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Linschoten M, Uijl A, Schut A, Jakob CEM, Romão LR, Bell RM, McFarlane E, Stecher M, Zondag AGM, van Iperen EPA, Hermans-van Ast W, Lea NC, Schaap J, Jewbali LS, Smits PC, Patel RS, Aujayeb A, van der Harst P, Siebelink HJ, van Smeden M, Williams S, Pilgram L, van Gilst WH, Tieleman RG, Williams B, Asselbergs FW, Al-Ali AK, Al-Muhanna FA, Al-Rubaish AM, Al-Windy NYY, Alkhalil M, Almubarak YA, Alnafie AN, Alshahrani M, Alshehri AM, Anning C, Anthonio RL, Badings EA, Ball C, van Beek EA, ten Berg JM, von Bergwelt-Baildon M, Bianco M, Blagova OV, Bleijendaal H, Bor WL, Borgmann S, van Boxem AJM, van den Brink FS, Bucciarelli-Ducci C, van Bussel BCT, Byrom-Goulthorp R, Captur G, Caputo M, Charlotte N, vom Dahl J, Dark P, De Sutter J, Degenhardt C, Delsing CE, Dolff S, Dorman HGR, Drost JT, Eberwein L, Emans ME, Er AG, Ferreira JB, Forner MJ, Friedrichs A, Gabriel L, Groenemeijer BE, Groenendijk AL, Grüner B, Guggemos W, Haerkens-Arends HE, Hanses F, Hedayat B, Heigener D, van der Heijden DJ, Hellou E, Hellwig K, Henkens MTHM, Hermanides RS, Hermans WRM, van Hessen MWJ, Heymans SRB, Hilt AD, van der Horst ICC, Hower M, van Ierssel SH, Isberner N, Jensen B, Kearney MT, van Kesteren HAM, Kielstein JT, Kietselaer BLJH, Kochanek M, Kolk MZH, Koning AMH, Kopylov PY, Kuijper AFM, Kwakkel-van Erp JM, Lanznaster J, van der Linden MMJM, van der Lingen ACJ, Linssen GCM, Lomas D, Maarse M, Macías Ruiz R, Magdelijns FJH, Magro M, Markart P, Martens FMAC, Mazzilli SG, McCann GP, van der Meer P, Meijs MFL, Merle U, Messiaen P, Milovanovic M, Monraats PS, Montagna L, Moriarty A, Moss AJ, Mosterd A, Nadalin S, Nattermann J, Neufang M, Nierop PR, Offerhaus JA, van Ofwegen-Hanekamp CEE, Parker E, Persoon AM, Piepel C, Pinto YM, Poorhosseini H, Prasad S, Raafs AG, Raichle C, Rauschning D, Redón J, Reidinga AC, Ribeiro MIA, Riedel C, Rieg S, Ripley DP, Römmele C, Rothfuss K, Rüddel J, Rüthrich MM, Salah R, Saneei E, Saxena M, Schellings DAAM, Scholte NTB, Schubert J, Seelig J, Shafiee A, Shore AC, Spinner C, Stieglitz S, Strauss R, Sturkenboom NH, Tessitore E, Thomson RJ, Timmermans P, Tio RA, Tjong FVY, Tometten L, Trauth J, den Uil CA, Van Craenenbroeck EM, van Veen HPAA, Vehreschild MJGT, Veldhuis LI, Veneman T, Verschure DO, Voigt I, de Vries JK, van de Wal RMA, Walter L, van de Watering DJ, Westendorp ICD, Westendorp PHM, Westhoff T, Weytjens C, Wierda E, Wille K, de With K, Worm M, Woudstra P, Wu KW, Zaal R, Zaman AG, van der Zee PM, Zijlstra LE, Alling TE, Ahmed R, van Aken K, Bayraktar-Verver ECE, Bermúdez Jiménes FJ, Biolé CA, den Boer-Penning P, Bontje M, Bos M, Bosch L, Broekman M, Broeyer FJF, de Bruijn EAW, Bruinsma S, Cardoso NM, Cosyns B, van Dalen DH, Dekimpe E, Domange J, van Doorn JL, van Doorn P, Dormal F, Drost IMJ, Dunnink A, van Eck JWM, Elshinawy K, Gevers RMM, Gognieva DG, van der Graaf M, Grangeon S, Guclu A, Habib A, Haenen NA, Hamilton K, Handgraaf S, Heidbuchel H, Hendriks-van Woerden M, Hessels-Linnemeijer BM, Hosseini K, Huisman J, Jacobs TC, Jansen SE, Janssen A, Jourdan K, ten Kate GL, van Kempen MJ, Kievit CM, Kleikers P, Knufman N, van der Kooi SE, Koole BAS, Koole MAC, Kui KK, Kuipers-Elferink L, Lemoine I, Lensink E, van Marrewijk V, van Meerbeeck JP, Meijer EJ, Melein AJ, Mesitskaya DF, van Nes CPM, Paris FMA, Perrelli MG, Pieterse-Rots A, Pisters R, Pölkerman BC, van Poppel A, Reinders S, Reitsma MJ, Ruiter AH, Selder JL, van der Sluis A, Sousa AIC, Tajdini M, Tercedor Sánchez L, Van De Heyning CM, Vial H, Vlieghe E, Vonkeman HE, Vreugdenhil P, de Vries TAC, Willems AM, Wils AM, Zoet-Nugteren SK. Clinical presentation, disease course, and outcome of COVID-19 in hospitalized patients with and without pre-existing cardiac disease: a cohort study across 18 countries. Eur Heart J 2022; 43:1104-1120. [PMID: 34734634 DOI: 10.1093/eurheartj/ehab656] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/22/2021] [Accepted: 09/01/2021] [Indexed: 12/25/2022] Open
Abstract
AIMS Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality. METHODS AND RESULTS We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66-75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02-1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10-1.30; P < 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20-1.64; P < 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients. CONCLUSION Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization.
