Utility of the NIH Toolbox for assessment of prodromal Alzheimer's disease and dementia

Neurovascular coupling, functional connectivity, and cerebrovascular endothelial extracellular vesicles as biomarkers of mild cognitive impairment

INTRODUCTION

Mild cognitive impairment (MCI) is a prodromal stage of dementia. Understanding the mechanistic changes from healthy aging to MCI is critical for comprehending disease progression and enabling preventative intervention.

METHODS

Patients with MCI and age-matched controls (CN) were administered cognitive tasks during functional near-infrared spectroscopy (fNIRS) recording, and changes in plasma levels of extracellular vesicles (EVs) were assessed using small-particle flow cytometry.

RESULTS

Neurovascular coupling (NVC) and functional connectivity (FC) were decreased in MCI compared to CN, prominently in the left-dorsolateral prefrontal cortex (LDLPFC). We observed an increased ratio of cerebrovascular endothelial EVs (CEEVs) to total endothelial EVs in patients with MCI compared to CN, correlating with structural MRI small vessel ischemic damage in MCI. LDLPFC NVC, CEEV ratio, and LDLPFC FC had the highest feature importance in the random Forest group classification.

DISCUSSION

NVC, CEEVs, and FC predict MCI diagnosis, indicating their potential as markers for MCI cerebrovascular pathology.

HIGHLIGHTS

Neurovascular coupling (NVC) is impaired in mild cognitive impairment (MCI). Functional connectivity (FC) compensation mechanism is lost in MCI. Cerebrovascular endothelial extracellular vesicles (CEEVs) are increased in MCI. CEEV load strongly associates with cerebral small vessel ischemic lesions in MCI. NVC, CEEVs, and FC predict MCI diagnosis over demographic and comorbidity factors.

Measuring Multidimensional Aspects of Health in the Oldest Old Using the NIH Toolbox: Results From the ARMADA Study

OBJECTIVE

The percentage of older adults living into their 80s and beyond is expanding rapidly. Characterization of typical cognitive performance in this population is complicated by a dearth of normative data for the oldest old. Additionally, little attention has been paid to other aspects of health, such as motor, sensory, and emotional functioning, that may interact with cognitive changes to predict quality of life and well-being. The current study used the NIH Toolbox (NIHTB) to determine age group differences between persons aged 65-84 and 85+ with normal cognition.

METHOD

Participants were recruited in two age bands (i.e., 65-84 and 85+). All participants completed the NIHTB Cognition, Motor, Sensation, and Emotion modules. Independent-samples t-tests determined age group differences with post-hoc adjustments using Bonferroni corrections. All subtest and composite scores were then regressed on age and other demographic covariates.

RESULTS

The 65-84 group obtained significantly higher scores than the 85+ group across all cognitive measures except oral reading, all motor measures except gait speed, and all sensation measures except pain interference. Age remained a significant predictor after controlling for covariates. Age was not significantly associated with differences in emotion scores.

CONCLUSIONS

Results support the use of the NIHTB in persons over 85 with normal cognition. As expected, fluid reasoning abilities and certain motor and sensory functions decreased with age in the oldest old. Inclusion of motor and sensation batteries is warranted when studying trajectories of aging in the oldest old to allow for multidimensional characterization of health.

Utility of the NIH Toolbox Cognition Battery in middle to older aged adults with longstanding type 1 diabetes: The DCCT/EDIC study

Objective: Adults with type 1 diabetes (T1D) face an increased risk for cognitive decline and dementia. Diabetes-related and vascular risk factors have been linked to cognitive decline using detailed neuropsychological testing; however, it is unclear if cognitive screening batteries can detect cognitive changes associated with aging in T1D. Method: 1,049 participants with T1D (median age 59 years; range 43-74) from the Diabetes Control and Complications Trial (DCCT), and the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study, completed the NIH Toolbox Cognition Battery (NIHTB-C) and Montreal Cognitive Assessment (MoCA). Neuropsychological assessments, depression, glycated hemoglobin levels (HbA1c), severe hypoglycemia, T1D complications, and vascular risk factors were assessed repeatedly over 32 years to determine associations with current NIHTB-C performance. Available cognitive data was clinically adjudicated to determine cognitive impairment status. Results: NIHTB-C scores had moderate associations (r = 0.36-0.53) with concurrently administered neuropsychological tests. In multivariate models, prior severe hypoglycemic episodes, depression symptoms, nephropathy, lower BMI, and higher HbA1c and LDL cholesterol were associated with poorer NIHTB-C Fluid Cognition Composite scores. The NIHTB-C adequately detected adjudicated cognitive impairment (Area Under the Curve = 0.86; optimal cut score ≤90). The MoCA performed similarly (Area Under the Curve = 0.83; optimal cut score ≤25). Conclusions: The NIHTB-C is sensitive to the cognitive effects of diabetes-related and vascular risk factors, correlated with neuropsychological testing, and accurately detects adjudicated cognitive impairment. These data support its use as a screening test in middle to older aged adults with T1D to determine if referral for detailed neuropsychological assessment is needed.

Protocol for a single-arm, pilot trial of creatine monohydrate supplementation in patients with Alzheimer's disease

BACKGROUND

Impaired brain bioenergetics is a pathological hallmark of Alzheimer's disease (AD) and is a compelling target for AD treatment. Patients with AD exhibit dysfunction in the brain creatine (Cr) system, which is integral in maintaining bioenergetic flux. Recent studies in AD mouse models suggest Cr supplementation improves brain mitochondrial function and may be protective of AD peptide pathology and cognition.

AIMS

The Creatine to Augment Bioenergetics in Alzheimer's disease (CABA) study is designed to primarily assess the feasibility of supplementation with 20 g/day of creatine monohydrate (CrM) in patients with cognitive impairment due to AD. Secondary aims are designed to generate preliminary data investigating changes in brain Cr levels, cognition, peripheral and brain mitochondrial function, and muscle strength and size.

