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1. Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program.

Author

Rose D L Huang, Xuan-Mai T Nguyen, Gina M Peloso, Mark Trinder, Daniel C Posner, Krishna G Aragam, Yuk-Lam Ho, Julie A Lynch, Scott M Damrauer, Kyong-Mi Chang, Philip S Tsao, Pradeep Natarajan, Themistocles Assimes, J Michael Gaziano, Luc Djousse, Kelly Cho, Peter W F Wilson, Jennifer E Huffman, Christopher J O'Donnell, and Veterans Affairs’ Million Veteran Program

Subjects
Medicine, Science
Abstract

BackgroundGenetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program.MethodsAn ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization.ResultsThe discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality.ConclusionA set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality.

Published
2022
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2. COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients.

Author

Mark Stewart, Carla Rodriguez-Watson, Adem Albayrak, Julius Asubonteng, Andrew Belli, Thomas Brown, Kelly Cho, Ritankar Das, Elizabeth Eldridge, Nicolle Gatto, Alice Gelman, Hanna Gerlovin, Stuart L Goldberg, Eric Hansen, Jonathan Hirsch, Yuk-Lam Ho, Andrew Ip, Monika Izano, Jason Jones, Amy C Justice, Reyna Klesh, Seth Kuranz, Carson Lam, Qingqing Mao, Samson Mataraso, Robertino Mera, Daniel C Posner, Jeremy A Rassen, Anna Siefkas, Andrew Schrag, Georgia Tourassi, Andrew Weckstein, Frank Wolf, Amar Bhat, Susan Winckler, Ellen V Sigal, and Jeff Allen

Subjects
Medicine, Science
Abstract

BackgroundThe COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments.MethodsElectronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined.ResultsNeither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events.ConclusionAdministration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.

Published
2021
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3. Comparison of methods for building polygenic scores for diverse populations

Author

Sophia Gunn, Xin Wang, Daniel C. Posner, Kelly Cho, Jennifer E. Huffman, Michael Gaziano, Peter W. Wilson, Yan V. Sun, Gina Peloso, and Kathryn L. Lunetta

Subjects
polygenic scores, underrepresented populations, diverse populations, Genetics, QH426-470
Abstract

Summary: Polygenic scores (PGSs) are a promising tool for estimating individual-level genetic risk of disease based on the results of genome-wide association studies (GWASs). However, their promise has yet to be fully realized because most currently available PGSs were built with genetic data from predominantly European-ancestry populations, and PGS performance declines when scores are applied to target populations different from the populations from which they were derived. Thus, there is a great need to improve PGS performance in currently under-studied populations. In this work we leverage data from two large and diverse cohorts the Million Veterans Program (MVP) and All of Us (AoU), providing us the unique opportunity to compare methods for building PGSs for multi-ancestry populations across multiple traits. We build PGSs for five continuous traits and five binary traits using both multi-ancestry and single-ancestry approaches with popular Bayesian PGS methods and both MVP META GWAS results and population-specific GWAS results from the respective African, European, and Hispanic MVP populations. We evaluate these scores in three AoU populations genetically similar to the respective African, Admixed American, and European 1000 Genomes Project superpopulations. Using correlation-based tests, we make formal comparisons of the PGS performance across the multiple AoU populations. We conclude that approaches that combine GWAS data from multiple populations produce PGSs that perform better than approaches that utilize smaller single-population GWAS results matched to the target population, and specifically that multi-ancestry scores built with PRS-CSx outperform the other approaches in the three AoU populations.

Published
2025
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4. Genetic Loci Associated With COVID-19 Positivity and Hospitalization in White, Black, and Hispanic Veterans of the VA Million Veteran Program

Author

Gina M. Peloso, Catherine Tcheandjieu, John E. McGeary, Daniel C. Posner, Yuk-Lam Ho, Jin J. Zhou, Austin T. Hilliard, Jacob Joseph, Christopher J. O’Donnell, Jimmy T. Efird, Dana C. Crawford, Wen-Chih Wu, Mehrdad Arjomandi, VA Million Veteran Program COVID-19 Science Initiative, Yan V. Sun, Themistocles L Assimes, and Jennifer E. Huffman

Subjects
COVID-19, genome-wide association study, million veteran program, hospitalization, ABO, Genetics, QH426-470
Abstract

