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Li G, Gerlovin H, Figueroa Muñiz MJ, Wise JK, Madenci AL, Robins JM, Aslan M, Cho K, Gaziano JM, Lipsitch M, Casas JP, Hernán MA, Dickerman BA. Comparison of the Test-negative Design and Cohort Design With Explicit Target Trial Emulation for Evaluating COVID-19 Vaccine Effectiveness. Epidemiology 2024; 35:137-149. [PMID: 38109485 PMCID: PMC11022682 DOI: 10.1097/ede.0000000000001709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
BACKGROUND Observational studies are used for estimating vaccine effectiveness under real-world conditions. The practical performance of two common approaches-cohort and test-negative designs-need to be compared for COVID-19 vaccines. METHODS We compared the cohort and test-negative designs to estimate the effectiveness of the BNT162b2 vaccine against COVID-19 outcomes using nationwide data from the United States Department of Veterans Affairs. Specifically, we (1) explicitly emulated a target trial using follow-up data and evaluated the potential for confounding using negative controls and benchmarking to a randomized trial, (2) performed case-control sampling of the cohort to confirm empirically that the same estimate is obtained, (3) further restricted the sampling to person-days with a test, and (4) implemented additional features of a test-negative design. We also compared their performance in limited datasets. RESULTS Estimated BNT162b2 vaccine effectiveness was similar under all four designs. Empirical results suggested limited residual confounding by healthcare-seeking behavior. Analyses in limited datasets showed evidence of residual confounding, with estimates biased downward in the cohort design and upward in the test-negative design. CONCLUSION Vaccine effectiveness estimates under a cohort design with explicit target trial emulation and a test-negative design were similar when using rich information from the VA healthcare system, but diverged in opposite directions when using a limited dataset. In settings like ours with sufficient information on confounders and other key variables, the cohort design with explicit target trial emulation may be preferable as a principled approach that allows estimation of absolute risks and facilitates interpretation of effect estimates.
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Affiliation(s)
- Guilin Li
- From the CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Hanna Gerlovin
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA
| | - Michael J Figueroa Muñiz
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jessica K Wise
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA
| | - Arin L Madenci
- From the CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Surgery, Boston Children's Hospital, Boston, MA
| | - James M Robins
- From the CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Mihaela Aslan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT
- Department of Medicine, Yale University School of Medicine, New Haven, CT
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - John Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Marc Lipsitch
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Miguel A Hernán
- From the CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Barbra A Dickerman
- From the CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
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Yan G, Nee R, Scialla JJ, Greene T, Yu W, Heng F, Cheung AK, Norris KC. Role of Age and Competing Risk of Death in the Racial Disparity of Kidney Failure Incidence after Onset of CKD. J Am Soc Nephrol 2024; 35:299-310. [PMID: 38254260 PMCID: PMC10914195 DOI: 10.1681/asn.0000000000000300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
SIGNIFICANCE STATEMENT Black adults in the United States have 2-4 times higher incidence of kidney failure than White adults. Yet, the reasons underlying this disparity remain poorly understood. Among 547,188 US veterans with new-onset CKD, according to a new race-free GFR equation, Black veterans had a 2.5-fold higher cumulative incidence of kidney failure, compared with White veterans, in any follow-up period from CKD onset. This disparity resulted from a combination of higher hazards of progression to kidney failure and lower hazards of competing-risk death in Black veterans. Both, in turn, were largely explained by the younger age at CKD onset in Black veterans, underscoring an urgent need to prevent early onset and slow progression of CKD in younger Black adults. BACKGROUND The Black adult population is well known to have higher incidence of kidney failure than their White counterpart in the United States, but the reasons underlying this disparity are unclear. We assessed the racial differences in kidney failure and death from onset of CKD on the basis of the race-free 2021 CKD Epidemiology Collaboration equation and examined the extent to which these differences could be explained by factors at the time of CKD onset. METHODS We analyzed a national cohort consisting of 547,188 US veterans (103,821 non-Hispanic Black and 443,367 non-Hispanic White), aged 18-85 years, with new-onset CKD between 2005 and 2016 who were followed through 10 years or May 2018 for incident kidney failure with replacement therapy (KFRT) and pre-KFRT death. RESULTS At CKD onset, Black veterans were, on average, 7.8 years younger than White veterans. In any time period from CKD onset, the cumulative incidence of KFRT was 2.5-fold higher for Black versus White veterans. Meanwhile, Black veterans had persistently >2-fold higher hazards of KFRT throughout follow-up (overall hazard ratio [95% confidence interval], 2.38 [2.31 to 2.45]) and conversely had 17%-48% decreased hazards of pre-KFRT death. These differences were reduced after accounting for the racial difference in age at CKD onset. CONCLUSIONS The 2.5-fold higher cumulative incidence of kidney failure in Black adults resulted from a combination of higher hazards of progression to kidney failure and lower hazards of the competing risk of death, both of which can be largely explained by the younger age at CKD onset in Black compared with White adults.
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Affiliation(s)
- Guofen Yan
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Robert Nee
- Nephrology Service, Walter Reed National Military Medical Center; Department of Medicine, Uniformed Services University, Bethesda, Maryland
| | - Julia J. Scialla
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia
- Division of Nephrology, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Tom Greene
- Division of Biostatistics, University of Utah School of Medicine, Salt Lake City, Utah
| | - Wei Yu
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Fei Heng
- Department of Mathematics and Statistics, University of North Florida, Jacksonville, Florida
| | - Alfred K. Cheung
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah, Salt Lake City, Utah
| | - Keith C. Norris
- Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
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Armbrust KR, Westanmo A, Gravely A, Chew EY, van Kuijk FJ. Adverse COVID-19 outcomes in American Veterans with age-related macular degeneration: a case-control study. BMJ Open 2023; 13:e071921. [PMID: 38110385 DOI: 10.1136/bmjopen-2023-071921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2023] Open
Abstract
OBJECTIVES Prior studies suggest that patients with age-related macular degeneration (AMD) have poorer COVID-19 outcomes. This study aims to evaluate whether AMD is associated with adverse COVID-19 outcomes in a large clinical database. DESIGN Case-control study. SETTING We obtained demographic and clinical data from a national US Veterans Affairs (VA) database for all Veterans aged 50 years or older with positive COVID-19 testing prior to 2 May 2021. PRIMARY AND SECONDARY OUTCOME MEASURES The primary outcome measure was hospitalisation. Secondary outcome measures were intensive care unit admission, mechanical ventilation and death. Potential associations between AMD and outcome measures occurring within 60 days of COVID-19 diagnosis were evaluated using multiple logistic regression analyses. RESULTS Of the 171 325 patients in the study cohort, 7913 (5%) had AMD and 2152 (1%) had severe AMD, defined as advanced atrophic or exudative AMD disease coding. Multiple logistic regression adjusting for age, Charlson Comorbidity Index, sex, race, ethnicity and COVID-19 timing showed that an AMD diagnosis did not significantly increase the odds of hospitalisation (p=0.11). Using a Bonferroni-adjusted significance level of 0.006, AMD and severe AMD also were not significant predictors for the secondary outcomes, except for AMD being modestly protective for death (p=0.002). CONCLUSIONS After adjusting for other variables, neither AMD nor severe AMD was a risk factor for adverse COVID-19 outcomes in the VA healthcare system. These findings indicate that an AMD diagnosis alone should not alter recommended ophthalmic management based on COVID-19 adverse outcome risk.
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Affiliation(s)
- Karen R Armbrust
- Department of Ophthalmology, Minneapolis VA Health Care System, Minneapolis, Minnesota, USA
- Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, Minnesota, USA
| | - Anders Westanmo
- Department of Pharmacy, Minneapolis VA Health Care System, Minneapolis, Minnesota, USA
| | - Amy Gravely
- Research Service, Minneapolis VA Health Care System, Minneapolis, Minnesota, USA
| | - Emily Y Chew
- National Eye Institute, Division of Epidemiology and Clinical Applications (Clinical Trial Branch), National Institutes of Health, Bethesda, Maryland, USA
| | - Frederik J van Kuijk
- Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, Minnesota, USA
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Koyama AK, Nee R, Yu W, Choudhury D, Heng F, Cheung AK, Norris KC, Cho ME, Yan G. Role of Anemia in Dementia Risk Among Veterans With Incident CKD. Am J Kidney Dis 2023; 82:706-714. [PMID: 37516301 PMCID: PMC10822015 DOI: 10.1053/j.ajkd.2023.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 03/30/2023] [Accepted: 04/30/2023] [Indexed: 07/31/2023]
Abstract
RATIONALE & OBJECTIVE Although some evidence exists of increased dementia risk from anemia, it is unclear whether this association persists among adults with CKD. Anemia may be a key marker for dementia among adults with CKD, so we evaluated whether anemia is associated with an increased risk of dementia among adults with CKD. STUDY DESIGN Retrospective cohort study. SETTING & PARTICIPANTS The study included 620,095 veterans aged≥45 years with incident stage 3 CKD (estimated glomerular filtration rate [eGFR]<60mL/min/1.73m2) between January 2005 and December 2016 in the US Veterans Health Administration system and followed through December 31, 2018, for incident dementia, kidney failure, or death. EXPOSURE Anemia was assessed based on the average of hemoglobin levels (g/L) during the 2 years before the date of incident CKD and categorized as normal, mild, or moderate/severe anemia (≥12.0, 11.0-11.9,<11.0g/dL, respectively, for women, and≥13.0, 11.0-12.9,<11.0g/dL for men). OUTCOME Dementia and the composite outcome of kidney failure or death. ANALYTICAL APPROACH Adjusted cause-specific hazard ratios were estimated for each outcome. RESULTS At the time of incident CKD, the mean age of the participants was 72 years, 97% were male, and their mean eGFR was 51mL/min per 1.73m2. Over a median 4.1 years of follow-up, 92,306 veterans (15%) developed dementia before kidney failure or death. Compared with the veterans with CKD without anemia, the multivariable-adjusted models showed a 16% (95% CI, 14%-17%) significantly higher risk of dementia for those with mild anemia and a 27% (95% CI, 23%-31%) higher risk with moderate/severe anemia. Combined risk of kidney failure or death was higher at 39% (95% CI, 37%-40%) and 115% (95% CI, 112%-119%) for mild and moderate/severe anemia, respectively, compared with no anemia. LIMITATIONS Residual confounding from the observational study design. Findings may not be generalizable to the broader US population. CONCLUSIONS Anemia was significantly associated with an increased risk of dementia among veterans with incident CKD, underscoring the role of anemia as a predictor of dementia risk. PLAIN-LANGUAGE SUMMARY Adults with chronic kidney disease (CKD) often have anemia. Prior studies among adults in the general population suggest anemia is a risk factor for dementia, though it is unclear whether this association persists among adults with CKD. In this large study of veterans in the United States, we studied the association between anemia and the risk of 2 important outcomes in this population: (1) dementia and (2) kidney failure or death. We found that anemia was associated with a greater risk of dementia as well as risk of kidney failure or death. The study findings therefore emphasize the role of anemia as a key predictor of dementia risk among adults with CKD.
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Affiliation(s)
- Alain K Koyama
- Centers for Disease Control and Prevention, Atlanta, Georgia.
| | - Robert Nee
- Walter Reed National Military Medical Center; Uniformed Services University, Bethesda, Maryland
| | - Wei Yu
- University of Virginia, Charlottesville, Virginia
| | - Devasmita Choudhury
- University of Virginia, Charlottesville, Virginia; Virginia-Tech Carilion School of Medicine Medical Center, Roanoke, Virginia; Salem Veterans Affairs Healthcare System, Salem, Virginia
| | - Fei Heng
- University of North Florida, Jacksonville, Florida
| | - Alfred K Cheung
- VA Salt Lake City Healthcare System, Salt Lake City, Utah; University of Utah, Salt Lake City, Utah
| | - Keith C Norris
- University of California-Los Angeles, Los Angeles, California
| | | | - Guofen Yan
- University of Virginia, Charlottesville, Virginia.
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Liu J, Hu S, Chen L, Daly C, Prada Medina CA, Richardson TG, Traylor M, Dempster NJ, Mbasu R, Monfeuga T, Vujkovic M, Tsao PS, Lynch JA, Voight BF, Chang KM, Million VA, Cobbold JF, Tomlinson JW, van Duijn CM, Howson JMM. Profiling the genome and proteome of metabolic dysfunction-associated steatotic liver disease identifies potential therapeutic targets. medRxiv 2023:2023.11.30.23299247. [PMID: 38076879 PMCID: PMC10705663 DOI: 10.1101/2023.11.30.23299247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
BACKGROUND & AIMS Metabolic dysfunction-associated steatotic liver disease (MASLD) affects over 25% of the population and currently has no effective treatments. Plasma proteins with causal evidence may represent promising drug targets. We aimed to identify plasma proteins in the causal pathway of MASLD and explore their interaction with obesity. METHODS We analysed 2,941 plasma proteins in 43,978 European participants from UK Biobank. We performed genome-wide association study (GWAS) for all MASLD-associated proteins and created the largest MASLD GWAS (109,885 cases/1,014,923 controls). We performed Mendelian Randomization (MR) and integrated proteins and their encoding genes in MASLD ranges to identify candidate causal proteins. We then validated them through independent replication, exome sequencing, liver imaging, bulk and single-cell gene expression, liver biopsies, pathway, and phenome-wide data. We explored the role of obesity by MR and multivariable MR across proteins, body mass index, and MASLD. RESULTS We found 929 proteins associated with MASLD, reported five novel genetic loci associated with MASLD, and identified 17 candidate MASLD protein targets. We identified four novel targets for MASLD (CD33, GRHPR, HMOX2, and SCG3), provided protein evidence supporting roles of AHCY, FCGR2B, ORM1, and RBKS in MASLD, and validated nine previously known targets. We found that CD33, FCGR2B, ORM1, RBKS, and SCG3 mediated the association of obesity and MASLD, and HMOX2, ORM1, and RBKS had effect on MASLD independent of obesity. CONCLUSIONS This study identified new protein targets in the causal pathway of MASLD, providing new insights into the multi-omics architecture and pathophysiology of MASLD. These findings advise further therapeutic interventions for MASLD.
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Affiliation(s)
- Jun Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Sile Hu
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Lingyan Chen
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Charlotte Daly
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | | | - Tom G Richardson
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Traylor
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Niall J Dempster
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - Richard Mbasu
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Thomas Monfeuga
- AI & Digital Research, Research & Early Development, Novo Nordisk Research Centre Oxford, UK
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - V A Million
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- AI & Digital Research, Research & Early Development, Novo Nordisk Research Centre Oxford, UK
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Jeremy F Cobbold
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Jeremy W Tomlinson
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
| | | | - Joanna M M Howson
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
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Chanfreau-Coffinier C, Friede KA, Plomondon ME, Lee KM, Lu Z, Lynch JA, DuVall SL, Vassy JL, Waldo SW, Cleator JH, Maddox TM, Rader DJ, Assimes TL, Damrauer SM, Tsao PS, Chang KM, Voora D, Giri J, Tuteja S. CYP2C19 Polymorphisms and Clinical Outcomes Following Percutaneous Coronary Intervention (PCI) in the Million Veterans Program. medRxiv 2023:2023.10.25.23297578. [PMID: 37961335 PMCID: PMC10635203 DOI: 10.1101/2023.10.25.23297578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background CYP2C19 loss-of-function (LOF) alleles decrease the antiplatelet effect of clopidogrel following percutaneous coronary intervention (PCI) in patients presenting with acute coronary syndrome (ACS). The impact of genotype in stable ischemic heart disease (SIHD) is unclear. Objectives Determine the association of CYP2C19 genotype with major adverse cardiac events (MACE) after PCI for ACS or SIHD. Methods Million Veterans Program (MVP) participants age <65 years with a PCI documented in the VA Clinical Assessment, Reporting and Tracking (CART) Program between 1/1/2009 to 9/30/2017, treated with clopidogrel were included. Time to MACE defined as the composite of all-cause death, stroke or myocardial infarction within 12 months following PCI. Results Among 4,461 Veterans (mean age 59.1 ± 5.1 years, 18% Black); 44% had ACS, 56% had SIHD and 29% carried a CYP2C19 LOF allele. 301 patients (6.7%) experienced MACE while being treated with clopidogrel, 155 (7.9%) in the ACS group and 146 (5.9%) in the SIHD group. Overall, MACE was not significantly different between LOF carriers vs. noncarriers (adjusted hazard ratio [HR] 1.18, confidence interval [95%CI] 0.97-1.45, p=0.096). Among patients presenting with ACS, MACE risk in LOF carriers versus non-carriers was numerically higher (HR 1.30, 95%CI 0.98-1.73, p=0.067). There was no difference in MACE risk in patients with SIHD (HR 1.09, 95%CI 0.82-1.44; p=0.565). Conclusions CYP2C19 LOF carriers presenting with ACS treated with clopidogrel following PCI experienced a numerically greater elevated risk of MACE events. CYP2C19 LOF genotype is not associated with MACE among patients presenting with SIHD.
