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Figure 1.  Distribution of Cortical β-Amyloid Protein Level
Distribution of Cortical β-Amyloid Protein Level

A, The histogram reveals a bimodal pattern in the distribution of cortical β-amyloid protein level (n = 1203). B, A histogram of protein level with β-amyloid deposits (n = 1055). C, A histogram of protein level without β-amyloid deposits (n = 148). D, Overlays of B and C further illustrate that the higher peak was exclusively made up of individuals with β-amyloid deposits; almost all individuals without β-amyloid deposits were clustered in the lower peak.

Figure 2.  β-Amyloid Protein and Cognitive Decline in the Absence of β-Amyloid Deposits
β-Amyloid Protein and Cognitive Decline in the Absence of β-Amyloid Deposits

A-F, Model expected values of cognition over time for representative participants (female participants aged 85 years with 15 years of education) with 25th (orange), 50th (dark gray), and 75th (blue) percentiles of β-amyloid level in global cognition (A), episodic memory (B), semantic memory (C), working memory (D), processing speed (E), and visuospatial ability (F). The expected values over time are calculated using point estimates of both intercept and slope as derived from the linear mixed models.

Table 1.  Characteristics of Study Participants
Characteristics of Study Participants
Table 2.  Associations of β-Amyloid Protein With Cognitive Decline in the Absence of β-Amyloid Depositsa
Associations of β-Amyloid Protein With Cognitive Decline in the Absence of β-Amyloid Depositsa
Table 3.  Associations of β-Amyloid Protein With Neuropathologic Conditions in the Absence of β-Amyloid Depositsa
Associations of β-Amyloid Protein With Neuropathologic Conditions in the Absence of β-Amyloid Depositsa
1.
Hyman  BT, Phelps  CH, Beach  TG,  et al.  National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease.  Alzheimers Dement. 2012;8(1):1-13. doi:10.1016/j.jalz.2011.10.007PubMedGoogle ScholarCrossref
2.
Schmechel  DE, Saunders  AM, Strittmatter  WJ,  et al.  Increased amyloid beta-peptide deposition in cerebral cortex as a consequence of apolipoprotein E genotype in late-onset Alzheimer disease.  Proc Natl Acad Sci U S A. 1993;90(20):9649-9653. doi:10.1073/pnas.90.20.9649PubMedGoogle ScholarCrossref
3.
Mishra  S, Blazey  TM, Holtzman  DM,  et al.  Longitudinal brain imaging in preclinical Alzheimer disease: impact of APOE ε4 genotype.  Brain. 2018;141(6):1828-1839. doi:10.1093/brain/awy103PubMedGoogle ScholarCrossref
4.
Reiman  EM, Chen  K, Liu  X,  et al.  Fibrillar amyloid-beta burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease.  Proc Natl Acad Sci U S A. 2009;106(16):6820-6825. doi:10.1073/pnas.0900345106PubMedGoogle ScholarCrossref
5.
Lambert  J-C, Ibrahim-Verbaas  CA, Harold  D,  et al; European Alzheimer’s Disease Initiative (EADI); Genetic and Environmental Risk in Alzheimer’s Disease; Alzheimer’s Disease Genetic Consortium; Cohorts for Heart and Aging Research in Genomic Epidemiology.  Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease.  Nat Genet. 2013;45(12):1452-1458. doi:10.1038/ng.2802PubMedGoogle ScholarCrossref
6.
Shulman  JM, Chen  K, Keenan  BT,  et al.  Genetic susceptibility for Alzheimer disease neuritic plaque pathology.  JAMA Neurol. 2013;70(9):1150-1157. doi:10.1001/jamaneurol.2013.2815PubMedGoogle ScholarCrossref
7.
Beecham  GW, Hamilton  K, Naj  AC,  et al; Alzheimer’s Disease Genetics Consortium (ADGC).  Genome-wide association meta-analysis of neuropathologic features of Alzheimer’s disease and related dementias.  PLoS Genet. 2014;10(9):e1004606. doi:10.1371/journal.pgen.1004606PubMedGoogle ScholarCrossref
8.
Brier  MR, Gordon  B, Friedrichsen  K,  et al.  Tau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease.  Sci Transl Med. 2016;8(338):338ra66.PubMedGoogle ScholarCrossref
9.
He  Z, Guo  JL, McBride  JD,  et al.  Amyloid-β plaques enhance Alzheimer’s brain tau-seeded pathologies by facilitating neuritic plaque tau aggregation.  Nat Med. 2018;24(1):29-38. doi:10.1038/nm.4443PubMedGoogle ScholarCrossref
10.
Bennett  DA, Schneider  JA, Wilson  RS, Bienias  JL, Arnold  SE.  Neurofibrillary tangles mediate the association of amyloid load with clinical Alzheimer disease and level of cognitive function.  Arch Neurol. 2004;61(3):378-384. doi:10.1001/archneur.61.3.378PubMedGoogle ScholarCrossref
11.
Aschenbrenner  AJ, Gordon  BA, Benzinger  TLS, Morris  JC, Hassenstab  JJ.  Influence of tau PET, amyloid PET, and hippocampal volume on cognition in Alzheimer disease.  Neurology. 2018;91(9):e859-e866. doi:10.1212/WNL.0000000000006075PubMedGoogle ScholarCrossref
12.
Malek-Ahmadi  M, Perez  SE, Chen  K, Mufson  EJ.  Neuritic and diffuse plaque associations with memory in non-cognitively impaired elderly.  J Alzheimers Dis. 2016;53(4):1641-1652. doi:10.3233/JAD-160365PubMedGoogle ScholarCrossref
13.
Boyle  PA, Yu  L, Wilson  RS, Schneider  JA, Bennett  DA.  Relation of neuropathology with cognitive decline among older persons without dementia.  Front Aging Neurosci. 2013;5:50. doi:10.3389/fnagi.2013.00050PubMedGoogle ScholarCrossref
14.
Doraiswamy  PM, Sperling  RA, Coleman  RE,  et al; AV45-A11 Study Group.  Amyloid-β assessed by florbetapir F 18 PET and 18-month cognitive decline: a multicenter study.  Neurology. 2012;79(16):1636-1644. doi:10.1212/WNL.0b013e3182661f74PubMedGoogle ScholarCrossref
15.
Resnick  SM, Sojkova  J, Zhou  Y,  et al.  Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB.  Neurology. 2010;74(10):807-815. doi:10.1212/WNL.0b013e3181d3e3e9PubMedGoogle ScholarCrossref
16.
Mormino  EC, Kluth  JT, Madison  CM,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects.  Brain. 2009;132(pt 5):1310-1323. doi:10.1093/brain/awn320PubMedGoogle ScholarCrossref
17.
