Rethinking the residual approach: Leveraging machine learning to operationalize cognitive resilience in Alzheimer's disease.

Cognitive resilience describes the phenomenon of individuals evading cognitive decline despite prominent Alzheimer's disease neuropathology. Operationalization and measurement of this latent construct is non-trivial as it cannot be directly observed. The residual approach has been widely applied to estimate CR, where the degree of resilience is estimated through a linear model's residuals. We demonstrate that this approach makes specific, uncontrollable assumptions and likely leads to biased and erroneous resilience estimates. We propose an alternative strategy which overcomes the standard approach's limitations using machine learning principles. Our proposed approach makes fewer assumptions about the data and construct to be measured and achieves better estimation accuracy on simulated ground-truth data.

Clearance and transport of amyloid ß by peripheral monocytes correlate with Alzheimer's disease progression.

Impaired clearance of amyloid ß (Aß) in late-onset Alzheimer's disease (AD) affects disease progression. The role of peripheral monocytes in Aß clearance from the central nervous system (CNS) is unclear. We use a flow cytometry assay to identify Aß-binding monocytes in blood, validated by confocal microscopy, Western blotting, and mass spectrometry. Flow cytometry immunophenotyping and correlation with AD biomarkers are studied in 150 participants from the AIBL study. We also examine monocytes in human cerebrospinal fluid (CSF) and their migration in an APP/PS1 mouse model. The assay reveals macrophage-like Aß-binding monocytes with high phagocytic potential in both the periphery and CNS. We find lower surface Aß levels in mild cognitive impairment (MCI) and AD-dementia patients compared to cognitively unimpaired individuals. Monocyte infiltration from blood to CSF and migration from CNS to peripheral lymph nodes and blood are observed. Here we show that Aß-binding monocytes may play a role in CNS Aß clearance, suggesting their potential as a biomarker for AD diagnosis and monitoring.

A Data-Driven Cognitive Composite Sensitive to Amyloid-ß for Preclinical Alzheimer's Disease.

Background: Integrating scores from multiple cognitive tests into a single cognitive composite has been shown to improve sensitivity to detect AD-related cognitive impairment. However, existing composites have little sensitivity to amyloid-ß status (Aß +/-) in preclinical AD. Objective: Evaluate whether a data-driven approach for deriving cognitive composites can improve the sensitivity to detect Aß status among cognitively unimpaired (CU) individuals compared to existing cognitive composites. Methods: Based on the data from the Anti-Amyloid Treatment in the Asymptomatic Alzheimer's Disease (A4) study, a novel composite, the Data-driven Preclinical Alzheimer's Cognitive Composite (D-PACC), was developed based on test scores and response durations selected using a machine learning algorithm from the Cogstate Brief Battery (CBB). The D-PACC was then compared with conventional composites in the follow-up A4 visits and in individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Result: The D-PACC showed a comparable or significantly higher ability to discriminate Aß status [median Cohen's d = 0.172] than existing composites at the A4 baseline visit, with similar results at the second visit. The D-PACC demonstrated the most consistent sensitivity to Aß status in both A4 and ADNI datasets. Conclusions: The D-PACC showed similar or improved sensitivity when screening for Aß+ in CU populations compared to existing composites but with higher consistency across studies.

Engagement in online cognitive testing with the Cogstate brief battery among a multinational cohort of people with focal epilepsy.

