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Predictive Modeling Leveraging Electronic Health Records Identifies Early Predictors of Alzheimer’s Disease

Alzheimer's & Dementia 2023年第S15期19卷

作者： Alice S Tang Katherine P Rankin Gabriel Cerano Silvia Miramontes Hunter Mills Tomiko Oskotsky Billy Zeng Charlotte Nelson Karthik Soman Sarah Woldemariam Yaqiao Li Albert M Lee Zachary Miller Isabel Elaine Allen Stephan Sanders Sergio Baranzini Marina Sirota Graduate Program in Bioengineering University of California San Francisco and Berkeley San Francisco CA USA Bakar Computational Health Sciences Institute University of California San Francisco San Francisco CA USA Correspondece Memory and Aging Center UCSF Weill Institute for Neurosciences University of California San Francisco San Francisco CA USA Department of Neurology University of California San Francisco San Francisco CA USA Department of Epidemiology and Biostatistics University of California San Francisco San Francisco CA USA Department of Paediatrics University of Oxford Oxford United Kingdom Department of Pediatrics University of California San Francisco San Francisco CA USA

Background Alzheimer’s Disease (AD) is a neurodegenerative disorder of aging that is difficult to diagnose. Electronic health records (EHR) are a valuable source of longitudinal data for disease phenotyping and prediction. Knowledge graphs, such as SPOKE (Scalable Precision Medicine Open Knowledge Engine), help derive biological meaning from phenotypic data. Here we utilize machine learning on EHR to predict and better understand AD. Method AD patients and controls were identified from the UCSF EHR. The index time was identified as the first dementia diagnosis or drug record among the AD patients, and 1 year before the last visit among controls. Controls matched on demographics and visit-related factors were identified at five time points relative to the index time (-7years, -5years, -3years, -1year, and -1day) at a 1:8 ratio. Random forest (RF) classification models for AD were trained utilizing clinical data (conditions, drugs, abnormal measurements) and evaluated with bootstrapped AUROCs on a 30% held-out set. Top features mapped to phecodes were ranked based on average impurity decrease. Networks were created from SPOKE knowledge graph by identifying shortest paths between top 25 model features and AD, and associations were validated with genetic colocalization analysis on shared variants in the UK Biobank. Result From the UCSF EHR, 749 AD patients and 250,545 Controls were identified with clinical concepts 7 years prior to each individual’s index time. RF trained on AD and matched control individuals’ data performed with AUROC of 0.58 (-7years) to 0.77 (-1day). Top phecode features from models include those that are important earlier (osteoarthritis, allergic rhinitis), progress in importance closer to index time (dizziness, vitamin D deficiency, memory loss), and persist in importance throughout time (hyperlipidemia) (Figure 1). Knowledge networks highlight shared biological relationships between top features (e.g., hyperlipidemia, osteoporosis), including ide

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Author Correction: Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

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Nature genetics 2023年第3期55卷 519-520页

