2025
Heterozygosity for neurodevelopmental disorder-associated TRIO variants yields distinct deficits in behavior, neuronal development, and synaptic transmission in mice
Ishchenko Y, Jeng A, Feng S, Nottoli T, Manriquez-Rodriguez C, Nguyen K, Carrizales M, Vitarelli M, Corcoran E, Greer C, Myers S, Koleske A. Heterozygosity for neurodevelopmental disorder-associated TRIO variants yields distinct deficits in behavior, neuronal development, and synaptic transmission in mice. ELife 2025, 13: rp103620. PMID: 40488445, PMCID: PMC12148328, DOI: 10.7554/elife.103620.Peer-Reviewed Original ResearchConceptsAutism spectrum disorderGuanine nucleotide exchange factorNeurodevelopmental disordersPresynaptic glutamate releaseLayer 5 pyramidal neuronsAssociated with neurodevelopmental disordersIntellectual disabilitySpectrum disorderMouse behaviorCognitive behaviorNucleotide exchange factorNeuronal developmentBrain developmentGlutamate releaseIncreased Rac1 activityBrain sizeSynaptic functionControlling neuronal developmentSchizophreniaImpaired abilityAssociated with increased levelsNeurodevelopmental eventsActive GTPaseGEF Tiam1Exchange factorHeterozygosity for neurodevelopmental disorder-associated TRIO variants yields distinct deficits in behavior, neuronal development, and synaptic transmission in mice
Ishchenko Y, Jeng A, Feng S, Nottoli T, Manriquez-Rodriguez C, Nguyen K, Carrizales M, Vitarelli M, Corcoran E, Greer C, Myers S, Koleske A. Heterozygosity for neurodevelopmental disorder-associated TRIO variants yields distinct deficits in behavior, neuronal development, and synaptic transmission in mice. ELife 2025, 13 DOI: 10.7554/elife.103620.3.Peer-Reviewed Original ResearchAutism spectrum disorderGuanine nucleotide exchange factorNeurodevelopmental disordersPresynaptic glutamate releaseLayer 5 pyramidal neuronsAssociated with neurodevelopmental disordersIntellectual disabilitySpectrum disorderMouse behaviorCognitive behaviorNucleotide exchange factorSchizophreniaNeuronal developmentBrain developmentGlutamate releaseIncreased Rac1 activityBrain sizeSynaptic functionControlling neuronal developmentImpaired abilityAssociated with increased levelsNeurodevelopmental eventsActive GTPaseGEF Tiam1Exchange factorA head start: The relationship of placental factors to craniofacial and brain development
Carver A, Dunnwald M, Stevens H. A head start: The relationship of placental factors to craniofacial and brain development. Developmental Dynamics 2025 PMID: 40105397, DOI: 10.1002/dvdy.70018.Peer-Reviewed Original ResearchPlacental functionBrain developmentCraniofacial developmentInsulin-like growth factor-1Etiology of neurodevelopmental disordersPlacental hormone productionGrowth factor-1Placental factorsCraniofacial skeletal growthFetal neurodevelopmentVitamin DGrowth hormoneCraniofacial morphogenesisHormone productionFactor 1PlacentaNeurodevelopmental disordersSkeletal growthBrainHormoneNutrient deliveryHead StartFunctional influenceNeuroplacentologyProlactinIdentification and external validation of a problem cannabis risk network
Lichenstein S, Kiluk B, Potenza M, Garavan H, Chaarani B, Banaschewski T, Bokde A, Desrivières S, Flor H, Grigis A, Gowland P, Heinz A, Brühl R, Martinot J, Paillère Martinot M, Artiges E, Nees F, Orfanos D, Poustka L, Hohmann S, Holz N, Baeuchl C, Smolka M, Vaidya N, Walter H, Whelan R, Schumann G, Pearlson G, Yip S. Identification and external validation of a problem cannabis risk network. Biological Psychiatry 2025 PMID: 39909136, DOI: 10.1016/j.biopsych.2025.01.022.Peer-Reviewed Original ResearchAlcohol use outcomesCannabis useNeural mechanismsSample of treatment-seeking adultsNeural mechanisms of riskTreatment-seeking adultsCannabis use disorderNon-clinical sampleMechanisms of riskFunctional connectivity dataSample of adolescentsTreatment outcomesAssociated with harmful outcomesPoor treatment outcomesAddiction severityUse disorderEmerging adulthoodWhole-brainCannabisCollege studentsBrain developmentConnectivity dataIdentified networksTreatment approachesAdultsModality-level obstacles and initiatives to improve representation in fetal, infant, and toddler neuroimaging research samples
