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Hutch MR, Son J, Le TT, Hong C, Wang X, Shakeri Hossein Abad Z, Morris M, Gutiérrez-Sacristán A, Klann JG, Spiridou A, Batugo A, Bellazzi R, Benoit V, Bonzel CL, Bryant WA, Chiudinelli L, Cho K, Das P, González González T, Hanauer DA, Henderson DW, Ho YL, Loh NHW, Makoudjou A, Makwana S, Malovini A, Moal B, Mowery DL, Neuraz A, Samayamuthu MJ, Sanz Vidorreta FJ, Schriver ER, Schubert P, Talbert J, Tan ALM, Tan BWL, Tan BWQ, Tibollo V, Tippman P, Verdy G, Yuan W, Avillach P, Gehlenborg N, Omenn GS, Visweswaran S, Cai T, Luo Y, Xia Z. Neurological diagnoses in hospitalized COVID-19 patients associated with adverse outcomes: A multinational cohort study. PLOS Digit Health 2024; 3:e0000484. [PMID: 38620037 PMCID: PMC11018281 DOI: 10.1371/journal.pdig.0000484] [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] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 03/06/2024] [Indexed: 04/17/2024]
Abstract
Few studies examining the patient outcomes of concurrent neurological manifestations during acute COVID-19 leveraged multinational cohorts of adults and children or distinguished between central and peripheral nervous system (CNS vs. PNS) involvement. Using a federated multinational network in which local clinicians and informatics experts curated the electronic health records data, we evaluated the risk of prolonged hospitalization and mortality in hospitalized COVID-19 patients from 21 healthcare systems across 7 countries. For adults, we used a federated learning approach whereby we ran Cox proportional hazard models locally at each healthcare system and performed a meta-analysis on the aggregated results to estimate the overall risk of adverse outcomes across our geographically diverse populations. For children, we reported descriptive statistics separately due to their low frequency of neurological involvement and poor outcomes. Among the 106,229 hospitalized COVID-19 patients (104,031 patients ≥18 years; 2,198 patients <18 years, January 2020-October 2021), 15,101 (14%) had at least one CNS diagnosis, while 2,788 (3%) had at least one PNS diagnosis. After controlling for demographics and pre-existing conditions, adults with CNS involvement had longer hospital stay (11 versus 6 days) and greater risk of (Hazard Ratio = 1.78) and faster time to death (12 versus 24 days) than patients with no neurological condition (NNC) during acute COVID-19 hospitalization. Adults with PNS involvement also had longer hospital stay but lower risk of mortality than the NNC group. Although children had a low frequency of neurological involvement during COVID-19 hospitalization, a substantially higher proportion of children with CNS involvement died compared to those with NNC (6% vs 1%). Overall, patients with concurrent CNS manifestation during acute COVID-19 hospitalization faced greater risks for adverse clinical outcomes than patients without any neurological diagnosis. Our global informatics framework using a federated approach (versus a centralized data collection approach) has utility for clinical discovery beyond COVID-19.
