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Chen, Yu

https://orcid.org/0000-0002-1519-4894

Mayo Clinic

NYU Langone Health

Citations 5

Different diabetes types and pancreatic ductal adenocarcinoma: a Mendelian randomization and pathway/gene-set analysis
Zhang, Ting , Mohindroo, Chirayu , Wang, Xiaoyu , Dutta, Diptavo , Liu, Jia , Katta, Shilpa, Li, Shengchao A. , Wang, Jiahui , Antwi, Samuel O. , Bracci, Paige M. , Du, Mengmeng, Gallinger, Steven , Goodman, Phyllis J. , Katzke, Verena, Patel, Alpa V. , Visvanathan, Kala , Andreotti, Gabriella , Brennan, Paul , Buring, Julie E. , Chanock, Stephen J., Chen, Yu , Giovannucci, Edward L. , Haiman, Christopher A. , Hassan, Manal M. , Holly, Elizabeth A., Jones, Miranda R. , Kraft, Peter, Kurtz, Robert C. , Ng, Kimmie , Oberg, Ann L. , Peters, Ulrike , Rabe, Kari G. , Rothman, Nathaniel , Sesso, Howard D. , Yuan, Chen, Wolpin, Brian M. , Yu, Kai , Stolzenberg‐Solomon, Rachael Z. , Mohindroo, Chirayu , Wang, Xiaoyu , Dutta, Diptavo , Liu, Jia , Li, Shengchao A , Antwi, Samuel O , Arslan, Alan A , Beane Freeman, Laura E , Canzian, Federico , Du, Mengmeng , Goodman, Phyllis J , Katzke, Verena , Kooperberg, Charles , Marchand, Loïc Le , Neale, Rachel E , Perdomo, Sandra , Shu, Xiao-Ou , Visvanathan, Kala , Van Den Eeden, Stephen K , White, Emily E. , Zheng, Wei , Albanes, Demetrius , Andreotti, Gabriella , Brennan, Paul , Buring, Julie E , Chanock, Stephen Jacob , Chen, Yu , Darst, Burcu F , Ferrari, Pietro , Giovannucci, Edward L , Goggins, Michael G , Haiman, Christopher A , Hassan, Manal M , Hung, Rayjean J , Jones, Miranda R , Kraft, Peter , Malats, Nuria , Moore, Steven C , Ng, Kimmie , Oberg, Ann L , Orlow, Irene , Peters, Ulrike , Porta, Miquel , Chaffee, Kari G. , Sánchez, Maria-Jose , Sesso, Howard D , Southey, Melissa C , Um, Caroline Y , Yarmolinsky, James , Yu, Herbert , Yuan, Chen , Zhong, Jun , Wolpin, Brian M , Risch, Harvey A , Amundadottir, Laufey , Klein, Alison P , Yu, Kai , Zhang, Haoyu , Stolzenberg-Solomon, Rachael , Zhang, Ting , Hua, Xing , Arslan, Alan A. , Freeman, Laura E. Beane , Canzian, Federico , Kooperberg, Charles , Marchand, Loı̈c Le , Neale, Rachel Ε. , Zheng, Wei , Albanes, Demetrius , Bamlet, William R. , Darst, Burcu F. , Goggins, Michael , Hung, Rayjean J. , Malats, Núria , Moore, Steven C. , Orlow, Irene , Porta, Miquel , Sánchez, María‐José , Silverman, Debra T. , Southey, Melissa C. , Um, Caroline Y. , Yu, Kai , Risch, Harvey A. , Ámundadóttir, Laufey T. , Klein, Alison P.

JNCI: Journal of the National Cancer Institute | November 8, 2025 | Volume: 118 | Issue: 3 | Pages: 437-447

