1
|
Silva EE, Moioffer SJ, Hassert M, Berton RR, Smith MG, van de Wall S, Meyerholz DK, Griffith TS, Harty JT, Badovinac VP. Defining Parameters That Modulate Susceptibility and Protection to Respiratory Murine Coronavirus MHV1 Infection. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2024; 212:563-575. [PMID: 38149923 PMCID: PMC10872354 DOI: 10.4049/jimmunol.2300434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 11/28/2023] [Indexed: 12/28/2023]
Abstract
Patients infected with SARS-CoV-2 experience variable disease susceptibility, and patients with comorbidities such as sepsis are often hospitalized for COVID-19 complications. However, the extent to which initial infectious inoculum dose determines disease outcomes and whether this can be used for immunological priming in a genetically susceptible host has not been completely defined. We used an established SARS-like murine model in which responses to primary and/or secondary challenges with murine hepatitis virus type 1 (MHV-1) were analyzed. We compared the response to infection in genetically susceptible C3H/HeJ mice, genetically resistant C57BL/6J mice, and genetically diverse, variably susceptible outbred Swiss Webster mice. Although defined as genetically susceptible to MHV-1, C3H/HeJ mice displayed decreasing dose-dependent pathological changes in disease severity and lung infiltrate/edema, as well as lymphopenia. Importantly, an asymptomatic dose (500 PFU) was identified that yielded no measurable morbidity/mortality postinfection in C3H/HeJ mice. Polymicrobial sepsis induced via cecal ligation and puncture converted asymptomatic infections in C3H/HeJ and C57BL/6J mice to more pronounced disease, modeling the impact of sepsis as a comorbidity to β-coronavirus infection. We then used low-dose infection as an immunological priming event in C3H/HeJ mice, which provided neutralizing Ab-dependent, but not circulating CD4/CD8 T cell-dependent, protection against a high-dose MHV-1 early rechallenge. Together, these data define how infection dose, immunological status, and comorbidities modulate outcomes of primary and secondary β-coronavirus infections in hosts with variable susceptibility.
Collapse
Affiliation(s)
- Elvia E Silva
- Department of Pathology, University of Iowa, Iowa City, IA
- Interdisciplinary Program in Immunology, University of Iowa, Iowa City, IA
| | | | - Mariah Hassert
- Department of Pathology, University of Iowa, Iowa City, IA
| | - Roger R Berton
- Department of Pathology, University of Iowa, Iowa City, IA
- Interdisciplinary Program in Immunology, University of Iowa, Iowa City, IA
| | - Matthew G Smith
- Department of Pathology, University of Iowa, Iowa City, IA
- Interdisciplinary Program in Immunology, University of Iowa, Iowa City, IA
| | | | | | - Thomas S Griffith
- Department of Urology, University of Minnesota, Minneapolis, MN
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN
| | - John T Harty
- Department of Pathology, University of Iowa, Iowa City, IA
- Interdisciplinary Program in Immunology, University of Iowa, Iowa City, IA
| | - Vladimir P Badovinac
- Department of Pathology, University of Iowa, Iowa City, IA
- Interdisciplinary Program in Immunology, University of Iowa, Iowa City, IA
| |
Collapse
|
2
|
Cao Q, Du X, Jiang XY, Tian Y, Gao CH, Liu ZY, Xu T, Tao XX, Lei M, Wang XQ, Ye LL, Duan DD. Phenome-wide association study and precision medicine of cardiovascular diseases in the post-COVID-19 era. Acta Pharmacol Sin 2023; 44:2347-2357. [PMID: 37532784 PMCID: PMC10692238 DOI: 10.1038/s41401-023-01119-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 05/29/2023] [Indexed: 08/04/2023] Open
Abstract
SARS-CoV-2 infection causes injuries of not only the lungs but also the heart and endothelial cells in vasculature of multiple organs, and induces systemic inflammation and immune over-reactions, which makes COVID-19 a disease phenome that simultaneously affects multiple systems. Cardiovascular diseases (CVD) are intrinsic risk and causative factors for severe COVID-19 comorbidities and death. The wide-spread infection and reinfection of SARS-CoV-2 variants and the long-COVID may become a new common threat to human health and propose unprecedented impact on the risk factors, pathophysiology, and pharmacology of many diseases including CVD for a long time. COVID-19 has highlighted the urgent demand for precision medicine which needs new knowledge network to innovate disease taxonomy for more precise diagnosis, therapy, and prevention of disease. A deeper understanding of CVD in the setting of COVID-19 phenome requires a paradigm shift from the current phenotypic study that focuses on the virus or individual symptoms to phenomics of COVID-19 that addresses the inter-connectedness of clinical phenotypes, i.e., clinical phenome. Here, we summarize the CVD manifestations in the full clinical spectrum of COVID-19, and the phenome-wide association study of CVD interrelated to COVID-19. We discuss the underlying biology for CVD in the COVID-19 phenome and the concept of precision medicine with new phenomic taxonomy that addresses the overall pathophysiological responses of the body to the SARS-CoV-2 infection. We also briefly discuss the unique taxonomy of disease as Zheng-hou patterns in traditional Chinese medicine, and their potential implications in precision medicine of CVD in the post-COVID-19 era.
Collapse
Affiliation(s)
- Qian Cao
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Xin Du
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Xiao-Yan Jiang
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Yuan Tian
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Chen-Hao Gao
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Zi-Yu Liu
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Ting Xu
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Xing-Xing Tao
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Ming Lei
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Xiao-Qiang Wang
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China
| | - Lingyu Linda Ye
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
- Institute of Integrated Chinese and Western Medicine, Southwest Medical University, Luzhou, 646000, China.
- Key Laboratory of Autoimmune Diseases and Precision Medicie, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, 750001, China.
| | - Dayue Darrel Duan
- Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
- Institute of Integrated Chinese and Western Medicine, Southwest Medical University, Luzhou, 646000, China.
- Key Laboratory of Autoimmune Diseases and Precision Medicie, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, 750001, China.
- The Department of Pharmacology, University of Nevada Reno School of Medicine, Reno, NV, 89557, USA.
| |
Collapse
|
3
|
Whitbourne SB, Moser J, Cho K, Deen J, Churby LL, Justice AC, Casas JP, Pyarajan S, Tsao PS, Gaziano JM, Muralidhar S. Leveraging the Million Veteran Program Infrastructure and Data for a Rapid Research Response to COVID-19. Fed Pract 2023; 40:S23-S28. [PMID: 38577307 PMCID: PMC10988626 DOI: 10.12788/fp.0416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
Background The Veterans Health Administration Office of Research and Development (ORD) played a key role in the federal government's response to the COVID-19 pandemic. The ORD effectively leveraged existing resources to answer questions related to the SARS-CoV-2 virus and COVID-19. Observations When the COVID-19 pandemic hit in 2020, the Million Veteran Program (MVP), one of the largest genomic cohorts in the world, extended the centralized recruitment and enrollment infrastructure to develop a COVID-19 research volunteer registry to assist enrollment in the vaccine and treatment trials in which the US Department of Veterans Affairs (VA) participated. In addition, the MVP allowed for new data collection and a large genomic cohort to understand host contributions to COVID-19. This article describes ways the MVP contributed to the VA's rapid research response to COVID-19. Several host genetic factors believed to play a role in the development and severity of COVID-19 were identified. Furthermore, existing MVP partnerships with other federal agencies, particularly with the Department of Energy, were leveraged to improve understanding and management of COVID-19. Conclusions A previously established enterprise approach and research infrastructure were essential to the VA's successful and timely COVID-19 research response. This infrastructure not only supported rapid recruitment in vaccine and treatment trials, but also leveraged the unique MVP and VA electronic health record data to drive rapid scientific discovery and inform clinical operations. Extending the models that VA research applied to the federal government at large and establishing centralized resources for shared or federated data analyses across federal agencies will better equip the nation to respond to future public health crises.
