2025
Identification of risk variants and cross-disorder pleiotropy through multi-ancestry genome-wide analysis of alcohol use disorder
Icick R, Shadrin A, Holen B, Karadag N, Parker N, O’Connell K, Frei O, Bahrami S, Høegh M, Lagerberg T, Cheng W, Seibert T, Djurovic S, Dale A, Zhou H, Edenberg H, Gelernter J, Smeland O, Hindley G, Andreassen O. Identification of risk variants and cross-disorder pleiotropy through multi-ancestry genome-wide analysis of alcohol use disorder. Nature Mental Health 2025, 3: 253-265. DOI: 10.1038/s44220-024-00353-8.Peer-Reviewed Original ResearchAlcohol use disorderGenome-wide association studiesUse disorderAssociation studiesMulti-ancestry genome-wide association studyEtiology of alcohol use disordersIdentification of risk variantsAlcohol use disorder phenotypesGenome-wide significant lociAlcohol use disorder riskMapped to genesComplications of alcohol usePotential drug targetsAlcohol phenotypesCross-disorderPolygenic overlapPositive genetic correlationSignificant lociGenetic architectureGenetic liabilityGenetic lociBrain regionsRisk variantsGenetic studiesImmune-related genes
2024
Deletion of miR‐33, a regulator of the ABCA1–APOE pathway, ameliorates neuropathological phenotypes in APP/PS1 mice
Tate M, Wijeratne H, Kim B, Philtjens S, You Y, Lee D, Gutierrez D, Sharify D, Wells M, Perez‐Cardelo M, Doud E, Fernandez‐Hernando C, Lasagna‐Reeves C, Mosley A, Kim J. Deletion of miR‐33, a regulator of the ABCA1–APOE pathway, ameliorates neuropathological phenotypes in APP/PS1 mice. Alzheimer's & Dementia 2024, 20: 7805-7818. PMID: 39345217, PMCID: PMC11567857, DOI: 10.1002/alz.14243.Peer-Reviewed Original ResearchAmyloid-betaAlzheimer's diseaseMicroglial migrationAmyloid mouse modelMiR-33Multi-omics studiesABCA1 levelsPotential drug targetsIncreased ABCA1 protein levelsMicroRNA-33ApoE lipidationProteomic changesRNA sequencingMulti-omicsNeuropathological phenotypeAmyloid pathologyInhibition of miR-33APP/PS1 micePhagocytosis in vitroRare variantsApolipoprotein EDrug targetsABCA1 protein levelsAmyloidPlaque depositionCirculating Proteins and IgA Nephropathy
Tang C, Chen P, Xu L, Lv J, Shi S, Zhou X, Liu L, Zhang H. Circulating Proteins and IgA Nephropathy. Journal Of The American Society Of Nephrology 2024, 35: 1045-1057. PMID: 38687828, PMCID: PMC11377805, DOI: 10.1681/asn.0000000000000379.Peer-Reviewed Original ResearchProtein-protein interaction networkProtein-disease pairsColocalization analysisInteraction networkEast Asian ancestryMendelian randomizationPotential drug targetsDrug repurposing opportunitiesVariant annotationAncestry populationsIdentified proteinsNetwork Mendelian randomizationMendelian randomization studiesAsian ancestryDrug targetsProteinAncestryEast AsiansTherapeutic targetColocalizationCirculating proteinsCausal effectsMedicationTargetAnnotation
2023
Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification
de Vries P, Conomos M, Singh K, Nicholson C, Jain D, Hasbani N, Jiang W, Lee S, Lino Cardenas C, Lutz S, Wong D, Guo X, Yao J, Young E, Tcheandjieu C, Hilliard A, Bis J, Bielak L, Brown M, Musharoff S, Clarke S, Terry J, Palmer N, Yanek L, Xu H, Heard-Costa N, Wessel J, Selvaraj M, Li R, Sun X, Turner A, Stilp A, Khan A, Newman A, Rasheed A, Freedman B, Kral B, McHugh C, Hodonsky C, Saleheen D, Herrington D, Jacobs D, Nickerson D, Boerwinkle E, Wang F, Heiss G, Jun G, Kinney G, Sigurslid H, Doddapaneni H, Hall I, Bensenor I, Broome J, Crapo J, Wilson J, Smith J, Blangero J, Vargas J, Mosquera J, Smith J, Viaud-Martinez K, Ryan K, Young K, Taylor K, Lange L, Emery L, Bittencourt M, Budoff M, Montasser M, Yu M, Mahaney M, Mahamdeh M, Fornage M, Franceschini N, Lotufo P, Natarajan P, Wong Q, Mathias R, Gibbs R, Do R, Mehran R, Tracy R, Kim R, Nelson S, Damrauer S, Kardia S, Rich S, Fuster V, Napolioni V, Zhao W, Tian W, Yin X, Min Y, Manning A, Peloso G, Kelly T, O’Donnell C, Morrison A, Curran J, Zapol W, Bowden D, Becker L, Correa A, Mitchell B, Psaty B, Carr J, Pereira A, Assimes T, Stitziel N, Hokanson J, Laurie C, Rotter J, Vasan R, Post W, Peyser P, Miller C, Malhotra R. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification. Nature Cardiovascular Research 2023, 2: 1159-1172. PMID: 38817323, PMCID: PMC11138106, DOI: 10.1038/s44161-023-00375-y.Peer-Reviewed Original ResearchGenome-wide association studiesMultiple ancestral groupsWhole-genome sequencingPotential drug targetsNovel lociAncestral groupsLociCoronary artery calcificationVascular smooth muscle cellsDrug targetsFunctional assaysPhenotypic switchingCoronary artery diseaseVascular smooth muscle cell phenotypic switchingHuman vascular smooth muscle cellsARSEG alleleArtery calcificationVascular calcificationPredictor of coronary artery diseaseReplicate analysesRegulation of vascular calcificationSmooth muscle cellsCalcifiersSequence9. THE GENETIC ARCHITECTURE OF PAIN INTENSITY IN THE MILLION VETERAN PROGRAM
Toikumo S, Vickers-Smith R, Jinwala Z, Xu H, Saini D, Hartwell E, Pavicic M, Sullivan K, Jacobson D, Cheatle M, Zhou H, Waxman S, Justice A, Kember R, Kranzler H. 9. THE GENETIC ARCHITECTURE OF PAIN INTENSITY IN THE MILLION VETERAN PROGRAM. European Neuropsychopharmacology 2023, 75: s60-s61. DOI: 10.1016/j.euroneuro.2023.08.120.Peer-Reviewed Original ResearchIndependent lociGenetic architectureMillion Veteran ProgramGenome-wide association testingIndependent genetic lociLinkage disequilibrium score regressionDrug-gene interaction databaseDisequilibrium score regressionNovel genetic variantsPotential drug targetsComplex traitsGWAS resultsCausal genesDruggable genomeDrug repurposing analysisGenetic lociDruggable genesInteraction databasesDrug targetsGenetic correlationsMolecular contributorsAssociation testingLociPsychiatric traitsScore regressionThe KDM6A-KMT2D-p300 axis regulates susceptibility to diverse coronaviruses by mediating viral receptor expression
Wei J, Alfajaro M, Cai W, Graziano V, Strine M, Filler R, Biering S, Sarnik S, Patel S, Menasche B, Compton S, Konermann S, Hsu P, Orchard R, Yan Q, Wilen C. The KDM6A-KMT2D-p300 axis regulates susceptibility to diverse coronaviruses by mediating viral receptor expression. PLOS Pathogens 2023, 19: e1011351. PMID: 37410700, PMCID: PMC10325096, DOI: 10.1371/journal.ppat.1011351.Peer-Reviewed Original ResearchConceptsMouse hepatitis virusReceptor expressionTherapeutic targetMERS-CoVMajor SARS-CoV-2 variantsPrimary human airwaySARS-CoV-2 variantsNovel therapeutic targetViral receptor expressionSARS-CoV-2Histone methyltransferase KMT2DIntestinal epithelial cellsCoronavirus SusceptibilityDiverse coronavirusesHistone demethylase KDM6ADPP4 expressionCoronavirus receptorsHost determinantsHepatitis virusHuman airwaysSARS-CoVSmall molecule inhibitionViral entryPotential drug targetsViral receptorsCD31 as a probable responding and gate-keeping protein of the blood-brain barrier and the risk of Alzheimer’s disease
Zhang Z, Gan Q, Han J, Tao Q, Qiu W, Madri J. CD31 as a probable responding and gate-keeping protein of the blood-brain barrier and the risk of Alzheimer’s disease. Cerebrovascular And Brain Metabolism Reviews 2023, 43: 1027-1041. PMID: 37051650, PMCID: PMC10291450, DOI: 10.1177/0271678x231170041.Peer-Reviewed Original ResearchConceptsPlatelet endothelial cell adhesion moleculeImmune cellsDisease riskBlood-brain barrier permeabilityMajor genetic risk factorBlood-brain barrierNeuronal cell injuryEndothelial cell adhesion moleculesAlzheimer's disease riskGenetic risk factorsPeripheral inflammationBrain axisAPOE4 carriersAD pathogenesisRisk factorsBarrier permeabilityAD developmentCell adhesion moleculeCell injuryImmune systemAlzheimer's diseaseCD31Transendothelial migrationPotential drug targetsAdhesion molecules
