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Warashina T, Sato A, Hinai H, Shaikhutdinov N, Shagimardanova E, Mori H, Tamaki S, Saito M, Sanada Y, Sasaki Y, Shimada K, Dotsuta Y, Kitagaki T, Maruyama S, Gusev O, Narumi I, Kurokawa K, Morita T, Ebisuzaki T, Nishimura A, Koma Y, Kanai A. Microbiome analysis of the restricted bacteria in radioactive element-containing water at the Fukushima Daiichi Nuclear Power Station. Appl Environ Microbiol 2024; 90:e0211323. [PMID: 38470121 PMCID: PMC11022576 DOI: 10.1128/aem.02113-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/21/2024] [Indexed: 03/13/2024] Open
Abstract
A major incident occurred at the Fukushima Daiichi Nuclear Power Station following the tsunami triggered by the Tohoku-Pacific Ocean Earthquake in March 2011, whereby seawater entered the torus room in the basement of the reactor building. Here, we identify and analyze the bacterial communities in the torus room water and several environmental samples. Samples of the torus room water (1 × 109 Bq137Cs/L) were collected by the Tokyo Electric Power Company Holdings from two sampling points between 30 cm and 1 m from the bottom of the room (TW1) and the bottom layer (TW2). A structural analysis of the bacterial communities based on 16S rRNA amplicon sequencing revealed that the predominant bacterial genera in TW1 and TW2 were similar. TW1 primarily contained the genus Limnobacter, a thiosulfate-oxidizing bacterium. γ-Irradiation tests on Limnobacter thiooxidans, the most closely related phylogenetically found in TW1, indicated that its radiation resistance was similar to ordinary bacteria. TW2 predominantly contained the genus Brevirhabdus, a manganese-oxidizing bacterium. Although bacterial diversity in the torus room water was lower than seawater near Fukushima, ~70% of identified genera were associated with metal corrosion. Latent environment allocation-an analytical technique that estimates habitat distributions and co-detection analyses-revealed that the microbial communities in the torus room water originated from a distinct blend of natural marine microbial and artificial bacterial communities typical of biofilms, sludge, and wastewater. Understanding the specific bacteria linked to metal corrosion in damaged plants is important for advancing decommissioning efforts. IMPORTANCE In the context of nuclear power station decommissioning, the proliferation of microorganisms within the reactor and piping systems constitutes a formidable challenge. Therefore, the identification of microbial communities in such environments is of paramount importance. In the aftermath of the Fukushima Daiichi Nuclear Power Station accident, microbial community analysis was conducted on environmental samples collected mainly outside the site. However, analyses using samples from on-site areas, including adjacent soil and seawater, were not performed. This study represents the first comprehensive analysis of microbial communities, utilizing meta 16S amplicon sequencing, with a focus on environmental samples collected from the radioactive element-containing water in the torus room, including the surrounding environments. Some of the identified microbial genera are shared with those previously identified in spent nuclear fuel pools in countries such as France and Brazil. Moreover, our discussion in this paper elucidates the correlation of many of these bacteria with metal corrosion.
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Affiliation(s)
- Tomoro Warashina
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, Japan
| | - Asako Sato
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan
| | | | - Nurislam Shaikhutdinov
- Regulatory Genomics Research Center, Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan, Russia
| | - Elena Shagimardanova
- Regulatory Genomics Research Center, Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan, Russia
- Life Improvement by Future Technologies (LIFT) Center, Skolkovo, Moscow, Russia
- Loginov Moscow Clinical Scientific Center, Moscow, Russia
| | | | - Satoshi Tamaki
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan
| | - Motofumi Saito
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, Japan
| | | | | | | | | | | | - Shigenori Maruyama
- Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan
| | - Oleg Gusev
- Regulatory Genomics Research Center, Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan, Russia
- Life Improvement by Future Technologies (LIFT) Center, Skolkovo, Moscow, Russia
- Intractable Disease Research Center, School of Medicine, Juntendo University, Tokyo, Japan
| | - Issay Narumi
- Faculty of Life Sciences, Toyo University, Oura-gun, Japan
| | | | - Teppei Morita
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, Japan
| | | | | | | | - Akio Kanai
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, Japan
- Faculty of Environment and Information Studies, Keio University, Fujisawa, Japan
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Cai CX, Nishimura A, Bowring MG, Westlund E, Tran D, Ng JH, Nagy P, Cook M, McLeggon JA, DuVall SL, Matheny ME, Golozar A, Ostropolets A, Minty E, Desai P, Bu F, Toy B, Hribar M, Falconer T, Zhang L, Lawrence-Archer L, Boland MV, Goetz K, Hall N, Shoaibi A, Reps J, Sena AG, Blacketer C, Swerdel J, Jhaveri KD, Lee E, Gilbert Z, Zeger SL, Crews DC, Suchard MA, Hripcsak G, Ryan PB. Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab: An Observational Health Data Sciences and Informatics Network Study. Ophthalmol Retina 2024:S2468-6530(24)00118-0. [PMID: 38519026 DOI: 10.1016/j.oret.2024.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 03/08/2024] [Accepted: 03/12/2024] [Indexed: 03/24/2024]
Abstract
PURPOSE To characterize the incidence of kidney failure associated with intravitreal anti-VEGF exposure; and compare the risk of kidney failure in patients treated with ranibizumab, aflibercept, or bevacizumab. DESIGN Retrospective cohort study across 12 databases in the Observational Health Data Sciences and Informatics (OHDSI) network. SUBJECTS Subjects aged ≥ 18 years with ≥ 3 monthly intravitreal anti-VEGF medications for a blinding disease (diabetic retinopathy, diabetic macular edema, exudative age-related macular degeneration, or retinal vein occlusion). METHODS The standardized incidence proportions and rates of kidney failure while on treatment with anti-VEGF were calculated. For each comparison (e.g., aflibercept versus ranibizumab), patients from each group were matched 1:1 using propensity scores. Cox proportional hazards models were used to estimate the risk of kidney failure while on treatment. A random effects meta-analysis was performed to combine each database's hazard ratio (HR) estimate into a single network-wide estimate. MAIN OUTCOME MEASURES Incidence of kidney failure while on anti-VEGF treatment, and time from cohort entry to kidney failure. RESULTS Of the 6.1 million patients with blinding diseases, 37 189 who received ranibizumab, 39 447 aflibercept, and 163 611 bevacizumab were included; the total treatment exposure time was 161 724 person-years. The average standardized incidence proportion of kidney failure was 678 per 100 000 persons (range, 0-2389), and incidence rate 742 per 100 000 person-years (range, 0-2661). The meta-analysis HR of kidney failure comparing aflibercept with ranibizumab was 1.01 (95% confidence interval [CI], 0.70-1.47; P = 0.45), ranibizumab with bevacizumab 0.95 (95% CI, 0.68-1.32; P = 0.62), and aflibercept with bevacizumab 0.95 (95% CI, 0.65-1.39; P = 0.60). CONCLUSIONS There was no substantially different relative risk of kidney failure between those who received ranibizumab, bevacizumab, or aflibercept. Practicing ophthalmologists and nephrologists should be aware of the risk of kidney failure among patients receiving intravitreal anti-VEGF medications and that there is little empirical evidence to preferentially choose among the specific intravitreal anti-VEGF agents. FINANCIAL DISCLOSURES Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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Affiliation(s)
- Cindy X Cai
- Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland.
| | - Akihiko Nishimura
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Mary G Bowring
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Erik Westlund
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Diep Tran
- Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Jia H Ng
- Division of Kidney Diseases and Hypertension, Donald and Barbara School of Medicine at Hofstra/Northwell, New York
| | - Paul Nagy
- Department of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | | | - Jody-Ann McLeggon
- Department of Biomedical Informatics, Columbia University, New York, New York
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, US Department of Veterans Affairs, Salt Lake City, Utah; Department of Internal Medicine Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
| | - Michael E Matheny
- VA Informatics and Computing Infrastructure, Tennessee Valley Healthcare System, Nashville, Tennessee; Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee
| | - Asieh Golozar
- Odysseus Data Services, Inc., Cambridge, Massachusetts; OHDSI Center at the Roux Institute, Northeastern University, Boston, Massachusetts
| | | | - Evan Minty
- O'Brien Center for Public Health, Department of Medicine, University of Calgary, Canada
| | - Priya Desai
- Technology / Digital Solutions, Stanford Health Care and Stanford University School of Medicine, Palo Alto, California
| | - Fan Bu
- Department of Biostatistics, University of California - Los Angeles, Los Angeles, California
| | - Brian Toy
- Roski Eye Institute, Keck School of Medicine, University of Southern California; Los Angeles, California
| | - Michelle Hribar
- National Eye Institute, National Institutes of Health, Bethesda, Maryland; Casey Eye Institute, Oregon Health & Science University, Portland, Oregon
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, New York
| | - Linying Zhang
- Department of Biomedical Informatics, Columbia University, New York, New York
| | - Laurence Lawrence-Archer
- Odysseus Data Services, Inc., Cambridge, Massachusetts; OHDSI Center at the Roux Institute, Northeastern University, Boston, Massachusetts
| | - Michael V Boland
- Mass Eye and Ear, and Harvard Medical School, Boston, Massachusetts
| | - Kerry Goetz
- National Eye Institute, National Institutes of Health, Bethesda, Maryland
| | - Nathan Hall
- Janssen Research and Development, Titusville, New Jersey
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, New Jersey
| | - Jenna Reps
- Janssen Research and Development, Titusville, New Jersey
| | - Anthony G Sena
- Janssen Research and Development, Titusville, New Jersey; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Joel Swerdel
- Janssen Research and Development, Titusville, New Jersey
| | - Kenar D Jhaveri
- Glomerular Center at Northwell Health, Division of Kidney Diseases and Hypertension, Donald and Barbara School of Medicine at Hofstra/Northwell, New York
| | - Edward Lee
- Roski Eye Institute, Keck School of Medicine, University of Southern California; Los Angeles, California
| | - Zachary Gilbert
- Roski Eye Institute, Keck School of Medicine, University of Southern California; Los Angeles, California
| | - Scott L Zeger
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Deidra C Crews
- Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Marc A Suchard
- VA Informatics and Computing Infrastructure, US Department of Veterans Affairs, Salt Lake City, Utah; Department of Biostatistics, University of California - Los Angeles, Los Angeles, California
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, New York
| | - Patrick B Ryan
- Janssen Research and Development, Titusville, New Jersey
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Khera R, Aminorroaya A, Dhingra LS, Thangaraj PM, Camargos AP, Bu F, Ding X, Nishimura A, Anand TV, Arshad F, Blacketer C, Chai Y, Chattopadhyay S, Cook M, Dorr DA, Duarte-Salles T, DuVall SL, Falconer T, French TE, Hanchrow EE, Kaur G, Lau WC, Li J, Li K, Liu Y, Lu Y, Man KK, Matheny ME, Mathioudakis N, McLeggon JA, McLemore MF, Minty E, Morales DR, Nagy P, Ostropolets A, Pistillo A, Phan TP, Pratt N, Reyes C, Richter L, Ross J, Ruan E, Seager SL, Simon KR, Viernes B, Yang J, Yin C, You SC, Zhou JJ, Ryan PB, Schuemie MJ, Krumholz HM, Hripcsak G, Suchard MA. Comparative Effectiveness of Second-line Antihyperglycemic Agents for Cardiovascular Outcomes: A Large-scale, Multinational, Federated Analysis of the LEGEND-T2DM Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.05.24302354. [PMID: 38370787 PMCID: PMC10871374 DOI: 10.1101/2024.02.05.24302354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Background SGLT2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP1-RAs) reduce major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head trials. Methods Across the LEGEND-T2DM network, we included ten federated international data sources, spanning 1992-2021. We identified 1,492,855 patients with T2DM and established cardiovascular disease (CVD) on metformin monotherapy who initiated one of four second-line agents (SGLT2is, GLP1-RAs, dipeptidyl peptidase 4 inhibitor [DPP4is], sulfonylureas [SUs]). We used large-scale propensity score models to conduct an active comparator, target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, we fit on-treatment Cox proportional hazard models for 3-point MACE (myocardial infarction, stroke, death) and 4-point MACE (3-point MACE + heart failure hospitalization) risk, and combined hazard ratio (HR) estimates in a random-effects meta-analysis. Findings Across cohorts, 16·4%, 8·3%, 27·7%, and 47·6% of individuals with T2DM initiated SGLT2is, GLP1-RAs, DPP4is, and SUs, respectively. Over 5·2 million patient-years of follow-up and 489 million patient-days of time at-risk, there were 25,982 3-point MACE and 41,447 4-point MACE events. SGLT2is and GLP1-RAs were associated with a lower risk for 3-point MACE compared with DPP4is (HR 0·89 [95% CI, 0·79-1·00] and 0·83 [0·70-0·98]), and SUs (HR 0·76 [0·65-0·89] and 0·71 [0·59-0·86]). DPP4is were associated with a lower 3-point MACE risk versus SUs (HR 0·87 [0·79-0·95]). The pattern was consistent for 4-point MACE for the comparisons above. There were no significant differences between SGLT2is and GLP1-RAs for 3-point or 4-point MACE (HR 1·06 [0·96-1·17] and 1·05 [0·97-1·13]). Interpretation In patients with T2DM and established CVD, we found comparable cardiovascular risk reduction with SGLT2is and GLP1-RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of GLP1-RAs and SGLT2is should be prioritized as second-line agents in those with established CVD. Funding National Institutes of Health, United States Department of Veterans Affairs.
