Chronic exposure to drugs of abuse is associated with an increased risk for infection or HIV disease progression. Genetic and environment factors play an important role in influencing host susceptibility;not all people exposed to the virus become infected, and those who do progress to AIDS at different rates. Common genetic variants explain only a small fraction of the heritable risk for HIV/AIDS, and therefore a significant proportion of risk may be due to the summation of the effects of many low frequency variants of assorted different genes that have relatively large effects on risk. To determine specific causal variants, the regulatory networks they impact, the relevant functional alterations they introduce, and the influence of substance use, we propose a systems biology approach to identify the many innate immune response factors that are relevant to the virus life cycle and immunity. We hypothesize that multiple as-yet-unidentified rare variants of regulators or effectors of innate immunity or inflammation with strong phenotypic effects are likely to contribute significantly to host susceptibility. To address this hypothesis, we have brought together a multidisciplinary team with complementary areas of expertise for a systems biology approach to identify genes with distinct and overlapping functions that affect HIV/AIDS susceptibility and drug abuse. Network analysis will be performed on data from large-scale measurements to decipher regulatory networks underpinning cell-mediated resistance and responses to HIV infection. Multivariate correlations that analyze gene modules underlying the response to these perturbations in terms of their additive or cooperative contributions towards the phenotype will provide insight into their synergistic interactions and a tractable, validated dataset for identifying candidate genes with high-confidence for further study. Targeted capture and massively parallel sequencing of the coding regions and consensus splice sites of candidate genes is a cost-effective strategy for the identification of base substitutions, small insertions or deletions, and copy number changes within exome-containing intervals of interest and their splice variants. Extreme quantitative trait sampling according to phenotype based on both drug exposure and risk profiles maximizes power for variant discovery for the number of people sequenced. Genotyping variants across individuals from the MACS and the WIHS, all of who are characterized for their HIV disease status, genetic ancestries, and histories of substance abuse, gives a discovery sample size that could identify the frequency of specific variants that predispose to disease risk. Functional validation of the predicted function-altering changes in innate immune response factors will elucidate the mechanisms by which they affect the life cycle of HIV and better define the complex networks and their properties that govern responses to these perturbations. The results of this hypothesis-driven, systems-level analysis of host susceptibility and drug abuse should increase our understanding of the complex properties that underlie the cellular response to perturbation and provide insight into the genetics and pathogenesis of HIV/AIDS.

Public Health Relevance

Systems biology approaches towards deciphering the regulatory networks underlying the cellular response to HIV infection in people who abuse drugs should identify genetic variants that have a substantial probability of influencing an individual's vulnerability to HIV/AIDS. A fundamental understanding of the molecular mechanisms through which they do so will lead to informative biomarkers, new insights into the predictive value of clinical trials involving gender and racial groups, and new opportunities for the development of small molecule-based therapies.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
3R01DA033773-02S1
Application #
8794566
Study Section
Special Emphasis Panel (ZAA1-DD (40))
Program Officer
Rutter, Joni
Project Start
2012-04-15
Project End
2017-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
2
Fiscal Year
2014
Total Cost
$191,100
Indirect Cost
$93,100
Name
Northwestern University Chicago
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
005436803
City
Chicago
State
IL
Country
United States
Zip Code
60611
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