Emeli Chatterjee, PhD, of the Cardiovascular Research Center at Massachusetts General Hospital, is the lead author and Saumya Das, MD, PhD, of the Division of Cardiology at Massachusetts General Hospital, is the senior author of a paper published in Cell Genomics, “The extracellular vesicle transcriptome provides tissue-specific functional genomic annotation relevant to disease susceptibility in obesity.”
Q: How would you summarize your study for a lay audience?
Our study examines how RNA in extracellular vesicles (EVs) can provide insights into metabolic phenotypes related to obesity. By using functional genomics approaches, we found a high representation of genes and regulatory elements previously associated with obesity and type 2 diabetes represented by the RNA cargo within these EVs. Notably, these EV transcripts represent regulatory elements and transcriptionally active genes in adipose tissue and are associated with metabolic phenotypes, including body mass index and type 2 diabetes.
We provide a roadmap to integrate EV transcript profiling with genetic approaches that could ultimately inform the development of novel diagnostic and therapeutic strategies, improving our ability to predict, prevent and treat obesity-related diseases.
Q: What question were you investigating?
We aimed to understand the circulating EV landscape and how it differed between obese and lean individuals. Our focus was on how the EV RNA cargo varies between obese and lean individuals and how integrating with large population-based genetic and transcriptomic databases can offer insights into obesity biology.
Q: What methods or approach did you use?
We optimized methods to culture adipose tissues explants from bariatric surgery for EV harvesting and isolation of circulating EVs and transcriptomic data generation. Computational innovations were made in collaboration with Dr. Ravi Shah and Dr. Eric Gamazon, both of Vanderbilt University Medical Center, to integrate EV transcriptomics with population ‘omics’, such as a genome-wide association study (GWAS), a transcriptome-wide association study (TWAS) and a phenome-wide association study (PheWAS).
Q: What did you find?
Our findings demonstrate that differences in EV-RNA in obesity are driven primarily by EVs released from adipose tissues, and that the RNAs within these EVs arise from different cell-types within adipose tissue. By using functional genomics approaches, we identify 282 transcripts (corresponding to 277 unique gene symbols) differentially expressed within circulating EVs between lean and obese individuals.
Q: What are the implications?
Our study outlines a method to integrate EV transcriptomics with large scale genetic studies. It also demonstrates that EV-RNAs, which are differentially expressed in obesity, are linked with genes associated with metabolic phenotypes, such as obesity and type 2 diabetes. These EV-RNAs represent regulatory elements and transcriptionally active genes in adipose tissue, and are associated with metabolic phenotypes.
Q: What are the next steps?
We are currently investigating how these EV transcripts change with weight loss (either induced by surgery or drugs, like GLP-1 agonists). We are also studying how adipose EVs signal to other cells, such as cardiac cells, liver cells and brain cells, to mediate obesity-related comorbidities. Our functional genomics study has yielded targets that may be used to treat some of these conditions.
Source:
Journal reference:
Chatterjee, E., et al. (2025). The extracellular vesicle transcriptome provides tissue-specific functional genomic annotation relevant to disease susceptibility in obesity. Cell Genomics. doi.org/10.1016/j.xgen.2025.100925.