Structural brain network measures in elderly patients with cerebral small vessel disease and depressive symptoms

An integration of neuroimaging and serum proteomics analysis suggests immune and inflammation are associated with white matter microstructure changes in cerebral small vessel disease with depressive symptoms

INTRODUCTION

Depressive symptoms are a common concomitant of cerebral small vessel disease (CSVD), of which pathogenesis requires more study. White matter microstructural abnormalities and proteomic alternation have been widely reported regarding depression in the elderly with CSVD. Exploring the relationship between cerebral white matter microstructural alterations and serum proteins may complete the explanation of molecular mechanisms for the findings from neuroimaging research of CSVD combined with depressive symptoms.

METHODS

An untargeted proteomics approach based on mass spectrometry was used to obtain serum proteomic profiles, which were clustered into co-expression protein modules. White matter microstructural integrity was measured using the FMRIB Software Library (FSL) and MATLAB to analyze diffusion tensor imaging (DTI) data and calculate the differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) for 50 regions of interest (ROI). Integrating the proteome with the DTI results, weighted gene co-expression analysis (WGCNA) was used to identify protein modules related to white matter microstructural alterations, and the proteins of the corresponding modules were analyzed for functional enrichment through bioinformatics techniques.

RESULTS

DTI measurements were analCerebral small vessel disease (CSVD); Depression; Diffusion tensor imaging (DTI); Proteomics; Inflammationyzed between individuals with CSVD and depressive symptoms (CSVD+D) (n = 24) and those without depressive symptoms (CSVD-D) (n = 35). Results showed an overall increase in MD, AD, and RD within the left hemisphere of the CSVD+D group, suggesting widespread loss of white matter integrity and axonal demyelination, including left superior longitudinal fasciculus (SLF), left posterior corona radiata (PCR) and right external capsule (EC). We identified two protein modules associated with DTI diffusivity, and functional enrichment analyses revealed that complement and coagulation cascades and immune responses participate in the alternation of white matter microstructure in the CSVD+D group.

CONCLUSION

The results suggested immune- and inflammation-related mechanism was associated with white matter microstructure changes in CSVD with depressive symptoms.

Causal effect of circulating cytokines on MRI markers of cerebral small vessel disease: A mendelian randomization study

BACKGROUND

Previous observational studies have reported the correlation between circulating inflammatory cytokines and cerebral small vessel disease (CSVD). However, the causality of this association is uncertain. This study used Mendelian randomization to investigate the causal effect of circulating inflammatory cytokines on neuroimaging changes in CSVD.

METHODS

This study utilized genetic variances of 41 inflammatory cytokines and 3 neuroimaging markers of CSVD from genome-wide association studies to assess the causal effects in a two-sample Mendelian randomization approach. Inverse variance weighted analysis was used as the main analytical method, and sensitivity analysis was used to further validate the robustness of the results.

RESULTS

Increased IL-18 was associated with increased white matter hyperintensity (WMH) and mean diffusivity (MD) (β = 0.034, 95 % CI 0.002, 0.065, P=0.038, β = 0.157, 95 % CI 0.015, 0.299, P=0.030). However, increased IL-18 was associated with decreased fractional anisotropy (FA) (β = -0.141, 95 % CI -0.279, -0.002, P=0.047). Increased monocyte chemotactic protein-1(MCP-1) was associated with decreased FA (β = -0.278, 95 % CI -0.502, -0.054, P=0.015). Increased IL-10 levels and IL-2ra levels were associated with decreased risks of MD (β = -0.228, 95 % CI -0.448, -0.009, p = 0.041; β = -0.204, 95 % CI=-0.377, -0.031, p = 0.021).

CONCLUSIONS

This study revealed that increased levels of IL-18 and MCP-1 were associated with white matter microstructural injury, and increased levels of IL-10 and IL-2ra were associated with decreased MD.

Establishment and evaluation of a clinical prediction model for cognitive impairment in patients with cerebral small vessel disease

BACKGROUND

There are currently no effective prediction methods for evaluating the occurrence of cognitive impairment in patients with cerebral small vessel disease (CSVD).

AIMS

To investigate the risk factors for cognitive dysfunction in patients with CSVD and to construct a risk prediction model.

METHODS

A retrospective study was conducted on 227 patients with CSVD. All patients were assessed by brain magnetic resonance imaging (MRI), and the Montreal Cognitive Assessment (MoCA) was used to assess cognitive status. In addition, the patient's medical records were also recorded. The clinical data were divided into a normal cognitive function group and a cognitive impairment group. A MoCA score < 26 (an additional 1 point for education < 12 years) is defined as cognitive dysfunction.