METHODS

CABA is an 8-week, single-arm pilot study that will recruit 20 patients with cognitive impairment due to AD. Participants attend five in-person study visits: two visits at baseline to conduct screening and baseline assessments, a 4-week visit, and two 8-week visits. Outcomes assessment includes recruitment, retention, and compliance, cognitive testing, magnetic resonance spectroscopy of brain metabolites, platelet and lymphocyte mitochondrial function, and muscle strength and morphology at baseline and 8 weeks.

DISCUSSION

CABA is the first study to investigate CrM as a potential treatment in patients with AD. The pilot data generated by this study are pertinent to inform the design of future large-scale efficacy trials.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT05383833 , registered on 20 May 2022.

Construct validation of NIH Toolbox Cognition Battery premorbid cognitive functioning scores in Black and White older Americans with and without mild cognitive impairment

OBJECTIVE

Valid estimates of premorbid cognitive functioning (PMIQ) are crucial for the assessment of older adults at risk for Alzheimer's disease. We investigated the relationship between the NIH Toolbox-Cognition Battery's (NIHTB-CB) Oral Reading Recognition (ORR) subtest and Wechsler Test of Adult Reading scores (WTAR, convergent validity). We also compared ORR to NIHTB-CB Flanker scores, where null relationships were expected (discriminant validity).

METHODS

The WTAR and NIHTB-CB were administered to 130 cognitively normal (CN) and 113 participants with mild cognitive impairment (MCI). Participants were community-dwelling, older Black and White adults, ages 55-88 years. Data analysis used uncorrected standard scores and Bayesian bivariate correlations. Supplemental materials include intraclass correlations.

RESULTS

ORR and WTAR scores were strongly positively associated, while ORR and Flanker scores were unrelated. This pattern held when restricting analyses to the two cognitive status groups, the two racial groups, and the four race-by-diagnosis subgroups.

CONCLUSION

The findings demonstrate convergent and discriminant validity and support NIHTB-CB ORR scores as valid estimates of scores on a PMIQ measure in older Black and White adults with and without MCI.

Psychometric properties of the NIH Toolbox Cognition and Emotion Batteries among children and adolescents with congenital heart defects

The NIH Toolbox offers brief, computerized measures of cognitive and psychosocial functioning. However, its psychometric properties were established among typically developing children and adolescents. The current study provides the first comprehensive assessment of its psychometric properties among young patients with congenital heart defects (CHD). We prospectively recruited 58 patients with CHD and 80 healthy controls between the ages of 6 and 17. Participants completed the NIH Toolbox Cognition and Emotion Batteries, a battery of clinician-administered neuropsychological tests, and ratings of their quality of life. Their parents also completed ratings of their functioning. On the Cognition Battery, we found expectable group differences and developmentally expected gains across ages. For the most part, composites and subtests were significantly correlated with neuropsychological measures of similar constructs. Higher scores were generally associated with ratings of better day-to-day functioning among children with CHD. On the Emotion Battery, we found no significant group differences, echoing prior research. For the most part, scales showed acceptable internal consistency among both groups. There was adequate construct coherence for most of questionnaires among healthy control but not participants with CHD. Correlations with a comparison tool were largely within expectable directions. The NIH Toolbox may provide a valid and useful assessment of cognitive functioning among youths with CHD. While it may offer reliable and valid scales of psychosocial functioning, further research is needed to understand the meaningfulness of the scales for participants with CHD.

Predicting Brain Amyloid Status Using the National Institute of Health Toolbox (NIHTB) for Assessment of Neurological and Behavioral Function

BACKGROUND

Amyloid-beta (Aβ) plaque is a neuropathological hallmark of Alzheimer's disease (AD). As anti-amyloid monoclonal antibodies enter the market, predicting brain amyloid status is critical to determine treatment eligibility.

OBJECTIVE

To predict brain amyloid status utilizing machine learning approaches in the Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA) study.

DESIGN

ARMADA is a multisite study that implemented the National Institute of Health Toolbox for Assessment of Neurological and Behavioral Function (NIHTB) in older adults with different cognitive ability levels (normal, mild cognitive impairment, early-stage dementia of the AD type).

SETTING

Participants across various sites were involved in the ARMADA study for validating the NIHTB.

PARTICIPANTS

199 ARMADA participants had either PET or CSF information (mean age 76.3 ± 7.7, 51.3% women, 42.3% some or complete college education, 50.3% graduate education, 88.9% White, 33.2% with positive AD biomarkers).

MEASUREMENTS

We used cognition, emotion, motor, sensation scores from NIHTB, and demographics to predict amyloid status measured by PET or CSF. We applied LASSO and random forest models and used the area under the receiver operating curve (AUROC) to evaluate the ability to identify amyloid positivity.

RESULTS

The random forest model reached AUROC of 0.74 with higher specificity than sensitivity (AUROC 95% CI:0.73 - 0.76, Sensitivity 0.50, Specificity 0.88) on the held-out test set; higher than the LASSO model (0.68 (95% CI:0.68 - 0.69)). The 10 features with the highest importance from the random forest model are: picture sequence memory, cognition total composite, cognition fluid composite, list sorting working memory, words-in-noise test (hearing), pattern comparison processing speed, odor identification, 2-minutes-walk endurance, 4-meter walk gait speed, and picture vocabulary. Overall, our model revealed the validity of measurements in cognition, motor, and sensation domains, in associating with AD biomarkers.

CONCLUSION

Our results support the utilization of the NIH toolbox as an efficient and standardizable AD biomarker measurement that is better at identifying amyloid negative (i.e., high specificity) than positive cases (i.e., low sensitivity).