10.1093/jnci/djaf308 Get It

Abstract Background The associations between different types of diabetes, characterized by distinct pathophysiology and genetic architecture, and pancreatic ductal adenocarcinoma (PDAC) risk are not understood. Methods We investigated associations of genetic susceptibility to type 2 diabetes (T2D), 8 T2D mechanistic clusters, type 1 diabetes (T1D), and maturity-onset diabetes of the young (MODY) with PDAC risk. We used genome-wide association study (GWAS) summary-level statistics for T2D (242 283 cases, 1 569 734 controls), T1D (18 942 cases, 501 638 controls), and PDAC (10 244 cases and 360 535 controls) in individuals of European ancestry. Results Two-sample Mendelian randomization (MR) using the Robust Adjusted Profile Score (MR-RAPS) method indicated that genetically predicted T2D was associated with PDAC risk (OR = 1.10; 95% CI = 1.05 to 1.15), particularly the T2D obesity (OR = 1.28; 95% CI = 1.15 to 1.42) and lipodystrophy (OR = 1.25; 95% CI = 1.03 to 1.51) clusters. No association was observed for T1D with PDAC risk (OR = 1.01; 95% CI = 0.99 to 1.02). Pathway/gene-set analysis using the summary-based Adaptive Rank Truncated Product (sARTP) method revealed a significant association between the MODY gene-sets and PDAC risk (P = 1.5 × 10−8), which remained after excluding 20 known PDAC GWAS loci (P = 7.6 × 10−4). HNF1A, FOXA3, and HNF4A were the top contributing genes after excluding the previously identified GWAS loci regions. Conclusions Our results from this genetic association study support that T2D, particularly the obesity and lipodystrophy mechanistic clusters, and MODY genomic susceptibility regions play a role in the etiology of PDAC.
Abstract 3583: The Breast Cancer Risk Prediction Project: a resource of 1.8 million women with diverse backgrounds from 20 prospective cohorts to improve breast cancer risk prediction and advance breast cancer epidemiology
Kraft, Peter, O’Meara, Ellen S. , Rohan, Thomas, Neuhouser, Marian L, Vachon, Celine M, Haiman, Christopher, White, Emily , Lee, I‐Min , Gaudet, Mia M. , Chatterjee, Nilanjan , Freeman, Laura E. Beane , Palmer, Julie R. , Genkinger, Jeanine M. , Lacey, James V. , Teras, Lauren R. , Visvanathan, Kala , Milne, Roger L. , Chen, Yu , Eliassen, A. Heather , Kitahara, Cari M. , O’Brien, Katie M. , Anderson, Garnet L. , Campbell, Archie I , Fortner, Renée T. , Lagerros, Ylva Trolle , Sandin, Sven , García‐Closas, Montserrat

Cancer Research | April 21, 2025 | Volume: 85 | Issue: 8_Supplement_1 | Pages: 3583-3583

10.1158/1538-7445.am2025-3583 Get It

Abstract Breast cancer risk assessment tools are widely used in clinical practice to guide decisions regarding screening timing and modality, lifestyle interventions, genetic testing, preventive therapy, and risk-reducing surgery. Although a number of tools designed for the general population are used in practice, they face a series of challenges including: (i) modest discriminatory ability due to lack of a unified model that flexibly incorporates a comprehensive set of risk factors; (ii) inability to produce subtype-specific risk estimates, relevant for tailoring screening and/or preventive strategies (e.g. prophylactic endocrine therapy that is effective only for hormone receptor positive tumors); (iii) lack of data from diverse populations to build models that work well for all women; and, (iv) scarcity of opportunities for comparative validation of different models. The Breast Cancer Risk Prediction Project (BCRPP), a collaboration currently including 20 prospective cohorts from the National Cancer Institute’s Cohort Consortium, is addressing these challenges by harmonizing, sharing, and analyzing data on over 1.8 million women, over 115, 000 of whom have developed breast cancer. The BCRPP is developing a comprehensive tool that will predict breast cancer risk, overall and by subtypes, across major racial and ethnic groups in the United States. This tool incorporates known and emerging risk factors (e.g. reproductive history, anthropometry, smoking, alcohol intake, medication use, mammography, family history, and measured genotypes). In parallel to model building and validation efforts, BCRPP investigators are developing privacy-preserving web and mobile interfaces to deliver the risk tools to patients and clinicians. Here we present descriptive data on participating cohorts (e.g. dates of enrollment, ages at enrollment, length of follow up, numbers of cases by subtype), summarize missing data patterns and our approach to model development and validation that accounts for heterogeneity in missingness patterns across cohorts, and describe data governance procedures and data sharing infrastructure (including pooled and federated analyses, to account for policy limitations on sharing individual data). Descriptive information and procedures for requesting and accessing data are available via the BCRPP data platform (https://epidataplatforms.cancer.gov/bcrpp/). Although originally assembled for risk model development, these data on a large and diverse sample of women with extensive harmonized risk factors and covariates can be a resource to address other outstanding questions in breast cancer epidemiology across time, the lifecourse, and diverse populations. Citation Format: Peter Kraft, Laura Beane-Freeman, Julie Palmer, Ellen O'Meara, Jeanine Genkinger, James Lacey, Thomas Rohan, Lauren Teras, Marian L. Neuhouser, Kala Visvanathan, Celine Vachon, Roger Milne, Christopher Haiman, Yu Chen, Heather Eliassen, Cari Kitahara, Katie O'Brien, Emily White, Garnet Anderson, I-Min Lee, Archie Campbell, Renee Fortner, Ylva Lagerros, Sven Sandin, Mia Gaudet, Montserrat Garcia-Closas, Nilanjan Chatterjee. The Breast Cancer Risk Prediction Project: a resource of 1.8 million women with diverse backgrounds from 20 prospective cohorts to improve breast cancer risk prediction and advance breast cancer epidemiology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3583.
International Pooled Analysis of Leisure-Time Physical Activity and Premenopausal Breast Cancer in Women From 19 Cohorts
Timmins, Iain R. , Jones, Michael E. , O’Brien, Katie M. , Adami, Hans‐Olov , Aune, Dagfinn , Brantley, Kristen D. , Chen, Yu , DeHart, Jessica Clague , Clendenen, Tess V. , Fournier, A. , Hankinson, Susan E. , Houlston, Richard S. , Kirsh, Victoria A. , Linet, Martha S. , May, Anne M. , Rohan, Thomas E. , Ruddy, Kathryn J. , Sund, Malin , Vachon, Celine M. , Vatten, Lars J. , Visvanathan, Kala , Yuan, Jian‐Min , Zheng, Wei , Nichols, Hazel B. , Baglietto, Laura , Bertrand, Kimberly A , Brantley, Kristen D , Clague DeHart, Jessica , Clendenen, Tess V , Dossus, Laure , Eliassen, A Heather , Fletcher, Olivia , Fournier, Agnès , Håkansson, Niclas , Houlston, Richard S , Joshu, Corinne E , Kirsh, Victoria A , Kitahara, Cari M , Linet, Martha S , Park, Hannah Lui , Lynch, Brigid M , May, Anne M , Mellemkjær, Lene , Milne, Roger L , Palmer, Julie R , Ruddy, Kathryn J , Sánchez, Maria-Jose , Shu, Xiao-Ou , Steindorf, Karen , Sund, Malin , Vachon, Celine M. , Vatten, Lars J , Visvanathan, Kala , Weiderpass, Elisabete , Willett, Walter C , Wolk, Alicja , Zheng, Wei , Nichols, Hazel B , Sandler, Dale P , Jones, Michael E , O'Brien, Katie M , Aune, Dagfinn , Chen, Yu , Baglietto, Laura , Bertrand, Kimberly A. , Eliassen, A. Heather , Fletcher, Olivia , Håkansson, Niclas , Hankinson, Susan E. , Kitahara, Cari M. , Koh, Woon‐Puay , Milne, Roger L. , Palmer, Julie R. , Ricceri, Fulvio , Sánchez, María‐José , Shu, Xiao‐Ou , Smith-Byrne, Karl , Weiderpass, Elisabete , Willett, Walter C. , Wolk, Alicja , Sandler, Dale P. , Swerdlow, Anthony J. , Schoemaker, Minouk J.