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Affiliation(s)
- Meghan R. Hutch
- Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Jiyeon Son
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Trang T. Le
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Chuan Hong
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, United States of America
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Xuan Wang
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Zahra Shakeri Hossein Abad
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Alba Gutiérrez-Sacristán
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Jeffrey G. Klann
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Anastasia Spiridou
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, United Kingdom
| | - Ashley Batugo
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Vincent Benoit
- IT Department, Innovation & Data, APHP Greater Paris University Hospital, Paris, France
| | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - William A. Bryant
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, United Kingdom
| | - Lorenzo Chiudinelli
- UOC Ricerca, Innovazione e Brand reputation, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Kelly Cho
- Population Health and Data Science, VA Boston Healthcare System, Boston Massachusetts, United States of America
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston Massachusetts, United States of America
| | - Priyam Das
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | | | - David A. Hanauer
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Darren W. Henderson
- Center for Clinical and Translational Science, University of Kentucky, Lexington, Kentucky, United States of America
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston Massachusetts, United States of America
| | - Ne Hooi Will Loh
- Department of Anaesthesia, National University Health System, Kent Ridge, Singapore
| | - Adeline Makoudjou
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Simran Makwana
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Alberto Malovini
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | - Bertrand Moal
- IAM Unit, Bordeaux University Hospital, Bordeaux, France
| | - Danielle L. Mowery
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Antoine Neuraz
- Department of biomedical informatics, Hôpital Necker-Enfants Malade, Assistance Publique Hôpitaux de Paris (APHP), University of Paris, Paris, France
| | | | - Fernando J. Sanz Vidorreta
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America
| | - Emily R. Schriver
- Data Analytics Center, University of Pennsylvania Health System, Philadelphia, Pennsylvania, United States of America
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston Massachusetts, United States of America
| | - Jeffery Talbert
- Division of Biomedical Informatics, University of Kentucky, Lexington, Kentucky, United States of America
| | - Amelia L. M. Tan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Byorn W. L. Tan
- Department of Medicine, National University Hospital, Singapore, Kent Ridge, Singapore
| | - Bryce W. Q. Tan
- Department of Medicine, National University Hospital, Singapore, Kent Ridge, Singapore
| | - Valentina Tibollo
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | - Patric Tippman
- Institute of Medical Biometry and University of Freiburg, Medical Center, Freiburg, Germany
| | | | - William Yuan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Paul Avillach
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Gilbert S. Omenn
- Departments of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | | | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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Zhang HG, Honerlaw JP, Maripuri M, Samayamuthu MJ, Beaulieu-Jones BR, Baig HS, L'Yi S, Ho YL, Morris M, Panickan VA, Wang X, Weber GM, Liao KP, Visweswaran S, Tan BWQ, Yuan W, Gehlenborg N, Muralidhar S, Ramoni RB, Kohane IS, Xia Z, Cho K, Cai T, Brat GA. Potential pitfalls in the use of real-world data for studying long COVID. Nat Med 2023; 29:1040-1043. [PMID: 37055567 PMCID: PMC10205658 DOI: 10.1038/s41591-023-02274-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
Affiliation(s)
- Harrison G Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Jacqueline P Honerlaw
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Monika Maripuri
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | | | | | - Huma S Baig
- Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sehi L'Yi
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Griffin M Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Katherine P Liao
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bryce W Q Tan
- Department of Medicine, National University Hospital, Singapore, Singapore, Singapore
| | - William Yuan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Sumitra Muralidhar
- Office of Research and Development, US Department of Veterans Affairs, Washington DC, USA
| | - Rachel B Ramoni
- Office of Research and Development, US Department of Veterans Affairs, Washington DC, USA
