2024
Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder
Nievergelt C, Maihofer A, Atkinson E, Chen C, Choi K, Coleman J, Daskalakis N, Duncan L, Polimanti R, Aaronson C, Amstadter A, Andersen S, Andreassen O, Arbisi P, Ashley-Koch A, Austin S, Avdibegoviç E, Babić D, Bacanu S, Baker D, Batzler A, Beckham J, Belangero S, Benjet C, Bergner C, Bierer L, Biernacka J, Bierut L, Bisson J, Boks M, Bolger E, Brandolino A, Breen G, Bressan R, Bryant R, Bustamante A, Bybjerg-Grauholm J, Bækvad-Hansen M, Børglum A, Børte S, Cahn L, Calabrese J, Caldas-de-Almeida J, Chatzinakos C, Cheema S, Clouston S, Colodro-Conde L, Coombes B, Cruz-Fuentes C, Dale A, Dalvie S, Davis L, Deckert J, Delahanty D, Dennis M, Desarnaud F, DiPietro C, Disner S, Docherty A, Domschke K, Dyb G, Kulenović A, Edenberg H, Evans A, Fabbri C, Fani N, Farrer L, Feder A, Feeny N, Flory J, Forbes D, Franz C, Galea S, Garrett M, Gelaye B, Gelernter J, Geuze E, Gillespie C, Goleva S, Gordon S, Goçi A, Grasser L, Guindalini C, Haas M, Hagenaars S, Hauser M, Heath A, Hemmings S, Hesselbrock V, Hickie I, Hogan K, Hougaard D, Huang H, Huckins L, Hveem K, Jakovljević M, Javanbakht A, Jenkins G, Johnson J, Jones I, Jovanovic T, Karstoft K, Kaufman M, Kennedy J, Kessler R, Khan A, Kimbrel N, King A, Koen N, Kotov R, Kranzler H, Krebs K, Kremen W, Kuan P, Lawford B, Lebois L, Lehto K, Levey D, Lewis C, Liberzon I, Linnstaedt S, Logue M, Lori A, Lu Y, Luft B, Lupton M, Luykx J, Makotkine I, Maples-Keller J, Marchese S, Marmar C, Martin N, Martínez-Levy G, McAloney K, McFarlane A, McLaughlin K, McLean S, Medland S, Mehta D, Meyers J, Michopoulos V, Mikita E, Milani L, Milberg W, Miller M, Morey R, Morris C, Mors O, Mortensen P, Mufford M, Nelson E, Nordentoft M, Norman S, Nugent N, O’Donnell M, Orcutt H, Pan P, Panizzon M, Pathak G, Peters E, Peterson A, Peverill M, Pietrzak R, Polusny M, Porjesz B, Powers A, Qin X, Ratanatharathorn A, Risbrough V, Roberts A, Rothbaum A, Rothbaum B, Roy-Byrne P, Ruggiero K, Rung A, Runz H, Rutten B, de Viteri S, Salum G, Sampson L, Sanchez S, Santoro M, Seah C, Seedat S, Seng J, Shabalin A, Sheerin C, Silove D, Smith A, Smoller J, Sponheim S, Stein D, Stensland S, Stevens J, Sumner J, Teicher M, Thompson W, Tiwari A, Trapido E, Uddin M, Ursano R, Valdimarsdóttir U, Van Hooff M, Vermetten E, Vinkers C, Voisey J, Wang Y, Wang Z, Waszczuk M, Weber H, Wendt F, Werge T, Williams M, Williamson D, Winsvold B, Winternitz S, Wolf C, Wolf E, Xia Y, Xiong Y, Yehuda R, Young K, Young R, Zai C, Zai G, Zervas M, Zhao H, Zoellner L, Zwart J, deRoon-Cassini T, van Rooij S, van den Heuvel L, Stein M, Ressler K, Koenen K. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder. Nature Genetics 2024, 56: 792-808. PMID: 38637617, PMCID: PMC11396662, DOI: 10.1038/s41588-024-01707-9.Peer-Reviewed Original ResearchConceptsMeta-analysis of genome-wide association studiesGenome-wide significant lociMulti-ancestry meta-analysisGenome-wide association analysisGenome-wide association studiesIndividuals of European ancestryPotential causal genesNative American ancestryMulti-omics approachPost-traumatic stress disorderAdmixed individualsSignificant lociRisk lociCausal genesAssociation studiesAssociation analysisFunctional genesTranscription factorsGenetic studiesAmerican ancestryEuropean ancestryAxon guidanceSynaptic structureLociGenes
2023
Multi‐omics cannot replace sample size in genome‐wide association studies
