2025
High MGMT expression identifies aggressive colorectal cancer with distinct genomic features and immune evasion properties
Zhang J, Rajendran B, Desai S, Gibson J, DiPalermo J, LoRusso P, Kong Y, Zhao H, Cecchini M, Schalper K. High MGMT expression identifies aggressive colorectal cancer with distinct genomic features and immune evasion properties. Journal For ImmunoTherapy Of Cancer 2025, 13: e011653. PMID: 40935566, DOI: 10.1136/jitc-2025-011653.Peer-Reviewed Original ResearchThis study shows that high MGMT expression in colorectal cancer is linked to aggressive behavior, distinct genomic features, immune evasion, and shorter survival, highlighting its potential as a biomarker for prognosis and therapeutic targeting.Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk
Hu J, Ye Y, Zhang C, Ruan Y, Natarajan P, Zhao H. Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk. PLOS Computational Biology 2025, 21: e1013191. PMID: 40570042, PMCID: PMC12212871, DOI: 10.1371/journal.pcbi.1013191.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresCAD-PRSUK BiobankCoronary artery disease polygenic risk scoreSummary-level dataCAD-related traitsSamples of European ancestryCoronary artery diseaseHigh-risk individualsPotential genetic heterogeneityCurrent smokingPolygenic scoresPolygenic riskTargeted interventionsEuropean ancestryRisk scorePleiotropic regionsRisk predictionGenetic heterogeneityBiological functionsPleiotropySignificant interactionPhenotypic heterogeneityBlood pressureDisease interpretationA 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 profilingA semicompeting risks model with an application to UK Biobank data to identify risk factors for diabetes onset and progression
Sheikh T, Zhao H. A semicompeting risks model with an application to UK Biobank data to identify risk factors for diabetes onset and progression. Biometrics 2025, 81: ujaf003. PMID: 40417914, PMCID: PMC12104815, DOI: 10.1093/biomtc/ujaf003.Peer-Reviewed Original ResearchConceptsUK Biobank dataRisk factorsBiobank dataType 2 diabetesUKB dataHealth concernVolunteer participantsDisease stageComplex diseasesT2D developmentNongenetic factorsDisease etiologyDiabetes onsetT2DModel fitRisk modelDiabetesRiskPower prior approachDeathUKBMultiple disease stagesTerminal eventNonterminal eventHealthGenomic analysis of 11,555 probands identifies 60 dominant congenital heart disease genes
Sierant M, Jin S, Bilguvar K, Morton S, Dong W, Jiang W, Lu Z, Li B, López-Giráldez F, Tikhonova I, Zeng X, Lu Q, Choi J, Zhang J, Nelson-Williams C, Knight J, Zhao H, Cao J, Mane S, Sedore S, Gruber P, Lek M, Goldmuntz E, Deanfield J, Giardini A, Mital S, Russell M, Gaynor J, King E, Wagner M, Srivastava D, Shen Y, Bernstein D, Porter G, Newburger J, Seidman J, Roberts A, Yandell M, Yost H, Tristani-Firouzi M, Kim R, Chung W, Gelb B, Seidman C, Brueckner M, Lifton R. Genomic analysis of 11,555 probands identifies 60 dominant congenital heart disease genes. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2420343122. PMID: 40127276, PMCID: PMC12002227, DOI: 10.1073/pnas.2420343122.Peer-Reviewed Original ResearchConceptsCongenital heart disease genesCongenital heart diseaseDamaging variantsMissense variantsAnalyzing de novo mutationsCHD probandsEpidermal growth factor (EGF)-like domainsNeurodevelopmental delayLoss of function variantsParent-offspring triosSyndromic congenital heart diseaseHeart disease genesDisease genesGenomic analysisCongenital heart disease subtypesAssociated with neurodevelopmental delayTetralogy of FallotFunctional variantsIncomplete penetranceCHD phenotypesGenesAssociated with developmentGenetic testingMolecular diagnosticsExtracardiac abnormalitiesRecessive genetic contribution to congenital heart disease in 5,424 probands
Dong W, Jin S, Sierant M, Lu Z, Li B, Lu Q, Morton S, Zhang J, López-Giráldez F, Nelson-Williams C, Knight J, Zhao H, Cao J, Mane S, Gruber P, Lek M, Goldmuntz E, Deanfield J, Giardini A, Mital S, Russell M, Gaynor J, Cnota J, Wagner M, Srivastava D, Bernstein D, Porter G, Newburger J, Roberts A, Yandell M, Yost H, Tristani-Firouzi M, Kim R, Seidman J, Chung W, Gelb B, Seidman C, Lifton R, Brueckner M. Recessive genetic contribution to congenital heart disease in 5,424 probands. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2419992122. PMID: 40030011, PMCID: PMC11912448, DOI: 10.1073/pnas.2419992122.Peer-Reviewed Original ResearchConceptsRecessive genotypeCHD probandsCongenital heart diseaseAssociated with laterality defectsGene-based analysisAnalyzed whole-exome sequencingLeft-sided congenital heart diseaseWhole-exome sequencingCongenital heart disease phenotypeAshkenazi Jewish probandsOffspring of consanguineous unionsSingle-cell transcriptomicsCHD geneExome sequencingMouse notochordSecreted proteinsConsanguineous familyFounder variantGenesSignificant enrichmentLaterality phenotypesHeart diseaseProbandsAbnormal contractile functionConsanguineous unionsBidirectional relationship between epigenetic age and stroke, dementia, and late-life depression
Rivier C, Szejko N, Renedo D, Clocchiatti-Tuozzo S, Huo S, de Havenon A, Zhao H, Gill T, Sheth K, Falcone G. Bidirectional relationship between epigenetic age and stroke, dementia, and late-life depression. Nature Communications 2025, 16: 1261. PMID: 39893209, PMCID: PMC11787333, DOI: 10.1038/s41467-024-54721-0.Peer-Reviewed Original ResearchThis study shows a bidirectional link between accelerated epigenetic aging and brain health events like stroke, dementia, and depression, supporting new prevention strategies for aging-related conditions.Polygenic Susceptibility to Diabetes and Poor Glycemic Control in Stroke Survivors
Demarais Z, Conlon C, Rivier C, Clocchiatti-Tuozzo S, Renedo D, Torres-Lopez V, Sheth K, Meeker D, Zhao H, Ohno-Machado L, Acosta J, Huo S, Falcone G. Polygenic Susceptibility to Diabetes and Poor Glycemic Control in Stroke Survivors. Neurology 2025, 104: e210276. PMID: 39889253, DOI: 10.1212/wnl.0000000000210276.Peer-Reviewed Original ResearchConceptsStroke survivorsWorse glycemic controlPoor glycemic controlStroke patientsAssociated with worse glycemic controlGlycemic controlPolygenic risk scoresClinical management of stroke patientsAssociated with poor glycemic controlManagement of stroke patientsCross-sectional designGenetic association studiesUncontrolled diabetesSusceptibility to T2DMUK BiobankType 2 diabetes mellitusAdverse vascular outcomesRisk scoreAssociation studiesHemoglobin A1cSurvivorsVascular outcomesSusceptibility to diabetesStrokeDiabetesThe left amygdala is genetically sexually-dimorphic: multi-omics analysis of structural MRI volumes