Hayden  EY, Teplow  DB.  Amyloid β-protein oligomers and Alzheimer’s disease.  Alzheimers Res Ther. 2013;5(6):60. doi:10.1186/alzrt226PubMedGoogle ScholarCrossref
18.
Selkoe  DJ, Hardy  J.  The amyloid hypothesis of Alzheimer’s disease at 25 years.  EMBO Mol Med. 2016;8(6):595-608. doi:10.15252/emmm.201606210PubMedGoogle ScholarCrossref
19.
Kayed  R, Head  E, Thompson  JL,  et al.  Common structure of soluble amyloid oligomers implies common mechanism of pathogenesis.  Science. 2003;300(5618):486-489. doi:10.1126/science.1079469PubMedGoogle ScholarCrossref
20.
Cline  EN, Bicca  MA, Viola  KL, Klein  WL.  The amyloid-β oligomer hypothesis: beginning of the third decade.  J Alzheimers Dis. 2018;64(s1):S567-S610.PubMedGoogle ScholarCrossref
21.
Lue  LF, Kuo  YM, Roher  AE,  et al.  Soluble amyloid beta peptide concentration as a predictor of synaptic change in Alzheimer’s disease.  Am J Pathol. 1999;155(3):853-862. doi:10.1016/S0002-9440(10)65184-XPubMedGoogle ScholarCrossref
22.
McLean  CA, Cherny  RA, Fraser  FW,  et al.  Soluble pool of Abeta amyloid as a determinant of severity of neurodegeneration in Alzheimer’s disease.  Ann Neurol. 1999;46(6):860-866. doi:10.1002/1531-8249(199912)46:6<860::AID-ANA8>3.0.CO;2-MPubMedGoogle ScholarCrossref
23.
Mc Donald  JM, Savva  GM, Brayne  C,  et al; Medical Research Council Cognitive Function and Ageing Study.  The presence of sodium dodecyl sulphate-stable Abeta dimers is strongly associated with Alzheimer-type dementia.  Brain. 2010;133(pt 5):1328-1341. doi:10.1093/brain/awq065PubMedGoogle ScholarCrossref
24.
Tasaki  S, Gaiteri  C, Mostafavi  S, De Jager  PL, Bennett  DA.  The molecular and neuropathological consequences of genetic risk for Alzheimer’s dementia.  Front Neurosci. 2018;12(699):699.PubMedGoogle ScholarCrossref
25.
Bennett  DA, Buchman  AS, Boyle  PA, Barnes  LL, Wilson  RS, Schneider  JA.  Religious Orders Study and Rush Memory and Aging Project.  J Alzheimers Dis. 2018;64(s1):S161-S189. doi:10.3233/JAD-179939PubMedGoogle ScholarCrossref
26.
Bennett  DA, Schneider  JA, Bienias  JL, Evans  DA, Wilson  RS.  Mild cognitive impairment is related to Alzheimer disease pathology and cerebral infarctions.  Neurology. 2005;64(5):834-841. doi:10.1212/01.WNL.0000152982.47274.9EPubMedGoogle ScholarCrossref
27.
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. doi:10.1212/WNL.0b013e3181d64786PubMedGoogle ScholarCrossref
28.
Yu  L, Petyuk  VA, Gaiteri  C,  et al.  Targeted brain proteomics uncover multiple pathways to Alzheimer’s dementia.  Ann Neurol. 2018;84(1):78-88. doi:10.1002/ana.25266PubMedGoogle ScholarCrossref
29.
Petyuk  VA, Qian  WJ, Smith  RD, Smith  DJ.  Mapping protein abundance patterns in the brain using voxelation combined with liquid chromatography and mass spectrometry.  Methods. 2010;50(2):77-84. doi:10.1016/j.ymeth.2009.07.009PubMedGoogle ScholarCrossref
30.
Andreev  VP, Petyuk  VA, Brewer  HM,  et al.  Label-free quantitative LC-MS proteomics of Alzheimer’s disease and normally aged human brains.  J Proteome Res. 2012;11(6):3053-3067. doi:10.1021/pr3001546PubMedGoogle ScholarCrossref
31.
MacLean  B, Tomazela  DM, Shulman  N,  et al.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.  Bioinformatics. 2010;26(7):966-968. doi:10.1093/bioinformatics/btq054PubMedGoogle ScholarCrossref
32.
Hardy  JA, Higgins  GA.  Alzheimer’s disease: the amyloid cascade hypothesis.  Science. 1992;256(5054):184-185. doi:10.1126/science.1566067PubMedGoogle ScholarCrossref
33.
Hardy  J, Selkoe  DJ.  The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics.  Science. 2002;297(5580):353-356. doi:10.1126/science.1072994PubMedGoogle ScholarCrossref
34.
Walsh  DM, Selkoe  DJ.  A beta oligomers—a decade of discovery.  J Neurochem. 2007;101(5):1172-1184. doi:10.1111/j.1471-4159.2006.04426.xPubMedGoogle ScholarCrossref
35.
Lesné  SE, Sherman  MA, Grant  M,  et al.  Brain amyloid-β oligomers in ageing and Alzheimer’s disease.  Brain. 2013;136(pt 5):1383-1398. doi:10.1093/brain/awt062PubMedGoogle ScholarCrossref
36.
Wang  J, Dickson  DW, Trojanowski  JQ, Lee  VM.  The levels of soluble versus insoluble brain Abeta distinguish Alzheimer’s disease from normal and pathologic aging.  Exp Neurol. 1999;158(2):328-337. doi:10.1006/exnr.1999.7085PubMedGoogle ScholarCrossref
37.
Farfel  JM, Yu  L, De Jager  PL, Schneider  JA, Bennett  DA.  Association of APOE with tau-tangle pathology with and without β-amyloid.  Neurobiol Aging. 2016;37:19-25. doi:10.1016/j.neurobiolaging.2015.09.011PubMedGoogle ScholarCrossref
38.
De Felice  FG, Wu  D, Lambert  MP,  et al.  Alzheimer’s disease-type neuronal tau hyperphosphorylation induced by A β oligomers.  Neurobiol Aging. 2008;29(9):1334-1347. doi:10.1016/j.neurobiolaging.2007.02.029PubMedGoogle ScholarCrossref
39.
Jin  M, Shepardson  N, Yang  T, Chen  G, Walsh  D, Selkoe  DJ.  Soluble amyloid beta-protein dimers isolated from Alzheimer cortex directly induce Tau hyperphosphorylation and neuritic degeneration.  Proc Natl Acad Sci U S A. 2011;108(14):5819-5824. doi:10.1073/pnas.1017033108PubMedGoogle ScholarCrossref
40.
Chabrier  MA, Blurton-Jones  M, Agazaryan  AA, Nerhus  JL, Martinez-Coria  H, LaFerla  FM.  Soluble Aβ promotes wild-type tau pathology in vivo.  J Neurosci. 2012;32(48):17345-17350. doi:10.1523/JNEUROSCI.0172-12.2012PubMedGoogle ScholarCrossref
41.
Ferreira  ST, Lourenco  MV, Oliveira  MM, De Felice  FG.  Soluble amyloid-β oligomers as synaptotoxins leading to cognitive impairment in Alzheimer’s disease.  Front Cell Neurosci. 2015;9:191. doi:10.3389/fncel.2015.00191PubMedGoogle Scholar
42.
Shankar  GM, Li  S, Mehta  TH,  et al.  Amyloid-beta protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory.  Nat Med. 2008;14(8):837-842. doi:10.1038/nm1782PubMedGoogle ScholarCrossref
Original Investigation
April 22, 2019