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Affiliation(s)
- Rohan Khera
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
- Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, CT, 06510, USA
- Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, 06520, USA
| | - Arya Aminorroaya
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
| | - Lovedeep Singh Dhingra
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
| | - Phyllis M Thangaraj
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
| | - Aline Pedroso Camargos
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
| | - Fan Bu
- Department of Biostatistics, University of Michigan - Ann Arbor, Ann Arbor, MI, 48105, USA
| | - Xiyu Ding
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Tara V Anand
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Faaizah Arshad
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Clair Blacketer
- Observational Health Data Analytics, Janssen Research and Development, LLC, Titusville, NJ, 8560, USA
| | - Yi Chai
- Department of Pharmacology and Pharmacy, LKS Faculty of Medicine, The University of Hong Kong
| | - Shounak Chattopadhyay
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Michael Cook
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - David A Dorr
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, 8007, Spain
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Scott L DuVall
- Veterans Affairs Informatics and Computing Infrastructure, United States Department of Veterans Affairs, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Tina E French
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Elizabeth E Hanchrow
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Guneet Kaur
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, DD1 9SY, United Kingdom
| | - Wallis Cy Lau
- Research Department of Practice and Policy, School of Pharmacy, University College London, London, WC1H 9JP, United Kingdom
- Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, United Kingdom
- Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, Hong Kong
| | - Jing Li
- Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA, Durham, NC, USA
| | - Kelly Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Yuntian Liu
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
- Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, CT, 06510, USA
| | - Yuan Lu
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
| | - Kenneth Kc Man
- Research Department of Practice and Policy, School of Pharmacy, University College London, London, WC1H 9JP, United Kingdom
- Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, United Kingdom
- Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, Hong Kong
| | - Michael E Matheny
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nestoras Mathioudakis
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jody-Ann McLeggon
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Michael F McLemore
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Evan Minty
- Faculty of Medicine, O'Brien Institute for Public Health, University of Calgary, Calgary, AB, T2N4N1, Canada
| | - Daniel R Morales
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, DD1 9SY, United Kingdom
| | - Paul Nagy
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anna Ostropolets
- Observational Health Data Analytics, Janssen Research and Development, LLC, Titusville, NJ, 8560, USA
| | - Andrea Pistillo
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, 8007, Spain
| | | | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Centre, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | - Carlen Reyes
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, 8007, Spain
| | - Lauren Richter
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Joseph Ross
- Section of General Medicine and National Clinician Scholars Program, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, CT, 06510, USA
| | - Elise Ruan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Sarah L Seager
- Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA, London, UK
| | - Katherine R Simon
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin Viernes
- Veterans Affairs Informatics and Computing Infrastructure, United States Department of Veterans Affairs, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Jianxiao Yang
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Can Yin
- Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA, Shanghai, China
| | - Seng Chan You
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, South Korea
- Institute for Innovation in Digital Healthcare, Yonsei University College of Medicine, Seoul, South Korea
| | - Jin J Zhou
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Patrick B Ryan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Martijn J Schuemie
- Epidemiology, Office of the Chief Medical Officer, Johnson & Johnson, Titusville, NJ, 8560, USA
| | - Harlan M Krumholz
- Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, CT, 06510, USA
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, 06510, USA
- Section of Cardiovascular Medicine, Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, 06510, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Marc A Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Veterans Affairs Informatics and Computing Infrastructure, United States Department of Veterans Affairs, Salt Lake City, UT, USA
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Bu F, Schuemie MJ, Nishimura A, Smith LH, Kostka K, Falconer T, McLeggon JA, Ryan PB, Hripcsak G, Suchard MA. Bayesian safety surveillance with adaptive bias correction. Stat Med 2024; 43:395-418. [PMID: 38010062 DOI: 10.1002/sim.9968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 11/03/2023] [Accepted: 11/08/2023] [Indexed: 11/29/2023]
Abstract
Postmarket safety surveillance is an integral part of mass vaccination programs. Typically relying on sequential analysis of real-world health data as they accrue, safety surveillance is challenged by sequential multiple testing and by biases induced by residual confounding in observational data. The current standard approach based on the maximized sequential probability ratio test (MaxSPRT) fails to satisfactorily address these practical challenges and it remains a rigid framework that requires prespecification of the surveillance schedule. We develop an alternative Bayesian surveillance procedure that addresses both aforementioned challenges using a more flexible framework. To mitigate bias, we jointly analyze a large set of negative control outcomes that are adverse events with no known association with the vaccines in order to inform an empirical bias distribution, which we then incorporate into estimating the effect of vaccine exposure on the adverse event of interest through a Bayesian hierarchical model. To address multiple testing and improve on flexibility, at each analysis timepoint, we update a posterior probability in favor of the alternative hypothesis that vaccination induces higher risks of adverse events, and then use it for sequential detection of safety signals. Through an empirical evaluation using six US observational healthcare databases covering more than 360 million patients, we benchmark the proposed procedure against MaxSPRT on testing errors and estimation accuracy, under two epidemiological designs, the historical comparator and the self-controlled case series. We demonstrate that our procedure substantially reduces Type 1 error rates, maintains high statistical power and fast signal detection, and provides considerably more accurate estimation than MaxSPRT. Given the extensiveness of the empirical study which yields more than 7 million sets of results, we present all results in a public R ShinyApp. As an effort to promote open science, we provide full implementation of our method in the open-source R package EvidenceSynthesis.
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Affiliation(s)
- Fan Bu
- Department of Biostatistics, University of California, Los Angeles, California, USA
- Department of Biostatistics, University of Michigan-Ann Arbor, Ann Arbor, Michigan, USA
| | - Martijn J Schuemie
- Department of Biostatistics, University of California, Los Angeles, California, USA
- Janssen Research and Development, Raritan, New Jersey, USA
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Louisa H Smith
- Department of Health Sciences, Northeastern University, Portland, Maine, USA
- The OHDSI Center at the Roux Institute, Northeastern University, Portland, Maine, USA
| | - Kristin Kostka
- The OHDSI Center at the Roux Institute, Northeastern University, Portland, Maine, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Jody-Ann McLeggon
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Patrick B Ryan
- Janssen Research and Development, Raritan, New Jersey, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Marc A Suchard
- Department of Biostatistics, University of California, Los Angeles, California, USA
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Fisher AA, Ji X, Nishimura A, Baele G, Lemey P, Suchard MA. Shrinkage-based Random Local Clocks with Scalable Inference. Mol Biol Evol 2023; 40:msad242. [PMID: 37950885 PMCID: PMC10665039 DOI: 10.1093/molbev/msad242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 10/23/2023] [Accepted: 11/07/2023] [Indexed: 11/13/2023] Open
Abstract
Molecular clock models undergird modern methods of divergence-time estimation. Local clock models propose that the rate of molecular evolution is constant within phylogenetic subtrees. Current local clock inference procedures exhibit one or more weaknesses, namely they achieve limited scalability to trees with large numbers of taxa, impose model misspecification, or require a priori knowledge of the existence and location of clocks. To overcome these challenges, we present an autocorrelated, Bayesian model of heritable clock rate evolution that leverages heavy-tailed priors with mean zero to shrink increments of change between branch-specific clocks. We further develop an efficient Hamiltonian Monte Carlo sampler that exploits closed form gradient computations to scale our model to large trees. Inference under our shrinkage clock exhibits a speed-up compared to the popular random local clock when estimating branch-specific clock rates on a variety of simulated datasets. This speed-up increases with the size of the problem. We further show our shrinkage clock recovers known local clocks within a rodent and mammalian phylogeny. Finally, in a problem that once appeared computationally impractical, we investigate the heritable clock structure of various surface glycoproteins of influenza A virus in the absence of prior knowledge about clock placement. We implement our shrinkage clock and make it publicly available in the BEAST software package.
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Affiliation(s)
| | - Xiang Ji
- Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, LA, USA
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Marc A Suchard
- Department of Computational Medicine, University of California, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA, USA
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6
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Khera R, Dhingra LS, Aminorroaya A, Li K, Zhou JJ, Arshad F, Blacketer C, Bowring MG, Bu F, Cook M, Dorr DA, Duarte-Salles T, DuVall SL, Falconer T, French TE, Hanchrow EE, Horban S, Lau WCY, Li J, Liu Y, Lu Y, Man KKC, Matheny ME, Mathioudakis N, McLemore MF, Minty E, Morales DR, Nagy P, Nishimura A, Ostropolets A, Pistillo A, Posada JD, Pratt N, Reyes C, Ross JS, Seager S, Shah N, Simon K, Wan EYF, Yang J, Yin C, You SC, Schuemie MJ, Ryan PB, Hripcsak G, Krumholz H, Suchard MA. Multinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM. BMJ Med 2023; 2:e000651. [PMID: 37829182 PMCID: PMC10565313 DOI: 10.1136/bmjmed-2023-000651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 07/07/2023] [Indexed: 10/14/2023]
Abstract
Objective To assess the uptake of second line antihyperglycaemic drugs among patients with type 2 diabetes mellitus who are receiving metformin. Design Federated pharmacoepidemiological evaluation in LEGEND-T2DM. Setting 10 US and seven non-US electronic health record and administrative claims databases in the Observational Health Data Sciences and Informatics network in eight countries from 2011 to the end of 2021. Participants 4.8 million patients (≥18 years) across US and non-US based databases with type 2 diabetes mellitus who had received metformin monotherapy and had initiated second line treatments. Exposure The exposure used to evaluate each database was calendar year trends, with the years in the study that were specific to each cohort. Main outcomes measures The outcome was the incidence of second line antihyperglycaemic drug use (ie, glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors, and sulfonylureas) among individuals who were already receiving treatment with metformin. The relative drug class level uptake across cardiovascular risk groups was also evaluated. Results 4.6 million patients were identified in US databases, 61 382 from Spain, 32 442 from Germany, 25 173 from the UK, 13 270 from France, 5580 from Scotland, 4614 from Hong Kong, and 2322 from Australia. During 2011-21, the combined proportional initiation of the cardioprotective antihyperglycaemic drugs (glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors) increased across all data sources, with the combined initiation of these drugs as second line drugs in 2021 ranging from 35.2% to 68.2% in the US databases, 15.4% in France, 34.7% in Spain, 50.1% in Germany, and 54.8% in Scotland. From 2016 to 2021, in some US and non-US databases, uptake of glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors increased more significantly among populations with no cardiovascular disease compared with patients with established cardiovascular disease. No data source provided evidence of a greater increase in the uptake of these two drug classes in populations with cardiovascular disease compared with no cardiovascular disease. Conclusions Despite the increase in overall uptake of cardioprotective antihyperglycaemic drugs as second line treatments for type 2 diabetes mellitus, their uptake was lower in patients with cardiovascular disease than in people with no cardiovascular disease over the past decade. A strategy is needed to ensure that medication use is concordant with guideline recommendations to improve outcomes of patients with type 2 diabetes mellitus.