SARS-CoV-2 has caused symptomatic COVID-19 and widespread death across the globe. We sought to determine genetic variants contributing to COVID-19 susceptibility and hospitalization in a large biobank linked to a national United States health system. We identified 19,168 (3.7%) lab-confirmed COVID-19 cases among Million Veteran Program participants between March 1, 2020, and February 2, 2021, including 11,778 Whites, 4,893 Blacks, and 2,497 Hispanics. A multi-population genome-wide association study (GWAS) for COVID-19 outcomes identified four independent genetic variants (rs8176719, rs73062389, rs60870724, and rs73910904) contributing to COVID-19 positivity, including one novel locus found exclusively among Hispanics. We replicated eight of nine previously reported genetic associations at an alpha of 0.05 in at least one population-specific or the multi-population meta-analysis for one of the four MVP COVID-19 outcomes. We used rs8176719 and three additional variants to accurately infer ABO blood types. We found that A, AB, and B blood types were associated with testing positive for COVID-19 compared with O blood type with the highest risk for the A blood group. We did not observe any genome-wide significant associations for COVID-19 severity outcomes among those testing positive. Our study replicates prior GWAS findings associated with testing positive for COVID-19 among mostly White samples and extends findings at three loci to Black and Hispanic individuals. We also report a new locus among Hispanics requiring further investigation. These findings may aid in the identification of novel therapeutic agents to decrease the morbidity and mortality of COVID-19 across all major ancestral populations.

Published
2022
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5. Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses

Author

Liam Gaziano, Luanluan Sun, Matthew Arnold, Steven Bell, Kelly Cho, Stephen K. Kaptoge, Rebecca J. Song, Stephen Burgess, Daniel C. Posner, Katja Mosconi, Cassianne Robinson-Cohen, Amy M. Mason, Thomas R. Bolton, Ran Tao, Elias Allara, Petra Schubert, Lingyan Chen, James R. Staley, Natalie Staplin, Servet Altay, Pilar Amiano, Volker Arndt, Johan Ärnlöv, Elizabeth L.M. Barr, Cecilia Björkelund, Jolanda M.A. Boer, Hermann Brenner, Edoardo Casiglia, Paolo Chiodini, Jackie A. Cooper, Josef Coresh, Mary Cushman, Rachel Dankner, Karina W. Davidson, Renate T. de Jongh, Chiara Donfrancesco, Gunnar Engström, Heinz Freisling, Agustín Gómez de la Cámara, Vilmundur Gudnason, Graeme J. Hankey, Per-Olof Hansson, Alicia K. Heath, Ewout J. Hoorn, Hironori Imano, Simerjot K. Jassal, Rudolf Kaaks, Verena Katzke, Jussi Kauhanen, Stefan Kiechl, Wolfgang Koenig, Richard A. Kronmal, Cecilie Kyrø, Deborah A. Lawlor, Börje Ljungberg, Conor MacDonald, Giovanna Masala, Christa Meisinger, Olle Melander, Conchi Moreno Iribas, Toshiharu Ninomiya, Dorothea Nitsch, Børge G. Nordestgaard, Charlotte Onland-Moret, Luigi Palmieri, Dafina Petrova, Jose Ramón Quirós Garcia, Annika Rosengren, Carlotta Sacerdote, Masaru Sakurai, Carmen Santiuste, Matthias B. Schulze, Sabina Sieri, Johan Sundström, Valérie Tikhonoff, Anne Tjønneland, Tammy Tong, Rosario Tumino, Ioanna Tzoulaki, Yvonne T. van der Schouw, W.M. Monique Verschuren, Henry Völzke, Robert B. Wallace, S. Goya Wannamethee, Elisabete Weiderpass, Peter Willeit, Mark Woodward, Kazumasa Yamagishi, Raul Zamora-Ros, Elvis A. Akwo, Saiju Pyarajan, David R. Gagnon, Philip S. Tsao, Sumitra Muralidhar, Todd L. Edwards, Scott M. Damrauer, Jacob Joseph, Lisa Pennells, Peter W.F. Wilson, Seamus Harrison, Thomas A. Gaziano, Michael Inouye, Colin Baigent, Juan P. Casas, Claudia Langenberg, Nick Wareham, Elio Riboli, J.Michael Gaziano, John Danesh, Adriana M. Hung, Adam S. Butterworth, Angela M. Wood, Emanuele Di Angelantonio, Anna Koettgen, Jonathan Shaw, Robert Atkins, Paul Zimmet, Peter Whincup, Johann Willeit, Christoph Leitner, Anne Tybjaerg-Hansen, Peter Schnohr, Shoaib Afzal, David Lora Pablos, Cristina Martin Arriscado, Carmen Romero Ferreiro, Hannah Stocker, Ben Schöttker, Bernd Holleczek, Angela Chetrit, Lennart Welin, Kurt Svärdsudd, Lauren Lissner, Dominique Hange, Kirsten Mehlig, Dorothea Nagel, Paul E. Norman, Osvaldo Almeida, Leon Flicker, Jun Hata, Takanori Honda, Yoshihiko Furuta, Hiroyasu Iso, Akihiko Kitamura, Isao Muraki, Jukka T. Salonen, Tomi-Pekka Tuomainen, E. M. van Zutphen, N. M. van Schoor, Cinzia Lo Noce, Richard Kronmal, Georg Lappas, Peter M. Nilsson, Bo Hedblad, Jonathan Shaffer, Joseph Schwartz, Daichi Shimbo, Shinichi Sato, Mina Hayama-Terada, Simerjot Jassal, Thor Aspelund, Bolli Thorsson, Gunnar Sigurdsson, Layal Chaker, Kamran M. Ikram, Maryam Kavousi, Hugh Tunstall-Pedoe, Günay Can, Hüsniye Yüksel, Uğur Özkan, Hideaki Nakagawa, Yuko Morikawa, Masao Ishizaki, Edith Feskens, Johanna M Geleijnse, Daan Kromhout, Internal Medicine, Neurology, Epidemiology, Bell, Steven [0000-0001-6774-3149], Posner, Daniel C [0000-0002-3056-6924], Mason, Amy M [0000-0002-8019-0777], Allara, Elias [0000-0002-1634-8330], Staplin, Natalie [0000-0003-4482-4418], Arndt, Volker [0000-0001-9320-8684], Ärnlöv, Johan [0000-0002-6933-4637], Barr, Elizabeth LM [0000-0003-4284-1716], Boer, Jolanda MA [0000-0002-9714-4304], Brenner, Hermann [0000-0002-6129-1572], Casiglia, Edoardo [0000-0002-0003-3289], Chiodini, Paolo [0000-0003-0139-2264], Coresh, Josef [0000-0002-4598-0669], Cushman, Mary [0000-0002-7871-6143], Davidson, Karina W [0000-0002-9162-477X], de Jongh, Renate T [0000-0001-8414-3938], Engström, Gunnar [0000-0002-8618-9152], de la Cámara, Agustín Gómez [0000-0001-6827-6319], Gudnason, Vilmundur [0000-0001-5696-0084], Hankey, Graeme J [0000-0002-6044-7328], Hansson, Per-Olof [0000-0001-6323-0506], Heath, Alicia K [0000-0001-6517-1300], Hoorn, Ewout