Cognitive Markers Research Articles

Age‐associated biomarker profiles in a non‐human primate model of sporadic CAA

AbstractBackgroundAdvancements of novel therapeutic interventions for Alzheimer’s disease (AD) have been hindered by a lack of animal models in preclinical research that naturally recapitulate the pathologic features of disease with age. Our prior work demonstrated the utility of squirrel monkeys (SQMs), a non‐human primate (NHP) model of sporadic AD pathology with abundant cerebral amyloid angiopathy (CAA), as an opportune species to assess the potential therapeutic outcomes and safety profile of our novel immunomodulatory approach using TLR9 agonist CpG‐ODN. Here we provide the first longitudinal and cross‐sectional study on aging and disease pathogenesis in SQMs by characterizing blood/CSF biomarker signatures of AD/CAA pathology.MethodSIMOA, ELISA, and Luminex platform immunoassays were utilized to investigate age‐associated profiles of plasma and CSF biomarkers involved in neurodegeneration (NfL, GFAP), brain and peripheral inflammation/glia activation (YKL‐40/CHI3L1, sTREM2), and cerebrovascular dysfunction/BBB integrity (albumin index, bFGF, VCAM‐1, MMPs).ResultCross‐sectional analysis revealed statistically significant differences in plasma NfL and GFAP levels between age groups ranging from 6 to 23 years old (NfL: one‐way ANOVA, f(6,84)) = 6.395, p<0.0001; GFAP: one‐way ANOVA, f(6,84)) = 8.111, p<0.0001). Preliminary assessments revealed significantly higher plasma YKL‐40/CHI3L1 and MMP1 levels, while VCAM‐1, bFGF, and MMP2 levels were significantly lower in the geriatric SQMs when compared to the young group. CSF analyses demonstrated significantly higher YKL‐40/CHI3L1 and bFGF levels, and an elevated albumin index among the geriatric cohort when compared to young monkeys. Moreover, a longitudinal follow‐up of a separate SQM cohort over three years (19‐22 years old) revealed a significant increase in plasma sTREM2 levels; neurogranin levels appeared to increase, but differences were not significant (p = 0.0625, Wilcoxon signed‐rank test). Further characterizations of fluid biomarker trajectories and their relationships with age‐associated changes in cognition and neuroimaging markers are forthcoming.ConclusionSQMs present a valuable opportunity to evaluate biomarker signatures associated with aging and the development of cerebrovascular amyloid pathology. The use of this advantageous model is important to enhance the translational potential of novel therapeutics for human benefit.

Clinical Manifestations.

In recent years, there has been an increase in the number of case reports of families with autosomal dominant Alzheimer's disease (ADAD) in Latin America (LA). Nevertheless, little is known about the clinical phenotypes and demographic characteristics of mutations in each country. Past literature has proved that variants in LA have different and unique characteristics than those reported in Asia, North America, and Europe. Clinical heterogeneity in ADAD supports the need to study clinical phenotypes, especially in preclinical stages, to develop cognitive and clinical markers of the disease. We aimed to describe clinical and cognitive characteristics at baseline assessment of an Argentina PSEN1 p.M146L family enrolled at DIAN. Fifteen Dian Participants living in Buenos Aires and its suburbs and in Taco Pozo, a rural and isolated community from the Province of Salta, positive for the PSEN1 p.M146L mutation, were recruited. DNA was obtained from peripheral blood leukocytes according to standard protocols. In addition, exon 5 of the PSEN1 gene was PCR-amplified, and Sanger sequencing was performed. NACC Uniform Data Set clinical assessment, including the 2.0 UDS Neuropsychological Battery, was administered. Two groups were used to compare cognitive data: Patients with CDR:0 (n:10) and patients with CDR>0 (n:5). The mean age at symptom onset reported in this cohort was 42,90 (SD: 4,62). Significant differences were found in several cognitive measures: Logical Memory Immediate, TMT B and Digit Backward (<0,001); MMSE, Category Fluency Animals, TMT A and Digit Symbol(<0,05). In neurological signs, paraplegia was reported in one of the patients. As expected, differences in neuropsychological tests showed a prevalence of memory deficits, however, dysexecutive symptoms were also present for this mutation. Paraplegia in PSEN1 p.M146L has not been reported in the literature so far. Ongoing longitudinal work will be important in tracking changes in this cohort. Other characteristics, proper of underrepresented groups, such as socioeconomic status, education, race, and ethnicity, deserve appropriate follow-up. Future studies are planned, comparing urban and rural populations in this cohort with the same mutation.

