2024
4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia
Pusuluri K, Fu Z, Miller R, Pearlson G, Kochunov P, Van Erp T, Iraji A, Calhoun V. 4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia. Human Brain Mapping 2024, 45: e26773. PMID: 39045900, PMCID: PMC11267451, DOI: 10.1002/hbm.26773.Peer-Reviewed Original ResearchConceptsBrain networksFunctional magnetic resonance imagingAssociated with cognitive performanceDynamics of functional brain networksAssociated with cognitionFunctional brain networksVoxel-wise changesVolumetric couplingDynamical variablesCognitive performanceTypical controlsSchizophreniaCognitive impairmentNetwork pairsMagnetic resonance imagingPair of networksCognitionAtypical variabilityResonance imagingCouplingNetwork connectivityNetwork growthImpairmentBrainStatic networksEvidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis
Meyhoefer I, Sprenger A, Derad D, Grotegerd D, Leenings R, Leehr E, Breuer F, Surmann M, Rolfes K, Arolt V, Romer G, Lappe M, Rehder J, Koutsouleris N, Borgwardt S, Schultze-Lutter F, Meisenzahl E, Kircher T, Keedy S, Bishop J, Ivleva E, McDowell J, Reilly J, Hill S, Pearlson G, Tamminga C, Keshavan M, Gershon E, Clementz B, Sweeney J, Hahn T, Dannlowski U, Lencer R. Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis. Scientific Reports 2024, 14: 13859. PMID: 38879556, PMCID: PMC11180169, DOI: 10.1038/s41598-024-64487-6.Peer-Reviewed Original ResearchConceptsSmooth pursuit eye movementsPsychosis syndromePursuit eye movementsNon-psychotic bipolar disorderNon-psychotic affective disorderEye movementsSmooth pursuit dysfunctionMultivariate pattern analysisHealthy controlsPsychiatric sampleNeurobiological markersPsychosis probandsPsychotic syndromesAffective disordersPsychosis researchBipolar disorderPsychosis statusPsychosisSensorimotor functionSensorimotor measuresIndividual levelSensorimotor dysfunctionSensorimotorDisordersPattern analysis
2023
Age-related, multivariate associations between white matter microstructure and behavioral performance in three executive function domains
Anderson J, Calhoun V, Pearlson G, Hawkins K, Stevens M. Age-related, multivariate associations between white matter microstructure and behavioral performance in three executive function domains. Developmental Cognitive Neuroscience 2023, 64: 101318. PMID: 37875033, PMCID: PMC10618425, DOI: 10.1016/j.dcn.2023.101318.Peer-Reviewed Original ResearchConceptsExecutive function domainsResponse inhibitionWhite matter microstructureLower response inhibitionStructure-cognition relationshipsEF abilitiesBehavioral performanceCognitive imbalanceNeurocognitive testsFunction domainTest performanceYoung adulthoodFractional anisotropyBrain changesAge 12Young adultsSS performanceWhite matter FA valuesGreater relianceWhite matter changesWhite matter microstructural differencesSubjects ages 12White matter skeletonIndependent componentsMultivariate associations
2020
Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA
Radua J, Vieta E, Shinohara R, Kochunov P, Quidé Y, Green M, Weickert C, Weickert T, Bruggemann J, Kircher T, Nenadić I, Cairns M, Seal M, Schall U, Henskens F, Fullerton J, Mowry B, Pantelis C, Lenroot R, Cropley V, Loughland C, Scott R, Wolf D, Satterthwaite T, Tan Y, Sim K, Piras F, Spalletta G, Banaj N, Pomarol-Clotet E, Solanes A, Albajes-Eizagirre A, Canales-Rodríguez E, Sarro S, Di Giorgio A, Bertolino A, Stäblein M, Oertel V, Knöchel C, Borgwardt S, du Plessis S, Yun J, Kwon J, Dannlowski U, Hahn T, Grotegerd D, Alloza C, Arango C, Janssen J, Díaz-Caneja C, Jiang W, Calhoun V, Ehrlich S, Yang K, Cascella N, Takayanagi Y, Sawa A, Tomyshev A, Lebedeva I, Kaleda V, Kirschner M, Hoschl C, Tomecek D, Skoch A, van Amelsvoort T, Bakker G, James A, Preda A, Weideman A, Stein D, Howells F, Uhlmann A, Temmingh H, López-Jaramillo C, Díaz-Zuluaga A, Fortea L, Martinez-Heras E, Solana E, Llufriu S, Jahanshad N, Thompson P, Turner J, van Erp T, collaborators E, Glahn D, Pearlson G, Hong E, Krug A, Carr V, Tooney P, Cooper G, Rasser P, Michie P, Catts S, Gur R, Gur R, Yang F, Fan F, Chen J, Guo H, Tan S, Wang Z, Xiang H, Piras F, Assogna F, Salvador R, McKenna P, Bonvino A, King M, Kaiser S, Nguyen D, Pineda-Zapata J. Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA. NeuroImage 2020, 218: 116956. PMID: 32470572, PMCID: PMC7524039, DOI: 10.1016/j.neuroimage.2020.116956.Peer-Reviewed Original Research
2019
Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol‐Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort
Meda SA, Narayanan B, Chorlian D, Meyers JL, Gelernter J, Hesselbrock V, Bauer L, Calhoun VD, Porjesz B, Pearlson G. Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol‐Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort. Alcohol Clinical And Experimental Research 2019, 43: 1462-1477. PMID: 31009096, DOI: 10.1111/acer.14063.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAlcoholismCase-Control StudiesCohort StudiesElectroencephalographyFemaleGenetic Association StudiesGenome-Wide Association StudyGenotypeHumansMaleMiddle AgedMultigene FamilyNeuronsPhenotypePolymorphism, Single NucleotideSignal TransductionSubstance-Related DisordersWhite PeopleYoung AdultConceptsGenetic clustersSingle nucleotide polymorphism dataSignificant genotype-phenotype associationsNucleotide polymorphism dataLipid/cholesterol metabolismLinkage-based analysisGenotype-phenotype relationshipsGenotype-phenotype associationsGene clusterCell signalingPolymorphism dataMolecular mechanismsAlcoholism datasetGenomewide associationTop hitsGenetic componentNeuronal signalingGeneticsSignalingBiological componentsRelationship pairsCholesterol metabolismNeurogenesisSNP componentParallel independent component analysis
2017
Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group
Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C, Andreassen O, Arango C, Banaj N, Bouix S, Bousman C, Brouwer R, Bruggemann J, Bustillo J, Cahn W, Calhoun V, Cannon D, Carr V, Catts S, Chen J, Chen J, Chen X, Chiapponi C, Cho K, Ciullo V, Corvin A, Crespo-Facorro B, Cropley V, De Rossi P, Diaz-Caneja C, Dickie E, Ehrlich S, Fan F, Faskowitz J, Fatouros-Bergman H, Flyckt L, Ford J, Fouche J, Fukunaga M, Gill M, Glahn D, Gollub R, Goudzwaard E, Guo H, Gur R, Gur R, Gurholt T, Hashimoto R, Hatton S, Henskens F, Hibar D, Hickie I, Hong L, Horacek J, Howells F, Hulshoff Pol H, Hyde C, Isaev D, Jablensky A, Jansen P, Janssen J, Jönsson E, Jung L, Kahn R, Kikinis Z, Liu K, Klauser P, Knöchel C, Kubicki M, Lagopoulos J, Langen C, Lawrie