Neuroradiology

, Volume 53, Issue 10, pp 733–748

Gray matter concentration and effective connectivity changes in Alzheimer’s disease: a longitudinal structural MRI study

  • Xingfeng Li
  • Damien Coyle
  • Liam Maguire
  • David R Watson
  • Thomas M McGinnity
Diagnostic Neuroradiology

Abstract

Introduction

Understanding disease progression in Alzheimer’s disease (AD) awaits the resolution of three fundamental questions: first, can we identify the location of “seed” regions where neuropathology is first present? Some studies have suggested the medial temporal lobe while others have suggested the hippocampus. Second, are there similar atrophy rates within affected regions in AD? Third, is there evidence of causality relationships between different affected regions in AD progression?

Methods

To address these questions, we conducted a longitudinal MRI study to investigate the gray matter (GM) changes in AD progression. Abnormal brain regions were localized by a standard voxel-based morphometry method, and the absolute atrophy rate in these regions was calculated using a robust regression method. Primary foci of atrophy were identified in the hippocampus and middle temporal gyrus (MTG). A model based upon the Granger causality approach was developed to investigate the cause–effect relationship over time between these regions based on GM concentration.

Results

Results show that in the earlier stages of AD, primary pathological foci are in the hippocampus and entorhinal cortex. Subsequently, atrophy appears to subsume the MTG.

Conclusion

The causality results show that there is in fact little difference between AD and age-matched healthy control in terms of hippocampus atrophy, but there are larger differences in MTG, suggesting that local pathology in MTG is the predominant progressive abnormality during intermediate stages of AD development.

Keywords

Voxel-based morphometry Longitudinal structural MRI Effective connectivity Alzheimer’s disease Hippocampus and medial temporal gyrus 