Baranger D, Hatoum A, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multi‐omics cannot replace sample size in genome‐wide association studies. Genes Brain & Behavior 2023, 22: e12846. PMID: 36977197, PMCID: PMC10733567, DOI: 10.1111/gbb.12846.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesLarge genome-wide association studiesNovel genesMulti-omics dataMulti-omics informationAssociation studiesGenome-wide significant lociSmall genome-wide association studyBrain-related traitsGWAS sample sizesEarly genome-wide association studiesNovel gene discoveryGene discoverySignificant lociAdditional genesPositional mappingHeritable traitVariant discoverySimilar traitsGenesNovel variant discoveryTraitsDisease biologyLociDiscoveryMultivariate 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
Exploring the genetic overlap between twelve psychiatric disorders
Romero C, Werme J, Jansen P, Gelernter J, Stein M, Levey D, Polimanti R, de Leeuw C, Posthuma D, Nagel M, van der Sluis S. Exploring the genetic overlap between twelve psychiatric disorders. Nature Genetics 2022, 54: 1795-1802. PMID: 36471075, DOI: 10.1038/s41588-022-01245-2.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsPleiotropic single nucleotide polymorphismsPositive genetic correlationStringent P-value thresholdGenetic architectureGenomic regionsGenetic covarianceBiological processesBiological pathwaysMolecular characterizationObserved phenotypicGenetic correlationsGenetic overlapBiological characterizationBiological mechanismsP-value thresholdOnly annotationGenesPleiotropicPairwise comparisonsPhenotypicPathwayAnnotationPolymorphismCharacterizationGenome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways
Watanabe K, Jansen PR, Savage JE, Nandakumar P, Wang X, Hinds D, Gelernter J, Levey D, Polimanti R, Stein M, Van Someren E, Smit A, Posthuma D. Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways. Nature Genetics 2022, 54: 1125-1132. PMID: 35835914, DOI: 10.1038/s41588-022-01124-w.Peer-Reviewed Original ResearchConceptsRisk lociGenome-wide association studiesSpecific gene setsPrevious genome-wide association studyGene prioritization strategyExternal biological resourcesExtreme polygenicityExpression specificityAssociated lociSignaling functionsGene setsAssociation studiesNeuronal differentiationFunctional interactionGenesLociBiological resourcesPolygenicityNovel strategyPrioritization strategiesSpecific hypothesesDifferentiationPathwayStatistical powerLarge numberGenetically regulated multi-omics study for symptom clusters of posttraumatic stress disorder highlights pleiotropy with hematologic and cardio-metabolic traits
Pathak GA, Singh K, Wendt FR, Fleming TW, Overstreet C, Koller D, Tylee DS, De Angelis F, Cabrera Mendoza B, Levey DF, Koenen KC, Krystal JH, Pietrzak RH, O’ Donell C, Gaziano JM, Falcone G, Stein MB, Gelernter J, Pasaniuc B, Mancuso N, Davis LK, Polimanti R. Genetically regulated multi-omics study for symptom clusters of posttraumatic stress disorder highlights pleiotropy with hematologic and cardio-metabolic traits. Molecular Psychiatry 2022, 27: 1394-1404. PMID: 35241783, PMCID: PMC9210390, DOI: 10.1038/s41380-022-01488-9.Peer-Reviewed Original ResearchConceptsLocal genetic correlationsCell type-specific expressionVanderbilt University biorepositoryMulti-omics studiesMulti-omics investigationsDorsolateral prefrontal cortex tissueGenomic evidenceLaboratory traitsSpecific expressionCardio-metabolic traitsMillion Veteran ProgramPrefrontal cortex tissueMiR-148GenesGenetic correlationsRegulatory profileTraitsProtein expressionCardiometabolic traitsExpressionVeteran ProgramCortex tissueBiological heterogeneitySplicingPrioritization approach
2021
