The Emergency Medicine Specimen Bank: An Innovative Approach To Biobanking In Acute Care

Host methylation predicts SARS-CoV-2 infection and clinical outcome

BACKGROUND

Since the onset of the SARS-CoV-2 pandemic, most clinical testing has focused on RT-PCR1. Host epigenome manipulation post coronavirus infection2-4 suggests that DNA methylation signatures may differentiate patients with SARS-CoV-2 infection from uninfected individuals, and help predict COVID-19 disease severity, even at initial presentation.

METHODS

We customized Illumina's Infinium MethylationEPIC array to enhance immune response detection and profiled peripheral blood samples from 164 COVID-19 patients with longitudinal measurements of disease severity and 296 patient controls.

RESULTS

Epigenome-wide association analysis revealed 13,033 genome-wide significant methylation sites for case-vs-control status. Genes and pathways involved in interferon signaling and viral response were significantly enriched among differentially methylated sites. We observe highly significant associations at genes previously reported in genetic association studies (e.g. IRF7, OAS1). Using machine learning techniques, models built using sparse regression yielded highly predictive findings: cross-validated best fit AUC was 93.6% for case-vs-control status, and 79.1%, 80.8%, and 84.4% for hospitalization, ICU admission, and progression to death, respectively.

CONCLUSIONS

In summary, the strong COVID-19-specific epigenetic signature in peripheral blood driven by key immune-related pathways related to infection status, disease severity, and clinical deterioration provides insights useful for diagnosis and prognosis of patients with viral infections.

The urgency of utilizing COVID-19 biospecimens for research in the heart of the global pandemic

The outbreak of the novel coronavirus disease 2019 (COVID-19) and consequent social distancing practices have disrupted essential clinical research functions worldwide. Ironically, this coincides with an immediate need for research to comprehend the biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the pathology of COVID-19. As the global crisis has already led to over 15,000 deaths out of 175,000 confirmed cases in New York City and Nassau County, NY alone, it is increasingly urgent to collect patient biospecimens linked to active clinical follow up. However, building a COVID-19 biorepository amidst the active pandemic is a complex and delicate task. To help facilitate rapid, robust, and regulated research on this novel virus, we report on the successful model implemented by New York University Langone Health (NYULH) within days of outbreak in the most challenging hot spot of infection globally. Using an amended institutional biobanking protocol, these efforts led to accrual of 11,120 patients presenting for SARS-CoV-2 testing, 4267 (38.4%) of whom tested positive for COVID-19. The recently reported genomic characterization of SARS-CoV-2 in the New York City Region, which is a crucial development in tracing sources of infection and asymptomatic spread of the novel virus, is the first outcome of this effort. While this growing resource actively supports studies of the New York outbreak in real time, a worldwide effort is necessary to build a collective arsenal of research tools to deal with the global crisis now, and to exploit the virus's biology for translational innovation that outlasts humanity's current dilemma.

Modeling Clinical Processes to Consent Research Donors of Remnant Biospecimens in an Outpatient Cardiology Clinic

Introduction: Informed consent for research biospecimen donations is traditionally obtained through a face-to-face interaction with research staff and by signing an Institutional Review Board (IRB)-approved printed form. Electronic signatures (eSign) are routinely used in the electronic medical record (EMR) for the consenting of clinical services after patients review printed documentation. Our goal was to develop an electronic self-consenting workflow that mimicked clinical services. Specifically, we tested a research consent process for the biobanking of remnant clinical samples that relies solely on clinical resources in a busy outpatient practice. Materials and Methods: The Biorepositories Core Resource (BCR) unit initiated a new enterprise-wide biobanking infrastructure for consenting patients, termed Biospecimen Use for Research-Related Investigations and Translational Objectives (BURRITO). BURRITO is modeled after an established clinical process called Terms and Conditions of Service (TACOS). The TACOS requires patients to annually review printed documentation and self-consent electronically for clinical services. BURRITO also requires patients to review printed documentation and self-consent with eSign to opt-in for remnant biospecimen banking, but patients must complete this process only once. We captured eSign for consents directly into the EMR without research staff. Results: Patients reviewed the IRB-approved documents and self-consented during their cardiology clinic visit. At checkout, their participation preferences were electronically documented by clinic staff. During a 6-month period, 123 patients agreed to donate. After a review of process, a second 3-month period identified 202 patients agreeing to donate. BURRITO did not require face-to-face interactions with research staff, used a "no-paper" eSign for consent, and created discrete fields in the clinical EMR of the patient's preference. Conclusions: BURRITO electronically documents informed consent using an EMR functionality and the least amount of clinical and research resources. Our results show promise for developing institutionally adopted processes, which could leverage existing clinical workflows for universal research consenting and scalability.