Amyloid-PET Levels in the Precuneus and Posterior Cingulate Cortices Are Associated with Executive Function Scores in Preclinical Alzheimer’s Disease Prior to Overt Global Amyloid Positivity

Abstract

Background:

Global amyloid-β (Aβ) deposition in the brain can be quantified by Aβ-PET scans to support or refute a diagnosis of preclinical Alzheimer’s disease (pAD). Yet, Aβ-PET scans enable quantitative evaluation of regional Aβ elevations in pAD, potentially allowing even earlier detection of pAD, long before global positivity is achieved. It remains unclear as to whether such regional changes are clinically meaningful.

Objective:

Test the hypothesis that early focal regional amyloid deposition in the brain is associated with cognitive performance in specific cognitive domain scores in pAD.

Methods:

Global and regional standardized uptake value ratios (SUVr) from ¹⁸F-florbetapir PET/CT scanning were determined using the Siemens Syngo.via® Neurology software package across a sample of 99 clinically normal participants with Montreal Cognitive Assessment (MoCA) scores≥23. Relationships between regional SUVr and cognitive test scores were analyzed using linear regression models adjusted for age, sex, and education. Participants were divided into two groups based on SUVr in the posterior cingulate and precuneus gyri (SUVR≥1.17). Between group differences in cognitive test scores were analyzed using ANCOVA models.

Results:

Executive function performance was associated with increased regional SUVr in the precuneus and posterior cingulate regions only (p < 0.05). There were no significant associations between memory and Aβ-PET SUVr in any regions of the brain.

Conclusion:

These data demonstrate that increased Aβ deposition in the precuneus and posterior cingulate (the earliest brain regions affected with Aβ pathology) is associated with changes in executive function that may precede memory decline in pAD.

Keywords

Amyloid-β positron emission tomography cognition preclinical Alzheimer’s disease regional standardized uptake value ratio

INTRODUCTION

Dementia is a major and increasing global health challenge with 40–50 million people currently living with dementia worldwide [1]. Alzheimer’s disease (AD) is the most common cause of dementia corresponding to about 60% of cases [2]. The neuropathological development of AD arguably begins with amyloid-β (Aβ) deposition in the brain, which occurs many years before the appearance of cognitive decline (preclinical Alzheimer’s disease (pAD)) [3, 4], and has been identified as a risk factor for subsequent dementia [5, 6]. The diagnosis of pAD is based on biomarker positivity using diagnostic tests such as amyloid tracer-based positron emission tomography (Aβ-PET) and cerebrospinal fluid (CSF) measures of Aβ [7].

It is challenging to detect clinically significant cognitive change in pAD, and results have been variable across studies [8 –20]. Although Aβ deposition is a gradual process [21] that develops over time in discrete regions of the brain in a temporally progressive manner [22], the majority of published studies have focused on global rather than regional measures of Aβ positivity. One recent study, however, demonstrated that patients with early focal Aβ deposition had clinical features that differed from persons with more diffuse global Aβ deposition, suggesting that further study is needed [23]. Another recent study has shown that preclinical Aβ accumulation in the precuneus, medial orbitofrontal, and posterior cingulate cortices can be detected in participants prior to the development of abnormal CSF Aβ₄₂ or global Aβ PET scan positivity [24, 25]. Limitations of recent studies on regional quantification of amyloid pathology also include a primary focus on memory domain impairment rather than examining a broader array of cognitive domain involvement [26 –28]. Additionally, previous studies examining relationships between regional Aβ deposition and different domains of cognition have largely focused on comparing cognitively normal participants to mild cognitively impaired or AD patients, but notably did not include pAD participants [29 –31]. As early identification of pAD is an important goal for the field, an accurate and thorough understanding of the cognitive and brain changes accompanying this stage of disease is critical [32].

The main objective of this study was to test the hypothesis that early focal regional amyloid depo-sition in the brain is associated with preclinical cognitive decline in specific cognitive domains (memory and executive function) in elderly cognitively intact persons (pAD).

METHODS

Study design and participants

This cross-sectional study included review of the neuroimaging and clinical data from participants who underwent F-florbetapir PET/CT scanning between 2015 and 2020 at the Sanders Brown Center on Aging. This study was approved by the University of Kentucky (UK) Institutional Review Board (IRB), and a signed IRB consent was obtained from each subject prior to participation.

Inclusion criteria included the availability of:

Complete demographic information (age, sex, and years of education)

Neurocognitive function that covered major cognitive functions [33], the Montreal Cognitive Assessment (MoCA) [34], The Trail Making Test (TMT), and California Verbal Learning Test -II (CVLT-II) [35],

Cognitively intact participants with a MoCA score≥23 to exclude participants with mild cognitive impairment (MCI) or dementia, as described previously [36].

