2024
A multimodal Neuroimaging-Based risk score for mild cognitive impairment
Zendehrouh E, Sendi M, Abrol A, Batta I, Hassanzadeh R, Calhoun V. A multimodal Neuroimaging-Based risk score for mild cognitive impairment. NeuroImage Clinical 2024, 45: 103719. PMID: 39637673, PMCID: PMC11664180, DOI: 10.1016/j.nicl.2024.103719.Peer-Reviewed Original ResearchMild cognitive impairment riskMild cognitive impairmentMild cognitive impairment groupRisk of mild cognitive impairmentRisk scoreUK Biobank participantsFunctional network connectivityCognitive impairmentPrecursor to ADSignificant cognitive declineBiobank participantsUK BiobankMild cognitive impairment individualsGenetic risk factorsAlzheimer's diseaseFunctional MRIHigh-risk groupStructural MRIAD riskRisk factorsCognitive declineFeatures of CNGray matterDifferentiate CNParticipantsAsian Cohort for Alzheimer Disease (ACAD) Pilot Study
Peavy G, Võ N, Revta C, Lu A, Lupo J, Nam P, Nguyễn K, Wang L, Feldman H. Asian Cohort for Alzheimer Disease (ACAD) Pilot Study. Alzheimer Disease & Associated Disorders 2024, 38: 277-284. PMID: 39177172, PMCID: PMC11340683, DOI: 10.1097/wad.0000000000000631.Peer-Reviewed Original ResearchConceptsSubjective cognitive complaintsOlder Vietnamese AmericansVascular risk factorsMild cognitive impairmentVietnamese AmericansRisk factorsMeasuring subjective cognitive complaintsPilot studyCommunity advisory boardNongenetic risk factorsCommunity-based researchAD risk factorsAlzheimer's diseaseDepressive symptomsConsensus teamCognitive complaintsBilingual/bicultural staffAD riskAssessment toolAdvisory BoardVietnamese communityExploratory analysisCognitive difficultiesCognitive impairmentParticipantsPharmacoepidemiology evaluation of bumetanide as a potential candidate for drug repurposing for Alzheimer's disease
Morales J, Gabriel N, Natarajan L, LaCroix A, Shadyab A, Xu R, Silverman J, Feldman H, Hernandez I, Aslanyan V, Bang A, Bevins E, Bowman G, Boyarko B, Chen X, Clelland C, Dodge H, Durant J, Edland S, Evans A, Galasko D, Gerwick W, Greenberg B, Herman M, Herold T, Hook V, Jacobs D, Kaye J, Kim D, Koo E, Kosik K, Léger G, Lupo J, Messer K, Momper J, Nygaard H, Pa J, Quinti L, Revta C, Rexach J, Rizzo S, Rynearson K, Schneider L, Slusher B, Tanzi R, Territo P, Yokoyama J. Pharmacoepidemiology evaluation of bumetanide as a potential candidate for drug repurposing for Alzheimer's disease. Alzheimer's & Dementia 2024, 20: 5236-5246. PMID: 39030734, PMCID: PMC11350022, DOI: 10.1002/alz.13872.Peer-Reviewed Original ResearchRisk of ADCross-sectional analysis of electronic health recordsAnalysis of electronic health recordsAD riskAssociated with risk of ADAssociated with AD riskAssociated with decreased prevalenceElectronic health recordsRetrospective cohort study designMedicare claims dataCohort study designCox proportional hazards regressionAssociated with riskCross-sectional analysisProportional hazards regressionPrevalence of ADMultiple sensitivity analysesAlzheimer's diseaseHealth recordsMedicare beneficiariesMedicare dataClaims dataStudy designHazards regressionPatient characteristicsRare genetic variation in fibronectin 1 (FN1) protects against APOEε4 in Alzheimer’s disease