Association of Cortical β-Amyloid Protein in the Absence of Insoluble Deposits With Alzheimer Disease

Author Affiliations
  • 1Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
  • 2Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
  • 3Pacific Northwest National Laboratory, Richland, Washington
  • 4Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
  • 5Department of Pathology, Rush University Medical Center, Chicago, Illinois
  • 6Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, New York
  • 7Cell Circuits Program, Broad Institute, Cambridge, Massachusetts
JAMA Neurol. 2019;76(7):818-826. doi:10.1001/jamaneurol.2019.0834
Key Points

Question  How is cortical β-amyloid protein in the absence of insoluble deposits associated with classic features of Alzheimer disease?

Findings  In this study of 148 older individuals without β-amyloid deposits, β-amyloid protein was associated with faster cognitive decline, although not in episodic memory. No association of protein with paired helical filament tau tangle density was observed, and neither apolipoprotein ε4 nor a polygenic Alzheimer risk score was associated with β-amyloid protein.

Meaning  Cortical soluble β-amyloid is neurotoxic in aging; the lack of protein association with paired helical filament tau tangles, episodic memory decline, or strong genetic drivers of deposited β-amyloid suggests an underlying neuropathologic change that differs from that of AD.

Abstract

Importance  β-Amyloid deposits are a pathologic hallmark of Alzheimer disease (AD). However, the extent to which cortical β-amyloid protein in the absence of insoluble deposits is associated with classic features of AD appear to be unknown.

Objective  To examine the associations of cortical β-amyloid protein in the absence of insoluble deposits with cognitive decline, neurofibrillary tangles, other age-associated neuropathologic conditions, and APOE.

Design, Setting, and Participants  This analysis combines data from 2 community-based clinicopathologic cohort studies of aging. The Religious Orders Study started in 1994, and the Rush Memory and Aging Project started in 1997. Both studies are ongoing. Participants without known dementia were enrolled and agreed to annual clinical evaluations and brain donation after death. Primary analyses focused on individuals without β-amyloid deposits. Data analyses occurred in mid-September 2018.

Main Outcomes and Measures  β-Amyloid protein abundance was measured by targeted proteomics using selected reaction monitoring. β-Amyloid deposits were detected using immunohistochemistry. Other neuropathologic indices were quantified via uniform structured evaluation. Linear mixed models were used to examine the association of β-amyloid protein with cognitive decline. Regression models examined the protein associations with neuropathologic outcomes and the APOE genotype.

Results  By mid-September 2018, 3575 older persons were enrolled, and 1559 had died and undergone brain autopsy. Proteomic data were collected in 1208 individuals, and 5 with missing cognitive scores were excluded. Of the remaining 1203, primary analyses focused on 148 individuals (12.3%) without β-amyloid deposits. In this group, the mean (SD) age at death was 87.0 (7.0) years, and 84 individuals (56.8%) were women. In the absence of β-amyloid deposits, we did not observe an association of β-amyloid protein with decline in episodic memory, but the protein was associated with faster rates of decline in processing speed (mean [SE] change, −0.014 [0.005]; P = .008) and visuospatial abilities (mean [SE] change, −0.013 [0.005]; P = .006). We did not observe protein association with paired helical filament tau tangle density. The protein was associated with amyloid angiopathy (odds ratio, 1.38 [95% CI, 1.15-1.67]; P < .001) but no other brain pathology. The associations with cognitive decline were unchanged after controlling for amyloid angiopathy. Neither APOE ε4 nor a polygenic Alzheimer risk score was associated with β-amyloid protein.

Conclusions and Relevance  Cortical β-amyloid protein was associated with faster cognitive decline in the absence of β-amyloid deposits, which supports the role of cortical soluble β-amyloid as a neurotoxic agent in aging. The lack of protein association with paired helical filament tau tangles, episodic memory decline, or strong genetic drivers of deposited β-amyloid suggests an underlying neuropathologic change that may differ from that of AD.

Introduction

Accumulation of β-amyloid is a pathologic hallmark of Alzheimer disease (AD).1 Findings from genetic, biomarker, and clinicopathologic studies have provided convincing evidence that β-amyloid plays a central role in AD. The apolipoprotein E (APOE) ε4 haplotype, the leading genetic risk variant of late-onset Alzheimer dementia, increases β-amyloid deposition in the human cortex.2-4 Other known risk loci of Alzheimer dementia are also implicated in cortical β-amyloid pathogenesis.5-7 β-Amyloid pathological changes are mechanistically linked to neurofibrillary tangles,8,9 the other histological lesions characteristic of AD. Earlier studies showed that the association of β-amyloid plaques with cognitive outcomes is mediated through neurofibrillary tangles.10,11 Furthermore, β-amyloid is inversely associated with cognition and episodic memory in particular.12 Higher levels of brain β-amyloid deposition are associated with faster cognitive decline among older persons.13-16

A large body of cell culture and animal models suggest that soluble β-amyloid is neurotoxic and leads to synaptic and neural damage.17-20 However, current neuroimaging and neuropathologic markers focus on insoluble β-amyloid deposits. Studies that examined soluble β-amyloid in association with AD and Alzheimer dementia in the human cortex21-23 have not specifically addressed whether the associations are independent of deposited β-amyloid. As a result, the extent to which soluble β-amyloid in the human neocortex is associated with classic features of AD remains largely unknown.

