2021
Diffusion Earth Mover's Distance and Distribution Embeddings.
Tong A, Huguet G, Natik A, MacDonald K, Kuchroo M, Coifman R, Wolf G, Krishnaswamy S. Diffusion Earth Mover's Distance and Distribution Embeddings. ArXiv 2021 PMID: 33655017, PMCID: PMC7924278.Peer-Reviewed Original ResearchStructural and developmental principles of neuropil assembly in C. elegans
Moyle MW, Barnes KM, Kuchroo M, Gonopolskiy A, Duncan LH, Sengupta T, Shao L, Guo M, Santella A, Christensen R, Kumar A, Wu Y, Moon KR, Wolf G, Krishnaswamy S, Bao Z, Shroff H, Mohler WA, Colón-Ramos DA. Structural and developmental principles of neuropil assembly in C. elegans. Nature 2021, 591: 99-104. PMID: 33627875, PMCID: PMC8385650, DOI: 10.1038/s41586-020-03169-5.Peer-Reviewed Original ResearchConceptsSpecific sensory organsNerve ringCaenorhabditis elegansC. elegansMuscle quadrantsNeuropil organizationDevelopmental principlesTissue organizationSensory organsBehavioral circuitsElegansPioneer neuronsCell positionDevelopmental sequenceStratified architectureTemporal progressionPrecise circuitsPacked neuronsUnique morphologyNeuronsSequenceOutgrowthAssemblyHierarchical developmentNeuropilTopological analysis of single-cell hierarchy reveals inflammatory glial landscape of macular degeneration.
Kuchroo M.*, Distasio M.*, Song E.*, Calapkulu E., Zhang L., Ige M., Sheth A.H., Menon M., Tong A., Godavarthi A., Xing Y., Gigante S., Steach H., Huang J., Huguet G., Narain J., Mourgkos G., Dhodapkar R.M., Hirn M.J, Rieck B., Wolf G. et al. (2021, Sep). Topological analysis of single-cell hierarchy reveals inflammatory glial landscape of macular degeneration. Cell.Peer-Reviewed Original Research In PressMultimodal data visualization and denoising with integrated diffusion. Machine Learning for Signal Processing.
Kuchroo M.*, Godavarthi A.*, Tong A., Wolf G., Krishnaswamy S. (2021, Aug). Multimodal data visualization and denoising with integrated diffusion. Machine Learning for Signal Processing.Peer-Reviewed Original ResearchMultiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease.
Kuchroo M.*, Huang J.*, Wong P.*,Grenier J.C., Shung D., Tong A., Lucas C., Klein J., Gamache I., Poujol R., Burkhardt D.B., Gigante S., Godavarthi A., Rieck B., Israelow B., Simonov M., Mao T., Eun Oh J., Silva J., Pesaranghader A., Takahashi T. et al.. (2021, Feb). Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease. Nature Biotechnology.Peer-Reviewed Original ResearchA reservoir of stem-like CD8+ T cells in the tumor-draining lymph node preserves the ongoing anti-tumor immune response.
Connolly, K.A., Kuchroo M., Venkat A., Khatun A., Wang J., William I., Hornick N., Fitzgerald B., Damo M., Kasmani M.Y., Cui C., Fagerberg E., Monroy I., Hutchins A., Cheung J.F., Foster G.G., Mariuzza D.L., Nader M., Zhao H., Cui W., et al. (2021, Sep). A reservoir of stem-like CD8+ T cells in the tumor-draining lymph node preserves the ongoing anti-tumor immune response. Science Immunology.Peer-Reviewed Original ResearchMechanisms of autoimmune diabetes in patients treated with checkpoint inhibitors.
Perdigoto A.L., Deng S., Du K., Kuchroo M., Burkhardt D.B., Tong A., Kirkiles-Smith N., Stamatouli A.M., Kluger H.M., Quandt A., Young A., Yang M., Mamula M.J., Robert M.E., Pober J.S., Weisberg S.P., Israel G., Anderson M.S., Krishnaswamy S., Herold K.C. (2021, Sep). Mechanisms of autoimmune diabetes in patients treated with checkpoint inhibitors. Cell Metabolism.Peer-Reviewed Original Research In PressEmbedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance.
