Biology subjects

Landegren, N.

Publications and source records attributed to Landegren, N..

3 recordsLinked to original sources

bioRxiv2025

Systemic Multi-Omics Analysis Reveals Interferon Response Heterogeneity and Links Lipid Metabolism to Immune Alterations in Severe COVID-19

The immune response to SARS-CoV-2 infection is highly heterogeneous, and interferon (IFN)-stimulated genes (ISGs) play a central but context-dependent role in antiviral defense and immune dysregulation. To investigate how ISG heterogeneity relates to immune and metabolic states, we performed an integrated analysis of whole-blood transcriptomics, plasma proteomics, metabolomics, and immune activation markers in hospitalized COVID-19 patients and COVID-negative healthy controls and covalescent individuals. Patients segregated into low (LIS), moderate (MIS), and high (HIS) ISG expression endotypes, largely independent of clinical severity. While high ISG expression was associated with systemic inflammation and innate immune activation, severe disease within the HIS endotype was characterized by marked metabolic perturbations, including depletion of tricarboxylic acid cycle intermediates and multiple lipid classes involved in membrane integrity and immunometabolic signaling. Plasma-transfer assays demonstrated that plasma from severe HIS patients impaired neutrophil and monocyte activation ex vivo, indicating functional attenuation of innate immune responses despite elevated ISG expression. These metabolic alterations correlated with reduced immune activation, supporting the existence of an interferon-associated immune-metabolic axis that constrains immune functionality in severe disease. Although type I IFN neutralization was detected in a subset of patients with IFN antigen reactivity, these samples did not account for ISG heterogeneity or disease severity. Together, these findings show that high ISG expression defines a transcriptional endotype permissive for inflammation but insufficient for effective immune function, highlighting the importance of immune-metabolic context in shaping COVID-19 disease outcomes.

immunology↗

bioRxiv2025

Immune-Coagulation Dynamics in Severe COVID-19: Insights from Autoantibody Profiling and Transcriptomics

Severe COVID-19 is characterized by immune dysregulation and coagulation abnormalities, leading to complications such as thromboembolism and multi-organ failure. This study explores the relationship between autoantibodies targeting coagulation-related factors and gene expression in severe COVID-19. Whole-blood transcriptomics revealed upregulation of coagulation-related genes, including VWF and Factor V, in severe patients compared to mild cases and healthy controls. Autoantibody profiling against seven coagulation-related proteins (ADAMTS13, Factor V, Protein S, SERPINC1, Apo-H, PROC1, and Prothrombin) showed reactivities below established positivity thresholds, but mean-fluorescent intensities were elevated numerically in severe (Protein S) and convalescent (SERPINC1) patients. Correlation analysis revealed trends of negative associations between autoantibody reactivities and coagulation gene expression in severe cases, suggesting a potential role for autoantibodies in modulating immune-coagulation interactions warranting further orthogonal validation. Furthermore, age-dependent increases in subthreshold autoantibody reactivities were observed in severe cases, highlighting the potential impact of immunosenescence on disease severity. These findings do not exclude the possibility that subthreshold autoantibodies may contribute indirectly to immune-coagulation dynamics in severe COVID-19 through mechanisms beyond direct transcriptional regulation. This study highlights the complexity of immune-coagulation interactions and provides foundation for future research into their biological and clinical relevance, particularly for identifying biomarkers and therapeutic targets in thromboinflammatory diseases.

immunology↗

bioRxiv2022

Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq

Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-Seq for autoantigen discovery, including our previous work (Vazquez et al. 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and finally, mild and severe forms of COVID19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.

immunology↗