Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease

Translational Neurodegeneration

Lan Tan¹  Joaquim Radua³  Lin Tan⁴  Jun Wang⁵  Hui-Fu Wang¹  Rui-Hua Yin⁵  Yong Liu²  Jin-Tai Yu¹  Wen-Ying Wang⁵ 

[1] Department of Neurology, Qingdao Municipal Hospital, Nanjing Medical University, Nanjing 266071, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;Research Unit, FIDMAG Germanes Hospitala’ries—CIBERSAM, Sant Boi de Llobregat, Barcelona, Spain;College of Medicine and Pharmaceutics, Ocean University of China, Qingdao 266011, China;Department of Neurology, Qingdao Municipal Hospital, School of Medicine, Qingdao University, No.5 Donghai Middle Road, Qingdao 266071, Shandong Province, China

关键词: Effect size signed differential mapping (ES-SDM);    Magnetic resonance imaging (MRI);    Meta-analysis;    Grey matter (GM);    Alzheimer’s disease (AD);    Voxel-based morphometry (VBM);   

Others  :  1172215
DOI  :  10.1186/s40035-015-0027-z

 received in 2014-11-08, accepted in 2015-03-18,  发布年份 2015

【 摘 要 】

Background

Voxel-based morphometry (VBM) using structural brain MRI has been widely used for the assessment of impairment in Alzheimer’s disease (AD), but previous studies in VBM studies on AD remain inconsistent.

Objective

We conducted meta-analyses to integrate the reported studies to determine the consistent grey matter alterations in AD based on VBM method.

Methods

The PubMed, ISI Web of Science, EMBASE and Medline database were searched for articles between 1995 and June 2014. Manual searches were also conducted, and authors of studies were contacted for additional data. Coordinates were extracted from clusters with significant grey matter difference between AD patients and healthy controls (HC). Meta-analysis was performed using a new improved voxel-based meta-analytic method, Effect Size Signed Differential Mapping (ES-SDM).

Results

Thirty data-sets comprising 960 subjects with AD and 1195 HC met inclusion criteria. Grey matter volume (GMV) reduction at 334 coordinates in AD and no GMV increase were found in the current meta-analysis. Significant reductions in GMV were robustly localized in the limbic regions (left parahippocampl gyrus and left posterior cingulate gyrus). In addition, there were GM decreases in right fusiform gyrus and right superior frontal gyrus. The findings remain largely unchanged in the jackknife sensitivity analyses.

Conclusions

Our meta-analysis clearly identified GMV atrophy in AD. These findings confirm that the most prominent and replicable structural abnormalities in AD are in the limbic regions and contributes to the understanding of pathophysiology underlying AD.

