Privacy-preserving record linkage across disparate institutions and datasets to enable a learning health system: The national COVID cohort collaborative (N3C) experience

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.

A framework for future national pediatric pandemic respiratory disease severity triage: The HHS pediatric COVID-19 data challenge

Introduction

With persistent incidence, incomplete vaccination rates, confounding respiratory illnesses, and few therapeutic interventions available, COVID-19 continues to be a burden on the pediatric population. During a surge, it is difficult for hospitals to direct limited healthcare resources effectively. While the overwhelming majority of pediatric infections are mild, there have been life-threatening exceptions that illuminated the need to proactively identify pediatric patients at risk of severe COVID-19 and other respiratory infectious diseases. However, a nationwide capability for developing validated computational tools to identify pediatric patients at risk using real-world data does not exist.

Methods

HHS ASPR BARDA sought, through the power of competition in a challenge, to create computational models to address two clinically important questions using the National COVID Cohort Collaborative: (1) Of pediatric patients who test positive for COVID-19 in an outpatient setting, who are at risk for hospitalization? (2) Of pediatric patients who test positive for COVID-19 and are hospitalized, who are at risk for needing mechanical ventilation or cardiovascular interventions?

Results

This challenge was the first, multi-agency, coordinated computational challenge carried out by the federal government as a response to a public health emergency. Fifty-five computational models were evaluated across both tasks and two winners and three honorable mentions were selected.

Conclusion

This challenge serves as a framework for how the government, research communities, and large data repositories can be brought together to source solutions when resources are strapped during a pandemic.

Accelerating Medicines Partnership: Parkinson's Disease. Genetic Resource

BACKGROUND

Whole-genome sequencing data are available from several large studies across a variety of diseases and traits. However, massive storage and computation resources are required to use these data, and to achieve sufficient power for discoveries, harmonization of multiple cohorts is critical.

OBJECTIVES

The Accelerating Medicines Partnership Parkinson's Disease program has developed a research platform for Parkinson's disease (PD) that integrates the storage and analysis of whole-genome sequencing data, RNA expression data, and clinical data, harmonized across multiple cohort studies.

METHODS

The version 1 release contains whole-genome sequencing data derived from 3941 participants from 4 cohorts. Samples underwent joint genotyping by the TOPMed Freeze 9 Variant Calling Pipeline. We performed descriptive analyses of these whole-genome sequencing data using the Accelerating Medicines Partnership Parkinson's Disease platform.

RESULTS

The clinical diagnosis of participants in version 1 release includes 2005 idiopathic PD patients, 963 healthy controls, 64 prodromal subjects, 62 clinically diagnosed PD subjects without evidence of dopamine deficit, and 705 participants of genetically enriched cohorts carrying PD risk-associated GBA variants or LRRK2 variants, of whom 304 were affected. We did not observe significant enrichment of pathogenic variants in the idiopathic PD group, but the polygenic risk score was higher in PD both in nongenetically enriched cohorts and genetically enriched cohorts. The population analysis showed a correlation between genetically enriched cohorts and Ashkenazi Jewish ancestry.

CONCLUSIONS

We describe the genetic component of the Accelerating Medicines Partnership Parkinson's Disease platform, a solution to democratize data access and analysis for the PD research community. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article is a U.S. Government work and is in the public domain in the USA.

Pre-Clinical Common Data Elements for Traumatic Brain Injury Research: Progress and Use Cases

