2024
Androgen deprivation increases frontopolar cortical thickness in prostate cancer patients: an effect of early neurodegeneration?
Chaudhary S, Roy A, Summers C, Ahles T, Li C, Chao H. Androgen deprivation increases frontopolar cortical thickness in prostate cancer patients: an effect of early neurodegeneration? American Journal Of Cancer Research 2024, 14: 3652-3664. PMID: 39113873, PMCID: PMC11301281, DOI: 10.62347/wola8904.Peer-Reviewed Original ResearchFrontopolar cortexCortical thicknessWorking memoryAndrogen deprivation therapyN-back performanceN-back taskProstate cancer patientsYears of educationPublished routinesNeural consequencesBrain changesBrain morphologyMediation analysisCT changesConsequences of androgen deprivation therapyMonths of androgen deprivation therapyTestosterone level changesImpact of androgen deprivation therapyCancer patientsNon-metastatic prostate cancerTestosterone levelsResponse to androgen deprivationLong duration of treatmentBrain imagingNeurodegenerative changes
2022
Cortical profiles of numerous psychiatric disorders and normal development share a common pattern
Cao Z, Cupertino R, Ottino-Gonzalez J, Murphy A, Pancholi D, Juliano A, Chaarani B, Albaugh M, Yuan D, Schwab N, Stafford J, Goudriaan A, Hutchison K, Li C, Luijten M, Groefsema M, Momenan R, Schmaal L, Sinha R, van Holst R, Veltman D, Wiers R, Porjesz B, Lett T, Banaschewski T, Bokde A, Desrivières S, Flor H, Grigis A, Gowland P, Heinz A, Brühl R, Martinot J, Martinot M, Artiges E, Nees F, Orfanos D, Paus T, Poustka L, Hohmann S, Millenet S, Fröhner J, Robinson L, Smolka M, Walter H, Winterer J, Schumann G, Whelan R, Bhatt R, Zhu A, Conrod P, Jahanshad N, Thompson P, Mackey S, Garavan H. Cortical profiles of numerous psychiatric disorders and normal development share a common pattern. Molecular Psychiatry 2022, 28: 698-709. PMID: 36380235, DOI: 10.1038/s41380-022-01855-6.Peer-Reviewed Original ResearchConceptsCortical thicknessPsychiatric disordersNumerous psychiatric disordersNeurological disordersDesikan-Killiany atlasLower cortical thicknessNormative maturationAllen Human Brain AtlasHealthy adult participantsCortical maturationExpression of PC1Cortical changesEmergence of psychopathologyBrain maturationPsychiatric diseasesMultiple gene ontology categoriesHuman Brain AtlasCortical profilesPubertal transitionCT differencesDisordersLate childhoodABCD studyAdult participantsNeurobiological basisThe relationship between TLR4/NF-κB/IL-1β signaling, cognitive impairment, and white-matter integrity in patients with stable chronic schizophrenia
Li H, Chen W, Gou M, Li W, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Pan S, Li N, Luo X, Zhang P, Huang J, Tian L, Li CR, Tan Y. The relationship between TLR4/NF-κB/IL-1β signaling, cognitive impairment, and white-matter integrity in patients with stable chronic schizophrenia. Frontiers In Psychiatry 2022, 13: 966657. PMID: 36051545, PMCID: PMC9424630, DOI: 10.3389/fpsyt.2022.966657.Peer-Reviewed Original ResearchStable chronic schizophreniaNF-κB/ILWhite matter integrityHealthy controlsMATRICS Consensus Cognitive BatteryFractional anisotropyChronic schizophreniaCortical thicknessCognitive impairmentInnate immunityCognitive functionToll-like receptor 4Higher TLR4 levelsLevels of TLR4Subcortical gray matter volumesWhite matter fractional anisotropyNegative Syndrome ScaleGray matter volumeTLR4 expressionTLR4 levelsWhite matter microstructureReceptor 4Cognitive deteriorationConsensus Cognitive BatteryLPS stimulationSerum hyperhomocysteine and cognitive impairment in first-episode patients with schizophrenia: Moderated by brain cortical thickness
