Featured Publications
Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment
Levey DF, Niculescu EM, Le-Niculescu H, Dainton HL, Phalen PL, Ladd TB, Weber H, Belanger E, Graham DL, Khan FN, Vanipenta NP, Stage EC, Ballew A, Yard M, Gelbart T, Shekhar A, Schork NJ, Kurian SM, Sandusky GE, Salomon DR, Niculescu AB. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment. Molecular Psychiatry 2016, 21: 768-785. PMID: 27046645, DOI: 10.1038/mp.2016.31.Peer-Reviewed Original ResearchConceptsFuture hospitalizationConvergent functional genomics approachSuicide completersPrimary end pointSingle blood biomarkerTop biomarkersReceiver-operating characteristic areaRisk prediction scoreClinical risk assessmentDisorder participantsIndependent test cohortForm of APPProphylactic benefitNeurotrophic effectsBlood biomarkersSleep abnormalitiesPsychiatric hospitalizationHospitalizationMood disordersTest cohortCandidate biomarkersSuicide completionSuicidal ideationDrug lithiumChronic stress
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 comparisonsPhenotypicPathwayAnnotationPolymorphismCharacterizationCollective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology
Lam M, Chen C, Hill W, Xia C, Tian R, Levey D, Gelernter J, Stein M, Hatoum A, Huang H, Malhotra A, Runz H, Ge T, Lencz T. Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology. Nature Communications 2022, 13: 6868. PMID: 36369282, PMCID: PMC9652380, DOI: 10.1038/s41467-022-34418-y.Peer-Reviewed Original Research
2021
Genetic contributions to anxiety disorders: where we are and where we are heading
Ask H, Cheesman R, Jami ES, Levey DF, Purves KL, Weber H. Genetic contributions to anxiety disorders: where we are and where we are heading. Psychological Medicine 2021, 51: 2231-2246. PMID: 33557968, DOI: 10.1017/s0033291720005486.Peer-Reviewed Original ResearchConceptsLarge-scale genome-wide association studiesGenome-wide association studiesGenetics of anxietyGenome-wide studiesRelated traitsAssociation studiesGeneticsGenetic contributionSpecific gene-environment interactionsGene-environment interactionsCurrent knowledgeTraitsNew therapeuticsSuch discoveriesDiscoveryNew research possibilitiesLifespanTherapeuticsCircuit mechanismsTranslation
2019
Towards precision medicine for pain: diagnostic biomarkers and repurposed drugs
Niculescu A, Le-Niculescu H, Levey D, Roseberry K, Soe K, Rogers J, Khan F, Jones T, Judd S, McCormick M, Wessel A, Williams A, Kurian S, White F. Towards precision medicine for pain: diagnostic biomarkers and repurposed drugs. Molecular Psychiatry 2019, 24: 501-522. PMID: 30755720, PMCID: PMC6477790, DOI: 10.1038/s41380-018-0345-5.Peer-Reviewed Original ResearchConceptsBlood gene expression biomarkersPossible new drug candidateFuture emergency department (ED) visitsEmergency department visitsHigh-risk groupDrug repurposing analysisCurrent opioid epidemicPerception of painSubjects longitudinal designGene expression signaturesPain statesDepartment visitsPain disordersTreatment dilemmaBlood biomarkersSC-560Opioid epidemicCohort designRisk groupsIndependent cohortPainGene expression biomarkersPsychiatric patientsDiagnostic biomarkersIndividual biomarkers
2017
Precision medicine for suicidality: from universality to subtypes and personalization
Niculescu A, Le-Niculescu H, Levey D, Phalen P, Dainton H, Roseberry K, Niculescu E, Niezer J, Williams A, Graham D, Jones T, Venugopal V, Ballew A, Yard M, Gelbart T, Kurian S, Shekhar A, Schork N, Sandusky G, Salomon D. Precision medicine for suicidality: from universality to subtypes and personalization. Molecular Psychiatry 2017, 22: 1250-1273. PMID: 28809398, PMCID: PMC5582166, DOI: 10.1038/mp.2017.128.Peer-Reviewed Original ResearchConceptsSuicidal ideationIndependent cohortPersonalized approachFuture hospitalizationPsychiatric diagnosisCandidate biomarkersUniversal biomarkerBlood gene expression biomarkersBiology of suicideTop biomarkersNovel predictive biomarkerHigh-risk groupNon-psychiatric disordersDrug repurposing analysisPublic health problemMonitoring of responseNovel potential therapeuticsHigher suicidal ideationPredictive biomarkersClinical trialsComprehensive stepwise approachRisk groupsLarge cohortMood disordersPreventive therapeutics
2015
Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach
Niculescu AB, Levey DF, Phalen PL, Le-Niculescu H, Dainton HD, Jain N, Belanger E, James A, George S, Weber H, Graham DL, Schweitzer R, Ladd TB, Learman R, Niculescu EM, Vanipenta NP, Khan FN, Mullen J, Shankar G, Cook S, Humbert C, Ballew A, Yard M, Gelbart T, Shekhar A, Schork NJ, Kurian SM, Sandusky GE, Salomon DR. Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach. Molecular Psychiatry 2015, 20: 1266-1285. PMID: 26283638, PMCID: PMC4759104, DOI: 10.1038/mp.2015.112.Peer-Reviewed Original ResearchConceptsFuture hospitalizationPsychiatric diagnosisSuicidal ideationCandidate biomarkersBipolar disorderPsychiatric participantsBlood gene expression biomarkersSuicidal behaviorConvergent functional genomics approachSuicide completersPreventive lifestyle modificationsTop candidate biomarkersTop biomarkersAcute panic attacksPotential therapeutic targetBipolar disorder participantsMajor psychiatric disordersIndependent test cohortSuicide risk factorsThoughts of suicideLifestyle modificationAcute suicidalityRisk factorsInflammatory responsePsychological stress responses
2014
Genetic risk prediction and neurobiological understanding of alcoholism
Levey DF, Le-Niculescu H, Frank J, Ayalew M, Jain N, Kirlin B, Learman R, Winiger E, Rodd Z, Shekhar A, Schork N, Kiefe F, Wodarz N, Müller-Myhsok B, Dahmen N, Nöthen M, Sherva R, Farrer L, Smith A, Kranzler H, Rietschel M, Gelernter J, Niculescu A. Genetic risk prediction and neurobiological understanding of alcoholism. Translational Psychiatry 2014, 4: e391-e391. PMID: 24844177, PMCID: PMC4035721, DOI: 10.1038/tp.2014.29.Peer-Reviewed Original ResearchConceptsTop candidate genesCandidate genesGenetic risk predictionGenome-wide association study dataFunctional genomics approachConvergent functional genomics approachAssociation study dataGene expression dataInitial discovery stepGenomic approachesKey genesSignal transductionSignificant genetic overlapTop genesRelevant genesBiological pathwaysExpression dataTop findingsGenesStrict Bonferroni correctionGenetic overlapProtein knockout miceSmall panelFatty acidsKnockout mice
2013
Discovery and validation of blood biomarkers for suicidality
Le-Niculescu H, Levey DF, Ayalew M, Palmer L, Gavrin LM, Jain N, Winiger E, Bhosrekar S, Shankar G, Radel M, Bellanger E, Duckworth H, Olesek K, Vergo J, Schweitzer R, Yard M, Ballew A, Shekhar A, Sandusky GE, Schork NJ, Kurian SM, Salomon DR, Niculescu AB. Discovery and validation of blood biomarkers for suicidality. Molecular Psychiatry 2013, 18: 1249-1264. PMID: 23958961, PMCID: PMC3835939, DOI: 10.1038/mp.2013.95.Peer-Reviewed Original ResearchMeSH KeywordsAcetyltransferasesAdultAgedBiomarkersBipolar DisorderGene ExpressionGene Expression ProfilingGenomicsHumansIntracellular Signaling Peptides and ProteinsMaleMAP Kinase Kinase Kinase 3Membrane ProteinsMiddle AgedMyristoylated Alanine-Rich C Kinase SubstrateOligonucleotide Array Sequence AnalysisPsychotic DisordersPTEN PhosphohydrolaseSuicidal IdeationSuicideConceptsBlood biomarkersMood disordersBlood gene expression biomarkersConvergent functional genomics approachCase-case designVisual analog scaleHigh-risk populationSimple visual analog scaleBlood expression levelsAge-matched cohortCause of deathMajor mood disordersBlood of subjectsBonferroni correctionExpression levelsBipolar disorder subjectsPsychosis subjectsBlood levelsFuture hospitalizationTime of testingMedication targetsPast hospitalizationHospitalization dataBipolar cohortCompleter group
2012
Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction
Ayalew M, Le-Niculescu H, Levey DF, Jain N, Changala B, Patel SD, Winiger E, Breier A, Shekhar A, Amdur R, Koller D, Nurnberger JI, Corvin A, Geyer M, Tsuang MT, Salomon D, Schork NJ, Fanous AH, O'Donovan MC, Niculescu AB. Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction. Molecular Psychiatry 2012, 17: 887-905. PMID: 22584867, PMCID: PMC3427857, DOI: 10.1038/mp.2012.37.Peer-Reviewed Original ResearchConceptsTop candidate genesCandidate genesG protein-coupled receptor signalingGenome-wide association study dataFunctional genomics approachReceptor signalingConvergent functional genomics approachAssociation study dataGene expression studiesFunctional genomicsGenomic approachesGlutamate receptor signalingSignificant genetic overlapSingle nucleotide polymorphismsEnvironmental stressTop genesExpression studiesPathway analysisBiological pathwaysGenetic risk predictionGenesCell adhesionBiological landscapeGenetic overlapSignaling