| | - Isaac S Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Gabriel A Brat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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Singh G, Zhang N, da Silva CFA, Agarwal D, Salloum-Asfar S, Mohammed S, Heim AB, Richter WE, Ji Y, Zhi Y, Tan BWQ, Bergh C, Powell JR, Sarnala S. The fruits of failure. Science 2023; 379:24-25. [PMID: 36603086 DOI: 10.1126/science.adg1443] [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: 01/07/2023]
Affiliation(s)
- Garima Singh
- Mott MacDonald, Noida, Uttar Pradesh 201301, India
| | - Ning Zhang
- First School of Clinical Medicine, Anhui Medical University, Hefei, Anhui 230032, China
| | | | - Divyansh Agarwal
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02108, USA
| | | | - Stephanie Mohammed
- Department of Physics, Faculty of Science and Technology, The University of the West Indies, St. Augustine Campus, Trinidad, St. Augustine, Trinidad and Tobago
| | - Ashley Barbara Heim
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
| | - Wagner Eduardo Richter
- Department of Chemistry, Federal University of Technology-Paraná, Ponta Grossa, Paraná, Brazil
| | - Yongsheng Ji
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Yuan Zhi
- School of Economics, Guizhou University, Guiyang, Guizhou 550025, China
| | - Bryce W Q Tan
- Department of Medicine, National University Hospital, Singapore 119228, Singapore
| | - Cathrine Bergh
- KTH Royal Institute of Technology, 11423 Stockholm, Sweden
| | - Jackson Ross Powell
- Vagelos Molecular Life Sciences Program, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sai Sarnala
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
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Zhang HG, Dagliati A, Shakeri Hossein Abad Z, Xiong X, Bonzel CL, Xia Z, Tan BWQ, Avillach P, Brat GA, Hong C, Morris M, Visweswaran S, Patel LP, Gutiérrez-Sacristán A, Hanauer DA, Holmes JH, Samayamuthu MJ, Bourgeois FT, L'Yi S, Maidlow SE, Moal B, Murphy SN, Strasser ZH, Neuraz A, Ngiam KY, Loh NHW, Omenn GS, Prunotto A, Dalvin LA, Klann JG, Schubert P, Vidorreta FJS, Benoit V, Verdy G, Kavuluru R, Estiri H, Luo Y, Malovini A, Tibollo V, Bellazzi R, Cho K, Ho YL, Tan ALM, Tan BWL, Gehlenborg N, Lozano-Zahonero S, Jouhet V, Chiovato L, Aronow BJ, Toh EMS, Wong WGS, Pizzimenti S, Wagholikar KB, Bucalo M, Cai T, South AM, Kohane IS, Weber GM. International electronic health record-derived post-acute sequelae profiles of COVID-19 patients. NPJ Digit Med 2022; 5:81. [PMID: 35768548 PMCID: PMC9242995 DOI: 10.1038/s41746-022-00623-8] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 05/19/2022] [Indexed: 11/10/2022] Open
Abstract
The risk profiles of post-acute sequelae of COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09–1.55), heart failure (RR 1.22, 95% CI 1.10–1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07–1.31), and fatigue (RR 1.18, 95% CI 1.07–1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58–2.76), venous embolism (RR 1.34, 95% CI 1.17–1.54), atrial fibrillation (RR 1.30, 95% CI 1.13–1.50), type 2 diabetes (RR 1.26, 95% CI 1.16–1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09–1.30). Outpatient COVID-19 cases were also at risk for loss of smell and taste (RR 2.42, 95% CI 1.90–3.06), inflammatory neuropathy (RR 1.66, 95% CI 1.21–2.27), and cognitive dysfunction (RR 1.18, 95% CI 1.04–1.33). The incidence of post-acute cardiovascular and pulmonary conditions decreased across time among inpatient cases while the incidence of cardiovascular, digestive, and metabolic conditions increased among outpatient cases. Our study, based on a federated international network, systematically identified robust conditions associated with PASC compared to control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.
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Affiliation(s)
- Harrison G Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Arianna Dagliati
- Department of Electrical Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | | | - Xin Xiong
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bryce W Q Tan
- Department of Medicine, National University Hospital, Singapore, Singapore
| | - Paul Avillach
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Gabriel A Brat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Chuan Hong
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.,Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lav P Patel
- Department of Internal Medicine, Division of Medical Informatics, University Of Kansas Medical Center, Kansas City, MO, USA
| | | | - David A Hanauer
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, MI, USA
| | - John H Holmes
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | | | - Sehi L'Yi
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Sarah E Maidlow
- Michigan Institute for Clinical and Health Research (MICHR) Informatics, University of Michigan, Ann Arbor, MI, USA
| | - Bertrand Moal
- IAM unit, Bordeaux University Hospital, Bordeaux, France
| | - Shawn N Murphy
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Antoine Neuraz