Bhattarai P, Gunasekaran T, Belloy M, Reyes-Dumeyer D, Jülich D, Tayran H, Yilmaz E, Flaherty D, Turgutalp B, Sukumar G, Alba C, McGrath E, Hupalo D, Bacikova D, Le Guen Y, Lantigua R, Medrano M, Rivera D, Recio P, Nuriel T, Ertekin-Taner N, Teich A, Dickson D, Holley S, Greicius M, Dalgard C, Zody M, Mayeux R, Kizil C, Vardarajan B. Rare genetic variation in fibronectin 1 (FN1) protects against APOEε4 in Alzheimer’s disease. Acta Neuropathologica 2024, 147: 70. PMID: 38598053, PMCID: PMC11006751, DOI: 10.1007/s00401-024-02721-1.Peer-Reviewed Original ResearchConceptsLoss-of-functionWhole-genome sequencingFibronectin 1Genetic variationAlzheimer's diseaseAD riskRare Coding VariantsLoss-of-function variantsRare genetic variationGene Ontology termsFamily based studyIn vivo functional studiesAD-related pathologyAlpha 2 chainOntology termsPresence of cellular mechanismsProtective variantsECM proteinsAD pathologyPathway analysisFunctional studiesUnaffected carriersZebrafish modelAPOEe4 alleleProtein levelsNative-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology
Kumar P, Goettemoeller A, Espinosa-Garcia C, Tobin B, Tfaily A, Nelson R, Natu A, Dammer E, Santiago J, Malepati S, Cheng L, Xiao H, Duong D, Seyfried N, Wood L, Rowan M, Rangaraju S. Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology. Nature Communications 2024, 15: 2823. PMID: 38561349, PMCID: PMC10985119, DOI: 10.1038/s41467-024-47028-7.Peer-Reviewed Original ResearchConceptsBiotinylation of proteinsAlzheimer's diseasePre-synaptic defectsDecreased mTOR signalingAD pathogenesisAD riskCytoskeletal disruptionProteomic alterationsTranslational activityMolecular insightsMTOR signalingProteomic findingsProteomicsProteomic signatureMolecular signaturesProteinOver-representedProgressive neuropathologyAlzheimer pathologyMouse modelPV-INsParvalbumin interneuronsMitochondriaAssociated with cognitive declineFast-spiking parvalbumin interneuronsLeveraging generative AI to prioritize drug repurposing candidates for Alzheimer’s disease with real-world clinical validation
Yan C, Grabowska M, Dickson A, Li B, Wen Z, Roden D, Michael Stein C, Embí P, Peterson J, Feng Q, Malin B, Wei W. Leveraging generative AI to prioritize drug repurposing candidates for Alzheimer’s disease with real-world clinical validation. Npj Digital Medicine 2024, 7: 46. PMID: 38409350, PMCID: PMC10897392, DOI: 10.1038/s41746-024-01038-3.Peer-Reviewed Original ResearchGenerative artificial intelligenceDrug repurposing candidatesAlzheimer's diseaseRepurposing candidatesSearch spaceGenerative AIArtificial intelligenceChatGPTAD riskClinical datasetsAssociated with lower AD riskLower AD riskDrug repurposingDrug developmentAlzheimerTreatment of diseasesTechnologyDatasetIntelligence
2023
A brain‐wide risk score of Alzheimer’s disease based on multimodal neuroimaging predicts cognition in large N>37000 population data
Zendehrouh E, Sendi M, Calhoun V. A brain‐wide risk score of Alzheimer’s disease based on multimodal neuroimaging predicts cognition in large N>37000 population data. Alzheimer's & Dementia 2023, 19 DOI: 10.1002/alz.077591.Peer-Reviewed Original ResearchMild cognitive impairmentAD riskGenetic risk of ADCognitive scoresRisk of ADFunctional network connectivityUK BiobankAlzheimer's diseaseGenetic riskRisk scoreBackground Alzheimer’s diseaseFI scoreFluid intelligenceCognitive impairmentPopulation dataEvaluate individualsGray matterScoresRiskReaction timeBiotypesTowards a multimodal neuroimaging-based risk score for Alzheimer’s disease by combining clinical and large N>37000 population data
Zendehrouh E, Sendi M, Calhoun V. Towards a multimodal neuroimaging-based risk score for Alzheimer’s disease by combining clinical and large N>37000 population data. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-4. PMID: 38083709, DOI: 10.1109/embc40787.2023.10340414.Peer-Reviewed Original Research
2022
