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Figure 1.  Flow Diagram Demonstrating the First 2 Screening Visits in the A4 Study Screening Process
Flow Diagram Demonstrating the First 2 Screening Visits in the A4 Study Screening Process

Screening visit 1 included collection of demographic information, apolipoprotein E (APOE) genotyping, cognitive testing, and clinical assessments to determine eligibility to proceed to screening visit 2 for positron emission tomography (PET) amyloid imaging. Numbers of participants evaluated at each step and classified as elevated amyloid (Aβ+) or not elevated amyloid (Aβ−) with florbetapir amyloid PET imaging are indicated.

Figure 2.  Comparison of Screening Neuropsychological Test Performance by Amyloid Status
Comparison of Screening Neuropsychological Test Performance by Amyloid Status

A, Box and whisker plot comparing the overall screening Preclinical Alzheimer Cognitive Composite (PACC) score demonstrating lower PACC performance among the elevated (Aβ+, dark blue) group compared with the not elevated (Aβ−, light blue).Individual components of the PACC comparing Aβ+ groups on the Mini-Mental State Examination (MMSE) (B), Digit Symbol Substitution Test (C), Logical Memory (LM) IIa Delayed Recall (D), and the Free and Cued Selective Reminding Test (FCSRT) (E) summing both Free and Total score (FCSRT96).

Figure 3.  Cognitive Function Index (CFI) Scores by Amyloid Status
Cognitive Function Index (CFI) Scores by Amyloid Status

A, Box and whisker plot of the CFI self-report by participant (CFI-Pt) in not elevated (Aβ−, light blue) compared with elevated (Aβ+, dark blue) group. B, Comparison of CFI study partner report (CFI-SP). C, Sum of participant and study partner CFI scores across amyloid groups.

Table 1.  Demographic Variables of All Participants Who Underwent Screening Amyloid PET With Comparison of Not Elevated (Aβ−) and Elevated Amyloid (Aβ+) Groups
Demographic Variables of All Participants Who Underwent Screening Amyloid PET With Comparison of Not Elevated (Aβ−) and Elevated Amyloid (Aβ+) Groups
Table 2.  Summary of Self-report of Lifestyle Habits, Cognitive Testing on the PACC With Subcomponents, and Self- and Study Partner Report of Change in Daily Cognitive Function Over the Past Year on the CFI in the Full Sample and Comparison of Not Elevated (Aβ−) and Elevated Amyloid (Aβ+) Groups
Summary of Self-report of Lifestyle Habits, Cognitive Testing on the PACC With Subcomponents, and Self- and Study Partner Report of Change in Daily Cognitive Function Over the Past Year on the CFI in the Full Sample and Comparison of Not Elevated (Aβ−) and Elevated Amyloid (Aβ+) Groups
1.
Price  JL, Morris  JC.  Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease.   Ann Neurol. 1999;45(3):358-368. doi:10.1002/1531-8249(199903)45:3<358::AID-ANA12>3.0.CO;2-X PubMedGoogle ScholarCrossref
2.
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(3):280-292. doi:10.1016/j.jalz.2011.03.003 PubMedGoogle ScholarCrossref
3.
Jack  CR  Jr, Bennett  DA, Blennow  K,  et al; Contributors.  NIA-AA research framework: toward a biological definition of Alzheimer’s disease.   Alzheimers Dement. 2018;14(4):535-562. doi:10.1016/j.jalz.2018.02.018 PubMedGoogle ScholarCrossref
4.
Lim  YY, Maruff  P, Pietrzak  RH,  et al; AIBL Research Group.  Effect of amyloid on memory and non-memory decline from preclinical to clinical Alzheimer’s disease.   Brain. 2014;137(pt 1):221-231. doi:10.1093/brain/awt286 PubMedGoogle ScholarCrossref
5.
Petersen  RC, Wiste  HJ, Weigand  SD,  et al.  Association of elevated amyloid levels with cognition and biomarkers in cognitively normal people from the community.   JAMA Neurol. 2016;73(1):85-92. doi:10.1001/jamaneurol.2015.3098 PubMedGoogle ScholarCrossref
6.
Mormino  EC, Papp  KV, Rentz  DM,  et al.  Early and late change on the preclinical Alzheimer’s cognitive composite in clinically normal older individuals with elevated amyloid β.   Alzheimers Dement. 2017;13(9):1004-1012. doi:10.1016/j.jalz.2017.01.018 PubMedGoogle ScholarCrossref
7.
Donohue  MC, Sperling  RA, Petersen  R, Sun  CK, Weiner  MW, Aisen  PS; Alzheimer’s Disease Neuroimaging Initiative.  Association between elevated brain amyloid and subsequent cognitive decline among cognitively normal persons.   JAMA. 2017;317(22):2305-2316. doi:10.1001/jama.2017.6669 PubMedGoogle ScholarCrossref
8.
Jack  CR  Jr, Wiste  HJ, Therneau  TM,  et al.  Associations of amyloid, tau, and neurodegeneration biomarker profiles with rates of memory decline among individuals without dementia.   JAMA. 2019;321(23):2316-2325. doi:10.1001/jama.2019.7437 PubMedGoogle ScholarCrossref
9.
Jessen  F, Amariglio  RE, van Boxtel  M,  et al; Subjective Cognitive Decline Initiative (SCD-I) Working Group.  A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease.   Alzheimers Dement. 2014;10(6):844-852. doi:10.1016/j.jalz.2014.01.001 PubMedGoogle ScholarCrossref
10.
Amariglio  RE, Buckley  RF, Mormino  EC,  et al.  Amyloid-associated increases in longitudinal report of subjective cognitive complaints.   Alzheimers Dement (N Y). 2018;4:444-449. doi:10.1016/j.trci.2018.08.005PubMedGoogle Scholar
11.
Vos  SJ, Xiong  C, Visser  PJ,  et al.  Preclinical Alzheimer’s disease and its outcome: a longitudinal cohort study.   Lancet Neurol. 2013;12(10):957-965. doi:10.1016/S1474-4422(13)70194-7 PubMedGoogle ScholarCrossref
12.
Insel  PS, Hansson  O, Mackin  RS, Weiner  M, Mattsson  N; Alzheimer’s Disease Neuroimaging Initiative.  Amyloid pathology in the progression to mild cognitive impairment.   Neurobiol Aging. 2018;64:76-84. doi:10.1016/j.neurobiolaging.2017.12.018 PubMedGoogle ScholarCrossref
13.
Doody  RS, Thomas  RG, Farlow  M,  et al; Alzheimer’s Disease Cooperative Study Steering Committee; Solanezumab Study Group.  Phase 3 trials of solanezumab for mild-to-moderate Alzheimer’s disease.   N Engl J Med. 2014;370(4):311-321. doi:10.1056/NEJMoa1312889 PubMedGoogle ScholarCrossref
14.
Hedden  T, Oh  H, Younger  AP, Patel  TA.  Meta-analysis of amyloid-cognition relations in cognitively normal older adults.   Neurology. 2013;80(14):1341-1348. doi:10.1212/WNL.0b013e31828ab35d PubMedGoogle ScholarCrossref
15.
Sperling  RA, Rentz  DM, Johnson  KA,  et al.  The A4 study: stopping AD before symptoms begin?   Sci Transl Med. 2014;6(228):228fs13. doi:10.1126/scitranslmed.3007941 PubMedGoogle Scholar
16.
Harkins  K, Sankar  P, Sperling  R,  et al.  Development of a process to disclose amyloid imaging results to cognitively normal older adult research participants.   Alzheimers Res Ther. 2015;7(1):26. doi:10.1186/s13195-015-0112-7 PubMedGoogle ScholarCrossref
17.
Amariglio  RE, Donohue  MC, Marshall  GA,  et al; Alzheimer’s Disease Cooperative Study.  Tracking early decline in cognitive function in older individuals at risk for Alzheimer disease dementia: the Alzheimer’s Disease Cooperative Study Cognitive Function Instrument.   JAMA Neurol. 2015;72(4):446-454. doi:10.1001/jamaneurol.2014.3375 PubMedGoogle ScholarCrossref
18.
Pontecorvo  MJ, Arora  AK, Devine  M,  et al.  Quantitation of PET signal as an adjunct to visual interpretation of florbetapir imaging.   Eur J Nucl Med Mol Imaging. 2017;44(5):825-837. doi:10.1007/s00259-016-3601-4 PubMedGoogle ScholarCrossref
19.
Johnson  KA, Sperling  RA, Gidicsin  CM,  et al; AV45-A11 study group.  Florbetapir (F18-AV-45) PET to assess amyloid burden in Alzheimer’s disease dementia, mild cognitive impairment, and normal aging.   Alzheimers Dement. 2013;9(5)(suppl):S72-S83. doi:10.1016/j.jalz.2012.10.007 PubMedGoogle ScholarCrossref
20.
Ward  A, Crean  S, Mercaldi  CJ,  et al.  Prevalence of apolipoprotein E4 genotype and homozygotes (APOE e4/4) among patients diagnosed with Alzheimer’s disease: a systematic review and meta-analysis.   Neuroepidemiology. 2012;38(1):1-17. doi:10.1159/000334607 PubMedGoogle ScholarCrossref
21.
Caselli  RJ, Walker  D, Sue  L, Sabbagh  M, Beach  T.  Amyloid load in nondemented brains correlates with APOE e4.   Neurosci Lett. 2010;473(3):168-171. doi:10.1016/j.neulet.2010.02.016 PubMedGoogle ScholarCrossref
22.
Vemuri  P, Knopman  DS, Lesnick  TG,  et al.  Evaluation of amyloid protective factors and Alzheimer disease neurodegeneration protective factors in elderly individuals.   JAMA Neurol. 2017;74(6):718-726. doi:10.1001/jamaneurol.2017.0244 PubMedGoogle ScholarCrossref
23.
Gottesman  RF, Schneider  AL, Zhou  Y,  et al.  Association between midlife vascular risk factors and estimated brain amyloid deposition.   JAMA. 2017;317(14):1443-1450. doi:10.1001/jama.2017.3090 PubMedGoogle ScholarCrossref
24.
Buckley  RF, Mormino  EC, Amariglio  RE,  et al; Alzheimer’s Disease Neuroimaging Initiative; Australian Imaging, Biomarker and Lifestyle study of ageing; Harvard Aging Brain Study.  Sex, amyloid, and APOE ε4 and risk of cognitive decline in preclinical Alzheimer’s disease: findings from three well-characterized cohorts.   Alzheimers Dement. 2018;14(9):1193-1203. doi:10.1016/j.jalz.2018.04.010 PubMedGoogle ScholarCrossref
25.
Rabin  JS, Klein  H, Kirn  DR,  et al.  Associations of physical activity and β-amyloid with longitudinal cognition and neurodegeneration in clinically normal older adults.   JAMA Neurol. 2019. doi:10.1001/jamaneurol.2019.1879 PubMedGoogle Scholar
26.
Gottesman  RF, Schneider  AL, Zhou  Y,  et al.  The ARIC-PET amyloid imaging study: brain amyloid differences by age, race, sex, and APOE.   Neurology. 2016;87(5):473-480. doi:10.1212/WNL.0000000000002914 PubMedGoogle ScholarCrossref
27.
Zahodne  LB, Manly  JJ, Narkhede  A,  et al.  Structural MRI predictors of late-life cognition differ across African Americans, Hispanics, and whites.   Curr Alzheimer Res. 2015;12(7):632-639. doi:10.2174/1567205012666150530203214 PubMedGoogle ScholarCrossref
28.
Barnes  LL, Leurgans  S, Aggarwal  NT,  et al.  Mixed pathology is more likely in black than white decedents with Alzheimer dementia.   Neurology. 2015;85(6):528-534. doi:10.1212/WNL.0000000000001834 PubMedGoogle ScholarCrossref
29.
Sperling  RA, Mormino  EC, Schultz  AP,  et al.  The impact of amyloid-beta and tau on prospective cognitive decline in older individuals.   Ann Neurol. 2019;85(2):181-193.PubMedGoogle Scholar
30.
Rabin  JS, Schultz  AP, Hedden  T,  et al.  Interactive associations of vascular risk and β-amyloid burden with cognitive decline in clinically normal elderly individuals: findings from the Harvard Aging Brain Study.   JAMA Neurol. 2018;75(9):1124-1131. doi:10.1001/jamaneurol.2018.1123 PubMedGoogle ScholarCrossref
31.
Vemuri  P, Lesnick  TG, Knopman  DS,  et al.  Amyloid, vascular, and resilience pathways associated with cognitive aging.   Ann Neurol. 2019;86(6):866-877. doi:10.1002/ana.25600 PubMedGoogle ScholarCrossref
32.
Soldan  A, Pettigrew  C, Fagan  AM,  et al.  ATN profiles among cognitively normal individuals and longitudinal cognitive outcomes.   Neurology. 2019;92(14):e1567-e1579. doi:10.1212/WNL.0000000000007248 PubMedGoogle ScholarCrossref
33.
Jansen  WJ, Ossenkoppele  R, Knol  DL,  et al; Amyloid Biomarker Study Group.  Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis.   JAMA. 2015;313(19):1924-1938. doi:10.1001/jama.2015.4668 PubMedGoogle ScholarCrossref
34.
Jack  CR  Jr, Wiste  HJ, Weigand  SD,  et al.  Age-specific and sex-specific prevalence of cerebral β-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50-95 years: a cross-sectional study.   Lancet Neurol. 2017;16(6):435-444. doi:10.1016/S1474-4422(17)30077-7 PubMedGoogle ScholarCrossref
35.
Dubois  B, Epelbaum  S, Nyasse  F,  et al; INSIGHT-preAD study group.  Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer’s disease (INSIGHT-preAD): a longitudinal observational study.   Lancet Neurol. 2018;17(4):335-346. doi:10.1016/S1474-4422(18)30029-2 PubMedGoogle ScholarCrossref
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    1 Comment for this article
    EXPAND ALL
    RE: Association of factors with elevated amyloid burden in clinically normal older individuals
    Tomoyuki Kawada, MD | Nippon Medical School
    Sperling et al. conducted a cross-sectional study to investigate the risk factors of elevated amyloid burden in clinically normal older individuals, including apolipoprotein E (APOE) genotyping, neuropsychological testing, and self- and study partner reports of cognitive function (1). Amyloid positron emission tomography (PET) imaging was used to classify participants as having elevated amyloid (Aβ+) or not having elevated amyloid (Aβ-). Percentages of family history of dementia and at least 1 APOE ε4 allele were significantly higher in Aβ+ individuals than Aβ- individuals. In addition, individuals with Aβ+ presented lower levels of test performance and increased reports of subtle recent declines in daily cognitive function. Regarding the fact that Aβ+ might represent a preclinical stage of Alzheimer disease (AD), I have two concerns as follows.

