0000000000306608

AUTHOR

Cornelia Huth

0000-0003-2421-433x

showing 2 related works from this author

Meta-Analysis of the INSIG2 Association with Obesity Including 74,345 Individuals: Does Heterogeneity of Estimates Relate to Study Design?

2009

The INSIG2 rs7566605 polymorphism was identified for obesity (BMI≥30 kg/m2) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status (‘healthy population’, HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-va…

MaleCancer ResearchobesityLIVERMedizinPROTEINBioinformatics0302 clinical medicineINSIG2GENETICS & HEREDITYPOPULATIONGenetics (clinical)METABOLIC SYNDROME0303 health scienceseducation.field_of_studyINSIG2Intracellular Signaling Peptides and ProteinsUPSTREAMMiddle AgedINSULINResearch DesignMeta-analysisFemaleLife Sciences & BiomedicineMedical GeneticsResearch ArticleEXPRESSIONAdultAdolescentlcsh:QH426-470PopulationPublic Health and EpidemiologyCOMMON GENETIC VARIANTBiologyChildhood obesity03 medical and health sciencesYoung AdultGeneticsmedicineBiochemical Phenomena Metabolism and NutritionHumansObesityeducationMolecular BiologyEcology Evolution Behavior and Systematics030304 developmental biology0604 GeneticsScience & TechnologyPolymorphism GeneticMembrane ProteinsOdds ratioBODY-MASSmedicine.diseaseObesityPOLYMORPHISMlcsh:GeneticsGenetics PopulationMetabolic syndromeBody mass index030217 neurology & neurosurgeryDevelopmental BiologyDemographyGenome-Wide Association StudyPLoS Genetics
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Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study

2021

Abstract It is still unclear how genetic information, provided as single‐nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population‐based case‐cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo); selection of the most predictive SNPs among these literature‐co…

Oncologymedicine.medical_specialtyEpidemiologyFramingham Risk Score ; Metabochip ; Coronary Heart Disease ; Genomic Risk Prediction ; Priority-lassoPopulationCoronary DiseaseSingle-nucleotide polymorphismKoronare HerzkrankheitPolymorphism Single NucleotideRisk AssessmentCohort Studies03 medical and health sciencesRisk FactorsInternal medicinemedicineHumansgenomic risk predictionddc:610coronary heart diseaseMetabochipGenetikeducationGenotypingGenetics (clinical)030304 developmental biologypriority‐Lasso0303 health scienceseducation.field_of_studyFramingham Risk ScoreModels GeneticProportional hazards modelbusiness.industry030305 genetics & heredityGenomicsConfidence intervalddc:Coronary disease; GeneticsRisk factorsCohortFramingham risk scorebusinessDDC 610 / Medicine & healthPredictive modelling
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