Journal of Clinical Oncology | December 11, 2023 | Volume: 42 | Issue: 8 | Pages: 927-939

10.1200/jco.23.01101 Get It

PURPOSE There is strong evidence that leisure-time physical activity is protective against postmenopausal breast cancer risk but the association with premenopausal breast cancer is less clear. The purpose of this study was to examine the association of physical activity with the risk of developing premenopausal breast cancer. METHODS We pooled individual-level data on self-reported leisure-time physical activity across 19 cohort studies comprising 547,601 premenopausal women, with 10,231 incident cases of breast cancer. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% CIs for associations of leisure-time physical activity with breast cancer incidence. HRs for high versus low levels of activity were based on a comparison of risk at the 90th versus 10th percentiles of activity. We assessed the linearity of the relationship and examined subtype-specific associations and effect modification across strata of breast cancer risk factors, including adiposity. RESULTS Over a median 11.5 years of follow-up (IQR, 8.0-16.1 years), high versus low levels of leisure-time physical activity were associated with a 6% (HR, 0.94 [95% CI, 0.89 to 0.99]) and a 10% (HR, 0.90 [95% CI, 0.85 to 0.95]) reduction in breast cancer risk, before and after adjustment for BMI, respectively. Tests of nonlinearity suggested an approximately linear relationship ( Pnonlinearity = .94). The inverse association was particularly strong for human epidermal growth factor receptor 2–enriched breast cancer (HR, 0.57 [95% CI, 0.39 to 0.84]; Phet = .07). Associations did not vary significantly across strata of breast cancer risk factors, including subgroups of adiposity. CONCLUSION This large, pooled analysis of cohort studies adds to evidence that engagement in higher levels of leisure-time physical activity may lead to reduced premenopausal breast cancer risk.
Comparison of Oral Collection Methods for Studies of Microbiota
Vogtmann, Emily , Chen, Jun , Amir, Amnon , Shi, Jianxin , Chen, Yu , Eunes, Mahbubul, Ahmed, Alauddin , Naher, Jabun, Rahman, Anisur, Barmon, Bhaswati, Knight, Rob , Ahsan, Habibul , Abnet, Christian C. , Chia, Nicholas , Abnet, Christian C , Kibriya, Muhammad Ghulam , Islam, Tariqul , Chia, Nicholas , Sinha, Rashmi R. , Chen, Yu