J [0000-0002-8738-3571], Imano, Hironori [0000-0002-6661-4254], Katzke, Verena [0000-0002-6509-6555], Kiechl, Stefan [0000-0002-9836-2514], Koenig, Wolfgang [0000-0002-2064-9603], Kronmal, Richard A [0000-0002-9897-7076], Kyrø, Cecilie [0000-0002-9083-8960], Ljungberg, Börje [0000-0002-4121-3753], MacDonald, Conor [0000-0002-4989-803X], Masala, Giovanna [0000-0002-5758-9069], Ninomiya, Toshiharu [0000-0003-1345-9032], Nordestgaard, Børge G [0000-0002-1954-7220], Onland-Moret, Charlotte [0000-0002-2360-913X], Palmieri, Luigi [0000-0002-4298-2642], Rosengren, Annika [0000-0002-5409-6605], Schulze, Matthias B [0000-0002-0830-5277], Sieri, Sabina [0000-0001-5201-172X], Sundström, Johan [0000-0003-2247-8454], Tikhonoff, Valérie [0000-0001-7846-0101], Tong, Tammy [0000-0002-0284-8959], Tzoulaki, Ioanna [0000-0002-4275-9328], van der Schouw, Yvonne T [0000-0002-4605-435X], Wannamethee, S Goya [0000-0001-9484-9977], Weiderpass, Elisabete [0000-0003-2237-0128], Willeit, Peter [0000-0002-1866-7159], Woodward, Mark [0000-0001-9800-5296], Yamagishi, Kazumasa [0000-0003-3301-5519], Zamora-Ros, Raul [0000-0002-6236-6804], Gagnon, David R [0000-0002-6367-3179], Tsao, Philip S [0000-0001-7274-9318], Edwards, Todd L [0000-0003-4318-6119], Damrauer, Scott M [0000-0001-8009-1632], Joseph, Jacob [0000-0002-7279-4896], Pennells, Lisa [0000-0002-8594-3061], Gaziano, Thomas A [0000-0002-5985-345X], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nick [0000-0003-1422-2993], Hung, Adriana M [0000-0002-3203-1608], Butterworth, Adam S [0000-0002-6915-9015], Di Angelantonio, Emanuele [0000-0001-8776-6719], Apollo - University of Cambridge Repository, Gaziano, Liam, Sun, Luanluan, Arnold, Matthew, Bell, Steven, Cho, Kelly, Kaptoge, Stephen K, Song, Rebecca J, Burgess, Stephen, Posner, Daniel C, Mosconi, Katja, Robinson-Cohen, Cassianne, Mason, Amy M, Bolton, Thomas R, Tao, Ran, Allara, Elia, Schubert, Petra, Chen, Lingyan, Staley, James R, Staplin, Natalie, Altay, Servet, Amiano, Pilar, Arndt, Volker, Ärnlöv, Johan, Barr, Elizabeth L M, Björkelund, Cecilia, Boer, Jolanda M A, Brenner, Hermann, Casiglia, Edoardo, Chiodini, Paolo, Cooper, Jackie A, Coresh, Josef, Cushman, Mary, Dankner, Rachel, Davidson, Karina W, de Jongh, Renate T, Donfrancesco, Chiara, Engström, Gunnar, Freisling, Heinz, de la Cámara, Agustín Gómez, Gudnason, Vilmundur, Hankey, Graeme J, Hansson, Per-Olof, Heath, Alicia K, Hoorn, Ewout J, Imano, Hironori, Jassal, Simerjot K, Kaaks, Rudolf, Katzke, Verena, Kauhanen, Jussi, Kiechl, Stefan, Koenig, Wolfgang, Kronmal, Richard A, Kyrø, Cecilie, Lawlor, Deborah A, Ljungberg, Börje, Macdonald, Conor, Masala, Giovanna, Meisinger, Christa, Melander, Olle, Moreno Iribas, Conchi, Ninomiya, Toshiharu, Nitsch, Dorothea, Nordestgaard, Børge G, Onland-Moret, Charlotte, Palmieri, Luigi, Petrova, Dafina, Garcia, Jose Ramón Quiró, Rosengren, Annika, Sacerdote, Carlotta, Sakurai, Masaru, Santiuste, Carmen, Schulze, Matthias B, Sieri, Sabina, Sundström, Johan, Tikhonoff, Valérie, Tjønneland, Anne, Tong, Tammy, Tumino, Rosario, Tzoulaki, Ioanna, van der Schouw, Yvonne T, Monique Verschuren, W M, Völzke, Henry, Wallace, Robert B, Wannamethee, S Goya, Weiderpass, Elisabete, Willeit, Peter, Woodward, Mark, Yamagishi, Kazumasa, Zamora-Ros, Raul, Akwo, Elvis A, Pyarajan, Saiju, Gagnon, David R, Tsao, Philip S, Muralidhar, Sumitra, Edwards, Todd L, Damrauer, Scott M, Joseph, Jacob, Pennells, Lisa, Wilson, Peter W F, Harrison, Seamu, Gaziano, Thomas A, Inouye, Michael, Baigent, Colin, Casas, Juan P, Langenberg, Claudia, Wareham, Nick, Riboli, Elio, Gaziano, J Michael, Danesh, John, Hung, Adriana M, Butterworth, Adam S, Wood, Angela M, Di Angelantonio, Emanuele, Internal medicine, AMS - Ageing & Vitality, AMS - Musculoskeletal Health, Amsterdam Gastroenterology Endocrinology Metabolism, Epidemiology and Data Science, APH - Aging & Later Life, and APH - Personalized Medicine