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Affiliation(s)
- Rohan Khera
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, USA
- Section of Health Informatics, Department of Biostatistics, Yale University School of Public Health, New Haven, CT, USA
| | - Lovedeep Singh Dhingra
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
| | - Arya Aminorroaya
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
| | - Kelly Li
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Jin J Zhou
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Faaizah Arshad
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Clair Blacketer
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Mary G Bowring
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fan Bu
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael Cook
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - David A Dorr
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University School of Medicine, Portland, OR, USA
| | - Talita Duarte-Salles
- Real-World Epidemiology Research Group, Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Scott L DuVall
- Veterans Affairs Informatics and Computing Infrastructure, United States Department of Veterans Affairs, Salt Lake City, UT, USA
- The University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Tina E French
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Elizabeth E Hanchrow
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Scott Horban
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Wallis CY Lau
- Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK
- Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, UK
- Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, China
| | - Jing Li
- Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA Inc, Durham, NC, USA
| | - Yuntian Liu
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, USA
| | - Yuan Lu
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
| | - Kenneth KC Man
- Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK
- Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, UK
- Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, China
| | - Michael E Matheny
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nestoras Mathioudakis
- Division of Endocrinology, Diabetes, and Metabolism, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael F McLemore
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Evan Minty
- Faculty of Medicine, O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada
| | - Daniel R Morales
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Paul Nagy
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Health Science Informatics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Akihiko Nishimura
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Andrea Pistillo
- Real-World Epidemiology Research Group, Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Jose D Posada
- Systems Engineering and Computing, School of Engineering, Universidad del Norte, Barranquilla, Colombia
| | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Centre, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Carlen Reyes
- Real-World Epidemiology Research Group, Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Joseph S Ross
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, USA
- Section of General Medicine and National Clinician Scholars Program, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Health Policy and Management, Yale University School of Public Health, New Haven, CT, USA
| | - Sarah Seager
- Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA Inc, Durham, NC, USA
| | - Nigam Shah
- Center for Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA, USA
- Clinical Excellence Research Center, Stanford University School of Medicine, Stanford, CA, USA
- Technology and Digital Solutions, Stanford Health Care, Stanford, CA, USA
| | - Katherine Simon
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Eric YF Wan
- Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, University of Hong Kong, Hong Kong, China
| | - Jianxiao Yang
- Department of Computational Medicine, University of California Los Angeles David Geffen School of Medicine, Los Angeles, CA, USA
| | - Can Yin
- Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA Inc, Durham, NC, USA
| | - Seng Chan You
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (aka South Korea)
- Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Republic of Korea (aka South Korea)
| | - Martijn J Schuemie
- Epidemiology, Office of the Chief Medical Officer, Johnson & Johnson, Titusville, NJ, USA
| | - Patrick B Ryan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Harlan Krumholz
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, USA
- Department of Health Policy and Management, Yale University School of Public Health, New Haven, CT, USA
| | - Marc A Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Veterans Affairs Informatics and Computing Infrastructure, United States Department of Veterans Affairs, Salt Lake City, UT, USA
- Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
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7
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Zhang Z, Nishimura A, Trovão NS, Cherry JL, Holbrook AJ, Ji X, Lemey P, Suchard MA. Accelerating Bayesian inference of dependency between mixed-type biological traits. PLoS Comput Biol 2023; 19:e1011419. [PMID: 37639445 PMCID: PMC10491301 DOI: 10.1371/journal.pcbi.1011419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/08/2023] [Accepted: 08/09/2023] [Indexed: 08/31/2023] Open
Abstract
Inferring dependencies between mixed-type biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible when trait and specimen counts grow large. The state-of-the-art approach uses a phylogenetic multivariate probit model to accommodate binary and continuous traits via a latent variable framework, and utilizes an efficient bouncy particle sampler (BPS) to tackle the computational bottleneck-integrating many latent variables from a high-dimensional truncated normal distribution. This approach breaks down as the number of specimens grows and fails to reliably characterize conditional dependencies between traits. Here, we propose an inference pipeline for phylogenetic probit models that greatly outperforms BPS. The novelty lies in 1) a combination of the recent Zigzag Hamiltonian Monte Carlo (Zigzag-HMC) with linear-time gradient evaluations and 2) a joint sampling scheme for highly correlated latent variables and correlation matrix elements. In an application exploring HIV-1 evolution from 535 viruses, the inference requires joint sampling from an 11,235-dimensional truncated normal and a 24-dimensional covariance matrix. Our method yields a 5-fold speedup compared to BPS and makes it possible to learn partial correlations between candidate viral mutations and virulence. Computational speedup now enables us to tackle even larger problems: we study the evolution of influenza H1N1 glycosylations on around 900 viruses. For broader applicability, we extend the phylogenetic probit model to incorporate categorical traits, and demonstrate its use to study Aquilegia flower and pollinator co-evolution.
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Affiliation(s)
- Zhenyu Zhang
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Nídia S. Trovão
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Joshua L. Cherry
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Andrew J. Holbrook
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
| | - Xiang Ji
- Department of Mathematics, Tulane University, New Orleans, Louisiana, United States of America
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Marc A. Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
- Department of Biomathematics, University of California Los Angeles, Los Angeles, California, United States of America
- Department of Human Genetics, University of California Los Angeles, Los Angeles, California, United States of America
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8
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Khera R, Dhingra L, Li K, Aminorroaya A, Zhou J, Arshad F, Bu F, Dorr D, Falconer T, French T, Lau W, Lu Y, Man K, Matheny ME, Minty E, Nishimura A, Ostropolets A, Seager S, Y.F. WE, Yang J, Yin C, Hripcsak G, Krumholz HM. MULTINATIONAL PATTERNS OF SECOND-LINE ANTI-HYPERGLYCEMIC DRUG INITIATION IN ESTABLISHED CARDIOVASCULAR DISEASE: A FEDERATED PHARMACOEPIDEMIOLOGIC EVALUATION IN LEGEND-T2DM. J Am Coll Cardiol 2023. [DOI: 10.1016/s0735-1097(23)02090-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
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9
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Schuemie MJ, Bu F, Nishimura A, Suchard MA. Adjusting for both sequential testing and systematic error in safety surveillance using observational data: Empirical calibration and MaxSPRT. Stat Med 2023; 42:619-631. [PMID: 36642826 PMCID: PMC10107810 DOI: 10.1002/sim.9631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 09/30/2022] [Accepted: 12/08/2022] [Indexed: 01/17/2023]
Abstract
Post-approval safety surveillance of medical products using observational healthcare data can help identify safety issues beyond those found in pre-approval trials. When testing sequentially as data accrue, maximum sequential probability ratio testing (MaxSPRT) is a common approach to maintaining nominal type 1 error. However, the true type 1 error may still deviate from the specified one because of systematic error due to the observational nature of the analysis. This systematic error may persist even after controlling for known confounders. Here we propose to address this issue by combing MaxSPRT with empirical calibration. In empirical calibration, we assume uncertainty about the systematic error in our analysis, the source of uncertainty commonly overlooked in practice. We infer a probability distribution of systematic error by relying on a large set of negative controls: exposure-outcome pairs where no causal effect is believed to exist. Integrating this distribution into our test statistics has previously been shown to restore type 1 error to nominal. Here we show how we can calibrate the critical value central to MaxSPRT. We evaluate this novel approach using simulations and real electronic health records, using H1N1 vaccinations during the 2009-2010 season as an example. Results show that combining empirical calibration with MaxSPRT restores nominal type 1 error. In our real-world example, adjusting for systematic error using empirical calibration has a larger impact than, and hence is just as essential as, adjusting for sequential testing using MaxSPRT. We recommend performing both, using the method described here.
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Affiliation(s)
- Martijn J Schuemie
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey.,Department of Biostatistics, University of California, Los Angeles, California
| | - Fan Bu
- Department of Biostatistics, University of California, Los Angeles, California.,Department of Human Genetics, University of California, Los Angeles, California
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Marc A Suchard
- Department of Biostatistics, University of California, Los Angeles, California.,Department of Human Genetics, University of California, Los Angeles, California.,VA Informatics and Computing Infrastructure, US Department of Veterans Affairs, Salt Lake City, Utah, USA
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10
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Nishimura A, Xie J, Kostka K, Duarte-Salles T, Fernández Bertolín S, Aragón M, Blacketer C, Shoaibi A, DuVall SL, Lynch K, Matheny ME, Falconer T, Morales DR, Conover MM, Chan You S, Pratt N, Weaver J, Sena AG, Schuemie MJ, Reps J, Reich C, Rijnbeek PR, Ryan PB, Hripcsak G, Prieto-Alhambra D, Suchard MA. International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients. Front Pharmacol 2022; 13:945592. [PMID: 36188566 PMCID: PMC9518954 DOI: 10.3389/fphar.2022.945592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 07/25/2022] [Indexed: 12/02/2022] Open
Abstract
Purpose: Alpha-1 blockers, often used to treat benign prostatic hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storm release. The proposed treatment based on this hypothesis currently lacks support from reliable real-world evidence, however. We leverage an international network of large-scale healthcare databases to generate comprehensive evidence in a transparent and reproducible manner. Methods: In this international cohort study, we deployed electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We assessed association between alpha-1 blocker use and risks of three COVID-19 outcomes—diagnosis, hospitalization, and hospitalization requiring intensive services—using a prevalent-user active-comparator design. We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We pooled database-specific estimates through random effects meta-analysis. Results: Our study overall included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH medications. We observed no significant difference in their risks for any of the COVID-19 outcomes, with our meta-analytic HR estimates being 1.02 (95% CI: 0.92–1.13) for diagnosis, 1.00 (95% CI: 0.89–1.13) for hospitalization, and 1.15 (95% CI: 0.71–1.88) for hospitalization requiring intensive services. Conclusion: We found no evidence of the hypothesized reduction in risks of the COVID-19 outcomes from the prevalent-use of alpha-1 blockers—further research is needed to identify effective therapies for this novel disease.
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Affiliation(s)
- Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Junqing Xie
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford University, Oxford, United Kingdom
| | - Kristin Kostka
- Real World Solutions, IQVIA, Cambridge, MA, United States
- The OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, United States
| | - Talita Duarte-Salles
- Fundació Institut Universitari Per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Sergio Fernández Bertolín
- Fundació Institut Universitari Per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - María Aragón
- Fundació Institut Universitari Per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Clair Blacketer
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
| | - Azza Shoaibi
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
| | - Scott L. DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, United States
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States
| | - Kristine Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, United States
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States
| | - Michael E. Matheny
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, United States
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Daniel R. Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, United Kingdom
- Department of Public Health, University of Southern Denmark, Southern Denmark, Denmark
| | - Mitchell M. Conover
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
| | - Seng Chan You
- Department of Preventive Medicine and Public Health, Yonsei University College of Medicine, Seoul, South Korea
| | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | - James Weaver
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
| | - Anthony G. Sena
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Martijn J. Schuemie
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jenna Reps
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
| | | | - Peter R. Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Patrick B. Ryan
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, United States
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford University, Oxford, United Kingdom
- *Correspondence: Daniel Prieto-Alhambra,
| | - Marc A. Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, United States
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Nishimura A, Kawahara M, Kawachi Y, Hasegawa J, Makino S, Kitami C, Nakano T, Otani T, Nemoto M, Hattori S, Nikkuni K. Totally laparoscopic resection of right-sided colon cancer using transvaginal specimen extraction with a 10-mm-long abdominal incision. Tech Coloproctol 2022; 26:755-760. [DOI: 10.1007/s10151-022-02636-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/01/2022] [Indexed: 11/24/2022]
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12
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Wang Z, Bowring MG, Rosen A, Garibaldi B, Zeger S, Nishimura A. Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring. Stat Sci 2022; 37:251-265. [DOI: 10.1214/22-sts861] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Zitong Wang
- Zitong Wang is a PhD student, Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Mary Grace Bowring
- Mary Grace Bowring is an MD/PhD student, Departments of Biomedical Engineering and Biostatistics, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Antony Rosen
- Antony Rosen is Mary Betty Stevens Professor of Medicine and Vice Dean for Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Brian Garibaldi
- Brian Garibaldi is Associate Professor, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Scott Zeger
- Scott L. Zeger (co-senior author) is John C. Malone Professor, Department of Biostatistics and Medicine, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Akihiko Nishimura
- Akihiko (Aki) Nishimura (co-senior author) is Assistant Professor, Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
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13
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Nishimura A, Suchard MA. Prior-preconditioned conjugate gradient method for accelerated Gibbs sampling in ‘large n & large p’ Bayesian sparse regression. J Am Stat Assoc 2022. [DOI: 10.1080/01621459.2022.2057859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
| | - Marc A. Suchard
- Department of Biomathematics, Biostatistics, and Human Genetics, University of California - Los Angeles
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14
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Togao O, Obara M, Kikuchi K, Helle M, Arimura K, Nishimura A, Wada T, Murazaki H, Van Cauteren M, Hiwatashi A, Ishigami K. Vessel-Selective 4D-MRA Using Superselective Pseudocontinuous Arterial Spin-Labeling with Keyhole and View-Sharing for Visualizing Intracranial Dural AVFs. AJNR Am J Neuroradiol 2022; 43:368-375. [PMID: 35241425 PMCID: PMC8910818 DOI: 10.3174/ajnr.a7426] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/11/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE An accurate assessment of the hemodynamics of an intracranial dural AVF is necessary for treatment planning. We aimed to investigate the utility of 4D-MRA based on superselective pseudocontinuous arterial spin-labeling with CENTRA-keyhole and view-sharing (4D-S-PACK) for the vessel-selective visualization of intracranial dural AVFs. MATERIALS AND METHODS We retrospectively analyzed the images of 21 patients (12 men and 9 women; mean age, 62.2 [SD,19.2] years) with intracranial dural AVFs, each of whom was imaged with DSA, 4D-S-PACK, and nonselective 4D-MRA based on pseudocontinuous arterial spin-labeling combined with CENTRA-keyhole and view-sharing (4D-PACK). The shunt location, venous drainage patterns, feeding artery identification, and Borden classification were evaluated by 2 observers using both MRA methods on separate occasions. Vessel selectivity was evaluated on 4D-S-PACK. RESULTS Shunt locations were correctly evaluated in all 21 patients by both observers on both MRA methods. With 4D-S-PACK, observers 1 and 2 detected 76 (80.0%, P < .001) and 73 (76.8%, P < .001) feeding arteries of the 95 feeding arteries identified on DSA but only 39 (41.1%) and 46 (48.4%) feeding arteries with nonselective 4D-PACK, respectively. Both observers correctly identified 10 of the 11 patients with cortical venous reflux confirmed by DSA with both 4D-S-PACK and 4D-PACK (sensitivity = 90.9%, specificity = 90.9% for each method), and they made accurate Borden classifications in 20 of the 21 patients (95.2%) on both MRA methods. Of the 84 vessel territories examined, vessel selectivity was graded 3 or 4 in 73 (91.2%) and 66 (88.0%) territories by observers 1 and 2, respectively. CONCLUSIONS 4D-S-PACK is useful for the identification of feeding arteries and accurate classifications of intracranial dural AVFs and can be a useful noninvasive clinical tool.
