenofibrate treatment in a family study of metabolic phenotypes. BMC Proc. 2018 Sep 17;12(Suppl 9):35. doi: 10.1186/s12919-018-0114-0. eCollection 2018.
- Dashti HS, Aslibekyan S, Scheer FA, Smith CE, Lamon-Fava S, Jacques P, Lai CQ, Tucker KL, Arnett DK, Ordovas JM. Clock Genes Explain a Large Proportion of Phenotypic Variance in Systolic Blood Pressure and This Control Is Not Modified by Environmental Temperature. Am J Hypertens. 2016 Jan;29(1):132-40. doi: 10.1093/ajh/hpv082. Epub 2015 Jun 4.
- Frazier-Wood AC, Kabagambe EK, Wojczynski MK, Borecki IB, Tiwari HK, Smith CE, Ordovas JM, Arnett DK. The association between LRP-1 variants and chylomicron uptake after a high fat meal. Nutr Metab Cardiovasc Dis. 2013 Nov;23(11):1154-8. doi: 10.1016/j.numecd.2012.12.007. Epub 2013 Feb 26.
研究记录日期
研究主要日期
学习开始
初级完成 (实际的)
研究完成 (实际的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (估计)
研究记录更新
最后更新发布 (估计)
上次提交的符合 QC 标准的更新
最后验证
更多信息
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