Todd M Brusko
· ProfessorVerifiedUniversity of Florida · Pathology, Immunology and Laboratory Medicine
Active 2003–2026
About
Dr. Todd M Brusko is a Professor in the Department of Pathology at the University of Florida College of Medicine and serves as the Research Director of the UF Diabetes Institute. His research interests are centered around understanding the mechanisms by which the immune system maintains a state of control, known as immunological tolerance. His work includes studies of the innate and adaptive immune systems, with a particular focus on the TCR repertoire and the costimulation of T cells and regulatory T cells. Dr. Brusko's laboratory investigates the genetic variants that influence these immune processes and aims to identify mechanisms involved in individuals who develop immune-mediated diseases. He has published over 100 studies reporting cellular immune defects in patients with conditions such as type 1 diabetes, lupus, sepsis, and cancer, exploring the cellular immune mechanisms and biological bases of these diseases. A major goal of his laboratory is to develop a comprehensive understanding of immune system development throughout the human lifespan, both in peripheral blood and within central and peripheral immune tissues. His research involves profiling immune system function in type 1 diabetes through various programs, including the Network for Pancreatic Organ Donors with Diabetes (nPOD), the Human Biomolecular Atlas Program (HuBMAP), the NIH Human Islet Research Network (HPAP), and the Human Atlas for Neonatal and Developmental Early Life – Immunity (HANDEL-I). These efforts leverage advanced techniques such as genotyping, single-cell epigenetics, transcriptomics, immune repertoire analysis, and high-parameter spectral flow cytometry, all within the UF Center for Immunology and Transplantation. His work aims to define immunity in health and disease states, ultimately contributing to the development of biomarkers and targeted immune interventions.
Research topics
- Medicine
- Immunology
- Biology
- Internal medicine
- Endocrinology
- Genetics
- Data Mining
- Computer Science
- Machine Learning
- Artificial Intelligence
- Bioinformatics
- Pathology
- Cell biology
- Data science
- Intensive care medicine
- World Wide Web
- Database
- Virology
Selected publications
2026-01-21
article<p dir="ltr">There is significant interest in antigen specific approaches both to delay type 1 diabetes in pre-clinical stages and after diagnosis to support tolerance. We conducted a Phase 1 trial of a non-integrating DNA plasmid constructed to secrete the type 1 diabetes antigen pre-proinsulin (PPI) and the immune modulatory cytokines transforming growth factor β1 (TGF-β1), interleukin-10 (IL-10), and interleukin-2 (IL-2). In this placebo controlled, double-masked study of 47 adults with stage 3 type 1 diabetes, we showed that the drug is safe and well tolerated, with most reported adverse events (AE) categorized as grade 1 and with no clinically significant difference in AE amongst treatment groups. There were no untoward metabolic or immune effects. We found pharmacodynamic evidence of treatment, as demonstrated by a dose dependent type 1 interferon (IFN) signature. Plasmid DNA, representing a pharmocokinetic measure, was detected in the two highest dosing groups. We did not find global or antigen-specific immune cell changes following treatment with a DNA plasmid expressing pre-proinsulin, IL-2, IL-10 and TGF-β1, nor did we detect IL-2, IL-10 or TGF-b1 driven immune changes. Our results support further trials of this novel tolerizing antigen construct.</p>
Cell Reports · 2026-03-23
articleOpen accessSenior authorThis study explores the inflammatory response observed in the pancreas and pancreatic lymph nodes (pLNs) during the natural history of type 1 diabetes (T1D). Using multicell-resolution spatial transcriptomics (ST), we profile individuals without diabetes (ND), at-risk autoantibody-positive (AAb+) individuals, and T1D donors. In the T1D pancreas, we observed global upregulation of inflammation-associated transcripts, including REG family genes, C3, SOD2, and OLFM4. In the T1D pLN, LTB was significantly upregulated within the lymphoid follicles. Using an orthogonal subcellular-resolution ST platform on an independent donor set, we identified follicular B cells as the primary source of LTB in the pLN and observed increased LTB expression in lymphocytes in insulitic lesions proximal to CCL19/CCL21-expressing endothelium. Collectively, these findings highlight lymphotoxin-β and downstream chemokine signatures in the pancreatic lymphatics as well as within the insulitic lesion, which can inform future therapeutic interventions.