Subjects
kidney disease, General Practice, Emerging Risk Factors Collaboration/EPIC-CVD/Million Veteran Program, Coronary Disease, coronary disease, Kidney, Malalties coronàries, 1117 Public Health and Health Services, Coronary diseases, SDG 3 - Good Health and Well-being, cardiovascular disease, Risk Factors, Physiology (medical), Diabetes Mellitus, Humans, Cardiac and Cardiovascular Systems, Prospective Studies, 1102 Cardiorespiratory Medicine and Haematology, Kardiologi, Kidney diseases, Malalties cardiovasculars, Cardiovascular Diseases, Kidney Diseases, Stroke, 1103 Clinical Sciences, Mendelian Randomization Analysis, kidney diseases, stroke, Allmänmedicin, Cardiovascular diseases, Cardiovascular System & Hematology, Malalties del ronyó, Cardiology and Cardiovascular Medicine, cardiovascular diseases
Abstract

Background: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. Methods: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition–Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. Results: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values 105 mL·min –1 ·1.73 m –2 , compared with those with eGFR between 60 and 105 mL·min –1 ·1.73 m –2 . Mendelian randomization analyses for CHD showed an association among participants with eGFR –1 ·1.73 m –2 , with a 14% (95% CI, 3%–27%) higher CHD risk per 5 mL·min –1 ·1.73 m –2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min –1 ·1.73 m –2 . Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. Conclusions: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function.

Published
2022
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6. COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients

Author

Carla V Rodriguez-Watson, Amy C. Justice, Seth Kuranz, Frank de Wolf, Tom Brown, Nicolle M. Gatto, Anna Siefkas, Andrew Weckstein, Elizabeth Eldridge, Kelly Cho, Yuk-Lam Ho, Julius Asubonteng, Samson Mataraso, Daniel C Posner, Adem Albayrak, Carson Lam, Ritankar Das, Stuart L. Goldberg, Jonathan Hirsch, Andrew J. Belli, Qingqing Mao, Andrew Schrag, Ellen V. Sigal, Mark Stewart, Alice Gelman, Georgia D. Tourassi, Monika A Izano, Reyna Klesh, Amar Bhat, Andrew Ip, Eric Hansen, Susan C. Winckler, Hanna Gerlovin, Jeremy A. Rassen, Jeff Allen, Jason Jones, and Robertino Mera

Subjects
Male, Viral Diseases, Cancer Treatment, Psychological intervention, Electronic Medical Records, Azithromycin, ACE inhibitor therapy, Medical Conditions, 0302 clinical medicine, Epidemiology, Medicine and Health Sciences, Medicine, 030212 general & internal medicine, Data Management, 0303 health sciences, Multidisciplinary, Catalysts, Pharmaceutics, Cardiovascular therapy, Electrocatalysts, Hospitals, Hospitalization, Chemistry, Infectious Diseases, Oncology, Research Design, Physical Sciences, Drug Therapy, Combination, Female, Information Technology, Research Article, Hydroxychloroquine, medicine.drug, Computer and Information Sciences, medicine.medical_specialty, Clinical Research Design, Science, Research and Analysis Methods, Antiviral Agents, Catalysis, 03 medical and health sciences, Pharmacotherapy, Drug Therapy, Humans, Adverse effect, Intensive care medicine, Pandemics, SARS-CoV-2, 030306 microbiology, business.industry, Proportional hazards model, Covid 19, Health Information Technology, COVID-19 Drug Treatment, Health Care, Health Care Facilities, Propensity score matching, Adverse Events, business
Abstract

Background The COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments. Methods Electronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined. Results Neither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events. Conclusion Administration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.

Published
2021

7. Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure

Author

Danielle Rasooly, Gina M. Peloso, Alexandre C. Pereira, Hesam Dashti, Claudia Giambartolomei, Eleanor Wheeler, Nay Aung, Brian R. Ferolito, Maik Pietzner, Eric H. Farber-Eger, Quinn Stanton Wells, Nicole M. Kosik, Liam Gaziano, Daniel C. Posner, A. Patrícia Bento, Qin Hui, Chang Liu, Krishna Aragam, Zeyuan Wang, Brian Charest, Jennifer E. Huffman, Peter W. F. Wilson, Lawrence S. Phillips, John Whittaker, Patricia B. Munroe, Steffen E. Petersen, Kelly Cho, Andrew R. Leach, María Paula Magariños, John Michael Gaziano, VA Million Veteran Program, Claudia Langenberg, Yan V. Sun, Jacob Joseph, and Juan P. Casas

Subjects
Science
Abstract

Abstract We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure.

Published
2023
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