    First, Biddle et al. evaluated the effect of widowhood status on the level of brain β-amyloid and cognitive decline in participants (2), and standardized regression coefficients (95% confidence intervals) of widowed participants with high β-amyloid deposition and married participants with high β-amyloid deposition were -0.33 (-0.46 to -0.19) and -0.12 (-0.18 to -0.01), respectively. These data present that the rate of cognitive decline among widowed participants was nearly 3 times faster than among married participants, if they have high levels of β-amyloid deposition. Sperling et al. could not recognize marital status as a significant risk factor of Aβ+ (1), and prospective/interventional studies might contribute to specify the causal association.

    Second, Köbe et al. conducted a cross-sectional study to assess the associations of vascular risk factors with AD pathogenesis in asymptomatic individuals with special reference to vascular medications (3). Cerebrospinal fluid Aβ1-42 and phosphorylated tau levels were also used for the analysis. There were significant associations of vascular risk factors with Aβ+, which was not observed with tau burden. These associations were found only among individuals without vascular medications, and there was a significant interaction between some vascular risk factors and vascular medications. As the frequency of vascular medications increases by aging, adjustment of comorbidities and their treatments should be made for the risk assessment of elevated amyloid burden.


    References

    1. Sperling RA, Donohue MC, Raman R, et al. Association of factors with elevated amyloid burden in clinically normal older individuals. JAMA Neurol. 2020 Apr 6. doi: 10.1001/jamaneurol.2020.0387

    2. Biddle KD, Jacobs HIL, d'Oleire Uquillas F, et al. Associations of widowhood and β-amyloid with cognitive decline in cognitively unimpaired older adults. JAMA Netw Open. 2020;3(2):e200121. doi: 10.1001/jamanetworkopen.2020.0121

    3. Köbe T, Gonneaud J, Pichet Binette A, et al. Association of vascular risk factors with β-amyloid peptide and tau burdens in cognitively unimpaired individuals and its interaction with vascular medication use. JAMA Netw Open. 2020;3(2):e1920780. doi: 10.1001/jamanetworkopen.2019.20780
    CONFLICT OF INTEREST: None Reported
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    Original Investigation
    April 6, 2020

    Association of Factors With Elevated Amyloid Burden in Clinically Normal Older Individuals

    Author Affiliations
    • 1Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
    • 2Harvard Aging Brain Study, Departments of Neurology and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston
    • 3Alzheimer Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego
    • 4Eli Lilly & Co, Indianapolis, Indiana
    • 5Siemers Integration LLC
    JAMA Neurol. 2020;77(6):735-745. doi:10.1001/jamaneurol.2020.0387
    Key Points

    Question  Is elevated amyloid-β deposition associated with demographic, genetic, and lifestyle factors; decreased performance on neuropsychological tests; and increased reports of recent changes in cognitive function among clinically normal older individuals?

    Findings  In this cross-sectional analysis of the A4 Study screening demographic, cognitive and amyloid positron emission tomography data, elevated amyloid was significantly associated with higher age, apolipoprotein E ε4 allele, and family history but not with sex, education, marital or retirement status, or multiple self-reported lifestyle variables. Elevated amyloid was significantly associated with lower performance on the Preclinical Alzheimer Cognitive Composite and each of its components, as well as with increased reports of recent subjective declines in high-level daily cognitive function by the participant and their study partner.

    Meaning  Elevated amyloid is associated with worse cognition and subtle changes in daily function, even among the restricted range of normal performance required for eligibility in this secondary prevention trial.

    Abstract

    Importance  The Anti-Amyloid Treatment in Asymptomatic Alzheimer disease (A4) Study is an ongoing prevention trial in clinically normal older individuals with evidence of elevated brain amyloid. The large number of participants screened with amyloid positron emission tomography (PET) and standardized assessments provides an unprecedented opportunity to evaluate factors associated with elevated brain amyloid.

    Objective  To investigate the association of elevated amyloid with demographic and lifestyle factors, apolipoprotein E (APOE), neuropsychological testing, and self- and study partner reports of cognitive function.

    Design, Setting, and Participants  This cross-sectional study included screening data in the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study collected from April 2014 to December 2017 and classified by amyloid status. Data were was analyzed from 2018 to 2019 across 67 sites in the US, Canada, Australia, and Japan and included 4486 older individuals (age 65-85 years) who were eligible for amyloid PET (clinically normal [Clinical Dementia Rating = 0] and cognitively unimpaired [Mini-Mental State Examination score, ≥25; logical memory IIa 6-18]).

    Main Outcomes and Measures  Screening demographics, lifestyle variables, APOE genotyping, and cognitive testing (Preclinical Alzheimer Cognitive Composite), self- and study partner reports of high-level daily cognitive function (Cognitive Function Index). Florbetapir amyloid PET imaging was used to classify participants as having elevated amyloid (Aβ+) or not having elevated amyloid (Aβ−).

    Results  Amyloid PET results were acquired for 4486 participants (mean [SD] age, 71.29 [4.67] years; 2647 women [59%]), with 1323 (29.5%) classified as Aβ+. Aβ+ participants were slightly older than Aβ−, with no observed differences in sex, education, marital or retirement status, or any self-reported lifestyle factors. Aβ+ participants were more likely to have a family history of dementia (3320 Aβ+ [74%] vs 3050 Aβ− [68%]) and at least 1 APOE ε4 allele (2602 Aβ+ [58%] vs 1122 Aβ− [25%]). Aβ+ participants demonstrated worse performance on screening Preclinical Alzheimer Cognitive Composite results and reported higher change scores on the Cognitive Function Index.

    Conclusions and Relevance  Among a large group of older individuals screening for an Alzheimer disease (AD) prevention trial, elevated brain amyloid was associated with family history and APOE ε4 allele but not with multiple other previously reported risk factors for AD. Elevated amyloid was associated with lower test performance results and increased reports of subtle recent declines in daily cognitive function. These results support the hypothesis that elevated amyloid represents an early stage in the Alzheimer continuum and demonstrate the feasibility of enrolling these high-risk participants in secondary prevention trials aimed at slowing cognitive decline during the preclinical stages of AD.