Collapse
Affiliation(s)
- Stacey B. Whitbourne
- Veterans Affairs Boston Healthcare System, Massachusetts
- Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jennifer Moser
- Office of Research and Development, Department of Veterans Affairs, Washington, DC
| | - Kelly Cho
- Veterans Affairs Boston Healthcare System, Massachusetts
- Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jennifer Deen
- Office of Research and Development, Department of Veterans Affairs, Washington, DC
| | - Lori L. Churby
- Veterans Affairs Palo Alto Healthcare System, California
| | - Amy C. Justice
- Veterans Affairs Connecticut Healthcare System, West Haven
- Yale University School of Medicine and School of Public Health, New Haven, Connecticut
| | - Juan P. Casas
- Novartis Institute for Biomedical Research, Cambridge, Massachusetts
| | - Saiju Pyarajan
- Veterans Affairs Boston Healthcare System, Massachusetts
| | - Phil S. Tsao
- Veterans Affairs Palo Alto Healthcare System, California
- Stanford University School of Medicine, Palo Alto, California
| | - J. Michael Gaziano
- Veterans Affairs Boston Healthcare System, Massachusetts
- Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC
| |
Collapse
|
4
|
Nealon CL, Halladay CW, Gorman BR, Simpson P, Roncone DP, Canania RL, Anthony SA, Rogers LRS, Leber JN, Dougherty JM, Bailey JNC, Crawford DC, Sullivan JM, Galor A, Wu WC, Greenberg PB, Lass JH, Iyengar SK, Peachey NS. Association Between Fuchs Endothelial Corneal Dystrophy, Diabetes Mellitus, and Multimorbidity. Cornea 2023; 42:1140-1149. [PMID: 37170406 PMCID: PMC10523841 DOI: 10.1097/ico.0000000000003311] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/11/2023] [Indexed: 05/13/2023]
Abstract
PURPOSE The aim of this study was to assess risk for demographic variables and other health conditions that are associated with Fuchs endothelial corneal dystrophy (FECD). METHODS We developed a FECD case-control algorithm based on structured electronic health record data and confirmed accuracy by individual review of charts at 3 Veterans Affairs (VA) Medical Centers. This algorithm was applied to the Department of VA Million Veteran Program cohort from whom sex, genetic ancestry, comorbidities, diagnostic phecodes, and laboratory values were extracted. Single-variable and multiple variable logistic regression models were used to determine the association of these risk factors with FECD diagnosis. RESULTS Being a FECD case was associated with female sex, European genetic ancestry, and a greater number of comorbidities. Of 1417 diagnostic phecodes evaluated, 213 had a significant association with FECD, falling in both ocular and nonocular conditions, including diabetes mellitus (DM). Five of 69 laboratory values were associated with FECD, with the direction of change for 4 being consistent with DM. Insulin dependency and type 1 DM raised risk to a greater degree than type 2 DM, like other microvascular diabetic complications. CONCLUSIONS Female sex, European ancestry, and multimorbidity increased FECD risk. Endocrine/metabolic clinic encounter codes and altered patterns of laboratory values support DM increasing FECD risk. Our results evoke a threshold model in which the FECD phenotype is intensified by DM and potentially other health conditions that alter corneal physiology. Further studies to better understand the relationship between FECD and DM are indicated and may help identify opportunities for slowing FECD progression.
Collapse
Affiliation(s)
- Cari L. Nealon
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Christopher W. Halladay
- Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, Rhode Island, USA
| | - Bryan R. Gorman
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, Massachusetts
- Booz Allen Hamilton, McLean, Virginia, USA
| | - Piana Simpson
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - David P. Roncone
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | | | - Scott A. Anthony
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | | | - Jenna N. Leber
- Ophthalmology Section, VA Western NY Health Care System, Buffalo, New York, USA
| | | | - Jessica N. Cooke Bailey
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Dana C. Crawford
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Jack M. Sullivan
- Ophthalmology Section, VA Western NY Health Care System, Buffalo, New York, USA
- Research Service, VA Western NY Health Care System, Buffalo, New York, USA
- Department of Ophthalmology (Ross Eye Institute), University at Buffalo-SUNY, Buffalo, New York, USA
| | - Anat Galor
- Miami Veterans Affairs Medical Center, Miami, Florida, USA
- Bascom Palmer Eye Institute, University of Miami, Miami, Florida, USA
| | - Wen-Chih Wu
- Cardiology Section, Medical Service, Providence VA Medical Center, Providence, Rhode Island, USA
| | - Paul B. Greenberg
- Ophthalmology Section, Providence VA Medical Center, Providence, Rhode Island, USA
- Division of Ophthalmology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | | | - Jonathan H. Lass
- Department of Ophthalmology & Visual Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- University Hospitals Eye Institute, Cleveland, Ohio, USA
| | - Sudha K. Iyengar
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Neal S. Peachey
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
- Cole Eye Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA
- Department of Ophthalmology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio, USA
| |
Collapse
|
5
|
Irizar P, Pan D, Kapadia D, Bécares L, Sze S, Taylor H, Amele S, Kibuchi E, Divall P, Gray LJ, Nellums LB, Katikireddi SV, Pareek M. Ethnic inequalities in COVID-19 infection, hospitalisation, intensive care admission, and death: a global systematic review and meta-analysis of over 200 million study participants. EClinicalMedicine 2023; 57:101877. [PMID: 36969795 PMCID: PMC9986034 DOI: 10.1016/j.eclinm.2023.101877] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 02/02/2023] [Accepted: 02/02/2023] [Indexed: 03/08/2023] Open
Abstract
Background COVID-19 has exacerbated existing ethnic inequalities in health. Little is known about whether inequalities in severe disease and deaths, observed globally among minoritised ethnic groups, relates to greater infection risk, poorer prognosis, or both. We analysed global data on COVID-19 clinical outcomes examining inequalities between people from minoritised ethnic groups compared to the ethnic majority group. Methods Databases (MEDLINE, EMBASE, EMCARE, CINAHL, Cochrane Library) were searched from 1st December 2019 to 3rd October 2022, for studies reporting original clinical data for COVID-19 outcomes disaggregated by ethnicity: infection, hospitalisation, intensive care unit (ICU) admission, and mortality. We assessed inequalities in incidence and prognosis using random-effects meta-analyses, with Grading of Recommendations Assessment, Development, and Evaluation (GRADE) use to assess certainty of findings. Meta-regressions explored the impact of region and time-frame (vaccine roll-out) on heterogeneity. PROSPERO: CRD42021284981. Findings 77 studies comprising over 200,000,000 participants were included. Compared with White majority populations, we observed an increased risk of testing positive for infection for people from Black (adjusted Risk Ratio [aRR]:1.78, 95% CI:1.59-1.99, I2 = 99.1), South Asian (aRR:3.00, 95% CI:1.59-5.66, I2 = 99.1), Mixed (aRR:1.64, 95% CI:1.02-1.67, I2 = 93.2) and Other ethnic groups (aRR:1.36, 95% CI:1.01-1.82, I2 = 85.6). Black, Hispanic, and South Asian people were more likely to be seropositive. Among population-based studies, Black and Hispanic ethnic groups and Indigenous peoples had an increased risk of hospitalisation; Black, Hispanic, South Asian, East Asian and Mixed ethnic groups and Indigenous peoples had an increased risk of ICU admission. Mortality risk was increased for Hispanic, Mixed, and Indigenous groups. Smaller differences were seen for prognosis following infection. Following hospitalisation, South Asian, East Asian, Black and Mixed ethnic groups had an increased risk of ICU admission, and mortality risk was greater in Mixed ethnic groups. Certainty of evidence ranged from very low to moderate. Interpretation Our study suggests that systematic ethnic inequalities in COVID-19 health outcomes exist, with large differences in exposure risk and some differences in prognosis following hospitalisation. Response and recovery interventions must focus on tackling drivers of ethnic inequalities which increase exposure risk and vulnerabilities to severe disease, including structural racism and racial discrimination. Funding ESRC:ES/W000849/1.