作者： Ceres Fernandez-Rozadilla Maria Timofeeva Zhishan Chen Philip Law Minta Thomas Stephanie Schmit Virginia Díez-Obrero Li Hsu Juan Fernandez-Tajes Claire Palles Kitty Sherwood Sarah Briggs Victoria Svinti Kevin Donnelly Susan Farrington James Blackmur Peter Vaughan-Shaw Xiao-Ou Shu Jirong Long Qiuyin Cai Xingyi Guo Yingchang Lu Peter Broderick James Studd Jeroen Huyghe Tabitha Harrison David Conti Christopher Dampier Mathew Devall Fredrick Schumacher Marilena Melas Gad Rennert Mireia Obón-Santacana Vicente Martín-Sánchez Ferran Moratalla-Navarro Jae Hwan Oh Jeongseon Kim Sun Ha Jee Keum Ji Jung Sun-Seog Kweon Min-Ho Shin Aesun Shin Yoon-Ok Ahn Dong-Hyun Kim Isao Oze Wanqing Wen Keitaro Matsuo Koichi Matsuda Chizu Tanikawa Zefang Ren Yu-Tang Gao Wei-Hua Jia John Hopper Mark Jenkins Aung Ko Win Rish Pai Jane Figueiredo Robert Haile Steven Gallinger Michael Woods Polly Newcomb David Duggan Jeremy Cheadle Richard Kaplan Timothy Maughan Rachel Kerr David Kerr Iva Kirac Jan Böhm Lukka-Pekka Mecklin Pekka Jousilahti Paul Knekt Lauri Aaltonen Harri Rissanen Eero Pukkala Johan Eriksson Tatiana Cajuso Ulrika Hänninen Johanna Kondelin Kimmo Palin Tomas Tanskanen Laura Renkonen-Sinisalo Brent Zanke Satu Männistö Demetrius Albanes Stephanie Weinstein Edward Ruiz-Narvaez Julie Palmer Daniel Buchanan Elizabeth Platz Kala Visvanathan Cornelia Ulrich Erin Siegel Stefanie Brezina Andrea Gsur Peter Campbell Jenny Chang-Claude Michael Hoffmeister Hermann Brenner Martha Slattery John Potter Konstantinos Tsilidis Matthias Schulze Marc Gunter Neil Murphy Antoni Castells Sergi Castellví-Bel Leticia Moreira Volker Arndt Anna Shcherbina Mariana Stern Bens Pardamean Timothy Bishop Graham Giles Melissa Southey Gregory Idos Kevin McDonnell Zomoroda Abu-Ful Joel Greenson Katerina Shulman Flavio Lejbkowicz Kenneth Offit Yu-Ru Su Robert Steinfelder Temitope Keku Bethany van Guelpen Thomas Hudson Heather Hampel Rachel Pearlman Sonja Berndt Richard Hayes Marie Elena Martinez Sushma Thomas Douglas Corley Paul Pharoah Susanna Larsson Yun Yen Heinz-Jo Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK. Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain. Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark. Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA. Division of Genetics and Epidemiology Institute of Cancer Research London UK. Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA. Genomic Medicine Institute Cleveland Clinic Cleveland OH USA. Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA. Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain. Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain. Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain. Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain. Department of Biostatistics School of Public Health University of Washington Seattle WA USA. Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK. Department of Public Health Richard Doll Building University of Oxford Oxford UK. Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA. Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA. Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA. De

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Author Correction: Multi-institutional atlas of brain metastases informs spatial modeling for precision imaging and personalized therapy

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Nature communications 2025年第1期16卷 5096页

作者： Jorge Barrios Evan Porter Dante P I Capaldi Taman Upadhaya William C Chen Julian R Perks Aditya Apte Michalis Aristophanous Eve LoCastro Dylan Hsu Payton H Stone Javier E Villanueva-Meyer Gilmer Valdes Fei Jiang Michael Maddalena Ase Ballangrud Kayla Prezelski Hui Lin Jinger Y Sun Muhtada A K Aldin Oi Wai Chau Benjamin Ziemer Maasa Seaberg Penny K Sneed Jean L Nakamura Lauren C Boreta Shannon E Fogh David R Raleigh Jessica Chew Harish Vasudevan Soonmee Cha Christopher Hess Ruben Fragoso David B Shultz Luke Pike Shawn L Hervey-Jumper Derek S Tsang Philip Theodosopoulos Daniel Cooke Stanley H Benedict Ke Sheng Jan Seuntjens Catherine Coolens Joseph O Deasy Steve Braunstein Olivier Morin Department of Radiation Oncology University of California San Francisco San Francisco CA USA. Department of Radiation Oncology University of California Davis Health Sacramento CA USA. Department of Radiation Oncology Memorial Sloan Kettering New York NY USA. Department of Medical Physics Memorial Sloan Kettering New York NY USA. Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA USA. Department of Neurological Surgery University of California San Francisco San Francisco CA USA. Department of Epidemiology and Biostatistics University of California San Francisco San Francisco CA USA. Moffit Cancer Center Tampa Florida USA. Radiation Medicine Program Princess Margaret Cancer Centre University Health Network Toronto ON Canada. Department of Medical Biophysics University of Toronto Toronto ON Canada. UCSF/UC Berkeley Graduate Program in Bioengineering San Francisco CA USA. Department of Pathology University of California San Francisco San Francisco CA USA. Department of Radiation Oncology University of California San Francisco San Francisco CA USA. Olivier.Morin@ucsf.edu. UCSF/UC Berkeley Graduate Program in Bioengineering San Francisco CA USA. Olivier.Morin@ucsf.edu.

