Biology subjects

Aschenbrenner, A. C.

Publications and source records attributed to Aschenbrenner, A. C..

5 recordsLinked to original sources

bioRxiv2026

Multi-Omics Clustering Differentiates the Total and Intact HIV Reservoirs and Related Host Immune Mechanisms

HIV reservoirs are heterogeneous across individuals, yet host determinants of this variability remain unclear. Applying multi-omics clustering to 1,230 people with HIV, integrating omics and functional data from circulating immune cells (transcriptomics, DNA methylation, immune phenotyping, ex-vivo cytokine production capacity), plasma proteomics, and CD4+ T-cell reservoir measurements (total and intact HIV-DNA copies), revealed three immunologically distinct endotypes: All Low (low total/low intact reservoir size), All High (high total/high intact reservoir size) and Mixed (high total/low intact reservoir size). Per endotype, distinct immune landscapes were noticed in single-layer analyses as well as differences in clinical signatures. Applying non-linear machine learning across all layers, key predictors not captured by linear single-layer approaches showed IFN-{gamma} production and TCF7/AK5 expression across T-cell and NK-cell populations as well as IL-1{beta}/MCP-1 production after 24h stimulation and MAN1C1/EDAR expression on T-cell populations, linked to intact and total reservoir size, respectively. This host-virus integrative multi-omics framework provides a systems-level resource that may help to personalize reservoir-reducing intervention studies aiming for HIV cure and/or comorbidity reductions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/734029v4_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@16fded7org.highwire.dtl.DTLVardef@18f2e69org.highwire.dtl.DTLVardef@12ffc9borg.highwire.dtl.DTLVardef@17127cc_HPS_FORMAT_FIGEXP M_FIG a) Multi-omics clustering of 1,230 virally suppressed PLHIV identified three immunologically distinct endotypes: All Low (n=428), Mixed (n=483), and All High (n=280), with distinct total and intact HIV reservoir sizes. b) Single-layer analyses reveal characteristic immune landscapes: All Low Th1-skewed, naive T cells (immunophenotyping), high IFN-{gamma} production (7-day), downregulated Type I IFN pathways (bulk transcriptome); Mixed intermediate Th1/Th2, CD8 and CD4 effector memory T cells (immunophenotyping), IL-5 production (7-day), downregulated Type I IFN pathways (bulk transcriptome); All High Th2-skewed, CD4 effector memory T cells (immunophenotyping), high IL-5 production (7-day), upregulated Type I IFN pathways (bulk transcriptome). c) Endotypes carry distinct comorbidity burdens: All Low lower carotid plaque, AIDS-defining malignancies, and residual viremia; Mixed intermediate burden; All High highest carotid plaque, AIDS-defining malignancies, opportunistic infections, and residual viremia. d) Non-linear classification models (XGBoost) prioritize top host predictive markers: IFN-{gamma} response (7-day), TCF7 and AK5 expression in CD4/CD8 T-cells and NK-cells (characterize All Low; IL-1 response (24-hour), MAN1C1 and EDAR in CD4/CD8 T-cells, and MCP1 response (24-hour) characterize All High. Created in BioRender. C_FIG

immunology↗

bioRxiv2026

A high-throughput cost-efficient in vitro platform for the screening of immune senomodulators

With advancing age, the immune systems capacity to effectively combat pathogens diminishes. This decline of the overall immune function impacts both the innate and adaptive compartments, contributing in many cases to a systemic state of chronic inflammation which further increases the risk of the most prevalent non-communicable diseases and severe infections. Given the increase in median life expectancy with a demographic development towards a larger number of elderly people, identifying interceptive strategies to mitigate the individual and societal impact of diseases related to immune aging is of paramount importance. We developed a molecularly defined strategy to guide interventions with the aim to reduce immune aging. We introduce an omics-based drug screening platform to identify and characterize the pharmacological profile of immune senomodulators applicable to cross-age human cohorts using human-derived peripheral immune cells. To this aim we developed a robust experimental approach to screen for effective anti-aging compounds directly on human cells. This methodology allows us to quickly screen for drug candidates at different scales: from cost-effective bulk transcriptomics for a broader high-throughput overview of cellular responses, down to single-cell resolution approaches for a more detailed look at gene expression and other molecular data. This in vitro screening method is designed to maximize the clinical relevance of our findings, providing a direct link between preclinical research and patient care. By analyzing how different compounds affect the immune cells of individual persons, we can identify treatments that are most likely to be effective against aging in a subject-specific manner--a key step toward personalized medicine. In short, our approach enables a faster translation of anti-aging immune treatments from the lab to the clinic, tailoring them to each individuals unique biological makeup.

systems biology↗

bioRxiv2021

Induction of peri-implantation stage synthetic embryos using reprogramming paradigms in ESCs

Blastocyst-derived stem cell lines were shown to self-organize into embryo-like structures in 3D cell culture environments. Here, we provide evidence that synthetic embryo-like structures are generated solely based on transcription factor-mediated molecular reprogramming of embryonic stem cells in a simple 3D co-culture system. ESCs in these cultures self-organize into elongated, compartmentalized synthetic embryo-like structures over the course of reprogramming exhibiting anterior visceral endoderm formation and symmetry breaking. Single-cell RNA-Seq reveals transcriptional profiles resembling epiblast, visceral endoderm, and extraembryonic ectoderm of early murine embryos around E4.5-E5.5. Within the epiblast, compartment marker gene expression supports primordial germ cell specification. After transplantation, synthetic embryo-like structures implant in uteri and initiate the formation of decidual tissues. This system allows for fast and reproducible generation of synthetic embryo-like structures, providing further insights into synthetic embryology.

synthetic biology↗

bioRxiv2020

Swarm Learning as a privacy-preserving machine learning approach for disease classification

Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis and COVID-19 is an important goal of precision medicine. We recently illustrated that leukemia patients are identified by machine learning (ML) based on their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, blockchain-based peer-to-peer networking and coordination as well as privacy protection without the need for a central coordinator thereby going beyond federated learning. Using more than 14,000 blood transcriptomes derived from over 100 individual studies with non-uniform distribution of cases and controls and significant study biases, we illustrate the feasibility of SL to develop disease classifiers based on distributed data for COVID-19, tuberculosis or leukemias that outperform those developed at individual sites. Still, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

bioinformatics↗

bioRxiv2020

Alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease

Despite the epidemics of chronic obstructive pulmonary disease (COPD), the cellular and molecular mechanisms of this disease are far from being understood. Here, we characterize and classify the cellular composition within the alveolar space and peripheral blood of COPD patients and control donors using a clinically applicable single-cell RNA-seq technology corroborated by advanced computational approaches for: machine learning-based cell-type classification, identification of differentially expressed genes, prediction of metabolic changes, and modeling of cellular trajectories within a patient cohort. These high-resolution approaches revealed: massive transcriptional plasticity of macrophages in the alveolar space with increased levels of invading and proliferating cells, loss of MHC expression, reduced cellular motility, altered lipid metabolism, and a metabolic shift reminiscent of mitochondrial dysfunction in COPD patients. Collectively, single-cell omics of multi-tissue samples was used to build the first cellular and molecular framework for COPD pathophysiology as a prerequisite to develop molecular biomarkers and causal therapies against this deadly disease.

systems biology↗