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Affiliation(s)
- O. Togao
- From the Departments of Molecular Imaging & Diagnosis (O.T.)
| | - M. Obara
- Philips Japan (M.O., M.V.C.), Tokyo, Japan
| | | | - M. Helle
- Philips Research (M.H.), Hamburg, Germany
| | - K. Arimura
- Neurosurgery (K.A., A.N.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - A. Nishimura
- Neurosurgery (K.A., A.N.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - T. Wada
- Division of Radiology (T.W., H.M.), Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan
| | - H. Murazaki
- Division of Radiology (T.W., H.M.), Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan
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15
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Koenecke A, Powell M, Xiong R, Shen Z, Fischer N, Huq S, Khalafallah AM, Trevisan M, Sparen P, Carrero JJ, Nishimura A, Caffo B, Stuart EA, Bai R, Staedtke V, Thomas DL, Papadopoulos N, Kinzler KW, Vogelstein B, Zhou S, Bettegowda C, Konig MF, Mensh B, Vogelstein JT, Athey S. Alpha-1 adrenergic receptor antagonists to prevent hyperinflammation and death from lower respiratory tract infection. ArXiv 2021:arXiv:2004.10117v8. [PMID: 32550250 PMCID: PMC7280904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Revised: 08/02/2021] [Indexed: 06/11/2023]
Abstract
In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation, which can lead to acute respiratory distress syndrome, multi-organ failure, and death. We previously demonstrated that alpha-1 adrenergic receptor ($\alpha_1$-AR) antagonists can prevent hyperinflammation and death in mice. Here, we conducted retrospective analyses in two cohorts of patients with acute respiratory distress (ARD, n=18,547) and three cohorts with pneumonia (n=400,907). Federated across two ARD cohorts, we find that patients exposed to $\alpha_1$-AR antagonists, as compared to unexposed patients, had a 34% relative risk reduction for mechanical ventilation and death (OR=0.70, p=0.021). We replicated these methods on three pneumonia cohorts, all with similar effects on both outcomes. All results were robust to sensitivity analyses. These results highlight the urgent need for prospective trials testing whether prophylactic use of $\alpha_1$-AR antagonists ameliorates lower respiratory tract infection-associated hyperinflammation and death, as observed in COVID-19.
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16
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Powell M, Koenecke A, Byrd JB, Nishimura A, Konig MF, Xiong R, Mahmood S, Mucaj V, Bettegowda C, Rose L, Tamang S, Sacarny A, Caffo B, Athey S, Stuart EA, Vogelstein JT. Ten Rules for Conducting Retrospective Pharmacoepidemiological Analyses: Example COVID-19 Study. Front Pharmacol 2021; 12:700776. [PMID: 34393782 PMCID: PMC8357144 DOI: 10.3389/fphar.2021.700776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 06/30/2021] [Indexed: 11/13/2022] Open
Abstract
Since the beginning of the COVID-19 pandemic, pharmaceutical treatment hypotheses have abounded, each requiring careful evaluation. A randomized controlled trial generally provides the most credible evaluation of a treatment, but the efficiency and effectiveness of the trial depend on the existing evidence supporting the treatment. The researcher must therefore compile a body of evidence justifying the use of time and resources to further investigate a treatment hypothesis in a trial. An observational study can provide this evidence, but the lack of randomized exposure and the researcher's inability to control treatment administration and data collection introduce significant challenges. A proper analysis of observational health care data thus requires contributions from experts in a diverse set of topics ranging from epidemiology and causal analysis to relevant medical specialties and data sources. Here we summarize these contributions as 10 rules that serve as an end-to-end introduction to retrospective pharmacoepidemiological analyses of observational health care data using a running example of a hypothetical COVID-19 study. A detailed supplement presents a practical how-to guide for following each rule. When carefully designed and properly executed, a retrospective pharmacoepidemiological analysis framed around these rules will inform the decisions of whether and how to investigate a treatment hypothesis in a randomized controlled trial. This work has important implications for any future pandemic by prescribing what we can and should do while the world waits for global vaccine distribution.
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Affiliation(s)
- Michael Powell
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, United States
| | - Allison Koenecke
- Institute for Computational & Mathematical Engineering, Stanford University, Stanford, CA, United States
| | - James Brian Byrd
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Akihiko Nishimura
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins University, Baltimore, MD, United States
| | - Maximilian F Konig
- Ludwig Center, Lustgarten Laboratory, Howard Hughes Medical Institute, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Division of Rheumatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Ruoxuan Xiong
- Graduate School of Business, Stanford University, Stanford, CA, United States
| | | | - Vera Mucaj
- Datavant Inc., San Francisco, CA, United States
| | - Chetan Bettegowda
- Ludwig Center, Lustgarten Laboratory, Howard Hughes Medical Institute, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Liam Rose
- VA Health Economics Resource Center, Palo Alto VA, Menlo Park, CA, United States
| | - Suzanne Tamang
- Department of Biomedical Data Science, Stanford University, Stanford, CA, United States
| | - Adam Sacarny
- Department of Health Policy and Management, Columbia University Mailman School of Public Health, New York, NY, United States
| | - Brian Caffo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins University, Baltimore, MD, United States
| | - Susan Athey
- Graduate School of Business, Stanford University, Stanford, CA, United States
| | - Elizabeth A Stuart
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins University, Baltimore, MD, United States
| | - Joshua T Vogelstein
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, United States.,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins University, Baltimore, MD, United States
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17
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Nishimura A, Xie J, Kostka K, Duarte-Salles T, Bertolín SF, Aragón M, Blacketer C, Shoaibi A, DuVall SL, Lynch K, Matheny ME, Falconer T, Morales DR, Conover MM, You SC, Pratt N, Weaver J, Sena AG, Schuemie MJ, Reps J, Reich C, Rijnbeek PR, Ryan PB, Hripcsak G, Prieto-Alhambra D, Suchard MA. Alpha-1 blockers and susceptibility to COVID-19 in benign prostate hyperplasia patients : an international cohort study. medRxiv 2021:2021.03.18.21253778. [PMID: 33791740 PMCID: PMC8010772 DOI: 10.1101/2021.03.18.21253778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Alpha-1 blockers, often used to treat benign prostate hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storms release. We conducted a prevalent-user active-comparator cohort study to assess association between alpha-1 blocker use and risks of three COVID-19 outcomes: diagnosis, hospitalization, and hospitalization requiring intensive services. Our study included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH therapy during the period between November 2019 and January 2020, found in electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We found no differential risk for any of COVID-19 outcome, pointing to the need for further research on potential COVID-19 therapies.
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Affiliation(s)
| | - Junqing Xie
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford University, Oxford, UK
| | - Kristin Kostka
- Real World Solutions, IQVIA, Cambridge, MA, USA
- The OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, USA
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Sergio Fernández Bertolín
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - María Aragón
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Clair Blacketer
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Azza Shoaibi
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Kristine Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Michael E Matheny
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, UK
- Department of Public Health, University of Southern Denmark, Denmark
| | - Mitchell M Conover
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Seng Chan You
- Department of Preventive Medicine and Public Health, Yonsei University College of Medicine, Seoul, Korea
| | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | - James Weaver
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Anthony G Sena
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Martijn J Schuemie
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jenna Reps
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | | | - Peter R Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Patrick B Ryan
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford University, Oxford, UK
| | - Marc A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA
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18
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Zhang Z, Nishimura A, Bastide P, Ji X, Payne RP, Goulder P, Lemey P, Suchard MA. Large-scale inference of correlation among mixed-type biological traits with phylogenetic multivariate probit models. Ann Appl Stat 2021. [DOI: 10.1214/20-aoas1394] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Zhenyu Zhang
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University
| | | | - Xiang Ji
- Department of Mathematics, School of Science & Engineering, Tulane University
| | - Rebecca P. Payne
- Translational and Clinical Research Institute, Newcastle University
| | - Philip Goulder
- Department of Paediatrics, University of Oxford, HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Ragon Institute of MGH, MIT and Harvard University
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven
| | - Marc A. Suchard
- Departments of Biomathematics, Biostatistics and Human Genetics, University of California, Los Angeles
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19
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Koenecke A, Powell M, Xiong R, Shen Z, Fischer N, Huq S, Khalafallah AM, Trevisan M, Sparen P, Carrero JJ, Nishimura A, Caffo B, Stuart EA, Bai R, Staedtke V, Thomas DL, Papadopoulos N, Kinzler KW, Vogelstein B, Zhou S, Bettegowda C, Konig MF, Mensh BD, Vogelstein JT, Athey S. Alpha-1 adrenergic receptor antagonists to prevent hyperinflammation and death from lower respiratory tract infection. eLife 2021; 10:61700. [PMID: 34114951 PMCID: PMC8195605 DOI: 10.7554/elife.61700] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 05/11/2021] [Indexed: 01/16/2023] Open
Abstract
In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation, which can lead to acute respiratory distress syndrome, multi-organ failure, and death. We previously demonstrated that alpha-1 adrenergic receptor (⍺1-AR) antagonists can prevent hyperinflammation and death in mice. Here, we conducted retrospective analyses in two cohorts of patients with acute respiratory distress (ARD, n = 18,547) and three cohorts with pneumonia (n = 400,907). Federated across two ARD cohorts, we find that patients exposed to ⍺1-AR antagonists, as compared to unexposed patients, had a 34% relative risk reduction for mechanical ventilation and death (OR = 0.70, p = 0.021). We replicated these methods on three pneumonia cohorts, all with similar effects on both outcomes. All results were robust to sensitivity analyses. These results highlight the urgent need for prospective trials testing whether prophylactic use of ⍺1-AR antagonists ameliorates lower respiratory tract infection-associated hyperinflammation and death, as observed in COVID-19.
