Cerebral Small Vessel Disease is Associated with Mild Cognitive Impairment in Type 2 Diabetes Mellitus

A Nomogram Including Total Cerebral Small Vessel Disease Burden Score for Predicting Mild Vascular Cognitive Impairment in Patients with Type 2 Diabetes Mellitus

Background

Total cerebral small vessel disease (CSVD) burden score is an important predictor of vascular cognitive impairment (VCI). However, few predictive models of VCI in type 2 diabetes mellitus (T2DM) patients have included the total CSVD burden score, especially in the early stage of VCI.

Objective

To develop and validate a nomogram that includes the total CSVD burden score to predict mild VCI in patients with T2DM.

Methods

A total of 322 eligible participants with T2DM who were divided into mild and normal cognitive groups were enrolled in this retrospective study. Demographic data, laboratory data and imaging markers of CSVD were collected. The total CSVD burden score was calculated by combining the different CSVD markers. Step-backward multivariable logistic regression analysis with the Akaike information criterion was applied to select significant predictors and develop a best-fit predictive nomogram. The performance of the nomogram was assessed in terms of discriminative ability, calibrated ability, and clinical usefulness.

Results

The nomogram model consisted of five variables: age, education, hemoglobin A1c level, serum homocysteine level, and total CSVD burden score. A nomogram with these variables showed good discriminative ability (area under the receiver operating characteristic curve was 0.801 in internal verification). In addition, the Hosmer-Lemeshow test (χ2 =9.226, P=0.417) and bootstrap-corrected calibration plot indicated that the nomogram had good calibration. The Brier score of the predictive model was 0.178. Decision curve analysis demonstrated that when the threshold probability ranged between 16% and 98%, the use of the nomogram to predict mild VCI in patients with T2DM provide a greater net benefit.

Conclusions

The nomogram, composed of age, education, stroke, HbA1c level, Hcy level, and total CSVD burden score, had good predictive accuracy and may provide clinicians with a practical tool for predicting the risk of mild VCI in T2DM patients.

ECHDC3 Variant Regulates the Right Hippocampal Microstructural Integrity and Verbal Memory in Type 2 Diabetes Mellitus

ECHDC3 is a risk gene for white matter (WM) hyperintensity and is associated with insulin resistance. This study aimed to investigate whether ECHDC3 variants selectively regulate brain WM microstructures and episodic memory in patients with type 2 diabetes mellitus (T2DM). We enrolled 106 patients with T2DM and 111 healthy controls. A voxel-wise general linear model was employed to explore the interaction effect between ECHDC3 rs11257311 polymorphism and T2DM diagnosis on fractional anisotropy (FA). A linear modulated mediation analysis was conducted to examine the potential of FA value to mediate the influence of T2DM on episodic memory in an ECHDC3-dependent manner. We observed a noteworthy interaction between genotype and diagnosis on FA in the right inferior temporal WM, right anterior limb of the internal capsule, right frontal WM, and the right hippocampus. Modulated mediation analysis revealed a significant ECHDC3 modulation on the T2DM → right hippocampal FA → short-term memory pathway, with only rs11257311 G risk homozygote demonstrating significant mediation effect. Together, our findings provide evidence of ECHDC3 modulating the effect of T2DM on right hippocampal microstructural impairment and short-term memory decline, which might be a neuro-mechanism for T2DM related episodic memory impairment.

White matter microstructure alterations in type 2 diabetes mellitus and its correlation with cerebral small vessel disease and cognitive performance

Microstructural abnormalities of white matter fiber tracts are considered as one of the etiology of diabetes-induced neurological disorders. We explored the cerebral white matter microstructure alteration accurately, and to analyze its correlation between cerebral small vessel disease (CSVD) burden and cognitive performance in type 2 diabetes mellitus (T2DM). The clinical-laboratory data, cognitive scores [including mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), California verbal learning test (CVLT), and symbol digit modalities test (SDMT)], CSVD burden scores of the T2DM group (n = 34) and healthy control (HC) group (n = 21) were collected prospectively. Automatic fiber quantification (AFQ) was applied to generate bundle profiles along primary white matter fiber tracts. Diffusion tensor images (DTI) metrics and 100 nodes of white matter fiber tracts between groups were compared. Multiple regression analysis was used to analyze the relationship between DTI metrics and cognitive scores and CSVD burden scores. For fiber-wise and node-wise, DTI metrics in some commissural and association fibers were increased in T2DM. Some white matter fiber tracts DTI metrics were independent predictors of cognitive scores and CSVD burden scores. White matter fiber tracts damage in patients with T2DM may be characterized in specific location, especially commissural and association fibers. Aberrational specific white matter fiber tracts are associated with visuospatial function and CSVD burden.

