2025
Genome-wide meta-analysis identifies nine loci to be associated with higher risk of hepatocellular carcinoma development.
Ghouse J, Gellert-Kristensen H, O’Rourke C, Seidelin A, Thorleifsson G, Sveinbjörnsson G, Tragante V, Konkwo C, Brancale J, Vilarinho S, Eyrich T, Ahlberg G, Bundgaard J, Rand S, Lundegaard P, Sørensen E, Mikkelsen C, Træholt J, Erikstrup C, Dinh K, Bruun M, Jensen B, Bay J, Brunak S, Banasik K, Ullum H, Consortium E, Laisk T, Mägi R, Nadauld L, Knowlton K, Knight S, Gluud L, Vistisen K, Björnsson E, Ulfarsson M, Sulem P, Holm H, Pedersen O, Ostrowski S, Gudbjartsson D, Rafnar T, Stefansson K, Lassen U, Pommergaard H, Hillingsø J, Andersen J, Bundgaard H, Stender S. Genome-wide meta-analysis identifies nine loci to be associated with higher risk of hepatocellular carcinoma development. JHEP Reports 2025, 101485. DOI: 10.1016/j.jhepr.2025.101485.Peer-Reviewed Original ResearchGenome-wide association studiesAssociated with higher riskGenome-wide statistical significanceIncident hepatocellular carcinomaMendelian randomization analysisGenome-wide meta-analysisIdentified variantsPer-allele effectsMeta-analysisMendelian randomizationGenetic risk lociPrevalent obesityRandomization analysisAlcohol intakeMeta-analysesRisk lociAssociation studiesRisk factorsGenetic variantsGenetic underpinningsRisk of hepatocellular carcinomaLociGenetic effectsCohortConcordant effectsPsychiatric genetics in the diverse landscape of Latin American populations
Bruxel E, Rovaris D, Belangero S, Chavarría-Soley G, Cuellar-Barboza A, Martínez-Magaña J, Nagamatsu S, Nievergelt C, Núñez-Ríos D, Ota V, Peterson R, Sloofman L, Adams A, Albino E, Alvarado A, Andrade-Brito D, Arguello-Pascualli P, Bandeira C, Bau C, Bulik C, Buxbaum J, Cappi C, Corral-Frias N, Corrales A, Corsi-Zuelli F, Crowley J, Cupertino R, da Silva B, De Almeida S, De la Hoz J, Forero D, Fries G, Gelernter J, González-Giraldo Y, Grevet E, Grice D, Hernández-Garayua A, Hettema J, Ibáñez A, Ionita-Laza I, Lattig M, Lima Y, Lin Y, López-León S, Loureiro C, Martínez-Cerdeño V, Martínez-Levy G, Melin K, Moreno-De-Luca D, Muniz Carvalho C, Olivares A, Oliveira V, Ormond R, Palmer A, Panzenhagen A, Passos-Bueno M, Peng Q, Pérez-Palma E, Prieto M, Roussos P, Sanchez-Roige S, Santamaría-García H, Shansis F, Sharp R, Storch E, Tavares M, Tietz G, Torres-Hernández B, Tovo-Rodrigues L, Trelles P, Trujillo-ChiVacuan E, Velásquez M, Vera-Urbina F, Voloudakis G, Wegman-Ostrosky T, Zhen-Duan J, Zhou H, Santoro M, Nicolini H, Atkinson E, Giusti-Rodríguez P, Montalvo-Ortiz J. Psychiatric genetics in the diverse landscape of Latin American populations. Nature Genetics 2025, 57: 1074-1088. PMID: 40175716, PMCID: PMC12133068, DOI: 10.1038/s41588-025-02127-z.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesPsychiatric genomicsPsychiatric genome-wide association studiesLarge-scale genome-wide association studiesGenetic risk lociNon-European populationsGenetic diversityRisk lociGenetic admixtureBurden of psychiatric disordersAssociation studiesPsychiatric disordersEuropean ancestryPsychiatric geneticsGenomeHealthcare disparitiesConsortium effortLatin American populationsPromote equityEnvironmental factorsDiversityAmerican populationDiverse landscapeLociAncestrySex‐Specific Association Between Polymorphisms in Estrogen Receptor Alpha Gene (ESR1) and Depression: A Genome‐Wide Association Study of All of Us and UK Biobank Data
