About

We investigate how metabolism shapes cellular function, physiology, and disease. Using AI-powered spatial biology, we resolve metabolic networks across tissues and cell types to uncover mechanisms of ageing, cognition, and cancer biology.

Research topics

• Biochemistry
• Chemistry
• Biology
• Cell biology
• Medicine
• Immunology
• Internal medicine
• Neuroscience
• Endocrinology

Selected publications

• Vitamin B2 and B3 nutrigenomics reveals a therapy for NAXD disease

  Cell · 2026-02-25 · 1 citations

  articleOpen access

  depletion, and impaired serine biosynthesis in neonatal KO brains. Spatial metabolomics, single-nuclei RNA sequencing (snRNA-seq), and histology pinpointed cortical and brain endothelial cell vulnerability. Low-vitamin B3 diets accelerated pathology, whereas vitamin B3 supplementation extended lifespan by more than 40-fold. These findings establish a nutritional genomics framework and demonstrate the therapeutic potential of precision vitamin interventions.

  PublisherDOI

• Multiomic integration reveals tumoral heterogeneity of lipid dependence within lethal group 3 medulloblastoma

  Cancer Cell · 2026-01-15 · 2 citations

  article
  PublisherDOI

• GLP-1 receptor agonists and acute diabetes complications in adults with type 1 diabetes

  iScience · 2026-04-14

  articleOpen access

  GLP-1 receptor agonists (GLP-1 RAs) are increasingly used for weight management in patients with obesity, yet their safety in those with comorbid type 1 diabetes (T1D) remains uncertain due to concerns about diabetic ketoacidosis (DKA). This targets trial emulation using OneFlorida+ EHR data (2014-2024). After 1:1 time-conditional propensity score matching, the cohort included 651 GLP-1 RA initiators and 651 matched non-initiators with T1D meeting anti-obesity medication criteria. DKA incidence rates were 13.5 vs. 21.8 per 1,000 person-years. GLP-1 RA initiation was not significantly associated with DKA (hazard ratio [HR], 0.62; 95% confidence interval [CI]: 0.33-1.17) or severe hypoglycemia (HR, 0.52; 95% CI: 0.17-1.55) but was associated with fewer hospitalizations (HR, 0.74; 95% CI: 0.62-0.90) and emergency department visits (HR, 0.73; 95% CI: 0.57-0.92). These findings suggest that GLP-1 RAs may be safely prescribed in adults with T1D and obesity without increasing acute diabetes complications, while potentially reducing healthcare utilization.

  PublisherDOI

• Mapping glycogen accumulation and treatment effect in Pompe disease with saturation transfer MRI

  Translational research · 2026-02-19

  articleOpen access

  Pompe disease is a glycogen storage disease caused by the impaired breakdown of glycogen in lysosomes, leading to abnormal glycogen accumulation in tissue. Here we use glycogen nuclear Overhauser effect (glycoNOE) MRI to detect glycogen levels in skeletal muscle in a mouse model of Pompe disease. Moreover, we evaluated if glycoNOE MRI could detect changes in glycogen load after enzyme replacement therapy. The results show that glycoNOE MRI can distinguish between Pompe mice and wildtype controls. Furthermore, the technique detected treatment-dependent changes in muscle glycoNOE signals, which were validated with ex vivo biochemical assays. To demonstrate potential human translation, glycoNOE MRI was applied to two Pompe patients and revealed elevated glycogen levels in patients compared to healthy controls.

  PublisherDOI

• Inferring high-fat dietary patterns from electronic health record data using machine learning

  JAMIA Open · 2026-01-03

  articleOpen access

  Objectives: Electronic health records (EHRs) rarely capture dietary detail, limiting diet-disease research. We aimed to develop machine learning (ML) computable phenotypes to identify high-fat diet (HFD) using variables typically available in EHRs. Materials and Methods: We used National Health and Nutrition Examination Survey (NHANES) 1999-2020 data, where 24-h dietary recall served as ground truth. Dietary fat intake was summarized into a score (0-30) based on percent energy from fat, carbohydrate, and protein; lower scores indicated HFD. We defined HFD at cutoffs of 10, 15, and 20, and trained ML models (Extreme Gradient Boosting, logistic regression, random forest) using EHR-compatible variables (demographics, comorbidities, labs, anthropometrics). Model interpretability was assessed using Shapley Additive Explanations. To evaluate clinical relevance, we compared cancer associations using ML-predicted vs true diet labels. Results: Machine learning models classified HFD with good performance, strongest at broader definitions. Random forest achieved an F1-score of 0.79 (recall 0.74, precision 0.84) at cutoff 20. Key predictors included race/ethnicity, triglycerides, obesity metrics (body mass index and derived indices), and metabolic panel results. Discussion: These findings indicate that dietary patterns, though seldom recorded in EHRs, can be inferred from routinely available variables. The ability of ML-derived phenotypes to reproduce known diet-disease relationships underscore their epidemiologic validity. Top predictors also align with established biological pathways linking obesity, lipid metabolism, and cancer risk, supporting plausibility. Conclusion: A high-fat dietary pattern can be inferred from EHR-compatible variables using ML-based phenotyping. This approach offers a scalable tool to integrate diet into EHR-based research and precision medicine.

