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Record W4300527788 · doi:10.17615/nv6z-xb80

Meta-Analysis Investigating Associations Between Healthy Diet and Fasting Glucose and Insulin Levels and Modification by Loci Associated With Glucose Homeostasis in Data From 15 Cohorts

2020· article· en· W4300527788 on OpenAlexfundno aff
Panos Deloukas, Kathleen Stirrups, Frida Renström, Stephen B. Kritchevsky, Paul F. Jacques, L. Adrienne Cupples, Rozenn N. Lemaître, M. Carola Zillikens, Marju Orho‐Melander, Paul W. Franks, Yongmei Liu, Erik Ingelsson, Adela Hruby, Ilkka Seppälä, Ani Manichaikul, George Dedoussis, Albert Hofman, Mika Kähönen, Lawrence de Koning, Ulrika Ericson, Jennifer A. Nettleton, Constantina Papoutsakis, Frank J.A. van Rooij, Kari E. North, Julius S. Ngwa, Stefania Bandinelli, Josée Dupuis, Kurt K. Lohman, David S. Siscovick, Neelam Hassanali, David R. Jacobs, Luigi Ferrucci, Jacqueline C.M. Witteman, Ingrid B. Borecki, Christopher J. Groves, Frank B. Hu, Mark I. McCarthy, André G. Uitterlinden, Terho Lehtimäki, Ingegerd Johansson, Emily Sonestedt, Dariush Mozaffarian, Ιωάννα Ντάλλα, Jessica C. Kiefte–de Jong, Inga Prokopenko, Jack L. Follis, James B. Meigs, Vera Mikkilä, Nicola M. McKeown, Olli T. Raitakari, Marie‐France Hivert, Olov Rolandsson, Mary K. Wojczynski, Erika Ax, Jorma Viikari, Kenneth J. Mukamal, Stavroula Kanoni, Luc Djoussé, Andrea Ganna, Denise K. Houston, Maria Dimitriou, Genovefa Kolovou, Per Sjögren, James S. Pankow, Toshiko Tanaka

Bibliographic record

VenueUNC Libraries · 2020
Typearticle
Languageen
FieldNursing
TopicNutrition, Health and Food Behavior
Canadian institutionsnot available
FundersSchool of Medicine, University of North Carolina at Chapel HillFaculty of Medicine and Health, University of SydneyMedicinska fakulteten, Umeå UniversitetMedicinska Fakulteten, Lunds UniversitetSchool of Public Health, University of Texas Health Science Center at HoustonU.S. Department of AgricultureBrigham and Women's HospitalUniversity of North Carolina at Chapel HillTurun Yliopistollinen KeskussairaalaUniversity of MinnesotaMassachusetts General HospitalHarokopio UniversityTampereen YliopistoLunds UniversitetUniversity of WashingtonUppsala UniversitetTurun YliopistoUniversity of OxfordHelsingin YliopistoUmeå UniversitetNational Institute for Health and Care ResearchUniversity of Texas Health Science Center at HoustonWake Forest School of MedicineTaysUniversité de SherbrookeWellcome TrustUniversity of St. ThomasKarolinska Institutet
KeywordsMeta-analysisGlucose homeostasisInternal medicineEndocrinologyHomeostasisInsulinBiologyInsulin resistanceMedicine

Abstract

fetched live from OpenAlex

Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 US and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG (β = −0.004 mmol/L, 95% confidence interval: −0.005, −0.003) and FI (β = −0.008 ln-pmol/L, 95% confidence interval: −0.009, −0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.

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)0.001
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 score0.034
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.255
GPT teacher head0.329
Teacher spread0.074 · 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
Published2020
Admission routes1
Has abstractyes

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