A new study has created the first single-cell map of how DNA is regulated and organized inside different cell-types of human fat tissue. The research shows that many genetic risk factors for abdominal obesity reside in epigenomic regions of fat cells, offering clues about how body fat is genetically and epigenetically regulated and how it might be better controlled. The study, by co-first authors Zeyuan (Johnson) Chen and Sankha Subhra Das , is published in Nature Genetics.
Why it matters
Excess belly fat is strongly linked to cardiometabolic diseases like type 2 diabetes and heart disease. While scientists have identified genetic variants associated with the increased risk of these common conditions, it wasn't clear what types of epigenomic regulatory mechanisms drive the risk in cells. This study helps annotate the genome through the lens of epigenomic regulation in fat tissue cell-types, especially in the mature fat cells, shedding light on cell-type level regulatory mechanisms underlying obesity in human fat tissue.
What the study did
Researchers analyzed cells isolated from adult fat tissue using single-cell technologies that examine how the DNA strands fold and loop inside the nucleus (3D genome structure) and how methyl groups attach to them (DNA methylation) to turn on or off gene expression. They looked at more than 36,075 individual cells to build a detailed map of expression and epigenomic regulation profiles in different types of cells in fat tissue. They then compared this map with regions known to harbor genetic risk for abdominal obesity.
What they found
- As adipocytes, the key fat-storing cells, mature, their DNA reorganizes in 3D space. The study reveals the regional architecture of this 3D space throughout the human genome in fat tissue cell-types, pinpointing key regulatory sites of the genome with genes active in adipocytes, such as ADIPOQ, LEP, and SREBF1.
- The investigators found that most known obesity-linked genetic variants are located in the large epigenomic regulatory stretches (megabases in length) of the fat cell chromosomes identified in this study.
- At a finer resolution, these obesity risk variants preferentially reside in shorter spans of DNA loci (hundreds of base pairs), acting like knobs to fine-tune the expression level of genes essential for adipocyte function.
What's next
Future studies will test whether manipulating those epigenetic marks affects adipocyte behavior in vitro or in animal models. Targeted epigenome editing could validate whether altering methylation or chromatin loops rescues metabolic dysfunction. This unique single-cell epigenome atlas also paves the way for disentangling the epigenomic profiles from fat tissue, elucidating the underlying cellular composition and its links to human disease. In the long term, it can advance precision medicine by facilitating the identification of adipocyte-specific biomarkers and therapies for cardiometabolic diseases, all tailored to an individual's unique genomic and epigenomic signature.
From the experts
"By working at single-cell resolution, we can pinpoint the cell types where obesity risk is written in the epigenome," said the study's corresponding author Paivi Pajukanta, MD, PhD , professor of Human Genetics at the David Geffen School of Medicine at UCLA. "This gives us an epigenomic roadmap for functionally studying how genetic risk of obesity impacts fat cell biology."
About the study.
Single cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue links partitioned polygenic risk of abdominal obesity to SAT cell types. Nature Genetics 2025 DOI: 10.1038/s41588-025-02300-4 .
Study authors: Zeyuan Johnson Chen, Sankha Subhra Das, Asha Kar, Seung Hyuk T. Lee, Kevin D. Abuhanna, Marcus Alvarez, Mihir G. Sukhatme, Zitian Wang, Kyla Z. Gelev, Matthew G. Heffel, Yi Zhang, Oren Avram, Elior Rahmani, Sriram Sankararaman, Eran Halperin, Chongyuan Luo, Päivi Pajukanta (UCLA), Markku Laakso (University of Eastern Finland and Kuopio University Hospital), Sini Heinonen, Kirsi H. Pietiläinen (University of Helsinki), Hilkka Peltoniemi (Eira Hospital, Helsinki)
Funding and Disclosures
This study was supported by NIH grants (grant nos. R01HL170604 to P.P., R01DK132775 to P.P., and R01HG010505 to E.H. and P.P.); Research Council of Finland (grant nos. 266286, 272376, 314383, and 335443 to K.H.P.); Finnish Medical Foundation; Gyllenberg Foundation; Novo Nordisk Foundation (grant nos. NNF20OC0060547, NNF17OC0027232, and NNF10OC1013354 to K.H.P.); Finnish Diabetes Research Foundation; Paulo Foundation; Sigrid Jusélius Foundation; University of Helsinki and Helsinki University Hospital; and Government Research Funds. This research was conducted using the UK Biobank Resource under application number 33934. This work uses data provided by patients and collected by the NHS as part of their care and support.
The authors declare no competing interests.
