Adjunct Faculty
Adjunct faculty typically have an academic or research appointment at another institution and contribute or collaborate with one or more School of Medicine faculty members or programs.
Adjunct rank detailsJoseph N Paulson, PhD
Assistant Professor AdjunctAbout
Research
Publications
Featured Publications
Differential richness inference for 16S rRNA marker gene surveys
Kumar M, Slud E, Hehnly C, Zhang L, Broach J, Irizarry R, Schiff S, Paulson J. Differential richness inference for 16S rRNA marker gene surveys. Genome Biology 2022, 23: 166. PMID: 35915508, PMCID: PMC9344657, DOI: 10.1186/s13059-022-02722-x.Peer-Reviewed Original ResearchConceptsMarker gene surveysRRNA marker gene surveysGene surveysMicrobial assemblagesSpecies discoveryMicrobial taxaMicrobial communitiesMicrobiome surveysRichness estimationSequencing readsDiversity measuresTaxaGenus abundanceMicrobiome dataR packageAbundanceRichnessDiscoveryDiversityReadsAssemblagesObserved numberExperimental evidenceAccumulationInferencePaenibacillus infection with frequent viral coinfection contributes to postinfectious hydrocephalus in Ugandan infants
Paulson J, Williams B, Hehnly C, Mishra N, Sinnar S, Zhang L, Ssentongo P, Mbabazi-Kabachelor E, Wijetunge D, von Bredow B, Mulondo R, Kiwanuka J, Bajunirwe F, Bazira J, Bebell L, Burgoine K, Couto-Rodriguez M, Ericson J, Erickson T, Ferrari M, Gladstone M, Guo C, Haran M, Hornig M, Isaacs A, Kaaya B, Kangere S, Kulkarni A, Kumbakumba E, Li X, Limbrick D, Magombe J, Morton S, Mugamba J, Ng J, Olupot-Olupot P, Onen J, Peterson M, Roy F, Sheldon K, Townsend R, Weeks A, Whalen A, Quackenbush J, Ssenyonga P, Galperin M, Almeida M, Atkins H, Warf B, Lipkin W, Broach J, Schiff S. Paenibacillus infection with frequent viral coinfection contributes to postinfectious hydrocephalus in Ugandan infants. Science Translational Medicine 2020, 12 PMID: 32998967, PMCID: PMC7774825, DOI: 10.1126/scitranslmed.aba0565.Peer-Reviewed Original ResearchConceptsPostinfectious hydrocephalusCSF samplesPIH casesPotential causative organismsCerebrospinal fluid accumulationCytomegalovirus coinfectionUgandan infantsNeonatal sepsisSurgical palliationNeonatal infectionInfant casesOptimal treatmentInfant cohortCommon causeCausative organismPediatric hydrocephalusFluid accumulationHydrocephalusAnaerobic bacterial isolatesControl casesInfectionFacultative anaerobic bacterial isolatesInfantsParasitic DNADiseaseNeoantigens in Patients with De Novo Follicular Lymphoma: Results from the PRIMA Study
Henneges C, Jin D, Venstrom J, Trabucco S, Nielsen T, Penuel E, Huet S, Salles G, Paulson J. Neoantigens in Patients with De Novo Follicular Lymphoma: Results from the PRIMA Study. Blood 2020, 136: 25-26. DOI: 10.1182/blood-2020-134795.Peer-Reviewed Original ResearchDiffuse large B-cell lymphomaDe novo diffuse large B-cell lymphomaProgression-free survivalTumor mutational burdenComprehensive genomic profilingCurrent equity holderAssociated with progression-free survivalFollicular lymphomaF. Hoffmann-La RocheFoundation MedicinePrognostic valueClinical outcomesMedian tumor mutation burdenProgression-free survival eventsPooled analysis of patientsLarge B-cell lymphomaResponse to induction treatmentCalculate tumor mutational burdenAssociated with clinical outcomesEZH2 mutation statusComprehensive genomic profiling dataB-cell lymphomaGenetic mutational landscapeAnalysis of patientsProportion of patientsDifferential abundance analysis for microbial marker-gene surveys
Paulson J, Stine O, Bravo H, Pop M. Differential abundance analysis for microbial marker-gene surveys. Nature Methods 2013, 10: 1200-1202. PMID: 24076764, PMCID: PMC4010126, DOI: 10.1038/nmeth.2658.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsArea Under CurveCluster AnalysisComputer SimulationDatabases, GeneticGene Expression ProfilingGenetic MarkersGenetic VariationHumansIntestinesMetagenomicsMiceMicrobiotaModels, GeneticModels, StatisticalNormal DistributionPhenotypeRNA, Ribosomal, 16SSequence Analysis, DNASoftware
2025
Poor surgical outcomes following Paenibacillus infant infectious hydrocephalus.