- Department of biomedical informatics, Hôpital Necker-Enfants Malade, Assistance Publique Hôpitaux de Paris (APHP), University of Paris, Paris, France
| | - Kee Yuan Ngiam
- Department of Biomedical informatics, WiSDM, National University Health Systems Singapore, Singapore, Singapore
| | - Ne Hooi Will Loh
- Department of Anaesthesia, National University Health Systems Singapore, Singapore, Singapore
| | - Gilbert S Omenn
- Department of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Andrea Prunotto
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Lauren A Dalvin
- Department of Ophthalmology, Mayo Clinic, Rochester, NY, USA
| | - Jeffrey G Klann
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | | | - Vincent Benoit
- IT Department, Innovation & Data, APHP Greater Paris University Hospital, Paris, France
| | | | - Ramakanth Kavuluru
- Division of Biomedical Informatics (Department of Internal Medicine), University of Kentucky, Lexington, KY, USA
| | - Hossein Estiri
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Alberto Malovini
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | - Valentina Tibollo
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.,Population Health and Data Science, VA Boston Healthcare System, Boston, MA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Amelia L M Tan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Byorn W L Tan
- Department of Medicine, National University Hospital, Singapore, Singapore
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Sara Lozano-Zahonero
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Vianney Jouhet
- IAM unit, INSERM Bordeaux Population Health ERIAS TEAM, Bordeaux University Hospital / ERIAS - Inserm, U1219 BPH, Bordeaux, France
| | - Luca Chiovato
- Unit of Internal Medicine and Endocrinology, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | - Bruce J Aronow
- Departments of Biomedical Informatics, Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Emma M S Toh
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wei Gen Scott Wong
- Department of Medicine, National University Health Systems Singapore, Singapore, Singapore
| | - Sara Pizzimenti
- Scientific Direction, IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy
| | | | - Mauro Bucalo
- BIOMERIS (BIOMedical Research Informatics Solutions), Pavia, Italy
| | | | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Andrew M South
- Department of Pediatrics-Section of Nephrology, Brenner Children's, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Isaac S Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Griffin M Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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5
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Hong C, Zhang HG, L'Yi S, Weber G, Avillach P, Tan BWQ, Gutiérrez-Sacristán A, Bonzel CL, Palmer NP, Malovini A, Tibollo V, Luo Y, Hutch MR, Liu M, Bourgeois F, Bellazzi R, Chiovato L, Sanz Vidorreta FJ, Le TT, Wang X, Yuan W, Neuraz A, Benoit V, Moal B, Morris M, Hanauer DA, Maidlow S, Wagholikar K, Murphy S, Estiri H, Makoudjou A, Tippmann P, Klann J, Follett RW, Gehlenborg N, Omenn GS, Xia Z, Dagliati A, Visweswaran S, Patel LP, Mowery DL, Schriver ER, Samayamuthu MJ, Kavuluru R, Lozano-Zahonero S, Zöller D, Tan ALM, Tan BWL, Ngiam KY, Holmes JH, Schubert P, Cho K, Ho YL, Beaulieu-Jones BK, Pedrera-Jiménez M, García-Barrio N, Serrano-Balazote P, Kohane I, South A, Brat GA, Cai T. Changes in laboratory value improvement and mortality rates over the course of the pandemic: an international retrospective cohort study of hospitalised patients infected with SARS-CoV-2. BMJ Open 2022; 12:e057725. [PMID: 35738646 PMCID: PMC9226470 DOI: 10.1136/bmjopen-2021-057725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 06/12/2022] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVE To assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic. DESIGN, SETTING AND PARTICIPANTS This is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic. PRIMARY AND SECONDARY OUTCOME MEASURES The primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the average rate of change in laboratory values during the first week of hospitalisation. RESULTS Baseline Charlson Comorbidity Index and laboratory values at admission were not significantly different between the first and second waves. The improvement in laboratory values over time was faster in the second wave compared with the first. The average C reactive protein rate of change was -4.72 mg/dL vs -4.14 mg/dL per day (p=0.05). The mortality rates within each risk category significantly decreased over time, with the most substantial decrease in the high-risk group (42.3% in March-April 2020 vs 30.8% in November 2020 to January 2021, p<0.001) and a moderate decrease in the intermediate-risk group (21.5% in March-April 2020 vs 14.3% in November 2020 to January 2021, p<0.001). CONCLUSIONS Admission profiles of patients hospitalised with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic, but there were notable differences in laboratory improvement rates during hospitalisation. Mortality risks among patients with similar risk profiles decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.
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Affiliation(s)
- Chuan Hong
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Harrison G Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Sehi L'Yi
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Griffin Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Paul Avillach
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Bryce W Q Tan
- Department of Medicine, National University Hospital, Singapore
| | | | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Nathan P Palmer
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Alberto Malovini
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy
| | - Valentina Tibollo
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Evanston, Illinois, USA
| | - Meghan R Hutch
- Department of Preventive Medicine, Northwestern University, Evanston, Illinois, USA
| | - Molei Liu
- Department of Biostatistics, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Florence Bourgeois
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Luca Chiovato
- Unit of Internal Medicine and Endocrinology, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy
| | | | - Trang T Le
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - William Yuan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Antoine Neuraz
- Department of Biomedical Informatics, Hopital Universitaire Necker-Enfants Malades, Paris, Île-de-France, France
| | - Vincent Benoit
- IT department, Innovation & Data, APHP Greater Paris University Hospital, Paris, France
| | - Bertrand Moal
- IAM unit, Bordeaux University Hospital, Bordeaux, France
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - David A Hanauer
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Sarah Maidlow
- MICHR Informatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Kavishwar Wagholikar
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Shawn Murphy
- Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Hossein Estiri
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Adeline Makoudjou
- Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany
| | - Patric Tippmann
- Institute of Medical Biometry and Statistics, Medical Center-University of Freiburg, Freiburg, Baden-Württemberg, Germany
| | - Jeffery Klann
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Robert W Follett
- Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Gilbert S Omenn
- Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Arianna Dagliati
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Kansas, USA
| | - Lav P Patel
- Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Danielle L Mowery
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Emily R Schriver
- Data Analytics Center, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA
| | | | - Ramakanth Kavuluru
- Institute for Biomedical Informatics, University of Kentucky, Lexington, Kentucky, USA
| | - Sara Lozano-Zahonero
- Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany
| | - Daniela Zöller
- Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany
| | - Amelia L M Tan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Byorn W L Tan
- Department of Medicine, National University Hospital, Singapore
| | - Kee Yuan Ngiam
- Department of Surgery, National University Hospital, Singapore
| | - John H Holmes
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | | | - Miguel Pedrera-Jiménez
- Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain
| | - Noelia García-Barrio
- Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain
| | - Pablo Serrano-Balazote
- Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain
| | - Isaac Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Andrew South
- Department of Pediatrics, Section of Nephrology, Wake Forest University, Winston Salem, North Carolina, USA
| | - Gabriel A Brat
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - T Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
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6
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Srinivas US, Tay NSC, Jaynes P, Anbuselvan A, Ramachandran GK, Wardyn JD, Hoppe MM, Hoang PM, Peng Y, Lim S, Lee MY, Peethala PC, An O, Shendre A, Tan BWQ, Jemimah S, Lakshmanan M, Hu L, Jakhar R, Sachaphibulkij K, Lim LHK, Pervaiz S, Crasta K, Yang H, Tan P, Liang C, Ho L, Khanchandani V, Kappei D, Yong WP, Tan DSP, Bordi M, Campello S, Tam WL, Frezza C, Jeyasekharan AD. PLK1 inhibition selectively induces apoptosis in ARID1A deficient cells through uncoupling of oxygen consumption from ATP production. Oncogene 2022; 41:1986-2002. [PMID: 35236967 DOI: 10.1038/s41388-022-02219-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [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: 06/16/2021] [Revised: 01/12/2022] [Accepted: 01/27/2022] [Indexed: 12/26/2022]
Abstract
Inhibitors of the mitotic kinase PLK1 yield objective responses in a subset of refractory cancers. However, PLK1 overexpression in cancer does not correlate with drug sensitivity, and the clinical development of PLK1 inhibitors has been hampered by the lack of patient selection marker. Using a high-throughput chemical screen, we discovered that cells deficient for the tumor suppressor ARID1A are highly sensitive to PLK1 inhibition. Interestingly this sensitivity was unrelated to canonical functions of PLK1 in mediating G2/M cell cycle transition. Instead, a whole-genome CRISPR screen revealed PLK1 inhibitor sensitivity in ARID1A deficient cells to be dependent on the mitochondrial translation machinery. We find that ARID1A knock-out (KO) cells have an unusual mitochondrial phenotype with aberrant biogenesis, increased oxygen consumption/expression of oxidative phosphorylation genes, but without increased ATP production. Using expansion microscopy and biochemical fractionation, we see that a subset of PLK1 localizes to the mitochondria in interphase cells. Inhibition of PLK1 in ARID1A KO cells further uncouples oxygen consumption from ATP production, with subsequent membrane depolarization and apoptosis. Knockdown of specific subunits of the mitochondrial ribosome reverses PLK1-inhibitor induced apoptosis in ARID1A deficient cells, confirming specificity of the phenotype. Together, these findings highlight a novel interphase role for PLK1 in maintaining mitochondrial fitness under metabolic stress, and a strategy for therapeutic use of PLK1 inhibitors. To translate these findings, we describe a quantitative microscopy assay for assessment of ARID1A protein loss, which could offer a novel patient selection strategy for the clinical development of PLK1 inhibitors in cancer.
