Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-24T01:43:03.913Z Has data issue: false hasContentIssue false
  • English
  • Français

The effects of apolipoprotein ε 4 on aging brain in cognitively normal Chinese elderly: a surface-based morphometry study

Published online by Cambridge University Press:  21 April 2016

Hanna Lu ,
Suk Ling Ma ,
Sandra Sau Man Chan  and
Linda Chiu Wa Lam
Hanna Lu*
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong, SAR China
Suk Ling Ma
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong, SAR China
Sandra Sau Man Chan
Affiliation:
Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Hong Kong, SAR China
Linda Chiu Wa 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 Address, Department of Psychiatry, The Chinese University of Hong Kong, G/F Multicenter, Tai Po Hospital, Tai Po, Hong Kong. Phone: +(852) 6464-1397; Fax: +(852) 2667-5464. Email: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

Default mode network (DMN) has been reported to be susceptible to APOE ε 4 genotype. However, the APOE ε 4-related brain changes in young carriers are different from the ones in elderly carriers. The current study aimed to evaluate the cortical morphometry of DMN subregions in cognitively normal elderly with APOE ε 4.

Method:

11 cognitively normal senior APOE ε 4 carriers and 27 matched healthy controls (HC) participated the neuropsychological tests, genotyping, and magnetic resonance imaging (MRI) scanning. Voxel-based morphometry (VBM) analysis was used to assess the global volumetric changes. Surface-based morphometry (SBM) analysis was performed to measure regional gray matter volume (GMV) and gray matter thickness (GMT).

Results:

Advancing age was associated with decreased GMV of DMN subregions. Compared to HC, APOE ε 4 carriers presented cortical atrophy in right cingulate gyrus (R_CG) (GMV: APOE carriers: 8475.23 ± 1940.73 mm3, HC: 9727.34 ± 1311.57 mm3, t = 2.314, p = 0.026, corrected) and left insular (GMT: APOE ε 4 carriers: 3.83 ± 0.37 mm, HC: 4.05 ± 0.25 mm, t = 2.197, p = 0.033, corrected).

Conclusions:

Our results highlight the difference between different cortical measures and suggest that the cortical reduction of CG and insular maybe a potential neuroimaging marker for APOE 4 ε senior carriers, even in the context of relatively intact cognition.