PCBrainAge: A Brain‐Specific AD‐Associated DNA Methylation Clock
Thrush K, Markov Y, Higgins‐Chen A, Morgan L. PCBrainAge: A Brain‐Specific AD‐Associated DNA Methylation Clock. Alzheimer's & Dementia 2022, 18 DOI: 10.1002/alz.069230.Peer-Reviewed Original ResearchΕ4 carrier statusAlzheimer's diseasePathogenesis of ADCarrier statusAPOE ε4 carrier statusAD diagnostic criteriaNeuropathological changesNeuropathological criteriaAD developmentBlood measuresDiagnostic criteriaAD riskBrain samplesBrain tissueClinical diagnosisNovel predictorCortical measuresDiseaseMolecular changesRecent evidenceSignificant differencesBlood tissueBloodDNA methylation agingDNA methylation clockAging the brain: multi-region methylation principal component based clock in the context of Alzheimer’s disease
Thrush KL, Bennett DA, Gaiteri C, Horvath S, Dyck CHV, Higgins-Chen AT, Levine ME. Aging the brain: multi-region methylation principal component based clock in the context of Alzheimer’s disease. Aging 2022, 14: 5641-5668. PMID: 35907208, PMCID: PMC9365556, DOI: 10.18632/aging.204196.Peer-Reviewed Original ResearchConceptsDisease risk increasesBrain agingAD brain tissueΕ4 carrier statusClinical AD dementiaMultiple brain regionsEpigenetic alterationsReligious Orders StudyAD dementiaTest-retest reliabilityCortical samplesAD riskEpigenetic age accelerationSubcortical regionsPathologic ADAlzheimer's diseaseBrain regionsBrain tissueEpigenetic clocksCarrier statusStrong associationRush MemoryAge accelerationRisk increaseAging ProjectAn IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer’s disease
Jiang Y, Zhou X, Wong H, Ouyang L, Ip F, Chau V, Lau S, Wu W, Wong D, Seo H, Fu W, Lai N, Chen Y, Chen Y, Tong E, Mok V, Kwok T, Mok K, Shoai M, Lehallier B, Losada P, O’Brien E, Porter T, Laws S, Hardy J, Wyss-Coray T, Masters C, Fu A, Ip N. An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer’s disease. Nature Aging 2022, 2: 616-634. PMID: 37117777, PMCID: PMC10154240, DOI: 10.1038/s43587-022-00241-9.Peer-Reviewed Original ResearchConceptsAssociated with Alzheimer's diseaseGenetic variantsGenome-wide association analysisDisease-causing roleCRISPR-Cas9 genome editingEuropean-descent populationsAlzheimer's diseaseMouse transcriptomeDisease-causing factorsGenetic variationAmyloid-betaEnhancer elementsAssociation analysisDownregulated genesAD riskGenome editingMendelian randomization analysisLower AD riskDecoy receptorProtein levelsAPOE-e4Female individualsProteinVariantsModulation of microglial activation
2021
Spreading of Alzheimer tau seeds is enhanced by aging and template matching with limited impact of amyloid-β
Nies SH, Takahashi H, Herber CS, Huttner A, Chase A, Strittmatter SM. Spreading of Alzheimer tau seeds is enhanced by aging and template matching with limited impact of amyloid-β. Journal Of Biological Chemistry 2021, 297: 101159. PMID: 34480901, PMCID: PMC8477193, DOI: 10.1016/j.jbc.2021.101159.Peer-Reviewed Original ResearchConceptsTau seedsAlzheimer's diseaseAD model miceWT mouse brainPathological tauSynaptic lossTau accumulationWT miceMouse tauTau pathologyTau burdenModel miceTau inclusionsPharmacological interventionsAD riskCognitive declineMouse brainTau aggregatesPyk2 kinaseKnowledge of factorsKinase inhibitorsMiceFyn kinase inhibitorAβMouse agingHbA1c and brain health across the entire glycaemic spectrum