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Affiliation(s)
- Allison Koenecke
- Institute for Computational & Mathematical Engineering, Stanford UniversityStanfordUnited States
| | - Michael Powell
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins UniversityBaltimoreUnited States
| | - Ruoxuan Xiong
- Management Science & Engineering, Stanford UniversityStanfordUnited States
| | - Zhu Shen
- Department of Statistics, Stanford UniversityStanfordUnited States
| | - Nicole Fischer
- The Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Sakibul Huq
- Department of Neurosurgery and Neurology, The Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Adham M Khalafallah
- Department of Neurosurgery and Neurology, The Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Marco Trevisan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SwedenSolnaSweden
| | - Pär Sparen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SwedenSolnaSweden
| | - Juan J Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SwedenSolnaSweden
| | - Akihiko Nishimura
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins UniversityBaltimoreUnited States
| | - Brian Caffo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins UniversityBaltimoreUnited States
| | - Elizabeth A Stuart
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins UniversityBaltimoreUnited States
| | - Renyuan Bai
- Department of Neurosurgery and Neurology, The Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Verena Staedtke
- Department of Neurosurgery and Neurology, The Johns Hopkins University School of MedicineBaltimoreUnited States
| | - David L Thomas
- The Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Nickolas Papadopoulos
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer CenterBaltimoreUnited States
| | - Ken W Kinzler
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer CenterBaltimoreUnited States
| | - Bert Vogelstein
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer CenterBaltimoreUnited States
| | - Shibin Zhou
- Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer CenterBaltimoreUnited States
| | - Chetan Bettegowda
- The Johns Hopkins University School of MedicineBaltimoreUnited States,Ludwig Center, Lustgarten Laboratory, and the Howard Hughes Medical Institute at The Johns Hopkins Kimmel Cancer CenterBaltimoreUnited States
| | - Maximilian F Konig
- Division of Rheumatology, Department of Medicine, The Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Brett D Mensh
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Joshua T Vogelstein
- Department of Biomedical Engineering, Institute for Computational Medicine, The Johns Hopkins UniversityBaltimoreUnited States,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health at Johns Hopkins UniversityBaltimoreUnited States
| | - Susan Athey
- Stanford Graduate School of Business, Stanford UniversityStanfordUnited States
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20
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Harada M, Nomura Y, Nishimura A, Motoike Y, Koshikawa M, Watanabe E, Izawa H, Ozaki Y. Factors associated with silent cerebral events during catheter ablation for atrial fibrillation in the era of uninterrupted oral anticoagulation therapy. Eur Heart J 2020. [DOI: 10.1093/ehjci/ehaa946.0577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
A silent cerebral event (SCE), detected by brain magnetic resonance imaging (MRI), is defined as an acute new brain lesion without clinically apparent neurological deficit, and is frequently observed after catheter ablation in atrial fibrillation (AF) patients. Although the small number of SCEs does not cause neurocognitive dysfunction, the greater volume and/or larger number of SCE lesions are reportedly related to neuropsychological decline; SCE incidence may be a surrogate marker for the potential thromboembolic risk. Thus, strategies to reduce SCEs would be beneficial. Uninterrupted oral anticoagulation strategy for peri-procedural period reportedly reduced the risk of SCEs, but the incidence hovers at 10% to 30%. We sought factors associated with SCEs during catheter ablation for AF in patients with peri-procedural uninterrupted oral anticoagulation (OAC) therapy.
Methods
AF patients undergoing catheter ablation were eligible (n=255). All patients took non-vitamin K antagonist oral anticoagulants (NOACs) or vitamin K antagonist (VKA) for peri-procedural OAC (>4 weeks) without interruption during the procedure. Brain MRI was performed within 2 days after the procedure to detect SCEs. Clinical characteristics and procedure-related parameters were compared between patients with and without SCEs.
Results
SCEs were detected in 59 patients (23%, SCE[+]) but not in 196 patients (77%, SCE[-]). Average age was higher in SCE[+] than SCE[-] (66±10 years vs. 62±12 years, p<0.05). Persistent AF prevalence, CHADS2/CHA2DS2-VASc scores, and serum NT-ProBNP levels increased in SCE[+] vs. SCE[-]. In transthoracic/transesophageal echocardiography, left-atrial dimension (LAD) was larger and AF rhythm/spontaneous echo contrast were more frequently observed in SCE[+] than SCE[-]. SCE[+] had lower initial activated clotting time (ACT) before unfractionated heparin (UFH) injection and longer time to reach optimal ACT (>300 sec) before trans-septal puncture than SCE [-]. In multivariate analysis, LAD, initial ACT before UFH injection, and time to reach optimal ACT were predictors for SCEs.
Conclusions
LAD and intra-procedural ACT kinetics affect SCEs during the procedure in patients with uninterrupted OAC for AF ablation. Shortening time to achieve optimal ACT during the procedure may reduce the risk of SCEs.
Funding Acknowledgement
Type of funding source: None
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Affiliation(s)
- M Harada
- Fujita Health University, Toyoake, Japan
| | - Y Nomura
- Fujita Health University, Toyoake, Japan
| | | | - Y Motoike
- Fujita Health University, Toyoake, Japan
| | | | - E Watanabe
- Fujita Health University, Toyoake, Japan
| | - H Izawa
- Fujita Health University, Toyoake, Japan
| | - Y Ozaki
- Fujita Health University, Toyoake, Japan
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21
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Ji X, Zhang Z, Holbrook A, Nishimura A, Baele G, Rambaut A, Lemey P, Suchard MA. Gradients Do Grow on Trees: A Linear-Time O(N)-Dimensional Gradient for Statistical Phylogenetics. Mol Biol Evol 2020; 37:3047-3060. [PMID: 32458974 PMCID: PMC7530611 DOI: 10.1093/molbev/msaa130] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Calculation of the log-likelihood stands as the computational bottleneck for many statistical phylogenetic algorithms. Even worse is its gradient evaluation, often used to target regions of high probability. Order O(N)-dimensional gradient calculations based on the standard pruning algorithm require O(N2) operations, where N is the number of sampled molecular sequences. With the advent of high-throughput sequencing, recent phylogenetic studies have analyzed hundreds to thousands of sequences, with an apparent trend toward even larger data sets as a result of advancing technology. Such large-scale analyses challenge phylogenetic reconstruction by requiring inference on larger sets of process parameters to model the increasing data heterogeneity. To make these analyses tractable, we present a linear-time algorithm for O(N)-dimensional gradient evaluation and apply it to general continuous-time Markov processes of sequence substitution on a phylogenetic tree without a need to assume either stationarity or reversibility. We apply this approach to learn the branch-specific evolutionary rates of three pathogenic viruses: West Nile virus, Dengue virus, and Lassa virus. Our proposed algorithm significantly improves inference efficiency with a 126- to 234-fold increase in maximum-likelihood optimization and a 16- to 33-fold computational performance increase in a Bayesian framework.
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Affiliation(s)
- Xiang Ji
- Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, LA
| | - Zhenyu Zhang
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA
| | - Andrew Holbrook
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Andrew Rambaut
- Institute of Evolutionary Biology, Centre for Immunology, Infection and Evolution, University of Edinburgh, Edinburgh, United Kingdom
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
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22
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Abstract
Summary
Hamiltonian Monte Carlo has emerged as a standard tool for posterior computation. In this article we present an extension that can efficiently explore target distributions with discontinuous densities. Our extension in particular enables efficient sampling from ordinal parameters through the embedding of probability mass functions into continuous spaces. We motivate our approach through a theory of discontinuous Hamiltonian dynamics and develop a corresponding numerical solver. The proposed solver is the first of its kind, with a remarkable ability to exactly preserve the Hamiltonian. We apply our algorithm to challenging posterior inference problems to demonstrate its wide applicability and competitive performance.
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Affiliation(s)
- Akihiko Nishimura
- Department of Biomathematics, University of California - Los Angeles, 695 Charles E. Young Dr. S., Los Angeles, California 90095, USA
| | - David B Dunson
- Department of Statistical Science, Duke University, Box 90251, Durham, North Carolina 27708, USA
| | - Jianfeng Lu
- Department of Mathematics, Duke University, Box 90320, Durham, North Carolina 27708, USA
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23
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Dóka É, Ida T, Dagnell M, Abiko Y, Luong NC, Balog N, Takata T, Espinosa B, Nishimura A, Cheng Q, Funato Y, Miki H, Fukuto JM, Prigge JR, Schmidt EE, Arnér ESJ, Kumagai Y, Akaike T, Nagy P. Control of protein function through oxidation and reduction of persulfidated states. Sci Adv 2020; 6:eaax8358. [PMID: 31911946 PMCID: PMC6938701 DOI: 10.1126/sciadv.aax8358] [Citation(s) in RCA: 102] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 11/05/2019] [Indexed: 05/17/2023]
Abstract
Irreversible oxidation of Cys residues to sulfinic/sulfonic forms typically impairs protein function. We found that persulfidation (CysSSH) protects Cys from irreversible oxidative loss of function by the formation of CysSSO1-3H derivatives that can subsequently be reduced back to native thiols. Reductive reactivation of oxidized persulfides by the thioredoxin system was demonstrated in albumin, Prx2, and PTP1B. In cells, this mechanism protects and regulates key proteins of signaling pathways, including Prx2, PTEN, PTP1B, HSP90, and KEAP1. Using quantitative mass spectrometry, we show that (i) CysSSH and CysSSO3H species are abundant in mouse liver and enzymatically regulated by the glutathione and thioredoxin systems and (ii) deletion of the thioredoxin-related protein TRP14 in mice altered CysSSH levels on a subset of proteins, predicting a role for TRP14 in persulfide signaling. Furthermore, selenium supplementation, polysulfide treatment, or knockdown of TRP14 mediated cellular responses to EGF, suggesting a role for TrxR1/TRP14-regulated oxidative persulfidation in growth factor responsiveness.
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Affiliation(s)
- É. Dóka
- Department of Molecular Immunology and Toxicology, National Institute of Oncology, 1122 Budapest, Hungary
| | - T. Ida
- Department of Environmental Medicine and Molecular Toxicology, Tohoku University Graduate School of Medicine, 980-8575 Sendai, Japan
| | - M. Dagnell
- Department of Medical Biochemistry and Biophysics, Division of Biochemistry, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Y. Abiko
- Environmental Biology Section, Faculty of Medicine, University of Tsukuba, 305-8575 Tsukuba, Japan
| | - N. C. Luong
- Environmental Biology Section, Faculty of Medicine, University of Tsukuba, 305-8575 Tsukuba, Japan
- Faculty of Pharmacy, Hue University of Medicine and Pharmacy, Hue University, 06 Ngo Quyen, Hue, Vietnam
| | - N. Balog
- Department of Molecular Immunology and Toxicology, National Institute of Oncology, 1122 Budapest, Hungary
| | - T. Takata
- Department of Environmental Medicine and Molecular Toxicology, Tohoku University Graduate School of Medicine, 980-8575 Sendai, Japan
| | - B. Espinosa
- Department of Medical Biochemistry and Biophysics, Division of Biochemistry, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - A. Nishimura
- Department of Environmental Medicine and Molecular Toxicology, Tohoku University Graduate School of Medicine, 980-8575 Sendai, Japan
| | - Q. Cheng
- Department of Medical Biochemistry and Biophysics, Division of Biochemistry, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Y. Funato
- Department of Cellular Regulation, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan
| | - H. Miki
- Department of Cellular Regulation, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan
| | - J. M. Fukuto
- Department of Chemistry, Sonoma State University, Rohnert Park, Sonoma, CA 94928, USA
| | - J. R. Prigge
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA
| | - E. E. Schmidt
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA
| | - E. S. J. Arnér
- Department of Medical Biochemistry and Biophysics, Division of Biochemistry, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Y. Kumagai
- Environmental Biology Section, Faculty of Medicine, University of Tsukuba, 305-8575 Tsukuba, Japan
| | - T. Akaike
- Department of Environmental Medicine and Molecular Toxicology, Tohoku University Graduate School of Medicine, 980-8575 Sendai, Japan
| | - P. Nagy
- Department of Molecular Immunology and Toxicology, National Institute of Oncology, 1122 Budapest, Hungary
- Corresponding author.
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24
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Saito Y, Shiraishi K, Nishimura A, Kirinaka T, Sakurai Y, Tomida T. Fluorescence Database of Aerosol-Candidate-Substances for Fluorescence Lidar Application. EPJ Web Conf 2020. [DOI: 10.1051/epjconf/202023707016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
A database containing spectrum and cross-section of the fluorescence of substances has been made. In test of forest environment monitoring by our Laser-Induced Fluorescence Spectrum (LIFS) lidar, the database showed that the origin substance of the aerosol observed by the lidar was cedar pollen, and the concentration was calculated using the cross-section. In the urban atmosphere monitoring, three substances stored in the database were proposed to be the origins of the aerosol. Based on these experiments, we discuss the usefulness of the fluorescence database in lidar observations.