RESULTS

A total of 227 patients (mean age 66.7 ± 6.99 years) with CSVD were included in this study, of whom 68.7% were male and 100 patients (44.1%) developed cognitive impairment. Age (OR = 1.070; 95% CI = 1.015 ~ 1.128, p < 0.05), hypertension (OR = 2.863; 95% CI = 1.438 ~ 5.699, p < 0.05), homocysteine(HCY) (OR = 1.065; 95% CI = 1.005 ~ 1.127, p < 0.05), lacunar infarct score(Lac_score) (OR = 2.732; 95% CI = 1.094 ~ 6.825, P < 0.05), and CSVD total burden (CSVD_score) (OR = 3.823; 95% CI = 1.496 ~ 9.768, P < 0.05) were found to be independent risk factors for cognitive decline in the present study. The above 5 variables were used to construct a nomogram, and the model was internally validated by using bootstrapping with a C-index of 0.839. The external model validation C-index was 0.867.

CONCLUSIONS

The nomogram model based on brain MR images and clinical data helps in individualizing the probability of cognitive impairment progression in patients with CSVD.

Disrupted brain structural networks associated with depression and cognitive dysfunction in cerebral small vessel disease with microbleeds

Emerging evidence highlights cerebral microbleeds (CMBs) as hallmarks of cerebral small vessel disease (CSVD) underlying depression and cognitive dysfunction. This study aimed to reveal how depression and cognition-related white matter (WM) abnormalities are topologically presented, and the network-level structural disruptions associated with CMBs in CSVD. We used probabilistic diffusion tractography and graph theory to investigate brain WM network topology in CSVD patients with (n = 64, CSVD-c) and without (n = 138, CSVD-n) CMBs and 90 healthy controls. Then we evaluated the Pearson's correlations between disrupted network metrics and neuropsychological parameters. For global topology, the CSVD-c group exhibited significantly decreased global (Eglob) and local (Eloc) efficiency and increased shortest path length compared with the controls, while no significant difference was found between the CSVD-c and CSVD-n groups. For regional topology, although all groups showed highly similar hub distributions, compare with control group, the CSVD-c group exhibited significantly decreased nodal efficiency mainly in the bilateral supplementary motor area (SMA), median cingulate gyrus (DCG) and right orbital middle frontal gyrus, while the CSVD-n group showed significantly decreased nodal efficiency only in the right SMA. Notably, Eglob, Eloc and nodal efficiency of the right anterior cingulate gyrus, DCG, middle temporal gyrus and left insula showed significantly negative correlations with depression score, significantly positive correlations with Rey auditory verbal learning test and symbol digit modalities test scores in CSVD-n group, as well as significantly negative correlations with Stroop color-word test scores in CSVD-c group. The WM networks of CSVD patients are characterized by decreased global integration and local specialization, and decreased nodal efficiency highly related to depression and cognitive dysfunction in the attention, default mode network and sensorimotor regions. These findings provide new insight into the neurobiological mechanisms of CSVD and concomitant affective and cognitive disorders.

White matter fiber integrity and structural brain network topology: implications for balance function in postischemic stroke patients

Previous studies have suggested that ischemic stroke can result in white matter fiber injury and modifications in the structural brain network. However, the relationship with balance function scores remains insufficiently explored. Therefore, this study aims to explore the alterations in the microstructural properties of brain white matter and the topological characteristics of the structural brain network in postischemic stroke patients and their potential correlations with balance function. We enrolled 21 postischemic stroke patients and 21 age, sex, and education-matched healthy controls (HC). All participants underwent balance function assessment and brain diffusion tensor imaging. Tract-based spatial statistics (TBSS) were used to compare the fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity of white matter fibers between the two groups. The white matter structural brain network was constructed based on the automated anatomical labeling atlas, and we conducted a graph theory-based analysis of its topological properties, including global network properties and local node properties. Additionally, the correlation between the significant structural differences and balance function score was analyzed. The TBSS results showed that in comparison to the HC, postischemic stroke patients exhibited extensive damage to their whole-brain white matter fiber tracts (P < 0.05). Graph theory analysis showed that in comparison to the HC, postischemic stroke patients exhibited statistically significant reductions in the values of global efficiency, local efficiency, and clustering coefficient, as well as an increase in characteristic path length (P < 0.05). In addition, the degree centrality and nodal efficiency of some nodes in postischemic stroke patients were significantly reduced (P < 0.05). The white matter fibers of the entire brain in postischemic stroke patients are extensively damaged, and the topological properties of the structural brain network are altered, which are closely related to balance function. This study is helpful in further understanding the neural mechanism of balance function after ischemic stroke from the white matter fiber and structural brain network topological properties.

