Scores range from −3.51 to 1.93, with higher scores indicating better performance. Quadratic rates of change in episodic memory are shown for each β-amyloid (Aβ)–negative and Aβ-positive group by apolipoprotein E ε4 allele carrier status. Shading indicates 95% CIs of slope.
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Lim YY, Kalinowski P, Pietrzak RH, et al. Association of β-Amyloid and Apolipoprotein E ε4 With Memory Decline in Preclinical Alzheimer Disease. JAMA Neurol. 2018;75(4):488–494. doi:10.1001/jamaneurol.2017.4325
What is the association of β-amyloid and the presence of the apolipoprotein E (APOE) ε4 with memory decline with increasing age?
In this longitudinal study of 447 cognitively healthy older adults, memory decline in β-amyloid–positive ɛ4 carriers began earlier (64.5 years of age) than in β-amyloid–positive ɛ4 noncarriers (76.5 years of age). The rate of decline was also faster, such that by 85 years of age, β-amyloid–positive ε4 carriers performed worse than β-amyloid–positive ε4 noncarriers.
These results suggest that memory decline in β-amyloid–positive adults may accelerate with older age and that this increase in acceleration may be associated with the APOE ε4 allele.
Older age, high levels of β-amyloid (Aβ), and the presence of the apolipoprotein E (APOE) ε4 allele are risk factors for Alzheimer disease (AD). However, the extent to which increasing age, Aβ, and ε4 are associated with memory decline remains unclear, and the age at which memory decline begins for Aβ-positive ε4 carriers and noncarriers has not been determined.
To determine the association of age, Aβ level, and APOE ε4 with memory decline in a large group of cognitively healthy older adults.
Design, Setting, and Participants
This longitudinal observational study included cognitively healthy older adults (age >60 years) enrolled in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study from March 31, 2006, through March 31, 2017; of 1583 individuals enrolled, 1136 refused or were excluded owing to other criteria (eg, having mild cognitive impairment or AD). Participants underwent Aβ imaging in research clinics in Perth and Melbourne and more than 72 months of follow-up (at 18-month intervals). The association of age with memory was fitted to a quadratic model. Age was treated as a continuous, time-dependent variable.
β-Amyloid imaging using positron emission tomography, genotyping for APOE ɛ4, and longitudinal neuropsychological assessments of episodic memory during the 72-month follow-up.
Main Outcomes and Measures
Episodic memory composite score.
Of the 447 participants, 203 (45.4%) were men and 244 (54.6%) were women; mean (SD) age was 72.5 (6.6) years. Equal proportions of female participants were observed in each Aβ-ɛ4 group (24 of 51 Aβ-positive ε4 noncarriers [47.1%] ; 35 of 64 Aβ-negative ε4 carriers [54.7%]; 40 of 72 Aβ-positive ε4 carriers [55.6%]; and 145 of 260 Aβ-negative ε4 noncarriers [55.8%]). Adults with Aβ findings (mean [SD] age, 74.4 [6.8] years) were approximately 4 years older than those negative for Aβ (mean [SD] age, 69.8 [6.1] years). Memory decline diverged significantly from Aβ-negative ɛ4 noncarriers at an earlier age in Aβ-positive ɛ4 carriers (64.5 years) than in Aβ-positive ɛ4 noncarriers (76.5 years), such that by 85 years of age, Aβ-positive ε4 carriers performed approximately 1.5 SD units worse on the episodic memory composite than Aβ-negative ε4 noncarriers and approximately 0.8 SD units worse than Aβ-positive ε4 noncarriers. Memory performance of Aβ-negative ɛ4 carriers did not differ from that of the Aβ-negative ɛ4 noncarriers (estimate [SE], 0.001 [0.001]; t = 0.526; P = .77).
Conclusions and Relevance
Prior work has shown that Aβ and ε4 combine to influence memory decline in nondemented older adults. Results of this study indicate that increasing age may further exacerbate these effects. The estimates provided may be used to determine the risk of memory decline associated with Aβ and ε4 at each age.
