2025
Exploration of Genetic Overlap of Brain Phenotypes With Schizophrenia: Different Methods Provide Complementary Insights
Wu X, Parekh P, Lin B, Pries L, Guloksuz S, Rutten B, Andreassen O, Linden D, van der Meer D. Exploration of Genetic Overlap of Brain Phenotypes With Schizophrenia: Different Methods Provide Complementary Insights. Schizophrenia Bulletin 2025, sbaf096. PMID: 40579369, DOI: 10.1093/schbul/sbaf096.Peer-Reviewed Original ResearchDiffusion tensor imagingBrain measuresPolygenic scoresRs-fMRIPolygenic overlapResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingGenome-wide association study summary statisticsLinkage disequilibrium score regressionConcordant effect directionsConjunctional false discovery rateSNP-based heritabilityFunctional brain featuresBrain imaging phenotypesSchizophreniaBrain structuresFunctional connectivityBrain phenotypesGenetic overlapScore regressionBrain featuresComplex genetic relationshipsRs-fMRI measuresIndividual locus levelCausal variantsAlcohol use disorder and body mass index show genetic pleiotropy and shared neural associations
Malone S, Davis C, Piserchia Z, Setzer M, Toikumo S, Zhou H, Winterlind E, Gelernter J, Justice A, Leggio L, Rentsch C, Kranzler H, Gray J. Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations. Nature Human Behaviour 2025, 9: 1056-1066. PMID: 40164914, DOI: 10.1038/s41562-025-02148-y.Peer-Reviewed Original ResearchConceptsAlcohol use disorderUse disorderBrain regionsGenotype-Tissue ExpressionSingle-nucleotide polymorphismsPolygenic overlapAssociated with alcohol use disorderCaudate nucleus volumeBody mass indexMultiple brain regionsConjunctional false discovery rateNeurobiological overlapExecutive functionNeurobiological mechanismsNeural associationsBrain phenotypesNucleus volumeFalse discovery rate methodFalse discovery rateGenetic architectureVariant effectsMass indexGenetic pleiotropyDiscovery rateTissue enrichment
2024
F85. GENETIC OVERLAP OF BRAIN STRUCTURE AND CONNECTIVITY WITH SCHIZOPHRENIA: DIFFERENT STATISTICAL METHODS PROVIDE COMPLEMENTARY INSIGHTS
Wu X, Parekh P, Lin B, Pries L, Guloksuz S, Rutten B, Andreassen O, Linden D, van der Meer D. F85. GENETIC OVERLAP OF BRAIN STRUCTURE AND CONNECTIVITY WITH SCHIZOPHRENIA: DIFFERENT STATISTICAL METHODS PROVIDE COMPLEMENTARY INSIGHTS. European Neuropsychopharmacology 2024, 87: 251. DOI: 10.1016/j.euroneuro.2024.08.496.Peer-Reviewed Original ResearchConcordant effect directionsLinkage disequilibrium score regressionGenome-wide association study dataCell adhesion molecule bindingGenetic architectureBrain measuresPolygenic scoresBrain phenotypesUnique genesGene OntologyBrain structuresConjunctional false discovery rateLinkage disequilibrium score regression analysisGenetic correlationsGenetic risk of schizophreniaComplex genetic architectureHeritable brain disorderKyoto Encyclopedia of GenesAssociated with schizophreniaInsignificant genetic correlationResting-state fMRIWhite matter integrityEncyclopedia of GenesPostsynaptic densityRisk of schizophreniaMulti-modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain
Bueichekú E, Diez I, Gagliardi G, Kim C, Mimmack K, Sepulcre J, Vannini P. Multi-modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain. Communications Medicine 2024, 4: 65. PMID: 38580832, PMCID: PMC10997795, DOI: 10.1038/s43856-024-00497-9.Peer-Reviewed Original ResearchMemory declineMedial anterior prefrontal cortexAging BrainWhole-brain voxel-wiseAnterior prefrontal cortexRegion-of-interest analysisResting-state functional MRIObjective memory declineOccipito-parietal regionsMulti-modal neuroimagingNetwork connectivity patternsAlzheimer's diseaseFunctional connectivity networksPrefrontal cortexMnemonic anosognosiaTau burdenBiomarkers of AD pathologyMode networkParieto-occipital areasFunctional network connectivity disruptionFunctional MRIBrain phenotypesVoxel-wiseBehavioral conditionsBehavioral biomarkers
2023
Multi‐modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain
Bueichekú E, Diez I, Gagliardi G, Kim C, Mimmack K, Sepulcre J, Vannini P. Multi‐modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain. Alzheimer's & Dementia 2023, 19 DOI: 10.1002/alz.080294.Peer-Reviewed Original ResearchMnemonic anosognosiaOccipito-parietal regionsMemory declineBrain phenotypesSelf-referential brain networkObjective memory testsObjective memory declineResting-state fMRIPosterior cerebral cortexMulti-modal neuroimagingNetwork connectivity patternsAlzheimer's diseaseFunctional connectivity networksGraph theory metricsTau burdenNeurocognitive profileBiomarkers of AD pathologyMemory testMemory impairmentBetween-group comparisonsFunctional network connectivity disruptionBrain networksAging BrainAnosognosiaBehavioral conditions
2021
Unveiling the neuroimaging-genetic intersections in the human brain
Diez I, Sepulcre J. Unveiling the neuroimaging-genetic intersections in the human brain. Current Opinion In Neurology 2021, 34: 480-487. PMID: 34227572, PMCID: PMC8265485, DOI: 10.1097/wco.0000000000000952.Peer-Reviewed Original ResearchConceptsSingle-cell transcriptomic dataExpression of genesFunctional annotationGenetic networksGenetic dataTranscriptome dataTranscriptomic datasetsBrain genesGenesBrain phenotypesBrain expressionBiological mechanismsNeuroimaging workNeuroimaging mapsBrain-wideNeuroimaging findingsLife spanExpressionTranscriptomeHuman brainNeuroimagingMapping cortical and subcortical asymmetries in substance dependence: Findings from the ENIGMA Addiction Working Group
Cao Z, Ottino‐Gonzalez J, Cupertino RB, Schwab N, Hoke C, Catherine O, Cousijn J, Dagher A, Foxe JJ, Goudriaan AE, Hester R, Hutchison K, Li C, London ED, Lorenzetti V, Luijten M, Martin‐Santos R, Momenan R, Paulus MP, Schmaal L, Sinha R, Sjoerds Z, Solowij N, Stein DJ, Stein EA, Uhlmann A, van Holst R, Veltman DJ, Wiers RW, Yücel M, Zhang S, Jahanshad N, Thompson PM, Conrod P, Mackey S, Garavan H. Mapping cortical and subcortical asymmetries in substance dependence: Findings from the ENIGMA Addiction Working Group. Addiction Biology 2021, 26: e13010. PMID: 33508888, PMCID: PMC8317852, DOI: 10.1111/adb.13010.Peer-Reviewed Original ResearchConceptsENIGMA Addiction Working GroupSubstance dependenceBrain asymmetrySubstance-specific effectsAltered brain structureNondependent participantsStructural brain asymmetrySubcortical asymmetriesNucleus accumbensNicotine dependencePsychiatric diagnosisSubcortical regionsAlcohol dependenceWorking GroupBrain phenotypesBrain structuresVolume asymmetryHemispheric differentiationIndividualsParticipantsPrevious studiesMRI datasetsGroupAccumbensFindings
2018
Analysis of shared heritability in common disorders of the brain
