The Compensatory Phenomenon of the Functional Connectome Related to Pathological Biomarkers in Individuals with Subjective Cognitive Decline

Overview

Journal Transl Neurodegener

Publisher Biomed Central

Date 2020 May 29

PMID 32460888

Citations 36

Authors

Haifeng Chen

Xiaoning Sheng

Caimei Luo

Ruomeng Qin

Qing Ye

Hui Zhao

Yun Xu

Feng Bai

Affiliations

Soon will be listed here.

Abstract

Background: Subjective cognitive decline (SCD) is a preclinical stage along the Alzheimer's disease (AD) continuum. However, little is known about the aberrant patterns of connectivity and topological alterations of the brain functional connectome and their diagnostic value in SCD.

Methods: Resting-state functional magnetic resonance imaging and graph theory analyses were used to investigate the alterations of the functional connectome in 66 SCD individuals and 64 healthy controls (HC). Pearson correlation analysis was computed to assess the relationships among network metrics, neuropsychological performance and pathological biomarkers. Finally, we used the multiple kernel learning-support vector machine (MKL-SVM) to differentiate the SCD and HC individuals.

Results: SCD individuals showed higher nodal topological properties (including nodal strength, nodal global efficiency and nodal local efficiency) associated with amyloid-β levels and memory function than the HC, and these regions were mainly located in the default mode network (DMN). Moreover, increased local and medium-range connectivity mainly between the bilateral parahippocampal gyrus (PHG) and other DMN-related regions was found in SCD individuals compared with HC individuals. These aberrant functional network measures exhibited good classification performance in the differentiation of SCD individuals from HC individuals at an accuracy up to 79.23%.

Conclusion: The findings of this study provide insight into the compensatory mechanism of the functional connectome underlying SCD. The proposed classification method highlights the potential of connectome-based metrics for the identification of the preclinical stage of AD.

Citing Articles

Research progress on brain network imaging biomarkers of subjective cognitive decline.

Yingmei H, Chaojie W, Yi Z, Yijie L, Heng Z, Ze F Front Neurosci. 2025; 19:1503955.

PMID: 40018359 PMC: 11865231. DOI: 10.3389/fnins.2025.1503955.

Research on the application of functional near-infrared spectroscopy in differentiating subjective cognitive decline and mild cognitive impairment.

Wang Z, Niu C, Duan Y, Yang H, Mi J, Liu C Front Aging Neurosci. 2025; 16():1469620.

PMID: 39777048 PMC: 11703808. DOI: 10.3389/fnagi.2024.1469620.

Abnormalities in rich-club connections are associated with an exacerbation of genetic susceptibility to schizophrenia.

Li Y, Sun E, Dai R, Chen J, Huang H, Shan X BMC Psychiatry. 2024; 24(1):951.

PMID: 39731072 PMC: 11673898. DOI: 10.1186/s12888-024-06411-w.

Association of precuneus Aβ burden with default mode network function.

Cui L, Zhang Z, Tu Y, Wang M, Guan Y, Li Y Alzheimers Dement. 2024; 21(1):e14380.

PMID: 39559982 PMC: 11772721. DOI: 10.1002/alz.14380.

Associations between the multitrajectory neuroplasticity of neuronavigated rTMS-mediated angular gyrus networks and brain gene expression in AD spectrum patients with sleep disorders.

Yao W, Hou X, Zhou H, You S, Lv T, Chen H Alzheimers Dement. 2024; 20(11):7885-7901.

PMID: 39324544 PMC: 11567849. DOI: 10.1002/alz.14255.

References

Miebach L, Wolfsgruber S, Polcher A, Peters O, Menne F, Luther K . Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study. Alzheimers Res Ther. 2019; 11(1):66. PMC: 6668160. DOI: 10.1186/s13195-019-0515-y. View

Dai Z, Yan C, Li K, Wang Z, Wang J, Cao M . Identifying and Mapping Connectivity Patterns of Brain Network Hubs in Alzheimer's Disease. Cereb Cortex. 2014; 25(10):3723-42. DOI: 10.1093/cercor/bhu246. View

Li W, Qiao L, Zhang L, Wang Z, Shen D . Functional Brain Network Estimation With Time Series Self-Scrubbing. IEEE J Biomed Health Inform. 2019; 23(6):2494-2504. PMC: 6904893. DOI: 10.1109/JBHI.2019.2893880. View

Rathore S, Habes M, Iftikhar M, Shacklett A, Davatzikos C . A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages. Neuroimage. 2017; 155():530-548. PMC: 5511557. DOI: 10.1016/j.neuroimage.2017.03.057. View

