Transfer transcriptomic signatures for infectious diseases

The modulation of the transcriptome is among the earliest responses to infection. However, defining the transcriptomic signatures of disease is challenging because logistic, technical, and cost factors limit the size and representativeness of samples in clinical studies. These limitations lead to a poor performance of signatures when applied to new datasets. Although the study focuses on infection, the central hypothesis of the work is the generalization of sets of signatures across diseases. We use a machine learning approach to identify common elements in datasets and then test empirically whether they are informative about a second dataset from a disease or process distinct from the original dataset. We identify sets of genes, which we name transfer signatures, that are predictive across diverse datasets and/or species (e.g., rhesus to humans). We demonstrate the usefulness of transfer signatures in two use cases: the progression of latent to active tuberculosis and the severity of COVID-19 and influenza A H1N1 infection. This indicates that transfer signatures can be deployed in settings that lack disease-specific biomarkers. The broad significance of our work lies in the concept that a small set of archetypal human immunophenotypes, captured by transfer signatures, can explain a larger set of responses to diverse diseases

Estimating the Respective Contributions of Human and Viral Genetic Variation to HIV Control

We evaluated the fraction of variation in HIV-1 set point viral load attributable to viral or human genetic factors by using joint host/pathogen genetic data from 541 HIV infected individuals. We show that viral genetic diversity explains 29% of the variation in viral load while host factors explain 8.4%. Using a joint model including both host and viral effects, we estimate a total of 30% heritability, indicating that most of the host effects are reflected in viral sequence variation

Genome-to-genome analysis highlights the effect of the human innate and adaptive immune systems on the hepatitis C virus

Outcomes of hepatitis C virus (HCV) infection and treatment depend on viral and host genetic factors. Here we use human genome-wide genotyping arrays and new whole-genome HCV viral sequencing technologies to perform a systematic genome-to-genome study of 542 individuals who were chronically infected with HCV, predominantly genotype 3. We show that both alleles of genes encoding human leukocyte antigen molecules and genes encoding components of the interferon lambda innate immune system drive viral polymorphism. Additionally, we show that IFNL4 genotypes determine HCV viral load through a mechanism dependent on a specific amino acid residue in the HCV NS5A protein. These findings highlight the interplay between the innate immune system and the viral genome in HCV control

Role of APOBEC3F Gene Variation in HIV-1 Disease Progression and Pneumocystis Pneumonia

Human APOBEC3 cytidine deaminases are intrinsic resistance factors to HIV-1. However, HIV-1 encodes a viral infectivity factor (Vif) that degrades APOBEC3 proteins. In vitro APO-BEC3F (A3F) anti-HIV-1 activity is weaker than A3G but is partially resistant to Vif degradation unlike A3G. It is unknown whether A3F protein affects HIV-1 disease in vivo. To assess the effect of A3F gene on host susceptibility to HIV-acquisition and disease progression, we performed a genetic association study in six well-characterized HIV-1 natural cohorts. A common six-Single Nucleotide Polymorphism (SNP) haplotype of A3F tagged by a codon-changing variant (p. I231V, with allele (V) frequency of 48% in European Americans) was associated with significantly lower set-point viral load and slower rate of progression to AIDS (Relative Hazards (RH) = 0.71, 95% CI: 0.56, 0.91) and delayed development of pneumocystis pneumonia (PCP) (RH = 0.53, 95% CI: 0.37-0.76). A validation study in the International Collaboration for the Genomics of HIV (ICGH) showed a consistent association with lower set-point viral load. An in vitro assay revealed that the A3F I231V variant may influence Vif mediated A3F degradation. Our results provide genetic epidemiological evidence that A3F modulates HIV-1/AIDS disease progression

The interplay between host genetic variation, viral replication and microbial translocation in untreated HIV-infected individuals.