OBJECTIVE: The Human Epilepsy Project (HEP) is a large multinational cohort study of people with newly diagnosed and treated focal epilepsy. HEP utilized the Cogstate Brief Battery (CBB) as a self-directed online assessment to examine cognitive outcomes in study participants. The CBB has previously been validated in healthy individuals and people with various brain disorders, but its use in adults participating in HEP has not been assessed. In this study, we describe how the CBB was used in the HEP cohort and assess factors associated with test completion among study participants. METHODS: Enrollment data for HEP included 408 participants with comprehensive enrollment records, of whom 249 completed CBB assessments. HEP enrolled cognitively normal-range participants between the ages of 12 and 60 from June 29, 2012, to November 7, 2017, with newly diagnosed focal epilepsy and within 4 months of initial treatment. Baseline participant characteristics were analyzed, including demographics, pre-treatment seizure histories, MRI abnormalities, and the presence of any learning difficulties while in school, including formal learning disability diagnoses, repeated grades, and remediation. HEP participant characteristics for those who completed CBB testing were compared to those who did not using multiple logistic regression. RESULTS: The analysis of HEP participants who completed CBB testing showed that, after controlling for other factors, male participants were more likely to engage in testing (OR 2.14, 95 % CI 1.29 to 3.5, p < 0.01), Black subjects were less likely (OR 0.45, 95 % CI 0.22 to 0.9, p = 0.02), primary English speakers were more likely (OR 3.1, 95 % CI 1.21 to 7.96, p = 0.02), and those with a history of learning challenges were less likely (OR 0.69, 95 % CI 0.49 to 0.97, p = 0.03). There were no significant associations between completing CBB testing and age, employment (employed or student vs not), education (higher education vs not), diagnostic delay, pre-diagnostic seizure burden, or initial seizure semiology (motor vs non-motor). SIGNIFICANCE: The findings from this study highlight factors associated with the application of remote and unsupervised assessments of cognition in a prospective cohort of adults with focal epilepsy. These factors can be considered when interpreting performance on the CBB in HEP, as well as assisting the design of future studies that use similar approaches.

Brain aging patterns in a large and diverse cohort of 49,482 individuals.

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.

Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning.

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

The nature and magnitude of cognitive impairment in narcolepsy type 1, narcolepsy type 2, and idiopathic hypersomnia: a meta-analysis.

People with narcolepsy type 1 (NT1), narcolepsy type 2 (NT2), and idiopathic hypersomnia (IH) often report cognitive impairment which can be quite burdensome but is rarely evaluated in routine clinical practice. In this systematic review and meta-analysis, we assessed the nature and magnitude of cognitive impairment in NT1, NT2, and IH in studies conducted from January 2000 to October 2022. We classified cognitive tests assessing memory, executive function, and attention by cognitive domain. Between-group differences were analyzed as standardized mean differences (Cohen's d), and Cohen's d for individual tests were integrated according to cognitive domain and clinical disease group. Eighty-seven studies were screened for inclusion; 39 satisfied inclusion criteria, yielding 73 comparisons (k): NT1, k = 60; NT2, k = 8; IH, k = 5. Attention showed large impairment in people with NT1 (d = -0.90) and IH (d = -0.97), and moderate impairment in NT2 (d = -0.60). Executive function was moderately impaired in NT1 (d = -0.30) and NT2 (d = -0.38), and memory showed small impairments in NT1 (d = -0.33). A secondary meta-analysis identified sustained attention as the most impaired domain in NT1, NT2, and IH (d ≈ -0.5 to -1). These meta-analyses confirm that cognitive impairments are present in NT1, NT2, and IH, and provide quantitative confirmation of reports of cognitive difficulties made by patients and clinicians. These findings provide a basis for the future design of studies to determine whether cognitive impairments can improve with pharmacologic and nonpharmacologic treatments for narcolepsy and IH.

Association of Basal Forebrain Atrophy With Cognitive Decline in Early Alzheimer Disease.

