Immune profiling in Puerto Rican injection drug users with and without HIV-1 infection

Abstract

Antiretroviral therapy has been effective in suppressing HIV viral load and enabling people living with HIV to experience longer, more conventional lives. However, as people living with HIV are living longer, they are developing aging-related diseases prematurely and are more susceptible to comorbidities that have been linked to chronic inflammation. Coincident with HIV infection and aging, drug abuse has also been independently associated with gut dysbiosis, microbial translocation, and inflammation. Here, we hypothesized that injection drug use would exacerbate HIV-induced immune activation and inflammation, thereby intensifying immune dysfunction. We recruited 50 individuals not using injection drugs (36/50 HIV+) and 47 people who inject drugs (PWID, 12/47 HIV+). All but 3 of the HIV+ subjects were on antiretroviral therapy. Plasma immune profiles were characterized by immunoproteomics, and cellular immunophenotypes were assessed using mass cytometry. The immune profiles of HIV+/PWID-, HIV-/PWID+, and HIV+/PWID+ were each significantly different from controls; however, few differences between these groups were detected, and only 3 inflammatory mediators and 2 immune cell populations demonstrated a combinatorial effect of injection drug use and HIV infection. In conclusion, a comprehensive analysis of inflammatory mediators and cell immunophenotypes revealed remarkably similar patterns of immune dysfunction in HIV-infected individuals and in people who inject drugs with and without HIV-1 infection.

Keywords: Olink; PLWH; PWID; inflammation; mass cytometry; soluble mediators; speedball.

Fig. 1.

Graphical representation of study design and methodology. Whole-blood samples were collected and partitioned into plasma while reserving some whole blood. The plasma was subjected to the Olink proximity extension assay with the Olink Target 96 inflammation panel. The reserved whole blood was heparin blocked and isotope labeled before stabilization, fixation, washing, and quantification on the mass cytometer at OMRF. Created with BioRender.com. Abbreviations: RBCs, red blood cells; WBC, white blood cells.

Fig. 2.

Exploratory PCA of inflammatory mediators and cellular immunophenotypes. A) Bridge normalized NPX values from Olink Target 96 Inflammation Panel, B) percentage of lineage parent population for each of 37 immune cell types, or C) the combined data sets were the inputs for PCA. In each case, the input data were standardized and centered. The individuals are colored by group (HIV: HIV⁺/PWID⁻, IDU: HIV⁻/PWID⁺, DP: HIV⁺/PWID⁺), and the control group (CON: HIV⁻/PWID⁻) was circled.

Fig. 3.

Pairwise comparison of the inflammatory mediators in HIV⁺/PWID⁻, HIV⁻/PWID⁺, and HIV⁺/PWID⁺. Bridge normalized NPX values from Olink Target 96 Inflammation Panel were used to compare levels of 74 inflammatory mediators between HIV⁻/PWID⁻ (controls; CON), HIV⁺/PWID⁻ (HIV), HIV⁻/PWID⁺ (IDU), and HIV⁺/PWID⁺ (DP) A) post-adjusting for age, homeless in the past year or now, male identity, married, employed, and some college experience (ANCOVA). B) The adjusted data were also subjected to 2-way ANOVA to identify HIV infection, injection drug use, and interaction (synergy) effects. C) GO enrichment analysis was performed for the inflammatory mediators with significant interaction effects in B, and the most specific subclass of the hierarchical ontology cluster is shown. The estimate difference (adjusted mean difference) (A), coefficient estimates (effect size) (B), and −log(false discovery rate) (C) are shown when significant (P < 0.05).

Fig. 4.

Pairwise comparison of the cellular immunophenotypes in HIV⁺/PWID⁻, HIV⁻/PWID⁺, and HIV⁺/PWID⁺. Percentage of lineage parent population was calculated for each of 37 immune cell types and compared between HIV⁻/PWID⁻ (controls; CON), HIV⁺/PWID⁻ (HIV), HIV⁻/PWID⁺ (IDU), and HIV⁺/PWID⁺ (DP) A) post-adjusting for age, homeless in the past year or now, male identity, married, employed, and some college experience (ANCOVA). B) The adjusted data were also subjected to 2-way ANOVA to identify HIV infection, injection drug use, and interaction effects. The estimate difference (adjusted mean difference) (A) and coefficient estimates (effect size) (B) are shown when significant (P < 0.05). EM, effector memory; TE, terminal effector.

Fig. 5.

The effects of HIV infection and injection drug use on the peripheral immune repertoire. The upregulated cytokines are shown in the cloud Venn diagram for HIV infection, injection drug use, and those that are in common. The dysregulated immune cell populations are also displayed with arrows indicating an increasing effect (“up” arrow) or decreasing effect (“down” arrow). The upregulated cytokines and dysregulated cell populations with significant interaction effects (synergy) between HIV infection and injection drug use are shown. The smaller text size indicates a less significant effect, while the larger text size indicates a more significant effect. Created with BioRender.com.