Garfield V, Farmaki A, Eastwood SV, Mathur R, Rentsch CT, Bhaskaran K, Smeeth L, Chaturvedi N. HbA1c and brain health across the entire glycaemic spectrum. Diabetes Obesity And Metabolism 2021, 23: 1140-1149. PMID: 33464682, PMCID: PMC8261644, DOI: 10.1111/dom.14321.Peer-Reviewed Original ResearchConceptsVascular dementiaHippocampal volumeGlycaemic spectrumBrain healthWMH volumeAlzheimer's dementiaAD riskCognitive declineWhite matter hyperintensity volumeIncident vascular dementiaLower WMH volumeHigher WMH volumeGreater hippocampal volumeBrain health outcomesLower hippocampal volumeUK Biobank cohortGlycaemic categoriesKnown diabetesAntihypertensive medicationsHbA1c levelsCause dementiaCertain cardiovascular drugsExcess riskNormoglycaemic individualsHyperintensity volume
2018
Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer’s disease pathogenesis
Zhou X, Chen Y, Mok K, Zhao Q, Chen K, Chen Y, Hardy J, Li Y, Fu A, Guo Q, Ip N, Saykin A, Toga A, Borowski B, Ward C, DeCarli C, Mathis C, Jack C, Harvey D, Holtzman D, Jones D, Gessert D, Lilly E, Reiman E, Franklin E, Hefti F, Sorensen G, Jimenez G, Fillit H, Gunter J, Salazar J, Hsiao J, Morris J, Trojanowki J, Neu K, Kantarci K, Faber K, Harless K, Chen K, Nho K, Beckett L, Thal L, Thal L, Shaw L, Kuller L, Shen L, Hergesheimer L, Taylor-Reinwald L, Mesulam M, Korecka M, Raichle M, Carrillo M, Albert M, Senjem M, Bernstein M, Donohue M, Weiner M, Figurski M, Buckholtz N, Fox N, Cairns N, Schuff N, Foster N, Aisen P, Thompson P, Davies P, Snyder P, Snyder P, Vemuri P, Frank R, Koeppe R, Green R, Petersen R, Walter S, Paul S, Potkin S, Kim S, Foroud T, Montine T, Lee V, Jagust W, Potter W, Cabrera Y, Khachaturian Z, Fleisher A, Pierce A, Mintz A, Lerner A, Norbash A, Levey A, Rosen A, Smith A, Ulysse A, Budson A, Kertesz A, Oliver A, Hake A, Burke A, Sarrael A, Porsteinsson A, Lamb A, Lee A, Raj B, Lane B, Yanez B, Ances B, Mudge B, Lind B, Stefanovic B, Goldstein B, Bonakdarpour B, Matthews B, Ott B, Reynolds B, Miller B, Spann B, Sadowsky C, Bernick C, Smith C, Onyike C, Heyn C, Hosein C, Leach C, Belden C, van Dyck C, Clark C, Wu C, Albers C, Brand C, Bodge C, Tatsuoka C, Carlsson C, Mathews D, D’Agostino D, Silverman D, Marson D, Wolk D, Bachman D, Clark D, Geldmacher D, Hart D, Knopman D, Perry D, Winkfield D, Miller D, Kerwin D, Drost D, Simpson D, Munic D, Scharre D, Bartha R, Celmins D, Zimmerman E, Teng E, Coleman E, Zamrini E, Mitsis E, Finger E, Oates E, Sosa E, Woo E, Rogalski E, Fletcher E, Parfitt F, Thai G, Marshall G, Conrad G, Tremont G, Bartzokis G, Hsiung G, Chiang G, Pearlson G, Jicha G, Vanderswag H, Grossman H, Capote H, Bergman H, Chertkow H, Feldman H, Rosen H, Koleva H, Shim H, Rachinsky I, Mintzer J, Ziolkowski J, Brewer J, Lah J, Singleton-Garvin J, Cellar J, Brosch J, Tinklenberg J, Karlawish J, Villanueva-Meyer J, Kaye J, Burns J, Petrella J, Yesavage J, Allard J, Lord J, Hetelle J, Brockington J, Morris J, Olichney J, Rogers J, Quinn J, Kass J, Taylor J, Heidebrink J, Anderson K, Blank K, Smith K, Bell K, Johnson K, Tingus K, DeMarco K, Sink K, Johnson K, Makino K, Spicer K, Nam K, Martin K, Poki-Walker K, Johnson K, Fargher K, Lipowski K, Womack K, Flashman L, Honig L, Apostolova L, Teodoro L, Silbert L, Ravdin L, Schneider L, Daiello L, Ismail M, Seltzer M, Mesulam M, Carroll M, Kataki M, Greig-Custo M, Love M, Mintun M, Farlow M, Sadowski M, Creech M, Hynes M, Quiceno M, Oakley M, Becerra M, Witbracht M, Keltz M, Lamar M, Yang M, Borrie M, Lin M, Assaly M, Rainka M, Dang M, Sheikh M, Gaikwad M, Chowdhury M, Trncic N, Johnson N, Kowalksi N, Pacini N, Kowall N, Graff-Radford N, Relkin N, Oyonumo N, Pomara N, James O, Ogunlana O, Lopez O, Carmichael O, Doraiswamy P, Fatica P, Johnson P, Samuels P, Malloy P, Ogrocki P, Maillard P, Hardy P, Tariot