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Record W2950576078 · doi:10.1093/cdn/nzz041.or09-02-19

Body Composition and Metabolomics in the Alberta Physical Activity and Breast Cancer Prevention Trial (OR09-02-19)

2019· article· en· W2950576078 on OpenAlexaffabout
Kathleen M. McClain, Christine M. Friedenreich, Darren R. Brenner, Kerry S. Courneya, Charles Matthews, Steven C. Moore

Bibliographic record

VenueCurrent Developments in Nutrition · 2019
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsLean body massMetaboliteBody mass indexMetabolomicsInternal medicineBreast cancerEndocrinologyChemistryMedicineCancerBody weightChromatography

Abstract

fetched live from OpenAlex

Recent metabolomics studies have identified metabolic correlates of body mass index (BMI), but the degree to which correlations are driven by fat mass as opposed to lean mass has not been established. Our objectives were to 1) replicate findings of BMI-metabolite correlations, and 2) to describe the contributions of FM and LM to the BMI-metabolite associations. The Alberta Physical Activity and Breast Cancer Prevention Trial was a two-center randomized trial of healthy but inactive, postmenopausal women (N = 304). BMI (kg/m2) was calculated using measured weight and height, while whole body dual X-ray absorptiometry estimated fat mass and lean mass. Serum metabolite levels were measured by ultra-performance liquid chromatography and high-resolution/accurate mass spectrometer. We estimated partial Pearson correlations between 1053 metabolites and BMI, adjusting for age, smoking, and study site. Fat mass/m2 and lean mass/m2 correlations were estimated similarly, with mutual adjustment for one another to evaluate independent effects after accounting for their positive intercorrelation. Using a Bonferroni-corrected alpha-level <4.75 × 10–5, we observed 39 metabolites correlated with BMI (|r|:0.24–0.42; lowest p-value:7.53 × 10–14), including 25 metabolites that replicate previously-reported associations. Of metabolites correlated with BMI, only 14 were robustly correlated with fat mass/m2 (|r| > 0.20), and five had virtually no fat mass/m2 correlation (|r| < 0.10). Six metabolites were more strongly correlated with lean mass/m2 than with fat mass/m2. When we extended the analysis to all metabolites, we found another eight metabolites that were robustly correlated with fat mass/m2 (|r|:0.24–0.29) and three with lean mass/m2 (r:0.24–0.27) despite no statistically significant correlation with BMI. BMI may be insufficiently specific, in some cases, for studies of the metabolic effects of adiposity. Many BMI-related metabolites are only weakly correlated with fat mass; some are more directly related to lean mass than fat mass. For those metabolites already being studied in relation to disease risk (e.g., branched chain amino acids), our study demonstrates which aspect of body composition may primarily underlie metabolite-disease associations. National Institutes of Health Intramural Research Program, Canadian Breast Cancer Research Alliance.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.341
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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