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25
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Harada M, Motoike Y, Nomura Y, Nishimura A, Nagasaka R, Koshikawa M, Ichikawa T, Watanabe E, Ozaki Y. P1901Use of direct thrombin inhibitor on the day of atrial fibrillation ablation decreases incidence of silent cerebral ischemia detected by magnetic resonance imaging. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz748.0648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
There is increasing evidence to use direct oral anticoagulants (DOACs) in atrial fibrillation (AF) ablation. Uninterrupted use of DOACs is recommended for peri-procedural anticoagulation; the ways of choosing and/or using DOACs depend on physicians' decisions and preferences. Uninterrupted dabigatran (DAB), a direct thrombin inhibitor, reportedly decreased the risk of major bleeding (MB) in AF ablation, compared to uninterrupted warfarin (NEJM 2017; 376:1627). Among DOACs, only regular-dose of DAB (150 mg b.i.d.), showed superiority to warfarin for preventing ischemic thromboembolism (TE) in patients with non-valvular AF, implicating the powerful anti-thrombotic agent. DAB may decrease the potential risk of procedure-related TE.
Purpose
To evaluate whether use of DAB on the day of AF ablation decreases the prevalence of silent cerebral ischemia (SCI) detected by magnetic resonance imaging (MRI).
Methods
414 AF patients on DOACs were enrolled and admitted on the day before AF ablation. Among 354 patients on factor Xa inhibitors (rivaroxaban, apixaban, and edoxaban), the original DOACs were switched to DAB (150 mg b.i.d.) on the day of the procedure in 172 patients (Group D); the treatment remained unchanged in 182 patients (Group non-D). In both groups, DOACs were continuously used throughout the procedure. After propensity-score matching, procedure-related parameters/events and the incidence of MRI-detected SCI were compared between Group D (n=134) and Group non-D (n=134). These parameters in patients originally taking DAB, used without interruption during the procedure (uninterrupted DAB, n=55), were also compared to Group D (n=55) after propensity-score matching.
Results
Baseline activated clotting time (ACT) before initial heparin injection was increased in Group D vs. Group-non-D (179±25* vs. 146±23 sec, *p<0.05 vs. Group non-D). The time to achieve optimal ACT (>300 sec) was shorter in Group D (34±29* vs. 43±32 min). The amounts of heparin needed to achieve optimal ACT and the total amount of heparin used during the procedure were unchanged between Group D and Group non-D. The incidence of SCI decreased in Group D (13.1%* vs. 21.9%), suggesting the potential anti-thrombotic efficacy of DAB. No MB or symptomatic TE events were observed in either group. Baseline ACT, the time to achieve ACT >300 sec, and the incidence of SCI in Group D were comparable to those in uninterrupted DAB (183±38 vs. 181±32 sec, 39±31 vs. 42±28 min, and 14.5% vs. 16.4%, respectively). No MB or symptomatic TE events were observed either in Group D or uninterrupted DAB.
Conclusions
Temporarily switching to DAB from the other DOACs and using it on the day of procedure enable us to achieve optimal ACT quickly and decrease the incidence of SCI, showing similar potential anti-thrombotic efficacy to uninterrupted DAB. Use of DAB on the day of AF ablation also benefits from the availability of its antidote in the case of MB during the procedure.
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Affiliation(s)
- M Harada
- Fujita Health University, Toyoake, Japan
| | - Y Motoike
- Fujita Health University, Toyoake, Japan
| | - Y Nomura
- Fujita Health University, Toyoake, Japan
| | | | - R Nagasaka
- Fujita Health University, Toyoake, Japan
| | | | - T Ichikawa
- Fujita Health University, Toyoake, Japan
| | - E Watanabe
- Fujita Health University, Toyoake, Japan
| | - Y Ozaki
- Fujita Health University, Toyoake, Japan
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26
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Mizuguchi Y, Maruta M, Moriyama S, Yamashita N, Okada C, Nishimura A, Fujiwara Y, Tahakashi A. P5434Evaluation of the determinant factors on the capacity for self-care in patients with acute myocardial infarction. Eur Heart J 2018. [DOI: 10.1093/eurheartj/ehy566.p5434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
| | - M Maruta
- Sakurakai Takahashi Hospital, Kobe, Japan
| | - S Moriyama
- Sakurakai Takahashi Hospital, Kobe, Japan
| | | | - C Okada
- Sakurakai Takahashi Hospital, Kobe, Japan
| | | | - Y Fujiwara
- Sakurakai Takahashi Hospital, Kobe, Japan
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27
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Miwa H, Uedo N, Watari J, Mori Y, Sakurai Y, Takanami Y, Nishimura A, Tatsumi T, Sakaki N. Randomised clinical trial: efficacy and safety of vonoprazan vs. lansoprazole in patients with gastric or duodenal ulcers - results from two phase 3, non-inferiority randomised controlled trials. Aliment Pharmacol Ther 2017; 45:240-252. [PMID: 27891632 PMCID: PMC6680291 DOI: 10.1111/apt.13876] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Revised: 06/14/2016] [Accepted: 11/03/2016] [Indexed: 12/11/2022]
Abstract
BACKGROUND Vonoprazan is a new potassium-competitive acid blocker for treatment of acid-related diseases. AIM To conduct two randomised-controlled trials, to evaluate the non-inferiority of vonoprazan vs. lansoprazole, a proton pump inhibitor, for treatment of gastric ulcer (GU) or duodenal ulcer (DU). METHODS Patients aged ≥20 years with ≥1 endoscopically-confirmed GU or DU (≥5 mm white coating) were randomised 1:1 using double-dummy blinding to receive lansoprazole (30 mg) or vonoprazan (20 mg) for 8 (GU study) or 6 (DU study) weeks. The primary endpoint was the proportion of patients with endoscopically confirmed healed GU or DU. RESULTS For GU, 93.5% (216/231) of vonoprazan-treated patients and 93.8% (211/225) of lansoprazole-treated patients achieved healed GU; non-inferiority of vonoprazan to lansoprazole was confirmed [difference = -0.3% (95% CI -4.750, 4.208); P = 0.0011]. For DU, 95.5% (170/178) of vonoprazan-treated patients and 98.3% (177/180) of lansoprazole-treated patients achieved healed DU; non-inferiority to lansoprazole was not confirmed [difference = -2.8% (95% CI -6.400, 0.745); P = 0.0654]. The incidences of treatment-emergent adverse events were slightly lower for GU and slightly higher for DU with vonoprazan than with lansoprazole. There was one death (subarachnoid haemorrhage) in the vonoprazan group (DU). The possibility of a relationship between this unexpected patient death and the study drug could not be ruled out. In both studies, increases in serum gastrin levels were greater in vonoprazan-treated vs. lansoprazole-treated patients; levels returned to baseline after treatment in both groups. CONCLUSIONS Vonoprazan 20 mg has a similar tolerability profile to lansoprazole 30 mg and is non-inferior with respect to GU healing and has similar efficacy for DU healing.
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Affiliation(s)
- H. Miwa
- Hyogo College of MedicineHyogoJapan
| | - N. Uedo
- Osaka Medical Center for Cancer and Cardiovascular DiseasesOsakaJapan
| | | | - Y. Mori
- Takeda Pharmaceutical Company LtdOsakaJapan
| | - Y. Sakurai
- Takeda Pharmaceutical Company LtdOsakaJapan
| | | | | | - T. Tatsumi
- Osaka University Graduate School of MedicineOsakaJapan
| | - N. Sakaki
- Foundation for Detection of Early Gastric CarcinomaTokyoJapan
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28
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Asanuma K, Yoshikawa T, Yoshida K, Okamoto T, Asanuma Y, Hayashi T, Akita N, Oi T, Nishimura A, Hasegawa M, Sudo A. Argatroban more effectively inhibits the thrombin activity in synovial fluid than naturally occurring thrombin inhibitors. Cell Mol Biol (Noisy-le-grand) 2016; 62:27-32. [PMID: 27262798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 05/03/2016] [Indexed: 06/05/2023]
Abstract
The purpose of this study was to clarify the precise effect of argatroban on the inhibition of cytokine secretion induced by thrombin on synovial cells. The efficiency of thrombin inactivation by thrombin inhibitors was evaluated in human synovial fluids (SFs). In SFs from 13 osteoarthritis (OA) and 11 rheumatoid arthritis (RA) patients, thrombin, Factor Xa (FXa), plasmin activity, IL-6, MMP-3, VEGF, and D-dimer concentrations were measured. Tissue factor (TF) activity or IL-6, MMP-3, and VEGF secretion of human synovial cells with or without thrombin and argatroban were measured. The efficiency of thrombin inactivation in SFs was compared for thrombin inhibitors: argatroban, antithrombin III (ATIII), or heparin cofactor II (HCII). In SFs, thrombin, FXa, plasmin, D-dimer, IL-6, and MMP-3 were significantly higher in RA than in OA. In synovial cell experiments, TNF-alpha and thrombin enhanced TF activity on the cell surface, and IL-6, MMP-3, and VEGF secretion were enhanced by thrombin. Increased TF activity, and IL-6, MMP-3, and VEGF secretion induced by thrombin were inhibited by argatroban. In SFs, argatroban inactivated thrombin more effectively than ATIII or HCII. Since thrombin plays an important role in the disease activity of OA and RA, it is a potential therapeutic molecular target. Argatroban was the most effective anticoagulant to inhibit thrombin activity in SF. Intra-articular injection is ideal administration because it can deliver high dose of argatroban without high risk of systematic complication.
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Affiliation(s)
- K Asanuma
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
| | - T Yoshikawa
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
| | - K Yoshida
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
| | - T Okamoto
- Mie University School of Medicine Department of Molecular Pathobiology Tsu City, Mie Japan
| | - Y Asanuma
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
| | - T Hayashi
- Mie Prefecture Collage of Nursing Department of Biochemistry Tsu City, Mie Japan
| | - N Akita
- Suzuka University of Medical Science Department of Medical Engineering Suzuka City, Mie Japan
| | - T Oi
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
| | - A Nishimura
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
| | - M Hasegawa
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
| | - A Sudo
- Mie University School of Medicine Department of Orthopedic Surgery Tsu City, Mie Japan
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29
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Ashida K, Sakurai Y, Hori T, Kudou K, Nishimura A, Hiramatsu N, Umegaki E, Iwakiri K. Randomised clinical trial: vonoprazan, a novel potassium-competitive acid blocker, vs. lansoprazole for the healing of erosive oesophagitis. Aliment Pharmacol Ther 2016; 43:240-51. [PMID: 26559637 PMCID: PMC4738414 DOI: 10.1111/apt.13461] [Citation(s) in RCA: 160] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2015] [Revised: 08/06/2015] [Accepted: 10/16/2015] [Indexed: 12/11/2022]
Abstract
BACKGROUND Vonoprazan is a novel potassium-competitive acid blocker which may provide clinical benefit in acid-related disorders. AIM To verify the non-inferiority of vonoprazan vs. lansoprazole in patients with erosive oesophagitis (EE), and to establish its long-term safety and efficacy as maintenance therapy. METHODS In this multicentre, randomised, double-blind, parallel-group comparison study, patients with endoscopically confirmed EE (LA Classification Grades A-D) were randomly allocated to receive vonoprazan 20 mg or lansoprazole 30 mg once daily after breakfast. The primary endpoint was the proportion of patients with healed EE confirmed by endoscopy up to week 8. In addition, subjects who achieved healed EE in the comparison study were re-randomised into a long-term study to investigate the safety and efficacy of vonoprazan 10 or 20 mg as maintenance therapy for 52 weeks. RESULTS Of the 409 eligible subjects randomised, 401 completed the comparison study, and 305 entered the long-term maintenance study. The proportion of patients with healed EE up to week 8 was 99.0% for vonoprazan (203/205) and 95.5% for lansoprazole (190/199), thus verifying the non-inferiority of vonoprazan (P < 0.0001). Vonoprazan was also effective in patients with more severe EE (LA Classification Grades C/D) and CYP2C19 extensive metabolisers. In the long-term maintenance study, there were few recurrences (<10%) of EE in patients treated with vonoprazan 10 or 20 mg. Overall, vonoprazan was well-tolerated. CONCLUSIONS The non-inferiority of vonoprazan to lansoprazole in EE was verified in the comparison study, and vonoprazan was well-tolerated and effective during the long-term maintenance study.