Collapse
Affiliation(s)
- Patricia Irizar
- School of Social Sciences, University of Manchester, United Kingdom
| | - Daniel Pan
- Department of Respiratory Sciences, University of Leicester, United Kingdom
- Department of Infection and HIV Medicine, University Hospitals Leicester NHS Trust, United Kingdom
- Li Ka Shing Centre for Health Information and Discovery, Oxford Big Data Institute, University of Oxford, United Kingdom
- NIHR Leicester Biomedical Research Centre, United Kingdom
| | - Dharmi Kapadia
- School of Social Sciences, University of Manchester, United Kingdom
| | - Laia Bécares
- Department of Global Health and Social Medicine, King's College London, United Kingdom
| | - Shirley Sze
- Department of Cardiovascular Sciences, University of Leicester, United Kingdom
| | - Harry Taylor
- School of Social Sciences, University of Manchester, United Kingdom
| | - Sarah Amele
- MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, United Kingdom
| | - Eliud Kibuchi
- MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, United Kingdom
| | - Pip Divall
- University Hospitals of Leicester, Education Centre Library, Glenfield Hospital and Leicester Royal Infirmary, United Kingdom
| | - Laura J Gray
- Department of Health Sciences, University of Leicester, United Kingdom
| | - Laura B Nellums
- Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, United Kingdom
| | | | - Manish Pareek
- Department of Respiratory Sciences, University of Leicester, United Kingdom
- Department of Infection and HIV Medicine, University Hospitals Leicester NHS Trust, United Kingdom
- NIHR Leicester Biomedical Research Centre, United Kingdom
| |
Collapse
|
6
|
Nguyen XMT, Whitbourne SB, Li Y, Quaden RM, Song RJ, Nguyen HNA, Harrington K, Djousse L, Brewer JVV, Deen J, Muralidhar S, Ramoni RB, Cho K, Casas JP, Tsao PS, Gaziano JM. Data Resource Profile: Self-reported data in the Million Veteran Program: survey development and insights from the first 850 736 participants. Int J Epidemiol 2023; 52:e1-e17. [PMID: 35748351 DOI: 10.1093/ije/dyac133] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/09/2022] [Indexed: 12/12/2022] Open
Affiliation(s)
- Xuan-Mai T Nguyen
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.,Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Champaign, IL, USA
| | - Stacey B Whitbourne
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | - Yanping Li
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Rachel M Quaden
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Rebecca J Song
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Hai-Nam A Nguyen
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Kelly Harrington
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Luc Djousse
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.,New England Geriatric Research, Education, and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
| | - Jessica V V Brewer
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Jennifer Deen
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Rachel B Ramoni
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | - Philip S Tsao
- VA Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - John M Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | | |
Collapse
|
7
|
Harley JB, Pyarajan S, Partan ES, Epstein L, Wertheim JA, Diwan A, Woods CW, Davey V, Blair S, Clark DH, Kaufman KM, Khan S, Chepelev I, Devine A, Cameron P, McCann MF, Ammons MCB, Bolz DD, Battles JK, Curtis JL, Holodniy M, Marconi VC, Searles CD, Beenhouwer DO, Brown ST, Moorman JP, Yao ZQ, Rodriguez-Barradas MC, Mohapatra S, Molina De Rodriguez OY, Padiernos EB, McIndoo ER, Price E, Burgoyne HM, Robey I, Schwenke DC, Shive CL, Przygodzki RM, Ramoni RB, Krull HK, Bonomo RA. The US Department of Veterans Affairs Science and Health Initiative to Combat Infectious and Emerging Life-Threatening Diseases (VA SHIELD): A Biorepository Addressing National Health Threats. Open Forum Infect Dis 2022; 9:ofac641. [PMID: 36601554 PMCID: PMC9801224 DOI: 10.1093/ofid/ofac641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Indexed: 12/15/2022] Open
Abstract
Background The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has demonstrated the need to share data and biospecimens broadly to optimize clinical outcomes for US military Veterans. Methods In response, the Veterans Health Administration established VA SHIELD (Science and Health Initiative to Combat Infectious and Emerging Life-threatening Diseases), a comprehensive biorepository of specimens and clinical data from affected Veterans to advance research and public health surveillance and to improve diagnostic and therapeutic capabilities. Results VA SHIELD now comprises 12 sites collecting de-identified biospecimens from US Veterans affected by SARS-CoV-2. In addition, 2 biorepository sites, a data processing center, and a coordinating center have been established under the direction of the Veterans Affairs Office of Research and Development. Phase 1 of VA SHIELD comprises 34 157 samples. Of these, 83.8% had positive tests for SARS-CoV-2, with the remainder serving as contemporaneous controls. The samples include nasopharyngeal swabs (57.9%), plasma (27.9%), and sera (12.5%). The associated clinical and demographic information available permits the evaluation of biological data in the context of patient demographics, clinical experience and management, vaccinations, and comorbidities. Conclusions VA SHIELD is representative of US national diversity with a significant potential to impact national healthcare. VA SHIELD will support future projects designed to better understand SARS-CoV-2 and other emergent healthcare crises. To the extent possible, VA SHIELD will facilitate the discovery of diagnostics and therapeutics intended to diminish COVID-19 morbidity and mortality and to reduce the impact of new emerging threats to the health of US Veterans and populations worldwide.
