Distinct Transcriptional Signatures of Monocytes Treated with α-linolenic Acid and Docosahexaenoic Acid
Bibliographic record
Abstract
Docosahexaenoic acid (DHA) can be obtained directly from the diet or produced by elongation and desaturation of α-linolenic acid (ALA). Both are proposed to reduce inflammation associated with obesity, however, fewer studies have investigated ALA. The objective of this study was to evaluate the gene expression changes in monocytes induced by each fatty acid and to compare the predicted functional outcomes. RNA was extracted from THP-1 monocytes treated with ALA, DHA or vehicle for 48 h and then transcriptomics profiles were assessed by microarray. Multiple tools were used for data interpretation, including fold change analysis, Principal Component Analysis (PCA), Variable Importance Projection (VIP), Ingenuity Pathway Analysis (IPA) and Network Analyst. We found that the ALA and DHA treatments produced distinct profiles with many individual genes making small contributions to the separation between groups. Relative to vehicle treatment, many downregulated targets were similarly affected by both ALA and DHA. Several of these downregulated genes are involved in cholesterol synthesis and are regulated by miR-335–5p, a microRNA upregulated by both treatments. Consistently, IPA predicted similar pathways and functions are decreased by ALA and DHA, most notably cholesterol biosynthesis. In contrast, ALA and DHA upregulated unique gene sets and in agreement IPA predicted each treatment would activate distinct pathways and functions. ALA was strongly and uniquely predicted to increase infection responses while only DHA was predicted to increase oxidative phosphorylation. Finally, analysis of the protein-protein interaction network involving the genes modified by each fatty acid treatment allowed us to predict the most functionally important gene targets, which will be tested in future studies. These analyses have revealed both unique and overlapping effects of ALA and DHA on the monocyte gene expression profile, providing further evidence that they have distinct bioactivities. Many novel predictions were made and these will form the basis for future studies investigating the effects of ALA and DHA on human physiology. Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".