Usage Information
Abstract
BACKGROUND. Accumulation of diacylglycerol (DAG) and sphingolipids is thought to promote skeletal muscle insulin resistance by altering cellular signaling specific to their location. However,the subcellular localization of bioactive lipids in human skeletal muscle is largely unknown. METHODS. We evaluated subcellular localization of skeletal muscle DAGs and sphingolipids in lean individuals (n = 15), endurance-trained athletes (n = 16), and obese men and women with (n = 12) and without type 2 diabetes (n = 15). Muscle biopsies were fractionated into sarcolemmal, cytosolic, mitochondrial/ER, and nuclear compartments. Lipids were measured using liquid chromatography tandem mass spectrometry, and insulin sensitivity was measured using hyperinsulinemic-euglycemic clamp. RESULTS. Sarcolemmal 1,2-DAGs were not significantly related to insulin sensitivity. Sarcolemmal ceramides were inversely related to insulin sensitivity, with a significant relationship found for the C18:0 species. Sarcolemmal sphingomyelins were also inversely related to insulin sensitivity, with the strongest relationships found for the C18:1, C18:0, and C18:2 species. In the mitochondrial/ER and nuclear fractions, 1,2-DAGs were positively related to, while ceramides were inversely related to, insulin sensitivity. Cytosolic lipids as well as 1,3-DAG, dihydroceramides, and glucosylceramides in any compartment were not related to insulin sensitivity. All sphingolipids but only specific DAGs administered to isolated mitochondria decreased mitochondrial state 3 respiration. CONCLUSION. These data reveal previously unknown differences in subcellular localization of skeletal muscle DAGs and sphingolipids that relate to whole-body insulin sensitivity and mitochondrial function in humans. These data suggest that whole-cell concentrations of lipids obscure meaningful differences in compartmentalization and suggest that subcellular localization of lipids should be considered when developing therapeutic interventions to treat insulin resistance. FUNDING. National Institutes of Health General Clinical Research Center (RR-00036), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (R01DK089170), NIDDK (T32 DK07658), and Colorado Nutrition Obesity Research Center (P30DK048520).
Authors
Leigh Perreault, Sean A. Newsom, Allison Strauss, Anna Kerege, Darcy E. Kahn, Kathleen A. Harrison, Janet K. Snell-Bergeon, Travis Nemkov, Angelo D’Alessandro, Matthew R. Jackman, Paul S. MacLean, Bryan C. Bergman
Usage data is cumulative from December 2024 through December 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 1,142 | 265 |
| 122 | 83 | |
| Figure | 552 | 42 |
| Table | 80 | 0 |
| Supplemental data | 49 | 3 |
| Citation downloads | 97 | 0 |
| Totals | 2,042 | 393 |
| Total Views | 2,435 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