S, Lenroot R, Lim K, Lopez-Jaramillo C, Lyall A, Magnotta V, Mandl R, Mathalon D, McCarley R, McCarthy-Jones S, McDonald C, McEwen S, McIntosh A, Melicher T, Mesholam-Gately R, Michie P, Mowry B, Mueller B, Newell D, O'Donnell P, Oertel-Knöchel V, Oestreich L, Paciga S, Pantelis C, Pasternak O, Pearlson G, Pellicano G, Pereira A, Pineda Zapata J, Piras F, Potkin S, Preda A, Rasser P, Roalf D, Roiz R, Roos A, Rotenberg D, Satterthwaite T, Savadjiev P, Schall U, Scott R, Seal M, Seidman L, Shannon Weickert C, Whelan C, Shenton M, Kwon J, Spalletta G, Spaniel F, Sprooten E, Stäblein M, Stein D, Sundram S, Tan Y, Tan S, Tang S, Temmingh H, Westlye L, Tønnesen S, Tordesillas-Gutierrez D, Doan N, Vaidya J, van Haren N, Vargas C, Vecchio D, Velakoulis D, Voineskos A, Voyvodic J, Wang Z, Wan P, Wei D, Weickert T, Whalley H, White T, Whitford T, Wojcik J, Xiang H, Xie Z, Yamamori H, Yang F, Yao N, Zhang G, Zhao J, van Erp T, Turner J, Thompson P, Donohoe G. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group. Molecular Psychiatry 2017, 23: 1261-1269. PMID: 29038599, PMCID: PMC5984078, DOI: 10.1038/mp.2017.170.Peer-Reviewed Original ResearchConceptsSchizophrenia patientsFractional anisotropyWM skeletonWhite matter microstructural differencesWhite matter abnormalitiesWidespread WM abnormalitiesOnset of schizophreniaAnterior corona radiataEffect sizeDiffusion tensor imaging (DTI) dataTensor imaging dataHealthy controlsMeta-analyzed effectsCorpus callosumMedication dosageCorona radiataPsychiatric disordersLarge effect sizesWM microstructural differencesPatientsWM abnormalitiesRadial diffusivitySchizophreniaSignificant decreaseDiffusivity measures
2016
Polygenic risk of Alzheimer disease is associated with early- and late-life processes
Mormino EC, Sperling RA, Holmes AJ, Buckner RL, De Jager PL, Smoller JW, Sabuncu MR, Weiner M, Aisen P, Weiner M, Aisen P, Petersen R, Jack C, Jagust W, Trojanowki J, Toga A, Beckett L, Green R, Saykin A, Morris J, Liu E, Green R, Montine T, Petersen R, Aisen P, Gamst A, Thomas R, Donohue M, Walter S, Gessert D, Sather T, Beckett L, Harvey D, Gamst A, Donohue M, Kornak J, Jack C, Dale A, Bernstein M, Felmlee J, Fox N, Thompson P, Schuff N, Alexander G, DeCarli C, Jagust W, Bandy D, Koeppe R, Foster N, Reiman E, Chen K, Mathis C, Morris J, Cairns N, Taylor-Reinwald L, Trojanowki J, Shaw L, Lee V, Korecka M, Toga A, Crawford K, Neu S, Saykin A, Foroud T, Potkin S, Shen L, Kachaturian Z, Frank R, Snyder P, Molchan S, Kaye J, Quinn J, Lind B, Dolen S, Schneider L, Pawluczyk S, Spann B, Brewer J, Vanderswag H, Heidebrink J, Lord J, Petersen R, Johnson K, Doody R, Villanueva-Meyer J, Chowdhury M, Stern Y, Honig L, Bell K, Morris J, Ances B, Carroll M, Leon S, Mintun M, Schneider S, Marson D, Griffith R, Clark D, Grossman H, Mitsis E, Romirowsky A, deToledo-Morrell L, Shah R, Duara R, Varon D, Roberts P, Albert M, Onyike C, Kielb S, Rusinek H, de Leon M, Glodzik L, De Santi S, Doraiswamy P, Petrella J, Coleman R, Arnold S, Karlawish J, Wolk D, Smith C, Jicha G, Hardy P, Lopez O, Oakley M, Simpson D, Porsteinsson A, Goldstein B, Martin K, Makino K, Ismail M, Brand C, Mulnard R, Thai G, Mc-Adams-Ortiz C, Womack K, Mathews D, Quiceno M, Diaz-Arrastia R, King R, Weiner M, Martin-Cook K, DeVous M, Levey