    Introduction

    Substantial evidence strongly suggests that the pathophysiological process of Alzheimer disease (AD) begins more than a decade before the clinical syndrome of AD dementia. The asymptomatic or preclinical phase of the Alzheimer continuum is defined by the presence of amyloid-β (Aβ) pathology,1-3 now detectable in vivo using molecular neuroimaging and fluid biomarkers in individuals who are cognitive unimpaired and clinically normal (CN). Multiple longitudinal observational studies have reported that CN with biomarker evidence of elevated brain amyloid (Aβ+) demonstrate more rapid declines on longitudinal neuropsychological testing results,4-8 increased subjective reports of a decline in cognitive function,9,10 and a greater risk of progression to mild cognitive impairment and dementia.7,11,12 This group of high-risk Aβ+ CN constitutes an ideal population for very early intervention trials aimed at slowing cognitive decline in sporadic AD.

    The Anti-Amyloid Treatment in Asymptomatic AD (A4) Study was launched in 2014 as a first-of-its-kind prevention trial in sporadic AD and was funded as a public private partnership. The A4 Study is an ongoing 240-week (66 clinic visits) trial testing whether solanezumab,13 an antibody directed against the midpeptide region of Aβ 1-42, can slow cognitive decline associated with AD at the preclinical stage of disease. This first report of the A4 Study screening experience focuses on amyloid eligibility, a comparison of the Aβ+ and not elevated amyloid (Aβ−) CN groups on demographic and lifestyle factors, and the primary cognitive and functional outcome measures obtained during screening. Although evidence of increased longitudinal decline associated with Aβ+ has been consistent, cross-sectional reports from smaller CN cohorts have been mixed.14 The A4 Study provides an opportunity to investigate associations among demographic factors, cognitive testing, subjective reports of cognitive function, and Aβ status in a very large cohort screened with standardized methods in this international multicenter study.

    Methods

    The A4 Study15 is being conducted at 67 clinical trial sites in the US, Canada, Australia, and Japan. Participants eligible for screening were age 65 to 85 years, assessed to be CN, living independently, and had a study partner who would be able to provide information on daily life cognitive function on an annual basis. Key exclusion criteria were diagnosis of cognitive impairment or dementia, use of AD medications, significant anxiety or depression that might indicate an increased risk associated with amyloid testing and disclosure, or unstable medical conditions, although participants with treated hypertension, diabetes, hypercholesterolemia, mild-to-moderate small vessel cerebrovascular disease, and other common medical ailments were permitted. Institutional review board approval was obtained at each of the performance sites.

    Screening Process

    Participants underwent a series of screening visits to determine their eligibility for the A4 Study (Figure 1). Before and during the written informed consent process, participants were provided educational materials and the opportunity to discuss amyloid PET imaging and the eligibility criteria for the A4 Study.16 Screening visit 1 (ScrV1) included demographic, family history, lifestyle questionnaires, cognitive testing, functional questionnaires, and medical screening. The cognitive criteria were broadened to include lower screening cut points very early in the recruitment period to include participants from a range of educational backgrounds. Participants with very high (>1.5 SD above norms in this age range) Logical Memory Delayed Recall (LMDR IIa) scores were excluded after ScrV1 to enhance the likelihood of Aβ+ and to enroll participants at higher risk of imminent cognitive decline associated with AD pathology. Participants with a Clinical Dementia Rating (global score of 0, Mini-Mental State Examination (MMSE) score of 25 to 30, and LMDR-IIa score of  6 to 18 were eligible to proceed to florbetapir PET imaging.

    Cognitive testing and subjective questionnaires were administered at ScrV1before determination of eligibility to proceed to PET imaging. The primary outcome measure in the A4 Study is the Preclinical Alzheimer Cognitive Composite (PACC),6 which includes 4 components: MMSE score (0-30), digit symbol substitution test (correct responses in 90 seconds; maximum raw score = 91), LMDR-IIa score (0-25), and the free and cued selective reminding test (FCSRT; sum of free and total cued recall; score, 0-96). The Cognitive Function Index (CFI)17 is a key secondary outcome in the A4 Study, consisting of a 15-item questionnaire administered separately to the participant and their study partner that asks for yes, no, and maybe responses about changes in cognitive function over the past year.

    Amyloid PET Imaging

    Eligible participants underwent amyloid PET imaging, acquired 50 to 70 minutes after receiving an injection of 10 mCi of florbetapir F 18 and measured using a mean cortical standardized uptake value ratio (SUVr) with a whole cerebellar reference region.18 Amyloid status was assessed using an algorithm combining quantitative SUVr methods and qualitative visual read performed at a central laboratory.18 A quantitative SUVr threshold of 1.15 or more was used to define elevated amyloid as the primary criterion rather than requiring visual read positivity to identify individuals with early amyloid accumulation.19 A SUVr between 1.10 and 1.15 was considered to be elevated amyloid only when a visual read was also considered positive by a 2-reader consensus determination.

    Statistical Analyses

    The Aβ+ and Aβ− groups were compared using the Fisher exact test for categorical demographic variables and 2-sample t tests with unequal variances for continuous variables. Comparisons across individual racial/ethnic categories and APOE genotype subgroups were performed using a Fisher exact test with a Holm adjusted P value to account for multiple comparisons. Analyses of covariance analyses were performed to compare the screening PACC and CFI scores across Aβ groups and were adjusted for age at screening, sex, and years of education. Potential interactions between sex, APOE, and other variables were assessed if the main effects were significant at P < .05. Statistical analyses were performed using the software R (R Foundation; http://www.r-project.org).

    Results

    Participants were recruited from the community using central media and local outreach initiatives. More than 15 000 individuals indicated interest in the study and underwent prescreening by telephone or via the A4 Study website for minimal exclusionary criteria. Across 67 sites, 6768 individuals signed informed consent, 6763 completed ScrV1, and 4486 eligible individuals underwent screening amyloid PET imaging at screening visit 2 and determination of Aβ status. Most participants were enrolled in the US (3835 [85%]), with smaller numbers from Australia (430 [10%]), Canada (121 [4%]), and Japan (100 [2%]).

    Based on the screening PET algorithm, 1323 (29.5%) were categorized as Aβ+ and 3163 (70.5%) were Aβ−. The mean (SD) SUVr of those classified as Aβ+ was 1.33 (0.18) and 663 of these Aβ+ individuals (50.1%) were visually read as positive.

    Aβ+ participants were slightly older than Aβ− (Table 1). No differences in the proportion of Aβ groups were observed by sex (Aβ+ women = 778 [29.2%]; Aβ+ men = 545 [29.8%]; P = .64), nor for years of education, marital, or retirement status. Nine hundred thirty-two individuals who underwent ScrV1 (13.7%) and 503 participants who underwent amyloid PET imaging (11.2%) self-identified as an underrepresented minority. Asian (30/171 [17.5%]) and African American (34/167 [20.4%]) participants were slightly less likely to be classified as Aβ+ compared with white (1240/4116 [30.4%]) participants, although there were small numbers of underrepresented minority participants. No difference in Aβ+ was observed among those reporting Latino/Hispanic ethnicity (39/142 [27.5%]) compared with non-Latino/Hispanic individuals (1269/4309 [29.4%]).

    A total of 3113 participants undergoing amyloid PET imaging (69%) reported a positive family history, defined as having a first-degree relative who developed dementia thought to be due to AD before age 80 years. Reports of family history were higher (976 [74%]) among those classified as Aβ+ compared to Aβ−. Fifty-eight percent of the Aβ+ participants carried at least 1 APOE ε4 allele compared with 25% of the Aβ− participants. Among the Aβ+ group, APOE ε4 carriers showed a higher amyloid burden (mean [SD] SUVr = 1.36 [0.176]) compared with noncarriers (mean [SD] SUVr = 1.2 [0.175]; P < .001; eFigure in the Supplement). Apolipoprotein E ε2 alleles were less frequent among the Aβ+ group (Table 1).

    No differences were observed between the Aβ groups for self-report of the amount of aerobic exercise, walking, or sleep time (Table 2). No differences in the reported intake of alcohol, caffeine, or tobacco or for body mass index (calculated as weight in kilograms divided by height in meters squared) were observed between the Aβ groups.

    Aβ+ participants performed less well on the overall PACC score (Cohen d = −0.32; P < .001; Figure 2 and Table 2). Although this effect size was somewhat diminished after accounting for age, sex, and education covariates, it remained highly significant (Cohen d = −0.18; P < .001). Aβ+ participants also performed less well on each of the PACC components, which remained significant with covariance adjustment with the exception of the MMSE scores, which dropped to the trend level. We observed a main association of sex with the PACC and all PACC components, such that women performed better than men overall, but did not find any significant interaction of sex by Aβ status for the overall PACC or components. We did not observe a main association of APOE with the overall PACC score but did observe an interaction of APOE by Aβ status for the FCSRT, in particular the FCSRT free recall, such that Aβ+ APOEε4 carriers performed worse than Aβ+ noncarriers (estimate, −0.920; SE, 0.363; t = −2.536, P = .01).

    Aβ+ participants also reported greater subjective declines in cognitive function over the past year on the CFI (Cohen d = 0.31; P < .001; Figure 3). The study partners also reported that the Aβ+ participants had greater recent declines on the CFI, although this effect size (Cohen d = 0.23) was somewhat smaller than the self-report by the participants themselves. The combined self- and study partner CFI reports showed the greatest difference between the Aβ groups (Cohen d = 0.33; P < .0001). Apolipoprotein ε4 carriers and their study partners reported higher CFI scores than noncarriers in both Aβ groups (Cohen d = 0.16; P = .01 self; Cohen d = 0.12; P = .03 study partner), but there was no significant interaction with Aβ status.

    Discussion

    To our knowledge, this analysis of 4486 CN older individuals who underwent amyloid PET imaging as part of the screening process for the A4 Study represents the largest cross-sectional study of preclinical AD conducted thus far. Our analyses demonstrate that elevated Aβ associated with worse cognitive performance and increased self- and study partner reports of subtle changes in cognitive function. These cross-sectional findings, in conjunction with reports from previous smaller longitudinal studies, provide additional support for the hypothesis that CN Aβ+ older individuals represent a preclinical stage of the AD continuum that is appropriate for early intervention trials aimed at slowing cognitive decline.