BACKGROUND AND OBJECTIVES: In early Alzheimer disease (AD), ß-amyloid (Aß) deposition is associated with volume loss in the basal forebrain (BF) and cognitive decline. However, the extent to which Aß-related BF atrophy manifests as cognitive decline is not understood. This study sought to characterize the relationship between BF atrophy and the decline in memory and attention in patients with early AD. METHODS: Participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study who completed Aß-PET imaging and repeated MRI and cognitive assessments were included. At baseline, participants were classified based on their clinical dementia stage and Aß status, yielding groups that were cognitively unimpaired (CU) Aß-, CU Aß+, and mild cognitive impairment (MCI) Aß+. Linear mixed-effects models were used to assess changes in volumetric measures of BF subregions and the hippocampus and changes in AIBL memory and attention composite scores for each group compared with CU Aß- participants. Associations between Aß burden, brain atrophy, and cognitive decline were evaluated and explored further using mediation analyses. RESULTS: The cohort included 476 participants (72.6 ± 5.9 years, 55.0% female) with longitudinal data from a median follow-up period of 6.1 years. Compared with the CU Aß- group (n = 308), both CU Aß+ (n = 107) and MCI Aß+ (n = 61) adults showed faster decline in BF and hippocampal volumes and in memory and attention (Cohen d = 0.73-1.74). Rates of atrophy in BF subregions and the hippocampus correlated with cognitive decline, and each individually mediated the impact of Aß burden on memory and attention decline. When all mediators were considered simultaneously, hippocampal atrophy primarily influenced the effect of Aß burden on memory decline (ß [SE] = -0.139 [0.032], proportion mediated [PM] = 28.0%) while the atrophy of the posterior nucleus basalis of Meynert in the BF (ß [SE] = -0.068 [0.029], PM = 13.1%) and hippocampus (ß [SE] = -0.121 [0.033], PM = 23.4%) distinctively influenced Aß-related attention decline. DISCUSSION: These findings highlight the significant role of BF atrophy in the complex pathway linking Aß to cognitive impairment in early stages of AD. Volumetric assessment of BF subregions could be essential in elucidating the relationships between the brain structure and behavior in AD.

Cognitive impairment among patients with chronic immune thrombocytopenia.

Immune thrombocytopenia (ITP) is an autoimmune disease typically associated with severely depleted platelet counts. However, additional symptoms (e.g. increased fatigue and memory/concentration difficulties) can profoundly impact patients' quality of life. The nature and severity of cognitive impairment in ITP, and potential association with patient/disease characteristics were evaluated in 49 adults with relapsed/refractory ITP. The Cogstate Brief Battery quantitatively assessed psychomotor function (DET), attention (IDN), visual learning (OCL) and working memory (ONB) individually, as well as DET/IDN and OCL/ONB composites. Clinically important cognitive impairment (defined as z-score ≤ -1) for ≥2 individual tests was observed in 29 patients (59%). Impairment was highest for IDN (67% of patients), followed by DET (53%), ONB (39%) and OCL (16%). A higher magnitude of impairment was observed for the DET/IDN composite (mean z-score -1.54; 95% CI, -1.94 to -1.13) than OCL/ONB (mean z-score -0.21; 95% CI, -0.49 to 0.07). The severity of cognitive impairment was comparable to mild traumatic brain injury and associated with increasing age and fatigue but unrelated to platelet count or corticosteroid use. Overall, these results warrant a clinical need to further consider the potential of cognitive dysfunction in assessing ITP patients.

Cross-sectional associations between neighborhood characteristics, cognition and dementia risk factor burden in middle-aged and older Australians.

Dementia disproportionately affects individuals from disadvantaged backgrounds, including those living in areas of lower neighborhood-level socioeconomic status. It is important to understand whether there are specific neighborhood characteristics associated with dementia risk factors and cognition which may inform dementia risk reduction interventions. We sought to examine whether greenspace, walkability, and crime associated with the cumulative burden of modifiable dementia risk factors and cognition. This was a cross-sectional analysis of 2016-2020 data from the Healthy Brain Project, a population-based cohort of community-dwelling individuals across Australia. Participants were aged 40-70 and free of dementia. Measures included greenspace (greenspace % in the local area, and distance to greenspace, n = 2,181); and intersection density (n = 1,159), and crime (rate of recorded offences; n = 1,159). Outcomes included a modified Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) dementia risk score to index the burden of modifiable vascular dementia risk factors; and composite scores of both memory and attention, derived from the Cogstate Brief Battery. Linear regressions adjusted for age, sex, education, and personal socio-economic status, demonstrated distance to greenspace (b ± SE per 2-fold increase = 0.09 ± 0.03, p =.005) and crime rate (b ± SE per 2-fold increase = 0.07 ± 0.03, p =.018) were associated with higher modified CAIDE. Higher crime was associated with lower memory performance (b ± SE = -0.03 ± 0.01, p =.018). The association between distance to greenspace and modified CAIDE was only present in low-moderate socioeconomic status neighborhoods (p interaction = 0.004). Dementia prevention programs that address modifiable risk factors in midlife should consider the possible role of neighborhood characteristics.

