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Aberrant interhemispheric functional connectivity within default mode network and its relationships with neurocognitive features in cognitively normal APOE ε 4 elderly carriers

Published online by Cambridge University Press:  26 January 2017

Hanna Lu Open the ORCID record for Hanna Lu [Opens in a new window] ,
Suk Ling Ma ,
Savio Wai Ho Wong ,
Cindy W. C. Tam ,
Sheung-Tak Cheng ,
Sandra S. M. Chan  and
Linda C. W. Lam
Hanna Lu*
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong SAR, China Department of Psychiatry, Guangzhou Brain Hospital, The Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
Suk Ling Ma
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong SAR, China
Savio Wai Ho Wong
Affiliation:
Department of Special Education and Counselling, Hong Kong Institute of Education Center for Brain and Education, The Hong Kong Institute of Education, Hong Kong SAR, China
Cindy W. C. Tam
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong SAR, China
Sheung-Tak Cheng
Affiliation:
Department of Health and Physical Education, The Education University of Hong Kong, Hong Kong SAR, China
Sandra S. M. Chan
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong SAR, China
Linda C. W. Lam*
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong SAR, China
*
Correspondence should be addressed to: Dr Hanna Lu and Prof Linda C. W. Lam, Address: Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Tai Po, Hong Kong, SAR China. Phone: +(852) 2831-4305; Fax: +(852) 2667-5464. Email: hannalu@cuhk.edu.hk; cwlam@cuhk.edu.hk.
Correspondence should be addressed to: Dr Hanna Lu and Prof Linda C. W. Lam, Address: Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Tai Po, Hong Kong, SAR China. Phone: +(852) 2831-4305; Fax: +(852) 2667-5464. Email: hannalu@cuhk.edu.hk; cwlam@cuhk.edu.hk.
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Abstract

Background:

Default mode network (DMN) is vulnerable to the effects of APOE genotype. Given the reduced brain volumes and APOE ε 4-related brain changes in elderly carriers, it is less known that whether these changes would influence the functional connectivity and to what extent. This study aimed to examine the functional connectivity within DMN, and its diagnostic value with age-related morphometric alterations considered.

Methods:

Whole brain and seed-based resting-state functional connectivity (RSFC) analysis were conducted in cognitively normal APOE ε 4 carriers and matched non-carriers (N=38). The absolute values of mean correlation coefficients (z-values) were used as a measure of functional connectivity strength (FCS) between DMN subregions, which were also used to estimate their diagnostic value by receiver-operating characteristic (ROC) curves.

Results:

APOE ε 4 carriers demonstrated decreased interhemispheric FCS, particularly between right hippocampal formation (R.HF) and left inferior parietal lobular (L.IPL) (t=3.487, p<0.001). ROC analysis showed that the FCS of R.HF and L.IPL could differentiate APOE ε 4 carriers from healthy counterparts (AUC value=0.734, p=0.025). Moreover, after adjusting the impact of morphometry, the differentiated value of FCS of R.HF and L.IPL was markedly improved (AUC value=0.828, p=0.002).

Conclusions:

Our findings suggest that APOE ε 4 allele affects the functional connectivity within posterior DMN, particularly the atrophy-corrected interhemispheric FCS before the clinical expression of neurodegenerative disease.

Keywords

apolipoprotein Efunctional connectivitydefault mode networkneurocognitive disorderAlzheimer's disease

Information

Type
Research Article
Information
International Psychogeriatrics , Volume 29 , Issue 5 , May 2017 , pp. 805 - 814
Copyright
Copyright © International Psychogeriatric Association 2017 

