Does Obesity or Hyperglycemia Alter Metabolic Endotoxemia?
Bibliographic record
Abstract
Obesity increases the risk of type 2 diabetes and non-alcoholic fatty liver disease, which are two interlinked diseases with a high health and economic burden. Obesogenic diets change the composition of intestinal microbes. Our objective is to move beyond associations of taxonomy and define specific microbial components that alter host immune and metabolic responses. Postbiotics are bacterial components or metabolites derived from living or dead bacteria that can modulate host immunity and metabolism. Lipopolysaccharide (LPS) is a classic example of a postbiotic that acts through toll-like receptor 4 (TLR4) to influence inflammation. Metabolic endotoxemia describes a chronic, low-level increase of LPS seen in blood during metabolic disease. However, it was recently shown that metabolic endotoxemia may be beneficial or detrimental to host metabolism depending on the type of LPS, which is dictated by different species of bacteria. It was previously unknown if obesity or hyperglycemia, is the main driver that alters metabolic endotoxemia. We hypothesized that obesity and hyperglycemia lead to an increase in the inflammatory properties of LPS found in the gut lumen and serum. We tested feces, and the systemic and portal serum obtained from mouse models of hyperglycemia (Akita+/- mice) and obesity ( ob/ob mice) for their TLR4 activation. It was found that hyperglycemia leads to increased fecal TLR4 activation, which can be reduced by lowering blood glucose in Akita+/- mice. In particular, a fed state promotes increased TLR4 activity in the serum of hyperglycemic mice. Elevated levels of TLR4 activity were observed in the serum of ob/ob mice. However, as these mice are transiently hyperglycemic, their elevated levels of blood glucose early on in their life may be a confounding factor leading to increased TLR4 activity. In conclusion, hyperglycemia is a main driver for metabolic endotoxemia and the increased inflammatory properties of LPS in the gut lumen. This research provides a framework of how specific metabolic disease characteristics influence inflammation and will help future studies looking to target the link between hyperglycemia and changes to the specific type of LPS. Canadian Institutes of Health Research, Farncombe Family Digestive Health and Research Institute This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".