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1. Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Author

Zhishan Chen, Xingyi Guo, Ran Tao, Jeroen R. Huyghe, Philip J. Law, Ceres Fernandez-Rozadilla, Jie Ping, Guochong Jia, Jirong Long, Chao Li, Quanhu Shen, Yuhan Xie, Maria N. Timofeeva, Minta Thomas, Stephanie L. Schmit, Virginia Díez-Obrero, Matthew Devall, Ferran Moratalla-Navarro, Juan Fernandez-Tajes, Claire Palles, Kitty Sherwood, Sarah E. W. Briggs, Victoria Svinti, Kevin Donnelly, Susan M. Farrington, James Blackmur, Peter G. Vaughan-Shaw, Xiao-Ou Shu, Yingchang Lu, Peter Broderick, James Studd, Tabitha A. Harrison, David V. Conti, Fredrick R. Schumacher, Marilena Melas, Gad Rennert, Mireia Obón-Santacana, Vicente Martín-Sánchez, Jae Hwan Oh, Jeongseon Kim, Sun Ha Jee, Keum Ji Jung, Sun-Seog Kweon, Min-Ho Shin, Aesun Shin, Yoon-Ok Ahn, Dong-Hyun Kim, Isao Oze, Wanqing Wen, Keitaro Matsuo, Koichi Matsuda, Chizu Tanikawa, Zefang Ren, Yu-Tang Gao, Wei-Hua Jia, John L. Hopper, Mark A. Jenkins, Aung Ko Win, Rish K. Pai, Jane C. Figueiredo, Robert W. Haile, Steven Gallinger, Michael O. Woods, Polly A. Newcomb, David Duggan, Jeremy P. Cheadle, Richard Kaplan, Rachel Kerr, David Kerr, Iva Kirac, Jan Böhm, Jukka-Pekka Mecklin, Pekka Jousilahti, Paul Knekt, Lauri A. Aaltonen, Harri Rissanen, Eero Pukkala, Johan G. Eriksson, Tatiana Cajuso, Ulrika Hänninen, Johanna Kondelin, Kimmo Palin, Tomas Tanskanen, Laura Renkonen-Sinisalo, Satu Männistö, Demetrius Albanes, Stephanie J. Weinstein, Edward Ruiz-Narvaez, Julie R. Palmer, Daniel D. Buchanan, Elizabeth A. Platz, Kala Visvanathan, Cornelia M. Ulrich, Erin Siegel, Stefanie Brezina, Andrea Gsur, Peter T. Campbell, Jenny Chang-Claude, Michael Hoffmeister, Hermann Brenner, Martha L. Slattery, John D. Potter, Kostas K. Tsilidis, Matthias B. Schulze, Marc J. Gunter, Neil Murphy, Antoni Castells, Sergi Castellví-Bel, Leticia Moreira, Volker Arndt, Anna Shcherbina, D. Timothy Bishop, Graham G. Giles, Melissa C. Southey, Gregory E. Idos, Kevin J. McDonnell, Zomoroda Abu-Ful, Joel K. Greenson, Katerina Shulman, Flavio Lejbkowicz, Kenneth Offit, Yu-Ru Su, Robert Steinfelder, Temitope O. Keku, Bethany van Guelpen, Thomas J. Hudson, Heather Hampel, Rachel Pearlman, Sonja I. Berndt, Richard B. Hayes, Marie Elena Martinez, Sushma S. Thomas, Paul D. P. Pharoah, Susanna C. Larsson, Yun Yen, Heinz-Josef Lenz, Emily White, Li Li, Kimberly F. Doheny, Elizabeth Pugh, Tameka Shelford, Andrew T. Chan, Marcia Cruz-Correa, Annika Lindblom, David J. Hunter, Amit D. Joshi, Clemens Schafmayer, Peter C. Scacheri, Anshul Kundaje, Robert E. Schoen, Jochen Hampe, Zsofia K. Stadler, Pavel Vodicka, Ludmila Vodickova, Veronika Vymetalkova, Christopher K. Edlund, W. James Gauderman, David Shibata, Amanda Toland, Sanford Markowitz, Andre Kim, Stephen J. Chanock, Franzel van Duijnhoven, Edith J. M. Feskens, Lori C. Sakoda, Manuela Gago-Dominguez, Alicja Wolk, Barbara Pardini, Liesel M. FitzGerald, Soo Chin Lee, Shuji Ogino, Stephanie A. Bien, Charles Kooperberg, Christopher I. Li, Yi Lin, Ross Prentice, Conghui Qu, Stéphane Bézieau, Taiki Yamaji, Norie Sawada, Motoki Iwasaki, Loic Le Marchand, Anna H. Wu, Chenxu Qu, Caroline E. McNeil, Gerhard Coetzee, Caroline Hayward, Ian J. Deary, Sarah E. Harris, Evropi Theodoratou, Stuart Reid, Marion Walker, Li Yin Ooi, Ken S. Lau, Hongyu Zhao, Li Hsu, Qiuyin Cai, Malcolm G. Dunlop, Stephen B. Gruber, Richard S. Houlston, Victor Moreno, Graham Casey, Ulrike Peters, Ian Tomlinson, and Wei Zheng

Subjects
Science
Abstract

Abstract Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Published
2024
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2. Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

Author

Velma K Lopez, Estee Y Cramer, Robert Pagano, John M Drake, Eamon B O'Dea, Madeline Adee, Turgay Ayer, Jagpreet Chhatwal, Ozden O Dalgic, Mary A Ladd, Benjamin P Linas, Peter P Mueller, Jade Xiao, Johannes Bracher, Alvaro J Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Yuxin Huang, Dasuni Jayawardena, Abdul H Kanji, Khoa Le, Anja Mühlemann, Jarad Niemi, Evan L Ray, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W Zorn, Sen Pei, Jeffrey Shaman, Teresa K Yamana, Samuel R Tarasewicz, Daniel J Wilson, Sid Baccam, Heidi Gurung, Steve Stage, Brad Suchoski, Lei Gao, Zhiling Gu, Myungjin Kim, Xinyi Li, Guannan Wang, Lily Wang, Yueying Wang, Shan Yu, Lauren Gardner, Sonia Jindal, Maximilian Marshall, Kristen Nixon, Juan Dent, Alison L Hill, Joshua Kaminsky, Elizabeth C Lee, Joseph C Lemaitre, Justin Lessler, Claire P Smith, Shaun Truelove, Matt Kinsey, Luke C Mullany, Kaitlin Rainwater-Lovett, Lauren Shin, Katharine Tallaksen, Shelby Wilson, Dean Karlen, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Jiang Bian, Wei Cao, Zhifeng Gao, Juan Lavista Ferres, Chaozhuo Li, Tie-Yan Liu, Xing Xie, Shun Zhang, Shun Zheng, Matteo Chinazzi, Jessica T Davis, Kunpeng Mu, Ana Pastore Y Piontti, Alessandro Vespignani, Xinyue Xiong, Robert Walraven, Jinghui Chen, Quanquan Gu, Lingxiao Wang, Pan Xu, Weitong Zhang, Difan Zou, Graham Casey Gibson, Daniel Sheldon, Ajitesh Srivastava, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav Marathe, Akhil Sai Peddireddy, Przemyslaw Porebski, Srinivasan Venkatramanan, Lijing Wang, Pragati V Prasad, Jo W Walker, Alexander E Webber, Rachel B Slayton, Matthew Biggerstaff, Nicholas G Reich, and Michael A Johansson

Subjects
Biology (General), QH301-705.5
Abstract

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

Published
2024
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3. Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

Author

Minta Thomas, Yu-Ru Su, Elisabeth A. Rosenthal, Lori C. Sakoda, Stephanie L. Schmit, Maria N. Timofeeva, Zhishan Chen, Ceres Fernandez-Rozadilla, Philip J. Law, Neil Murphy, Robert Carreras-Torres, Virginia Diez-Obrero, Franzel J. B. van Duijnhoven, Shangqing Jiang, Aesun Shin, Alicja Wolk, Amanda I. Phipps, Andrea Burnett-Hartman, Andrea Gsur, Andrew T. Chan, Ann G. Zauber, Anna H. Wu, Annika Lindblom, Caroline Y. Um, Catherine M. Tangen, Chris Gignoux, Christina Newton, Christopher A. Haiman, Conghui Qu, D. Timothy Bishop, Daniel D. Buchanan, David R. Crosslin, David V. Conti, Dong-Hyun Kim, Elizabeth Hauser, Emily White, Erin Siegel, Fredrick R. Schumacher, Gad Rennert, Graham G. Giles, Heather Hampel, Hermann Brenner, Isao Oze, Jae Hwan Oh, Jeffrey K. Lee, Jennifer L. Schneider, Jenny Chang-Claude, Jeongseon Kim, Jeroen R. Huyghe, Jiayin Zheng, Jochen Hampe, Joel Greenson, John L. Hopper, Julie R. Palmer, Kala Visvanathan, Keitaro Matsuo, Koichi Matsuda, Keum Ji Jung, Li Li, Loic Le Marchand, Ludmila Vodickova, Luis Bujanda, Marc J. Gunter, Marco Matejcic, Mark A. Jenkins, Martha L. Slattery, Mauro D’Amato, Meilin Wang, Michael Hoffmeister, Michael O. Woods, Michelle Kim, Mingyang Song, Motoki Iwasaki, Mulong Du, Natalia Udaltsova, Norie Sawada, Pavel Vodicka, Peter T. Campbell, Polly A. Newcomb, Qiuyin Cai, Rachel Pearlman, Rish K. Pai, Robert E. Schoen, Robert S. Steinfelder, Robert W. Haile, Rosita Vandenputtelaar, Ross L. Prentice, Sébastien Küry, Sergi Castellví-Bel, Shoichiro Tsugane, Sonja I. Berndt, Soo Chin Lee, Stefanie Brezina, Stephanie J. Weinstein, Stephen J. Chanock, Sun Ha Jee, Sun-Seog Kweon, Susan Vadaparampil, Tabitha A. Harrison, Taiki Yamaji, Temitope O. Keku, Veronika Vymetalkova, Volker Arndt, Wei-Hua Jia, Xiao-Ou Shu, Yi Lin, Yoon-Ok Ahn, Zsofia K. Stadler, Bethany Van Guelpen, Cornelia M. Ulrich, Elizabeth A. Platz, John D. Potter, Christopher I. Li, Reinier Meester, Victor Moreno, Jane C. Figueiredo, Graham Casey, Iris Lansdorp Vogelaar, Malcolm G. Dunlop, Stephen B. Gruber, Richard B. Hayes, Paul D. P. Pharoah, Richard S. Houlston, Gail P. Jarvik, Ian P. Tomlinson, Wei Zheng, Douglas A. Corley, Ulrike Peters, and Li Hsu