Aberrant spontaneous static and dynamic amplitude of low-frequency fluctuations in cerebral small vessel disease with or without mild cognitive impairment

BACKGROUND

Cerebral small vessel disease (CSVD) is considered an age-related degenerative neurological disorder and the most common risk factor for vascular cognitive impairment (VCI). The amplitude of fluctuation of low frequency (ALFF) can detect altered intrinsic brain activity in CSVD. This study explored the static and dynamic ALFFs in the early stage of CSVD with (CSVD-M) or without (CSVD-W) mild cognitive impairment (MCI) in these patients and how these changes contribute to cognitive deterioration.

METHODS

Thirty consecutive CSVD cases and 18 healthy controls (HC) were included in this study. All the participants underwent a 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images. Simultaneous multislice imaging 5(SMS5) was used for resting-state functional MRI (rs-fMRI), and Data Processing and Analysis of Brain Imaging software helped determine static ALFF (sALFF). The dynamic ALFF (dALFF) was calculated using the sliding window method of DynamicBC software. Analysis of Covariance (ANCOVA) and two-sample t-test were used to evaluate the sALFF and temporal variability of dALFF among the three groups. The subjects were rated on a broad standard neuropsychological scale. Partial correlation analysis was used to evaluate the correlation between sALFF and dALFF variability and cognition (Bonferroni correction, statistical threshold set at p < .05).

RESULTS

Compared with HCs, the CSVD-M group indicated decreased sALFF values in the bilateral cerebellum posterior lobe (CPL) and the left inferior Parietal Lobule (IPL), with increased sALFF values in the right SFG. For dALFF analysis, the CSVD-W group had significant dALFF variability in the right fusiform gyrus compared with HC. Moreover, the postcentral gyrus (PoCG) was significantly high in the CSVD-W group. While in the CSVD-M group, the bilateral paracentral lobules (PL) revealed significantly elevated dALFF variability and low dALFF variability in the left CPL and right IPL compared with HCs. The CSVD-M group had high dALFF variability in the bilateral PL but low dALFF variability in the left middle temporal gyrus (MTG) and right PoCG compared with the CSVD-W group. The partial correlation analysis indicated that dALFF variability in the left MTG was positively associated with EM (r = 0.713, p = .002) in CSVD-W and CSVD-M groups. In the groups with CSVD-M and HC, altered dALFF variability in the bilateral PL was negatively correlated with EM (r = -0.560, p = .002).

CONCLUSION

There were significant changes in sALFF and dALFF variability in CSVD patients. Abnormal spontaneous static and dynamic ALFFs may provide new insights into cognitive dysfunction in CSVD with MCI and may be valuable biomarkers for early diagnosis.

Why Are Perivascular Spaces Important?

Perivascular spaces (PVS) and their enlargement (EPVS) have been gaining interest as EPVS can be visualized non-invasively by magnetic resonance imaging (MRI) when viewing T-2-weighted images. EPVS are most commonly observed in the regions of the basal ganglia and the centrum semiovale; however, they have also been identified in the frontal cortex and hippocampal regions. EPVS are known to be increased in aging and hypertension, and are considered to be a biomarker of cerebral small vessel disease (SVD). Interest in EPVS has been significantly increased because these PVS are now considered to be an essential conduit necessary for the glymphatic pathway to provide the necessary efflux of metabolic waste. Metabolic waste includes misfolded proteins of amyloid beta and tau that are known to accumulate in late-onset Alzheimer's disease (LOAD) within the interstitial fluid that is delivered to the subarachnoid space and eventually the cerebral spinal fluid (CSF). The CSF acts as a sink for accumulating neurotoxicities and allows clinical screening to potentially detect if LOAD may be developing early on in its clinical progression via spinal fluid examination. EPVS are thought to occur by obstruction of the PVS that associates with excessive neuroinflammation, oxidative stress, and vascular stiffening that impairs flow due to a dampening of the arterial and arteriolar pulsatility that aids in the convective flow of the metabolic debris within the glymphatic effluxing system. Additionally, increased EPVS has also been associated with Parkinson's disease and non-age-related multiple sclerosis (MS).

