2024
Genomic insights into the comorbidity between type 2 diabetes and schizophrenia
Arruda A, Khandaker G, Morris A, Smith G, Huckins L, Zeggini E. Genomic insights into the comorbidity between type 2 diabetes and schizophrenia. Schizophrenia 2024, 10: 22. PMID: 38383672, PMCID: PMC10881980, DOI: 10.1038/s41537-024-00445-5.Peer-Reviewed Original ResearchBody mass indexType 2 diabetesType 2 diabetes riskEffect of body mass indexPutative effector genesN-methyl-D-aspartatePublic health challengeIncreased body mass indexLipid-related pathwaysRisk-increasing effectMulti-omics dataMendelian randomizationPotential causal relationshipGene expression studiesDirection of effectMental healthDrug repurposing opportunitiesAssociation signalsGenomic lociGenomic insightsHealth challengesEffector genesGenetic liabilityMass indexExpression studies
2023
W22. DISENTANGLING THE ROLES OF GENETICS AND BODY MASS INDEX ACROSS PSYCHIATRIC DISORDERS
Signer R, Seah C, Young H, de Pins A, Johnson J, Cote A, Huckins L. W22. DISENTANGLING THE ROLES OF GENETICS AND BODY MASS INDEX ACROSS PSYCHIATRIC DISORDERS. European Neuropsychopharmacology 2023, 75: s116. DOI: 10.1016/j.euroneuro.2023.08.213.Peer-Reviewed Original ResearchExpression quantitative trait lociBody mass indexGenome-wide association studiesEffect of body mass indexAssociation studiesAvailability of genome-wide association studyGenetic riskPhenome-wide association studyIndirect effect of body mass indexPsychiatric disordersBody mass index spectrumStatistical fine-mappingQuantitative trait lociGenetic risk modelsCell-type specific mannerTissue enrichmentImpact of body mass indexGWAS lociTranscriptome imputationGenomic lociWhole genomeFine-mappingTrait lociGenomic underpinningsPhenotypic consequences
2022
Mapping anorexia nervosa genes to clinical phenotypes
Johnson J, Cote A, Dobbyn A, Sloofman L, Xu J, Cotter L, Charney A, Consortium E, Birgegård A, Jordan J, Kennedy M, Landén M, Maguire S, Martin N, Mortensen P, Thornton L, Bulik C, Huckins L. Mapping anorexia nervosa genes to clinical phenotypes. Psychological Medicine 2022, 53: 2619-2633. PMID: 35379376, PMCID: PMC10123844, DOI: 10.1017/s0033291721004554.Peer-Reviewed Original ResearchConceptsBody mass indexGenome-wide association studiesTranscriptome imputationElectronic health record phenotypingAssociation studiesPhenome-wide association studyS-PrediXcan analysisMeasurement of cholesterolTraditional genome-wide association studiesGenes associated with ANAssociation of genetic variantsSubstance useGenetically regulated gene expressionImpact of body mass indexConsequences of aberrant expressionBiobank cohortBiobank populationAssociated with measuresAssociation of ANGWAS findingsSecondary analysisS-PrediXcanDisease riskMass indexSignificant genesPredicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits
Highland H, Wojcik G, Graff M, Nishimura K, Hodonsky C, Baldassari A, Cote A, Cheng I, Gignoux C, Tao R, Li Y, Boerwinkle E, Fornage M, Haessler J, Hindorff L, Hu Y, Justice A, Lin B, Lin D, Stram D, Haiman C, Kooperberg C, Le Marchand L, Matise T, Kenny E, Carlson C, Stahl E, Avery C, North K, Ambite J, Buyske S, Loos R, Peters U, Young K, Bien S, Huckins L. Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits. American Journal Of Human Genetics 2022, 109: 669-679. PMID: 35263625, PMCID: PMC9069067, DOI: 10.1016/j.ajhg.2022.02.013.Peer-Reviewed Original ResearchConceptsAncestrally diverse populationsBody mass indexCardiometabolic traitsEuropean ancestryGene expressionTranscriptomic imputation modelsNon-EA populationsDiverse populationsWhite British participantsReference panelGenetically regulated gene expressionGene-trait associationsTissue-specific gene expressionPopulation ArchitectureUK BiobankMeasurement of gene expressionPredicting gene expressionMulti-omics datasetsRelevant tissuesSusceptibility lociMass indexComplex traitsIdentified genesNovel associationsDiverse sample