Subjects
Science
Abstract

Abstract Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values

Published
2023
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4. Multi‐omic analysis in normal colon organoids highlights MSH4 as a novel marker of defective mismatch repair in Lynch syndrome and microsatellite instability

Author

Matthew Devall, Mourad W. Ali, Stephen Eaton, Daniel J. Weisenberger, Matthew J. Reilley, Steven M. Powell, Li Li, and Graham Casey

Subjects
colon organoids, colorectal cancer, Lynch syndrome, microsatellite instability, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Introduction Lynch syndrome (LS) is a hereditary condition that increases the risk of colorectal (CRC) and extracolonic cancers that exhibit microsatellite instability (MSI‐H). MSI‐H is driven by defective mismatch repair (dMMR), and approximately 15% of nonhereditary CRCs also exhibit MSI‐H. Here, we aimed to better define mechanisms underlying tumor initiation in LS and MSI‐H cancers through multi‐omic analyses of LS normal colon organoids and MSI‐H tumors. Methods Right (n = 35) and left (n = 23) colon organoids generated from normal colon biopsies at routine colonoscopy of LS and healthy individuals were subjected to Illumina EPIC array. Differentially methylated region (DMR) analysis was performed by DMRcate. RNA‐sequencing (n = 16) and bisulfite‐sequencing (n = 15) were performed on a subset of right colon organoids. CRISPR‐cas9‐mediated editing of MMR genes in colon organoids of healthy individuals was followed by quantitative PCR of MSH4. The relationship between MSH4 expression and tumor mutational burden was further explored in three independent tumor data sets. Results We identified a hypermethylated region of MSH4 in both the right and left colon organoids of LS versus healthy controls, which we validated using bisulfite‐sequencing. DMR analysis in three gastrointestinal and one endometrial data set revealed that this region was also hypermethylated in MSI‐H versus microsatellite stable (MSS) tumors. MSH4 expression was increased in colon organoids of LS versus healthy subjects and in publicly available MSI‐H versus MSS tumors across four RNA‐seq and four microarray data sets. CRISPR‐cas9 editing of MLH1 and MSH2, but not MSH6, in normal colon organoids significantly increased MSH4 expression. MSH4 expression was significantly associated with tumor mutational burden in three publicly available data sets. Conclusions Our findings implicate DNA methylation and gene expression differences of MSH4 as a marker of dMMR and as a potential novel biomarker of LS. Our study of LS colon organoids supports the hypothesis that dMMR exists in the colons of LS subjects prior to CRC.

Published
2023
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5. Application of Mendelian randomization to explore the causal role of the human gut microbiome in colorectal cancer

Author

Charlie Hatcher, George Richenberg, Samuel Waterson, Long H. Nguyen, Amit D. Joshi, Robert Carreras-Torres, Victor Moreno, Andrew T. Chan, Marc Gunter, Yi Lin, Conghui Qu, Mingyang Song, Graham Casey, Jane C. Figueiredo, Stephen B. Gruber, Jochen Hampe, Heather Hampel, Mark A. Jenkins, Temitope O. Keku, Ulrike Peters, Catherine M. Tangen, Anna H. Wu, David A. Hughes, Malte C. Rühlemann, Jeroen Raes, Nicholas J. Timpson, and Kaitlin H. Wade

Subjects
Medicine, Science
Abstract

Abstract The role of the human gut microbiome in colorectal cancer (CRC) is unclear as most studies on the topic are unable to discern correlation from causation. We apply two-sample Mendelian randomization (MR) to estimate the causal relationship between the gut microbiome and CRC. We used summary-level data from independent genome-wide association studies to estimate the causal effect of 14 microbial traits (n = 3890 individuals) on overall CRC (55,168 cases, 65,160 controls) and site-specific CRC risk, conducting several sensitivity analyses to understand the nature of results. Initial MR analysis suggested that a higher abundance of Bifidobacterium and presence of an unclassified group of bacteria within the Bacteroidales order in the gut increased overall and site-specific CRC risk. However, sensitivity analyses suggested that instruments used to estimate relationships were likely complex and involved in many potential horizontal pleiotropic pathways, demonstrating that caution is needed when interpreting MR analyses with gut microbiome exposures. In assessing reverse causality, we did not find strong evidence that CRC causally affected these microbial traits. Whilst our study initially identified potential causal roles for two microbial traits in CRC, importantly, further exploration of these relationships highlighted that these were unlikely to reflect causality.

Published
2023
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6. Author Correction: Application of Mendelian randomization to explore the causal role of the human gut microbiome in colorectal cancer

Author

Charlie Hatcher, George Richenberg, Samuel Waterson, Long H. Nguyen, Amit D. Joshi, Robert Carreras-Torres, Victor Moreno, Andrew T. Chan, Marc Gunter, Yi Lin, Conghui Qu, Mingyang Song, Graham Casey, Jane C. Figueiredo, Stephen B. Gruber, Jochen Hampe, Heather Hampel, Mark A. Jenkins, Temitope O. Keku, Ulrike Peters, Catherine M. Tangen, Anna H. Wu, David A. Hughes, Malte C. Rühlemann, Jeroen Raes, Nicholas J. Timpson, and Kaitlin H. Wade

Subjects
Medicine, Science
Published
2023
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7. Interactions between folate intake and genetic predictors of gene expression levels associated with colorectal cancer risk

Author

Cameron B. Haas, Yu-Ru Su, Paneen Petersen, Xiaoliang Wang, Stephanie A. Bien, Yi Lin, Demetrius Albanes, Stephanie J. Weinstein, Mark A. Jenkins, Jane C. Figueiredo, Polly A. Newcomb, Graham Casey, Loic Le Marchand, Peter T. Campbell, Victor Moreno, John D. Potter, Lori C. Sakoda, Martha L. Slattery, Andrew T. Chan, Li Li, Graham G. Giles, Roger L. Milne, Stephen B. Gruber, Gad Rennert, Michael O. Woods, Steven J. Gallinger, Sonja Berndt, Richard B. Hayes, Wen-Yi Huang, Alicja Wolk, Emily White, Hongmei Nan, Rami Nassir, Noralane M. Lindor, Juan P. Lewinger, Andre E. Kim, David Conti, W. James Gauderman, Daniel D. Buchanan, Ulrike Peters, and Li Hsu

Subjects
Medicine, Science
Abstract

Abstract Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene–environment (G × E) interactions and may provide information on the underlying biological pathway. We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based G × E approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case–control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4839 genes with available genetically predicted expression. We pooled results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. We used a false discovery rate of 0.2 to identify genes with suggestive evidence of an interaction. We found suggestive evidence of interaction with folate intake on CRC risk for genes including glutathione S-Transferase Alpha 1 (GSTA1; p = 4.3E−4), Tonsuko Like, DNA Repair Protein (TONSL; p = 4.3E−4), and Aspartylglucosaminidase (AGA: p = 4.5E−4). We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk. Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein.

Published
2022
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8. Association between germline variants and somatic mutations in colorectal cancer

Author

Richard Barfield, Conghui Qu, Robert S. Steinfelder, Chenjie Zeng, Tabitha A. Harrison, Stefanie Brezina, Daniel D. Buchanan, Peter T. Campbell, Graham Casey, Steven Gallinger, Marios Giannakis, Stephen B. Gruber, Andrea Gsur, Li Hsu, Jeroen R. Huyghe, Victor Moreno, Polly A. Newcomb, Shuji Ogino, Amanda I. Phipps, Martha L. Slattery, Stephen N. Thibodeau, Quang M. Trinh, Amanda E. Toland, Thomas J. Hudson, Wei Sun, Syed H. Zaidi, and Ulrike Peters

Subjects
Medicine, Science
Abstract

Abstract Colorectal cancer (CRC) is a heterogeneous disease with evidence of distinct tumor types that develop through different somatically altered pathways. To better understand the impact of the host genome on somatically mutated genes and pathways, we assessed associations of germline variations with somatic events via two complementary approaches. We first analyzed the association between individual germline genetic variants and the presence of non-silent somatic mutations in genes in 1375 CRC cases with genome-wide SNPs data and a tumor sequencing panel targeting 205 genes. In the second analysis, we tested if germline variants located within previously identified regions of somatic allelic imbalance were associated with overall CRC risk using summary statistics from a recent large scale GWAS (n≃125 k CRC cases and controls). The first analysis revealed that a variant (rs78963230) located within a CNA region associated with TLR3 was also associated with a non-silent mutation within gene FBXW7. In the secondary analysis, the variant rs2302274 located in CDX1/PDGFRB frequently gained/lost in colorectal tumors was associated with overall CRC risk (OR = 0.96, p = 7.50e-7). In summary, we demonstrate that an integrative analysis of somatic and germline variation can lead to new insights about CRC.

Published
2022
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9. Genetically proxied therapeutic inhibition of antihypertensive drug targets and risk of common cancers: A mendelian randomization analysis.