    We evaluated demographic variables previously reported to increase risk for AD dementia. Family history was reported more frequently in participants who were later determined to be Aβ+. Apolipoprotein ε4 was overrepresented and APOE ε2 was underrepresented in the Aβ+ group, consistent with previous reports. The percentage of APOEε4 carriers in the Aβ+ group (58%) is similar to the approximately 60% of patients with AD dementia estimated to carry an APOE ε4 allele, although the exact proportion varies by geographic region and the racial composition of the sample.20 We also observed that among the Aβ+ participants, APOE ε4 carriers had a higher amyloid burden, consistent with previous literature suggesting that APOE ε4 carriers begin to accumulate Aβ at a younger age.21

    We did not find evidence to support that other putative AD risk factors, such as female sex, lower education, decreased physical activity, body mass index, or other lifestyle factors, were associated with elevated amyloid in late life. Previous reports of lifestyle associations with amyloid burden in the literature have been variable and suggest that midlife factors may have a stronger association with late-life amyloid burden than concurrent reports.22,23 Our findings, consistent with recent longitudinal studies investigating the association of sex and physical activity, suggest that these risk factors for AD dementia may play a role in the vulnerability/resilience to cognitive decline in the setting of elevated Aβ rather than serving as a risk factor for Aβ accumulation itself.24,25

    Our study had relatively few participants of color who underwent amyloid PET imaging; thus, our ability to address the association of race/ethnicity with amyloid is limited. As expected, because of the lower prevalence of APOE ε4 allele among those of Asian descent, Asian individuals were less likely to show elevated Aβ. Somewhat surprisingly given previous reports,26 we observed that African American individuals tended to have a lower proportion of elevated Aβ. This finding may reflect a potential bias in the eligibility for PET imaging, given higher rates of exclusionary medical conditions in people of color, but may also support the hypothesis that factors other than increased risk of elevated Aβ may contribute to the increased risk of cognitive decline among older black populations.27,28

    Our analyses revealed lower performance for all neuropsychological test measures and a greater report of recent decline in cognitive function among the Aβ+ participants compared with the Aβ− peers. All cognitive testing and questionnaires were administered before amyloid PET, eliminating any potential bias associated with participant or study team knowledge of amyloid status. The Aβ group differences are relatively small, which is expected given the eligibility requirements for normal performance and Clinical Dementia Rating score of 0. Nevertheless, these Aβ group differences remained highly significant after correction for age, sex, and education covariates. Finally, our findings confirmed previous reports that elevated Aβ is associated with increased subjective reporting of recent cognitive decline.9,10 It is notable that the self-report on the CFI, a simple 15-item questionnaire about change in cognitive function over the past year, demonstrated a similar effect size between Aβ groups as that of detailed neuropsychological testing with the PACC. The CFI self-report shows a slightly greater amyloid effect than the study partner report at the screening stage. This finding is perhaps not surprising, as individuals may note very subtle changes before others notice any changes. The sum of the self- and study partner reports will be used as a key secondary outcome measure to allow for the contribution of the participants’ own perceptions but also the study partners’ observations, as early anosognosia may develop with increasing cognitive decline over the 4.5-year trial.

    The A4 Study is testing whether solanezumab, a monoclonal antibody aimed at reducing Aβ accumulation in the brain, can slow cognitive decline at this preclinical stage of the AD continuum, with results expected in late 2022. The cross-sectional findings from the cognitive tests and subjective report in the Aβ+ group at screening support the supposition that this is a preclinical AD population at high risk for future cognitive decline. However, based on previous observational studies, it is very likely that additional factors, such as the degree of tau pathology,8,29 vascular disease,30,31 and markers of neurodegeneration,8,32 will be associated with the rate of cognitive decline among the Aβ+ participants.

    Finally, these results demonstrate the feasibility of recruiting and successfully screening CN older participants with elevated brain amyloid for a large secondary prevention trial aimed at slowing cognitive decline due to sporadic AD. Based on prior reports from autopsy studies and observational cohorts using cerebrospinal fluid and PET imaging in older CN, we estimated that the rates of Aβ+ in the screening cohort of individuals aged 65 to 85 years who qualified for PET imaging would be approximately 30%,33-35 which was close to the observed 29.5%. The choice to rely primarily on quantitative assessment (SUVr) rather than visual read was important, as only about 50% of those classified as Aβ+ by SUVr criteria had a positive visual read. This is perhaps not surprising given that we were targeting cognitively unimpaired individuals at early stages of amyloid accumulation and that the visual read criteria for amyloid PET imaging were optimized to detect higher levels of amyloid burden typically observed at the symptomatic stages of AD. Participants whose screening results failed for the A4 Study on the basis of having not elevated amyloid were eligible to screen for the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study, a companion observational study funded by the Alzheimer Association, which will serve as a longitudinal comparison group with the treatment and placebo Aβ+ arms randomized in the A4 Study. Participants with elevated amyloid (Aβ+) were eligible to proceed through additional screening steps toward potential randomization to placebo vs solanezumab treatment arms. The A4 Study completed enrollment in December 2017 with 1169 participants randomized.

    Limitations

    There are multiple factors that limit the generalizability of these findings. The population that was eligible for amyloid PET imaging was highly educated, generally healthy, and able to visit tertiary medical centers. Although substantial efforts were undertaken to increase racial and ethnic diversity in the A4 screening process, the amyloid PET cohort is clearly not representative of the older population at risk for dementia in the US. We excluded participants with very high or very low logical memory delayed paragraph recall, truncating the full range of cognitive performance in those who were eligible to undergo amyloid PET imaging. We used an algorithm that used quantitative and qualitative measures to assess eligibility for elevated amyloid using florbetapir, and specific associations might be slightly altered with different amyloid PET tracers or different SUVr thresholds. The lifestyle variables were assessed with very brief self-questionnaires on current habits and do not fully reflect the potential association of lifestyle variables over the life span. Perhaps most importantly, individuals interested in screening for a long and relatively intensive AD prevention trial likely represent a highly motivated cohort that may reflect some selection bias that limits generalizability to the general public. For example, the proportion of A4 screening participants reporting a positive family history (69%) is much higher than reported in observational studies, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI), in which only 39% of cognitively normal participants reported a positive family history.7 Nevertheless, this A4 Study screening cohort may be indicative of populations likely to screen for future prevention trials and those who may ultimately seek preventative treatment should any of these trials demonstrate benefits.

    Conclusions

    Given the 3-year time frame and the large number of participants screened to achieve our randomized cohort, it will be important to learn as much as possible from the A4 screening data to try to optimize the efficiency of screening and enrollment. Despite the significant differences in cognitive performance and subjective report in daily function, it remains challenging to use any one of these variables to accurately predict amyloid status given the relatively modest effect size. Work is ongoing to determine whether some combination of test scores, subjective reports, family history, genetic testing, and eventually blood-based biomarkers of amyloid and tau can improve the accuracy of predicting amyloid status in cognitive unimpaired individuals, perhaps particularly among APOE noncarriers. The A4/LEARN prerandomization data are freely available to the field to assist these efforts (https://ida.loni.usc.edu/).

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    Article Information

    Accepted for Publication: January 24, 2020.

    Corresponding Author: Reisa A. Sperling, MD, Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, 60 Fenwood Rd, Boston, MA 02115 (reisa@bwh.harvard.edu).

    Published Online: April 6, 2020. doi:10.1001/jamaneurol.2020.0387

    Author Contributions: Dr Sperling 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: Sperling, Donohue, Siemers, Johnson.

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

    Drafting of the manuscript: Sperling, Sun, Johnson.

    Critical revision of the manuscript for important intellectual content: Donohue, Raman, Yaari, Holdridge, Siemers, Johnson, Aisen.

    Statistical analysis: Donohue, Raman, Sun, Johnson.

    Obtained funding: Sperling, Siemers, Johnson, Aisen.

    Administrative, technical, or material support: Sun, Yaari, Holdridge, Siemers, Johnson, Aisen.

    Supervision: Sperling, Donohue, Siemers, Johnson.

    Conflict of Interest Disclosures: Dr Sperling reported grant support from the National Institutes of Health (NIH), Eli Lilly, Alzheimer's Association, GHR Foundation, Fidelity, and Gates Ventures; nonfinancial support from CogState, and Mount Sinai; grants and personal fees from Janssen; and personal fees from AC Immune, Biogen, Neurocentria, Eisai, Roche, Takeda, and Novartis. Dr Donohue reported grants from the NIH, a spouse’s employment with Janssen, and personal fees from Roche and Biogen. Dr Raman reported grants from the NIH, Eli Lilly, and Janssen. Dr Siemers reported being an employee of Eli Lilly from November 1998 until December 31, 2017; consulting fees from Acelot, Acumen Pharmaceuticals, Aquestive Therapeutics, Athira Pharma Inc, Biogen, Cogstate, Cortexyme, Gates Ventures LLC, Hoffman La-Roche, Indiana University, LuMind Research Down Syndrome Foundation, Partner Therapeutics, Pinteon Therapeutics, Prothena, Servier, Sangamo Therapeutics, Takeda Development Center Americas, Vaccinex, Washington University (St. Louis), and Weston Foundation; being a shareholder in Eli Lilly; and owning stock options in Acumen Pharmaceuticals. Dr Johnson reported grants from the NIH and Lilly and personal fees from AC Immune, Novartis, Janssen, and Takeda. Dr Aisen reported grants from Lilly and personal fees from Merck, Roche, Biogen, ImmunoBrain Checkpoint, and Samus. No other disclosures were reported.

    Funding/Support: This study was funded by the National Institute on Aging (grants U19AG010483 and R01AG063689), Eli Lilly and Co, and several philanthropic organizations (NCT02008357). The A4 Study is funded by a public-private philanthropic partnership, including funding from the NIH National Institute on Aging (grants U19AG010483 and R01AG063689), Eli Lilly and Company, Alzheimer’s Association, Accelerating Medicines Partnership, GHR Foundation, and an anonymous foundation and additional private donors, with in-kind support from Avid, Cogstate, Albert Einstein College of Medicine, US Against Alzheimer’s disease, and Foundation for Neurologic Diseases. The companion observational Longitudinal Evaluation of Amyloid Risk and Neurodegeneration Study is funded by the Alzheimer’s Association and GHR Foundation.

