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Screening for pancreatic cancer among smokers as high-risk individuals: Systematic review and meta-analysis of prospective cohort studies

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health Sciences Review 2024年 13卷 100203-100203页

作者： Elder, Melissa M. Vincent Mbous, Yves Paul Rudisill, Toni Marie Kelley, George A. Department of Epidemiology & Biostatistics West Virginia University School of Public Health USA School of Pharmacy Department of Pharmaceutical Systems and Policy West Virginia University Morgantown WV USA PhD Program Advisor for Epidemiology School of Public Health West Virginia University Department of Epidemiology and Biostatistics Robert C. Byrd Health Sciences Center West Virginia University Morgantown WV 26506-9190 USA Meta-Analytic Research Group School of Public Health Department of Epidemiology and Biostatistics Robert C. Byrd Health Sciences Center West Virginia University Morgantown WV 26506-9190 USA School of Public and Population Health and Department of Kinesiology Boise State University Boise Idaho 83725-1835 USA

Highlights•There are no formal screening guidelines for pancreatic cancer and often diagnosed late, with a high mortality rate. •This manuscript provides clinically relevant information for health care providers who manage this patient population. •This research is unique given its focus on asymptomatic versus hereditary diagnosis, using a robust search strategy. •This study is innovative for the following reasons: (1) use of the IVhet model over the less robust random-effects and fixed-effect(s) models that are used, (2) use of what is considered to be the more interpretable DOI plot versus the traditionally used funnel plot for small-study effects, (3) use of what is the more robust LFK index versus the traditionally used Egger's regression intercept test for the quantitative assessment of small-study, (4) use of 95 % prediction intervals, a statistic that is rarely used but a better measure of between-study heterogeneity than Q and I-squared.

关键词： Meta-analysis Pancreatic cancer Screening Smokers

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The overlapping burden of the three leading causes of disability and death in sub-Saharan African children

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Nature Communications 2022年第1期13卷 1-14页

作者： Reiner, Robert C. Welgan, Catherine A. Troeger, Christopher E. Baumann, Mathew M. Weiss, Daniel J. Deshpande, Aniruddha Blacker, Brigette F. Miller-Petrie, Molly K. Earl, Lucas Bhatt, Samir Abolhassani, Hassan Abosetugn, Akine Eshete Abu-Gharbieh, Eman Adekanmbi, Victor Adetokunboh, Olatunji O. Aghaali, Mohammad Aji, Budi Alahdab, Fares Al-Aly, Ziyad Alhassan, Robert Kaba Ali, Saqib Alizade, Hesam Aljunid, Syed Mohamed Almasi-Hashiani, Amir Al-Mekhlafi, Hesham M. Altirkawi, Khalid A. Alvis-Guzman, Nelson Amare, Azmeraw T. Amini, Saeed Amugsi, Dickson A. Ancuceanu, Robert Andrei, Catalina Liliana Ansari, Fereshteh Anvari, Davood Appiah, Seth Christopher Yaw Arabloo, Jalal Aremu, Olatunde Atout, Maha Moh’d Wahbi Ausloos, Marcel Ausloos, Floriane Ayanore, Martin Amogre Aynalem, Yared Asmare Azene, Zelalem Nigussie Badawi, Alaa Baig, Atif Amin Banach, Maciej Bedi, Neeraj Bhagavathula, Akshaya Srikanth Bhandari, Dinesh Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bhutta, Zulfiqar A. Bijani, Ali Birhanu, Tesega Tesega Mengistu Bitew, Zebenay Workneh Boloor, Archith Brady, Oliver J. Butt, Zahid A. Car, Josip Carvalho, Felix Casey, Daniel C. Chattu, Vijay Kumar Chowdhury, Mohiuddin Ahsanul Kabir Chu, Dinh-Toi Coelho, Camila H. Cook, Aubrey J. Damiani, Giovanni Daoud, Farah Gela, Jiregna Darega Darwish, Amira Hamed Daryani, Ahmad Das, Jai K. Davis Weaver, Nicole Deribe, Kebede Desalew, Assefa Dharmaratne, Samath Dhamminda Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Dorostkar, Fariba Dubljanin, Eleonora Duko, Bereket Dwyer-Lindgren, Laura Effiong, Andem El Sayed Zaki, Maysaa El Tantawi, Maha Enany, Shymaa Fattahi, Nazir Feigin, Valery L. Fernandes, Eduarda Ferrara, Pietro Fischer, Florian Foigt, Nataliya A. Folayan, Morenike Oluwatoyin Foroutan, Masoud Frostad, Joseph Jon Fukumoto, Takeshi Gaidhane, Abhay Motiramji Gebrekrstos, Hailemikael Gebrekidan G. K. Gebremeskel, Leake Gebreslassie, Assefa Ayalew Gething, Peter W. Gezae, Kebede Embaye Ghadiri, Keyghobad Ghashghaee, Ahmad Golechha, Mahaveer Gubar Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Malaria Atlas Project University of Oxford Oxford United Kingdom Imperial College London London United Kingdom Department of Laboratory Medicine Karolinska University Hospital Huddinge Sweden Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Public Health Debre Berhan University Debre Berhan Ethiopia Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Population Health Sciences King’s College London London United Kingdom Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Stellenbosch South Africa Department of Global Health Stellenbosch University Cape Town South Africa Department of Epidemiology and Biostatistics Qom University of Medical Sciences Qom Iran Faculty of Medicine and Public Health Jenderal Soedirman University Purwokerto Indonesia Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center Department of Veterans Affairs St Louis MO United States Institute of Health Research University of Health and Allied Sciences Ho Ghana Department of Information Systems College of Economics and Political Science Sultan Qaboos University Muscat Oman Infectious and Tropical Disease Research Center Hormozgan University of Medical Sciences Bandar Abbas Iran Department of Health Policy and Management Kuwait University Safat Kuwait International Centre for Casemix and Clinical Coding National University of Malaysia Bandar Tun Razak Malaysia Department of Epidemiology Arak University of Medical Sciences Arak Iran Medical Research Center

