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Record W2979590648 · doi:10.3389/fgene.2019.00994

The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study

2019· article· en· W2979590648 on OpenAlexafffundabout
Juan de Toro‐Martín, Frédéric Guénard, Claude Bouchard, Angelo Tremblay, Louis Përusse, Marie‐Claude Vohl

Bibliographic record

VenueFrontiers in Genetics · 2019
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité Laval
FundersCanada Research ChairsHeart and Stroke Foundation of Canada
KeywordsObesityEnvironmental healthMedicineBiologyGeographyDemographyPsychologyInternal medicineSociology

Abstract

fetched live from OpenAlex

Background and aims. Obesity is a major health problem worldwide. Given the heterogeneous obesity phenotype, an optimal obesity stratification would improve clinical management. Since obesity has a strong genetic component, we aimed to develop a polygenic risk score (PRS) to stratify obesity according to the genetic background of the individuals. Methods. A total of 231 single nucleotide polymorphisms (SNP) significantly associated to body mass index (BMI) from 21 genome-wide association studies were genotyped or imputed in 881 subjects from the Quebec Family Study (QFS). The population was randomly split into discovery (80%; n=704) and validation (20%; n=177) samples with similar obesity (BMI  30) prevalence (27.8% and 28.2%, respectively). Family-based associations with obesity were tested for every SNP in the discovery sample and a weighed and continuous PRS231 was constructed. Generalized linear mixed effects models were used to test the association of PRS231 with obesity in the QFS discovery sample and validated in the QFS replication sample. Further, the Fatty Acid Sensor (FAS) study (n=141; 27.7% obesity prevalence) was used as an independent sample to replicate the results. Results. The linear trend test demonstrated a significant association of PRS231 with obesity in the QFS discovery sample (ORtrend=1.19 [95% CI, 1.14-1.24]; P=2.0x10-16). We also found that the obesity prevalence was significantly greater in the higher PRS231 quintiles compared to the lowest quintile. Significant and consistent results were obtained in the QFS validation sample for both the linear trend test (ORtrend=1.16 [95% CI, 1.07-1.26]; P=6.7x10-4), and obesity prevalence across quintiles. These results were partially replicated in the FAS sample (ORtrend=1.12 [95% CI, 1.02-1.24]; P=2.2x10-2). PRS231 explained 7.5%, 3.2% and 1.2% of BMI variance in QFS discovery, QFS validation, and FAS samples, respectively. Conclusions. These results revealed that genetic background in the form of a 231 BMI-associated PRS has a significant impact on obesity, but a limited potential to accurately stratify it. Further studies are encouraged on larger populations.

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 imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.090
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.276
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2019
Admission routes3
Has abstractyes

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