    A4 Study Team: Reisa Sperling, MD, Harvard Medical School; Paul Aisen, MD, University of Southern California; Roy Yaari, MD, Eli Lilly and Company; Phyllis Barkman Ferrell, MBA, Eli Lilly and Company; Eric Siemers, MD, Eli Lilly and Company; Keith Johnson, MD; Janice Hitchcock, PhD, Eli Lilly and Company; Karen Holdridge, MPH, Eli Lilly and Company; Isabella Velona, MS, Eli Lilly and Company; John Sims, Eli Lilly and Company; Jason Karlawish, MD, University of Pennsylvania; Tiffany Chow, MD, University of Southern California; Veasna Tan, MA, University of Southern California; Clifford R. Jack, Jr, MD, Mayo Clinic; James B. Brewer, MD, PhD, ADCS Imaging; Paul Maruff, PhD, Cogstate; Alison Belsha, BS, University of Southern California; Gabriela Muranevici, MD, University of Southern California; Mike Rafii, MD, PhD, University of Southern California; Robert Rissman, PhD, University of California, San Diego; Cecily Jenkins, PhD, University of Southern California; Kenneth Marek, MD, Invicro; John Seibyl, MD, Invicro; Mark Mintun, MD, Avid/Eli Lilly and Company; Steve Bruno III, BA, University of Southern California; Kate Papp, PhD, Brigham and Women’s Hospital; Aaron Schultz, PhD, Brigham and Women’s Hospital; Beth Mormino, PhD, Brigham and Women’s Hospital; Justin Sanchez, Brigham and Women’s Hospital; Rebecca Amariglio, PhD, Brigham and Women’s Hospital; Gad Marshall, MD, Brigham and Women’s Hospital; Dylan Kirn, Brigham and Women’s Hospital; Dorene Rentz, PsyD, Brigham and Women’s Hospital; Michael Properzi, Brigham and Women’s Hospital; J. Alex Becker, PhD, Brigham and Women’s Hospital; Matthew Scott, Brigham and Women’s Hospital; Devon Gessert, BS, University of Southern California; Alison Belsha, BS, University of Southern California; Jennifer Salazar, MBS, University of Southern California; Kelly Harless, BA, University of Southern California; Sarah Walter, MSc, University of Southern California; Teresa Diaz, MS, University of Southern California; Vianica Arguello, BS, University of Southern California; Thea J. Morris, MA, University of Southern California; Edna Stirewalt, BS, CRP, CPM, University of Southern California; Robin Fluty, CRA, LPN, University of Southern California; Alyssa Schmitt, MS, University of Southern California; Renarda Jones, MS, University of Southern California; Sarah L. Danowski, MA, University of Southern California; Ryan Black, BS, University of Southern California; Callyn Buchel, BS, CCRP, University of Southern California; Robyn Jucius, MPH, University of Southern California; Gina Garcia-Camilo, MD, University of Southern California; Viviana Messick, BS, University of Southern California; Deborah Tobias, University of Southern California; Jeremy Pizzola, University of Southern California; Lindsey Earp, BA, University of Southern California; Dan Abinsay, University of Southern California; Karen Bowman, MCM, University of Southern California; Shelley Moore, BA, University of Southern California; Taylor Clanton, MPH, CHES, University of Southern California; Gustavo Jimenez-Maggiora, MBA, University of Southern California; Phuoc Hong, BA, University of Southern California; Stefania Bruschi, MS, MBA, University of Southern California; Hongmei Qiu, MS, University of Southern California; Jia-shing So, BS, University of Southern California; Elizabeth Shaffer, BS, University of Southern California; Emily Voeller, BA, University of Southern California; Rema Raman, PhD, University of Southern California; Michael Donohue, PhD, University of Southern California; Chung-Kai Sun, MS, University of Southern California; Karin Ernstrom, MS, University of Southern California; Yanxin Jiang, MS, University of Southern California; Cecily Jenkins, PhD, University of Southern California; Xavier Salazar, PhD, University of Southern California; Ryoko Ihara, MD, PhD, University of Southern California; Barbara Bartocci, MPH, University of Southern California; Kimberlee Eudy, JD, University of Southern California; Quin Revel, JD, University of Southern California; Michael Selsnik, BS, University of Southern California; Anne Micol, BS, Eli Lilly and Company; Julie Bush, MS, Eli Lilly and Company; Anita Suppiger, RN, Eli Lilly and Company; Wendy Sorg, Eli Lilly and Company; Traci Peddie, BA, Eli Lilly and Company; AnnCatherine Downing, PhD, Eli Lilly and Company; Brian Willis, PhD, Eli Lilly and Company; Cheryl Brown, RPh, PMP, Eli Lilly and Company; Russell Barton, MS, Eli Lilly and Company; Cheryl Rumer, BSN, Eli Lilly and Company; Connie Yan Tong, MD, Eli Lilly and Company; James Senetar, PhD, Eli Lilly and Company; Julie Chandler, PhD, Eli Lilly and Company; Deanilee Deckard, MS, RN, Eli Lilly and Company; Brandon Talkington, Eli Lilly and Company; Shiloh Scott, Eli Lilly and Company; Giedra Campbell, MA, Eli Lilly and Company; Gopalan Sethuraman, PhD, Eli Lilly and Company; Melissa Pugh, PhD, Eli Lilly and Company; James David Barfield, MS, Eli Lilly and Company; Hong Liu-Seifert, PhD, Eli Lilly and Company; Holly Barce, MBA, Eli Lilly and Company; Lynne Johnson, MSN, Eli Lilly and Company; Kathryn Broderick, PhD, Eli Lilly and Company; Keith Parson, BS, MBA, Eli Lilly and Company; Brian Steuerwald, Eli Lilly and Company); Lauren Brunke, PharmD, Eli Lilly and Company; Lisa Ferguson-Sells, BSc, Eli Lilly andCompany; Kristina Dinkel, MS, Eli Lilly and Company; Jane Njoroge, Eli Lilly and Company; Michele Mancini, MD, Eli Lilly and Company; Morris Bret Haisley, Eli Lilly and Company; Leigh Cipriani, BS, Eli Lilly and Company; Shamrock Garrett, Eli Lilly and Company; Angela Corbly, RVT, Eli Lilly and Company; Deborah Falk, RPh, Eli Lilly and Company; Sheila Miller, PharmD, Eli Lilly and Company; Adam Schwarz, PhD, Eli Lilly and Company; Keita Asato, Eli Lilly and Company; Tomomi Nakamura, MD, Eli Lilly and Company; Diana Xiaoying Lau, BN, RN, Eli Lilly and Company; Naohisa Hatakeyama, Eli Lilly and Company; Mariela Gonzalez, BSc, Eli Lilly and Company; Monica Tjan, Eli Lilly and Company; John Holmes, Eli Lilly and Company; Sibyl Chauncy Materman, MA, Eli Lilly and Company; Jeffrey L. Gunter, PhD, Mayo Clinic); Cory A. Johnson, Mayo Clinic; Denise A. Reyes, Mayo Clinic; Kejal Kantarci, MD, Mayo Clinic; Leonard C. Matoush, Jr, Mayo Clinic; Greg M. Preboske, MS, Mayo Clinic; Bret J. Borowski, RT, Mayo Clinic; Samantha M. Zuk, Mayo Clinic; Kaely B. Thostenson, RT, Mayo Clinic; Jeffrey M. Burns, MD, MS, University of Kansas Alzheimer’s Disease Center; Joshua D. Grill, PhD, University of California, Irvine; David Sultzer, MD, UCLA; Louise Monte, MS, University of California, San Diego; Sarah Abdel-Latin, BS, University of California, San Diego; Natalie Abu Hamden, BS, University of California, San Diego; Nicholas Monte, BS, University of California, San Diego; Howard Feldman, MD, ADCS, University of California, San Diego; Genny Matthews, University of California, San Diego; Stephanie Parks, University of California, San Diego; Jen Mason, MPH, University of California, San Diego; Jason Young, PhD, University of California, San Diego; Ashlee Heldreth, BA, University of California, San Diego; Renarda Jones, MPH, University of California; Janet Kastelan, BA, University of California, San Diego; Lindsay Cotton, MPH, University of California, San Diego; Maria Bulger Lennox, RN, University of California, San Diego; Ronelyn Chavez, BA, University of California, San Diego; Tilman Oltersdorf, MD, University of California, San Diego; Curtis Taylor, PhD, University of California, San Diego; Barbara LaPlante, MA, University of California, San Diego); Meghan Stirn, MBA, University of California, San Diego; Joanne Brechlin, MBA, MPH, ADCS – University of California, San Diego, Transition Team); Gina Varner, MPH, University of California, San Diego; Carol Evans, BA, University of California, San Diego; Karim Hussein, JD, University of California, San Diego; Erika Wilson, University of California, San Diego; Ronald Thomas, PhD, University of California, San Diego; Rebecca Ryan-Jones, PhD, University of California, San Diego, Monitor); Sheila Jin, PhD, University of California, San Diego; John R. Hesselink, MD, University of California, San Diego); Nichol Ferng, BS, University of California, San Diego; Robin Jennings, BS, MS, University of California, San Dieg); Leonardino Digma, BA, University of California, San Diego; Heidi Jacobs, PhD, Massachusetts General Hospital; Justin Sanchez, Massachusetts General Hospital; Aaron Schultz, PhD, Massachusetts General Hospital; Jorge Sepulcre, MD, Massachusetts General Hospital; Matthew Scott, Massachusetts General Hospital; J. Alex Becker, PhD, Massachusetts General Hospital; Michael Properzi, Massachusetts General Hospital; Stephen Truocchio, MS, Avid; Myrellen Merry, Avid; Michael Pontecorvo, PhD, Avid; Alexander Pratt, Avid; Andrea Abram, MBA, Avid; Michael Devous, PhD, Avid; Marybeth Howlett, MEM, Avid; Robert Purtle, Avid; Reneé Tschopp, MS, PMP, Invicro; Donna Miles, Invicro; Ariel Matasci, BA, Cogstate; Pawel Kalinowski, BBSC (Hons), PhD, Cogstate; Tanya O’Connor, BA, Cogstate; Patrick