Despite substantial declines since 2000, lower respiratory infections (LRIs), diarrhoeal diseases, and malaria remain among the leading causes of nonfatal and fatal disease burden for children under 5 years of age (under 5), primarily in sub-Saharan Africa (SSA). The spatial burden of each of these diseases has been estimated subnationally across SSA, yet no prior analyses have examined the pattern of their combined burden. Here we synthesise subnational estimates of the burden of LRIs, diarrhoea, and malaria in children under-5 from 2000 to 2017 for 43 sub-Saharan countries. Some units faced a relatively equal burden from each of the three diseases, while others had one or two dominant sources of unit-level burden, with no consistent pattern geographically across the entire subcontinent. Using a subnational counterfactual analysis, we show that nearly 300 million DALYs could have been averted since 2000 by raising all units to their national average. Our findings are directly relevant for decision-makers in determining which and targeting where the most appropriate interventions are for increasing child survival. © 2022, The Author(s).

关键词： Biogeography epidemiology Infectious diseases Malaria

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Urinary oxidative stress biomarkers are associated with preterm birth: an Environmental Influences on Child health Outcomes program study

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AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY 2023年第5期228卷 576.e1-576.e22页

作者： Eick, Stephanie M. Geiger, Sarah D. Alshawabkeh, Akram Aung, Max Barrett, Emily S. Bush, Nicole Carroll, Kecia N. Cordero, Jose F. Goin, Dana E. Ferguson, Kelly K. Kahn, Linda G. Liang, Donghai Meeker, John D. Milne, Ginger L. Nguyen, Ruby H. N. Padula, Amy M. Sathyanarayana, Sheela Taibl, Kaitlin R. Schantz, Susan L. Woodruff, Tracey J. Morello-Frosch, Rachel [a]Gangarosa Department of Environmental Health Rollins School of Public Health Emory University Atlanta GA [b]Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Champaign IL [c]Department of Kinesiology and Community Health University of Illinois at Urbana-Champaign Champaign IL [d]College of Engineering Northeastern University Boston MA [e]Department of Population and Public Health Sciences Keck School of Medicine University of Southern California Los Angeles CA [f]Environmental and Occupational Health Sciences Institute Rutgers School of Public Health Rutgers University Piscataway NJ [g]Department of Psychiatry and Behavioral Sciences University of California San Francisco San Francisco CA [h]Departments of Pediatrics and Environmental Medicine and Public Health The Icahn School of Medicine at Mount Sinai New York NY [i]Department of Epidemiology and Biostatistics College of Public Health University of Georgia Athens GA [j]Program on Reproductive Health and the Environment University of California San Francisco San Francisco CA [k]Epidemiology Branch National Institute of Environmental Health Sciences Durham NC [l]Departments of Pediatrics and Population Health New York University Grossman School of Medicine New York NY [m]Department of Environmental Health Sciences University of Michigan School of Public Health Ann Arbor MI [n]Division of Clinical Pharmacology Department of Medicine Vanderbilt University Medical Center Nashville TN [o]Department of Epidemiology and Community Health University of Minnesota Minneapolis MN [p]Department of Pediatrics University of Washington Seattle WA [q]Seattle Children’s Research Institute Seattle WA [r]Department of Comparative Biosciences University of Illinois at Urbana-Champaign Champaign IL [s]Department of Environmental Science Policy and Management School of Public Health University of California Berkeley Berkeley CA

BACKGROUND: Preterm birth is the leading cause of infant morbidity and mortality worldwide. Elevated levels of oxidative stress have been associated with an increased risk of delivering before term. However, most studies testing this hypothesis have been conducted in racially and demographically homogenous study populations, which do not reflect the diversity within the United States. OBJECTIVE: We leveraged 4 cohorts participating in the Environmental Influences on Child health Outcomes program to conduct the largest study to date examining biomarkers of oxidative stress and preterm birth (N1/41916). Furthermore, we hypothesized that elevated oxidative stress would be associated with higher odds of preterm birth, particularly preterm birth of spontaneous origin. STUDY DESIGN: This study was a pooled analysis and meta-analysis of 4 birth cohorts spanning multiple geographic regions in the mainland United States and Puerto Rico (208 preterm births and 1708 full-term births). Of note, 8-iso-prostaglandin-F2a, 2,3-dinor-5,6-dihydro-8-iso-prostaglandin-F2a (F2-IsoP-M;the major 8-iso-prostaglandin-F2a metabolite), and prostaglandin-F2a were measured in urine samples ob-tained during the second and third trimesters of pregnancy. Logistic regression was used to calculate adjusted odds ratios and 95% confidence intervals for the associations between averaged biomarker concentrations for each participant and all preterm births, spontaneous preterm births, nonspontaneous preterm births (births of medically indicated or unknown origin), and categories of preterm birth (early, moderate, and late). Indi-vidual oxidative stress biomarkers were examined in separate ***: Approximately 11% of our analytical sample was born before term. Relative to full-term births, an interquartile range increase in aver-aged concentrations of F2-IsoP-M was associated with higher odds of all preterm births (odds ratio, 1.29;95% confidence interval, 1.11-1.51), with a stronger association

关键词： 8-iso-prostaglandin-F-2a adverse pregnancy outcomes F- 2- IsoP-M isoprostanes lipid peroxidation oxidative stress oxylipins pre-term birth preterm labor preterm premature rupture of membranes prostaglandin F2a spontaneous preterm birth

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Colorectal cancer susceptibility variants and risk of conventional adenomas and serrated polyps: results from three cohort studies (vol 49, pg 352, 2020)

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INTERNATIONAL JOURNAL OF epidemiology 2020年第1期49卷 352-352页