Hu Y, Che M, Zhang H. Sex‐Specific Association Between Polymorphisms in Estrogen Receptor Alpha Gene (ESR1) and Depression: A Genome‐Wide Association Study of All of Us and UK Biobank Data. Genetic Epidemiology 2025, 49: e70004. PMID: 40007508, PMCID: PMC11924109, DOI: 10.1002/gepi.70004.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesSingle-nucleotide polymorphismsAssociation studiesAlpha geneEstrogen receptor alpha geneGenetic risk factorsRisk lociGenomic associationsMajor depressive disorderMDD phenotypesGenetic studiesGenetic associationRisk factors of MDDGenesESR1 geneUK BiobankESR1Participant genotypesPolymorphismSex-specificSex-specific associationsDepressive disorderRacial/ethnic disparitiesFindings lack consistencyLength of life
2024
Epigenomics and single cell CRISPR screening to investigate the risk‐modifying role of microglia in Alzheimer’s disease and multiple sclerosis
Gallagher M, Du W, Hazel K, Aydin Z, Cheng Y, Yuan B, Bell G, Young R, Jaenisch R, Corradin O. Epigenomics and single cell CRISPR screening to investigate the risk‐modifying role of microglia in Alzheimer’s disease and multiple sclerosis. Alzheimer's & Dementia 2024, 20: e093591. PMCID: PMC11710746, DOI: 10.1002/alz.093591.Peer-Reviewed Original ResearchSingle nucleotide polymorphismsRisk lociMS risk lociEnhancer landscapeSingle cell screeningCell type-specific enhancersGenome-wide association studiesMicroglia-specific enhancersH3K27ac ChIP-seqNeurodegenerative diseasesCell type-specificEx vivo microgliaSNP enrichmentChIP-seqHi-C.CRISPRi screenEnhancer/promoter interactionNoncoding regionsRNA-seqAssociation studiesCRISPR screensCRISPRiNucleotide polymorphismsSafe harbor locusCell screeningPolygenic Risk of Epilepsy and Poststroke Epilepsy
Clocchiatti-Tuozzo S, Rivier C, Misra S, Zelano J, Mazumder R, Sansing L, de Havenon A, Hirsch L, Liebeskind D, Gilmore E, Sheth K, Kim J, Worrall B, Falcone G, Mishra N. Polygenic Risk of Epilepsy and Poststroke Epilepsy. Stroke 2024, 55: 2835-2843. PMID: 39502073, PMCID: PMC11653790, DOI: 10.1161/strokeaha.124.047459.Peer-Reviewed Original ResearchParticipants of European ancestryRisk of poststroke epilepsyPolygenic riskPoststroke epilepsyEuropean ancestryGenome-wide association study meta-analysisPRS decileCase-control genetic association studyGenetic risk lociLowest decilePolygenic risk scoresGenetic association studiesMultivariate logistic regression modelStudy meta-analysisMultivariate logistic regression resultsHistory of strokeLogistic regression modelsRisk lociAssociation studiesStroke survivorsUK BiobankGenetic informationGenetic ancestryLogistic regression resultsGenetic variantsGenome-Wide Association Study of Acute Lymphoblastic Leukemia in Hispanic/Latino Children Identifies a Putatively Novel Risk Locus at Chromosome 5q31.1
Liu T, Langie J, Yang W, Morimoto L, Ma X, Metayer C, Lupo P, Scheurer M, Yang J, Wiemels J, Chiang C, de Smith A. Genome-Wide Association Study of Acute Lymphoblastic Leukemia in Hispanic/Latino Children Identifies a Putatively Novel Risk Locus at Chromosome 5q31.1. Blood 2024, 144: 317. DOI: 10.1182/blood-2024-208796.Peer-Reviewed Original ResearchGenome-wide association studiesMulti-Ethnic Study of AtherosclerosisCalifornia Childhood Leukemia StudySingle nucleotide polymorphismsMinor allele frequencyRisk lociHispanic/Latino individualsHispanic/Latino populationFixed-effect inverse-variance weighted meta-analysisMeta-analysis genome-wide association studyInverse-variance weighted meta-analysisHispanic Community Health Study/Study of LatinosHispanic Community Health Study/StudyHigher risk of acute lymphoblastic leukemiaHigher risk allele frequencyOdds of acute lymphoblastic leukemiaGenome-wide significant association signalsImputation quality scoreSNPs' minor allele frequencyRisk of acute lymphoblastic leukemiaGenome-wide significance thresholdAcute lymphoblastic leukemia riskEuropean ancestry populationsGenome-wide imputationMulti-Ethnic Study94. THE GENETIC ARCHITECTURE OF MOOD AND ANXIETY DISORDER SYMPTOMS
