Abstract WP404: Intestinal Microbiome and Carotid Atherosclerosis
Bibliographic record
Abstract
Background: It is increasingly recognized that metabolic products of the intestinal microbiome may have important effects on cardiovascular disease. Methods: We studied dietary intake of precursors and plasma levels of toxic metabolic products of the intestinal microbiome in patients at extremes of carotid plaque burden, defined by residual scores (Res) in multiple regression with coronary risk factors: Protected (Res <-2, n = 83), Explained (Res -2 to 2 n = 82) and Unexplained atherosclerosis (Res >2 n = 62). Diet was assessed by a Harvard Food Frequency Questionnaire, and metabolites were measured by ultra-performance liquid chromatography (UPLC) coupled to mass spectrometry (MS). Microbiota were studied by DNA extraction from stool samples; bacteria in each sample were identified and quantitated based upon amplification and sequencing of 16S rRNA variable regions. Results: There were no significant differences in Mediterranean diet score, renal function, intake of protein, total choline, carnitine, phenylalanine or tyrosine or the fecal microbiota amongst the groups. However, plasma levels of trimethylamine n-oxide (TMAO), indoxylsulfate, p-cresylsulfate, and phenylacetylglutamine were significantly lower in Protected patients and higher in Unexplained patients (Table 1). Serum creatinine and 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid ( a marker of renal function) were not different among the groups. In this small sample we did not detect differences in the fecal microbiota. Discussion: Despite no difference in dietary precursors, renal function or the fecal microbiota, patients protected from atherosclerosis had lower levels and those with unexplained atherosclerosis had higher levels of toxic metabolites of the intestinal microbiome. This suggests their intestinal microbiota are responding differently to dietary intake of precursors from those of patients with explained atherosclerosis. Conclusion: This finding raises the potential for manipulation of the intestinal microbiota function through probiotic or prebiotic intake, or replacement of intestinal bacteria, to reduce the risk of carotid atherosclerosis and stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.009 | 0.001 |
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".