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Affiliation(s)
| | - Y. Sakurai
- Takeda Pharmaceutical Company Ltd.OsakaJapan
| | - T. Hori
- Takeda Pharmaceutical Company Ltd.OsakaJapan
| | - K. Kudou
- Takeda Pharmaceutical Company Ltd.OsakaJapan
| | | | - N. Hiramatsu
- Osaka University Graduate School of MedicineOsakaJapan
| | - E. Umegaki
- Kobe University Graduate School of MedicineKobeJapan
| | - K. Iwakiri
- Nippon Medical School Graduate School of MedicineTokyoJapan
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30
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Ashida K, Sakurai Y, Nishimura A, Kudou K, Hiramatsu N, Umegaki E, Iwakiri K, Chiba T. Randomised clinical trial: a dose-ranging study of vonoprazan, a novel potassium-competitive acid blocker, vs. lansoprazole for the treatment of erosive oesophagitis. Aliment Pharmacol Ther 2015; 42. [PMID: 26201312 PMCID: PMC5014135 DOI: 10.1111/apt.13331] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND The potassium-competitive acid blocker vonoprazan (VPZ) has potent acid-inhibitory effects and may offer clinical advantages over conventional therapy for acid-related disorders. AIM To investigate the efficacy and safety of VPZ in patients with erosive oesophagitis (EO). METHODS In this multicentre, randomised, double-blind, parallel-group, dose-ranging study, patients ≥20 years with endoscopically confirmed EO [Los Angeles (LA) grades A-D] received VPZ 5, 10, 20 or 40 mg, or lansoprazole (LPZ) 30 mg once daily for 8 weeks. The primary endpoint was the proportion of healed EO subjects as shown by endoscopy at week 4. RESULTS A total of 732 subjects received VPZ or LPZ. The proportion of healed EO subjects at week 4 was 92.3%, 92.5%, 94.4%, 97.0% and 93.2%, respectively, with VPZ 5, 10, 20 and 40 mg and LPZ 30 mg. All VPZ doses were non-inferior to LPZ when adjusted for baseline LA grades A/B and C/D. Among those with LA grades C/D, the proportions of healed EO subjects were 87.3%, 86.4%, 100%, 96.0% and 87.0%, respectively, with VPZ 5, 10, 20 and 40 mg and LPZ 30 mg. The incidence of adverse events was similar across the groups. CONCLUSIONS Vonoprazan was effective and non-inferior to LPZ in healing EO. VPZ 20 mg or higher was highly efficacious for severe EO (LA grades C/D). VPZ was associated with no safety concern during this 8-week study, while there was a dose-dependent increase in serum gastrin. Once-daily VPZ 20 mg is the recommended clinical dose for treating EO.
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Affiliation(s)
| | - Y. Sakurai
- Takeda Pharmaceutical Company Ltd.OsakaJapan
| | | | - K. Kudou
- Takeda Pharmaceutical Company Ltd.OsakaJapan
| | - N. Hiramatsu
- Osaka University Graduate School of MedicineOsakaJapan
| | - E. Umegaki
- Kobe University Graduate School of MedicineKobeJapan
| | - K. Iwakiri
- Nippon Medical School Graduate School of MedicineTokyoJapan
| | - T. Chiba
- Graduate School of Medicine and Faculty of MedicineKyoto UniversityKyotoJapan
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31
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Sakurai Y, Mori Y, Okamoto H, Nishimura A, Komura E, Araki T, Shiramoto M. Acid-inhibitory effects of vonoprazan 20 mg compared with esomeprazole 20 mg or rabeprazole 10 mg in healthy adult male subjects--a randomised open-label cross-over study. Aliment Pharmacol Ther 2015; 42:719-30. [PMID: 26193978 DOI: 10.1111/apt.13325] [Citation(s) in RCA: 228] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Revised: 02/12/2015] [Accepted: 06/29/2015] [Indexed: 12/13/2022]
Abstract
BACKGROUND Proton pump inhibitors (PPIs) are widely used for the treatment of acid-related diseases. Vonoprazan is a member of a new class of acid suppressants; potassium-competitive acid blockers. Vonoprazan may thus be an alternative to PPIs. AIM To evaluate efficacy, rapidity and duration of acid-inhibitory effects of vonoprazan vs. two control PPIs, esomeprazole and rabeprazole, in 20 healthy Japanese adult male volunteers with CYP2C19 extensive metaboliser genotype. METHODS In this randomised, open-label, two-period cross-over study, vonoprazan 20 mg and esomeprazole 20 mg (Study V vs. E) or rabeprazole 10 mg (Study V vs. R) were orally administered daily for 7 days. Primary pharmacodynamic endpoint was gastric pH over 24 h measured as percentage of time pH ≥3, ≥4 and ≥5 (pH holding time ratios; HTRs) and mean gastric pH. RESULTS Acid-inhibitory effect (pH4 HTR) of vonoprazan was significantly greater than that of esomeprazole or rabeprazole on both Days 1 and 7; Day 7 difference in pH4 HTR for vonoprazan vs. esomeprazole was 24.6% [95% confidence interval (CI): 16.2-33.1] and for vonoprazan vs. rabeprazole 28.8% [95% CI: 17.2-40.4]. The Day 1 to Day 7 ratio of 24-h pH4 HTRs was >0.8 for vonoprazan, compared with 0.370 for esomeprazole and 0.393 for rabeprazole. Vonoprazan was generally well tolerated. One vonoprazan subject withdrew due to a rash which resolved after discontinuation. CONCLUSIONS This study demonstrated a more rapid and sustained acid-inhibitory effect of vonoprazan 20 mg vs. esomeprazole 20 mg or rabeprazole 10 mg. Therefore, vonoprazan may be a potentially new treatment for acid-related diseases.
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Affiliation(s)
- Y Sakurai
- Takeda Pharmaceutical Company Ltd., Osaka, Japan
| | - Y Mori
- Takeda Pharmaceutical Company Ltd., Osaka, Japan
| | - H Okamoto
- Takeda Pharmaceutical Company Ltd., Osaka, Japan
| | - A Nishimura
- Takeda Pharmaceutical Company Ltd., Osaka, Japan
| | - E Komura
- Takeda Pharmaceutical Company Ltd., Osaka, Japan
| | - T Araki
- Takeda Pharmaceutical Company Ltd., Osaka, Japan
| | - M Shiramoto
- Medical Co. LTA Hakata Clinic, Fukuoka, Japan
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32
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Abstract
OBJECTIVES Salubrinal is a synthetic agent that elevates phosphorylation of eukaryotic translation initiation factor 2 alpha (eIF2α) and alleviates stress to the endoplasmic reticulum. Previously, we reported that in chondrocytes, Salubrinal attenuates expression and activity of matrix metalloproteinase 13 (MMP13) through downregulating nuclear factor kappa B (NFκB) signalling. We herein examine whether Salubrinal prevents the degradation of articular cartilage in a mouse model of osteoarthritis (OA). METHODS OA was surgically induced in the left knee of female mice. Animal groups included age-matched sham control, OA placebo, and OA treated with Salubrinal or Guanabenz. Three weeks after the induction of OA, immunoblotting was performed for NFκB p65 and p-NFκB p65. At three and six weeks, the femora and tibiae were isolated and the sagittal sections were stained with Safranin O. RESULTS Salubrinal suppressed the progression of OA by downregulating p-NFκB p65 and MMP13. Although Guanabenz elevates the phosphorylation level of eIF2α, it did not suppress the progression of OA. CONCLUSIONS Administration of Salubrinal has chondroprotective effects in arthritic joints. Salubrinal can be considered as a potential therapeutic agent for alleviating symptoms of OA. Cite this article: Bone Joint Res 2015;4:84-92.
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Affiliation(s)
- K Hamamura
- Indiana University, Purdue University, Indianapolis, 723 West Michigan Street, Indianapolis, Indiana 46202, USA
| | - A Nishimura
- Indiana University, Purdue University, Indianapolis, 723 West Michigan Street, Indianapolis, Indiana 46202, USA. Mie University Graduate School of Medicine, Mie 514, Japan
| | - T Iino
- Mie University Graduate School of Medicine, Mie 514, Japan
| | - S Takigawa
- Indiana University, Purdue University, Indianapolis, 723 West Michigan Street, Indianapolis, Indiana 46202, USA
| | - A Sudo
- Mie University Graduate School of Medicine, Mie 514, Japan
| | - H Yokota
- Indiana University, Purdue University, Indianapolis, 723 West Michigan Street, Indianapolis, Indiana 46202, USA
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Abstract
Proliferation and differentiation of the epidermis in organ culture of adult human skin by the sponge matrix method were studied histologically and autoradiographically, and the following results were obtained: 1) On the first day of culture, mitotic figures were already observable in the epidermis. The outgrowth of epidermal cells at the margins of the explants started. On the second day, there was transformation to a zone that will be referred to as the newly formed stratum corneum in the upper epidermis. 2) On the third and fourth days, the increased growth of epidermal cells caused thickening of the epidermis. Simultaneously, Malpighian cells progressively differentiated into a cornified layer. 3) On and after the fifth day, the basospinous cell layer was reduced in thickness in most of explants. On the ninth and tenth days, DNA synthesis in the basal layer was still obvious, although the epidermis showed a thickness of only one or two cells overlaid with a large number of horny layers. 4) In the culture medium supplemented with corticosteroid, the epidermal growth was slightly depressed with lessened formation of stratum corneum in the early stages of culture as compared with the explants cultured in the basic medium. The reduction of the basospinous layer was scarcely notable after the fifth day. Even after 10-11 days, epidermal cells were well preserved and their stratified squamous architecture was less disorganized. It seemed that corticosteroid could prolong the survival of adult human skin in vitro. These findings indicate that this culture technique could be used as a model for organ culture of adult human skin.
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Affiliation(s)
- H Yasuno
- Department of Dermatology, Kyoto Prefectural University of Medicine, Kawara-machi, Hirokoji, Kamikyo-ku, Kyoto, Japan
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Jenkins H, Sakurai Y, Nishimura A, Okamoto H, Hibberd M, Jenkins R, Yoneyama T, Ashida K, Ogama Y, Warrington S. Randomised clinical trial: safety, tolerability, pharmacokinetics and pharmacodynamics of repeated doses of TAK-438 (vonoprazan), a novel potassium-competitive acid blocker, in healthy male subjects. Aliment Pharmacol Ther 2015; 41:636-48. [PMID: 25707624 PMCID: PMC4654261 DOI: 10.1111/apt.13121] [Citation(s) in RCA: 184] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2014] [Revised: 09/25/2014] [Accepted: 01/26/2015] [Indexed: 12/11/2022]
Abstract
BACKGROUND TAK-438 (vonoprazan) is a potassium-competitive acid blocker that reversibly inhibits gastric H(+) , K(+) -ATPase. AIM To evaluate the safety, tolerability, pharmacokinetics and pharmacodynamics of TAK-438 in healthy Japanese and non-Japanese men. METHODS In two Phase I, randomised, double-blind, placebo-controlled studies, healthy men (Japan N = 60; UK N = 48) received TAK-438 10-40 mg once daily at a fixed dose level for 7 consecutive days. Assessments included safety, tolerability, pharmacokinetics and pharmacodynamics (intragastric pH). RESULTS Plasma concentration-time profiles of TAK-438 at all dose levels showed rapid absorption (median Tmax ≤2 h). Mean elimination half-life was up to 9 h. Exposure was slightly greater than dose proportional, with no apparent time-dependent inhibition of metabolism. There was no important difference between the two studies in AUC0-tau on Day 7. TAK-438 caused dose-dependent acid suppression. On Day 7, mean 24-h intragastric pH>4 holding time ratio (HTR) with 40 mg TAK-438 was 100% (Japan) and 93.2% (UK), and mean night-time pH>4 HTR was 100% (Japan) and 90.4% (UK). TAK-438 was well tolerated. The frequency of adverse events was similar at all dose levels and there were no serious adverse events. There were no important increases in serum alanine transaminase activity. Serum gastrin and pepsinogen I and II concentrations increased with TAK-438 dose. CONCLUSIONS TAK-438 in multiple rising oral dose levels of 10-40 mg once daily for 7 days was safe and well tolerated in healthy men and caused rapid, profound and sustained suppression of gastric acid secretion throughout each 24-h dosing interval. Clinicaltrials.gov identifiers: NCT02123953 and NCT02141711.