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Affiliation(s)
- Upadhyayula S Srinivas
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Norbert S C Tay
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Patrick Jaynes
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Akshaya Anbuselvan
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Gokula K Ramachandran
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Joanna D Wardyn
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Michal M Hoppe
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Phuong Mai Hoang
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Yanfen Peng
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Sherlly Lim
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - May Yin Lee
- Genome Institute of Singapore (GIS), Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - Praveen C Peethala
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Omer An
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Akshay Shendre
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Bryce W Q Tan
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Sherlyn Jemimah
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Manikandan Lakshmanan
- Institute of Molecular and Cell Biology (IMCB), Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - Longyu Hu
- Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore
| | - Rekha Jakhar
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
- Centre for Healthy Longevity, National University Health System (NUHS), Singapore, Singapore
| | - Karishma Sachaphibulkij
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
| | - Lina H K Lim
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
| | - Shazib Pervaiz
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
| | - Karen Crasta
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
- Centre for Healthy Longevity, National University Health System (NUHS), Singapore, Singapore
| | - Henry Yang
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Patrick Tan
- Genome Institute of Singapore (GIS), Agency for Science Technology and Research (A*STAR), Singapore, Singapore
- Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore
| | - Chao Liang
- Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Lena Ho
- Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Vartika Khanchandani
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
| | - Dennis Kappei
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
- NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
| | - Wei Peng Yong
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
- National University Cancer Institute, Singapore (NCIS), National University Hospital (NUH), Singapore, Singapore
| | - David S P Tan
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
- National University Cancer Institute, Singapore (NCIS), National University Hospital (NUH), Singapore, Singapore
| | - Matteo Bordi
- Department of Biology, University of Rome 'Tor Vergata', Rome, Italy
| | - Silvia Campello
- Department of Biology, University of Rome 'Tor Vergata', Rome, Italy
| | - Wai Leong Tam
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore
- Genome Institute of Singapore (GIS), Agency for Science Technology and Research (A*STAR), Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
| | | | - Anand D Jeyasekharan
- Cancer Science Institute of Singapore, National University of Singapore (NUS), Singapore, Singapore.
- NUS Center for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore.
- National University Cancer Institute, Singapore (NCIS), National University Hospital (NUH), Singapore, Singapore.
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7
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Tan BWQ, Sim WL, Cheong JK, Kuan WS, Tran T, Lim HF. MicroRNAs in chronic airway diseases: Clinical correlation and translational applications. Pharmacol Res 2020; 160:105045. [PMID: 32590100 DOI: 10.1016/j.phrs.2020.105045] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 06/18/2020] [Accepted: 06/19/2020] [Indexed: 12/19/2022]
Abstract
MicroRNAs (miRNAs) are short single-stranded RNAs that have pivotal roles in disease pathophysiology through transcriptional and translational modulation of important genes. It has been implicated in the development of many diseases, such as stroke, cardiovascular conditions, cancers and inflammatory airway diseases. There is recent evidence that miRNAs play important roles in the pathogenesis of asthma and chronic obstructive pulmonary disease (COPD), and could help to distinguish between T2-low (non-eosinophilic, steroid-insensitive) versus T2-high (eosinophilic, steroid-sensitive) disease endotypes. As these are the two most prevalent chronic respiratory diseases globally, with rising disease burden, miRNA research might lead to the development of new diagnostic and therapeutic targets. Research involving miRNAs in airway disease is challenging because: (i) asthma and COPD are heterogeneous inflammatory airway diseases; there are overlapping but distinct inter- and intra-disease differences in the immunological pathophysiology, (ii) there exists more than 2000 known miRNAs and a single miRNA can regulate multiple targets, (iii) differential effects of miRNAs could be present in different cellular subtypes and tissues, and (iv) dysregulated miRNA expression might be a direct consequence of an indirect effect of airway disease onset or progression. As miRNAs are actively secreted in fluids and remain relatively stable, they have the potential for biomarker development and therapeutic targets. In this review, we summarize the preclinical data on potential miRNA biomarkers that mediate different pathophysiological mechanisms in airway disease. We discuss the framework for biomarker development using miRNA and highlight the need for careful patient characterization and endotyping in the screening and validation cohorts, profiling both airway and blood samples to determine the biological fluids of choice in different disease states or severity, and adopting an untargeted approach. Collaboration between the various stakeholders - pharmaceutical companies, laboratory professionals and clinician-scientists is crucial to reduce the difficulties and cost required to bring miRNA research into the translational stage for airway diseases.