2022
A novel 7 RNA-based signature for prediction of prognosis and therapeutic responses of wild-type BRAF cutaneous melanoma
Sun R, Liu Y, Lei C, Tang Z, Lu L. A novel 7 RNA-based signature for prediction of prognosis and therapeutic responses of wild-type BRAF cutaneous melanoma. Biological Procedures Online 2022, 24: 7. PMID: 35751033, PMCID: PMC9233353, DOI: 10.1186/s12575-022-00170-2.Peer-Reviewed Original ResearchCutaneous melanomaLack of therapeutic optionsPrediction of prognosisHigh-risk groupBackgroundThe prognosisMalignancy of cancerTherapeutic optionsTherapeutic responseClinical factorsPrognosisCellular proliferationClinical practicePatientsPI3K/AKT/mTOR pathwayTCGA databaseMelanomaUp-regulatedFunctional analysisPotential drug targetsMolecular mechanismsBioinformatic evidenceDrug targetsRNA splicing
2021
Noncoding RNAs: biology and applications—a Keystone Symposia report
Cable J, Heard E, Hirose T, Prasanth KV, Chen L, Henninger JE, Quinodoz SA, Spector DL, Diermeier SD, Porman AM, Kumar D, Feinberg MW, Shen X, Unfried JP, Johnson R, Chen C, Wilusz JE, Lempradl A, McGeary SE, Wahba L, Pyle AM, Hargrove AE, Simon MD, Marcia M, Przanowska RK, Chang HY, Jaffrey SR, Contreras LM, Chen Q, Shi J, Mendell JT, He L, Song E, Rinn JL, Lalwani MK, Kalem MC, Chuong EB, Maquat LE, Liu X. Noncoding RNAs: biology and applications—a Keystone Symposia report. Annals Of The New York Academy Of Sciences 2021, 1506: 118-141. PMID: 34791665, PMCID: PMC9808899, DOI: 10.1111/nyas.14713.Peer-Reviewed Original ResearchConceptsPIWI-interacting RNAsKeystone Symposia reportPotential drug targetsRNA biologyHuman transcriptomeEpigenetic modificationsKeystone eSymposiumNoncoding RNAsCell signalingBasic biologyDrug targetsRNABiologyDisease mechanismsNucleotidesSpeciesTranscriptomeImportant roleRNAsTranscriptionSymposium reportSignalingTranslationRoleTargetGlobal proteomic analysis of extracellular matrix in mouse and human brain highlights relevance to cerebrovascular disease
Pokhilko A, Brezzo G, Handunnetthi L, Heilig R, Lennon R, Smith C, Allan S, Granata A, Sinha S, Wang T, Markus H, Naba A, Fischer R, Van Agtmael T, Horsburgh K, Cader M. Global proteomic analysis of extracellular matrix in mouse and human brain highlights relevance to cerebrovascular disease. Cerebrovascular And Brain Metabolism Reviews 2021, 41: 2423-2438. PMID: 33730931, PMCID: PMC8392779, DOI: 10.1177/0271678x211004307.Peer-Reviewed Original Research
2020
The Global and Local Distribution of RNA Structure throughout the SARS-CoV-2 Genome
de Cesaris Araujo Tavares R, Mahadeshwar G, Wan H, Huston NC, Pyle AM. The Global and Local Distribution of RNA Structure throughout the SARS-CoV-2 Genome. Journal Of Virology 2020, 95: 10.1128/jvi.02190-20. PMID: 33268519, PMCID: PMC8092842, DOI: 10.1128/jvi.02190-20.Peer-Reviewed Original ResearchSARS-CoV-2 genomeRNA structureRNA genomeRNA virusesViral genomeIndividual RNA structuresDrug targetsSARS-CoV-2 RNA genomeSilico pipelineMost RNA virusesRNA structural featuresComplex viral genomesRNA drug targetsStructured viral RNAsPotential drug targetsViral RNAViral infection cycleBase pair contentRNA biologyStructural ORFsLong genomeCellular mixturesGenomeRNA transcriptsInfection cycleNeuronal Calcium Sensor 1 (NCS1) as a Potential Drug Target for Treatment of Wolfram Syndrome