A, Lah J, Cellar J, Burns J, Anderson H, Swerdlow R, Apostolova L, Lu P, Bartzokis G, Silverman D, Graff-Radford N, Parfitt F, Johnson H, Farlow M, Hake A, Matthews B, Herring S, van Dyck C, Carson R, MacAvoy M, Chertkow H, Bergman H, Hosein C, Black S, Stefanovic B, Caldwell C, Robin Hsiung G, Feldman H, Mudge B, Assaly M, Kertesz A, Rogers J, Trost D, Bernick C, Munic D, Kerwin D, Mesulam M, Lipowski K, Wu C, Johnson N, Sadowsky C, Martinez W, Villena T, Turner R, Johnson K, Reynolds B, Sperling R, Johnson K, Marshall G, Frey M, Yesavage J, Taylor J, Lane B, Rosen A, Tinklenberg J, Sabbagh M, Belden C, Jacobson S, Kowall N, Killiany R, Budson A, Norbash A, Johnson P, Obisesan T, Wolday S, Bwayo S, Lerner A, Hudson L, Ogrocki P, Fletcher E, Carmichael O, Olichney J, DeCarli C, Kittur S, Borrie M, Lee T, Bartha D, Johnson S, Asthana S, Carlsson C, Potkin S, Preda A, Nguyen D, Tariot P, Fleisher A, Reeder S, Bates V, Capote H, Rainka M, Scharre D, Kataki M, Zimmerman E, Celmins D, Brown A, Pearlson G, Blank K, Anderson K, Saykin A, Santulli R, Schwartz E, Sink K, Williamson J, Garg P, Watkins F, Ott B, Querfurth H, Tremont G, Salloway S, Malloy P, Correia S, Rosen H, Miller B, Mintzer J, Longmire C, Spicer K, Finger E, Rachinsky I, Rogers J, Kertesz A, Drost D, Pomara N, Hernando R, Sarrael A, Schultz S, Boles Ponto L, Shim H, Smith K, Relkin N, Chaing G, Raudin L, Smith A, Fargher K, Raj B. Polygenic risk of Alzheimer disease is associated with early- and late-life processes. Neurology 2016, 87: 481-488. PMID: 27385740, PMCID: PMC4970660, DOI: 10.1212/wnl.0000000000002922.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAlzheimer DiseaseAmyloid beta-PeptidesAniline CompoundsAtrophyBiomarkersCognition DisordersCohort StudiesEarly DiagnosisEthylene GlycolsFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHippocampusHumansMaleMemory DisordersMultifactorial InheritancePolymorphism, Single NucleotidePositron-Emission TomographyYoung AdultConceptsHigher polygenic risk scorePolygenic risk scoresHippocampus volumeRisk scoreLarge observational cohort studyCommon genetic risk lociSmaller hippocampus volumesΒ-amyloid burdenObservational cohort studyGenetic riskElevated polygenic risk scoresAlzheimer's disease markersCSF β-amyloidLongitudinal cognitive declineHealthy young participantsCohort studyClinical progressionClinical symptomsAD dementiaAD markersSmaller hippocampiFlorbetapir PETAggregate genetic riskΒ-amyloidGenome-wide association studies
2014
Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia
Meda SA, Ruaño G, Windemuth A, O’Neil K, Berwise C, Dunn SM, Boccaccio LE, Narayanan B, Kocherla M, Sprooten E, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA, Calhoun VD, Pearlson GD. Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia. Proceedings Of The National Academy Of Sciences Of The United States Of America 2014, 111: e2066-e2075. PMID: 24778245, PMCID: PMC4024891, DOI: 10.1073/pnas.1313093111.Peer-Reviewed Original ResearchConceptsDefault mode networkPsychotic bipolar disorderUnaffected first-degree relativesFirst-degree relativesSZ probandsResting-state functional MRI scansBipolar disorderMode networkFunctional MRI scansLong-term potentiationBrain's default mode networkGlobal enrichment analysisSubset of controlsPatient groupHealthy controlsDMN modulationDrug treatmentImmune responsePsychiatric disordersStudy subjectsMRI scansDMN connectivityMultivariate analysisFunctional connectivitySchizophrenia