Mild Cognitive Impairment Subtype Performance in Comparison to Healthy Older Controls on the NIH Toolbox and Cogstate

BACKGROUND

Early detection is necessary for the treatment of dementia. Computerized testing has become more widely used in clinical trials; however, it is unclear how sensitive these measures are to early signs of neurodegeneration. We investigated the use of the NIH Toolbox-Cognition (NIHTB-CB) and Cogstate-Brief computerized neuropsychological batteries in the identification of mild cognitive impairment (MCI) versus healthy older adults [healthy control (HC)] and amnestic (aMCI) versus nonamnestic MCI (naMCI). Exploratory analyses include investigating potential racial differences.

METHODS

Two hundred six older adults were diagnosed as aMCI (n = 58), naMCI (n = 15), or cognitively healthy (HC; n = 133).

RESULTS

The NIH Toolbox-CB subtests of Flanker, Picture Sequence Memory, and Picture Vocabulary significantly differentiated MCI from HC. Further, subtests from both computerized batteries differentiated patients with aMCI from those with naMCI. Although the main effect of race differences was noted on tests and in diagnostic groups was significant, there were no significant race-by-test interactions.

CONCLUSIONS

Computer-based subtests vary in their ability to help distinguish MCI subtypes, though these tests provide less expensive and easier-to-administer clinical screeners to help identify patients early who may qualify for more comprehensive evaluations. Further work is needed, however, to refine computerized tests to achieve better precision in distinguishing impairment subtypes.

Vascular mechanisms leading to progression of mild cognitive impairment to dementia after COVID-19: Protocol and methodology of a prospective longitudinal observational study

INTRODUCTION

Mild cognitive impairment (MCI) is a prodromal stage to dementia, affecting up to 20% of the aging population worldwide. Patients with MCI have an annual conversion rate to dementia of 15-20%. Thus, conditions that increase the conversion from MCI to dementia are of the utmost public health concern. The COVID-19 pandemic poses a significant impact on our aging population with cognitive decline as one of the leading complications following recovery from acute infection. Recent findings suggest that COVID-19 increases the conversion rate from MCI to dementia in older adults. Hence, we aim to uncover a mechanism for COVID-19 induced cognitive impairment and progression to dementia to pave the way for future therapeutic targets that may mitigate COVID-19 induced cognitive decline.

METHODOLOGY

A prospective longitudinal study is conducted at the University of Oklahoma Health Sciences Center. Patients are screened in the Department of Neurology and must have a formal diagnosis of MCI, and MRI imaging prior to study enrollment. Patients who meet the inclusion criteria are enrolled and followed-up at 18-months after their first visit. Visit one and 18-month follow-up will include an integrated and cohesive battery of vascular and cognitive measurements, including peripheral endothelial function (flow-mediated dilation, laser speckle contrast imaging), retinal and cerebrovascular hemodynamics (dynamic vessel retinal analysis, functional near-infrared spectroscopy), and fluid and crystalized intelligence (NIH-Toolbox, n-back). Multiple logistic regression will be used for primary longitudinal data analysis to determine whether COVID-19 related impairment in neurovascular coupling and increases in white matter hyperintensity burden contribute to progression to dementia.

Quantifying the Neuropsychiatric Symptoms in Post-Acute Sequelae of COVID-19 (PASC) using the NIH Toolbox® and PROMIS

Objective

To quantify neuropsychiatric symptoms reported by individuals with Post-Acute Sequelae of COVID-19 (PASC) using the NIH Toolbox^® for Assessment of Neurological and Behavioral Function (NIHTB) and Patient-Reported Outcomes Measurement Information System (PROMIS).

Methods

30 PASC (20 women, 21-63 years) and 27 control (16 women, 25-68 years) participants completed three NIHTB batteries and selected PROMIS tests. Group differences on fully corrected T-scores were evaluated using analysis of covariance and Cohen's d effect sizes. A linear regression model predicted the effects from time since diagnosis.

Results

PASC had poorer emotional health and motor function than controls, including poorer locomotion, endurance and dexterity, but normal cognitive function, ~7 months post-infection, compared to controls. PASC participants had a steeper age-related decline on 2-Minute Walk than controls. T-scores on four cognitive and three motor tests improved with longer time since diagnosis.

Conclusion

NIHTB and PROMIS captured the poorer emotional health and motor function in PASC, including the novel findings of deficits locomotion and dexterity. The normal cognitive performance suggests subclinical effects that may be compensated by neural and cognitive reserves, and manifested subjectively by the negative psychological effects and fatigue. The persistent emotional and psychiatric symptoms necessitate mental health treatment be prioritized.

Neuropsychological assessment of adults with phenylketonuria using the NIH toolbox

Among researchers and clinicians, there is a call for the development and validation of new measures to better assess and characterize neurocognitive difficulties associated with early-treated phenylketonuria (ETPKU) and other metabolic disorders. The NIH Toolbox represents a relatively new computer-administered assessment tool and provides a sampling of performance across multiple cognitive domains, several of which (e.g., executive function, processing speed) are at risk for disruption in ETPKU. The goal of the present study was to provide an initial evaluation of the value and sensitivity of the NIH Toolbox for use with individuals with ETPKU. To this end, a sample of adults with ETPKU and a demographically-matched comparison group without PKU completed the cognitive and motor batteries of the Toolbox. Results indicate that overall performance (as reflected by the Fluid Cognition Composite) was sensitive to both group differences (ETPKU vs non-PKU) as well as blood Phe levels (a marker of metabolic control). The present findings offer preliminary support for the utility of the NIH Toolbox as a measure of neurocognitive functioning in individuals with ETPKU. Future research including a larger sample size and broader age range is needed to fully validate the Toolbox for clinical and research use with individuals with ETPKU.

Age differences in the functional architecture of the human brain

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience-dependent changes, or both, is uncertain. We employed a multimethod strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n = 181) and older (n = 120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multiscale, multimethod approaches to characterize the architecture of functional brain aging.

