Mining for humoral correlates of HIV control and latent reservoir size

Abstract

While antiretroviral therapy (ART) has effectively revolutionized HIV care, the virus is never fully eliminated. Instead, immune dysfunction, driven by persistent non-specific immune activation, ensues and progressively leads to premature immunologic aging. Current biomarkers monitoring immunologic changes encompass generic inflammatory biomarkers, that may also change with other infections or disease states, precluding the antigen-specific monitoring of HIV-infection associated changes in disease. Given our growing appreciation of the significant changes in qualitative and quantitative properties of disease-specific antibodies in HIV infection, we used a systems approach to explore humoral profiles associated with HIV control. We found that HIV-specific antibody profiles diverge by spontaneous control of HIV, treatment status, viral load and reservoir size. Specifically, HIV-specific antibody profiles representative of changes in viral load were largely quantitative, reflected by differential HIV-specific antibody levels and Fc-receptor binding. Conversely, HIV-specific antibody features that tracked with reservoir size exhibited a combination of quantitative and qualitative changes marked by more distinct subclass selection profiles and unique HIVspecific Fc-glycans. Our analyses suggest that HIV-specific antibody Fc-profiles provide antigen-specific resolution on both cell free and cell-associated viral loads, pointing to potentially novel biomarkers to monitor reservoir activity.

Delayed fractional dosing with RTS,S/AS01 improves humoral immunity to malaria via a balance of polyfunctional NANP6- and Pf16-specific antibodies

“…All assays correlate significantly (p < 0.001) across donors, confirming they are reproducible and not biased by differences in FcR alleles or expression patterns. The observed significant correlations across technical replicates are in agreement with similar assays used by us in a range of other contexts, 10,29,30,51 as well as in several technical benchmarks. 47,50,52 Antibody isotype and subclass analysis The isotypes and subclasses of malaria antigen-specific antibodies were quantified using a previously described method.…”

“…To further explore the specific differences in humoral immune profiles between the RRR and RRr regimens, we used a least absolute shrinkage and selection operator (LASSO)-based modeling approach, 10,29,30 which helps to prevent overfitting in high-dimensional datasets (i.e., a dataset with more antibody measurements than subjects). 31 We identified just four antibody features that could accurately discriminate between the vaccine groups (Figures 1C-1E).…”

Essential Regression - a generalizable framework for inferring causal latent factors from multi-omic human datasets

“…The predictive performance of all methods was evaluated in a stringent leave-one-out cross-validation (LOOCV) framework (Methods). We have previously demonstrated that on such multi-omic datasets, cross-validation is a gold standard to evaluate model performance with data held out 5, 6, 8 . In a LOOCV framework, we found that PFR had no predictive power (AUC < 0.5), while LASSO and PLS had weak predictive power in predicting age as a categorical variable (Fig.…”

“…Existing analytical approaches have primarily focused on individual "omic" datasets with relatively few attempts at integration of multi-omic datasets. In either case, we [5][6][7][8][9] and others [10][11][12] have primarily emphasized on uncovering predictive biomarkers (Fig. 1a).…”

Are HIV-1-Specific Antibody Levels Potentially Useful Laboratory Markers to Estimate HIV Reservoir Size? A Review

“…whether humoral biomarkers of reservoir size can estimate the reservoir size in ART-treated subjects, and they observed that IgG-gp41 (r=0.597, p=0.011) and IgG3-gp120 (r=0.135, p=0.029) HIV-specific antibodies correlate with the size of the HIV reservoir in these subjects (99).…”