In cognitively healthy older adults (eg, >60 years of age), an elevated level of β-amyloid (Aβ), determined from positron emission tomography (PET) or examination of cerebrospinal fluid samples, indicates that Alzheimer disease (AD) has begun.1-3 This hypothesis is supported by observations that Aβ positivity in cognitively healthy older adults is associated with a decline in episodic memory and other aspects of cognition,2,3 greater loss of volume in medial temporal lobe areas,4 faster accumulation of Aβ,5 and greater rates of progression to clinical classification of mild cognitive impairment or AD dementia.6 The greatest risk for Aβ positivity in cognitively healthy adults is age, with approximately 10% of cognitively healthy adults aged 60 to 70 years, 25% aged 71 to 80 years, and 40% older than 80 years classified as being Aβ positive.7
Age-related risk for AD dementia is increased further by carriage of the apolipoprotein E (APOE) ε4 allele. For example, carriage of an APOE ε4 allele lowers the age of onset of AD dementia in a gene-dose–dependent manner, with the mean age of onset of AD dementia in ε4 homozygotes at 68 years compared with 76 years for ε4 heterozygotes and 84 years for ε4 noncarriers.8 Consistent with these findings, a meta-analysis of clinicopathologic studies of preclinical AD showed that although cognitively healthy APOE ε4 carriers are more likely to be classified as positive for Aβ, this risk increases with age. For example, 20% of cognitively healthy ε4 carriers aged 60 years are classified as positive for Aβ (compared with <10% of ε4 noncarriers), which increases to 70% at 80 years of age (compared with 25% of ε4 noncarriers).7
Although greater Aβ-associated memory decline in APOE ε4 carriers has been observed consistently in preclinical AD,9-12 whether this association also increases with age remains unknown. In cognitively healthy adults, application of nonlinear analyses showed that APOE ε4 carriage accelerated age-related memory decline in a gene-dose manner. Although Aβ levels were not determined in these studies, a substantial proportion of the age-related variance in memory decline observed in the ε4 carriers was likely owing to the presence of Aβ. However, APOE ε4 may have been associated with age-related memory decline in addition to Aβ. Both potential explanations require extension of the approach of Caselli et al13,14 to modeling interactions among APOE ε4, age, and memory decline to include Aβ levels.
The aim of this study was therefore to determine the extent to which Aβ levels (as determined by PET neuroimaging) and APOE ε4 are associated with age-related changes in memory in cognitively healthy adults. The first hypothesis was that Aβ-related memory decline would accelerate with age and that this acceleration would be greater in ε4 carriers than noncarriers. The second hypothesis was that in the absence of Aβ, APOE ε4 would not be associated with age-related memory decline.
Four hundred forty-seven cognitively healthy older adults enrolled in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study15 from March 31, 2006, through March 31, 2017, underwent Aβ neuroimaging and APOE genotyping (Table 1) and completed neuropsychological testing at baseline and 18-, 36-, 54-, and 72-month follow-up.15 Of the 1583 individuals enrolled in AIBL, 1136 refused or were excluded owing to other criteria (eg, having mild cognitive impairment or AD). Details of the recruitment process and classification of the cognitive health of the participants has been reported elsewhere.15,16 The AIBL study was approved by institutional human research and ethics committees of Austin Health, Heidelberg, Australia, St Vincent’s Health, Kew, Australia, Hollywood Private Hospital, Perth, Australia, and Edith Cowan University, Joondalup, Australia, which also ensured compliance with study protocols.15 Written informed consent was obtained from all participants before study participation.
In brief, exclusion criteria included a previous confirmed diagnosis of any of the following: schizophrenia, Parkinson disease, sleep apnea, depression (eg, Geriatric Depression Score of 6 or greater of a possible range of 0-15), cancer (except basal cell skin carcinoma) in the past 2 years, symptomatic stroke, or uncontrolled diabetes and if current alcohol use exceeded 4 standard drinks per day for men or 2 per day for women. All neuropsychological, psychiatric, and medical information for participants was reviewed by an expert clinical panel led by one of us (D.A.) to determine the cognitive health of participants. This panel was masked to outcomes of PET imaging and APOE genotyping.
