While episodic memory decline is the most common cognitive symptom of Alzheimer's disease (AD), changes in attentional control have also been found to be sensitive to early AD pathology. The relations between longitudinal trajectories of these specific cognitive domains, especially attentional control, and biomarkers of tau and neurodegeneration have not been thoroughly examined.
Objective:
We examined whether baseline tau positron emission tomography (PET) and cortical thickness, relatively later markers within the AD cascade, predicted cross-sectional and longitudinal changes in episodic memory and attentional control.
Methods:
Cognitively normal individuals ([Clinical Dementia Rating CDR®] = 0; n = 249) at baseline completed a magnetic resonance imaging (MRI), tau PET, and multiple assessments of episodic memory and attentional control. Generalized additive mixed-effects models examined whether tau PET summary measure and cortical thickness signature predicted cross-sectional and longitudinal trajectories of attentional control and episodic memory.
Results:
Higher tau PET and lower MRI cortical thickness were generally associated with worse cross-sectional cognitive performance. Our exploratory analyses found cortex-wide associations between tau PET and episodic memory, with limited suggestions of region-specific associations with attentional control. On longitudinal follow-up, higher tau PET was associated with a greater decline in episodic memory.
Conclusions:
These results indicate that tau PET is particularly sensitive to detecting longitudinal changes in episodic memory. This further informs relevant endpoints for clinical drug trials in cognitively normal individuals. Future studies might consider longer follow-ups and lag associations between changes in AD biomarkers and changes in cognition.
BatemanRJXiongCBenzingerTLS, et al.Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med2012; 367: 795–804.
3.
JackCRBennettDABlennowK, et al.A/T/N: an unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology2016; 87: 539–547.
4.
PriceJLMcKeelDWBucklesVD, et al.Neuropathology of nondemented aging: presumptive evidence for preclinical Alzheimer disease. Neurobiol Aging2009; 30: 1026–1036.
5.
EconomouARoutsisCPapageorgiouSG. Episodic memory in Alzheimer disease, frontotemporal dementia, and dementia with Lewy bodies/Parkinson disease dementia. Alzheimer Dis Assoc Disord2016; 30: 47–52.
6.
CraikFIMLockhartRS. Levels of processing: a framework for memory research. J Verb Learn Verb Behav1972; 11: 671–684.
7.
JacobyLL. A process dissociation framework: separating automatic from intentional uses of memory. J Mem Lang1991; 30: 513–541.
8.
AschenbrennerAJBalotaDATseC-S, et al.Alzheimer disease biomarkers, attentional control, and semantic memory retrieval: synergistic and mediational effects of biomarkers on a sensitive cognitive measure in non-demented older adults. Neuropsychology2015; 29: 368–381.
9.
AschenbrennerAJBalotaDAFaganAM, et al.Alzheimer disease cerebrospinal fluid biomarkers moderate baseline differences and predict longitudinal change in attentional control and episodic memory composites in the Adult Children Study. J Int Neuropsychol Soc2015; 21: 573–583.
10.
BalotaDADuchekJM, et al.Attention, variability, and biomarkers in Alzheimer’s disease. In: LindsayDSKelleyCMYonelinasAP (eds) Remembering: attributions, processes, and control in human memory: essays in honor of Larry Jacoby. New York: Psychology Press, 2015, pp.285–303.
11.
FriedmanNPMiyakeA. Unity and diversity of executive functions: individual differences as a window on cognitive structure. Cortex2017; 86: 186–204.
12.
McCabeDPRoedigerHLMcDanielMA, et al.The relationship between working memory capacity and executive functioning: evidence for a common executive attention construct. Neuropsychology2010; 24: 222–243.
13.
EngleRW. Working memory capacity as executive attention. Curr Dir Psychol Sci2002; 11: 19–23.
14.
BotvinickMMBraverTSBarchDM, et al.Conflict monitoring and cognitive control. Psychol Rev2001; 108: 624–652.
15.
BalotaDATseC-SHutchisonKA, et al.Predicting conversion to dementia of the Alzheimer’s type in a healthy control sample: the power of errors in Stroop color naming. Psychol Aging2010; 25: 208–218.
16.
DuchekJMBalotaDAThomasJB, et al.Relationship between stroop performance and resting state functional connectivity in cognitively normal older adults. Neuropsychology2013; 27: 516–528.
17.
JackCRKnopmanDSJagustWJ, et al.Update on hypothetical model of Alzheimer’s disease biomarkers. Lancet Neurol2013; 12: 207–216.
18.
BrierMRGordonBFriedrichsenK, et al.Tau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease. Sci Transl Med2016; 8: 338ra66.
19.
MishraSGordonBASuY, et al.AV-1451 PET imaging of tau pathology in preclinical Alzheimer disease: defining a summary measure. Neuroimage2017; 161: 171–178.