Collapse
Affiliation(s)
- John B Harley
- Correspondence: John B. Harley, Cincinnati VA Medical Center, 3200 Vine St., John B. Harley (151), Cincinnati, OH 45220 ()
| | - Saiju Pyarajan
- Center for Data and Computational Sciences, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA
| | - Elizabeth S Partan
- Center for Data and Computational Sciences, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA
| | - Lauren Epstein
- Infectious Diseases, US Department of Veterans Affairs Medical Center, Atlanta, Georgia, USA
| | - Jason A Wertheim
- Research & Development, Southern Arizona Veterans Affairs Healthcare System, US Department of Veterans Affairs, Tucson, Arizona, USA
| | - Abhinav Diwan
- Cardiology, Veterans Affairs Saint Louis Healthcare System, US Department of Veterans Affairs,Saint Louis, Missouri, USA
| | - Christopher W Woods
- Medicine, US Department of Veterans Affairs Medical Center, Durham, North Carolina, USA
| | - Victoria Davey
- Office of Research and Development, US Department of Veterans Affairs, Washington, District of Columbia, USA
| | - Sharlene Blair
- Research Services, US Department of Veterans Affairs Medical Center, Cincinnati, Ohio, USA
| | - Dennis H Clark
- Research Services, US Department of Veterans Affairs Medical Center, Cincinnati, Ohio, USA
| | - Kenneth M Kaufman
- Research Services, US Department of Veterans Affairs Medical Center, Cincinnati, Ohio, USA
| | - Shagufta Khan
- Research Services, US Department of Veterans Affairs Medical Center, Cincinnati, Ohio, USA
| | - Iouri Chepelev
- Research Services, US Department of Veterans Affairs Medical Center, Cincinnati, Ohio, USA
| | - Alexander Devine
- Prometheus Federal Services, Titan Alpha, Washington, District of Columbia, USA
| | - Perry Cameron
- Customer Value Partners, Titan Alpha, Washington, District of Columbia, USA
| | - Monica F McCann
- Office of Research and Development, Chesapeake Medical Communications, Contractor for the US Department of Veterans Affairs, Washington, District of Columbia, USA
| | - Mary Cloud B Ammons
- Research, US Department of Veterans Affairs Medical Center, Boise, Idaho, USA,Idaho Veterans Research and Education Foundation, Boise, Idaho, USA
| | - Devin D Bolz
- Research, US Department of Veterans Affairs Medical Center, Boise, Idaho, USA
| | - Jane K Battles
- Office of Research and Development, US Department of Veterans Affairs, Washington, District of Columbia, USA
| | - Jeffrey L Curtis
- Medicine Service, Veteran Affairs Ann Arbor Healthcare System, US Department of Veterans Affairs, Ann Arbor, Michigan, USA
| | - Mark Holodniy
- Public Health Surveillance, Veterans Affairs Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, California, USA
| | - Vincent C Marconi
- Infectious Diseases, US Department of Veterans Affairs Medical Center, Atlanta, Georgia, USA,Division of Infectious Diseases, Emory School of Medicine and Rollins School of Public Health, Atlanta, Georgia, USA
| | - Charles D Searles
- Infectious Diseases, US Department of Veterans Affairs Medical Center, Atlanta, Georgia, USA
| | - David O Beenhouwer
- Medicine, Veterans Affairs Greater Los Angeles Healthcare System, US Department of Veterans Affairs, Los Angeles, California, USA
| | - Sheldon T Brown
- Infectious Diseases, James J. Peters Veterans Affairs Medical Center, US Department of Veterans Affairs, Bronx, New York, USA
| | - Jonathan P Moorman
- Infectious Diseases, James H. Quillen Veterans Affairs Medical Center, US Department of Veterans Affairs, Mountain Home, Tennessee, USA,Center of Excellence in Inflammation, Infectious Diseases, and Immunity, East Tennessee State University, Johnson City, Tennessee, USA
| | - Zhi Q Yao
- Infectious Diseases, James H. Quillen Veterans Affairs Medical Center, US Department of Veterans Affairs, Mountain Home, Tennessee, USA,Center of Excellence in Inflammation, Infectious Diseases, and Immunity, East Tennessee State University, Johnson City, Tennessee, USA
| | - Maria C Rodriguez-Barradas
- Infectious Diseases Section, Michael E. DeBakey Veterans Affairs Medical Center, US Department of Veterans Affairs, Houston, Texas, USA,Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Shyam Mohapatra
- Medicine, James A. Haley Veterans Hospital, US Department of Veterans Affairs, Tampa, Florida, USA
| | - Osmara Y Molina De Rodriguez
- Research & Development, Southern Arizona Veterans Affairs Healthcare System, US Department of Veterans Affairs, Tucson, Arizona, USA
| | - Emerson B Padiernos
- Research, US Department of Veterans Affairs Medical Center, Boise, Idaho, USA
| | - Eric R McIndoo
- Research, US Department of Veterans Affairs Medical Center, Boise, Idaho, USA,Idaho Veterans Research and Education Foundation, Boise, Idaho, USA
| | - Emily Price
- Research, US Department of Veterans Affairs Medical Center, Boise, Idaho, USA,Idaho Veterans Research and Education Foundation, Boise, Idaho, USA
| | - Hailey M Burgoyne
- Research, US Department of Veterans Affairs Medical Center, Boise, Idaho, USA,Idaho Veterans Research and Education Foundation, Boise, Idaho, USA
| | - Ian Robey
- Research & Development, Southern Arizona Veterans Affairs Healthcare System, US Department of Veterans Affairs, Tucson, Arizona, USA
| | - Dawn C Schwenke
- Research & Development, Southern Arizona Veterans Affairs Healthcare System, US Department of Veterans Affairs, Tucson, Arizona, USA
| | - Carey L Shive
- Medicine, Veterans Affairs Northeast Ohio Healthcare System, US Department of Veterans Affairs, Cleveland, Ohio, USA
| | - Ronald M Przygodzki
- Office of Research and Development, US Department of Veterans Affairs, Washington, District of Columbia, USA
| | - Rachel B Ramoni
- Office of Research and Development, US Department of Veterans Affairs, Washington, District of Columbia, USA
| | | | | |
Collapse
|
8
|
Haupert SR, Shi X, Chen C, Fritsche LG, Mukherjee B. A Case-Crossover Phenome-wide association study (PheWAS) for understanding Post-COVID-19 diagnosis patterns. J Biomed Inform 2022; 136:104237. [PMID: 36283580 PMCID: PMC9595430 DOI: 10.1016/j.jbi.2022.104237] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/30/2022] [Accepted: 10/19/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND Post COVID-19 condition (PCC) is known to affect a large proportion of COVID-19 survivors. Robust study design and methods are needed to understand post-COVID-19 diagnosis patterns in all survivors, not just those clinically diagnosed with PCC. METHODS We applied a case-crossover Phenome-Wide Association Study (PheWAS) in a retrospective cohort of COVID-19 survivors, comparing the occurrences of 1,671 diagnosis-based phenotype codes (PheCodes) pre- and post-COVID-19 infection periods in the same individual using a conditional logistic regression. We studied how this pattern varied by COVID-19 severity and vaccination status, and we compared to test negative and test negative but flu positive controls. RESULTS In 44,198 SARS-CoV-2-positive patients, we foundenrichment in respiratory,circulatory, and mental health disorders post-COVID-19-infection. Top hits included anxiety disorder (p = 2.8e-109, OR = 1.7 [95 % CI: 1.6-1.8]), cardiac dysrhythmias (p = 4.9e-87, OR = 1.7 [95 % CI: 1.6-1.8]), and respiratory failure, insufficiency, arrest (p = 5.2e-75, OR = 2.9 [95 % CI: 2.6-3.3]). In severe patients, we found stronger associations with respiratory and circulatory disorders compared to mild/moderate patients. Fully vaccinated patients had mental health and chronic circulatory diseases rise to the top of the association list, similar to the mild/moderate cohort. Both control groups (test negative, test negative and flu positive) showed a different pattern of hits to SARS-CoV-2 positives. CONCLUSIONS Patients experience myriad symptoms more than 28 days after SARS-CoV-2 infection, but especially respiratory, circulatory, and mental health disorders. Our case-crossover PheWAS approach controls for within-person confounders that are time-invariant. Comparison to test negatives and test negative but flu positive patients with a similar design helped identify enrichment specific to COVID-19. This design may be applied other emerging diseases with long-lasting effects other than a SARS-CoV-2 infection. Given the potential for bias from observational data, these results should be considered exploratory. As we look into the future, we must be aware of COVID-19 survivors' healthcare needs.
