Role of β-Amyloidosis and Neurodegeneration in Subsequent Imaging Changes in Mild Cognitive Impairment | Dementia and Cognitive Impairment | JAMA Neurology | JAMA Network
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1.
Wilson  RS, Aggarwal  NT, Barnes  LL, Mendes de Leon  CF, Hebert  LE, Evans  DA.  Cognitive decline in incident Alzheimer disease in a community population.  Neurology. 2010;74(12):951-955. PubMedGoogle ScholarCrossref
2.
Landau  SM, Harvey  D, Madison  CM,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI.  Neurobiol Aging. 2011;32(7):1207-1218.PubMedGoogle ScholarCrossref
3.
Vemuri  P, Wiste  HJ, Weigand  SD,  et al; Alzheimer’s Disease Neuroimaging Initiative.  MRI and CSF biomarkers in normal, MCI, and AD subjects: diagnostic discrimination and cognitive correlations.  Neurology. 2009;73(4):287-293.PubMedGoogle ScholarCrossref
4.
Jack  CR  Jr, Wiste  HJ, Vemuri  P,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease.  Brain. 2010;133(11):3336-3348.PubMedGoogle ScholarCrossref
5.
Tosun  D, Schuff  N, Mathis  CA, Jagust  W, Weiner  MW; Alzheimer’s Disease NeuroImaging Initiative.  Spatial patterns of brain amyloid-beta burden and atrophy rate associations in mild cognitive impairment.  Brain. 2011;134(pt 4):1077-1088.PubMedGoogle ScholarCrossref
6.
Chételat  G, Villemagne  VL, Bourgeat  P,  et al; Australian Imaging Biomarkers and Lifestyle Research Group.  Relationship between atrophy and beta-amyloid deposition in Alzheimer disease.  Ann Neurol. 2010;67(3):317-324.PubMedGoogle Scholar
7.
Henneman  WJ, Sluimer  JD, Barnes  J,  et al.  Hippocampal atrophy rates in Alzheimer disease: added value over whole brain volume measures.  Neurology. 2009;72(11):999-1007.PubMedGoogle ScholarCrossref
8.
Whitwell  JL, Shiung  MM, Przybelski  SA,  et al.  MRI patterns of atrophy associated with progression to AD in amnestic mild cognitive impairment.  Neurology. 2008;70(7):512-520.PubMedGoogle ScholarCrossref
9.
Bernard  C, Helmer  C, Dilharreguy  B,  et al.  Time course of brain volume changes in the preclinical phase of Alzheimer's disease.  Alzheimers Dement. 2014;10(2):143-151.e1. 24418054Google ScholarCrossref
10.
Chen  K, Langbaum  JB, Fleisher  AS,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Twelve-month metabolic declines in probable Alzheimer’s disease and amnestic mild cognitive impairment assessed using an empirically pre-defined statistical region-of-interest: findings from the Alzheimer’s Disease Neuroimaging Initiative.  Neuroimage. 2010;51(2):654-664.PubMedGoogle ScholarCrossref
11.
Fouquet  M, Desgranges  B, Landeau  B,  et al.  Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer’s disease.  Brain. 2009;132(pt 8):2058-2067.PubMedGoogle ScholarCrossref
12.
Jack  CR  Jr, Knopman  DS, Jagust  WJ,  et al.  Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers.  Lancet Neurol. 2013;12(2):207-216.PubMedGoogle ScholarCrossref
13.
Knopman  DS, Jack  CRJ, Wiste  HJ,  et al.  Selective worsening of brain injury biomarker abnormalities in cognitively normal elderly persons with β-amyloidosis.  JAMA Neurol. 2013;70(8):1030-1038. PubMedGoogle ScholarCrossref
14.
Roberts  RO, Geda  YE, Knopman  D,  et al.  The Mayo Clinic Study of Aging: design and sampling, participation, baseline measures and sample characteristics.  Neuroepidemiology. 2008;30(1):58-69. PubMedGoogle ScholarCrossref
15.
Petersen  RC.  Mild cognitive impairment as a diagnostic entity.  J Intern Med. 2004;256(3):183-194.PubMedGoogle ScholarCrossref
16.
Roberts  RO, Knopman  DS, Mielke  MM,  et al.  Higher risk of progression to dementia in mild cognitive impairment cases who revert to normal.  Neurology. 2014;82(4):317-325.PubMedGoogle ScholarCrossref
17.
Roberts  RO, Geda  YE, Knopman  DS,  et al.  The incidence of MCI differs by subtype and is higher in men: the Mayo Clinic Study of Aging.  Neurology. 2012;78(5):342-351.PubMedGoogle ScholarCrossref
18.
Petersen  RC, Roberts  RO, Knopman  DS,  et al; The Mayo Clinic Study of Aging.  Prevalence of mild cognitive impairment is higher in men.  Neurology. 2010;75(10):889-897.PubMedGoogle ScholarCrossref
19.
Albert  M, DeKosky  ST, Dickson  D,  et al.  The diagnosis of mild cognitive impairment due to 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(3):270-279. PubMedGoogle ScholarCrossref
20.
Jack  CR  Jr, Wiste  HJ, Knopman  DS,  et al.  Rates of β-amyloid accumulation are independent of hippocampal neurodegeneration.  Neurology. 2014;82(18):1605-1612.PubMedGoogle ScholarCrossref
21.
Jack  CR  Jr, Wiste  HJ, Weigand  SD,  et al.  Age-specific population frequencies of cerebral β-amyloidosis and neurodegeneration among people with normal cognitive function aged 50-89 years: a cross-sectional study.  Lancet Neurol. 2014;13(10):997-1005.PubMedGoogle ScholarCrossref
22.
