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Tachinardi U, Grannis SJ, Michael SG, Misquitta L, Dahlin J, Sheikh U, Kho A, Phua J, Rogovin SS, Amor B, Choudhury M, Sparks P, Mannaa A, Ljazouli S, Saltz J, Prior F, Baghal A, Gersing K, Embi PJ. Privacy-preserving record linkage across disparate institutions and datasets to enable a learning health system: The national COVID cohort collaborative (N3C) experience. Learn Health Syst 2024; 8:e10404. [PMID: 38249841 PMCID: PMC10797567 DOI: 10.1002/lrh2.10404] [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: 07/22/2023] [Revised: 12/06/2023] [Accepted: 12/06/2023] [Indexed: 01/23/2024] Open
Abstract
Introduction Research driven by real-world clinical data is increasingly vital to enabling learning health systems, but integrating such data from across disparate health systems is challenging. As part of the NCATS National COVID Cohort Collaborative (N3C), the N3C Data Enclave was established as a centralized repository of deidentified and harmonized COVID-19 patient data from institutions across the US. However, making this data most useful for research requires linking it with information such as mortality data, images, and viral variants. The objective of this project was to establish privacy-preserving record linkage (PPRL) methods to ensure that patient-level EHR data remains secure and private when governance-approved linkages with other datasets occur. Methods Separate agreements and approval processes govern N3C data contribution and data access. The Linkage Honest Broker (LHB), an independent neutral party (the Regenstrief Institute), ensures data linkages are robust and secure by adding an extra layer of separation between protected health information and clinical data. The LHB's PPRL methods (including algorithms, processes, and governance) match patient records using "deidentified tokens," which are hashed combinations of identifier fields that define a match across data repositories without using patients' clear-text identifiers. Results These methods enable three linkage functions: Deduplication, Linking Multiple Datasets, and Cohort Discovery. To date, two external repositories have been cross-linked. As of March 1, 2023, 43 sites have signed the LHB Agreement; 35 sites have sent tokens generated for 9 528 998 patients. In this initial cohort, the LHB identified 135 037 matches and 68 596 duplicates. Conclusion This large-scale linkage study using deidentified datasets of varying characteristics established secure methods for protecting the privacy of N3C patient data when linked for research purposes. This technology has potential for use with registries for other diseases and conditions.
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Affiliation(s)
- Umberto Tachinardi
- Department of Biomedical InformaticsUniversity of Cincinnati College of MedicineCincinnatiOhioUSA
| | - Shaun J. Grannis
- Center for Biomedical Informatics, Regenstrief InstituteDepartment of Family Medicine, IU School of MedicineRegenstrief Institute, Inc. and Indiana University School of MedicineIndianapolisIndianaUSA
| | - Sam G. Michael
- National Center for Advancing Translational ScienceNIHBethesdaMarylandUSA
| | - Leonie Misquitta
- National Center for Advancing Translational ScienceNIHBethesdaMarylandUSA
| | - Jayme Dahlin
- National Center for Advancing Translational ScienceNIHBethesdaMarylandUSA
| | - Usman Sheikh
- National Center for Advancing Translational ScienceNIHBethesdaMarylandUSA
| | - Abel Kho
- Department of MedicineNorthwestern University, Feinberg School of MedicineChicagoIllinoisUSA
- Public SectorDatavant, IncSan FranciscoCaliforniaUSA
| | - Jasmin Phua
- Public SectorDatavant, IncSan FranciscoCaliforniaUSA
| | | | - Benjamin Amor
- Federal HealthPalantir TechnologiesDenverColoradoUSA
| | | | - Philip Sparks
- Federal HealthPalantir TechnologiesDenverColoradoUSA
| | - Amin Mannaa
- Federal HealthPalantir TechnologiesDenverColoradoUSA
| | - Saad Ljazouli
- Federal HealthPalantir TechnologiesDenverColoradoUSA
| | - Joel Saltz
- School of MedicineStony Brook UniversityStony BrookNew YorkUSA
| | - Fred Prior
- COM Biomedical InformaticsUniversity of Arkansas for Medical SciencesLittle RockArkansasUSA
| | - Ahmen Baghal
- COM Biomedical InformaticsUniversity of Arkansas for Medical SciencesLittle RockArkansasUSA
| | - Kenneth Gersing
- National Center for Advancing Translational ScienceNIHBethesdaMarylandUSA
| | - Peter J. Embi
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTennesseeUSA
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Kwiatkowski M, Wurlitzer M, Krutilin A, Kiani P, Nimer R, Omidi M, Mannaa A, Bussmann T, Bartkowiak K, Kruber S, Uschold S, Steffen P, Lübberstedt J, Küpker N, Petersen H, Knecht R, Hansen NO, Zarrine-Afsar A, Robertson WD, Miller RJD, Schlüter H. Homogenization of tissues via picosecond-infrared laser (PIRL) ablation: Giving a closer view on the in-vivo composition of protein species as compared to mechanical homogenization. J Proteomics 2016; 134:193-202. [PMID: 26778141 PMCID: PMC4767054 DOI: 10.1016/j.jprot.2015.12.029] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Revised: 12/22/2015] [Accepted: 12/31/2015] [Indexed: 12/30/2022]
