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Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Nature communications 2023年第1期14卷 3043页

作者： Jianxin Shi Kouya Shiraishi Jiyeon Choi Keitaro Matsuo Tzu-Yu Chen Juncheng Dai Rayjean J Hung Kexin Chen Xiao-Ou Shu Young Tae Kim Maria Teresa Landi Dongxin Lin Wei Zheng Zhihua Yin Baosen Zhou Bao Song Jiucun Wang Wei Jie Seow Lei Song I-Shou Chang Wei Hu Li-Hsin Chien Qiuyin Cai Yun-Chul Hong Hee Nam Kim Yi-Long Wu Maria Pik Wong Brian Douglas Richardson Karen M Funderburk Shilan Li Tongwu Zhang Charles Breeze Zhaoming Wang Batel Blechter Bryan A Bassig Jin Hee Kim Demetrius Albanes Jason Y Y Wong Min-Ho Shin Lap Ping Chung Yang Yang She-Juan An Hong Zheng Yasushi Yatabe Xu-Chao Zhang Young-Chul Kim Neil E Caporaso Jiang Chang James Chung Man Ho Michiaki Kubo Yataro Daigo Minsun Song Yukihide Momozawa Yoichiro Kamatani Masashi Kobayashi Kenichi Okubo Takayuki Honda Dean H Hosgood Hideo Kunitoh Harsh Patel Shun-Ichi Watanabe Yohei Miyagi Haruhiko Nakayama Shingo Matsumoto Hidehito Horinouchi Masahiro Tsuboi Ryuji Hamamoto Koichi Goto Yuichiro Ohe Atsushi Takahashi Akiteru Goto Yoshihiro Minamiya Megumi Hara Yuichiro Nishida Kenji Takeuchi Kenji Wakai Koichi Matsuda Yoshinori Murakami Kimihiro Shimizu Hiroyuki Suzuki Motonobu Saito Yoichi Ohtaki Kazumi Tanaka Tangchun Wu Fusheng Wei Hongji Dai Mitchell J Machiela Jian Su Yeul Hong Kim In-Jae Oh Victor Ho Fun Lee Gee-Chen Chang Ying-Huang Tsai Kuan-Yu Chen Ming-Shyan Huang Wu-Chou Su Yuh-Min Chen Adeline Seow Jae Yong Park Sun-Seog Kweon Kun-Chieh Chen Yu-Tang Gao Biyun Qian Chen Wu Daru Lu Jianjun Liu Ann G Schwartz Richard Houlston Margaret R Spitz Ivan P Gorlov Xifeng Wu Ping Yang Stephen Lam Adonina Tardon Chu Chen Stig E Bojesen Mattias Johansson Angela Risch Heike Bickeböller Bu-Tian Ji H-Erich Wichmann David C Christiani Gadi Rennert Susanne Arnold Paul Brennan James McKay John K Field Sanjay S Shete Loic Le Marchand Geoffrey Liu Angeline Andrew Lambertus A Kiemeney Shan Zienolddiny-Narui Kjell Grankvist Mikael Johansson Angela Cox Fiona Taylor Jian-Min Yuan Philip Lazarus Matthew B Schabath Melinda C Aldrich Hyo-Sung Jeon Shih Sheng Jiang Jae Sook Sung C Division of Cancer Epidemiology and Genetics National Cancer Institute Rockville MD USA. jianxin.shi@nih.gov. Division of Genome Biology National Cancer Research Institute Tokyo Japan. Division of Cancer Epidemiology and Genetics National Cancer Institute Rockville MD USA. Division of Cancer Epidemiology and Prevention Aichi Cancer Center Research Institute Nagoya Japan. Institute of Population Health Sciences National Health Research Institutes Zhunan Taiwan. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Jiangsu Key Lab of Cancer Biomarkers Prevention and Treatment Collaborative Innovation Center for Cancer Medicine Nanjing Medical University Nanjing China. Prosserman Centre for Population Health Research Lunenfeld-Tanenbaum Research Institute Sinai Health Toronto ON Canada. Department of Epidemiology and Biostatistics National Clinical Research Center for Cancer Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin Medical University Cancer Institute and Hospital Tianjin Medical University Tianjin China. Division of Epidemiology Department of Medicine Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center Nashville TN USA. Cancer Research Institute Seoul National University College of Medicine Seoul Republic of Korea. Department of Etiology & Carcinogenesis and State Key Laboratory of Molecular Oncology Cancer Institute and Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China. Department of Epidemiology School of Public Health China Medical University Shenyang China. Department of Clinical Epidemiology and Center of Evidence Based Medicine The First Hospital of China Medical University Shenyang China. Department of Oncology Shandong Cancer Hospital and Institute Shandong Academy of Medical Sciences Jinan China. Ministry of Education Key Laboratory of Contemporary Anthropology School of Life Sciences Fudan University Shanghai China. S