Fischer T, Nguyen L, Ehrlich B. Neuronal Calcium Sensor 1 (NCS1) as a Potential Drug Target for Treatment of Wolfram Syndrome. The FASEB Journal 2020, 34: 1-1. DOI: 10.1096/fasebj.2020.34.s1.00556.Peer-Reviewed Original ResearchNeuronal calcium sensor-1Wolfram syndromeHigh glucose treatmentDiabetes mellitusFunction of WFS1Lack of therapyGlucose treatmentCalcium-dependent protease calpainMajority of casesRat insulinoma cellsBaseline calciumCalcium binding proteinOptical atrophyKO cellsGlucose toxicityCalcium responseCalcium homeostasisPathophysiological consequencesCTRL cellsPhospho-AktDiscovery of drugsPotential drug targetsProtease calpainGenetic causeProtein expression
2019
A small-molecule inhibitor of the DNA recombinase Rad51 from Plasmodium falciparum synergizes with the antimalarial drugs artemisinin and chloroquine
Vydyam P, Dutta D, Sutram N, Bhattacharyya S, Bhattacharyya M. A small-molecule inhibitor of the DNA recombinase Rad51 from Plasmodium falciparum synergizes with the antimalarial drugs artemisinin and chloroquine. Journal Of Biological Chemistry 2019, 294: 8171-8183. PMID: 30936202, PMCID: PMC6527153, DOI: 10.1074/jbc.ra118.005009.Peer-Reviewed Original ResearchConceptsMultidrug-resistant parasitesAnti-parasitic activitySmall molecule inhibitorsMalaria drugsAntimalarial drugsChloroquinePotential drug targetsAntigenic diversityAntimalarial activityCell linesParasitic DNADNA double-strand breaksSpecific inhibitorDrug targetsDrugsInhibitorsParasitesPfRad51DNA-damaging agentsHigh affinityScreening approachFindingsHomologous recombinationMammalian cell linesActivity
2018
Evolving Genomics of Pulmonary Fibrosis
Ibarra G, Herazo-Maya J, Kaminski N. Evolving Genomics of Pulmonary Fibrosis. Respiratory Medicine 2018, 207-239. DOI: 10.1007/978-3-319-99975-3_9.Peer-Reviewed Original ResearchTranscript profiling approachesProfiling approachPotential drug targetsNonspecific interstitial pneumoniaIdiopathic pulmonary fibrosisFibrotic lung diseaseGenomic profiling studiesLung diseaseDrug targetsPulmonary fibrosisHypersensitivity pneumonitisKey moleculesProfiling studiesCells of patientsUnbiased viewDifferent interstitial lung diseasesInterstitial lung diseaseInterstitial pneumoniaLung fibrosisAnimal modelsTranscriptomeCellsGenomicsFibrosisDiseaseA Role for the Non-Receptor Tyrosine Kinase Abl2/Arg in Experimental Neuroinflammation
Jacobsen FA, Scherer AN, Mouritsen J, Bragadóttir H, Thomas Bäckström B, Sardar S, Holmberg D, Koleske AJ, Andersson Å. A Role for the Non-Receptor Tyrosine Kinase Abl2/Arg in Experimental Neuroinflammation. Journal Of Neuroimmune Pharmacology 2018, 13: 265-276. PMID: 29550892, PMCID: PMC5928183, DOI: 10.1007/s11481-018-9783-8.Peer-Reviewed Original ResearchConceptsMultiple sclerosisExperimental autoimmune encephalomyelitis (EAE) modelT cell receptorCongenic mouse strainsExperimental neuroinflammationInflammation pathogenesisMyelin antigensEAE developmentExperimental arthritisAutoimmune responseImmune cellsDisease susceptibility factorsCongenic miceLymphocyte activationPharmacological inhibitionAbl kinaseSclerosisSusceptibility factorsMouse strainsDegenerative diseasesPotential drug targetsMouse genetic locusSingle nucleotide polymorphismsDisease etiologyAmino acid changes
2017
Fragile X targeted pharmacotherapy: lessons learned and future directions
Erickson C, Davenport M, Schaefer T, Wink L, Pedapati E, Sweeney J, Fitzpatrick S, Brown W, Budimirovic D, Hagerman R, Hessl D, Kaufmann W, Berry-Kravis E. Fragile X targeted pharmacotherapy: lessons learned and future directions. Journal Of Neurodevelopmental Disorders 2017, 9: 7. PMID: 28616096, PMCID: PMC5467059, DOI: 10.1186/s11689-017-9186-9.Peer-Reviewed Original ResearchClinical trial rationaleCurrent prescribing practicesDrug targetsAppropriate outcome measuresClinical trial designTreatment development effortsFXS animal modelsNumerous potential drug targetsTrial rationaleGABAergic neurotransmissionPrescribing practicesSyndrome pathophysiologyClinical trialsOutcome measuresTrial designAnimal modelsDrug approachSingle gene disordersPotential drug targetsTreatment developmentPharmacotherapyDrugsPathophysiologyTrial executionIdentification of the gene that codes for the σ2 receptor
