BACKGROUND While most hypertriglyceridemia is asymptomatic, hypertriglyceridemia-associated acute pancreatitis (HTG-AP) can be more severe than AP of other etiologies. The reasons underlying this are unclear. We thus examined whether lipolytic generation of nonesterified fatty acids (NEFAs) from circulating triglycerides (TGs) could worsen clinical outcomes.METHODS Admission serum TGs, NEFA composition, and concentrations were analyzed prospectively for 269 patients with AP. These parameters, demographics, and clinical outcomes were compared between HTG-AP (TGs >500 mg/dL; American Heart Association [AHA] 2018 guidelines) and AP of other etiologies. Serum NEFAs were correlated with serum TG fatty acids (TGFAs) alone and with the product of TGFA serum lipase (NEFAs – TGFAs × lipase). Studies in mice and rats were conducted to understand the role of HTG lipolysis in organ failure and to interpret the NEFA-TGFA correlations.RESULTS Patients with HTG-AP had higher serum NEFA and TG levels and more severe AP (19% vs. 7%; P < 0.03) than did individuals with AP of other etiologies. Correlations of long-chain unsaturated NEFAs with corresponding TGFAs increased with TG concentrations up to 500 mg/dL and declined thereafter. However, NEFA – TGFA × lipase correlations became stronger with TGs above 500 mg/dL. AP and intravenous lipase infusion in rodents caused lipolysis of circulating TGs to NEFAs. This led to multisystem organ failure, which was prevented by pancreatic TG lipase deletion or lipase inhibition.CONCLUSIONS HTG-AP is made severe by the NEFAs generated from intravascular lipolysis of circulating TGs. Strategies that prevent TG lipolysis may be effective in improving clinical outcomes for patients with HTG-AP.FUNDING National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK, NIH) (RO1DK092460 and R01DK119646); Department of Defense (PR191945 under W81XWH-20-1-0400); National Institute on Alcohol Abuse and Alcoholism (NIAAA), NIH (R01AA031257).
Prasad Rajalingamgari, Biswajit Khatua, Megan J. Summers, Sergiy Kostenko, Yu-Hui H. Chang, Mohamed Elmallahy, Arti Anand, Anoop Narayana Pillai, Mahmoud Morsy, Shubham Trivedi, Bryce McFayden, Sarah Jahangir, Christine L.H. Snozek, Vijay P. Singh
Usage data is cumulative from November 2024 through October 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 4,066 | 605 |
1,260 | 171 | |
Figure | 424 | 1 |
Table | 87 | 0 |
Supplemental data | 360 | 17 |
Citation downloads | 111 | 0 |
Totals | 6,308 | 794 |
Total Views | 7,102 |
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.