References

  1. 1.
    Chetelat G, Degranges B, Sayette VDL, Viader F, Eustache, Baron JC (2002) Mapping grey matter loss with voxel-based morphometry in mild cognitive impairment. NeuroReport 13:1939–1943PubMedCrossRefGoogle Scholar
  2. 2.
    Karas G, Burton EJ, Rombouts SARB, Schijndel RAV, O'Brien JT, Scheltens PH, McKeith IG, Williams D, Ballard C, Barkhof F (2003) A comprehensive study of grey matter loss in patients with Alzheimer's disease using optimized voxel-based morphometry. Neuroimage 18:895–907PubMedCrossRefGoogle Scholar
  3. 3.
    Ashburner J, Friston KJ (2000) Voxel-based morphometry-the methods. Neuroimage 11:805–821PubMedCrossRefGoogle Scholar
  4. 4.
    Davies RR, Scahill VL, Graham A, Williams GB, Graham KS, Hodges JR (2008) Development of an MRI rating scale for multiple brain regions: comparison with volumetrics and with voxel-based morphometry. Neuroradiology 51:491–503CrossRefGoogle Scholar
  5. 5.
    Kakeda S, Korogi Y (2010) The efficacy of a voxel-based morphometry on the analysis of imaging in schizophrenia, temporal lobe epilepsy, and Alzheimer's disease/mild cognitive impairment: a review. Neuroradiology 52:711–721PubMedCrossRefGoogle Scholar
  6. 6.
    Takao H, Abe O, Ohtomo K (2010) Computational analysis of cerebral cortex. Neuroradiology 52:691–698PubMedCrossRefGoogle Scholar
  7. 7.
    Hirata Y, Matsuda H, Nemoto K, Ohnishi T, Hirao K, Yamashita F, Asada T, Iwabuchi S, Samejima H (2005) Voxel-based morphometry to discriminate early Alzheimer's disease from controls. Neurosci Lett 382:269–274PubMedCrossRefGoogle Scholar
  8. 8.
    Li X, Messé A, Marrelec G, Pélégrini-Issac M, Benali H (2010) An enhanced voxel-based morphometry method to investigate structural changes: application to Alzheimer’s disease. Neuroradiology 52:203–213PubMedCrossRefGoogle Scholar
  9. 9.
    Chetelat G, Landeau B, Eustache F, Mezenge F, Viader F, de la Sayette V, Desgranges B, Baron JC (2005) Using voxel-based morphometry to map the structrual changes associated with rapid conversion in MCI: A longitudinal MRI study. Neuroimage 27:934–946PubMedCrossRefGoogle Scholar
  10. 10.
    Nestor PJ, Schetens P, Hodges JR (2004) Advances in the early detection of Alzheimer's disease. Nat Rev Neurosci 7:s34–s41CrossRefGoogle Scholar
  11. 11.
    Fox NC, Warrington EK, Freeborough PA, Hartikainen P, Kennedy AM, Stevens JM, Rossor MN (1996) Presymptomatic hippocampal atrophy in Alzheimer's disease: a longitudinal MRI study. Brain 119:2001–2007PubMedCrossRefGoogle Scholar
  12. 12.
    Whitwell JL, Przybelski SA, Weigand SD, Knopman DS, Boeve BF, Petersen RC, Jack CR Jr (2007) 3D maps from multiple MRI illustrate changing atrophy patterns as subjects progress from mild cognitive impairment to Alzheimer's disease. Brain 130:1777–1786PubMedCrossRefGoogle Scholar
  13. 13.
    Chan D, Janssen JC, Whitwell JL, Watt HC, Jenkins R, Frost C, Rossor MN, Fox NC (2003) Change in rates of cerebral atrophy over time in early-onset Alzheimer's disease: longitudinal MRI study. Lancet 362:1121–1122PubMedCrossRefGoogle Scholar
  14. 14.
    Schott JM, Fox NC, Frost C, Scahill RI, Jassen JC, Chan D, Jenkins R, Rossor MN (2003) Assessing the onset of structural change in familial Alzheimer's disease. Ann Neurol 53:181–188PubMedCrossRefGoogle Scholar
  15. 15.
    Fox NC, Schott JM (2004) Imaging cerebral atrophy: normal ageing to Alzheimer's disease. Lancet 363:392–394PubMedCrossRefGoogle Scholar
  16. 16.
    Schuff N, Woerner N, Boreta L, Kornfield T, Shaw LM, Trojanowski JQ, Thompson PM, Jack CR Jr, Weiner MW (2009) MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers. Brain 132:1067–1077PubMedCrossRefGoogle Scholar
  17. 17.
    Ridha BH, Barnes J, Barlett JW, Godolt A, Pepple T, Rossor MN, Fox NC (2006) Tracking atrophy progression in familial Alzheimer's disease: a serial MRI study. Lancet Neurol 5:824–834CrossRefGoogle Scholar
  18. 18.
    Schill RI, Frost C, Jenkins R, Whitwell JL, Rossor MN, Fox NC (2003) A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. Arch Neurol 60:989–994CrossRefGoogle Scholar
  19. 19.
    Zeger SL, Liang KY (1991) Feedback models for discrete and continuous time series. Stat Sin 1:51–64Google Scholar
  20. 20.
    Diggle PJ, Heagerty P, Liang KY, Zeger S (2003) Analysis of longitudinal data, 2nd edn. Oxford University Press, OxfordGoogle Scholar
  21. 21.
    Whitwell JL (2008) Longitudinal imaging: change and causality. Curr Opin Neurol 21:410–416PubMedCrossRefGoogle Scholar
  22. 22.
    Granger C (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37:424–438CrossRefGoogle Scholar
  23. 23.
    Braak H, Braak E (1996) Evolution of the neuropathology of Alzheimer's disease. Acta Neurol Scand Suppl 165:3–12PubMedGoogle Scholar
