2024
Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations
Liu J, Borsari B, Li Y, Liu S, Gao Y, Xin X, Lou S, Jensen M, Garrido-Martín D, Verplaetse T, Ash G, Zhang J, Girgenti M, Roberts W, Gerstein M. Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations. Cell 2024 PMID: 39706190, DOI: 10.1016/j.cell.2024.11.012.Peer-Reviewed Original ResearchGenome-wide association studiesCase-control genome-wide association studyMultivariate genome-wide association studyGenetic lociAssociation studiesGenetic dataGenetic associationPhenotypeGeneticsEnvironmental factorsDetection powerElfn1Adolescent Brain Cognitive DevelopmentLociGenesPsychiatric disordersADORA3Digital phenotyping42. STRESS EXPOSURE DYNAMICALLY REGULATES EQTL ACTIVITY IN THE POST-MORTEM BRAIN AND IN HIPSC-DERIVED NEURONS
Seah C, Signer R, Young H, Hicks E, Rusielewicz T, Bader H, Xu C, Breen M, Paull D, Yehuda R, Girgenti M, Brennand K, Huckins L. 42. STRESS EXPOSURE DYNAMICALLY REGULATES EQTL ACTIVITY IN THE POST-MORTEM BRAIN AND IN HIPSC-DERIVED NEURONS. European Neuropsychopharmacology 2024, 87: 71-72. DOI: 10.1016/j.euroneuro.2024.08.156.Peer-Reviewed Original ResearchPost-mortem brainsTranscription factor binding sitesAbsence of cellular stressCombat-exposed veteransFactor binding sitesImpact gene expressionBinding sitesGR binding sitesPositive regulatory activityMotif enrichmentSequence readsCRISPRi screenOpen chromatinFunctional annotationBrain regionsTraumatic stressCRISPR screensEQTLTraumatic experiencesLeading locusPTSDPerturbed genesRegulatory architectureTranscriptomic activityTranscriptomic responseSingle-cell genomics and regulatory networks for 388 human brains
Emani P, Liu J, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee C, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken T, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard J, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman G, Huang A, Jiang Y, Jin T, Jorstad N, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran J, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan A, Riesenmy T, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini K, Wamsley B, Wang G, Xia Y, Xiao S, Yang A, Zheng S, Gandal M, Lee D, Lein E, Roussos P, Sestan N, Weng Z, White K, Won H, Girgenti M, Zhang J, Wang D, Geschwind D, Gerstein M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Berretta S, Bharadwaj R, Bhattacharya A, Brennand K, Capauto D, Champagne F, Chatzinakos C, Chen H, Cheng L, Chess A, Chien J, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Davila-Velderrain J, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duong D, Eagles N, Edelstein J, Galani K, Girdhar K, Goes F, Greenleaf W, Guo H, Guo Q, Hadas Y, Hallmayer J, Han X, Haroutunian V, He C, Hicks S, Ho M, Ho L, Huang Y, Huuki-Myers L, Hyde T, Iatrou A, Inoue F, Jajoo A, Jiang L, Jin P, Jops C, Jourdon A, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Li J, Li M, Lin X, Liu S, Liu C, Loupe J, Lu D, Ma L, Mariani J, Martinowich K, Maynard K, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Mukamel E, Nairn A, Nemeroff C, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Pinto D, Pochareddy S, Pollard K, Pollen A, Przytycki P, Purmann C, Qin Z, Qu P, Raj T, Reach S, Reimonn T, Ressler K, Ross D, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Seyfried N, Shao Z, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Voloudakis G, Wang T, Wang S, Wang Y, Wei Y, Weimer A, Weinberger D, Wen C, Whalen S, Willsey A, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang Y, Ziffra R, Zeier Z, Zintel T. Single-cell genomics and regulatory networks for 388 human brains. Science 2024, 384: eadi5199. PMID: 38781369, PMCID: PMC11365579, DOI: 10.1126/science.adi5199.Peer-Reviewed Original ResearchConceptsSingle-cell genomicsSingle-cell expression quantitative trait locusExpression quantitative trait lociDrug targetsQuantitative trait lociPopulation-level variationSingle-cell expressionCell typesDisease-risk genesTrait lociGene familyRegulatory networksGene expressionCell-typeMultiomics datasetsSingle-nucleiGenomeGenesCellular changesHeterogeneous tissuesExpressionCellsChromatinLociMultiomicsThe Prefrontal Cortex Transcriptomic Landscape of the Comorbidity Between Post-Traumatic Stress Disorder and Opioid Misuse
