Changes In Cortical Thickness Mirror Loss of Network Connectivity in AD

The arrangement of linked brain regions into functional networks supports complex mental activity, and these critical connections have been found repeatedly to break up early in Alzheimer disease (see ARF related news story and ARF news story). In particular, the disruption of networks involved in memory formation have been extensively studied in both AD and normal aging using functional MRI (see ARF related news story and ARF news story).

A new report from Alan Evans of McGill University in Montreal, Quebec, puts a structural face on these functional studies. Just as functional correlations among brain regions weaken in AD, so do correlations of cortical thickness as measured by MRI, Evans and coauthors report in the April 30 Journal of Neuroscience. The work provides a different, anatomical measure of brain organization and its disruption in disease.

The cerebral cortex is the grey matter that forms the outermost layer of the cerebrum. It varies in thickness from about 1 mm to 7 mm in different parts of the brain, and grows thinner with age and with Alzheimer disease. Recent work from Evans and others has suggested that cortical thickness is correlated in regions of the brain that are known to be functionally connected. This has led to the idea that brain-wide maps of thickness correlations reveal the architecture of cortical networks (He et al., 2007; Chen et al., 2008).

In the current study, coauthors Yong He and Zhang Chen analyze global cortical thickness measures from MRI images of 97 healthy elderly people and 92 with AD, all from the Open Access Series of Imaging Studies database (OASIS, see Marcus et al., 2007). Their results indicate that interregional thickness correlations are greatly disrupted in the AD patients. This disruption shows up in the form of mismatches in thickness between specific cortical regions that are normally similar. The AD brains also reveal global changes in correlation characteristics, and a network analysis indicates the changes could result in a less efficient network architecture and lower resistance to further disruption.

Cortical thickness reflects the size, density, and arrangement of cells, and so it might not be surprising that structural correlations diminish under assault from AD pathology and associated cortical thinning. But do these structural alterations relate to the functional changes seen in AD patients? In support of this idea, the authors note that the structural networks they identify in healthy brain coincide with functional networks defined by fMRI, and are known to be disrupted in AD.

Interestingly, Evans and colleagues observed an increased positive correlation among several brain regions involved in the default network. That distributed network has gotten a lot of attention in AD, as it is involved in memory, is functionally disturbed early on in AD, and is an early site of amyloid deposition (see ARF related news story). Evans and coauthors speculate that the increased correlation of cortical thickness in these areas “may reflect a correlative cortical shrinking because of shared vulnerability to an insult, as preferentially affected by the pathological process of this disease.” In support of this idea, data tying amyloid deposition to cortical thinning in the default regions was presented recently by Keith Johnson of Massachusetts General Hospital, Boston, at the Human Amyloid Imaging conference in Chicago (see ARF related news story).

Beyond the current study, analysis of cortical thickness correlations represents a promising approach to look at distributed changes in the brain in AD, Evans told ARF. Rather than look at morphological changes in select regions of the brain, for example, by measuring hippocampal volume, Evans said, “Cortical thickness is a global index. We can extract it automatically over the entire cortex, and do exploratory analysis without making assumptions about which areas are important.” The program that Evans has developed to automate the analysis can be applied to large collections of MRI data. Using such collections, Evans has worked on large studies looking at cortical thickness during brain development in children (Evans et al., 2006, and see ARF related news story). With the advent of large, collaborative imaging studies such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and its counterparts in Japan and Europe, there will be a lot more data available to pursue with this approach. One goal will be to determine which changes in cortical thickness networks correlate best with the progression of AD, Evans said.—Pat McCaffrey

Comments

  1. This just published paper takes an interesting approach to analyzing structural MRI in AD patients. The authors establish a relationship between regional changes in cortical thickness to identify structural brain networks. As with other previous studies examining cortical changes such as thickness, ventricular enlargement, or morphological assessment of specific structures and regions (frequently in the limbic system), these studies provide a framework for understanding the pathophysiology of AD. This paper also is one of the first to integrate what are frequently independent assessments of regional cortical changes in AD. Since the brain is highly connected and any disruption of that connection likely has profound behavioral consequences, this kind of topological approach is an important contribution. Related findings using a mapping approach that incorporates a temporal domain (Thompson et al., 2003) have also demonstrated disruption of systems and networks in AD. Collectively, these approaches, in combination with functional measures, will help establish a comprehensive view of the degenerative effects of AD.

    References:

    Thompson PM, Hayashi KM, de Zubicaray G, Janke AL, Rose SE, Semple J, Herman D, Hong MS, Dittmer SS, Doddrell DM, Toga AW. Dynamics of gray matter loss in Alzheimer's disease. J Neurosci. 2003 Feb 1;23(3):994-1005. PubMed.

    View all comments by Arthur Toga

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References

News Citations

  1. Network Diagnostics: "Default-Mode" Brain Areas Identify Early AD
  2. Boston: Resting State MRI Shows Loss of Network Connectivity Early in AD
  3. New Technologies Help Define Old Age
  4. Deactivation Flaws Predict Memory Troubles
  5. Network News: Images of AD Brains Reveal Widespread Snafus
  6. HAI Chicago: PIB and Aβ Show Regional Nuances and Sleep-Wake Rhythm
  7. Little Einsteins: High IQ Linked to Plasticity in Young Cortex

Paper Citations

  1. He Y, Chen ZJ, Evans AC. Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb Cortex. 2007 Oct;17(10):2407-19. PubMed.
  2. Chen ZJ, He Y, Rosa-Neto P, Germann J, Evans AC. Revealing modular architecture of human brain structural networks by using cortical thickness from MRI. Cereb Cortex. 2008 Oct;18(10):2374-81. PubMed.
  3. Marcus DS, Wang TH, Parker J, Csernansky JG, Morris JC, Buckner RL. Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. J Cogn Neurosci. 2007 Sep;19(9):1498-507. PubMed.

Further Reading

Primary Papers

  1. He Y, Chen Z, Evans A. Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's disease. J Neurosci. 2008 Apr 30;28(18):4756-66. PubMed.

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