Gui Y, Zhou G, Cui S, Li H, Lu H, Zhao H. The left amygdala is genetically sexually-dimorphic: multi-omics analysis of structural MRI volumes. Translational Psychiatry 2025, 15: 17. PMID: 39843917, PMCID: PMC11754786, DOI: 10.1038/s41398-025-03223-8.Peer-Reviewed Original ResearchConceptsLeft amygdala volumePolygenic risk scoresLeft amygdalaSex differencesBrain volumeMental disordersAmygdala volumeBrain anatomyEffect of polygenic risk scoresStudy of sex differencesExamined sex differencesPsychiatric Genomics ConsortiumMechanisms of sex differencesSex-specific genetic correlationsGenetic correlation analysisAmygdalaStructural MRI volumesSexually-dimorphicGenetic correlationsBrainDisordersRNA-seq dataGenomics ConsortiumCell-type compositionKnowledge of genetic basisThe human and non-human primate developmental GTEx projects
Bell T, Blanchard T, Hernandez R, Linn R, Taylor D, VonDran M, Ahooyi T, Beitra D, Bernieh A, Delaney M, Faith M, Fattahi E, Footer D, Gilbert M, Guambaña S, Gulino S, Hanson J, Hattrell E, Heinemann C, Kreeb J, Leino D, Mcdevitt L, Palmieri A, Pfeiffer M, Pryhuber G, Rossi C, Rasool I, Roberts R, Salehi A, Savannah E, Stachowicz K, Stokes D, Suplee L, Van Hoose P, Wilkins B, Williams-Taylor S, Zhang S, Ardlie K, Getz G, Lappalainen T, Montgomery S, Aguet F, Anderson L, Bernstein B, Choudhary A, Domenech L, Gaskell E, Johnson M, Liu Q, Marderstein A, Nedzel J, Okonda J, Padhi E, Rosano M, Russell A, Walker B, Sestan N, Gerstein M, Milosavljevic A, Borsari B, Cho H, Clarke D, Deveau A, Galeev T, Gobeske K, Hameed I, Huttner A, Jensen M, Jiang Y, Li J, Liu J, Liu Y, Ma J, Mane S, Meng R, Nadkarni A, Ni P, Park S, Petrosyan V, Pochareddy S, Salamon I, Xia Y, Yates C, Zhang M, Zhao H, Conrad D, Feng G, Brady F, Boucher M, Carbone L, Castro J, del Rosario R, Held M, Hennebold J, Lacey A, Lewis A, Lima A, Mahyari E, Moore S, Okhovat M, Roberts V, de Castro S, Wessel B, Zaniewski H, Zhang Q, Arguello A, Baroch J, Dayal J, Felsenfeld A, Ilekis J, Jose S, Lockhart N, Miller D, Minear M, Parisi M, Price A, Ramos E, Zou S. The human and non-human primate developmental GTEx projects. Nature 2025, 637: 557-564. PMID: 39815096, PMCID: PMC12013525, DOI: 10.1038/s41586-024-08244-9.Peer-Reviewed Original ResearchConceptsChromatin accessibility dataFunctional genomic studiesWhole-genome sequencingEffects of genetic variationSpatial gene expression profilesNon-human primatesGenotype-Tissue ExpressionGene expression profilesGenomic studiesGene regulationGenetic dataGenetic variationGenomic researchDonor diversityCommunity engagementHuman evolutionEarly developmental defectsGene expressionCell statesDevelopmental programmeHuman diseasesExpression profilesAdult tissuesDevelopmental defectsSingle-cellHypermethylation of PM20D1 Is Associated With Carotid Bifurcation Intima‐Media Thickness in Dominican Republic Families