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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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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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Comparative effectiveness of psychotherapies in adults with posttraumatic stress disorder: a network meta-analysis of randomised controlled trials

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Psychological medicine 2023年第13期53卷 6376-6388页

作者： Ninik Yunitri Hsin Chu Xiao Linda Kang Bayu Satria Wiratama Tso-Ying Lee Li-Fang Chang Doresses Liu Christina Yeni Kustanti Kai-Jo Chiang Ruey Chen Philip Tseng Kuei-Ru Chou School of Nursing College of Nursing Taipei Medical University Taipei Taiwan. Mental Health and Psychiatric Nursing Department Faculty of Nursing Universitas Muhammadiyah Jakarta Indonesia. Institute of Aerospace and Undersea Medicine School of Medicine National Defense Medical Center Taipei Taiwan. Department of Neurology Tri-Service General Hospital National Defense Medical Center Taipei Taiwan. School of Nursing University of Pennsylvania Philadelphia USA. Department of Biostatistics Epidemiology and Population Health Universitas Gadjah Mada Yogyakarta Indonesia. Nursing Research Center Department of Nursing Taipei Medical University Hospital Taipei Taiwan. Department of Medical Education & Emergency and Critical Care Medicine Taipei Medical University Hospital Taipei Taiwan. School of Nursing National Defense Medical Center Taipei Taiwan. Graduate Institute of Medical Sciences National Defense Medical Center Taipei Taiwan. Department of Nursing Wan Fang Hospital Taipei Medical University Taipei Taiwan. Center for Nursing and Healthcare Research in Clinical Practice Application Wan Fang Hospital Taipei Medical University Taipei Taiwan. Sekolah Tinggi Ilmu Kesehatan Bethesda Yakkum Yogyakarta Indonesia. Department of Nursing Tri-Service General Hospital National Defense Medical Center Taipei Taiwan. Department of Nursing Taipei Medical University-Shuang Ho Hospital New Taipei Taiwan. Post-Baccalaureate Program in Nursing College of Nursing Taipei Medical University Taipei Taiwan. Graduate Institute of Mind Brain and Consciousness Taipei Medical University Taipei Taiwan. Brain and Consciousness Research Center TMU - Shuang Ho Hospital New Taipei Taiwan. Research Center for Mind Brain & Learning National Chengchi University Taipei Taiwan. Psychiatric Research Center Taipei Medical University Hospital Taipei Taiwan. Neuroscience Research Center Taipei Medical University Taipei Taiwan.

BACKGROUND:Evidence on the long-term comparative effectiveness of posttraumatic stress disorder (PTSD) psychotherapies in adults remains unknown. Therefore, we performed an extensive network meta-analysis of randomised controlled trials (RCTs) to determine the comparative effectiveness of psychotherapies for people diagnosed with PTSD. METHODS:A comprehensive search was conducted in Cochrane library, Embase, Medline-OVID, PubMed, Scopus, and Psych-Info until March 2021. Studies on the effectiveness of cognitive processing therapy (CPT), cognitive therapy (CT), eye movement desensitisation reprocessing (EMDR), narrative exposure therapy (NET), prolonged exposure (PE), cognitive behavioural therapy (CBT), present-centred therapy (PCT), brief eclectic psychotherapies (BEP), psychodynamic therapy (PDT) or combination therapies compared to no treatment (NT) or treatment as usual (TAU) in adults with PTSD were included. Frequentist and Bayesian approaches were used for analysis in R-software. RESULTS:We included 98 RCTs with 5567 participants from 18 897 studies. CPT, EMDR, CT, NET, PE, CBT, and PCT were significant to reduce PTSD symptoms (SMD range: -1.53 to -0.75; Certainty: very low to high) at immediate post-treatment and ranked accordingly. Longitudinal analysis found EMDR (1.02) and CPT (0.85) as the significant therapies with large effect size in short-term and long-term follow-up, respectively. NET and CPT showed higher proportion of loss of PTSD diagnosis (RR range: 5.51-3.45) while there were no significant psychotherapies for retention rate compared to NT. CONCLUSIONS:Our findings provide evidence for improving current guidelines and informing clinical decision-making for PTSD management. However, the best PTSD treatment plan should be tailored to patients' needs, characteristics, and clinician expertise. REGISTRATION:PROSPERO CRD42020162143.