Systemic immune activation, a major determinant of HIV disease progression, is the result of a complex interplay between viral replication, dysregulation of the immune system, and microbial translocation due to gut mucosal damage. While human genetic variants influencing HIV viral load have been identified, it is unknown to what extent the host genetic background contributes to inter-individual differences in other determinants of HIV pathogenesis like gut damage and microbial translocation. Using samples and data from 717 untreated participants in the Swiss HIV Cohort Study and a genome-wide association study design, we searched for human genetic determinants of plasma levels of intestinal fatty-acid binding protein (I-FABP/FABP2), a marker of gut damage, and of soluble sCD14 (sCD14), a marker of LPS bioactivity and microbial translocation. We also assessed the correlations between HIV viral load, sCD14 and I-FABP. While we found no genome-wide significant determinant of the tested plasma markers, we observed strong associations between sCD14 and both HIV viral load and I-FABP, shedding new light on the relationships between processes that drive progression of untreated HIV infection

Broad betacoronavirus neutralization by a stem helix–specific human antibody

The spillovers of betacoronaviruses in humans and the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlight the need for broad coronavirus countermeasures. We describe five monoclonal antibodies (mAbs) cross-reacting with the stem helix of multiple betacoronavirus spike glycoproteins isolated from COVID-19 convalescent individuals. Using structural and functional studies, we show that the mAb with the greatest breadth (S2P6) neutralizes pseudotyped viruses from three different subgenera through the inhibition of membrane fusion, and we delineate the molecular basis for its cross-reactivity. S2P6 reduces viral burden in hamsters challenged with SARS-CoV-2 through viral neutralization and Fc-mediated effector functions. Stem helix antibodies are rare, oftentimes of narrow specificity, and can acquire neutralization breadth through somatic mutations. These data provide a framework for structure-guided design of pan-betacoronavirus vaccines eliciting broad protection

Maturation of SARS-CoV-2 Spike-specific memory B cells drives resilience to viral escape

SUMMARYMemory B cells (MBCs) generate rapid antibody responses upon secondary encounter with a pathogen. Here, we investigated the kinetics, avidity and cross-reactivity of serum antibodies and MBCs in 155 SARS-CoV-2 infected and vaccinated individuals over a 16-month timeframe. SARS-CoV-2-specific MBCs and serum antibodies reached steady-state titers with comparable kinetics in infected and vaccinated individuals. Whereas MBCs of infected individuals targeted both pre- and postfusion Spike (S), most vaccine-elicited MBCs were specific for prefusion S, consistent with the use of prefusion-stabilized S in mRNA vaccines. Furthermore, a large fraction of MBCs recognizing postfusion S cross-reacted with human betacoronaviruses. The avidity of MBC-derived and serum antibodies increased over time resulting in enhanced resilience to viral escape by SARS-CoV-2 variants, including Omicron BA.1 and BA.2 sub-lineages, albeit only partially for BA.4 and BA.5 sublineages. Overall, the maturation of high-affinity and broadly-reactive MBCs provides the basis for effective recall responses to future SARS-CoV-2 variants

A framework for future national pediatric pandemic respiratory disease severity triage: The HHS pediatric COVID-19 data challenge

Abstract Introduction: With persistent incidence, incomplete vaccination rates, confounding respiratory illnesses, and few therapeutic interventions available, COVID-19 continues to be a burden on the pediatric population. During a surge, it is difficult for hospitals to direct limited healthcare resources effectively. While the overwhelming majority of pediatric infections are mild, there have been life-threatening exceptions that illuminated the need to proactively identify pediatric patients at risk of severe COVID-19 and other respiratory infectious diseases. However, a nationwide capability for developing validated computational tools to identify pediatric patients at risk using real-world data does not exist. Methods: HHS ASPR BARDA sought, through the power of competition in a challenge, to create computational models to address two clinically important questions using the National COVID Cohort Collaborative: (1) Of pediatric patients who test positive for COVID-19 in an outpatient setting, who are at risk for hospitalization? (2) Of pediatric patients who test positive for COVID-19 and are hospitalized, who are at risk for needing mechanical ventilation or cardiovascular interventions? Results: This challenge was the first, multi-agency, coordinated computational challenge carried out by the federal government as a response to a public health emergency. Fifty-five computational models were evaluated across both tasks and two winners and three honorable mentions were selected. Conclusion: This challenge serves as a framework for how the government, research communities, and large data repositories can be brought together to source solutions when resources are strapped during a pandemic