Dueker N, Zhao H, Gardener H, Kaur S, Dong C, Cabral D, Sacco R, Blanton S, Rundek T, Wang L. Hypermethylation of PM20D1 Is Associated With Carotid Bifurcation Intima‐Media Thickness in Dominican Republic Families. Journal Of The American Heart Association 2025, 14: e034033. PMID: 39791430, PMCID: PMC12054445, DOI: 10.1161/jaha.123.034033.Peer-Reviewed Original ResearchConceptsDifferentially Methylated RegionsMendelian randomization analysisCytosine nucleotidesCarotid intima-media thicknessExpression quantitative trait loci studiesRandomization analysisExpression quantitative trait lociIntima-media thicknessQuantitative trait loci studiesEpigenome-wide association studiesQuantitative trait lociTraditional vascular risk factorsBifurcation intima-media thicknessBlood-derived DNAGuanine nucleotide siteLinear mixed model analysisNucleotide sitesVascular risk factorsMeasures of atherosclerosisCarotid bifurcation intima-media thicknessTrait lociAssociation studiesNucleotide methylationLoci studiesGenetic variantsPerformance of Polygenic Risk Scores for Primary Open-Angle Glaucoma in Populations of African Descent
Chang-Wolf J, Kinzy T, Driessen S, Cruz L, Iyengar S, Peachey N, Aung T, Khor C, Williams S, Ramsay M, Olawoye O, Ashaye A, Klaver C, Hauser M, Thiadens A, Cooke Bailey J, Bonnemaijer P, Sanywia A, Cook C, Hassan H, Kanyaro N, Ntomoka C, Allingham R, van der Heide C, Taylor K, Rotter J, Wang S, ABDULLAHI S, Abu-Amero K, Anderson M, Akafo S, ALHASSAN M, Asimadu I, Ayyagari R, BAKAYOKO S, BIANGOUP NYAMSI P, Bowden D, Bromley W, Budenz D, Carmichael T, Challa P, Chen Y, Chuka-Okosa C, Costa V, Cruz D, DuBiner H, Ervin J, Feldman R, Flamme-Wiese M, Gaasterland D, Garnai S, Girkin C, GUIROU N, Guo X, Haines J, Hammond C, Herndon L, Hoffmann T, Hulette C, Hydara A, Igo Jr. R, Jorgenson E, KABWE J, KILANGALANGA N, Kizor-Akaraiwe N, Kuchtey R, LAMARI H, Li Z, Liebmann J, Liu Y, Loos R, Melo M, Moroi S, Msosa J, Mullins R, Nadkarni G, NAPO A, Ng M, Nunes H, Obeng-Nyarkoh E, Okeke A, Okeke S, OLANIYI O, Oliveira M, Pasquale L, Perez-Grossmann R, Pericak-Vance M, Qin X, RESNIKOFF S, Richards J, Schimiti R, Sim K, Sponsel W, Svidnicki P, Uche N, van Duijn C, Vasconcellos J, Wiggs J, Zangwill L, Risch N, Milea D, Weinreb R, Ashley-Koch A, Fingert J, Aslan M, Antonelli M, de Asis M, Bauer M, Brophy M, Concato J, Cunningham F, Freedman R, Gaziano M, Gleason T, Harvey P, Huang G, Kelsoe J, Kosten T, Lehner T, Lohr J, Marder S, Miller P, O Leary T, Patterson T, Peduzzi P, Przygodski R, Siever L, Sklar P, Strakowski S, Zhao H, Fanous A, Farwell W, Malhorta A, Mane S, Palacios P, Bigdeli T, Corsey M, Zaluda L, Johnson J, Sueiro M, Cavaliere D, Jeanpaul V, Maffucci A, Mancini L, Deen J, Muldoon G, Whitbourne S, Canive J, Adamson L, Calais L, Fuldauer G, Kushner R, Toney G, Lackey M, Mank A, Mahdavi N, Villarreal G, Muly E, Amin F, Dent M, Wold J, Fischer B, Elliott A, Felix C, Gill G, Parker P, Logan C, McAlpine J, DeLisi L, Reece S, Hammer M, Agbor‐Tabie D, Goodson W, Aslam M, Grainger M, Richtand N, Rybalsky A, Al Jurdi R, Boeckman E, Natividad T, Smith D, Stewart M, Torres S, Zhao Z, Mayeda A, Green A, Hofstetter J, Ngombu S, Scott M, Strasburger A, Sumner J, Paschall G, Mucciarelli