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Affiliation(s)
| | - Kevin A. Friede
- Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Mary E. Plomondon
- CART Program, Office of Quality and Patient Safety, Veterans Health Administration, Washington, DC
| | - Kyung Min Lee
- VA Salt Lake City Heath Care System, Salt Lake City, UT
| | - Zhenyu Lu
- VA Salt Lake City Heath Care System, Salt Lake City, UT
| | - Julie A. Lynch
- VA Salt Lake City Heath Care System, Salt Lake City, UT
- Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT
| | - Scott L. DuVall
- VA Salt Lake City Heath Care System, Salt Lake City, UT
- Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT
| | - Jason L. Vassy
- VA Boston Healthcare System, Harvard Medical School, and Brigham and Women’s Hospital, Boston, MA
| | - Stephen W. Waldo
- CART Program, Office of Quality and Patient Safety, Veterans Health Administration, Washington, DC
- Rocky Mountain Regional VA Medical Center and University of Colorado School of Medicine, Aurora, CO
| | | | - Thomas M. Maddox
- Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Daniel J. Rader
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | | | - Scott M. Damrauer
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
| | - Philip S. Tsao
- VA Palo Alto Healthcare System and Stanford University, Palo Alto, CA
| | - Kyong-Mi Chang
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
| | - Deepak Voora
- Durham VA Healthcare System and Duke University, Durham, NC
| | - Jay Giri
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
| | - Sony Tuteja
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
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Shabani S, Houlton S, Ghimire B, Tonello D, Reed C, Baba H, Aldrich S, Phillips TJ. Robust aversive effects of trace amine-associated receptor 1 activation in mice. Neuropsychopharmacology 2023; 48:1446-1454. [PMID: 37055488 PMCID: PMC10425385 DOI: 10.1038/s41386-023-01578-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 03/03/2023] [Accepted: 03/26/2023] [Indexed: 04/15/2023]
Abstract
Drugs that stimulate the trace amine-associated receptor 1 (TAAR1) are under clinical investigation as treatments for several neuropsychiatric disorders. Previous studies in a genetic mouse model of voluntary methamphetamine intake identified TAAR1, expressed by the Taar1 gene, as a critical mediator of aversive methamphetamine effects. Methamphetamine is a TAAR1 agonist, but also has actions at monoamine transporters. Whether exclusive activation of TAAR1 has aversive effects was not known at the time we conducted our studies. Mice were tested for aversive effects of the selective TAAR1 agonist, RO5256390, using taste and place conditioning procedures. Hypothermic and locomotor effects were also examined, based on prior evidence of TAAR1 mediation. Male and female mice of several genetic models were used, including lines selectively bred for high and low methamphetamine drinking, a knock-in line in which a mutant form of Taar1 that codes for a non-functional TAAR1 was replaced by the reference Taar1 allele that codes for functional TAAR1, and their matched control line. RO5256390 had robust aversive, hypothermic and locomotor suppressing effects that were found only in mice with functional TAAR1. Knock-in of the reference Taar1 allele rescued these phenotypes in a genetic model that normally lacks TAAR1 function. Our study provides important data on TAAR1 function in aversive, locomotor, and thermoregulatory effects that are important to consider when developing TAAR1 agonists as therapeutic drugs. Because other drugs can have similar consequences, potential additive effects should be carefully considered as these treatment agents are being developed.
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Affiliation(s)
- Shkelzen Shabani
- Department of Biomedical Sciences, Grand Valley State University, Allendale, MI, USA
- Department of Biology, Minot State University, Minot, ND, USA
- Biomedical Sciences at Grand Valley State University, Allendale, MI, USA
| | - Sydney Houlton
- Department of Biology, Minot State University, Minot, ND, USA
| | - Bikalpa Ghimire
- Department of Biology, Minot State University, Minot, ND, USA
| | - Derek Tonello
- Department of Biomedical Sciences, Grand Valley State University, Allendale, MI, USA
| | - Cheryl Reed
- Department of Behavioral Neuroscience and Methamphetamine Abuse Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Harue Baba
- Department of Behavioral Neuroscience and Methamphetamine Abuse Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Sara Aldrich
- Department of Behavioral Neuroscience and Methamphetamine Abuse Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Tamara J Phillips
- Department of Behavioral Neuroscience and Methamphetamine Abuse Research Center, Oregon Health & Science University, Portland, OR, USA.
- VA Portland Health Care System, Portland, OR, USA.
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8
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Shevach JW, Aiello LB, Lynch JA, Petersen J, Hoffman-Hogg L, Hartzfeld D, Lundquist M, Kelley MJ, Scheuner MT, Montgomery R, Damjanov N, Robinson K, Wong YN, Jhala D, Parikh RB, Maxwell KN. On-Site Nurse-Led Cancer Genetics Program Increases Cancer Genetic Testing Completion in Black Veterans. JCO Oncol Pract 2023; 19:637-644. [PMID: 37220320 PMCID: PMC10424905 DOI: 10.1200/op.22.00738] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/03/2023] [Accepted: 03/17/2023] [Indexed: 05/25/2023] Open
Abstract
PURPOSE Telegenetics services can expand access to guideline-recommended cancer genetic testing. However, access is often not distributed equitably to all races and ethnicities. We evaluated the impact of an on-site nurse-led cancer genetics service in a diverse Veterans Affairs Medical Center (VAMC) oncology clinic on likelihood of germline testing (GT) completion. METHODS We conducted an observational retrospective cohort study of patients who were referred for cancer genetics services at the Philadelphia VAMC between October 1, 2020, and February 28, 2022. We evaluated the association between genetics service (on-site v telegenetics) and likelihood of GT completion in a subcohort of new consults, excluding patients with prior consults and those referred for known history of germline mutations. RESULTS A total of 238 Veterans, including 108 (45%) seen on site, were identified for cancer genetics services during the study period, with the majority referred for a personal (65%) or family (26%) history of cancer. In the subcohort of new consults, 121 Veterans (54% self-identified race/ethnicity [SIRE]-Black), including 60 (50%) seen on site, were included in the analysis of germline genetic testing completion. In a univariate analysis, patients who were seen by the on-site genetics service had 3.2-fold higher likelihood of completing GT (relative risk, 3.22; 95% CI, 1.89 to 5.48) compared with the telegenetics service. In multivariable regression analysis, the on-site genetics service was associated with higher likelihood of GT completion, but this association was only statistically significant in SIRE-Black compared with SIRE-White Veterans (adjusted RR, 4.78; 95% CI, 1.53 to 14.96; P < .001; P-interaction of race × genetics service = .016). CONCLUSION An on-site nurse-led cancer genetics service embedded in a VAMC Oncology practice was associated with higher likelihood of germline genetic testing completion than a telegenetics service among self-identified Black Veterans.
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Affiliation(s)
- Jeffrey W. Shevach
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Medicine-Hematology-Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Lisa B. Aiello
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
| | - Julie A. Lynch
- George E. Whalen Veterans Affairs Medical Center, Salt Lake City, UT
- Division of Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT
| | - Jeffrey Petersen
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Lori Hoffman-Hogg
- Veterans Health Administration National Center for Health Promotion and Disease Prevention, Durham, NC
- Veterans Health Administration Office of Nursing Services, Washington, DC
| | - Deborah Hartzfeld
- George E. Whalen Veterans Affairs Medical Center, Salt Lake City, UT
| | | | - Michael J. Kelley
- Durham VA Medical Center, Durham, NC
- Department of Medicine, Duke University, Durham, NC
| | - Maren T. Scheuner
- San Francisco Veterans Affairs Health Care System, San Francisco, CA
- Departments of Medicine and Pediatrics, University of California San Francisco, School of Medicine, San Francisco, CA
| | - Robert Montgomery
- Division of Medical Oncology, University of Washington and Seattle Cancer Care Alliance, Seattle, WA
- Veterans Affairs Puget Sound Health Care System, Seattle, WA
| | - Nevena Damjanov
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Medicine-Hematology-Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Kyle Robinson
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Medicine-Hematology-Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Yu-Ning Wong
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Medicine-Hematology-Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Darshana Jhala
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Ravi B. Parikh
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Medicine-Hematology-Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Kara N. Maxwell
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA
- Department of Medicine-Hematology-Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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Gan Q, Hu M, Peterson KS, Eyre H, Alba PR, Bowles AE, Stanley JC, DuVall SL, Shi J. A deep learning approach for medication disposition and corresponding attributes extraction. J Biomed Inform 2023; 143:104391. [PMID: 37196988 PMCID: PMC10527481 DOI: 10.1016/j.jbi.2023.104391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 05/05/2023] [Accepted: 05/10/2023] [Indexed: 05/19/2023]
Abstract
OBJECTIVE This article summarizes our approach to extracting medication and corresponding attributes from clinical notes, which is the focus of track 1 of the 2022 National Natural Language Processing (NLP) Clinical Challenges(n2c2) shared task. METHODS The dataset was prepared using Contextualized Medication Event Dataset (CMED), including 500 notes from 296 patients. Our system consisted of three components: medication named entity recognition (NER), event classification (EC), and context classification (CC). These three components were built using transformer models with slightly different architecture and input text engineering. A zero-shot learning solution for CC was also explored. RESULTS Our best performance systems achieved micro-average F1 scores of 0.973, 0.911, and 0.909 for the NER, EC, and CC, respectively. CONCLUSION In this study, we implemented a deep learning-based NLP system and demonstrated that our approach of (1) utilizing special tokens helps our model to distinguish multiple medications mentions in the same context; (2) aggregating multiple events of a single medication into multiple labels improves our model's performance.
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Affiliation(s)
- Qiwei Gan
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA
| | - Mengke Hu
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA
| | - Kelly S Peterson
- Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA; Veterans Health Administration Office of Analytics and Performance Integration, 500, Foothill Boulevard, Salt Lake City 84148, USA
| | - Hannah Eyre
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA
| | - Patrick R Alba
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA
| | - Annie E Bowles
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA
| | - Johnathan C Stanley
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA
| | - Scott L DuVall
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA
| | - Jianlin Shi
- VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA.
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10
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Santilli CM, Johnson S, Thunstrom CR, Armbrust KR. Glycated Hemoglobin Improvement After Medical and Surgical Eye Care in American Veterans Involves Multidisciplinary Care. Clin Ophthalmol 2023; 17:1675-1682. [PMID: 37325065 PMCID: PMC10266375 DOI: 10.2147/opth.s412187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 05/12/2023] [Indexed: 06/17/2023] Open
Abstract
Purpose The effects of diabetes mellitus (DM) on visual function have been extensively studied. Fewer studies evaluate the effect of visual function on DM, and previous small studies have shown mixed results concerning the relationship between glycated hemoglobin (HbA1c) and cataract surgery. We performed a retrospective, observational, single-site study at a Veterans hospital to evaluate this relationship and the relationship between HbA1c and non-surgical eye care. Patients and Methods We compared pre- and post-operative/examination HbA1c in 431 surgical and 431 matched, non-surgical subjects who underwent eye examination at the same institution. Subgroup analysis was performed by age, elevated (≥8) pre-operative/examination HbA1c, and change in diabetic management. We also assessed for a relationship between changes in best-corrected visual acuity (BCVA) and HbA1c. The Minneapolis Veterans Affairs Health Care System Research Administration determined this study to be Institutional Review Board exempt from the requirements of 38 CFR 16 under Category 4 (iii). Results Pairwise comparison of pre- versus post-operative HbA1c trended towards reduction at 3-6 months in all surgical subjects, with a statistically significant reduction in older subjects, and those with higher pre-operative HbA1c. Eye examination subjects experienced a significant HbA1c reduction 3-6 months after eye examination. Reduction in post-operative/examination HbA1c was associated with concurrent change in diabetic management. Conclusion We found an overall reduction in HbA1c in diabetic Veterans who interacted with an ophthalmologist, whether for cataract surgery or eye examination. HbA1c reduction was greatest when ophthalmic care was delivered as part of a multidisciplinary care team. Our findings add new evidence to further support the importance of ophthalmic care in patients with DM and suggest improved visual function may facilitate improved glycemic control.
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Affiliation(s)
- Christopher M Santilli
- Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, MN, USA
| | - Shaun Johnson
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Coltt R Thunstrom
- Department of Statistics, University of Minnesota, Minneapolis, MN, USA
| | - Karen R Armbrust
- Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, MN, USA
- Department of Ophthalmology, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA
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11
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Valle LF, Nickols NG, Hausler R, Alba PR, Anglin-Foote T, Perez C, Yamoah K, Rose BS, Kelley MJ, DuVall SL, Garraway IP, Maxwell KN, Lynch JA. Actionable Genomic Alterations in Prostate Cancer Among Black and White United States Veterans. Oncologist 2023; 28:e473-e477. [PMID: 37084789 PMCID: PMC10243786 DOI: 10.1093/oncolo/oyad042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/01/2023] [Indexed: 04/23/2023] Open
Abstract
Black Veterans have higher a incidence of localized and metastatic prostate cancer compared to White Veterans yet are underrepresented in reports of frequencies of somatic and germline alterations. This retrospective analysis of somatic and putative germline alterations was conducted in a large cohort of Veterans with prostate cancer (N = 835 Black, 1613 White) who underwent next generation sequencing through the VA Precision Oncology Program, which facilitates molecular testing for Veterans with metastatic cancer. No differences were observed in gene alterations for FDA approved targetable therapies (13.5% in Black Veterans vs. 15.5% in White Veterans, P = .21), nor in any potentially actionable alterations (25.5% vs. 28.7%, P =.1). Black Veterans had higher rates of BRAF (5.5% vs. 2.6%, P < .001) alterations, White Veterans TMPRSS2 fusions (27.2% vs. 11.7%, P < .0001). Putative germline alteration rates were higher in White Veterans (12.0% vs. 6.1%, P < .0001). Racial disparities in outcome are unlikely attributable to acquired somatic alterations in actionable pathways.
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Affiliation(s)
- Luca F Valle
- Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Department of Radiation Oncology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - Nicholas G Nickols
- Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Department of Radiation Oncology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
- UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA
- Department of Urology, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
| | - Ryan Hausler
- Department of Veterans Affairs Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Patrick R Alba
- Department of Veterans Affairs Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Tori Anglin-Foote
- Department of Veterans Affairs Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Cristina Perez
- Department of Veterans Affairs Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Kosj Yamoah
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
- James A. Haley Veterans’ Hospital, Tampa, FL, USA
| | - Brent S Rose
- Department of Radiation Oncology, University of California, San Diego, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA
| | - Michael J Kelley
- Duke University Medical Center, Durham, NC, USA
- Department of Veteran Affairs Medical Center, Durham, NC, USA
| | - Scott L DuVall
- Department of Veterans Affairs Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Isla P Garraway
- Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA
- Department of Urology, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
| | - Kara N Maxwell
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Julie A Lynch
- Department of Veterans Affairs Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Nursing and Health Sciences, University of Massachusetts, Boston, MA, USA
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12
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Baptista LC, Zumbro EL, Graham ZA, Hernandez AR, Buchanan T, Sun Y, Yang Y, Banerjee A, Verma A, Li Q, Carter CS, Buford TW. Multiomics profiling of the impact of an angiotensin (1-7)-expressing probiotic combined with exercise training in aged male rats. J Appl Physiol (1985) 2023; 134:1135-1153. [PMID: 36892893 PMCID: PMC10125028 DOI: 10.1152/japplphysiol.00508.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 02/28/2023] [Accepted: 02/28/2023] [Indexed: 03/10/2023] Open
Abstract
Angiotensin (1-7) [Ang (1-7)] is an active heptapeptide of the noncanonical arm of the renin-angiotensin system that modulates molecular signaling pathways associated with vascular and cellular inflammation, vasoconstriction, and fibrosis. Preclinical evidence suggests that Ang (1-7) is a promising therapeutic target that may ameliorate physical and cognitive function in late life. However, treatment pharmacodynamics limits its clinical applicability. Therefore, this study explored the underlying mechanisms altered by a genetically modified probiotic (GMP) that expresses Ang (1-7) combined with and without exercise training in an aging male rat model as a potential adjunct strategy to exercise training to counteract the decline of physical and cognitive function. We evaluated cross-tissue (prefrontal cortex, hippocampus, colon, liver, and skeletal muscle) multi-omics responses. After 12 wk of intervention, the 16S mRNA microbiome analysis revealed a main effect of probiotic treatment within- and between groups. The probiotic treatment enhanced α diversity (Inverse Simpson (F[2,56] = 4.44; P = 0.02); Shannon-Wiener (F[2,56] = 4.27; P = 0.02)) and β-diversity (F[2,56] = 2.66; P = 0.01) among rats receiving our GMP. The analysis of microbes' composition revealed three genera altered by our GMP (Enterorhabdus, Muribaculaceae unclassified, and Faecalitalea). The mRNA multi-tissue data analysis showed that our combined intervention upregulated neuroremodeling pathways on prefrontal cortex (i.e., 140 genes), inflammation gene expression in the liver (i.e., 63 genes), and circadian rhythm signaling on skeletal muscle. Finally, the integrative network analysis detected different communities of tightly (|r| > 0.8 and P < 0.05) correlated metabolites, genera, and genes in these tissues.NEW & NOTEWORTHY This manuscript uses a multiomics approach (i.e., microbiome, metabolomics, and transcriptomics) to explore the underlying mechanisms driven by a genetically modified probiotic (GMP) designed to express angiotensin (1-7) combined with moderate exercise training in an aged male rat model. After 12 wk of intervention, our findings suggest that our GMP enhanced gut microbial diversity while exercise training altered the transcriptional response in relevant neuroremodeling genes, inflammation, and circadian rhythm signaling pathways in an aging animal model.
