Dataset Information

Connectome gradient dysfunction contributes to white matter hyperintensity-related cognitive decline.

ABSTRACT:

Background

Although white matter hyperintensity (WMH) is closely associated with cognitive decline, the precise neurobiological mechanisms underlying this relationship are not fully elucidated. Connectome studies have identified a primary-to-transmodal gradient in functional brain networks that support the spectrum from sensation to cognition. However, whether connectome gradient structure is altered as WMH progresses and how this alteration is associated with WMH-related cognitive decline remain unknown.

Methods

A total of 758 WMH individuals completed cognitive assessment and resting-state functional MRI (rs-fMRI). The functional connectome gradient was reconstructed based on rs-fMRI by using a gradient decomposition framework. Interrelations among the spatial distribution of WMH, functional gradient measures, and specific cognitive domains were explored.

Results

As the WMH volume increased, the executive function (r = -0.135, p = 0.001) and information-processing speed (r = -0.224, p = 0.001) became poorer, the gradient range (r = -0.099, p = 0.006), and variance (r = -0.121, p < 0.001) of the primary-to-transmodal gradient reduced. A narrower gradient range (r = 0.131, p = 0.001) and a smaller gradient variance (r = 0.136, p = 0.001) corresponded to a poorer executive function. In particular, the relationship between the frontal/occipital WMH and executive function was partly mediated by gradient range/variance of the primary-to-transmodal gradient.

Conclusions

These findings indicated that WMH volume, the primary-to-transmodal gradient, and cognition were interrelated. The detrimental effect of the frontal/occipital WMH on executive function was partly mediated by the decreased differentiation of the connectivity pattern between the primary and transmodal areas.

SUBMITTER: Yang D

PROVIDER: S-EPMC11245402 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Publications

Connectome gradient dysfunction contributes to white matter hyperintensity-related cognitive decline.

Yang Dan D Tan Yi Y Zhou ZhiXin Z Ke Zhihong Z Huang Lili L Mo Yuting Y Tang Limoran L Mao ChengLu C Hu Zheqi Z Cheng Yue Y Shao Pengfei P Zhang Bing B Zhu Xiaolei X Xu Yun Y

CNS neuroscience & therapeutics 20240701 7

<h4>Background</h4>Although white matter hyperintensity (WMH) is closely associated with cognitive decline, the precise neurobiological mechanisms underlying this relationship are not fully elucidated. Connectome studies have identified a primary-to-transmodal gradient in functional brain networks that support the spectrum from sensation to cognition. However, whether connectome gradient structure is altered as WMH progresses and how this alteration is associated with WMH-related cognitive decli ...[more]

PMID: 38997814

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Project description:BackgroundWhite matter hyperintensity (WMH) is one of the typical neuroimaging manifestations of cerebral small vessel disease (CSVD), and the WMH correlates closely to cognitive impairment (CI). CSVD patients with WMH own altered topological properties of brain functional network, which is a possible mechanism that leads to CI. This study aims to identify differences in the characteristics of some brain functional network among patients with different grades of WMH and estimates the correlations between these different brain functional network characteristics and cognitive assessment scores.Methods110 CSVD patients underwent 3.0 T Magnetic resonance imaging scans and neuropsychological cognitive assessments. WMH of each participant was graded on the basis of Fazekas grade scale and was divided into two groups: (A) WMH score of 1-2 points (n = 64), (B) WMH score of 3-6 points (n = 46). Topological indexes of brain functional network were analyzed using graph-theoretical method. T-test and Mann-Whitney U test was used to compare the differences in topological properties of brain functional network between groups. Partial correlation analysis was applied to explore the relationship between different topological properties of brain functional networks and overall cognitive function.ResultsPatients with high WMH scores exhibited decreased clustering coefficient values, global and local network efficiency along with increased shortest path length on whole brain level as well as decreased nodal efficiency in some brain regions on nodal level (p < 0.05). Nodal efficiency in the left lingual gyrus was significantly positively correlated with patients' total Montreal Cognitive Assessment (MoCA) scores (p < 0.05). No significant difference was found between two groups on the aspect of total MoCA and Mini-mental State Examination (MMSE) scores (p > 0.05).ConclusionTherefore, we come to conclusions that patients with high WMH scores showed less optimized small-world networks compared to patients with low WMH scores. Global and local network efficiency on the whole-brain level, as well as nodal efficiency in certain brain regions on the nodal level, can be viewed as markers to reflect the course of WMH.

Project description:White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

Dataset Information

Connectome gradient dysfunction contributes to white matter hyperintensity-related cognitive decline.

Background

Methods

Results

Conclusions

Publications

Connectome gradient dysfunction contributes to white matter hyperintensity-related cognitive decline.

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