Author

James Yarmolinsky, Virginia Díez-Obrero, Tom G Richardson, Marie Pigeyre, Jennifer Sjaarda, Guillaume Paré, Venexia M Walker, Emma E Vincent, Vanessa Y Tan, Mireia Obón-Santacana, Demetrius Albanes, Jochen Hampe, Andrea Gsur, Heather Hampel, Rish K Pai, Mark Jenkins, Steven Gallinger, Graham Casey, Wei Zheng, Christopher I Amos, International Lung Cancer Consortium, PRACTICAL consortium, MEGASTROKE consortium, George Davey Smith, Richard M Martin, and Victor Moreno

Subjects
Medicine
Abstract

BackgroundEpidemiological studies have reported conflicting findings on the potential adverse effects of long-term antihypertensive medication use on cancer risk. Naturally occurring variation in genes encoding antihypertensive drug targets can be used as proxies for these targets to examine the effect of their long-term therapeutic inhibition on disease outcomes.Methods and findingsWe performed a mendelian randomization analysis to examine the association between genetically proxied inhibition of 3 antihypertensive drug targets and risk of 4 common cancers (breast, colorectal, lung, and prostate). Single-nucleotide polymorphisms (SNPs) in ACE, ADRB1, and SLC12A3 associated (P < 5.0 × 10-8) with systolic blood pressure (SBP) in genome-wide association studies (GWAS) were used to proxy inhibition of angiotensin-converting enzyme (ACE), β-1 adrenergic receptor (ADRB1), and sodium-chloride symporter (NCC), respectively. Summary genetic association estimates for these SNPs were obtained from GWAS consortia for the following cancers: breast (122,977 cases, 105,974 controls), colorectal (58,221 cases, 67,694 controls), lung (29,266 cases, 56,450 controls), and prostate (79,148 cases, 61,106 controls). Replication analyses were performed in the FinnGen consortium (1,573 colorectal cancer cases, 120,006 controls). Cancer GWAS and FinnGen consortia data were restricted to individuals of European ancestry. Inverse-variance weighted random-effects models were used to examine associations between genetically proxied inhibition of these drug targets and risk of cancer. Multivariable mendelian randomization and colocalization analyses were employed to examine robustness of findings to violations of mendelian randomization assumptions. Genetically proxied ACE inhibition equivalent to a 1-mm Hg reduction in SBP was associated with increased odds of colorectal cancer (odds ratio (OR) 1.13, 95% CI 1.06 to 1.22; P = 3.6 × 10-4). This finding was replicated in the FinnGen consortium (OR 1.40, 95% CI 1.02 to 1.92; P = 0.035). There was little evidence of association of genetically proxied ACE inhibition with risk of breast cancer (OR 0.98, 95% CI 0.94 to 1.02, P = 0.35), lung cancer (OR 1.01, 95% CI 0.92 to 1.10; P = 0.93), or prostate cancer (OR 1.06, 95% CI 0.99 to 1.13; P = 0.08). Genetically proxied inhibition of ADRB1 and NCC were not associated with risk of these cancers. The primary limitations of this analysis include the modest statistical power for analyses of drug targets in relation to some less common histological subtypes of cancers examined and the restriction of the majority of analyses to participants of European ancestry.ConclusionsIn this study, we observed that genetically proxied long-term ACE inhibition was associated with an increased risk of colorectal cancer, warranting comprehensive evaluation of the safety profiles of ACE inhibitors in clinical trials with adequate follow-up. There was little evidence to support associations across other drug target-cancer risk analyses, consistent with findings from short-term randomized controlled trials for these medications.

Published
2022
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10. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Author

Cramer, Estee Y, Ray, Evan L, Lopez, Velma K, Bracher, Johannes, Brennen, Andrea, Rivadeneira, Alvaro J Castro, Gerding, Aaron, Gneiting, Tilmann, House, Katie H, Huang, Yuxin, Jayawardena, Dasuni, Kanji, Abdul H, Khandelwal, Ayush, Le, Khoa, Mühlemann, Anja, Niemi, Jarad, Shah, Apurv, Stark, Ariane, Wang, Yijin, Wattanachit, Nutcha, Zorn, Martha W, Gu, Youyang, Jain, Sansiddh, Bannur, Nayana, Deva, Ayush, Kulkarni, Mihir, Merugu, Srujana, Raval, Alpan, Shingi, Siddhant, Tiwari, Avtansh, White, Jerome, Abernethy, Neil F, Woody, Spencer, Dahan, Maytal, Fox, Spencer, Gaither, Kelly, Lachmann, Michael, Meyers, Lauren Ancel, Scott, James G, Tec, Mauricio, Srivastava, Ajitesh, George, Glover E, Cegan, Jeffrey C, Dettwiller, Ian D, England, William P, Farthing, Matthew W, Hunter, Robert H, Lafferty, Brandon, Linkov, Igor, Mayo, Michael L, Parno, Matthew D, Rowland, Michael A, Trump, Benjamin D, Zhang-James, Yanli, Chen, Samuel, Faraone, Stephen V, Hess, Jonathan, Morley, Christopher P, Salekin, Asif, Wang, Dongliang, Corsetti, Sabrina M, Baer, Thomas M, Eisenberg, Marisa C, Falb, Karl, Huang, Yitao, Martin, Emily T, McCauley, Ella, Myers, Robert L, Schwarz, Tom, Sheldon, Daniel, Gibson, Graham Casey, Yu, Rose, Gao, Liyao, Ma, Yian, Wu, Dongxia, Yan, Xifeng, Jin, Xiaoyong, Wang, Yu-Xiang, Chen, YangQuan, Guo, Lihong, Zhao, Yanting, Gu, Quanquan, Chen, Jinghui, Wang, Lingxiao, Xu, Pan, Zhang, Weitong, Zou, Difan, Biegel, Hannah, Lega, Joceline, McConnell, Steve, Nagraj, VP, Guertin, Stephanie L, Hulme-Lowe, Christopher, Turner, Stephen D, Shi, Yunfeng, Ban, Xuegang, Walraven, Robert, Hong, Qi-Jun, Kong, Stanley, and van de Walle, Axel

Subjects
Bioengineering, Good Health and Well Being, COVID-19, Data Accuracy, Forecasting, Humans, Pandemics, Probability, Public Health, United States, forecasting, ensemble forecast, model evaluation
Abstract

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

Published
2022

11. Assessment of Colorectal Cancer Risk Factors through the Application of Network-Based Approaches in a Racially Diverse Cohort of Colon Organoid Stem Cells

Author

Li, Matthew Devall, Stephen Eaton, Cynthia Yoshida, Steven M. Powell, and Graham Casey

Subjects
colon organoid, stem cell, racial disparities, colorectal cancer risk, network analysis, WGCNA, smoking, aging, body mass index
Abstract

Numerous demographic factors have been associated with colorectal cancer (CRC) risk. To better define biological mechanisms underlying these associations, we performed RNA sequencing of stem-cell-enriched organoids derived from the healthy colons of seven European Americans and eight African Americans. A weighted gene co-expression network analysis was performed following RNA sequencing. Module–trait relationships were determined through the association testing of each module and five CRC risk factors (age, body mass index, sex, smoking history, and race). Only modules that displayed a significantly positive correlation for gene significance and module membership were considered for further investigation. In total, 16 modules were associated with known CRC risk factors (p < 0.05). To contextualize the role of risk modules in CRC, publicly available RNA-sequencing data from TCGA-COAD were downloaded and re-analyzed. Differentially expressed genes identified between tumors and matched normal-adjacent tissue were overlaid across each module. Loci derived from CRC genome-wide association studies were additionally overlaid across modules to identify robust putative targets of risk. Among them, MYBL2 and RXRA represented strong plausible drivers through which cigarette smoking and BMI potentially modulated CRC risk, respectively. In summary, our findings highlight the potential of the colon organoid system in identifying novel CRC risk mechanisms in an ancestrally diverse and cellularly relevant population.

Published
2023
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12. A risk variant for Barrett’s esophagus and esophageal adenocarcinoma at chr8p23.1 affects enhancer activity and implicates multiple gene targets

Author

Mourad Wagdy Ali, Jianhong Chen, Li Yan, Xiaoyu Wang, James Y Dai, Thomas L Vaughan, Graham Casey, and Matthew F Buas

Subjects
Barrett Esophagus, Esophageal Neoplasms, Quantitative Trait Loci, Genetics, Humans, Original Article, General Medicine, Adenocarcinoma, Molecular Biology, Genetics (clinical), Genome-Wide Association Study
Abstract

Nineteen genetic susceptibility loci for esophageal adenocarcinoma (EAC) and its precursor Barrett’s esophagus (BE) have been identified through genome-wide association studies (GWAS). Clinical translation of such discoveries, however, has been hindered by the slow pace of discovery of functional/causal variants and gene targets at these loci. We previously developed a systematic informatics pipeline to prioritize candidate functional variants using functional potential scores, applied the pipeline to select high-scoring BE/EAC risk loci and validated a functional variant at chr19p13.11 (rs10423674). Here, we selected two additional prioritized loci for experimental interrogation: chr3p13/rs1522552 and chr8p23.1/rs55896564. Candidate enhancer regions encompassing these variants were evaluated using luciferase reporter assays in two EAC cell lines. One of the two regions tested exhibited allele-specific enhancer activity – 8p23.1/rs55896564. CRISPR-mediated deletion of the putative enhancer in EAC cell lines correlated with reduced expression of three candidate gene targets: B lymphocyte kinase (BLK), nei like DNA glycosylase 2 (NEIL2) and cathepsin B (CTSB). Expression quantitative trait locus (eQTL) mapping in normal esophagus and stomach revealed strong associations between the BE/EAC risk allele at rs55896564 (G) and lower expression of CTSB, a protease gene implicated in epithelial wound repair. These results further support the utility of functional potential scores for GWAS variant prioritization, and provide the first experimental evidence of a functional variant and risk enhancer at the 8p23.1 GWAS locus. Identification of CTSB, BLK and NEIL2 as candidate gene targets suggests that altered expression of these genes may underlie the genetic risk association at 8p23.1 with BE/EAC.

Published
2022

15. Supplementary Figure from Transcriptome-wide In Vitro Effects of Aspirin on Patient-derived Normal Colon Organoids

Author

Graham Casey, Ulrike Peters, Andrew T. Chan, Steven M. Powell, Victor Moreno, Ömer H. Yilmaz, Mourad W. Ali, Lucas T. Jennelle, Oliver Takacsi-Nagy, Dylan C. Zerjav, Dmitriy Kedrin, Jiancheng Mo, Virginia Díez-Obrero, Jennifer Bryant, Stephen Eaton, Sarah J. Plummer, Christopher H. Dampier, David A. Drew, and Matthew A.M. Devall

Abstract

Supplementary Figure from Transcriptome-wide In Vitro Effects of Aspirin on Patient-derived Normal Colon Organoids

Published
2023

16. Supplementary Data from Transcriptome-wide In Vitro Effects of Aspirin on Patient-derived Normal Colon Organoids

Author

Graham Casey, Ulrike Peters, Andrew T. Chan, Steven M. Powell, Victor Moreno, Ömer H. Yilmaz, Mourad W. Ali, Lucas T. Jennelle, Oliver Takacsi-Nagy, Dylan C. Zerjav, Dmitriy Kedrin, Jiancheng Mo, Virginia Díez-Obrero, Jennifer Bryant, Stephen Eaton, Sarah J. Plummer, Christopher H. Dampier, David A. Drew, and Matthew A.M. Devall

Abstract

Supplementary Data from Transcriptome-wide In Vitro Effects of Aspirin on Patient-derived Normal Colon Organoids

Published
2023

18. Supplementary Tables from Identification of Novel Variants in Colorectal Cancer Families by High-Throughput Exome Sequencing

