2025
scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links
Wang G, Zhao J, Lin Y, Liu T, Zhao Y, Zhao H. scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links. Nature Communications 2025, 16: 4994. PMID: 40442129, PMCID: PMC12122792, DOI: 10.1038/s41467-025-60333-z.Peer-Reviewed Original ResearchConceptsDeep learning frameworkSingle-cell multi-omics researchSingle-cell multi-omics dataLearning frameworkMulti-omics dataGenerative adversarial networkSingle-cell technologiesData alignmentSingle-cell resolutionMulti-omics researchDownstream analysisCellular statesOmics datasetsAdversarial networkNeural networkProteomic profilingCorrelated featuresBiological informationOmics perspectiveDiverse datasetsFeature topologyDisease mechanismsCell embeddingData resourcesRelationship inferenceA novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics
Cheng Z, Ren Y, Wang X, Zhang Y, Hua Y, Zhao H, Lu H. A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics. Briefings In Bioinformatics 2025, 26: bbaf216. PMID: 40381315, PMCID: PMC12085197, DOI: 10.1093/bib/bbaf216.Peer-Reviewed Original ResearchConceptsHepatocellular carcinoma patientsHepatocellular carcinomaHCC patientsPrognostic modelAdverse prognosisClinically relevant risk groupsRisk groupsTreatment of hepatocellular carcinomaTumor immune microenvironmentAlpha-fetoprotein levelsHigh-risk HCC patientsRelevant risk groupsPrognosis of HCC patientsHBV-infected hepatocellular carcinomaIron metabolismOverall survivalDifferential expression patternsDistant metastasisImmune microenvironmentTumor sizeLiver cancer progressionTumor differentiationMicrovascular invasionPredictive nomogramValidation cohortA multi-omic approach implicates novel protein dysregulation in post-traumatic stress disorder
Wang J, Liu Y, Li H, Nguyen T, Soto-Vargas J, Wilson R, Wang W, Lam T, Zhang C, Lin C, Lewis D, Glausier J, Holtzheimer P, Friedman M, Williams K, Picciotto M, Nairn A, Krystal J, Duman R, Young K, Zhao H, Girgenti M. A multi-omic approach implicates novel protein dysregulation in post-traumatic stress disorder. Genome Medicine 2025, 17: 43. PMID: 40301990, PMCID: PMC12042318, DOI: 10.1186/s13073-025-01473-1.Peer-Reviewed Original ResearchConceptsPost-traumatic stress disorderDorsolateral prefrontal cortexPsychiatric disordersAutism spectrum disorderPrefrontal cortexDepressive disorderStress disorderGamma-aminobutyric acidGenome-wide association studiesPTSD brainsGenome-wide measurementsStudies of postmortem brainsSubgenual prefrontal cortexDisabling psychiatric disorderMultiple psychiatric disordersPrefrontal cortical areasPTSD casesHuman brain studiesBrain regionsSpectrum disorderGABAergic processesPostmortem brainsMDDProtein co-expression modulesProteomic profiling
2024
Single-cell transcriptomic and proteomic analysis of Parkinson’s disease brains
Zhu B, Park J, Coffey S, Russo A, Hsu I, Wang J, Su C, Chang R, Lam T, Gopal P, Ginsberg S, Zhao H, Hafler D, Chandra S, Zhang L. Single-cell transcriptomic and proteomic analysis of Parkinson’s disease brains. Science Translational Medicine 2024, 16: eabo1997. PMID: 39475571, PMCID: PMC12372474, DOI: 10.1126/scitranslmed.abo1997.Peer-Reviewed Original ResearchConceptsProteomic analysisAlzheimer's diseasePrefrontal cortexBrain cell typesGenetics of PDParkinson's diseaseCell-cell interactionsChaperone expressionSingle-nucleus transcriptomesExpressed genesTranscriptional changesPostmortem human brainPostmortem brain tissueDiseased brainSynaptic proteinsSingle-cellDown-regulationBrain cell populationsBrain regionsCell typesNeurodegenerative disordersLate-stage PDParkinson's disease brainsDisease etiologyNeuronal vulnerability
2023
Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
Ruan P, Todd J, Zhao H, Liu Y, Vinisko R, Soellner J, Schmid R, Kaner R, Luckhardt T, Neely M, Noth I, Porteous M, Raj R, Safdar Z, Strek M, Hesslinger C, Palmer S, Leonard T, Salisbury M. Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression. Respiratory Research 2023, 24: 141. PMID: 37344825, PMCID: PMC10283254, DOI: 10.1186/s12931-023-02435-0.Peer-Reviewed Original ResearchMeSH KeywordsDisease ProgressionFemaleHumansIdiopathic Pulmonary FibrosisLungMaleMicroRNAsMultiomicsProteomicsConceptsComposite physiologic indexProgression-free survivalTransplant-free survivalMolecular subtypesSubtype 1Risk groupsProspective registrySubtype 2Disease progressionProspective registry of patientsIPF-PRO RegistryB-cell receptor signalingBackgroundIdiopathic pulmonary fibrosisRegistry of patientsCox proportional hazards modelsIntegrative multi-omics analysisAccumulation of extracellular matrixProportional hazards modelTransplant-freeProgression-FreeMolecular endotypesEnrichment of clinical trialsAntifibrotic treatmentMulti-omics analysisPulmonary fibrosis
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