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

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Cover Image, Volume 59, Issue 7

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Molecular Carcinogenesis 2020年第7期59卷

作者： Elizabeth Mitchell Sonali Jindal Tiffany Chan Jayasri Narasimhan Shamilene Sivagnanam Elliot Gray Young Hwan Chang Sheila Weinmann Pepper Schedin Department of Cell Developmental and Cancer Biology Oregon Health and Science University Portland Oregon Cancer Prevention and Control Knight Cancer Institute Oregon Health and Science University Portland Oregon Computational Biology Program Department of Cell Developmental and Cancer Biology Oregon Health and Science University Portland Oregon Department of Biomedical Engineering Oregon Center for Spatial Systems Biomedicine Oregon Health and Science University Portland Oregon Center for Health Research Kaiser Permanente Northwest Portland Oregon

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Correction: Salutary effects of moderate but not high intensity aerobic exercise training on the frequency of peripheral T-cells associated with immunosenescence in older women at high risk of breast cancer: a randomized controlled trial

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Immunity & ageing : I & A 2022年第1期19卷 30页

作者： Grace M Niemiro Adriana M Coletta Nadia H Agha Preteesh Leo Mylabathula Forrest L Baker Abenaa M Brewster Therese B Bevers Enrique Fuentes-Mattei Karen Basen-Engquist Emmanuel Katsanis Susan C Gilchrist Richard J Simpson Department of Pediatrics The University of Arizona Tucson Arizona USA. The University of Arizona Cancer Center Tucson Arizona USA. Department of Health and Kinesiology The University of Utah Salt Lake City Utah USA. Cancer Control and Population Sciences Program Huntsman Cancer Institute Salt Lake City Utah USA. Department of Health and Human Performance University of Houston Houston Texas USA. School of Nutritional Sciences and Wellness The University of Arizona Tucson Arizona USA. Department of Clinical Cancer Prevention The University of Texas MD Anderson Cancer Center Houston Texas USA. Department of Radiation Oncology Clinical Research The University of Texas MD Anderson Cancer Center Houston Texas USA. Department of Behavioral Science The University of Texas MD Anderson Cancer Center Houston Texas USA. Department of Immunobiology The University of Arizona Tucson Arizona USA. Department of Cardiology The University of Texas MD Anderson Cancer Center Houston Texas USA. Department of Pediatrics The University of Arizona Tucson Arizona USA. rjsimpson@arizona.edu. The University of Arizona Cancer Center Tucson Arizona USA. rjsimpson@arizona.edu. Department of Health and Human Performance University of Houston Houston Texas USA. rjsimpson@arizona.edu. School of Nutritional Sciences and Wellness The University of Arizona Tucson Arizona USA. rjsimpson@arizona.edu. Department of Behavioral Science The University of Texas MD Anderson Cancer Center Houston Texas USA. rjsimpson@arizona.edu. Department of Immunobiology The University of Arizona Tucson Arizona USA. rjsimpson@arizona.edu.