In this study, we examined cortical β-amyloid protein levels in postmortem human brains that did not have deposited β-amyloid. Cortical β-amyloid protein was measured by selected reaction monitoring (SRM) proteomics, and β-amyloid deposits were detected using immunohistochemistry during uniform neuropathologic evaluation. First, we tested the hypothesis that in the absence of deposited β-amyloid, a higher level of β-amyloid protein is associated with clinical diagnosis of cognitive impairment and dementia as well as faster cognitive decline. Next, we examined the protein associations with neurofibrillary tangles and other age-associated neuropathologic conditions, including infarcts, Lewy bodies, hippocampal sclerosis, hyperphosphorylated transactive response DNA-binding protein (TDP), amyloid angiopathy, atherosclerosis, and arteriolosclerosis. Finally, we examined the β-amyloid protein level in the absence of deposited β-amyloid and in association with the APOE genotype and a polygenic risk score of Alzheimer dementia, which have previously been shown24 to be strongly associated with deposited β-amyloid.

Methods
Study Participants

Participants came from 2 ongoing community-based clinicopathologic cohort studies of aging, the Religious Orders Study and the Rush Memory and Aging Project.25 Both community-based studies enrolled persons 65 years or older without known dementia. Participants were followed up every year with uniform clinical and neuropsychological evaluations, and all agreed to brain donation after death. The follow-up rate among survivors was more than 90%, with an autopsy rate of about 85%. The 2 studies share a large common core of testing batteries and are conducted by a same team of investigators, which facilitates combined analyses. The studies were approved by the institutional review board of Rush University Medical Center and were conducted in compliance with Declaration of Helsinki and its later amendments. Written informed consent and an anatomical gift act form were provided by each participant.

Cognitive Assessment and Clinical Diagnosis

Cognitive and neurological assessments were administered at baseline and annual follow-up visits.26,27 Cognitive assessment covers 5 dissociable domains of episodic memory (7 tests), semantic memory (3 tests), working memory (3 tests), processing speed (2 tests), and visuospatial ability (2 tests). Raw scores for each test were standardized using means and SDs at the study baseline, and a mean was determined across standardized scores of all 17 tests to obtain a global cognitive score. Domain-specific scores were computed similarly by determining the mean of the standardized scores of the tests within corresponding domains. Higher scores indicate higher cognitive function. Details on clinical diagnosis are provided in the eMethods in the Supplement.

Selected Reaction Monitoring

Cortical β-amyloid protein abundance was measured with SRM proteomics using frozen tissue from dorsolateral prefrontal cortex, as previously reported.28 Sample preparation followed standard protocol29,30 (eMethods in the Supplement). The SRM experiments were performed on a nanoACQUITY UPLC (Waters) coupled to TSQ Vantage MS instrument (ThermoFisher Scientific), as previously described.28 The SRM data were analyzed by Skyline software (64-bit version [MacCoss Lab Software])31 and were manually inspected to ensure correct peak assignment, transitions, and boundaries. The peak area ratios of endogenous light (L) peptides and their heavy (H) isotope-labeled internal standards (ie, L/H peak-area ratios) were used for accurate quantification. The peptide L/H ratios were log2 transformed and centered at the median.

Neuropathologic Evaluation

At autopsy, the brains of participants were removed and sliced into 1-cm coronal slabs. In each brain, the hemisphere with more visible gross pathology was fixed in paraformaldehyde, 4%, for diagnostic purposes. Neuropathologic evaluation was blinded to the results from clinical or cognitive assessments. Details on quantification of individual neuropathologic indices are provided in the eMethods in the Supplement.

Statistical Analysis

We used χ2, t, and nonparametric Wilcoxon rank sum tests to compare the differences between individuals with and without β-amyloid deposits. Primary analyses were restricted to individuals without β-amyloid deposits. Ordinal logistic regression model examined the association of β-amyloid protein with odds of having mild cognitive impairment or dementia diagnosis proximate to death. Linear mixed models examined the association of β-amyloid protein with annual rates of decline in global cognition and individual cognitive domains. In a series of linear and logistic regression models, we examined the associations of β-amyloid protein with paired helical filament (PHF) tau tangle density, cerebral amyloid angiopathy, and other age-associated neuropathologic conditions, as well as the associations of APOE ε4 and polygenic risk score with β-amyloid protein.

Statistical models were run using SAS/STAT version 9.4 (SAS Institute). Statistical significance was determined at nominal α level .05. Unless otherwise noted, all models were adjusted for age, sex, and education. Data analyses occurred in mid-September 2018.

Results

At the time of the analyses, a total of 3575 participants in the Religious Orders Study and the Rush Memory and Aging Project had completed baseline evaluations, of whom 1559 had died and undergone brain autopsy. Proteomic data were collected and available in 1208 individuals (77.5%), and we excluded 5 individuals with missing cognitive scores. Of the remaining 1203 individuals, the primary analyses focused on 148 individuals (12.3%) without deposited β-amyloid based on immunohistochemical testing (eMethods in the Supplement). The mean (SD) age at death was 87.0 (7.0) years, and the mean (SD) length of education was 16.6 (3.7) years. Of the 148 participants, 84 were women (56.8%), and almost all were non-Latino white individuals (n = 141 [95.3%]).

Demographic, clinical, and neuropathologic characteristics of the study participants are summarized in Table 1. Compared with those with β-amyloid deposits (n = 1055), participants without β-amyloid deposits (n = 148) were about 2.7 years younger (mean [SD] age: with β-amyloid deposits, 89.7 [6.4]; without β-amyloid deposits, 87.0 [7.0] years; t1201 = −4.79; P < .001) and were less likely to be female (female participants: with β-amyloid deposits, 734 [69.6%]; without β-amyloid deposits, 84 [56.8%]; χ21 = 9.8; P = .002). We did not observe differences in education or race/ethnicity. As expected, individuals without β-amyloid deposits were less likely to have a dementia diagnosis (χ21 = 25.7; P < .001); a quarter of these individuals (n = 37 [25.0%]) died with dementia compared with 47.1% of individuals (n = 496) with β-amyloid deposits. Most participants with dementia but without β-amyloid deposits (n = 34) had vascular disease, 9 had cortical Lewy bodies, and 13 had TDP inclusions that extended beyond the amygdala or hippocampal sclerosis. Among participants with dementia but without β-amyloid deposits, mixed pathological conditions were present in all participants with cortical Lewy bodies or TDP or hippocampal sclerosis, and almost half (n = 16 [47.1%]) of participants with vascular disease (eFigure 1 in the Supplement).

None of the 148 individuals without β-amyloid deposits had a pathologic diagnosis of AD based on modified National Institute on Aging–Reagan criteria, compared with almost three-quarters of individuals (775 [73.5%]) with β-amyloid deposits. Those without β-amyloid deposits had fewer PHF tau tangles (z = −9.68; P < .001) and were less likely to have more advanced TDP-43 pathology (χ23 = 27.3; P < .001) or amyloid angiopathy (χ23 = 111.9; P < .001). No significant differences were observed in macroscopic or microinfarcts, neocortical Lewy bodies, hippocampal sclerosis, atherosclerosis, or arteriolosclerosis.