Tzourio-Mazoyer  N, Landeau  B, Papathanassiou  D,  et al.  Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.  Neuroimage. 2002;15(1):273-289.PubMedGoogle ScholarCrossref
23.
Whitwell  JL, Josephs  KA, Murray  ME,  et al.  MRI correlates of neurofibrillary tangle pathology at autopsy: a voxel-based morphometry study.  Neurology. 2008;71(10):743-749.PubMedGoogle ScholarCrossref
24.
Knol  MJ, Pestman  WR, Grobbee  DE.  The (mis)use of overlap of confidence intervals to assess effect modification.  Eur J Epidemiol. 2011;26(4):253-254.PubMedGoogle ScholarCrossref
25.
Knopman  DS.  β-Amyloidosis and neurodegeneration in Alzheimer disease: who’s on first?  Neurology. 2014;82(20):1756-1757.PubMedGoogle ScholarCrossref
26.
Buckner  RL, Andrews-Hanna  JR, Schacter  DL.  The brain's default network: anatomy, function, and relevance to disease.  Ann N Y Acad Sci. 2008;1124:1-38. PubMedGoogle ScholarCrossref
27.
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):4637-4642.PubMedGoogle ScholarCrossref
28.
Knopman  DS, Jack  CR  Jr,, Wiste  HJ,  et al.  Brain injury biomarkers are not dependent on β-amyloid in normal elderly.  Ann Neurol. 2013;73(4):472-480. PubMedGoogle ScholarCrossref
29.
Braak  H, Braak  E.  Neuropathological stageing of Alzheimer-related changes.  Acta Neuropathol. 1991;82(4):239-259.PubMedGoogle ScholarCrossref
30.
Arnold  SE, Hyman  BT, Flory  J, Damasio  AR, Van Hoesen  GW.  The topographical and neuroanatomical distribution of neurofibrillary tangles and neuritic plaques in the cerebral cortex of patients with Alzheimer’s disease.  Cereb Cortex. 1991;1(1):103-116.PubMedGoogle ScholarCrossref
31.
Dickerson  BC, Stoub  TR, Shah  RC,  et al.  Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults.  Neurology. 2011;76(16):1395-1402.PubMedGoogle ScholarCrossref
32.
Braak  H, Del Tredici  K.  The pathological process underlying Alzheimer’s disease in individuals under thirty.  Acta Neuropathol. 2011;121(2):171-181.PubMedGoogle ScholarCrossref
33.
Delacourte  A, Sergeant  N, Wattez  A,  et al.  Tau aggregation in the hippocampal formation: an ageing or a pathological process?  Exp Gerontol. 2002;37(10-11):1291-1296.PubMedGoogle ScholarCrossref
34.
Duyckaerts  C, Hauw  JJ.  Prevalence, incidence and duration of Braak’s stages in the general population: can we know?  Neurobiol Aging. 1997;18(4):362-369.PubMedGoogle ScholarCrossref
35.
Murray  ME, Graff-Radford  NR, Ross  OA, Petersen  RC, Duara  R, Dickson  DW.  Neuropathologically defined subtypes of Alzheimer’s disease with distinct clinical characteristics: a retrospective study.  Lancet Neurol. 2011;10(9):785-796.PubMedGoogle ScholarCrossref
36.
Petersen  RC, Aisen  P, Boeve  BF,  et al.  Mild cognitive impairment due to Alzheimer’s disease in the community.  Ann Neurol. 2013;74(2):199-208. PubMedGoogle Scholar
37.
Prestia  A, Caroli  A, van der Flier  WM,  et al.  Prediction of dementia in MCI patients based on core diagnostic markers for Alzheimer disease.  Neurology. 2013;80(11):1048-1056.PubMedGoogle ScholarCrossref
38.
van Harten  AC, Smits  LL, Teunissen  CE,  et al.  Preclinical AD predicts decline in memory and executive functions in subjective complaints.  Neurology. 2013;81(16):1409-1416.PubMedGoogle ScholarCrossref
39.
Caroli  A, Prestia  A, Galluzzi  S,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Mild cognitive impairment with suspected nonamyloid pathology (SNAP): prediction of progression.  Neurology. 2015;84(5):508-515.PubMedGoogle ScholarCrossref
40.
Crary  JF, Trojanowski  JQ, Schneider  JA,  et al.  Primary age-related tauopathy (PART): a common pathology associated with human aging.  Acta Neuropathol. 2014;128(6):755-766.PubMedGoogle ScholarCrossref
41.
Nelson  PT, Schmitt  FA, Lin  Y,  et al.  Hippocampal sclerosis in advanced age: clinical and pathological features.  Brain. 2011;134(pt 5):1506-1518.PubMedGoogle ScholarCrossref
42.
Villemagne  VL, Burnham  S, Bourgeat  P,  et al; Australian Imaging Biomarkers and Lifestyle (AIBL) Research Group.  Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study.  Lancet Neurol. 2013;12(4):357-367.PubMedGoogle ScholarCrossref
43.
Price  JL, Morris  JC.  Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease.  Ann Neurol. 1999;45(3):358-368.PubMedGoogle ScholarCrossref
44.
Mungas  D, Tractenberg  R, Schneider  JA, Crane  PK, Bennett  DA.  A 2-process model for neuropathology of Alzheimer’s disease.  Neurobiol Aging. 2014;35(2):301-308.PubMedGoogle ScholarCrossref
45.
Jack  CR  Jr, Wiste  HJ, Weigand  SD,  et al.  Age, sex, and apoe ε4 effects on memory, brain structure, and β-amyloid across the adult life span.  JAMA Neurol. 2015;72(5):511-519.PubMedGoogle ScholarCrossref
46.
Förster  S, Grimmer  T, Miederer  I,  et al.  Regional expansion of hypometabolism in Alzheimer’s disease follows amyloid deposition with temporal delay.  Biol Psychiatry. 2012;71(9):792-797.PubMedGoogle ScholarCrossref
Original Investigation
December 2015