Collapse
Affiliation(s)
- Spencer R Haupert
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Xu Shi
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Chen Chen
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Lars G Fritsche
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
| |
Collapse
|
9
|
Hung TY, Liu KL, Wen SH. Using the Phecode System to Identify the Preoperative Clinical Phenotypes Associated with Surgical Site Infection in Patients Undergoing Primary Total Knee Arthroplasty: The Sex Differences. J Clin Med 2022; 11:5784. [PMID: 36233652 PMCID: PMC9573756 DOI: 10.3390/jcm11195784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 09/27/2022] [Accepted: 09/27/2022] [Indexed: 11/17/2022] Open
Abstract
Sex-related differences among comorbid conditions associated with surgical site infection (SSI) after total knee arthroplasty (TKA) are unclear. This population-based cohort study used a novel approach with a Phecode system to evaluate preoperative clinical phenotypes (i.e., comorbid conditions) associated with SSI after TKA and delineate sex-related differences in phenotypes. Using the Taiwan National Health Insurance Research Database (2014-2018), 83,870 patients who underwent TKA were identified. Demographic and SSI data during the 90-day postoperative follow-up were obtained. Comorbidities identified by the International Classification of Diseases within 1 year before TKA were recorded and mapped into Phecodes representing phenotypes. The overall rate of 90-day SSI was 1.3%. In total, 1663 phenotypes were identified among 83,870 patients-1585 and 1458 phenotypes for female (n = 62,018) and male (n = 21,852) patients, respectively. According to multivariate logistic regression analysis, the SSI odds ratio significantly increased with the presence of each of the 16 phenotypes. Subgroup analysis revealed that the presence of 10 and 4 phenotypes significantly increased SSI risk in both sexes; only one phenotype was common to both sexes. Therefore, comorbid conditions and sex should be considered in preoperative SSI risk evaluation in patients undergoing primary TKA. These findings provide new perspectives on susceptibility, prevention, and treatment in these patients.
Collapse
Affiliation(s)
- Ting-Yu Hung
- Sports Medicine Center, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970473, Taiwan
- Department of Orthopedics, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970473, Taiwan
| | - Kuan-Lin Liu
- Sports Medicine Center, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970473, Taiwan
- Department of Orthopedics, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970473, Taiwan
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
| | - Shu-Hui Wen
- Department of Public Health, College of Medicine, Tzu Chi University, Hualien 97004, Taiwan
| |
Collapse
|
10
|
Verma A, Huffman JE, Gao L, Minnier J, Wu WC, Cho K, Ho YL, Gorman BR, Pyarajan S, Rajeevan N, Garcon H, Joseph J, McGeary JE, Suzuki A, Reaven PD, Wan ES, Lynch JA, Petersen JM, Meigs JB, Freiberg MS, Gatsby E, Lynch KE, Zekavat SM, Natarajan P, Dalal S, Jhala DN, Arjomandi M, Bonomo RA, Thompson TK, Pathak GA, Zhou JJ, Donskey CJ, Madduri RK, Wells QS, Gelernter J, Huang RDL, Polimanti R, Chang KM, Liao KP, Tsao PS, Sun YV, Wilson PWF, O’Donnell CJ, Hung AM, Gaziano JM, Hauger RL, Iyengar SK, Luoh SW. Association of Kidney Comorbidities and Acute Kidney Failure With Unfavorable Outcomes After COVID-19 in Individuals With the Sickle Cell Trait. JAMA Intern Med 2022; 182:796-804. [PMID: 35759254 PMCID: PMC9237798 DOI: 10.1001/jamainternmed.2022.2141] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Importance Sickle cell trait (SCT), defined as the presence of 1 hemoglobin beta sickle allele (rs334-T) and 1 normal beta allele, is prevalent in millions of people in the US, particularly in individuals of African and Hispanic ancestry. However, the association of SCT with COVID-19 is unclear. Objective To assess the association of SCT with the prepandemic health conditions in participants of the Million Veteran Program (MVP) and to assess the severity and sequelae of COVID-19. Design, Setting, and Participants COVID-19 clinical data include 2729 persons with SCT, of whom 353 had COVID-19, and 129 848 SCT-negative individuals, of whom 13 488 had COVID-19. Associations between SCT and COVID-19 outcomes were examined using firth regression. Analyses were performed by ancestry and adjusted for sex, age, age squared, and ancestral principal components to account for population stratification. Data for the study were collected between March 2020 and February 2021. Exposures The hemoglobin beta S (HbS) allele (rs334-T). Main Outcomes and Measures This study evaluated 4 COVID-19 outcomes derived from the World Health Organization severity scale and phenotypes derived from International Classification of Diseases codes in the electronic health records. Results Of the 132 577 MVP participants with COVID-19 data, mean (SD) age at the index date was 64.8 (13.1) years. Sickle cell trait was present in 7.8% of individuals of African ancestry and associated with a history of chronic kidney disease, diabetic kidney disease, hypertensive kidney disease, pulmonary embolism, and cerebrovascular disease. Among the 4 clinical outcomes of COVID-19, SCT was associated with an increased COVID-19 mortality in individuals of African ancestry (n = 3749; odds ratio, 1.77; 95% CI, 1.13 to 2.77; P = .01). In the 60 days following COVID-19, SCT was associated with an increased incidence of acute kidney failure. A counterfactual mediation framework estimated that on average, 20.7% (95% CI, -3.8% to 56.0%) of the total effect of SCT on COVID-19 fatalities was due to acute kidney failure. Conclusions and Relevance In this genetic association study, SCT was associated with preexisting kidney comorbidities, increased COVID-19 mortality, and kidney morbidity.