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Correction: Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

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Leukemia 2023年第10期37卷 2142页

作者： Sonja I Berndt Joseph Vijai Yolanda Benavente Nicola J Camp Alexandra Nieters Zhaoming Wang Karin E Smedby Geffen Kleinstern Henrik Hjalgrim Caroline Besson Christine F Skibola Lindsay M Morton Angela R Brooks-Wilson Lauren R Teras Charles Breeze Joshua Arias Hans-Olov Adami Demetrius Albanes Kenneth C Anderson Stephen M Ansell Bryan Bassig Nikolaus Becker Parveen Bhatti Brenda M Birmann Paolo Boffetta Paige M Bracci Paul Brennan Elizabeth E Brown Laurie Burdett Lisa A Cannon-Albright Ellen T Chang Brian C H Chiu Charles C Chung Jacqueline Clavel Pierluigi Cocco Graham Colditz Lucia Conde David V Conti David G Cox Karen Curtin Delphine Casabonne Immaculata De Vivo Arjan Diepstra W Ryan Diver Ahmet Dogan Christopher K Edlund Lenka Foretova Joseph F Fraumeni Attilio Gabbas Hervé Ghesquières Graham G Giles Sally Glaser Martha Glenn Bengt Glimelius Jian Gu Thomas M Habermann Christopher A Haiman Corinne Haioun Jonathan N Hofmann Theodore R Holford Elizabeth A Holly Amy Hutchinson Aalin Izhar Rebecca D Jackson Ruth F Jarrett Rudolph Kaaks Eleanor Kane Laurence N Kolonel Yinfei Kong Peter Kraft Anne Kricker Annette Lake Qing Lan Charles Lawrence Dalin Li Mark Liebow Brian K Link Corrado Magnani Marc Maynadie James McKay Mads Melbye Lucia Miligi Roger L Milne Thierry J Molina Alain Monnereau Rebecca Montalvan Kari E North Anne J Novak Kenan Onel Mark P Purdue Kristin A Rand Elio Riboli Jacques Riby Eve Roman Gilles Salles Douglas W Sborov Richard K Severson Tait D Shanafelt Martyn T Smith Alexandra Smith Kevin W Song Lei Song Melissa C Southey John J Spinelli Anthony Staines Deborah Stephens Heather J Sutherland Kaitlyn Tkachuk Carrie A Thompson Hervé Tilly Lesley F Tinker Ruth C Travis Jenny Turner Celine M Vachon Claire M Vajdic Anke Van Den Berg David J Van Den Berg Roel C H Vermeulen Paolo Vineis Sophia S Wang Elisabete Weiderpass George J Weiner Stephanie Weinstein Nicole Wong Doo Yuanqing Ye Meredith Yeager Kai Yu Anne Zeleniuch-Jacquotte Yawei Zhang Tongzhang Zheng Elad Ziv Joshua Sampson Nilanjan Chatterjee Kenn Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda Md USA. berndts@mail.nih.gov. Department of Medicine Memorial Sloan Kettering Cancer Center New York NY USA. Cancer Epidemiology Research Programme Catalan Institute of Oncology-IDIBELL L'Hospitalet de Llobregat Barcelona Spain. CIBER de Epidemiología y Salud Pública (CIBERESP) Barcelona Spain. Department of Internal Medicine and Huntsman Cancer Institute University of Utah School of Medicine Salt Lake City UT USA. Institute for Immunodeficiency University Medical Center Freiburg Freiburg Germany. Department of Epidemiology and Cancer Control St. Jude Children's Research Hospital Memphis TN USA. Laboratory of Translational Genomics Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda MD USA. Department of Medicine Solna Karolinska Institutet Stockholm Sweden. Hematology Center Karolinska University Hospital Stockholm Sweden. School of Public Health University of Haifa Haifa Israel. Department of Epidemiology Research Division of Health Surveillance and Research Statens Serum Institut Copenhagen Denmark. Department of Clinical Medicine University of Copenhagen Copenhagen Denmark. Department of Haematology Rigshospitalet Copenhagen Denmark. Danish Cancer Society Research Center Danish Cancer Society Copenhagen Denmark. Centre Hospitalier de Versailles Le Chesnay France. Université Paris-Saclay UVSQ Inserm Équipe "Exposome et Hérédité" CESP Villejuif France. Department of Hematology and Medical Oncology Emory University School of Medicine Atlanta GA USA. Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda Md USA. Genome Sciences Centre BC Cancer Agency Vancouver BC Canada. Department of Biomedical Physiology and Kinesiology Simon Fraser University Burnaby BC Canada. Department of Population Science American Cancer Society Atlanta GA USA. Department of Medical Epidemiology and Biostatistics Karolinska In

