Lipedema: The Use of Cultured Adipocytes for Identification of Diagnostic Markers.

BACKGROUND: Lipedema, diagnosed most often in women, is a progressive disease characterized by the disproportionate and symmetrical distribution of adipose tissue, primarily in the extremities. Although numerous results from in vitro and in vivo studies have been published, many questions regarding the pathology and genetic background of lipedema remain unanswered. METHODS: In this study, adipose tissue-derived stromal/stem cells were isolated from lipoaspirates derived from nonobese and obese donors with or without lipedema. Growth and morphology, metabolic activity, differentiation potential, and gene expression were evaluated using quantification of lipid accumulation, metabolic activity assay, live-cell imaging, reverse transcription polymerase chain reaction, quantitative polymerase chain reaction, and immunocytochemical staining. RESULTS: The adipogenic potential of lipedema and nonlipedema adipose tissue-derived stromal/stem cells did not rise in parallel with the donors' body mass index and did not differ significantly between groups. However, in vitro differentiated adipocytes from nonobese lipedema donors showed significant upregulation of adipogenic gene expression compared with nonobese controls. All other genes tested were expressed equally in lipedema and nonlipedema adipocytes. The adiponectin/leptin ratio was significantly reduced in adipocytes from obese lipedema donors compared with their nonobese lipedema counterparts. Increased stress fiber-integrated smooth muscle actin was visible in lipedema adipocytes compared with nonlipedema controls and appeared enhanced in adipocytes from obese lipedema donors. CONCLUSIONS: Not only lipedema per se but also body mass index of donors affect adipogenic gene expression substantially in vitro. The significantly reduced adiponectin/leptin ratio and the increased occurrence of myofibroblast-like cells in obese lipedema adipocyte cultures underscores the importance of attention to the co-occurrence of lipedema and obesity. These are important findings toward accurate diagnosis of lipedema. CLINICAL RELEVANCE STATEMENT: Our study highlights not only the difficulty in lipedema diagnostics but also the tremendous need for further studies on lipedema tissue. Although lipedema might seem to be an underestimated field in plastic and reconstructive surgery, the power it holds to provide better treatment to future patients can not be promoted enough.

EVAnalyzer: High content imaging for rigorous characterisation of single extracellular vesicles using standard laboratory equipment and a new open-source ImageJ/Fiji plugin.

Extracellular vesicle (EV) research increasingly demands for quantitative characterisation at the single vesicle level to address heterogeneity and complexity of EV subpopulations. Emerging, commercialised technologies for single EV analysis based on, for example, imaging flow cytometry or imaging after capture on chips generally require dedicated instrumentation and proprietary software not readily accessible to every lab. This limits their implementation for routine EV characterisation in the rapidly growing EV field. We and others have shown that single vesicles can be detected as light diffraction limited fluorescent spots using standard confocal and widefield fluorescence microscopes. Advancing this simple strategy into a process for routine EV quantitation, we developed 'EVAnalyzer', an ImageJ/Fiji (Fiji is just ImageJ) plugin for automated, quantitative single vesicle analysis from imaging data. Using EVAnalyzer, we established a robust protocol for capture, (immuno-)labelling and fluorescent imaging of EVs. To exemplify the application scope, the process was optimised and systematically tested for (i) quantification of EV subpopulations, (ii) validation of EV labelling reagents, (iii) in situ determination of antibody specificity, sensitivity and species cross-reactivity for EV markers and (iv) optimisation of genetic EV engineering. Additionally, we show that the process can be applied to synthetic nanoparticles, allowing to determine siRNA encapsulation efficiencies of lipid-based nanoparticles (LNPs) and protein loading of SiO2 nanoparticles. EVAnalyzer further provides a pipeline for automated quantification of cell uptake at the single cell-single vesicle level, thereby enabling high content EV cell uptake assays and plate-based screens. Notably, the entire procedure from sample preparation to the final data output is entirely based on standard reagents, materials, laboratory equipment and open access software. In summary, we show that EVAnalyzer enables rigorous characterisation of EVs with generally accessible tools. Since we further provide the plugin as open-source code, we expect EVAnalyzer to not only be a resource of immediate impact, but an open innovation platform for the EV and nanoparticle research communities.