Impact of Plasma Xanthine Oxidoreductase Activity on the Mechanisms of Distal Symmetric Polyneuropathy Development in Patients with Type 2 Diabetes

To unravel associations between plasma xanthine oxidoreductase (XOR) and diabetic vascular complications, especially distal symmetric polyneuropathy (DSP), we investigated plasma XOR activities using a novel assay. Patients with type 2 diabetes mellitus (T2DM) with available nerve conduction study (NCS) data were analyzed. None were currently taking XOR inhibitors. XOR activity of fasting blood samples was assayed using a stable isotope-labeled substrate and LC-TQMS. JMP Clinical version 5.0. was used for analysis. We analyzed 54 patients. Mean age was 64.7 years, mean body mass index was 26.0 kg/m2, and mean glycated hemoglobin was 9.4%. The logarithmically transformed plasma XOR activity (ln-XOR) correlated positively with hypoxanthine, xanthine, visceral fatty area, and liver dysfunction but negatively with HDL cholesterol. ln-XOR correlated negatively with diabetes duration and maximum intima-media thickness. Stepwise multiple regression analysis revealed ln-XOR to be among selected explanatory factors for various NCS parameters. Receiver operating characteristic curves showed the discriminatory power of ln-XOR. Principal component analysis revealed a negative relationship of ln-XOR with F-waves as well as positive relationships of ln-XOR with hepatic steatosis and obesity-related disorders. Taken together, our results show plasma XOR activity to be among potential disease status predictors in T2DM patients. Plasma XOR activity measurements might reliably detect pre-symptomatic DSP.

Association of Cardiovascular Autonomic Neuropathy and Distal Symmetric Polyneuropathy with All-Cause Mortality: A Retrospective Cohort Study

Background. People with diabetic cardiovascular autonomic neuropathy (CAN) have increased cardiovascular mortality. However, the association between distal symmetric polyneuropathy (DSPN) or CAN with all-cause mortality is much less investigated. Thus, we set out to examine the effect of CAN and DSPN on all-cause mortality in a well-phenotyped cohort. Methods. All diabetes cases ( n = 1,347 ) from the catchment area of a secondary diabetes care centre who had medical examination including neuropathy assessment between 1997 and 2016 were followed up for all-cause mortality in the NHS Hungary reimbursement database until 2018. We investigated the association of CAN (Ewing tests) and DSPN (Neurometer) with all-cause mortality using Cox models stratified by diabetes type. Results. Altogether, n = 131 / 1,011 persons with type 1/type 2 diabetes were included. Of the participants, 53%/43% were male, mean age was 46 ± 12 / 64 ± 10 years, diabetes duration was 13 ± 10 / 7 ± 8 years, 42%/29% had CAN, and 39%/37% had DSPN. During the 9 ± 5 / 8 ± 5 -year follow-up, n = 28 / 494 participants died. In fully adjusted models, participants with type 1 diabetes patients with versus without DSPN had an increased mortality (HR 2.99, 95% CI 1.4-8.63), while no association with CAN was observed. In type 2 diabetes, both DSPN and CAN independently increased mortality (HR 1.32, 95% CI: 1.07-1.64, and HR 1.44, 95% CI: 1.17-1.76). Conclusions. Our results are compatible with an increased risk of mortality in people with type 1 diabetes and DSPN. Furthermore, we report a similarly strong association between DSPN and CAN and all-cause mortality in type 2 diabetes mellitus.

Painful and non-painful diabetic neuropathy, diagnostic challenges and implications for future management

Peripheral neuropathy is one of the most common complications of both type 1 and type 2 diabetes. Up to half of patients with diabetes develop neuropathy during the course of their disease, which is accompanied by neuropathic pain in to 30–40% of cases. Peripheral nerve injury in diabetes can manifest as progressive distal symmetric polyneuropathy, autonomic neuropathy, radiculo-plexopathies, and mononeuropathies. The most common diabetic neuropathy is distal symmetric polyneuropathy, which we will refer to as DN, with its characteristic glove and stocking like presentation of distal sensory or motor function loss. DN or its painful counterpart, painful DN, are associated with increased mortality and morbidity; thus, early recognition and preventive measures are essential. Nevertheless, it is not easy to diagnose DN or painful DN, particularly in patients with early and mild neuropathy, and there is currently no single established diagnostic gold standard. The most common diagnostic approach in research is a hierarchical system, which combines symptoms, signs, and a series of confirmatory tests. The general lack of long-term prospective studies has limited the evaluation of the sensitivity and specificity of new morphometric and neurophysiological techniques. Thus, the best paradigm for screening DN and painful DN both in research and in clinical practice remains uncertain. Herein, we review the diagnostic challenges from both clinical and research perspectives and their implications for managing patients with DN. There is no established DN treatment, apart from improved glycemic control, which is more effective in type 1 than in type 2 diabetes, and only symptomatic management is available for painful DN. Currently, less than one third of painful DN patients derive sufficient pain relief with existing pharmacotherapies. A more precise and distinct sensory profile from patients with DN and painful DN may help identify responsive patients to one treatment versus another. Detailed sensory profiles will lead to tailored treatment for patient subgroups with painful DN by matching to novel or established DN pathomechanisms and also for improved clinical trials stratification. Large randomized clinical trials are needed to identify the interventions, i.e. pharmacological, physical, cognitive, educational, etc, which leads to the best therapeutic outcomes.

Distal Symmetric Polyneuropathy Identification in Type 2 Diabetes Subjects: A Random Forest Approach

The prevalence of diabetes mellitus is increasing worldwide, causing health and economic implications. One of the principal microvascular complications of type 2 diabetes is Distal Symmetric Polyneuropathy (DSPN), affecting 42.6% of the population in Mexico. Therefore, the purpose of this study was to find out the predictors of this complication. The dataset contained a total number of 140 subjects, including clinical and paraclinical features. A multivariate analysis was constructed using Boruta as a feature selection method and Random Forest as a classification algorithm applying the strategy of K-Folds Cross Validation and Leave One Out Cross Validation. Then, the models were evaluated through a statistical analysis based on sensitivity, specificity, area under the curve (AUC) and receiving operating characteristic (ROC) curve. The results present significant values obtained by the model with this approach, presenting 67% of AUC with only three features as predictors. It is possible to conclude that this proposed methodology can classify patients with DSPN, obtaining a preliminary computer-aided diagnosis tool for the clinical area in helping to identify the diagnosis of DSPN.