作者： Hang, Dong Joshi, Amit D. He, Xiaosheng Chan, Andrew T. Jovani, Manol Gala, Manish K. Ogino, Shuji Kraft, Peter Turman, Constance Peters, Ulrike Bien, Stephanie A. Lin, Yi Hu, Zhibin Shen, Hongbing Wu, Kana Giovannucci, Edward L. Song, Mingyang Department of Epidemiology and Biostatistics Jiangsu Key Lab of Cancer Biomarkers Prevention and Treatment Nanjing Medical University Nanjing China Department of Nutrition Harvard T.H. Chan School of Public Health Boston MA USA Clinical and Translational Epidemiology Unit and Division of Gastroenterology Massachusetts General Hospital and Harvard Medical School Boston MA USA Clinical and Translational Epidemiology Unit and Division of Gastroenterology Massachusetts General Hospital and Harvard Medical School Boston MA USA Department of Colorectal Surgery Sixth Affiliated Hospital Sun Yat-sen University Guangzhou China Clinical and Translational Epidemiology Unit and Division of Gastroenterology Massachusetts General Hospital and Harvard Medical School Boston MA USA Channing Division of Network Medicine Brigham and Women’s Hospital and Harvard Medical School Boston MA USA Broad Institute of Massachusetts Institute of Technology and Harvard Cambridge MA USA Clinical and Translational Epidemiology Unit and Division of Gastroenterology Massachusetts General Hospital and Harvard Medical School Boston MA USA Clinical and Translational Epidemiology Unit and Division of Gastroenterology Massachusetts General Hospital and Harvard Medical School Boston MA USA Broad Institute of Massachusetts Institute of Technology and Harvard Cambridge MA USA Department of Oncologic Pathology Dana-Farber Cancer Institute Boston MA USA Program in MPE Molecular Pathological Epidemiology Brigham and Women’s Hospital and Harvard Medical School Boston MA USA Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA Department of Biostatistics Harvard T.H. Chan School of Public Health Boston MA USA Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA Program in Genetic Epidemiology and Statistical Genetics Harvard T.H. Chan School of Public H

Background Increasing evidence suggests that conventional adenomas (CAs) and serrated polyps (SPs) represent two distinct groups of precursor lesions for colorectal cancer (CRC). The influence of common genetic variants on risk of CAs and SPs remain largely *** Among 27 426 participants within three prospective cohort studies, we created a weighted genetic risk score (GRS) based on 40 CRC-related single nucleotide polymorphisms (SNPs) identified in previous genome-wide association studies; and we examined the association of GRS (per one standard deviation increment) with risk of CAs, SPs and synchronous CAs and SPs, by multivariable logistic regression. We also analysed individual variants in the secondary *** During 18-20 years of follow-up, we documented 2952 CAs, 1585 SPs and 794 synchronous CAs and SPs. Higher GRS was associated with increased risk of CAs [odds ratio (OR) = 1.17, 95% confidence interval (CI): 1.12-1.21] and SPs (OR = 1.09, 95% CI: 1.03-1.14), with a stronger association for CAs than SPs (Pheterogeneity=0.01). An even stronger association was found for patients with synchronous CAs and SPs (OR = 1.32), advanced CAs (OR = 1.22) and multiple CAs (OR = 1.25). Different sets of variants were associated with CAs and SPs, with a Spearman correlation coefficient of 0.02 between the ORs associating the 40 SNPs with the two lesions. After correcting for multiple testing, three variants were associated with CAs (rs3802842, rs6983267 and rs7136702) and two with SPs (rs16892766 and rs4779584).Conclusions Common genetic variants play a potential role in the conventional and serrated pathways of CRC. Different sets of variants are identified for the two pathways, further supporting the aetiological heterogeneity of CRC.

关键词： Colorectal adenomas polyp genetics colorectal cancer

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A Causal Roadmap for Generating High-Quality Real-World Evidence