Lin C, Gou M, Pan S, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Luo X, Li CR, Zhang P, Huang J, Hong L, Tan Y. Serum hyperhomocysteine and cognitive impairment in first-episode patients with schizophrenia: Moderated by brain cortical thickness. Neuroscience Letters 2022, 788: 136826. PMID: 35944595, DOI: 10.1016/j.neulet.2022.136826.Peer-Reviewed Original ResearchConceptsBrain cortical thicknessCognitive impairmentCognitive deficitsGray matter thicknessSchizophrenia (MATRICS) Consensus Cognitive BatteryAttention/vigilanceConsensus Cognitive BatteryCortical thicknessSerum Hcy levelsFirst-episode patientsHealthy controlsHigh homocysteineWorking memoryHcy levelsCognitive batteryNegative Symptom ScaleCognitive functionTreatment researchHigh-resolution magnetic resonance imagingSymptom ScaleSandwich enzyme-linked immunosorbentSchizophreniaHigher cortical thicknessImpairmentEnzyme-linked immunosorbentHistory of suicide attempts associated with the thinning right superior temporal gyrus among individuals with schizophrenia
Yin Y, Tong J, Huang J, Tian B, Chen S, Tan S, Wang Z, Yang F, Tong Y, Fan F, Kochunov P, Jahanshad N, Li CR, Hong LE, Tan Y. History of suicide attempts associated with the thinning right superior temporal gyrus among individuals with schizophrenia. Brain Imaging And Behavior 2022, 16: 1893-1901. PMID: 35545740, PMCID: PMC10025969, DOI: 10.1007/s11682-021-00624-3.Peer-Reviewed Original ResearchConceptsRight superior temporal gyrusSuperior temporal gyrusCortical surface areaSuicide attemptsTemporal gyrusSuicide attemptersMean cortical thicknessIndividual brain regionsCortical thinningCortical abnormalitiesHealthy volunteersCortical thicknessGeneral populationThinner cortexMorphometric alterationsWhole brainBrain regionsStructural MRISuicidal behaviorGyrusSchizophreniaHigh rateAttemptersIndividualsGroupBrain structural covariance network differences in adults with alcohol dependence and heavy‐drinking adolescents
Ottino‐González J, Garavan H, Albaugh M, Cao Z, Cupertino R, Schwab N, Spechler P, Allen N, Artiges E, Banaschewski T, Bokde A, Burke Quinlan E, Brühl R, Orr C, Cousijn J, Desrivières S, Flor H, Foxe J, Fröhner J, Goudriaan A, Gowland P, Grigis A, Heinz A, Hester R, Hutchison K, Li C, London E, Lorenzetti V, Luijten M, Nees F, Martín‐Santos R, Martinot J, Millenet S, Momenan R, Paillère Martinot M, Papadopoulos Orfanos D, Paulus M, Poustka L, Schmaal L, Schumann G, Sinha R, Smolka MN, Solowij N, Stein DJ, Stein EA, Uhlmann A, van Holst RJ, Veltman DJ, Walter H, Whelan R, Wiers RW, Yücel M, Zhang S, Jahanshad N, Thompson PM, Conrod P, Mackey S. Brain structural covariance network differences in adults with alcohol dependence and heavy‐drinking adolescents. Addiction 2022, 117: 1312-1325. PMID: 34907616, DOI: 10.1111/add.15772.Peer-Reviewed Original ResearchConceptsAlcohol dependenceHeavy drinking adolescentsStructural covariance networksAge 19Non-dependent controlsPre-existing risk factorsAge 14Cohort of adolescentsCross-sectional analysisRisk factorsAlcohol exposureEnhancing Neuroimaging GeneticsCortical thicknessHazardous drinkersEarly markerMeta-AnalysisNetwork segregationCross-sectional sampleIMAGEN studySubstantial exposureAdultsDrinking adolescentsCovariance networksBrain organizationAdolescents
2021
Perceived stress, self-efficacy, and the cerebral morphometric markers in binge-drinking young adults
Li G, Le TM, Wang W, Zhornitsky S, Chen Y, Chaudhary S, Zhu T, Zhang S, Bi J, Tang X, Li CR. Perceived stress, self-efficacy, and the cerebral morphometric markers in binge-drinking young adults. NeuroImage Clinical 2021, 32: 102866. PMID: 34749288, PMCID: PMC8569726, DOI: 10.1016/j.nicl.2021.102866.Peer-Reviewed Original ResearchConceptsGray matter volumePerceived stressNeural markersRegional cortical thicknessCortical structuresAlcohol use behaviorsNon-binge drinkersHuman Connectome ProjectChronic alcohol exposure altersCortical thicknessVoxel-based morphometryEmotional distressConnectome ProjectDrinking menPath analysisCortical regionsDrinking womenBinge drinkingMatter volumeYoung adultsUse behaviorsStress regulationPCC thicknessBingeAlcohol exposure altersIdentification of Binge Drinkers via Convolutional Neural Network and Support Vector Machine
