Investigating the Association Between Genetic Variants and Response to a One-Year Lifestyle Intervention Targeting Metabolic Syndrome
Bibliographic record
Abstract
Although lifestyle interventions are generally successful for reducing metabolic syndrome (MetS) risk, significant variability in response between people exists. This thesis investigated factors that influence response to a 1-year, personalized, team-based lifestyle intervention targeting individuals with MetS. Using data collected from the Canadian Health Advanced by Nutrition and Graded Exercise (CHANGE) program, it was found that reductions in continuous MetS (cMetS) score at 3 months and 1 year were associated with two single nucleotide polymorphisms: rs662799 (A/G) in apolipoprotein A5 (APOA5) and rs1501299 (G/T) in adiponectin (ADIPOQ). Next, predictive models were developed to investigate if baseline variables could predict cMetS score at 1 year in the CHANGE program. Baseline systolic blood pressure and short-term changes in cMetS score were found to be predictive of 1-year cMetS score. Collectively, this thesis demonstrates the power of genetic and bioclinical measurements to unravel the inter-individual variability in response to lifestyle interventions targeting MetS.
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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".