Tong A., Huguet G., Shung D., Natik A., KUCHROO M., Lajoie G., Wolf G., Krishnaswamy S. (2021, Sep). Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. OTML Workshop at Conference on Neural Information. Processing Systems.Peer-Reviewed Original Research In Press
2019
Coarse Graining of Data via Inhomogeneous Diffusion Condensation
Brugnone N, Gonopolskiy A, Moyle MW, Kuchroo M, van Dijk D, Moon KR, Colon-Ramos D, Wolf G, Hirn MJ, Krishnaswamy S. Coarse Graining of Data via Inhomogeneous Diffusion Condensation. 2019, 00: 2624-2633. PMID: 32747879, PMCID: PMC7398322, DOI: 10.1109/bigdata47090.2019.9006013.Peer-Reviewed Original ResearchA Forward Chemical Genetic Screen Reveals Gut Microbiota Metabolites That Modulate Host Physiology
Chen H, Nwe PK, Yang Y, Rosen CE, Bielecka AA, Kuchroo M, Cline GW, Kruse AC, Ring AM, Crawford JM, Palm NW. A Forward Chemical Genetic Screen Reveals Gut Microbiota Metabolites That Modulate Host Physiology. Cell 2019, 177: 1217-1231.e18. PMID: 31006530, PMCID: PMC6536006, DOI: 10.1016/j.cell.2019.03.036.Peer-Reviewed Original ResearchConceptsHost physiologyBioactive microbial metabolitesHuman gut bacteriaHost sensingProlific producersG proteinsGut microbiota metabolitesBlood-brain barrierL-PheMicrobial metabolitesOrphan GPCRsGut bacteriaColonic motilityInhibitor administrationMicrobiota metabolitesIntestinal microbiotaSmall moleculesDietary histidineBacteriaPhysiologyMicrobiota metabolomeMetabolitesGPR97Orthogonal approachGPCRs
2013
Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis
Cui J, Stahl EA, Saevarsdottir S, Miceli C, Diogo D, Trynka G, Raj T, Mirkov MU, Canhao H, Ikari K, Terao C, Okada Y, Wedrén S, Askling J, Yamanaka H, Momohara S, Taniguchi A, Ohmura K, Matsuda F, Mimori T, Gupta N, Kuchroo M, Morgan AW, Isaacs JD, Wilson AG, Hyrich KL, Herenius M, Doorenspleet ME, Tak PP, Crusius JB, van der Horst-Bruinsma IE, Wolbink GJ, van Riel PL, van de Laar M, Guchelaar HJ, Shadick NA, Allaart CF, Huizinga TW, Toes RE, Kimberly RP, Bridges SL, Criswell LA, Moreland LW, Fonseca JE, de Vries N, Stranger BE, De Jager PL, Raychaudhuri S, Weinblatt ME, Gregersen PK, Mariette X, Barton A, Padyukov L, Coenen MJ, Karlson EW, Plenge RM. Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis. PLOS Genetics 2013, 9: e1003394. PMID: 23555300, PMCID: PMC3610685, DOI: 10.1371/journal.pgen.1003394.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAllelesAntigens, CDAntirheumatic AgentsArthritis, RheumatoidAsian PeopleBiomarkers, PharmacologicalEtanerceptFemaleGene Expression RegulationGenome-Wide Association StudyHumansImmunoglobulin GMaleMiddle AgedPolymorphism, Single NucleotideReceptors, Tumor Necrosis FactorSignaling Lymphocytic Activation Molecule FamilyTumor Necrosis Factor-alphaWhite PeopleConceptsGenome-wide association studiesGene expressionAssociation studiesAnti-TNF therapyRA patientsRheumatoid arthritisNon-significant trendGene expression dataEtanercept therapySite motifTranscription factorsImmune-related genesPeripheral blood mononuclear cellsExpression dataAnti-TNF medicationsDisease Activity ScoreBlood mononuclear cellsPredictors of responseCD84 expressionCommon variantsCD84European ancestryDisease activityBiologic therapyRefractory casesCommon Risk Alleles for Inflammatory Diseases Are Targets of Recent Positive Selection
Raj T, Kuchroo M, Replogle JM, Raychaudhuri S, Stranger BE, De Jager PL. Common Risk Alleles for Inflammatory Diseases Are Targets of Recent Positive Selection. American Journal Of Human Genetics 2013, 92: 517-529. PMID: 23522783, PMCID: PMC3617371, DOI: 10.1016/j.ajhg.2013.03.001.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesProtein-protein interaction networkRecent positive selectionPositive selectionInteraction networksExpression quantitative trait loci (eQTL) mapping studiesSelective pressureQuantitative trait locus (QTL) mapping studiesRecent positive natural selectionHundreds of lociPositive natural selectionFunctional genomics dataCis-regulatory effectsInflammatory disease susceptibilityHost resistanceSignificant selective pressureCommon risk allelesEvolutionary forcesMolecular functionsAssociated lociNatural selectionGenetic variationGenomic signaturesGenomic dataGene expression
2012
An RNA Profile Identifies Two Subsets of Multiple Sclerosis Patients Differing in Disease Activity
Ottoboni L, Keenan BT, Tamayo P, Kuchroo M, Mesirov JP, Buckle GJ, Khoury SJ, Hafler DA, Weiner HL, De Jager PL. An RNA Profile Identifies Two Subsets of Multiple Sclerosis Patients Differing in Disease Activity. Science Translational Medicine 2012, 4: 153ra131. PMID: 23019656, PMCID: PMC3753678, DOI: 10.1126/scitranslmed.3004186.Peer-Reviewed Original ResearchConceptsGlatiramer acetateDisease activityPatient populationFirst-line disease-modifying treatmentsMultiple sclerosis (MS) patient populationPeripheral blood mononuclear cellsMS patient populationDisease-modifying treatmentsMultiple sclerosis patientsBlood mononuclear cellsSubset of subjectsDisease courseSclerosis patientsMS subjectsMononuclear cellsInflammatory eventsTreatment responseUntreated subjectsAdditional groupHigh expressionTranscriptional signatureSubjectsRNA profilesTreatmentTranscriptional profiles