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References

Bero, A. W. et al. (2011). Neuronal activity regulates the regional vulnerability to amyloid-β deposition. Nature Neuroscience, 14, 750–756.Google Scholar
Braak, H. and Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82, 239–259.CrossRefGoogle ScholarPubMed
Buckner, R. L., Andrews-Hanna, J. R. and Schacter, D. L. (2008). The brain's default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38.Google Scholar
Buckner, R. L. et al. (2005). Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. Journal of Neuroscience, 25, 7709–7717.Google Scholar
Buckner, R. L. and Vincent, J. L. (2007). Unrest at rest: default activity and spontaneous network correlations. NeuroImage, 37, 1091–1096.CrossRefGoogle ScholarPubMed
Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E. and Gaskell, P. C. (1993). Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science, 261, 921–923.Google Scholar
Dai, Z. et al. (2014). Identifying and mapping connectivity patterns of brain network hubs in Alzheimer's disease. Cereb Cortex, bhu246.Google Scholar
Damoiseaux, J. S., Prater, K. E., Miller, B. L. and Greicius, M. D. (2012). Functional connectivity tracks clinical deterioration in Alzheimer's disease. Neurobiology Aging, 33, 828.e19–30.Google Scholar
Davies, G. et al. (2014). A genome-wide association study implicates the ApoE locus in nonpathological cognitive ageing. Molecular Psychiatry, 19, 76–87.Google Scholar
De Leon, M. J. et al. (2001). Prediction of cognitive decline in normal elderly subjects with 2-[18F] fluoro-2-deoxy-D-glucose/positron-emission tomography (FDG/PET). Proceedings of National Academy of Sciences USA, 98, 10966–10971.CrossRefGoogle Scholar
Delbeuck, X., Linden, M. V. D. and Collette, F. (2003). Alzheimer's disease as a disconnection syndrome?. Neuropsychology Review, 13, 79–92.Google Scholar
Ding, W. N. et al. (2013). Altered default network resting-state functional connectivity in adolescents with Internet gaming addiction. PloS One, 8, e59902.Google Scholar
Diwadkar, V. A., Carpenter, P. A. and Just, M. A. (2000). Collaborative activity between parietal and dorso-lateral prefrontal cortex in dynamic spatial working memory revealed by fMRI. NeuroImage, 12, 85–99.Google Scholar
Donix, M. et al. (2013). ApoE associated hemispheric asymmetry of entorhinal cortical thickness in aging and Alzheimer's disease. Psychiatry Research, 214, 212–220.Google Scholar
Filippini, N. et al. (2011). Differential effects of the APOE genotype on brain function across the lifespan. Neuroimage, 54, 602–610.Google Scholar
Filippini, N. et al. (2009). Anatomically-distinct genetic associations of ApoE epsilon4 allele load with regional cortical atrophy in Alzheimer's disease. NeuroImage, 44, 724–728.Google Scholar
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C. and Raichle, M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences USA, 102, 9673–9678.Google Scholar
Goveas, J. S. et al. (2013). Functional network endophenotypes unravel the effects of apolipoprotein E epsilon 4 in middle-aged adults. PloS one, 8, e55902.Google Scholar
Greicius, M. D., Srivastava, G., Reiss, A. L. and Menon, V. (2004). Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI. Proceedings of National Academy of Sciences U S A, 101, 4637–4642.Google Scholar
Jack, C. R. et al. (2013). Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurology, 12, 207–216.CrossRefGoogle ScholarPubMed
Jiang, T., He, Y., Zang, Y. and Weng, X. (2004). Modulation of functional connectivity during the resting state and the motor task. Human Brain Mapping, 22, 63–71.Google Scholar
Jones, D. T. et al. (2011). Age-related changes in the default mode network are more advanced in Alzheimer disease. Neurology, 77, 1524–1531.Google Scholar
Kim, D. Y. and Lee, J. H. (2011). Are posterior default-mode networks more robust than anterior default-mode networks? evidence from resting-state fMRI data analysis. Neuroscience Letters, 498, 57–62.Google Scholar
Leech, R. and Sharp, D. J. (2014). The role of the posterior cingulate cortex in cognition and disease. Brain, 137, 12–32.Google Scholar
Li, R. et al. (2014). Multimodal intervention in older adults improves resting-state functional connectivity between the medial prefrontal cortex and medial temporal lobe. Front Aging Neurosci, 6, 39.Google Scholar
Liu, C. C., Kanekiyo, T., Xu, H. and Bu, G. (2013). Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nature Reviews Neurology, 9, 106–118.Google Scholar
Lou, W. et al. (2015). Decreased activity with increased background network efficiency in amnestic MCI during a visuospatial working memory task. Human Brain Mapping, 36, 3387–3403.Google Scholar