  24. 24.
    Jack CR Jr, Weigand SD, Shiung MM, Przybelski SA, O'Brien PC, Gunter JL, Knopman DS, Boeve BF, Smith GE, Petersen RC (2008) Atrophy rates accelerate in Amnestic mild cognitive impairment. Neurology 70:1740–1752PubMedCrossRefGoogle Scholar
  25. 25.
    Jack CR Jr, Shiung MM, Gunter JL, O'Brien PC, Weigand SD, Knopman DS, Boeve BF, Ivnik RJ, Smith GE, Cha RH, Tangalos EG, Petersen RC (2004) Comparison of different MRI atrophy rate measures with clinical disease progression in AD. Neurology 62:591–600PubMedGoogle Scholar
  26. 26.
    Resnick SM, Pham DL, Kraut MA, Zonderman AB, Davatzikos C (2003) Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain. J Neurosci 23:3295–3301PubMedGoogle Scholar
  27. 27.
    Marcus DS, Fotenos AF, Csernansky JG, Morris JC, Buckner RL (2009) Open access series of imaging studies: longitudinal MRI data in nondemented and demented older adults. J Cog Neurosci 22(12):2677–2678CrossRefGoogle Scholar
  28. 28.
    Marcus DS, Wang TH, Parker J, Csernansky JG, Morris JC, Buckner RL (2007) Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. J Cog Neurosci 19:1498–1507CrossRefGoogle Scholar
  29. 29.
    Morris JC (1997) Clinical dementia rating: A reliable and valid diagnostic and staging measure for dementia of the Alzheimer type. Int Psychogenatrics 9(suppl 1):173–176CrossRefGoogle Scholar
  30. 30.
    Morris JC (1993) The clinical dementia rating (CDR): Current version and scoring rules. Neurology 43:2412b–2414bGoogle Scholar
  31. 31.
    Talairach J, Tournoux P (1998) Coplanar stereotaxic atlas of the human brain. Thieme, StuttgartGoogle Scholar
  32. 32.
    Smith SM (2002) Fast robust automated brain extraction. Hum Brain Mapp 17:143–155PubMedCrossRefGoogle Scholar
  33. 33.
    Zhang Y, Brady M, Smith SM (2001) Segmentation of brain MR images through a hidden Markov random field model and the expectation maximization. IEEE Trans Med Imag 21:45–47CrossRefGoogle Scholar
  34. 34.
    Jenkinson M, Smith SM (2001) A global optimisation method for robust affine registration of brain images. Med Image Anal 5:143–156PubMedCrossRefGoogle Scholar
  35. 35.
    Rueckert D, Sonda LI, Hayes C, Hill DLG, Leach MO, Hawkes DJ (1999) Non-rigid registration using free-form deformations: application to breast MR images. IEEE Trans Med Imag 18:712–721CrossRefGoogle Scholar
  36. 36.
    Nichols TE, Hayasaka S (2003) Controlling the familywise error rate in functional neuroimaging: a comparative reviews. Stat Meth Med Res 12:419–446CrossRefGoogle Scholar
  37. 37.
    Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M (2002) Automated anatomical labelling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273–289PubMedCrossRefGoogle Scholar
  38. 38.
    Huber PJ (1981) Robust statistics. Wiley, HobokenCrossRefGoogle Scholar
  39. 39.
    Bryk AS, Raudenbush SW (1992) Hierarchical linear models: applications and data analysis methods. Sage, New DelhiGoogle Scholar
  40. 40.
    Sullivan LM, Dukes KA, Losina E (1999) Tutorial in biostatistics: An introduction to hierarachical linear modelling. Statist Med 18:855–888CrossRefGoogle Scholar
  41. 41.
    Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A (2004) Changes in grey matter induced by training. Nature 427:311–312PubMedCrossRefGoogle Scholar
  42. 42.
    Draganski B, Gaser C, Kempermann G, Kuhn HG, Winkler J, Buchel C, May A (2006) Temporal and spatial dynamics of brain structure changes during extensive learning. J Neurosci 26:6314–6317PubMedCrossRefGoogle Scholar
  43. 43.
    Salat DH, Tuch DS, van der Kouwe AJW, Greve DN, Pappu V, Lee SY, Hevelonea ND, Zalet AK, Growdon JH, Corkin S, Fischl B, Rosasa HD (2010) White matter pathology isolates the hippocampal formation in Alzheimer's disease. Neurobiol Aging 31:244–256PubMedCrossRefGoogle Scholar
  44. 44.
    Zhang Y, Schuff N, Du AT, Rosen HJ, Kramer JH, Gorno-Tempini ML, Miller BL, Weiner MW (2009) White matter damage in frontotemporal dementia and Alzheimer's disease measured by diffusion MRI. Brain 132:2579–2592PubMedCrossRefGoogle Scholar
  45. 45.
    Fellgiebel A, Wille P, Muller MJ, Winterer G, Scheurich A, Vucurevic G, Schmidt LG, Stoeter P (2004) Ultrastructural hippocampal and white matter alterations in mild cognitive impairment: a diffusion tensor imaging study. Dement Geriatr Cogn Disord 18:101–108PubMedCrossRefGoogle Scholar
  46. 46.
    Muller MJ, Greverus D, Dellani PR, Weibrich C, Wille PR, Scheurich A, Stoeter P, Fellgiebel A (2005) Functional implications of hippocampal volume and diffusivity in mild cognitive impairment. Neuroimage 28:1033–1042PubMedCrossRefGoogle Scholar
  47. 47.