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A tale of two tools: Reliability and feasibility of social media measurement tools examining e-cigarette twitter mentions

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Informatics in Medicine Unlocked 2017年 8卷 8-12页

作者： Burke-Garcia, Amelia Stanton, Cassandra A. Westat 1600 Research Blvd Rockville 20850 MD United States Department of Oncology Georgetown University Medical Center/Cancer Prevention and Control Program Lombardi Comprehensive Cancer Center United States

Given 70% of Americans are seeking health information online, social media are becoming main sources of health-related information and discussions. Specifically, compounding rising trends in use of e-cigarettes in the US, there has been a rapid rise in e-cigarette marketing – much of which is happening on social media. Public health professionals seeking to understand consumer knowledge, attitudes and beliefs about e-cigarettes should consider analyzing social media data and to do so, there are numerous free and paid tools available. However, each uses different sources and processes, which makes data validation challenging. This exploratory study sought to understand the reliability and feasibility of two social media data tools analyzing e-cigarette tweets. Twitter mentions were pulled from two different industry standard tools (GNIP and Radian6) and data were evaluated on six measures, e.g. Cost, Feasibility, Ease of Use, Poster Type (individual/organization), Context (tweet content analysis), and Valence (positive/negative). Findings included similarities amongst the data sets in terms of the content themes but differences in cost and ease of use of the tools themselves. These findings align with prior research, notably that e-cigarette marketing tweets are most common and public health-related content is noticeably absent. Findings from this exploratory study can inform future social media studies as well as communication campaigns seeking to address the emerging issue of e-cigarette use. © 2017

关键词： E-cigarettes Social media Tweets Twitter Vaping

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Association Between Household Food Security and Disordered Eating Behaviors Among Young Adults with Diabetes: The SEARCH for Diabetes in Youth Study

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Current Developments in Nutrition 2020年第SUPPL 2期4卷 4141419-4141419页

作者： Jackson, Emahlea Liese, Angela Pihoker, Catherine Malik, Faisal Jones-Smith, Jessica Qu, Pingping Crow, Scott Loots, Beth Reboussin, Beth Dolan, Lawrence Igudesman, Daria Sauder, Katherine Shapiro, Allison Siegel, Karen Turley, Christine Mendoza, Jason University of Washington University of South Carolina Seattle Children's Research Institution Seattle Children's Research Institute The Emily Program St. Paul MN University of Minnesota Wake Forest University School of Medicine University of Cincinnati University of North Carolina at Chapel Hill University of Colorado Denver University of Colorado Anschutz Medical Campus Centers for Disease Control and Prevention Emory University Medical University of South Carolina Fred Hutchinson Cancer Research Center

AbstractObjectivesExamine the relationship between household food insecurity (HFS; i.e., access to nutritionally adequate and safe food) and disordered eating behaviors (i.e., restriction, bingeing, insulin manipulation, etc.) among a sample of young adults with youth-onset type 1 (T1D) or type 2 diabetes (T2D). MethodsWe used cross-sectional data from the SEARCH for Diabetes in Youth Study. Individuals ( n = 792) ages ≥18 years completed the U.S. Household Food Security Survey Module and the Diabetes Eating Problem Survey-Revised (DEPS-R) between 2016 and 2019. We converted HFS scores to a 10-point scale and dichotomized scores into food secure (HFS ≤ 2.2) vs. food insecure (HFS > 2.2). Multivariable linear regression was used to evaluate the association of HFS with continuous DEPS-R score (i.e., 0–80, with a greater score indicating greater symptoms of disordered eating), adjusting for potential confounders (i.e., sex, age, race/ethnicity, education, household income, insurance, depressive symptoms, and duration of diabetes). We further stratified analyses by diabetes type. ResultsParticipants were on average 23.8 ± 3.7 years, 59.6% female, 49.6% non-Latino white, and had a mean diabetes duration of 11.5 ± 3.1 years. The overall mean DEPS-R score was 17.3 ± 10.0 points. Mean DEPS-R scores in individuals living in food secure households ( n = 709) and food insecure households ( n = 83) were 16.6 ± 9.45 and 23.4 ± 12.4, respectively. The adjusted DEPS-R scores were 3.6 points (95% CI = 1.5, 5.7; P < 0.001) higher in food insecure compared to food secure households. In individuals with T1D ( n = 600), the adjusted DEPS-R scores were 5.0 points (95% CI = 2.6, 7.4; P < 0.001) higher in food insecure ( n = 55) compared to food secure ( n = 545) households. In individuals with T2D ( n = 192), there was no significant difference in mean DEPS-R scores between food insecure ( n = 28) versus food secure ( n = 164) households in unadjusted or adjusted models ( P > 0.05). Conc

