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Dellacasa C, Ortali M, Rossi E, Abu Attieh H, Osmo T, Puskaric M, Rinaldi E, Prasser F, Stellmach C, Cataudella S, Agarwal B, Mata Naranjo J, Scipione G. An innovative technological infrastructure for managing SARS-CoV-2 data across different cohorts in compliance with General Data Protection Regulation. Digit Health 2024; 10:20552076241248922. [PMID: 38766364 PMCID: PMC11100396 DOI: 10.1177/20552076241248922] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 04/04/2024] [Indexed: 05/22/2024] Open
Abstract
Background The ORCHESTRA project, funded by the European Commission, aims to create a pan-European cohort built on existing and new large-scale population cohorts to help rapidly advance the knowledge related to the prevention of the SARS-CoV-2 infection and the management of COVID-19 and its long-term sequelae. The integration and analysis of the very heterogeneous health data pose the challenge of building an innovative technological infrastructure as the foundation of a dedicated framework for data management that should address the regulatory requirements such as the General Data Protection Regulation (GDPR). Methods The three participating Supercomputing European Centres (CINECA - Italy, CINES - France and HLRS - Germany) designed and deployed a dedicated infrastructure to fulfil the functional requirements for data management to ensure sensitive biomedical data confidentiality/privacy, integrity, and security. Besides the technological issues, many methodological aspects have been considered: Berlin Institute of Health (BIH), Charité provided its expertise both for data protection, information security, and data harmonisation/standardisation. Results The resulting infrastructure is based on a multi-layer approach that integrates several security measures to ensure data protection. A centralised Data Collection Platform has been established in the Italian National Hub while, for the use cases in which data sharing is not possible due to privacy restrictions, a distributed approach for Federated Analysis has been considered. A Data Portal is available as a centralised point of access for non-sensitive data and results, according to findability, accessibility, interoperability, and reusability (FAIR) data principles. This technological infrastructure has been used to support significative data exchange between population cohorts and to publish important scientific results related to SARS-CoV-2. Conclusions Considering the increasing demand for data usage in accordance with the requirements of the GDPR regulations, the experience gained in the project and the infrastructure released for the ORCHESTRA project can act as a model to manage future public health threats. Other projects could benefit from the results achieved by ORCHESTRA by building upon the available standardisation of variables, design of the architecture, and process used for GDPR compliance.
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Affiliation(s)
- Chiara Dellacasa
- HPC Department, CINECA Consorzio Interuniversitario,
Bologna, Italy
| | - Maurizio Ortali
- HPC Department, CINECA Consorzio Interuniversitario,
Bologna, Italy
| | - Elisa Rossi
- HPC Department, CINECA Consorzio Interuniversitario,
Bologna, Italy
| | - Hammam Abu Attieh
- Berlin Institute of Health (BIH), Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Thomas Osmo
- Département Archivage et Services aux Données (DASD), Centre Informatique National de l'Enseignement Supérieur (CINES), Montpellier, France
| | - Miroslav Puskaric
- High Performance Computing Center Stuttgart (HLRS), University of Stuttgart, Stuttgart, Germany
| | - Eugenia Rinaldi
- Berlin Institute of Health (BIH), Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Fabian Prasser
- Berlin Institute of Health (BIH), Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Caroline Stellmach
- Berlin Institute of Health (BIH), Charité – Universitätsmedizin Berlin, Berlin, Germany
| | | | - Bhaskar Agarwal
- HPC Department, CINECA Consorzio Interuniversitario,
Bologna, Italy
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Gentilotti E, Górska A, Tami A, Gusinow R, Mirandola M, Rodríguez Baño J, Palacios Baena ZR, Rossi E, Hasenauer J, Lopes-Rafegas I, Righi E, Caroccia N, Cataudella S, Pasquini Z, Osmo T, Del Piccolo L, Savoldi A, Kumar-Singh S, Mazzaferri F, Caponcello MG, de Boer G, Hara GL, De Nardo P, Malhotra S, Canziani LM, Ghosn J, Florence AM, Lafhej N, van der Gun BT, Giannella M, Laouénan C, Tacconelli E. Clinical phenotypes and quality of life to define post-COVID-19 syndrome: a cluster analysis of the multinational, prospective ORCHESTRA cohort. EClinicalMedicine 2023; 62:102107. [PMID: 37654668 PMCID: PMC10466236 DOI: 10.1016/j.eclinm.2023.102107] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 06/30/2023] [Accepted: 06/30/2023] [Indexed: 09/02/2023] Open
Abstract