Brennan, BA, Cogstate; Emina Behlic, BS, Cogstate; Patrick McCabe, BA, McCabe Message Partners; Becky Watt Knight, MA, McCabe Message Partners; Amy Martin Vogt, BA, McCabe Message Partners; Rachel Griffith, BA, McCabe Message Partners; Camille Ahearn, BA, McCabe Message Partners; Melissa McGue, BSBA, BA, McCabe Message Partners; Marissa C. Natelson Love, MD, University of Alabama, Birmingham; David S. Geldmacher, MD, University of Alabama, Birmingham; P. Denise Ledlow, RN, University of Alabama, Birmingham; Jacqueline Vaughn, RN, University of Alabama, Birmingham; William J. Burke, MD, Banner Alzheimer’s Institute; Roma Patel, MS, MBA, Banner Alzheimer’s Institute; Daniel Viramontes Apodaca, Banner Alzheimer’s Institute; Sachin Y. Pandya, Banner Alzheimer’s Institute; Anna D. Burke, MD, Banner Alzheimer’s Institute; Edward Zamrini, MD, Banner Sun Health Research Institute; Zoran Obradov, CRC, Banner Sun Health Research Institute; Christine M. Beldan, PsyD, Banner Sun Health Research Institute; Carol Cline, MSW, LMSW, CSP, Banner Sun Health Research Institute; Margaret Rich, CSP, Banner Sun Health Research Institute; Lisa Roye, MS, Banner Sun Health Research Institute; Marwan Sabbagh, MD, Banner Sun Health Research Institute; Jerome Yesavage, MD, Stanford University School of Medicine, VA Aging Clinical Research Center; Steven Z. Chao, MD, PhD, Stanford University School of Medicine; Karlos E. Zepeda, BS, Stanford University School of Medicine; Tamara Beales, MA, Stanford University School of Medicine; Vivian Q. Chu, BA, Stanford University School of Medicine; Shawn Kile, MD, Sutter Institute for Medical Research; William Au, MD, Sutter Institute for Medical Research; Yvonne Au, LCSW, PACC, Sutter Institute for Medical Research; Mary Vaughn, RN, Sutter Institute for Medical Research; Sampreet Kaur, CRC, Sutter Institute for Medical Research; Tammy Donnell, CCRC, Sutter Institute for Medical Research; Dawn Lenakakis, CRC, Sutter Institute for Medical Research; John Gregory Duffy, MD, Syrentis Clinical Research; Lorrie Bisesi, PhD, Syrentis Clinical Research; Poonam Nina Banerjee, PhD, Syrentis Clinical Research; Eloisa Vasquez, BSc, Syrentis Clinical Research; Rebecca Sanchez, Syrentis Clinical Research; John Olichney, MD, University of California, Davis; Charles DeCarli, MD, University of California, Davis; Hongzheng Zhang, PhD, University of California, Davis; Antoinette Lopez, MD, University of California, Davis; Mary McPhail-Ciufo, MD, University of California,Davis; Adrian Preda, MD, University of California, Irvine; Andrea Weideman, University of California, Irvine; Steven Potkin, MD, University of California,Irvine; Aimee L. Pierce, MD, University of California, Irvine;Joshua D. Grill, PhD, University of California, Irvine; Malcolm B. Dick, PhD, University of California, Irvine=; Gaby T. Thai, MD, University of California, Irvine=; Steven Tam, MD, University of California, Irvine=; Joshua Grill, PhD, University of California, Los Angeles=; Sarah Kremen, MD, University of California, Los Angeles; Maryam Beigi, MD, University of California, Los Angeles; Celine Ossinalde, MA, University of California, Los Angeles; Michelle Craig, MA, LMFT, University of California, Los Angeles; Michelle Torreliza, University of California, Los Angeles; Douglas Galasko, MD, University of California, San Diego; Helen Vanderswag, RNC, BSN, University of California, San Diego; Asmaa Al Hamdani, MBChB, MAS, University of California, San Diego; Chi Kim, BS, University of California, San Diego; Shawnees Peacock, BS, University of California, San Diego; Adam L. Boxer, MD, PhD, University of California, San Francisco; Gil Rabinovici, MD, University of California, San Francisco; Richard M. Tsai, MD, University of California, San Francisco; Peter Ljubenkov, MD, University of California, San Francisco; Julio C. Rojas, MD, PhD, University of California, San Francisco; Mauricio Becerra, University of Southern California Alzheimer’s Disease Research Center; Liberty Teodoro, RN, University of Southern California Alzheimer’s Disease Research Center; Sonia Pawluczyk, MD, University of Southern California Alzheimer’s Disease Research Center; Karen Dagerman, MS, University of Southern California Alzheimer’s Disease Research Center; Lon Schneider, MD, University of Southern California Alzheimer’s Disease Research Center; Christopher H. van Dyck, MD, Yale Alzheimer’s Disease Research Unit; Julia W. McDonald, BA, Yale Alzheimer’s Disease Research Unit); Joanna E. Harris, BA, Yale Alzheimer’s Disease Research Unit; Srinath Ramanan, BS, Yale Alzheimer’s Disease Research Unit; Erika A. Pugh, MA, Yale Alzheimer’s Disease Research Unit; Raymond Scott Turner, MD, PhD, Georgetown University; Melanie Chadwick, RN, MS, NP, Georgetown University; Kathleen Johnson, RN, MSN, NP , Georgetown University; Brigid Reynolds, RN, MSN, NP, Georgetown University; Kelly McCann, BA, Georgetown University; Thomas O. Obisesan, MD, MPH, Howard University; Oyonumo E. Ntekim, MD, PhD, Howard University; Sheeba R. Nadarajah, PhD, Howard University; Sharlene Leong, MSc, Howard University; Saba Wolday, MSc, Howard University; David C. Subich, MD, FAPCR, CPI, Bioclinica Research; Steph Krauchunas, PA, Bioclinica Research; Ruth Paiano, ARNP, Bioclinica Research; Ayesha Lall, MD, Bioclinica Research; Randall Braddom, MD, Bioclinica Research; Esteban Olivera, MD, Bioclinica Research; Craig Curtis, MD, Bioclinica Research; Jennifer West, PAC, Bioclinica Research; Maria A. Edridge, L-CRC, Bioclinica Research; Shayna Carter, CRNI, Bioclinica Research; Mark Brody, MD, Brain Matters Research; Paayal Patel, MD, Brain Matters Research; Elizabeth Diebel, CCRC, Brain Matters Research; Daisy Acevedo, Brain Matters Research; Cynthia Stimeck, PA-C, Brain Matters Research; Neill R. Graff-Radford, MD, Mayo Clinic; Rita M. Fletcher, RN, BSN, Mayo Clinic; Dana L. Haley, MPH, Mayo Clinic; Carl Sadowsky, MD, Premiere Research Institute; Teresa Villena, MD, Premiere Research Institute; Alfonso Moreno, MD, Premiere Research Institute; Amanda G. Smith, MD, USF Health Byrd Alzheimer’s Institute; Kelly Rodrigo, BA, CCRC, USF Health Byrd Alzheimer’s Institute; Beth Major, LPN, CCRC, USF Health Byrd Alzheimer’s Institute; Ijeoma Mba, MBBS, USF Health Byrd Alzheimer’s Institute; Juris Janavs, MD, USF Health Byrd Alzheimer’s Institute; Ranjan Duara, MD, Wien Center for Alzheimer’s Disease and Dementia; Maria T. Greig Custo, MD, Wien Center for Alzheimer’s Disease and Dementia; Rosemarie A. Rodriguez, PhD, Wien Center for Alzheimer’s Disease and Dementia; Huston Powell, PharmD, MBA, Wien Center for Alzheimer’s Disease and Dementia; Warren Barker, MA, Wien Center for Alzheimer’s Disease and Dementia; Florencia Tocasuche, AS, Wien Center for Alzheimer’s Disease and Dementia; James J. Lah, MD, PhD, Emory University; Allan I. Levey, MD, PhD, Emory University; Deborah Westover, BSN, RN, Emory University; Sarah Evans, BS, Emory University; Jeffrey Ross, MD, Great Lakes Clinical Trials; Linda Rice, PhD, Great Lakes Clinical Trials; Sandra Weintraub, PhD, Northwestern University; Ian Grant, MD, Northwestern University; Borna Bonakdarpour, MD, Northwestern University; Kristine Lipowski, MA, CCRC, Northwestern University; Jordan Robson, BS, Northwestern University; Neelum T. Aggarwal, MD, Rush University Medical Center; Raj C. Shah, MD, Rush University Medical Center; Mary Schum, MA, PA-C, Rush University Medical Center; Amelia Williams, Rush University Medical Center; Martin Farlow, MD, Indiana University; Jared Brosch, MD, Indiana University; Nancy McClaskey, RN, Indiana University; Gena Antonopoulos, RN, Indiana University; Lizeth Achury, BS, Indiana University; Del D. Miller, PharmD, MD, University of Iowa; Hristina K. Koleva, MD, University of Iowa; Karen Ekstam Smith, RN, University of Iowa; Laura Temple, MS, University of Iowa; Susan Schultz, MD, University of Iowa; Anne Arthur, APRN, University of Kansas Medical Center Alzheimer’s Disease Center; Rebecca Bothwell, MS, CCRP, University of Kansas Medical Center Alzheimer’s Disease Center; Aiden Bondurant, CCRP, University of Kansas Medical Center Alzheimer’s Disease Center; Phyllis Switzer, University of Kansas Medical Center Alzheimer’s Disease Center; Gregory A. Jicha, MD, PhD, University of Kentucky; Kendra Bates, BA, University of Kentucky; Shoshana Bardach, PhD, University of Kentucky; Molly Harper, MA, University of Kentucky Kelly Parsons, MSW, University of Kentucky; Jeffrey N. Keller, Pennington Biomedical Research Center; William P. Gahan, MD, Pennington Biomedical Research Center; Robert Brouillette, MS, Pennington Biomedical Research Center; Heather Foil, MS (Pennington Biomedical Research Center; Owen Carmichael, PhD, Pennington Biomedical Research Center; Paul B. Rosenberg, MD, Johns Hopkins University; Meghan Schultz, RN, MSN, Johns Hopkins University; Sarah Lawrence, MS, Johns Hopkins University; Caitlin Romano, BS, Johns Hopkins University; Robert A. Stern, PhD, Boston University School of Medicine; Jane Mwicigi, MBChB, MPH, Boston University