关键词： Effectiveness PTSD network meta-analysis psychotherapies

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POS0206-HPR POSTPARTUM DEPRESSION AMONG REPRODUCTIVE-AGE WOMEN WITH AND WITHOUT RHEUMATIC DISEASE: A POPULATION-BASED MATCHED COHORT STUDY

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Annals of the Rheumatic Diseases 2023年 82卷 329-329页

作者： D. Shridharmurthy K. Lapane A. Nunes J. Baek M. Weisman J. Kay S.H. Liu UMass Chan Medical School Division of Epidemiology Department of Population and Quantitative Health Sciences Worcester United States of America UMass Chan Medical School Clinical and Population Health Research Program Graduate School of Biomedical Sciences Worcester United States of America UMass Chan Medical School Division of Biostatistics and Health Services Research Department of Population and Quantitative Health Sciences Worcester United States of America Stanford University Division of Immunology and Rheumatology School of Medicine Palo Alto United States of America UMass Chan Medical School Division of Rheumatology Department of Medicine Worcester United States of America UMass Memorial Medical Center - Memorial Campus Division of Rheumatology Worcester United States of America

Background Postpartum depression is a psychiatric illness that occurs after the birth of a child and affects 12.5% of women in the United States (1) and 17.2% of women globally [2]. Women of reproductive age with rheumatic diseases (RD) are at increased risk of clinical depression [3]. However, research examining postpartum depression in women with RD is scarce. Objectives We examined postpartum depression among women with axial spondyloarthritis (axSpA), rheumatoid arthritis (RA), or psoriatic arthritis (PsA) compared to a matched population without RD in the United States. Methods A retrospective analysis using data from the 2013-2018 IBM MarketScan Commercial Claims and Encounters Database was conducted. Pregnant women with axSpA, RA, or PsA were identified, and the date of delivery was used as the index date. We restricted the sample to women ≤ 55 years with continuous enrollment ≥ 6 months before date of last menstrual period and throughout pregnancy (baseline period). Each patient was matched with four individuals without RD on: 1) maternal age at delivery; 2) prior history of depression; and 2) duration of depression before delivery. The outcome of interest was a diagnosis of depression within one year of the index date. Cox frailty proportional hazards models adjusting for sociodemographic and clinical characteristics in the baseline period were used to estimate the crude and adjusted hazard ratios and 95% confidence interval (CI) of incident postpartum depression among women with axSpA, RA, or PsA (axSpA/RA/PsA group) compared to the matched non-RD comparison group. Results Overall, 2,667 women with axSpA, RA, or PsA and 10,668 patients without any RD were included. The average age at baseline was 33 years (SD: 5.0), and nearly two in five women were older than 35 years. The median follow-up time in days was 256 (Interquartile range (IQR): 553) and 265 (IQR: 564) for the axSpA/RA/PsA and matched non-RD comparison groups. Development of postpartum depression

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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

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The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

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Correction: High-intensity sweet taste as a predictor of subjective alcohol responses to the ascending limb of an intravenous alcohol prime: an fMRI study

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Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 2024年第3期49卷 633页