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Pan B, Ren L, Onuchic V, Guan M, Kusko R, Bruinsma S, Trigg L, Scherer A, Ning B, Zhang C, Glidewell-Kenney C, Xiao C, Donaldson E, Sedlazeck FJ, Schroth G, Yavas G, Grunenwald H, Chen H, Meinholz H, Meehan J, Wang J, Yang J, Foox J, Shang J, Miclaus K, Dong L, Shi L, Mohiyuddin M, Pirooznia M, Gong P, Golshani R, Wolfinger R, Lababidi S, Sahraeian SME, Sherry S, Han T, Chen T, Shi T, Hou W, Ge W, Zou W, Guo W, Bao W, Xiao W, Fan X, Gondo Y, Yu Y, Zhao Y, Su Z, Liu Z, Tong W, Xiao W, Zook JM, Zheng Y, Hong H. Assessing reproducibility of inherited variants detected with short-read whole genome sequencing. Genome Biol 2022; 23:2. [PMID: 34980216 PMCID: PMC8722114 DOI: 10.1186/s13059-021-02569-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [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: 11/22/2021] [Accepted: 12/06/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. RESULTS To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. CONCLUSIONS Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.
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Affiliation(s)
- Bohu Pan
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Luyao Ren
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | | | | | | | - Len Trigg
- Real Time Genomics, Hamilton, New Zealand
| | - Andreas Scherer
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- EATRIS ERIC- European Infrastructure for Translational Medicine, Amsterdam, the Netherlands
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Chaoyang Zhang
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
| | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Eric Donaldson
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | | | - Gokhan Yavas
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | | | | | | | - Joe Meehan
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Jing Wang
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, 100013, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10021, USA
| | - Jun Shang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | - Lianhua Dong
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, 100013, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ping Gong
- Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS, 39180, USA
| | | | | | - Samir Lababidi
- Office of Health Informatics, Office of the Commissioner, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | | | - Steve Sherry
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Tao Han
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tao Chen
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tieliu Shi
- The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Wanwan Hou
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Weigong Ge
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wen Zou
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenjing Guo
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenjun Bao
- SAS Institute Inc., Cary, NC, 27513, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA, 94305, USA
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yoichi Gondo
- Department of Molecular Life Sciences, Tokai University School of Medicine, 143 Shimokasuya, Isehara, 259-1193, Japan
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Yongmei Zhao
- CCR-SF Bioinformatics Group, Advanced Biomedical and Computational Sciences, Biomedical Informatics and Data Science, Frederick National Laboratory for Cancer Research, Frederick, MD, 21701, USA
| | - Zhenqiang Su
- Takeda Pharmaceuticals, Cambridge, MA, 02139, USA
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenming Xiao
- Division of Molecular Genetics and Pathology, Center for Device and Radiological Health, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA.
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Fudan University, Shanghai, 200438, China.
| | - Huixiao Hong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
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