Visual examination of cortical β-amyloid protein data revealed a distinct bimodal distribution (Figure 1). In particular, the higher peak was exclusively made up of individuals with β-amyloid deposits and almost all individuals without β-amyloid deposits were clustered near the lower peak. Notably, a sizable number of individuals had deposited β-amyloid but low β-amyloid expression. Overall, this bimodal feature provides empirical support that it is reasonable to separate cortical β-amyloid protein based on presence and absence of β-amyloid deposits.

β-Amyloid Protein With Clinical Diagnosis and Cognitive Decline in the Absence of β-Amyloid Deposits

In the absence of β-amyloid deposits, the association of β-amyloid protein level with diagnoses of mild cognitive impairment and Alzheimer dementia proximate to death did not reach statistical significance. The result from a linear mixed model shows that for a representative female participant (85 years of age, with 15 years of education and a β-amyloid protein level at the median), the mean (SE) rate of decline in global cognition is about −0.056 (0.014) unit per year (P < .001). With every additional log2 unit increment of β-amyloid protein level, the annual rate of decline was increased by about 25% (estimate [SE] of the increase per log2 increment, −0.014 [0.005] unit per year; P = .008; Figure 2).

We repeated the analysis for each of the 5 cognitive domains (Table 2 and eFigure 2 in the Supplement). In the absence of β-amyloid deposits, β-amyloid protein level was not associated with decline in episodic memory, the clinical hallmark of Alzheimer dementia. By contrast, a higher β-amyloid protein level was associated with faster rates of decline in processing speed (mean [SE] change, −0.014 [0.005]; P = .008) and visuospatial abilities (mean [SE] change, −0.013 [0.005]; P = .006). The protein level was not associated with decline in either semantic or working memory (Figure 2).

β-Amyloid Protein With PHF Tau Tangles and Other Neuropathologic Changes in the Absence of β-Amyloid Deposits

Next, we examined the associations of β-amyloid protein level with PHF tau tangle density and other age-associated neuropathologic indices in a series of regression models (Table 3). In the absence of β-amyloid deposits, β-amyloid protein was not associated with PHF tau tangles. The results remain the same for both neocortical tangles and mesial temporal tangles. However, the protein was associated with amyloid angiopathy. Individuals with higher β-amyloid levels tend to have more advanced amyloid angiopathy (odds ratio, 1.38 [95% CI, 1.15-1.67]; P < .001). β-Amyloid protein was not associated with any of the other age-associated neuropathologic indices.

Since β-amyloid protein was associated with amyloid angiopathy, we further examined whether the protein associations with cognitive decline were attributable to amyloid angiopathy. We repeated the linear mixed models by including terms to adjust for amyloid angiopathy. In these analyses, amyloid angiopathy was not associated with cognitive decline. The β-amyloid protein association with decline in global cognition was essentially unchanged (estimate [SE] of the increase per log2 increment, −0.015 [0.005]; P = .005), as were the protein associations with processing speed and visuospatial ability (data not shown).

β-Amyloid Protein With Risk Variants of Alzheimer Dementia in the Absence of β-Amyloid Deposits

The APOE ε4 allele was present in only 9 of 148 individuals (6.1%) without β-amyloid deposits, and this percentage was much lower than those with β-amyloid deposits (298 of 1055 [28.5%]; χ21 = 33.8; P < .001). Similarly, the non-APOE polygenic Alzheimer risk score was lower in individuals without β-amyloid deposits (t1040 = −3.58; P < .001). Adjusted for demographics, β-amyloid level did not differ by APOE ε4 status in individuals without β-amyloid deposits. Neither did we observe an association of the polygenic risk score with β-amyloid protein level.

Discussion

To our knowledge, this is the first study that has investigated associations of β-amyloid protein in postmortem human brains without deposited β-amyloid with Alzheimer genetics, common age-associated neuropathologic conditions, clinical outcomes, and cognitive outcomes. These data show that, of more than 1200 community-based persons aged 65 years and older whose bodies came to autopsy, approximately 12% did not have cortical β-amyloid deposits. These individuals in general had less neuropathologic burden including PHF tau tangles, TDP-43, and cerebral amyloid angiopathy compared with those with β-amyloid deposits. None of them were diagnosed with pathologic AD, and only 9 individuals were APOE ε4 carriers. In the absence of β-amyloid deposits, β-amyloid protein level detected in the cortex was associated with decline in global cognition and decline in perceptual speed and visuospatial ability but not with decline in episodic memory, the clinical hallmark of Alzheimer dementia. β-Amyloid protein levels were also associated with amyloid angiopathy. However, they were not correlated with PHF tau tangles, other age-associated neuropathologic changes, or known Alzheimer genetic risk loci. This study adds new evidence to the current literatures on the role of cortical soluble β-amyloid as a neurotoxic agent in aging.

The traditional amyloid cascade hypothesis of AD proposes that β-amyloid deposition triggers neuropathologic changes, including the development of neurofibrillary tangles and neuronal loss.32 Alternatively, the β-amyloid oligomer hypothesis proposes that it is soluble β-amyloid oligomers that not only lead to aggregation of β-amyloid fibrils but also directly cause synaptic and neuronal damages. The second of these hypotheses was incorporated into a revised version of the cascade theory.33 Indeed, the neurotoxicity of soluble β-amyloid, small β-amyloid oligomers in particular, has been widely reported in in vivo or in vitro experiments.20,34 However, there have been few data from postmortem human brains on if and how cortical soluble β-amyloid is correlated with other age-associated brain lesions as well as downstream cognitive outcomes. There are a few studies21,22 using data from the human cortex that examined the soluble and insoluble β-amyloid in association with AD pathologies and Alzheimer dementia, and 1 study23 has reported that β-amyloid monomer and dimers level in extracts of 43 human brains were associated with Alzheimer dementia and Alzheimer-associated pathological changes. A more recent study35 using brain tissues from the Religious Orders Study cohort showed that levels of different β-amyloid oligomers varied by cognitive status and were correlated with plaque load. Unfortunately, these findings did not address an important question regarding whether the outcomes associated with soluble β-amyloid are independent of or simply mediated or confounded by insoluble deposits, and earlier evidence36 suggests that trafficking from soluble to insoluble pools of β-amyloid drives the progression of AD. This study is distinct from these prior reports in that we specifically targeted β-amyloid protein in the absence of β-amyloid deposits, and the results reveal a protein association with late-life cognitive decline independent of deposited β-amyloid.