arXiv

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arXiv 2023年

作者： Dang, Lauren E. Gruber, Susan Lee, Hana Dahabreh, Issa Stuart, Elizabeth A. Williamson, Brian D. Wyss, Richard Díaz, Iván Ghosh, Debashis Kıcıman, Emre Alemayehu, Demissie Hoffman, Katherine L. Vossen, Carla Y. Huml, Raymond A. Ravn, Henrik Kvist, Kajsa Pratley, Richard Shih, Mei-Chiung Pennello, Gene Martin, David Waddy, Salina P. Barr, Charles E. Akacha, Mouna Buse, John B. van der Laan, Mark Petersen, Maya Department of Biostatistics University of California BerkeleyCA United States TL Revolution CambridgeMA United States Office of Biostatistics Office of Translational Sciences Center for Drug Evaluation and Research U.S. Food and Drug Administration Silver SpringMD United States Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Department of Mental Health Johns Hopkins Bloomberg School of Public Health BaltimoreMD United States Biostatistics Division Kaiser Permanente Washington Health Research Institute SeattleWA United States Division of Pharmacoepidemiology and Pharmacoeconomics Brigham and Women’s Hospital Harvard Medical School BostonMA United States Division of Biostatistics Department of Population Health New York University Grossman School of Medicine New YorkNY United States Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Microsoft Research RedmondWA United States Global Biometrics and Data Management Pfizer Inc. New YorkNY United States Department of Epidemiology Mailman School of Public Health Columbia University New YorkNY United States Syneos Health Clinical Solutions Amsterdam Netherlands Syneos Health Clinical Solutions MorrisvilleNC United States Novo Nordisk Søborg Denmark AdventHealth Translational Research Institute OrlandoFL United States Cooperative Studies Program Coordinating Center VA Palo Alto Health Care System Palo AltoCA United States Department of Biomedical Data Science Stanford University StanfordCA United States Division of Imaging Diagnostics and Software Reliability Office of Science and Engineering Laboratories Center for Devices and Radiological Health U.S. Food and Drug Administration Silver SpringMD United States Global Real World Evidence Group Moderna CambridgeMA United States National Center for Advancing Translational Sciences BethesdaMD United States G

Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized controlled trials with outcomes assessed using RWD to fully observational studies. Yet many RWE study proposals lack sufficient detail to evaluate adequacy, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. The Causal Roadmap is an explicit, itemized, iterative process that guides investigators to pre-specify analytic study designs;it addresses a wide range of guidance within a single framework. By requiring transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on pre-specified criteria, the Roadmap can help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend the Causal Roadmap framework for use by clinical and translational researchers, with companion papers demonstrating application of the Causal Roadmap for specific use cases. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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Identification and external validation of tumor DNA methylation panel for the recurrence risk stratification of stage II colon cancer

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Translational Oncology 2025年 57卷 102405-102405页

作者： Yuan, Tanwei Edelmann, Dominic Moreno, Víctor Georgii, Elisabeth de Andrade e Sousa, Lisa Barros Pelin, Helena Jiang, Xiaofeng Kather, Jakob Nikolas Tagscherer, Katrin E. Roth, Wilfried Bewerunge-Hudler, Melanie Brobeil, Alexander Kloor, Matthias Bläker, Hendrik Brenner, Hermann Hoffmeister, Michael Division of Clinical Epidemiology and Aging Research German Cancer Research Center (DKFZ) Heidelberg Germany Medical Faculty Heidelberg Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Oncology Data Analytics Program Catalan Institute of Oncology (ICO). Hospitalet de Llobregat Barcelona Spain Colorectal Cancer Group ONCOBELL Bellvitge Biomedical Research Institute (IDIBELL). Hospitalet de Llobregat Barcelona Spain Biomedical Research Centre Network for Epidemiology and Public Health (CIBERESP) Madrid Spain Department of Clinical Sciences Faculty of Medicine and health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS) University of Barcelona Barcelona Spain Helmholtz AI Helmholtz Munich Munich Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Institute of Pathology University Medical Center Mainz Mainz Germany Institute of Pathology Heidelberg University Hospital Heidelberg Germany Microarray Core Facility German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pathology University of Leipzig Medical Center Leipzig Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany

Background: Tailoring surveillance and treatment strategies for stage II colon cancer (CC) after curative surgery remains challenging, and personalized approaches are lacking. We aimed to identify a gene methylation panel capable of stratifying high-risk stage II CC patients for recurrence beyond traditional clinical variables. Methods: Genome-wide tumor tissue DNA methylation data were analyzed from 562 stage II CC patients who underwent surgery in Germany (DACHS study). The cohort was divided into a training set (N = 395) and an internal validation set (N = 131), with external validation performed on 97 stage II CC patients from Spain. DNA methylation markers were primarily selected using the Elastic Net Cox model. The resulting prognostic index (PI), a combination of clinical factors and selected methylation markers, was compared to baseline models using clinical variables or microsatellite instability (MSI), with discrimination and prediction accuracy assessed through time-dependent receiver operating characteristic curves (AUC) and Brier scores. Results: The final PI incorporated age, sex, tumor stage, location, and 27 DNA methylation markers. The PI consistently outperformed the baseline model including age, sex, and tumor stage in time-dependent AUC across validation cohorts (e.g., 1-year AUC and 95 % confidence interval: internal validation set, PI: 0.66, baseline model: 0.52;external validation set, PI: 0.72, baseline model: 0.64). In internal validation, the PI also showed a consistently improved time-dependent AUC compared with a combination of MSI and tumor stage only. Nevertheless, the PI did not improve the prediction accuracy of CC recurrence compared to the baseline model. Conclusions: This study identified 27 tumor tissue DNA methylation biomarkers that improved the discriminative power in classifying recurrence risk among stage II colon cancer patients. While this methylation panel alone lacks sufficient prediction accuracy for clinical application

关键词： Colon cancer DNA methylation panel Prognostic index Recurrence risk

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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction (vol 53, pg 65, 2021)

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NATURE GENETICS 2021年第3期53卷 413-413页

作者： Conti, David V. Darst, Burcu F. Moss, Lilit C. Saunders, Edward J. Sheng, Xin Chou, Alisha Schumacher, Fredrick R. Al Olama, Ali Amin Benlloch, Sara Dadaev, Tokhir Brook, Mark N. Sahimi, Ali Hoffmann, Thomas J. Takahashi, Atushi Matsuda, Koichi Momozawa, Yukihide Fujita, Masashi Muir, Kenneth Lophatananon, Artitaya Wan, Peggy Le Marchand, Loic Wilkens, Lynne R. Stevens, Victoria L. Gapstur, Susan M. Carter, Brian D. Schleutker, Johanna Tammela, Teuvo L. J. Sipeky, Csilla Auvinen, Anssi Giles, Graham G. Southey, Melissa C. MacInnis, Robert J. Cybulski, Cezary Wokolorczyk, Dominika Lubinski, Jan Neal, David E. Donovan, Jenny L. Hamdy, Freddie C. Martin, Richard M. Nordestgaard, Borge G. Nielsen, Sune F. Weischer, Maren Bojesen, Stig E. Roder, Martin Andreas Iversen, Peter Batra, Jyotsna