This is the first validation study of DN4 for painful diabetic polyneuropathy, which supports its usefulness as both a screening tool for neuropathic pain in diabetes and a reliable component of the diagnostic work up for painful diabetic polyneuropathy.

MicroRNAs are small single-stranded molecules that have emerged as important genomic regulators in different pathways. Different studies have shown that they are implicated in the metabolism and glucose homeostasis, and therefore, they could also be involved in the pathogenesis of metabolic disorders such as type 2 diabetes (T2DM). The aim of this study was to verify whether genetic variations in candidate microRNA (miRNA or miR) genes could contribute to T2DM susceptibility. We have selected 13 miRNAs as candidate loci according to literature data and to a computational analysis. MicroRNA genes were analyzed by direct sequencing in a cohort of 163 Italian T2DM patients and 185 healthy controls. We identified 6 novel variants never described before and 9 SNPs already described in databases. Five newly identified variants were found only in the cases group. We performed a case/control association study to test the associations of particular alleles/genotypes of identified SNPs with the disease. Two polymorphisms were associated with T2DM susceptibility: in particular, the G allele of rs895819 in hsa-mir-27a has shown a significantly protective effect (OR = 0.58 and P = 0.008), while the G allele of rs531564 in hsa-mir-124a appears to be a risk allele (OR = 2.15, P = 0.008). This is the first report indicating that genetic polymorphisms in miRNA regions could contribute to T2DM susceptibility.

Neuropad is a reliable diagnostic tool for both CAN and DPN, albeit of only moderate accuracy. Extending the observation period to 15 min provides greater diagnostic usefulness.

COMPASS 31 can represent a valid, easy-to-use, quantitative assessment tool for autonomic symptoms in diabetic neuropathy, with a fair diagnostic accuracy for both cardiovascular autonomic neuropathy and diabetic polyneuropathy.

Type 2 diabetes (T2DM) is a complex disease resulting from the contribution of both environmental and genetic factors. Recently, the list of genes implicated in the susceptibility to T2DM has substantially grown, also as a consequence of the great development of the genome-wide association studies in the last decade. Common polymorphisms in TCF7L2 gene have shown to have a strong effect with respect to many other involved genes. The aims of our study were to confirm the role of TCF7L2 in the susceptibility to T2DM in the Italian population and to investigate whether TCF7L2 genotypes also contribute to the clinical phenotypes variability and to diabetic complications development. Three TCF7L2 polymorphisms (rs7903146, rs7901695 and rs12255372) have been analyzed by allelic discrimination assays in a cohort of 154 Italian patients with T2DM and 171 healthy controls. A case-control association study and a genotype-phenotype correlation study have been carried out. Consistent with previous studies, all three SNPs showed a strong association with susceptibility to T2DM, both at genotypic (P = 0.003, P = 0.004 and P = 0.012) and at allelic level (P = 0.0004, P = 0.0004 and P = 0.003). Moreover, we observed associations between TCF7L2 variants and the following diabetic complications: diabetic retinopathy, cardiovascular disease and coronary artery disease. We also found a strong correlation between the rs7903146 and the presence of cardiovascular autonomic neuropathy (P = 0.02 with a high OR = 8.28). In conclusion, our study, in addition to confirming the involvement of TCF7L2 gene in the T2DM susceptibility, has shown that TCF7L2 genetic variability also contributes to the development of diabetic complications such as retinopathy and cardiovascular autonomic neuropathy.

Diabetic polyneuropathy (DPN) and cardiovascular autonomic neuropathy (CAN) are common type 2 diabetes complications with a large inter-individual variability in terms of clinical manifestations and severity. Our aim was to evaluate a possible involvement of genetic polymorphisms in miRNA regions in the susceptibility to DPN and CAN. Nine polymorphisms in miRNA genes were studied in a sample of 132 type 2 diabetes patients (T2D) analysed for DPN and 128 T2D patients analysed for CAN. A genotype-phenotype correlation analysis was performed. The T allele of rs11888095 single nucleotide polymorphism (SNP) in MIR128a was significantly associated with a higher risk (ORadj = 4.89, P adj = 0.02), whereas the C allele of rs2910164 SNP in MIR146a was associated with a lower risk to develop DPN (ORadj = 0.49, P adj = 0.09), respectively. A multivariate logistic regression analysis confirmed that both SNPs contribute to DPN (p < 0.001 and p = 0.01 for MIR128a and MIR146a, respectively). MIR128a SNP significantly contributed also to DPN score (p = 0.026). Rs895819 SNP in MIR27a was significantly associated with a higher risk to develop early CAN (P adj = 0.023 and ORadj = 3.43). The rs2910164 SNP in MIR146a showed a protective effect respect to early CAN (P adj = 0.052, ORadj = 0.32) and to confirmed CAN (P adj = 0.041, ORadj = 0.13). The same SNP resulted significantly associated with a lower CAN score and a higher E/I (p = 0.002 and p = 0.003, respectively). In conclusion, we described associations of MIR128a and MIR146a SNPs with DPN susceptibility and of MIR146a and MIR27a SNPs with CAN susceptibility. This is the first study showing that genetic variability in miRNA genes could be involved in diabetic neuropathies susceptibility.

BMI and sensorimotor deficits were the main determinants of PDPN and, as a novel finding, neuropathic pain intensity was related to the degree of neuropathy deficits. Thus, some peculiarity exists in metabolic correlates of diabetic neuropathic pain compared to insensate neuropathy but painfulness can still coexist with insensitivity.

Aims: To investigate the independent effect on depression of painless diabetic polyneuropathy, painful diabetic polyneuropathy, and general and diabetes-related comorbidities. Methods: In 181 patients, the presence of painless diabetic polyneuropathy, painful diabetic polyneuropathy, comorbidities and depression was assessed using the Michigan Neuropathy Screening Instrument Questionnaire, the Michigan Diabetic Neuropathy Score, nerve conduction studies, the Douleur Neuropathique en 4 Questions, the Charlson Comorbidity Index and the Beck Depression Inventory-II. Results: In all, 46 patients met the criteria of confirmed painless diabetic polyneuropathy and 25 of painful diabetic polyneuropathy. Beck Depression Inventory-II scores indicative of mild-moderate-severe depression were reached in 36 patients (19.7%). In a multiple logistic regression analysis (including age, sex, body mass index, being unemployed, duration, haemoglobin A1c, insulin treatment, systolic blood pressure, nephropathy, retinopathy, Charlson Comorbidity Index and painful diabetic polyneuropathy), female sex (odds ratio: 5.9, p = 0.005) and painful diabetic polyneuropathy (odds ratio: 4.6, p = 0.038) were the only independent predictors of depression. Multiple regression analysis, including Douleur Neuropathique en 4 Questions and Michigan Diabetic Neuropathy Score instead of painful diabetic polyneuropathy, showed that Douleur Neuropathique en 4 Questions, in addition to female sex, was a significant predictor of depressive symptoms severity (p =0.005). Conclusion: Painful diabetic polyneuropathy is a greater determinant of depression than other diabetes-related complications and comorbidities. Painful symptoms enhance depression severity more than objective insensitivity.