Collapse
Affiliation(s)
- Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
| | | | - Lina Gao
- Knight Cancer Institute, Biostatistics Shared Resource, Oregon Health & Science University, Portland
- VA Portland Health Care System, Portland, Oregon
| | - Jessica Minnier
- VA Portland Health Care System, Portland, Oregon
- OHSU-PSU School of Public Health, Oregon Health & Science University, Portland
- Knight Cancer Institute, Biostatistics Shared Resource, Oregon Health & Science University, Portland
| | - Wen-Chih Wu
- Department of Medicine, Cardiology, Providence VA Healthcare System, Providence, Rhode Island
- Alpert Medical School & School of Public Health, Brown University, Providence, Rhode Island
| | - Kelly Cho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
- Medicine, Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Yuk-Lam Ho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
| | | | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Nallakkandi Rajeevan
- Yale Center for Medical Informatics, Yale School of Medicine, New Haven, Connecticut
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven
| | - Helene Garcon
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
| | - Jacob Joseph
- Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts
- Brigham & Women’s Hospital, Boston, Massachusetts
| | - John E. McGeary
- Department of Psychiatry and Human Behavior, Providence VA Medical Center, Providence, Rhode Island
- Brown University Medical School, Providence, Rhode Island
| | - Ayako Suzuki
- Department of Medicine, Gastroenterology, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Gastroenterology, Duke University, Durham, North Carolina
| | - Peter D. Reaven
- Department of Medicine, Phoenix VA Healthcare System, Phoenix, Arizona
- University of Arizona, Phoenix
| | - Emily S. Wan
- Department of Medicine, Pulmonary, Critical Care, Sleep, and Allergy Section, VA Boston Healthcare System, Boston, Massachusetts
- Channing Division of Network Medicine, Brigham & Women’s Hospital, Boston, Massachusetts
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure, VA Salt Lake City Utah & University of Utah, School of Medicine, Salt Lake City
| | - Jeffrey M. Petersen
- Pathology and Laboratory Medicine, Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - James B. Meigs
- Medicine, General Internal Medicine, Massachusetts General Hospital, Boston
| | | | - Elise Gatsby
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Kristine E. Lynch
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
- Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City
| | - Seyedeh Maryam Zekavat
- Computational Biology & Bioinformatics, Yale School of Medicine, New Haven, Connecticut
- Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Clinical Data Science Research Group, ORD, Portland VA Medical Center, Portland, Oregon
| | - Sharvari Dalal
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Pathology and Laboratory Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Darshana N. Jhala
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Pathology and Laboratory Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Mehrdad Arjomandi
- Medicine, Pulmonary and Critical Care, San Francisco VA Healthcare System, San Francisco, California
- University of California San Francisco
| | - Robert A. Bonomo
- Cleveland VA Medical Center, Cleveland, Ohio
- Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | | | - Gita A. Pathak
- Department of Psychiatry, Division of Human Genetics, Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare System, West Haven
| | - Jin J. Zhou
- Medicine, University of California, Los Angeles
- Epidemiology and Biostatistics, University of Arizona, Phoenix
| | - Curtis J. Donskey
- Infectious Disease Section, Louis Stokes Cleveland VA, Cleveland, Ohio
- Case Western Reserve University, Cleveland, Ohio
| | - Ravi K. Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, Illinois
| | - Quinn S. Wells
- Departments of Medicine, Biomedical Informatics, and Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Joel Gelernter
- VA Connecticut Healthcare System, West Haven
- Psychiatry, Human Genetics, Yale University School of Medicine, West Haven, Connecticut
| | | | - Renato Polimanti
- Departments of Medicine, Biomedical Informatics, and Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
- Psychiatry, Human Genetics, Yale University School of Medicine, West Haven, Connecticut
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Katherine P. Liao
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, Massachusetts
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Medicine & Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Philip S. Tsao
- Precision Medicine, VA Palo Alto Health Care System, Palo Alto, California
| | - Yan V. Sun
- Epidemiology, Emory University School of Public Health, Atlanta, Georgia
- Atlanta VA Health Care System, Decatur, Georgia
| | - Peter W. F. Wilson
- Atlanta VA Health Care System, Decatur, Georgia
- Emory University School of Medicine, Atlanta, Georgia
| | | | - Adriana M. Hung
- Vanderbilt University Medical Center, Nashville, Tennessee
- Nashville VA Medical Center, Nashville, Tennessee
| | - J. Michael Gaziano
- VA Boston Health Care System, Boston, Massachusetts
- Medicine, Harvard Medical School, Boston, Massachusetts
| | - Richard L. Hauger
- Center of Excellence for Stress & Mental Health, VA San Diego Healthcare System, San Diego, California
- Center for Behavioral Genetics of Aging, University of California, San Diego, La Jolla
| | - Sudha K. Iyengar
- Departments of Population and Quantitative Health Sciences, Ophthalmology and Visual Sciences and Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio
- Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, Oregon
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland
| |
Collapse
|
11
|
Tuteja S, Yu Z, Wilson O, Chen H, Wendt F, Chung CP, Shah SC, Hunt CM, Suzuki A, Chanfreau C, Gorman BR, Joseph J, Luoh S, Napolioni V, Robinson‐Cohen C, Tao R, Zhou J, Chang K, Hung AM. Pharmacogenetic variants and risk of remdesivir-associated liver enzyme elevations in Million Veteran Program participants hospitalized with COVID-19. Clin Transl Sci 2022; 15:1880-1886. [PMID: 35684976 PMCID: PMC9347806 DOI: 10.1111/cts.13313] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 05/04/2022] [Accepted: 05/06/2022] [Indexed: 01/17/2023] Open
Abstract
Remdesivir is the first US Food and Drug Administration (FDA)-approved drug for the treatment of coronavirus disease 2019 (COVID-19). We conducted a retrospective pharmacogenetic study to examine remdesivir-associated liver enzyme elevation among Million Veteran Program participants hospitalized with COVID-19 between March 15, 2020, and June 30, 2021. Pharmacogene phenotypes were assigned using Stargazer. Linear regression was performed on peak log-transformed enzyme values, stratified by population, adjusted for age, sex, baseline liver enzymes, comorbidities, and 10 population-specific principal components. Patients on remdesivir had higher peak alanine aminotransferase (ALT) values following treatment initiation compared with patients not receiving remdesivir. Remdesivir administration was associated with a 33% and 24% higher peak ALT in non-Hispanic White (NHW) and non-Hispanic Black (NHB) participants (p < 0.001), respectively. In a multivariable model, NHW CYP2C19 intermediate/poor metabolizers had a 9% increased peak ALT compared with NHW normal/rapid/ultrarapid metabolizers (p = 0.015); this association was not observed in NHB participants. In summary, remdesivir-associated ALT elevations appear to be multifactorial, and further studies are needed.
Collapse
Affiliation(s)
- Sony Tuteja
- Corporal Michael J. Crescenz VA Medical Center and University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Zhihong Yu
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Otis Wilson
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Hua‐Chang Chen
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Frank Wendt
- VA CT Healthcare System and Yale School of Medicine Department of PsychiatryNew HavenConnecticutUSA
| | - Cecilia P. Chung
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Shailja C. Shah
- VA San Diego Healthcare System and Division of GastroenterologyUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Christine M. Hunt
- Durham VA Healthcare System and Duke University School of MedicineDurhamNorth CarolinaUSA
| | - Ayako Suzuki
- Durham VA Healthcare System and Duke University School of MedicineDurhamNorth CarolinaUSA
| | - Catherine Chanfreau
- VA Informatics and Computing Infrastructure (VINCI)VA Salt Lake City Health Care SystemSalt Lake CityUtahUSA
| | | | - Jacob Joseph
- Cardiology Section, VA Boston Healthcare System and Cardiovascular DivisionBrigham & Women's HospitalBostonMassachusettsUSA
| | | | - Valerio Napolioni
- School of Biosciences and Veterinary MedicineUniversity of CamerinoCamerinoItaly,Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Cassianne Robinson‐Cohen
- Division of Nephrology and Hypertension, Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Ran Tao
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jin Zhou
- Department of Epidemiology and BiostatisticsUniversity of ArizonaTucsonArizonaUSA
| | - Kyong‐Mi Chang
- Corporal Michael J. Crescenz VA Medical Center and University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Adriana M. Hung
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | | |
Collapse
|
12
|
Wu Q, Pennini ME, Bergmann JN, Kozak ML, Herring K, Sciarretta KL, Armstrong KL. Applying lessons learned from COVID-19 therapeutic trials to improve future ALI/ARDS trials. Open Forum Infect Dis 2022; 9:ofac381. [PMID: 35983268 PMCID: PMC9379817 DOI: 10.1093/ofid/ofac381] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 07/28/2022] [Indexed: 12/15/2022] Open
Abstract
Host-directed therapeutics targeting immune dysregulation are considered the most promising approach to address the unmet clinical need for acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) related to coronavirus disease 2019 (COVID-19). To better understand the current clinical study landscape and gaps in treating hospitalized patients with severe or critical COVID-19, we identified COVID-19 trials developing host-directed therapies registered at ClinicalTrials.gov and discussed the factors contributing to the success vs failure of these studies. We have learned, instead of the one-size-fits-all approach, future clinical trials evaluating a targeted immunomodulatory agent in heterogeneous patients with ALI/ARDS due to COVID-19 or other infectious diseases can use immune-based biomarkers in addition to clinical and demographic characteristics to improve patient stratification and inform clinical decision-making. Identifying distinct patient subgroups based on immune profiles across the disease trajectory, regardless of the causative pathogen, may accelerate evaluating host-directed therapeutics in trials of ALI/ARDS and related conditions (eg, sepsis).
