# Project 003 - VICI

> **NIH NIH P01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2022 · $331,765

## Abstract

PROJECT 3. Viral, Immunologic and Cellular data Integration (VICI) Research Project - ABSTRACT
For 40 years, research has advanced HIV medicine to the point where persons with HIV (PWH) can live normal
and healthy lives if they have access to antiretroviral therapy (ART). Nevertheless, HIV cannot be readily cured.
Curing HIV requires further advances in approaches to investigating biological systems at multiple scales, from
interactions among genes within a cell to migration of HIV between tissues. Innovative methods are needed to
characterize HIV dynamics more fully in settings where ART is and is not stopped.
These methods are urgently needed to address the challenges that arise in proof-of-concept studies with a small
number of participants. The VICI Research Project (RP) proposes development and validation of methods for
analyzing large and complex datasets generated by the other RPs (VENI and VIDI) from 20 well-characterize
participants enrolled in the innovative Last Gift cohort. As reproducible scientific results depend as much on
development of novel analytical methods to address the challenges posed by these datasets as on their
generation, we propose to devote considerable resources and talent to the proposed VICI RP.
Throughout this VICI RP, we describe development, statistical validation, and application of models that integrate
high-dimensional, single-cell and single-genome data with clinical and other low-dimensional covariates.
Proposed methods use a ‘systems’ approach that incorporates connections among complex and distinct entities
(e.g., gene expression, integration site, epigenetic marks, tissue types) or elucidates relationships among
predictors to integrate the totality of the data.
Aims 1 and 2 focus on novel statistical methods to (1) combine novel network methods with the discrete trait
analyses (described in the VENI RP) to infer viral migration networks and its predictors, and (2) identify cell
phenotypes based on classes of gene regulatory networks identified through a novel form of recursive
partitioning. These methods will be directly applied to analyze HIV activation and repopulation of tissues.
Aim 3 uses mediation analysis⸺including novel tests for heterogeneity in mediation effects⸺to assess
mechanisms that drive HIV persistence in the body.
These complementary aims share the same overarching goal of providing a system-based framework that
facilitates analysis of large, complex, and high dimensional datasets. To illustrate the study framework and guide
reviewers, we describe the application of the proposed innovative methods on the study-defined reservoir states
of HIV leaving, coming, and staying HOME on and off ART.

## Key facts

- **NIH application ID:** 10459876
- **Project number:** 1P01AI169609-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** VICTOR GERARD DEGRUTTOLA
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $331,765
- **Award type:** 1
- **Project period:** 2022-04-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10459876

## Citation

> US National Institutes of Health, RePORTER application 10459876, Project 003 - VICI (1P01AI169609-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10459876. Licensed CC0.

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