Reliability, Validity, and User-Experience of Remote Unsupervised Computerized Neuropsychological Assessments in Community-Living 55- to 75-Year-Olds

BACKGROUND

Self-administered computerized neuropsychological assessments (CNAs) provide lower cost, more accessible alternatives to traditional in-person assessments but lack critical information on psychometrics and subjective experience of older adults in remote testing environments.

OBJECTIVE

We used an online brief battery of computerized tasks selected from the Cogstate Brief Battery (CBB) and Cambridge Brain Sciences (CBS) to 1) determine test-retest reliability in an unsupervised setting; 2) examine convergent validity with a comprehensive 'gold standard' paper-and-pencil neuropsychological test battery administered in-person; and 3) explore user-experience of remote computerized testing and individual tests.

METHODS

Fifty-two participants (mean age 65.8±5.7 years) completed CBB and CBS tests on their own computer, unsupervised from home, on three occasions, and visited a research center for an in-person paper-and-pencil assessment. They also completed a user-experience questionnaire.

RESULTS

Test-retest reliabilities varied for individual measures (ICCs = 0.20 to 0.83). Global cognition composites showed excellent reliability (ICCs > 0.8 over 1-month follow-up). A strong relationship between a combination of CNA measures and paper-and-pencil battery was found (canonical correlation R = 0.87, p = 0.04). Most tests were rated as enjoyable with easy-to-understand instructions. Ratings of general experience with online testing were mostly favorable; few had difficulty concentrating (17%) or using the computer for tasks (10%), although over one-third experienced performance anxiety (38%).

CONCLUSION

A combined brief online battery selected from two CNAs demonstrated robust psychometric standards for reliability (global composite), and convergent validity with a gold standard battery, and mostly good usability and acceptability in the remote testing environment.

Unsupervised Clustering of Olfactory Phenotypes

BACKGROUND

Current clinical classifications of olfactory function are based primarily upon a percentage of correct answers in olfactory identification testing. This simple classification provides little insight into etiologies of olfactory loss, associated comorbidities, or impact on the quality of life (QOL).

METHODS

Community-based subjects underwent olfactory psychophysical testing using Sniffin Sticks to measure threshold (T), discrimination (D), and identification (I). The cognitive screening was performed using Mini-Mental Status Examination (MMSE). Unsupervised clustering was performed based upon T, D, I, and MMSE. Post hoc differences in demographics, comorbidities, and QOL measures were assessed.

RESULTS

Clustering of 219 subjects, mean age 51 years (range 20-93 years) resulted in 4 unique clusters. Cluster 1 was the largest and predominantly younger normosmics. Cluster 2 had the worst olfaction with impairment in nearly all aspects of olfaction and decreased MMSE scores. This cluster had higher rates of smoking, heart disease, and cancer and had the worst olfactory-specific QOL. Cluster 3 had normal MMSE with relative preservation of D and I, but severely impaired T. This cluster had higher rates of smoking and heart disease with moderately impaired QOL. Cluster 4 was notable for the worst MMSE scores, but general preservation of D and I with moderate loss of T. This cluster had higher rates of Black subjects, diabetes, and viral/traumatic olfactory loss.

CONCLUSION

Unsupervised clustering based upon detailed olfactory testing and cognitive testing results in clinical phenotypes with unique risk factors and QOL impacts. These clusters may provide additional information regarding etiologies and subsequent therapies to treat olfactory loss.

Dementia Prevention in Clinical Practice

Over 55 million people globally are living with dementia and, by 2050, this number is projected to increase to 131 million. This poses immeasurable challenges for patients and their families and a significant threat to domestic and global economies. Given this public health crisis and disappointing results from disease-modifying trials, there has been a recent shift in focus toward primary and secondary prevention strategies. Approximately 40% of Alzheimer's disease (AD) cases, which is the most common form of dementia, may be prevented or at least delayed. Success of risk reduction studies through addressing modifiable risk factors, in addition to the failure of most drug trials, lends support for personalized multidomain interventions rather than a "one-size-fits-all" approach. Evolving evidence supports early intervention in at-risk patients using individualized interventions directed at modifiable risk factors. Comprehensive risk stratification can be informed by emerging principals of precision medicine, and include expanded clinical and family history, anthropometric measurements, blood biomarkers, neurocognitive evaluation, and genetic information. Risk stratification is key in differentiating subtypes of dementia and identifies targetable areas for intervention. This article reviews a clinical approach toward dementia risk stratification and evidence-based prevention strategies, with a primary focus on AD.

Combination of structural and functional connectivity explains unique variation in specific domains of cognitive function

The relationship between structural and functional brain networks has been characterised as complex: the two networks mirror each other and show mutual influence but they also diverge in their organisation. This work explored whether a combination of structural and functional connectivity can improve the fit of regression models of cognitive performance. Principal Component Analysis (PCA) was first applied to cognitive data from the Human Connectome Project to identify latent cognitive components: Executive Function, Self-regulation, Language, Encoding and Sequence Processing. A Principal Component Regression approach with embedded Step-Wise Regression (SWR-PCR) was then used to fit regression models of each cognitive domain based on structural (SC), functional (FC) or combined structural-functional (CC) connectivity. Executive Function was best explained by the CC model. Self-regulation was equally well explained by SC and FC. Language was equally well explained by CC and FC models. Encoding and Sequence Processing were best explained by SC. Evaluation of out-of-sample models' skill via cross-validation showed that SC, FC and CC produced generalisable models of Language performance. SC models performed most effectively at predicting Language performance in unseen sample. Executive Function was most effectively predicted by SC models, followed only by CC models. Self-regulation was only effectively predicted by CC models and Sequence Processing was only effectively predicted by FC models. The present study demonstrates that integrating structural and functional connectivity can help explaining cognitive performance, but that the added explanatory value (in sample) may be domain-specific and can come at the expense of reduced generalisation performance (out-of-sample).