Suboptimal self-reported sleep efficiency and duration are associated with faster accumulation of brain amyloid beta in cognitively unimpaired older adults.

INTRODUCTION: This study investigated whether self-reported sleep quality is associated with brain amyloid beta (Aß) accumulation. METHODS: Linear mixed effect model analyses were conducted for 189 cognitively unimpaired (CU) older adults (mean ± standard deviation 74.0 ± 6.2; 53.2% female), with baseline self-reported sleep data, and positron emission tomography-determined brain Aß measured over a minimum of three time points (range 33.3-72.7 months). Analyses included random slopes and intercepts, interaction for apolipoprotein E (APOE) ε4 allele status, and time, adjusting for sex and baseline age. RESULTS: Sleep duration <6 hours, in APOE ε4 carriers, and sleep efficiency <65%, in the whole sample and APOE ε4 non-carriers, is associated with faster accumulation of brain Aß. DISCUSSION: These findings suggest a role for self-reported suboptimal sleep efficiency and duration in the accumulation of Alzheimer's disease (AD) neuropathology in CU individuals. Additionally, poor sleep efficiency represents a potential route via which individuals at lower genetic risk may progress to preclinical AD. Highlights: In cognitively unimpaired older adults self-report sleep is associated with brain amyloid beta (Aß) accumulation.Across sleep characteristics, this relationship differs by apolipoprotein E (APOE) genotype.Sleep duration <6 hours is associated with faster brain Aß accumulation in APOE ε4 carriers.Sleep efficiency < 65% is associated with faster brain Aß accumulation in APOE ε4 non-carriers.Personalized sleep interventions should be studied for potential to slow Aß accumulation.

Associations between multidomain modifiable dementia risk factors with AD biomarkers and cognition in middle-aged and older adults.

This study aimed to determine associations between modifiable dementia risk factors (MDRF), across domains mood symptomatology, lifestyle behaviors, cardiovascular conditions, cognitive/social engagement, sleep disorders/symptomatology, with cognition, beta-amyloid (Aß) and tau, and brain volume. Middle-aged/older adults (n=82) enrolled in a sub-study of the Healthy Brain Project completed self-report questionnaires and a neuropsychological battery. Cerebrospinal fluid levels of Aß 1-42, total tau (t-tau), and phosphorylated tau (p-tau181) (Roche Elecsys), and MRI markers of hippocampal volume and total brain volume were obtained. Participants were classified as no/single domain risk (≤1 domains) or multidomain risk (≥2 domains). Compared to the no/single domain risk group, the multidomain risk group performed worse on the Preclinical Alzheimer's Cognitive Composite (d=0.63, p=.005), and Executive Function (d=0.50, p=.016), and had increased p-tau181 (d=0.47, p=.042) and t-tau (d=0.54, p=.021). In middle-aged/older adults, multidomain MDRFs were related to increases in tau and worse cognition, but not Aß or brain volume. Findings suggest that increases in AD biomarkers are apparent in midlife, particularly for individuals with greater burden, or variety of MDRFs.

BDNF Val66Met moderates episodic memory decline and tau biomarker increases in early sporadic Alzheimer's disease.

OBJECTIVE: Allelic variation in the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism has been shown to moderate rates of cognitive decline in preclinical sporadic Alzheimer's disease (AD; i.e., Aß + older adults), and pre-symptomatic autosomal dominant Alzheimer's disease (ADAD). In ADAD, Met66 was also associated with greater increases in CSF levels of total-tau (t-tau) and phosphorylated tau (p-tau181). This study sought to determine the extent to which BDNF Val66Met is associated with changes in episodic memory and CSF t-tau and p-tau181 in Aß + older adults in early-stage sporadic AD. METHOD: Aß + Met66 carriers (n = 94) and Val66 homozygotes (n = 192) enrolled in the Alzheimer's Disease Neuroimaging Initiative who did not meet criteria for AD dementia, and with at least one follow-up neuropsychological and CSF assessment, were included. A series of linear mixed models were conducted to investigate changes in each outcome over an average of 2.8 years, covarying for CSF Aß42, APOE ε4 status, sex, age, baseline diagnosis, and years of education. RESULTS: Aß + Met66 carriers demonstrated significantly faster memory decline (d = 0.33) and significantly greater increases in CSF t-tau (d = 0.30) and p-tau181 (d = 0.29) compared to Val66 homozygotes, despite showing equivalent changes in CSF Aß42. CONCLUSIONS: These findings suggest that reduced neurotrophic support, which is associated with Met66 carriage, may increase vulnerability to Aß-related tau hyperphosphorylation, neuronal dysfunction, and cognitive decline even prior to the emergence of dementia. Additionally, these findings highlight the need for neuropsychological and clinicopathological models of AD to account for neurotrophic factors and the genes which moderate their expression.

Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals.

Importance: Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases. Objective: To derive subgroups with common patterns of variation in participants without diagnosed cognitive impairment (WODCI) in a data-driven manner and relate them to genetics, biomedical measures, and cognitive decline trajectories. Design, Setting, and Participants: Data acquisition for this cohort study was performed from 1999 to 2020. Data consolidation and harmonization were conducted from July 2017 to July 2021. Age-specific subgroups of structural brain measures were modeled in 4 decade-long intervals spanning ages 45 to 85 years using a deep learning, semisupervised clustering method leveraging generative adversarial networks. Data were analyzed from July 2021 to February 2023 and were drawn from the Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) international consortium. Individuals WODCI at baseline spanning ages 45 to 85 years were included, with greater than 50 000 data time points. Exposures: Individuals WODCI at baseline scan. Main Outcomes and Measures: Three subgroups, consistent across decades, were identified within the WODCI population. Associations with genetics, cardiovascular risk factors (CVRFs), amyloid ß (Aß), and future cognitive decline were assessed. Results: In a sample of 27 402 individuals (mean [SD] age, 63.0 [8.3] years; 15 146 female [55%]) WODCI, 3 subgroups were identified in contrast with the reference group: a typical aging subgroup, A1, with a specific pattern of modest atrophy and white matter hyperintensity (WMH) load, and 2 accelerated aging subgroups, A2 and A3, with characteristics that were more distinct at age 65 years and older. A2 was associated with hypertension, WMH, and vascular disease-related genetic variants and was enriched for Aß positivity (ages ≥65 years) and apolipoprotein E (APOE) ε4 carriers. A3 showed severe, widespread atrophy, moderate presence of CVRFs, and greater cognitive decline. Genetic variants associated with A1 were protective for WMH (rs7209235: mean [SD] B = -0.07 [0.01]; P value = 2.31 × 10-9) and Alzheimer disease (rs72932727: mean [SD] B = 0.1 [0.02]; P value = 6.49 × 10-9), whereas the converse was observed for A2 (rs7209235: mean [SD] B = 0.1 [0.01]; P value = 1.73 × 10-15 and rs72932727: mean [SD] B = -0.09 [0.02]; P value = 4.05 × 10-7, respectively); variants in A3 were associated with regional atrophy (rs167684: mean [SD] B = 0.08 [0.01]; P value = 7.22 × 10-12) and white matter integrity measures (rs1636250: mean [SD] B = 0.06 [0.01]; P value = 4.90 × 10-7). Conclusions and Relevance: The 3 subgroups showed distinct associations with CVRFs, genetics, and subsequent cognitive decline. These subgroups likely reflect multiple underlying neuropathologic processes and affect susceptibility to Alzheimer disease, paving pathways toward patient stratification at early asymptomatic stages and promoting precision medicine in clinical trials and health care.

Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering.

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes.

Physical activity and brain amyloid beta: A longitudinal analysis of cognitively unimpaired older adults.