Diabetes · 2026-01-21 · 1 citations
articleOpen accessThere is significant interest in antigen-specific approaches to delaying type 1 diabetes in preclinical stages and supporting tolerance after diagnosis. We conducted a phase I trial of a nonintegrating DNA plasmid constructed to secrete the type 1 diabetes antigen preproinsulin (PPI) and the immune modulatory cytokines transforming growth factor-β1 (TGF-β1), interleukin-10 (IL-10), and IL-2. In this placebo-controlled, double-masked study of 47 adults with stage 3 type 1 diabetes, we showed that the drug is safe and well tolerated, with most reported adverse events (AEs) categorized as grade 1 and with no clinically significant difference in AEs among treatment groups. There were no untoward metabolic or immune effects. We found pharmacodynamic evidence of treatment, as demonstrated by a dose-dependent type 1 interferon (IFN) signature. Plasmid DNA, representing a pharmocokinetic measure, was detected in the two highest dosing groups. We did not find global or antigen-specific immune cell changes following treatment with a DNA plasmid expressing PPI, IL-2, IL-10, and TGF-β1, and we did not detect immune changes driven by IL-2, IL-10, or TGF-β1. Our results support further trials of this novel tolerizing antigen construct. ARTICLE HIGHLIGHTS: Antigen-specific therapy is needed to induce tolerance in type 1 diabetes at early disease stages or in combination with immunotherapy. We conducted a phase I trial in type 1 diabetes of a novel plasmid construct expressing the islet antigen preproinsulin (PPI) and immunomodulatory cytokines transforming growth factor-β1 (TGF-β1), interleukin-10 (IL-10), and IL-2. The therapy was safe and well tolerated. Dose-dependent changes in DNA plasmid levels and type 1 interferon signatures were detected; however, global and antigen-specific immune changes to PPI, IL-2, IL-10, or TGF-β1 were not observed. Further trials are needed to assess efficacy.
PLoS Computational Biology · 2026-01-16
articleOpen accessT cell receptors (TCRs) recognize peptides presented by polymorphic human leukocyte antigen (HLA) molecules, but HLA genotype data are often missing from TCR repertoire sequencing studies. To address this, we developed TCR2HLA, an open-source tool that infers HLA genotypes from TCRβ repertoires. Expanding on work linking public TRBV-CDR3 sequences to HLA genotypes, we incorporated "quasi-public" metaclonotypes - composed of rarer TCRβ sequences with shared amino acid features - enriched by HLA genotypes. Using four TCRβseq datasets from 3,150 individuals, we applied TRBV gene partitioning and locality-sensitive hashing to identify ~96,000 TCRβ features strongly associated with specific HLA alleles from 71M input TCRs. Binary HLA classifiers built with these features achieved high balanced accuracy (>0.9) across common HLA-A (9/12), B (9/12), C (6/13), DRB1 (11/11) alleles and prevalent DPA1/DPB1 (6/10), DQA1/DQB1 (8/17) heterodimers. We also introduced a high-sensitivity calibration to support predictions in samples with as few as 5,000 unique clonotypes. Calibrated predictions with confidence filtering improved reliability. Beyond genotype imputation, TCR2HLA enables the discovery of novel HLA- and exposure-associated TCRs, as shown by the identification of SARS-CoV-2 related TCRs in a large COVID-19 dataset lacking HLA data. TCR2HLA provides a scalable framework for bridging the gap between TCRseq data and HLA genotype for biomarker discovery.
Science Advances · 2026-02-13 · 1 citations
articleOpen accessSenior authorType 1 diabetes (T1D) is a T cell-mediated disease with a strong immunogenetic human leukocyte antigen (HLA) dependence. HLA allelic influence on the T cell receptor (TCR) repertoire shapes thymic selection and controls activation of diabetogenic clones yet remains largely unresolved in T1D. We sequenced the circulating TCRβ chain repertoire from 2250 HLA-typed participants across three cross-sectional cohorts, including individuals with T1D and healthy related and unrelated controls. We found that HLA risk alleles show higher restriction of TCR repertoires in individuals with T1D. We leveraged deep learning to identify T1D-associated TCR subsequence motifs that were also observed in independent TCR cohorts residing in pancreas-draining lymph nodes of individuals with T1D. Collectively, our data demonstrate T1D-related TCR motif enrichment based on genetic risk, offering a potential metric for autoreactivity and groundwork for TCR-based diagnostics and therapeutics.
A Community Challenge to Benchmark Machine Learning
Figshare · 2026-03-12
articleOpen accessAdaptive immune receptors (B- and T-cell receptors; BCRs and TCRs) can recognise a diverse array of different antigens, initiating and maintaining the adaptive immune response. There is immense interest in academia and industry to discover immune receptors for diagnostics and therapeutics utilizing machine learning (ML). We propose the first community challenge to systematically benchmark ML methods on two tasks: given a dataset of immune state-labeled immune repertoires, predict (1) immune state (diagnostic use case), and (2) infer immune-state-associated receptors (therapeutic discovery use case). We conceived a benchmarking database of real-world relevant data including ~75,000 high-fidelity simulated (ground-truth) and experimentally generated TCR repertoires. By quantifying the performance of state-of-the-art techniques and identifying methodological gaps, this community challenge contributes to expediting ML-based solutions for immunodiagnostics and therapeutics discovery.