ARMADA: Assessing reliable measurement in Alzheimer's disease and cognitive aging project methods

INTRODUCTION

Early detection of cognitive decline in older adults is a public health priority. Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA), a multisite study, is validating cognition, emotion, motor, and sensory modules of the National Institutes of Health Toolbox for Assessment of Neurological and Behavioral Function (NIHTB) in the aging spectrum from cognitively normal to dementia of the Alzheimer's type (DAT).

METHODS

Participants 65 to 85 years old, in demographic groups racially proportional to the general US population, are recruited in one of three groups to validate the NIHTB: cognitively normal, amnestic mild cognitive impairment (aMCI), or mild DAT. Additional special emphasis cohorts include (1) Blacks in the three clinical groups; (2) Spanish-speakers in the three clinical groups; (3) cognitively normal, population-proportional, over age 85.

DISCUSSION

Longitudinal study will determine whether NIHTB can predict cognitive decline and is associated with Alzheimer's disease biomarkers. Here, we detail the methods for the ARMADA study.

Uses of the NIH Toolbox® in Clinical Samples: A Scoping Review

Background and Objectives

The NIH Toolbox® for the Assessment of Neurologic and Behavioral Function is a compilation of computerized measures designed to assess sensory, motor, emotional, and cognitive functioning of individuals across the life span. The NIH Toolbox was initially developed for use with the general population and was not originally validated in clinical populations. The objective of this scoping review was to assess the extent to which the NIH Toolbox has been used with clinical populations.

Methods

Guided by the Joanna Briggs Methods Manual for Scoping Reviews, records were identified through searches of PubMed MEDLINE, PsycINFO, ClinicalTrials.gov, EMBASE, and ProQuest Dissertations and Theses Global (2008-2020). Database searches yielded 5,693 unique titles of original research that used at least one NIH Toolbox assessment in a sample characterized by any clinical diagnosis. Two reviewers screened titles, abstracts, and full texts for inclusion in duplicate. Conflicts at each stage of the review process were resolved by a group discussion.

Results

Ultimately, 281 publication records were included in this scoping review (nJournal Articles = 104, nConference Abstracts = 84, nClinical Trial Registrations = 86, and nTheses/Dissertations = 7). The NIH Toolbox Cognition Battery was by far the most used of the 4 batteries in the measurement system (nCognition = 225, nEmotion = 49, nMotor = 29, and nSensation = 16). The most represented clinical category was neurologic disorders (n = 111), followed by psychological disorders (n = 39) and cancer (n = 31). Most (96.8%) of the journal articles and conference abstracts reporting the use of NIH Toolbox measures with clinical samples were published in 2015 or later. As of May 2021, these records had been cited a total of nearly 1,000 times.

Discussion

The NIH Toolbox measures have been widely used among individuals with various clinical conditions across the life span. Our results lay the groundwork to support the feasibility and utility of administering the NIH Toolbox measures in research conducted with clinical populations and further suggest that these measures may be of value for implementation in fast-paced clinical settings as part of routine practice.

Construct validity of the NIH toolbox cognitive domains: A comparison with conventional neuropsychological assessments

OBJECTIVE

Previous studies have assessed the construct validity of individual subtests in the National Institutes of Health (NIH) Toolbox Cognition Battery (NIHTB-CB), though none have examined the construct validity of the cognitive domains. Importantly, the original NIHTB-CB validation studies were administered on a desktop computer, though the NIHTB-CB is now solely administered via an iPad. We examined the construct validity of each cognitive domain assessed in the NIHTB-CB, including a motor dexterity domain using the iPad application compared to a neuropsychological battery in a sample of healthy adults.

METHOD

Eighty-three adults aged 20-66 years (M = 44.35 ± 13.41 years) completed the NIHTB-CB and a comprehensive neuropsychological assessment. Domain scores for each of six cognitive domains (attention and executive function, episodic memory, working memory, processing speed, language, and motor dexterity) and the fluid composite were computed for both batteries. We then assessed the construct validity using Pearson correlations and intraclass correlation coefficients (ICCs) for both demographically corrected and uncorrected domains.

RESULTS

We found the attention and executive function, episodic memory, and processing speed domains had poor-to-adequate construct validity (ICCConsistency = -0.029 to 0.517), the working memory and motor dexterity domains and the fluid composite had poor-to-good construct validity (ICCConsistency = 0.215-0.801), and the language domain had adequate-to-good construct validity (ICCConsistency = 0.408-0.829).

CONCLUSION

The NIHTB-CB cognitive domains have poor-to-good construct validity, thus researchers should be aware that some tests representing cognitive constructs may not fully reflect the cognitive domain of interest. Future investigation of the construct validity and reliability of the NIHTB-CB administered using the iPad is recommended. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Lessons from Detecting Cognitive Impairment Including Dementia (DetectCID) in Primary Care

Background: Cognitive impairment, including dementia, is frequently under-detected in primary care. The Consortium for Detecting Cognitive Impairment, including Dementia (DetectCID) convenes three multidisciplinary teams that are testing novel paradigms to improve the frequency and quality of patient evaluations for detecting cognitive impairment in primary care and appropriate follow-up. Objective: Our objective was to characterize the three paradigms, including similarities and differences, and to identify common key lessons from implementation. Methods: A qualitative evaluation study with dementia specialists who were implementing the detection paradigms. Data was analyzed using content analysis. Results: We identified core components of each paradigm. Key lessons emphasized the importance of engaging primary care teams, enabling primary care providers to diagnose cognitive disorders and provide ongoing care support, integrating with the electronic health record, and ensuring that paradigms address the needs of diverse populations. Conclusion: Approaches are needed that address the arc of care from identifying a concern to post-diagnostic management, are efficient and adaptable to primary care workflows, and address a diverse aging population. Our work highlights approaches to partnering with primary care that could be useful across specialties and paves the way for developing future paradigms that improve differential diagnosis of symptomatic cognitive impairment, identifying not only its presence but also its specific syndrome or etiology.

