Back

Adipose tissue-derived fibroblasts engage in immune-stromal crosstalk during obesity-aggravated atherosclerosis in mice

Mikkola, L.; Boluk, A.; Piipponen, M.; Mikocziova, I.; Valkonen, M.; Fagersund, J.; Hakovirta, H.; Saraste, A.; Hernandez de Sande, A.; Palani, S.; Ord, T.; Roivainen, A.; Ruusuvuori, P.; Heinaniemi, M.; Kaikkonen, M. U.; Lonnberg, T.

2025-09-05 genomics
10.1101/2025.09.02.673686 bioRxiv
Show abstract

Atherosclerosis involves changes in the vascular wall and surrounding perivascular adipose tissue, yet the cellular contributors to disease progression remain incompletely understood. Obesity exacerbates atherogenesis, but the cell types driving this aggravation are unclear. We aimed to define the key cell populations across tissues in a highly atherogenic mouse model under obese and normal-weight conditions and to identify obesity-associated cellular changes. We employed 5 single-cell RNA sequencing combined with antibody staining in Ldlr-/-Apob100/100 male mice fed either a high-fat or control diet. Aorta, perivascular and epididymal adipose tissues, and spleen were analyzed, with CD45 enrichment of aortic samples and CITE-seq using a 138-antibody panel. Key findings were validated in mice by immunohistochemistry and multiplexed immunofluorescence and explored in human aorta and carotid arteries using spatial transcriptomics. Analysis of [~]46,000 cells enabled characterization of cell states, gene enrichment, regulon activity, and inferred interactions. Adipose-derived fibroblast subsets displayed immune-associated transcriptional programs in obesity. Pi16 progenitor fibroblasts were reduced alongside marked PVAT remodeling, and the top mouse differentially expressed genes exhibited clear spatial patterning in human arteries.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.