Margolis E, Nelson P, Fiske A, Champaud J, Olson H, Gomez M, Dineen Á, Bulgarelli C, Troller-Renfree S, Donald K, Spann M, Howell B, Scheinost D, Korom M. Modality-level obstacles and initiatives to improve representation in fetal, infant, and toddler neuroimaging research samples. Developmental Cognitive Neuroscience 2025, 72: 101505. PMID: 39954600, PMCID: PMC11875194, DOI: 10.1016/j.dcn.2024.101505.Peer-Reviewed Original ResearchConceptsFunctional near-infrared spectroscopyEarly brain developmentNeurobiological vulnerabilityNeuroimaging researchModality-specificNeuroimaging techniquesNeurodevelopmental processesNeuroimaging modalitiesBrain developmentResearch sampleMagnetic resonance imagingNear-infrared spectroscopyEquitable representationMarginalized communitiesExcluded peopleStudy early brain developmentToddlersCranial ultrasonographyResonance imagingInsufficient resourcesTangible solutionsEarly markersPrenatal stress alters mouse offspring dorsal striatal development and placental function in sex-specific ways
Maurer S, Hing B, Lussier S, Radhakrishna S, Davis J, Abbott P, Michaelson J, Stevens H. Prenatal stress alters mouse offspring dorsal striatal development and placental function in sex-specific ways. Journal Of Psychiatric Research 2025, 182: 149-160. PMID: 39809011, PMCID: PMC11959308, DOI: 10.1016/j.jpsychires.2024.12.048.Peer-Reviewed Original ResearchConceptsPrenatal stressAutism spectrum disorderSex-specific wayDorsal striatumNeurodevelopmental disordersGABAergic populationEffects of prenatal stressStriatal GABAergic neuronsReversal learningVentral forebrain regionsBrain changesSpectrum disorderForebrain regionsStriatal developmentGABAergic neuronsBehavioral assaysBrain developmentPlacental transcriptomeStriatumCognitionDevelopmental originsDisordersPlacental differencesPlacental functionPlacenta functionBrain Development and the Risk for Substance Use, Misuse, and Substance Use Disorders
Ruiz S, Casey B, Baskin-Sommers A. Brain Development and the Risk for Substance Use, Misuse, and Substance Use Disorders. 2025, 675-684. DOI: 10.1093/med/9780197640654.003.0049.Peer-Reviewed Original ResearchSubstance use disordersSubstance useMaintenance of substance use disordersFamily history of substance use disorderHistory of substance use disorderRegulation of rewardStress-related circuitryEarly life adversityAdolescent substance useCognitive controlPersonality traitsSensation seekingLife adversityNeurodevelopmental changesUse disorderAbstract AdolescentsIntervention scienceInfluence of peersSubstance exposureBrain developmentAdolescentsDisordersRewardMisuseCircuitry
2024
Noncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact
Mondragon-Estrada E, Newburger J, DePalma S, Brueckner M, Cleveland J, Chung W, Gelb B, Goldmuntz E, Hagler D, Huang H, McQuillen P, Miller T, Panigrahy A, Porter G, Roberts A, Rollins C, Russell M, Tristani-Firouzi M, Grant P, Im K, Morton S. Noncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact. IScience 2024, 28: 111707. PMID: 39877905, PMCID: PMC11772982, DOI: 10.1016/j.isci.2024.111707.Peer-Reviewed Original ResearchNoncoding variantsCongenital heart diseaseFunctions related to neuronal developmentGene regulatory signalsH3K9me2 modificationRegulatory signalsCongenital heart disease cohortsDevelopmental pathwaysNeuronal developmentFolding patternHeart diseaseFunctional impactGenetic factorsGenesVariantsBrain developmentPredictive impactSulcal patternsOnline Gambling in Youth
