Metabolomics Analysis of Serum and Urine After Bean Consumption by Patients with Peripheral Arterial Disease
Bibliographic record
Abstract
Peripheral artery disease (PAD) is symptomatic of systemic atherosclerosis, and is characterized by the presence of plaques that occlude the arteries of the lower extremities. PAD substantially increases the incidence for myocardial infarction, ischemic stroke, and cardiovascular death. The risk factors for PAD include advanced age (over 40 years), smoking, hypertension, diabetes mellitus, hyperlipidemia, and hyperhomocysteinemia. Treatments for PAD can be divided into three categories: risk‐factor modification, drug therapy, and catheter‐based endovascular intervention. Bean consumption has been shown to reduce risk factors of PAD (e.g. blood pressure, LDL‐cholesterol), however, beans have not been directly investigated as a dietary intervention in the PAD population. Given that common beans (pinto, red kidney, black and navy) are rich in dietary fibre, this component has been assumed to be responsible for the cholesterol‐lowering effects. However, beans also contain phenolic acids, which may explain their risk factor lowering actions. Objective To determine whether 8 weeks of bean consumption affects the profile of metabolites in serum and urine of individuals with PAD. A non‐targetted metabolomics approach was therefore employed to profile compounds in serum and urine associated with bean consumption and with PAD. Participants PAD patients (n=75) were randomly assigned to 3 groups (n=25/group): i. pulse‐free foods (rice instead of beans = control), ii. 1.5 cups/week, or iii. 3 cups/week of mixed cooked beans (pinto, red kidney, black and navy) for 8 weeks. Urine and serum were collected at baseline and week 8. Extraction Procedure Urine (250 μL) and serum (100 μL) were extracted with 500 μL and 250 μL of acetonitrile, respectively, and centrifuged (10,000 g, 10 min at 4ºC). The supernatants were dried under vacuum and kept at −20ºC. Dried samples were reconstituted in 200 μL of 1:4 acetonitrile:deionized water (urine) and in 100 μL of 4:1 acetonitrile:deionized water (serum) using glass inserts and brown Gas Chromatography vials for Liquid chromatography‐Quadrupole Time Of Flight‐Mass Spectrometry analysis. Results Several endogenous metabolites in serum and urine were significantly affected (P<0.05; ≥2‐fold change) by the consumption of beans relative to the comparator study foods. Specific alterations were detected in several class of compounds, including amino acids (His, Arg, Ser, Pro, Leu, Glu), peptides (Lys‐Ala‐His), glutathione, bile salts (glycocholic acid), phospholipids (PE, PS, PI, LysoPE) and products of arachidonic acid metabolism by cyclooxygenase (prostaglandin E2 p‐acetamidophenyl ester). Additionally, this approach detected a number of pharmaceuticals and their corresponding metabolites. In a subset of participants, the decrease in the metabolites of several anti‐hypertensive drugs in urine after 8 weeks of bean consumption suggested the existence of potential drug‐diet interactions that could affect the required dosage of certain anti‐hypertensive medications. Conclusion The use of a non‐targeted metabolomics approach in our study was invaluable as a screening tool to obtain insight into the biochemical pathways that are affected by bean consumption. Furthermore, by conducting these analyses on samples from individuals with PAD, it was revealed that bean consumption might influence management strategies for hypertension. Support or Funding Information Pulse Science Cluster, and Agriculture and Agri‐Food Canada, Natural Sciences and Engineering Research Council of Canada and Canada Foundation for Innovation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".