Author

Ellen L. Goode, Stephen N. Thibodeau, Noralane M. Lindor, Loïc Le Marchand, Polly A. Newcomb, John D. Potter, Graham Casey, Steven N. Gallinger, Michael O. Woods, Robert W. Haile, Mark Clendenning, Daniel Buchanan, David J. Duggan, Mark A. Jenkins, Mine S. Cicek, William R. Bamlet, Daniel J. Serie, Brooke L. Fridley, Julie M. Cunningham, Bruce W. Eckloff, Shaun M. Riska, Shannon K. McDonnell, Daniel J. Schaid, Yan W. Asmann, Sumit Middha, Shanaka R. Gunawardena, and Melissa S. DeRycke

Abstract

Supplementary Tables - PDF file 193K, File contains Tables S1-S11

Published
2023

19. Data from Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer

Author

Robert J. MacInnis, John L. Hopper, Polly A. Newcomb, Noralane M. Lindor, Yingye Zheng, John D. Potter, Robert W. Haile, Loïc Le Marchand, Steven Gallinger, Graham Casey, Stephen N. Thibodeau, Dennis J. Ahnen, Christophe Rosty, Mark Clendenning, Daniel D. Buchanan, Graham G. Giles, Andrew Lee, Antonis C. Antoniou, James G. Dowty, Mark A. Jenkins, and Aung Ko Win

Abstract

Background: Although high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and MUTYH) account for some familial aggregation of colorectal cancer, their population prevalence and the causes of the remaining familial aggregation are not known.Methods: We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the United States, Canada, and Australia and screened probands for mutations in mismatch repair genes and MUTYH. We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the proband's age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of HR for unidentified major gene mutations, and the variance of the residual polygenic component.Results: We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (MLH1 = 1 in 1,946, MSH2 = 1 in 2,841, MSH6 = 1 in 758, PMS2 = 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30% to 50% after allowing for unidentified major genes and decreased from 3.3 for age Conclusions: Unidentified major genes might explain one third to one half of the missing heritability of colorectal cancer.Impact: Our findings could aid gene discovery and development of better colorectal cancer risk prediction models. Cancer Epidemiol Biomarkers Prev; 26(3); 404–12. ©2016 AACR.

Published
2023

20. Data from Validation of Genome-Wide Prostate Cancer Associations in Men of African Descent

Author

Timothy R. Rebbeck, Charnita Zeigler-Johnson, Klara Stefflova, Jong Park, Esther M. John, Jennifer J. Hu, Stephen Chanock, Ann W. Hsing, Rosalind Eeles, Graham Casey, John Witte, Janet L. Stanford, Elaine A. Ostrander, Robin J. Leach, Ian M. Thompson, Adam S. Kibel, Christine Neslund-Dudas, Benjamin Rybicki, Veda N. Giri, Jianfeng Xu, Amit D. Joshi, Roman Corral, Mariana C. Stern, Sue Ann Ingles, Sara Strom, Kathleen Cooney, LaCreis R. Kidd, Marnita L. Benford, William Isaacs, Brian Henderson, Christopher A. Haiman, Stephen Gallagher, Elaine Spangler, and Bao-Li Chang

Abstract

Background: Genome-wide association studies (GWAS) have identified numerous prostate cancer susceptibility alleles, but these loci have been identified primarily in men of European descent. There is limited information about the role of these loci in men of African descent.Methods: We identified 7,788 prostate cancer cases and controls with genotype data for 47 GWAS-identified loci.Results: We identified significant associations for SNP rs10486567 at JAZF1, rs10993994 at MSMB, rs12418451 and rs7931342 at 11q13, and rs5945572 and rs5945619 at NUDT10/11. These associations were in the same direction and of similar magnitude as those reported in men of European descent. Significance was attained at all reported prostate cancer susceptibility regions at chromosome 8q24, including associations reaching genome-wide significance in region 2.Conclusion: We have validated in men of African descent the associations at some, but not all, prostate cancer susceptibility loci originally identified in European descent populations. This may be due to the heterogeneity in genetic etiology or in the pattern of genetic variation across populations.Impact: The genetic etiology of prostate cancer in men of African descent differs from that of men of European descent. Cancer Epidemiol Biomarkers Prev; 20(1); 23–32. ©2011 AACR.

Published
2023

21. Data from A Genome-wide Association Study of Early-Onset Breast Cancer Identifies PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age

Author

Alice S. Whittemore, Nancy J. Cox, Douglas F. Easton, Dan Nicolae, Fernando Rivadeneira, Andre G. Uitterlinden, Hanne Meijers-Heijboer, Quinten Waisfisz, Paul Pharoah, Alison M. Dunning, Clare Turnbull, Nazneen Rahman, Jianjun Liu, Astrid Irwanto, Kamila Czene, Per Hall, Carl Blomqvist, Kristiina Aittomäki, Heli Nevanlinna, Norbert Dahmen, Dieter Flesch-Janys, Jennifer Stone, Quang Minh Bui, Daniel F. Schmidt, Enes Makalic, Rebecca Hein, Lars Beckmann, Magdalena Lochmann, Bertram Müller-Myhsok, Rita K. Schmutzler, Alfons Meindl, Stephen J. Chanock, David J. Hunter, Mark Lathrop, Isabel dos Santos Silva, Olivia Fletcher, Julian Peto, Daniel J. Park, Carmel Apicella, Kyriaki Michailidou, Polly Newcomb, Noralane M. Lindor, Mark Jenkins, Robert Haile, Steve Gallinger, David Duggan, David Conti, Eunjung Lee, Regina M. Santella, Graham G. Giles, Melissa C. Southey, Julia A. Knight, Graham Casey, Daniela Seminara, Duncan C. Thomas, Marilie D. Gammon, Giske Ursin, Kathi Malone, Esther M. John, John L. Hopper, Irene Andrulis, Jenny Chang-Claude, Stephanie Melkonian, Maria Argos, Rachelle Brutus, Shantanu Roy, Farzana Jasmine, Jianxin Shi, Anna Felberg, Valerie McGuire, Eric Gamazon, Lin Tong, Brandon L. Pierce, Muhammad G. Kibriya, Jerry Halpern, and Habibul Ahsan

Abstract

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10−8) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10−4) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10−6. In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer. Cancer Epidemiol Biomarkers Prev; 23(4); 658–69. ©2014 AACR.

Published
2023

22. Supplementary Materials from Validation of Genome-Wide Prostate Cancer Associations in Men of African Descent

Author

Timothy R. Rebbeck, Charnita Zeigler-Johnson, Klara Stefflova, Jong Park, Esther M. John, Jennifer J. Hu, Stephen Chanock, Ann W. Hsing, Rosalind Eeles, Graham Casey, John Witte, Janet L. Stanford, Elaine A. Ostrander, Robin J. Leach, Ian M. Thompson, Adam S. Kibel, Christine Neslund-Dudas, Benjamin Rybicki, Veda N. Giri, Jianfeng Xu, Amit D. Joshi, Roman Corral, Mariana C. Stern, Sue Ann Ingles, Sara Strom, Kathleen Cooney, LaCreis R. Kidd, Marnita L. Benford, William Isaacs, Brian Henderson, Christopher A. Haiman, Stephen Gallagher, Elaine Spangler, and Bao-Li Chang

Abstract

Supplementary Materials from Validation of Genome-Wide Prostate Cancer Associations in Men of African Descent

Published
2023

23. Supplementary Figure 1 from Identification of Novel Variants in Colorectal Cancer Families by High-Throughput Exome Sequencing

Author

Ellen L. Goode, Stephen N. Thibodeau, Noralane M. Lindor, Loïc Le Marchand, Polly A. Newcomb, John D. Potter, Graham Casey, Steven N. Gallinger, Michael O. Woods, Robert W. Haile, Mark Clendenning, Daniel Buchanan, David J. Duggan, Mark A. Jenkins, Mine S. Cicek, William R. Bamlet, Daniel J. Serie, Brooke L. Fridley, Julie M. Cunningham, Bruce W. Eckloff, Shaun M. Riska, Shannon K. McDonnell, Daniel J. Schaid, Yan W. Asmann, Sumit Middha, Shanaka R. Gunawardena, and Melissa S. DeRycke

Abstract

Supplementary Figure 1 - PDF file 44K, Figure S1, containing pedigrees for each of the 16 families sequenced for the study. Sixteen pages are included.

Published
2023

24. Data from Association of the Colorectal CpG Island Methylator Phenotype with Molecular Features, Risk Factors, and Family History

Author

Kimberly D. Siegmund, Peter W. Laird, Joanne P. Young, John L. Hopper, Robert W. Haile, John A. Baron, Dennis J. Ahnen, Graham Casey, Peter T. Campbell, Polly A. Newcomb, Bharati Bapat, Teresa Selander, Steven Gallinger, Darshana Daftary, Noralane M. Lindor, Loic Le Marchand, Mariana C. Stern, Amit D. Joshi, Christophe Rosty, Mark Clendenning, Rhiannon Walters, Daniel D. Buchanan, Tiffany I. Long, A. Joan Levine, and Daniel J. Weisenberger

Abstract

Background: The CpG island methylator phenotype (CIMP) represents a subset of colorectal cancers characterized by widespread aberrant DNA hypermethylation at select CpG islands. The risk factors and environmental exposures contributing to etiologic heterogeneity between CIMP and non-CIMP tumors are not known.Methods: We measured the CIMP status of 3,119 primary population-based colorectal cancer tumors from the multinational Colon Cancer Family Registry. Etiologic heterogeneity was assessed by a case–case study comparing risk factor frequency of colorectal cancer cases with CIMP and non-CIMP tumors using logistic regression to estimate the case–case odds ratio (ccOR).Results: We found associations between tumor CIMP status and MSI-H (ccOR = 7.6), BRAF V600E mutation (ccOR = 59.8), proximal tumor site (ccOR = 9; all P < 0.0001), female sex [ccOR = 1.8; 95% confidence interval (CI), 1.5–2.1], older age (ccOR = 4.0 comparing over 70 years vs. under 50; 95% CI, 3.0–5.5), and family history of CRC (ccOR = 0.6; 95% CI, 0.5–0.7). While use of NSAIDs varied by tumor CIMP status for both males and females (P = 0.0001 and P = 0.02, respectively), use of multivitamin or calcium supplements did not. Only for female colorectal cancer was CIMP status associated with increased pack-years of smoking (Ptrend < 0.001) and body mass index (BMI; Ptrend = 0.03).Conclusions: The frequency of several colorectal cancer risk factors varied by CIMP status, and the associations of smoking and obesity with tumor subtype were evident only for females.Impact: Differences in the associations of a unique DNA methylation–based subgroup of colorectal cancer with important lifestyle and environmental exposures increase understanding of the molecular pathologic epidemiology of this heavily methylated subset of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 24(3); 512–9. ©2015 AACR.