Collapse
Affiliation(s)
- Qun Wu
- Influenza and Emerging Infectious Diseases Division (IEIDD), Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS) , Washington, DC , United States of America
| | - Meghan E Pennini
- Division of Research Innovation and Ventures (DRIVe), Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS) , Washington, DC , United States of America
| | - Julie N Bergmann
- Division of Chemical Biological Radiological Nuclear (CBRN), Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS) , Washington, DC , United States of America
| | - Marina L Kozak
- Division of Chemical Biological Radiological Nuclear (CBRN), Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS) , Washington, DC , United States of America
| | - Kristen Herring
- Division of Chemical Biological Radiological Nuclear (CBRN), Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS) , Washington, DC , United States of America
| | - Kimberly L Sciarretta
- Division of Research Innovation and Ventures (DRIVe), Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS) , Washington, DC , United States of America
| | - Kimberly L Armstrong
- Influenza and Emerging Infectious Diseases Division (IEIDD), Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS) , Washington, DC , United States of America
| |
Collapse
|
13
|
Whitbourne SB, Nguyen XMT, Song RJ, Lord E, Lyden M, Harrington KM, Ward R, Li Y, Brewer JVV, Cho KM, Djousse L, Muralidhar S, Tsao PS, Gaziano JM, Casas JP. Million Veteran Program's response to COVID-19: Survey development and preliminary findings. PLoS One 2022; 17:e0266381. [PMID: 35468170 PMCID: PMC9037905 DOI: 10.1371/journal.pone.0266381] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 03/18/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND In response to the novel Coronavirus Disease 2019 (COVID-19) pandemic, the Department of Veterans Affairs (VA) Million Veteran Program (MVP) organized efforts to better understand the impact of COVID-19 on Veterans by developing and deploying a self-reported survey. METHODS The MVP COVID-19 Survey was developed to collect COVID-19 specific elements including symptoms, diagnosis, hospitalization, behavioral and psychosocial factors and to augment existing MVP data with longitudinal collection of key domains in physical and mental health. Due to the rapidly evolving nature of the pandemic, a multipronged strategy was implemented to widely disseminate the COVID-19 Survey and capture data using both the online platform and mailings. RESULTS We limited the findings of this paper to the initial phase of survey dissemination which began in May 2020. A total of 729,625 eligible MVP Veterans were invited to complete version 1 of the COVID-19 Survey. As of October 31, 2020, 58,159 surveys have been returned. The mean and standard deviation (SD) age of responders was 71 (11) years, 8.6% were female, 8.2% were Black, 5.6% were Hispanic, and 446 (0.8%) self-reported a COVID-19 diagnosis. Over 90% of responders reported wearing masks, practicing social distancing, and frequent hand washing. CONCLUSION The MVP COVID-19 Survey provides a systematic collection of data regarding COVID-19 behaviors among Veterans and represents one of the first large-scale, national surveillance efforts of COVID-19 in the Veteran population. Continued work will examine the overall response to the survey with comparison to available VA health record data.
Collapse
Affiliation(s)
- Stacey B. Whitbourne
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Xuan-Mai T. Nguyen
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Carle Illinois College of Medicine, University of Illinois, Champaign, IL, United States of America
| | - Rebecca J. Song
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States of America
| | - Emily Lord
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
| | - Michelle Lyden
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
| | - Kelly M. Harrington
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States of America
| | - Rachel Ward
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- New England Geriatric Research, Education, and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, United States of America
| | - Yanping Li
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
| | - Jessica V. V. Brewer
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
| | - Kelly M. Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Luc Djousse
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- New England Geriatric Research, Education, and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, United States of America
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, D.C., United States of America
| | - Philip S. Tsao
- VA Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, Palo Alto, CA, United States of America
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, United States of America
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Juan P. Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
| | | |
Collapse
|
14
|
Chuang YC, Tsai HW, Liu SA, Wu MJ, Liu PY. COVID-19 in Veterans: A Narrative Review. Risk Manag Healthc Policy 2022; 15:805-815. [PMID: 35502442 PMCID: PMC9056054 DOI: 10.2147/rmhp.s354814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 04/09/2022] [Indexed: 01/08/2023] Open
Affiliation(s)
- Yu-Chuan Chuang
- Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Hung-Wen Tsai
- Medical Administration Department, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Shih-An Liu
- Center of Quality Management, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Ming-Ju Wu
- Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Po-Yu Liu
- Division of Infection, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Correspondence: Po-Yu Liu, Division of Infection, Department of Internal Medicine, Taichung Veterans General Hospital, No. 1650, Sec. 4, Taiwan Blvd., Xitun Dist., Taichung City, 407219, Taiwan, Tel +886 4 2359 2525, Email
| |
Collapse
|
15
|
Peloso GM, Tcheandjieu C, McGeary JE, Posner DC, Ho YL, Zhou JJ, Hilliard AT, Joseph J, O’Donnell CJ, Efird JT, Crawford DC, Wu WC, Arjomandi M, Sun YV, Assimes TL, Huffman JE. Genetic Loci Associated With COVID-19 Positivity and Hospitalization in White, Black, and Hispanic Veterans of the VA Million Veteran Program. Front Genet 2022; 12:777076. [PMID: 35222515 PMCID: PMC8864634 DOI: 10.3389/fgene.2021.777076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022] Open
Abstract
SARS-CoV-2 has caused symptomatic COVID-19 and widespread death across the globe. We sought to determine genetic variants contributing to COVID-19 susceptibility and hospitalization in a large biobank linked to a national United States health system. We identified 19,168 (3.7%) lab-confirmed COVID-19 cases among Million Veteran Program participants between March 1, 2020, and February 2, 2021, including 11,778 Whites, 4,893 Blacks, and 2,497 Hispanics. A multi-population genome-wide association study (GWAS) for COVID-19 outcomes identified four independent genetic variants (rs8176719, rs73062389, rs60870724, and rs73910904) contributing to COVID-19 positivity, including one novel locus found exclusively among Hispanics. We replicated eight of nine previously reported genetic associations at an alpha of 0.05 in at least one population-specific or the multi-population meta-analysis for one of the four MVP COVID-19 outcomes. We used rs8176719 and three additional variants to accurately infer ABO blood types. We found that A, AB, and B blood types were associated with testing positive for COVID-19 compared with O blood type with the highest risk for the A blood group. We did not observe any genome-wide significant associations for COVID-19 severity outcomes among those testing positive. Our study replicates prior GWAS findings associated with testing positive for COVID-19 among mostly White samples and extends findings at three loci to Black and Hispanic individuals. We also report a new locus among Hispanics requiring further investigation. These findings may aid in the identification of novel therapeutic agents to decrease the morbidity and mortality of COVID-19 across all major ancestral populations.