Chambers, Suzanne Moya, Leire Horvath, Lisa Clements, Judith A. Tilley, Wayne Risbridger, Gail P. Gronberg, Henrik Aly, Markus Szulkin, Robert Eklund, Martin Nordstrom, Tobias Pashayan, Nora Dunning, Alison M. Ghoussaini, Maya Travis, Ruth C. Key, Tim J. Riboli, Elio Park, Jong Y. Sellers, Thomas A. Lin, Hui-Yi Albanes, Demetrius Weinstein, Stephanie J. Mucci, Lorelei A. Giovannucci, Edward Lindstrom, Sara Kraft, Peter Hunter, David J. Penney, Kathryn L. Turman, Constance Tangen, Catherine M. Goodman, Phyllis J. Thompson, Ian M., Jr. Hamilton, Robert J. Fleshner, Neil E. Finelli, Antonio Parent, Marie-Elise Stanford, Janet L. Ostrander, Elaine A. Geybels, Milan S. Koutros, Stella Freeman, Laura E. Beane Stampfer, Meir Wolk, Alicja Hakansson, Niclas Andriole, Gerald L. Hoover, Robert N. Machiela, Mitchell J. Sorensen, Karina Dalsgaard Borre, Michael Blot, William J. Zheng, Wei Yeboah, Edward D. Mensah, James E. Lu, Yong-Jie Zhang, Hong-Wei Feng, Ninghan Mao, Xueying Wu, Yudong Zhao, Shan-Chao Sun, Zan Thibodeau, Stephen N. McDonnell, Shannon K. Schaid, Daniel J. West, Catharine M. L. Burnet, Neil Barnett, Gill Maier, Christiane Schnoeller, Thomas Luedeke, Manuel Kibel, Adam S. Drake, Bettina F. Cussenot, Olivier Cancel-Tassin, Gerald Center for Genetic Epidemiology Department of Preventive Medicine Keck School of Medicine University of Southern California/Norris Comprehensive Cancer Center Los Angeles CA USA The Institute of Cancer Research London UK Department of Population and Quantitative Health Sciences Case Western Reserve University Cleveland OH USA Seidman Cancer Center University Hospitals Cleveland OH USA Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care University of Cambridge Strangeways Research Laboratory Cambridge UK Stroke Research Group Department of Clinical Neurosciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics University of California San Francisco CA USA Institute for Human Genetics University of California San Francisco CA USA Laboratory for Statistical Analysis RIKEN Center for Integrative Medical Sciences Yokohama Japan Department of Genomic Medicine National Cerebral and Cardiovascular Center Research Institute Suita Japan Laboratory of Clinical Genome Sequencing Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan Biobank Tokyo Japan Laboratory for Genotyping Development RIKEN Center of Integrative Medical Sciences Yokohama Japan Laboratory for Cancer Genomics RIKEN Center of Integrative Medical Sciences Yokohama Japan Division of Population Health Health Services Research and Primary Care School of Health Sciences Faculty of Biology Medicine and Health University of Manchester Manchester UK Warwick Medical School University of Warwick Coventry UK Epidemiology Program University of Hawaii Cancer Center Honolulu HI USA Behavioral and Epidemiology Research Group Research Program American Cancer Society Atlanta GA USA Institute of Biomedicine University of Turku Turku Finland Department of Medical Genetics Genomics Laboratory Division Turku University Hospital Turku Finland Department of Urolog