Traumatic brain injury (TBI) is an extremely complex condition due to heterogeneity in injury mechanism, underlying conditions, and secondary injury. Pre-clinical and clinical researchers face challenges with reproducibility that negatively impact translation and therapeutic development for improved TBI patient outcomes. To address this challenge, TBI Pre-clinical Working Groups expanded upon previous efforts and developed common data elements (CDEs) to describe the most frequently used experimental parameters. The working groups created 913 CDEs to describe study metadata, animal characteristics, animal history, injury models, and behavioral tests. Use cases applied a set of commonly used CDEs to address and evaluate the degree of missing data resulting from combining legacy data from different laboratories for two different outcome measures (Morris water maze [MWM]; RotorRod/Rotarod). Data were cleaned and harmonized to Form Structures containing the relevant CDEs and subjected to missing value analysis. For the MWM dataset (358 animals from five studies, 44 CDEs), 50% of the CDEs contained at least one missing value, while for the Rotarod dataset (97 animals from three studies, 48 CDEs), over 60% of CDEs contained at least one missing value. Overall, 35% of values were missing across the MWM dataset, and 33% of values were missing for the Rotarod dataset, demonstrating both the feasibility and the challenge of combining legacy datasets using CDEs. The CDEs and the associated forms created here are available to the broader pre-clinical research community to promote consistent and comprehensive data acquisition, as well as to facilitate data sharing and formation of data repositories. In addition to addressing the challenge of standardization in TBI pre-clinical studies, this effort is intended to bring attention to the discrepancies in assessment and outcome metrics among pre-clinical laboratories and ultimately accelerate translation to clinical research.

Development of an informatics system for accelerating biomedical research

The Biomedical Research Informatics Computing System (BRICS) was developed to support multiple disease-focused research programs. Seven service modules are integrated together to provide a collaborative and extensible web-based environment. The modules-Data Dictionary, Account Management, Query Tool, Protocol and Form Research Management System, Meta Study, Data Repository and Globally Unique Identifier -facilitate the management of research protocols, to submit, process, curate, access and store clinical, imaging, and derived genomics data within the associated data repositories. Multiple instances of BRICS are deployed to support various biomedical research communities focused on accelerating discoveries for rare diseases, Traumatic Brain Injury, Parkinson's Disease, inherited eye diseases and symptom science research. No Personally Identifiable Information is stored within the data repositories. Digital Object Identifiers are associated with the research studies. Reusability of biomedical data is enhanced by Common Data Elements (CDEs) which enable systematic collection, analysis and sharing of data. The use of CDEs with a service-oriented informatics architecture enabled the development of disease-specific repositories that support hypothesis-based biomedical research.

The completion of the Mammalian Gene Collection (MGC)

Since its start, the Mammalian Gene Collection (MGC) has sought to provide at least one full-protein-coding sequence cDNA clone for every human and mouse gene with a RefSeq transcript, and at least 6200 rat genes. The MGC cloning effort initially relied on random expressed sequence tag screening of cDNA libraries. Here, we summarize our recent progress using directed RT-PCR cloning and DNA synthesis. The MGC now contains clones with the entire protein-coding sequence for 92% of human and 89% of mouse genes with curated RefSeq (NM-accession) transcripts, and for 97% of human and 96% of mouse genes with curated RefSeq transcripts that have one or more PubMed publications, in addition to clones for more than 6300 rat genes. These high-quality MGC clones and their sequences are accessible without restriction to researchers worldwide.

Collection of Drosophila Embryos for RNA Interference (RNAi)

INTRODUCTIONRNA interference (RNAi) is a powerful method for determining the role of specific genes during Drosophila embryogenesis. This protocol describes a method for collection of Drosophila embryos for RNA interference (RNAi) experiments. The embryos are collected in a simple, homemade apparatus, arrayed on prepared glass slides, and readied for injection. It is important to keep the embryos moist and oxygenated. Work expeditiously, because embryos should be injected within 30-60 min after collection.

Injection of dsRNA into Drosophila Embryos for RNA Interference (RNAi)

INTRODUCTIONRNA interference (RNAi) is a powerful method for determining the role of specific genes during Drosophila embryogenesis. This protocol describes a technique by which Drosophila embryos can be injected with dsRNA in order to disrupt targeted gene function. The approach is straightforward, utilizing improved methods for injecting the dsRNA directly through the chorion of the embryo. This strategy minimizes problems normally associated with desiccation of the dechorionated embryo and facilitates post-injection analysis of gene expression.