Acquisition of florbetapir PET/CT

For each scan, the participant received a single intravenous administration of approximately 370 MBq (10 mCi) of florbetapir F 18 (fast intravenous push). The injection of the imaging agent was followed by a saline flush. After an uptake period of 50 min, participants were positioned in a head stabilization unit designed for PET/CT scanners. All PET/CT scans were performed on a Siemens Biograph TruePoint 6-slice (Siemens Healthcare, Erlangen, Germany). Low resolution CT images of the head will be acquired (120 kVp, FOV 50 cm, pitch 0.55, 0.5 s rotation time, slice thickness 4 mm, care dose). PET images of the brain were then collected for a 20 min, 3D emission scan. The emission images are reconstructed using 256×256 matrix and all-pass filter.

All F-florbetapir PET/CT images were analyzed using dedicated viewing software (Syngo.via^®; Siemens) [37]. Siemens Syngo.VIA Amyloid Plaque (Siemens Medical Solutions Inc., Malvern, PA, USA) software package was used for neurological evaluations of PET/CT. Quantitative parametric analysis was performed with Database Comparison software (Siemens Medical Solutions, Inc.) that automatically identifies regions of interest (ROIs) based on the analysis method used by Fleisher [38]. The regions (frontal, temporal, parietal, anterior cingulate, posterior cingulate, and precuneus) were selected based on the analysis described by Fleisher and Clark in the use of florbetapir-PET in Aβ imaging analysis [38, 39]. Since the occipital region is significantly affected more than any other region in cerebral amyloid angiopathy, we exclude this region from the analysis [40, 41]. The mean uptake of ROIs was calculated. Standardized uptake value (SUV) is a semi quantitative measure of the intensity of radiotracer activity at each voxel [42]. The mean SUV of each region is normalized to the mean SUV of the cerebellum (SUVr) (SUVr = SUV target/ SUV reference) [43].

A threshold of SUVrs greater than or equal to 1.17 was used to reflect pathological levels of amyloid associated with MCI and AD [38 , 45]. We choose to focus on the mean score of posterior cingulate and precuneus gyri SUVrs as these regions are among the earliest brain regions of amyloid deposition [46 –49]. The participants were divided into two groups (pAD and control group) based on SUVr in the posterior cingulate and precuneus gyri (SUVr≥1.17).

Neuropsychological cognitive tests

We examined cognitive test scores that assess major cognitive functions, including global cognition with the MoCA [34], processing speed, attention and executive function with TMT [50] and memory function with the CVLT-II [35]. The MoCA is a brief test of cognitive function that assesses visuospatial, naming, attention, language, abstraction, delayed recall, and orientation. Total score is generated by summing scores across all of these domains [51]. TMT is a neuropsychological test of visual attention and task switching. In Part A, participants were asked to link numbered points randomly distributed on a sheet of paper in ascending order according to numbers. In Part B, the participants were asked to link numbers and letters alternately. The time of each test performance was measured, the number of errors were counted, and the difference in times: B-A was calculated [52]. CVLT-II is a widely used measure of verbal episodic learning and memory. A list of 16 items organized into four semantic categories are presented to the subject over five immediate recall trials, free and category cued recall is tested after short and longer (20 min) intervals. We chose to focus on the CVLT-II learning component of the test, which is the sum of the five immediate recall trials, as well as free delayed recall scores.

Statistical analyses

Statistical analyses were performed in IBM SPSS Statistics v28. Significance was set at p < 0.05, with Bonferroni correction based on the number of cognitive tests as a dependent variable.

In the first analysis, we used ANCOVA to evaluate whether the means of score of cognitive tests are equal across different levels of posterior cingulate and precuneus SUVr, while statistically controlling for the covariates (age, sex, and education). We tested the homogeneity to make sure the values of covariates did not vary and equal over all the two groups using ANOVA. Differences in performance on the neuropsychological cognitive tests between pAD and controlled group were tested using one-way ANCOVA after adjustment for covariates. The difference in the scores of cognitive function tests across different level of global SUVr were assessed using ANCOVA again.

In the second analysis, linear regression adjusted for age, sex and education was used to explore the relationship between regional SUVr (independent variables) and the cognitive function scores (dependent variable). Due to high co-linearity between regional SUVr measures regressions were initially run separately for each region. This process was repeated for each cognitive test (TMT B, TMT B-A, MoCA, and CVLT (learning score, short free delay recall, and long free delay recall)). Relationships between regional SUVr from multiple regression from the prior step and MoCA domain scores were analyzed using linear regression models adjusted for age and education.