Schultz L, Mollon J, Jacquemont S, Almasy L, Glahn D. 94. THE GENETIC ARCHITECTURE OF MOOD AND ANXIETY DISORDER SYMPTOMS. European Neuropsychopharmacology 2024, 87: 100. DOI: 10.1016/j.euroneuro.2024.08.208.Peer-Reviewed Original ResearchEuropean ancestryPrefrontal cortexPsychiatric diagnosisGene set analysisAssociated with genesInverse-variance weighted meta-analysisICD-10 psychiatric diagnosisMeta-analysisAnxiety disorder symptomsUK Biobank (UKBMulti-ancestry meta-analysisGenome-wide significant variantsGenetic architectureRisk lociMSigDB geneChromosome 8Confirmatory factor modelsGenomic risk lociEuropean ancestry individualsAnxiety disordersDisorder symptomsMood/anxiety symptomsIdentified risk lociDopamine receptorsFrontal cortexEXPLORING THE IMMUNOGENETIC BASIS OF POST-TRAUMATIC STRESS DISORDER
Braun A, Maihofer A, Katrinli S, Panagiotaropoulou G, Levey D, Ripke S, Gelernter J, Nievergelt C, Group P. EXPLORING THE IMMUNOGENETIC BASIS OF POST-TRAUMATIC STRESS DISORDER. European Neuropsychopharmacology 2024, 87: 4-5. DOI: 10.1016/j.euroneuro.2024.08.017.Peer-Reviewed Original ResearchGenome-wide association studiesAssociation analysisPost-traumatic stress disorderMajor histocompatibility complexHuman leukocyte antigen imputationComplex linkage disequilibrium structureGenomes reference panelLinkage disequilibrium structureMajor histocompatibility complex class III regionRisk-conferring allelesClass III regionPsychiatric Genomics ConsortiumHuman leukocyte antigen allelesMillion Veteran ProgramDisequilibrium structureLatin American ancestryRisk lociRisk-conferring variantsCross-ancestryAssociation studiesPopulation stratificationReference panelGenetic variantsSusceptibility to post-traumatic stress disorderAmerican ancestryPOST-GWAS FOR PTSD: FROM RISK LOCI TO BIOLOGICAL MEANING
Nievergelt C, Ongeri L, Gelernter J. POST-GWAS FOR PTSD: FROM RISK LOCI TO BIOLOGICAL MEANING. European Neuropsychopharmacology 2024, 87: 2-3. DOI: 10.1016/j.euroneuro.2024.08.013.Peer-Reviewed Original ResearchPosttraumatic stress disorderPGC-PTSDLocal ancestry inferencePTSD associationsRisk lociPosttraumatic stress disorder casenessThreat-related processingGenome-wide association study resultsCo-morbid disordersComplex patterns of admixtureStress-related disordersMental health disordersPatterns of admixturePotential causal genesMajor histocompatibility complexMental health consequencesAssociation study resultsMDD patientsMulti-omics approachStress disorderMulti-omics studiesHuman leukocyte antigenAncestry inferenceAdmixed individualsMDDW32. A GENOME-WIDE ASSOCIATION STUDY OF BIPOLAR DISORDER FROM INDIA
Mahadevan J, Holla B, Ganesh S, Shankarappa B, Paul P, Sud R, Jain S, Purushottam M, Viswanath B. W32. A GENOME-WIDE ASSOCIATION STUDY OF BIPOLAR DISORDER FROM INDIA. European Neuropsychopharmacology 2024, 87: 118. DOI: 10.1016/j.euroneuro.2024.08.241.Peer-Reviewed Original ResearchGenome-wide association studiesGenomic risk lociRisk lociAssociation studiesGenome-wide association study of BDGenome wide association studiesAncestry principal componentsSevere mental illnessWhole-genome sequencingTissue expression analysisBiology of BdPatients of European ancestryBipolar disorderHRC panelGenome sequenceMental illnessAncestry samplesGenomic methodsEpisodes of depressionAllele dosageGenetic studiesEuropean ancestryICD-10Outpatient clinicTrained psychiatristsDiversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program
