November 20, 2025
Publications Highlights
As the year comes to a close, we want to take a moment to spotlight some recent publications of work by our customers and partners where GMet’s metabolomics, lipidomics, isotopic labeling, or integrated omics data were a part of the story. Our goal is to highlight the amazing work that our customers are doing while also demonstrating how GMet’s omics offerings can help support biological research.
One common thread in the following research is how the power of omics studies are often connected to being able to acquire many samples. When looking for metabolite-gene or metabolite-disease associations it’s critical to be able to measure hundreds or thousands of samples to build enough statistical power to make novel observations
Congratulations to all of the authors in these terrific publications!
Duncan Holbrook-Smith, PhD
This study from Qi et al sheds light on different aspects of alterations in epigenetic profiles and immune responses as they relate to BCG vaccination. What we find particularly innovative is how they integrate multiple molecular layers (including metabolites) to show how vaccination leads to long-term immune “memory-like” effects. This kind of integrative omics approach is precisely the kind of analysis which GMet’s metabolomics offerings enable due to their coverage and scalability.
Genetic and molecular landscape of comorbidities in people living with HIV (Nature Medicine, 2025)
This is a standout because it brings together five distinct omics layers (epigenomics, transcriptomics, proteomics, metabolomics and immune function) in a large cohort (1,342 people living with HIV) to explore the drivers of non-AIDS comorbidities in this population. This analysis allows for the identification of how genetically determined changes in molecules are causally related to immune function. These kinds of large studies are a nice application for GMet’s flow injection metabolomics methodology since it allows for fast and robust measurements at large scales.
This study uses untargeted metabolomics on serum samples collected before breast cancer diagnosis (on average ~5.3 years ahead) in a nested case-control design (593 cases vs 593 matched controls) to determine which metabolite profiles help predict risk of breast cancer. The study demonstrates how metabolic markers can move beyond assisting in diagnosis for existing health problems and move into a more predictive mode in healthy individuals. As with the previously highlighted paper, GMet’s flow injection methodology works well for this application due to its robustness and the tractability of population-scale study designs.
In this paper Guerrero et al explore how the modulation of the expression of the glucose transporter GLUT1 can increase immune function of CAR-T cells. This work is clearly important since it demonstrates how immune therapies for cancer can be improved but also emphasizes the importance of metabolism in immune function. In this paper GMet’s stable isotope tracing platform was used to show that altered GLUT1 expression was in fact affecting the rate of accumulation of downstream glucose products in central metabolism which bolstered the connection between metabolic reprogramming and improved cellular potency.