Ericson J, Natukwatsa D, Ssenyonga P, Onen J, Mugamba J, Mulondo R, Morton S, Movassagh M, Templeton K, Hehnly C, Mbabazi-Kabachelor E, Kulkarni A, Warf B, Broach J, Paulson J, Schiff S. Poor surgical outcomes following Paenibacillus infant infectious hydrocephalus. Journal Of Neurosurgery Pediatrics 2025, 36: 145-156. PMID: 40378477, PMCID: PMC12211056, DOI: 10.3171/2025.1.peds24254.Peer-Reviewed Original ResearchPostinfectious hydrocephalusPP patientsPN patientsEndoscopic diversionHydrocephalus surgeryPositive CSF polymerase chain reactionPrimary outcomeMedian follow-up periodCSF polymerase chain reactionFailure-free survivalPoor surgical outcomesPrimary event rateFollow-up periodOverall survivalCSF diversionHydrocephalic infantsSurgical outcomesNeurosurgical evaluationPolymerase chain reactionCompare outcomesSecondary outcomesPatientsEvent ratesInfantsChain reactionP-1158. Surgical Outcomes Following Paenibacillus Infant Infectious Hydrocephalus
Ericson J, Natukwatsa D, Ssenyonga P, Onen J, Mugamba J, Mulondo R, Morton S, Templeton K, Hehnly C, Mbabazi-Kabachelor E, Kulkarni A, Warf B, Broach J, Paulson J, Schiff S. P-1158. Surgical Outcomes Following Paenibacillus Infant Infectious Hydrocephalus. Open Forum Infectious Diseases 2025, 12: ofae631.1344. PMCID: PMC11776767, DOI: 10.1093/ofid/ofae631.1344.Peer-Reviewed Original ResearchPostinfectious hydrocephalusPP patientsPN patientsCerebrospinal fluidEndoscopic diversionHydrocephalus surgeryPositive CSF polymerase chain reactionPrimary outcomeMedian follow-up periodCSF polymerase chain reactionFailure-free survivalPrimary event rateFollow-up periodOverall survivalSurgical outcomesHydrocephalic infantsSurgical managementSurgery typePreoperative testingNeurosurgical evaluationPolymerase chain reactionCompare outcomesSecondary outcomesPatientsSurgery
2024
Evaluation of completeness of commonly used data elements for clinical trial eligibility criteria using a registry-enhanced data collection process: Results from patients with non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) at three community oncology practices.
Campbell Fontaine A, McAneny B, Tucker V, Koontz M, Trotter C, Paulson J, McMurdie P, Tezcan A, Peguero J, Peguero J, Campos L. Evaluation of completeness of commonly used data elements for clinical trial eligibility criteria using a registry-enhanced data collection process: Results from patients with non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) at three community oncology practices. Journal Of Clinical Oncology 2024, 20: 346-346. DOI: 10.1200/op.2024.20.10_suppl.346.Peer-Reviewed Original ResearchNon-small cell lung cancerCommunity oncology practicesColorectal cancerDiagnosis dateOncology practiceCancer diagnosisData elementsEligibility assessmentColorectal cancer patientsCompletion ratesGenomic test resultsEssential data elementsLung cancerClinical trialsRemote staffMale to female ratioSystemic anti-cancer treatmentTrial eligibility criteriaPatient identificationECOG performance statusICD10 codesPatient RegistryYears of ageLung cancer diagnosisCell lung cancerLubricating gel influence on vaginal microbiome sampling
Amitai Komem D, Hadar R, Paulson J, Mordechai Y, Eskandarian H, Efroni G, Amir A, Haberman Y, Tsur A. Lubricating gel influence on vaginal microbiome sampling. Scientific Reports 2024, 14: 18223. PMID: 39107405, PMCID: PMC11303677, DOI: 10.1038/s41598-024-68948-w.Peer-Reviewed Original ResearchConceptsMicrobial compositionVaginal samplesVaginal microbiome samplesBeta diversityVaginal microbiome studiesMicrobiome studiesMicrobiome samplesTaxa abundanceGynecological examinationPregnant womenLubricant gelReduce painMicrobial dataGel exposureEmergency roomSterile swabsEffect of gelMicrobial analysisPatients with a history of more than one cancer diagnosis: An opportunity to expand eligibility criteria?
Campos L, Peguero J, Koontz M, Trotter C, Svedman C, Paulson J, Chung W, Tucker V, McAneny B, Campbell Fontaine A. Patients with a history of more than one cancer diagnosis: An opportunity to expand eligibility criteria? Journal Of Clinical Oncology 2024, 42: e23019-e23019. DOI: 10.1200/jco.2024.42.16_suppl.e23019.Peer-Reviewed Original ResearchMedian ageCancer diagnosisIncreasing proportion of elderly patientsProportion of elderly patientsMedian time intervalHistory of 2Early-stage cancerCommunity oncology sitesAnalyzed patientsClinical characteristicsNSCLC diagnosisCure rateElderly patientsGenomic alterationsClinical trialsNSCLCPatientsExclusion criteriaCancerOncology sitesLonger life expectancyDiagnosisEligibility criteriaTesting ratesLife expectancyDevelopment and preliminary validation of a platform for systematic, unbiased pre-screening of non-small cell lung cancer (NSCLC) across three community oncology practices.
Campbell Fontaine A, McAneny B, Tucker V, Koontz M, Trotter C, Paulson J, Svedman C, Pan A, Peguero J, Campos L. Development and preliminary validation of a platform for systematic, unbiased pre-screening of non-small cell lung cancer (NSCLC) across three community oncology practices. Journal Of Clinical Oncology 2024, 42: e23230-e23230. DOI: 10.1200/jco.2024.42.16_suppl.e23230.Peer-Reviewed Original ResearchNon-small cell lung cancerClinical trialsCommunity oncology practicesMedical oncologistsNon-small cell lung cancer ptsOncology practiceCell lung cancerClinical trial patient populationTrial patient populationTesting ratesPre-screening of patientsIdentification of eligible patientsAssessment of eligibilityECOG PSClinical trial sitesMetastatic statusEligible patientsLung cancerRoutine clinical workflowPatient populationOncology patientsPatientsOncologist assessmentGold standardTreatment history