20.
PelgrimTADBeranMTwaitEL, et al.Cross-sectional associations of tau protein biomarkers with semantic and episodic memory in older adults without dementia: a systematic review and meta-analysis. Ageing Res Rev2021; 71: 101449.
21.
TannerJARabinoviciGD. Relationship between tau and cognition in the evolution of Alzheimer’s disease: new insights from tau PET. J Nucl Med2021; 62: 612–613.
22.
DickersonBCFeczkoEAugustinackJC, et al.Differential effects of aging and Alzheimer’s disease on medial temporal lobe cortical thickness and surface area. Neurobiol Aging2009; 30: 432–440.
23.
WangLBenzingerTLHassenstabJ, et al.Spatially distinct atrophy is linked to β-amyloid and tau in preclinical Alzheimer disease. Neurology2015; 84: 1254–1260.
24.
OssenkoppeleRSmithROhlssonT, et al.Associations between tau, Aβ, and cortical thickness with cognition in Alzheimer disease. Neurology2019; 92: e601–e612.
25.
SpielerDHBalotaDAFaustME. Stroop performance in healthy younger and older adults and in individuals with dementia of the Alzheimer’s type. J Exp Psychol Hum Percept Perform1996; 22: 461–479.
26.
CastelADBalotaDAHutchisonKA, et al.Spatial attention and response control in healthy younger and older adults and individuals with Alzheimer’s disease: evidence for disproportionate selection impairments in the simon task. Neuropsychology2007; 21: 170–182.
27.
HuffMJBalotaDAMinearM, et al.Dissociative global and local task-switching costs across younger adults, middle-aged adults, older adults, and very mild Alzheimer’s disease individuals. Psychol Aging2015; 30: 727–739.
28.
McKayNSDincerAMehrotraV, et al.Beta-amyloid moderates the relationship between cortical thickness and attentional control in middle- and older-aged adults. Neurobiol Aging2022; 112: 181–190.
29.
GorbachTPudasSLundquistA, et al.Longitudinal association between hippocampus atrophy and episodic-memory decline. Neurobiol Aging2017; 51: 167–176.
30.
MaassALockhartSNHarrisonTM, et al.Entorhinal tau pathology, episodic memory decline, and neurodegeneration in aging. J Neurosci2018; 38: 530–543.
31.
BejaninASchonhautDRLa JoieR, et al.Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer’s disease. Brain2017; 140: 3286–3300.
32.
AschenbrennerAJGordonBAFaganAM, et al.Neurofilament light predicts decline in attention but not episodic memory in preclinical Alzheimer’s disease. J Alzheimers Dis2020; 74: 1119–1129.
33.
DincerAGordonBAHari-RajA, et al.Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease. Neuroimage Clin2020; 28: 102491.
34.
MorrisJC. The clinical dementia rating (CDR): current version and scoring rules. Neurology1993; 43: 2412–2414.
35.
GordonBABlazeyTMChristensenJ, et al.Tau PET in autosomal dominant Alzheimer’s disease: relationship with cognition, dementia and other biomarkers. Brain2019; 142: 1063–1076.
36.
SuYD’AngeloGMVlassenkoAG, et al.Quantitative analysis of PiB-PET with FreeSurfer ROIs. PLoS One2013; 8: e73377.
37.
LimYYSnyderPJPietrzakRH, et al.Sensitivity of composite scores to amyloid burden in preclinical Alzheimer’s disease: introducing the Z-scores of attention, verbal fluency, and episodic memory for nondemented older adults composite score. Alzheimers Dement (Amst)2016; 2: 19–26.
38.
McKayNSMillarPRNicosiaJ, et al.Pick a PACC: comparing domain-specific and general cognitive composites in Alzheimer disease research. Neuropsychology2024; 38: 443–464.
39.
GroberEBuschkeHCrystalH, et al.Screening for dementia by memory testing. Neurology1988; 38: 900–900.
40.
WechslerD. Wechsler memory scale–third edition (WMS-III). San Antonio, TX: The Psychological Corporation, 1997.
41.
CraftSNewcomerJKanneS, et al.Memory improvement following induced hyperinsulinemia in Alzheimer’s disease. Neurobiol Aging1996; 17: 123–130.
42.
MonsellSEDodgeHHZhouX-H, et al.Results from the NACC uniform data set neuropsychological battery crosswalk study. Alzheimer Dis Assoc Disord2016; 30: 134.
43.
CruchagaCKauweJSKMayoK, et al.SNPs associated with cerebrospinal fluid phospho-tau levels influence rate of decline in Alzheimer’s disease. PLoS Genet2010; 6: e1001101.
44.
RStudio Team. RStudio: Integrated development environment for R. Boston, MA: Posit Software, PBC. URL http://www.posit.co/. (2020).
45.