INTRODUCTION: The current study evaluated the relationship between habitual physical activity (PA) levels and brain amyloid beta (Aß) over 15 years in a cohort of cognitively unimpaired older adults. METHODS: PA and Aß measures were collected over multiple timepoints from 731 cognitively unimpaired older adults participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Aging. Regression modeling examined cross-sectional and longitudinal relationships between PA and brain Aß. Moderation analyses examined apolipoprotein E (APOE) ε4 carriage impact on the PA-Aß relationship. RESULTS: PA was not associated with brain Aß at baseline (ß = -0.001, p = 0.72) or over time (ß = -0.26, p = 0.24). APOE ε4 status did not moderate the PA-Aß relationship over time (ß = 0.12, p = 0.73). Brain Aß levels did not predict PA trajectory (ß = -54.26, p = 0.59). DISCUSSION: Our study did not identify a relationship between habitual PA and brain Aß levels. HIGHLIGHTS: Physical activity levels did not predict brain amyloid beta (Aß) levels over time in cognitively unimpaired older adults (≥60 years of age). Apolipoprotein E (APOE) ε4 carrier status did not moderate the physical activity-brain Aß relationship over time. Physical activity trajectories were not impacted by brain Aß levels.

Evolocumab in paediatric heterozygous familial hypercholesterolaemia: cognitive function during 80 weeks of open-label extension treatment.

AIMS: PCSK9 inhibition intensively lowers low density lipoprotein cholesterol and is well tolerated in adults and paediatric patients with familial hypercholesterolaemia (FH). HAUSER-RCT showed that 24 weeks of treatment with evolocumab in paediatric patients did not affect cognitive function. This study determined the effects of 80 additional weeks of evolocumab treatment on cognitive function in paediatric patients with heterozygous FH. METHODS AND RESULTS: HAUSER-OLE was an 80-week open-label extension of HAUSER-RCT, a randomized, double-blind, 24-week trial evaluating the efficacy and safety of evolocumab in paediatric patients (ages 10-17 years) with FH. During the OLE, all patients received monthly 420 mg subcutaneous evolocumab injections. Tests of psychomotor function, attention, visual learning, and executive function were administered at baseline and Weeks 24 and 80 of the OLE. Changes over time were analysed descriptively and using analysis of covariance. Cohen's d statistic was used to evaluate the magnitude of treatment effects. Analysis of covariance results indicated no decrease in performance across visits during 80 weeks of evolocumab treatment for Groton Maze Learning, One Card Learning accuracy, Identification speed, or Detection speed (all P > 0.05). Performance on all tasks was similar for those who received placebo or evolocumab in the RCT (all P > 0.05). For all tests, the least square mean differences between patients who received placebo vs. evolocumab in the parent study were trivial (all Cohen's d magnitude < 0.2). CONCLUSION: In paediatric patients with FH, 80 weeks of open-label evolocumab treatment had no negative impact on cognitive function. REGISTRATION: ClinicalTrials.gov identifier: NCT02624869.

Some children are born with a genetic disorder that causes high cholesterol, which leads to heart disease. Children with high cholesterol can be treated with evolocumab, a medication that lowers blood cholesterol. Because cholesterol is important for development and adequate function of the brain, there is a concern that lowering cholesterol in children may affect mental ability. In this study, we tested whether treating children with evolocumab for 80 weeks affected mental ability in performing several tasks. A battery of tests that measure executive function (Groton Maze Learning Test), visual learning (One Card Learning Test), visual attention (Identification Test), and psychomotor function (Detection Test) showed no decrease in performance across visits during 80 weeks of evolocumab treatment. Performance on all tasks was similar for the children who received placebo for the first 24 weeks then received evolocumab for an additional 80 weeks (placebo/evolocumab) and those who received evolocumab for 24 weeks then received evolocumab for an additional 80 weeks (evolocumab/evolocumab).

Increased intraindividual variability in reaction time performance is associated with emerging cognitive decline in cognitively unimpaired adults.