Role of β-Amyloidosis and Neurodegeneration in Subsequent Imaging Changes in Mild Cognitive Impairment

Author Affiliations
  • 1Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
  • 2Mayo Clinic Alzheimer’s Disease Research Center, Mayo Clinic and Foundation, Rochester, Minnesota
  • 3Department of Radiology, Mayo Clinic and Foundation, Rochester, Minnesota
  • 4Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, Minnesota
  • 5Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, Minnesota
  • 6Division of Psychology, Department of Psychiatry, Mayo Clinic and Foundation, Rochester, Minnesota
JAMA Neurol. 2015;72(12):1475-1483. doi:10.1001/jamaneurol.2015.2323
Abstract

Importance  To understand how a model of Alzheimer disease pathophysiology based on β-amyloidosis and neurodegeneration predicts the regional anatomic expansion of hypometabolism and atrophy in persons with mild cognitive impairment (MCI).

Objective  To define the role of β-amyloidosis and neurodegeneration in the subsequent progression of topographic cortical structural and metabolic changes in MCI.

Design, Setting, and Participants  Longitudinal, observational study with serial brain imaging conducted from March 28, 2006, to January 6, 2015, using a population-based cohort. A total of 96 participants with MCI (all aged >70 years) with serial imaging biomarkers from the Mayo Clinic Study of Aging or Mayo Alzheimer’s Disease Research Center were included. Participants were characterized initially as having elevated or not elevated brain β-amyloidosis (A+ or A−) based on 11C-Pittsburgh compound B positron emission tomography. They were further characterized initially by the presence or absence of neurodegeneration (N+ or N−), where the presence of neurodegeneration was defined by abnormally low hippocampal volume or hypometabolism in an Alzheimer disease–like pattern on 18fluorodeoxyglucose (FDG)–positron emission tomography.

Main Outcomes and Measures  Regional FDG standardized uptake value ratio (SUVR) and gray matter volumes in medial temporal, lateral temporal, lateral parietal, and medial parietal regions.

Results  In the primary regions of interest (ROI), the A+N+ group (n = 45) had lower FDG SUVR at baseline compared with the A+N− group (n = 17) (all 4 ROIs; P < .001). The A+N+ group also had lower FDG SUVR at baseline (all 4 ROIs; P < .01) compared with the A−N− group (n = 12). The A+N+ group had lower medial temporal gray matter volume at baseline (P < .001) compared with either the A+N− group or A−N− group. The A+N+ group showed large longitudinal declines in FDG SUVR (P < .05 for medial temporal, lateral temporal, and medial parietal regions) and gray matter volumes (P < .05 for medial temporal and lateral temporal regions) compared with the A−N+ group (n = 22). The A+N+ group also showed large longitudinal declines compared with the A−N− group on FDG SUVR (P < .05 for medial temporal and lateral parietal regions) and gray matter volumes (all 4 ROIs; P < .05) compared with the A+N− group. The A−N+ group did not show declines in FDG SUVR or gray matter volume compared with the A+N− or A−N− groups.

Conclusions and Relevance  Persons with MCI who were A+N+ demonstrated volumetric and metabolic worsening in temporal and parietal association areas, consistent with the expectation that the MCI stage in the Alzheimer pathway heralds incipient isocortical involvement. The A−N+ group, those with suspected non-Alzheimer pathophysiology, lacked a distinctive longitudinal volumetric or metabolic profile.

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