Peripheral neuropathy is a frequent complication of type 2 diabetes mellitus (T2DM). We investigated whether human islet amyloid polypeptide (hIAPP), which forms pathogenic aggregates that damage pancreatic islet β cells in T2DM, is involved in T2DM-associated peripheral neuropathy. In vitro, hIAPP incubation with sensory neurons reduced neurite outgrowth and increased levels of mitochondrial reactive oxygen species. hIAPP-transgenic mice, which have elevated plasma hIAPP levels without hyperglycemia, developed peripheral neuropathy as evidenced by pain-associated behavior and reduced intraepidermal nerve fiber (IENF) density. Similarly, hIAPP Ob/Ob mice, which have hyperglycemia in combination with elevated plasma hIAPP levels, had signs of neuropathy, although more aggravated. In wild-type mice, intraplantar and intravenous hIAPP injections induced long-lasting allodynia and decreased IENF density. Non-aggregating murine IAPP, mutated hIAPP (pramlintide), or hIAPP with pharmacologically inhibited aggregation did not induce these effects. T2DM patients had reduced IENF density and more hIAPP oligomers in the skin compared with non-T2DM controls. Thus, we provide evidence that hIAPP aggregation is neurotoxic and mediates peripheral neuropathy in mice. The increased abundance of hIAPP aggregates in the skin of T2DM patients supports the notion that hIAPP is a potential contributor to T2DM neuropathy in humans.
Mohammed M.H. Albariqi, Sabine Versteeg, Elisabeth M. Brakkee, J. Henk Coert, Barend O.W. Elenbaas, Judith Prado, C. Erik Hack, Jo W.M. Höppener, Niels Eijkelkamp
Usage data is cumulative from December 2023 through December 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 983 | 488 |
193 | 172 | |
Figure | 344 | 11 |
Table | 54 | 0 |
Supplemental data | 66 | 7 |
Citation downloads | 72 | 0 |
Totals | 1,712 | 678 |
Total Views | 2,390 |
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.