Keywords

Apolipoprotein Edefault mode networksurface-based morphometryvoxel-based morphometrycingulate gyrusinsula
Type
Research Article
Information
International Psychogeriatrics , Volume 28 , Issue 9 , September 2016 , pp. 1503 - 1511
Copyright
Copyright © International Psychogeriatric Association 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexander, G. E. et al. (2012). Gray matter network associated with risk for Alzheimer's disease in young to middle-aged adults. Neurobiology of Aging, 33, 2723–2732.Google Scholar
Apostolova, L. G. et al. (2010). Surface feature-guided mapping of cerebral metabolic changes in cognitively normal and mildly impaired elderly. Molecular Imaging and Biology: MIB: The Official Publication of the Academy of Molecular Imaging, 12, 218–224.Google Scholar
Ashburner, J. and Friston, K. J. (2005). Unified segmentation. NeuroImage, 26, 839–851.Google Scholar
Association, A. (2015). 2015 Alzheimer's disease facts and figures. Alzheimer's & Dementia, 11, 332–384.Google Scholar
Beckmann, C. F., DeLuca, M., Devlin, J. T. and Smith, S. M. (2005). Investigations into resting-state connectivity using independent component analysis. Philosophical Transactions of the Royal Society B, 360, 1001–1013.Google Scholar
Bero, A. W. et al. (2011). Neuronal activity regulates the regional vulnerability to amyloid-[beta] deposition. Nature Neuroscience, 14, 750–756.Google Scholar
Bonthius, D. J., Solodkin, A. and Van Hoesen, G. W. (2005). Pathology of the insular cortex in Alzheimer disease depends on cortical architecture. Journal of Neuropathology & Experimental Neurology, 64, 910–922.Google Scholar
Braak, H. and Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82, 239–259.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. The Journal of Neuroscience, 25, 7709–7717.Google Scholar
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. and Krienen, F. M. (2013). The evolution of distributed association networks in the human brain. Trends in Cognitive Sciences, 17, 648–665.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
Bunce, D. et al. (2012). APOE genotype and entorhinal cortex volume in non-demented community-dwelling adults in midlife and early old age. Journal of Alzheimer's Disease, 30, 935–942.Google Scholar
Cendes, F., Andermann, F., Frcp, C., Gloor, P. and Evans, A. (1993). MRI volumetric measurement of amygdala and hippocampus in temporal lobe epilepsy. Neurology, 43 (4), 719–725.Google Scholar
Chang, L. J., Yarkoni, T., Khaw, M. W. and Sanfey, A. G. (2013). Decoding the role of the insula in human cognition: functional parcellation and large-scale reverse inference. Cerebral Cortex, 23, 739–749.Google Scholar
Chen, K. et al. (2007). Correlations between apolipoprotein E ε4 gene dose and whole brain atrophy rates. American Journal of Psychiatry, 164, 916–921.Google Scholar
Chu, L. W. et al. (2000). The reliability and validity of the Alzheimer's disease assessment scale cognitive subscale (ADAS-Cog) among the elderly Chinese in Hong Kong. Annals of the Academy of Medicine, Singapore, 29, 474–485.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 the National Academy of Sciences of the United States of America, 98, 10966–10971.Google Scholar
Espeseth, T. et al. (2008). Accelerated age-related cortical thinning in healthy carriers of apolipoprotein E ɛ4. Neurobiology of Aging, 29, 329–340.Google Scholar
Fennema-Notestine, C. et al. (2011). Presence of ApoE ε4 allele associated with thinner frontal cortex in middle age. Journal of Alzheimer's Disease, 26, 49–60.CrossRefGoogle ScholarPubMed
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
Filippini, N. et al. (2011). Differential effects of the APOE genotype on brain function across the lifespan. NeuroImage, 54, 602–610.Google Scholar
Fox, M. D. et al. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102, 9673–9678.CrossRefGoogle Scholar
Frisoni, G. B., Prestia, A., Rasser, P. E., Bonetti, M. and Thompson, P. M. (2009). In vivo mapping of incremental cortical atrophy from incipient to overt Alzheimer's disease. Journal of Neurology, 256, 916–924.Google Scholar
Gomar, J. J. et al. (2014). APOE genotype modulates proton magnetic resonance spectroscopy metabolites in the aging brain. Biological Psychiatry, 75, 686–692.Google Scholar
Good, C. D. et al. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. NeuroImage, 14, 21–36.Google Scholar
Gutiérrez-Galve, L. et al. (2009). Patterns of cortical thickness according to APOE genotype in Alzheimer's disease. Dementia and Geriatric Cognitive Disorders, 28, 476–485.Google Scholar
Honea, R. A., Vidoni, E., Harsha, A. and Burns, J. M. (2009). Impact of APOE on the healthy aging brain: a voxel-based MRI and DTI study. Journal of Alzheimer's Disease, 18, 553–564.Google Scholar
