Variance In Cognitive Performance Research Articles

0739 Does Benzodiazepine Receptor Agonist Use, Insomnia, and OSA Explain Variation in Cognitive Performance?

0739 Does Benzodiazepine Receptor Agonist Use, Insomnia, and OSA Explain Variation in Cognitive Performance?

Arousal and performance: revisiting the famous inverted-U-shaped curve

Arousal level is thought to be a key determinant of variability in cognitive performance. In a recent study, Beerendonk, Mejías et al. show that peak performance in decision-making tasks is reached at moderate levels of arousal. They also propose a neurobiologically informed computational model that can explain the inverted-U-shaped relationship.

Effects of a Physical Training Program on Cognitive and Physical Performance and Health-Related Variables in Professional esports Players: A Pilot Study

The present study focused on the effects of a physical training program on physical- and psychological-related variables in professional esports players. Five professional League of Legends (LOL) players belonging to the highest national category participated in this study. Data were obtained before and after a 5 h virtual training session (acute), as well as before and after an 8-week intervention period, focused on decreasing the impact of fatigue on players’ health and performance. The results showed that a complete virtual training session influences their performance, decreasing jump height and joint mobility (p < 0.01), as well as increasing perceived physical and cognitive exertion by 76.9% (p < 0.01) and 166.67% on the “Rating of Fatigue” scale (p = 0.002). Moreover, the intervention was able to reduce the impact of fatigue (30.8% and 43.3% reduction in cognitive and overall fatigue, respectively, p < 0.05), improving, at the same time, the amount of muscle mass by 2%, jumping ability by 9.8% to 21%, and strength levels in various exercises by 63% to 173% (p < 0.01). The implementation of a physical training program is capable of reducing the players’ fatigue perception, improving their physical conditioning and health status, and decreasing the injury risk.

Investigating the Impact of Polypharmacy and Anticholinergic Medication Burden on Objective Cognitive Performance in Adults With Multiple Sclerosis.

Polypharmacy, or the use of 5 or more daily medications, is common in adults with multiple sclerosis (MS), and is often due to various physical, cognitive, and emotional symptoms. However, research regarding the association between polypharmacy and cognitive outcomes in MS is sparse. Furthermore, individuals with MS often use medications with anticholinergic properties, which are commonly associated with cognitive impairment and other central nervous system adverse effects. Currently, the utility of scales measuring anticholinergic burden in MS is unknown. This study aims to investigate the relationship between polypharmacy, anticholinergic burden, and objective cognitive performance in MS. We recruited 90 individuals with MS during routine visits at an MS specialty clinic in Kansas City. Participants completed a brief, virtual cognitive assessment and answered questions about their health. Participants provided their medication lists from which we determined polypharmacy and scores on several anticholinergic burden scales. Statistical analyses included Spearman correlations and linear regression models. Approximately 44% of the individuals surveyed met the criteria for polypharmacy. The number of daily medications was negatively correlated with cognitive performance (rs = -0.45, P < .001). Further, the Drug Burden Index accounted for additional variance in cognitive performance beyond that explained by age, education, MS disease duration, and comorbidities [ΔR2 = .12, F(5, 84) = 7.84, P < .001.]. Clinicians should consider the possible negative consequences of polypharmacy when addressing cognitive concerns in MS. Anticholinergic burden scales may be valuable in this regard. Future investigations could explore behavioral and pharmacological interventions aimed at reducing polypharmacy in MS.

Heritability of cognitive performance in wild Western Australian magpies.

Individual differences in cognitive performance can have genetic, social and environmental components. Most research on the heritability of cognitive traits comes from humans or captive non-human animals, while less attention has been given to wild populations. Western Australian magpies (Gymnorhina tibicen dorsalis, hereafter magpies) show phenotypic variation in cognitive performance, which affects reproductive success. Despite high levels of individual repeatability, we do not know whether cognitive performance is heritable in this species. Here, we quantify the broad-sense heritability of associative learning ability in a wild population of Western Australian magpies. Specifically, we explore whether offspring associative learning performance is predicted by maternal associative learning performance or by the social environment (group size) when tested at three time points during the first year of life. We found little evidence that offspring associative learning performance is heritable, with an estimated broad-sense heritability of just -0.046 ± 0.084 (confidence interval: -0.234/0.140). However, complementing previous findings, we find that at 300 days post-fledging, individuals raised in larger groups passed the test in fewer trials compared with individuals from small groups. Our results highlight the pivotal influence of the social environment on cognitive development.