School of Medicine; Dawn Jacobs, BSN, MPH, Boston University School of Medicine; Jesse Mez, MD, MS, Boston University School of Medicine; Wendy Qiu, MD, PhD, Boston University School of Medicine; Eric Steinberg, MSN, RN, CS, CANP, Boston University School of Medicine; Gad A. Marshall, MD, Brigham and Women’s Hospital; Kirsten A. Glennon, RN, Brigham and Women’s Hospital; Nancy Coppelman, BA, Brigham and Women’s Hospital; Martha Vander Vliet, RN, Brigham and Women’s Hospital; Dorene Rentz, PsyD, Brigham and Women’s Hospital; Judith L. Heidebrink, MD, MS, University of Michigan; Jaimie Ziolkowski, MA, BS, TLLP, University of Michigan; David S. Knopman, MD, Mayo Clinic; Jon Graf Radford, MD, Mayo Clinic; Sara Mason, RN, Mayo Clinic; Karen Kuntz, Mayo Clinic; Kari Baxter, ACRC, Mayo Clinic ; Randall Bateman, MD, Washington University School of Medicine; Joy Snider, MD, PhD, Washington University School of Medicine; Gregory Day, MD, Washington University School of Medicine; Nupur Ghoshal, MD, PhD, Washington University School of Medicine; Erik Musiek, MD, PhD, Washington University School of Medicine; John Morris, MD, Washington University School of Medicine; Tammie Benzinger, MD, PhD, Washington University School of Medicine; Daniel L. Murman, MD, MS, University of Nebraska Medical Center; Mary Horrum, RN, University of Nebraska Medical Center; Renee Hogue, RN, University of Nebraska Medical Center; Deb Heimes, BS, University of Nebraska Medical Center; Nick Miller, BS, University of Nebraska Medical Center; Charles Bernick, MD, MPH, Cleveland Clinic Lou Ruvo Center for Brain Health; Donna Munic-Miller, PhD, Cleveland Clinic Lou Ruvo Center for Brain Health; Samuel Hickson, LSW, MSSA, Cleveland Clinic Lou Ruvo Center for Brain Health Garam Lee, PharmD, RPh, Cleveland Clinic Lou Ruvo Center for Brain Health; Milagros Formoso, BS, CCRP, Cleveland Clinic Lou Ruvo Center for Brain Health) Karen L. Bell, MD, Columbia University Medical Center; Ruth Tejeda, MD, MS, Columbia University Medical Center; Betina Idnay, RN, Columbia University Medical Center; Lawrence Honig, MD, PhD, Columbia University Medical Center; Evelyn Dominguez, MD, MS, Columbia University Medical Center; Horacio A. Capote, MD, Dent Neurologic Institute; Caroline Kumm, MS, CRC, Dent Neurologic Institute; Michelle Rainka, PharmD, Dent Neurologic Institute; Mary Sano, MD, Icahn School of Medicine at Mount Sinai; Judith Neugroschl, MD, Icahn School of Medicine at Mount Sinai; Kelly Pun, BA, Icahn School of Medicine at Mount Sinai; Hillel Grossman, MD, Icahn School of Medicine at Mount Sinai; Amy Aloyisi, MD, Icahn School of Medicine at Mount Sinai; Melanie Shulman, MD, NYU Langone Medical Center; Anaztasia Ulysse, BA, CRC, NYU Langone Medical Center; Jamika Singleton-Garvin, CCRC, NYU Langone Medical Center; Mohammed Sheikh, BS, CCRC, NYU Langone Medical Center; Mrunaliniash Gaikwad, BS, CRC, NYU Langone Medical Center; Anton P. Porsteinsson, MD, University of Rochester; Audrey Rice, RN, ANP, University of Rochester; Susan Salem-Spencer, RN, MSN, University of Rochester); Kaitlyn Lane, BA, University of Rochester); Asa Widman, BA, University of Rochester; Michael Lin, MD, Weill Cornell Medical Center); Norman Relkin, MD, PhD, Weill Cornell Medical Center; Suzanne Craft, PhD, Wake Forest University School of Medicine; Patricia Wittmer, Wake Forest University School of Medicine; Mary Hayworth Troncale, PA, Wake Forest University School of Medicine; Alexis Webb, MS, Wake Forest University School of Medicine; Deborah Dahl, RN, MSN, Wake Forest University School of Medicine; Alan J. Lerner, MDCase Western Reserve University; Maria Gross, RN, Case Western Reserve University; Parianne Fatica, CCRC, Case Western Reserve University; Susie Sami, MA, CCRC, Case Western Reserve University; Paula Ogrocki, PhD, Case Western Reserve University; Marianne Sanders, RN, Case Western Reserve University; Ralph W. Richter, MD, Tulsa Clinical Research, LLC; Christy Lisenbee, BS, Tulsa Clinical Research, LLC; John Parsons, BS, Tulsa Clinical Research, LLC; Sarah Fowler, CPhbT, Tulsa Clinical Research, LLC; Carmen Toegel, LPN, Tulsa Clinical Research, LLC; Lisa C. Silbert, MD, Oregon Health and Science University; Chad Sorenson, BS, Oregon Health and Science University; Betty Lind, BS, Oregon Health and Science University; Jeffrey Kaye, MD, Oregon Health and Science University; Jason David, BA, Oregon Health and Science University; G. Peter Gliebus, MD, Drexel University; Katherine Rife, BS, Drexel University; Melinda Webster, BS, Drexel University; Christine Barr, RN, Drexel University; Monica Mazurek, Drexel University; Sanjeev N. Vaishnavi, MD, PhD, University of Pennsylvania; Martha Combs, BS, MS, University of Pennsylvania; Jessica Nunez, University of Pennsylvania; Loren Terrill, University of Pennsylvania; Oscar Lopez, MD, University of Pittsburgh) Thomas Baumgartner, LSW, MPH, University of Pittsburgh Sara Goldberg, MS, University of Pittsburgh; Donna Simpson, CRNP, MSN, MPH, University of Pittsburgh; Stephen P. Salloway, MD, MS, Butler Hospital Memory and Aging Program; Vanessa Rua, BSN, RN, Butler Hospital Memory and Aging Program; Diane Monast, RN, MSN, CNS, Butler Hospital Memory and Aging Program; Athene K.W. Lee, PhD, Butler Hospital Memory and Aging Program; Jessica Alber, PhD, Butler Hospital Memory and Aging Program; Brain R. Ott, MD, Rhode Island Hospital; Lori A. Daiello, PharmD, ScM, Rhode Island Hospital; Jonathan D. Drake, MD, Rhode Island Hospital; Alisa Omert, RN, Rhode Island Hospital; Jacobo Mintzer, MD, Roper St. Francis; Sheila Howland, RN, BSN, Roper St. Francis; Allison Lapp, MS, CHES, Roper St. Francis; Abigail O’Connell, MS, APRN, FNP-C, Roper St. Francis; Arthur Williams, BS, BA, Roper St. Francis; Sydney O’Connor, BA, MA, Baylor College of Medicine; Valory Pavlik, PhD, Baylor College of Medicine; Joseph Kass, JD, MD, Baylor College of Medicine; Rachelle Doody, MD, PhD, Baylor College of Medicine; Joseph C. Masdeu, MD, PhD, Nantz National Alzheimer Center; Belen Pascual, PhD, Nantz National Alzheimer Center,; Jennifer M. Garrett, RN, Nantz National Alzheimer Center; Brendan Kelley, MD, University of Texas Southwestern Medical Center; Kyle Womack, MD, University of Texas Southwestern Medical Center; Roger Rosenberg, MD, University of Texas Southwestern Medical Center; Trung Nguyen, MD, University of Texas Southwestern Medical Center; Mary Quiceno, MD, University of Texas Southwestern Medical Center; Elaine Peskind, MD, Seattle Institute for Biomedical & Clinical Research; James O’Connell, MSW, Seattle Institute for Biomedical & Clinical Research; Robert Turner, PA-C, Seattle Institute for Biomedical & Clinical Research; Murray A. Raskind, MD, PhD, Seattle Institute for Biomedical & Clinical Research; Debra Burges, BSN, RN, Seattle Institute for Biomedical & Clinical Research; Anita Ranta, BS, Seattle Institute for Biomedical & Clinical Research; Cynthia M. Carlsson, MD, MS, University of Wisconsin; Benjamin Farral, BS, University of Wisconsin; Karen K. Lazar, MS, University of Wisconsin; Sandra Harding, MS, University of Wisconsin; Aleshia Cole, RN, APNP, University of Wisconsin; Sarah Best, BSc, CCRP, MHM, Parkwood Institute; Abigail Korczak, BScN, RN, Parkwood Institute; Kayla VanderPloeg, BScN, Parkwood Institute; Elsa Mann, BScN, Parkwood Institute; Julia Truemner, BA, CCRP, Parkwood Institute; Sandra Black, OC, OOnt, MD, FRCP(C), FRSC, FAAN, FAHA, FANA, Sunnybrook Health Sciences Centre; Benjamin Lam, MD, MSc, FRCP(C), Sunnybrook Health Sciences Centre; Chinthaka Heyn, PhD, MD, FRCP(C), Sunnybrook Health Sciences Centre; Samantha Paul-Stotz, RN, BSc, Sunnybrook Health Sciences Centre; Maryna Butenko, MSc, Sunnybrook Health Sciences Centre; Sharon Cohen, MD, FRCPC, Toronto Memory Program; C. Ian Cohen, MD, CCFP, Toronto Memory Program; Ellen Buchman, MD, Toronto Memory Program; Atif Shaikh, MBBS, RPN, Toronto Memory Program; Linda Schlesinger, BA, CCRP, Toronto Memory Program; Robin Hsiung, MD, MHSc, FRCPC, FACP, FAAN, University of British Columbia, Clinic for Alzheimer Disease and Related Disorder; Benita Mudge, BSc, University of British Columbia, Clinic for Alzheimer Disease and Related Disorders; Eloise Nicklin, MSc, University of British Columbia, Clinic for Alzheimer Disease and Related Disorders; Michele Assaly, MA, University of British Columbia, Clinic for Alzheimer Disease and Related Disorders; Haakon Nygaard, MD, PhD, University of British Columbia, Clinic for Alzheimer Disease and Related Disorders; Colin L. Masters, MD, The University of Melbourne; Maree Mastwyk, PhD, The University of Melbourne; Paul Yates, MBBS, PhD, FRACP, The University of Melbourne; Anne Buckland, RN, The University of Melbourne; David Darby, MBBS, FRACP, PhD, The University of Melbourne; Takeshi Iwatsubo, MD, The University of Tokyo, School of Medicine; Atushi Iwata, MD, PhD, The University of Tokyo; Kazushi Suzuki, MD, PhD, The University of Tokyo; Ryoko Ihara, MD, PhD, The University of Tokyo; and Chie Sakanaka, MD, PhD, The University of Tokyo.

