Pterostilbene Burns Muscle Fat by Stabilizing PPARδ — SkimNews
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- Shinshu University researchers identified pterostilbene — a polyphenol in blueberries and grapes — as the strongest fat-reducing compound when screening food-derived phytochemicals on cultured C2C12 mouse skeletal muscle cells, while treated cells continued to grow and differentiate normally.
- The compound increased glycerol release outside the cells and boosted expression of genes involved in fatty acid oxidation, indicating stored lipids were being broken down for energy rather than blocked from entering the cells in the first place.
- Pterostilbene works by preventing PPARδ protein degradation through the ubiquitin-proteasome pathway, allowing more of the receptor to remain available — a mechanism distinct from experimental compounds that bind directly to PPARδ to activate it.
- The study was led by Associate Professor Takakazu Mitani of Shinshu University and published in Volume 83 of the Food Bioscience journal on September 1, 2026.
- Dr. Mitani said the findings establish a scientific framework for developing functional foods and nutritional supplements targeting muscle fat metabolism, and for screening other natural compounds that stabilize the PPARδ protein.
- Results are limited to cultured mouse cells; in vivo studies remain necessary to evaluate whether pterostilbene's effects translate to animals and humans for conditions including obesity, type 2 diabetes, and age-related metabolic decline.
- The research targets myosteatosis — excess lipid droplet accumulation inside skeletal muscle driven by high-fat diets, inactivity, and aging — for which the researchers note there are currently no approved treatments.
Why it matters: No approved treatments exist for myosteatosis, the intramuscular fat buildup linked to insulin resistance and aging, and this study points to a previously unexplored mechanism — protein stabilization rather than direct receptor binding — giving the food and supplement industry a concrete screening target even as animal and human data remain years away.
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