A Community Challenge to Benchmark Machine Learning
Figshare · 2026-03-12
articleOpen accessAdaptive immune receptors (B- and T-cell receptors; BCRs and TCRs) can recognise a diverse array of different antigens, initiating and maintaining the adaptive immune response. There is immense interest in academia and industry to discover immune receptors for diagnostics and therapeutics utilizing machine learning (ML). We propose the first community challenge to systematically benchmark ML methods on two tasks: given a dataset of immune state-labeled immune repertoires, predict (1) immune state (diagnostic use case), and (2) infer immune-state-associated receptors (therapeutic discovery use case). We conceived a benchmarking database of real-world relevant data including ~75,000 high-fidelity simulated (ground-truth) and experimentally generated TCR repertoires. By quantifying the performance of state-of-the-art techniques and identifying methodological gaps, this community challenge contributes to expediting ML-based solutions for immunodiagnostics and therapeutics discovery.
2026-01-21
article<p dir="ltr">There is significant interest in antigen specific approaches both to delay type 1 diabetes in pre-clinical stages and after diagnosis to support tolerance. We conducted a Phase 1 trial of a non-integrating DNA plasmid constructed to secrete the type 1 diabetes antigen pre-proinsulin (PPI) and the immune modulatory cytokines transforming growth factor β1 (TGF-β1), interleukin-10 (IL-10), and interleukin-2 (IL-2). In this placebo controlled, double-masked study of 47 adults with stage 3 type 1 diabetes, we showed that the drug is safe and well tolerated, with most reported adverse events (AE) categorized as grade 1 and with no clinically significant difference in AE amongst treatment groups. There were no untoward metabolic or immune effects. We found pharmacodynamic evidence of treatment, as demonstrated by a dose dependent type 1 interferon (IFN) signature. Plasmid DNA, representing a pharmocokinetic measure, was detected in the two highest dosing groups. We did not find global or antigen-specific immune cell changes following treatment with a DNA plasmid expressing pre-proinsulin, IL-2, IL-10 and TGF-β1, nor did we detect IL-2, IL-10 or TGF-b1 driven immune changes. Our results support further trials of this novel tolerizing antigen construct.</p>
Corrigendum to: Autoreactive T cell receptors with shared germline-like α chains in type 1 diabetes
JCI Insight · 2026-04-21
articleOpen accessBeta cell–targeted PD-1 agonist inhibits cell-mediated autoimmunity in pancreas tissue slices
Science Advances · 2026-04-01
articleOpen accessThis research evaluates a therapeutic approach based on tissue-targeted immunomodulation with a potential broad application to treat autoimmune diseases including type 1 diabetes (T1D). We generated a bispecific immune agonist that binds beta cells and suppresses autoreactive T cells. These bispecific molecules called immune modulating monoclonal-T cell receptor (TCR) against autoimmune disease (ImmTAAI), consist of a human-specific TCR-targeting domain fused with a programmed death-1 agonist. We used live pancreas slices to demonstrate targeting of ImmTAAI molecules to preproinsulin peptide-HLA-A2 complexes on human beta cells. ImmTAAI molecules protected beta cells from T cell killing by increasing T cell motility and inhibiting effector molecule and cytokine secretion. ImmTAAI treatment also increased the motility of islet-infiltrating T cells in slices from a donor with recent-onset T1D and preserved insulin secretion in slices cocultured with T cell avatars transduced with diabetogenic TCRs. These data demonstrate that ImmTAAI molecules have the potential to limit T cell activity locally, making this an attractive platform to elicit targeted immunoregulation in T1D.
Recent grants
The CD226 costimulatory axis in type 1 diabetes
NIH · $4.4M · 2016–2027
Administration and Sample Acquisition
NIH · $55.7M · 1997–2028
Engineering a Human Microphysiological System for the Characterization of Islet-Immune Interactions
NIH · $2.1M · 2019–2024
Engineering a Human Microphysiological System for the Characterization of Islet-Immune Interactions
NIH · $3.0M · 2019–2025
Frequent coauthors
- 161 shared
Mark A. Atkinson
University of Florida
- 90 shared
Clive Wasserfall
University of Florida
- 67 shared
Desmond Schatz
University of Florida
- 63 shared
Maigan A. Brusko
Florida College
- 59 shared
Michael J. Haller
- 56 shared
Amanda L. Posgai
University of Florida
- 54 shared
Clayton E. Mathews
University of Florida
- 42 shared
Daniel J. Perry
Century Therapeutics (United States)
Education
Postdoc, Immunology & Molecular Genetics
University of Florida
BS, Microbiology & Cell Science
University of Florida
Postdoc, Molecular Immunology & Cell Therapy
Diabetes Center, University of California, San Francisco
PhD, Immunology
University of Florida
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