Importantly, many aspects of these findings suggest that the adverse outcomes associated with β-amyloid protein in the absence of insoluble deposits may be reflective of neuropathologic change that differs from that of AD. First, we did not observe a strong genetic footprint of AD among elderly participants without β-amyloid deposits. These individuals were predominantly non–APOE ε4 carriers (93.9%), a percentage much higher than that of the general population. Separately, a non-APOE polygenic Alzheimer risk score is significantly lower in individuals without β-amyloid deposits than in those with deposits. Further, we did not observe a genetic association (either ε4 or polygenic Alzheimer risk score) with β-amyloid protein in the absence of insoluble deposits. Second, we did not observe a link between β-amyloid protein and PHF tau tangles among elderly persons without insoluble deposits. This is consistent with a prior report on this cohort37 that showed that APOE was not associated with PHF tau tangles in the absence of β-amyloid deposits. There is no association between β-amyloid protein with tangle density, and additional analyses on region-specific tangle pathology measures revealed the same results. Third, while higher β-amyloid protein level in the absence of insoluble deposits is associated with faster decline in cognition, the association is driven by nonmemory cognitive domains of processing speed and visuospatial ability rather than by episodic memory, the clinical hallmark of Alzheimer dementia. The differential associations of protein with decline in select cognitive domains are intriguing and need to be confirmed.

Mechanisms underlying the association between β-amyloid and cognitive decline in the absence of insoluble deposits remain speculative. Experiments on cell culture and animal brains show that tau is hyperphosphorylated with increased β-amyloid oligomer levels, which link soluble β-amyloid to the pathology of neurofibrillary tangles.38-40 In this study, β-amyloid was not correlated with tangle density without insoluble deposits, and the protein association with cognitive decline did not change even after controlling for PHF tau tangles pathology. Other potential mechanisms have also been proposed, including abnormal calcium signaling, oxidative stress, impaired synaptic plasticity, and neuronal insulin signaling.41 Separately, these data show that higher levels of β-amyloid protein were associated with more advanced cerebral amyloid angiopathy, suggesting this association may work through a cerebral vascular pathway. However, amyloid angiopathy was not associated with cognitive decline in this analysis, and the protein association with cognitive decline persisted after amyloid angiopathy was controlled in these models.

Individuals without deposited β-amyloid may represent a resilient group of elderly persons. Indeed, these neuropathologic data reveal that individuals without β-amyloid had a lower burden of AD-associated pathological signs, including tangles and cerebral amyloid angiopathy, as well as other pathologic conditions, such as TDP, that often co-occur with AD. The result is that, compared with individuals with β-amyloid deposits, those without deposits had lower risks of cognitive impairment or dementia. However, a quarter of the individuals without deposits still had dementia, and neuropathologic signs other than deposited β-amyloid were commonly found at autopsy. This finding has important implications for future prevention trials. First, it is unclear whether any of the persons with β-amyloid protein but without deposited β-amyloid would have progressed to develop AD had they survived longer. Therefore, it is hard to know whether it would be of benefit to administer medications to elderly persons with evidence of β-amyloid protein in the absence of a positive amyloid positron emission tomographic scan result. Second, the therapeutic effectiveness of targeting β-amyloid concentration in an effort to prevent cognitive impairment or AD remains to be determined. On the one hand, laboratory evidence suggests that soluble β-amyloid impairs synaptic function and memory.42 On the other hand, these data reveal a sizable number of individuals with deposited β-amyloid but low concentrations of β-amyloid. This discordance suggests that β-amyloid deposition may not be entirely dependent on β-amyloid concentration, and factors such as cleanup, misfolding, and prionlike mechanisms may also play a role. Collectively, these questions highlight that more work in this space is warranted.

Several technical details of the β-amyloid quantification in this study are noted. The assay configuration does not distinguish β-amyloid from other species. The tryptic peptide used to quantify β-amyloid, LVFFAEDVGSNK, corresponds to 688 to 699 amino acids mapped to all species of β-amyloid, as well as C99, C83, P3, and full-length β-amyloid precursor protein (APP) (eFigure 3 in the Supplement). We measure APP separately with 2 peptides mapped to the N-terminal region (THPHFVIPYR; 107-116 AAs) and central region (EVCSEQAETGPCR; 299-301 AAs) of the full-length protein. These 2 peptides are not correlated with β-amyloid, suggesting that the level of APP can be ruled out as a confounding factor. In addition, the β-amyloid measure in this study does not distinguish between monomers and oligomers. Future work also needs to investigate whether the β-amyloid 42:β-amyloid 40 ratio differs between individuals with or without visible deposits.

The study has strengths. We are not aware of any prior study that has systematically interrogated β-amyloid protein in postmortem human cortex in the absence of β-amyloid deposits. By leveraging multilevel data from more than 1200 elderly participants in this community-based study who had agreed to annual evaluations and brain donation, we are able to identify nearly 150 individuals who had no β-amyloid deposits, which allowed us to cross-examine the protein association with AD genetics, clinical outcomes, and cognitive outcomes, as well as common age-associated neuropathologic conditions.

Limitations

The Religious Orders Study and the Rush Memory and Aging Project are voluntary cohorts. Participants in this study are elderly and predominantly non-Latino white individuals. There were few APOE ε4 carriers, which may limit power to find an association of this variable with other factors. Findings in this study may not be readily translatable to individuals with both soluble β-amyloid and insoluble deposits. Current cortical proteomics data are restricted to dorsolateral prefrontal cortex, and data collection from multiple brain regions is planned.

Conclusions

In conclusion, cortical β-amyloid protein was implicated in faster cognitive decline in the absence of β-amyloid deposits, which supports the role of cortical soluble β-amyloid as a neurotoxic agent in aging. The lack of protein association with PHF tau tangles, episodic memory decline, or strong genetic drivers of deposited β-amyloid suggests an underlying neuropathologic change that may differ from that of AD.

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Article Information

Accepted for Publication: February 7, 2019.

Corresponding Author: Lei Yu, PhD, Rush Alzheimer’s Disease Center, 1750 W Harrison St, Ste 1000, Chicago, IL 60612 (lei_yu@rush.edu).

Published Online: April 22, 2019. doi:10.1001/jamaneurol.2019.0834

Author Contributions: Dr Yu had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Petyuk, Bennett.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Yu, Petyuk, De Jager.

Critical revision of the manuscript for important intellectual content: Petyuk, Tasaki, Boyle, Gaiteri, Schneider, De Jager, Bennett.

Statistical analysis: Yu, Gaiteri.

Obtained funding: Boyle, De Jager, Bennett.

Administrative, technical, or material support: Petyuk, Schneider, Bennett.

Supervision: Petyuk, De Jager, Bennett.

Conflict of Interest Disclosures: Drs Yu and Bennett report grants from the National Institute on Aging during the conduct of the study. Dr Schneider reports personal fees from AVID radiopharmaceuticals, Eli Lilly, Genetech, and Grifols, outside the submitted work. No other disclosures were reported.