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Affiliation(s)
- Liliana C Baptista
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
- Research Center for Physical Activity, Health and Leisure, Faculty of Sport, University of Porto, Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health, University of Porto, Porto, Portugal
| | - Emily L Zumbro
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Zachary A Graham
- Research Service, Birmingham Veterans Affair Medical Center, Birmingham, Alabama, United States
- Healthspan, Resilience and Performance, Florida Institute for Human and Machine Cognition, Pensacola, Florida, United States
- Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Abbi R Hernandez
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Taylor Buchanan
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Yi Sun
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
- Department of Life, Health, and Physical Sciences, Gordon College, Wenham, Massachusetts, United States
| | - YouFeng Yang
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Anisha Banerjee
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Amrisha Verma
- Department of Life, Health, and Physical Sciences, Gordon College, Wenham, Massachusetts, United States
| | - Qiuhong Li
- Department of Ophthalmology, College of Medicine, University of Florida, Gainesville, Florida, United States
| | - Christy S Carter
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Thomas W Buford
- Division of Gerontology, Geriatrics and Palliative Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
- Geriatric Research Education and Clinical Center, Birmingham VA Medical Center, Birmingham, Alabama, United States
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13
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Maguen S, Madden E, Holder N, Li Y, Seal KH, Neylan TC, Lujan C, Patterson OV, DuVall SL, Shiner B. Effectiveness and comparative effectiveness of evidence-based psychotherapies for posttraumatic stress disorder in clinical practice. Psychol Med 2023; 53:419-428. [PMID: 34001290 PMCID: PMC9899565 DOI: 10.1017/s0033291721001628] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 04/06/2021] [Accepted: 04/13/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND While evidence-based psychotherapy (EBP) for posttraumatic stress disorder (PTSD) is a first-line treatment, its real-world effectiveness is unknown. We compared cognitive processing therapy (CPT) and prolonged exposure (PE) each to an individual psychotherapy comparator group, and CPT to PE in a large national healthcare system. METHODS We utilized effectiveness and comparative effectiveness emulated trials using retrospective cohort data from electronic medical records. Participants were veterans with PTSD initiating mental healthcare (N = 265 566). The primary outcome was PTSD symptoms measured by the PTSD Checklist (PCL) at baseline and 24-week follow-up. Emulated trials were comprised of 'person-trials,' representing 112 discrete 24-week periods of care (10/07-6/17) for each patient. Treatment group comparisons were made with generalized linear models, utilizing propensity score matching and inverse probability weights to account for confounding, selection, and non-adherence bias. RESULTS There were 636 CPT person-trials matched to 636 non-EBP person-trials. Completing ⩾8 CPT sessions was associated with a 6.4-point greater improvement on the PCL (95% CI 3.1-10.0). There were 272 PE person-trials matched to 272 non-EBP person-trials. Completing ⩾8 PE sessions was associated with a 9.7-point greater improvement on the PCL (95% CI 5.4-13.8). There were 232 PE person-trials matched to 232 CPT person-trials. Those completing ⩾8 PE sessions had slightly greater, but not statistically significant, improvement on the PCL (8.3-points; 95% CI 5.9-10.6) than those completing ⩾8 CPT sessions (7.0-points; 95% CI 5.5-8.5). CONCLUSIONS PTSD symptom improvement was similar and modest for both EBPs. Although EBPs are helpful, research to further improve PTSD care is critical.
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Affiliation(s)
- Shira Maguen
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA
| | - Erin Madden
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA
| | - Nicholas Holder
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA
| | - Yongmei Li
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA
| | - Karen H. Seal
- Integrative Health Service, San Francisco VA Health Care System, San Francisco, CA
- Department of Medicine and Psychiatry, University of California, San Francisco, San Francisco, CA
| | - Thomas C. Neylan
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA
- Department of Neurology, University of California, San Francisco, San Francisco, CA
| | - Callan Lujan
- Mental Health Service, San Francisco VA Health Care System, San Francisco, CA
| | - Olga V. Patterson
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah, School of Medicine, Salt Lake City, Utah
| | - Scott L. DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah, School of Medicine, Salt Lake City, Utah
| | - Brian Shiner
- Mental Health Service, White River Junction VA Medical Center, and National Center for Posttraumatic Stress Disorder, Executive Division, White River Junction, VT
- Department of Psychiatry, Geisel School of Medicine at Dartmouth, Hanover, NH
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14
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Murata GH, Murata AE, Perkins DJ, Campbell HM, Mao JT, Wagner B, McMahon BH, Hagedorn CH. Effect of vaccination on the case fatality rate for COVID-19 infections 2020-2021: multivariate modelling of data from the US Department of Veterans Affairs. BMJ Open 2022; 12:e064135. [PMID: 36564105 PMCID: PMC9791110 DOI: 10.1136/bmjopen-2022-064135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 11/04/2022] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVES To evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections. DESIGN, SETTING AND PARTICIPANTS The US Department of Veterans Affairs has 130 medical centres. We created multivariate models from these data-339 772 patients with COVID-19-as of 30 September 2021. OUTCOME MEASURES The primary outcome for all models was death within 60 days of the diagnosis. Logistic regression was used to derive adjusted ORs for vaccination and infection with Delta versus earlier variants. Models were adjusted for confounding factors, including demographics, comorbidity indices and novel parameters representing prior diagnoses, vital signs/baseline laboratory tests and outpatient treatments. Patients with a Delta infection were divided into eight cohorts based on the time from vaccination to diagnosis. A common model was used to estimate the odds of death associated with vaccination for each cohort relative to that of unvaccinated patients. RESULTS 9.1% of subjects were vaccinated. 21.5% had the Delta variant. 18 120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for a Delta infection was 1.87±0.05, which corresponds to a relative risk (RR) of 1.78. The overall adjusted OR for prior vaccination was 0.280±0.011 corresponding to an RR of 0.291. Raw CFR rose steadily after 10-14 weeks. The OR for vaccination remained stable for 10-34 weeks. CONCLUSIONS Our CFR model controls for the severity of confounding factors and priority of vaccination, rather than solely using the presence of comorbidities. Our results confirm that Delta was more lethal than earlier variants and that vaccination is an effective means of preventing death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks. We suggest that this model can be used to evaluate vaccines designed for emerging variants.
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Affiliation(s)
- Glen H Murata
- Research Service, New Mexico VA Health Care System, Albuquerque, New Mexico, USA
| | - Allison E Murata
- Clinical Research Pharmacy Coordinating Center, VHA Cooperative Studies Program, Albuquerque, New Mexico, USA
| | - Douglas J Perkins
- Center for Global Health, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Heather M Campbell
- Clinical Research Pharmacy Coordinating Center, VHA Cooperative Studies Program, Albuquerque, New Mexico, USA
| | - Jenny T Mao
- Medicine Service, New Mexico VA Health Care System, Albuquerque, New Mexico, USA
| | - Brent Wagner
- Research Service, New Mexico VA Health Care System, Albuquerque, New Mexico, USA
- Medicine Service, New Mexico VA Health Care System, Albuquerque, New Mexico, USA
- Kidney Institute of New Mexico, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Benjamin H McMahon
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, USA
| | - Curt H Hagedorn
- Medicine Service, New Mexico VA Health Care System, Albuquerque, New Mexico, USA
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Hawn SE, Zhao X, Sullivan DR, Logue M, Fein-Schaffer D, Milberg W, McGlinchey R, Miller MW, Wolf EJ. For whom the bell tolls: psychopathological and neurobiological correlates of a DNA methylation index of time-to-death. Transl Psychiatry 2022; 12:406. [PMID: 36153327 PMCID: PMC9509393 DOI: 10.1038/s41398-022-02164-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 09/06/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
Psychopathology is a risk factor for accelerated biological aging and early mortality. We examined associations between broad underlying dimensions of psychopathology (reflecting internalizing and externalizing psychiatric symptoms), PTSD, and age-adjusted GrimAge ("GrimAge residuals"), a DNA methylation biomarker of mortality risk relative to age. We also examined neurobiological correlates of GrimAge residuals, including neurocognitive functioning, blood-based biomarkers (of inflammation, neuropathology, metabolic disease), and cortical thickness. Data from two independent trauma-exposed military cohorts (n = 647 [62.9% male, Mage = 52], n = 434 [90% male, Mage = 32]) were evaluated using linear regression models to test associations between GrimAge residuals, psychopathology, and health correlates. Externalizing psychopathology significantly predicted GrimAge residuals in both cohorts (ps < 0.028). PTSD predicted GrimAge residuals in the younger (p = 0.001) but not the older cohort. GrimAge residuals were associated with several neurobiological variables available in the younger cohort, including cognitive disinhibition (padj = 0.021), poorer memory recall (padj = 0.023), cardiometabolic pathology (padj < 0.001), oxidative stress (padj = 0.003), astrocyte damage (padj = 0.021), inflammation (C-reactive protein: padj < 0.001; IL-6: padj < 0.001), and immune functioning (padj < 0.001). A subset of inflammatory and neuropathology analytes were available in the older cohort and showed associations with GrimAge residuals (IL-6: padj < 0.001; TNF-α: padj < 0.001). GrimAge residuals were also associated with reduced cortical thickness in right lateral orbitofrontal cortex (padj = 0.018) and left fusiform gyrus (padj = 0.030), which are related to emotion regulation and facial recognition, respectively. Psychopathology may be a common risk factor for elevated mortality risk. GrimAge could help identify those at risk for adverse health outcomes and allow for early disease identification and treatment.
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Affiliation(s)
- Sage E Hawn
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA
- Department of Psychology, Old Dominion University, Mills Godwin Bldg (134A), Norfolk, VA, USA
| | - Xiang Zhao
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA
| | - Danielle R Sullivan
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA
| | - Mark Logue
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA
- Boston University School of Medicine, Department of Medicine, Biomedical Genetics, Boston, MA, USA
- Boston University School of Public Health, Department of Biostatistics, Boston, MA, USA
| | - Dana Fein-Schaffer
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
| | - William Milberg
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Regina McGlinchey
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Mark W Miller
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA
| | - Erika J Wolf
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA.
- Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA.
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16
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Yan G, Nee R, Scialla JJ, Greene T, Yu W, Cheung AK, Norris KC. Estimation of Black-White Disparities in CKD Outcomes: Comparison Using the 2021 Versus the 2009 CKD-EPI Creatinine Equations. Am J Kidney Dis 2022; 80:423-426. [PMID: 35007626 PMCID: PMC10118241 DOI: 10.1053/j.ajkd.2021.12.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 12/03/2021] [Indexed: 01/27/2023]
Affiliation(s)
- Guofen Yan
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia.
| | - Robert Nee
- Nephrology Service, Walter Reed National Military Medical Center, Bethesda, Maryland; Department of Medicine, Uniformed Services University, Bethesda, Maryland
| | - Julia J Scialla
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia; Division of Nephrology, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Tom Greene
- Division of Biostatistics, University of Utah School of Medicine, Salt Lake City, Utah
| | - Wei Yu
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Alfred K Cheung
- Division of Nephrology & Hypertension, Department of Internal Medicine, University of Utah, Salt Lake City, Utah; Renal Section, Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Keith C Norris
- Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
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17
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Choi SH, Nguyen H, Kanjwal S, Ibrahim I, Bat T, Thomas A, Jeon-Slaughter H. COVID-19 associated Venous Thromboembolism (VTE) burden in Black women: Findings of Veterans Affairs COVID-19 Shared Data. Thromb Res 2022; 217:60-63. [PMID: 35908381 PMCID: PMC9303072 DOI: 10.1016/j.thromres.2022.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/03/2022] [Accepted: 07/18/2022] [Indexed: 12/04/2022]
Affiliation(s)
- Sung-Hee Choi
- Veterans Affairs North Texas Health Care System, Dallas, TX, United States of America; Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Hang Nguyen
- Veterans Affairs North Texas Health Care System, Dallas, TX, United States of America; Southern Methodist University, Dallas, TX, United States of America
| | - Shifa Kanjwal
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Ibrahim Ibrahim
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Taha Bat
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Abey Thomas
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Haekyung Jeon-Slaughter
- Veterans Affairs North Texas Health Care System, Dallas, TX, United States of America; Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States of America.
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Tang F, Hammel IS, Andrew MK, Ruiz JG. COVID-19 mRNA vaccine effectiveness against hospitalisation and death in veterans according to frailty status during the SARS-CoV-2 delta (B.1.617.2) variant surge in the USA: a retrospective cohort study. Lancet Healthy Longev 2022; 3:e589-e598. [PMID: 35935474 PMCID: PMC9342932 DOI: 10.1016/s2666-7568(22)00166-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Background Studies have shown that COVID-19 vaccination is effective at preventing infection and death in older populations. However, whether vaccination effectiveness is reduced in patients with frailty is unclear. We aimed to compare vaccine effectiveness against hospitalisation and death after COVID-19 during the surge of the delta (B.1.617.2) variant of SARS-CoV-2 according to patients' frailty status. Methods In this retrospective cohort study, we used data derived from the US Veterans Health Administration (VHA) facilities and the US Department of Veterans Affairs (VA) COVID-19 Shared Data Resource, which contains information from the VA National Surveillance Tool, death certificates, and National Cemetery Administration. We included veterans aged 19 years or older who tested positive for SARS-CoV-2 using RT-PCR or antigen tests between July 25 and Sept 30, 2021, with no record of a previous positive test. Deaths were identified through VHA facilities, death certificates, and National Cemetery Administration data available from VA databases. We also retrieved data including sociodemographic characteristics, medical conditions diagnosed at baseline, frailty score, and vaccination information. The primary outcomes were COVID-19-associated hospitalisations and all-cause deaths at 30 days from testing positive for SARS-CoV-2. The odds ratio (OR) for COVID-19-associated hospitalisation and hazard ratio (HR) for death of vaccinated patients compared with the unvaccinated patients were estimated according to frailty categories of robust, pre-frail, or frail. Vaccine effectiveness was estimated as 1 minus the OR for COVID-19-associated hospitalisation, and 1 minus the HR for death. Findings We identified 57 784 veterans (mean age 57·5 years [SD 16·7], 50 642 [87·6%] males, and 40 743 [70·5%] White people), of whom 28 497 (49·3%) were categorised as robust, 16 737 (29·0%) as pre-frail, and 12 550 (21·7%) as frail. There were 2577 all-cause deaths (676 [26·2%] in the vaccinated group and 1901 [73·8%] in the unvaccinated group), and 7857 COVID-19-associated hospitalisations (2749 [35·0%] in the vaccinated group and 5108 [65·0%] in the unvaccinated group) within 30 days of a positive SARS-CoV-2 test. Vaccine effectiveness against COVID-19-associated hospitalisation within 30 days of a positive SARS-CoV-2 test was 65% (95% CI 61-69) in the robust group, 54% (48-58) in the pre-frail group, and 36% (30-42) in the frail group. By 30 days of a positive SARS-CoV-2 test, the vaccine effectiveness for all-cause death was 79% (95% CI 74-84) in the robust group, 79% (75-83) in the pre-frail group, and 68% (63-71) in the frail group. Interpretation Compared with non-frail patients (pre-frail and robust), those with frailty had lower levels of vaccination protection against COVID-19-associated hospitalisation and all-cause death. Future studies investigating COVID-19 vaccine effectiveness should incorporate frailty assessments and actively recruit older adults with frailty. Funding Miami VA Healthcare System Geriatric Research Education and Clinical Center.