    Chetelat G, Villain N, Desgranges B, Eustache F, Baron JC (2009) Posterior cingulate hypometabolism in early Alzheimer's disease: what is the contribution of local atrophy versus disconnection? Brain 132:1–2CrossRefGoogle Scholar
  48. 48.
    Vincent JL, Snyder AZ, Fox MD, Shannon BJ, Andrews JR, Raichle ME, Buckner RL (2006) Coherent spontaneous activity identifies a hippocampal-parietal memory network. J Neurophysiol 96:3517–3531PubMedCrossRefGoogle Scholar
  49. 49.
    Seeley WM, Crawford RK, Zhou J, Miller BL, Greicius MD (2009) Neurodegenerative diseases target large-scale human brain networks. Neuron 62:42–56PubMedCrossRefGoogle Scholar
  50. 50.
    Haan WD, Pijnenburg YL, Strijers RLM, Made YVD, Flier WMVD, Scheltens P, Stam CJ (2009) Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory. BMC Neurosci 10:1–12CrossRefGoogle Scholar
  51. 51.
    Stam CJ, Haan WDE, Daffertshofer A, Jones BF, Manshanden I, Van Cappellen V, Van Walsum AM, Montez T, Verbunt JPA, de Munck JC, Van Dijk BW, Berendse HW, Scheltens P (2009) Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer's disease. Brain 132:213–224PubMedCrossRefGoogle Scholar
  52. 52.
    Celone K, Calhoun V, Dickerson B, Atri A, Chua EF, Miller SL, DePeau K, Rentz DM, Selkoe DJ, Blacker D, Albert MS, Sperling RA (2006) Alterations in memory networks in mild cognitive impairment and Alzheimer's Disease: an independent component analysis. J Neurosci 26:10222–10231PubMedCrossRefGoogle Scholar
  53. 53.
    Supekar K, Menon V, Rubin D, Musen M, Greicius MD (2008) Network analysis of Intrinsic functional brain connectivity in Alzheimer's Disease. PLoS Comput Biol 4:1–11CrossRefGoogle Scholar
  54. 54.
    Greicius MD, Srivastava G, Reiss A, Menon V (2004) Default-mode network activity distinguishes Alzheimer's Disease from healthy aging: Evidence from functional MRI. Proc Nat Acad Sci 101:4637–4642PubMedCrossRefGoogle Scholar
  55. 55.
    Lemieux L (2008) Causes, relationships and explanations: the power and limitations of observational longitudinal imaging studies. Curr Opin Neurol 21:391–392PubMedCrossRefGoogle Scholar
  56. 56.
    Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198PubMedCrossRefGoogle Scholar
  57. 57.
    Good C, Johnsrude IS, Ashburner J, Henson RN, Friston KJ, Frackowiak RS (2001) A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 14:21–36PubMedCrossRefGoogle Scholar
  58. 58.
    Faes L, Nollo G, Chon KH (2008) Assessment of Granger causality by nonlinear model identification: application to short-term cardiovascular variability. Ann Biomed Eng 36:381–395PubMedCrossRefGoogle Scholar
  59. 59.
    Shaman P, Stine RA (1998) The bias of autoregressive coefficient estimators. J Am Stat Assoc 83:842–848CrossRefGoogle Scholar
  60. 60.
    Li X, Marrelec G, Hess RF, Benali H (2010) A nonlinear identification method to study effective connectivity in functional MRI. Med Image Analy 14:30–38CrossRefGoogle Scholar
  61. 61.
    Wernerheim C (2000) Cointegration and causality in the exports-GDP nexus: the post-war evidence for Canada. Empirical Econ 25:111–125CrossRefGoogle Scholar
  62. 62.
    Oxley L, Greasley D (1998) Vector autoregression, cointegration and causality: testing for causes of the British industrial revolution. Appl Econ 30:1387–1397CrossRefGoogle Scholar
  63. 63.
    Doornik J (1996) Testing vector error autocorrelation and heteroscdasticity. The Econometric Society 7th World Congress, Tokyo, 1996.Google Scholar
  64. 64.
    Durbin J (1970) Testing for serial correlation in least squares regression when some of the regressors are lagged dependent variables. Econometrica 38:410–421CrossRefGoogle Scholar
  65. 65.
    Breslow NE, Clayton DG (1993) Approximate inference in generalized linear mixed models. J Am Stat Assoc 88:9–25CrossRefGoogle Scholar
  66. 66.
    Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J Roy Stat Soc B 39:1–38Google Scholar
  67. 67.
    Laird NM, Lange N, Stram D (1987) Maximum likelihood computations with repeated measures: Application of the EM algorithm. J Am Stat Assoc 82:97–105CrossRefGoogle Scholar
  68. 68.
    Laird NM, Ware JH (1982) Random-effects models for longitudinal data. Biometrics 38:963–974PubMedCrossRefGoogle Scholar
  69. 69.
    Worsley K, Liao CH, Aston J, Petre V, Duncan GH, Morales F, Evans AC (2002) A general statistical analysis for fMRI data. Neuroimage 15:1–15PubMedCrossRefGoogle Scholar
  70. 70.
    Liang KY, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73:13–22, Neuroimage 11:805–821CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Xingfeng Li
    • 1
  • Damien Coyle
    • 1
  • Liam Maguire
    • 1
  • David R Watson
    • 1
  • Thomas M McGinnity
    • 1
  1. 1.Intelligent Systems Research Centre, Magee CampusUniversity of UlsterDerryUK

Personalised recommendations