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

关键词： epidemiology Genome-wide association studies Personalized medicine Prostate cancer

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Cell-type-specific and inflammatory DNA methylation patterns associated with PTSD

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Brain, Behavior, and Immunity 2025年 128卷 540-548页

作者： Smith, Alicia K. Katrinli, Seyma Maihofer, Adam X. Aiello, Allison E. Baker, Dewleen G. Boks, Marco P. Brick, Leslie A. Chen, Chia-Yen Dalvie, Shareefa Fani, Negar Fortier, Catherine B. Gelernter, Joel Geuze, Elbert Gillespie, Charles F. Hayes, Jasmeet P. Hong, Suzi Kessler, Ronald C. King, Anthony P. Koen, Nastassja Koenen, Karestan C. Liberzon, Israel Linnstaedt, Sarah D. McLean, Samuel A. Michopoulos, Vasiliki Milberg, William P. Miller, Mark W. Mufford, Mary S. Nugent, Nicole R. Orcutt, Holly K. Powers, Abigail Rauch, Sheila A.M. Ressler, Kerry J. Risbrough, Victoria B. Rutten, Bart P.F. Smoller, Jordan W. Stein, Dan J. Stein, Murray B. Ursano, Robert J. Verfaellie, Mieke H. Vermetten, Eric Vinkers, Christiaan H. Wani, Agaz H. WareVinkers, Erin B. Wildman, Derek E. Wolf, Erika J. Zhao, Ying Logue, Mark W. Nievergelt, Caroline M. Uddin, Monica Zannas, Anthony S. Emory University Department of Gynecology and Obstetrics Atlanta GA United States Emory University Department of Human Genetics Atlanta GA United States Emory University Department of Psychiatry and Behavioral Sciences Atlanta GA United States University of California San Diego Department of Psychiatry La Jolla CA United States Veterans Affairs San Diego Healthcare System Center of Excellence for Stress and Mental Health San Diego CA United States Veterans Affairs San Diego Healthcare System Research Service San Diego CA United States Columbia University Robert N Butler Columbia Aging Center Department of Epidemiology New York NY United States Amsterdam UMC Department of Psychiatry NH Amsterdam Netherlands Dimence Specialised Mental Health Mood Disorders OV Deventer Netherlands University Medical Center Utrecht Department Psychiatry UT Utrecht Netherlands Alpert Medical School of Brown University Department of Psychiatry and Human Behavior Providence RI United States Biogen Inc. Translational Medicine Cambridge MA United States University of Cape Town Division of Human Genetics Western Province Cape Town South Africa Harvard Medical School Department of Psychiatry Boston MA United States VA Boston Healthcare System Geriatric Research Education and Clinical Center (GRECC) Boston MA United States VA Boston Healthcare System Translational Research Center for Traumatic Brain Injury and Stress Disorders (TRACTS) Boston MA United States VA Connecticut Healthcare Center Psychiatry Service West Haven CT United States Yale University School of Medicine Departments of Psychiatry Genetics and Neuroscience New Haven CT United States Netherlands Ministry of Defence Brain Research and Innovation Centre UT Utrecht Netherlands UMC Utrecht Brain Center Rudolf Magnus Department of Psychiatry UT Utrecht Netherlands The Ohio State University Department of Psychology Columbus OH United States University of California San Diego Herbert Wertheim Sch

