AHA_Obesity-SFRN-related data
Description
Title Source data for the AHA SFRN final report: adipose- and liver-derived extracellular vesicles in obesity and MASLD alter cardiomyocyte, cardiac fibroblast and macrophage phenotypes Description This dataset contains the source data behind the figures of the American Heart Association Strategically Focused Research Network (SFRN) final report. The project studied how extracellular vesicles (EVs) released in obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) affect the heart. (1) Obesity EVs. EVs were isolated by size-exclusion chromatography from the plasma of lean and obese subjects and from visceral adipose tissue (VAT) culture supernatant. Files include particle size and concentration (Fig 2A), uncropped Western blots (Fig 2B), and TEM images (Fig 2C). They also include per-sample counts and DESeq2 results for 282 EV transcripts that differ between lean (n=6) and obese (n=9) plasma (Fig 2D–F). A further table links these genes to adipose-specific regulatory SNPs with GWAS statistics and mouse knockout phenotypes (Fig 3–4; full analyses in doi:10.1016/j.xgen.2025.100925). (2) MASLD EVs. EVs from a humanized liver-on-chip under control or fatty-acid (MASLD) conditions were applied to iPSC-derived cardiomyocytes. Files include cardiomyocyte RNA-seq (7,486 DEGs at FDR<0.05; Fig 5C) and amino acid and media metabolomics (Fig 5D). They also include per-ROI single-molecule localization microscopy of the chip effluent EVs with statistics (Fig 6A), and hepatocyte-EV miRNA differential expression, which is also the source of the pathway enrichment in Fig 6C (Fig 6B–C). (3) Functional effects of adipose EVs. Action potential durations of iPSC-derived ventricular and atrial myocytes treated with lean vs obese plasma EVs, or with VAT EVs from 4 donors vs control EVs (Fig 8–9). An early-afterdepolarization trace first published in doi:10.1016/j.jacbts.2026.101577 (Fig 10). Fibroblast fibrosis-gene qPCR and collagen secretion (Fig 11B–C), and macrophage M1/M2 marker qPCR (Fig 12B). All tables contain individual-level values. Human samples are identified only by study codes. README.txt maps each file to its figure panel, and DataDictionary_SFRN_EV.xlsx defines every variable and unit.
Files
Steps to reproduce
EV isolation and characterization (Fig 2A–C): Isolate EVs from plasma and VAT culture supernatant by size-exclusion chromatography. Measure size and concentration on a Spectradyne nCS1 (C400 cartridge, 65–400 nm). Run Western blots for CD63, CD81, TSG101, Alix, Perilipin 1 and 58K Golgi protein, and image by TEM. EV RNA-seq (Fig 2D–F): Run DESeq2 on the counts in Fig02DEF_…xlsx, obese vs lean. Call DEGs at padj ≤ 0.1 and |fold change| ≥ 1.5, which gives the 282 transcripts. Use those DEGs for the volcano plot, clustering and PCA. Genetic annotation (Fig 3–4): Intersect adipose-specific regulatory elements in Hi-C contact with the DEGs with BMI and T2D GWAS and PheWAS, using the code at doi:10.5281/zenodo.15492519. Liver-on-chip (Fig 5–6): Treat iPSC-CMs with control or MASLD (fatty acid) liver-on-chip EVs, then run RNA-seq with DESeq2 at FDR<0.05 and amino acid and media metabolomics. For SMLM, capture EVs with CD9/CD63/CD81 antibodies, image on a Nikon N-STORM, and cluster in SEVEN (MATLAB). Compare groups with Brown-Forsythe/Welch ANOVA and Dunnett’s T3. Analyze the miRNA DESeq2 output for pathway enrichment. Electrophysiology (Fig 8–10): Load cells with FluoVolt dye, image at 95 frames/s during 1 Hz pacing (Vala Kinetic Imaging Cytometry), extract intensity in ImageJ and calculate APD in MATLAB. Fibroblasts and macrophages (Fig 11–12): Run RT-qPCR with 2^-ΔΔCt, normalized to GAPDH for fibroblasts and RPS18 for macrophages. Measure collagen with the Sirius Red kit (Amsbio 9062). Statistics: Each data file contains the individual values for its panel, so every figure can be re-plotted and re-tested directly.
Institutions
- Massachusetts General HospitalMassachusetts, Boston
Categories
Funders
- National Human Genome Research InstituteNational Institutes of HealthMaryland, BethesdaGrant ID: R35HG010718 , R01HG011138
- National Center for Advancing Translational SciencesNational Institutes of HealthMaryland, RockvilleGrant ID: UH3 TR002878
- National Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthMaryland, BethesdaGrant ID: U01DK140952, RC2 DK116691
- National Institute of General Medical SciencesNational Institutes of HealthMaryland, BethesdaGrant ID: R01GM140287
- National Heart, Lung, and Blood InstituteNational Institutes of HealthMaryland, BethesdaGrant ID: 1R35HL150807-01