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Affiliation(s)
- Fei Tang
- Geriatric Research Education and Clinical Center, Miami VA Healthcare System, Miami, FL, USA
| | - Iriana S Hammel
- Geriatric Research Education and Clinical Center, Miami VA Healthcare System, Miami, FL, USA
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Melissa K Andrew
- Department of Medicine (Geriatrics) and Canadian Center for Vaccinology, Dalhousie University, Halifax, NS, Canada
| | - Jorge G Ruiz
- Geriatric Research Education and Clinical Center, Miami VA Healthcare System, Miami, FL, USA
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
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Affiliation(s)
- Florian B Mayr
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA
| | - Victor B Talisa
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA
| | - Obaid Shaikh
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA
| | - Sachin Yende
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA
| | - Adeel A Butt
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA
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20
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Dickerman BA, Gerlovin H, Madenci AL, Kurgansky KE, Ferolito BR, Figueroa Muñiz MJ, Gagnon DR, Gaziano JM, Cho K, Casas JP, Hernán MA. Comparative Effectiveness of BNT162b2 and mRNA-1273 Vaccines in U.S. Veterans. N Engl J Med 2022; 386:105-115. [PMID: 34942066 PMCID: PMC8693691 DOI: 10.1056/nejmoa2115463] [Citation(s) in RCA: 143] [Impact Index Per Article: 71.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND The messenger RNA (mRNA)-based vaccines BNT162b2 and mRNA-1273 are more than 90% effective against coronavirus disease 2019 (Covid-19). However, their comparative effectiveness for a range of outcomes across diverse populations is unknown. METHODS We emulated a target trial using the electronic health records of U.S. veterans who received a first dose of the BNT162b2 or mRNA-1273 vaccine between January 4 and May 14, 2021, during a period marked by predominance of the SARS-CoV-2 B.1.1.7 (alpha) variant. We matched recipients of each vaccine in a 1:1 ratio according to their risk factors. Outcomes included documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, symptomatic Covid-19, hospitalization for Covid-19, admission to an intensive care unit (ICU) for Covid-19, and death from Covid-19. We estimated risks using the Kaplan-Meier estimator. To assess the influence of the B.1.617.2 (delta) variant, we emulated a second target trial that involved veterans vaccinated between July 1 and September 20, 2021. RESULTS Each vaccine group included 219,842 persons. Over 24 weeks of follow-up in a period marked by alpha-variant predominance, the estimated risk of documented infection was 5.75 events per 1000 persons (95% confidence interval [CI], 5.39 to 6.23) in the BNT162b2 group and 4.52 events per 1000 persons (95% CI, 4.17 to 4.84) in the mRNA-1273 group. The excess number of events per 1000 persons for BNT162b2 as compared with mRNA-1273 was 1.23 (95% CI, 0.72 to 1.81) for documented infection, 0.44 (95% CI, 0.25 to 0.70) for symptomatic Covid-19, 0.55 (95% CI, 0.36 to 0.83) for hospitalization for Covid-19, 0.10 (95% CI, 0.00 to 0.26) for ICU admission for Covid-19, and 0.02 (95% CI, -0.06 to 0.12) for death from Covid-19. The corresponding excess risk (BNT162b2 vs. mRNA-1273) of documented infection over 12 weeks of follow-up in a period marked by delta-variant predominance was 6.54 events per 1000 persons (95% CI, -2.58 to 11.82). CONCLUSIONS The 24-week risk of Covid-19 outcomes was low after vaccination with mRNA-1273 or BNT162b2, although risks were lower with mRNA-1273 than with BNT162b2. This pattern was consistent across periods marked by alpha- and delta-variant predominance. (Funded by the Department of Veterans Affairs and others.).
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Affiliation(s)
- Barbra A Dickerman
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Hanna Gerlovin
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Arin L Madenci
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Katherine E Kurgansky
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Brian R Ferolito
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Michael J Figueroa Muñiz
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - David R Gagnon
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - J Michael Gaziano
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Kelly Cho
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Juan P Casas
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
| | - Miguel A Hernán
- From CAUSALab (B.A.D., A.L.M., M.A.H.) and the Departments of Epidemiology (B.A.D., A.L.M., M.A.H.) and Biostatistics (M.A.H.), Harvard T.H. Chan School of Public Health, Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System (H.G., K.E.K., B.R.F., M.J.F.M., D.R.G., J.M.G., K.C., J.P.C.), the Department of Surgery (A.L.M.) and Division of Aging (J.M.G., K.C., J.P.C.), Brigham and Women's Hospital, Harvard Medical School, and the Department of Biostatistics (M.J.F.M., D.R.G.), Boston University School of Public Health - all in Boston
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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. Int J Environ Res 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] [What about the content of this article? (0)] [Affiliation(s)] [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.
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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
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22
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Reyes C, Pistillo A, Fernández-Bertolín S, Recalde M, Roel E, Puente D, Sena AG, Blacketer C, Lai L, Alshammari TM, Ahmed WUR, Alser O, Alghoul H, Areia C, Dawoud D, Prats-Uribe A, Valveny N, de Maeztu G, Sorlí Redó L, Martinez Roldan J, Lopez Montesinos I, Schilling LM, Golozar A, Reich C, Posada JD, Shah N, You SC, Lynch KE, DuVall SL, Matheny ME, Nyberg F, Ostropolets A, Hripcsak G, Rijnbeek PR, Suchard MA, Ryan P, Kostka K, Duarte-Salles T. Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension: a multinational cohort study. BMJ Open 2021; 11:e057632. [PMID: 34937726 PMCID: PMC8704062 DOI: 10.1136/bmjopen-2021-057632] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 11/09/2021] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVE To characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients. DESIGN AND SETTING This is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020. PARTICIPANTS Two non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days. OUTCOMES Demographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported. RESULTS We identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension. CONCLUSIONS COVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension.
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Affiliation(s)
- Carlen Reyes
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Andrea Pistillo
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Sergio Fernández-Bertolín
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Martina Recalde
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Elena Roel
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Diana Puente
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Anthony G Sena
- Janssen Research and Development Titusville, Titusville, New Jersey, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Clair Blacketer
- Janssen Research and Development Titusville, Titusville, New Jersey, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lana Lai
- School of Medical Sciences, The University of Manchester, Manchester, UK
| | | | - Waheed-Ui-Rahman Ahmed
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Center, Oxford, UK
- College of Medicine and Health, University of Exeter, St Luke's Campus, Exeter, UK
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Dalia Dawoud
- National Institute for Health and Care Excellence (NICE), London, UK
- Faculty of Pharmacy, Cairo University, Cairo, Egypt
| | - Albert Prats-Uribe
- Center for Statistics in Medicine, NDORMS, University of Oxford, Botnar Research Center, Nuffield Orthopaedic Center, Oxford, UK
| | | | | | - Luisa Sorlí Redó
- Universitat Autonoma de Barcelona, Barcelona, Spain
- Department of Infectious Diseases, Hospital del Mar, Institut Hospital del Mar d'Investigació Mèdica (IMIM), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Jordi Martinez Roldan
- Director of Innovation and Digital Transformation, Hospital del Mar, Barcelona, Spain
| | - Inmaculada Lopez Montesinos
- Department of Infectious Diseases, Hospital del Mar, Institut Hospital del Mar d'Investigació Mèdica (IMIM), Barcelona, Spain
| | - Lisa M Schilling
- University of Colorado - Anschutz Medical Campus, Aurora, Colorado, USA
| | - Asieh Golozar
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | - Jose D Posada
- Stanford University School of Medicine, Stanford, California, USA
| | - Nigam Shah
- Stanford University School of Medicine, Stanford, California, USA
| | - Seng Chan You
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea (the Republic of)
| | - Kristine E Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, The University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, The University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Michael E Matheny
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, The University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
- Medical Informatics Services, New York-Presbyterial Hospital, New York, NY, USA
| | - Peter R Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Marc A Suchard
- Department of Biostatistics, Fielding School of Publich Health, University of California, Los Angeles, California, USA
| | - Patrick Ryan
- Janssen Research and Development Titusville, Titusville, New Jersey, USA
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Kristin Kostka
- Real-World Solutions, IQVIA, Cambridge, Massachusetts, USA
- The OHDSI Center at the Roux Institute, Northeastern University, Portland, ME, USA
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
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23
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Guzman-Clark J, Wakefield BJ, Farmer MM, Yefimova M, Viernes B, Lee ML, Hahn TJ. Adherence to the Use of Home Telehealth Technologies and Emergency Room Visits in Veterans with Heart Failure. Telemed J E Health 2021; 27:1003-1010. [PMID: 33275527 PMCID: PMC8172647 DOI: 10.1089/tmj.2020.0312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background: Prior studies have posited poor patient adherence to remote patient monitoring as the reason for observed lack of benefits. Introduction: The purpose of this study was to examine the relationship between average adherence to the daily use of home telehealth (HT) and emergency room (ER) visits in Veterans with heart failure. Materials and Methods: This was a retrospective study using administrative data of Veterans with heart failure enrolled in Veterans Affairs (VA) HT Program in the first half of 2014. Zero-inflated negative binomial regression was used to determine which predictors affect the probability of having an ER visit and the number of ER visits. Results: The final sample size was 3,449 with most being white and male. There were fewer ER visits after HT enrollment (mean ± standard deviation of 1.85 ± 2.8) compared with the year before (2.2 ± 3.4). Patient adherence was not significantly associated with ER visits. Age and being from a racial minority group (not white or black) and belonging to a large HT program were associated with having an ER visit. Being in poorer health was associated with higher expected count of ER visits. Discussion: Subgroups of patients (e.g., with depression, sicker, or from a racial minority group) may benefit from added interventions to decrease ER use. Conclusions: This study found that adherence was not associated with ER visits. Reasons other than adherence should be considered when looking at ER use in patients with heart failure enrolled in remote patient monitoring programs.
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Affiliation(s)
| | - Bonnie J Wakefield
- Comprehensive Access & Delivery Research & Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, Iowa, USA
- Sinclair School of Nursing, University of Missouri, Columbia Missouri, USA
| | - Melissa M Farmer
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, California, USA
| | - Maria Yefimova
- VA/UCLA National Clinician Scholar, Los Angeles, California, USA
- Office of Research Patient Care Services Stanford Healthcare, Stanford, California, USA
| | - Benjamin Viernes
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Martin L Lee
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, California, USA
- Department of Biostatistics, University of California Los Angeles (UCLA) Fielding School of Public Health Los Angeles, California, USA
| | - Theodore J Hahn
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, California, USA
- Geriatric Research, Education and Clinical Center (GRECC), VA Greater Los Angeles Healthcare System, Los Angeles, California, USA
- Department of Medicine, UCLA School of Medicine, Los Angeles, California, USA
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24
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Lane JCE, Weaver J, Kostka K, Duarte-Salles T, Abrahao MTF, Alghoul H, Alser O, Alshammari TM, Areia C, Biedermann P, Banda JM, Burn E, Casajust P, Fister K, Hardin J, Hester L, Hripcsak G, Kaas-Hansen BS, Khosla S, Kolovos S, Lynch KE, Makadia R, Mehta PP, Morales DR, Morgan-Stewart H, Mosseveld M, Newby D, Nyberg F, Ostropolets A, Woong Park R, Prats-Uribe A, Rao GA, Reich C, Rijnbeek P, Sena AG, Shoaibi A, Spotnitz M, Subbian V, Suchard MA, Vizcaya D, Wen H, de Wilde M, Xie J, You SC, Zhang L, Lovestone S, Ryan P, Prieto-Alhambra D. Risk of depression, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis: a multinational network cohort study. Rheumatology (Oxford) 2021; 60:3222-3234. [PMID: 33367863 PMCID: PMC7798671 DOI: 10.1093/rheumatology/keaa771] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [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: 08/13/2020] [Revised: 10/19/2020] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES Concern has been raised in the rheumatology community regarding recent regulatory warnings that HCQ used in the coronavirus disease 2019 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation or psychosis associated with HCQ as used for RA. METHODS We performed a new-user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and USA). RA patients ≥18 years of age and initiating HCQ were compared with those initiating SSZ (active comparator) and followed up in the short (30 days) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HRs), with estimates pooled where I2 <40%. RESULTS A total of 918 144 and 290 383 users of HCQ and SSZ, respectively, were included. No consistent risk of psychiatric events was observed with short-term HCQ (compared with SSZ) use, with meta-analytic HRs of 0.96 (95% CI 0.79, 1.16) for depression, 0.94 (95% CI 0.49, 1.77) for suicide/suicidal ideation and 1.03 (95% CI 0.66, 1.60) for psychosis. No consistent long-term risk was seen, with meta-analytic HRs of 0.94 (95% CI 0.71, 1.26) for depression, 0.77 (95% CI 0.56, 1.07) for suicide/suicidal ideation and 0.99 (95% CI 0.72, 1.35) for psychosis. CONCLUSION HCQ as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation or psychosis compared with SSZ. No effects were seen in the short or long term. Use at a higher dose or for different indications needs further investigation. TRIAL REGISTRATION Registered with EU PAS (reference no. EUPAS34497; http://www.encepp.eu/encepp/viewResource.htm? id=34498). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine2.
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Affiliation(s)
- Jennifer C E Lane
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - James Weaver
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | | | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thamir M Alshammari
- Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | | | - Edward Burn
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Paula Casajust
- Real-World Evidence, Trial Form Support, Barcelona,Spain
| | - Kristina Fister
- School of Medicine, Andrija Štampar School of Public Health, University of Zagreb, Zagreb, Croatia
| | - Jill Hardin
- Janssen Research and Development, Titusville, NJ, USA
| | - Laura Hester
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Benjamin Skov Kaas-Hansen
- Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark
- NNF Centre for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Sajan Khosla
- Real World Science & Digital, AstraZeneca, Cambridge, UK
| | - Spyros Kolovos
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Kristine E Lynch
- Department of Veterans Affairs, Salt Lake City, UT, USA
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | - Paras P Mehta
- College of Medicine, University of Arizona, Tucson, AZ, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, UK
| | | | - Mees Mosseveld
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon-si, Gyeonggi-do, South Korea
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Gowtham A Rao
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Anthony G Sena
- Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Matthew Spotnitz
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Vignesh Subbian
- College of Engineering, University of Arizona, Tucson, AZ, USA
| | - Marc A Suchard
- Departments of Biomathematics and Human Genetics David Geffen School of Medicine at UCLA, and Department of Biostatistics, UCLA School of Public Health, South Los Angeles, CA, USA
| | - David Vizcaya
- Bayer Pharmaceuticals, Sant Joan Despi, Barcelona, Spain
| | - Haini Wen
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Marcel de Wilde
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Junqing Xie
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon-si, Gyeonggi-do, South Korea
| | - Lin Zhang
- School of Public Health, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, P.R. China
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Simon Lovestone
- Janssen-Cilag, 50-100 Holmers Farm Way, High Wycombe HP12 4EG, UK
| | - Patrick Ryan
- Janssen Research and Development, Titusville, NJ, USA
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
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25
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Keaton JM, Hellwege JN, Giri A, Torstenson ES, Kovesdy CP, Sun YV, Wilson PW, O’Donnell CJ, Edwards TL, Hung AM, Velez Edwards DR. Associations of biogeographic ancestry with hypertension traits. J Hypertens 2021; 39:633-642. [PMID: 33534346 PMCID: PMC8362794 DOI: 10.1097/hjh.0000000000002701] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Ethnic disparities in hypertension prevalence are well documented, though the influence of genetic ancestry is unclear. The aim of this study was to evaluate associations of geographic genetic ancestry with hypertension and underlying blood pressure traits. METHODS We tested genetically inferred ancestry proportions from five 1000 Genomes reference populations (GBR, PEL, YRI, CHB, and LWK) for association with four continuous blood pressure (BP) traits (SBP, DBP, PP, MAP) and the dichotomous outcomes hypertension and apparent treatment-resistant hypertension in 220 495 European American, 59 927 African American, and 21 273 Hispanic American individuals from the Million Veteran Program. Ethnicity stratified results were meta-analyzed to report effect estimates per 10% difference for a given ancestry proportion in all samples. RESULTS Percentage GBR was negatively associated with BP (P = 2.13 × 10-19, 7.92 × 10-8, 4.41 × 10-11, and 3.57 × 10-13 for SBP, DBP, PP, and MAP, respectively; coefficient range -0.10 to -0.21 mmHg per 10% increase in ancestry proportion) and was protective against hypertension [P = 2.59 × 10-5, odds ratio (OR) = 0.98] relative to other ancestries. YRI percentage was positively associated with BP (P = 1.63 × 10-23, 1.94 × 10-26, 0.012, and 3.26 × 10-29 for SBP, DBP, PP, and MAP, respectively; coefficient range 0.06-0.32 mmHg per 10% increase in ancestry proportion) and was positively associated with hypertension risk (P = 3.10 × 10-11, OR = 1.04) and apparent treatment-resistant hypertension risk (P = 1.86 × 10-4, OR = 1.04) compared with other ancestries. Percentage PEL was inversely associated with DBP (P = 2.84 × 10-5, beta = -0.11 mmHg per 10% increase in ancestry proportion). CONCLUSION These results demonstrate that risk for BP traits varies significantly by genetic ancestry. Our findings provide insight into the geographic origin of genetic factors underlying hypertension risk and establish that a portion of BP trait ethnic disparities are because of genetic differences between ancestries.