Gray and White Matter Metrics Demonstrate Distinct and Complementary Prediction of Differences in Cognitive Performance in Children: Findings from ABCD (N = 11,876).

Individual differences in cognitive performance in childhood are a key predictor of significant life outcomes such as educational attainment and mental health. Differences in cognitive ability are governed in part by variations in brain structure. However, studies commonly focus on either gray or white matter metrics in humans, leaving open the key question as to whether gray or white matter microstructure plays distinct or complementary roles supporting cognitive performance. To compare the role of gray and white matter in supporting cognitive performance, we used regularized structural equation models to predict cognitive performance with gray and white matter measures. Specifically, we compared how gray matter (volume, cortical thickness, and surface area) and white matter measures (volume, fractional anisotropy, and mean diffusivity) predicted individual differences in cognitive performance. The models were tested in 11,876 children (ABCD Study; 5,680 female, 6,196 male) at 10 years old. We found that gray and white matter metrics bring partly nonoverlapping information to predict cognitive performance. The models with only gray or white matter explained respectively 15.4 and 12.4% of the variance in cognitive performance, while the combined model explained 19.0%. Zooming in, we additionally found that different metrics within gray and white matter had different predictive power and that the tracts/regions that were most predictive of cognitive performance differed across metrics. These results show that studies focusing on a single metric in either gray or white matter to study the link between brain structure and cognitive performance are missing a key part of the equation.

Personality traits and cognitive reserve—High openness benefits cognition in the presence of age-related brain changes

Cognitive reserve explains differential susceptibility of cognitive performance to neuropathology. We investigated whether certain personality traits underlie cognitive reserve and are accordingly associated with better cognition and less cognitive decline in the presence of age-related brain changes. We included healthy adults aged 19–80 years for cross-sectional (N=399) and longitudinal (N=273, mean follow-up time=5 years, SD=0.7 years) analyses. Assessment of the BIG5 personality traits openness, conscientiousness, extraversion, agreeableness, and neuroticism was questionnaire-based. Each cognitive domain (perceptual speed, memory, fluid reasoning, vocabulary) was measured with up to six tasks. Cognitive domain-specific brain status variables were obtained by combining 77 structural brain measures into single scores using elastic net regularization. These brain status variables explained up to 43.1% of the variance in cognitive performance. We found that higher openness was associated with higher fluid reasoning and better vocabulary after controlling for brain status, age, and sex. Further, lower brain status was associated with a greater decline in perceptual speed only in individuals with low openness. We conclude that high openness benefits cognitive reserve.

NUTRITIONAL AND SOCIOECONOMIC DETERMINANTS OF COGNITIVE STATUS AND SELF-ESTEEM AMONG SCHOOLCHILDREN IN THE URBAN AREA OF KENITRA (MOROCCO)

Low cognitive performance and low self-esteem can be influenced by nutritional factors, such as dietary deficiencies, as well as socio-economic aspects including the level of education and economic status. These elements can interact in complex ways, contributing to variations in cognitive performance and self-es- teem. It is important to consider all aspects of mental and physical health to fully understand this relationship.A sample of 174 urban schoolchildren, aged between 15 and 19, and hailing from modest socio-economic backgrounds, participated in the study. They underwent a cognitive test (the Raven test) to evaluate their intellectual induction abilities. Additionally, a questionnaire was administered to gauge their socio-economic status. Nutritional status was assessed through various indices, including weight, height, and indicators such as weight-for-age, height-for-age, and emaciation. Self-esteem was measured using the French translation of Pelham and Swann’s self-assessment questionnaire, completed by the students.Neurocognitive abilities exhibited significant correlations with gender, mathematical performance, nutritional status, and the educational level of mothers. Conversely, self-esteem demonstrated correlations with parental education levels and the presence of emaciation.The results of this study highlight a significant relation between malnutrition and neurocognitive abilities, as well as self-esteem in schoolgirls. These findings suggest that nutritional management could play an essential role in preventing self-esteem problems and cognitive difficulties among schoolchildren.

