2023
Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications
Levey D, Galimberti M, Deak J, Wendt F, Bhattacharya A, Koller D, Harrington K, Quaden R, Johnson E, Gupta P, Biradar M, Lam M, Cooke M, Rajagopal V, Empke S, Zhou H, Nunez Y, Kranzler H, Edenberg H, Agrawal A, Smoller J, Lencz T, Hougaard D, Børglum A, Demontis D, Gaziano J, Gandal M, Polimanti R, Stein M, Gelernter J. Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications. Nature Genetics 2023, 55: 2094-2103. PMID: 37985822, PMCID: PMC10703690, DOI: 10.1038/s41588-023-01563-z.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphism-based heritabilityMulti-ancestry genome-wide association studyAssociation studiesMillion Veteran ProgramGenome-wide association studiesWide significant lociWide association studySignificant lociReference panelSmall populationDisease biologyAncestryAmerican ancestryHeritabilityVeteran ProgramNumerous medical comorbiditiesLung cancer riskRelationship analysisLociBiologyPublic health implicationsEast AsiansPublic health consequencesMedical comorbiditiesCigarette smokingGenome-wide association studies and cross-population meta-analyses investigating short and long sleep duration
Austin-Zimmerman I, Levey D, Giannakopoulou O, Deak J, Galimberti M, Adhikari K, Zhou H, Denaxas S, Irizar H, Kuchenbaecker K, McQuillin A, Concato J, Buysse D, Gaziano J, Gottlieb D, Polimanti R, Stein M, Bramon E, Gelernter J. Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration. Nature Communications 2023, 14: 6059. PMID: 37770476, PMCID: PMC10539313, DOI: 10.1038/s41467-023-41249-y.Peer-Reviewed Original ResearchConceptsAssociation studiesGenome-wide association studiesGenetic correlationsWide association studyLinkage disequilibrium scorePositive genetic correlationSleep traitsIndependent lociMillion Veteran ProgramTraitsAncestryUK BiobankVeteran ProgramMendelian randomisationLociHeritabilitySNPsPhenotypeEast AsiansSimilar patternCardiometabolic phenotypesMultivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders
Hatoum A, Colbert S, Johnson E, Huggett S, Deak J, Pathak G, Jennings M, Paul S, Karcher N, Hansen I, Baranger D, Edwards A, Grotzinger A, Tucker-Drob E, Kranzler H, Davis L, Sanchez-Roige S, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders. Nature Mental Health 2023, 1: 210-223. PMID: 37250466, PMCID: PMC10217792, DOI: 10.1038/s44220-023-00034-y.Peer-Reviewed Original ResearchGenome-wide associationGenetic risk lociIndependent single nucleotide polymorphismsProblematic tobacco useSingle nucleotide polymorphismsRisk lociHigh polygenicityLociReceptor geneAddiction risk factorsPolygenic risk scoresEuropean descentPolygenicityGenesSummary statisticsSubstance use disordersSomatic conditionsAncestryRegulationConfersUse disordersPolymorphismGenetic liabilityDopamine regulationPDE4B
2022
From Evolutionary History to the Concepts of Race and Ancestry: Shifting Our Perspective in Clinical Research
Haeny AM, Polimanti R. From Evolutionary History to the Concepts of Race and Ancestry: Shifting Our Perspective in Clinical Research. Biological Psychiatry 2022, 91: e51-e52. PMID: 35483984, PMCID: PMC9527646, DOI: 10.1016/j.biopsych.2022.02.953.Peer-Reviewed Original Research
2021
Ancestry may confound genetic machine learning: Candidate-gene prediction of opioid use disorder as an example
Hatoum AS, Wendt FR, Galimberti M, Polimanti R, Neale B, Kranzler HR, Gelernter J, Edenberg HJ, Agrawal A. Ancestry may confound genetic machine learning: Candidate-gene prediction of opioid use disorder as an example. Drug And Alcohol Dependence 2021, 229: 109115. PMID: 34710714, PMCID: PMC9358969, DOI: 10.1016/j.drugalcdep.2021.109115.Peer-Reviewed Original ResearchConceptsGenome-wide significant variantsCandidate gene predictionGenetic predictionRandom SNPsPolygenic traitRandom phenotypeCandidate SNPsSimulated phenotypesPsychiatric geneticsGenetic machineSignificant variantsBinary phenotypesCandidate variantsSNPsAncestryPhenotypeAllele frequenciesVariantsMachine learning modelsGenetic testsLearning modelBi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions
Levey DF, Stein MB, Wendt FR, Pathak GA, Zhou H, Aslan M, Quaden R, Harrington KM, Nuñez YZ, Overstreet C, Radhakrishnan K, Sanacora G, McIntosh AM, Shi J, Shringarpure SS, Concato J, Polimanti R, Gelernter J. Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nature Neuroscience 2021, 24: 954-963. PMID: 34045744, PMCID: PMC8404304, DOI: 10.1038/s41593-021-00860-2.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association studyMillion Veteran ProgramTranscriptome-wide association study (TWAS) analysisGenomic risk lociComplex psychiatric traitsGenetic architectureRisk lociGene expressionAssociation studiesLikely pathogenicityPsychiatric traitsVeteran ProgramNew therapeutic directionEuropean ancestryNew insightsAncestryUK BiobankAfrican ancestrySubstantial replicationExpressionLarge independent cohortsGWASTherapeutic directionsGenesLociCross-ancestry genome-wide association studies identified heterogeneous loci associated with differences of allele frequency and regulome tagging between participants of European descent and other ancestry groups from the UK Biobank
De Lillo A, D'Antona S, Pathak GA, Wendt FR, De Angelis F, Fuciarelli M, Polimanti R. Cross-ancestry genome-wide association studies identified heterogeneous loci associated with differences of allele frequency and regulome tagging between participants of European descent and other ancestry groups from the UK Biobank. Human Molecular Genetics 2021, 30: 1457-1467. PMID: 33890984, PMCID: PMC8283210, DOI: 10.1093/hmg/ddab114.Peer-Reviewed Original ResearchConceptsGWS associationsHeterogeneous lociGenome-wide association studiesEuropean populationsAncestry-specific effectsAllele frequenciesWide significant associationsPhenome-wide analysisAncestry groupsComplex traitsLD variationPhenotypic classesAssociation studiesUK BiobankMapping variantsLociConcordant effectsCentral/South AsianAncestryWorldwide populationTraitsAsian ancestryDiscordant effectsSouth Asian ancestryEuropean descent
2015
Genetic diversity of disease-associated loci in Turkish population
Karaca S, Cesuroglu T, Karaca M, Erge S, Polimanti R. Genetic diversity of disease-associated loci in Turkish population. Journal Of Human Genetics 2015, 60: 193-198. PMID: 25716910, DOI: 10.1038/jhg.2015.8.Peer-Reviewed Original ResearchConceptsHealth-related traitsGenetic diversityNon-European ancestryHuman genetic variationDisease-associated lociGenetic structureComplex traitsGenetic variationTraitsEuropean individualsGenesEast populationDiversityGenetic featuresAncestryPolygenic scoresMiddle East populationLociPopulationPeculiar genetic featuresGenetic predispositionHuman groupsLarge numberTurkish populationLast finding