P, Lu P, Varma P, Doody R, Carter R, Shah R, Griffith R, Yeh R, Duara R, Tarawneh R, Turner R, Hernando R, Sperling R, Carson R, El Khouli R, Santulli R, Killiany R, Rodriguez R, Swerdlow R, Borges-Neto S, Black S, Weintraub S, Asthana S, Vaishnavi S, Dolen S, Mason S, Kremen S, Herring S, Sirrel S, Kittur S, Pawluczyk S, Schneider S, Kielb S, Reeder S, Correia S, Pasternack S, Pasternak S, Salloway S, Johnson S, Chao S, Arnold S, Schultz S, Rountree S, Lee T, Wong T, Villena T, Obisesan T, Pavlik V, Bates V, Sossi V, Shibley V, Brooks W, Pavlosky W, Stern Y, Simon A, Dongre A, Dean B, Navia B, Spellman D, Lee D, Shera D, Siemers E, Pickering E, Swenson F, Immerman F, Nomikos G, Soares H, Wan H, Seeburger J, Waring J, Trojanowski J, Siuciak J, Duffin K, Shaw L, Wang L, Thambisetty M, Walton M, Savage M, Ferm M, Kuhn M, Buckholtz N, Zagouras P, Cole P, Hendrickson R, Xie S, Allauzen S, Koroshetz W, Potter W. Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer’s disease pathogenesis. Proceedings Of The National Academy Of Sciences Of The United States Of America 2018, 115: 1697-1706. PMID: 29432188, PMCID: PMC5828602, DOI: 10.1073/pnas.1715554115.Peer-Reviewed Original ResearchConceptsAlzheimer's diseaseChinese populationAD subjectsDisease pathogenesisImmune systemPlasma biomarker levelsEarly disease onsetMinor allele carriersAlzheimer's disease (AD) pathogenesisGenetic risk factorsImmune-related pathwaysCommon variantsGenotype-phenotype analysisDisease onsetRisk factorsBiomarker levelsLeading causeOnset ageAllele carriersAD riskAD cohortPossible risk effectsFunctional effectsExpression levelsRegulatory effects
2017
Microglia-Mediated Neuroprotection, TREM2, and Alzheimer’s Disease: Evidence From Optical Imaging
Condello C, Yuan P, Grutzendler J. Microglia-Mediated Neuroprotection, TREM2, and Alzheimer’s Disease: Evidence From Optical Imaging. Biological Psychiatry 2017, 83: 377-387. PMID: 29169609, PMCID: PMC5767550, DOI: 10.1016/j.biopsych.2017.10.007.Peer-Reviewed Original ResearchConceptsAlzheimer's diseasePlaque compactionAmyloid depositsInvolvement of microgliaPlaque-associated microgliaLate-onset Alzheimer's diseaseMyeloid cells 2Onset Alzheimer's diseaseMicroglia receptorMicroglia polarizationAD neuropathologyAxonal pathologyNeuroprotective functionDisease progressionOptical imaging studiesCurrent evidenceAD riskMicrogliaTherapeutic targetingAdjacent axonsImaging studiesCells 2DiseasePrecise mechanismRecent genetic studies
2014
Low-copper diet as a preventive strategy for Alzheimer's disease
Squitti R, Siotto M, Polimanti R. Low-copper diet as a preventive strategy for Alzheimer's disease. Neurobiology Of Aging 2014, 35: s40-s50. PMID: 24913894, DOI: 10.1016/j.neurobiolaging.2014.02.031.Peer-Reviewed Original ResearchConceptsLow copper dietAlzheimer's diseasePreventive strategiesRisk of ADSporadic Alzheimer's diseaseCopper metabolismAdverse sequelaeDietary intakePathogenetic mechanismsGeneral populationAD riskPathogenic mechanismsDiseaseDietCopper deficiencyRecent studiesRiskMetabolismPhenotypeSequelaeDerangementIntake
2013
Intronic rs2147363 Variant in ATP7B Transcription Factor-Binding Site Associated with Alzheimer's Disease