J, Owen R, Theus S, Tompkins D, Potkin S, Reist C, Novin M, Khalaghizadeh S, Douyon R, Kumar N, Martinez B, Sponheim S, Bender T, Lucas H, Lyon A, Marggraf M, Sorensen L, Surerus C, Sison C, Amato J, Johnson D, Pagan‐Howard N, Adler L, Alerpin S, Leon T, Mattocks K, Araeva N, Sullivan J, Suppes T, Bratcher K, Drag L, Fischer E, Fujitani L, Gill S, Grimm D, Hoblyn J, Nguyen T, Nikolaev E, Shere L, Relova R, Vicencio A, Yip M, Hurford I, Acheampong S, Carfagno G, Haas G, Appelt C, Brown E, Chakraborty B, Kelly E, Klima G, Steinhauer S, Hurley R, Belle R, Eknoyan D, Johnson K, Lamotte J, Granholm E, Bradshaw K, Holden J, Jones R, Le T, Molina I, Peyton M, Ruiz I, Sally L, Tapp A, Devroy S, Jain V, Kilzieh N, Maus L, Miller K, Pope H, Wood A, Meyer E, Givens P, Hicks P, Justice S, McNair K, Pena J, Tharp D, Davis L, Ban M, Cheatum L, Darr P, Grayson W, Munford J, Whitfield B, Wilson E, Melnikoff S, Schwartz B, Tureson M, D Souza D, Forselius K, Ranganathan M, Rispoli L, Sather M, Colling C, Haakenson C, Kruegar D, Muralidhar S, Ramoni R, Breeling J, Chang K, O Donnell C, Tsao P, Moser J, Brewer J, Warren S, Argyres D, Stevens B, Humphries D, Do N, Shayan S, Nguyen X, Pyarajan S, Cho K, Hauser E, Sun Y, Wilson P, McArdle R, Dellitalia L, Harley J, Whittle J. Performance of Polygenic Risk Scores for Primary Open-Angle Glaucoma in Populations of African Descent. JAMA Ophthalmology 2025, 143: 7-14. PMID: 39541127, PMCID: PMC11565374, DOI: 10.1001/jamaophthalmol.2024.4784.Peer-Reviewed Original ResearchConceptsPrimary open-angle glaucomaEuropean ancestry groupsArea under the receiver operating characteristic curveAfrican descentSouth AfricaOpen-angle glaucomaCross-sectional studyIndividuals of African descentBaseline of ageAfrican ancestryOdds ratioGlaucoma patientsRisk stratificationMillion Veteran ProgramPolygenic risk scoresGenetics of glaucomaRisk scorePatients of African descentEuropean ancestryRisk quintileReceiver operating characteristic curveGhanaiansGhanaPopulations of African descentAmerican individuals
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 vulnerabilitySystems biology dissection of PTSD and MDD across brain regions, cell types, and blood
Daskalakis N, Iatrou A, Chatzinakos C, Jajoo A, Snijders C, Wylie D, DiPietro C, Tsatsani I, Chen C, Pernia C, Soliva-Estruch M, Arasappan D, Bharadwaj R, Collado-Torres L, Wuchty S, Alvarez V, Dammer E, Deep-Soboslay A, Duong D, Eagles N, Huber B, Huuki L, Holstein V, Logue M, Lugenbühl J, Maihofer A, Miller M, Nievergelt C, Pertea G, Ross D, Sendi M, Sun B, Tao R, Tooke J, Wolf E, Zeier Z, Berretta S, Champagne F, Hyde T, Seyfried N, Shin J, Weinberger D, Nemeroff C, Kleinman J, Ressler K, Nievergelt C, Maihofer A, Atkinson E, Chen C, Choi K, Coleman J, Daskalakis N, Duncan L, Polimanti R, Aaronson C, Amstadter A, Andersen S, Andreassen O, Arbisi P, Ashley-Koch A, Austin S, Avdibegoviç E, Babić D, Bacanu S, Baker D, Batzler A, Beckham J, Belangero S, Benjet C, Bergner C, Bierer L, Biernacka J, Bierut L, Bisson J, Boks M, Bolger E, Brandolino A, Breen G, Bressan R, Bryant R, Bustamante A, Bybjerg-Grauholm J, Bækvad-Hansen M, Børglum A, Børte S, Cahn L, Calabrese