Consortium T, Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, Duncan L, Escott-Price V, Falcone GJ, Gormley P, Malik R, Patsopoulos NA, Ripke S, Wei Z, Yu D, Lee PH, Turley P, Grenier-Boley B, Chouraki V, Kamatani Y, Berr C, Letenneur L, Hannequin D, Amouyel P, Boland A, Deleuze JF, Duron E, Vardarajan BN, Reitz C, Goate AM, Huentelman MJ, Kamboh MI, Larson EB, Rogaeva E, St George-Hyslop P, Hakonarson H, Kukull WA, Farrer LA, Barnes LL, Beach TG, Demirci FY, Head E, Hulette CM, Jicha GA, Kauwe JSK, Kaye JA, Leverenz JB, Levey AI, Lieberman AP, Pankratz VS, Poon WW, Quinn JF, Saykin AJ, Schneider LS, Smith AG, Sonnen JA, Stern RA, Van Deerlin VM, Van Eldik LJ, Harold D, Russo G, Rubinsztein DC, Bayer A, Tsolaki M, Proitsi P, Fox NC, Hampel H, Owen MJ, Mead S, Passmore P, Morgan K, Nöthen MM, Schott J, Rossor M, Lupton M, Hoffmann P, Kornhuber J, Lawlor B, McQuillin A, Al-Chalabi A, Bis J, Ruiz A, Boada M, Seshadri S, Beiser A, Rice K, van der Lee S, De Jager P, Geschwind D, Riemenschneider M, Riedel-Heller S, Rotter J, Ransmayr G, Hyman B, Cruchaga C, Alegret M, Winsvold B, Palta P, Farh K, Cuenca-Leon E, Furlotte N, Kurth T, Ligthart L, Terwindt G, Freilinger T, Ran C, Gordon S, Borck G, Adams H, Lehtimäki T, Wedenoja J, Buring J, Schürks M, Hrafnsdottir M, Hottenga J, Penninx B, Artto V, Kaunisto M, Vepsäläinen S, Martin N, Montgomery G, Kurki M, Hämäläinen E, Huang H, Huang J, Sandor C, Webber C, Muller-Myhsok B, Schreiber S, Salomaa V, Loehrer E, Göbel H, Macaya A, Pozo-Rosich P, Hansen T, Werge T, Kaprio J, Metspalu A, Kubisch C, Ferrari M, Belin A, van den Maagdenberg A, Zwart J, Boomsma D, Eriksson N, Olesen J, Chasman D, Nyholt D, Anney R, Avbersek A, Baum L, Berkovic S, Bradfield J, Buono R, Catarino C, Cossette P, De Jonghe P, Depondt C, Dlugos D, Ferraro T, French J, Hjalgrim H, Jamnadas-Khoda J, Kälviäinen R, Kunz W, Lerche H, Leu C, Lindhout D, Lo W, Lowenstein D, McCormack M, Møller R, Molloy A, Ng P, Oliver K, Privitera M, Radtke R, Ruppert A, Sander T, Schachter S, Schankin C, Scheffer I, Schoch S, Sisodiya S, Smith P, Sperling M, Striano P, Surges R, Thomas G, Visscher F, Whelan C, Zara F, Heinzen E, Marson A, Becker F, Stroink H, Zimprich F, Gasser T, Gibbs R, Heutink P, Martinez M, Morris H, Sharma M, Ryten M, Mok K, Pulit S, Bevan S, Holliday E, Attia J, Battey T, Boncoraglio G, Thijs V, Chen W, Mitchell B, Rothwell P, Sharma P, Sudlow C, Vicente A, Markus H, Kourkoulis C, Pera J, Raffeld M, Silliman S, Perica V, Thornton L, Huckins L, Rayner N, Lewis C, Gratacos M, Rybakowski F, Keski-Rahkonen A, Raevuori A, Hudson J, Reichborn-Kjennerud T, Monteleone P, Karwautz A, Mannik K, Baker J, O’Toole J, Trace S, Davis O, Helder S, Ehrlich S, Herpertz-Dahlmann B, Danner U, van Elburg A, Clementi M, Forzan M, Docampo E, Lissowska J, Hauser J, Tortorella A, Maj M, Gonidakis F, Tziouvas K, Papezova H, Yilmaz Z, Wagner G, Cohen-Woods S, Herms S, Julià A, Rabionet R, Dick D, Ripatti S, Andreassen O, Espeseth T, Lundervold A, Steen V, Pinto D, Scherer S, Aschauer H, Schosser A, Alfredsson L, Padyukov L, Halmi K, Mitchell J, Strober M, Bergen A, Kaye W, Szatkiewicz J, Cormand B, Ramos-Quiroga J, Sánchez-Mora C, Ribasés M, Casas M, Hervas A, Arranz M, Haavik J, Zayats T, Johansson S, Williams N, Elia J, Dempfle A, Rothenberger A, Kuntsi J, Oades R, Banaschewski T, Franke B, Buitelaar J, Vasquez A, Doyle A, Reif A, Lesch K, Freitag C, Rivero O, Palmason H, Romanos M, Langley K, Rietschel M, Witt S, Dalsgaard S, Børglum A, Waldman I, Wilmot B, Molly N, Bau C, Crosbie J, Schachar R, Loo S, McGough J, Grevet