Potenza M, Mestre-Bach G, Demetrovics Z, Derevensky J, Fernandez-Aranda F, Gainsbury S, Jiménez-Murcia S, Kraus S. Online Gambling in Youth. 2024, 597-603. DOI: 10.1007/978-3-031-69362-5_81.Peer-Reviewed Original ResearchLevels of sensation-seekingYouth gambling behaviourGambling disorderSensation-seekingSocial explorationDevelopmental trajectoriesGambling behaviorGambling problemsBrain developmentGamblingSports bettingIdentity formationOnline gamblingDaily fantasy sportsFantasy sportsYouthSocial acceptanceVulnerable populationsIncreased autonomyEvolving digital environmentSportsA Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development
Wang Y, Qiao C, Qu G, Calhoun V, Stephen J, Wilson T, Wang Y. A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development. IEEE Transactions On Biomedical Engineering 2024, 71: 3390-3401. PMID: 38968024, PMCID: PMC11700232, DOI: 10.1109/tbme.2024.3423803.Peer-Reviewed Original ResearchDynamic effective connectivityEffective connectivityBrain developmentBrain developmental trajectoriesPhiladelphia Neurodevelopmental CohortLearning modelsNeurodevelopmental CohortBrain regionsDevelopmental trajectoriesSpatio-temporal dataInformation processing capabilitiesFuse informationCausal LearnerYoung adultsProtective Factors Predict Resilient Outcomes in Clinical High-Risk Youth with the Highest Individualized Psychosis Risk Scores
Cadenhead K, Addington J, Bearden C, Cannon T, Cornblatt B, Keshavan M, Mathalon D, Perkins D, Stone W, Walker E, Woods S. Protective Factors Predict Resilient Outcomes in Clinical High-Risk Youth with the Highest Individualized Psychosis Risk Scores. Schizophrenia Bulletin 2024, sbae182. PMID: 39488001, DOI: 10.1093/schbul/sbae182.Peer-Reviewed Original ResearchClinical high riskClinical high-risk participantsClinical high-risk researchPremorbid functioningResilient outcomesProtective factorsClinical high-risk youthClinical high-risk populationsReduced startle reactivityPrediction of psychosisAssociated with greater resilienceHigh-risk youthStudy of protective factorsStartle reactivityPsychotic conversionBrain areasPsychosisChildhood environmentBrain developmentGreater resilienceExploratory analysisLife experiencesPreventive interventionsSocial engagementHispanic heritageGenomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries
García-Marín L, Campos A, Diaz-Torres S, Rabinowitz J, Ceja Z, Mitchell B, Grasby K, Thorp J, Agartz I, Alhusaini S, Ames D, Amouyel P, Andreassen O, Arfanakis K, Arias-Vasquez A, Armstrong N, Athanasiu L, Bastin M, Beiser A, Bennett D, Bis J, Boks M, Boomsma D, Brodaty H, Brouwer R, Buitelaar J, Burkhardt R, Cahn W, Calhoun V, Carmichael O, Chakravarty M, Chen Q, Ching C, Cichon S, Crespo-Facorro B, Crivello F, Dale A, Smith G, de Geus E, De Jager P, de Zubicaray G, Debette S, DeCarli C, Depondt C, Desrivières S, Djurovic S, Ehrlich S, Erk S, Espeseth T, Fernández G, Filippi I, Fisher S, Fleischman D, Fletcher E, Fornage M, Forstner A, Francks C, Franke B, Ge T, Goldman A, Grabe H, Green R, Grimm O, Groenewold N, Gruber O, Gudnason V, Håberg A, Haukvik U, Heinz A, Hibar D, Hilal S, Himali J, Ho B, Hoehn D, Hoekstra P, Hofer E, Hoffmann W, Holmes A, Homuth G, Hosten N, Ikram M, Ipser J, Jack Jr C, Jahanshad N, Jönsson E, Kahn R, Kanai R, Klein M, Knol M, Launer L, Lawrie S, Hellard S, Lee P, Lemaître H, Li S, Liewald D, Lin H, Longstreth W, Lopez O, Luciano M, Maillard P, Marquand A, Martin N, Martinot J, Mather K, Mattay V, McMahon K, Mecocci P, Melle I, Meyer-Lindenberg A, Mirza-Schreiber N, Milaneschi Y, Mosley T, Mühleisen T, Müller-Myhsok B, Maniega S, Nauck M, Nho K, Niessen W, Nöthen M, Nyquist P, Oosterlaan J, Pandolfo M, Paus T, Pausova Z, Penninx B, Pike G, Psaty B, Pütz B, Reppermund S, Rietschel M, Risacher S, Romanczuk-Seiferth N, Romero-Garcia R, Roshchupkin G, Rotter J, Sachdev P, Sämann P, Saremi A, Sargurupremraj M, Saykin A, Schmaal L, Schmidt H, Schmidt R, Schofield P, Scholz M, Schumann G, Schwarz E, Shen L, Shin J, Sisodiya S, Smith A, Smoller J, Soininen H, Steen V, Stein D, Stein J, Thomopoulos S, Toga A, Tordesillas-Gutiérrez D, Trollor J, Valdes-Hernandez M, van ′t Ent D, van Bokhoven H, van der Meer D, van der Wee N, Vázquez-Bourgon J, Veltman D, Vernooij M, Villringer A, Vinke L, Völzke H, Walter H, Wardlaw J, Weinberger D, Weiner M, Wen W, Westlye L, Westman E, White T, Witte A, Wolf C, Yang J, Zwiers M, Ikram M, Seshadri S, Thompson P, Satizabal C, Medland S, Rentería M. Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries. Nature Genetics 2024, 56: 2333-2344. PMID: 39433889, PMCID: PMC12088653, DOI: 10.1038/s41588-024-01951-z.Peer-Reviewed Original ResearchSubcortical brain volumesBrain volumePolygenic scoresEffects of brain volumeAttention-deficit/hyperactivity disorderIndividuals of diverse ancestryComorbid neuropsychiatric disordersSubcortical brain structuresGenome-wide association study meta-analysesBrain substratesParticipants of European ancestryAttention-deficit/hyperactivityGene expression patternsNeuropsychiatric disordersDifferentiation time pointsBrain structuresGenomic analysisDiverse ancestryBrain developmentStudy meta-analysesGenetic variantsNeural cell typesPhenotypic varianceRisk genesAging-related processesCC2D1A causes ciliopathy, intellectual disability, heterotaxy, renal dysplasia, and abnormal CSF flow
Kim A, Sakin I, Viviano S, Tuncel G, Aguilera S, Goles G, Jeffries L, Ji W, Lakhani S, Kose C, Silan F, Oner S, Kaplan O, Group M, Ergoren M, Mishra-Gorur K, Gunel M, Sag S, Temel S, Deniz E. CC2D1A causes ciliopathy, intellectual disability, heterotaxy, renal dysplasia, and abnormal CSF flow. Life Science Alliance 2024, 7: e202402708. PMID: 39168639, PMCID: PMC11339347, DOI: 10.26508/lsa.202402708.Peer-Reviewed Original ResearchConceptsDevelopmental disabilitiesIntellectual disabilityPatient-derived fibroblastsMidbrain regionsBrain developmentDefective ciliogenesisCSF circulationDisabilityCSF flowAbnormal CSF flowNervous system developmentMutant tadpolesCiliated tissuesMultiple model systemsVariant functionPronephric ductUnrelated familiesCC2D1AExpression patternsCiliogenesisRenal dysplasiaLeft-right organizerFunctional analysisDisease mechanismsBrainBrain‐age prediction: Systematic evaluation of site effects, and sample age range and size
Yu Y, Cui H, Haas S, New F, Sanford N, Yu K, Zhan D, Yang G, Gao J, Wei D, Qiu J, Banaj N, Boomsma D, Breier A, Brodaty H, Buckner R, Buitelaar J, Cannon D, Caseras X, Clark V, Conrod P, Crivello F, Crone E, Dannlowski U, Davey C, de Haan L, de Zubicaray G, Di Giorgio A, Fisch L, Fisher S, Franke B, Glahn D, Grotegerd D, Gruber O, Gur R, Gur R, Hahn T, Harrison B, Hatton S, Hickie I, Pol H, Jamieson A, Jernigan T, Jiang J, Kalnin A, Kang S, Kochan N, Kraus A, Lagopoulos J, Lazaro L, McDonald B, McDonald C, McMahon K, Mwangi B, Piras F, Rodriguez‐Cruces R, Royer J, Sachdev P, Satterthwaite T, Saykin A, Schumann G, Sevaggi P, Smoller J, Soares J, Spalletta G, Tamnes C, Trollor J, Ent D, Vecchio D, Walter H, Wang Y, Weber B, Wen W, Wierenga L, Williams S, Wu M, Zunta‐Soares G, Bernhardt B, Thompson P, Frangou S, Ge R, Group E. Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size. Human Brain Mapping 2024, 45: e26768. PMID: 38949537, PMCID: PMC11215839, DOI: 10.1002/hbm.26768.Peer-Reviewed Original ResearchConceptsBrain-aging modelBrain-age predictionBrain-ageDiscovery sampleBrain morphometric measuresStructural neuroimaging dataSamples of healthy individualsSample age rangeNeuroimaging metricsNeuroimaging dataHealthy individualsLongitudinal consistencyBrain developmentIndependent samplesAge varianceAge rangeBrainSample sizeAge binsMorphometry dataIndividualsHuman lifespanEmpirical examinationMeaningful measuresFindingsReplication and Refinement of Brain Age Model for Adolescent Development
Ray B, Chen J, Fu Z, Suresh P, Thapaliya B, Farahdel B, Calhoun V, Liu J. Replication and Refinement of Brain Age Model for Adolescent Development. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635532.Peer-Reviewed Original ResearchBrain age modelAdolescent Brain Cognitive DevelopmentInformation processing speedBrain age gapABCD participantsBrain agingVerbal comprehension abilityEstimated brain ageEstimation of brain ageNeuropsychiatric problemsProcessing speedCognitive developmentAdolescent developmentAge gapComprehension abilityBrain developmentAge rangeBrainChronological ageAdolescentsParticipantsBaselineEvaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data
