Decoding Neural Metabolic Markers From the Carotid Sinus Nerve in a Type 2 Diabetes Model

Marina Cracchiolo, Joana F. Sacramento, Alberto Mazzoni, Alessandro Panarese, Jacopo Carpaneto, Silvia Conde, Silvestro Micera

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Recent studies showed that the carotid sinus nerve (CSN) and the sympathetic nervous system (SNS) are overactivated in type 2 diabetes and that restoring the correct CSN neural activity can re-establish the proper metabolism. However, a robust characterization of the relationship between CSN and SNS neural activities and metabolism in type 2 diabetes is still missing. Here, we investigated the relationship between neural activity of CSN and SNS in control rats and in rats with diet-induced type 2 diabetes and the animal condition during metabolic challenges. We found that the diabetic condition can be discriminated on the basis of CSN and SNS neural activities due to a high-frequency shift in both spectra. This shift is suppressed in the SNS in case of CSN denervation, confirming the role of CSN in driving sympathetic overactivation in type 2 diabetes. Interestingly, the Inter-Burst-Intervals (IBIs) calculated from CSN bursts strongly correlate with perturbations in glycaemia levels. This finding, held for both control and diabetic rats, indicates the possibility of detecting metabolic information from neural recordings even in pathological conditions. Our results suggest that CSN activity could serve as a marker to monitor glycaemic alterations and, therefore, it could be used for closed-loop control of CSN neuromodulation. This paves the way to the development of novel and effective bioelectronic therapies for type 2 diabetes.

Original languageEnglish
Pages (from-to)2034-2043
Number of pages10
JournalIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Volume27
Issue number10
DOIs
Publication statusPublished - 1 Oct 2019

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