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Affiliation(s)
- Jacob M. Keaton
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center
- Van-Vanderbilt Genetics Institute, Vanderbilt University
- Institute for Medicine and Public Health, Vanderbilt University Medical Center
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University
| | - Jacklyn N. Hellwege
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center
- Van-Vanderbilt Genetics Institute, Vanderbilt University
- Institute for Medicine and Public Health, Vanderbilt University Medical Center
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University
| | - Ayush Giri
- Van-Vanderbilt Genetics Institute, Vanderbilt University
- Institute for Medicine and Public Health, Vanderbilt University Medical Center
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University
- Di-Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center
| | - Eric S. Torstenson
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University
| | - Csaba P. Kovesdy
- Nephrology Section, Memphis VA Medical Center, Memphis, Nashville, Tennessee
| | - Yan V. Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Department of Biomedical Informatics, Emory University School of Medicine
| | - Peter W.F. Wilson
- Atlanta VAMC and Emory Clinical Cardiovascular Research Institute, Atlanta, Georgia
| | - Christopher J. O’Donnell
- VA Boston Healthcare, Section of Cardiology and Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Todd L. Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center
- Van-Vanderbilt Genetics Institute, Vanderbilt University
- Institute for Medicine and Public Health, Vanderbilt University Medical Center
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University
| | - Adriana M. Hung
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University
- Division of Nephrology and Hypertension, Department of Medicine
| | - Digna R. Velez Edwards
- Van-Vanderbilt Genetics Institute, Vanderbilt University
- Institute for Medicine and Public Health, Vanderbilt University Medical Center
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University
- Di-Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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26
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Nishimura A, Xie J, Kostka K, Duarte-Salles T, Bertolín SF, Aragón M, Blacketer C, Shoaibi A, DuVall SL, Lynch K, Matheny ME, Falconer T, Morales DR, Conover MM, You SC, Pratt N, Weaver J, Sena AG, Schuemie MJ, Reps J, Reich C, Rijnbeek PR, Ryan PB, Hripcsak G, Prieto-Alhambra D, Suchard MA. Alpha-1 blockers and susceptibility to COVID-19 in benign prostate hyperplasia patients : an international cohort study. medRxiv 2021:2021.03.18.21253778. [PMID: 33791740 PMCID: PMC8010772 DOI: 10.1101/2021.03.18.21253778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Alpha-1 blockers, often used to treat benign prostate hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storms release. We conducted a prevalent-user active-comparator cohort study to assess association between alpha-1 blocker use and risks of three COVID-19 outcomes: diagnosis, hospitalization, and hospitalization requiring intensive services. Our study included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH therapy during the period between November 2019 and January 2020, found in electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We found no differential risk for any of COVID-19 outcome, pointing to the need for further research on potential COVID-19 therapies.
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Affiliation(s)
| | - Junqing Xie
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford University, Oxford, UK
| | - Kristin Kostka
- Real World Solutions, IQVIA, Cambridge, MA, USA
- The OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, USA
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Sergio Fernández Bertolín
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - María Aragón
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Clair Blacketer
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Azza Shoaibi
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Kristine Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Michael E Matheny
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, UK
- Department of Public Health, University of Southern Denmark, Denmark
| | - Mitchell M Conover
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Seng Chan You
- Department of Preventive Medicine and Public Health, Yonsei University College of Medicine, Seoul, Korea
| | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, Australia
| | - James Weaver
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - Anthony G Sena
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Martijn J Schuemie
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jenna Reps
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | | | - Peter R Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Patrick B Ryan
- Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford University, Oxford, UK
| | - Marc A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA
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27
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Burn E, You SC, Sena AG, Kostka K, Abedtash H, Abrahão MTF, Alberga A, Alghoul H, Alser O, Alshammari TM, Aragon M, Areia C, Banda JM, Cho J, Culhane AC, Davydov A, DeFalco FJ, Duarte-Salles T, DuVall S, Falconer T, Fernandez-Bertolin S, Gao W, Golozar A, Hardin J, Hripcsak G, Huser V, Jeon H, Jing Y, Jung CY, Kaas-Hansen BS, Kaduk D, Kent S, Kim Y, Kolovos S, Lane JCE, Lee H, Lynch KE, Makadia R, Matheny ME, Mehta PP, Morales DR, Natarajan K, Nyberg F, Ostropolets A, Park RW, Park J, Posada JD, Prats-Uribe A, Rao G, Reich C, Rho Y, Rijnbeek P, Schilling LM, Schuemie M, Shah NH, Shoaibi A, Song S, Spotnitz M, Suchard MA, Swerdel JN, Vizcaya D, Volpe S, Wen H, Williams AE, Yimer BB, Zhang L, Zhuk O, Prieto-Alhambra D, Ryan P. Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study. Nat Commun 2020; 11:5009. [PMID: 33024121 PMCID: PMC7538555 DOI: 10.1038/s41467-020-18849-z] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 09/10/2020] [Indexed: 01/08/2023] Open
Abstract
Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.
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Affiliation(s)
- Edward Burn
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
| | - Anthony G Sena
- Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | | | | | - Amanda Alberga
- Observational Health Data Sciences and Informatics Network, Alberta, Canada
| | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thamir M Alshammari
- Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia
| | - Maria Aragon
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Juan M Banda
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Jaehyeong Cho
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
| | - Aedin C Culhane
- Data Science, Dana-Farber Cancer Institute. Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Alexander Davydov
- Odysseus Data Services, Inc., Cambridge, MA, USA
- Department for Microbiology, Virology and Immunology, Belarusian State Medical University, Minsk, Belarus
| | | | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Scott DuVall
- Department of Veterans Affairs, Salt Lake City, UT, USA
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Weihua Gao
- Health Economics and Outcomes Research, AbbVie, North Chicago, IL, USA
| | - Asieh Golozar
- Pharmacoepidemiology, Regeneron, NY, USA
- Department of Epidemiology, Johns Hopkins School of Public, Baltimore, MD, USA
| | - Jill Hardin
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Vojtech Huser
- National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Hokyun Jeon
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Yonghua Jing
- Health Economics and Outcomes Research, AbbVie, North Chicago, IL, USA
| | - Chi Young Jung
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Daegu Catholic University Medical Center, Daegu, Korea
| | - Benjamin Skov Kaas-Hansen
- Clinical Pharmacology Unit, Zealand University Hospital, Køge, Denmark
- NNF Centre for Protein Research, University of Copenhagen, København, Denmark
| | - Denys Kaduk
- Odysseus Data Services, Inc., Cambridge, MA, USA
- Department of Pediatrics № 2, V. N. Karazin Kharkiv National University, Kharkiv, Ukraine
| | - Seamus Kent
- Science Policy and Research, National Institute for Health and Care Excellence, London, UK
| | - Yeesuk Kim
- Department of Orthopaedic Surgery, College of Medicine, Hanyang University, Seoul, Korea
| | - Spyros Kolovos
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Jennifer C E Lane
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Hyejin Lee
- Bigdata Department, Health Insurance Review & Assessment Service, Wonju, Korea
| | - Kristine E Lynch
- Department of Veterans Affairs, Salt Lake City, UT, USA
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | - Michael E Matheny
- GRECC, Tennessee Valley Healthcare System VA, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paras P Mehta
- College of Medicine-Tucson, University of Arizona, Tucson, AZ, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, UK
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Jimyung Park
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Jose D Posada
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Gowtham Rao
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Yeunsook Rho
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lisa M Schilling
- Data Science to Patient Value Program, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Martijn Schuemie
- Janssen Research and Development, Titusville, NJ, USA
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Nigam H Shah
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Seokyoung Song
- Department of Anesthesiology and Pain Medicine, Catholic University of Daegu, School of Medicine, Gyeongsan, Korea
| | - Matthew Spotnitz
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Marc A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | | | | | - Salvatore Volpe
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Haini Wen
- Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Andrew E Williams
- Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, USA
| | - Belay B Yimer
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Lin Zhang
- School of Public Health, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Oleg Zhuk
- Odysseus Data Services, Inc., Cambridge, MA, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK.
| | - Patrick Ryan
- Janssen Research and Development, Titusville, NJ, USA
- Columbia University, New York, NY, USA
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Cheng ZY, Chueh FS, Peng SF, Lin CH, Kuo CL, Huang WW, Chen PY, Way TD, Chung JG. Combinational treatment of 5-fluorouracil and casticin induces apoptosis in mouse leukemia WEHI-3 cells in vitro. Environ Toxicol 2020; 35:911-921. [PMID: 32270916 DOI: 10.1002/tox.22927] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 03/09/2020] [Accepted: 03/20/2020] [Indexed: 06/11/2023]
Abstract
Leukemia is one of the major diseases causing cancer-related deaths in the young population, and its cure rate is unsatisfying with side effects on patients. Fluorouracil (5-FU) is currently used as an anticancer drug for leukemia patients. Casticin, a natural polymethoxyflavone, exerts anticancer activity against many human cancer cell lines in vitro, but no other reports show 5-FU combined with casticin increased the mouse leukemia cell apoptosis in vitro. Herein, the antileukemia activity of 5-FU combined with casticin in WEHI-3 mouse leukemia cells was investigated in vitro. Treatment of two-drug combination had a higher decrease in cell viability and a higher increase in apoptotic cell death, the level of DNA condensation, and the length of comet tail than that of 5-FU or casticin treatment alone in WEHI-3 cells. In addition, the two-drug combination has a greater production rate of reactive oxygen species but a lower level of Ca2+ release and mitochondrial membrane potential (ΔΨm ) than that of 5-FU alone. Combined drugs also induced higher caspase-3 and caspase-8 activities than that of casticin alone and higher caspase-9 activity than that of 5-FU or casticin alone at 48 hours treatment. Furthermore, 5-FU combined with casticin has a higher expression of Cu/Zn superoxide dismutase (SOD [Cu/Zn]) and lower catalase than that of 5-FU or casticin treatment alone. The combined treatment has higher levels of Bax, Endo G, and cytochrome C of proapoptotic proteins than that of casticin alone and induced lower levels of B-cell lymphoma 2 (BCL-2) and BCL-X of antiapoptotic proteins than that of 5-FU or casticin only. Furthermore, the combined treatment had a higher expression of cleaved poly (ADP-ribose) polymerase (PARP) than that of casticin only. Based on these findings, we may suggest that 5-FU combined with casticin treatment increased apoptotic cell death in WEHI-3 mouse leukemia cells that may undergo mitochondria and caspases signaling pathways in vitro.
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Affiliation(s)
- Zheng-Yu Cheng
- Department of Biological Science and Technology, China Medical University, Taichung, Taiwan
| | - Fu-Shin Chueh
- Department of Food Nutrition and Health Biotechnology, Asia University, Taichung, Taiwan
| | - Shu-Fen Peng
- Department of Biological Science and Technology, China Medical University, Taichung, Taiwan
- Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Chia-Hsin Lin
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung, Taiwan
| | - Chao-Lin Kuo
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung, Taiwan
| | - Wen-Wen Huang
- Department of Biological Science and Technology, China Medical University, Taichung, Taiwan
| | - Po-Yuan Chen
- Department of Biological Science and Technology, China Medical University, Taichung, Taiwan
| | - Tzong-Der Way
- Department of Biological Science and Technology, China Medical University, Taichung, Taiwan
| | - Jing-Gung Chung
- Department of Biological Science and Technology, China Medical University, Taichung, Taiwan
- Department of Biotechnology, College of Medical and Health Science, Asia University, Taichung, Taiwan
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Guzman-Clark J, Yefimova M, Farmer MM, Wakefield BJ, Viernes B, Lee ML, Hahn TJ. Home Telehealth Technologies for Heart Failure: An Examination of Adherence Among Veterans. J Gerontol Nurs 2020; 46:26-34. [PMID: 32597998 PMCID: PMC7375894 DOI: 10.3928/00989134-20200605-05] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The current retrospective cohort study uses Department of Veterans Affairs (VA) clinical and facility data of Veterans with heart failure enrolled in the VA Home Tele-health (HT) Program. General estimating equations with facility as a covariate were used to model percent average adherence at 1, 3, 6, and 12 months post-enrollment. Most HT patients were White, male, and of older age (mean = 71 years). Average adherence increased the longer patients remained in the HT program. Number of weekly reports of HT use, not having depression, and being of older age were all associated with higher adherence. Compared to White Veterans, Black and other non-White Veterans had lower adherence. These findings identify subgroups of patients (e.g., those with depression, of younger age, non-White) that may benefit from additional efforts to improve adherence to HT technologies. [Journal of Gerontological Nursing, 46(7), 26-34.].
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30
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Mosley JD, Levinson RT, Farber-Eger E, Edwards TL, Hellwege JN, Hung AM, Giri A, Shuey MM, Shaffer CM, Shi M, Brittain EL, Chung WK, Kullo IJ, Arruda-Olson AM, Jarvik GP, Larson EB, Crosslin DR, Williams MS, Borthwick KM, Hakonarson H, Denny JC, Wang TJ, Stein CM, Roden DM, Wells QS. The polygenic architecture of left ventricular mass mirrors the clinical epidemiology. Sci Rep 2020; 10:7561. [PMID: 32372017 PMCID: PMC7200691 DOI: 10.1038/s41598-020-64525-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [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: 09/15/2019] [Accepted: 04/16/2020] [Indexed: 02/07/2023] Open
Abstract
Left ventricular (LV) mass is a prognostic biomarker for incident heart disease and all-cause mortality. Large-scale genome-wide association studies have identified few SNPs associated with LV mass. We hypothesized that a polygenic discovery approach using LV mass measurements made in a clinical population would identify risk factors and diseases associated with adverse LV remodeling. We developed a polygenic single nucleotide polymorphism-based predictor of LV mass in 7,601 individuals with LV mass measurements made during routine clinical care. We tested for associations between this predictor and 894 clinical diagnoses measured in 58,838 unrelated genotyped individuals. There were 29 clinical phenotypes associated with the LV mass genetic predictor at FDR q < 0.05. Genetically predicted higher LV mass was associated with modifiable cardiac risk factors, diagnoses related to organ dysfunction and conditions associated with abnormal cardiac structure including heart failure and atrial fibrillation. Secondary analyses using polygenic predictors confirmed a significant association between higher LV mass and body mass index and, in men, associations with coronary atherosclerosis and systolic blood pressure. In summary, these analyses show that LV mass-associated genetic variability associates with diagnoses of cardiac diseases and with modifiable risk factors which contribute to these diseases.
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Affiliation(s)
- Jonathan D Mosley
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Rebecca T Levinson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Eric Farber-Eger
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Todd L Edwards
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jacklyn N Hellwege
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Tennessee Valley Healthcare System (626), Vanderbilt University, Nashville, TN, USA
| | - Adriana M Hung
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Tennessee Valley Healthcare System (626), Vanderbilt University, Nashville, TN, USA
| | - Ayush Giri
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Megan M Shuey
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christian M Shaffer
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mingjian Shi
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Evan L Brittain
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wendy K Chung
- Office of Research & Development, Department of Veterans Affairs, Washington DC, DC, USA
- Departments of Pediatrics and Medicine, Columbia University Medical Center, New York, NY, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | | | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA
| | - Eric B Larson
- Kaiser Permanente Washington Health Research Institute and Department of Medicine, University of Washington, Seattle, WA, USA
| | - David R Crosslin
- Departments of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | | | - Ken M Borthwick
- Biomedical and Translational Informatics, Geisinger, Danville, PA, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
| | - Joshua C Denny
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Thomas J Wang
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Charles M Stein
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dan M Roden
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quinn S Wells
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
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31
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Singh AB, Dong B, Kraemer FB, Liu J. FXR activation promotes intestinal cholesterol excretion and attenuates hyperlipidemia in SR-B1-deficient mice fed a high-fat and high-cholesterol diet. Physiol Rep 2020; 8:e14387. [PMID: 32170842 PMCID: PMC7070099 DOI: 10.14814/phy2.14387] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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: 11/15/2019] [Revised: 01/27/2020] [Accepted: 01/28/2020] [Indexed: 12/14/2022] Open
Abstract
Obeticholic acid (OCA) activates the farnesoid X receptor (FXR) to lower circulating total cholesterol (TC) and high density lipoprotein-cholesterol (HDL-C) concentrations and to stimulate fecal cholesterol excretion in mice by increasing hepatic SR-B1 expression. Here we show that hepatic SR-B1 depletion by an adenovirus expressing Sr-b1 shRNA (Ad-shSR-B1) attenuated these beneficial effects of OCA in mice on a chow diet. The mRNA levels of ABC cholesterol transporter genes (Abca1, Abcg1, Abcg5, and Abcg8) were unchanged in the liver of hepatic SR-B1-depleted mice regardless of OCA treatment; however, a modest increase in Abca1, Abcg5, and Abcg8 mRNA levels was observed in the ileum of vehicle-treated control mice and Abca1 and Abcg8 mRNA levels were increased more by OCA administration. OCA treatment of Sr-b1 knock out (KO) mice (Sr-b1-/-) fed a normal chow diet (NCD) displayed a similar lack of transhepatic cholesterol movement, as well as a modest increase in the levels of ileum cholesterol transporter expression. However, OCA treatment of Sr-b1 KO mice fed a cholesterol-enriched diet reduced circulating cholesterol and increased fecal cholesterol output to comparable degrees to that of wild-type (WT) mice, and these effects were accompanied by substantial elevations of mRNA levels of Abca1, Abcg1, Abcg5, and Abcg8 in the ileum of Sr-b1 KO mice. Our studies suggest that FXR activation stimulates intestinal cholesterol excretion and reduces diet-induced hyperlipidemia through increased expression of ileal cholesterol transporters when hepatic SR-B1-mediated cholesterol movement is absent.