Assessing Cognitive Function in Multiple Sclerosis With Digital Tools: Observational Study

BACKGROUND

Cognitive impairment (CI) is one of the most prevalent symptoms of multiple sclerosis (MS). However, it is difficult to include cognitive assessment as part of MS standard care since the comprehensive neuropsychological examinations are usually time-consuming and extensive.

OBJECTIVE

To improve access to CI assessment, we evaluated the feasibility and potential assessment sensitivity of a tablet-based cognitive battery in patients with MS.

METHODS

In total, 53 participants with MS (24 [45%] with CI and 29 [55%] without CI) and 24 non-MS participants were assessed with a tablet-based cognitive battery (Adaptive Cognitive Evaluation [ACE]) and standard cognitive measures, including the Symbol Digit Modalities Test (SDMT) and the Paced Auditory Serial Addition Test (PASAT). Associations between performance in ACE and the SDMT/PASAT were explored, with group comparisons to evaluate whether ACE modules can capture group-level differences.

RESULTS

Correlations between performance in ACE and the SDMT (R=-0.57, P<.001), as well as PASAT (R=-0.39, P=.01), were observed. Compared to non-MS and non-CI MS groups, the CI MS group showed a slower reaction time (CI MS vs non-MS: P<.001; CI MS vs non-CI MS: P=.004) and a higher attention cost (CI MS vs non-MS: P=.02; CI MS vs non-CI MS: P<.001).

CONCLUSIONS

These results provide preliminary evidence that ACE, a tablet-based cognitive assessment battery, provides modules that could potentially serve as a digital cognitive assessment for people with MS.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03569618; https://clinicaltrials.gov/ct2/show/NCT03569618.

Utility of the iPad NIH Toolbox Cognition Battery in a clinical trial of older adults

BACKGROUND

To demonstrate feasibility and utility of the iPad version of the NIH Toolbox Cognition Battery (NIHTB-CB) in a clinical trial of older adults.

METHODS

Fifty-one adults, aged 55 and older without dementia were tested twice on NIHTB-CB and more traditional paper-and-pencil neuropsychological measures after meal ingestion, with approximately a 4-week interval. We also compared performances at Time 1 and Time 2 for significant change. We also extracted the response times and errors for available NIHTB-CB subtests to determine subtle changes in performance.

RESULTS

Over the interval, improvement in fluid cognitive measures was noted at Time 2 (t = -3.07, p = 0.004), whereas crystallized measures were unchanged. Tests of fluid cognition negatively correlated with age, particularly for the second visit. Analysis of the average speed per item showed that, for two of the tests, speed increased at Time 2. Traditional neuropsychological tests correlated with many of the NIHTB-CB measures. Response times for all five timed tests decreased at Time 2, although only statistically significant for Picture Sequence and Picture Vocabulary.

CONCLUSIONS

The iPad version of the NIH Toolbox Cognition Battery appears to be an adequate measure to assess cognitive functioning in a clinical trial of older adults. Psychometric analyses suggest stability in measures of crystallized functioning, whereas measures of fluid abilities revealed improvements over the short time frame of the study. Response times and errors for individual tests revealed intriguing relationships that should be further evaluated to determine the utility in clinical sample analysis, as this could aid identification of subtle cognitive change over short periods. Additional studies with larger sample sizes will be helpful to understanding the reliability, sensitivity, and specificity of the NIHTB-CB sub-scores in older adults. In addition, further evaluations with clinical populations, including individuals with cognitive impairment, are warranted.

Latent Factor Structure and Measurement Invariance of the NIH Toolbox Cognition Battery in an Alzheimer's Disease Research Sample

OBJECTIVE

This study investigated the latent factor structure of the NIH Toolbox Cognition Battery (NIHTB-CB) and its measurement invariance across clinical diagnosis and key demographic variables including sex, race/ethnicity, age, and education for a typical Alzheimer's disease (AD) research sample.

METHOD

The NIHTB-CB iPad English version, consisting of 7 tests, was administered to 411 participants aged 45-94 with clinical diagnosis of cognitively unimpaired, dementia, mild cognitive impairment (MCI), or impaired not MCI. The factor structure of the whole sample was first examined with exploratory factor analysis (EFA) and further refined using confirmatory factor analysis (CFA). Two groups were classified for each variable (diagnosis or demographic factors). The confirmed factor model was next tested for each group with CFA. If the factor structure was the same between the groups, measurement invariance was then tested using a hierarchical series of nested two-group CFA models.

RESULTS

A two-factor model capturing fluid cognition (executive function, processing speed, and memory) versus crystalized cognition (language) fit well for the whole sample and each group except for those with age < 65. This model generally had measurement invariance across sex, race/ethnicity, and education, and partial invariance across diagnosis. For individuals with age < 65, the language factor remained intact while the fluid cognition was separated into two factors: (1) executive function/processing speed and (2) memory.

CONCLUSIONS

The findings mostly supported the utility of the battery in AD research, yet revealed challenges in measuring memory for AD participants and longitudinal change in fluid cognition.

The influence of cognitive tasks on sensory organization test performance

Introduction

Many static postural tasks requiring vestibular contributions are completed while dual- tasking.

Objective

We investigated the influence of dual-tasks on sensory integration for postural control and cognitive performance during the sensory organization test and examined the relationship between cognitive function and dual-task cost during the sensory organization test.

