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Enregistrement W4385335039 · doi:10.1101/2023.07.25.23293180

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus

2023· preprint· en· W4385335039 sur OpenAlexaff
Soo Heon Kwak, Ryan B. Hernandez-Cancela, Daniel DiCorpo, David E. Condon, Jordi Merino, Peitao Wu, Jennifer A. Brody, Jie Yao, Xiuqing Guo, Fariba Ahmadizar, Mariah Meyer, Murat Sincan, Josep M. Mercader, Sujin Lee, Jeffrey Haessler, Ha My T. Vy, Zhaotong Lin, Nicole D. Armstrong, Shaopeng Gu, Noah L. Tsao, Leslie A. Lange, N. Wang, Kerri L. Wiggins, Stella Trompet, Simin Liu, Ruth J. F. Loos, Renae Judy, Philip Schroeder, Natalie R. Hasbani, Maxime M. Bos, Alanna C. Morrison, Rebecca D. Jackson, Alex P. Reiner, JoAnn E. Manson, Ninad S. Chaudhary, Lynn K. Carmichael, Yii‐Der Ida Chen, Kent D. Taylor, Mohsen Ghanbari, Joyce B. J. van Meurs, Achilleas Pitsillides, Bruce M. Psaty, Raymond Noordam, Ron Do, Kyong Soo Park, J. Wouter Jukema, Maryam Kavousi, Adolfo Correa, Stephen S. Rich, Scott M. Damrauer, Catherine Hajek, Nam H. Cho, Marguerite R. Irvin, James S. Pankow, Girish N. Nadkarni, Robert Sladek, Mark O. Goodarzi, José C. Florez, Daniel I. Chasman, Susan R. Heckbert, Charles Kooperberg, Josée Dupuis, Rajeev Malhotra, Paul S. de Vries, Ching‐Ti Liu, Jerome I. Rotter, James B. Meigs

Notice bibliographique

RevuemedRxiv · 2023
Typepreprint
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenetic Associations and Epidemiology
Établissements canadiensMcGill University
Organismes subventionnairesOffice of Research Infrastructure Programs, National Institutes of HealthNational Institute on Minority Health and Health DisparitiesNational Center for Advancing Translational SciencesNational Human Genome Research InstituteUniversity of Pennsylvania Health SystemNational Heart, Lung, and Blood InstituteNational Institute on AgingKorea Health Industry Development InstitutePerelman School of Medicine, University of PennsylvaniaNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesEuropean CommissionAmerican Diabetes AssociationMississippi State Department of HealthGeorgia Clinical and Translational Science AllianceUniversity of PennsylvaniaNational Institute of Diabetes and Digestive and Kidney DiseasesJackson State UniversityNational Institutes of HealthRegeneron PharmaceuticalsFred Hutchinson Cancer Research CenterBristol-Myers SquibbU.S. Department of Veterans AffairsAmerican Heart AssociationU.S. Department of Health and Human Services
Mots-clésHazard ratioGenome-wide association studyMedicineType 2 diabetesProportional hazards modelType 2 Diabetes MellitusInternal medicineDiseaseDiabetes mellitusCoronary artery diseaseCohortCohort studyConfidence intervalGeneticsSingle-nucleotide polymorphismBiologyEndocrinologyGeneGenotype

Résumé

récupéré en direct d'OpenAlex

BACKGROUND Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD. METHODS From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D. RESULTS A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance ( P <5.0×10 -8 ): rs147138607 (intergenic variant between CACNA1E and ZNF648 ) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 – 1.32, P =3.6×10 -9 , rs11444867 (intergenic variant near HS3ST1 ) with HR 1.89, 95% CI 1.52 – 2.35, P =9.9×10 -9 , and rs335407 (intergenic variant between TFB1M and NOX3 ) HR 1.25, 95% CI 1.16 – 1.35, P =1.5×10 -8 . Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with P <0.05, and 5 were significant after Bonferroni correction ( P <0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 – 1.16) per 1 standard deviation increase ( P =1.0×10 -16 ). CONCLUSIONS The data point to novel and known genomic regions associated with incident CVD among individuals with T2D. CLINICAL PERSPECTIVE What is new? We conducted a large-scale multi-ancestry time-to-event GWAS to identify genetic variants associated with CVD among people with T2D. Three variants were significantly associated with incident CVD in people with T2D: rs147138607 (intergenic variant between CACNA1E and ZNF648 ), rs11444867 (intergenic variant near HS3ST1 ), and rs335407 (intergenic variant between TFB1M and NOX3 ). A polygenic score composed of known CAD variants identified in the general population was significantly associated with the risk of CVD in people with T2D. What are the clinical implications? There are genetic risk factors specific to T2D that could at least partially explain the excess risk of CVD in people with T2D. In addition, we show that people with T2D have enrichment of known CAD association signals which could also explain the excess risk of CVD.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,017

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,004
Bibliométrie0,0010,003
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,252
Écart entre enseignants0,239 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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