The effect of last meal "Suhoor" timing on diurnal variations in cognitive performance during Ramadan fasting among female athletes.

The present study aimed to investigate the effect of the timing of the last meal, "Suhoor", on diurnal variation in cognitive performance during Ramadan intermittent fasting (RIF). In a randomized order, 26 adolescent female athletes (aged 15.9 ± 0.9 y) were tested in three sessions at 7:00 a.m., 12:00 p.m., and 5:00 p.m. across four different conditions: the 10 days preceding Ramadan (PR); the final 12 days of Ramadan (RO): two different conditions: Early Suhoor (SEarly), and Late Suhoor (SLate); and, ultimately, the 10 days immediately after Ramadan (AR) with an in-between recovery period of ≥24 h. During each test session, the oral temperature (OT), simple reaction time test (SRT), choice reaction time test (CRT), attention test (ATT), and mental rotation test (MRT) were evaluated. The Pittsburgh Sleep Quality Index (PSQI) and daily diary intake were assessed across the three periods. Compared to PR, the sleep parameters assessed by the PSQI were significantly lower during the RO and AR periods. However, neither total dietary intake nor OT showed any changes due to RIF. Compared to PR, the afternoon performances of SRT, CRT, ATT, and MRT significantly declined under both the SEarly and SLate conditions. Notably, midday performance decreased only during SLate, while morning performance remained unaffected in both conditions. Additionally, compared to SEarly, these performances were better during SLate in the afternoon and at midday. In summary, nutrient intake timing had a significant effect on the diurnal fluctuations in cognitive functions during Ramadan fasting, particularly around noon and in the afternoon. Our results illustrate the benefits of a late last meal (Suhoor) in preserving optimal morning cognitive abilities and preventing any impairment during the fasted state at midday or in the afternoon, which could affect overall athletic performance.

Relationships between hourly cognitive variability and risk of Alzheimer's disease revealed with mixed-effects location scale models.

Observational studies on aging and Alzheimer's disease (AD) typically focus on mean-level changes in cognitive performance over relatively long periods of time (years or decades). Additionally, some studies have examined how trial-level fluctuations in speeded reaction time are related to both age and AD. The aim of the current project was to describe patterns of variability across repeated days of testing as a function of AD risk in cognitively normal older adults. The current project examined the performance of the Ambulatory Research in Cognition (ARC) smartphone application, a high-frequency remote cognitive assessment paradigm, that administers brief tests of episodic memory, spatial working memory, and processing speed. Bayesian mixed-effects location scale models were used to explore differences in mean cognitive performance and intraindividual variability across 28 repeated sessions over a 1-week assessment interval as function of age and genetic risk of AD, specifically the presence of at least one apolipoprotein E (APOE) ε4 allele. Mean performance on processing speed and working memory was negatively related to age and APOE status. More importantly, e4 carriers exhibited increased session-level variability on a test of processing speed compared to noncarriers. Age and education did not consistently relate to cognitive variability, contrary to expectations. Preclinical AD risk, defined as possessing at least one APOE ε4 allele, is not only associated with mean-level performance differences, but also with increases in variability across repeated testing occasions particularly on a test of processing speed. Thus, cognitive variability may serve as an additional and important indicator of AD risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

USING HIGH-FREQUENCY ASSESSMENTS TO EXPLORE WITHIN-PERSON COUPLING OF PSYCHOLOGICAL STATES AND COGNITION

Abstract From the perspective of traditional assessment approaches, variation in cognitive performance due to participant factors (e.g. mood, fatigue) are treated as part of measurement error. This talk will discuss how high-frequency assessment methods, such as ecological momentary assessment (EMA), can be leveraged to capture meaningful signal from variation in cognitive performance. This approach will be used to explore fluctuations in thought valence and levels of arousal as short-term mechanisms for change in working memory and processing speed performance. Participants (n = 265, aged 25-65, 64.9% female) completed a 14-day measurement burst that included five EMAs per day. Each EMA included self-report measures of current thought valence (pleasant-unpleasant) and level of arousal (sleepy/tired-alert/active), as well as two brief cognitive tasks. We use multi-level modelling to disaggregate between- and within-person effects of thought valence and arousal, and to examine within-person coupling with performance on each of the cognitive tasks. Models also include demographic and contextual covariates (e.g. current location), as well as linear and quadratic functions of time and session number to account for time of day and retest effects. We found that at moments when individuals were experiencing more unpleasant thoughts than usual for them, they also made more errors on the working memory task. Additionally, at moments where individuals were feeling more sleepy/tired than usual for them, they performed more slowly on the processing speed task. These results will be discussed from the perspective of using models of within-person coupling to understand short-term mechanisms for cognitive change.

