Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states
ObjectivesCerebral small vessel disease (CSVD) is a heterogeneous cerebrovascular syndrome with a variety of pathological mechanisms and clinical manifestations. A majority of research have shown that CSVD is associated with reduced expression of structural covariance networks (SCNs), but most of th...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2025.1541709/full |
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| author | Shiyu Zhang Yue Chen Hua Zhou Zhong Zhao |
| author_facet | Shiyu Zhang Yue Chen Hua Zhou Zhong Zhao |
| author_sort | Shiyu Zhang |
| collection | DOAJ |
| description | ObjectivesCerebral small vessel disease (CSVD) is a heterogeneous cerebrovascular syndrome with a variety of pathological mechanisms and clinical manifestations. A majority of research have shown that CSVD is associated with reduced expression of structural covariance networks (SCNs), but most of these SCN studies based on the group-level, which limits their ability to reflect individual variations in heterogeneous diseases. The purpose of this study is to analyze the structural covariance aberrations in patients with cerebral small vessels by utilizing individualized differential structural covariance network (IDSCN) analysis to explore the differences in SCNs and depressive states at the individual-level.MethodsA total of 22 CSVD patients with depression (CSVD+D) and 34 healthy controls (HCs) were included in this study. IDSCNs were constructed for each subject based on regional gray matter volumes derived from their T1-weighted MRI images. The unpaired-sample t-test was used to compare the IDSCNs between the two groups to obtain the differential structural covariance edge and its distribution. Finally, correlation analyses were performed between the differential edge, the total CSVD imaging burden and Hamilton Rating Scale for Depression (HAMD) score.Results(1) Compared with HCs, the CSVD+D patients exhibited heterogeneous distributions of differential structural covariance edge, with the differential edge located between the caudate nucleus and the cerebellum. (2) There was a significant positive correlation between the total CSVD imaging burden and HAMD scores in CSVD patients with depression (r = 0.692, p < 0.001).ConclusionThis study analyzed the IDSCNs between CSVD+D patients and HCs, which may indicate that the individual structural covariance aberrations between the caudate nucleus and cerebellum may contribute to depression in CSVD patients. Additionally, the higher total CSVD imaging burden of CSVD patients may indicate more severe depression. This finding suggests that early magnetic resonance imaging (MRI) assessment in CSVD patients may facilitate the early identification of depressive states and their severity in the near future. |
| format | Article |
| id | doaj-art-5d2a4e50e1d648d7a3d404e8e6193dec |
| institution | OA Journals |
| issn | 1664-2295 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Neurology |
| spelling | doaj-art-5d2a4e50e1d648d7a3d404e8e6193dec2025-08-20T02:16:21ZengFrontiers Media S.A.Frontiers in Neurology1664-22952025-04-011610.3389/fneur.2025.15417091541709Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive statesShiyu Zhang0Yue Chen1Hua Zhou2Zhong Zhao3The First People’s Hospital of Kunshan, Suzhou, ChinaDepartment of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Liaoning, ChinaDepartment of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Liaoning, ChinaDepartment of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Liaoning, ChinaObjectivesCerebral small vessel disease (CSVD) is a heterogeneous cerebrovascular syndrome with a variety of pathological mechanisms and clinical manifestations. A majority of research have shown that CSVD is associated with reduced expression of structural covariance networks (SCNs), but most of these SCN studies based on the group-level, which limits their ability to reflect individual variations in heterogeneous diseases. The purpose of this study is to analyze the structural covariance aberrations in patients with cerebral small vessels by utilizing individualized differential structural covariance network (IDSCN) analysis to explore the differences in SCNs and depressive states at the individual-level.MethodsA total of 22 CSVD patients with depression (CSVD+D) and 34 healthy controls (HCs) were included in this study. IDSCNs were constructed for each subject based on regional gray matter volumes derived from their T1-weighted MRI images. The unpaired-sample t-test was used to compare the IDSCNs between the two groups to obtain the differential structural covariance edge and its distribution. Finally, correlation analyses were performed between the differential edge, the total CSVD imaging burden and Hamilton Rating Scale for Depression (HAMD) score.Results(1) Compared with HCs, the CSVD+D patients exhibited heterogeneous distributions of differential structural covariance edge, with the differential edge located between the caudate nucleus and the cerebellum. (2) There was a significant positive correlation between the total CSVD imaging burden and HAMD scores in CSVD patients with depression (r = 0.692, p < 0.001).ConclusionThis study analyzed the IDSCNs between CSVD+D patients and HCs, which may indicate that the individual structural covariance aberrations between the caudate nucleus and cerebellum may contribute to depression in CSVD patients. Additionally, the higher total CSVD imaging burden of CSVD patients may indicate more severe depression. This finding suggests that early magnetic resonance imaging (MRI) assessment in CSVD patients may facilitate the early identification of depressive states and their severity in the near future.https://www.frontiersin.org/articles/10.3389/fneur.2025.1541709/fullindividualized differential structural covariance networkcerebral small vessel diseasedepressionstructural covariance network (SCN)heterogeneity |
| spellingShingle | Shiyu Zhang Yue Chen Hua Zhou Zhong Zhao Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states Frontiers in Neurology individualized differential structural covariance network cerebral small vessel disease depression structural covariance network (SCN) heterogeneity |
| title | Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states |
| title_full | Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states |
| title_fullStr | Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states |
| title_full_unstemmed | Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states |
| title_short | Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states |
| title_sort | using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states |
| topic | individualized differential structural covariance network cerebral small vessel disease depression structural covariance network (SCN) heterogeneity |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2025.1541709/full |
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