MRI Visible Perivascular Spaces and the Risk of Incident Mild Cognitive Impairment in a Community Sample

BACKGROUND

Magnetic resonance imaging (MRI) visible perivascular spaces (PVS) are associated with the risk of incident dementia but their association with the early stages of cognitive impairment remains equivocal.

OBJECTIVE

We examined the association between MRI visible PVS and the risk of incident mild cognitive impairment (MCI) in the community-based Framingham Heart Study (FHS).

METHODS

FHS participants aged at least 50 years free of stroke, cognitive impairment, and dementia at the time of MRI were included. PVS were rated according to severity in the basal ganglia and centrum semiovale (CSO) using established criteria. Cox regression analyses were used to relate PVS to incident MCI adjusted for demographic and cardiovascular variables.

RESULTS

The mean age of the sample (1,314 participants) at MRI was 68 years (SD, 9; 54% women). There were 263 cases of incident MCI over a median 7.4 years follow-up (max, 19.8 years). MCI risk increased with higher PVS severity in the CSO. Relative to persons with the lowest severity rating, persons with the highest severity rating in the CSO had a higher risk of incident MCI (hazard ratio [HR] = 2.55; 95% confidence interval [CI], 1.48-4.37; p = 0.0007). In secondary analysis, this association seemed stronger in women. Risk of incident MCI was nominally higher for participants with the highest severity grade of PVS in the basal ganglia, though not statistically significant relative to the lowest grade (HR = 2.19; 95% CI, 0.78-6.14; p = 0.14).

CONCLUSIONS

PVS burden in the CSO may be a risk marker for early cognitive impairment.

Adjuvant Chinese Medicine for the Treatment of Type 2 Diabetes Mellitus Combined with Mild Cognitive Impairment: A Systematic Review and Meta-Analysis of a Randomised Controlled Trial

Mild cognitive impairment has a high prevalence in the type 2 diabetic population. Adjuvant therapy with Chinese herbal medicine can effectively improve the clinical symptoms of patients with T2DM combined with MCI. The aim of this study was to systematically evaluate the efficacy and safety of Chinese herbal adjunctive therapy in the treatment of diabetes mellitus combined with cognitive impairment. Information was analysed using the China Knowledge Network, Vip Database, Wanfang Database, China Biomedical Literature Database, PubMed, EMbase, Web of Science, and MedLine Database. The total clinical efficiency, blood glucose, blood lipids, Simple Mental-State Examination Scale (MMSE), Montreal Cognitive Assessment Scale (MoCA), Traditional Chinese Medicine Symptom Score (TCMSS), and incidence of adverse reactions were recorded. The methodological quality of the included studies was evaluated using the application of the Cochrane Collaboration Network Risk Bias Assessment Tool, and meta-analysis was performed using RevMan 5.4 software. Adjuvant treatment with Chinese herbal medicine was effective in improving the clinical outcomes (OR = 5.33, 95% CI (3.62, 7.84), p < 0.00001) and cognitive function by comparing with the control group: MMSE (MD = 1.56, 95% CI (1.29, 1.84), p < 0.00001) and MoCA (MD = 2.77, 95% CI (1.81, 3.73), p < 0.0001); lowered blood glucose: fasting blood glucose (FBG) (MD = −0.27, 95% CI (−0.42, −0.12), p = 0.0006), 2 hPG (MD = −0.28, 95% CI (−0.45, −0.10), p = 0.002), and glycated haemoglobin (HbA1c) (MD = −0.26, 95% CI (−0.39, −0.14), p < 0.001); and improved lipids: total cholesterol (TC) (MD = −0.51, 95% CI (−0.82, −0.21), p = 0.001), triglycerides (TGs) (MD = −0.46, 95% CI −0.46, 95% CI (−0.80, −0.11), p = 0.009), low-density lipoprotein (LDL-C) (MD = −0.28, 95% CI (−0.55, −0.02), p = 0.04), high-density lipoprotein (HDL-C) (MD = 0.17, 95% CI (0.07, 0.28), p = 0.001), reduced TCMSS (MD = −1.84, 95% CI (−2.58, −1.10), p < 0.0001), and incidence of adverse events (OR = 0.46, 95% CI (0.24, 0.88), p = 0.02). In conclusion, through the available evidence, herbal adjuvant therapy for T2DM combined with MCI was observed to be effective and did not significantly increase the adverse effects. Due to the limitation of the number and quality of the included studies, the abovementioned results need to be validated by further high-quality studies.