【 授权许可】

   
2015 Wang et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

【 参考文献 】

• [1]Pereira JM, Xiong L, Acosta-Cabronero J, Pengas G, Williams GB, Nestor PJ: Registration accuracy for VBM studies varies according to region and degenerative disease grouping. NeuroImage 2010, 49(3):2205-15. doi:10.1016/j.neuroimage.2009.10.068
• [2]Busatto GF, Diniz BS, Zanetti MV: Voxel-based morphometry in Alzheimer’s disease. Expert Rev Neurother 2008, 8(11):1691-702. doi:10.1586/14737175.8.11.1691
• [3]Costafreda SG, David AS, Brammer MJ: A parametric approach to voxel-based meta-analysis. NeuroImage 2009, 46(1):115-22. doi:10.1016/j.neuroimage.2009.01.031
• [4]Ferreira LK, Diniz BS, Forlenza OV, Busatto GF, Zanetti MV: Neurostructural predictors of Alzheimer’s disease: a meta-analysis of VBM studies. Neurobiol Aging 2011, 32(10):1733-41. doi:10.1016/j.neurobiolaging.2009.11.008
• [5]Whitwell JL, Przybelski SA, Weigand SD, Knopman DS, Boeve BF, Petersen RC, et al.: 3D maps from multiple MRI illustrate changing atrophy patterns as subjects progress from mild cognitive impairment to Alzheimer’s disease. Brain 2007, 130(Pt 7):1777-86. doi:10.1093/brain/awm112
• [6]Karas GB, Burton EJ, Rombouts SA, van Schijndel RA, O’Brien JT, Scheltens P, et al.: A comprehensive study of gray matter loss in patients with Alzheimer’s disease using optimized voxel-based morphometry. NeuroImage 2003, 18(4):895-907.
• [7]Hirata Y, Matsuda H, Nemoto K, Ohnishi T, Hirao K, Yamashita F, et al.: Voxel-based morphometry to discriminate early Alzheimer’s disease from controls. Neurosci Lett 2005, 382(3):269-74. doi:10.1016/j.neulet.2005.03.038
• [8]Whitwell JL, Jack CR Jr, Przybelski SA, Parisi JE, Senjem ML, Boeve BF, et al.: Temporoparietal atrophy: a marker of AD pathology independent of clinical diagnosis. Neurobiol Aging 2011, 32(9):1531-41. doi:10.1016/j.neurobiolaging.2009.10.012
• [9]Radua J, Mataix-Cols D, Phillips ML, El-Hage W, Kronhaus DM, Cardoner N, et al.: A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. Eur Psychiatry 2012, 27(8):605-11. doi:10.1016/j.eurpsy.2011.04.001
• [10]Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al.: Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000, 283(15):2008-12.
• [11]Guo Y, Zhang Z, Zhou B, Wang P, Yao H, Yuan M, et al.: Grey-matter volume as a potential feature for the classification of Alzheimer’s disease and mild cognitive impairment: an exploratory study. Neurosci Bull 2014, 30(3):477-89. doi:10.1007/s12264-013-1432-x
• [12]Rami L, Sole-Padulles C, Fortea J, Bosch B, Llado A, Antonell A, et al.: Applying the new research diagnostic criteria: MRI findings and neuropsychological correlations of prodromal AD. Int J Geriatr Psychiatry 2012, 27(2):127-34. doi:10.1002/gps.2696
• [13]Lehmann M, Crutch SJ, Ridgway GR, Ridha BH, Barnes J, Warrington EK, et al.: Cortical thickness and voxel-based morphometry in posterior cortical atrophy and typical Alzheimer’s disease. Neurobiol Aging 2011, 32(8):1466-76. doi:10.1016/j.neurobiolaging.2009.08.017
• [14]Serra L, Cercignani M, Lenzi D, Perri R, Fadda L, Caltagirone C, et al.: Grey and white matter changes at different stages of Alzheimer’s disease. J Alzheimers Dis 2010, 19(1):147-59. doi:10.3233/JAD-2010-1223
• [15]Kanda T, Ishii K, Uemura T, Miyamoto N, Yoshikawa T, Kono AK, et al.: Comparison of grey matter and metabolic reductions in frontotemporal dementia using FDG-PET and voxel-based morphometric MR studies. Eur J Nucl Med Mol Imaging 2008, 35(12):2227-34. doi:10.1007/s00259-008-0871-5
• [16]Whitwell JL, Jack CR Jr, Kantarci K, Weigand SD, Boeve BF, Knopman DS, et al.: Imaging correlates of posterior cortical atrophy. Neurobiol Aging 2007, 28(7):1051-61. doi:10.1016/j.neurobiolaging.2006.05.026