The Early Detection of Neurodegenerative diseases initiative: emerging insights from the initial implementation of a digital toolkit

AbstractBackgroundThe benefits of the early detection of the neurodegenerative and vascular pathologies which cause dementia are widely acknowledged. These include the opportunity to initiate risk‐reduction strategies, disease‐modifying therapies, and future care planning. However, current pathological biomarkers have several important drawbacks, as they are typically invasive, expensive, impractical, insensitive, or lack real‐world validation. Conversely, the targeted utilization of non‐invasive and inexpensive digital technologies which can be integrated into everyday life raises the possibility of capturing a ‘digital‐fingerprint’ of early disease.MethodThe Early Detection of Neurodegenerative diseases (EDoN) initiative is a meta‐cohort study spearheaded by Alzheimer’s Research UK. EDoN is acquiring high‐dimensional data from a ‘digital toolkit’ comprising a smartwatch (Fitbit Charge 4/5), smartphone software (Mezurio and Longevity), and an electroencephalography headband (Dreem 3). In combination with conventional digital, cognitive and biological markers, these data will inform the development of powerful machine learning models to detect dementia‐causing diseases at the very earliest stages. The initial phase, incorporating four cohorts across three continents, is already underway, and will recruit nearly 900 participants. Cohorts are recruiting healthy individuals, as well as patients with subjective/mild cognitive impairment, or established dementia. Data from version‐1 of the toolkit is being collected over two‐week periods at 3‐monthly intervals for a minimum of 12 months.ResultWe will present early insights from the implementation of the EDoN digital toolkit version‐1. These will include sample characteristics, feasibility and acceptability, and participants’ compliance. PPI data confirmed good acceptability but the potential for inequity due to technical problems and poor digital literacy. Pilot data indicate that six‐month adherence to the EDoN digital tools varies between 82‐89%. The forthcoming AAIC presentation will include important recruitment, toolkit acceptability and analytic updates.ConclusionThe initial implementation of the EDoN digital toolkit suggests that it is feasible and acceptable to collect high‐dimensional digital data over a six‐month period. These ‘digital‐fingerprints’ will form the basis of the initial development of machine learning models to identify dementia‐causing pathologies substantially earlier. The insights gained will also inform the development of version‐2 of the EDoN digital toolkit which will be incorporated into the next meta‐cohort prospective study of around 4,000 participants.

CSF‐plasma albumin ratio differs by sex in community dwelling older adults

AbstractBackgroundBlood‐brain barrier (BBB) permeability is associated with Alzheimer’s disease (AD) and neurodegeneration. Cerebrospinal fluid (CSF)/plasma albumin ratio (QAlb) is a biomarker commonly used to approximate BBB and blood‐CSF barrier (BCSFB) integrity. While sex‐based differences in AD risk are well‐established, limited work has evaluated these differences with QAlb and neurodegeneration and neuropsychological outcomes. Here, we examine if sex modifies the association of QAlb with neuropsychological and structural neuroimaging markers of neurodegeneration in community‐dwelling older adults.MethodVanderbilt Memory and Aging Project participants (n = 152, 72±7 years, 33% female) completed a fasting blood draw, lumbar puncture, neuropsychological assessment, and multimodal 3T brain magnetic resonance imaging (MRI) to capture grey matter volumes and white matter hyperintensities (WMHs). Ordinary least squares regressions cross‐sectionally related sex to QAlb. Follow‐up models tested a sex x QAlb interaction with neuropsychological and MRI outcomes. Models adjusted for age, sex, race/ethnicity, education, cognitive status, Framingham Stroke Risk Profile score (minus age), apolipoprotein (APOE)‐e4 status, and (for MRI outcomes) intracranial volume.ResultFemale sex was associated with lower QAlb (p&lt;0.001). However, sex did not interact with QAlb on any neuropsychological (p‐values&gt;0.7) or neuroimaging outcomes (p‐values&gt;0.2). Models stratified by sex were also null for neuropsychological (p‐values&gt;0.93) and neuroimaging outcomes (p‐values&gt;0.11).ConclusionElevated QAlb is believed to reflect disrupted brain‐barrier integrity such that blood‐based albumin (which lacks an active transport mechanism across the BBB) can enter the brain parenchyma and travel to the CSF. We found that female sex is associated with lower QAlb levels but does not interact with early cognitive or neuroimaging markers of AD‐associated neurodegeneration. The strong association between female sex and higher brain‐barrier integrity highlights the importance of considering sex differences when applying QAlb in clinical and research settings. Funding: R01‐AG034962, K24‐AG046373, T32‐AG058524, P20‐AG068082

Developing Topics.

