Unrecognized preclinical Alzheimer disease confounds rs-fcMRI studies of normal aging

Neurology

Volumn 83, Issue 18, 2014, Pages 1613-1619

  Brier, Matthew R ^a   Thomas, Jewell B ^b   Snyder, Abraham Z ^b,c   Wang, Liang ^b   Fagan, Anne M ^b,c   Benzinger, Tammie ^c   Morris, John C ^b,c   Ances, Beau M ^b,c,d  

^a Division of Biological and Biomedical Sciences   (United States)

^b Departments of Neurology   (United States)

^c WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGED; ALZHEIMER DISEASE; ARTICLE; CEREBELLUM; CEREBROSPINAL FLUID; CLINICAL ASSESSMENT; DISEASE MARKER; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HIPPOCAMPUS; HUMAN; MAJOR CLINICAL STUDY; MALE; PRECLINICAL ALZHEIMER DISEASE; PREFRONTAL CORTEX; PRIORITY JOURNAL; RESTING STATE NETWORK; THALAMUS; AGE; AGING; BRAIN CORTEX; DEVICES; MIDDLE AGED; NERVE CELL NETWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOPHYSIOLOGY; PHYSIOLOGY; PROCEDURES; PRODROMAL SYMPTOM; VERY ELDERLY;

BIOLOGICAL MARKER;

AGE FACTORS; AGED; AGED, 80 AND OVER; AGING; ALZHEIMER DISEASE; BIOMARKERS; CEREBRAL CORTEX; FEMALE; FUNCTIONAL NEUROIMAGING; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; NERVE NET; PRODROMAL SYMPTOMS;

EID: 84912108664     PISSN: 00283878     EISSN: 1526632X     Source Type: Journal    
DOI: 10.1212/WNL.0000000000000939     Document Type: Article

References (36)

1. Andrews-Hanna JR, Snyder AZ, Vincent JL, et al. Disruption of large-scale brain systems in advanced aging. Neuron 2007;56:924-935.
2. Biswal BB, Mennes M, Zuo XN, et al. Toward discovery science of human brain function. Proc Natl Acad Sci USA 2010;107:4734-4739.
3. KochW, Teipel S, Mueller S, et al. Effects of aging on default mode network activity in resting state fMRI: does the method of analysis matter? Neuroimage 2010;51:280-287.
4. Tomasi D, Volkow ND. Aging and functional brain networks. Mol Psychiatry 2012;471:549-458.
5. Knopman DS, Parisi JE, Salviati A, et al. Neuropathology of cognitively normal elderly. J Neuropathol Exp Neurol 2003;62:1087-1095.
6. Jack CR, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013;12:207-216.
7. Drzezga A, Becker JA, Van Dijk KR, et al. Neuronal dysfunction and disconnection of cortical hubs in nondemented subjects with elevated amyloid burden. Brain 2011;134:1635-1646.
8. Hedden T, Van Dijk KR, Becker JA, et al. Disruption of functional connectivity in clinically normal older adults harboring amyloid burden. J Neurosci 2009;29:12686-12694.
9. Mormino EC, Smiljic A, Hayenga AO, et al. Relationships between beta-amyloid and functional connectivity in different components of the default mode network in aging. Cereb Cortex 2011;21:2399-2407.
10. Sheline YI, Raichle ME, Snyder AZ, et al. Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly. Biol Psychiatry 2010;67:584-587.
11. Filippini N, MacIntosh BJ, Hough MG, et al. Distinct patterns of brain activity in young carriers of the APOE-epsilon4 allele. Proc Natl Acad Sci USA 2009;106:7209-7214.
12. Machulda MM, Jones DT, Vemuri P, et al. Effect of APOE epsilon4 status on intrinsic network connectivity in cognitively normal elderly subjects. Arch Neurol 2011; 68:1131-1136.
13. Sheline YI, Morris JC, Snyder AZ, et al. APOE4 allele disrupts resting state fMRI connectivity in the absence of amyloid plaques or decreased CSF Abeta42. J Neurosci 2010;30:17035-17040.
14. Greicius MD, Srivastava G, Reiss AL, Menon V. Defaultmode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci USA 2004;101:4637-4642.
15. Zhou J, Greicius MD, Gennatas ED, et al. Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer's disease. Brain 2010; 133:1352-1367.
16. Brier MR, Thomas JB, Snyder AZ, et al. Loss of intranetwork and internetwork resting state functional connections with Alzheimer's disease progression. J Neurosci 2012;32: 8890-8899.
17. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993;43:2412-2414.
18. Wang L, Roe CM, Snyder AZ, et al. Alzheimer disease family history impacts resting state functional connectivity. Ann Neurol 2012;72:571-577.
19. Brier MR, Thomas JB, Fagan AM, et al. Functional connectivity and graph theory in preclinical Alzheimer's disease. Neurobiol Aging 2014;35:757-768.
20. Sperling RA, Aisen PS, Beckett LA, et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement 2011;7:280-292.
21. Jack CR Jr, Knopman DS, Weigand SD, et al. An operational approach to National Institute on Aging-Alzheimer's Association criteria for preclinical Alzheimer disease. Ann Neurol 2012;71:765-775.
22. Hallquist MN, Hwang K, Luna B. The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity. Neuroimage 2013;82:208-225.
23. Fischl B, Salat DH, van der Kouwe AJ, et al. Sequenceindependent segmentation of magnetic resonance images. Neuroimage 2004;23:S69-S84.
24. Bullmore ET, Suckling J, Overmeyer S, Rabe-Hesketh S, Taylor E, Brammer MJ. Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Trans Med Imaging 1999;18:32-42.
25. Hayasaka S, Nichols TE. Combining voxel intensity and cluster extent with permutation test framework. Neuroimage 2004;23:54-63.
26. Nichols T, Hayasaka S. Controlling the familywise error rate in functional neuroimaging: a comparative review. Stat Methods Med Res 2003;12:419-446.
27. Nichols T, Holmes AP. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 2001;15:1-25.
28. Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 2012;59:2142-2154.
29. Power JD, Mitra A, Laumann TO, Snyder AZ, Schlaggar BL, Petersen SE. Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 2014;84:320-341.
30. Ferreira LK, Busatto GF. Resting-state functional connectivity in normal brain aging. Neurosci Biobehav Rev 2013; 37:384-400.
31. Wang L, Brier MR, Snyder AZ, et al. Cerebrospinal fluid Abeta42, phosphorylated tau181, and resting-state functional connectivity. JAMA Neurol 2013;70:1242-1248.
32. Price JL, McKeel DW Jr, Buckles VD, et al. Neuropathology of nondemented aging: presumptive evidence for preclinical Alzheimer disease. Neurobiol Aging 2009;30: 1026-1036.
33. Jones DT, Machulda MM, Vemuri P, et al. Age-related changes in the default mode network are more advanced in Alzheimer disease. Neurology 2011;77:1524-1531.
34. Meunier D, Achard S, Morcom A, Bullmore E. Agerelated changes in modular organization of human brain functional networks. Neuroimage 2009;44:715-723.
35. Meunier D, Stamatakis EA, Tyler LK. Age-related functional reorganization, structural changes, and preserved cognition. Neurobiol Aging 2014;35:42-54.
36. Geerligs L, Renken RJ, Saliasi E, Maurits NM, Lorist MM. A brain-wide study of age-related changes in functional connectivity. Cereb Cortex Epub 2014 Feb 13.