Background: Epigenetic modifications, including DNA methylation (DNAm), can change in response to traumatic stress exposure, and may help to distinguish between individuals with and without PTSD. Here, we examine the DNAm patterns specific to immune cell types and inflammation in those with PTSD. Methods: This study includes 3,277 participants from 11 cohorts participating in the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup. DNAm was assayed from blood with the MethylationEPIC BeadChip. A standardized QC pipeline was applied and used to impute cell composition. Within each cohort, we identified cell-type-specific DNAm patterns associated with PTSD, controlling for sex (if applicable), age, and ancestry. Meta-analyses were performed from summary statistics. Results: PTSD cases had lower proportions of B cells and NK cells as well as higher proportions of neutrophils when compared to trauma-exposed controls. Overall, we identified 96 PTSD-associated CpGs across six types of immune cells. Most of these differences were identified in B cells, with 95 % exhibiting lower methylation levels in those with PTSD. Interestingly, the PTSD-associated CpGs annotated to a gene in B cells were enriched in a recent GWAS of PTSD (p < 0.0001). Conclusions: This study identifies novel PTSD-associated CpGs in individual immune cell types and supports the role of immune dysregulation and inflammation in PTSD. © 2025 The Author(s)

关键词： B-cells CRP DNA methylation EWAS Immune Inflammation PTSD Trauma

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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On Anticipation Effect in Stepped Wedge Cluster Randomized Trials

arXiv

引用

arXiv 2025年

作者： Wang, Hao Chen, Xinyuan Courtright, Katherine R. Halpern, Scott D. Harhay, Michael O. Taljaard, Monica Li, Fan Department of Biostatistics Yale School of Public Health CT United States Department of Mathematics and Statistics Mississippi State University MS United States Department of Medicine Hospital of the University of Pennsylvania PhiladelphiaPA United States Department of Biostatistics Epidemiology and Informatics Perelman School of Medicine the University of Pennsylvania PhiladelphiaPA United States Center Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Clinical Epidemiology Program Ottawa Hospital Research Institute OttawaON Canada School of Epidemiology and Public Health University of Ottawa OttawaON Canada Center for Methods in Implementation and Prevention Science Yale School of Public Health CT United States

In stepped wedge cluster randomized trials (SW-CRTs), the intervention is rolled out to clusters over multiple periods. A standard approach for analyzing SW-CRTs utilizes the linear mixed model where the treatment effect is only present after the treatment adoption, under the assumption of no anticipation. This assumption, however, may not always hold in practice because stakeholders, providers, or individuals who are aware of the treatment adoption timing (especially when blinding is challenging or infeasible) can inadvertently change their behaviors in anticipation of the intervention for maximizing potential benefits. We provide an analytical framework to address the anticipation effect in SW-CRTs and study its impact when the treatment effect may or may not depend on the exposure time. We derive expectations of the estimators based on a collection of linear mixed models and demonstrate that when the anticipation effect is ignored, these estimators give biased estimates of the treatment effect. We also provide updated sample size formulas that explicitly account for anticipation effects, exposure-time heterogeneity, or both in SW-CRTs and illustrate how failing to account for these effects when they exist may lead to an underpowered study. Through simulation studies and empirical analyses, we compare the treatment effect estimators under considerations and discuss practical considerations for addressing anticipation in SW-CRTs. Copyright © 2025, The Authors. All rights reserved.

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