ACE2 Netlas: In silico Functional Characterization and Drug-Gene Interactions of ACE2 Gene Network to Understand Its Potential Involvement in COVID-19 Susceptibility
Pathak GA, Wendt FR, Goswami A, Koller D, De Angelis F, Initiative C, Polimanti R. ACE2 Netlas: In silico Functional Characterization and Drug-Gene Interactions of ACE2 Gene Network to Understand Its Potential Involvement in COVID-19 Susceptibility. Frontiers In Genetics 2021, 12: 698033. PMID: 34512723, PMCID: PMC8429844, DOI: 10.3389/fgene.2021.698033.Peer-Reviewed Original ResearchGenome-wide association studiesGenetic variationFunctional characterizationCOVID-19 susceptibilityHuman genetic variationSilico functional characterizationDrug-gene interaction databaseTranscriptomic regulationGene networksGenetic variant associationsMetabolic domainsMulti-level characterizationPhenome-wide associationAssociation studiesDrug-gene interactionsVariant associationsInteraction databasesGenesKey adhesion moleculeGenetic variantsPhenotype categoriesPotential involvementMiRNAsAdhesion moleculesPotential mechanismsIntegrative genomic analyses identify susceptibility genes underlying COVID-19 hospitalization
Pathak GA, Singh K, Miller-Fleming TW, Wendt FR, Ehsan N, Hou K, Johnson R, Lu Z, Gopalan S, Yengo L, Mohammadi P, Pasaniuc B, Polimanti R, Davis LK, Mancuso N. Integrative genomic analyses identify susceptibility genes underlying COVID-19 hospitalization. Nature Communications 2021, 12: 4569. PMID: 34315903, PMCID: PMC8316582, DOI: 10.1038/s41467-021-24824-z.Peer-Reviewed Original ResearchConceptsPutative causal genesGenome-wide association studiesUnderstanding of genesIntegrative genomic analysisTrans-ethnic studiesAssociation scanCausal genesGenomic analysisAssociation studiesDiverse ancestral backgroundsGenesSusceptibility genesBiobank JapanHost geneticsProtein levelsAncestral backgroundPathwayExpressionMRNA expressionSplicingRapid progressPhenomeGeneticsHost inflammatory responseCoagulation pathwayInvestigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder
Johnson EC, Kapoor M, Hatoum AS, Zhou H, Polimanti R, Wendt FR, Walters RK, Lai D, Kember RL, Hartz S, Meyers JL, Peterson RE, Ripke S, Bigdeli TB, Fanous AH, Pato CN, Pato MT, Goate AM, Kranzler HR, O'Donovan MC, Walters JTR, Gelernter J, Edenberg HJ, Agrawal A. Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder. Psychological Medicine 2021, 53: 1196-1204. PMID: 34231451, PMCID: PMC8738774, DOI: 10.1017/s003329172100266x.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significant single nucleotide polymorphismsLarge-scale genome-wide association studiesSignificant single nucleotide polymorphismsIndependent genome-wide significant single nucleotide polymorphismsSignificant genetic correlationsGenomic regionsSingle nucleotide polymorphismsGene expressionGenetic covariancePleiotropic associationsAssociation studiesGenetic correlationsGenetic variantsNucleotide polymorphismsGenetic overlapDisorder-specific effectsAlcohol use disorderGenetic influencesGenesUse disordersBi-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 directionsGenesLociPleiotropic effects of telomere length loci with brain morphology and brain tissue expression
