Quantitative proteomic analysis of human peripheral nerves from subjects with type 2 diabetes

• Published in: Diabetic medicine Vol. 38; no. 11; pp. e14658 - n/a
• Main Authors: Ising, Erik, Åhrman, Emma, Thomsen, Niels O. B., Eriksson, Karl‐Fredrik, Malmström, Johan, Dahlin, Lars B.
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.11.2021
• Subjects: Aged; Biopsy; Clinical Medicine; Diabetes; diabetes mellitus; Diabetes mellitus (non-insulin dependent); Diabetes Mellitus, Type 2 - complications; Diabetes Mellitus, Type 2 - epidemiology; diabetic neuropathies; Diabetic Neuropathies - epidemiology; Diabetic Neuropathies - etiology; Electrophysiology; Endocrinology and Diabetes; Endokrinologi och diabetes; Feasibility studies; Female; Gene polymorphism; Humans; Incidence; Klinisk medicin; Male; Mass spectrometry; Mass spectroscopy; Medical and Health Sciences; Medicin och hälsovetenskap; Nervous system; Peripheral nerves; Peripheral Nerves - physiopathology; peripheral neuropathies; Peripheral neuropathy; Proteins; proteome; Proteomes; Proteomics; Proteomics - methods; Scientific imaging; Sural nerve; Sweden - epidemiology; type 2; Sweden; diabetic neuropathies; diabetes mellitus; type 2; peripheral neuropathies; proteome
• ISSN: 0742-3071; 1464-5491; 1464-5491
• DOI: 10.1111/dme.14658

Aims Diabetic peripheral neuropathy (DPN) is a common and severe complication to type 2 diabetes. The pathogenesis of DPN is not fully known, but several pathways and gene polymorphisms contributing to DPN are described. DPN can be studied using nerve biopsies, but studies on the proteome of the nerve itself, and its surrounding tissue as a whole, are lacking. Studies on the posterior interosseous nerve (PIN) have proposed PIN a useful indicator of DPN. Methods A quantitative mass spectrometry‐based proteomics analysis was made of peripheral nerves from age‐ and gender‐matched living human male tissue donors; nine type 2 diabetes subjects, with decreased sural nerve action potentials indicating DPN, and six controls without type 2 diabetes, with normal electrophysiology results. Results A total of 2617 proteins were identified. Linear regression was used to discover which proteins were differentially expressed between type 2 diabetes and controls. Only soft signals were found. Therefore, clustering of the 500 most variable proteins was made to find clusters of similar proteins in type 2 diabetes subjects and healthy controls. Conclusions This feasibility study shows, for the first time, that the use of quantitative mass spectrometry enables quantification of proteins from nerve biopsies from subjects with and without type 2 diabetes, which may aid in finding biomarkers of importance to DPN development.