Lu, H., Fung, A. W., Chan, S. S. and Lam, L. C. (2016). Disturbance of attention network functions in Chinese healthy older adults: an intra-individual perspective. International Psychogeriatrics, 28, 291–301.Google Scholar
Lu, H., Ma, S. L., Chan, S. S. and Lam, L. C. (2016). The effects of apolipoprotein ε 4 on aging brain in cognitively normal Chinese elderly: a surface-based morphometry study. International Psychogeriatrics, 28, 1503–1511.Google Scholar
Luo, X. et al. (2016). Decreased inter-hemispheric functional connectivity in cognitively intact elderly APOE ɛ4 carriers: a preliminary study. Journal of Alzheimers Disease, 50, 1137–1148.Google Scholar
Ma, S. L., Tang, N. L., Lam, L. C. and Chiu, H. F. (2005). The association between promoter polymorphism of the interleukin-10 gene and Alzheimer's disease. Neurobiology of Aging, 26, 1005–1010.Google Scholar
Machulda, M. M. et al. (2011). Effect of APOE ε4 status on intrinsic network connectivity in cognitively normal elderly subjects. Archives of Neurology, 68, 1131–1136.Google Scholar
Mahley, R. W., Weisgraber, K. H. and Huang, Y. (2006). Apolipoprotein E4: a causative factor and therapeutic target in neuropathology, including Alzheimer's disease. Proceedings of the National Academy of Sciences USA, 103, 5644–5651.Google Scholar
Manza, P., Zhang, S., Hu, S., Chao, H. H., Leung, H. C. and Chiang-shan, R. L. (2015). The effects of age on resting state functional connectivity of the basal ganglia from young to middle adulthood. Neuroimage, 107, 311–322.Google Scholar
Papenberg, G., Lindenberger, U. and Bäckman, L. (2015). Aging-related magnification of genetic effects on cognitive and brain integrity. Trends in Cognitive Sciences, 19, 506–514.Google Scholar
Petersen, S. E. and Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Reviews Neuroscience, 35, 73.Google Scholar
Prince, M., Bryce, R., Albanese, E., Wimo, A., Ribeiro, W. and Ferri, C. P. (2013). The global prevalence of dementia: a systematic review and metaanalysis. Alzheimer's & Dementia, 9, 63–75.Google Scholar
Salvador, R., Suckling, J., Coleman, M. R., Pickard, J. D., Menon, D. and Bullmore, E. D. (2005). Neurophysiological architecture of functional magnetic resonance images of human brain. Cerebral Cortex, 15, 1332–1342.Google Scholar
Saunders, A. M. et al. (1993). Association of apolipoprotein E allele ϵ4 with late-onset familial and sporadic Alzheimer's disease. Neurology, 43, 1467–1467.Google Scholar
Sheline, Y. I. and Raichle, M. E. (2013). Resting state functional connectivity in preclinical Alzheimer's disease. Biological Psychiatry, 74, 340–347.Google Scholar
Sluimer, J. D. et al. (2008). Whole-brain atrophy rate and cognitive decline: longitudinal MR study of memory clinic patients 1. Radiology, 248, 590–598.CrossRefGoogle Scholar
Song, X. W. et al. (2011). REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PloS One, 6, e25031.Google Scholar
Sperling, R. A. et al. (2009). Amyloid deposition is associated with impaired default network function in older persons without dementia. Neuron, 63, 178–188.CrossRefGoogle ScholarPubMed
Szczepanski, S. M. and Knight, R. T. (2014). Insights into human behavior from lesions to the prefrontal cortex. Neuron, 83, 1002–1018.Google Scholar
Tondelli, M., Wilcock, G. K., Nichelli, P., De Jager, C. A., Jenkinson, M. and Zamboni, G. (2012). Structural MRI changes detectable up to ten years before clinical Alzheimer's disease. Neurobiology of Aging, 33, 825–e25.Google Scholar
Vemuri, P. et al. (2010). Effect of apolipoprotein E on biomarkers of amyloid load and neuronal pathology in Alzheimer disease. Annals of Neurology, 67, 308–316.Google Scholar
Vergun, S. et al. (2013). Characterizing functional connectivity differences in aging adults using machine learning on resting state fMRI data. Frontiers in Computational Neuroscience, 7, 38.Google Scholar
Wang, J., Wang, X., He, Y., Yu, X., Wang, H. and He, Y. (2015). Apolipoprotein E ε4 modulates functional brain connectome in Alzheimer's disease. Human Brain Mapping, 36, 1828–1846.Google Scholar
Watanabe, T. et al. (2013). A pairwise maximum entropy model accurately describes resting-state human brain networks. Nature Communications, 4, 1370.Google Scholar
Wikenheiser, A. M. and Redish, A. D. (2012). Hippocampal sequences link past, present, and future. Trends in Cognitive Sciences, 16, 361–362.Google Scholar
Wu, X. et al. (2016). A triple network connectivity study of large-scale brain systems in cognitively normal APOE 4 carriers. Frontiers in Aging Neuroscience, 8, 231.Google Scholar
Xia, M., Wang, J. and He, Y. (2013). BrainNet viewer: the visualization tool a network for human brain connectomics pIoS one, 8.7, e68910.Google Scholar
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