2022
Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19
Unterman A, Sumida TS, Nouri N, Yan X, Zhao AY, Gasque V, Schupp JC, Asashima H, Liu Y, Cosme C, Deng W, Chen M, Raredon MSB, Hoehn KB, Wang G, Wang Z, DeIuliis G, Ravindra NG, Li N, Castaldi C, Wong P, Fournier J, Bermejo S, Sharma L, Casanovas-Massana A, Vogels CBF, Wyllie AL, Grubaugh ND, Melillo A, Meng H, Stein Y, Minasyan M, Mohanty S, Ruff WE, Cohen I, Raddassi K, Niklason L, Ko A, Montgomery R, Farhadian S, Iwasaki A, Shaw A, van Dijk D, Zhao H, Kleinstein S, Hafler D, Kaminski N, Dela Cruz C. Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19. Nature Communications 2022, 13: 440. PMID: 35064122, PMCID: PMC8782894, DOI: 10.1038/s41467-021-27716-4.Peer-Reviewed Original ResearchMeSH KeywordsAdaptive ImmunityAgedAntibodies, Monoclonal, HumanizedCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesCells, CulturedCOVID-19COVID-19 Drug TreatmentFemaleGene Expression ProfilingGene Expression RegulationHumansImmunity, InnateMaleReceptors, Antigen, B-CellReceptors, Antigen, T-CellRNA-SeqSARS-CoV-2Single-Cell AnalysisConceptsProgressive COVID-19B cell clonesSingle-cell analysisT cellsImmune responseMulti-omics single-cell analysisCOVID-19Cell clonesAdaptive immune interactionsSevere COVID-19Dynamic immune responsesGene expressionSARS-CoV-2 virusAdaptive immune systemSomatic hypermutation frequenciesCellular effectsProtein markersEffector CD8Immune signaturesProgressive diseaseHypermutation frequencyProgressive courseClassical monocytesClonesImmune interactions
2021
Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks
Sehanobish A, Ravindra N, Van Dijk D. Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks. Proceedings Of The AAAI Conference On Artificial Intelligence 2021, 35: 4864-4873. DOI: 10.1609/aaai.v35i6.16619.Peer-Reviewed Original ResearchSARS-CoV-2 infectionSingle-cell omics dataCOVID-19 severitySingle-cell RNA sequencing datasetsCell typesRNA sequencing datasetsSARS-CoV-2Transcriptomic patternsSequencing datasetsOmics dataCellular determinantsCellular understandingIndividual cellsBronchoalveolar lavage fluid samplesInfected cellsSevere COVID-19Lavage fluid samplesCOVID-19Lung organoidsDisease statesInfectionTranscriptomeCellsSeverityFluid samplesA neutrophil activation signature predicts critical illness and mortality in COVID-19
Meizlish ML, Pine AB, Bishai JD, Goshua G, Nadelmann ER, Simonov M, Chang CH, Zhang H, Shallow M, Bahel P, Owusu K, Yamamoto Y, Arora T, Atri DS, Patel A, Gbyli R, Kwan J, Won CH, Dela Cruz C, Price C, Koff J, King BA, Rinder HM, Wilson FP, Hwa J, Halene S, Damsky W, van Dijk D, Lee AI, Chun HJ. A neutrophil activation signature predicts critical illness and mortality in COVID-19. Blood Advances 2021, 5: 1164-1177. PMID: 33635335, PMCID: PMC7908851, DOI: 10.1182/bloodadvances.2020003568.Peer-Reviewed Original ResearchConceptsCritical illnessHealth system databaseNeutrophil activationCOVID-19Neutrophil activation signatureSevere COVID-19Intensive care unitGranulocyte colony-stimulating factorHigh mortality rateColony-stimulating factorSystem databaseHepatocyte growth factorClinical decompensationNeutrophil countImmune hyperactivationCare unitEarly elevationLipocalin-2Interleukin-8Longitudinal cohortClinical dataMortality ratePatientsIllnessActivation signature