Published
2023

25. Supplementary Tables from Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer

Author

Robert J. MacInnis, John L. Hopper, Polly A. Newcomb, Noralane M. Lindor, Yingye Zheng, John D. Potter, Robert W. Haile, Loïc Le Marchand, Steven Gallinger, Graham Casey, Stephen N. Thibodeau, Dennis J. Ahnen, Christophe Rosty, Mark Clendenning, Daniel D. Buchanan, Graham G. Giles, Andrew Lee, Antonis C. Antoniou, James G. Dowty, Mark A. Jenkins, and Aung Ko Win

Abstract

Supplementary Table 1: Results of segregation analyses incorporating mismatch repair gene and MUTYH mutation carrier status. Supplementary Table 2. Estimated population carrier frequency of a mismatch repair gene or MUTYH mutation from previous studies and current study.

Published
2023

26. Description of supplementary files from Identification of Novel Variants in Colorectal Cancer Families by High-Throughput Exome Sequencing

Author

Ellen L. Goode, Stephen N. Thibodeau, Noralane M. Lindor, Loïc Le Marchand, Polly A. Newcomb, John D. Potter, Graham Casey, Steven N. Gallinger, Michael O. Woods, Robert W. Haile, Mark Clendenning, Daniel Buchanan, David J. Duggan, Mark A. Jenkins, Mine S. Cicek, William R. Bamlet, Daniel J. Serie, Brooke L. Fridley, Julie M. Cunningham, Bruce W. Eckloff, Shaun M. Riska, Shannon K. McDonnell, Daniel J. Schaid, Yan W. Asmann, Sumit Middha, Shanaka R. Gunawardena, and Melissa S. DeRycke

Abstract

Description of supplementary files - PDF file 44K, File contains description of supplementary files.

Published
2023

27. Data from Genetic Predictors of Circulating 25-Hydroxyvitamin D and Risk of Colorectal Cancer

Author

Andrew T. Chan, Ulrike Peters, Peter Kraft, Brent W. Zanke, Kana Wu, Emily White, Jean Wactawski-Wende, Martha L. Slattery, Daniela Seminara, Fredrick R. Schumacher, Robert E. Schoen, John D. Potter, Kimmie Ng, Polly A. Newcomb, Hongmei Nan, JoAnn E. Manson, Jing Ma, Mathieu Lemire, Loic Le Marchand, Sébastien Küry, Mark A. Jenkins, Thomas J. Hudson, John L. Hopper, Michael Hoffmeister, Brian Henderson, Aditi Hazra, Richard B. Hayes, Tabitha A. Harrison, Edward L. Giovannucci, Steven Gallinger, Charles S. Fuchs, David Duggan, David V. Conti, Stephen J. Chanock, Jenny Chang-Claude, Graham Casey, Bette J. Caan, Hermann Brenner, Stéphane Bézieau, Sonja I. Berndt, John A. Baron, Carolyn M. Hutter, Conghui Qu, and Linda T. Hiraki

Abstract

Background: Experimental evidence has demonstrated an antineoplastic role for vitamin D in the colon, and higher circulating 25-hydroxyvitamin D [25(OH)D] levels are consistently associated with a lower risk of colorectal cancer. Genome-wide association studies have identified loci associated with levels of circulating 25(OH)D. The identified single-nucleotide polymorphisms (SNPs) from four gene regions collectively explain approximately 5% of the variance in circulating 25(OH)D.Methods: We investigated whether five polymorphisms in GC, CYP2R1, CYP24A1, and DHCR7/NADSYN1, genes previously shown to be associated with circulating 25(OH)D levels, were associated with colorectal cancer risk in 10,061 cases and 12,768 controls drawn from 13 studies included in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR). We conducted a meta-analysis of crude and multivariate-adjusted logistic regression models to calculate odds ratios and associated confidence intervals for SNPs individually, SNPs simultaneously, and for a vitamin D additive genetic risk score (GRS).Results: We did not observe a statistically significant association between the 25(OH)D-associated SNPs and colorectal cancer marginally, conditionally, or as a GRS, or for colon or rectal cancer separately.Conclusions: Our findings do not support an association between SNPs associated with circulating 25(OH)D and risk of colorectal cancer. Additional work is warranted to investigate the complex relationship between 25(OH)D and colorectal cancer risk.Impact: There was no association observed between genetic markers of circulating 25(OH)D and colorectal cancer. These genetic markers account for a small proportion of the variance in 25(OH)D. Cancer Epidemiol Biomarkers Prev; 22(11); 2037–46. ©2013 AACR.

Published
2023

28. Supplementary Table 2 and Supplemental Figures from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Table S2: Odds ratio and 95% confidence limits for cancers associated with variants with pleiotropic associations. Figure S1: Flowchart showing analysis steps. Figure S2. Manhattan plots by chromosome for individual cancer sites. Figure S3. Results for rs11571833. Figure S4: Conditional QQ-plots.

Published
2023

29. Appendix - clean version from Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer

Author

Robert J. MacInnis, John L. Hopper, Polly A. Newcomb, Noralane M. Lindor, Yingye Zheng, John D. Potter, Robert W. Haile, Loïc Le Marchand, Steven Gallinger, Graham Casey, Stephen N. Thibodeau, Dennis J. Ahnen, Christophe Rosty, Mark Clendenning, Daniel D. Buchanan, Graham G. Giles, Andrew Lee, Antonis C. Antoniou, James G. Dowty, Mark A. Jenkins, and Aung Ko Win

Abstract

We used modified segregation analysis to fit a range of genetic models to the observed colorectal cancer family histories for the proband and their first-degree relatives.

Published
2023

30. Supplementary Material 1 from A Pooled Analysis of Smoking and Colorectal Cancer: Timing of Exposure and Interactions with Environmental Factors

Author

Ulrike Peters, John Potter, Emily White, Greg Warnick, Fridtjof Thomas, Deanna Stelling, Martha L. Slattery, Daniela Seminara, Robert Schoen, Thomas Rohan, Amanda I. Phipps, Bethann Pflugeisen, Polly Newcomb, Noralane M. Lindor, Yi Lin, Shuo Jiao, Li Hsu, Richard Hayes, Tabitha Harrison, Edward Giovannucci, Steven Gallinger, Charles S. Fuchs, Michelle Cotterchio, Andrew T. Chan, Graham Casey, Peter T. Campbell, Bette Caan, Sonja Berndt, John A. Baron, Carolyn Hutter, and Jian Gong

Abstract

PDF file - 59K, The description of studies included in this pooled analysis

Published
2023

31. Supplementary Tables S1-3 from Mendelian Randomization Study of Body Mass Index and Colorectal Cancer Risk

Author

Peter T. Campbell, Li Hsu, Emily White, Hermann Brenner, Michael Hoffmeister, Polly A. Newcomb, John D. Potter, Cornelia M. Ulrich, John L. Hopper, Mark A. Jenkins, Aung Ko Win, Michelle Cotterchio, Stephen N. Thibodeau, Kana Wu, Mingyang Song, Daniela Seminara, Noralane M. Lindor, Loïc Le Marchand, David J. Duggan, Mark Thornquist, Tabitha A. Harrison, Mengmeng Du, Robert W. Haile, Graham Casey, Stephen J. Chanock, Sonja I. Berndt, Shuji Ogino, Bette J. Caan, John A. Baron, Richard B. Hayes, Steven Gallinger, Tune H. Pers, Anne E. Justice, Bratati Kahali, Adam E. Locke, Andrew T. Chan, Martha L. Slattery, Anja Rudolph, Jenny Chang-Claude, Ulrike Peters, Jian Gong, and Aaron P. Thrift

Abstract

Supplementary Tables S1-3. Supplementary Table S1 Description of the characteristics by study. Supplementary Table S2 Associations between confounders and body mass index and the weighted genetic risk score among controls. Supplementary Table S3 Odds ratios (OR) and 95% confidence intervals (CI) for the association between a 1-unit increase in the weighted genetic risk score (the instrumental variable [IV]) and risk of colorectal cancer.

Published
2023

32. Supplementary Data from Genomic Analysis of Germline Variation Associated with Survival of Patients with Colorectal Cancer Treated with Chemotherapy Plus Biologics in CALGB/SWOG 80405 (Alliance)

Author

Kouros Owzar, Mark J. Ratain, Joel S. Parker, Heinz-Josef Lenz, Michiaki Kubo, Alan P. Venook, Yoichi Furukawa, Charles D. Blanke, James T. Auman, Howard L. McLeod, Monica M. Bertagnolli, Graham Casey, Sarah J. Plummer, Stefanie D. Howell, Fang-Shu Ou, Chen Jiang, Amy S. Etheridge, Sushant A. Patil, Alexander B. Sibley, and Federico Innocenti

Abstract

Supplementary Figures 1-5 and Supplementary Tables 1-5

Published
2023

33. Data from A Pooled Analysis of Smoking and Colorectal Cancer: Timing of Exposure and Interactions with Environmental Factors

Author

Ulrike Peters, John Potter, Emily White, Greg Warnick, Fridtjof Thomas, Deanna Stelling, Martha L. Slattery, Daniela Seminara, Robert Schoen, Thomas Rohan, Amanda I. Phipps, Bethann Pflugeisen, Polly Newcomb, Noralane M. Lindor, Yi Lin, Shuo Jiao, Li Hsu, Richard Hayes, Tabitha Harrison, Edward Giovannucci, Steven Gallinger, Charles S. Fuchs, Michelle Cotterchio, Andrew T. Chan, Graham Casey, Peter T. Campbell, Bette Caan, Sonja Berndt, John A. Baron, Carolyn Hutter, and Jian Gong

Abstract

Background: Considerable evidence suggests that cigarette smoking is associated with a higher risk of colorectal cancer (CRC). What is unclear, however, is the impact of quitting smoking on risk attenuation and whether other risk factors for CRC modify this association.Methods: We conducted a pooled analysis of eight studies, including 6,796 CRC cases and 7,770 controls, to evaluate the association between cigarette smoking history and CRC risk and to investigate potential effect modification by other risk factors.Results: Current smokers [OR, 1.26; 95% confidence interval (CI), 1.11–1.43] and former smokers (OR, 1.18; 95% CI, 1.09–1.27), relative to never smokers, showed higher risks of CRC. Former smokers remained at higher CRC risk, relative to never smokers, for up to about 25 years after quitting. The impact of time since quitting varied by cancer subsite: The excess risk due to smoking decreased immediately after quitting for proximal colon and rectal cancer but not until about 20 years post-quitting for distal colon cancer. Furthermore, we observed borderline statistically significant additive interactions between smoking status and body mass index [BMI; relative excess risk due to interaction (RERI]), 0.15; 95% CI, −0.01 to 0.31; P = 0.06] and significant additive interaction between smoking status and fruit consumption (RERI, 0.16; 95% CI, 0.01–0.30; P = 0.04).Conclusion: CRC risk remained increased for about 25 years after quitting smoking, and the pattern of decline in risk varied by cancer subsite. BMI and fruit intake modified the risk associated with smoking.Impact: These results contribute to a better understanding of the mechanisms through which smoking impacts CRC etiology. Cancer Epidemiol Biomarkers Prev; 21(11); 1974–85. ©2012 AACR.