AGE-VARYING COGNITIVE IMPAIRMENT AND SOCIAL SUPPORT AMONG PEOPLE AGING WITH AND WITHOUT HIV

Abstract There is compelling but limited evidence that the combination of HIV, methamphetamine (meth) use, and aging form a deleterious trio that undermines cognitive functioning. Currently, a gap exists in our understanding of the intertwining relationships among drug use, HIV, and cognitive function across biological ages and over time. Interventions to reduce meth use and support brain health among aging PWH are vital and improving social relationships is a promising area of intervention. Cross-sectional and limited longitudinal studies indicate that positive social relationships and social support are associated with better cognitive function among healthy older populations. This association has received limited attention among PWH who use drugs beyond adolescence and young adulthood. This study leverages NIH’s prior and ongoing investments in research to develop a new analytic cohort by combining participants from 23 studies at the HIV Neurobehavioral Research program. Enrollment in this cohort spans from 2009-2021. At baseline, our sample consists of 862 people with a mean age of 52 (range 18-81). Most participants are male (73%), White (74%), and over half (61%) are living with HIV. Using a life course perspective and time-varying estimation modeling, we examine age-varying cognitive impairment and variation in cognitive function across age by HIV status, meth use, and social relationships. First, we examine how cognitive impairment changes over time for the full sample then examine the differing transitions/turning points among those aging with and without HIV and meth use. Lastly, we show how positive and negative social relationships alter these trajectories among each group.

Peering further into the mind's eye: combining visual evoked potential and optical coherence tomography measures enhances insight into the variance in cognitive functioning in multiple sclerosis.

Spectral Optical Coherence Tomography (OCT) and Visual Evoked Potentials (VEPs) have both emerged as potentially useful biomarkers of cognitive decline in people with multiple sclerosis (PwMS). Their combined use may provide additional predictive value for identifying disease impact, progression, and remyelination capacity above-and-beyond what is captured using either approach alone. We examined the relationship between OCT/VEP measures and cognitive functioning in 205 PwMS. OCT measures included Retinal Nerve Fiber Layer Volume (RNFLV), Papillo-Macular Bundle Volume (PBMV), and Macular Volume (MV). VEP measures included latency of the P100, and inter-ocular latency. Cognitive performance was evaluated across seven separate domains of performance, and for overall cognition, using the NeuroTrax computerized testing battery. Both OCT and VEP measures were significantly correlated with cognitive performance across several domains. Linear regression models that controlled for the influence of visual acuity revealed (1) that reduced MV was significantly predictive of poorer visual-spatial functioning, and (2) that delayed VEP latency was significantly predictive of performance in global cognitive functioning and visual-spatial functioning, after controlling for multiple comparisons. Among PwMS with normal visual acuity, PwMS with a combination of both relatively low MV and delayed VEP latency tended to have poorer performance in the domains of global, executive, and visual-spatial functioning compared to PwMS with both high MV and normal VEP latency. Approaches that combine the use of OCT and VEP measures can enhance insight into underlying factors that contribute to variance in cognitive functioning in PwMS.

Multi-modal neuroimaging signatures predict cognitive decline in multiple sclerosis: A 5-year longitudinal study

