Biology subjects

Hagan, T.

Publications and source records attributed to Hagan, T..

6 recordsLinked to original sources

bioRxiv2026

From mice to humans: A multi-omic predictive framework for translational immunology

Mice are key preclinical animal models in vaccine and immunological research, yet their predictive value for human immunity remains contested. Here, we evaluated the translatability of murine models across inactivated and subunit vaccination (influenza, hepatitis B), acute infection (S. aureus, E. coli), and injury (burns and trauma), integrating transcriptomic profiles with sequence evolution, cis-regulatory architecture, and functional annotation. Functional modules were more conserved between species than individual orthologous genes. Translational accuracy depended on stimulus intensity, as infections and injuries engaged conserved signatures, while single-dose vaccination diverged. We then built multilayer models to predict human expression rank and direction of change, and to classify shared leading-edge genes. Adding evolutionary and regulatory layers improved these predictions. We provide a step-by-step R Markdown notebook to apply the models to user data. The study code and datasets are available at https://github.com/wapsyed/mousetohuman_multilayer

bioinformatics↗

bioRxiv2026

Large scale application of species distribution models to predict future vulnerability to social wasp invasions

Social wasps (family: Vespidae) are increasingly concerning invaders and have been subject to increased detections and a growing number of invasive populations in the last few decades. As established invasive populations are challenging to eradicate, preventing introductions and prioritizing early interventions are the most cost-effective management solutions to mitigate these effects. A current challenge to this approach is that species distribution data is limited for many social wasp species, hindering our ability to accurately predict novel habitats with high suitability. To address this gap, we used MAXENT to create species distribution models (SDM) for 299 species of social vespid. We identified existing invasive populations of social wasps and incorporated their current invasive ranges to improve the transferability of our models in predicting habitat suitability in new environments. Current range sizes and habitat suitability varied widely among species and genera. We identified new species of high invasive concern, particularly in the genus Vespa. We also identified previously unrecognized regions that may be at high risk of future invasion primarily in Central Africa and the Indo-Australian Archipelago. Combining current and suitable ranges, we calculated an "Invasion Risk Score" to compare the relative likelihood of each species establishing a new invasive population based upon habitat suitability. To assess invasion risk in the future, we projected habitat suitability under four Shared Socioeconomic Pathway (SSP) climate change scenarios. Under all scenarios, species faced significant changes in habitat suitability for current native ranges. Habitat suitability generally shrank and shifted towards the poles, leaving equatorial species at highest risk of habitat loss. Notably, Vespa was the only genus whose suitable habitat expanded under these climate scenarios. Our framework demonstrates how multi-species SDMs can be applied to risk management of invasive populations.

ecology↗

bioRxiv2025

HIV-1 infection of human microglia activates inflammatory pathways associated with HIV-associated neurocognitive disorders (HAND)

HIV-associated neurocognitive disorders (HAND) cause significant dysfunction among people living with HIV. Microglia are the primary immune cells of the central nervous system and are readily infected by HIV. Microglia are thought to contribute to neuroinflammation and cognitive dysfunction in neurodegenerative diseases such as Alzheimers Disease and are likely to play an important role in the pathogenesis of HAND. In order to identify pathways that may contribute to neuropathogenesis in HAND, we infected induced pluripotent stem cell-derived microglia (iMG) with HIV and defined gene expression changes over an 8-day period. Monocyte-derived macrophages (MDMs) were studied in parallel to identify common pathways stimulated in myeloid cells versus the unique aspects of microglia infection. Infection of iMG led to the induction of a robust early inflammatory response triggered within hours of infection, a pattern that differed significantly from that seen in MDMs. Remarkably, gene expression changes in iMG reproduced many of the characteristic genetic signatures previously identified in brain tissues obtained from individuals clinically diagnosed with HAND. Inflammatory activation representing interferon-mediated signaling, TNF/NF-{kappa}B, and IL-6/JAK/STAT pathways were particularly prominent over the time course of infection. Interferon-mediated signaling led to enhanced expression of multiple HIV restriction factors, yet viral replication in iMG remained robust. These findings suggest that HIV infection of microglia is the key cellular driver of neuroinflammation in the CNS of HIV-infected individuals. Further studies of infected microglia are likely to aid in understanding the pathogenesis of HAND and in evaluating therapeutic strategies to limit or eliminate HIV-induced neuropathogenesis. Author SummaryPersons living with HIV frequently develop debilitating problems with brain function that are collectively known as HIV-associated neurocognitive disorders (HAND). Treatment with antiretroviral drugs to control HIV has largely eliminated the most severe form of HIV-related brain dysfunction, HIV encephalitis, but a significant proportion of HIV-infected individuals receiving antiviral therapy still develop significant problems with cognitive function. Microglia are the major macrophage-like cells of the brain and are highly susceptible to HIV infection. Inflammation in the brain following infection contributes to damage to neurons and is the likely source of decline of brain function. This study used microglia that were derived from induced pluripotent stem cells, termed iMG, to study the kinetics of gene expression changes in HIV-infected microglia and compared those changes to those seen in monocyte-derived macrophages (MDMs). iMG were found to be easily infected with a macrophage-tropic HIV strain and exhibited a rapid increase in gene expression associated with inflammatory signaling through interferon- and tumor necrosis factor/NF-kappa B-mediated pathways. Remarkably, the patterns of gene expression in microglia strongly overlapped with gene expression signatures derived from brain tissue samples of HIV patients with HAND. The rapid onset and magnitude of inflammation as well as induction of specific HIV restriction factors differed from that seen in infected macrophages/MDMs. These studies reinforce the central role of microglia in the pathogenesis of HAND and provide insights into HIV-microglia interactions that can help direct interventions to reduce inflammation and preserve brain function.