Characteristic patterns of functional connectivity-mediated cerebral small vessel disease-related cognitive impairment and depression

Cerebral small vessel disease is common in most individuals aged 60 years or older, and it is associated with cognitive dysfunction, depression, anxiety disorder, and mobility problems. Currently, many cerebral small vessel disease patients have both cognitive impairment and depressive symptoms, but the relationship between the 2 is unclear. The present research combined static and dynamic functional network connectivity methods to explore the patterns of functional networks in cerebral small vessel disease individuals with cognitive impairment and depression (cerebral small vessel disease-mild cognitive impairment with depression) and their relationship. We found specific functional network patterns in the cerebral small vessel disease-mild cognitive impairment with depression individuals (P < 0.05). The cerebral small vessel disease individuals with depression exhibited unstable dynamic functional network connectivity states (transitions likelihood: P = 0.040). In addition, we found that the connections within the lateral visual network between the sensorimotor network and ventral attention network could mediate white matter hyperintensity-related cognitive impairment (indirect effect: 0.064; 95% CI: 0.003, 0.170) and depression (indirect effect: -0.415; 95% CI: -1.080, -0.011). Cognitive function can negatively regulate white matter hyperintensity-related depression. These findings elucidate the association between cognitive impairment and depression and provide new insights into the underlying mechanism of cerebral small vessel disease-related cognitive dysfunction and depression.

Decreased Local Specialization of Brain Structural Networks Associated with Cognitive Dysfuntion Revealed by Probabilistic Diffusion Tractography for Different Cerebral Small Vessel Disease Burdens

To reveal the network-level structural disruptions associated with cognitive dysfunctions in different cerebral small vessel disease (CSVD) burdens, we used probabilistic diffusion tractography and graph theory to investigate the brain network topology in 67 patients with a severe CSVD burden (CSVD-s), 133 patients with a mild CSVD burden (CSVD-m) and 89 healthy controls. We used one-way analysis of covariance to assess the altered topological measures between groups, and then evaluated their Pearson correlation with cognitive parameters. Both the CSVD and control groups showed efficient small-world organization in white matter (WM) networks. However, compared with CSVD-m patients and controls, CSVD-s patients exhibited significantly decreased local efficiency, with partially reorganized hub distributions. For regional topology, CSVD-s patients showed significantly decreased nodal efficiency in the bilateral anterior cingulate gyrus, caudate nucleus, right opercular inferior frontal gyrus (IFGoperc), supplementary motor area (SMA), insula and left orbital superior frontal gyrus and angular gyrus. Intriguingly, global/local efficiency and nodal efficiency of the bilateral caudate nucleus, right IFGoperc, SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group, while only the left pallidum showed significant correlations with cognitive metrics in the CSVD-m group. In conclusion, the decreased local specialization of brain structural networks in patients with different CSVD burdens provides novel insights into understanding the brain structural alterations in relation to CSVD severity. Cognitive correlations with brain structural network efficiency suggest their potential use as neuroimaging biomarkers to assess the severity of CSVD.

Correlation between lenticulostriate arteries and white matter microstructure changes in patients with cerebral small vessel disease

To explore the correlation between the number of lenticulostriate arteries (LSAs) and the white matter features in cerebral small vessel diseases (CSVD) by 3T magnetic resonance imaging (MRI). Seventy-one patients with diagnoses of CSVD were prospectively enrolled to undergo 3T MRI examination, including high-resolution vascular wall imaging (VWI) and diffusion tensor imaging (DTI). The LSAs were observed and counted on VWI, and the patients were divided into three groups according to the LSA counts. The presence of white matter hyperintensities (WMHs), lacunes, cerebral microbleeds (CMBs), and enlarged perivascular spaces (EPVS) was assessed in each patient, and a composite CSVD score was calculated. Periventricular and deep white matter hyperintensity (PVWMH, DWMH) volume ratios were obtained based on automatic segmentation. Fractional anisotropy (FA) and mean diffusivity (MD) were processed by using tract-based spatial statistics (TBSS) analysis. These parameters were compared among the three groups. Correlations between the LSA counts and white matter features were also analyzed. There were differences in WMHs (P = 0.001), CMBs (P < 0.001), EPVS (P = 0.017), composite CSVD scores (P < 0.001), PVWMH volume ratios (P = 0.001), DWMH volume ratios (P < 0.001), global FA (P = 0.001), and global MD (P = 0.002) among the three groups. There were correlations between the LSA counts and WMHs (r = -0.45, P < 0.001), CMBs (r = -0.44, P < 0.001), EPVS (r = -0.28, P = 0.020), the composite CSVD score (r = -0.52, P < 0.001), DWMH volume ratio (r = -0.47, P < 0.001), PWMH volume ratio (r = -0.34, P = 0.004), global FA (r = 0.36, P = 0.002), and global MD (r = -0.33, P = 0.005). Diabetes mellitus (OR 3.36, 95% CI 1.06-10.63; P = 0.039) and increased DWMH volume ratios (OR 1.04, 95% CI 1.00-1.08; P = 0.048) were independent risk factors for a decrease in LSA counts. TBSS analysis showed differences among the three groups in global FA and MD after adjusting for age and sex (P < 0.05). The LSA counts was associated with white matter microstructure changes in CSVD and has the potential to represent the extent of subcortical microvascular damage in CSVD patients.