Drosophila RNA Interference (RNAi) Using a Gal-4 Inducible Transgene Vector

INTRODUCTIONRNA interference (RNAi) is a powerful method for determining the role of specific genes during Drosophila embryogenesis. This protocol describes a method for RNAi in vivo using tissue-specific Gal-4 transgenes to induce dsRNA synthesis from an upstream activator sequence (UAS) vector. This vector contains the desired exonic inverted sequences representing the target gene (preferably more than 400 bp) separated by a unique spacer, the first intron of the actin 5C gene. The inverted repeats are stable during cloning in E. coli with this intronic spacer and the intron is spliced out to produce an almost perfect dsRNA target for Dicer cleavage and the production of siRNAs.

Preparation of Double-Stranded RNA for Drosophila RNA Interference (RNAi)

INTRODUCTIONRNA interference (RNAi) is a powerful method for determining the role of specific genes during Drosophila embryogenesis. It has been used in our laboratory to phenocopy a series of known mutations in Drosophila, including twist, engrailed, daughterless, Dmef2, and, to a lesser extent, white in the adult eye. This protocol describes the preparation of dsRNA by in vitro transcription of complementary strands of a cloned DNA fragment that codes for all or a portion of the gene of interest, followed by annealing of the transcribed RNA.

The status, quality, and expansion of the NIH full-length cDNA project: the Mammalian Gene Collection (MGC)

The National Institutes of Health's Mammalian Gene Collection (MGC) project was designed to generate and sequence a publicly accessible cDNA resource containing a complete open reading frame (ORF) for every human and mouse gene. The project initially used a random strategy to select clones from a large number of cDNA libraries from diverse tissues. Candidate clones were chosen based on 5'-EST sequences, and then fully sequenced to high accuracy and analyzed by algorithms developed for this project. Currently, more than 11,000 human and 10,000 mouse genes are represented in MGC by at least one clone with a full ORF. The random selection approach is now reaching a saturation point, and a transition to protocols targeted at the missing transcripts is now required to complete the mouse and human collections. Comparison of the sequence of the MGC clones to reference genome sequences reveals that most cDNA clones are of very high sequence quality, although it is likely that some cDNAs may carry missense variants as a consequence of experimental artifact, such as PCR, cloning, or reverse transcriptase errors. Recently, a rat cDNA component was added to the project, and ongoing frog (Xenopus) and zebrafish (Danio) cDNA projects were expanded to take advantage of the high-throughput MGC pipeline.

Targeted disruption of gene function in Drosophila by RNA interference (RNA-i): a role for nautilus in embryonic somatic muscle formation

The expression of the MyoD gene homolog, nautilus (nau), in the Drosophila embryo defines a subset of mesodermal cells known as the muscle "pioneer" or "founder" cells. These cells are thought to establish the future muscle pattern in each hemisegment. Founders appear to recruit fusion-competent mesodermal cells to establish a particular muscle fiber type. In support of this concept every somatic muscle in the embryo is associated with one or more nautilus-positive cells. However, because of the lack of known (isolated) nautilus mutations, no direct test of the founder cell hypothesis has been possible. We now have utilized toxin ablation and genetic interference by double-stranded RNA (RNA interference or RNA-i) to determine both the role of the nautilus-expressing cells and the nautilus gene, respectively, in embryonic muscle formation. In the absence of nautilus-expressing cells muscle formation is severely disrupted or absent. A similar phenotype is observed with the elimination of the nautilus gene product by genetic interference upon injection of nautilus double-stranded RNA. These results define a crucial role for nautilus in embryonic muscle formation. The application of RNA interference to a variety of known Drosophila mutations as controls gave phenotypes essentially indistinguishable from the original mutation. RNA-i provides a powerful approach for the targeted disruption of a given genetic function in Drosophila.