Cognitive Dysfunction in Type 2 Diabetes Is Not a One-Way Process: Evidence From a Longitudinal Brain Connectivity Study.

Background: Cognitive dysfunction is an important comorbidity of diabetes characterized by brain functional hypo-connectivity. However, our recent study demonstrated an adaptive hyper-connectivity in young type 2 diabetes with cognitive decrements. This longitudinal study aimed to further explore the changes in functional connectivity and cognitive outcomes after regular glycemic control. Methods: At 18 months after recruitment, participants underwent a second cognitive assessment and magnetic resonance imaging. Three enhanced functional connectivities previously identified at baseline were followed up. Linear mixed-effects models were performed to compare the longitudinal changes of cognition and functional connectivity in patients with type 2 diabetes and non-diabetic controls. A linear regression model was used to investigate the association between changes in functional connectivity and changes in cognitive performance. Results: Improvements in multiple cognitive domains were observed in diabetes; however, the enhanced functional connectivity at baseline decreased significantly. Moreover, the decrease in hippocampal connectivity was correlated with an increase in the accuracy of Stroop task and the decrease in posterior cingulate cortex connectivity was correlated with an increase in Montreal Cognitive Assessment in diabetes. Conclusion: This study suggests diabetes-related cognitive dysfunction is not a one-way process and the early-stage enhancement of brain connectivity was a potential "window period" for cognitive reversal.

Decreased Microstructural Integrity of the Central Somatosensory Tracts in Diabetic Peripheral Neuropathy.

CONTEXT: Although diabetic peripheral neuropathy (DPN) is predominantly considered a disorder of the peripheral nerves, some evidence for central nervous system involvement has recently emerged. However, whether or to what extent the microstructure of central somatosensory tracts may be injured remains unknown. OBJECTIVE: This work aimed to detect the microstructure of central somatosensory tracts in type 2 diabetic patients and to correlate it with the severity of DPN. METHODS: A case-control study at a tertiary referral hospital took place with 57 individuals with type 2 diabetes (25 with DPN, 32 without DPN) and 33 nondiabetic controls. The fractional anisotropy (FA) values of 2 major somatosensory tracts (the spinothalamic tract and its thalamocortical [spino-thalamo-cortical, STC] pathway, the medial lemniscus and its thalamocortical [medial lemnisco-thalamo-cortical, MLTC] pathway) were assessed based on diffusion tensor tractography. Regression models were further applied to detect the association of FA values with the severity of DPN in diabetic patients. RESULTS: The mean FA values of left STC and left MLTC pathways were significantly lower in patients with DPN than those without DPN and controls. Moreover, FA values of left STC and left MLTC pathways were significantly associated with the severity of DPN (expressed as Toronto Clinical Scoring System values) in patients after adjusting for multiple confounders. CONCLUSION: Our findings demonstrated the axonal degeneration of central somatosensory tracts in type 2 diabetic patients with DPN. The parallel disease progression of the intracranial and extracranial somatosensory system merits further attention to the central nerves in diabetic patients with DPN.

Bioinformatics method identifies potential biomarkers of dilated cardiomyopathy in a human induced pluripotent stem cell-derived cardiomyocyte model.

Dilated cardiomyopathy (DCM) is the most common type of cardiomyopathy that account for the majority of heart failure cases. The present study aimed to reveal the underlying molecular mechanisms of DCM and provide potential biomarkers for detection of this condition. The public dataset of GSE35108 was downloaded, and 4 normal induced pluripotent stem cell (iPSC)-derived cardiomyocytes (N samples) and 4 DCM iPSC-derived cardiomyocytes (DCM samples) were utilized. Raw data were preprocessed, followed by identification of differentially expressed genes (DEGs) between N and DCM samples. Crucial functions and pathway enrichment analysis of DEGs were investigated, and protein-protein interaction (PPI) network analysis was conducted. Furthermore, a module network was extracted from the PPI network, followed by enrichment analysis. A set of 363 DEGs were identified, including 253 upregulated and 110 downregulated genes. Several biological processes (BPs), such as blood vessel development and vasculature development (FLT1 and MMP2), cell adhesion (CDH1, ITGB6, COL6A3, COL6A1 and LAMC2) and extracellular matrix (ECM)-receptor interaction pathway (CDH1, ITGB6, COL6A3, COL6A1 and LAMC2), were significantly enriched by these DEGs. Among them, MMP2, CDH1 and FLT1 were hub nodes in the PPI network, while COL6A3, COL6A1, LAMC2 and ITGB6 were highlighted in module 3 network. In addition, PENK and APLNR were two crucial nodes in module 2, which were linked to each other. In conclusion, several potential biomarkers for DCM were identified, such as MMP2, FLT1, CDH1, ITGB6, COL6A3, COL6A1, LAMC2, PENK and APLNR. These genes may serve significant roles in DCM via involvement of various BPs, such as blood vessel and vasculature development and cell adhesion, and the ECM-receptor interaction pathway.