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Ten quick tips for deep learning in biology

arXiv

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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

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Gynecologic oncology 2019年第2期153卷 343-355页

作者： Kate Lawrenson Fengju Song Dennis J Hazelett Siddhartha P Kar Jonathan Tyrer Catherine M Phelan Rosario I Corona Norma I Rodríguez-Malavé Ji-Hei Seo Emily Adler Simon G Coetzee Felipe Segato Marcos A S Fonseca Christopher I Amos Michael E Carney Georgia Chenevix-Trench Jiyeob Choi Jennifer A Doherty Weihua Jia Gang J Jin Byoung-Gie Kim Nhu D Le Juyeon Lee Lian Li Boon K Lim Noor A Adenan Mika Mizuno Boyoung Park Celeste L Pearce Kang Shan Yongyong Shi Xiao-Ou Shu Weiva Sieh Pamela J Thompson Lynne R Wilkens Qingyi Wei Yin L Woo Li Yan Beth Y Karlan Matthew L Freedman Houtan Noushmehr Ellen L Goode Andrew Berchuck Thomas A Sellers Soo-Hwang Teo Wei Zheng Keitaro Matsuo Sue Park Kexin Chen Paul D P Pharoah Simon A Gayther Marc T Goodman Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute Cedars-Sinai Medical Center 8700 Beverly Boulevard Suite 290W Los Angeles CA USA Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Electronic address: kate.lawrenson@***. National Clinical Research Center for Cancer Tianjin Medical University Cancer Institute and Hospital Tianjin China Department of Epidemiology and Biostatistics Key Laboratory of Cancer Prevention and Therapy Tianjin China. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Oncology Centre for Cancer Genetic Epidemiology University of Cambridge Strangeways Research Laboratory Cambridge UK. Department of Gynecologic Oncology Moffitt Cancer Center Tampa FL USA Department of Cancer Epidemiology Moffitt Cancer Center Tampa FL USA. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA. Department of Preventive Medicine University of Southern California Keck School of Medicine 1450 Biggy Street Los Angeles CA USA. Department of Genetics Ribeirão Preto Medical School University of São Paulo 14049-900 Brazil. Institute for Clinical and Translational Research Department of Medicine Baylor School of Medicine HoustonTX USA. Department of Obstetrics and Gynecology John A. Burns School of Medicine University of Hawaii Honolulu HI USA. Genetics and Computational Biology Department QIMR Berghofer Medical Research Institute 300 Herston Road Herston QLD 4006 Australia. Department of Preventive Medicine Seoul National University College of Medicine Seoul Republic of Korea Cancer Research Institute Seoul National University Seoul Republic of Korea Department of Biomedical Science Graduate School Seoul National Un

OBJECTIVE:Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS:Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS:At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10). SNP rs6902488 at 6p25.2 (r = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10). CONCLUSION:While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

关键词： Asian ancestry Enhancer Epithelial ovarian cancer Gene regulation Genome-wide association study eQTL

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Expenditure and financial burden for the diagnosis and treatment of colorectal cancer in China:a ***,multicenter,cross-sectional survey

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Chinese Journal of cancer 2017年第8期36卷 352-366页