Gifford K, Liu D, Damon S, Chapman 4th W, Romano Iii R, Samuels L . Subjective memory complaint only relates to verbal episodic memory performance in mild cognitive impairment. J Alzheimers Dis. 2014; 44(1):309-18. PMC: 4351870. DOI: 10.3233/JAD-140636. View

Rodda J, Dannhauser T, Cutinha D, Shergill S, Walker Z . Subjective cognitive impairment: functional MRI during a divided attention task. Eur Psychiatry. 2010; 26(7):457-62. DOI: 10.1016/j.eurpsy.2010.07.003. View

Khazaee A, Ebrahimzadeh A, Babajani-Feremi A . Identifying patients with Alzheimer's disease using resting-state fMRI and graph theory. Clin Neurophysiol. 2015; 126(11):2132-41. DOI: 10.1016/j.clinph.2015.02.060. View

Toppi J, De Vico Fallani F, Vecchiato G, Maglione A, Cincotti F, Mattia D . How the statistical validation of functional connectivity patterns can prevent erroneous definition of small-world properties of a brain connectivity network. Comput Math Methods Med. 2012; 2012:130985. PMC: 3420234. DOI: 10.1155/2012/130985. View

Ye Q, Su F, Shu H, Gong L, Xie C, Zhou H . Shared effects of the clusterin gene on the default mode network among individuals at risk for Alzheimer's disease. CNS Neurosci Ther. 2017; 23(5):395-404. PMC: 6492680. DOI: 10.1111/cns.12682. View

10.

Jessen F, Amariglio R, van Boxtel M, Breteler M, Ceccaldi M, Chetelat G . A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease. Alzheimers Dement. 2014; 10(6):844-52. PMC: 4317324. DOI: 10.1016/j.jalz.2014.01.001. View

11.

Chiesa P, Cavedo E, Grothe M, Houot M, Teipel S, Potier M . Relationship between Basal Forebrain Resting-State Functional Connectivity and Brain Amyloid-β Deposition in Cognitively Intact Older Adults with Subjective Memory Complaints. Radiology. 2018; 290(1):167-176. DOI: 10.1148/radiol.2018180268. View

12.

Khazaee A, Ebrahimzadeh A, Babajani-Feremi A . Classification of patients with MCI and AD from healthy controls using directed graph measures of resting-state fMRI. Behav Brain Res. 2016; 322(Pt B):339-350. DOI: 10.1016/j.bbr.2016.06.043. View

13.

Bryan R . Machine Learning Applied to Alzheimer Disease. Radiology. 2016; 281(3):665-668. DOI: 10.1148/radiol.2016162151. View

14.

Jones D, Knopman D, Gunter J, Graff-Radford J, Vemuri P, Boeve B . Cascading network failure across the Alzheimer's disease spectrum. Brain. 2015; 139(Pt 2):547-62. PMC: 4805086. DOI: 10.1093/brain/awv338. View

15.

Sperling R, Jack Jr C, Aisen P . Testing the right target and right drug at the right stage. Sci Transl Med. 2011; 3(111):111cm33. PMC: 3752906. DOI: 10.1126/scitranslmed.3002609. View

16.

Wen H, Liu Y, Rekik I, Wang S, Zhang J, Zhang Y . Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children. Hum Brain Mapp. 2017; 38(8):3988-4008. PMC: 6866946. DOI: 10.1002/hbm.23643. View

17.

Liang X, Hsu L, Lu H, Sumiyoshi A, He Y, Yang Y . The Rich-Club Organization in Rat Functional Brain Network to Balance Between Communication Cost and Efficiency. Cereb Cortex. 2017; 28(3):924-935. PMC: 6059143. DOI: 10.1093/cercor/bhw416. View

18.

Perrotin A, Mormino E, Madison C, Hayenga A, Jagust W . Subjective cognition and amyloid deposition imaging: a Pittsburgh Compound B positron emission tomography study in normal elderly individuals. Arch Neurol. 2012; 69(2):223-9. PMC: 4004919. DOI: 10.1001/archneurol.2011.666. View

19.

Zalesky A, Fornito A, Bullmore E . Network-based statistic: identifying differences in brain networks. Neuroimage. 2010; 53(4):1197-207. DOI: 10.1016/j.neuroimage.2010.06.041. View

20.

Collin G, Scholtens L, Kahn R, Hillegers M, van den Heuvel M . Affected Anatomical Rich Club and Structural-Functional Coupling in Young Offspring of Schizophrenia and Bipolar Disorder Patients. Biol Psychiatry. 2017; 82(10):746-755. DOI: 10.1016/j.biopsych.2017.06.013. View