# MWCCS NIAID Data Ecosystem Supplement

> **NIH NIH U01** · JOHNS HOPKINS UNIVERSITY · 2024 · $818,355

## Abstract

Project Summary
The MACS WIHS Combined Cohort Study (MWCCS) is the largest ongoing longitudinal cohort study
of adults living with and without HIV. To date, the MWCCS has followed more than 13,828 unique
participants and collected data at 285,840 person-visits over a 40-year period. This study has
generated a large body of high-dimensional data including clinical, behavioral, social, genomic, and
metabolomic. These data have led to more than 3000 peer-reviewed publications and are in high
demand by investigators. Despite extensive documentation of the data, given their complexity, it
can be challenging for investigators to understand what data is available for use. Therefore, efforts
to make the MWCCS data more discoverable to investigators would be valuable and are aligned
with the mission of the MWCCS Data Analysis and Coordinating Center (DACC). The goal of this
proposal is to engage with the team at GO FAIR US to make the MWCCS data more discoverable to
investigators and more interoperable with the NIAID data environment and other repositories
across multiple platforms. We aim to 1) provide standardized metadata to share with the NIAID
Data Ecosystem Discovery Portal, 2) develop aggregate-level count tables to populate a basic data
dashboard, and 3) plan technologic feasibility for future data visiting of study data.

## Key facts

- **NIH application ID:** 11127129
- **Project number:** 3U01HL146193-06S1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Gypsyamber D'Souza
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $818,355
- **Award type:** 3
- **Project period:** 2019-04-09 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11127129

## Citation

> US National Institutes of Health, RePORTER application 11127129, MWCCS NIAID Data Ecosystem Supplement (3U01HL146193-06S1). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/11127129. Licensed CC0.

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