Martinez-Magaña J, Nagamatsu S, Nunez-Rios D, Krystal J, Girgenti M, Group T, Montalvo-Ortiz J. The Prefrontal Cortex Transcriptomic Landscape of the Comorbidity Between Post-Traumatic Stress Disorder and Opioid Misuse. Biological Psychiatry 2024, 95: s69. DOI: 10.1016/j.biopsych.2024.02.169.Peer-Reviewed Original Research361. Imaging HDAC6 in PTSD
Bonomi R, Girgenti M, Cosgrove K. 361. Imaging HDAC6 in PTSD. Biological Psychiatry 2024, 95: s247. DOI: 10.1016/j.biopsych.2024.02.860.Peer-Reviewed Original Research209 Transcriptomic Analysis of the Post-mortem Brain in Intracranial Atherosclerosis Implicates Interferon Signaling
Seah C, Devarajan A, Jurczyszak D, Chakka A, Huckins L, Brennand K, Girgenti M. 209 Transcriptomic Analysis of the Post-mortem Brain in Intracranial Atherosclerosis Implicates Interferon Signaling. Neurosurgery 2024, 70: 55-56. DOI: 10.1227/neu.0000000000002809_209.Peer-Reviewed Original ResearchIntracranial atherosclerotic stenosisIntracranial arteriesInterferon-inducible genesInterferon signalingPeripheral atherosclerosisCerebral atherosclerosisExpression of interferon-inducible genesGlial cellsSymptomatic intracranial atherosclerotic stenosisInduced pluripotent stem cellsPost-mortem brainsWorsened functional outcomesHuman induced pluripotent stem cellsUpregulation of interferon inducible genesCause of ischemic strokePluripotent stem cellsRisk of atherosclerosisLipid-rich plaquesRisk factor managementClinical outcomesPoor prognosisExcitatory neuronsIncreased morbidityHistopathological profileFunctional outcomesscENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding
Duan Z, Xu S, Srinivasan S, Hwang A, Lee C, Yue F, Gerstein M, Luan Y, Girgenti M, Zhang J. scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding. Briefings In Bioinformatics 2024, 25: bbae096. PMID: 38493342, PMCID: PMC10944576, DOI: 10.1093/bib/bbae096.Peer-Reviewed Original ResearchConceptsA/B compartmentsEpigenetic dataChromatin interaction frequenciesCell type-specific mannerChromatin conformational changesGenome binsGenomic regionsChromatin conformationEukaryotic DNAChromatin compartmentsDynamic compartmentalizationRepressed stateGenetic blueprintTranscriptional programsTranscriptional changesChromatinConformational changesComplex tissuesInteraction frequencyCompartmentGenomeChromosomeStructural heterogeneityDNAA/BTuning parameters for polygenic risk score methods using GWAS summary statistics from training data
Jiang W, Chen L, Girgenti M, Zhao H. Tuning parameters for polygenic risk score methods using GWAS summary statistics from training data. Nature Communications 2024, 15: 24. PMID: 38169469, PMCID: PMC10762162, DOI: 10.1038/s41467-023-44009-0.Peer-Reviewed Original Research
2023
Novel hippocampal genes involved in enhanced susceptibility to chronic pain-induced behavioral emotionality
Garman A, Ash A, Kokkinos E, Nerland D, Winter L, Langreck C, Forgette M, Girgenti M, Banasr M, Duric V. Novel hippocampal genes involved in enhanced susceptibility to chronic pain-induced behavioral emotionality. European Journal Of Pharmacology 2023, 964: 176273. PMID: 38135263, DOI: 10.1016/j.ejphar.2023.176273.Peer-Reviewed Original ResearchBlood-brain barrier integrityChronic pain statesBehavioral emotionalityHippocampal genesPain statesGenome-wide RNA-seq analysisStress responseBarrier integrityCommon stress responseRNA-seq analysisAurora kinase BChronic inflammatory painDepressive-like behaviorChronic pain conditionsRodent stress modelsLimbic brain regionsTight junction proteinsBioinformatics analysisInflammatory painAstrocyte activationPain groupPain conditionsTranscriptomic profilesAltered moodKinase BUncommon Protein-Coding Variants Associated With Suicide Attempt in a Diverse Sample of U.S. Army Soldiers
