Cognitive Compensation of Frontoparietal Network Structure-Function Coupling in Mild WMH
Poster No:
81
Submission Type:
Abstract Submission
Authors:
Xiao Zhu1, Yifei Li1, Ying Zhou1, Yaode He1, Haiwei Huang1, Huihong Ke1, Jianzhong Sun1, Min Lou1
Institutions:
1Zhejiang University, Hangzhou, Zhejiang
First Author:
Co-Author(s):
Introduction:
White matter hyperintensity (WMH) is one of the main neuroimaging markers of cerebral small vessel disease. Of note, severe WMH is associated with the development of cognitive impairment, especially affecting executive functions (Alber et al., 2019). However, the relationship between WMH and cognition in patients with mild burden is less obvious (Zeng et al., 2020), suggesting unidentified neuroimaging mechanisms might exist to support cognitive function in these patients. Most researches focus either on structure or function to explain the underlying mechanism, while the coupling between structure and function remains largely unexplored. This coupling may play a crucial role in cognitive cognition during early stage of WMH. Therefore, we utilized network structure-function coupling (SC-FC coupling) to investigate the neuroimaging mechanism underlying cognition in patients with mild WMH.
Methods:
We retrospectively reviewed the data of consecutive patients recruited in the CIRCLE study (ClinicalTrials.gov ID: NCT03542734) between December 2019 and November 2023. All patients underwent neuropsychological assessment using NINDS-CSN battery and multimodal MRI scans, including T1, T2FLAIR, DTI, and resting-state fMRI. WMH was defined as subcortical hyperintensities without cavitation on T2 FLAIR based on the recommendations of Standards for Reporting Vascular Changes on Neuroimaging (Wardlaw et al., 2013). WMH was segmented from T2FLAIR imaging and quantified after normalizing to MNI152 space. Severe WMH was defined as periventricular WMH score of 3 and/or deep WMH score ≥ 2, otherwise was defined as mild WMH (Song et al., 2021). We used the Schaefer400 parcellation scheme (Schaefer et al., 2018), dividing cortex into seven canonical functional networks according to the resting-state fMRI. As for ROI-wise SC-FC coupling, for each region in one specific network, its structural and functional connectivity matrix with other regions in this network were extracted and calculated for Spearman correlation. Network SC-FC coupling was defined as the mean of ROI-wise SC-FC coupling across all regions in this network. False Discovery Rate was used to correct for multiple comparisons.
Results:
A total of 617 participants were finally included in the cross-sectional analysis (mean age = 61 [SD = 8]; 287 females [46.5%]). Mean WMH volume was 3.78 [SD = 8.00] ml. Across networks, frontoparietal network (FPN) exhibited the lowest structure-function coupling while somatomotor network was the highest. Within the mild WMH subgroup (n = 374), only FPN SC-FC coupling positively correlated with WMH volume (β = 0.136, p = 0.014), a pattern not observed in the entire cohort and severe WMH subgroup. Furthermore, in the mild WMH subgroup, FPN SC-FC coupling was also positively correlated with cognitive performance on the digit span forward task in both cross-sectional (β = 0.110, p = 0.023) and longitudinal analyses (β = 0.245, p = 0.038).
Conclusions:
By integrating both cross-sectional and longitudinal cohorts, we have illustrated how FPN SC-FC coupling within neural networks evolves with presence of WMH. Further, we clarified its compensatory role in preserving executive function and working memory, especially during the early stage. Our findings not only underscore the potential of FPN SC-FC coupling as a predictive biomarker for cognitive performance, but also suggest it as a novel target for early intervention strategies in WMH patients.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making
Lifespan Development:
Aging 2
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Keywords:
Aging
Cerebrovascular Disease
Cognition
Cortex
Data analysis
Demyelinating
FUNCTIONAL MRI
MRI
STRUCTURAL MRI
1|2Indicates the priority used for review
·Figure 1. Network structure-function coupling (SC-FC coupling) and its association with white matter hyperintensity volume (WMHV).
·Figure 2. Association of frontoparietal network (FPN) structure-function coupling (SC-FC coupling) with cognitive function in both cross-sectional
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Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X. N., Holmes, A. J., Eickhoff, S. B., & Yeo, B. T. T. (2018). Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI. Cereb Cortex, 28(9), 3095-3114. https://doi.org/10.1093/cercor/bhx179
Song, Q., Cheng, Y., Wang, Y., Liu, J., Wei, C., & Liu, M. (2021). Enlarged perivascular spaces and hemorrhagic transformation after acute ischemic stroke. Ann Transl Med, 9(14), 1126. https://doi.org/10.21037/atm-21-1276
Wardlaw, J. M., Smith, E. E., Biessels, G. J., Cordonnier, C., Fazekas, F., Frayne, R., Lindley, R. I., O'Brien, J. T., Barkhof, F., Benavente, O. R., Black, S. E., Brayne, C., Breteler, M., Chabriat, H., Decarli, C., de Leeuw, F. E., Doubal, F., Duering, M., Fox, N. C., . . . Dichgans, M. (2013). Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol, 12(8), 822-838. https://doi.org/10.1016/s1474-4422(13)70124-8
Zeng, W., Chen, Y., Zhu, Z., Gao, S., Xia, J., Chen, X., Jia, J., & Zhang, Z. (2020). Severity of white matter hyperintensities: Lesion patterns, cognition, and microstructural changes. J Cereb Blood Flow Metab, 40(12), 2454-2463. https://doi.org/10.1177/0271678X19893600