Abstract
Posttranslational modifications and proteolytic processing regulate almost all physiological processes. Dysregulation can potentially result in pathologic protein species causing diseases. Thus, tissue species proteomes of diseased individuals provide diagnostic information. Since the composition of tissue proteomes can rapidly change during tissue homogenization by the action of enzymes released from their compartments, disease specific protein species patterns can vanish. Recently, we described a novel, ultrafast and soft method for cold vaporization of tissue via desorption by impulsive vibrational excitation (DIVE) using a picosecond-infrared-laser (PIRL). Given that DIVE extraction may provide improved access to the original composition of protein species in tissues, we compared the proteome composition of tissue protein homogenates after DIVE homogenization with conventional homogenizations. A higher number of intact protein species was observed in DIVE homogenates. Due to the ultrafast transfer of proteins from tissues via gas phase into frozen condensates of the aerosols, intact protein species were exposed to a lesser extent to enzymatic degradation reactions compared with conventional protein extraction. In addition, total yield of the number of proteins is higher in DIVE homogenates, because they are very homogenous and contain almost no insoluble particles, allowing direct analysis with subsequent analytical methods without the necessity of centrifugation. Biological significance Enzymatic protein modifications during tissue homogenization are responsible for changes of the in-vivo protein species composition. Cold vaporization of tissues by PIRL-DIVE is comparable with taking a snapshot at the time of the laser irradiation of the dynamic changes that occur continuously under in-vivo conditions. At that time point all biomolecules are transferred into an aerosol, which is immediately frozen.
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Affiliation(s)
- M Kwiatkowski
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - M Wurlitzer
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - A Krutilin
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - P Kiani
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - R Nimer
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - M Omidi
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - A Mannaa
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - T Bussmann
- Beiersdorf AG, Research & Development, Unnastrasse 48, 20245, Hamburg, Germany
| | - K Bartkowiak
- University Medical Centre Hamburg-Eppendorf, Department of Tumor Biology, Martinistraße 52, 20246 Hamburg, Germany
| | - S Kruber
- Max Planck Institute for the Structure and Dynamics of Matter, Atomically Resolved Dynamics Division, Luruper Chaussee 149, 22761 Hamburg, Germany
| | - S Uschold
- Max Planck Institute for the Structure and Dynamics of Matter, Atomically Resolved Dynamics Division, Luruper Chaussee 149, 22761 Hamburg, Germany
| | - P Steffen
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - J Lübberstedt
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - N Küpker
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany
| | - H Petersen
- University Medical Centre Hamburg-Eppendorf, Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, Martinistraße 52, 20246 Hamburg, Germany
| | - R Knecht
- University Medical Centre Hamburg-Eppendorf, Department of Otorhinolaryngology, Head and Neck Surgery and Oncology, Martinistraße 52, 20246 Hamburg, Germany
| | - N O Hansen
- Max Planck Institute for the Structure and Dynamics of Matter, Atomically Resolved Dynamics Division, Luruper Chaussee 149, 22761 Hamburg, Germany
| | - A Zarrine-Afsar
- Techna Institute for the Advancement of Technology for Health, University Health Network, Toronto, ON M5G-1P5, Canada & Department of Medical Biophysics, University of Toronto, 101 College Street Suite 15-701, Toronto, ON M5G 1L7, Canada
| | - W D Robertson
- Max Planck Institute for the Structure and Dynamics of Matter, Atomically Resolved Dynamics Division, Luruper Chaussee 149, 22761 Hamburg, Germany
| | - R J D Miller
- Max Planck Institute for the Structure and Dynamics of Matter, Atomically Resolved Dynamics Division, Luruper Chaussee 149, 22761 Hamburg, Germany
| | - H Schlüter
- University Medical Centre Hamburg-Eppendorf, Institute for Clinical Chemistry, Department for Mass Spectrometric Proteomics, Martinistraße 52, 20246 Hamburg, Germany.
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