Funding/Support: This study was funded by the National Institute on Aging (grants P30AG10161, R01AG17917, R01AG34374, RF1AG15819, RF1AG36042, and U01AG46152). The proteomics work described herein was performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the Department of Energy (contract DE-AC05-76RL0 1830).

Role of the Funder/Sponsor: The funding organizations had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Additional Contributions: We thank participants in the Religious Orders Study and the Rush Memory and Aging Project for donating their data and biospecimens. We are also thankful to investigators and staff at the Rush Alzheimer’s Disease Center for their professional contributions; they were not compensated with study funds for their contributions.

Additional Information: Data used in this study can be requested through the Rush Alzheimer’s Disease Center Research Resource Sharing Hub (http://www.radc.rush.edu).

References
1.
Hyman  BT, Phelps  CH, Beach  TG,  et al.  National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease.  Alzheimers Dement. 2012;8(1):1-13. doi:10.1016/j.jalz.2011.10.007PubMedGoogle ScholarCrossref
2.
Schmechel  DE, Saunders  AM, Strittmatter  WJ,  et al.  Increased amyloid beta-peptide deposition in cerebral cortex as a consequence of apolipoprotein E genotype in late-onset Alzheimer disease.  Proc Natl Acad Sci U S A. 1993;90(20):9649-9653. doi:10.1073/pnas.90.20.9649PubMedGoogle ScholarCrossref
3.
Mishra  S, Blazey  TM, Holtzman  DM,  et al.  Longitudinal brain imaging in preclinical Alzheimer disease: impact of APOE ε4 genotype.  Brain. 2018;141(6):1828-1839. doi:10.1093/brain/awy103PubMedGoogle ScholarCrossref
4.
Reiman  EM, Chen  K, Liu  X,  et al.  Fibrillar amyloid-beta burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease.  Proc Natl Acad Sci U S A. 2009;106(16):6820-6825. doi:10.1073/pnas.0900345106PubMedGoogle ScholarCrossref
5.
Lambert  J-C, Ibrahim-Verbaas  CA, Harold  D,  et al; European Alzheimer’s Disease Initiative (EADI); Genetic and Environmental Risk in Alzheimer’s Disease; Alzheimer’s Disease Genetic Consortium; Cohorts for Heart and Aging Research in Genomic Epidemiology.  Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease.  Nat Genet. 2013;45(12):1452-1458. doi:10.1038/ng.2802PubMedGoogle ScholarCrossref
6.
Shulman  JM, Chen  K, Keenan  BT,  et al.  Genetic susceptibility for Alzheimer disease neuritic plaque pathology.  JAMA Neurol. 2013;70(9):1150-1157. doi:10.1001/jamaneurol.2013.2815PubMedGoogle ScholarCrossref
7.
Beecham  GW, Hamilton  K, Naj  AC,  et al; Alzheimer’s Disease Genetics Consortium (ADGC).  Genome-wide association meta-analysis of neuropathologic features of Alzheimer’s disease and related dementias.  PLoS Genet. 2014;10(9):e1004606. doi:10.1371/journal.pgen.1004606PubMedGoogle ScholarCrossref
8.
Brier  MR, Gordon  B, Friedrichsen  K,  et al.  Tau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease.  Sci Transl Med. 2016;8(338):338ra66.PubMedGoogle ScholarCrossref
9.
He  Z, Guo  JL, McBride  JD,  et al.  Amyloid-β plaques enhance Alzheimer’s brain tau-seeded pathologies by facilitating neuritic plaque tau aggregation.  Nat Med. 2018;24(1):29-38. doi:10.1038/nm.4443PubMedGoogle ScholarCrossref
10.
Bennett  DA, Schneider  JA, Wilson  RS, Bienias  JL, Arnold  SE.  Neurofibrillary tangles mediate the association of amyloid load with clinical Alzheimer disease and level of cognitive function.  Arch Neurol. 2004;61(3):378-384. doi:10.1001/archneur.61.3.378PubMedGoogle ScholarCrossref
11.
Aschenbrenner  AJ, Gordon  BA, Benzinger  TLS, Morris  JC, Hassenstab  JJ.  Influence of tau PET, amyloid PET, and hippocampal volume on cognition in Alzheimer disease.  Neurology. 2018;91(9):e859-e866. doi:10.1212/WNL.0000000000006075PubMedGoogle ScholarCrossref
12.
Malek-Ahmadi  M, Perez  SE, Chen  K, Mufson  EJ.  Neuritic and diffuse plaque associations with memory in non-cognitively impaired elderly.  J Alzheimers Dis. 2016;53(4):1641-1652. doi:10.3233/JAD-160365PubMedGoogle ScholarCrossref
13.
Boyle  PA, Yu  L, Wilson  RS, Schneider  JA, Bennett  DA.  Relation of neuropathology with cognitive decline among older persons without dementia.  Front Aging Neurosci. 2013;5:50. doi:10.3389/fnagi.2013.00050PubMedGoogle ScholarCrossref
14.
Doraiswamy  PM, Sperling  RA, Coleman  RE,  et al; AV45-A11 Study Group.  Amyloid-β assessed by florbetapir F 18 PET and 18-month cognitive decline: a multicenter study.  Neurology. 2012;79(16):1636-1644. doi:10.1212/WNL.0b013e3182661f74PubMedGoogle ScholarCrossref
15.
Resnick  SM, Sojkova  J, Zhou  Y,  et al.  Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB.  Neurology. 2010;74(10):807-815. doi:10.1212/WNL.0b013e3181d3e3e9PubMedGoogle ScholarCrossref
16.
Mormino  EC, Kluth  JT, Madison  CM,  et al; Alzheimer’s Disease Neuroimaging Initiative.  Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects.  Brain. 2009;132(pt 5):1310-1323. doi:10.1093/brain/awn320PubMedGoogle ScholarCrossref
17.
Hayden  EY, Teplow  DB.  Amyloid β-protein oligomers and Alzheimer’s disease.  Alzheimers Res Ther. 2013;5(6):60. doi:10.1186/alzrt226PubMedGoogle ScholarCrossref
18.
Selkoe  DJ, Hardy  J.  The amyloid hypothesis of Alzheimer’s disease at 25 years.  EMBO Mol Med. 2016;8(6):595-608. doi:10.15252/emmm.201606210PubMedGoogle ScholarCrossref
19.