J, Caldas-de-Almeida J, Chatzinakos C, Cheema S, Clouston S, Colodro-Conde L, Coombes B, Cruz-Fuentes C, Dale A, Dalvie S, Davis L, Deckert J, Delahanty D, Dennis M, Desarnaud F, DiPietro C, Disner S, Docherty A, Domschke K, Dyb G, Kulenović A, Edenberg H, Evans A, Fabbri C, Fani N, Farrer L, Feder A, Feeny N, Flory J, Forbes D, Franz C, Galea S, Garrett M, Gelaye B, Gelernter J, Geuze E, Gillespie C, Goleva S, Gordon S, Goçi A, Grasser L, Guindalini C, Haas M, Hagenaars S, Hauser M, Heath A, Hemmings S, Hesselbrock V, Hickie I, Hogan K, Hougaard D, Huang H, Huckins L, Hveem K, Jakovljević M, Javanbakht A, Jenkins G, Johnson J, Jones I, Jovanovic T, Karstoft K, Kaufman M, Kennedy J, Kessler R, Khan A, Kimbrel N, King A, Koen N, Kotov R, Kranzler H, Krebs K, Kremen W, Kuan P, Lawford B, Lebois L, Lehto K, Levey D, Lewis C, Liberzon I, Linnstaedt S, Logue M, Lori A, Lu Y, Luft B, Lupton M, Luykx J, Makotkine I, Maples-Keller J, Marchese S, Marmar C, Martin N, Martínez-Levy G, McAloney K, McFarlane A, McLaughlin K, McLean S, Medland S, Mehta D, Meyers J, Michopoulos V, Mikita E, Milani L, Milberg W, Miller M, Morey R, Morris C, Mors O, Mortensen P, Mufford M, Nelson E, Nordentoft M, Norman S, Nugent N, O'Donnell M, Orcutt H, Pan P, Panizzon M, Pathak G, Peters E, Peterson A, Peverill M, Pietrzak R, Polusny M, Porjesz B, Powers A, Qin X, Ratanatharathorn A, Risbrough V, Roberts A, Rothbaum A, Rothbaum B, Roy-Byrne P, Ruggiero K, Rung A, Runz H, Rutten B, de Viteri S, Salum G, Sampson L, Sanchez S, Santoro M, Seah C, Seedat S, Seng J, Shabalin A, Sheerin C, Silove D, Smith A, Smoller J, Sponheim S, Stein D, Stensland S, Stevens J, Sumner J, Teicher M, Thompson W, Tiwari A, Trapido E, Uddin M, Ursano R, Valdimarsdóttir U, Van Hooff M, Vermetten E, Vinkers C, Voisey J, Wang Y, Wang Z, Waszczuk M, Weber H, Wendt F, Werge T, Williams M, Williamson D, Winsvold B, Winternitz S, Wolf C, Wolf E, Xia Y, Xiong Y, Yehuda R, Young K, Young R, Zai C, Zai G, Zervas M, Zhao H, Zoellner L, Zwart J, deRoon-Cassini T, van Rooij S, van den Heuvel L, Stein M, Ressler K, Koenen K. Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood. Science 2024, 384: eadh3707. PMID: 38781393, PMCID: PMC11203158, DOI: 10.1126/science.adh3707.Peer-Reviewed Original ResearchConceptsMajor depressive disorderPosttraumatic stress disorderMedial prefrontal cortexStudies of posttraumatic stress disorderStress-related disordersHippocampal dentate gyrusDorsolateral PFCPrefrontal cortexDepressive disorderStress disorderBrain regionsCentral nucleusDentate gyrusGenome-wide association studiesSynaptic regulationMolecular pathologyMultiomics studiesStress hormonesGene network analysisDisordersCell typesNon-neuronal cell typesSingle nucleus RNA sequencingGenomic structureFine-mappingTlr9 deficiency in B cells leads to obesity by promoting inflammation and gut dysbiosis
