2025
The 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 basis
2024
Fine-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 investigations
2022
SCADIE: simultaneous estimation of cell type proportions and cell type-specific gene expressions using SCAD-based iterative estimating procedure
Tang D, Park S, Zhao H. SCADIE: simultaneous estimation of cell type proportions and cell type-specific gene expressions using SCAD-based iterative estimating procedure. Genome Biology 2022, 23: 129. PMID: 35706040, PMCID: PMC9199219, DOI: 10.1186/s13059-022-02688-w.Peer-Reviewed Original ResearchConceptsCell type-specific gene expressionType-specific gene expressionCell type proportionsDifferential expression analysisCell type-specific gene expression profilesExpression analysisGene expressionSingle-cell RNA-seq dataRNA-seq dataGene differential expression analysisGene expression profilesType proportionsExpression profilesExpressionGenesCells
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply