Translocated microbiome composition determines immunological outcome in treated HIV infection.

The impact of the microbiome on HIV disease is widely acknowledged although the mechanisms downstream of fluctuations in microbial composition remain speculative. We detected rapid, dynamic changes in translocated microbial constituents during two years after cART initiation. An unbiased systems biology approach revealed two distinct pathways driven by changes in the abundance ratio of Serratia to other bacterial genera. Increased CD4 T cell numbers over the first year were associated with high Serratia abundance, pro-inflammatory innate cytokines, and metabolites that drive Th17 gene expression signatures and restoration of mucosal integrity. Subsequently, decreased Serratia abundance and downregulation of innate cytokines allowed re-establishment of systemic T cell homeostasis promoting restoration of Th1 and Th2 gene expression signatures. Analyses of three other geographically distinct cohorts of treated HIV infection established a more generalized principle that changes in diversity and composition of translocated microbial species influence systemic inflammation and consequently CD4 T cell recovery.

Altered differentiation is central to HIV-specific CD4+ T cell dysfunction in progressive disease.

Dysfunction of virus-specific CD4+ T cells in chronic human infections is poorly understood. We performed genome-wide transcriptional analyses and functional assays of CD4+ T cells specific for human immunodeficiency virus (HIV) from HIV-infected people before and after initiation of antiretroviral therapy (ART). A follicular helper T cell (TFH cell)-like profile characterized HIV-specific CD4+ T cells in viremic infection. HIV-specific CD4+ T cells from people spontaneously controlling the virus (elite controllers) robustly expressed genes associated with the TH1, TH17 and TH22 subsets of helper T cells. Viral suppression by ART resulted in a distinct transcriptional landscape, with a reduction in the expression of genes associated with TFH cells, but persistently low expression of genes associated with TH1, TH17 and TH22 cells compared to the elite controller profile. Thus, altered differentiation is central to the impairment of HIV-specific CD4+ T cells and involves both gain of function and loss of function.

The dynamic changes and sex differences of 147 immune-related proteins during acute COVID-19 in 580 individuals.

INTRODUCTION: Severe COVID-19 leads to important changes in circulating immune-related proteins. To date it has been difficult to understand their temporal relationship and identify cytokines that are drivers of severe COVID-19 outcomes and underlie differences in outcomes between sexes. Here, we measured 147 immune-related proteins during acute COVID-19 to investigate these questions. METHODS: We measured circulating protein abundances using the SOMAscan nucleic acid aptamer panel in two large independent hospital-based COVID-19 cohorts in Canada and the United States. We fit generalized additive models with cubic splines from the start of symptom onset to identify protein levels over the first 14 days of infection which were different between severe cases and controls, adjusting for age and sex. Severe cases were defined as individuals with COVID-19 requiring invasive or non-invasive mechanical respiratory support. RESULTS: 580 individuals were included in the analysis. Mean subject age was 64.3 (sd 18.1), and 47% were male. Of the 147 proteins, 69 showed a significant difference between cases and controls (p < 3.4 × 10-4). Three clusters were formed by 108 highly correlated proteins that replicated in both cohorts, making it difficult to determine which proteins have a true causal effect on severe COVID-19. Six proteins showed sex differences in levels over time, of which 3 were also associated with severe COVID-19: CCL26, IL1RL2, and IL3RA, providing insights to better understand the marked differences in outcomes by sex. CONCLUSIONS: Severe COVID-19 is associated with large changes in 69 immune-related proteins. Further, five proteins were associated with sex differences in outcomes. These results provide direct insights into immune-related proteins that are strongly influenced by severe COVID-19 infection.

Using virtual patient cohorts to uncover immune response differences in cancer and immunosuppressed COVID-19 patients.

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in millions of deaths globally. Adults with immunosuppression (e.g., solid organ transplant recipients) and those undergoing active cancer treatments experience worse infections and more severe COVID-19. It is difficult to conduct clinical studies in these populations, resulting in a restricted amount of data that can be used to relate mechanisms of immune dysfunction to COVID-19 outcomes in these vulnerable groups. To study immune dynamics after infection with SARS-CoV-2 and to investigate drivers of COVID-19 severity in individuals with cancer and immunosuppression, we adapted our mathematical model of the immune response during COVID-19 and generated virtual patient cohorts of cancer and immunosuppressed patients. The cohorts of plausible patients recapitulated available longitudinal clinical data collected from patients in Montréal, Canada area hospitals. Our model predicted that both cancer and immunosuppressed virtual patients with severe COVID-19 had decreased CD8+ T cells, elevated interleukin-6 concentrations, and delayed type I interferon peaks compared to those with mild COVID-19 outcomes. Additionally, our results suggest that cancer patients experience higher viral loads (however, with no direct relation with severity), likely because of decreased initial neutrophil counts (i.e., neutropenia), a frequent toxic side effect of anti-cancer therapy. Furthermore, severe cancer and immunosuppressed virtual patients suffered a high degree of tissue damage associated with elevated neutrophils. Lastly, parameter values associated with monocyte recruitment by infected cells were found to be elevated in severe cancer and immunosuppressed patients with respect to the COVID-19 reference group. Together, our study highlights that dysfunction in type I interferon and CD8+ T cells are key drivers of immune dysregulation in COVID-19, particularly in cancer patients and immunosuppressed individuals.

Intra-Host Evolution Analyses in an Immunosuppressed Patient Supports SARS-CoV-2 Viral Reservoir Hypothesis.

Throughout the SARS-CoV-2 pandemic, several variants of concern (VOCs) have been identified, many of which share recurrent mutations in the spike glycoprotein's receptor-binding domain (RBD). This region coincides with known epitopes and can therefore have an impact on immune escape. Protracted infections in immunosuppressed patients have been hypothesized to lead to an enrichment of such mutations and therefore drive evolution towards VOCs. Here, we present the case of an immunosuppressed patient that developed distinct populations with immune escape mutations throughout the course of their infection. Notably, by investigating the co-occurrence of substitutions on individual sequencing reads in the RBD, we found quasispecies harboring mutations that confer resistance to known monoclonal antibodies (mAbs) such as S:E484K and S:E484A. These mutations were acquired without the patient being treated with mAbs nor convalescent sera and without them developing a detectable immune response to the virus. We also provide additional evidence for a viral reservoir based on intra-host phylogenetics, which led to a viral substrain that evolved elsewhere in the patient's body, colonizing their upper respiratory tract (URT). The presence of SARS-CoV-2 viral reservoirs can shed light on protracted infections interspersed with periods where the virus is undetectable, and potential explanations for long-COVID cases.

Gaining Biological Insights through Supervised Data Visualization.

Dimensionality reduction-based data visualization is pivotal in comprehending complex biological data. The most common methods, such as PHATE, t-SNE, and UMAP, are unsupervised and therefore reflect the dominant structure in the data, which may be independent of expert-provided labels. Here we introduce a supervised data visualization method called RF-PHATE, which integrates expert knowledge for further exploration of the data. RF-PHATE leverages random forests to capture intricate featurelabel relationships. Extracting information from the forest, RF-PHATE generates low-dimensional visualizations that highlight relevant data relationships while disregarding extraneous features. This approach scales to large datasets and applies to classification and regression. We illustrate RF-PHATE's prowess through three case studies. In a multiple sclerosis study using longitudinal clinical and imaging data, RF-PHATE unveils a sub-group of patients with non-benign relapsingremitting Multiple Sclerosis, demonstrating its aptitude for time-series data. In the context of Raman spectral data, RF-PHATE effectively showcases the impact of antioxidants on diesel exhaust-exposed lung cells, highlighting its proficiency in noisy environments. Furthermore, RF-PHATE aligns established geometric structures with COVID-19 patient outcomes, enriching interpretability in a hierarchical manner. RF-PHATE bridges expert insights and visualizations, promising knowledge generation. Its adaptability, scalability, and noise tolerance underscore its potential for widespread adoption.

Sustained IFN signaling is associated with delayed development of SARS-CoV-2-specific immunity.

Plasma RNAemia, delayed antibody responses and inflammation predict COVID-19 outcomes, but the mechanisms underlying these immunovirological patterns are poorly understood. We profile 782 longitudinal plasma samples from 318 hospitalized patients with COVID-19. Integrated analysis using k-means reveals four patient clusters in a discovery cohort: mechanically ventilated critically-ill cases are subdivided into good prognosis and high-fatality clusters (reproduced in a validation cohort), while non-critical survivors segregate into high and low early antibody responders. Only the high-fatality cluster is enriched for transcriptomic signatures associated with COVID-19 severity, and each cluster has distinct RBD-specific antibody elicitation kinetics. Both critical and non-critical clusters with delayed antibody responses exhibit sustained IFN signatures, which negatively correlate with contemporaneous RBD-specific IgG levels and absolute SARS-CoV-2-specific B and CD4+ T cell frequencies. These data suggest that the "Interferon paradox" previously described in murine LCMV models is operative in COVID-19, with excessive IFN signaling delaying development of adaptive virus-specific immunity.

Plasma SARS-CoV-2 RNA elimination and RAGE kinetics distinguish COVID-19 severity.

Objectives: Identifying biomarkers causing differential SARS-CoV-2 infection kinetics associated with severe COVID-19 is fundamental for effective diagnostics and therapeutic planning. Methods: In this work, we applied mathematical modelling to investigate the relationships between patient characteristics, plasma SARS-CoV-2 RNA dynamics and COVID-19 severity. Using a straightforward mathematical model of within-host viral kinetics, we estimated key model parameters from serial plasma viral RNA (vRNA) samples from 256 hospitalised COVID-19+ patients. Results: Our model predicted that clearance rates distinguish key differences in plasma vRNA kinetics and severe COVID-19. Moreover, our analyses revealed a strong correlation between plasma vRNA kinetics and plasma receptor for advanced glycation end products (RAGE) concentrations (a plasma biomarker of lung damage), collected in parallel to plasma vRNA from patients in our cohort, suggesting that RAGE can substitute for viral plasma shedding dynamics to prospectively classify seriously ill patients. Conclusion: Overall, our study identifies factors of COVID-19 severity, supports interventions to accelerate viral clearance and underlines the importance of mathematical modelling to better understand COVID-19.

Predicting severity in COVID-19 disease using sepsis blood gene expression signatures.

Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1-5 days post-hospital admission) and late (6-20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.

Circulating proteins to predict COVID-19 severity.

Predicting COVID-19 severity is difficult, and the biological pathways involved are not fully understood. To approach this problem, we measured 4701 circulating human protein abundances in two independent cohorts totaling 986 individuals. We then trained prediction models including protein abundances and clinical risk factors to predict COVID-19 severity in 417 subjects and tested these models in a separate cohort of 569 individuals. For severe COVID-19, a baseline model including age and sex provided an area under the receiver operator curve (AUC) of 65% in the test cohort. Selecting 92 proteins from the 4701 unique protein abundances improved the AUC to 88% in the training cohort, which remained relatively stable in the testing cohort at 86%, suggesting good generalizability. Proteins selected from different COVID-19 severity were enriched for cytokine and cytokine receptors, but more than half of the enriched pathways were not immune-related. Taken together, these findings suggest that circulating proteins measured at early stages of disease progression are reasonably accurate predictors of COVID-19 severity. Further research is needed to understand how to incorporate protein measurement into clinical care.

Immune checkpoint expression on HIV-specific CD4+ T cells and response to their blockade are dependent on lineage and function.

BACKGROUND: Immune checkpoint blockade (ICB) partially reverses the dysfunctional state of antigen-specific T cell in chronic infections. However, its impact on the diverse subsets of CD4+ T cells in humans is largely unknown. METHODS: We examined immune checkpoint (IC) expression and function in HIV-specific CD4+ T cells of viremic individuals (≥5000 vRNA cp/ml, n = 17) prior to ART and persons with spontaneous (n = 11) or therapy-induced (n = 16) viral suppression (<40 cp/ml). We investigated IC patterns associated with exhaustion-related transcription factors and chemokine receptors using activation-induced marker assays. We determined effector functions representative of TFH, TH1, and TH17/TH22 using RNA flow cytometric fluorescence in situ hybridization (FISH). We compared increase in cytokine expression upon ICB across functions and patient status. FINDINGS: Expression of dysfunction-related molecules, such as transcription factors and ICs PD-1, TIGIT, and CD200, followed a hierarchy associated with infection status and effector profile. In vitro responsiveness to PD-L1 blockade varied with defined functions rather than IC levels: frequencies of cells with TH1- and TH17/TH22-, but not TFH-related functions, increased. Cells co-expressing TH1 and TFH functions showed response to ICB, suggesting that the cell's state rather than function dictates responsiveness to PD-L1 blockade. Response to PD-L1 blockade was strongest in viremic participants and reduced after ART initiation. INTERPRETATION: Our data highlight a polarization-specific regulation of IC expression and differing sensitivities of antigen-specific T helper subsets to PD-1-mediated inhibition. This heterogeneity may direct and constrain ICB efficacy in restoring CD4+ T cell function in HIV infection and other diseases. FUNDING: NIH, CIHR, CFI, FRQS.

Combined single-cell transcriptional, translational, and genomic profiling reveals HIV-1 reservoir diversity.

Although understanding the diversity of HIV-1 reservoirs is key to achieving a cure, their study at the single-cell level in primary samples remains challenging. We combine flow cytometric multiplexed fluorescent in situ RNA hybridization for different viral genes with HIV-1 p24 protein detection, cell phenotyping, and downstream near-full-length single-cell vDNA sequencing. Stimulation-induced viral RNA-positive (vRNA+) cells from viremic and antiretroviral-therapy (ART)-suppressed individuals differ in their ability to produce p24. In participants on ART, latency-reversing agents (LRAs) induce a wide variety of viral gene transcription and translation patterns with LRA class-specific differences in reactivation potency. Reactivated proviruses, including in p24+ cells, are mostly defective. Although LRAs efficiently induce transcription in all memory cell subsets, we observe induction of translation mostly in effector memory cells, rather than in the long-lived central memory pool. We identify HIV-1 clones with diverse transcriptional and translational patterns between individual cells, and this finding suggests that cell-intrinsic factors influence reservoir persistence and heterogeneity.

Longitudinal analysis of humoral immunity against SARS-CoV-2 Spike in convalescent individuals up to 8 months post-symptom onset.

With the recent approval of highly effective coronavirus disease 2019 (COVID-19) vaccines, functional and lasting immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently under investigation as antibody levels in plasma were shown to decline during convalescence. Since the absence of antibodies does not equate to absence of immune memory, we evaluate the presence of SARS-CoV-2-specific memory B cells in convalescent individuals. Here, we report a longitudinal assessment of humoral immune responses on 32 donors up to 8 months post-symptom onset. Our observations indicate that anti-Spike and anti-receptor binding domain (RBD) immunoglobulin M (IgM) in plasma decay rapidly, whereas the reduction of IgG is less prominent. Neutralizing activity also declines rapidly when compared to Fc-effector functions. Concomitantly, the frequencies of RBD-specific IgM+ B cells wane significantly when compared to RBD-specific IgG+ B cells, which remain stable. Our results add to the current understanding of immune memory following SARS-CoV-2 infection, which is critical for secondary infection prevention and vaccine efficacy.

Longitudinal analysis of humoral immunity against SARS-CoV-2 Spike in convalescent individuals up to 8 months post-symptom onset.

Functional and lasting immune responses to the novel coronavirus (SARS-CoV-2) are currently under intense investigation as antibody titers in plasma have been shown to decline during convalescence. Since the absence of antibodies does not equate to absence of immune memory, we sought to determine the presence of SARS-CoV-2-specific memory B cells in COVID-19 convalescent patients. In this study, we report on the evolution of the overall humoral immune responses on 101 blood samples obtained from 32 COVID-19 convalescent patients between 16 and 233 days post-symptom onset. Our observations indicate that anti-Spike and anti-RBD IgM in plasma decay rapidly, whereas the reduction of IgG is less prominent. Neutralizing activity in convalescent plasma declines rapidly compared to Fc-effector functions. Concomitantly, the frequencies of RBD-specific IgM+ B cells wane significantly when compared to RBD-specific IgG+ B cells, which increase over time, and the number of IgG+ memory B cells which remain stable thereafter for up to 8 months after symptoms onset. With the recent approval of highly effective vaccines for COVID-19, data on the persistence of immune responses are of central importance. Even though overall circulating SARS-CoV-2 Spike-specific antibodies contract over time during convalescence, we demonstrate that RBD-specific B cells increase and persist up to 8 months post symptom onset. We also observe modest increases in RBD-specific IgG+ memory B cells and importantly, detectable IgG and sustained Fc-effector activity in plasma over the 8-month period. Our results add to the current understanding of immune memory following SARS-CoV-2 infection, which is critical for the prevention of secondary infections, vaccine efficacy and herd immunity against COVID-19.

A Neanderthal OAS1 isoform protects individuals of European ancestry against COVID-19 susceptibility and severity.

To identify circulating proteins influencing Coronavirus Disease 2019 (COVID-19) susceptibility and severity, we undertook a two-sample Mendelian randomization (MR) study, rapidly scanning hundreds of circulating proteins while reducing bias due to reverse causation and confounding. In up to 14,134 cases and 1.2 million controls, we found that an s.d. increase in OAS1 levels was associated with reduced COVID-19 death or ventilation (odds ratio (OR) = 0.54, P = 7 × 10-8), hospitalization (OR = 0.61, P = 8 × 10-8) and susceptibility (OR = 0.78, P = 8 × 10-6). Measuring OAS1 levels in 504 individuals, we found that higher plasma OAS1 levels in a non-infectious state were associated with reduced COVID-19 susceptibility and severity. Further analyses suggested that a Neanderthal isoform of OAS1 in individuals of European ancestry affords this protection. Thus, evidence from MR and a case-control study support a protective role for OAS1 in COVID-19 adverse outcomes. Available pharmacological agents that increase OAS1 levels could be prioritized for drug development.

Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality.

Despite advances in COVID-19 management, identifying patients evolving toward death remains challenging. To identify early predictors of mortality within 60 days of symptom onset (DSO), we performed immunovirological assessments on plasma from 279 individuals. On samples collected at DSO11 in a discovery cohort, high severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA), low receptor binding domain­specific immunoglobulin G and antibody-dependent cellular cytotoxicity, and elevated cytokines and tissue injury markers were strongly associated with mortality, including in patients on mechanical ventilation. A three-variable model of vRNA, with predefined adjustment by age and sex, robustly identified patients with fatal outcome (adjusted hazard ratio for log-transformed vRNA = 3.5). This model remained robust in independent validation and confirmation cohorts. Since plasma vRNA's predictive accuracy was maintained at earlier time points, its quantitation can help us understand disease heterogeneity and identify patients who may benefit from new therapies.

Persistent expansion and Th1-like skewing of HIV-specific circulating T follicular helper cells during antiretroviral therapy.

BACKGROUND: Untreated HIV infection leads to alterations in HIV-specific CD4+ T cells including increased expression of co-inhibitory receptors (IRs) and skewing toward a T follicular helper cell (Tfh) signature. However, which changes are maintained after suppression of viral replication with antiretroviral therapy (ART) is poorly known. METHODS: We analyzed blood CD4+ T cells specific to HIV and comparative viral antigens in ART-treated people using a cytokine-independent activation-induced marker assay alone or in combination with functional readouts. FINDINGS: In intra-individual comparisons, HIV-specific CD4+ T cells were characterized by a larger fraction of circulating Tfh (cTfh) cells than CMV- and HBV-specific cells and preferentially expressed multiple IRs and showed elevated production of the Tfh cytokines CXCL13 and IL-21. In addition, HIV-specific cTfh exhibited a predominant Th1-like phenotype and function when compared to cTfh of other specificities, contrasting with a reduction in Th1-functions in HIV-specific non-cTfh. Using longitudinal samples, we demonstrate that this distinct HIV-specific cTfh profile was induced during chronic untreated HIV infection, persisted on ART and correlated with the translation-competent HIV reservoir but not with the total HIV DNA reservoir. INTERPRETATION: Expansion and altered features of HIV-specific cTfh cells are maintained during ART and may be driven by persistent HIV antigen expression. FUNDING: This work was supported by the National Institutes of Health (NIH), the Canadian Institutes of Health Research (CIHR) and the FRQS AIDS and Infectious Diseases Network.

Targeting Mitochondria to Revive Dysfunctional Regulatory T Cells.

Immunometabolism is important to T cell dysfunction in chronic infections. A recent publication in The Journal of Clinical Investigation (2018;128:5083-5094) [1] shows reduced mitochondrial fitness in regulatory CD4+ T cells (Tregs) of patients with HIV and failed immune restoration on antiretroviral therapy (ART). This defect can be reversed by IL-15, revealing a new immunotherapy target for regulatory T cell restoration.