microbiology↗

bioRxiv2022

Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses

Systems biology approaches have been used to define molecular signatures and mechanisms of immunity to vaccination. However, most such studies have been done with single vaccines, and comparative analysis of the response to different vaccines is lacking. We integrated temporal transcriptional data of over 3,000 samples, obtained from 820 healthy adults across 28 studies of 13 different vaccines and analyzed vaccination-induced signatures associated with the antibody response. Most vaccines induced similar kinetics of shared transcriptional signatures, including signatures of innate immunity occurring 1-3 days post-vaccination, as well as the canonical plasmablast and cell cycle signatures appearing 7 days post-vaccination. However, the yellow fever vaccine YF-17D uniquely induced an early transient signature of T and B cell activation at Day 1, followed by delayed antiviral/interferon and plasmablast signatures that peaked at Days 7 and 14-21, respectively. Thus, despite the shared transcriptional response to most vaccines, at any given time point there was no evidence for a "universal signature" that could be used to predict the antibody response to all vaccines. However, accounting for the asynchronous nature of responses led to the identification of a time-adjusted signature that improved prediction antibody of responses across vaccines. These results provide a transcriptional atlas of the human immune response to vaccination and define a common, time-adjusted signature of antibody responses to vaccination.

immunology↗

bioRxiv2021

The Immune Signatures Data Resource: A compendium of systems vaccinology datasets

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines, including those targeting seasonal influenza, yellow fever, and hepatitis B. These data are made available to the broader scientific community through the ImmuneSpace data portal and analysis engine leveraging the NIH/NIAID ImmPort repository1,2. However, a barrier to progress in this area is that comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines and includes transcriptional profiles and antibody response measurements. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses. [Table 1]

systems biology↗

bioRxiv2021

An innate immune activation state prior to vaccination predicts responsiveness to multiple vaccines

Many factors determine whether an individual responding to vaccination will generate an immune response that can lead to protection. Several studies have shown that the pre-vaccination immune state is associated with the antibody response to vaccines. However, the generalizability and mechanisms that underlie this association remain poorly defined. Here, we sought to identify a common pre-vaccination signature and mechanisms that could predict the immune response across a wide variety of vaccines. We leveraged the "Immune Signatures Data Resource" created by the NIH Human Immunology Project Consortium (HIPC) to integrate data from 28 studies involving 13 different vaccines and associate the blood transcriptional status of 820 healthy young adults with their responses. An unsupervised analysis of blood transcriptional profiles across studies revealed three distinct pre-vaccination states, characterized by the differential expression of genes associated with a pro-inflammatory response, cell proliferation, and metabolism alterations downstream of NF{kappa}B and IRF7. Innate and adaptive immune cell subset-specific genes were also associated with the three pre-vaccination states. Importantly, individuals whose pre-vaccination state was enriched in pro-inflammatory response genes known to be downstream of NF{kappa}B tended to have higher serum antibody responses one month after vaccination. A supervised analysis of the same data resulted in a single classifier, also enriched for NF{kappa}B regulated genes, that predicted the antibody response across most of the vaccines. Projection into single-cell RNA-sequencing data suggested that this pre-vaccination state was attributable to the signature of activation of non-classical monocytes and myeloid dendritic cells. Transcriptional signatures of acute responses to bacterial and not viral infections were enriched in the high pro-inflammatory pre-vaccination state and also included NF{kappa}B regulated genes. The pro-inflammatory pre-vaccination state was highly reminiscent of the innate activation state triggered by TLR ligands or adjuvants. These results demonstrate that wide variations in the transcriptional state of the immune system in humans can be a key determinant of responsiveness to vaccination. They also define a transcriptional signature NF{kappa}B activation at baseline, that is associated with a greater magnitude of antibody response to multiple vaccines, and suggest that modulation of the innate immune system by next-generation adjuvants targeting NF{kappa}B before vaccine administration may improve vaccine responsiveness.

systems biology↗