Dai R, Chu T, Zhang M, Wang X, Jourdon A, Wu F, Mariani J, Vaccarino F, Lee D, Fullard J, Hoffman G, Roussos P, Wang Y, Wang X, Pinto D, Wang S, Zhang C, consortium P, Chen C, Liu C. Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data. Science Advances 2024, 10: eadh2588. PMID: 38781336, PMCID: PMC11114236, DOI: 10.1126/sciadv.adh2588.Peer-Reviewed Original ResearchConceptsHuman brain transcriptome dataBrain transcriptomic dataRNA-seqTranscriptome dataCell-type gene expressionGene expressionCell-type proportionsSingle-cell dataMultiple brain disordersBrain cell typesCell deconvolution methodsPostmortem brainsRNA sequencingBrain disordersBrain developmentSchizophreniaEQTLAlzheimer's diseaseCell typesOrganoid samplesBrainBiological applicationsDevelopment of human visual cortical function: A scoping review of task- and naturalistic-fMRI studies through the interactive specialization and maturational frameworks
Tansey R, Graff K, Rai S, Merrikh D, Godfrey K, Vanderwal T, Bray S. Development of human visual cortical function: A scoping review of task- and naturalistic-fMRI studies through the interactive specialization and maturational frameworks. Neuroscience & Biobehavioral Reviews 2024, 162: 105729. PMID: 38763178, DOI: 10.1016/j.neubiorev.2024.105729.Peer-Reviewed Original ResearchInteractive specializationHuman functional brain developmentFunctional brain developmentVisual fMRI studyFMRI studyNaturalistic studyFMRI literatureExperimental tasksDevelopmental frameworkVisual processingNaturalistic paradigmBrain developmentWell-poweredLongitudinal studyFMRINeuroimagingYounger ageSpecialization frameworkChildhoodTaskParadigmAppraisalStudyFindingsSub-domainsCortical grey matter volume differences in children with developmental coordination disorder compared to typically developing children
Malik M, Weber A, Lang D, Vanderwal T, Zwicker J. Cortical grey matter volume differences in children with developmental coordination disorder compared to typically developing children. Frontiers In Human Neuroscience 2024, 18: 1276057. PMID: 38826616, PMCID: PMC11140146, DOI: 10.3389/fnhum.2024.1276057.Peer-Reviewed Original ResearchLeft superior frontal gyrusGray matter volumeSuperior frontal gyrusVoxel-based morphometryGreater gray matter volumeDevelopmental coordination disorderCortical gray matter volumeFrontal gyrusMatter volumeTD childrenTD groupRight middle frontal gyrusGray matter volume differencesCoordination disorderBrain developmentSuperior parietal lobeMiddle frontal gyrusThreshold-free cluster enhancementConners 3 ADHD IndexNeuroimaging evidenceAttention difficultiesFrontal poleAttention skillsFunctional connectivityParietal lobeTranscriptome-Connectome association from fetal stage to adulthood
Ouyang M, Poddar T, Santpere G, Andrijevic D, Ma S, Pattabiraman K, Gobeske K, Sestan N, Huang H. Transcriptome-Connectome association from fetal stage to adulthood. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/2389.Peer-Reviewed Original ResearchmTOR in Acquired and Genetic Models of Epilepsy
Wong M, Bordey A, Danzer S. mTOR in Acquired and Genetic Models of Epilepsy. 2024, 45-74. DOI: 10.1093/med/9780197549469.003.0004.Peer-Reviewed Original ResearchDisrupted mTOR signalingMTOR signalingDysregulation of mTOR signalingCellular functionsMTOR pathway signalingAbstract MutationsTarget of rapamycinPathway signalingSignaling pathwayGenetic modelsMTOR pathwayPathway disruptionMTORPathwayNongenetic causesRegulate brain developmentGeneral patternTraumatic brain injuryTuberous sclerosis complexGenetic model of epilepsyPatterns of brain pathologyPotential mechanismsSignalBrain developmentModulator of epileptogenesis
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