Kayed  R, Head  E, Thompson  JL,  et al.  Common structure of soluble amyloid oligomers implies common mechanism of pathogenesis.  Science. 2003;300(5618):486-489. doi:10.1126/science.1079469PubMedGoogle ScholarCrossref
20.
Cline  EN, Bicca  MA, Viola  KL, Klein  WL.  The amyloid-β oligomer hypothesis: beginning of the third decade.  J Alzheimers Dis. 2018;64(s1):S567-S610.PubMedGoogle ScholarCrossref
21.
Lue  LF, Kuo  YM, Roher  AE,  et al.  Soluble amyloid beta peptide concentration as a predictor of synaptic change in Alzheimer’s disease.  Am J Pathol. 1999;155(3):853-862. doi:10.1016/S0002-9440(10)65184-XPubMedGoogle ScholarCrossref
22.
McLean  CA, Cherny  RA, Fraser  FW,  et al.  Soluble pool of Abeta amyloid as a determinant of severity of neurodegeneration in Alzheimer’s disease.  Ann Neurol. 1999;46(6):860-866. doi:10.1002/1531-8249(199912)46:6<860::AID-ANA8>3.0.CO;2-MPubMedGoogle ScholarCrossref
23.
Mc Donald  JM, Savva  GM, Brayne  C,  et al; Medical Research Council Cognitive Function and Ageing Study.  The presence of sodium dodecyl sulphate-stable Abeta dimers is strongly associated with Alzheimer-type dementia.  Brain. 2010;133(pt 5):1328-1341. doi:10.1093/brain/awq065PubMedGoogle ScholarCrossref
24.
Tasaki  S, Gaiteri  C, Mostafavi  S, De Jager  PL, Bennett  DA.  The molecular and neuropathological consequences of genetic risk for Alzheimer’s dementia.  Front Neurosci. 2018;12(699):699.PubMedGoogle ScholarCrossref
25.
Bennett  DA, Buchman  AS, Boyle  PA, Barnes  LL, Wilson  RS, Schneider  JA.  Religious Orders Study and Rush Memory and Aging Project.  J Alzheimers Dis. 2018;64(s1):S161-S189. doi:10.3233/JAD-179939PubMedGoogle ScholarCrossref
26.
Bennett  DA, Schneider  JA, Bienias  JL, Evans  DA, Wilson  RS.  Mild cognitive impairment is related to Alzheimer disease pathology and cerebral infarctions.  Neurology. 2005;64(5):834-841. doi:10.1212/01.WNL.0000152982.47274.9EPubMedGoogle ScholarCrossref
27.
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. doi:10.1212/WNL.0b013e3181d64786PubMedGoogle ScholarCrossref
28.
Yu  L, Petyuk  VA, Gaiteri  C,  et al.  Targeted brain proteomics uncover multiple pathways to Alzheimer’s dementia.  Ann Neurol. 2018;84(1):78-88. doi:10.1002/ana.25266PubMedGoogle ScholarCrossref
29.
Petyuk  VA, Qian  WJ, Smith  RD, Smith  DJ.  Mapping protein abundance patterns in the brain using voxelation combined with liquid chromatography and mass spectrometry.  Methods. 2010;50(2):77-84. doi:10.1016/j.ymeth.2009.07.009PubMedGoogle ScholarCrossref
30.
Andreev  VP, Petyuk  VA, Brewer  HM,  et al.  Label-free quantitative LC-MS proteomics of Alzheimer’s disease and normally aged human brains.  J Proteome Res. 2012;11(6):3053-3067. doi:10.1021/pr3001546PubMedGoogle ScholarCrossref
31.
MacLean  B, Tomazela  DM, Shulman  N,  et al.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.  Bioinformatics. 2010;26(7):966-968. doi:10.1093/bioinformatics/btq054PubMedGoogle ScholarCrossref
32.
Hardy  JA, Higgins  GA.  Alzheimer’s disease: the amyloid cascade hypothesis.  Science. 1992;256(5054):184-185. doi:10.1126/science.1566067PubMedGoogle ScholarCrossref
33.
Hardy  J, Selkoe  DJ.  The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics.  Science. 2002;297(5580):353-356. doi:10.1126/science.1072994PubMedGoogle ScholarCrossref
34.
Walsh  DM, Selkoe  DJ.  A beta oligomers—a decade of discovery.  J Neurochem. 2007;101(5):1172-1184. doi:10.1111/j.1471-4159.2006.04426.xPubMedGoogle ScholarCrossref
35.
Lesné  SE, Sherman  MA, Grant  M,  et al.  Brain amyloid-β oligomers in ageing and Alzheimer’s disease.  Brain. 2013;136(pt 5):1383-1398. doi:10.1093/brain/awt062PubMedGoogle ScholarCrossref
36.
Wang  J, Dickson  DW, Trojanowski  JQ, Lee  VM.  The levels of soluble versus insoluble brain Abeta distinguish Alzheimer’s disease from normal and pathologic aging.  Exp Neurol. 1999;158(2):328-337. doi:10.1006/exnr.1999.7085PubMedGoogle ScholarCrossref
37.
Farfel  JM, Yu  L, De Jager  PL, Schneider  JA, Bennett  DA.  Association of APOE with tau-tangle pathology with and without β-amyloid.  Neurobiol Aging. 2016;37:19-25. doi:10.1016/j.neurobiolaging.2015.09.011PubMedGoogle ScholarCrossref
38.
De Felice  FG, Wu  D, Lambert  MP,  et al.  Alzheimer’s disease-type neuronal tau hyperphosphorylation induced by A β oligomers.  Neurobiol Aging. 2008;29(9):1334-1347. doi:10.1016/j.neurobiolaging.2007.02.029PubMedGoogle ScholarCrossref
39.
Jin  M, Shepardson  N, Yang  T, Chen  G, Walsh  D, Selkoe  DJ.  Soluble amyloid beta-protein dimers isolated from Alzheimer cortex directly induce Tau hyperphosphorylation and neuritic degeneration.  Proc Natl Acad Sci U S A. 2011;108(14):5819-5824. doi:10.1073/pnas.1017033108PubMedGoogle ScholarCrossref
40.
Chabrier  MA, Blurton-Jones  M, Agazaryan  AA, Nerhus  JL, Martinez-Coria  H, LaFerla  FM.  Soluble Aβ promotes wild-type tau pathology in vivo.  J Neurosci. 2012;32(48):17345-17350. doi:10.1523/JNEUROSCI.0172-12.2012PubMedGoogle ScholarCrossref
41.
Ferreira  ST, Lourenco  MV, Oliveira  MM, De Felice  FG.  Soluble amyloid-β oligomers as synaptotoxins leading to cognitive impairment in Alzheimer’s disease.  Front Cell Neurosci. 2015;9:191. doi:10.3389/fncel.2015.00191PubMedGoogle Scholar
42.
Shankar  GM, Li  S, Mehta  TH,  et al.  Amyloid-beta protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory.  Nat Med. 2008;14(8):837-842. doi:10.1038/nm1782PubMedGoogle ScholarCrossref
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