Wilkerson M, Hupalo D, Gray J, Zhang X, Wang J, Girgenti M, Alba C, Sukumar G, Lott N, Naifeh J, Aliaga P, Kessler R, Turner C, Pollard H, Dalgard C, Ursano R, Stein M. Uncommon Protein-Coding Variants Associated With Suicide Attempt in a Diverse Sample of U.S. Army Soldiers. Biological Psychiatry 2023, 96: 15-25. PMID: 38141912, DOI: 10.1016/j.biopsych.2023.12.008.Peer-Reviewed Original ResearchSingle variant analysisProtein-coding variantsVariant analysisCommon genetic variantsWhole-genome sequencingMost genesWhole genomeGenome sequencingSignificant genesMolecular characterizationGenesGenetic variantsAncestry groupsGenetic risk factorsExomeYWHAERecent studiesVariantsATAD3ARC3H2EP400GenomeRcn2SGMS1STARD9Ketamine and the neurobiology of depression: Toward next-generation rapid-acting antidepressant treatments
Krystal J, Kaye A, Jefferson S, Girgenti M, Wilkinson S, Sanacora G, Esterlis I. Ketamine and the neurobiology of depression: Toward next-generation rapid-acting antidepressant treatments. Proceedings Of The National Academy Of Sciences Of The United States Of America 2023, 120: e2305772120. PMID: 38011560, PMCID: PMC10710048, DOI: 10.1073/pnas.2305772120.Peer-Reviewed Original ResearchSTRESS IN A DISH: MODELING THE IMPACT OF COMMON GENETIC VARIATION ON STRESS RESPONSE IN HIPSC-DERIVED NEURONS IN PTSD
Seah C, Signer R, Young H, Kozik E, Rusielewicz T, Bader H, Xu C, de Pins A, Breen M, Paull D, Yehuda R, Girgenti M, Brennand K, Huckins L. STRESS IN A DISH: MODELING THE IMPACT OF COMMON GENETIC VARIATION ON STRESS RESPONSE IN HIPSC-DERIVED NEURONS IN PTSD. European Neuropsychopharmacology 2023, 75: s40. DOI: 10.1016/j.euroneuro.2023.08.081.Peer-Reviewed Original ResearchCommon genetic variationGenetic variationStress responseCell typesEQTL associationsTranscriptional stress responseGenomic risk lociTissue-specific mannerChIP-seq datasetsCell type deconvolutionCommon genetic variantsPost-mortem brainsGene expression signaturesHiPSC-derived neuronsTranscription factorsSuch lociCatalog genesRisk lociGenetic studiesExpression signaturesGenetic variantsRegulatory activityGenesEQTLsMechanistic understandingiHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease
Duan Z, Dai Y, Hwang A, Lee C, Xie K, Xiao C, Xu M, Girgenti M, Zhang J. iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease. PLOS Computational Biology 2023, 19: e1011444. PMID: 37695793, PMCID: PMC10513318, DOI: 10.1371/journal.pcbi.1011444.Peer-Reviewed Original ResearchConceptsDriver genesRisk genesCritical cellular functionsDeeper molecular insightsDivergent genesPhenotypic variationCellular functionsTranscriptome perturbationsGene embeddingsGCN analysisGene prioritizationPathway levelDifferent genesGene classificationMolecular insightsGenesNetwork modulesComplex networksDifferent diseasesHierarchical levelsCellsProfiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex
Rompala G, Nagamatsu S, Martínez-Magaña J, Nuñez-Ríos D, Wang J, Girgenti M, Krystal J, Gelernter J, Hurd Y, Montalvo-Ortiz J. Profiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex. Nature Communications 2023, 14: 4544. PMID: 37507366, PMCID: PMC10382503, DOI: 10.1038/s41467-023-40285-y.Peer-Reviewed Original ResearchConceptsOpioid use disorderMulti-omics findingsGene expression patternsCo-methylation analysisGene expression profilesMulti-omics profilingGene networksDNA methylationNeuronal methylomesDNA hydroxymethylationMethylomic analysisExpression patternsExpression profilesEpigenetic disturbancesUse disordersPsychiatric traitsOrbitofrontal cortexOpioid-related drugsPostmortem orbitofrontal cortexEnvironmental factorsDrug interaction analysisOUD treatmentHuman orbitofrontal cortexOpioid signalingInteraction analysisModeling Gene by Environment Interactions in Post-Traumatic Stress Disorder Across the Post-Mortem Brain and in hiPSC-Derived Neurons