Verma A, Huffman J, Rodriguez A, Conery M, Liu M, Ho Y, Kim Y, Heise D, Guare L, Panickan V, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner D, Sangar R, Murray M, Wang X, Dochtermann D, Devineni P, Shi Y, Nandi T, Assimes T, Brunette C, Carroll R, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar S, Joseph J, Kember R, Kranzler H, Kripke C, Levey D, Luoh S, Merritt V, Overstreet C, Deak J, Grant S, Polimanti R, Roussos P, Shakt G, Sun Y, Tsao N, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao P, O'Donnell C, Muralidhar S, Moser J, Casas J, Bick A, Zhou W, Cai T, Voight B, Cho K, Gaziano J, Madduri R, Damrauer S, Liao K. Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. Science 2024, 385: eadj1182. PMID: 39024449, DOI: 10.1126/science.adj1182.Peer-Reviewed Original ResearchConceptsMillion Veteran ProgramNon-European populationsVeteran ProgramGenetic architectureAtlas of genetic associationsVeterans Affairs Million Veteran ProgramVA Million Veteran ProgramGenomic risk lociGenome-wide associationHuman genetic studiesHealth disparitiesUnited States veteransCausal variantsRisk lociGenetic insightsGenetic studiesGenetic associationGenetic causeStates veteransDiverse populationsDisease factorsLack of inclusionLongitudinal studyParticipantsTraitsGenome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations
Gelernter J, Levey D, Galimberti M, Harrington K, Zhou H, Adhikari K, Gupta P, Program V, Gaziano J, Eliott D, Stein M. Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations. Cell Genomics 2024, 4: 100582. PMID: 38870908, PMCID: PMC11228954, DOI: 10.1016/j.xgen.2024.100582.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesMillion Veteran ProgramRisk lociAssociation studiesTrans-ancestry meta-analysisSignificant risk lociPathway enrichment analysisEpiretinal membraneTrans-ancestryGenome-wideMultiple traitsGenetic associationEnrichment analysisGene expressionEuropean AmericansLoss of visual acuityVeteran ProgramGenetic correlationsLociBiological mechanismsAmerican populationVisual acuityRetinal conditionsControl individualsRetinal surfaceSupervised latent factor modeling isolates cell-type-specific transcriptomic modules that underlie Alzheimer’s disease progression
Hodgson L, Li Y, Iturria-Medina Y, Stratton J, Wolf G, Krishnaswamy S, Bennett D, Bzdok D. Supervised latent factor modeling isolates cell-type-specific transcriptomic modules that underlie Alzheimer’s disease progression. Communications Biology 2024, 7: 591. PMID: 38760483, PMCID: PMC11101463, DOI: 10.1038/s42003-024-06273-8.Peer-Reviewed Original ResearchConceptsGene programAlzheimer's diseaseLate-onset Alzheimer's diseaseAD risk lociCell type-specificSingle-nucleus RNA sequencingRisk lociAD brainAlzheimer's disease progressionSnRNA-seqRNA sequencingAD pathophysiologySignaling cascadesTranscriptome modulationProgressive neurodegenerative diseaseCell-typeGWASNeurodegenerative diseasesNeuronal lossGlial cellsTranscriptomeLociGenesPseudo-trajectoriesDisease progressionIntegrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions
Dareng E, Coetzee S, Tyrer J, Peng P, Rosenow W, Chen S, Davis B, Dezem F, Seo J, Nameki R, Reyes A, Aben K, Anton-Culver H, Antonenkova N, Aravantinos G, Bandera E, Freeman L, Beckmann M, Beeghly-Fadiel A, Benitez J, Bernardini M, Bjorge L, Black A, Bogdanova N, Bolton K, Brenton J, Budzilowska A, Butzow R, Cai H, Campbell I, Cannioto R, Chang-Claude J, Chanock S, Chen K, Chenevix-Trench G, Group A, Chiew Y, Cook L, DeFazio A, Dennis J, Doherty J, Dörk T, du Bois A, Dürst M, Eccles D, Ene G, Fasching P, Flanagan J, Fortner R, Fostira F, Gentry-Maharaj A, Giles G, Goodman M, Gronwald J, Haiman C, Håkansson N, Heitz F, Hildebrandt M, Høgdall E, Høgdall C, Huang R, Jensen A, Jones M, Kang D, Karlan B, Karnezis A, Kelemen L, Kennedy C, Khusnutdinova E, Kiemeney L, Kjaer S, Kupryjanczyk J, Labrie M, Lambrechts D, Larson M, Le N, Lester J, Li L, Lubiński J, Lush M, Marks J, Matsuo K, May T, McLaughlin J, McNeish I, Menon U, Missmer S, Modugno F, Moffitt M, Monteiro A, Moysich K, Narod S, Nguyen-Dumont T, Odunsi K, Olsson H, Onland-Moret N, Park S, Pejovic T, Permuth J, Piskorz A, Prokofyeva D, Riggan M, Risch H, Rodríguez-Antona C, Rossing M, Sandler D, Setiawan V, Shan K, Song H, Southey M, Steed H, Sutphen R, Swerdlow A, Teo S, Terry K, Thompson P, Thomsen L, Titus L, Trabert B, Travis R, Tworoger S, Valen E, Van Nieuwenhuysen E, Edwards D, Vierkant R, Webb P, Group O, Weinberg C, Weise R, Wentzensen N, White E, Winham S, Wolk A, Woo Y, Wu A, Yan L, Yannoukakos D, Zeinomar N, Zheng W, Ziogas A, Berchuck A, Goode E, Huntsman D, Pearce C, Ramus S, Sellers T, Consortium T, Freedman M, Lawrenson K, Schildkraut J, Hazelett D, Plummer J, Kar S, Jones M, Pharoah P, Gayther S. Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions. American Journal Of Human Genetics 2024, 111: 1061-1083. PMID: 38723632, PMCID: PMC11179261, DOI: 10.1016/j.ajhg.2024.04.011.Peer-Reviewed Original ResearchTranscriptome-wide association studyRisk lociAssociation studiesTranscription factor ChIP-seqSusceptibility genesGenome-wide association analysisGenome-wide association studiesCausal risk variantsControls of European originTranscriptome-wide associationEpithelial ovarian cancerVariant Effect PredictorIntegrative multi-omics analysisMulti-omics analysisChIP-seqChromatin marksGenomic regionsFine-mappingSusceptibility lociInteractome analysisAssociation analysisEpithelial ovarian cancer histotypesRisk variantsTissue-specificLociGenome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder
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. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder. Nature Genetics 2024, 56: 792-808. PMID: 38637617, PMCID: PMC11396662, DOI: 10.1038/s41588-024-01707-9.Peer-Reviewed Original ResearchConceptsMeta-analysis of genome-wide association studiesGenome-wide significant lociMulti-ancestry meta-analysisGenome-wide association analysisGenome-wide association studiesIndividuals of European ancestryPotential causal genesNative American ancestryMulti-omics approachPost-traumatic stress disorderAdmixed individualsSignificant lociRisk lociCausal genesAssociation studiesAssociation analysisFunctional genesTranscription factorsGenetic studiesAmerican ancestryEuropean ancestryAxon guidanceSynaptic structureLociGenesMulti-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes
Toikumo S, Jennings M, Pham B, Lee H, Mallard T, Bianchi S, Meredith J, Vilar-Ribó L, Xu H, Hatoum A, Johnson E, Pazdernik V, Jinwala Z, Pakala S, Leger B, Niarchou M, Ehinmowo M, Jenkins G, Batzler A, Pendegraft R, Palmer A, Zhou H, Biernacka J, Coombes B, Gelernter J, Xu K, Hancock D, Cox N, Smoller J, Davis L, Justice A, Kranzler H, Kember R, Sanchez-Roige S. Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes. Nature Human Behaviour 2024, 8: 1177-1193. PMID: 38632388, PMCID: PMC11199106, DOI: 10.1038/s41562-024-01851-6.Peer-Reviewed Original ResearchConceptsTobacco use disorderPotential risk genesMulti-ancestry meta-analysisMultiple health outcomesElectronic health recordsSource of phenotypic informationGenome-wide association studiesUse disorderAscertainment cohortHealth outcomesHealth recordsPrevalent substance use disordersRisk genesIndependent risk lociUK BiobankSubstance use disordersSmoking behaviorMedical outcomesFunctional genomics toolsPsychiatric traitsAssociation studiesRisk lociRisk variantsHeart diseaseGenomic toolsGenetics of IgA nephrology: risks, mechanisms, and therapeutic targets
Qu S, Zhou X, Zhang H. Genetics of IgA nephrology: risks, mechanisms, and therapeutic targets. Pediatric Nephrology 2024, 39: 3157-3165. PMID: 38600219, DOI: 10.1007/s00467-024-06369-7.Peer-Reviewed Original ResearchGenome-wide association studiesPopulation-based genome-wide association studiesComplex multifactorial traitsPolygenic risk scoresRisk lociAssociation studiesTherapeutic targetMultifactorial traitGenetic explorationGenetic researchGenetic causationMolecular mechanismsRisk scoreElevated serum Gd-IgA1 levelsIncreased riskPathogenesis modelGroup of individualsSerum Gd-IgA1 levelsGd-IgA1 levelsMedical treatmentLociGalactose-deficient IgA1RiskGeneticsGd-IgA1Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression
Tian R, Ge T, Kweon H, Rocha D, Lam M, Liu J, Singh K, Levey D, Gelernter J, Stein M, Tsai E, Huang H, Chabris C, Lencz T, Runz H, Chen C. Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression. Nature Communications 2024, 15: 1755. PMID: 38409228, PMCID: PMC10897433, DOI: 10.1038/s41467-024-45774-2.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesRare coding variantsWhole-exome sequencingGenetic architectureGenetic relationshipsLoss-of-function intolerant genesContribution of rare coding variantsRare damagingAssociated with risk of depressionElectronic health recordsUK Biobank participantsPolygenic risk scoresRisk of depressionAssociated with riskIntolerant genesRisk lociAssociation studiesCoding variantsBiobank participantsHealth recordsUK BiobankDepression definitionsDepression riskBurden analysisRare variants
2023
An Update on the Genetics of IgA Nephropathy
Xu L, Zhou X, Zhang H. An Update on the Genetics of IgA Nephropathy. Journal Of Clinical Medicine 2023, 13: 123. PMID: 38202130, PMCID: PMC10780034, DOI: 10.3390/jcm13010123.Peer-Reviewed Original ResearchGenome-wide association studiesWhole-genome sequencingEnd-stage kidney diseaseCandidate causal variantsNext-generation sequencing technologiesInvolvement of epigeneticsPathogenesis of IgANFine-mapping studiesPathogenic molecular pathwaysGenetic architectureSequencing technologiesCausal variantsRisk lociAssociation studiesGenetic studiesNew potential therapeutic targetsMolecular pathwaysImmunoglobulin A (IgA) nephropathyPhenotypic variabilityPotential pathogenic mechanismsDevelopment of IgANPotential therapeutic targetComplexity of pathogenesisLinkage studiesExome sequencingGenome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability
Holen B, Kutrolli G, Shadrin A, Icick R, Hindley G, Rødevand L, O'Connell K, Frei O, Parker N, Tesfaye M, Deak J, Jahołkowski P, Dale A, Djurovic S, Andreassen O, Smeland O. Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability. Drug And Alcohol Dependence 2023, 256: 111058. PMID: 38244365, PMCID: PMC11831617, DOI: 10.1016/j.drugalcdep.2023.111058.Peer-Reviewed Original ResearchGenetic basisBivariate causal mixture modelRisk lociGenome-wide analysisNovel risk lociNegative genetic correlationSpecific genetic lociUnderlying molecular mechanismsGenetic risk architectureSpecific genetic variantsGenetic architectureGenetic lociBiological functionsMolecular mechanismsGenetic relationshipsLociGenetic correlationsGenetic variantsGenetic overlapRisk architectureConjunctional FDRNew insightsRecent studiesBiological substratesGenes
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