Pathak GA, Wendt FR, Levey DF, Mecca AP, van Dyck CH, Gelernter J, Polimanti R. Pleiotropic effects of telomere length loci with brain morphology and brain tissue expression. Human Molecular Genetics 2021, 30: 1360-1370. PMID: 33831179, PMCID: PMC8255129, DOI: 10.1093/hmg/ddab102.Peer-Reviewed Original ResearchConceptsMethylation expressionGenetic variantsMapping gene functionTelomere lengthChromatin associationChromatin profilesGene functionGenetic colocalizationGene mappingGenomic relationshipsNeuropsychiatric traitsPleiotropic rolesDrug-gene interactionsCertain lociBrain tissue expressionGenesLociPleiotropic effectsBrain morphology measuresNucleotide polymorphismsAncestry populationsTissue expressionPhenotypic associationsPleiotropyAncestry groupsSex-stratified gene-by-environment genome-wide interaction study of trauma, posttraumatic-stress, and suicidality
Wendt FR, Pathak GA, Levey DF, Nuñez YZ, Overstreet C, Tyrrell C, Adhikari K, De Angelis F, Tylee DS, Goswami A, Krystal JH, Abdallah CG, Stein MB, Kranzler HR, Gelernter J, Polimanti R. Sex-stratified gene-by-environment genome-wide interaction study of trauma, posttraumatic-stress, and suicidality. Neurobiology Of Stress 2021, 14: 100309. PMID: 33665242, PMCID: PMC7905234, DOI: 10.1016/j.ynstr.2021.100309.Peer-Reviewed Original ResearchGenome-wide interaction studyRisk lociChromatin interaction profilesExtracellular matrix biologyGene-based analysisMatrix biologyMolecular basisTranscriptomic profilesInteraction studiesMultivariate geneGenetic perspectiveSNP effectsSuicidal behavior severityLociNovel targetGenesInteraction profilesSynaptic plasticityCellsInteractorsGenetic riskBiologyStressGxEIndependent cohort
2020
Epigenetic profiling of Italian patients identified methylation sites associated with hereditary transthyretin amyloidosis
De Lillo A, Pathak GA, De Angelis F, Di Girolamo M, Luigetti M, Sabatelli M, Perfetto F, Frusconi S, Manfellotto D, Fuciarelli M, Polimanti R. Epigenetic profiling of Italian patients identified methylation sites associated with hereditary transthyretin amyloidosis. Clinical Epigenetics 2020, 12: 176. PMID: 33203445, PMCID: PMC7672937, DOI: 10.1186/s13148-020-00967-6.Peer-Reviewed Original ResearchConceptsEpigenome-wide association studiesMethylation sitesEpigenetic differencesSignificant epigenetic differencesProtein interaction networksSignificant methylation changesAmyloidogenic mutationsDisease-causing mutationsProtein interactorsEpigenetic regulationHigh phenotypic variabilityEpigenetic profilingMethylation changesInteraction networksGene regionBiological processesMolecular mechanismsAssociation studiesMolecular pathwaysCoding mutationsPhenotypic variabilityNovel insightsGenesFiber formationMutationsGenome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits
Zhou H, Sealock JM, Sanchez-Roige S, Clarke TK, Levey DF, Cheng Z, Li B, Polimanti R, Kember RL, Smith RV, Thygesen JH, Morgan MY, Atkinson SR, Thursz MR, Nyegaard M, Mattheisen M, Børglum AD, Johnson EC, Justice AC, Palmer AA, McQuillin A, Davis LK, Edenberg HJ, Agrawal A, Kranzler HR, Gelernter J. Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nature Neuroscience 2020, 23: 809-818. PMID: 32451486, PMCID: PMC7485556, DOI: 10.1038/s41593-020-0643-5.Peer-Reviewed Original ResearchConceptsRegulatory genomic regionsGenome-wide association studiesNovel risk lociEuropean ancestry individualsPolygenic risk score analysisIndependent risk variantsGenetic architectureGenomic regionsRisk lociAssociation studiesGenetic relationshipsRisk genesGenetic correlationsPsychiatric traitsRisk variantsRisk score analysisTraitsGenetic heritabilityYields insightsBiobank samplesMendelian randomizationGenesLociBiologyHeritability
2019
Phenome-wide association study of TTR and RBP4 genes in 361,194 individuals reveals novel insights in the genetics of hereditary and wildtype transthyretin amyloidoses
