Mark M. Davis

The paper develops an immune proteomic signature (iPACE) from serum proteins in elderly patients that predicts cardiovascular risk and mortality.

This study identifies donor-derived CD8+CD122+ Tregs in mixed chimeric NOD mice that suppress autoreactive T cells and may offer a new therapeutic strategy for autoimmune diabetes.

This paper identifies 23 candidate causal genes for critical COVID-19 by integrating severity-stratified, longitudinal cis-eQTL mapping with GWAS signals from 1,031 patients.

The paper shows that simulated microgravity causes aging-like transcriptional changes in human organoids, with effects varying by tissue type.

The paper introduces IMM-AGE, a metric of immune-aging, and shows it independently predicts cardiovascular disease risk across multiple cohorts.

This paper develops TGF-β agonists targeting specific T and B cells to selectively suppress pathogenic immune responses in autoimmune and inflammatory diseases.

This paper develops KAT-TCIPs to induce cell death in diffuse large B cell lymphoma by redirecting p300 and CBP to activate programmed cell death genes repressed by BCL6.

The paper identifies CD38 as a marker for pathogenic T cells in T1D and shows that anti-CD38 mAb selectively depletes these cells to prevent diabetes without affecting Tregs.

The paper identifies a mechanism where TLR4-driven cross-presentation of citrullinated antigens by dendritic cells and autoreactive B cells activates CD8+ T cells in rheumatoid arthritis.

This study identifies age-related defects in CXCL13+ T follicular helper cells in human tonsil organoids, linking them to reduced antibody responses.

The paper uses patient-derived organoids to study TAM responses to CD47 checkpoint blockade, revealing a conversion to an immunosuppressive SPP1+ phenotype in clear cell renal cell carcinoma.

This study shows that malaria exposure increases cytotoxic Vδ2+ T cell expansion in human tonsil and spleen organoids, with clonal expansion and activation, while not significantly affecting influenza vaccine responses.

This study uses simulated microgravity to model biological aging in humans, finding similar transcriptional changes to natural aging across multiple systems and aging hallmarks.

This study develops an immune organoid model to study HIV infection, treatment, rebound, and intervention in human lymphoid tissues.

The paper shows that fetal thymic expression of tumor-associated antigens (TAAs) predicts their immunogenicity and guides rational antigen selection for immunotherapy.

This study identifies cytokines that enhance influenza vaccine antibody responses in human organoids and mice, showing their potential as adjuvants to improve vaccine efficacy.

This study identifies elevated oxidative stress in both ME/CFS and Long COVID patients through blood cell analysis, suggesting shared molecular mechanisms and potential therapeutic targets.

The paper identifies a multi-omics recovery factor predictive of long COVID using data from the IMPACC study, showing it can predict LC risk early after infection.

This study identifies immune subtypes in hospitalized COVID-19 patients linked to clinical outcomes and long COVID risk through longitudinal multi-omics analysis.

The paper integrates single-cell chromatin and transcriptomic data from human scalp to identify gene regulatory mechanisms and causal variants in hair and skin diseases.

This study combines common and rare variant analyses with single-cell multiomics to identify cell-type-specific genetic risk factors for severe COVID-19, revealing molecular mechanisms and potential therapeutic targets.

This paper introduces ENTER-seq, a method using engineered lentiviral particles to systematically discover receptor-ligand interactions and map TCR specificity in single cells.

The paper uses single-cell transcriptomics and epigenomics to analyze immune cell subsets in human tonsils, revealing that autoimmune risk variants have strong regulatory potential in germinal center cells.

SIMON is an open-source platform that enables biomedical researchers to apply machine learning algorithms to high-dimensional data without requiring advanced programming skills.

The paper introduces FluPRINT, a database integrating multiple parameters to study influenza vaccine immunity, enabling machine learning analysis of vaccine response markers.

This study identifies novel MHC-I antigens specific to dengue virus infection using an immuno-proteomics approach, revealing ligands associated with distinct HLA haplotypes and T-cell recognition.

This paper introduces immunoStates, a basis matrix that reduces biological and technical biases in cell-mixture deconvolution by incorporating diverse disease states and microarray platforms.