Alon A, Schmidt H, Wood M, Sahn J, Martin S, Kruse A. Identification of the gene that codes for the σ2 receptor. Proceedings Of The National Academy Of Sciences Of The United States Of America 2017, 114: 7160-7165. PMID: 28559337, PMCID: PMC5502638, DOI: 10.1073/pnas.1705154114.Peer-Reviewed Original ResearchMeSH KeywordsAlzheimer DiseaseAnimalsAspartic AcidCarrier ProteinsCattleCholesterolEndoplasmic ReticulumGene Expression RegulationHumansInsectaIntracellular Signaling Peptides and ProteinsLigandsLiverMCF-7 CellsMembrane GlycoproteinsMembrane ProteinsNiemann-Pick C1 ProteinPC12 CellsProtein BindingRatsReceptors, sigmaRecombinant ProteinsRNA, Small InterferingSchizophreniaConceptsEndoplasmic reticulum-resident transmembrane proteinChemical biology approachPotential drug targetsTransmembrane proteinsMolecular cloningBiology approachLigand recognitionDrug targetsGenesBiological methodsTMEM97Therapeutic targetProteinMedical interestReceptorsAsp56NPC1ClonesS2 receptorsMolecular propertiesNeurological disordersSterolsTarget
2016
Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets
Vinayagam A, Gibson TE, Lee HJ, Yilmazel B, Roesel C, Hu Y, Kwon Y, Sharma A, Liu YY, Perrimon N, Barabási AL. Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets. Proceedings Of The National Academy Of Sciences Of The United States Of America 2016, 113: 4976-4981. PMID: 27091990, PMCID: PMC4983807, DOI: 10.1073/pnas.1603992113.Peer-Reviewed Original ResearchConceptsPPI networkDisease genesProtein-protein interaction networkDrug targetsCellular information processingHuman PPI networkNovel disease genesCopy number alteration dataPotential drug targetsNumber alteration dataDisease-causing mutationsIndispensable proteinsInteraction networksCell deathGenesProteinCell proliferationDifferent cancersHuman virusesPrimary targetAlteration dataDisease statesTargetMutationsNetwork control properties
2015
Bactericidal/Permeability-Increasing Protein Fold–Containing Family Member A1 in Airway Host Protection and Respiratory Disease
Britto CJ, Cohn L. Bactericidal/Permeability-Increasing Protein Fold–Containing Family Member A1 in Airway Host Protection and Respiratory Disease. American Journal Of Respiratory Cell And Molecular Biology 2015, 52: 525-534. PMID: 25265466, PMCID: PMC4491141, DOI: 10.1165/rcmb.2014-0297rt.BooksConceptsPulmonary diseaseHost protectionChronic obstructive pulmonary diseaseObstructive pulmonary diseaseIdiopathic pulmonary fibrosisMember A1Immune cell functionMultiple lung diseasesBactericidal/permeability-increasing proteinRespiratory malignanciesPulmonary pathogenesisPulmonary fibrosisPermeability-increasing proteinRespiratory secretionsLung diseaseUpper airwayRespiratory tractRespiratory diseaseProximal tracheaImmunomodulatory propertiesBPIFA1Cystic fibrosisDiseasePotential drug targetsEnvironmental exposures
2013
Systems biology‐embedded target validation: improving efficacy in drug discovery
Vandamme D, Minke BA, Fitzmaurice W, Kholodenko BN, Kolch W. Systems biology‐embedded target validation: improving efficacy in drug discovery. WIREs Mechanisms Of Disease 2013, 6: 1-11. PMID: 24214316, DOI: 10.1002/wsbm.1253.Peer-Reviewed Original ResearchConceptsSystems biology approachBiology approachDrug discoveryPotential drug targetsOmics technologiesMolecular mechanismsMultidrug treatmentDrug targetsMedical treatmentNovel targetDrug pipelineDrug developmentEfficacyAttrition ratesTreatmentDiscoveryGreater personalizationReductionist modelPatients
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