# Analysis Resource Core

> **NIH NIH U54** · JOHNS HOPKINS UNIVERSITY · 2020 · $527,294

## Abstract

JH-EPICS Analysis Resource Core Summary
The JH-EPICS Analysis Resource Core (ARC) will provide statistical modeling and analysis support to
investigators in this U54 proposal. In addition, the ARC will provide guidance in the framing and testing of
hypotheses about the intersectionality of gender, age, racial, and ethnic differences in immune mechanisms in
COVID-19. In both roles, the ARC will assure that the U54 research is valid, transparent, and reproducible.
Current evidence shows that the COVID-19 pandemic has differential effects on men and women, including in
relation to disease severity and mortality and negative social and economic impacts. It is vital that we explore
how sex and gender intersect with other biological and social stratifiers if we are to have effective and
appropriate therapeutic treatment and interventions. In its statistical analysis role, the ARC will develop and
implement statistical models and methods for comparing longitudinal trajectories among subgroups of the
Johns Hopkins COVID-19 registry using multiple measures of immune function. We will support the three
Research Projects to devise tests of specific hypotheses about baseline and time-varying factors that affect
disease progression. In its intersectionality function, the Core will provide expert guidance to both Projects to
test hypotheses about the intersectionality of gender (social construct), sex (biological construct), race,
ethnicity, and age differences with the effects of SARS-CoV-2 on the human immune system. In collaboration
with the U54 investigators, the ARC will: 1. Acquire, manage, and curate data from laboratory experiments
and from the Johns Hopkins CROWN (COVID-19 Precision Medicine Analytics Platform) Registry of all
COVID-19 patients who receive health services within the Johns Hopkins network of 5 hospitals. 2. Frame the
investigators’ scientific questions in statistical terms, then design laboratory and/or clinical studies that
produce the strongest possible evidence to answer the questions posed. 3. Design and implement statistical
analyses and collaborate on interpretation of results so as to produce valid, transparent, and reproducible
scientific findings. Validity will be assured by distinguishing hypothesis generating from hypothesis testing
analyses. Each hypothesis testing analysis will have a pre-specified statistical analysis plan in advance of
working with the data. 4. Analyze the role of sex and gender and the intersection of sex and gender with
other biological and social stratifiers, such as age, race, and ethnicity, on COVID-19 immunologic
responses and clinical outcomes. These analyses will be integrated into Research Projects 1-3.

## Key facts

- **NIH application ID:** 10221907
- **Project number:** 1U54CA260492-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** SCOTT L. ZEGER
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $527,294
- **Award type:** 1
- **Project period:** 2020-09-30 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10221907

## Citation

> US National Institutes of Health, RePORTER application 10221907, Analysis Resource Core (1U54CA260492-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10221907. Licensed CC0.

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