BackgroundCognitive impairment is a hallmark of multiple sclerosis (MS) but is usually an under-recorded symptom of disease progression. Identifying the predictive signatures of cognitive decline in people with MS (pwMS) over time is important to ensure effective preventative treatment strategies. Structural and functional brain characteristics as measured by various magnetic resonance (MR) methods have been correlated with variation in cognitive function in MS, but typically these studies are limited to a single MR modality and/or are cross-sectional designs. Here we assess the predictive value of multiple different MR modalities in relation to cognitive decline in pwMS over 5 years. MethodsA cohort of 43 pwMS was assessed at baseline and 5 years follow-up. Baseline (input) data consisted of 70 multi-modal MRI measures for different brain regions including magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and standard volumetrics. Age, sex, disease duration and treatment were included as clinical inputs. Cognitive function was assessed using the Audio Recorded Cognitive Screen (ARCS) and the Symbol Digit Modalities Test (SDMT). Prediction modelling was performed using the machine learning package - GLMnet, where a penalised regression was applied to identify multi-modal signatures with the most predictive value (and the least error) for each outcome. ResultsThe multi-modal approach to neuroimaging was able to accurately predict cognitive decline in pwMS. The best performing model for change in total ARCS (tARCS) included 16 features from across the various MR modalities and explained 54 % of the variation in change over time (R2=0.54, 95 % CI=0.48–0.51). The features included nine MRS, four volumetric and two DTI parameters. The model also selected disease duration, but not treatment, as a predictive feature. By comparison, the best model for SDMT included several of the same above features and explained 39 % of the change over time (R2=0.39, 95 % CI=0.48–0.51). Conventional volumetric measures were about half as good at predicting change in tARCS score compared to the best multi-modal model (R2=0.26 95 % CI:0.22–0.29). The clinical interpretation of the best predictive model for change in tARCS showed that cognitive decline could be predicted with >90 % accuracy in this cohort (AUC=0.92, SE=0.86 - 0.94). ConclusionMulti-modal MRI signatures can predict cognitive decline in a cohort of pwMS over 5 years with high accuracy. Future studies will benefit from the inclusion of even more MR modalities e.g., functional MRI, quantitative susceptibility mapping, magnetisation transfer imaging, as well as other potential predictors e.g., genetic and environmental factors. With further validation, this signature could be used in future trials with high-risk patients to personalise the management of cognitive decline in pwMS, even in the absence of relapses.

The Association between Education and Cognitive Performance Varies at Different Levels of Cognitive Performance: A Quantile Regression Approach

Introduction: Educational differences in cognitive performance among older adults are well documented. Studies that explore this association typically estimate a single average effect of education on cognitive performance. We argue that the processes that contribute to the association between education and cognitive performance are unlikely to have equal effects at all levels of cognitive performance. In this study, we employ an analytical approach that enables us to go beyond averages to examine the association between education and five measures of global and domain-specific cognitive performance across the outcome distributions. Methods: This cross-sectional study included 1,780 older adults aged 58–68 years from the Longitudinal Aging Study Amsterdam. Conditional quantile regression was used to examine variation across the outcome distribution. Cognitive outcomes included Mini-Mental State Examination (MMSE) score, crystallized intelligence, information processing speed, episodic memory, and a composite score of global cognitive performance. Results: The results showed that the associations between education and different cognitive measures varied across the outcome distributions. Specifically, we found that education had a stronger association with crystallized intelligence, MMSE, and a composite cognitive performance measure in the lower tail of performance distributions. The associations between education and information processing speed and episodic memory were uniform across the outcome distributions. Conclusion: Larger associations between education and some domains of cognitive performance in the lower tail of the performance distributions imply that inequalities are primarily generated among individuals with lower performance rather than among average and high performers. Additionally, the varying associations across some of the outcome distributions indicate that estimating a single average effect through standard regression methods may overlook variations in cognitive performance between educational groups. Future studies should consider heterogeneity across the outcome distribution.

Risk Polymorphisms of FNDC5, BDNF, and NTRK2 and Poor Education Interact and Aggravate Age-Related Cognitive Decline.

Cognitive abilities tend to decline with aging, with variation between individuals, and many studies seek to identify genetic biomarkers that more accurately anticipate risks related to pathological aging. We investigated the influence of BDNF, NTRK2, and FNDC5 single nucleotide polymorphisms (SNPs) on the cognitive performance of young and older adults with contrasting educational backgrounds. We addressed three questions: (1) Is education associated with reduced age-related cognitive decline? (2) Does the presence of SNPs explain the variation in cognitive performance observed late in life? (3) Is education differentially associated with cognition based on the presence of BDNF, NTRK2, or FNDC5 polymorphisms? We measured the cognitive functions of young and older participants, with lower and higher education, using specific and sensitive tests of the Cambridge Automated Neuropsychological Test Assessment Battery. A three-way ANOVA revealed that SNPs were associated with differential performances in executive functions, episodic memory, sustained attention, mental and motor response speed, and visual recognition memory and that higher educational levels improved the affected cognitive functions. The results revealed that distinct SNPs affect cognition late in life differentially, suggesting their utility as potential biomarkers and emphasizing the importance of cognitive stimulation that advanced education early in life provides.