• [17]Rabinovici GD, Seeley WW, Kim EJ, Gorno-Tempini ML, Rascovsky K, Pagliaro TA, et al.: Distinct MRI atrophy patterns in autopsy-proven Alzheimer’s disease and frontotemporal lobar degeneration. Am J Alzheimers Dis Other Demen 2007, 22(6):474-88. doi:10.1177/1533317507308779
• [18]Di Paola M, Macaluso E, Carlesimo GA, Tomaiuolo F, Worsley KJ, Fadda L, et al.: Episodic memory impairment in patients with Alzheimer’s disease is correlated with entorhinal cortex atrophy. A voxel-based morphometry study. J Neurol 2007, 254(6):774-81. doi:10.1007/s00415-006-0435-1
• [19]Ishii K, Kawachi T, Sasaki H, Kono AK, Fukuda T, Kojima Y, et al.: Voxel-based morphometric comparison between early- and late-onset mild Alzheimer’s disease and assessment of diagnostic performance of z score images. AJNR Am J Neuroradiol 2005, 26(2):333-40.
• [20]Boxer AL, Rankin KP, Miller BL, Schuff N, Weiner M, Gorno-Tempini ML, et al.: Cinguloparietal atrophy distinguishes Alzheimer disease from semantic dementia. Arch Neurol 2003, 60(7):949-56. doi:10.1001/archneur.60.7.949
• [21]Frisoni GB, Testa C, Zorzan A, Sabattoli F, Beltramello A, Soininen H, et al.: Detection of grey matter loss in mild Alzheimer’s disease with voxel based morphometry. J Neurol Neurosurg Psychiatry 2002, 73(6):657-64.
• [22]Ibrahim I, Horacek J, Bartos A, Hajek M, Ripova D, Brunovsky M, et al.: Combination of voxel based morphometry and diffusion tensor imaging in patients with Alzheimer’s disease. Neuro Endocrinol Lett 2009, 30(1):39-45.
• [23]Guo X, Wang Z, Li K, Li Z, Qi Z, Jin Z, et al.: Voxel-based assessment of gray and white matter volumes in Alzheimer’s disease. Neurosci Lett 2010, 468(2):146-50. doi:10.1016/j.neulet.2009.10.086
• [24]Hamalainen A, Pihlajamaki M, Tanila H, Hanninen T, Niskanen E, Tervo S, et al.: Increased fMRI responses during encoding in mild cognitive impairment. Neurobiol Aging 2007, 28(12):1889-903. doi:10.1016/j.neurobiolaging.2006.08.008
• [25]Ohnishi T, Matsuda H, Tabira T, Asada T, Uno M: Changes in brain morphology in Alzheimer disease and normal aging: is Alzheimer disease an exaggerated aging process? AJNR Am J Neuroradiol 2001, 22(9):1680-5.
• [26]Bozzali M, Filippi M, Magnani G, Cercignani M, Franceschi M, Schiatti E, et al.: The contribution of voxel-based morphometry in staging patients with mild cognitive impairment. Neurology 2006, 67(3):453-60. doi:10.1212/01.wnl.0000228243.56665.c2
• [27]Shiino A, Watanabe T, Maeda K, Kotani E, Akiguchi I, Matsuda M: Four subgroups of Alzheimer’s disease based on patterns of atrophy using VBM and a unique pattern for early onset disease. NeuroImage 2006, 33(1):17-26. doi:10.1016/j.neuroimage.2006.06.010
• [28]Samuraki M, Matsunari I, Chen WP, Yajima K, Yanase D, Fujikawa A, et al.: Partial volume effect-corrected FDG PET and grey matter volume loss in patients with mild Alzheimer’s disease. Eur J Nucl Med Mol Imaging 2007, 34(10):1658-69. doi:10.1007/s00259-007-0454-x
• [29]Gili T, Cercignani M, Serra L, Perri R, Giove F, Maraviglia B, et al.: Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution. J Neurol Neurosurg Psychiatry 2011, 82(1):58-66. doi:10.1136/jnnp.2009.199935
• [30]Teipel SJ, Wegrzyn M, Meindl T, Frisoni G, Bokde AL, Fellgiebel A, et al.: Anatomical MRI and DTI in the diagnosis of Alzheimer’s disease: a European multicenter study. J Alzheimers Dis 2012, 31(Suppl 3):S33-47. doi:10.3233/JAD-2012-112118
• [31]Raji CA, Lopez OL, Kuller LH, Carmichael OT, Becker JT: Age, Alzheimer disease, and brain structure. Neurology 2009, 73(22):1899-905. doi:10.1212/WNL.0b013e3181c3f293
• [32]Honea RA, Thomas GP, Harsha A, Anderson HS, Donnelly JE, Brooks WM, et al.: Cardiorespiratory fitness and preserved medial temporal lobe volume in Alzheimer disease. Alzheimer Dis Assoc Disord 2009, 23(3):188-97. doi:10.1097/WAD.0b013e31819cb8a2
• [33]Brambati SM, Belleville S, Kergoat MJ, Chayer C, Gauthier S, Joubert S: Single- and multiple-domain amnestic mild cognitive impairment: two sides of the same coin? Dement Geriatr Cogn Disord 2009, 28(6):541-9. doi:10.1159/000255240
