ArticleMolecular nutrition & food research2019
Integrated Analys of High-Fat Challenge-Induced Changes in Blood Cell Whole-Genome Gene Expression.
Article in Molecular nutrition & food research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- A nine-hub-gene signature of metabolic syndrome identified using machine learning algorithms and integrated bioinformatics.Bioengineered · 2021Article
- Integrated Analys of High-Fat Challenge-Induced Changes in Blood Cell Whole-Genome Gene Expression.Molecular nutrition & food research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
scopeSeveral studies have examined the whole-genome gene expression response in blood cells to high-fat challenges with differing results. The study aims to identify consistently up- or downregulated genes and pathways in response to a high-fat challenge using several integration methods. METHODS AND
resultsThree studies measuring the gene expression response to a high-fat challenge in white blood cells are evaluated for common trends using several integration methods. Overlap in differentially expressed genes between separate studies is examined, p-values of each separate study are combined, and data are analyzed as one merged dataset. Differentially expressed genes and pathways are compared between these methods. Selecting genes differentially expressed in the three separate studies result in 67 differentially expressed genes, primarily involved in circadian pathways. Using the Fishers p-value method and a merged dataset analysis, changes in 1097 and 1182 genes, respectively, are observed. The upregulated genes upon a high-fat challenge are related to inflammation, whereas downregulated genes are related to unfolded protein response, protein processing, cholesterol biosynthesis, and translation.
conclusionA general gene expression response to a high-fat challenge is identified. Compared to separate analyses, integrated analysis provides added value for the discovery of a consistent gene expression response.
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.