2024
Leveraging 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
Digital biobanks are underutilized in dermatology and create opportunities to reduce the burden of skin disease
Jumonville G, Hong D, Khan A, DeWan A, Leal S, Weng C, Petukhova L. Digital biobanks are underutilized in dermatology and create opportunities to reduce the burden of skin disease. British Journal Of Dermatology 2023, 190: 566-568. PMID: 37936310, PMCID: PMC10941321, DOI: 10.1093/bjd/ljad439.Peer-Reviewed Original ResearchConceptsBurden of skin diseaseGenetic architectureDiscover genesGenetic dataGene-environment interactionsClinical areasBiobank dataHealth dataMedical careDisease mechanismsGlobal burdenDisease relationshipsMedical interventionsDrug repurposingPharmacogenetic relationshipBiobankSkin diseasesGlobal burden of skin diseaseGenesKnowledge promisesAdverse eventsCareDermatologyHealthDiseaseIdentification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects
Zhong H, Zhu J, Liu S, Ghoneim D, Surendran P, Liu T, Fahle S, Butterworth A, Alam A, Deng H, Yu H, Wu C, Wu L. Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects. Human Molecular Genetics 2023, 32: 3181-3193. PMID: 37622920, PMCID: PMC10630250, DOI: 10.1093/hmg/ddad139.Peer-Reviewed Original ResearchConceptsPCa riskProstate cancerHuge public health burdenEtiology of PCaBlood protein biomarkersConventional epidemiologic studiesProstate cancer riskPublic health burdenConventional observational studiesCancer Genome AtlasPCa patientsHealth burdenProtein biomarker candidatesObservational studyEpidemiologic studiesCancer riskTherapeutic strategiesCancer-related pathwaysSignificant associationBiomarker candidatesGenome AtlasProtein levelsDrug repurposingRiskPositive associationRepurposing Drugs for Alzheimer's Diseases through Link Prediction on Biomedical Literature
Xiao Y, Hou Y, Zhou H, Diallo G, Fiszman M, Wolfson J, Kilicoglu H, Chen Y, Xu H, Mantyh W, Zhang R. Repurposing Drugs for Alzheimer's Diseases through Link Prediction on Biomedical Literature. 2023, 00: 750-752. DOI: 10.1109/ichi57859.2023.00137.Peer-Reviewed Original ResearchAlzheimer's diseaseKnowledge graphKnowledge graph embedding modelsGraph convolutional network modelComputational drug repurposingGraph embedding modelsTest setConvolutional network modelBiomedical knowledge graphComprehensive knowledge graphDietary supplementsR-GCNEmbedding modelDrug repurposingLink predictionPrediction taskSemantic triplesNetwork modelAlzheimerBiomedical literatureNovel drugsRepurposed drugsGraphMulti-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing
Chen F, Wang X, Jang S, Quach B, Weissenkampen J, Khunsriraksakul C, Yang L, Sauteraud R, Albert C, Allred N, Arnett D, Ashley-Koch A, Barnes K, Barr R, Becker D, Bielak L, Bis J, Blangero J, Boorgula M, Chasman D, Chavan S, Chen Y, Chuang L, Correa A, Curran J, David S, Fuentes L, Deka R, Duggirala R, Faul J, Garrett M, Gharib S, Guo X, Hall M, Hawley N, He J, Hobbs B, Hokanson J, Hsiung C, Hwang S, Hyde T, Irvin M, Jaffe A, Johnson E, Kaplan R, Kardia S, Kaufman J, Kelly T, Kleinman J, Kooperberg C, Lee I, Levy D, Lutz S, Manichaikul A, Martin L, Marx O, McGarvey S, Minster R, Moll M, Moussa K, Naseri T, North K, Oelsner E, Peralta J, Peyser P, Psaty B, Rafaels N, Raffield L, Reupena M, Rich S, Rotter J, Schwartz D, Shadyab A, Sheu W, Sims M, Smith J, Sun X, Taylor K, Telen M, Watson H, Weeks D, Weir D, Yanek L, Young K, Young K, Zhao W, Hancock D, Jiang B, Vrieze S, Liu D. Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. Nature Genetics 2023, 55: 291-300. PMID: 36702996, PMCID: PMC9925385, DOI: 10.1038/s41588-022-01282-x.Peer-Reviewed Original ResearchConceptsTWAS methodsExpression quantitative trait loci (eQTL) dataQuantitative trait loci dataTranscriptome-wide associationWide association studyGenome-wide association study summary statisticsWhole genome sequencesSubsequent fine mappingEQTL datasetNew genesLoci dataFine mappingPhenotypic effectsTobacco use phenotypesDiverse ancestryAssociation studiesBiological relevanceEuropean ancestryGenesAncestryGWASSummary statisticsBiologyDrug repurposingDiversity
2022
Overcoming Therapy Resistance in Colon Cancer by Drug Repurposing
