Trial reportPloS one2014
Genomics of post-prandial lipidomic phenotypes in the Genetics of Lipid lowering Drugs and Diet Network (GOLDN) study.
Trial report in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Profiling of Endogenous and Gut Microbial Metabolites to Indicate Metabotype-Specific Dietary Responses: A Systematic Review.Advances in nutrition (Bethesda, Md.) · 2020Pooled it
- Age and sex are associated with the plasma lipidome: findings from the GOLDN study.Lipids in health and disease · 2021Trial
- Peripheral blood gene expression signatures which reflect smoking and aspirin exposure are associated with cardiovascular events.BMC medical genomics · 2018Trial
- Comparative analysis of postprandial changes in the lipidome of capillary plasma and dry blood spots of young women.European journal of nutrition · 2026Article
- Gene-environment interactions in the influence of maternal education on adolescent neurodevelopment using ABCD study.Science advances · 2024Article
- Review
- Expression Variation ofInternational journal of molecular sciences · 2023Article
- Determination of the postprandial cut-off value of triglyceride after a daily meal corresponding to fasting optimal triglyceride level in Chinese subjects.Frontiers in nutrition · 2023Article
- Review
- Proximal and distal effects of genetic susceptibility to multiple sclerosis on the T cell epigenome.Nature communications · 2021Article
- Polymorphisms ofAnimals : an open access journal from MDPI · 2021Article
- A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies.PloS one · 2021Article
- Nutrigenetics-personalized nutrition in obesity and cardiovascular diseases.International journal of obesity supplements · 2020Review
- Detecting responses to treatment with fenofibrate in pedigrees.BMC genetics · 2018Article
- Nutriepigenetics and cardiovascular disease.Current opinion in clinical nutrition and metabolic care · 2018Review
- CD36 Modulates Fasting and Preabsorptive Hormone and Bile Acid Levels.The Journal of clinical endocrinology and metabolism · 2018Article
- An efficient analytic approach in genome-wide identification of methylation quantitative trait loci response to fenofibrate treatment.BMC proceedings · 2018Article
- Homozygosity disequilibrium associated with treatment response and its methylation regulation.BMC proceedings · 2018Article
- Higher chylomicron remnants and LDL particle numbers associate with CD36 SNPs and DNA methylation sites that reduce CD36.Journal of lipid research · 2016Article
- Nutrigenomics, the Microbiome, and Gene-Environment Interactions: New Directions in Cardiovascular Disease Research, Prevention, and Treatment: A Scientific Statement From the American Heart Association.Circulation. Cardiovascular genetics · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundIncreased postprandial lipid (PPL) response to dietary fat intake is a heritable risk factor for cardiovascular disease (CVD). Variability in postprandial lipids results from the complex interplay of dietary and genetic factors. We hypothesized that detailed lipid profiles (eg, sterols and fatty acids) may help elucidate specific genetic and dietary pathways contributing to the PPL response. METHODS AND
resultsWe used gas chromatography mass spectrometry to quantify the change in plasma concentration of 35 fatty acids and 11 sterols between fasting and 3.5 hours after the consumption of a high-fat meal (PPL challenge) among 40 participants from the GOLDN study. Correlations between sterols, fatty acids and clinical measures were calculated. Mixed linear regression was used to evaluate associations between lipidomic profiles and genomic markers including single nucleotide polymorphisms (SNPs) and methylation markers derived from the Affymetrix 6.0 array and the Illumina Methyl450 array, respectively. After the PPL challenge, fatty acids increased as well as sterols associated with cholesterol absorption, while sterols associated with cholesterol synthesis decreased. PPL saturated fatty acids strongly correlated with triglycerides, very low-density lipoprotein, and chylomicrons. Two SNPs (rs12247017 and rs12240292) in the sorbin and SH3 domain containing 1 (SORBS1) gene were associated with b-Sitosterol after correction for multiple testing (P≤4.5*10(-10)). SORBS1 has been linked to obesity and insulin signaling. No other markers reached the genome-wide significance threshold, yet several other biologically relevant loci are highlighted (eg, PRIC285, a co-activator of PPARa).
conclusionsIntegration of lipidomic and genomic data has the potential to identify new biomarkers of CVD risk.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.