  PublisherDOI

• GAA-based therapeutic strategies for neurological glycogen storage diseases

  Molecular Genetics and Metabolism · 2026-02-01

  articleOpen access
  PublisherDOI

• Shaping Human Health and Nutrition Through Innovations in Spatial Metabolism

  Annual Review of Nutrition · 2026-05-19

  articleSenior author

  Spatial metabolomics has emerged as a transformative approach for understanding how metabolism is organized within tissues and how nutritional factors influence health and disease. By preserving the spatial context of metabolites within intact tissue architecture, techniques such as MALDI and DESI imaging mass spectrometry reveal metabolic heterogeneity that bulk analyses cannot capture. This review examines how spatial metabolomics advances nutrition research across multiple domains: from mapping nutrient distributions in foods to understanding how diet reshapes tissue metabolism in disease states. We highlight recent innovations, including single-cell-resolution imaging, 3D metabolome reconstruction, stable isotope tracing, and multiomics integration. Key applications demonstrate how dietary patterns drive glycogen accumulation in cancer, alter lipid zonation in fatty liver disease, and modulate brain metabolism through the gut-brain axis. These spatially resolved insights establish direct mechanistic links between nutrition, tissue metabolism, and disease pathogenesis.

  PublisherDOI

• New approaches to uncover COPD pathobiology and develop therapies

  JCI Insight · 2026-02-23

  articleOpen access

  Chronic obstructive pulmonary disease (COPD) was the third leading cause of global mortality in 2011 but receives limited attention and research funding. This Review describes the current knowledge on COPD risk factors, including genetic and epigenetic determinants and their interactions with the microbiome and environmental exposures. Preclinical models are being refined and single-cell transcriptomic, metabolomic, and proteomic technologies are being implemented to investigate the molecular mechanisms of disease progression. Patient cohorts to define biomarkers of early disease and the latest approaches to diagnose pre-COPD are essential to accelerate the development of novel and effective therapeutic interventions and translate new findings into clinical trials. This Review is a summary of topics covered by a symposium organized by the COPD-iNET consortium, an international network of researchers who have established a platform that facilitates collaboration of this multidisciplinary group of preclinical, translational, and clinical researchers.

  PublisherOA PDFDOI

• Neonatal systemic gene therapy restores cardiorespiratory function in a rat model of Pompe disease

  Molecular Therapy · 2025-06-14 · 2 citations

  articleOpen access
  PublisherOA PDFDOI

• Preoperative GLP-1 receptor agonist use and postoperative respiratory complications in patients undergoing elective surgeries: a target trial emulation study

  American Journal of Respiratory and Critical Care Medicine · 2025-10-10

  articleOpen access
  PublisherOA PDFDOI

Recent grants

• Aberrant Glycogen in Lung Adenocarcinoma Tumorigenesis

  NIH · $2.1M · 2022–2027

• Aberrant Glycogen Modulates Cerebral Glucose Metabolism in Aging and Alzheimer's Disease

  NIH · $1.9M · 2020–2026

Frequent coauthors

• Matthew S. Gentry

  155 shared

• Lyndsay E.A. Young

  University of Kentucky

  136 shared

• Lindsey R. Conroy

  University of Kentucky

  94 shared

• Harrison A. Clarke

  University of Florida

  78 shared

• Tara R. Hawkinson

  University of Florida

  66 shared

• Derek B. Allison

  Markey Cancer Center

  61 shared

• Jinze Liu

  Virginia Commonwealth University

  34 shared

• Chi Wang

  Markey Cancer Center

  32 shared

Labs

• Sun LabPI

Awards & honors

• Finalist, Life Science Breakthrough of the year 2025 Falling…
• Significant achievement award. 2024 Society for glycobiology
• V-Scholar 2021 V foundation
• St Baldricks Scholar 2020 St Baldricks Foundation