Zarif T, Yibirin M, De Oliveira-Gomes D, Machaalani M, Nawfal R, Bittar G, Bahmad H, Bitar N. Overcoming Therapy Resistance in Colon Cancer by Drug Repurposing. Cancers 2022, 14: 2105. PMID: 35565237, PMCID: PMC9099737, DOI: 10.3390/cancers14092105.Peer-Reviewed Original ResearchColorectal cancerDecreases chemotherapy toxicityTreatment of colorectal cancerOvercome therapy resistanceDevelopment of promising therapiesRates of obesityMetastatic settingChemotherapy toxicityStandard screening methodTherapy resistanceAnti-diabetic agentsAdjuvant roleColon cancerSurvival rateAnti-malarialsPromising therapiesDrug repurposingIncreased life expectancyPoor dietCancerGeneral populationAnti-hypertensiveDrugAnti-inflammatoryComorbidities
2021
Mendelian Randomization in Stroke: A Powerful Approach to Causal Inference and Drug Target Validation
Acosta JN, Szejko N, Falcone GJ. Mendelian Randomization in Stroke: A Powerful Approach to Causal Inference and Drug Target Validation. Frontiers In Genetics 2021, 12: 683082. PMID: 34456968, PMCID: PMC8387928, DOI: 10.3389/fgene.2021.683082.Peer-Reviewed Original ResearchMendelian randomizationCardiovascular risk factorsRisk of strokeAvailable treatment optionsInflammation-related mechanismsIschemic strokeHemorrhagic strokeTreatment optionsRisk factorsLeading causeCurrent evidenceTherapeutic targetStrokeMR studiesNovel biological pathwaysDrug repurposingDrug developmentDrug target validationRandomizationTarget validationExposureBiological pathwaysCausal relationshipDisease
2019
Discovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing
Wu Y, Warner J, Wang L, Jiang M, Xu J, Chen Q, Nian H, Dai Q, Du X, Yang P, Denny J, Liu H, Xu H. Discovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing. JCO Clinical Cancer Informatics 2019, 3: cci.19.00001. PMID: 31141421, PMCID: PMC6693869, DOI: 10.1200/cci.19.00001.Peer-Reviewed Original ResearchConceptsVanderbilt University Medical CenterCancer survivalMayo ClinicDrug repurposingNoncancer drugsElectronic health record dataCancer registry dataEHR dataClinical trial evaluationOverall cancer survivalUniversity Medical CenterHealth record dataElectronic health recordsTreatment of cancerClinical trialsDrug classesRegistry dataMedical CenterDrug effectsSignificant associationLongitudinal EHRNew indicationsPatientsCancerHealth records
2018
Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding–Based Machine Learning Approach
Patrick M, Raja K, Miller K, Sotzen J, Gudjonsson J, Elder J, Tsoi L. Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding–Based Machine Learning Approach. Journal Of Investigative Dermatology 2018, 139: 683-691. PMID: 30342048, PMCID: PMC6387843, DOI: 10.1016/j.jid.2018.09.018.Peer-Reviewed Original ResearchConceptsImmune-mediated diseasesCutaneous diseaseEfficient bioinformatics approachBioinformatics approachDrug-disease relationshipsDrug repurposing approachChronic inflammatory condition of skinChronic inflammatory conditionsSequencing cohortPsoriatic lesional skinReceiver Operating CharacteristicRNA-sequencing cohortsClinical efficacyTreat other diseasesLesional skinAutoimmune diseasesRepurposing approachDrug repurposingCondition of skinOther diseasesDrugDisease
2017
A systematic analysis of FDA-approved anticancer drugs
Sun J, Wei Q, Zhou Y, Wang J, Liu Q, Xu H. A systematic analysis of FDA-approved anticancer drugs. BMC Systems Biology 2017, 11: 87. PMID: 28984210, PMCID: PMC5629554, DOI: 10.1186/s12918-017-0464-7.Peer-Reviewed Original ResearchConceptsDrug-cancer associationsAnticancer drugsTarget-based drugsEfficient anticancer drugsTarget-based approachCancer typesNew anticancer drugsNovel anticancer drugsClinical trial studyPharmaceutical researchTrial studyMore cancer typesUS FoodDrug AdministrationCytotoxic drugsPatient treatmentPotential candidateDrug mechanismsDrugsDrug repurposingSystematic investigationAssociationDrug targetsTyrosine kinaseSystematic discovery
2014
Overcoming Drug Development Bottlenecks With Repurposing: Old drugs learn new tricks
Strittmatter SM. Overcoming Drug Development Bottlenecks With Repurposing: Old drugs learn new tricks. Nature Medicine 2014, 20: 590-591. PMID: 24901567, PMCID: PMC4371131, DOI: 10.1038/nm.3595.Peer-Reviewed Original Research
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