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Affiliation(s)
- Amar B. Singh
- Veterans Affairs Palo Alto Health Care SystemPalo AltoCAUSA
| | - Bin Dong
- Veterans Affairs Palo Alto Health Care SystemPalo AltoCAUSA
| | - Fredric B. Kraemer
- Veterans Affairs Palo Alto Health Care SystemPalo AltoCAUSA
- Department of MedicineStanford University School of MedicineStanfordCAUSA
| | - Jingwen Liu
- Veterans Affairs Palo Alto Health Care SystemPalo AltoCAUSA
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Klarin D, Busenkell E, Judy R, Lynch J, Levin M, Haessler J, Aragam K, Chaffin M, Haas M, Lindström S, Assimes TL, Huang J, Min Lee K, Shao Q, Huffman JE, Kabrhel C, Huang Y, Sun YV, Vujkovic M, Saleheen D, Miller DR, Reaven P, DuVall S, Boden WE, Pyarajan S, Reiner AP, Trégouët DA, Henke P, Kooperberg C, Gaziano JM, Concato J, Rader DJ, Cho K, Chang KM, Wilson PWF, Smith NL, O'Donnell CJ, Tsao PS, Kathiresan S, Obi A, Damrauer SM, Natarajan P. Genome-wide association analysis of venous thromboembolism identifies new risk loci and genetic overlap with arterial vascular disease. Nat Genet 2019; 51:1574-1579. [PMID: 31676865 PMCID: PMC6858581 DOI: 10.1038/s41588-019-0519-3] [Citation(s) in RCA: 125] [Impact Index Per Article: 25.0] [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: 03/05/2019] [Accepted: 09/24/2019] [Indexed: 12/22/2022]
Abstract
Venous thromboembolism is a significant cause of mortality1, yet its genetic determinants are incompletely defined. We performed a discovery genome-wide association study in the Million Veteran Program and UK Biobank, with testing of approximately 13 million DNA sequence variants for association with venous thromboembolism (26,066 cases and 624,053 controls) and meta-analyzed both studies, followed by independent replication with up to 17,672 venous thromboembolism cases and 167,295 controls. We identified 22 previously unknown loci, bringing the total number of venous thromboembolism-associated loci to 33, and subsequently fine-mapped these associations. We developed a genome-wide polygenic risk score for venous thromboembolism that identifies 5% of the population at an equivalent incident venous thromboembolism risk to carriers of the established factor V Leiden p.R506Q and prothrombin G20210A mutations. Our data provide mechanistic insights into the genetic epidemiology of venous thromboembolism and suggest a greater overlap among venous and arterial cardiovascular disease than previously thought.
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Affiliation(s)
- Derek Klarin
- Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Vascular Surgery and Endovascular Therapy, University of Florida School of Medicine, Gainesville, FL, USA
| | - Emma Busenkell
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Renae Judy
- Corporal Michael Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Julie Lynch
- Veterans Affairs Informatics and Computing Infrastructure, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
- University of Massachusetts College of Nursing & Health Sciences, Boston, MA, USA
| | - Michael Levin
- Corporal Michael Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffery Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Krishna Aragam
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark Chaffin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mary Haas
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sara Lindström
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Themistocles L Assimes
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Jie Huang
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Kyung Min Lee
- Veterans Affairs Informatics and Computing Infrastructure, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
- Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA
- Boston University School of Public Health, Department of Health Law, Policy & Management, Boston, MA, USA
| | - Qing Shao
- Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Christopher Kabrhel
- Center for Vascular Emergencies, Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yunfeng Huang
- Department of Epidemiology, Emory University Rollins School of Public Health, Department of Biomedical Informatics Emory University School of Medicine, Atlanta, GA, USA
- Atlanta Veterans Affairs Health Care System, Decatur, GA, USA
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Department of Biomedical Informatics Emory University School of Medicine, Atlanta, GA, USA
- Atlanta Veterans Affairs Health Care System, Decatur, GA, USA
| | - Marijana Vujkovic
- Corporal Michael Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, Philadelphia, PA, USA
| | - Danish Saleheen
- Corporal Michael Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, Philadelphia, PA, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA
- Boston University School of Public Health, Department of Health Law, Policy & Management, Boston, MA, USA
| | - Peter Reaven
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ, USA
| | - Scott DuVall
- Veterans Affairs Informatics and Computing Infrastructure, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - William E Boden
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Saiju Pyarajan
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - David-Alexandre Trégouët
- Bordeaux Population Health Research Center (INSERM UMR S 1219), University of Bordeaux, Bordeaux, France
| | - Peter Henke
- Section of Vascular Surgery, Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - John Concato
- Clinical Epidemiology Research Center, Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Daniel J Rader
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kyong-Mi Chang
- Corporal Michael Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter W F Wilson
- Atlanta Veterans Affairs Health Care System, Decatur, GA, USA
- Emory Clinical Cardiovascular Research Institute, Atlanta, GA, USA
| | - Nicholas L Smith
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Christopher J O'Donnell
- Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Cardiovascular Medicine Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Philip S Tsao
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Sekar Kathiresan
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Andrea Obi
- Section of Vascular Surgery, Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Scott M Damrauer
- Corporal Michael Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pradeep Natarajan
- Veterans Affairs Boston Healthcare System, Boston, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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Abstract
Urodynamic studies are a key component of the clinical evaluation of lower urinary tract dysfunction and include filling cystometry, pressure-flow studies, uroflowmetry, urethral function tests and electromyography. However, pitfalls of traditional urodynamics include physical and emotional discomfort, artificial test conditions with catheters and rapid retrograde filling of the bladder, which result in variable diagnostic accuracy. Ambulatory urodynamic monitoring (AUM) uses physiological anterograde filling and, therefore, offers a longer and more physiologically relevant evaluation. However, AUM methods rely on traditional catheters and pressure transducers and do not measure volume continuously, which is required to provide context for pressure changes. Novel telemetric AUM (TAUM) methods that use wireless, catheter-free, battery-powered devices to monitor bladder pressure and volume while patients carry out their daily activities are currently being investigated. TAUM devices under current development are innovating in the areas of remote monitoring, rechargeable energy sources, device deployment and retrieval and materials engineering to provide increased diagnostic accuracy and improved comfort for patients with incontinence or voiding dysfunction. These devices hold promise for improving the diagnosis and management of patients with lower urinary tract disorders.
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Affiliation(s)
- Benjamin Abelson
- Cleveland Clinic, Glickman Urological & Kidney Institute, Cleveland, OH, USA
| | - Steve Majerus
- Advanced Platform Technology Center, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA
- Cleveland Clinic, Lerner Research Institute, Department of Biomedical Engineering, Cleveland, OH, USA
| | - Daniel Sun
- Cleveland Clinic, Glickman Urological & Kidney Institute, Cleveland, OH, USA
| | - Bradley C Gill
- Cleveland Clinic, Glickman Urological & Kidney Institute, Cleveland, OH, USA
| | - Eboo Versi
- Department of Obstetrics, Gynecology and Reproductive Sciences, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Margot S Damaser
- Cleveland Clinic, Glickman Urological & Kidney Institute, Cleveland, OH, USA.
- Advanced Platform Technology Center, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA.
- Cleveland Clinic, Lerner Research Institute, Department of Biomedical Engineering, Cleveland, OH, USA.
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Preti M, Vieira-Baptista P, Digesu GA, Bretschneider CE, Damaser M, Demirkesen O, Heller DS, Mangir N, Marchitelli C, Mourad S, Moyal-Barracco M, Peremateu S, Tailor V, Tarcan T, De EJB, Stockdale CK. The Clinical Role of LASER for Vulvar and Vaginal Treatments in Gynecology and Female Urology: An ICS/ISSVD Best Practice Consensus Document. J Low Genit Tract Dis 2019; 23:151-160. [PMID: 30789385 PMCID: PMC6462818 DOI: 10.1097/lgt.0000000000000462] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
In this best practice document, we propose recommendations for the use of LASER for gynecologic and urologic conditions such as vulvovaginal atrophy, urinary incontinence, vulvodynia, and lichen sclerosus based on a thorough literature review. Most of the available studies are limited by their design; for example, they lack a control group, patients are not randomized, follow-up is short term, series are small, LASER is not compared with standard treatments, and most studies are industry sponsored. Because of these limitations, the level of evidence for the use of LASER in the treatment of these conditions remains low and does not allow for definitive recommendations for its use in routine clinical practice. Histological evidence is commonly reported as proof of tissue regeneration after LASER treatment. However, the histological changes noted can also be consistent with reparative changes after a thermal injury rather than necessarily representing regeneration or restoration of function. The use of LASER in women with vulvodynia or lichen sclerosus should not be recommended in routine clinical practice. There is no biological plausibility or safety data on its use on this population of women. The available clinical studies do not present convincing data regarding the efficacy of LASER for the treatment of vaginal atrophy or urinary incontinence. Also, although short-term complications seem to be uncommon, data concerning long-term outcomes are lacking. Therefore, at this point, LASER is not recommended for routine treatment of the aforementioned conditions unless part of well-designed clinical trials or with special arrangements for clinical governance, consent, and audit.
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Affiliation(s)
- Mario Preti
- Department of Obstetrics and Gynecology, University of Torino, Torino, Italy
| | - Pedro Vieira-Baptista
- Hospital Lusíadas Porto
- Lower Genital Tract Unit, Centro Hospitalar de São João, Porto, Portugal
| | | | - Carol Emi Bretschneider
- Center for Urogynecology and Pelvic Reconstructive Surgery, Obstetrics, Gynecology and Women's Health Institute, Cleveland Clinic
| | - Margot Damaser
- Center for Urogynecology and Pelvic Reconstructive Surgery, Obstetrics, Gynecology and Women's Health Institute, Cleveland Clinic
- Glickman Urological and Kidney Institute and Department of Biomedical Engineering Lerner Research Institute, Cleveland Clinic
- Advanced Platform Technology Center Louis Stokes Cleveland VA Medical Center, Cleveland, OH
| | - Oktay Demirkesen
- Istanbul University Cerrahpaşa Faculty of Medicine, Department of Urology, Istanbul, Turkey
| | - Debra S Heller
- Department of Pathology & Laboratory Medicine, Rutgers-New Jersey Medical School, Newark, NJ
| | - Naside Mangir
- Kroto Research Institute, Department of Material Science and Engineering, University of Sheffield
- Royal Hallamshire Hospital, Department of Urology, Sheffield, UK
| | - Claudia Marchitelli
- Department of Gynecology, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
| | - Sherif Mourad
- Ain Shams University, Department of Urology, Cairo, Egypt
| | | | - Sol Peremateu
- Department of Gynecology, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
| | - Visha Tailor
- Imperial College Healthcare, Department of Urogynaecology, London, UK
| | - Tufan Tarcan
- Marmara University School of Medicine, Department of Urology, Istanbul, Turkey
| | - Elise J B De
- Department of Urology, Massachusetts General Hospital-Harvard Medical School Boston, MA
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Wilcox MA, Coppola D, Bailey N, Wilson A, Kamauu AWC, Alba PR, Patterson OV, Viernes B, Denhalter DW, Solomon ID, DuVall SL. Risperdal ® CONSTA ® Needle Detachment. Incidence Rates Before and After Kit Redesign: A Retrospective Study using Electronic Health Records and Natural Language Processing in the Department of Veterans Affairs. Neurol Ther 2019; 8:95-108. [PMID: 30847767 PMCID: PMC6534640 DOI: 10.1007/s40120-019-0130-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Indexed: 11/27/2022] Open
Abstract
Introduction Janssen received reports of needle detachments for Risperdal® CONSTA® and, in response, redesigned the kit. Objective The study objective was to estimate the rate of Risperdal® CONSTA® needle detachments prior to and after the introduction of a redesigned kit. Methods This retrospective study used record abstraction in the US Department of Veterans Affairs (VA). The 3 phases included: (1) a pilot study for methods evaluation in a sample of 6 hospitals with previously reported detachments; (2) a baseline study to ascertain the baseline detachment rate; and (3) a follow-up study to ascertain the rate for the redesigned kit. Administrative codes and natural language processing with clinical review were used to identify detachments. Results Pilot: we identified a subset of spontaneously reported detachments and several previously unreported events. In the baseline study (original device), from January through December 2013, 22 needle detachments were identified among 47,934 administrations of the drug in a census of administrations in the VA; an incidence of 0.0459%. In the follow-up study (redesigned device), from December 2015 through December 2016, there were 14 reported detachments in 41,819 injections, 0.0335%. This represents a reduction of 27% from the baseline. Conclusion This approach enabled us to identify needle detachments we would not have otherwise found (“solicited”). However, it likely resulted in incomplete outcome ascertainment. While this may have resulted in lower overall rates, it did not bias the comparison of the baseline and follow-up studies. The results showed that the redesigned Risperdal® CONSTA® kit reduced the incidence of needle detachment events in the VA. Funding Janssen Pharmaceuticals, Inc.
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Affiliation(s)
- Marsha A Wilcox
- Epidemiology, Janssen Pharmaceutical Research and Development, LLC, 1125 Trenton-Harbourton Rd., Titusville, NJ, 08560, USA.
| | - Danielle Coppola
- Therapy Area Safety Head Immunology, Janssen Pharmaceutical Research and Development, LLC, 1125 Trenton-Harbourton Rd., Titusville, NJ, 08560, USA
| | - Nicole Bailey
- Epidemiology, Anolinx, Inc., 428 E 2400 S, # 202, Salt Lake City, UT, 84107, USA
| | - Andrew Wilson
- Anolinx, Inc., 428 E 2400 S, # 202, Salt Lake City, UT, 84107, USA
| | - Aaron W C Kamauu
- Anolinx, Inc., 428 E 2400 S, # 202, Salt Lake City, UT, 84107, USA
| | - Patrick R Alba
- Department of Veterans Affairs, Salt Lake City Health Care System, VA Informatics and Computing Infrastructure, Salt Lake City, 500 Foothill Blvd, Salt Lake City, UT, 84148, USA
- University of Utah School of Medicine, 30 N 1900 E, Salt Lake City, UT, 84132, USA
| | - Olga V Patterson
- Department of Veterans Affairs, Salt Lake City Health Care System, VA Informatics and Computing Infrastructure, Salt Lake City, 500 Foothill Blvd, Salt Lake City, UT, 84148, USA
- University of Utah School of Medicine, 30 N 1900 E, Salt Lake City, UT, 84132, USA
| | - Benjamin Viernes
- Department of Veterans Affairs, Salt Lake City Health Care System, VA Informatics and Computing Infrastructure, Salt Lake City, 500 Foothill Blvd, Salt Lake City, UT, 84148, USA
- University of Utah School of Medicine, 30 N 1900 E, Salt Lake City, UT, 84132, USA
| | - Daniel W Denhalter
- Department of Veterans Affairs, Salt Lake City Health Care System, VA Informatics and Computing Infrastructure, Salt Lake City, 500 Foothill Blvd, Salt Lake City, UT, 84148, USA
- University of Utah School of Medicine, 30 N 1900 E, Salt Lake City, UT, 84132, USA
| | - Ira D Solomon
- Established Products, CNS Portfolio, Janssen Pharmaceutical Research and Development, LLC, 1125 Trenton-Harbourton Rd., Titusville, NJ, 08560, USA
| | - Scott L DuVall
- Department of Veterans Affairs, Salt Lake City Health Care System, VA Informatics and Computing Infrastructure, Salt Lake City, 500 Foothill Blvd, Salt Lake City, UT, 84148, USA
- University of Utah School of Medicine, 30 N 1900 E, Salt Lake City, UT, 84132, USA
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Abstract
There is a considerable body of evidence indicating that chronic adverse experience, especially chronic psychosocial stress/trauma, represents a major risk factor for the development of many somatic and affective disorders, including inflammatory bowel disease (IBD) and posttraumatic stress disorder (PTSD). However, the mechanisms underlying the development of chronic stress-associated disorders are still in large part unknown, and current treatment and prevention strategies lack efficacy and reliability. A greater understanding of mechanisms involved in the development and persistence of chronic stress-induced disorders may lead to novel approaches to prevention and treatment of these disorders. In this review, we provide evidence indicating that increases in immune (re-)activity and inflammation, potentially promoted by a reduced exposure to immunoregulatory microorganisms ("Old Friends") in today's modern society, may be causal factors in mediating the vulnerability to development and persistence of stress-related pathologies. Moreover, we discuss strategies to increase immunoregulatory processes and attenuate inflammation, as for instance contact with immunoregulatory Old Friends, which appears to be a promising strategy to promote stress resilience and to prevent/treat chronic stress-related disorders.