Wang P, Yang X, Zhang L, Sha S, Huang J, Peng J, Gu J, Pearson J, Hu Y, Zhao H, Wong F, Wang Q, Wen L. Tlr9 deficiency in B cells leads to obesity by promoting inflammation and gut dysbiosis. Nature Communications 2024, 15: 4232. PMID: 38762479, PMCID: PMC11102548, DOI: 10.1038/s41467-024-48611-8.Peer-Reviewed Original ResearchConceptsToll-like receptor 9Gut microbiotaGut microbial communityTransferred to germ-free miceB cellsGerm-free miceTLR9 deficiencyKO miceGene sequencesGerminal center B cellsMicrobial communitiesMarginal zone B cellsGut dysbiosisFollicular helper cellsSelf-DNAMetabolic homeostasisAssociated with increased frequencyPro-inflammatory stateFat tissue inflammationGutHigh-fat dietMicrobiotaHelper cellsT cellsControl miceGlis2 is an early effector of polycystin signaling and a target for therapy in polycystic kidney disease
Zhang C, Rehman M, Tian X, Pei S, Gu J, Bell T, Dong K, Tham M, Cai Y, Wei Z, Behrens F, Jetten A, Zhao H, Lek M, Somlo S. Glis2 is an early effector of polycystin signaling and a target for therapy in polycystic kidney disease. Nature Communications 2024, 15: 3698. PMID: 38693102, PMCID: PMC11063051, DOI: 10.1038/s41467-024-48025-6.Peer-Reviewed Original ResearchConceptsMouse models of autosomal dominant polycystic kidney diseaseModel of autosomal dominant polycystic kidney diseasePolycystin signalingAutosomal dominant polycystic kidney diseasePolycystin-1Polycystic kidney diseaseTreat autosomal dominant polycystic kidney diseaseGlis2Primary ciliaKidney tubule cellsSignaling pathwayMouse modelDominant polycystic kidney diseasePotential therapeutic targetTranslatomeAntisense oligonucleotidesKidney diseasePolycystinMouse kidneyFunctional effectorsCyst formationTherapeutic targetInactivationFunctional targetPharmacological targetsFine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes
Chen Z, Guo X, Tao R, Huyghe J, Law P, Fernandez-Rozadilla C, Ping J, Jia G, Long J, Li C, Shen Q, Xie Y, Timofeeva M, Thomas M, Schmit S, Díez-Obrero V, Devall M, Moratalla-Navarro F, Fernandez-Tajes J, Palles C, Sherwood K, Briggs S, Svinti V, Donnelly K, Farrington S, Blackmur J, Vaughan-Shaw P, Shu X, Lu Y, Broderick P, Studd J, Harrison T, Conti D, Schumacher F, Melas M, Rennert G, Obón-Santacana M, Martín-Sánchez V, Oh J, Kim J, Jee S, Jung K, Kweon S, Shin M, Shin A, Ahn Y, Kim D, Oze I, Wen W, Matsuo K, Matsuda K, Tanikawa C, Ren Z, Gao Y, Jia W, Hopper J, Jenkins M, Win A, Pai R, Figueiredo J, Haile R, Gallinger S, Woods M, Newcomb P, Duggan D, Cheadle J, Kaplan R, Kerr R, Kerr D, Kirac I, Böhm J, Mecklin J, Jousilahti P, Knekt P, Aaltonen L, Rissanen H, Pukkala E, Eriksson J, Cajuso T, Hänninen U, Kondelin J, Palin K, Tanskanen T, Renkonen-Sinisalo L, Männistö S, Albanes D, Weinstein S, Ruiz-Narvaez E, Palmer J, Buchanan D, Platz E, Visvanathan K, Ulrich C, Siegel E, Brezina S, Gsur A, Campbell P, Chang-Claude J, Hoffmeister M, Brenner H, Slattery M, Potter J, Tsilidis K, Schulze M, Gunter M, Murphy N, Castells A, Castellví-Bel S, Moreira L, Arndt V, Shcherbina A, Bishop D, Giles G, Southey M, Idos G, McDonnell K, Abu-Ful Z, Greenson J, Shulman K, Lejbkowicz F, Offit K, Su Y, Steinfelder R, Keku T, van Guelpen B, Hudson T, Hampel H, Pearlman R, Berndt S, Hayes R, Martinez M, Thomas S, Pharoah P, Larsson S, Yen Y, Lenz H, White E, Li L, Doheny K, Pugh E, Shelford T, Chan A, Cruz-Correa M, Lindblom A, Hunter D, Joshi A, Schafmayer C, Scacheri P, Kundaje A, Schoen R, Hampe J, Stadler Z, Vodicka P, Vodickova L, Vymetalkova V, Edlund C, Gauderman W, Shibata D, Toland A, Markowitz S, Kim A, Chanock S, van Duijnhoven F, Feskens E, Sakoda L, Gago-Dominguez M, Wolk A, Pardini B, FitzGerald L, Lee S, Ogino S, Bien S, Kooperberg C, Li C, Lin Y, Prentice R, Qu C, Bézieau S, Yamaji T, Sawada N, Iwasaki M, Le Marchand L, Wu A, Qu C, McNeil C, Coetzee G, Hayward C, Deary I, Harris S, Theodoratou E, Reid S, Walker M, Ooi L, Lau K, Zhao H, Hsu L, Cai Q, Dunlop M, Gruber S, Houlston R, Moreno V, Casey G, Peters U, Tomlinson I, Zheng W. Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes. Nature Communications 2024, 15: 3557. PMID: 38670944, PMCID: PMC11053150, DOI: 10.1038/s41467-024-47399-x.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesCredible causal variantsColorectal cancer susceptibility genesSusceptibility genesAssociation signalsAnalysis of single-cell RNA-seq dataAnalysis of whole-exome sequencing dataGenome-wide association study dataColorectal cancer risk lociSingle-cell RNA-seq dataTarget genesWhole-exome sequencing dataFunctional genomic investigationsFine-mapping analysisRNA-seq dataExome sequencing dataTissue-specific transcriptomesColorectal cancerCancer susceptibility genesCausal variantsFine-mappingRisk lociMethylome dataSequence dataGenomic investigationsClustering-aided prediction of outcomes in patients with idiopathic pulmonary fibrosis
Wang L, Wu P, Liu Y, Patel D, Leonard T, Zhao H. Clustering-aided prediction of outcomes in patients with idiopathic pulmonary fibrosis. Respiratory Research 2024, 25: 383. PMID: 39443991, PMCID: PMC11515489, DOI: 10.1186/s12931-024-03015-6.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisProgression of idiopathic pulmonary fibrosisMatrix metalloproteinase-9IPF-PRO RegistryClinical factorsC-indexPulmonary fibrosisBlood biomarkersMedian Follow-UpVascular cell adhesion protein 1Area under the curveHarrell's C-indexSurfactant protein DPredictive of outcomeClinical characteristicsComposite outcomeFollow-upCarcinoembryonic antigenCox regressionMetalloproteinase-9Disease progressionProtein DAverage C-indexPatientsCirculating proteins
2023
A genome-wide association study of frailty identifies significant genetic correlation with neuropsychiatric, cardiovascular, and inflammation pathways
Ye Y, Noche R, Szejko N, Both C, Acosta J, Leasure A, Brown S, Sheth K, Gill T, Zhao H, Falcone G. A genome-wide association study of frailty identifies significant genetic correlation with neuropsychiatric, cardiovascular, and inflammation pathways. GeroScience 2023, 45: 2511-2523. PMID: 36928559, PMCID: PMC10651618, DOI: 10.1007/s11357-023-00771-z.Peer-Reviewed Original ResearchConceptsFried frailty scoreBiology of frailtyEuropean descent participantsOccurrence of frailtyGenome-wide association studiesMendelian randomization analysisFrailty scoreChronic painJoint disordersPolygenic risk scoresRespiratory diseaseInflammation pathwaysRisk scoreClinical phenotypeBrain tissueCausal associationFrailtyAge-related pathwaysRandomization analysisGenetic factorsAssociation studiesUK BiobankRetirement StudyPerson's vulnerabilitySignificant genetic correlations
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