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Affiliation(s)
- Bryce W Q Tan
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Wei Liang Sim
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jit Kong Cheong
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Win Sen Kuan
- Department of Emergency Medicine, National University Hospital, National University Health System, Singapore
| | - Thai Tran
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Hui Fang Lim
- Division of Respiratory & Critical Care Medicine, Department of Medicine, National University Hospital, National University Health System, Singapore; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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8
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Abstract
Reactive oxygen species (ROS) are a group of short-lived, highly reactive, oxygen-containing molecules that can induce DNA damage and affect the DNA damage response (DDR). There is unequivocal pre-clinical and clinical evidence that ROS influence the genotoxic stress caused by chemotherapeutics agents and ionizing radiation. Recent studies have provided mechanistic insight into how ROS can also influence the cellular response to DNA damage caused by genotoxic therapy, especially in the context of Double Strand Breaks (DSBs). This has led to the clinical evaluation of agents modulating ROS in combination with genotoxic therapy for cancer, with mixed success so far. These studies point to context dependent outcomes with ROS modulator combinations with Chemotherapy and radiotherapy, indicating a need for additional pre-clinical research in the field. In this review, we discuss the current knowledge on the effect of ROS in the DNA damage response, and its clinical relevance.
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Affiliation(s)
| | - Bryce W Q Tan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore
| | | | - Anand D Jeyasekharan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore; Department of Haematology-Oncology, National University Hospital, Singapore.
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9
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Olmeta-Schult F, Segal LM, Tyner S, Moon TA, Chow RDW, Chakrabarty P, Pacesa M, Podgornaia AI, Chen J, Singh B, Cao B, Sidhu RRS, Tan BWQ, Sood P, Parker S, Scult MA, Van Haute D, Konstantinides N, Schwendimann BA, Srivastava S, Fiorenza R, Dutton-Regester K, Hale R, Polat EO, Lau E, Mayer AL, White ER. NextGen VOICES: Research resolutions. Science 2018; 359:26-28. [PMID: 29301998 DOI: 10.1126/science.aar7504] [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: 11/02/2022]
Affiliation(s)
- Felicia Olmeta-Schult
- Environmental and Natural Resource Sciences, Washington State University, Vancouver, WA 98686, USA.
| | - Lauren Massa Segal
- Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, NE 68583, USA.
| | - Sam Tyner
- Center for Statistics and Applications in Forensic Evidence, Iowa State University, Ames, IA 50014, USA.
| | - Twila Alexandra Moon
- National Snow and Ice Data Center, University of Colorado, Boulder, CO 80309, USA.
| | | | - Prosanta Chakrabarty
- Museum of Natural Science, Louisiana State University, Baton Rouge, LA 70803, USA.
| | - Martin Pacesa
- Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
| | | | | | - Bipin Singh
- School of Engineering and Technology, BML Munjal University, Gurgaon, Haryana 122413, India.
| | - Bo Cao
- Core Research Laboratory, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an Shaanxi, 710004, China.
| | - Rishi Raj Singh Sidhu
- Electrical Engineering, Centre of Excellence in IC Design (VIRTUS), Nanyang Technological University, Singapore, 639798, Singapore.
| | - Bryce W Q Tan
- Department of Physiology, National University of Singapore, Singapore 117456, Singapore.