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Affiliation(s)
- Dominik Langgartner
- Laboratory for Molecular Psychosomatics, Department of Psychosomatic Medicine and Psychotherapy, University Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Germany
| | - Christopher A Lowry
- Department of Integrative Physiology and Center for Neuroscience, University of Colorado Boulder, Boulder, CO, 80309, USA
- Department of Physical Medicine & Rehabilitation and Center for Neuroscience, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
- Veterans Health Administration, Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC), Denver Veterans Affairs Medical Center (VAMC), Denver, CO, 80220, USA
- Military and Veteran Microbiome Consortium for Research and Education (MVM-CoRE), Denver, CO, 80220, USA
| | - Stefan O Reber
- Laboratory for Molecular Psychosomatics, Department of Psychosomatic Medicine and Psychotherapy, University Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Germany.
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Abstract
There has been recent interest in placing pressure-sensing elements beneath the bladder mucosa to facilitate chronic bladder pressure monitoring. Wired submucosal sensors with the wires passed through detrusor have been demonstrated in vivo, with limited chronic retention, potentially due to the cable tethering the detrusor. Published studies of submucosal implants have shown that high correlation coefficients between submucosal and lumen pressures can be obtained in caprine, feline, and canine models. We have developed a wireless pressure monitor and surgical technique for wireless submucosal implantation and present our initial chronic implantation study here. Pressure monitors were implanted (n = 6) in female calf models (n = 5). Five devices were implanted cystoscopically with a 25-French rigid cystoscope. One device was implanted suprapubically to test device retention with an intact mucosa. Wireless recordings during anesthetized cystometry simultaneous with catheter-based reference vesical pressure measurements during filling and manual bladder compressions were recorded. Individual analysis of normalised data during bladder compressions (n = 12) indicated high correlation (r = 0.85-0.94) between submucosal and reference vesical pressure. The healing response was robust over 4 weeks; however, mucosal erosion occurred 2-4 weeks after implantation, leading to device migration into the bladder lumen and expulsion during urination. Wireless pressure monitors may be successfully placed in a suburothelial position. Submucosal pressures are correlated with vesical pressure, but may differ due to biomechanical forces pressing on an implanted sensor. Fully wireless devices implanted beneath the mucosa have risk of erosion through the mucosa, potentially caused by disruption of blood flow to the urothelium, or an as-yet unstudied mechanism of submucosal regrowth. Further investigation into device miniaturisation, anchoring methods, and understanding of submucosal pressure biomechanics may enable chronic submucosal pressure monitoring. However, the risk of erosion with submucosal implantation highlights the need for investigation of devices designed for chronic intravesical pressure monitoring.
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Affiliation(s)
- Anisha S. Basu
- Dept of Biomedical Engineering, Case Western Reserve University, Cleveland, OH USA
- Dept of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
| | - Steve Majerus
- Dept of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
- Dept of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Dept. of Veterans Affairs Medical Center, Cleveland, OH USA
| | - Liz Ferry
- Department of Urology, SUNY Upstate Medical University, Syracuse, NY USA
| | - Iryna Makovey
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH USA
| | - Hui Zhu
- Advanced Platform Technology Center, Louis Stokes Cleveland Dept. of Veterans Affairs Medical Center, Cleveland, OH USA
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH USA
| | - Margot S. Damaser
- Dept of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Dept. of Veterans Affairs Medical Center, Cleveland, OH USA
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH USA
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38
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Abstract
INTRODUCTION Identifying occurrences of medication side effects and adverse drug events (ADEs) is an important and challenging task because they are frequently only mentioned in clinical narrative and are not formally reported. METHODS We developed a natural language processing (NLP) system that aims to identify mentions of symptoms and drugs in clinical notes and label the relationship between the mentions as indications or ADEs. The system leverages an existing word embeddings model with induced word clusters for dimensionality reduction. It employs a conditional random field (CRF) model for named entity recognition (NER) and a random forest model for relation extraction (RE). RESULTS Final performance of each model was evaluated separately and then combined on a manually annotated evaluation set. The micro-averaged F1 score was 80.9% for NER, 88.1% for RE, and 61.2% for the integrated systems. Outputs from our systems were submitted to the NLP Challenges for Detecting Medication and Adverse Drug Events from Electronic Health Records (MADE 1.0) competition (Yu et al. in http://bio-nlp.org/index.php/projects/39-nlp-challenges , 2018). System performance was evaluated in three tasks (NER, RE, and complete system) with multiple teams submitting output from their systems for each task. Our RE system placed first in Task 2 of the challenge and our integrated system achieved third place in Task 3. CONCLUSION Adding to the growing number of publications that utilize NLP to detect occurrences of ADEs, our study illustrates the benefits of employing innovative feature engineering.
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Affiliation(s)
| | - Kelly S Peterson
- VA Salt Lake City Health Care System, University of Utah, Salt Lake City, UT, USA
- Division of Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Patrick R Alba
- VA Salt Lake City Health Care System, University of Utah, Salt Lake City, UT, USA
- Division of Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Scott L DuVall
- VA Salt Lake City Health Care System, University of Utah, Salt Lake City, UT, USA
- Division of Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Olga V Patterson
- VA Salt Lake City Health Care System, University of Utah, Salt Lake City, UT, USA.
- Division of Epidemiology, University of Utah, Salt Lake City, UT, USA.
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39
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Karam R, Majerus SJA, Bourbeau DJ, Damaser MS, Bhunia S. Tunable and Lightweight On-Chip Event Detection for Implantable Bladder Pressure Monitoring Devices. IEEE Trans Biomed Circuits Syst 2017; 11:1303-1312. [PMID: 29028208 PMCID: PMC6944980 DOI: 10.1109/tbcas.2017.2748981] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Lower urinary tract dysfunctions, such as urinary incontinence and overactive bladder, are conditions that greatly affect the quality of life for millions of individuals worldwide. For those with more complex pathophysiologies, diagnosis of these conditions often requires a urodynamics study, providing physicians with a snapshot view of bladder mechanics. Recent advancements in implantable bladder pressure monitors and advanced data analysis techniques have made diagnosis through chronic monitoring a promising prospect. However, implants targeted at treatment must remain in the bladder for long periods of time, making minimizing power consumption a primary design objective. Currently, much of the typical implant's power draw is due to data transmission. Previous work has demonstrated an adaptive rate transmission technique to reduce power consumption. However, the ultimate reduction in power consumption can only be attained when the device does not transmit bladder pressure samples, but rather bladder events. In this paper, we present an algorithm and circuit level implementation for on-chip bladder pressure data compression and event detection. It is designed to be a complete, tunable, and lightweight diagnosis and treatment framework for bladder pressure monitoring implants, capable of selectively transmitting compressed bladder pressure data with tunable quality, "snapshots" of significant bladder events, or simply indicate events occurred for the highest energy efficiency. The design aims to minimize area through resource reuse, leading to a total area of 1.75 , and employs advanced VLSI techniques for power reduction. With compression and event detection enabled, the design consumes roughly 2.6 nW in TSMC technology. With only event detection, this reduces to 2.1 nW, making this approach ideal for long-life implantable bladder pressure monitoring devices.
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40
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Karam R, Bhunia S, Majerus S, Brose SW, Damaser MS, Bourbeau D. Real-time, autonomous bladder event classification and closed-loop control from single-channel pressure data. Annu Int Conf IEEE Eng Med Biol Soc 2017; 2016:5789-5792. [PMID: 28269570 DOI: 10.1109/embc.2016.7592043] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Urinary incontinence, or the loss of bladder control, is a debilitating condition affecting millions worldwide, which significantly reduces quality of life. Neuromodulation of lower urinary tract nerves can be used to treat sensations of urgency in many subjects, including those with Spinal Cord Injury (SCI). Event driven, or conditional stimulation has been investigated as a possible improvement to the state-of-the-art open-loop stimulation systems available today. However, this requires a robust, adaptive, and noise-tolerant method of classifying bladder function from real-time bladder pressure measurements. Context-Aware Thresholding (CAT) has been previously shown to work well on prerecorded single contraction urodynamic data. In this work, for the first time, we present real-time detection of multiple serial bladder contractions using urodynamic recordings from human subjects with SCI and Neurogenic Detrusor Overactivity (NDO). CAT demonstrated a high degree of accuracy and noise tolerance on prerecorded data from 15 human subjects, with a mean accuracy of 92% and average false positive rate of 0.3 false positives per contraction. Analysis of event detection latencies showed that CAT identified and responded to events 1.4 seconds faster than the original human experimenter. Finally, we present a case study in which CAT was used live for real-time autonomous, closed-loop bladder control in a single human subject with SCI and NDO, successfully inhibiting four consecutive unwanted bladder contractions and increasing bladder capacity by 40%.
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Majerus SJA, Fletter PC, Ferry EK, Zhu H, Gustafson KJ, Damaser MS. Suburothelial Bladder Contraction Detection with Implanted Pressure Sensor. PLoS One 2017; 12:e0168375. [PMID: 28060842 PMCID: PMC5218553 DOI: 10.1371/journal.pone.0168375] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 11/29/2016] [Indexed: 12/31/2022] Open
Abstract
Aims Managing bladder pressure in patients with neurogenic bladders is needed to improve rehabilitation options, avoid upper tract damage, incontinence, and their associated co-morbidities and mortality. Current methods of determining bladder contractions are not amenable to chronic or ambulatory settings. In this study we evaluated detection of bladder contractions using a novel piezoelectric catheter-free pressure sensor placed in a suburothelial bladder location in animals. Methods Wired prototypes of the pressure monitor were implanted into 2 nonsurvival (feline and canine) and one 13-day survival (canine) animal. Vesical pressures were obtained from the device in both suburothelial and intraluminal locations and simultaneously from a pressure sensing catheter in the bladder. Intravesical pressure was monitored in the survival animal over 10 days from the suburothelial location and necropsy was performed to assess migration and erosion. Results In the nonsurvival animals, the average correlation between device and reference catheter data was high during both electrically stimulated bladder contractions and manual compressions (r = 0.93±0.03, r = 0.89±0.03). Measured pressures correlated strongly (r = 0.98±0.02) when the device was placed in the bladder lumen. The survival animal initially recorded physiologic data, but later this deteriorated. However, endstage intraluminal device recordings correlated (r = 0.85±0.13) with the pressure catheter. Significant erosion of the implant through the detrusor was found. Conclusions This study confirms correlation between suburothelial pressure readings and intravesical bladder pressures. Due to device erosion during ambulatory studies, a wireless implant is recommended for clinical rehabilitation applications.
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Affiliation(s)
- Steve J. A. Majerus
- Advanced Pltatform Technology Center, Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, United States of America
- Department of Electrical Engineering and Computer Sciences, Case Western Reserve University, Cleveland, OH, United States of America
- Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH, United States of America
| | - Paul C. Fletter
- Advanced Pltatform Technology Center, Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, United States of America
- Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH, United States of America
| | - Elizabeth K. Ferry
- Division of Urology, Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, United States of America
- Urology Institute, University Hospitals, Case Medical Center, Cleveland, OH, United States of America
| | - Hui Zhu
- Advanced Pltatform Technology Center, Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, United States of America
- Division of Urology, Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, United States of America
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland OH, United States of America
| | - Kenneth J. Gustafson
- Urology Institute, University Hospitals, Case Medical Center, Cleveland, OH, United States of America
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Functional Electrical Stimulation Center, Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | - Margot S. Damaser
- Advanced Pltatform Technology Center, Louis Stokes Veterans Affairs Medical Center, Cleveland, OH, United States of America
- Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH, United States of America
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland OH, United States of America
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- * E-mail:
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Karam R, Bourbeau D, Majerus S, Makovey I, Goldman HB, Damaser MS, Bhunia S. Real-Time Classification of Bladder Events for Effective Diagnosis and Treatment of Urinary Incontinence. IEEE Trans Biomed Eng 2016; 63:721-9. [PMID: 26292331 PMCID: PMC6946053 DOI: 10.1109/tbme.2015.2469604] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Diagnosis of lower urinary tract dysfunction with urodynamics has historically relied on data acquired from multiple sensors using nonphysiologically fast cystometric filling. In addition, state-of-the-art neuromodulation approaches to restore bladder function could benefit from a bladder sensor for closed-loop control, but a practical sensor and automated data analysis are not available. We have developed an algorithm for real-time bladder event detection based on a single in situ sensor, making it attractive for both extended ambulatory bladder monitoring and closed-loop control of stimulation systems for diagnosis and treatment of bladder overactivity. Using bladder pressure data acquired from 14 human subjects with neurogenic bladder, we developed context-aware thresholding, a novel, parameterized, user-tunable algorithmic framework capable of real-time classification of bladder events, such as detrusor contractions, from single-sensor bladder pressure data. We compare six event detection algorithms with both single-sensor and two-sensor systems using a metric termed Conditional Stimulation Score, which ranks algorithms based on projected stimulation efficacy and efficiency. We demonstrate that adaptive methods are more robust against day-to-day variations than static thresholding, improving sensitivity and specificity without parameter modifications. Relative to other methods, context-aware thresholding is fast, robust, highly accurate, noise-tolerant, and amenable to energy-efficient hardware implementation, which is important for mapping to an implant device.
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Abstract
Experimental studies suggest perinatal exposures to synthetic chemicals may be associated with early onset obesity, although this hypothesis has not been extensively examined in humans. This article summarizes the evidence relating maternal perinatal exposure to common persistent organic compounds (polychlorinated biphenyl, dichlorodiphenyldichloroethylene, dichlorodiphenyltrichloroethane, hexachlorobenzene, hexachlorocyclohexane), perfluoroalkyls, perfluorooctane sulfonate, polybrominated diphenyl ethers and tributyltin, and nonpersistent compounds (phthalates, bisphenol A) on child obesity during sensitive developmental periods. Twenty-two epidemiologic studies published from 2011 to 2015 offer inconsistent support for the obesogenic effects of most substances and are limited by relatively small sample sizes and indirect measures of adiposity. The clearest findings suggest an influence of maternal dichlorodiphenyldichloroethylene exposure on offspring overweight and obesity. Recommendations for future epidemiological research include longer follow-up of effects of pre- and postnatal exposures in large samples; utilization of direct measures of adiposity; and consideration of effect modification by sex, birth weight, dietary fat, and maternal weight status.
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Affiliation(s)
- Yun Liu
- Department of Nutritional Sciences, University of Michigan School of Public Health, 1415 Washington Heights, 1-1867, Ann Arbor, MI, 48109-2029, USA.
| | - Karen E Peterson
- Department of Nutritional Sciences, University of Michigan School of Public Health, 1415 Washington Heights, 1-1867, Ann Arbor, MI, 48109-2029, USA.
- Center for Human Growth and Development, University of Michigan, Ann Arbor, MI, USA.
- Departments of Nutrition and of Health and Social Behavior, Harvard W.T. Chan School of Public Health, Boston, MA, USA.
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Abstract
This paper presents an implantable wireless battery recharging system design for bladder pressure chronic monitoring. The wireless recharging system consists of an external 15 cm-diameter 6-turn powering coil and a silicone-encapsulated implantable rectangular coil with a dimension of 7 mm × 17 mm × 2.5 mm and 18 turns, which further encloses a 3 mm-diameter and 12 mm-long rechargeable battery, two ferrite rods, an ASIC, and a tuning capacitor. For a constant recharging current of 100 μA, an RF power of 700 μW needs to be coupled into the implantable module through the tuned coils. Analyses and experiments confirm that with the two coils aligned coaxially or with a 6 cm axial offset and a tilting angle of 30°, an external power of 3.5 W or 10 W is required, respectively, at an optimal frequency of 3 MHz to cover a large implant depth of 20 cm.