• [34]Matsuda H, Kitayama N, Ohnishi T, Asada T, Nakano S, Sakamoto S, et al.: Longitudinal evaluation of both morphologic and functional changes in the same individuals with Alzheimer’s disease. J Nucl Med 2002, 43(3):304-11.
• [35]Busatto GF, Garrido GE, Almeida OP, Castro CC, Camargo CH, Cid CG, et al.: A voxel-based morphometry study of temporal lobe gray matter reductions in Alzheimer’s disease. Neurobiol Aging 2003, 24(2):221-31.
• [36]Brenneis C, Wenning GK, Egger KE, Schocke M, Trieb T, Seppi K, et al.: Basal forebrain atrophy is a distinctive pattern in dementia with Lewy bodies. Neuroreport 2004, 15(11):1711-4.
• [37]Zahn R, Buechert M, Overmans J, Talazko J, Specht K, Ko CW, et al.: Mapping of temporal and parietal cortex in progressive nonfluent aphasia and Alzheimer’s disease using chemical shift imaging, voxel-based morphometry and positron emission tomography. Psychiatr Res 2005, 140(2):115-31. doi:10.1016/j.pscychresns.2005.08.001
• [38]Baxter LC, Sparks DL, Johnson SC, Lenoski B, Lopez JE, Connor DJ, et al.: Relationship of cognitive measures and gray and white matter in Alzheimer’s disease. J Alzheimers Dis 2006, 9(3):253-60.
• [39]Hirao K, Ohnishi T, Matsuda H, Nemoto K, Hirata Y, Yamashita F, et al.: Functional interactions between entorhinal cortex and posterior cingulate cortex at the very early stage of Alzheimer’s disease using brain perfusion single-photon emission computed tomography. Nucl Med Commun 2006, 27(2):151-6.
• [40]Tombaugh TN, McIntyre NJ: The mini-mental state examination: a comprehensive review. J Am Geriatr Soc 1992, 40(9):922-35.
• [41]Goto M, Abe O, Aoki S, Hayashi N, Ohtsu H, Takao H, et al.: Longitudinal gray-matter volume change in the default-mode network: utility of volume standardized with global gray-matter volume for Alzheimer’s disease: a preliminary study. Radiol Phys Technol 2015, 8(1):64-72. doi:10.1007/s12194-014-0295-9
• [42]Wu X, Li R, Fleisher AS, Reiman EM, Guan X, Zhang Y, et al.: Altered default mode network connectivity in Alzheimer’s disease–a resting functional MRI and Bayesian network study. Hum Brain Mapp 2011, 32(11):1868-81. doi:10.1002/hbm.21153
• [43]Greicius MD, Srivastava G, Reiss AL, Menon V: Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A 2004, 101(13):4637-42. doi:10.1073/pnas.0308627101
• [44]Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD: Neurodegenerative diseases target large-scale human brain networks. Neuron 2009, 62(1):42-52. doi:10.1016/j.neuron.2009.03.024
• [45]Pagani M, Salmaso D, Rodriguez G, Nardo D, Nobili F: Principal component analysis in mild and moderate Alzheimer’s disease–a novel approach to clinical diagnosis. Psychiatr Res 2009, 173(1):8-14. doi:10.1016/j.pscychresns.2008.07.016
• [46]Jacobs HI, Van Boxtel MP, Jolles J, Verhey FR, Uylings HB: Parietal cortex matters in Alzheimer’s disease: an overview of structural, functional and metabolic findings. Neurosci Biobehav Rev 2012, 36(1):297-309. doi:10.1016/j.neubiorev.2011.06.009
• [47]Wang Y, Chen K, Yao L, Jin Z, Guo X: Structural interactions within the default mode network identified by Bayesian network analysis in Alzheimer’s disease. PLoS One 2013, 8(8):e74070. doi:10.1371/journal.pone.0074070
• [48]Yang J, Pan P, Song W, Huang R, Li J, Chen K, et al.: Voxelwise meta-analysis of gray matter anomalies in Alzheimer’s disease and mild cognitive impairment using anatomic likelihood estimation. J Neurol Sci 2012, 316(1–2):21-9. doi:10.1016/j.jns.2012.02.010
• [49]Zhong J, Pan P, Dai Z, Shi H: Voxelwise meta-analysis of gray matter abnormalities in dementia with Lewy bodies. Eur J Radiol 2014, 83(10):1870-4. doi:10.1016/j.ejrad.2014.06.014