β-Amyloid PET imaging was conducted using the Pittsburgh Compound B (PiB), florbetapir F 18, or flutemetamol F 18 radioligands, with the acquisition protocol for each radioligand described previously.16-18 In brief, a 30-minute acquisition was started 40 minutes after PiB injection, and 20-minute acquisitions were performed 50 minutes after florbetapir F 18 injection and 90 minutes after flutemetamol F 18 injection. For PiB acquisition, standardized uptake value (SUV) data for key regions of interest were summed and normalized to the cerebellar cortex SUV. This process resulted in a region-to-cerebellar ratio termed the SUV ratio (SUVR). For florbetapir F 18, the SUVR is generated using the whole cerebellum as the reference region19; for flutemetamol F 18, the pons is used as the reference region. A linear regression transformation was applied to the SUVRs for florbetapir F 18 and flutemetamol F 18 to transform them into a PiB-like SUVR.20 These SUVRs were termed BECKET (before the centiloid kernel transformation).20 An SUVR/BECKET threshold of at least 1.5 was used to classify Aβ positivity. Participants in the AIBL study underwent Aβ neuroimaging a mean (SD) of 2.5 (1.6) years after their baseline assessment (Table 1). This scan time difference was included as a covariate in all statistical models.
A blood sample from each participant was forwarded for DNA extraction using commercially available kits (QIAamp DNA blood Midi or Maxi kit; Qiagen), applying the protocol given by the manufacturer. The APOE genotype was determined through genotyping assays (TaqMan; Life Technologies) for rs7412 (assay identification: C____904973_10) and rs429358 (assay identification: C___3084793_20) on a real-time polymerase chain reaction system (QuantStudio 12K-Flex; Applied Biosystems) using the genotyping master mix (TaqMan GTXpress; Life Technologies) methods according to the manufacturer’s instructions.
The rationale and validation of the AIBL episodic memory composite score has been described elsewhere.2 First, scores on the California Verbal Learning Test (Second Edition) delayed recall trial,21 the Logical Memory delayed recall trial,22 and the Rey Complex Figure Test 30-minute delayed recall trial23 were standardized using the baseline mean and SD in the cognitively healthy group. A mean (SD) score was then calculated for these standard scores for each assessment.
All statistical analyses were conducted in SAS software (version 9.2; SAS Institute). A 1-way analysis of variance was conducted to investigate group differences at baseline. Demographic or clinical factors that differed between groups were entered as covariates in subsequent statistical models.
To test our hypotheses that acceleration of memory decline with age in Aβ-positive adults would be greater in ε4 carriers than ε4 noncarriers and that, in the absence of Aβ, APOE ε4 would not be associated with age-related memory decline, a mixed-effects model with an unstructured covariance matrix was used. The episodic memory composite was defined as the dependent variable, age as the continuous time-dependent variable, and group (Aβ-negative ɛ4 noncarriers, Aβ-negative ɛ4 carriers, Aβ-positive ɛ4 noncarriers, and Aβ-positive ɛ4 carriers) as a fixed factor. Time was modeled as a repeated measure within participants. The time from the baseline assessment to Aβ PET (ie, scan time) was also entered as a covariate. Model best fits were determined by least squares estimations of linear, quadratic, and cubic terms with the derived goodness-of-fit coefficients (ie, variance in memory scores explained) for each model compared statistically with that of the previous model.
Once the best-fit characteristic had been determined, data for the association between the change in episodic memory and increasing age were modeled separately for each group. To determine the age at which memory decline for each group became abnormal, the point at which the trajectory of each quadratic curve became different from that of the Aβ-negative ɛ4 noncarriers was estimated by computing the 95% CIs for each curve and determining the age at which the CIs did not overlap with those of the Aβ-negative ɛ4 noncarrier group.24 We conducted a series of planned comparisons to determine whether differences existed between (1) Aβ-negative ɛ4 noncarriers and carriers, (2) Aβ-positive ɛ4 noncarriers and carriers, and (3) Aβ-negative ɛ4 noncarriers and Aβ-positive ɛ4 carriers.
Of the 447 participants, 203 (45.4%) were men and 244 (54.6%) were women; mean (SD) age was 72.5 (6.6) years. Table 1 summarizes the demographic and clinical characteristics of each Aβ-ɛ4 group. A series of planned comparisons determined that no differences existed in the proportion of female participants in each group (24 of 51 Aβ-positive ε4 noncarriers [47.1%]; 35 of 64 Aβ-negative ε4 carriers [54.7%]; 40 of 72 Aβ-positive ε4 carriers [55.6%]; and 145 of 260 Aβ-negative ε4 noncarriers [55.8%]). Adults with Aβ findings (mean [SD] age, 74.4 [6.8] years) were approximately 4 years older than those negative for Aβ (mean [SD] age, 69.8 [6.1] years). Premorbid intelligence and levels of depressive symptoms were also equivalent across all groups. However, both Aβ-positive groups were on average 4 years older (mean [SD] ages, 75.7 [5.9] and 73.1 [6.4] years) than Aβ-negative groups (mean [SD] ages, 70.2 [6.0] and 69.4 [6.0] years). When we compared the mean (SD) time between PET scans with that of Aβ-negative ɛ4 noncarriers (3.20 [1.55] years), time between PET scans was shorter for Aβ-negative ɛ4 carriers (2.69 [1.51] years; P = .02), Aβ-positive ɛ4 noncarriers (2.66 [1.73] years; P = .02), and Aβ-positive ɛ4 carriers (1.99 [1.40] years; P < .001).
A quadratic model explained significantly more variance in the association between age and change in episodic memory than the linear model (−2 log likelihood ratio, 3491.8, in which a lower number indicates a better fit). Compared with the quadratic model (−2 log likelihood ratio, 3473.09; χ24 = 18.67; P < .001), the cubic model did not provide a statistically significant increase in variance explained and was not as parsimonious (−2 log likelihood ratio, 3470.1; χ24 = 2.96; P = .56). Scan time was not a significant covariate in these analyses and was therefore removed from the model.
The longitudinal association of group (F3,640 = 9.42; P < .001), age (F1,559 = 10.31; P = .001), and square of age (F1,578 = 12.15; P = .001) with memory was statistically different between groups. The interaction between the square of age and group was also statistically significant (F3,767 = 16.60; P < .001). The Figure shows that this interaction occurred because the quadratic association between change in memory and increasing age was greatest in Aβ-positive ɛ4 carriers, followed by Aβ-positive ɛ4 noncarriers. The Figure also shows no statistically significant decline in memory as age increased in Aβ-negative ɛ4 carriers (estimate [SE], −0.001 [0.001]; t = −1.268; P = .21) and Aβ-negative ɛ4 noncarriers (estimate [SE], −0.001 [0.001]; t = −1.017; P = .11). In contrast, significantly greater decline in memory as age increased was found in the Aβ-positive ɛ4 noncarriers (estimate (SE), = −0.118 [0.012]; t = −0.980; P = .02) and Aβ-positive ɛ4 carriers (estimate [SE] = −0.551 [0.093]; t = −5.960; P < .001). A series of planned comparisons determined that the trajectory of memory decline of Aβ-positive ɛ4 carriers was statistically different from that of Aβ-negative ɛ4 noncarriers (estimate [SE], −0.019 [0.012]; t = −1.605; P = .049) and Aβ-negative ɛ4 noncarriers (estimate [SE], −0.033 (0.011); t = −2.869; P < .001). The estimated age at which the trajectory of memory decline became different from that of Aβ-negative ɛ4 noncarriers was 64.5 years in Aβ-positive ɛ4 carriers and 76.5 years in Aβ-positive ɛ4 noncarriers. The trajectory of memory decline in Aβ-negative ɛ4 carriers was not statistically different from that of Aβ-negative ɛ4 noncarriers (estimate [SE], 0.001 [0.001]; t = 0.526; P = .77). Thus, at no estimated age did trajectories of memory decline for Aβ-negative ɛ4 carriers differ from those of Aβ-negative ɛ4 noncarriers.
The greater acceleration of memory decline in Aβ-positive ɛ4 carriers was also revealed by the lower intercept and higher slope estimates compared with Aβ-positive ɛ4 noncarriers, Aβ-negative ɛ4 carriers, and Aβ-negative ɛ4 noncarriers (Table 2). These intercept and slope estimates can also be used to estimate an individual’s memory performance at a given age. In Table 3, three examples of estimated memory performance at ages 65, 75, and 85 for Aβ-negative ɛ4 noncarriers, Aβ-negative ɛ4 carriers, Aβ-positive ɛ4 noncarriers, and Aβ-positive ɛ4 carriers are given. Estimation of memory performance at any age throughout the range studied in each of the groups can also be calculated using the following formula: c + (β1 × age) + [β2(age × age)].
The first hypothesis, that memory decline would accelerate with age in Aβ-positive adults and that this acceleration would be greater in ε4 carriers than ε4 noncarriers, was supported. Specifically, in Aβ-positive ε4 carriers, memory decline began at approximately 64.5 years of age and accelerated thereafter, such that by 85 years of age, Aβ-positive ε4 carriers performed approximately 1.5 SD units worse than matched Aβ-negative ε4 noncarriers and 0.8 SD units worse than Aβ-positive ε4 noncarriers (Table 2). Although memory decline also accelerated with increasing age in Aβ-positive ε4 noncarriers, this acceleration began later (76.5 years of age) and was not as great as that in Aβ-positive ε4 carriers. Thus, by 85 years of age, episodic memory in Aβ-positive ε4 noncarriers was approximately 0.70 SD units worse than that in Aβ-negative ε4 noncarriers. Previous studies of Aβ-positive adults have observed faster memory decline in ε4 carriers than ε4 noncarriers9-12; however, in all studies to date, associations between time and memory decline have been modeled using linear methods, with age treated as a baseline covariate.9-12 Thus, although the nonlinear associations observed in the present study suggest that the presence of the ε4 allele is associated with increases in memory decline in Aβ-positive adults, they also extend understanding of this phenomena by showing that Aβ-related memory decline may accelerate with increasing age and may be increased further by ε4 carriage. The observations also demonstrate that in Aβ-positive ε4 carriers, memory decline may begin more than 10 years earlier than in Aβ-positive ε4 noncarriers (Figure). This acceleration of memory decline in Aβ-positive ε4 carriers is also consistent with data from epidemiologic studies25 showing that APOE ε4 hastens the age of onset of AD dementia by approximately 8 years.
The earlier presentation and faster acceleration of memory decline with increasing age in Aβ-positive ε4 carriers also provides a clinical expression of data from in vitro experiments,26,27 which demonstrate that APOE ε4 disrupts clearance of Aβ. Although ε4 carriers and noncarriers in the present sample showed equivalent levels of Aβ, the use of the single Aβ PET scan did not allow us to determine whether the deleterious association of ε4 with memory decline in Aβ-positive individuals was accompanied by accelerating Aβ accumulation. However, previous studies examining the association between memory decline and AD biomarkers in older adults without dementia suggest that this acceleration is likely.5,28 The results of our study are also consistent with those of studies that have used the same statistical modeling approach to demonstrate that memory decline accelerates with increasing age in APOE ε4 carriers,13,14 albeit in the absence of information about Aβ levels.
The results of the present study also support our second hypothesis, that in the absence of Aβ, APOE ε4 would not be associated with age-related memory decline. Despite the risk for AD and Aβ positivity associated with carriage of the APOE ε4 allele,16,29APOE ε4 did not increase the risk for memory decline in Aβ-negative older adults in our study. Despite the long period of investigation and the large sample size of our study, we observed that episodic memory remained stable in Aβ-negative ε4 carriers even with increasing age, and the rate of episodic memory decline from 65 to 85 years of age was indistinguishable from that of Aβ-negative ε4 noncarriers (Figure). This finding is consistent with those of previous studies9-12 demonstrating that in the absence of Aβ, APOE ε4 is not associated with increased cognitive decline in cognitively healthy adults. Considered together, these results suggest that in the absence of occult disease, episodic memory does not deteriorate with increasing age, even in the presence of ε4.
Previously, age-related acceleration in memory decline was observed in APOE ε4 homozygotes compared with ε4 heterozygotes and noncarriers, albeit with unknown Aβ status.13 The age-related acceleration of memory decline observed in the present study was qualitatively similar to that observed for ε4 homozygotes in this previous study. However, in the current sample, only a small proportion (6 [8.3%]) of the Aβ-positive ε4 carriers, who showed the greatest acceleration of age-related memory decline, were ε4 homozygotes. Furthermore, Aβ-negative ε4 carriers showed no age-related decline in memory. Thus, the present data suggest that the memory decline observed in the older ε4 homozygotes in the previous studies reflected their risk of Aβ positivity rather than a specific effect of APOE ε4.26 Thus, in the presence of Aβ, even a single copy of the ε4 allele may be associated with memory decline that accelerates with increasing age.
When considered together, the findings of our study confirm initial observations that in preclinical AD, Aβ-positive ε4 carriers may have a faster rate of decline in episodic memory9,10,12 and that Aβ-related memory decline may also occur in ε4 noncarriers, albeit at a slower rate.11 Our present findings extend knowledge of the association among Aβ, APOE ε4, and memory decline because memory decline in Aβ-positive older adults accelerated with age and this acceleration was moderated by the APOE ε4 allele. Conversely, in Aβ-negative older adults, memory function did not change substantially with increasing age irrespective of the presence of the APOE ε4 allele. We have provided estimates (Table 3) to assist researchers and clinicians in determining the risk of memory decline given 3 known variables (ie, age, Aβ status, and APOE ε4 status). Although these estimations require further refinement and replication, they provide a foundation for predictions about the nature of the course of AD through its preclinical phase.
Several points warrant consideration before generalizing the results of this study. First, the AIBL study is not a population-based sample. Strict inclusion and exclusion criteria were applied to the selection of participants, and consequently the sample is relatively free of cardiovascular risk factors and other medical and psychiatric illnesses. Most participants also had tertiary educational levels and high premorbid intelligence levels. Some or all of these factors may have limited the presence of memory decline in Aβ-negative ε4 carriers. Therefore, replication of these data in other cohorts of individuals at risk of developing AD will be important.12 Second, despite the relatively large sample, the study lacked sufficient statistical power to investigate any gene-dose effects of ε4 on Aβ-related memory decline. Previous investigators13,14,30 have reported that ε4 homozygotes show nearly double the magnitude of cognitive impairment compared with ε4 heterozygotes, although the extent to which this outcome occurs prospectively and in the presence of Aβ remains unclear. Finally, owing to limited samples with serial imaging measures, the extent to which memory decline in Aβ-positive ε4 carriers is associated with Aβ accumulation and brain volume loss could not be determined.
Prior work has shown that Aβ and ε4 combined are associated with memory decline in older adults without dementia. Results of this study suggest that increasing age may strengthen this association. The estimates provided can be used to determine the risk of memory decline due to Aβ and ε4 at each age.
Accepted for Publication: October 6, 2017.
Corresponding Author: Yen Ying Lim, PhD, The Florey Institute of Neuroscience and Mental Health, University of Melbourne, 155 Oak St, Parkville, Victoria, Australia 3052 (firstname.lastname@example.org).
Published Online: January 22, 2018. doi:10.1001/jamaneurol.2017.4325
Author Contributions: Drs Lim and Kalinowski had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Lim, Ames, Rowe, Masters, Maruff.
Acquisition, analysis, or interpretation of data: Lim, Kalinowski, Pietrzak, Laws, Burnham, Ames, Villemagne, Fowler, Rainey-Smith, Martins, Masters, Maruff.
Drafting of the manuscript: Lim, Kalinowski, Masters, Maruff.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Lim, Kalinowski, Pietrzak, Maruff.
Obtained funding: Laws, Ames, Martins, Rowe, Masters, Maruff.
Administrative, technical, or material support: Pietrzak, Laws, Ames, Fowler, Rainey-Smith, Rowe, Masters, Maruff.
Study supervision: Pietrzak, Ames, Rowe, Masters, Maruff.
Conflict of Interest Disclosures: Dr Lim reports serving as a scientific consultant to CogState, Ltd, Biogen, and Lundbeck. Dr Pietrzak reports serving as a scientific consultant to CogState, Ltd. Dr Villemagne reports serving as a consultant for Bayer Pharma and receiving research support from a New Energy and Industrial Technology Development Organization grant from Japan. Dr Masters reports serving as an advisor to Prana Biotechnology, Ltd, and a consultant to Eli Lilly and Company. Dr Rowe reports serving on scientific advisory boards for Bayer Pharma, Elan Corporation, GE Healthcare, and AstraZeneca; receiving speaker honoraria from Bayer Pharma and GE Healthcare; and receiving research support from Bayer Pharma, GE Healthcare, Piramal Lifesciences, and Avid Radiopharmaceuticals not related to the content of the manuscript. No other disclosures were reported.
Funding/Support: This study was supported in part by the study partners Commonwealth Scientific Industrial and Research Organization (CSIRO), Edith Cowan University, Mental Health Research Institute, National Ageing Research Institute, Austin Health, and CogState, Ltd; the National Health and Medical Research Council (NHMRC) and the Dementia Collaborative Research Centres program; the Science and Industry Endowment Fund (SIEF); the Cooperative Research Centre for Mental Health, an Australian government initiative; and the Dementia Research Development Fellowship from the NHMRC–Australian Research Council (Dr Lim).
Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: Alzheimer’s Australia (Victoria and Western Australia) assisted with promotion of the study and the screening of telephone calls from volunteers. The following physicians referred patients with mild cognitive impairment or Alzheimer disease to the study, for which they were not compensated: Brian Chambers, MD, Edmond Chiu, MD, Mary Davison, MD, Kwang Lim, MD, Nicola Lautenschlager, MD, Dina LoGiudice, MD, and Michael Woodward, MD, University of Melbourne, Parkville, Australia; Roger Clarnette, MD, Mathew Samuel, MD, and Darshan Trivedi, MD, Hollywood Specialist Center, Perth, Australia; David Darby, MD, Florey Institute of Neuroscience and Mental Health, Parkville, Australia; John Drago, MD, St Vincent’s Private Hospital, Kew, Australia; Peter Drysdale, MD, Delmont Memory Clinic, Burwood, Australia; Jacqueline Gilbert, MD, Melbourne Private Hospital, Parkville, Australia; Peter McCardle, MD, Albert Road Clinic, Melbourne, Australia; Steve McFarlane, MD, Alfred Health, Melbourne, Australia; Alastair Mander, MD, Deakin University, Melbourne, Australia; John Merory, MD, Heidelberg Neurology, Heidelberg, Australia; Daniel O’Connor, MD, private practice, Victoria, Australia; and Ron Scholes, MD, Donvale Rehabilitation Hospital, Donvale, Australia. We thank all who participated in the study for their commitment and dedication to helping advance research into the early detection and causation of Alzheimer disease.