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Affiliation(s)
- Darrin J Young
- Electrical and Computer Engineering Department, University of Utah, Salt Lake City, Utah, USA.
| | - Peng Cong
- Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, Ohio, USA.
| | - Michael A Suster
- Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, Ohio, USA.
| | - Margot Damaser
- Advanced Platform Technology Center, Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, USA. and Pathology, Macromolecular Science and Engineering, Biomedical Engineering Department, Case Western Reserve University, Cleveland, Ohio, USA.
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Durda P, Sabourin J, Lange EM, Nalls MA, Mychaleckyj JC, Jenny NS, Li J, Walston J, Harris TB, Psaty BM, Valdar W, Liu Y, Cushman M, Reiner AP, Tracy RP, Lange LA. Plasma Levels of Soluble Interleukin-2 Receptor α: Associations With Clinical Cardiovascular Events and Genome-Wide Association Scan. Arterioscler Thromb Vasc Biol 2015; 35:2246-53. [PMID: 26293465 PMCID: PMC5395092 DOI: 10.1161/atvbaha.115.305289] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2015] [Accepted: 08/03/2015] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Interleukin (IL) -2 receptor subunit α regulates lymphocyte activation, which plays an important role in atherosclerosis. Associations between soluble IL-2Rα (sIL-2Rα) and cardiovascular disease (CVD) have not been widely studied and little is known about the genetic determinants of sIL-2Rα levels. APPROACH AND RESULTS We measured baseline levels of sIL-2Rα in 4408 European American (EA) and 766 African American (AA) adults from the Cardiovascular Health Study (CHS) and examined associations with baseline CVD risk factors, subclinical CVD, and incident CVD events. We also performed a genome-wide association study for sIL-2Rα in CHS (2964 EAs and 683 AAs) and further combined CHS EA results with those from two other EA cohorts in a meta-analysis (n=4464 EAs). In age, sex- and race- adjusted models, sIL-2Rα was positively associated with current smoking, type 2 diabetes mellitus, hypertension, insulin, waist circumference, C-reactive protein, IL-6, fibrinogen, internal carotid wall thickness, all-cause mortality, CVD mortality, and incident CVD, stroke, and heart failure. When adjusted for baseline CVD risk factors and subclinical CVD, associations with all-cause mortality, CVD mortality, and heart failure remained significant in both EAs and AAs. In the EA genome-wide association study analysis, we observed 52 single-nucleotide polymorphisms in the chromosome 10p15-14 region, which contains IL2RA, IL15RA, and RMB17, that reached genome-wide significance (P<5×10(-8)). The most significant single-nucleotide polymorphism was rs7911500 (P=1.31×10(-75)). The EA meta-analysis results were highly consistent with CHS-only results. No single-nucleotide polymorphisms reached statistical significance in the AAs. CONCLUSIONS These results support a role for sIL-2Rα in atherosclerosis and provide evidence for multiple-associated single-nucleotide polymorphisms at chromosome 10p15-14.
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Affiliation(s)
- Peter Durda
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Jeremy Sabourin
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Ethan M Lange
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Mike A Nalls
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Josyf C Mychaleckyj
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Nancy Swords Jenny
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Jin Li
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Jeremy Walston
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Tamara B Harris
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Bruce M Psaty
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - William Valdar
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Yongmei Liu
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Mary Cushman
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Alex P Reiner
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
| | - Russell P Tracy
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.).
| | - Leslie A Lange
- From the Departments of Pathology (P.D., N.S.J., M.C., R.P.T.), Medicine (M.C.), and Biochemistry (R.P.T.), University of Vermont College of Medicine, Burlington; Departments of Genetics (J.S., E.M.L., J.L., W.V., L.A.L.), Biostatistics (E.M.L., W.V.), Lineberger Comprehensive Cancer Center, School of Medicine (J.S., E.M.L., W.V.), University of North Carolina, Chapel Hill; Laboratory of Neurogenetics, Porter Neuroscience Research Center, National Institute on Aging, National Institute of Health, Bethesda, MD (M.A.N.); Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville (J.C.M.); Johns Hopkins Medical Institutions, Department of Medicine Geriatrics, Johns Hopkins University, John R. Burton Pavilion, Baltimore, MD (J.D.W.); Geriatric Epidemiology Section, National Institute on Aging, National Institute of Health, Bethesda, MD (T.B.H.); Cardiovascular Health Research Unit (B.M.P.), Departments of Medicine (B.M.P.) and Epidemiology (B.M.P., A.P.R.), University of Washington, Seattle; Group Health Research Institute, Division of Cardiology, Group Health Cooperative, Seattle, WA (B.M.P.); and Wake Forest University School of Medicine, Center for Genomics and Personalized Medicine Research, Winston-Salem, NC (Y.L.)
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de Foy B, Schauer JJ. Origin of high particle number concentrations reaching the St. Louis, Midwest Supersite. J Environ Sci (China) 2015; 34:219-231. [PMID: 26257365 DOI: 10.1016/j.jes.2014.12.026] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2014] [Revised: 12/09/2014] [Accepted: 12/15/2014] [Indexed: 06/04/2023]
Abstract
Ultrafine particles are associated with adverse health effects. Total Particle Number Concentration (TNC) of fine particles were measured during 2002 at the St. Louis - Midwest supersite. The time series showed overall low level with frequent large peaks. The time series was analyzed alongside criteria pollutant measurements and meteorological observations. Multiple regression analysis was used to identify further contributing factors and to determine the association of different pollutants with TNC levels. This showed the strong contribution of sulfur dioxide (SO2) and nitrogen oxides (NOx) to high TNC levels. The analysis also suggested that increased dispersion resulting from faster winds and higher mixing heights led to higher TNC levels. Overall, the results show that there were intense particle nucleation events in a SO2 rich plume reaching the site which contributed around 29% of TNC. A further 40% was associated with primary emissions from mobile sources. By separating the remaining TNC by time of day and clear sky conditions, we suggest that most likely 8% of TNC are due to regional nucleation events and 23% are associated with the general urban background.
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Affiliation(s)
- Benjamin de Foy
- Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, USA.
| | - James J Schauer
- Civil and Environmental Engineering, University of Wisconsin, Madison, WI, USA
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Kayser BD, Goran MI, Bouret SG. Perinatal overnutrition exacerbates adipose tissue inflammation caused by high-fat feeding in C57BL/6J mice. PLoS One 2015; 10:e0121954. [PMID: 25835281 PMCID: PMC4383546 DOI: 10.1371/journal.pone.0121954] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Accepted: 02/06/2015] [Indexed: 12/24/2022] Open
Abstract
Obesity causes white adipose tissue (WAT) inflammation and insulin resistance in some, but not all individuals. Here, we used a mouse model of early postnatal overfeeding to determine the role of neonatal nutrition in lifelong WAT inflammation and metabolic dysfunction. C57BL/6J mice were reared in small litters of 3 (SL) or normal litters of 7 pups (NL) and fed either regular chow or a 60% high fat diet (HFD) from 5 to 17 weeks. At weaning, SL mice did not develop WAT inflammation despite increased fat mass, although there was an up-regulation of WAT Arg1 and Tlr4 expression. On HFD, adult SL mice had greater inguinal fat mass compared to NL mice, however both groups showed similar increases in visceral fat depots and adipocyte hypertrophy. Despite the similar levels of visceral adiposity, SL-HFD mice displayed greater impairments in glucose homeostasis and more pronounced hepatic steatosis compared to NL-HFD mice. In addition, WAT from SL mice fed a HFD displayed greater crown-like structure formation, increased M1 macrophages, and higher cytokine gene expression. Together, these data suggest that early postnatal overnutrition may be a critical determinant of fatty liver and insulin resistance in obese adults by programming the inflammatory capacity of adipose tissue.
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Affiliation(s)
- Brandon D. Kayser
- Human and Evolutionary Biology Program, Department of Biological Sciences, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, United States of America
- Department of Preventive Medicine, Keck School of Medicine, Childhood Obesity Research Center, University of Southern California, Los Angeles, California, United States of America
| | - Michael I. Goran
- Department of Preventive Medicine, Keck School of Medicine, Childhood Obesity Research Center, University of Southern California, Los Angeles, California, United States of America
| | - Sebastien G. Bouret
- Developmental Neuroscience Program, The Saban Research Institute, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, California, United States of America
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Zhao J, Song Q, Wang L, Dong X, Yang X, Bai X, Song B, Damaser M, Li L. Detrusor myocyte autophagy protects the bladder function via inhibiting the inflammation in cyclophosphamide-induced cystitis in rats. PLoS One 2015; 10:e0122597. [PMID: 25830308 PMCID: PMC4382282 DOI: 10.1371/journal.pone.0122597] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2014] [Accepted: 02/11/2015] [Indexed: 11/18/2022] Open
Abstract
Autophagy, a highly conserved homeostatic cellular process that removes and recycles damaged proteins and organelles in response to cellular stress, is believed to play a crucial role in the immune response and inflammation. The role of autophagy in bladder cystitis, however, has not well been clarified. Here we investigate the role of detrusor myocytes autophagy (DMA) in cyclophosphamide-induced cystitis animal model. 164 female Sprague-Dawley rats were randomized into three experimental groups and compared to three control groups, respectively. The expressions of microtubule-associated protein 1 light chain 3 (LC3), p-p70s6k (the phosphorylated form of ribosomal protein S6), SOD2 (superoxide dismutase 2) in the bladder muscular layer were measured using western blot. The co-location of LC3, alpha-smooth muscle actin (α-SMA), and autophagic vacuoles were investigated with double-labeled immunofluorescence and transmission electron microscopy (TEM). The expression of lL-1β, IL-6, IL-8, malondialdehyde (MDA), and glutathione (GSH) in the detrusor layer were analyzed using ELISA. The bladder inflammation and the number of mast cells in the muscular layer were analyzed by histology. The bladder function was evaluated using cystometry. In cyclophosphamide-induced cystitis, autophagy was detected in detrusor myocytes by increased LC3, p-p70s6k expression, and autophagosomes. However, the presence of enhanced inflammation and oxidative stress in the cyclophosphamide-treated group suggest autophagy of detrusor myocytes may not be sufficiently activated. Inflammation and oxidative stress were significantly decreased and the bladder histology and micturition function were significantly improved with rapamycin (RAPA, autophagy agonist) pre-treatment. In contrast, inflammation and oxidative stress were dramatically increased and the bladder histology and function were negatively affected with chloroquine (CQ, autophagy blocker) pre-treated. These findings preferentially provide evidence of the association between DMA and cyclophosphamide-induced cystitis in rats. The autophagy agonist RAPA significantly decreased the inflammation and protected the bladder function, which might be considered as a potential treatment for interstitial cystitis.
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Affiliation(s)
- Jiang Zhao
- Department of Urology, Second Affiliated Hospital, Third Military Medical University, Chongqing, China
| | - Qixiang Song
- Department of Biomedical Engineering, the Cleveland Clinic, Cleveland, OH, United States of America
| | - Liang Wang
- Department of Urology, Second Affiliated Hospital, Third Military Medical University, Chongqing, China
| | - Xingyou Dong
- Department of Urology, Second Affiliated Hospital, Third Military Medical University, Chongqing, China
| | - Xingliang Yang
- Department of Urology, Second Affiliated Hospital, Third Military Medical University, Chongqing, China
| | - Xinyu Bai
- Department of Urology, Second Affiliated Hospital, Third Military Medical University, Chongqing, China
| | - Bo Song
- Department of Urology, Second Affiliated Hospital, Third Military Medical University, Chongqing, China
| | - Margot Damaser
- Department of Biomedical Engineering, the Cleveland Clinic, Cleveland, OH, United States of America
| | - Longkun Li
- Department of Urology, Second Affiliated Hospital, Third Military Medical University, Chongqing, China
- * E-mail:
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49
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Romano ME, Webster GM, Vuong AM, Thomas Zoeller R, Chen A, Hoofnagle AN, Calafat AM, Karagas MR, Yolton K, Lanphear BP, Braun JM. Gestational urinary bisphenol A and maternal and newborn thyroid hormone concentrations: the HOME Study. Environ Res 2015; 138:453-60. [PMID: 25794847 PMCID: PMC4403004 DOI: 10.1016/j.envres.2015.03.003] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Revised: 02/14/2015] [Accepted: 03/08/2015] [Indexed: 05/20/2023]
Abstract
Bisphenol A (BPA), an endocrine disruptor used in consumer products, may perturb thyroid function. Prenatal BPA exposure may have sex-specific effects on thyroid hormones (THs). Our objectives were to investigate whether maternal urinary BPA concentrations during pregnancy were associated with THs in maternal or cord serum, and whether these associations differed by newborn sex or maternal iodine status. We measured urinary BPA concentrations at 16 and 26 weeks gestation among pregnant women in the HOME Study (2003-2006, Cincinnati, Ohio). Thyroid stimulating hormone (TSH) and free and total thyroxine (T4) and triiodothyronine (T3) were measured in maternal serum at 16 weeks (n=181) and cord serum at delivery (n=249). Associations between BPA concentrations and maternal or cord serum TH levels were estimated by multivariable linear regression. Mean maternal urinary BPA was not associated with cord THs in all newborns, but a 10-fold increase in mean BPA was associated with lower cord TSH in girls (percent change=-36.0%; 95% confidence interval (CI): -58.4, -1.7%), but not boys (7.8%; 95% CI: -28.5, 62.7%; p-for-effect modification=0.09). We observed no significant associations between 16-week BPA and THs in maternal or cord serum, but 26-week maternal BPA was inversely associated with TSH in girls (-42.9%; 95% CI: -59.9, -18.5%), but not boys (7.6%; 95% CI: -17.3, 40.2%; p-for-effect modification=0.005) at birth. The inverse BPA-TSH relation among girls was stronger, but less precise, among iodine deficient versus sufficient mothers. Prenatal BPA exposure may reduce TSH among newborn girls, particularly when exposure occurs later in gestation.
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Affiliation(s)
- Megan E Romano
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA.
| | - Glenys M Webster
- Child and Family Research Institute, BC Children's and Women's Hospital and Faculty of Health Sciences, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Ann M Vuong
- Division of Epidemiology and Biostatistics, Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - R Thomas Zoeller
- Department of Biology, University of Massachusetts, Amherst, MA, USA
| | - Aimin Chen
- Division of Epidemiology and Biostatistics, Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Margaret R Karagas
- Children's Environmental Health and Disease Prevention Research Center and Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Kimberly Yolton
- Division of General and Community Pediatrics, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Bruce P Lanphear
- Child and Family Research Institute, BC Children's and Women's Hospital and Faculty of Health Sciences, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Joseph M Braun
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
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50
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Abstract
Obesity and type 2 diabetes mellitus (T2DM) often occur together and affect a growing number of individuals in both the developed and developing worlds. Both are associated with a number of other serious illnesses that lead to increased rates of mortality. There is likely a polygenic mode of inheritance underlying both disorders, but it has become increasingly clear that the pre- and postnatal environments play critical roles in pushing predisposed individuals over the edge into a disease state. This review focuses on the many genetic and environmental variables that interact to cause predisposed individuals to become obese and diabetic. The brain and its interactions with the external and internal environment are a major focus given the prominent role these interactions play in the regulation of energy and glucose homeostasis in health and disease.
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Affiliation(s)
- Sebastien Bouret
- The Saban Research Institute, Neuroscience Program, Childrens Hospital Los Angeles, University of Southern California, Los Angeles, California; Inserm U837, Jean-Pierre Aubert Research Center, University Lille 2, Lille, France; Neurology Service, Veterans Administration Medical Center, East Orange, New Jersey; Department of Neurology and Neurosciences, Rutgers, New Jersey Medical School, Newark, New Jersey; and University of Cambridge Institute of Metabolic Science and MRC Metabolic Diseases Unit, Cambridge, United Kingdom
| | - Barry E Levin
- The Saban Research Institute, Neuroscience Program, Childrens Hospital Los Angeles, University of Southern California, Los Angeles, California; Inserm U837, Jean-Pierre Aubert Research Center, University Lille 2, Lille, France; Neurology Service, Veterans Administration Medical Center, East Orange, New Jersey; Department of Neurology and Neurosciences, Rutgers, New Jersey Medical School, Newark, New Jersey; and University of Cambridge Institute of Metabolic Science and MRC Metabolic Diseases Unit, Cambridge, United Kingdom
| | - Susan E Ozanne
- The Saban Research Institute, Neuroscience Program, Childrens Hospital Los Angeles, University of Southern California, Los Angeles, California; Inserm U837, Jean-Pierre Aubert Research Center, University Lille 2, Lille, France; Neurology Service, Veterans Administration Medical Center, East Orange, New Jersey; Department of Neurology and Neurosciences, Rutgers, New Jersey Medical School, Newark, New Jersey; and University of Cambridge Institute of Metabolic Science and MRC Metabolic Diseases Unit, Cambridge, United Kingdom
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