Methods

Twenty adults completed single and dual-task versions of the six conditions of the sensory organization test were completed during two visits separated by one week. A subset of 13 participants completed three National Institute of Health (NIH)-toolbox cognitive tests including the Flanker inhibitory control and attention test, dimensional change card sort test and pattern comparison processing speed test. Wilcoxon signed rank tests were used to compare postural sway during single and dual-task sensory organization test. Friedman’s test, with pairwise comparison post-hoc tests, was used to compare single task serial subtraction performance to the 6 dual-task sensory organization test conditions. Spearman’s correlation coefficients were used to assess the relationship between cognitive performance on NIH-toolbox test and postural and cognitive dual-task cost during the sensory organization test.

Results

Performing a cognitive dual-task during the sensory organization test resulted in a significant increase in postural sway during condition 1 (Z = −3.26, p = 0.001, ES = 0.73), condition 3 (Z = −2.53, p = 0.012, ES = 0.56), and condition 6 (Z = −2.02, p = 0.044, ES = 0.45). Subtraction performance significantly decreased in during condition 6 (Z = −2.479, p = 0.011, ES = 0.55) compared to single-task. The dimensional change card sort test demonstrated moderate correlations with dual-task cost of serial subtraction performance in condition 5 (dimensional change card sort test: r = −0.62, p = 0.02) and condition 6 (dimensional change card sort test: r = −0.56, p = 0.04). Pattern comparison processing speed test scores were significantly correlated with dual-task cost of postural control during condition 2.

Conclusion

Performing a cognitive task during the sensory organization test resulted in significantly increased postural sway during three conditions, particularly during visual environment manipulation oppose to vestibular and somatosensory manipulation. Cognitive performance decreased during the most complex sensory organization test condition. Additionally, we found participants with poorer executive function had greater dual-task cost during more complex sensory integration demands.

Light in the Senior Home: Effects of Dynamic and Individual Light Exposure on Sleep, Cognition, and Well-Being

Disrupted sleep is common among nursing home patients and is associated with cognitive decline and reduced well-being. Sleep disruptions may in part be a result of insufficient daytime light exposure. This pilot study examined the effects of dynamic “circadian” lighting and individual light exposure on sleep, cognitive performance, and well-being in a sample of 14 senior home residents. The study was conducted as a within-subject study design over five weeks of circadian lighting and five weeks of conventional lighting, in a counterbalanced order. Participants wore wrist accelerometers to track rest–activity and light profiles and completed cognitive batteries (National Institute of Health (NIH) toolbox) and questionnaires (depression, fatigue, sleep quality, lighting appraisal) in each condition. We found no significant differences in outcome variables between the two lighting conditions. Individual differences in overall (indoors and outdoors) light exposure levels varied greatly between participants but did not differ between lighting conditions, except at night (22:00–6:00), with maximum light exposure being greater in the conventional lighting condition. Pooled data from both conditions showed that participants with higher overall morning light exposure (6:00–12:00) had less fragmented and more stable rest–activity rhythms with higher relative amplitude. Rest–activity rhythm fragmentation and long sleep duration both uniquely predicted lower cognitive performance.

Executive function in children with sickle cell anemia on transfusion: NIH toolbox utility in the clinical context

OBJECTIVE

The aim of this study was to establish the utility of the NIH Toolbox as a cognitive screener of executive functions in the clinical context. Additionally, we aimed to investigate whether age and time on transfusion were related to executive function performance. Method: Twenty-eight children and adolescents with sickle cell anemia (SCA) between 8 and 18 years (M = 13.28, SD = 3.05) on transfusion treatment were included. Participants completed five NIH Toolbox tasks (three executive function tasks and two non-executive function control tasks). Results: Mean scores on one of the three executive function measures (inhibitory control) fell below the average range (M = 81.36, SD = 14.01) with approximately 70% of children from both groups below the average range. Scores for processing speed (M = 86.82, SD = 22.01) and cognitive flexibility (M = 85.75, SD = 12.67) were low averages. As expected, scores on non-executive measures (language and memory) fell within the average range. No significant differences were observed between children with silent stroke and no stroke on executive function measures. Older age (p < .01) and length of time on transfusion (p < .05) predicted lower inhibitory control scores. Conclusions: Findings provide evidence for poor development of inhibitory control with age in this patient population. As the NIH Toolbox successfully highlighted expected deficits in this patient population, this study supports the use of this tool as a brief screening measure for children with SCD. The clinical and theoretical implications of the findings are discussed.

Associations between NIH Toolbox Cognition Battery and in vivo brain amyloid and tau pathology in non-demented older adults

INTRODUCTION

The National Institutes of Health (NIH) Toolbox Cognition Battery (NIHTB-CB) was developed to be a common assessment metric across a broad array of research studies. We investigated associations between NIHTB-CB and brain amyloid and tau deposition in cognitively unimpaired older adults.

METHODS

One hundred eighteen community-based volunteers completed magnetic resonance imaging (MRI), Pittsburgh compound B (PiB)-PET (positron emission tomography) and AV-1451-PET neuroimaging, a neuropsychological evaluation, NIHTB-CB, and the Clinical Dementia Rating (CDR) scale. Demographically adjusted regression models evaluated cognition-biomarker associations; standardized effect sizes allowed comparison of association strength across measures.

RESULTS

No NIHTB-CB measures were associated with amyloid deposition. NIHTB-CB measures of fluid cognition, including Pattern Comparison Processing Speed, Dimensional Change Card Sort, and Fluid Cognition Composite, were associated with tau deposition in higher Braak regions. Pattern Comparison Processing Speed was the most robust association with sensitivity analyses.

DISCUSSION

NIHTB-CB tasks of processing speed and executive functions may be sensitive to pathologic tau deposition on imaging in normal aging.