2012
Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia
Sui J, He H, Liu J, Yu Q, Adali T, Pearlson G, Calhoun V. Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2012, 2012: 2692-2695. PMID: 23366480, DOI: 10.1109/embc.2012.6346519.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlgorithmsFemaleHumansMagnetic Resonance ImagingMaleMultivariate AnalysisSchizophreniaYoung AdultConceptsMulti-set canonical correlation analysisData fusionMulti-modal fusionDisparate data setsMultiple data typesJoint independent component analysisData typesFusion modelJoint informationData setsIndependent component analysisHigher decomposition accuracyEffective mannerCanonical correlation analysisDecomposition accuracyLimited viewEffective approachPromising approachBiomedical imagingFusionComponent analysisAccuracyIllness biomarkersInformationSetHexanucleotide repeat expansions in C9ORF72 in the spectrum of motor neuron diseases
van Rheenen W, van Blitterswijk M, Huisman M, Vlam L, van Doormaal P, Seelen M, Medic J, Dooijes D, de Visser M, van der Kooi A, Raaphorst J, Schelhaas H, van der Pol W, Veldink J, van den Berg L, Weiner M, Aisen P, Petersen R, Clifford R, Jagust W, Trojanowki J, Toga A, Beckett L, Green R, Saykin A, Morris J, Liu E, Montine T, Gamst A, Thomas R, Donohue M, Walter S, Gessert D, Sather T, Beckett L, Harvey D, Gamst A, Donohue M, Kornak J, Dale A, Bernstein M, Felmlee J, Fox N, Thompson P, Schuff N, Alexander G, DeCarli C, Bandy D, Koeppe R, Foster N, Reiman E, Chen K, Mathis C, Cairns N, Taylor-Reinwald L, Shaw L, Lee V, Korecka M, Crawford K, Neu S, Foroud T, Potkin S, Shen L, Kachaturian Z, Frank R, Snyder P, Kaye J, Dolen S, Quinn J, Schneider L, Pawluczyk S, Spann B, Brewer J, Vanderswag H, Heidebrink J, Lord J, Petersen R, Johnson K, S. Doody R, Villanueva-Meyer J, Chowdhury M, Stern Y, Honig L, Bell K, Morris J, Mintun M, Schneider S, Marson D, Griffith R, Clark D, Grossman H, Mitsis E, Romirowsky A, deToledo-Morrell L, Shah R, Duara R, Varon D, Roberts P, Albert M, Onyike C, Kielb S, Rusinek H, de Leon M, Glodzik L, Doraiswamy P, Petrella J, Arnold S, Karlawish J, Wolk D, Smith C, Jicha G, Hardy P, Lopez O, Oakley M, Simpson D, Ismail M, Brand C, Mulnard R, Thai G, Mc-Adams-Ortiz C, Diaz-Arrastia R, Martin-Cook K, DeVous M, Levey A, Lah J, Cellar J, Burns J, Anderson H, Swerdlow R, Bartzokis G, Silverman D, Lu P, Apostolova L, Graff-Radford N, Parfitt F, Johnson H, Farlow M, Herring S, Hake A, van Dyck C, Carson R, MacAvoy M, Chertkow H, Bergman H, Hosein C, Black S, Stefanovic B, Caldwell C, Hsiung G, Feldman H, Assaly M, Kertesz A, Rogers J, Trost D, Bernick C, Munic D, Wu C, Johnson N, Mesulam M, Sadowsky C, Martinez W, Villena T, Turner R, Johnson K, Reynolds B, Sperling R, Frey M, Johnson K, Rosen A, Tinklenberg J, Sabbagh M, Belden C, Jacobson S, Killiany R, Norbash A, Obisesan T, Wolday S, Bwayo S, Lerner A, Hudson L, Ogrocki P, DeCarli C, Fletcher E, Carmichael O, Kittur S, Borrie M, Lee T, Bartha R, Johnson S, Asthana S, Carlsson C, Potkin S, Preda A, Nguyen D, Tariot P, Fleisher