2023
Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions
Lindström S, Wang L, Feng H, Majumdar A, Huo S, Macdonald J, Harrison T, Turman C, Chen H, Mancuso N, Bammler T, Consortium B, Gallinger S, Gruber S, Gunter M, Le Marchand L, Moreno V, Offit K, Study G, De Vivo I, O’Mara T, Spurdle A, Tomlinson I, Consortium E, Fitzgerald R, Gharahkhani P, Gockel I, Jankowski J, Macgregor S, Schumacher J, Barnholtz-Sloan J, Bondy M, Houlston R, Jenkins R, Melin B, Wrensch M, Brennan P, Christiani D, Johansson M, Mckay J, Aldrich M, Amos C, Landi M, Tardon A, Consortium I, Bishop D, Demenais F, Goldstein A, Iles M, Kanetsky P, Law M, Consortium O, Amundadottir L, Stolzenberg-Solomon R, Wolpin B, Consortium P, Klein A, Petersen G, Risch H, Consortium T, Chanock S, Purdue M, Scelo G, Pharoah P, Kar S, Hung R, Pasaniuc B, Kraft P. Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions. Journal Of The National Cancer Institute 2023, 115: 712-732. PMID: 36929942, PMCID: PMC10248849, DOI: 10.1093/jnci/djad043.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesTranscriptome-wide association studyCancer susceptibility lociGenome-wide genetic correlationSusceptibility lociAssociation studiesMultiple cancer typesCancer genome-wide association studyGenome-wide analysisCross-disease analysisGenetic correlationsSusceptibility regionsGWAS summary statisticsCancer typesGenetic risk variantsDistinct lociCancer heritabilityLociRisk variantsGenetic contributionEuropean ancestryPleiotropyAdditional regionsDifferent cancersHeritability
2020
Genome-Wide Gene–Diabetes and Gene–Obesity Interaction Scan in 8,255 Cases and 11,900 Controls from PanScan and PanC4 Consortia
Tang H, Jiang L, Stolzenberg-Solomon RZ, Arslan AA, Beane Freeman LE, Bracci PM, Brennan P, Canzian F, Du M, Gallinger S, Giles GG, Goodman PJ, Kooperberg C, Le Marchand L, Neale RE, Shu XO, Visvanathan K, White E, Zheng W, Albanes D, Andreotti G, Babic A, Bamlet WR, Berndt SI, Blackford A, Bueno-de-Mesquita B, Buring JE, Campa D, Chanock SJ, Childs E, Duell EJ, Fuchs C, Gaziano JM, Goggins M, Hartge P, Hassam MH, Holly EA, Hoover RN, Hung RJ, Kurtz RC, Lee IM, Malats N, Milne RL, Ng K, Oberg AL, Orlow I, Peters U, Porta M, Rabe KG, Rothman N, Scelo G, Sesso HD, Silverman DT, Thompson IM, Tjønneland A, Trichopoulou A, Wactawski-Wende J, Wentzensen N, Wilkens LR, Yu H, Zeleniuch-Jacquotte A, Amundadottir LT, Jacobs EJ, Petersen GM, Wolpin BM, Risch HA, Chatterjee N, Klein AP, Li D, Kraft P, Wei P. Genome-Wide Gene–Diabetes and Gene–Obesity Interaction Scan in 8,255 Cases and 11,900 Controls from PanScan and PanC4 Consortia. Cancer Epidemiology Biomarkers & Prevention 2020, 29: 1784-1791. PMID: 32546605, PMCID: PMC7483330, DOI: 10.1158/1055-9965.epi-20-0275.Peer-Reviewed Original ResearchConceptsSNP levelGenome-wide association study datasetGenome-wide levelGene-based analysisGWAS summary statisticsJoint effect testsGxE analysisGWAS top hitsPopulation substructureSignificant GxE interactionGene levelGene-environment interaction analysisAdditional genetic factorsTop hitsEnvironmental variablesGenetic variantsDiabetes/obesityGxE interactionsPancreatic cancerStudy sitesGenetic factorsMajor modifiable risk factorHit regionsModifiable risk factorsInteraction analysis