Feasibility of Using a Wearable Biosensor Device in Patients at Risk for Alzheimer's Disease Dementia

BACKGROUND

Alzheimer's disease (AD) is the most common and most costly chronic neurodegenerative disease globally. AD develops over an extended period prior to cognitive symptoms, leaving a "window of opportunity" for targeted risk-reduction interventions. Further, this pre-dementia phase includes early physiological changes in sleep and autonomic regulation, for which wearable biosensor devices may offer a convenient and cost-effective method to assess AD-risk.

METHODS

Patients with a family history of AD and no or minimal cognitive complaints were recruited from the Alzheimer's Prevention Clinic at Weill Cornell Medicine and New York-Presbyterian. Of the 40 consecutive patients screened, 34 (85%) agreed to wear a wearable biosensor device (WHOOP). One subject (2.5%) lost the device prior to data collection. Of the remaining subjects, 24 were classified as normal cognition and were asymptomatic, 6 were classified as subjective cognitive decline, and 3 were amyloid-positive (one with pre-clinical AD, one with pre-clinical Lewy-Body Dementia, and one with mild cognitive impairment due to AD). Sleep-cycle, autonomic (heart rate variability [HRV]) and activity measures were collected via WHOOP. Blood biomarkers and neuropsychological testing sensitive to cognitive changes in pre-clinical AD were obtained. Participants completed surveys assessing their sleep-patterns, exercise habits, and attitudes towards WHOOP. The goal of this prospective observational study was to determine the feasibility of using a wrist-worn biosensor device in patients at-risk for AD dementia. Unsupervised machine learning was performed to first separate participants into distinct phenotypic groups using the multivariate biometric data. Additional statistical analyses were conducted to examine correlations between individual biometric measures and cognitive performance.

RESULTS

27 (81.8%) participants completed the follow-up surveys. Twenty-four participants (88.9%) were satisfied with WHOOP after six months, and twenty-three (85.2%) wanted to continue wearing WHOOP. K-means clustering separated participants into two groups. Group 1 was older, had lower HRV, and spent more time in slow-wave sleep (SWS) than Group 2. Group 1 performed better on two cognitive tests assessing executive function: Flanker Inhibitory Attention/Control (FIAC) (p=.031), and Dimensional Change Card Sort (DCCS) (p=.061). In Group 1, DCCS was correlated with SWS (ρ=.68, p=0.024) and HRV (ρ=.6, p=0.019). In Group 2, DCCS was correlated with HRV (ρ=.55, p=0.018). There were no significant differences in blood biomarkers between the two groups.

CONCLUSIONS

Wearable biosensor devices may be a feasible tool to assess AD-related physiological changes. Longitudinal collection of sleep and HRV data may potentially be a non-invasive method for monitoring cognitive changes related to pre-clinical AD. Further study is warranted in larger populations.

Individualized clinical management of patients at risk for Alzheimer's dementia

INTRODUCTION

Multidomain intervention for Alzheimer's disease (AD) risk reduction is an emerging therapeutic paradigm.

METHODS

Patients were prescribed individually tailored interventions (education/pharmacologic/nonpharmacologic) and rated on compliance. Normal cognition/subjective cognitive decline/preclinical AD was classified as Prevention. Mild cognitive impairment due to AD/mild-AD was classified as Early Treatment. Change from baseline to 18 months on the modified Alzheimer's Prevention Cognitive Composite (primary outcome) was compared against matched historical control cohorts. Cognitive aging composite (CogAging), AD/cardiovascular risk scales, and serum biomarkers were secondary outcomes.

RESULTS

One hundred seventy-four were assigned interventions (age 25-86). Higher-compliance Prevention improved more than both historical cohorts (P = .0012, P < .0001). Lower-compliance Prevention also improved more than both historical cohorts (P = .0088, P < .0055). Higher-compliance Early Treatment improved more than lower compliance (P = .0007). Higher-compliance Early Treatment improved more than historical cohorts (P < .0001, P = .0428). Lower-compliance Early Treatment did not differ (P = .9820, P = .1115). Similar effects occurred for CogAging. AD/cardiovascular risk scales and serum biomarkers improved.

DISCUSSION

Individualized multidomain interventions may improve cognition and reduce AD/cardiovascular risk scores in patients at-risk for AD dementia.

Psychometric Properties of the NIH Toolbox Cognition Battery in Healthy Older Adults: Reliability, Validity, and Agreement with Standard Neuropsychological Tests

OBJECTIVE

Few independent studies have examined the psychometric properties of the NIH Toolbox Cognition Battery (NIHTB-CB) in older adults, despite growing interest in its use for clinical purposes. In this paper we report the test-retest reliability and construct validity of the NIHTB-CB, as well as its agreement or concordance with traditional neuropsychological tests of the same construct to determine whether tests could be used interchangeably.

METHODS

Sixty-one cognitively healthy adults ages 60-80 completed "gold standard" (GS) neuropsychological tests, NIHTB-CB, and brain MRI. Test-retest reliability, convergent/discriminant validity, and agreement statistics were calculated using Pearson's correlations, concordance correlation coefficients (CCC), and root mean square deviations.

RESULTS

Test-retest reliability was acceptable (CCC = .73 Fluid; CCC = .85 Crystallized). The NIHTB-CB Fluid Composite correlated significantly with cerebral volumes (r's = |.35-.41|), and both composites correlated highly with their respective GS composites (r's = .58-.84), although this was more variable for individual tests. Absolute agreement was generally lower (CCC = .55 Fluid; CCC = .70 Crystallized) due to lower precision in fluid scores and systematic overestimation of crystallized composite scores on the NIHTB-CB.

CONCLUSIONS

These results support the reliability and validity of the NIHTB-CB in healthy older adults and suggest that the fluid composite tests are at least as sensitive as standard neuropsychological tests to medial temporal atrophy and ventricular expansion. However, the NIHTB-CB may generate different estimates of performance and should not be treated as interchangeable with established neuropsychological tests.