Li G, Du S, Niu J, Zhang Z, Gao T, Tang X, Wang W, Li C. Identification of Binge Drinkers via Convolutional Neural Network and Support Vector Machine. 2021, 00: 715-720. DOI: 10.1109/icma52036.2021.9512720.Peer-Reviewed Original ResearchConvolutional neural networkNeural networkGray matter volumeSVM modelSupport vector machineNon-binge drinkersVector machine modelDeep learningVector machinePsychosocial measuresTraining samplesBinge drinkingYoung adult binge drinkingMachine modelAdult binge drinkingHuman Connectome ProjectNetworkPsychosocial markersClassificationConnectome ProjectBinge drinkersCortical thicknessMatter volumeBingeVolumetric differences
2020
Predicting alcohol dependence from multi‐site brain structural measures
Hahn S, Mackey S, Cousijn J, Foxe JJ, Heinz A, Hester R, Hutchinson K, Kiefer F, Korucuoglu O, Lett T, Li C, London E, Lorenzetti V, Maartje L, Momenan R, Orr C, Paulus M, Schmaal L, Sinha R, Sjoerds Z, Stein DJ, Stein E, van Holst R, Veltman D, Walter H, Wiers RW, Yucel M, Thompson PM, Conrod P, Allgaier N, Garavan H. Predicting alcohol dependence from multi‐site brain structural measures. Human Brain Mapping 2020, 43: 555-565. PMID: 33064342, PMCID: PMC8675424, DOI: 10.1002/hbm.25248.Peer-Reviewed Original ResearchConceptsAlcohol dependenceRight lateral orbitofrontal cortexLeft superior frontal gyrusCurrent alcohol dependenceTransverse temporal gyrusENIGMA Addiction Working GroupInclusion of casesSuperior frontal gyrusStructural magnetic resonanceCortical surface areaRight transverse temporal gyrusLateral orbitofrontal cortexBrain structural measuresCortical thicknessPutamen volumePotential biomarkersCortical Thickness in Alcohol Dependent Patients With Apathy
Yang K, Yang Q, Niu Y, Fan F, Chen S, Luo X, Tan S, Wang Z, Tong J, Yang F, Le TM, Li CR, Tan Y. Cortical Thickness in Alcohol Dependent Patients With Apathy. Frontiers In Psychiatry 2020, 11: 364. PMID: 32431630, PMCID: PMC7214693, DOI: 10.3389/fpsyt.2020.00364.Peer-Reviewed Original ResearchInferior parietal cortexHealthy controlsCortical thicknessSuperior parietal cortexOccipito-temporal cortexParietal cortexOccipital gyrusBilateral superior parietal cortexCritical clinical featuresStructural brain changesEducation-matched healthy controlsSeverity of apathyRight superior occipital gyrusAlcohol-dependent patientsBilateral lingual gyrusLeft middle occipital gyrusSuperior occipital gyrusMiddle occipital gyrusBilateral inferior parietal cortexOccipital-temporal cortexClinical featuresDependent patientsRight intraparietal sulcusMagnetic resonance imaging dataBrain changes
2018
Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects
Mackey S, Allgaier N, Chaarani B, Spechler P, Orr C, Bunn J, Allen NB, Alia-Klein N, Batalla A, Blaine S, Brooks S, Caparelli E, Chye YY, Cousijn J, Dagher A, Desrivieres S, Feldstein-Ewing S, Foxe JJ, Goldstein RZ, Goudriaan AE, Heitzeg MM, Hester R, Hutchison K, Korucuoglu O, Li CR, London E, Lorenzetti V, Luijten M, Martin-Santos R, May A, Momenan R, Morales A, Paulus MP, Pearlson G, Rousseau ME, Salmeron BJ, Schluter R, Schmaal L, Schumann G, Sjoerds Z, Stein DJ, Stein EA, Sinha R, Solowij N, Tapert S, Uhlmann A, Veltman D, van Holst R, Whittle S, Wiers R, Wright M, Yücel M, Zhang S, Yurgelun-Todd D, Hibar D, Jahanshad N, Evans A, Thompson P, Glahn D, Conrod P, Garavan H. Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects. American Journal Of Psychiatry 2018, 176: 119-128. PMID: 30336705, PMCID: PMC6427822, DOI: 10.1176/appi.ajp.2018.17040415.Peer-Reviewed Original ResearchConceptsRegional brain volumesControl subjectsSubstance dependenceBrain volumeBrain regionsLower brain volumeAlcohol use disorderGray matter volumeTotal intracranial volumeMedial orbitofrontal cortexCommon neural substrateCortical thicknessUse disordersUseful biomarkerMatter volumeSubcortical volumesImaging biomarkersAlcohol dependenceIntracranial volumeOrbitofrontal cortexRegional volumesBrain structuresRelevant imaging biomarkersLow volumeNeural substrates