RESULTS

The demographic, clinical and imaging characteristics of the sample are provided in Table 1. Briefly, the sample included 68 women and 31 men with a mean age of 74.2±6.3 years, education 16.7±2.6 years. Posterior cingulate and precuneus SUVrs ranged from 0.85 to 2.43 in this study cohort. Dividing the cohort into two groups based on SUVr of posterior cingulate and precuneus SUVr > 1.17, allowed an analysis of 45 participants in the pAD group and 54 participants in the control group. Between-group differences on demographic variables were not significant, including sex at birth, where a chi-square test showed non-significant between group differences (p = 0.83; data not shown in Table 1). Cognitive and imaging measures that clearly defined the groups as distinct are presented in Table 1.

Table 1

No significant between group differences on demographic variables were seen between pAD (n = 45) and control groups (n = 54). Significant between group differences were seen for MoCA, TMT B, and TMT B-A scores

	pAD		Control
	Mean	SD	Mean	SD	p
Age	75.08	7.01	73.46	5.6	0.203
Education	16.8	2.93	16.57	2.39	0.69
MoCA	26.2	1.85	27	1.83	0.036
TMT A	34.51	11.73	33.6	10.91	0.92
TMT B	92.07	38.41	73.36	27.6	0.011
TMT B-A	57.56	31.62	39.75	21.3	0.002
CVLT-II Total Learning	47	11.67	47.83	10.89	0.7
CVLT-II Short-Delay Free	9.91	4.25	11.3	3.57	0.089
CVLT-II Long-Delay Free	9.98	3.99	11.39	3.53	0.072

SD, standard deviation; SUVr, standardized uptake value ratio; AD, Alzheimer’s disease; MoCA, Montreal Cognitive Assessment; TMT, Trail Making Test; CVLT, California Verbal Learning Test–II.

ANCOVA demonstrated that statistically significant between group differences were seen for TMT B, TMT B-A, and MoCA (p = 0.02, 0.004 and 0.036, respectively) (Fig. 1). No significant differences were seen between groups in delayed recall measures on the CVLT-II (short and long (p = 0.089 and 0.072; shown in Table 1). When global rather than regional SUVr cutoff > 1.17 were used, no significant difference were observed between the groups on cognitive measures TMT (part A, part B, and part B-A (p = 0.736, 0.447, and 0.284), MoCA (p = 0.266) or CVLT-II (short and long (p = 0.875 and 0.372).

Fig. 1

The differences of the cognitive measures (MoCA and TMT B-A) between the preclinical and control group. Comparison of cognitive measure scores Trail Making Test (TMT) part B-A, and The Montreal Cognitive Assessment (MoCA) among preclinical group and control group based on SUVr of posterior cingulate and precuneus SUVr > 1.17 after adjusted for age, education, and sex. Panel A shows the difference in the scores of TMT part B-A between the groups. Box and whisker plots of the MoCA score (B) show medians, lower to upper quartile, and lines extending from minimum to maximum values.

In the second set of analyses (shown in Table 2), linear regression analysis was used with each region (Aβ-PET SUVr of independent frontal, parietal, temporal, anterior cingulate, posterior cingulate, and precuneus cortical regions) used as independent variables and cognitive test scores as a dependent variable to explore associations of amyloid deposition in regions of the brain with MoCA, TMT, and CVLT. Age, sex, and education were entered as covariates in the analysis. The adjusted linear regression analyses demonstrated that increased regional SUVr in the precuneus and posterior cingulate regions only were associated with reduced global MoCA score and TMT B-A scores (shown in Fig. 2) (p < 0.05).

Table 2

Testing the independent effect of regional Aβ SUVr burden on cognitive function test scores

Cognitive Function test	Regional SUVr	Coeff. B (p)	Adjusted R square
MoCA	Frontal SUVr	–1.01 (0.172)	0.052
	Parietal SUVr	–1.141 (0.176)	0.052
	Temporal SUVr	–1.244 (0.157)	0.054
	PCC &precuneus SUVr	–1.612 (0.023)	0.086
	Anterior cingulate SUVr	–0.479 (0.434)	0.039
TMT part A	Frontal SUVr	–1.92 (0.671)	0.028
	Parietal SUVr	1.31 (0.799)	0.027
	Temporal SUVr	–1.49 (0.781)	0.027
	PCC. &precuneus SUVr	0.804 (0.854)	0.027
	Anterior cingulate SUVr	–0.26 (0.944)	0.026
TMT (B)	Frontal SUVr	11.231 (0.401)	0.093
	Parietal SUVr	16.833 (0.268)	0.098
	Temporal SUVr	9.57 (0.547)	0.089
	PCC &precuneus SUVr	20.971 (0.102)	0.112
	Anterior cingulate SUVr	9.25 (0.401)	0.093
TMT (B-A)	Frontal SUVr	13.15 (0.228)	0.108
	Parietal SUVr	15.526 (0.210)	0.109
	Temporal SUVr	11.066 (0.393)	0.100
	PCC &precuneus SUVr	20.17 (0.04)	0.130
	Anterior cingulate SUVr	9.507 (0.290)	0.104
CVLT (learning score)	Frontal SUVr	–1.38 (0.772)	0.105
	Parietal SUVr	1.83 (0.736)	0.106
	Temporal SUVr	0.07 (0.991)	0.105
	PCC &precuneus SUVr	–2.59 (0.6)	0.107
	Anterior cingulate SUVr	0.17 (0.965)	0.105
CVLT (short free delay recall)	Frontal SUVr	–0.66 (0.692)	0.124
	Parietal SUVr	–0.57 (0.764)	0.123
	Temporal SUVr	–1.44 (0.484)	0.127
	PCC &precuneus SUVr	–1.63 (0.343)	0.131
	Anterior cingulate SUVr	–0.06 (0.965)	0.123
CVLT (long free delay recall)	Frontal SUVr	–1.70 (0.273)	0.180
	Parietal SUVr	–1.75 (0.320)	0.178
	Temporal SUVr	–2.73 (0.155)	0.188
	PCC &precuneus SUVr	–2.35 (0.143)	0.189
	Anterior cingulate SUVr	–0.91 (0.470)	0.174

Coeff. B, coefficient β, SUVr, standardized uptake value ratio; MoCA, Montreal Cognitive Assessment; TMT, Trail Making Test; CVLT, California Verbal Learning Test–II; PCC, posterior cingulate cortex. (All coefficient β values are adjusted for the covariates age, sex, and education. Adjusted R square is the proportion of variance in the cognitive function scores that was explained by the model discounted for age, sex, education, and regional SUVr).

Fig. 2

Scatterplot between the mean score of posterior cingulate cortex and precuneus SUVr with cognitive function scores (MoCA and TMT B-A). The scatterplots show the fitted regression line of the posterior cingulate cortex (PCC) and precuneus SUVrs as independent variables and cognitive function test scores (MoCA global score, and TMT part B completion time- TMT part A completion time) as the dependent variable. A) Removing the visually obvious outlier (The mean SUVr of PCC and precuneus = 2.43 (p = 0.048)) did not alter the statistically significant correlation between MoCA global score and the mean SUVr of PCC and precuneus.

DISCUSSION

The main finding of this study is that regional amyloid deposition in the precuneus and posterior cingulate are associated with early preclinical decline in executive function in pAD, irrespective of global SUVr. Prior studies that have focused on regional amyloid deposition in the brain have shown that regional amyloid deposition in posterior cingulate gyri and precuneus are associated with global cognition [28, 53] and lower preclinical memory scores; however, analyses of Aβ influences on non-memory cognitive domains were not assessed [26 –28]. Such studies with an a priori focus on memory domain impairment rather than exploring a broader array of cognitive domain relationships introduces a bias that limits our full understanding of the impact of early preclinical Aβ deposition.

While the majority of observational studies and clinical trials for pAD have defined populations on the basis of global SUVr cut-offs, the present data suggests that such criteria may be selecting for a later pathological stage of disease, perhaps mediated by cognitive reserve mechanisms. As the field moves towards earlier diagnosis and intervention, considering the development of modified biomarker criteria that takes into account the wealth of data accumulated in the area of pAD just makes sense. Such attempts to date, include lowering global Aβ SUVr cut-off scores for the diagnosis of pAD [54 –56], that have enabled an even earlier examination of pAD. Our data suggests we can go even earlier by focusing on regional Aβ-PET SUVr levels in the precuneus and posterior cingulate rather than on global SUVr data that has already been adjusted to its threshold. While concerns about using such an approach might include a possibility of simply detecting incidental cerebral amyloidosis that may never progress, the present data demonstrating early preclinical cognitive test score associations argue against such a possibility, demonstrating that such early regional Aβ deposition is clinically meaningful. Moreover, accumulation of amyloid in precuneus had shown to be predictive of future global amyloid deposition in the brain [28].

In this context, the present data demonstrate that changes in executive function may be the earliest signs of pAD. Consistent with our findings, Snitz et al. reported that nonmemory domains, primarily executive functions, are changed 7 to 9 years prior to neuroimaging change in Aβ-positive clinically normal participants comparing to Aβ-negative participants [57]. A more recent study using random forest machine learning analysis to rank the AD biomarkers in prediction of clinical dementia status in AD [58] found that Aβ deposition in precuneus, temporal, and frontal as well as tau levels are highly correlated with cognitive function in cognitively normal participants and are predictors for early preclinical impairments in executive and memory function. This same study also demonstrated that increased tau burden is associated with lower memory but not executive function scores in clinically normal older individuals. Our data is aligned with these previous results suggesting that early change in executive function in pAD may be explained by preclinical Aβ deposition in precuneus and posterior cingulate gyri. Both posterior cingulate gyri and precuneus are part of default mode network, which is involved in attention and executive function [59].

It is also possible that the lower executive function performance associated with early preclinical Aβ deposition in the precuneus and posterior cingulate seen in the present study may not be dependent on neuroanatomic involvement of these regions but rather may be associated with more global changes in brain function and or pathology that lie below the level of Aβ-PET detection. As such, it is possible that early Aβ deposition in the precuneus and posterior cingulate is related to a more widespread production of early synaptotoxic soluble oligomeric Aβ species affecting regions such as the dorsolateral prefrontal cortex that is more widely recognized as a neuroanatomic substrate for executive dysfunction [60]. Interstitial fluid accumulation of such soluble oligomeric Aβ species may be well below the threshold of Aβ-PET detection. Alternatively, early tau abnormalities, inflammatory, or oxidative stress related mechanisms are just a few of the concomitant mechanisms that could be at play but remain below the level of detection in brain regions responsible for early executive dysfunction in pAD [61]. Much further work is needed before we fully understand the still enigmatic state of pAD.

Cognitive screening instruments such as MoCA are widely used to detect cognitive decline as one transitions from pAD to mild cognitive impairment or dementia due to AD [9], but are relatively insensitive for tracking cognitive decline in pAD. Our data, however, using adjusted linear multiple regression, demonstrates that increased Aβ deposition in the precuneus and posterior cingulate (the earliest brain regions affected with Aβ pathology [24, 62]) are associated with decreased global cognitive performance MoCA, further supporting at least one prior study in the literature [63]. The relationship of MoCA scores with Aβ deposition in the precuneus and posterior cingulate seen in the present study appeared to be driven by language domain subscores in individuals with pAD (data not shown). This result conceptually is in accordance with prior findings from a much smaller study (n = 11 AD and 15 healthy control) that found a significant relationship between greater florbetapir F18 precuneus SUVr and poorer verbal fluency in AD [64].

The main limitations of our study include the relatively small sample size, and an absence of tau measures in the analysis. Another main limitation of the study is unavailability of APOE in the analysis, despite its well-recognized influence on amyloid deposition in cognitively healthy individuals. Another limitation of this study is the use of a highly educated, predominantly white sample that limits the generalizability of the results to underrepresented groups. Despite this limitation it should be noted that the participants represented a well-characterized cohort that has undergone comprehensive longitudinal medical and neuropsychological exams. The strengths of our work include a focus on early regions of the brain affected by Aβ pathology and their relation to domain-specific cognitive test performance in pAD, prior to development of global Aβ positivity.

While the prevailing view in the field suggests that memory performance is the earliest clinical hallmark of AD, the present data demonstrate that changes in executive function, mediated by Aβ deposition in the precuneus and posterior cingulate may precede memory decline in pAD. Ongoing and future efforts at developing more sensitive tests for preclinical executive function deficits may serve as the most sensitive, low cost, non-invasive clinical biomarkers of preclinical AD. Further studies are needed to show the longitudinal clinical and cognitive outcome of this early preclinical amyloid change, and for a complete understanding of the temporal progression of domain specific cognitive change in relation to regional progression of amyloid deposition in the brain.

Footnotes

ACKNOWLEDGMENTS

The authors would like to thank the participants and their study partners. In addition, the authors would like to thank University of Kentucky Alzheimer’s Disease Center (UK-ADC) cohort and affiliated clinical trials especially INtervention for Cognitive Reserve Enhancement in delaying the onset of Alzheimer’s Symptomatic Expression (INCREASE) study. This study was funded by NIH/NIA P30 AG028383, U19AG010483, and R01 AG054130.

Authors’ disclosures available online ().

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