De Lillo A, De Angelis F, Di Girolamo M, Luigetti M, Frusconi S, Manfellotto D, Fuciarelli M, Polimanti R. Phenome-wide association study of TTR and RBP4 genes in 361,194 individuals reveals novel insights in the genetics of hereditary and wildtype transthyretin amyloidoses. Human Genetics 2019, 138: 1331-1340. PMID: 31659433, DOI: 10.1007/s00439-019-02078-6.Peer-Reviewed Original ResearchConceptsNon-coding variantsPhenome-wide association studyAssociation studiesNovel insightsPhenotypic traitsMolecular basisPossible modifier genesRBP4 geneModifier genesRelevant phenotypesTTR locusGenesTTR functionTransthyretin amyloidosesMultiple testing correctionGene variationRBP4 variantsGeneticsPhenotypeTransthyretin geneTTR geneConvergent associationsHereditary formsClinical phenotypeVariantsInternational meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci
Nievergelt CM, Maihofer AX, Klengel T, Atkinson EG, Chen CY, Choi KW, Coleman JRI, Dalvie S, Duncan LE, Gelernter J, Levey DF, Logue MW, Polimanti R, Provost AC, Ratanatharathorn A, Stein MB, Torres K, Aiello AE, Almli LM, Amstadter AB, Andersen SB, Andreassen OA, Arbisi PA, Ashley-Koch AE, Austin SB, Avdibegovic E, Babić D, Bækvad-Hansen M, Baker DG, Beckham JC, Bierut LJ, Bisson JI, Boks MP, Bolger EA, Børglum AD, Bradley B, Brashear M, Breen G, Bryant RA, Bustamante AC, Bybjerg-Grauholm J, Calabrese JR, Caldas- de- Almeida J, Dale AM, Daly MJ, Daskalakis NP, Deckert J, Delahanty DL, Dennis MF, Disner SG, Domschke K, Dzubur-Kulenovic A, Erbes CR, Evans A, Farrer LA, Feeny NC, Flory JD, Forbes D, Franz CE, Galea S, Garrett ME, Gelaye B, Geuze E, Gillespie C, Uka AG, Gordon SD, Guffanti G, Hammamieh R, Harnal S, Hauser MA, Heath AC, Hemmings SMJ, Hougaard DM, Jakovljevic M, Jett M, Johnson EO, Jones I, Jovanovic T, Qin XJ, Junglen AG, Karstoft KI, Kaufman ML, Kessler RC, Khan A, Kimbrel NA, King AP, Koen N, Kranzler HR, Kremen WS, Lawford BR, Lebois LAM, Lewis CE, Linnstaedt SD, Lori A, Lugonja B, Luykx JJ, Lyons MJ, Maples-Keller J, Marmar C, Martin AR, Martin NG, Maurer D, Mavissakalian MR, McFarlane A, McGlinchey RE, McLaughlin KA, McLean SA, McLeay S, Mehta D, Milberg WP, Miller MW, Morey RA, Morris CP, Mors O, Mortensen PB, Neale BM, Nelson EC, Nordentoft M, Norman SB, O’Donnell M, Orcutt HK, Panizzon MS, Peters ES, Peterson AL, Peverill M, Pietrzak RH, Polusny MA, Rice JP, Ripke S, Risbrough VB, Roberts AL, Rothbaum AO, Rothbaum BO, Roy-Byrne P, Ruggiero K, Rung A, Rutten BPF, Saccone NL, Sanchez SE, Schijven D, Seedat S, Seligowski AV, Seng JS, Sheerin CM, Silove D, Smith AK, Smoller JW, Sponheim SR, Stein DJ, Stevens JS, Sumner JA, Teicher MH, Thompson WK, Trapido E, Uddin M, Ursano RJ, van den Heuvel LL, Van Hooff M, Vermetten E, Vinkers CH, Voisey J, Wang Y, Wang Z, Werge T, Williams MA, Williamson DE, Winternitz S, Wolf C, Wolf EJ, Wolff JD, Yehuda R, Young RM, Young KA, Zhao H, Zoellner LA, Liberzon I, Ressler KJ, Haas M, Koenen KC. International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci. Nature Communications 2019, 10: 4558. PMID: 31594949, PMCID: PMC6783435, DOI: 10.1038/s41467-019-12576-w.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesDisease genesAssociation studiesGenome-wide significant lociAfrican-ancestry analysesNon-coding RNAsGenetic risk lociParkinson's disease genesEuropean ancestry populationsNovel genesSignificant lociGenetic variationSpecific lociRisk lociAdditional lociLociAncestry populationsCommon variantsHeritability estimatesGenesGWASRNABiologySNPsPARK2
2018
Effect of the GSTM1 gene deletion on glycemic variability, sympatho-vagal balance and arterial stiffness in patients with metabolic syndrome, but without diabetes