Seah C, Signer R, Young H, Rusielewicz T, Bader H, Xu C, dePins A, Breen M, Paull D, Girgenti M, Yehuda R, Brennand K, Huckins L. Modeling Gene by Environment Interactions in Post-Traumatic Stress Disorder Across the Post-Mortem Brain and in hiPSC-Derived Neurons. Biological Psychiatry 2023, 93: s11. DOI: 10.1016/j.biopsych.2023.02.048.Peer-Reviewed Original ResearchSingle Cell Genomic Analysis Reveals Cell Type-Specific Molecular Signatures in the Human PTSD Prefrontal Cortex
Girgenti M, Zhang J, Skarica M, Hwang A, Xu K, Young K, Zhao H, Sestan N, Krystal J. Single Cell Genomic Analysis Reveals Cell Type-Specific Molecular Signatures in the Human PTSD Prefrontal Cortex. Biological Psychiatry 2023, 93: s11-s12. DOI: 10.1016/j.biopsych.2023.02.049.Peer-Reviewed Original ResearchTuning Parameters for Polygenic Risk Score Methods Using GWAS Summary Statistics from Training Data
Jiang W, Chen L, Girgenti M, Zhao H. Tuning Parameters for Polygenic Risk Score Methods Using GWAS Summary Statistics from Training Data. 2023 DOI: 10.21203/rs.3.rs-2939390/v1.Peer-Reviewed Original ResearchIntegrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings
Hicks E, Seah C, Cote A, Marchese S, Brennand K, Nestler E, Girgenti M, Huckins L. Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings. Translational Psychiatry 2023, 13: 129. PMID: 37076454, PMCID: PMC10115809, DOI: 10.1038/s41398-023-02412-7.Peer-Reviewed Original ResearchConceptsBioinformatics approachTranscriptomic dataBrain transcriptomeGenome-wide analysisDynamic transcriptional landscapeBrain gene expression dataGene expression dataTranscriptional landscapeTranscriptomic studiesIntegrating GeneticExpression dataPhenotypic signaturesGenomic driversTranscriptomeMajor depressive disorderValuable resourceRecent findingsEnvironmental influencesTranscriptomicsDepressive disorderGeneticsMultiple approachesPathophysiology of depressionSignaturesDysregulation
2022
Genetic liability to suicidal thoughts and behaviors and risk of suicide attempt in US military veterans: moderating effects of cumulative trauma burden
Nichter B, Koller D, De Angelis F, Wang J, Girgenti M, Na P, Hill M, Norman S, Krystal J, Gelernter J, Polimanti R, Pietrzak R. Genetic liability to suicidal thoughts and behaviors and risk of suicide attempt in US military veterans: moderating effects of cumulative trauma burden. Psychological Medicine 2022, 53: 6325-6333. PMID: 36444557, DOI: 10.1017/s0033291722003646.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresUS military veteransLifetime suicide attemptsSuicide attemptsTrauma exposureTrauma burdenGenetic liabilityMilitary veteransDrug repurposing analysisPopulation-based sampleCumulative trauma exposureLifetime trauma exposureLow trauma exposureSuicide prediction modelsChronic inflammationInflammatory processNervous system developmentRisk scorePsychiatric characteristicsSuicidal behaviorExposure interactionsLarge genome-wide association studiesHigh levelsVeteransSuicidalityVenus: An efficient virus infection detection and fusion site discovery method using single-cell and bulk RNA-seq data
Lee CY, Chen Y, Duan Z, Xu M, Girgenti MJ, Xu K, Gerstein M, Zhang J. Venus: An efficient virus infection detection and fusion site discovery method using single-cell and bulk RNA-seq data. PLOS Computational Biology 2022, 18: e1010636. PMID: 36301997, PMCID: PMC9642901, DOI: 10.1371/journal.pcbi.1010636.Peer-Reviewed Original ResearchConceptsHBV-hepatocellular carcinomaAntiretroviral therapyHIV infectionImmune cellsT cellsViral pathophysiologyNeurological patientsNovel targetVirusInfection detectionVirus of interestPotential pathogensVirus detectionBulk RNA-seq dataCell typesViral transcriptsSingle-cell sequencingRNA-seq dataPublic healthcareCellsHIVPatientsCarcinomaPathogensPathophysiology