Collapse
Affiliation(s)
- Gina M. Peloso
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Catherine Tcheandjieu
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, United States
| | - John E. McGeary
- Providence VA Healthcare System, Providence, RI, United States
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, United States
| | - Daniel C. Posner
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
| | - Jin J. Zhou
- Phoenix VA Health Care System, Phoenix, AZ, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, United States
| | | | - Jacob Joseph
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Cardiology Section, VA Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Christopher J. O’Donnell
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Cardiology Section, VA Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Jimmy T. Efird
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC, United States
| | - Dana C. Crawford
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United States
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, United States
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States
| | - Wen-Chih Wu
- Providence VA Healthcare System, Providence, RI, United States
- Department of Medicine, Alpert Medical School, Brown University, Providence, RI, United States
| | - Mehrdad Arjomandi
- Medical Service, San Francisco VA Medical Center, San Francisco, CA, United States
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | | | - Yan V. Sun
- Atlanta VA Health Care System, Decatur, GA, United States
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Themistocles L Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, United States
| | - Jennifer E. Huffman
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
| |
Collapse
|
16
|
Efird JT, Anderson EJ, Jindal C, Redding TS, Thompson AD, Press AM, Upchurch J, Williams CD, Choi YM, Suzuki A. The Interaction of Vitamin D and Corticosteroids: A Mortality Analysis of 26,508 Veterans Who Tested Positive for SARS-CoV-2. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 19:447. [PMID: 35010701 PMCID: PMC8744830 DOI: 10.3390/ijerph19010447] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 12/21/2021] [Accepted: 12/28/2021] [Indexed: 12/15/2022]
Abstract
This data-based cohort consisted of 26,508 (7%) United States veterans out of the 399,290 who tested positive for SARS-CoV-2 from 1 March to 10 September 2020. We aimed to assess the interaction of post-index vitamin D (Vit D) and corticosteroid (CRT) use on 30-day mortality among hospitalized and non-hospitalized patients with coronavirus disease 2019 (COVID-19). Combination Vit D and CRT drug use was assessed according to four multinomial pairs (-|+, -|-, +|+, +|-). Respective categorical effects were computed on a log-binomial scale as adjusted relative risk (aRR). Approximately 6% of veterans who tested positive for SARS-CoV-2 died within 30 days of their index date. Among hospitalized patients, a significantly decreased aRR was observed for the use of Vit D in the absence of CRTs relative to patients who received CRTs but not Vit D (aRR = 0.30; multiplicity corrected, p = 0.0004). Among patients receiving systemically administered CRTs (e.g., dexamethasone), the use of Vit D was associated with fewer deaths in hospitalized patients (aRR = 0.51) compared with non-hospitalized patients (aRR = 2.5) (P-for-Interaction = 0.0071). Evaluating the effect of modification of these compounds in the context of hospitalization may aid in the management of COVID-19 and provide a better understanding of the pathophysiological mechanisms underlying this and future infectious disease outbreaks.
Collapse
Affiliation(s)
- Jimmy T. Efird
- Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC 27705, USA; (T.S.R.); (A.D.T.); (A.M.P.); (J.U.); (C.D.W.); (A.S.)
| | | | - Charulata Jindal
- Harvard Medical School, Harvard University, Boston, MA 02115, USA;
| | - Thomas S. Redding
- Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC 27705, USA; (T.S.R.); (A.D.T.); (A.M.P.); (J.U.); (C.D.W.); (A.S.)
| | - Andrew D. Thompson
- Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC 27705, USA; (T.S.R.); (A.D.T.); (A.M.P.); (J.U.); (C.D.W.); (A.S.)
| | - Ashlyn M. Press
- Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC 27705, USA; (T.S.R.); (A.D.T.); (A.M.P.); (J.U.); (C.D.W.); (A.S.)
| | - Julie Upchurch
- Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC 27705, USA; (T.S.R.); (A.D.T.); (A.M.P.); (J.U.); (C.D.W.); (A.S.)
| | - Christina D. Williams
- Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC 27705, USA; (T.S.R.); (A.D.T.); (A.M.P.); (J.U.); (C.D.W.); (A.S.)
- Department of Medicine, Duke University, Durham, NC 27710, USA
- Duke Cancer Institute, Duke University, Durham, NC 27710, USA
| | | | - Ayako Suzuki
- Cooperative Studies Program Epidemiology Center, Durham VA Health Care System, Durham, NC 27705, USA; (T.S.R.); (A.D.T.); (A.M.P.); (J.U.); (C.D.W.); (A.S.)
- Division of Gastroenterology, Duke University, Durham, NC 27710, USA
- The Division of Gastroenterology, Durham VA Medical Center, Durham, NC 27705, USA
| |
Collapse
|
17
|
Zhang S, Cooper-Knock J, Weimer AK, Harvey C, Julian TH, Wang C, Li J, Furini S, Frullanti E, Fava F, Renieri A, Pan C, Song J, Billing-Ross P, Gao P, Shen X, Timpanaro IS, Kenna KP, Davis MM, Tsao PS, Snyder MP. Common and rare variant analyses combined with single-cell multiomics reveal cell-type-specific molecular mechanisms of COVID-19 severity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.06.15.21258703. [PMID: 34189540 PMCID: PMC8240695 DOI: 10.1101/2021.06.15.21258703] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The determinants of severe COVID-19 in non-elderly adults are poorly understood, which limits opportunities for early intervention and treatment. Here we present novel machine learning frameworks for identifying common and rare disease-associated genetic variation, which outperform conventional approaches. By integrating single-cell multiomics profiling of human lungs to link genetic signals to cell-type-specific functions, we have discovered and validated over 1,000 risk genes underlying severe COVID-19 across 19 cell types. Identified risk genes are overexpressed in healthy lungs but relatively downregulated in severely diseased lungs. Genetic risk for severe COVID-19, within both common and rare variants, is particularly enriched in natural killer (NK) cells, which places these immune cells upstream in the pathogenesis of severe disease. Mendelian randomization indicates that failed NKG2D-mediated activation of NK cells leads to critical illness. Network analysis further links multiple pathways associated with NK cell activation, including type-I-interferon-mediated signalling, to severe COVID-19. Our rare variant model, PULSE, enables sensitive prediction of severe disease in non-elderly patients based on whole-exome sequencing; individualized predictions are accurate independent of age and sex, and are consistent across multiple populations and cohorts. Risk stratification based on exome sequencing has the potential to facilitate post-exposure prophylaxis in at-risk individuals, potentially based around augmentation of NK cell function. Overall, our study characterizes a comprehensive genetic landscape of COVID-19 severity and provides novel insights into the molecular mechanisms of severe disease, leading to new therapeutic targets and sensitive detection of at-risk individuals.
Collapse
|