OBJECTIVE: To investigate whether intraindividual variability (IIV) in reaction time (RT) over monthly administered cognitive tasks is increased in cognitively unimpaired older adults who are at risk for cognitive decline, and whether this is independent of mean RT performance. METHOD: N = 109 cognitively unimpaired individuals (age 77.4 ± 5.0, 61.5% female, Mini-Mental State Examination 29.1 ± 1.3) from the Harvard Aging Brain Study completed the self-administered Computerized Cognitive Composite (C3) monthly at home for up to 1 year (12.7 ± 3.2 C3 assessments). Baseline C3 assessment coincided with routine in-clinic visits, including amyloid and tau positron emission tomography imaging and standardized cognitive testing, with cognitive testing repeated annually (1.6 ± 1.2 years follow-up). The C3 includes two simple RT tasks and two complex RT tasks. IIV estimates were derived by computing intraindividual standard deviations on residual RT scores after regressing out age and session order effects. Cross-sectional associations of IIV with cognition (global cognition, memory, executive functions [EF], processing speed) and amyloid and tau burden were examined using linear regression analyses correcting for demographics and mean RT. The association between IIV and cognitive decline was assessed using linear mixed models correcting for demographic factors, mean RT, and amyloid burden. RESULTS: After adjusting for mean RT, increased IIV on complex RT tasks was independently associated with worse EF performance (ß = -0.10, 95% CI [-.16, -0.03], p = .004), greater inferior-temporal tau deposition (ß = 0.18, 95% CI [0.02, 0.34], p = .024), and faster cognitive decline in those with elevated amyloid (ß = -0.62, 95% CI [-1.18, -0.06], p = .033). CONCLUSIONS: Increased variability in monthly RT may reflect subtle EF deficits and provide unique information about short-term cognitive decline in preclinical Alzheimer's disease. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Sensitivity of Individual and Composite Test Scores from the Cogstate Brief Battery to Mild Cognitive Impairment and Dementia Due to Alzheimer's Disease.

BACKGROUND: The Cogstate Brief Battery (CBB) is a computerized cognitive test battery used commonly to identify cognitive deficits related to Alzheimer's disease (AD). However, AD and normative samples used to understand the sensitivity of the CBB to AD in the clinic have been limited, as have the outcome measures studied. OBJECTIVE: This study investigated the sensitivity of CBB outcomes, including potential composite scores, to cognitive impairment in mild cognitive impairment (MCI) and dementia due to AD, in carefully selected samples. METHODS: Samples consisted of 4,871 cognitively unimpaired adults and 184 adults who met clinical criteria for MCI (Clinical Dementia Rating (CDR) = 0.5) or dementia (CDR > 0.5) due to AD and CBB naive. Speed and accuracy measures from each test were examined, and theoretically- and statistically-derived composites were created. Sensitivity and specificity of classification of cognitive impairment were compared between outcomes. RESULTS: Individual CBB measures of learning and working memory showed high discriminability for AD-related cognitive impairment for CDR 0.5 (AUCs ∼ 0.79-0.88), and CDR > 0.5 (AUCs ∼ 0.89-0.96) groups. Discrimination ability for theoretically derived CBB composite measures was high, particularly for the Learning and Working Memory (LWM) composite (CDR 0.5 AUC = 0.90, CDR > 0.5 AUC = 0.97). As expected, statistically optimized linear composite measures showed strong discrimination abilities albeit similar to the LWM composite. CONCLUSIONS: In older adults, the CBB is effective for discriminating cognitive impairment due to MCI or AD-dementia from unimpaired cognition with the LWM composite providing the strongest sensitivity.

Longitudinal trajectories of basal forebrain volume in normal aging and Alzheimer's disease.

Dysfunction of the cholinergic basal forebrain (BF) system and amyloid-ß (Aß) deposition are early pathological features in Alzheimer's disease (AD). However, their association in early AD is not well-established. This study investigated the nature and magnitude of volume loss in the BF, over an extended period, in 516 older adults who completed Aß-PET and serial magnetic resonance imaging scans. Individuals were grouped at baseline according to the presence of cognitive impairment (CU, CI) and Aß status (Aß-, Aß+). Longitudinal volumetric changes in the BF and hippocampus were assessed across groups. The results indicated that high Aß levels correlated with faster volume loss in the BF and hippocampus, and the effect of Aß varied within BF subregions. Compared to CU Aß+ individuals, Aß-related loss among CI Aß+ adults was much greater in the predominantly cholinergic subregion of Ch4p, whereas no difference was observed for the Ch1/Ch2 region. The findings support early and substantial vulnerability of the BF and further reveal distinctive degeneration of BF subregions during early AD.