Iorio A, Ylli D, Polimanti R, Picconi F, Maggio P, Francomano D, Aversa A, Manfellotto D, Fuciarelli M, Frontoni S. Effect of the GSTM1 gene deletion on glycemic variability, sympatho-vagal balance and arterial stiffness in patients with metabolic syndrome, but without diabetes. Diabetes Research And Clinical Practice 2018, 138: 158-168. PMID: 29452132, DOI: 10.1016/j.diabres.2018.02.006.Peer-Reviewed Original ResearchConceptsProtein kinase regulationGlutathione S-transferase geneCellular detoxification processesKinase regulationInvolvement of GSTRisk lociFunctional variantsGene deletionPutative roleDetoxification processDeletionGenesPolymorphism analysisOxidative stressCrucial roleGene polymorphism analysisGST gene polymorphismsNovel findingsGSTM1 gene deletionLociGSTM1 deletionRoleGSTRegulationPathway
2017
ADH1B: From alcoholism, natural selection, and cancer to the human phenome
Polimanti R, Gelernter J. ADH1B: From alcoholism, natural selection, and cancer to the human phenome. American Journal Of Medical Genetics Part B Neuropsychiatric Genetics 2017, 177: 113-125. PMID: 28349588, PMCID: PMC5617762, DOI: 10.1002/ajmg.b.32523.Peer-Reviewed Original ResearchConceptsHuman phenomeMultiple human tissuesPhenome-wide association studyMolecular functionsGene regulationPhenotypic traitsBioinformatics analysisEvolutionary dataFunctional allelesAssociation studiesMetabolic traitsAlcohol metabolismMolecular pathwaysMultiple molecular pathwaysHuman evolutionPhenomeGenesADH1B geneTraitsComplex mechanismsHuman tissuesMetabolismAllelesADH1BADH1B locusA genome-wide gene-by-trauma interaction study of alcohol misuse in two independent cohorts identifies PRKG1 as a risk locus
Polimanti R, Kaufman J, Zhao H, Kranzler HR, Ursano RJ, Kessler RC, Gelernter J, Stein MB. A genome-wide gene-by-trauma interaction study of alcohol misuse in two independent cohorts identifies PRKG1 as a risk locus. Molecular Psychiatry 2017, 23: 154-160. PMID: 28265120, PMCID: PMC5589475, DOI: 10.1038/mp.2017.24.Peer-Reviewed Original ResearchConceptsGenome-wide interaction studyGene Ontology (GO) enrichment analysisOntology enrichment analysisProtein kinase 1Protein regulationSame effect directionCyclic GMP-dependent protein kinase 1Circadian rhythm regulationRisk lociWide geneEnrichment analysisInteraction studiesKinase 1Individual genetic riskPsychiatric geneticsCalcium-activated potassium channelsGenesLociPRKG1Potassium channelsEffect directionRhythm regulationAlcohol use problemsRegulationAlcohol misuse
2015
Dissecting ancestry genomic background in substance dependence genome-wide association studies
Polimanti R, Yang C, Zhao H, Gelernter J. Dissecting ancestry genomic background in substance dependence genome-wide association studies. Pharmacogenomics 2015, 16: 1487-1498. PMID: 26267224, PMCID: PMC4632979, DOI: 10.2217/pgs.15.91.Peer-Reviewed Original ResearchMeSH KeywordsAlcoholismAlgorithmsAllelesBlack or African AmericanGene FrequencyGene-Environment InteractionGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyHaplotypesHumansMolecular Sequence AnnotationOpioid-Related DisordersSubstance-Related DisordersTobacco Use DisorderWhite PeopleConceptsGenome-wide association studiesGenomic backgroundFunctional allelesAssociation studiesCommon functional allelesWide association studyLocal haplotype structureGenetic lociSD traitHaplotype structureRelevant genesGenesLociInteractive partnersPopulation diversityHigh frequency differencesAllelesFrequency differenceGenomeTraitsDiversityRoleVariants