Background Lack of specific definitions of clinical characteristics, disease severity, and risk and preventive factors of post-COVID-19 syndrome (PCS) severely impacts research and discovery of new preventive and therapeutics drugs. Methods This prospective multicenter cohort study was conducted from February 2020 to June 2022 in 5 countries, enrolling SARS-CoV-2 out- and in-patients followed at 3-, 6-, and 12-month from diagnosis, with assessment of clinical and biochemical features, antibody (Ab) response, Variant of Concern (VoC), and physical and mental quality of life (QoL). Outcome of interest was identification of risk and protective factors of PCS by clinical phenotype, setting, severity of disease, treatment, and vaccination status. We used SF-36 questionnaire to assess evolution in QoL index during follow-up and unsupervised machine learning algorithms (principal component analysis, PCA) to explore symptom clusters. Severity of PCS was defined by clinical phenotype and QoL. We also used generalized linear models to analyse the impact of PCS on QoL and associated risk and preventive factors. CT registration number: NCT05097677. Findings Among 1796 patients enrolled, 1030 (57%) suffered from at least one symptom at 12-month. PCA identified 4 clinical phenotypes: chronic fatigue-like syndrome (CFs: fatigue, headache and memory loss, 757 patients, 42%), respiratory syndrome (REs: cough and dyspnoea, 502, 23%); chronic pain syndrome (CPs: arthralgia and myalgia, 399, 22%); and neurosensorial syndrome (NSs: alteration in taste and smell, 197, 11%). Determinants of clinical phenotypes were different (all comparisons p < 0.05): being female increased risk of CPs, NSs, and CFs; chronic pulmonary diseases of REs; neurological symptoms at SARS-CoV-2 diagnosis of REs, NSs, and CFs; oxygen therapy of CFs and REs; and gastrointestinal symptoms at SARS-CoV-2 diagnosis of CFs. Early treatment of SARS-CoV-2 infection with monoclonal Ab (all clinical phenotypes), corticosteroids therapy for mild/severe cases (NSs), and SARS-CoV-2 vaccination (CPs) were less likely to be associated to PCS (all comparisons p < 0.05). Highest reduction in QoL was detected in REs and CPs (43.57 and 43.86 vs 57.32 in PCS-negative controls, p < 0.001). Female sex (p < 0.001), gastrointestinal symptoms (p = 0.034) and renal complications (p = 0.002) during the acute infection were likely to increase risk of severe PCS (QoL <50). Vaccination and early treatment with monoclonal Ab reduced the risk of severe PCS (p = 0.01 and p = 0.03, respectively). Interpretation Our study provides new evidence suggesting that PCS can be classified by clinical phenotypes with different impact on QoL, underlying possible different pathogenic mechanisms. We identified factors associated to each clinical phenotype and to severe PCS. These results might help in designing pathogenesis studies and in selecting high-risk patients for inclusion in therapeutic and management clinical trials. Funding The study received funding from the Horizon 2020 ORCHESTRA project, grant 101016167; from the Netherlands Organisation for Health Research and Development (ZonMw), grant 10430012010023; from Inserm, REACTing (REsearch & ACtion emergING infectious diseases) consortium and the French Ministry of Health, grant PHRC 20-0424.
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Affiliation(s)
- Elisa Gentilotti
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Anna Górska
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Adriana Tami
- University of Groningen, University Medical Center Groningen, Department
of Medical Microbiology and Infection Prevention, Groningen, The
Netherlands
| | - Roy Gusinow
- The Life & Medical Sciences Institute (LIMES), University of
Bonn-Institute for Computational Biology, Helmholtz Munich; Research Center for
Environmental Health, Neuherberg, Germany
| | - Massimo Mirandola
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Jesús Rodríguez Baño
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital
Universitario Virgen Macarena, Departamento de Medicina, Universidad de Sevilla,
Spain
- Instituto de Biomedicina de Sevilla (IBiS)/CSIC, Seville,
Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Zaira R. Palacios Baena
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital
Universitario Virgen Macarena, Departamento de Medicina, Universidad de Sevilla,
Spain
- Instituto de Biomedicina de Sevilla (IBiS)/CSIC, Seville,
Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Elisa Rossi
- CINECA Interuniversity Consortium, Bologna, Italy
| | - Jan Hasenauer
- The Life & Medical Sciences Institute (LIMES), University of
Bonn-Institute for Computational Biology, Helmholtz Munich; Research Center for
Environmental Health, Neuherberg, Germany
| | - Iris Lopes-Rafegas
- Barcelona Institute for Global Health (ISGlobal), Hospital Clínic,
University of Barcelona, Spain
| | - Elda Righi
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Natascia Caroccia
- Department of Medical and Surgical Sciences, Alma Mater Studiorum,
University of Bologna, Bologna, Italy
| | | | - Zeno Pasquini
- Infectious Diseases Unit, IRCCS Azienda Ospedaliero-Universitaria di
Bologna, Bologna, Italy
| | - Thomas Osmo
- Centre Informatique National de l'Enseignement Supérieur CINES,
France
| | - Lidia Del Piccolo
- Department of Neurosciences, Biomedicine and Movement Sciences,
University of Verona, Verona, Italy
| | - Alessia Savoldi
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Samir Kumar-Singh
- Molecular Pathology Group, Cell Biology & Histology, and Laboratory
of Medical Microbiology, Vaccine & Infectious Disease Institute, Faculty of
Medicine, University of Antwerp, Antwerp, Belgium
| | - Fulvia Mazzaferri
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Maria Giulia Caponcello
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital
Universitario Virgen Macarena, Departamento de Medicina, Universidad de Sevilla,
Spain
- Instituto de Biomedicina de Sevilla (IBiS)/CSIC, Seville,
Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Gerolf de Boer
- University of Groningen, University Medical Center Groningen, Department
of Medical Microbiology and Infection Prevention, Groningen, The
Netherlands
| | - Gabriel Levy Hara
- Instituto Alberto C. Taquini de Investigaciones en Medicina Traslacional,
Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Pasquale De Nardo
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Surbhi Malhotra
- Molecular Pathology Group, Cell Biology & Histology, and Laboratory
of Medical Microbiology, Vaccine & Infectious Disease Institute, Faculty of
Medicine, University of Antwerp, Antwerp, Belgium
| | - Lorenzo Maria Canziani
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
| | - Jade Ghosn
- Université Paris Cité, INSERM IAME UMR 1137, Paris, France
- AP-HP Nord, Hôpital Bichat, Department of Infectious and Tropical
Diseases, Paris, France
| | - Aline-Marie Florence
- Université Paris Cité, INSERM IAME UMR 1137, Paris, France
- AP-HP Nord, Hôpital Bichat, Department of Epidemiology Biostatistics and
Clinical Research, Paris, France
| | - Nadhem Lafhej
- AP-HP Nord, Hôpital Bichat, Department of Epidemiology Biostatistics and
Clinical Research, Paris, France
| | - Bernardina T.F. van der Gun
- University of Groningen, University Medical Center Groningen, Department
of Medical Microbiology and Infection Prevention, Groningen, The
Netherlands
| | - Maddalena Giannella
- Department of Medical and Surgical Sciences, Alma Mater Studiorum,
University of Bologna, Bologna, Italy
- Infectious Diseases Unit, IRCCS Azienda Ospedaliero-Universitaria di
Bologna, Bologna, Italy
| | - Cédric Laouénan
- Université Paris Cité, INSERM IAME UMR 1137, Paris, France
- AP-HP Nord, Hôpital Bichat, Department of Epidemiology Biostatistics and
Clinical Research, Paris, France
| | - Evelina Tacconelli
- Infectious Disease, Department of Diagnostics and Public Health,
University of Verona, Verona, Italy
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Dellacasa C, Ortali M, Rossi E, D'Antonio M, Osmo T, Prasser F, Puskaric M, Rinaldi E, Scipione G. European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR. Eur J Public Health 2022; 32:ckac129.427. [PMCID: PMC9620090 DOI: 10.1093/eurpub/ckac129.427] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023] Open
Abstract
The Connecting European SARS-CoV-2 Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic (ORCHESTRA) consortium, led by University of Verona (Italy), brings together key European academic experts and research institutions in infectious diseases, data management and High Performance Computing (HPC) from 26 organizations (extending to 37 partners) from 15 countries. The project aims to create a new pan-European cohort built on existing and new large-scale population cohorts in European and non-European countries to significantly impact on the responsiveness to SARS-CoV-2. The integration and analysis of the very heterogeneous characteristics of SARS-CoV-2 data coming from many different sources such as EHR, retrospective and prospective patient registries, and related ‘omics’ data (incl. genomics, proteomics and transcriptomics) can benefit of data analytics enabled by HPC, where both high compute performance and fast storage capabilities are immensely important. During the first year of the project, a dedicated HPC cloud infrastructure have been designed and partially deployed to fulfill the functional requirements for data management ensuring healthcare data confidentiality/privacy, integrity and security in compliance with the European GDPR regulations. The result is an infrastructure for Data Management composed by three main layers: National Data Providers; National Hubs (one for each HPC center involved: CINECA - Italy, CINES - France and HLRS - Germany), to centralize data at national level and to support data storage, sharing and analysis on data ingested from the National Data Providers; ORCHESTRA Data Portal: the pan-European portal for sharing aggregated data and results. Currently data collection is on going; at the end of the project, clinical centers are expected to have enrolled more than 10.000 patients with about 50.000 samples for the prospective studies. Key messages • The SARS-CoV-2 crisis made evident the need to manage and analyse very heterogeneous health data coming from many different resources across different countries. • The HPC cloud infrastructure released for the Orchestra project can act as a model to manage future public health threats.
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Affiliation(s)
- C Dellacasa
- HPC Department, CINECA Consorzio Interuniversitario, Casalecchio di Reno, Italy
| | - M Ortali
- HPC Department, CINECA Consorzio Interuniversitario, Casalecchio di Reno, Italy
| | - E Rossi
- HPC Department, CINECA Consorzio Interuniversitario, Casalecchio di Reno, Italy
| | - M D'Antonio
- HPC Department, CINECA Consorzio Interuniversitario, Casalecchio di Reno, Italy
| | - T Osmo
- CINES Centre Informatique National de l'Enseigneme, Montpellier, France
| | - F Prasser
- Berlin Institute of Health (BIH), Charité, Berlin, Germany
| | - M Puskaric
- High Performance Computing Center Stuttgart (HLRS), Stuttgart, Germany
| | - E Rinaldi
- Berlin Institute of Health (BIH), Charité, Berlin, Germany
| | | | - G Scipione
- HPC Department, CINECA Consorzio Interuniversitario, Casalecchio di Reno, Italy
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