WoodSN. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J R Stat Soc B Stat Method2011; 73: 3–36.
46.
SørensenØWalhovdKBFjellAM. A recipe for accurate estimation of lifespan brain trajectories, distinguishing longitudinal and cohort effects. Neuroimage2021; 226: 117596.
47.
ZuurAFIenoENWalkerNJ, et al.Things are not always linear; additive modelling. In: ZuurAFIenoENWalkerN, et al. (eds) Mixed effects models and extensions in ecology with R. New York, NY: Springer, 2009, pp.35–69.
48.
HeddenTVan DijkKRAShireEH, et al.Failure to modulate attentional control in advanced aging linked to white matter pathology. Cereb Cortex2012; 22: 1038–1051.
49.
DulasMRDuarteA. Aging affects the interaction between attentional control and source memory: an fMRI study. J Cogn Neurosci2014; 26: 2653–2669.
50.
MilhamMPBanichMTClausED, et al.Practice-related effects demonstrate complementary roles of anterior cingulate and prefrontal cortices in attentional control. Neuroimage2003; 18: 483–493.
51.
MilhamMPBanichMTWebbA, et al.The relative involvement of anterior cingulate and prefrontal cortex in attentional control depends on nature of conflict. Cogn Brain Res2001; 12: 467–473.
52.
SchwindtGCBlackSE. Functional imaging studies of episodic memory in Alzheimer’s disease: a quantitative meta-analysis. Neuroimage2009; 45: 181–190.
53.
OssenkoppeleRSchonhautDRSchöllM, et al.Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer’s disease. Brain2016; 139: 1551–1567.
54.
CieslikECMuellerVIEickhoffCR, et al.Three key regions for supervisory attentional control: evidence from neuroimaging meta-analyses. Neurosci Biobehav Rev2015; 48: 22–34.
55.
HopfingerJBBuonocoreMHMangunGR. The neural mechanisms of top-down attentional control. Nat Neurosci2000; 3: 284–291.
56.
AschenbrennerAJGordonBABenzingerTLS, et al.Influence of tau PET, amyloid PET, and hippocampal volume on cognition in Alzheimer disease. Neurology2018; 91: e859–e866.
57.
BucciMChiotisKNordbergA. Alzheimer’s disease profiled by fluid and imaging markers: tau PET best predicts cognitive decline. Mol Psychiatry2021; 26: 5888–5898.
58.
BurggrenACRennerBJonesM, et al.Thickness in entorhinal and subicular cortex predicts episodic memory decline in mild cognitive impairment. Int J Alzheimers Dis2011; 2011: 956053.
59.
DoréVVillemagneVLBourgeatP, et al.Cross-sectional and longitudinal analysis of the relationship between aβ deposition, cortical thickness, and memory in cognitively unimpaired individuals and in Alzheimer disease. JAMA Neurol2013; 70: 903–911.
60.
HassenstabJRuvoloDJasielecM, et al.Absence of practice effects in preclinical Alzheimer’s disease. Neuropsychology2015; 29: 940–948.
61.
BeglingerLJGaydosBTangphao-DanielsO, et al.Practice effects and the use of alternate forms in serial neuropsychological testing. Arch Clin Neuropsychol2005; 20: 517–529.
62.
BurgerLFaySAngelL, et al.Benefit of practice of the Stroop test in young and older adults: pattern of gain and impact of educational level. Exp Aging Res2020; 46: 52–67.
63.
LuethiMSFrieseMBinderJ, et al.Motivational incentives lead to a strong increase in lateral prefrontal activity after self-control exertion. Soc Cogn Affect Neurosci2016; 11: 1618–1626.
64.
IversonGLBrooksBLAshtonVL, et al.Does familiarity with computers affect computerized neuropsychological test performance?J Clin Exp Neuropsychol2009; 31: 594–604.
65.
SperlingRAMorminoECSchultzAP, et al.The impact of amyloid-beta and tau on prospective cognitive decline in older individuals. Ann Neurol2019; 85: 181–193.
66.
SimonSSVarangisELeeS, et al.In vivo tau is associated with change in memory and processing speed, but not reasoning, in cognitively unimpaired older adults. Neurobiol Aging2024; 133: 28–38.
67.
AschenbrennerAJBalotaDAGordonBA, et al.A diffusion model analysis of episodic recognition in preclinical individuals with a family history for Alzheimer’s disease: the adult children study. Neuropsychology2016; 30: 225–238.
68.
Rey-MermetAGadeMOberauerK. Should we stop thinking about inhibition? Searching for individual and age differences in inhibition ability. J Exp Psychol Learn Mem Cogn2018; 44: 501–526.
69.
SimsJRZimmerJAEvansCD, et al.Donanemab in early symptomatic Alzheimer disease: the TRAILBLAZER-ALZ 2 randomized clinical trial. JAMA2023; 330: 512–527.
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