Study Suggests Potassium Sorbate Could Cause Kidney Injury

Potassium sorbate, a widely used preservative in processed foods and beverages, is typically classified as safe, but a recent study suggests that long-term or high-level exposure may pose health risks. In new research published in iMetaMed, scientists presented evidence that potassium sorbate can induce acute kidney injury through mechanisms involving oxidative stress, inflammation, and altered cell communication.

The research team—based at Shanghai Jiao Tong University School of Medicine and Guangdong Medical University—applied a multi-disciplinary strategy to uncover how potassium sorbate damages renal tissue. They began by predicting potential targets using network toxicology, then validated interactions through molecular docking and dynamics simulations. Machine learning algorithms further prioritized key genes from clinical datasets.

Amyloid precursor protein (APP) was identified as a major regulator among these genes. Single-cell RNA sequencing on human kidney tissue revealed that APP supports communication between endothelial cells and immune cells—like monocytes and natural killer cells—via APP-CD74 and APP-PTGER2 ligand-receptor pairs. Corresponding author Dr. Meng-Yao Li explained, “This is the first time that APP has been implicated in potassium sorbate-induced kidney injury, and the first evidence that it facilitates endothelial-immune crosstalk in a toxicological context.” According to the authors, “Our findings provide a cellular mechanism that helps explain how a common food additive could trigger renal inflammation and functional decline.”

Laboratory experiments with human renal tubular cells confirmed that potassium sorbate decreases cell viability, hampers cell migration (a repair process), and increases APP protein expression, all in a dose-dependent way. Additional targets noted were MMP9 and SIRT1, with links to lipid metabolism, atherosclerosis, and the AGE–RAGE pathway, which are established features of kidney disease development.

The authors conclude that these results sharpen the understanding of food additive safety and highlight a new strategy for investigating environmental toxin risks by blending computational prediction with experimental validation.