Hwang, K. S. et al. (2013). Mapping cortical atrophy in Parkinson's disease patients with dementia. Journal of Parkinson's Disease, 3, 69–76.CrossRefGoogle ScholarPubMed
Jiang, T., He, Y., Zang, Y. and Weng, X. (2004). Modulation of functional connectivity during the resting state and the motor task. Hum Brain Mapp, 22, 63–71.Google Scholar
Lam, L. C. et al. (2015). Intellectual and physical activities, but not social activities, are associated with better global cognition: a multi-site evaluation of the cognition and lifestyle activity study for seniors in Asia (CLASSA). Age and Ageing, 44, 835–840.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
Lemaître, H. et al. (2005). No epsilon4 gene dose effect on hippocampal atrophy in a large MRI database of healthy elderly subjects. NeuroImage, 24, 1205–1213.CrossRefGoogle 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
Lu, H., Fung, A. W. T., Chan, S. S. M. and Lam, L. C. W. (2015). Disturbance of attention network functions in Chinese healthy older adults: an intra-individual perspective. International Psychogeriatrics, 9, 1–11.Google Scholar
Ma, S. L., Tang, N. L. S., Lam, L. C. W. and Chiu, H. F. K. (2005). The association between promoter polymorphism of the interleukin-10 gene and Alzheimer's disease. Neurobiology of Aging, 26, 1005–1010.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 of the United States of America, 103, 5644–5651.Google Scholar
Pantazis, D. et al. (2010). Comparison of landmark-based and automatic methods for cortical surface registration. NeuroImage, 49, 2479–2493.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
Reiman, E. M. et al. (2012). Brain imaging and fluid biomarker analysis in young adults at genetic risk for autosomal dominant Alzheimer's disease in the presenilin 1 E280A kindred: a case-control study. Lancet Neurology, 11, 1048–1056.Google Scholar
Reiter, K. et al. (2012). Cognitively normal individuals with AD parents may be at risk for developing aging-related cortical thinning patterns characteristic of AD. NeuroImage, 61, 525–532.CrossRefGoogle ScholarPubMed
Saunders, A. M. et al. (1993). Association of apolipoprotein E allele 4 with late-onset familial and sporadic Alzheimer's disease. Neurology, 43, 1467–1472.Google Scholar
Shattuck, D. W. et al. (2008). Construction of a 3D probabilistic atlas of human cortical structures. NeuroImage, 39, 1064–1080.Google Scholar
Shattuck, D. W. and Leahy, R. M. (2002). BrainSuite: An automated cortical surface identification tool. Medical Image Analysis, 6, 129–142.Google Scholar
Shaw, P. et al. (2007). Cortical morphology in children and adolescents with different apolipoprotein E gene polymorphisms: an observational study. The Lancet Neurology, 6, 494–500.Google Scholar
Shi, J. et al. (2014). Genetic influence of apolipoprotein E4 genotype on hippocampal morphometry: an N = 725 surface-based Alzheimer's disease neuroimaging initiative study. Human Brain Mapping, 35, 3903–3918.Google Scholar
Shiino, A. et al. (2006). Four subgroups of Alzheimer's disease based on patterns of atrophy using VBM and a unique pattern for early onset disease. NeuroImage, 33, 17–26.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.Google Scholar
Smith, S. M. et al. (2009). Correspondence of the brain's functional architecture during activation and rest. Proceedings of the National Academy of Sciences of the United States of America, 106, 13040–13045.Google Scholar
Szczepanski, S. M. and Knight, R. T. (2014). Insights into human behavior from lesions to the prefrontal cortex. Neuron, 83, 1002–1018.Google Scholar
Taylor, J. L. et al. (2014). APOE-epsilon4 and aging of medial temporal lobe gray matter in healthy adults over 50. Neurobiology of Aging, 35, 2479–2485.Google Scholar
Uddin, L. Q. (2015). Salience processing and insular cortical function and dysfunction. Nature Reviews Neuroscience, 16, 55–61.Google Scholar
Walhovd, K. B. et al. (2011). Consistent neuroanatomical age-related volume differences across multiple samples. Neurobiology of Aging, 32, 916–932.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
Westlye, L. T., Grydeland, H., Walhovd, K. B. and Fjell, A. M. (2011). Associations between regional cortical thickness and attentional networks as measured by the attention network test. Cerebral Cortex, 21, 345–356.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
Wishart, H. A. et al. (2006). Regional brain atrophy in cognitively intact adults with a single APOE ε4 allele. Neurology, 67, 1221–1224.Google Scholar
Yao, Z. et al. (2015). A FDG-PET study of metabolic networks in apolipoprotein E ε4 allele carriers. PloS One, 10, e0132300.CrossRefGoogle ScholarPubMed
Zhuang, L. et al. (2012). Microstructural white matter changes in cognitively normal individuals at risk of amnestic MCI. Neurology, 79, 748–754.CrossRefGoogle ScholarPubMed