White matter hyperintensities and post-stroke depression: A systematic review and meta-analysis

INTRODUCTION

Post-stroke depression (PSD) is the most common emotional problem following a stroke. White matter hyperintensities (WMHs) are often reported in patients with a stroke, and are often divided into deep WMHs (DWMHs) and periventricular WMHs (PVWMHs). The relationship between WMHs and PSD remains controversial. This review aims to resolve this controversy.

METHODS

A systematic search of electronic databases was conducted for studies. We extracted the relevant data and evaluated the study quality by using the Newcastle-Ottawa Scale. We pooled odds ratios (OR) for the same type of WMHs that were present in the relevant PSD period.

RESULTS

15 studies (n = 4133 patients) met our inclusion criteria. In the acute phase, WMHs, DWMHs, severe WMHs, and severe DWMHs were not significant risk factors for incident depression, but PVWMHs (pooled OR, 1.21; 95 % CI, 1.01-1.44) and severe PVWMHs (pooled OR, 1.72; 95 % CI, 1.12-2.65) had a significant association with PSD. In the subacute phase, DWMHs, DWMHs, and severe WMHs were not significantly associated with PSD, but PVWMHs (pooled OR, 2.44; 95 % CI, 1.25-4.76) showed a significant association with PSD. In the chronic phase, severe PVWMHs had no significant association with PSD, while WMHs (pooled OR, 1.063; 95 % CI, 1.03-1.09), DWMHs (pooled OR, 1.40; 95 % CI, 1.11-1.76), PVWMHs (pooled OR, 1.28; 95 % CI, 1.11-1.48), and severe DWMHs (pooled OR, 1.52; 95 % CI, 1.12-2.05) showed a significant association with PSD.

CONCLUSION

We found a significant association between WMHs/DWMHs/PVWMHs and PSD in the chronic post-stroke phase. PVWMHs had a stronger correlation with PSD in each period after stroke than WMHs and DWMHs. High-quality prospective studies are still needed to fully resolve this relationship.

A new nomogram including total cerebral small vessel disease burden for individualized prediction of early-onset depression in patients with acute ischemic stroke

Objectives

The present study was designed to evaluate the effects of total cerebral small vessel disease (CSVD) on early-onset depression after acute ischemic stroke (AIS), and to develop a new nomogram including total CSVD burden to predict early-onset post-stroke depression (PSD).

Methods

We continuously enrolled patients with AIS who were hospitalized at the First Affiliated Hospital of Soochow University between October 2017 and June 2019. All patients were assessed for depressive symptoms using the 17-item Hamilton Depression Scale (HAMD-17) at 14 ± 2 days after the onset of AIS. The diagnosis for depression was made according to the American Diagnostic and Statistical Manual of Mental Disorders Version 5 (DSM-5). The demographic and clinical data were collected including total CSVD burden. On the basis of a multivariate logistic model, the independent factors of early-onset PSD were identified and the predictive nomogram was generated. The performance of the nomogram was evaluated by Harrell's concordance index (C-index) and calibration plot.

Results

A total of 346 patients were enrolled. When contrasted to a 0 score of total CSVD burden, the score ≥2 (moderate to severe total CSVD burden) was an independent risk factor for early-onset PSD. Besides, gender, cognitive impairments, baseline Barthel Index (BI), and plasma fibrinogen were independently associated with early-onset PSD. The nomogram based on all these five independent risk factors was developed and validated with an Area Under Curve (AUC) of 0.780. In addition, the calibration plot revealed an adequate fit of the nomogram in predicting the risk of early-onset depression in patients with AIS.

Conclusions

Our study found the total CSVD burden score of 2–4 points was an independent risk factor of early-onset PSD. The proposed nomogram based on total CSVD burden, gender, cognitive impairments, baseline BI, and plasma fibrinogen concentration gave rise to a more accurate and more comprehensive prediction for early-onset PSD.