| | - Prashant Sood
- MRC Centre for Medical Mycology, Institute of Medical Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK.
| | | | - Matthew A Scult
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA.
| | | | | | | | - Sudhakar Srivastava
- Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India.
| | - Raffaele Fiorenza
- Sequencing Operations Lab, New York Genome Center, New York, NY 10013, USA.
| | | | - Rachel Hale
- Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton Waterfront Campus, Southampton, Hampshire SO14 3ZH, UK.
| | - Emre Ozan Polat
- ICFO-The Institute of Photonic Sciences, 08860 Barcelona, Spain.
| | - Edward Lau
- School of Medicine, Stanford University, Palo Alto, CA 94305, USA.
| | - Audrey L Mayer
- SFRES, Michigan Technological University, Houghton, MI 49931, USA.
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10
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Zhang CW, Tai YK, Chai BH, Chew KCM, Ang ET, Tsang F, Tan BWQ, Hong ETE, Asad ABA, Chuang KH, Lim KL, Soong TW. Transgenic Mice Overexpressing the Divalent Metal Transporter 1 Exhibit Iron Accumulation and Enhanced Parkin Expression in the Brain. Neuromolecular Med 2017; 19:375-386. [PMID: 28695462 PMCID: PMC5570798 DOI: 10.1007/s12017-017-8451-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 07/01/2017] [Indexed: 12/15/2022]
Abstract
Exposure to divalent metals such as iron and manganese is thought to increase the risk for Parkinson's disease (PD). Under normal circumstances, cellular iron and manganese uptake is regulated by the divalent metal transporter 1 (DMT1). Accordingly, alterations in DMT1 levels may underlie the abnormal accumulation of metal ions and thereby disease pathogenesis. Here, we have generated transgenic mice overexpressing DMT1 under the direction of a mouse prion promoter and demonstrated its robust expression in several regions of the brain. When fed with iron-supplemented diet, DMT1-expressing mice exhibit rather selective accumulation of iron in the substantia nigra, which is the principal region affected in human PD cases, but otherwise appear normal. Alongside this, the expression of Parkin is also enhanced, likely as a neuroprotective response, which may explain the lack of phenotype in these mice. When DMT1 is overexpressed against a Parkin null background, the double-mutant mice similarly resisted a disease phenotype even when fed with iron- or manganese-supplemented diet. However, these mice exhibit greater vulnerability toward 6-hydroxydopamine-induced neurotoxicity. Taken together, our results suggest that iron accumulation alone is not sufficient to cause neurodegeneration and that multiple hits are required to promote PD.
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Affiliation(s)
- Cheng-Wu Zhang
- National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
- Institute of Advanced Materials, Nanjing Tech University, Nanjing, 211816, People's Republic of China
| | - Yee Kit Tai
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive, Singapore, 117597, Singapore
| | - Bing-Han Chai
- National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
| | - Katherine C M Chew
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive, Singapore, 117597, Singapore
| | - Eng-Tat Ang
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive, Singapore, 117597, Singapore
| | - Fai Tsang
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive, Singapore, 117597, Singapore
| | - Bryce W Q Tan
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive, Singapore, 117597, Singapore
| | - Eugenia T E Hong
- National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
| | - Abu Bakar Ali Asad
- Singapore Bioimaging Consortium (SBIC), A*STAR, Singapore, 138667, Singapore
| | - Kai-Hsiang Chuang
- Singapore Bioimaging Consortium (SBIC), A*STAR, Singapore, 138667, Singapore
| | - Kah-Leong Lim
- National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore.
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive, Singapore, 117597, Singapore.
- Duke-NUS Medical School, Singapore, 169857, Singapore.
- NUS Graduate School for Integrative Science and Engineering, Singapore, 117456, Singapore.
- LSI Neurobiology/Ageing Programme, NUS, Singapore, 117456, Singapore.
| | - Tuck Wah Soong
- National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore.
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive, Singapore, 117597, Singapore.
- NUS Graduate School for Integrative Science and Engineering, Singapore, 117456, Singapore.
- LSI Neurobiology/Ageing Programme, NUS, Singapore, 117456, Singapore.
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