Cancer Epidemiology, Biomarkers & Prevention | September 27, 2018 | Volume: 28 | Issue: 1 | Pages: 137-143

10.1158/1055-9965.epi-18-0312 Get It

Abstract Background: A number of cohort studies have collected Scope mouthwash samples by mail, which are being used for microbiota measurements. We evaluated the stability of Scope mouthwash samples at ambient temperature and determined the comparability of Scope mouthwash with saliva collection using the OMNIgene ORAL Kit. Methods: Fifty-three healthy volunteers from Mayo Clinic and 50 cohort members from Bangladesh provided oral samples. One aliquot of the OMNIgene ORAL and Scope mouthwash were frozen immediately and one aliquot of the Scope mouthwash remained at ambient temperature for 4 days and was then frozen. DNA was extracted and the V4 region of the 16S rRNA gene was PCR amplified and sequenced using the HiSeq. Intraclass correlation coefficients (ICC) were calculated. Results: The overall stability of the Scope mouthwash samples was relatively high for alpha and beta diversity. For example, the meta-analyzed ICC for the Shannon index was 0.86 (95% confidence interval, 0.76–0.96). Similarly, the ICCs for the relative abundance of the top 25 genera were generally high. The comparability of the two sample types was relatively low when measured using ICCs, but were increased by using a Spearman correlation coefficient (SCC) to compare the rank order of individuals. Conclusions: Overall, the Scope mouthwash samples appear to be stable at ambient temperature, which suggests that oral rinse samples received by the mail can be used for microbial analyses. However, Scope mouthwash samples were distinct compared with OMNIgene ORAL samples. Impact: Studies should try to compare oral microbial metrics within one sample collection type.
Comparison of Fecal Collection Methods for Microbiota Studies in Bangladesh
Vogtmann, Emily , Chen, Jun , Chen, Yu , Eunes, Mahbubul, Ahmed, Alauddin , Naher, Jabun, Rahman, Anisur, Amir, Amnon , Shi, Jianxin , Abnet, Christian C. , Nelson, Heidi , Knight, Rob , Ahsan, Habibul , Chia, Nicholas , Kibriya, Muhammad Ghulam , Islam, Tariqul , Chia, Nicholas , Sinha, Rashmi R. , Abnet, Christian C , Chen, Yu

Applied and Environmental Microbiology | March 4, 2017 | Volume: 83 | Issue: 10 | Pages: No page available

10.1128/aem.00361-17 Get It

ABSTRACT To our knowledge, fecal microbiota collection methods have not been evaluated in low- and middle-income countries. Therefore, we evaluated five different fecal sample collection methods for technical reproducibility, stability, and accuracy within the Health Effects of Arsenic Longitudinal Study (HEALS) in Bangladesh. Fifty participants from the HEALS provided fecal samples in the clinic which were aliquoted into no solution, 95% ethanol, RNAlater, postdevelopment fecal occult blood test (FOBT) cards, and fecal immunochemical test (FIT) tubes. Half of the aliquots were frozen immediately at −80°C (day 0) and the remaining samples were left at ambient temperature for 96 h and then frozen (day 4). Intraclass correlation coefficients (ICC) were calculated for the relative abundances of the top three phyla, for two alpha diversity measures, and for four beta diversity measures. The duplicate samples had relatively high ICCs for technical reproducibility at day 0 and day 4 (range, 0.79 to 0.99). The FOBT card and samples preserved in RNAlater and 95% ethanol had the highest ICCs for stability over 4 days. The FIT tube had lower stability measures overall. In comparison to the “gold standard” method using immediately frozen fecal samples with no solution, the ICCs for many of the microbial metrics were low, but the rank order appeared to be preserved as seen by the Spearman correlation. The FOBT cards, 95% ethanol, and RNAlater were effective fecal preservatives. These fecal collection methods are optimal for future cohort studies, particularly in low- and middle-income countries. IMPORTANCE The collection of fecal samples in prospective cohort studies is essential to provide the opportunity to study the effect of the human microbiota on numerous health conditions. However, these collection methods have not been adequately tested in low- and middle-income countries. We present estimates of technical reproducibility, stability at ambient temperature for 4 days, and accuracy comparing a “gold standard” for fecal samples in no solution, 95% ethanol, RNAlater, postdevelopment fecal occult blood test cards, and fecal immunochemical test tubes in a study conducted in Bangladesh. Fecal occult blood test cards and fecal samples stored in 95% ethanol or RNAlater adequately preserve fecal samples in this setting. Therefore, new studies in low- and middle-income countries should include collection of fecal samples using fecal occult blood test cards, 95% ethanol, or RNAlater for prospective cohort studies.