Published
2023

34. Data from Genomic Analysis of Germline Variation Associated with Survival of Patients with Colorectal Cancer Treated with Chemotherapy Plus Biologics in CALGB/SWOG 80405 (Alliance)

Author

Kouros Owzar, Mark J. Ratain, Joel S. Parker, Heinz-Josef Lenz, Michiaki Kubo, Alan P. Venook, Yoichi Furukawa, Charles D. Blanke, James T. Auman, Howard L. McLeod, Monica M. Bertagnolli, Graham Casey, Sarah J. Plummer, Stefanie D. Howell, Fang-Shu Ou, Chen Jiang, Amy S. Etheridge, Sushant A. Patil, Alexander B. Sibley, and Federico Innocenti

Abstract

Purpose:Irinotecan/5-fluorouracil (5-FU; FOLFIRI) or oxaliplatin/5-FU (FOLFOX), combined with bevacizumab or cetuximab, are approved, first-line treatments for metastatic colorectal cancer (mCRC). We aimed at identifying germline variants associated with survival in patients with mCRC treated with these regimens in Cancer and Leukemia Group B/SWOG 80405.Experimental Design:Patients with mCRC receiving either FOLFOX or FOLFIRI were randomized to either cetuximab or bevacizumab. DNA from peripheral blood was genotyped for approximately 700,000 SNPs. The association between SNPs and overall survival (OS) was tested in 613 patients of genetically estimated European ancestry using Cox proportional hazards models.Results:The four most significant SNPs associated with OS were three haplotypic SNPs between microsomal glutathione S-transferase 1 (MGST1) and LIM domain only 3 (LMO3, representative HR, 1.56; P = 1.30 × 10−6), and rs11644916 in AXIN1 (HR, 1.39, P = 4.26 × 10−6). AXIN1 is a well-established tumor suppressor gene in colorectal cancer, and rs11644916 (G>A) conferred shorter OS. Median OS for patients with the AA, AG, or GG genotypes was 18.4, 25.6, or 36.4 months, respectively. In 90 patients with stage IV colorectal cancer from The Cancer Genome Atlas (TCGA), rs11649255 in AXIN1 [in almost complete linkage disequilibrium (LD) with rs11644916], was associated with shorter OS (HR, 2.24, P = 0.0096). Using rs11648673 in AXIN1 (in very high LD with rs11644916 and with functional evidence), luciferase activity in three colorectal cancer cell lines was reduced.Conclusions:This is the first large genome-wide association study ever conducted in patients with mCRC treated with first-line standard treatment in a randomized phase III trial. A common SNP in AXIN1 conferred worse OS and the effect was replicated in TCGA. Further studies in colorectal cancer experimental models are required.

Published
2023

35. Data from Mendelian Randomization Study of Body Mass Index and Colorectal Cancer Risk

Author

Peter T. Campbell, Li Hsu, Emily White, Hermann Brenner, Michael Hoffmeister, Polly A. Newcomb, John D. Potter, Cornelia M. Ulrich, John L. Hopper, Mark A. Jenkins, Aung Ko Win, Michelle Cotterchio, Stephen N. Thibodeau, Kana Wu, Mingyang Song, Daniela Seminara, Noralane M. Lindor, Loïc Le Marchand, David J. Duggan, Mark Thornquist, Tabitha A. Harrison, Mengmeng Du, Robert W. Haile, Graham Casey, Stephen J. Chanock, Sonja I. Berndt, Shuji Ogino, Bette J. Caan, John A. Baron, Richard B. Hayes, Steven Gallinger, Tune H. Pers, Anne E. Justice, Bratati Kahali, Adam E. Locke, Andrew T. Chan, Martha L. Slattery, Anja Rudolph, Jenny Chang-Claude, Ulrike Peters, Jian Gong, and Aaron P. Thrift

Abstract

Background: High body mass index (BMI) is consistently linked to increased risk of colorectal cancer for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate the causal association between BMI and colorectal cancer.Methods: We used data from 10,226 colorectal cancer cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study–identified variants associated with higher BMI, as an instrumental variable (IV). We compared the IV odds ratio (IV-OR) with the OR obtained using a conventional covariate-adjusted analysis.Results: Individuals carrying greater numbers of BMI-increasing alleles had higher colorectal cancer risk [per weighted allele OR, 1.31; 95% confidence interval (CI), 1.10–1.57]. Our IV estimation results support the hypothesis that genetically influenced BMI is directly associated with risk for colorectal cancer (IV-OR per 5 kg/m2, 1.50; 95% CI, 1.13–2.01). In the sex-specific IV analyses higher BMI was associated with higher risk of colorectal cancer among women (IV-OR per 5 kg/m2, 1.82; 95% CI, 1.26–2.61). For men, genetically influenced BMI was not associated with colorectal cancer (IV-OR per 5 kg/m2, 1.18; 95% CI, 0.73–1.92).Conclusions: High BMI was associated with increased colorectal cancer risk for women. Whether abdominal obesity, rather than overall obesity, is a more important risk factor for men requires further investigation.Impact: Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 24(7); 1024–31. ©2015 AACR.

Published
2023

36. Data from Identification of Novel Variants in Colorectal Cancer Families by High-Throughput Exome Sequencing

Author

Ellen L. Goode, Stephen N. Thibodeau, Noralane M. Lindor, Loïc Le Marchand, Polly A. Newcomb, John D. Potter, Graham Casey, Steven N. Gallinger, Michael O. Woods, Robert W. Haile, Mark Clendenning, Daniel Buchanan, David J. Duggan, Mark A. Jenkins, Mine S. Cicek, William R. Bamlet, Daniel J. Serie, Brooke L. Fridley, Julie M. Cunningham, Bruce W. Eckloff, Shaun M. Riska, Shannon K. McDonnell, Daniel J. Schaid, Yan W. Asmann, Sumit Middha, Shanaka R. Gunawardena, and Melissa S. DeRycke

Abstract

Background: Colorectal cancer (CRC) in densely affected families without Lynch Syndrome may be due to mutations in undiscovered genetic loci. Familial linkage analyses have yielded disparate results; the use of exome sequencing in coding regions may identify novel segregating variants.Methods: We completed exome sequencing on 40 affected cases from 16 multicase pedigrees to identify novel loci. Variants shared among all sequenced cases within each family were identified and filtered to exclude common variants and single-nucleotide variants (SNV) predicted to be benign.Results: We identified 32 nonsense or splice-site SNVs, 375 missense SNVs, 1,394 synonymous or noncoding SNVs, and 50 indels in the 16 families. Of particular interest are two validated and replicated missense variants in CENPE and KIF23, which are both located within previously reported CRC linkage regions, on chromosomes 1 and 15, respectively.Conclusions: Whole-exome sequencing identified DNA variants in multiple genes. Additional sequencing of these genes in additional samples will further elucidate the role of variants in these regions in CRC susceptibility.Impact: Exome sequencing of familial CRC cases can identify novel rare variants that may influence disease risk. Cancer Epidemiol Biomarkers Prev; 22(7); 1239–51. ©2013 AACR.

Published
2023

37. Supplemental Table 1 from Association of the Colorectal CpG Island Methylator Phenotype with Molecular Features, Risk Factors, and Family History

Author

Kimberly D. Siegmund, Peter W. Laird, Joanne P. Young, John L. Hopper, Robert W. Haile, John A. Baron, Dennis J. Ahnen, Graham Casey, Peter T. Campbell, Polly A. Newcomb, Bharati Bapat, Teresa Selander, Steven Gallinger, Darshana Daftary, Noralane M. Lindor, Loic Le Marchand, Mariana C. Stern, Amit D. Joshi, Christophe Rosty, Mark Clendenning, Rhiannon Walters, Daniel D. Buchanan, Tiffany I. Long, A. Joan Levine, and Daniel J. Weisenberger

Abstract

Supplemental Table 1. Distribution of CIMP status1 by selected characteristics

Published
2023

38. Data from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.

Published
2023

39. Supplementary Data and Supplementary Tables 1 and 2 from Genetic Predictors of Circulating 25-Hydroxyvitamin D and Risk of Colorectal Cancer

Author

Andrew T. Chan, Ulrike Peters, Peter Kraft, Brent W. Zanke, Kana Wu, Emily White, Jean Wactawski-Wende, Martha L. Slattery, Daniela Seminara, Fredrick R. Schumacher, Robert E. Schoen, John D. Potter, Kimmie Ng, Polly A. Newcomb, Hongmei Nan, JoAnn E. Manson, Jing Ma, Mathieu Lemire, Loic Le Marchand, Sébastien Küry, Mark A. Jenkins, Thomas J. Hudson, John L. Hopper, Michael Hoffmeister, Brian Henderson, Aditi Hazra, Richard B. Hayes, Tabitha A. Harrison, Edward L. Giovannucci, Steven Gallinger, Charles S. Fuchs, David Duggan, David V. Conti, Stephen J. Chanock, Jenny Chang-Claude, Graham Casey, Bette J. Caan, Hermann Brenner, Stéphane Bézieau, Sonja I. Berndt, John A. Baron, Carolyn M. Hutter, Conghui Qu, and Linda T. Hiraki

Abstract

Contains more detailed information on the individual cohorts contributing to the study and their genotyping results; Supplemental Tables 1 and 2