作者： Hui-Yao Huang Ju-Fang Shi Lan-Wei Guo Ya-Na Bai Xian-Zhen Liao Guo-iangLiu A-Yan Mao Jian-Song Ren Xiao-Jie Sun Xin-Yu Zhu Le Wang Bing-Bing Song Ling-Bin Du Lin Zhu Ji-Yong Gong Qi Zhou Yu-Qin Liu Rong Cao Ling Mai Li Lan Xiao-Hua Sun Ying Ren Jin-Yi Zhou Yuan-Zheng Wang Xiao Qi Pei-An Lou Dian Shi Ni Li Kai Zhang Jie He Min Dai Program Office for Cancer Screening in Urban China National Cancer Center/Cancer HospitalChinese Academy of Medical SciencesPeking Union Medical College17 South Panjiayuan LaneChaoyang DistrictBeijing 100021P.R.China Department of Cancer Epidemiology Henan Cancer HospitalAffiliated Cancer Hospital of Zhengzhou UniversityZhengzhouHenan 450008P.R.China Institute of Epidemiology and Health Statistics Lanzhou UniversityLanzhouGansu 730000P.R.China Hunan Office for Cancer Control and Research Hunan Provincial Cancer HospitalChangshaHunan 410006P.R.China Department of Health Economics School of Health ManagementHarbin Medical UniversityHarbinHeilongjiang 150081P.R.China Public Health Information Research Office Institute of Medical InformationChinese Academy of Medical SciencesBeijing 100020P.R.China Center for Health Management and Policy Key Lab of Health Economics and PolicyShandong UniversityJinanShandong 250012P.R.China Heilongjiang Office for Cancer Control and Research Affiliated Cancer Hospital of Harbin Medical UniversityHarbinHeilongjiang 150081P.R.China Zhejiang Office for Cancer Control and Research Zhejiang Cancer HospitalHangzhouZhejiang 310022P.R.China Teaching and Research Department Affiliated Cancer Hospital of Xinjiang Medical UniversityürümqiXinjiang 830011P.R.China Science and Education Department of Public Health Division Shandong Tumor HospitalJinanShandong 250117P.R.China Chongqing Office for Cancer Control and Research Chongqing Cancer HospitalChongqing 400030P.R.China Cancer Epidemiology Research Center Gansu Provincial Cancer HospitalLanzhouGansu 730050P.R.China Department of Health Policy and Economic Research Guangdong Provincial Institute of Public HealthGuangzhouGuangdong 511430P.R.China Department of Institute of Tumor Research Henan Cancer HospitalAffiliated Cancer Hospital of Zhengzhou UniversityZhengzhouHenan 450008P.R.China Institute of Chronic Disease Prevention and Control Harbin Center for Disease Control and PreventionHarbinHei

Background: The increasing prevalence of colorectal cancer(CRC) in China and the paucity of information about relevant expenditure highlight the necessity of better understanding the financial burden and effect of CRC diagnosis and treatment. We performed a survey to quantify the direct medical and non-medical expenditure as well as the resulting financial burden of CRC patients in ***: We conducted a multicenter, cross-sectional survey in 37 tertiary hospitals in 13 provinces across China between 2012 and 2014. Each enrolled patient was interviewed using a structured questionnaire. All expenditure data were inflated to the 2014 Chinese Yuan(CNY; 1 CNY = 0.163 USD). We quantified the overall expenditure and financial burden and by subgroup(hospital type, age at diagnosis, sex, education, occupation, insurance type, household income, clinical stage, pathologic type, and therapeutic regimen). We then performed generalized linear modeling to determine the factors associated with overall ***: A total of 2356 patients with a mean age of 57.4 years were included, 57.1 % of whom were men; 13.9% of patients had stage I cancer; and the average previous-year household income was 54,525 *** overall average direct expenditure per patient was estimated to be 67,408 CNY, and the expenditures for stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ disease were 56,099 CNY, 59,952 CNY, 67,292 CNY, and 82,729 CNY, respectively. Non-medical expenditure accounted for 8.3%of the overall expenditure. The 1-year out-of-pocket expenditure of a newly diagnosed patient was 32,649 CNY, which accounted for 59.9% of their previous-year household income and caused 75.0% of families to suffer an unmanageable financial burden. Univariate analysis showed that financial burden and overall expenditure differed in almost all subgroups(P < 0.05), except for sex. Multivariate analysis showed that patients who were treated in specialized hospitals and those who were diagnosed with adenocarcinoma or diagno

关键词： Colorectal neoplasms Direct expenditure Financial burden China

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The effects of the Multicultural Healthy Diet on cognitive decline & Alzheimer's disease risk: A randomized controlled trial in middle-aged adults

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The American journal of clinical nutrition 2025年

作者： Yasmin Mossavar-Rahmani Noorie Hyun Jonathan G Hakun Mindy J Katz Jelena M Pavlovic Henrik Zetterberg Zheng Wang Jasper B Yang Judith Wylie-Rosett James R Hebert Martin J Sliwinski Pamela A Shaw Division of Health Behavior Research & Implementation Science Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Electronic address: yasmin.mossavar-rahmani@einsteinmed.edu. Division of Biostatistics Kaiser Permanente Washington Health Research Institute Seattle WA Department of Biostatistics University of Washington Seattle WA. Department of Neurology The Pennsylvania State University College of Medicine Hershey PA Department of Psychology The Pennsylvania State University University Park PA Department of Public Health Sciences The Pennsylvania State University College of Medicine Hershey PA Center for Healthy Aging The Pennsylvania State University University Park PA. Department of Neurology Albert Einstein College of Medicine Bronx NY. Department of Neurology Albert Einstein College of Medicine & Montefiore Medical Center Bronx NY. Institute of Neuroscience and Physiology Dept. of Psychiatry and Neurochemistry University of Gothenburg Mölndal Sweden Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden Department of Neurodegenerative Disease UCL Institute of Neurology Queen Square London UK UK Dementia Research Institute at UCL London UK Hong Kong Center for Neurodegenerative Diseases InnoHK Hong Kong China Wisconsin Alzheimer's Disease Research Center University of Wisconsin School of Medicine and Public Health University of Wisconsin-Madison Madison WI. Division of Biostatistics Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Division of Biostatistics Kaiser Permanente Washington Health Research Institute Seattle WA. Division of Health Behavior Research & Implementation Science Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Department of Epidemiology and Biostatistics and Cancer Prevention and Control Program Arnold School of Public Health University of South Carolina Columbia SC Depart

BACKGROUND:Anti-inflammatory dietary patterns are associated with slower cognitive decline in older adults; however, little is known about effects of an anti-inflammatory dietary pattern in middle-age. OBJECTIVES:To adapt an anti-inflammatory diet to a multicultural setting and assess its impact on cognitive decline and Alzheimer's Disease risk and related dementias in healthy middle-aged adults. METHODS:We performed a phase II pilot randomized clinical trial in adults (40-65 years old; n=290) in Bronx, New York. Participants were assigned to follow either the Multicultural Healthy Diet (MHD) an anti-inflammatory diet, or usual diet (Comparison). Diet was evaluated using National cancer Institute's Automated Self-Administered 24-hr food records. The primary cognitive outcome was assessed at 9 months following randomization using a global composite score derived from three ambulatory cognitive assessments of visuospatial memory (Grid Memory), processing speed (Symbol Search) and short-term associative memory binding (Color Shapes). Secondary outcomes included performance on individual tests and association of dietary components with cognitive performance. RESULTS:At 9 month follow-up the MHD arm had a lower Dietary Inflammatory Index (DII) score based on self-reported diet, with an adjusted MHD minus Comparison difference of -0.64 (95% CI: -1.02, -0.27) and -0.94 (95% CI: -1.34, -0.54) for the DII and energy-adjusted DII scores respectively, indicating intervention participants had adhered to an anti-inflammatory dietary pattern. Group session and telephone contact completion averaged 93% and 72% respectively for the MHD arm. No statistically significant difference between arms was found in the primary outcome- cognitive global score change- from baseline: -0.06 (95% CI: -0.15, 0.04), p=0.259. CONCLUSIONS:The MHD was feasible and acceptable in this multicultural US cohort. While the influence of MHD at 9 months was non-significant based on the composite cognitive sco

关键词： Alzheimer’s disease and related dementias Diet assessment ambulatory cognitive monitoring cognitive function dietary inflammatory index multicultural healthy diet randomized controlled clinical trial

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