E, Medland S, Robinson E, Weiss L, Bacchelli E, Bailey A, Bal V, Battaglia A, Betancur C, Bolton P, Cantor R, Celestino-Soper P, Dawson G, De Rubeis S, Duque F, Green A, Klauck S, Leboyer M, Levitt P, Maestrini E, Mane S, De-Luca D, Parr J, Regan R, Reichenberg A, Sandin S, Vorstman J, Wassink T, Wijsman E, Cook E, Santangelo S, Delorme R, Rogé B, Magalhaes T, Arking D, Schulze T, Thompson R, Strohmaier J, Matthews K, Melle I, Morris D, Blackwood D, McIntosh A, Bergen S, Schalling M, Jamain S, Maaser A, Fischer S, Reinbold C, Fullerton J, Grigoroiu-Serbanescu M, Guzman-Parra J, Mayoral F, Schofield P, Cichon S, Mühleisen T, Degenhardt F, Schumacher J, Bauer M, Mitchell P, Gershon E, Rice J, Potash J, Zandi P, Craddock N, Ferrier I, Alda M, Rouleau G, Turecki G, Ophoff R, Pato C, Anjorin A, Stahl E, Leber M, Czerski P, Edenberg H, Cruceanu C, Jones I, Posthuma D, Andlauer T, Forstner A, Streit F, Baune B, Air T, Sinnamon G, Wray N, MacIntyre D, Porteous D, Homuth G, Rivera M, Grove J, Middeldorp C, Hickie I, Pergadia M, Mehta D, Smit J, Jansen R, de Geus E, Dunn E, Li Q, Nauck M, Schoevers R, Beekman A, Knowles J, Viktorin A, Arnold P, Barr C, Bedoya-Berrio G, Bienvenu O, Brentani H, Burton C, Camarena B, Cappi C, Cath D, Cavallini M, Cusi D, Darrow S, Denys D, Derks E, Dietrich A, Fernandez T, Figee M, Freimer N, Gerber G, Grados M, Greenberg E, Hanna G, Hartmann A, Hirschtritt M, Hoekstra P, Huang A, Huyser C, Illmann C, Jenike M, Kuperman S, Leventhal B, Lochner C, Lyon G, Macciardi F, Madruga-Garrido M, Malaty I, Maras A, McGrath L, Miguel E, Mir P, Nestadt G, Nicolini H, Okun M, Pakstis A, Paschou P, Piacentini J, Pittenger C, Plessen K, Ramensky V, Ramos E, Reus V, Richter M, Riddle M, Robertson M, Roessner V, Rosário M, Samuels J, Sandor P, Stein D, Tsetsos F, Van Nieuwerburgh F, Weatherall S, Wendland J, Wolanczyk T, Worbe Y, Zai G, Goes F, McLaughlin N, Nestadt P, Grabe H, Depienne C, Konkashbaev A, Lanzagorta N, Valencia-Duarte A, Bramon E, Buccola N, Cahn W, Cairns M, Chong S, Cohen D, Crespo-Facorro B, Crowley J, Davidson M, DeLisi L, Dinan T, Donohoe G, Drapeau E, Duan J, Haan L, Hougaard D, Karachanak-Yankova S, Khrunin A, Klovins J, Kučinskas V, Keong J, Limborska S, Loughland C, Lönnqvist J, Maher B, Mattheisen M, McDonald C, Murphy K, Murray R, Nenadic I, van Os J, Pantelis C, Pato M, Petryshen T, Quested D, Roussos P, Sanders A, Schall U, Schwab S, Sim K, So H, Stögmann E, Subramaniam M, Toncheva D, Waddington J, Walters J, Weiser M, Cheng W, Cloninger R, Curtis D, Gejman P, Henskens F, Mattingsdal M, Oh S, Scott R, Webb B, Breen G, Churchhouse C, Bulik C, Daly M, Dichgans M, Faraone S, Guerreiro R, Holmans P, Kendler K, Koeleman B, Mathews C, Price A, Scharf J, Sklar P, Williams J, Wood N, Cotsapas C, Palotie A, Smoller J, Sullivan P, Rosand J, Corvin A, Neale B. Analysis of shared heritability in common disorders of the brain. Science 2018, 360 PMID: 29930110, PMCID: PMC6097237, DOI: 10.1126/science.aap8757.Peer-Reviewed Original ResearchConceptsPsychiatric disordersBrain disordersCommon variant riskRisk factorsCommon disorderNeurological disordersDiagnostic misclassificationBrain phenotypesCommon genetic variationControl participantsDisordersVariant riskPhenotypic heterogeneityBrainEtiologic overlapGenetic sharingGenome-wide association studiesCognitive measuresAssociation studiesPhenotype
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