Within‐Day Variability in Mobile Cognitive Assessments: Associations with Mild Cognitive Impairment and Sociodemographic Factors

AbstractBackgroundGreater within‐person variability in cognitive performance on mobile devices is emerging as a sensitive marker of mild cognitive impairment (MCI). It is unclear if sociodemographic differences are associated with this variability, and if so, whether these differences moderate associations between MCI status and within‐person variability. We use a digital health approach with ecological momentary assessments (EMA) to examine sociodemographic differences in within‐day variability among individuals with MCI and those who were cognitively unimpaired (CU).MethodA sample of 308 community‐dwelling older adults from the Einstein Aging Study (mean age = 77.49 years, SD = 4.86, range = 70‐90; 67% female; 45% non‐Hispanic White, 41% non‐Hispanic Black) completed neuropsychological testing and self‐reported questionnaires. Ninety‐eight individuals met Jak/Bondi criteria for MCI. All participants performed mobile tests of processing speed and memory binding on a smartphone up to six times daily over a two‐week period. We employed heterogeneous variance multilevel models to assess sociodemographic and MCI status associations with within‐day variability across assessments. We further tested whether differences in age, gender, race, and education moderated associations between MCI status and within‐day variability.ResultFor processing speed, greater variability was apparent in individuals with MCI, non‐Hispanic Black participants, and individuals with less education (ps&lt;.001). A MCI status*gender interaction occurred; the association between MCI status and variability remained significant for both genders but was smaller among women (p&lt;.01). For memory binding, greater variability was apparent in individuals with MCI, older participants, non‐Hispanic Black participants, and individuals with less education (ps&lt;.001). Numerous interactions occurred; in separate analyses, associations between MCI status and variability remained significant, but were smaller among women, non‐Hispanic Black participants, and individuals with less education (ps&lt;.05).ConclusionIndividuals with MCI exhibited greater within‐day variability in mobile cognitive performance than those who were CU, but the strength of these associations varied by sociodemographic factors. These indices of variability in everyday life may serve as sensitive markers of early cognitive impairment. Future research should examine daily mechanisms and environmental perturbations (e.g., stress, sleep, air pollution) that may explain why associations between MCI status and cognitive variability appeared smaller among women, non‐Hispanic Black participants, and individuals with less education.

A Study on the effects of seasonal variations in cognitive function on driving behaviour.

AbstractBackgroundThe population in Japan is ageing, and approximately 30% of the elderly are said to have Alzheimer’s disease. On the other hand, however, there are areas with insufficient transport services due to the declining birth rate, and the elderly have to drive cars. In order to reduce accidents caused by drivers with dementia, it is necessary to know the relationship between cognitive function and driving, but cognitive function is said to fluctuate daily. The aim of this study is to obtain knowledge that contributes to the prediction of accidents by observing the seasonal variation in cognitive function and driving using the same subjects.MethodA cognitive function test, a driving skill test at a driving school and an observation 1‐month survey of driving behaviour on public open roads were conducted on 40 drivers aged 70 years or older who drive their cars daily. The survey was conducted twice on the same subjects, once between April and June and once between October and December. From the data obtained, seasonal differences were verified.ResultIt is said that elderly drivers often drive short distances in their neighbourhood, but in reality they also make long trips. Comparing spring/summer and autumn/winter, autumn/winter drivers are more likely to be in a state of cognitive decline and drive more unevenly.ConclusionCognitive function and driving behaviour of older drivers differ depending on the season. As the passage of time and more short‐term fluctuations may have an impact, it is important to systematise the fluctuating changes in various cycles and link them to safe driving support.