    Additional Contributions: We acknowledge the dedication of all the participants, site personnel, and partnership team members who continue to make the A4 and LEARN studies possible.

    Additional Information: The A4 and LEARN Studies are led by Dr Sperling at Brigham and Women’s Hospital, Harvard Medical School and Dr Aisen at the Alzheimer’s Therapeutic Research Institute (ATRI), University of Southern California. The A4 and LEARN Studies are coordinated by ATRI at the University of Southern California and the data are made available through the Laboratory for Neuro Imaging at the University of Southern California. The participants screening for the A4 Study provided permission to share their deidentified data to advance the objective to find a successful treatment for Alzheimer disease. The A4 Study is a secondary prevention trial in preclinical Alzheimer disease aiming to slow cognitive decline associated with brain amyloid accumulation in clinically normal older individuals. Dr Siemers retired from Eli Lilly & Co.

    References
    1.
    Price  JL, Morris  JC.  Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease.   Ann Neurol. 1999;45(3):358-368. doi:10.1002/1531-8249(199903)45:3<358::AID-ANA12>3.0.CO;2-X PubMedGoogle ScholarCrossref
    2.
    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(3):280-292. doi:10.1016/j.jalz.2011.03.003 PubMedGoogle ScholarCrossref
    3.
    Jack  CR  Jr, Bennett  DA, Blennow  K,  et al; Contributors.  NIA-AA research framework: toward a biological definition of Alzheimer’s disease.   Alzheimers Dement. 2018;14(4):535-562. doi:10.1016/j.jalz.2018.02.018 PubMedGoogle ScholarCrossref
    4.
    Lim  YY, Maruff  P, Pietrzak  RH,  et al; AIBL Research Group.  Effect of amyloid on memory and non-memory decline from preclinical to clinical Alzheimer’s disease.   Brain. 2014;137(pt 1):221-231. doi:10.1093/brain/awt286 PubMedGoogle ScholarCrossref
    5.
    Petersen  RC, Wiste  HJ, Weigand  SD,  et al.  Association of elevated amyloid levels with cognition and biomarkers in cognitively normal people from the community.   JAMA Neurol. 2016;73(1):85-92. doi:10.1001/jamaneurol.2015.3098 PubMedGoogle ScholarCrossref
    6.
    Mormino  EC, Papp  KV, Rentz  DM,  et al.  Early and late change on the preclinical Alzheimer’s cognitive composite in clinically normal older individuals with elevated amyloid β.   Alzheimers Dement. 2017;13(9):1004-1012. doi:10.1016/j.jalz.2017.01.018 PubMedGoogle ScholarCrossref
    7.
    Donohue  MC, Sperling  RA, Petersen  R, Sun  CK, Weiner  MW, Aisen  PS; Alzheimer’s Disease Neuroimaging Initiative.  Association between elevated brain amyloid and subsequent cognitive decline among cognitively normal persons.   JAMA. 2017;317(22):2305-2316. doi:10.1001/jama.2017.6669 PubMedGoogle ScholarCrossref
    8.
    Jack  CR  Jr, Wiste  HJ, Therneau  TM,  et al.  Associations of amyloid, tau, and neurodegeneration biomarker profiles with rates of memory decline among individuals without dementia.   JAMA. 2019;321(23):2316-2325. doi:10.1001/jama.2019.7437 PubMedGoogle ScholarCrossref
    9.
    Jessen  F, Amariglio  RE, van Boxtel  M,  et al; Subjective Cognitive Decline Initiative (SCD-I) Working Group.  A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease.   Alzheimers Dement. 2014;10(6):844-852. doi:10.1016/j.jalz.2014.01.001 PubMedGoogle ScholarCrossref
    10.
    Amariglio  RE, Buckley  RF, Mormino  EC,  et al.  Amyloid-associated increases in longitudinal report of subjective cognitive complaints.   Alzheimers Dement (N Y). 2018;4:444-449. doi:10.1016/j.trci.2018.08.005PubMedGoogle Scholar
    11.
    Vos  SJ, Xiong  C, Visser  PJ,  et al.  Preclinical Alzheimer’s disease and its outcome: a longitudinal cohort study.   Lancet Neurol. 2013;12(10):957-965. doi:10.1016/S1474-4422(13)70194-7 PubMedGoogle ScholarCrossref
    12.
    Insel  PS, Hansson  O, Mackin  RS, Weiner  M, Mattsson  N; Alzheimer’s Disease Neuroimaging Initiative.  Amyloid pathology in the progression to mild cognitive impairment.   Neurobiol Aging. 2018;64:76-84. doi:10.1016/j.neurobiolaging.2017.12.018 PubMedGoogle ScholarCrossref
    13.
    Doody  RS, Thomas  RG, Farlow  M,  et al; Alzheimer’s Disease Cooperative Study Steering Committee; Solanezumab Study Group.  Phase 3 trials of solanezumab for mild-to-moderate Alzheimer’s disease.   N Engl J Med. 2014;370(4):311-321. doi:10.1056/NEJMoa1312889 PubMedGoogle ScholarCrossref
    14.
    Hedden  T, Oh  H, Younger  AP, Patel  TA.  Meta-analysis of amyloid-cognition relations in cognitively normal older adults.   Neurology. 2013;80(14):1341-1348. doi:10.1212/WNL.0b013e31828ab35d PubMedGoogle ScholarCrossref
    15.
    Sperling  RA, Rentz  DM, Johnson  KA,  et al.  The A4 study: stopping AD before symptoms begin?   Sci Transl Med. 2014;6(228):228fs13. doi:10.1126/scitranslmed.3007941 PubMedGoogle Scholar
    16.
    Harkins  K, Sankar  P, Sperling  R,  et al.  Development of a process to disclose amyloid imaging results to cognitively normal older adult research participants.   Alzheimers Res Ther. 2015;7(1):26. doi:10.1186/s13195-015-0112-7 PubMedGoogle ScholarCrossref
    17.
    Amariglio  RE, Donohue  MC, Marshall  GA,  et al; Alzheimer’s Disease Cooperative Study.  Tracking early decline in cognitive function in older individuals at risk for Alzheimer disease dementia: the Alzheimer’s Disease Cooperative Study Cognitive Function Instrument.   JAMA Neurol. 2015;72(4):446-454. doi:10.1001/jamaneurol.2014.3375 PubMedGoogle ScholarCrossref
    18.
    Pontecorvo  MJ, Arora  AK, Devine  M,  et al.  Quantitation of PET signal as an adjunct to visual interpretation of florbetapir imaging.   Eur J Nucl Med Mol Imaging. 2017;44(5):825-837. doi:10.1007/s00259-016-3601-4 PubMedGoogle ScholarCrossref
    19.
    Johnson  KA, Sperling  RA, Gidicsin  CM,  et al; AV45-A11 study group.  Florbetapir (F18-AV-45) PET to assess amyloid burden in Alzheimer’s disease dementia, mild cognitive impairment, and normal aging.   Alzheimers Dement. 2013;9(5)(suppl):S72-S83. doi:10.1016/j.jalz.2012.10.007 PubMedGoogle ScholarCrossref
    20.
    Ward  A, Crean  S, Mercaldi  CJ,  et al.  Prevalence of apolipoprotein E4 genotype and homozygotes (APOE e4/4) among patients diagnosed with Alzheimer’s disease: a systematic review and meta-analysis.   Neuroepidemiology. 2012;38(1):1-17. doi:10.1159/000334607 PubMedGoogle ScholarCrossref
    21.
    Caselli  RJ, Walker  D, Sue  L, Sabbagh  M, Beach  T.  Amyloid load in nondemented brains correlates with APOE e4.   Neurosci Lett. 2010;473(3):168-171. doi:10.1016/j.neulet.2010.02.016 PubMedGoogle ScholarCrossref
    22.
    Vemuri  P, Knopman  DS, Lesnick  TG,  et al.  Evaluation of amyloid protective factors and Alzheimer disease neurodegeneration protective factors in elderly individuals.   JAMA Neurol. 2017;74(6):718-726. doi:10.1001/jamaneurol.2017.0244 PubMedGoogle ScholarCrossref
    23.
    Gottesman  RF, Schneider  AL, Zhou  Y,  et al.  Association between midlife vascular risk factors and estimated brain amyloid deposition.   JAMA. 2017;317(14):1443-1450. doi:10.1001/jama.2017.3090 PubMedGoogle ScholarCrossref
    24.
    Buckley  RF, Mormino  EC, Amariglio  RE,  et al; Alzheimer’s Disease Neuroimaging Initiative; Australian Imaging, Biomarker and Lifestyle study of ageing; Harvard Aging Brain Study.  Sex, amyloid, and APOE ε4 and risk of cognitive decline in preclinical Alzheimer’s disease: findings from three well-characterized cohorts.   Alzheimers Dement. 2018;14(9):1193-1203. doi:10.1016/j.jalz.2018.04.010 PubMedGoogle ScholarCrossref
    25.
    Rabin  JS, Klein  H, Kirn  DR,  et al.  Associations of physical activity and β-amyloid with longitudinal cognition and neurodegeneration in clinically normal older adults.   JAMA Neurol. 2019. doi:10.1001/jamaneurol.2019.1879 PubMedGoogle Scholar
    26.
    Gottesman  RF, Schneider  AL, Zhou  Y,  et al.  The ARIC-PET amyloid imaging study: brain amyloid differences by age, race, sex, and APOE.   Neurology. 2016;87(5):473-480. doi:10.1212/WNL.0000000000002914 PubMedGoogle ScholarCrossref
    27.
    Zahodne  LB, Manly  JJ, Narkhede  A,  et al.  Structural MRI predictors of late-life cognition differ across African Americans, Hispanics, and whites.   Curr Alzheimer Res. 2015;12(7):632-639. doi:10.2174/1567205012666150530203214 PubMedGoogle ScholarCrossref
    28.
    Barnes  LL, Leurgans  S, Aggarwal  NT,  et al.  Mixed pathology is more likely in black than white decedents with Alzheimer dementia.   Neurology. 2015;85(6):528-534. doi:10.1212/WNL.0000000000001834 PubMedGoogle ScholarCrossref
    29.
    Sperling  RA, Mormino  EC, Schultz  AP,  et al.  The impact of amyloid-beta and tau on prospective cognitive decline in older individuals.   Ann Neurol. 2019;85(2):181-193.PubMedGoogle Scholar
    30.
    Rabin  JS, Schultz  AP, Hedden  T,  et al.  Interactive associations of vascular risk and β-amyloid burden with cognitive decline in clinically normal elderly individuals: findings from the Harvard Aging Brain Study.   JAMA Neurol. 2018;75(9):1124-1131. doi:10.1001/jamaneurol.2018.1123 PubMedGoogle ScholarCrossref
    31.
    Vemuri  P, Lesnick  TG, Knopman  DS,  et al.  Amyloid, vascular, and resilience pathways associated with cognitive aging.   Ann Neurol. 2019;86(6):866-877. doi:10.1002/ana.25600 PubMedGoogle ScholarCrossref
    32.
    Soldan  A, Pettigrew  C, Fagan  AM,  et al.  ATN profiles among cognitively normal individuals and longitudinal cognitive outcomes.   Neurology. 2019;92(14):e1567-e1579. doi:10.1212/WNL.0000000000007248 PubMedGoogle ScholarCrossref
    33.
    Jansen  WJ, Ossenkoppele  R, Knol  DL,  et al; Amyloid Biomarker Study Group.  Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis.   JAMA. 2015;313(19):1924-1938. doi:10.1001/jama.2015.4668 PubMedGoogle ScholarCrossref
    34.
    Jack  CR  Jr, Wiste  HJ, Weigand  SD,  et al.  Age-specific and sex-specific prevalence of cerebral β-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50-95 years: a cross-sectional study.   Lancet Neurol. 2017;16(6):435-444. doi:10.1016/S1474-4422(17)30077-7 PubMedGoogle ScholarCrossref
    35.
    Dubois  B, Epelbaum  S, Nyasse  F,  et al; INSIGHT-preAD study group.  Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer’s disease (INSIGHT-preAD): a longitudinal observational study.   Lancet Neurol. 2018;17(4):335-346. doi:10.1016/S1474-4422(18)30029-2 PubMedGoogle ScholarCrossref
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