Published
2023

40. Supplementary Methods and Tables from The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers

Author

Douglas F. Easton, Jacques Simard, Stephen J. Chanock, Georgia Chenevix-Trench, Paul D.P. Pharoah, Antonis C. Antoniou, Daniela Seminara, Elizabeth Gillanders, Michael F. Seldin, Rosalind A. Eeles, Ulrike Peters, Ali Amin Al Olama, Jonathan Marchini, Rayjean J. Hung, Laura Ottini, Rita Schmutzler, Mads Thomassen, Kenneth Offit, Sue K. Park, John K. Field, Jack A. Taylor, Christopher K. Edlund, Tameka Shelford, Stephanie L. Schmit, Sylvie Laboissiere, Andrew Berchuck, Sune F. Nielsen, Marc T. Goodman, Deborah J. Thompson, Yongyong Shi, Hongbing Shen, Tracy A. O'Mara, Marjorie Riggan, Paul Brennan, Linda E. Kelemen, Sara Benlloch, Catherine M. Phelan, James D. McKay, Marcia Adams, Sara Lindström, Liesel FitzGerald, Peter Kraft, Zsofia Kote-Jarai, Katja Butterbach, Julie M. Cunningham, Judith Manz, Penny Soucy, Karoline Kuchenbaecker, Andrew Lee, Lesley McGuffog, Hua Ling, Belynda D. Hicks, Irene Brüske-Hohlfeld, Melanie Waldenberger, Angela Risch, Heike Bickeböller, David V. Conti, Graham G. Giles, Judith L. Forman, Fergus J. Couch, David E. Goldgar, Stephen Demetriades, Stefanie Nelson, David J. Van Den Berg, François Bacot, Daniel Vincent, Daniel Tessier, Craig Luccarini, Ahsan Kamal, Christopher A. Haiman, Charlisse Caga-Anan, Stig E. Bojesen, Dennis J. Hazelett, Gerhard A. Coetzee, Elizabeth Pugh, Jane Romm, Xiangjun Xiao, Yafang Li, Amanda B. Spurdle, Kimberly Doheny, Laura Fachal, Kyriaki Michailidou, Alison M. Dunning, Stephen B. Gruber, Thomas A. Sellers, David J. Hunter, Graham Casey, Simon A. Gayther, Fredrick R. Schumacher, Jinyoung Byun, Zhaoming Wang, Joe Dennis, and Christopher I. Amos

Abstract

Supplementary Methods and Tables

Published
2023

41. Data Supplement from Gene–Environment Interaction Involving Recently Identified Colorectal Cancer Susceptibility Loci

Author

Emily White, Li Hsu, Ulrike Peters, Brent W. Zanke, Greg S. Warnick, Cornelia M. Ulrich, Mark Thornquist, Fridtjof Thomas, Deanna L. Stelling, Martha L. Slattery, Daniela Seminara, Robert E. Schoen, Anja Rudolph, John D. Potter, Bethann M. Pflugeisen, Heather M. Ochs-Balcom, Polly A. Newcomb, Jing Ma, Mathieu Lemire, Loic Le Marchand, Laurence N. Kolonel, Shuo Jiao, Mark A. Jenkins, John L. Hopper, Michael Hoffmeister, Brian E. Henderson, Richard B. Hayes, Tabitha A. Harrison, Jian Gong, Edward L. Giovannucci, Charles S. Fuchs, David Duggan, Mengmeng Du, Michelle Cotterchio, Stephen J. Chanock, Jenny Chang-Claude, Andrew T. Chan, Graham Casey, Christopher S. Carlson, Peter T. Campbell, Bette J. Caan, Hermann Brenner, Sonja I. Berndt, Jessica Minnier, Carolyn M. Hutter, and Elizabeth D. Kantor

Abstract

Supplemental Table 3. Environmental Factors and colorectal cancer: associations by study design

Published
2023

42. Data from The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers

Author

Douglas F. Easton, Jacques Simard, Stephen J. Chanock, Georgia Chenevix-Trench, Paul D.P. Pharoah, Antonis C. Antoniou, Daniela Seminara, Elizabeth Gillanders, Michael F. Seldin, Rosalind A. Eeles, Ulrike Peters, Ali Amin Al Olama, Jonathan Marchini, Rayjean J. Hung, Laura Ottini, Rita Schmutzler, Mads Thomassen, Kenneth Offit, Sue K. Park, John K. Field, Jack A. Taylor, Christopher K. Edlund, Tameka Shelford, Stephanie L. Schmit, Sylvie Laboissiere, Andrew Berchuck, Sune F. Nielsen, Marc T. Goodman, Deborah J. Thompson, Yongyong Shi, Hongbing Shen, Tracy A. O'Mara, Marjorie Riggan, Paul Brennan, Linda E. Kelemen, Sara Benlloch, Catherine M. Phelan, James D. McKay, Marcia Adams, Sara Lindström, Liesel FitzGerald, Peter Kraft, Zsofia Kote-Jarai, Katja Butterbach, Julie M. Cunningham, Judith Manz, Penny Soucy, Karoline Kuchenbaecker, Andrew Lee, Lesley McGuffog, Hua Ling, Belynda D. Hicks, Irene Brüske-Hohlfeld, Melanie Waldenberger, Angela Risch, Heike Bickeböller, David V. Conti, Graham G. Giles, Judith L. Forman, Fergus J. Couch, David E. Goldgar, Stephen Demetriades, Stefanie Nelson, David J. Van Den Berg, François Bacot, Daniel Vincent, Daniel Tessier, Craig Luccarini, Ahsan Kamal, Christopher A. Haiman, Charlisse Caga-Anan, Stig E. Bojesen, Dennis J. Hazelett, Gerhard A. Coetzee, Elizabeth Pugh, Jane Romm, Xiangjun Xiao, Yafang Li, Amanda B. Spurdle, Kimberly Doheny, Laura Fachal, Kyriaki Michailidou, Alison M. Dunning, Stephen B. Gruber, Thomas A. Sellers, David J. Hunter, Graham Casey, Simon A. Gayther, Fredrick R. Schumacher, Jinyoung Byun, Zhaoming Wang, Joe Dennis, and Christopher I. Amos

Abstract

Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits.Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background.Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis.Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures.Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.

Published
2023

43. Supplementary Material 2 from A Pooled Analysis of Smoking and Colorectal Cancer: Timing of Exposure and Interactions with Environmental Factors

Author

Ulrike Peters, John Potter, Emily White, Greg Warnick, Fridtjof Thomas, Deanna Stelling, Martha L. Slattery, Daniela Seminara, Robert Schoen, Thomas Rohan, Amanda I. Phipps, Bethann Pflugeisen, Polly Newcomb, Noralane M. Lindor, Yi Lin, Shuo Jiao, Li Hsu, Richard Hayes, Tabitha Harrison, Edward Giovannucci, Steven Gallinger, Charles S. Fuchs, Michelle Cotterchio, Andrew T. Chan, Graham Casey, Peter T. Campbell, Bette Caan, Sonja Berndt, John A. Baron, Carolyn Hutter, and Jian Gong

Abstract

PDF file - 68K, The description of smoking variables included in this analysis

Published
2023

44. Supplementary Methods, Tables 1 - 6 from A Genome-wide Association Study of Early-Onset Breast Cancer Identifies PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age

Author

Alice S. Whittemore, Nancy J. Cox, Douglas F. Easton, Dan Nicolae, Fernando Rivadeneira, Andre G. Uitterlinden, Hanne Meijers-Heijboer, Quinten Waisfisz, Paul Pharoah, Alison M. Dunning, Clare Turnbull, Nazneen Rahman, Jianjun Liu, Astrid Irwanto, Kamila Czene, Per Hall, Carl Blomqvist, Kristiina Aittomäki, Heli Nevanlinna, Norbert Dahmen, Dieter Flesch-Janys, Jennifer Stone, Quang Minh Bui, Daniel F. Schmidt, Enes Makalic, Rebecca Hein, Lars Beckmann, Magdalena Lochmann, Bertram Müller-Myhsok, Rita K. Schmutzler, Alfons Meindl, Stephen J. Chanock, David J. Hunter, Mark Lathrop, Isabel dos Santos Silva, Olivia Fletcher, Julian Peto, Daniel J. Park, Carmel Apicella, Kyriaki Michailidou, Polly Newcomb, Noralane M. Lindor, Mark Jenkins, Robert Haile, Steve Gallinger, David Duggan, David Conti, Eunjung Lee, Regina M. Santella, Graham G. Giles, Melissa C. Southey, Julia A. Knight, Graham Casey, Daniela Seminara, Duncan C. Thomas, Marilie D. Gammon, Giske Ursin, Kathi Malone, Esther M. John, John L. Hopper, Irene Andrulis, Jenny Chang-Claude, Stephanie Melkonian, Maria Argos, Rachelle Brutus, Shantanu Roy, Farzana Jasmine, Jianxin Shi, Anna Felberg, Valerie McGuire, Eric Gamazon, Lin Tong, Brandon L. Pierce, Muhammad G. Kibriya, Jerry Halpern, and Habibul Ahsan

Abstract

PDF file - 197K, Table S1. Discovery set study populations. Table S2. Distribution of discovery set subjects by site, case-control status and chip. Table S3. Discovery set quality control summary. Table S4. SNPs with score-based P-values < 4 X 10-8 among 58016 SNPs for which Plink aborted the logistic regressions. Table S5. Replication set study populations. Table S6. Distribution of replication set subjects by site, case-control status and

Published
2023

45. Data from Gene–Environment Interaction Involving Recently Identified Colorectal Cancer Susceptibility Loci

Author

Emily White, Li Hsu, Ulrike Peters, Brent W. Zanke, Greg S. Warnick, Cornelia M. Ulrich, Mark Thornquist, Fridtjof Thomas, Deanna L. Stelling, Martha L. Slattery, Daniela Seminara, Robert E. Schoen, Anja Rudolph, John D. Potter, Bethann M. Pflugeisen, Heather M. Ochs-Balcom, Polly A. Newcomb, Jing Ma, Mathieu Lemire, Loic Le Marchand, Laurence N. Kolonel, Shuo Jiao, Mark A. Jenkins, John L. Hopper, Michael Hoffmeister, Brian E. Henderson, Richard B. Hayes, Tabitha A. Harrison, Jian Gong, Edward L. Giovannucci, Charles S. Fuchs, David Duggan, Mengmeng Du, Michelle Cotterchio, Stephen J. Chanock, Jenny Chang-Claude, Andrew T. Chan, Graham Casey, Christopher S. Carlson, Peter T. Campbell, Bette J. Caan, Hermann Brenner, Sonja I. Berndt, Jessica Minnier, Carolyn M. Hutter, and Elizabeth D. Kantor

Abstract

Background: Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer. Prior research has evaluated the presence of gene–environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279.Methods: Data on 9,160 cases and 9,280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, postmenopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons.Results: None of the permutation-adjusted P values reached statistical significance.Conclusions: The associations between recently identified genetic susceptibility loci and colorectal cancer are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors.Impact: Results suggest no evidence of strong gene–environment interactions involving the recently identified 16 susceptibility loci for colorectal cancer taken one at a time. Cancer Epidemiol Biomarkers Prev; 23(9); 1824–33. ©2014 AACR.