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Affiliation(s)
- H Jenkins
- Takeda Development Centre Europe LtdLondon, UK
| | - Y Sakurai
- Takeda Pharmaceutical Company LtdOsaka, Japan
| | - A Nishimura
- Takeda Pharmaceutical Company LtdOsaka, Japan
| | - H Okamoto
- Takeda Pharmaceutical Company LtdOsaka, Japan
| | - M Hibberd
- Takeda Development Centre Europe LtdLondon, UK
| | - R Jenkins
- Takeda Development Centre Europe LtdLondon, UK
| | - T Yoneyama
- Takeda Pharmaceutical Company Ltd, FujisawaJapan
| | - K Ashida
- Department of Gastroenterology and Hepatology, Saiseikai Nakatsu HospitalOsaka, Japan
| | - Y Ogama
- Medical Co. LTA Honjo Clinic (current Sumida Hospital)Tokyo, Japan
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Ito C, Naito H, Nishimura A, Ohba H, Wakaida I, Sugiyama A, Chatani K. Development of radiation-resistant optical fiber for application to observation and laser spectroscopy under high radiation dose. J NUCL SCI TECHNOL 2014. [DOI: 10.1080/00223131.2014.924883] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Moroto M, Nishimura A, Morimoto M, Isoda K, Morita T, Yoshida M, Morioka S, Tozawa T, Hasegawa T, Chiyonobu T, Yoshimoto K, Hosoi H. Altered somatosensory barrel cortex refinement in the developing brain of Mecp2-null mice. Brain Res 2013; 1537:319-26. [DOI: 10.1016/j.brainres.2013.09.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2013] [Revised: 09/13/2013] [Accepted: 09/16/2013] [Indexed: 12/13/2022]
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Shintaku H, Nakajima T, Sawada Y, Hase Y, Fujioka M, Nishimura A, Isshiki G, Oura T, Hsiao ΚJ, Chen RG. Prenatal Diagnosis of Tetrahydrobiopterin (BH4) Synthase Deficiency. Pteridines 2013. [DOI: 10.1515/pteridines.1991.3.12.17] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- H. Shintaku
- Dept. of Osaka City Univ. Medical School, Osaka 545, Japan
| | - T. Nakajima
- Dept. of Osaka City Univ. Medical School, Osaka 545, Japan
| | - Y. Sawada
- Dept. of Pediatrics Juso Citizens' Hospital, Osaka 532, Japan
| | - Y. Hase
- First Division of Pediatrics Children's Medical Center of Osaka City, Osaka 537, Japan
| | - M. Fujioka
- Dept. of Pediatrics PL Hospital, Tondabayashi 584, Japan
| | - A. Nishimura
- Dept. of Pediatrics PL Hospital, Tondabayashi 584, Japan
| | - G. Isshiki
- Dept. of Osaka City Univ. Medical School, Osaka 545, Japan
| | - T. Oura
- Osaka Municipal Rehabilitation Center for the Disabled, Osaka 547, Japan
| | - Κ. J. Hsiao
- Veterans General Hospital, Taipei 11216, Republic of China
| | - R. G. Chen
- Shanghai Institute for Pediatric Research, Shanghai, China
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Sakaue S, Chiyonobu T, Moroto M, Morita T, Yoshida M, Morioka S, Tokuda S, Nishimura A, Morimoto M, Hosoi H. [A case with recurrent asystole due to breath-holding spells: successful treatment with levetiracetam]. No To Hattatsu 2012; 44:496-498. [PMID: 23240534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
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Isoda K, Tomoyasu C, Fujii N, Nishimura A. [Levetiracetam-induced aggravation to non-convulsive status epilepticus in a boy with Lennox-Gastaut syndrome]. No To Hattatsu 2012; 44:401-402. [PMID: 23012871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
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Nonaka M, Nishimura A, Nakamura S, Nakayama K, Mochizuki A, Iijima T, Inoue T. Convergent Pre-motoneuronal Inputs to Single Trigeminal Motoneurons. J Dent Res 2012; 91:888-93. [DOI: 10.1177/0022034512453724] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Because pre-motor neurons targeting trigeminal motoneurons are located in various regions, including the supratrigeminal (SupV) and intertrigeminal (IntV) regions, the principal sensory trigeminal nucleus (PrV), and the region dorsal to the PrV (dRt), a single trigeminal motoneuron may receive differential convergent inputs from these regions. We thus examined the properties of synaptic inputs from these regions to masseter motoneurons (MMNs) and digastric motoneurons (DMNs) in brainstem slice preparations obtained from P1-5 neonatal rats, using whole-cell recordings and laser photolysis of caged glutamate. Photostimulation of multiple regions within the SupV, IntV, PrV, and dRt induced post-synaptic currents (PSCs) in 14 of 19 MMNs and 18 of 26 DMNs. Furthermore, the stimulation of the lateral SupV significantly induced burst PSCs in MMNs more often than low-frequency PSCs in MMNs or burst PSCs in DMNs. Similar results were obtained in the presence of the GABAA receptor antagonist SR95531 and the glycine receptor antagonist strychnine. These results suggest that both neonatal MMNs and DMNs receive convergent glutamatergic inputs from the SupV, IntV, PrV, and dRt, and that the lateral SupV sends burst inputs predominantly to the MMNs. Such convergent pre-motoneuronal inputs to trigeminal motoneurons may contribute to the proper execution of neonatal oro-motor functions.
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Affiliation(s)
- M. Nonaka
- Department of Oral Anesthesia, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
- Department of Oral Physiology, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
| | - A. Nishimura
- Department of Oral Anesthesia, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
| | - S. Nakamura
- Department of Oral Physiology, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
| | - K. Nakayama
- Department of Oral Physiology, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
| | - A. Mochizuki
- Department of Oral Physiology, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
| | - T. Iijima
- Department of Oral Anesthesia, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
| | - T. Inoue
- Department of Oral Physiology, Showa University School of Dentistry, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, Japan
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Tadaki H, Saitsu H, Kanegane H, Miyake N, Imagawa T, Kikuchi M, Hara R, Kaneko U, Kishi T, Miyamae T, Nishimura A, Doi H, Tsurusaki Y, Sakai H, Yokota S, Matsumoto N. Exonic deletion of CASP10 in a patient presenting with systemic juvenile idiopathic arthritis, but not with autoimmune lymphoproliferative syndrome type IIa. Int J Immunogenet 2011; 38:287-93. [DOI: 10.1111/j.1744-313x.2011.01005.x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Harada H, Nishimura A, Nishimura T, Matsushita H, Okamura S, Shimokawa Y, Kimura M. [Experience with surgical resections of metachronous liver and bilateral pulmonary metastases from gastric cancer]. Kyobu Geka 2010; 63:1094-1097. [PMID: 21066856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
A 75-year-old female patient underwent distal gastrectomy with lymph node dissection for gastric cancer. Six months later, computed tomography (CT) and magnetic resonance imaging (MRI) revealed liver metastasis and radio frequency ablation (RFA) was performed. Ten months later, she underwent a partial hepatectomy for recurrent hepatic metastasis. Then, pulmonary nodules were revealed 1 year later, and segmentectomy (S4 + S5) for left pulmonary metastasis and wedge resection for right middle lobe pulmonary metastasis were sequentially performed after 9 months and 10 months observation by CT, respectively. Two years have passed since the last surgery, and the patient has survived more than 5 years since initial gastrectomy.
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Affiliation(s)
- H Harada
- Department of Respiratory Surgery, Kure Medical Center, Chugoku Cancer Center, Kure, Japan
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Yano S, Baskin B, Bagheri A, Watanabe Y, Moseley K, Nishimura A, Matsumoto N, Ray PN. Familial Simpson-Golabi-Behmel syndrome: studies of X-chromosome inactivation and clinical phenotypes in two female individuals with GPC3 mutations. Clin Genet 2010; 80:466-71. [PMID: 20950395 DOI: 10.1111/j.1399-0004.2010.01554.x] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Simpson-Golabi-Behmel syndrome (SGBS) is an overgrowth/multiple congenital anomalies syndrome with an X-linked inheritance. Most cases of SGBS are attributed to mutations in the glypican 3-gene (GPC3), which is highly expressed in the mesodermal embryonic tissues and involves in a local growth regulation. Typical clinical features include pre/postnatal overgrowth, developmental delay, macrocephaly, characteristic facies with prominent eyes and macroglossia, diaphragmatic hernia, congenital heart defects, kidney anomalies, and skeletal anomalies. Obligate carrier females with GPC3 mutations are usually asymptomatic or with mild symptoms. It is thought that skewed X-inactivation is the underlining mechanism for the female patients to present with findings of SGBS. We identified three siblings with typical SGBS (two male and one female cases) and their mother with very mild symptoms in a family carrying c.256C>T (p.Arg86X) mutation in GPC3. X-inactivation studies on the androgen-receptor gene (AR) and the Fragile XE (FRAXE) gene were performed with blood, buccal swabs, and fibroblasts in the carrier females. The studies with blood showed moderately skewed X-inactivation with paternal X-chromosome being preferentially inactivated (71-80% inactivated) in the female patient with SGBS and no skewing was shown in the mother with very mild symptoms. The X-inactivation studies in the mother showed inactivation of the X-chromosome with the mutation by 57%. This suggests that loss of the functional GPC3 protein by 43% is closed to the threshold to develop the SGBS phenotype. Studies with buccal swabs and fibroblasts failed to show different X-inactivation patterns between the two female individuals.
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Affiliation(s)
- S Yano
- Genetics Division, Department of Pediatrics, LAC+USC Medical Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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Ogiya M, Shioiri S, Nishimura A, Tsutsui KI, Kimura K. The effect of peripheral task on the training for enlarging useful visual field. J Vis 2010. [DOI: 10.1167/10.7.146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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45
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Nishimura A, Yokosawa K. Cueing of the stimulus location in polarity correspondence effect. J Vis 2010. [DOI: 10.1167/6.6.217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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46
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Nishimura A, Yokosawa K. Orthogonal Simon effect: A new interference effect with vertically arrayed stimuli and horizontally arrayed responses. J Vis 2010. [DOI: 10.1167/5.8.168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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47
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Nishimura A, Yokosawa K. Orthogonal S-R compatibility and stimulus saliency. J Vis 2010. [DOI: 10.1167/3.9.226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Kasuga K, Shimohata T, Nishimura A, Shiga A, Mizuguchi T, Tokunaga J, Ohno T, Miyashita A, Kuwano R, Matsumoto N, Onodera O, Nishizawa M, Ikeuchi T. Identification of independent APP locus duplication in Japanese patients with early-onset Alzheimer disease. J Neurol Neurosurg Psychiatry 2009; 80:1050-2. [PMID: 19684239 DOI: 10.1136/jnnp.2008.161703] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BACKGROUND The occurrence of duplications of the amyloid precursor protein gene (APP) has been described in European families with early-onset familial Alzheimer disease (EO-FAD) and cerebral amyloid angiopathy. However, the contribution of APP duplication to the development of AD in other ethnic populations remains undetermined. METHODS The occurrence of APP duplication in probands from 25 families with FAD and 11 sporadic EO-AD cases in the Japanese population was examined by quantitative PCR and microarray-based comparative genomic hybridisation analyses. APP expression level was determined by real-time quantitative reverse-transcription (RT) PCR analysis using mRNA extracted from the peripheral blood of the patients. RESULTS We identified APP locus duplications in two unrelated EO-FAD families. The duplicated genomic regions in two patients of these families differed from each other. No APP duplication was found in the late-onset FAD families or sporadic EO-AD patients. The patients with APP duplication developed insidious memory disturbance in their fifties without intracerebral haemorrhage and epilepsy. Quantitative RT-PCR analysis showed the increased APP mRNA expression levels in these patients compared with those in age- and sex-matched controls. CONCLUSIONS Our results suggest that APP duplication should be considered in patients with EO-FAD in various ethnic groups, and that increased APP mRNA expression level owing to APP duplication contributes to AD development.
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Affiliation(s)
- K Kasuga
- Department of Molecular Neuroscience, Bioresource Science Branch, Center for Bioresources, Brain Research Institute, Niigata University, Niigata, Japan
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Mitsui Y, Konishi K, Nishimura A, Kajima M, Tamura O, Endo K. EXPERIMENTS IN HUMAN VOLUNTEERS WITH TRACHOMA AND INCLUSION CONJUNCTIVITIS AGENT. Br J Ophthalmol 2009; 46:651-9. [PMID: 18170828 DOI: 10.1136/bjo.46.11.651] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Y Mitsui
- Department of Ophthalmology, School of Medicine, Tokushima University, Japan
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