• [50]Schwindt GC, Black SE: Functional imaging studies of episodic memory in Alzheimer’s disease: a quantitative meta-analysis. NeuroImage 2009, 45(1):181-90. doi:10.1016/j.neuroimage.2008.11.024
• [51]Ranganath C, Ritchey M: Two cortical systems for memory-guided behaviour. Nat Rev Neurosci 2012, 13(10):713-26. doi:10.1038/nrn3338
• [52]Smith AD: Imaging the progression of Alzheimer pathology through the brain. Proc Natl Acad Sci U S A 2002, 99(7):4135-7. doi:10.1073/pnas.082107399
• [53]Jin K, Peel AL, Mao XO, Xie L, Cottrell BA, Henshall DC, et al.: Increased hippocampal neurogenesis in Alzheimer’s disease. Proc Natl Acad Sci U S A 2004, 101(1):343-7. doi:10.1073/pnas.2634794100
• [54]Zakzanis KK, Graham SJ, Campbell Z: A meta-analysis of structural and functional brain imaging in dementia of the Alzheimer’s type: a neuroimaging profile. Neuropsychol Rev 2003, 13(1):1-18.
• [55]Burgmans S, van Boxtel MP, van den Berg KE, Gronenschild EH, Jacobs HI, Jolles J, et al.: The posterior parahippocampal gyrus is preferentially affected in age-related memory decline. Neurobiol Aging 2011, 32(9):1572-8. doi:10.1016/j.neurobiolaging.2009.09.008
• [56]Barkhof F, Polvikoski TM, van Straaten EC, Kalaria RN, Sulkava R, Aronen HJ, et al.: The significance of medial temporal lobe atrophy: a postmortem MRI study in the very old. Neurology 2007, 69(15):1521-7. doi:10.1212/01.wnl.0000277459.83543.99
• [57]Echavarri C, Aalten P, Uylings HB, Jacobs HI, Visser PJ, Gronenschild EH, et al.: Atrophy in the parahippocampal gyrus as an early biomarker of Alzheimer’s disease. Brain Struct Funct 2011, 215(3–4):265-71. doi:10.1007/s00429-010-0283-8
• [58]Soldner J, Meindl T, Koch W, Bokde AL, Reiser MF, Moller HJ, et al.: Structural and functional neuronal connectivity in Alzheimer’s disease: a combined DTI and fMRI study. Nervenarzt 2012, 83(7):878-87. doi:10.1007/s00115-011-3326-3
• [59]Park KW, Yoon HJ, Kang DY, Kim BC, Kim S, Kim JW: Regional cerebral blood flow differences in patients with mild cognitive impairment between those who did and did not develop Alzheimer’s disease. Psychiatr Res 2012, 203(2–3):201-6. doi:10.1016/j.pscychresns.2011.12.007
• [60]Morris JC, Roe CM, Grant EA, Head D, Storandt M, Goate AM, et al.: Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease. Arch Neurol 2009, 66(12):1469-75. doi:10.1001/archneurol.2009.269
• [61]Edison P, Archer HA, Hinz R, Hammers A, Pavese N, Tai YF, et al.: Amyloid, hypometabolism, and cognition in Alzheimer disease: an [11C]PIB and [18F]FDG PET study. Neurology 2007, 68(7):501-8. doi:10.1212/01.wnl.0000244749.20056.d4
• [62]Rami L, Sala-Llonch R, Sole-Padulles C, Fortea J, Olives J, Llado A, et al.: Distinct functional activity of the precuneus and posterior cingulate cortex during encoding in the preclinical stage of Alzheimer’s disease. J Alzheimers Dis 2012, 31(3):517-26. doi:10.3233/JAD-2012-120223
• [63]Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE: Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol 1997, 42(1):85-94. doi:10.1002/ana.410420114
• [64]Hauser T, Schonknecht P, Thomann PA, Gerigk L, Schroder J, Henze R, et al.: Regional cerebral perfusion alterations in patients with mild cognitive impairment and Alzheimer disease using dynamic susceptibility contrast MRI. Acad Radiol 2013, 20(6):705-11. doi:10.1016/j.acra.2013.01.020
• [65]Chen Z, Ma L: Grey matter volume changes over the whole brain in amyotrophic lateral sclerosis: A voxel-wise meta-analysis of voxel based morphometry studies. Amyotroph Lateral Scler 2010, 11(6):549-54. doi:10.3109/17482968.2010.516265
• [66]Radua J, Mataix-Cols D: Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. Br J Psychiatry 2009, 195(5):393-402. doi:10.1192/bjp.bp.108.055046
• [67]Bora E, Fornito A, Yucel M, Pantelis C: Voxelwise meta-analysis of gray matter abnormalities in bipolar disorder. Biol Psychiatr 2010, 67(11):1097-105. doi:10.1016/j.biopsych.2010.01.020