Published
2023

46. Supplementary Table 1 from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Variants selected for replication

Published
2023

47. Supplementary Material: Funding, Acknowledgements, Consortia, and Bioinformatics Tools Funding sources from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Author

Rayjean J. Hung, Brian E. Henderson, Christopher A. Haiman, David J. Hunter, Douglas F. Easton, Thomas A. Sellers, Christopher I. Amos, Stephen B. Gruber, Ulrike Peters, Jian Gong, Stephen J. Chanock, Daniela Seminara, Qiyuan Li, Matthew L. Freedman, Wim Timens, David Nickle, Ma'en Obeidat, Yohan Bossé, Atsushi Takahashi, Kouya Shiraishi, Xiao-Ou Shu, Zhibin Hu, Hongbing Shen, Yongyue Wei, David C. Christiani, Jonathan P. Tyrer, Y. Ann Chen, Patrick Sulem, Kari Stefansson, Simon N. Stacey, Julius Gudmundsson, Thorunn Rafnar, Michael O. Woods, Stephen N. Thibodeau, Stephanie L. Schmit, Noralene M. Lindor, Li Li, Loïc Le Marchand, Mark Jenkins, Robert W. Haile, Steven Gallinger, Christopher K. Edlund, David V. Conti, Graham Casey, Daniel D. Buchanan, Wei Zheng, Xiaohong R. Yang, Alice S. Whittemore, Zhaoming Wang, Andre G. Uitterlinden, Clare Turnbull, Ruth C. Travis, Rulla Tamimi, Melissa C. Southey, Rita K. Schmutzler, Daniel F. Schmidt, Maria Jose Sanchez, Nazneen Rahman, Ross L. Prentice, Julian Peto, Petra H. Peeters, Heli Nevanlinna, Taru A. Muranen, Bertram Müller-Myhsok, Alfons Meindl, Enes Makalic, Eiliv Lund, Jianjun Liu, Peter Lichtner, Muhammad G. Kibriya, Rudolf Kaaks, Mattias Johansson, Astrid Irwanto, John L. Hopper, Albert Hofman, Rebecca Hein, Aditi Hazra, Per Hall, Nichola Johnson, Mia M. Gaudet, Montserrat Garcia-Closas, Olivia Fletcher, Dieter Flesch-Janys, Jonine D. Figueroa, A. Heather Eliassen, Isabel dos-Santos-Silva, Kamila Czene, Federico Canzian, Carl Blomquist, Laura Baglietto, Kristiina Aittomäki, Habibul Ahsan, Muriel A. Adank, Emily White, Martha L. Slattery, Robert E. Schoen, Polly A. Newcomb, Jonathan K. Kocarnik, Thomas J. Hudson, Jenny Chang-Claude, Andrew T. Chan, Hermann Brenner, Stephane Bezieau, Brett M. Reid, Harvey A. Risch, Jennifer B. Permuth, Ellen L. Goode, Walter C. Willett, Fredrik Wiklund, Victoria L. Stevens, Meir J. Stampfer, Kenneth Muir, Jing Ma, Zsofia Kote-Jarai, Henrik Grönberg, Edward L. Giovannucci, Sonja I. Berndt, Ali Amin Al Olama, Angela Risch, Neil Caporaso, Maria Teresa Landi, Richard S. Houlston, Heike Bickeböller, Paul Brennan, Sara Lindström, Joellen M. Schildkraut, Fredrick R. Schumacher, Nilanjan Chatterjee, Rosalind A. Eeles, Paul D. Pharoah, Peter Kraft, and Gordon Fehringer

Abstract

Funding sources, acknowledgements, consortia involved in study and bioinformatics tools used

Published
2023

48. Data from Confirmation of Linkage to and Localization of Familial Colon Cancer Risk Haplotype on Chromosome 9q22

Author

Georgia L. Wiesner, Sanford D. Markowitz, Robert Elston, Joseph Willis, Susan Lewis, Mark Adams, Steve Gallinger, Daniel Buchanan, Joanne Young, Mark Jenkins, John Hopper, Robert Haile, Graham Casey, Loic Le Marchand, Robert Jenkins, Brooke L. Fridley, Ellen L. Goode, Noralane Lindor, Cornelia M. Ulrich, Elizabeth M. Poole, Polly Newcomb, John D. Potter, Leanna Natale, Chee Paul Lin, Indra Adrianto, Kishore Guda, and Courtney Gray-McGuire

Abstract

Genetic risk factors are important contributors to the development of colorectal cancer. Following the definition of a linkage signal at 9q22-31, we fine mapped this region in an independent collection of colon cancer families. We used a custom array of single-nucleotide polymorphisms (SNP) densely spaced across the candidate region, performing both single-SNP and moving-window association analyses to identify a colon neoplasia risk haplotype. Through this approach, we isolated the association effect to a five-SNP haplotype centered at 98.15 Mb on chromosome 9q. This haplotype is in strong linkage disequilibrium with the haplotype block containing HABP4 and may be a surrogate for the effect of this CD30 Ki-1 antigen. It is also in close proximity to GALNT12, also recently shown to be altered in colon tumors. We used a predictive modeling algorithm to show the contribution of this risk haplotype and surrounding candidate genes in distinguishing between colon cancer cases and healthy controls. The ability to replicate this finding, the strength of the haplotype association (odds ratio, 3.68), and the accuracy of our prediction model (∼60%) all strongly support the presence of a locus for familial colon cancer on chromosome 9q. Cancer Res; 70(13); 5409–18. ©2010 AACR.

Published
2023

49. Supplementary Table 1 from Confirmation of Linkage to and Localization of Familial Colon Cancer Risk Haplotype on Chromosome 9q22

Author

Georgia L. Wiesner, Sanford D. Markowitz, Robert Elston, Joseph Willis, Susan Lewis, Mark Adams, Steve Gallinger, Daniel Buchanan, Joanne Young, Mark Jenkins, John Hopper, Robert Haile, Graham Casey, Loic Le Marchand, Robert Jenkins, Brooke L. Fridley, Ellen L. Goode, Noralane Lindor, Cornelia M. Ulrich, Elizabeth M. Poole, Polly Newcomb, John D. Potter, Leanna Natale, Chee Paul Lin, Indra Adrianto, Kishore Guda, and Courtney Gray-McGuire

Abstract

Supplementary Table 1 from Confirmation of Linkage to and Localization of Familial Colon Cancer Risk Haplotype on Chromosome 9q22

Published
2023

50. Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry

Author

Fei Chen, Ravi K. Madduri, Alex A. Rodriguez, Burcu F. Darst, Alisha Chou, Xin Sheng, Anqi Wang, Jiayi Shen, Edward J. Saunders, Suhn K. Rhie, Jeannette T. Bensen, Sue A. Ingles, Rick A. Kittles, Sara S. Strom, Benjamin A. Rybicki, Barbara Nemesure, William B. Isaacs, Janet L. Stanford, Wei Zheng, Maureen Sanderson, Esther M. John, Jong Y. Park, Jianfeng Xu, Ying Wang, Sonja I. Berndt, Chad D. Huff, Edward D. Yeboah, Yao Tettey, Joseph Lachance, Wei Tang, Christopher T. Rentsch, Kelly Cho, Benjamin H. Mcmahon, Richard B. Biritwum, Andrew A. Adjei, Evelyn Tay, Ann Truelove, Shelley Niwa, Thomas A. Sellers, Kosj Yamoah, Adam B. Murphy, Dana C. Crawford, Alpa V. Patel, William S. Bush, Melinda C. Aldrich, Olivier Cussenot, Gyorgy Petrovics, Jennifer Cullen, Christine M. Neslund-Dudas, Mariana C. Stern, Zsofia Kote-Jarai, Koveela Govindasami, Michael B. Cook, Anand P. Chokkalingam, Ann W. Hsing, Phyllis J. Goodman, Thomas J. Hoffmann, Bettina F. Drake, Jennifer J. Hu, Jacob M. Keaton, Jacklyn N. Hellwege, Peter E. Clark, Mohamed Jalloh, Serigne M. Gueye, Lamine Niang, Olufemi Ogunbiyi, Michael O. Idowu, Olufemi Popoola, Akindele O. Adebiyi, Oseremen I. Aisuodionoe-Shadrach, Hafees O. Ajibola, Mustapha A. Jamda, Olabode P. Oluwole, Maxwell Nwegbu, Ben Adusei, Sunny Mante, Afua Darkwa-Abrahams, James E. Mensah, Halimatou Diop, Stephen K. Van Den Eeden, Pascal Blanchet, Jay H. Fowke, Graham Casey, Anselm J. Hennis, Alexander Lubwama, Ian M. Thompson, Robin Leach, Douglas F. Easton, Michael H. Preuss, Ruth J. Loos, Susan M. Gundell, Peggy Wan, James L. Mohler, Elizabeth T. Fontham, Gary J. Smith, Jack A. Taylor, Shiv Srivastava, Rosaline A. Eeles, John D. Carpten, Adam S. Kibel, Luc Multigner, Marie-Élise Parent, Florence Menegaux, Geraldine Cancel-Tassin, Eric A. Klein, Caroline Andrews, Timothy R. Rebbeck, Laurent Brureau, Stefan Ambs, Todd L. Edwards, Stephen Watya, Stephen J. Chanock, John S. Witte, William J. Blot, J. Michael Gaziano, Amy C. Justice, David V. Conti, Christopher A. Haiman, University of Southern California (USC), Keck School of Medicine [Los Angeles], Centre de Recherche pour les Pathologies Prostatiques [Paris] (CeRePP), Sorbonne Université (SU), Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), CHU Pointe-à-Pitre/Abymes [Guadeloupe], Centre de recherche en épidémiologie et santé des populations (CESP), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay

Subjects
Prostate cancer, MESH: Humans, Urology, MESH: Genetic Predisposition to Disease, MESH: Black People, [SDV.CAN]Life Sciences [q-bio]/Cancer, [SDV.MHEP.UN]Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology, MESH: Male, Polygenic risk score, African ancestry, MESH: Risk Factors, MESH: Prostatic Neoplasms, MESH: Genome-Wide Association Study, Susceptibility loci, Aggressive prostate cancer
Abstract

Background: Genetic factors play an important role in prostate cancer (PCa) susceptibility.Objective: To discover common genetic variants contributing to the risk of PCa in men of African ancestry.Design, setting, and participants: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.Outcome measurements and statistical analysis: Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness.Results and limitations: Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4).Conclusions: This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry.Patient summary: In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.

Published
2023

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