作者： Jonathan Alessi Mario Dzemidzic Katherine Benson George Chittum Ann Kosobud Jaroslaw Harezlak Martin H Plawecki Sean J O'Connor David A Kareken Medical Neuroscience Graduate Program Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN USA. Indiana Alcohol Research Center Indiana University School of Medicine Indianapolis IN USA. Department of Neurology Indiana University School of Medicine Indianapolis IN USA. Department of Radiology Indiana University School of Medicine Indianapolis IN USA. Clinical Psychology Graduate Program Department of Psychology and Neuroscience University of North Carolina- Chapel Hill Chapel Hill NC USA. Department of Pharmacology & Toxicology Indiana University School of Medicine Indianapolis IN USA. Department of Epidemiology and Biostatistics Indiana University School of Public Health Bloomington IN USA. Department of Psychiatry Indiana University School of Medicine Indianapolis IN USA. Indiana Alcohol Research Center Indiana University School of Medicine Indianapolis IN USA. dkareken@iu.edu. Department of Neurology Indiana University School of Medicine Indianapolis IN USA. dkareken@iu.edu. Department of Radiology Indiana University School of Medicine Indianapolis IN USA. dkareken@iu.edu. Department of Psychiatry Indiana University School of Medicine Indianapolis IN USA. dkareken@iu.edu.

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Hypoxia-responsive circular RNA circAAGAB reduces breast cancer malignancy by activating p38 MAPK and sponging miR-378 h

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Cancer cell international 2023年第1期23卷 45页

作者： Kuan-Yi Lee Chia-Ming Liu Li-Han Chen Chien-Yueh Lee Tzu-Pin Lu Li-Ling Chuang Liang-Chuan Lai Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan. Institute of Fisheries Science College of Life Science National Taiwan University Taipei Taiwan. Department of Life Science College of Life Science National Taiwan University Taipei Taiwan. Master Program for Biomedical Engineering College of Biomedical Engineering China Medical University Taichung Taiwan. Institute of Epidemiology and Preventive Medicine Department of Public Health National Taiwan University Taipei Taiwan. School of Physical Therapy and Graduate Institute of Rehabilitation Science College of Medicine Chang Gung University Taoyuan Taiwan. lchuang@gap.cgu.edu.tw. Department of Physical Medicine and Rehabilitation Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. lchuang@gap.cgu.edu.tw. Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan. llai@ntu.edu.tw. Bioinformatics and Biostatistics Core Center of Genomic and Precision Medicine National Taiwan University Taipei Taiwan. llai@ntu.edu.tw.

BACKGROUND:Breast cancer is a prevalent disease in women, with high prevalence worldwide. The hypoxic microenvironment of solid tumors develops during the progress of carcinogenesis and leads to greater malignancy and treatment resistance. Recently, accumulating evidence indicates that non-coding RNAs, such as circular RNAs (circRNAs), play a pivotal role in altering cellular functions. However, the underlying mechanisms of circRNAs in breast cancer are still unclear. Therefore, the purpose of this study was to investigate the role of a tumor-suppressive circRNA, circAAGAB, in breast cancer by assuming down-regulation of circAAGAB under hypoxia and the properties of a tumor suppressor. METHODS:Firstly, circAAGAB was identified from expression profiling by next generation sequencing. Next, the stability of circAAGAB increased by interacting with the RNA binding protein FUS. Moreover, cellular and nuclear fractionation showed that most circAAGAB resided in the cytoplasm and that it up-regulated KIAA1522, NKX3-1, and JADE3 by sponging miR-378 h. Lastly, the functions of circAAGAB were explored by identifying its down-stream genes using Affymetrix microarrays and validated by in vitro assays. RESULTS:The results showed that circAAGAB reduced cell colony formation, cell migration, and signaling through p38 MAPK pathway, as well as increased radiosensitivity. CONCLUSION:These findings suggest that the oxygen-responsive circAAGAB acts as a tumor suppressor in breast cancer, and may contribute to the development of a more specific therapeutic regimen for breast cancer.

关键词： Breast cancer Hypoxia Radiosensitivity Tumor suppressor circAAGAB miRNA sponge p38 MAPK

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