Bucossi S, Polimanti R, Ventriglia M, Mariani S, Siotto M, Ursini F, Trotta L, Scrascia F, Callea A, Vernieri F, Squitti R. Intronic rs2147363 Variant in ATP7B Transcription Factor-Binding Site Associated with Alzheimer's Disease. Journal Of Alzheimer’s Disease 2013, 37: 453-459. PMID: 23948886, DOI: 10.3233/jad-130431.Peer-Reviewed Original ResearchConceptsLinkage disequilibriumDisease-causing variantsCis-regulatory elementsNon-coding regionsObserved genetic associationIntronic single nucleotide polymorphismSingle nucleotide polymorphismsTranscription factorsGenetic variationATP7B variantsSilico analysisRegulatory functionsLD analysisNucleotide polymorphismsGenetic associationSites AssociatedAlzheimer's diseaseAD riskKey roleVariantsATP7B gene
2012
GSTM1 null genotype as risk factor for late-onset Alzheimer's disease in Italian patients
Piacentini S, Polimanti R, Squitti R, Ventriglia M, Cassetta E, Vernieri F, Rossini PM, Manfellotto D, Fuciarelli M. GSTM1 null genotype as risk factor for late-onset Alzheimer's disease in Italian patients. Journal Of The Neurological Sciences 2012, 317: 137-140. PMID: 22381228, DOI: 10.1016/j.jns.2012.01.026.Peer-Reviewed Original ResearchConceptsGSTM1 null genotypeAlzheimer's diseaseNull genotypeRisk factorsItalian patientsCause of ADLate-onset Alzheimer's diseaseLogistic regression analysisGlutathione S-transferaseCase-control populationAD patientsAD riskGSTM1 geneGSTT1 genesGenotype distributionDisease riskNeurodegenerative disordersDiseasePatientsOxidative stressEndogenous metabolitesCommon formRegression analysisPositive associationGSTM1
2011
GSTO1*E155del polymorphism associated with increased risk for late-onset Alzheimer's disease: Association hypothesis for an uncommon genetic variant
Piacentini S, Polimanti R, Squitti R, Mariani S, Migliore S, Vernieri F, Rossini PM, Manfellotto D, Fuciarelli M. GSTO1*E155del polymorphism associated with increased risk for late-onset Alzheimer's disease: Association hypothesis for an uncommon genetic variant. Neuroscience Letters 2011, 506: 203-207. PMID: 22100662, DOI: 10.1016/j.neulet.2011.11.005.Peer-Reviewed Original ResearchConceptsUncommon genetic variantsGSTO1-1Genetic variantsClass genesGlutathione S-transferaseGenetic variationMultifunctional enzymeCellular detoxificationAlzheimer's diseaseGSTO2 genesGenetic linkageAllele-specific PCRS-transferaseChromosome 10qAD riskGene polymorphismsInterleukin-1β activationSpecific PCRPathophysiology of ADGenesLate-onset Alzheimer's diseasePolymorphismAD risk factorsOxidative stressPCR-RFLPA CRHR1 haplotype moderates the effect of adverse childhood experiences on lifetime risk of major depressive episode in African‐American women
Kranzler HR, Feinn R, Nelson EC, Covault J, Anton RF, Farrer L, Gelernter J. A CRHR1 haplotype moderates the effect of adverse childhood experiences on lifetime risk of major depressive episode in African‐American women. American Journal Of Medical Genetics Part B Neuropsychiatric Genetics 2011, 156: 960-968. PMID: 21998007, PMCID: PMC3227028, DOI: 10.1002/ajmg.b.31243.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAlcohol DrinkingBlack or African AmericanChildChild AbuseDepressionDepressive Disorder, MajorFemaleGene FrequencyGenetic Predisposition to DiseaseHaplotypesHumansMiddle AgedPolymorphism, Single NucleotideReceptors, Corticotropin-Releasing HormoneStress, PsychologicalSubstance-Related DisordersConceptsMajor depressive episodeAdverse childhood experiencesRisk of depressionTAT haplotypeAlcohol dependenceDepressive episodeLifetime riskAA womenCorticotropin-releasing hormone type 1 receptorOdds of MDERisk of MDELifetime substance use disorderType 1 receptorSubstance use disordersAfrican AmericansAfrican American womenChildhood experiencesDepression riskThree-SNP haplotypeAD riskUse disordersAdult depressionAlcohol consumptionCRHR1 haplotypeCRHR1
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply