2021
A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer
López de Maturana E, Rodríguez JA, Alonso L, Lao O, Molina-Montes E, Martín-Antoniano IA, Gómez-Rubio P, Lawlor R, Carrato A, Hidalgo M, Iglesias M, Molero X, Löhr M, Michalski C, Perea J, O’Rorke M, Barberà VM, Tardón A, Farré A, Muñoz-Bellvís L, Crnogorac-Jurcevic T, Domínguez-Muñoz E, Gress T, Greenhalf W, Sharp L, Arnes L, Cecchini L, Balsells J, Costello E, Ilzarbe L, Kleeff J, Kong B, Márquez M, Mora J, O’Driscoll D, Scarpa A, Ye W, Yu J, García-Closas M, Kogevinas M, Rothman N, Silverman D, Albanes D, Arslan A, Beane-Freeman L, Bracci P, Brennan P, Bueno-de-Mesquita B, Buring J, Canzian F, Du M, Gallinger S, Gaziano J, Goodman P, Gunter M, LeMarchand L, Li D, Neale R, Peters U, Petersen G, Risch H, Sánchez M, Shu X, Thornquist M, Visvanathan K, Zheng W, Chanock S, Easton D, Wolpin B, Stolzenberg-Solomon R, Klein A, Amundadottir L, Marti-Renom M, Real F, Malats N. A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer. Genome Medicine 2021, 13: 15. PMID: 33517887, PMCID: PMC7849104, DOI: 10.1186/s13073-020-00816-4.Peer-Reviewed Original ResearchConceptsSilico functional analysisFunctional analysisPublic genomic informationUnfolded protein responseMeta-analysis p-valueLow-frequency variantsPc locusGWAS hitsGenomic informationPhenotypic varianceProtein responseSpatial autocorrelation analysisER stressMajor regulatorFrequency variantsPancreatic acinar cellsGenetic susceptibilityCandidate variantsFactor interplayComplex diseasesIndependent variantsGWASInherited basisLow p-valuesAcinar cells
2017
Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence
Liu G, Mukherjee B, Lee S, Lee AW, Wu AH, Bandera EV, Jensen A, Rossing MA, Moysich KB, Chang-Claude J, Doherty JA, Gentry-Maharaj A, Kiemeney L, Gayther SA, Modugno F, Massuger L, Goode EL, Fridley BL, Terry KL, Cramer DW, Ramus SJ, Anton-Culver H, Ziogas A, Tyrer JP, Schildkraut JM, Kjaer SK, Webb PM, Ness RB, Menon U, Berchuck A, Pharoah PD, Risch H, Pearce CL, Consortium F. Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence. American Journal Of Epidemiology 2017, 187: 366-377. PMID: 28633381, PMCID: PMC5860584, DOI: 10.1093/aje/kwx243.Peer-Reviewed Original Research
2016
Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data
Shi J, Park JH, Duan J, Berndt ST, Moy W, Yu K, Song L, Wheeler W, Hua X, Silverman D, Garcia-Closas M, Hsiung CA, Figueroa JD, Cortessis VK, Malats N, Karagas MR, Vineis P, Chang IS, Lin D, Zhou B, Seow A, Matsuo K, Hong YC, Caporaso NE, Wolpin B, Jacobs E, Petersen GM, Klein AP, Li D, Risch H, Sanders AR, Hsu L, Schoen RE, Brenner H, , , , , , , Stolzenberg-Solomon R, Gejman P, Lan Q, Rothman N, Amundadottir LT, Landi MT, Levinson DF, Chanock SJ, Chatterjee N. Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data. PLOS Genetics 2016, 12: e1006493. PMID: 28036406, PMCID: PMC5201242, DOI: 10.1371/journal.pgen.1006493.Peer-Reviewed Original Research