Cohort heterogeneity and AD biomarkers in older adults without significant cognitive impairment: A comparison of U.S. POINTER and ADNI

AbstractBackgroundA key focus of the U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is recruitment of unimpaired older individuals at risk for cognitive decline with heterogeneous characteristics (under‐represented racial and ethnicity groups (URG), family history of cognitive decline, hypertension, geographic diversity), and a subset of individuals undergo PET and MRI.MethodTo examine effects of heterogeneity on relationships between risk factors, AD biomarkers (Aß and entorhinal tau PET, hippocampal volume (HV)) and cognition (global, executive function, and memory) were examined from U.S. POINTER neuroimaging participants (N = 602, about 65% of the anticipated total sample) and a subset of Alzheimer’s Disease Neuroimaging Initiative participants (N = 503). Neuroimaging data were processed and analyzed using harmonized methods across studies. Some cohort‐specific measurements were standardized using a within‐cohort reference group (Aß‐negative individuals &lt;70yrs and with global CDR = 0).ResultU.S. POINTER imaging participants are younger than those in ADNI (68.6+/‐5.0yrs vs 70.7+/‐4.4yrs), more likely to be female (65% vs 58%) and from URG (27% vs 15%), and had lower education (14.7+/‐3.3yrs vs 16.7+/‐2.3yrs) and higher Framingham Cardiovascular Risk scores (9.9+/‐8.3 vs 7.7+/‐5.3). The groups differed on several AD biomarkers and cognitive measures (Table). In regression models, AD biomarkers were stronger predictors of cognitive performance in ADNI compared to POINTER. Specifically, Aß+ individuals with elevated tau had disproportionately poorer cognitive performance in ADNI, and this relationship remained consistent across cognitive measures (Figure). Conversely, demographic/risk variables were stronger predictors in POINTER. Demographic/risk predictors (age, sex, education, race, and FRS) together explained twice as much variance in global cognition in POINTER compared to ADNI (Adjusted R2 = 29% vs 14%). The addition of AD biomarkers to the model further increased the amount of variance in global cognition explained from 14% to 34% in ADNI, but addition of AD biomarkers did not increase variance explained in the POINTER model.ConclusionHeterogeneity among study participants appears to influence baseline biomarker‐cognition relationships such that AD biomarkers explain more variability in cognitive performance in ADNI than POINTER. These findings further suggest that cohort characteristics may affect the potential influence of amyloid‐ and tau‐modifying treatments on cognition.

Naturalistic Assessment of Reaction Time Variability in Older Adults at Risk for Alzheimer’s Disease

AbstractBackgroundBreakdowns in attentional control may underscore cognitive changes seen in the earliest stages of Alzheimer’s disease (AD). One way to measure these changes is to assess variability in cognitive performance. Variability in cognition may be most evident when repeatedly sampled over hours or days and in different environmental contexts or at different times of day. We analyzed data from an ongoing smartphone‐based study of cognition in AD which utilizes extremely brief cognitive tests taken remotely over several days in natural environments.MethodOlder adults (N = 319, aged 75 +/‐ 5 years) completed repeated cognitive testing on the Ambulatory Research in Cognition (ARC) platform and had CSF or PET amyloid biomarkers and APOE genotype available. RTSD was assessed in a brief processing speed task by taking the SD of correct RTs. All models adjusted for baseline age, education, and gender.ResultAveraging across sessions, symptomatic participants (indicated by Clinical Dementia Rating® (CDR®) &gt; 0) showed more variability than asymptomatic (CDR 0) participants (p = 0.009). APOE ε4 carriers showed more variability than non‐carriers, although this was not significant (p = 0.067). More fine‐grained models considered RTSD within each session (e.g. from trial‐to‐trial) using mixed effects models. Symptomatic participants exhibited greater trial‐to‐trial RTSD compared to asymptomatic participants (p = 0.001). APOE ε4 carriers also exhibited greater trial‐to‐trial RTSD compared to non‐carriers (p = 0.004). When limiting the sample to asymptomatic participants to determine if there were changes in the preclinical stage of AD, there remained a strong APOE ε4 effect, with carriers exhibiting greater trial‐to‐trial RTSD than non‐carriers (p = 0.005). Interestingly, amyloid was not significant in any models.ConclusionOlder adults at risk for AD show increased RTSD even in brief assessments. These subtle fluctuations in attention were most evident in APOE e4 carriers at very short time intervals, and less so when averaged across trials and sessions. Overall, these findings suggest that fluctuations in attention in preclinical AD are most evident from moment to moment, highlighting the need for fine‐grained and repeated assessment of attentional control.