A, Reeder S, Bates V, Capote H, Rainka M, Hendin B, Scharre D, Kataki M, Zimmerman E, Celmins D, Brown A, Pearlson G, Blank K, Anderson K, Saykin A, Santulli R, Schwartz E, Williamson J, Sink K, Watkins F, Ott B, Querfurth H, Tremont G, Salloway S, Malloy P, Correia S, Rosen H, Miller B, Mintzer J, Longmire C, Spicer K, Kwon S, Kim J, Cho K, Shin D, Ko Y, Lee S, Cha J, Kim Y, Shin D, Jang H, Choi N, Hong S, Rha J, Hong K, Kim E, Choi J, Sohn S, Shin W, HyukHeo S, Chung K, Park J, Lee J, Park J, Park T, Bae H, Han M, Kwon H, Lee K, Lee T, Jeong D, Lee J, Ashwal S, deVeber G, Ferriero D, Fullerton H, Ichord R, Kirkham F, Lynch J, O'Callaghan F, Pavlakis S, Sebire G, Willan A, Willan A, Sofronas M, Dlamini N, Elbers J, Nowak-Göttl U, Düring C, Krümpel A, Plumb P, Journeycake J, van de Bruinhorst K, Gossett D, Hernandez Chavez M, Monagle P, MacKay M, Barnes C, Furmedge J, Gordon A, Benedict S, Bale J, Nielson D, Abdalla A, Chadehumbe M, Kabbouche M, Karti P, Phillips T, Friedman N, Rizkallah E, Zamel K, Wiznitzer M, Lidsky K, Bernard T, Goldenberg N, Armstrong-Wells J, Booth F, Nash M, Beslow L, Carpenter J, Chang T, Weinstein S, Kan L, Smith R, Maytal J, Sy-Kho R, Yager J, Massicotte P, Ashwal S, McClure C, Bjornson B, Hukin J, Bucevska M, Kent S, Riviello J, Rivkin M, Trenor C, Amlie-Lefond C, Whelan H, Ferriero D, Fullerton H, Fox C, Pavlakis S, Goodman S, Levinson K, Kolk A, Laugesaar R, Talvik T, Imam H, Thomas T, Golomb M, Kirton A, Heyer G, Ganesan V, Saengpattrachai M, Crosswell H, Mancuso A, Tatishvili N, Yeh A, Humpherys P, Abraham L, Alveal L, Ortiz M, Altuna D, Maxit C, Gonzalez V, Alam M, Buckley D, Penney S, Jordan L, Grabowski E, Chan A, Deray M, Khatib Z, Kovacevic G, Kosofsky B, Leifer D, Nass R, Wong V, Catsman C, El-Hakam L, Sebire G, Cholette J, Narang S, Lerner N, Carpenter S, Bischoff K, Frei-Jones M, Masur D, Epstein L, Bagiella E, Hinton V, Gallentine W, Rende E, Provenzale J, Voyvodic J, Song A, Conklin T, O'Hara K, Seinfeld S, Conry J, Glauser T, Ayala J, Facchini R, Sigalova M, Hannigan J, Weiss E, Mancini A, Curran J, Ahlm S, Renaldi J, Umanzour D, Kim A, Hamidullah A, Litherland C, Bonner M, Xu Y, Van de Water V, Grasso S, Kushner D, Culbert J, Bush B, Chandrasekaran S, Davis L, Rogers C, Sabo C, Wang H, Noebels J. Hexanucleotide repeat expansions in C9ORF72 in the spectrum of motor neuron diseases. Neurology 2012, 79: 878-882. PMID: 22843265, DOI: 10.1212/wnl.0b013e3182661d14.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge of OnsetAgedAged, 80 and overAmyotrophic Lateral SclerosisC9orf72 ProteinCohort StudiesConfidence IntervalsDementiaDNADNA Repeat ExpansionFemaleFrontotemporal Lobar DegenerationGenotypeHumansMaleMiddle AgedMotor Neuron DiseaseMuscular Atrophy, SpinalMutationParkinson DiseasePolymerase Chain ReactionProportional Hazards ModelsProteinsSurvivalYoung AdultConceptsProgressive muscular atrophyPrimary lateral sclerosisAmyotrophic lateral sclerosisSporadic amyotrophic lateral sclerosisParkinson's diseaseShorter survivalLateral sclerosisRelatives of patientsFamilial aggregationRepeat expansionHexanucleotide repeat expansionControl subjectsMotor neuronsLarge cohortPatientsMuscular atrophyGenetic testingEarly onsetMajor causeDementiaC9orf72SclerosisFALSEarly ageDutch descent