Cell and transcriptomic diversity of infrapatellar fat pad during knee osteoarthritis.

Abstract

Objectives: In this study, we employ a multiomic approach to identify major cell types and subsets, and their transcriptomic profiles within the infrapatellar fat pad (IFP), and to determine differences in the IFP based on knee osteoarthritis (KOA), sex and obesity status.

Methods: Single-nucleus RNA sequencing of 82 924 nuclei from 21 IFPs (n=6 healthy control and n=15 KOA donors), spatial transcriptomics and bioinformatic analyses were used to identify contributions of the IFP to KOA. We mapped cell subclusters from other white adipose tissues using publicly available literature. The diversity of fibroblasts within the IFP was investigated by bioinformatic analyses, comparing by KOA, sex and obesity status. Metabolomics was used to further explore differences in fibroblasts by obesity status.

Results: We identified multiple subclusters of fibroblasts, macrophages, adipocytes and endothelial cells with unique transcriptomic profiles. Using spatial transcriptomics, we resolved distributions of cell types and their transcriptomic profiles and computationally identified putative cell-cell communication networks. Furthermore, we identified transcriptomic differences in fibroblasts from KOA versus healthy control donor IFPs, female versus male KOA-IFPs and obese versus normal body mass index (BMI) KOA-IFPs. Finally, using metabolomics, we defined differences in metabolite levels in supernatants of naïve, profibrotic stimuli-treated and proinflammatory stimuli-treated fibroblasts from obese compared to normal BMI KOA-IFPs.

Conclusions: Overall, by employing a multiomic approach, this study provides the first comprehensive map of the cellular and transcriptomic diversity of human IFP and identifies IFP fibroblasts as key cells contributing to transcriptomic and metabolic differences related to KOA disease, sex or obesity.