Phosphorylated tau (pTau) in cerebrospinal fluid (CSF) is a biomarker of Alzheimer's disease (AD) pathology. Recent studies confirm that pTau levels in plasma may provide a more cost-effective and less invasive method of assessing AD pathology, which have shown to also be relevant in preclinical populations. Neurofilament light (NfL) is a measure of neuroaxonal damage associated with poorer cognitive outcomes. Generalization is a validated cognitive marker of hippocampal dysfunction, with individuals showing deficits years before overt cognitive impairment. Using a computer generalization task sensitive to medial temporal lobe (MTL) pathology, the current study examined the relationship between generalization performance and plasma pTau and NfL levels in a population with elevated AD risk, older African Americans. 130 older, cognitively normal African Americans (M age = 71.60 years, SD = 6.58; M edu = 13.88 years, SD = 2.37; n = 98 women) provided blood samples and completed a hippocampal-dependent cognitive task. Participants' normal cognitive status was confirmed using the Mini-Mental State Examination (M MMSE = 26.98, SD = 2.14) and generalization performance was assessed using the Acquired Equivalence Task. Plasma was extracted from blood samples to assess pTau181, pTau231, and NfL levels. Based on the sample median thresholds, participants were characterized as plasma tau positive (≥16.189 for pTau181 and ≥17.537 for pTau231). Participants positive for plasma pTau231 (n = 76) demonstrated worse generalization performance with increased pTau231 levels, B = -0.296, p = 0.024, as did participants positive for plasma pTau181, B = -0.247. p = 0.042, demonstrating that tau positivity status is related to MTL dysfunction. Moreover, pTau231 was more strongly associated with generalization performance, indicating that it is a more sensitive biomarker than pTau181 among preclinical AD populations. Higher levels of plasma NfL were also significantly associated with lower generalization performance B = -0.243. p = 0.008. Plasma isoforms pTau181 and pTau231 may reflect different phases of tau progression, with plasma pTau231 shown to be better at capturing subtle MTL dysfunction. Plasma tau positivity status and measures of axonal damage along with lower generalization performance scores may be useful indicators of cognitive dysfunction in preclinical AD populations.

Semantic cognition as an early cognitive marker of Alzheimer’s disease: importance of executive processes mediation

AbstractBackgroundImpaired semantic memory is one of the earliest characteristic features of Alzheimer’s disease. Its assessment is crucial to accurately predict conversion to Alzheimer disease related disorders (ADRD). Recent evidence supports the necessity to differentiate between subprocesses of semantic cognition: a) activation in the semantic representation system; b) executive processes to control or select relevant aspects of semantic knowledge. In this study we compare semantic memory tests that differ in these subprocesses to find out which of them are the best predictors of conversion of MCI to ACD in two years. We also want to identify which semantic memory tests have more sensitivity and specificity at the baseline in the differentiation MCI‐no converters and MCI converters after two yearsMethodWe assessed 130 amnestic MCI patients. Semantic memory tests more based on integrity of semantic knowledge (Similarities, ACE‐language) and more executive determined (verbal fluency – phonemic and categories, Boston Naming Test) were administered at baseline and at 2‐years follow‐up, together with cognitive screening tools and IADL measures. A binary regression model was used to examine which semantic memory tests predict MCI progression to Alzheimer’s Clinical Syndrome (ACS) in two years. ROC curves were used to study early clinical diagnosis differentiating MCI converters and MCI non convertersResultOnly semantic category fluency test significantly explained the conversion to ACS (p&lt;.01). Baseline score semantic categories fluency were significantly lower in MCI patients who develop ACS after two years (p&lt;.001). ROC curves showed that semantic categories fluency and Boston Naming tests were the best tests to differentiate at baseline between MCI converter and non‐converter (AUC = 0.768, p&lt;0,0001 and AUC = 0.712, p&lt;0,01, respectively)ConclusionSemantic category fluency test was the best predictor from MCI to ACS conversion in two years. Semantic category fluency and Boston Naming tests clearly identify people with high risk to develop ACS in two years. Semantic memory tests including executive contributions could detect and characterize prodromal Alzheimer’s disease

Primacy and recency effects in verbal memory are differentially associated with post‐mortem frontal cortex p‐tau217 level in a mixed sample of community‐dwelling older adults

AbstractBackgroundEmerging research indicates plasma phosphorylated (p)‐tau217 levels may demonstrate sensitivity to preclinical and symptomatic Alzheimer’s disease (AD). Serial position effects (primacy and recency) in verbal memory are sensitive cognitive markers of early AD; however associations between these measures and p‐tau217 in postmortem brain samples are unclear. In a mixed sample of older adults, this study examined how primacy and recency scores measured years before death are associated with post‐mortem levels of p‐tau217, with p‐tau202 as a complementary post‐mortem measure of early tau phosphorylation.MethodData were used from the Rush University Religious Orders Study and the Memory and Aging Project. Participants were 1098 community‐dwelling older adults (68.9% female, M age = 80.1) who were non‐demented at baseline and followed until death (M follow‐up years = 9.2; status at death: 34.7% unimpaired, 26.0% mild cognitive impairment, 39.3% dementia). Baseline serial position scores were calculated as the proportion of words recalled from the beginning (primacy) and end (recency) of the CERAD Word Memory List. A neuropathological exam classified Braak stage. A middle frontal gyrus tissue sample was used to quantify p‐tau217 and p‐tau202 with selected reaction monitoring proteomics. Linear regression analyses examined associations of cognitive scores with p‐tau, adjusting for age, sex, education, APOE e4 status, Braak stage, and time to death.ResultAs expected, higher Braak scores were associated with higher levels of brain p‐tau217. In the fully adjusted model, higher baseline primacy scores (b = ‐.27, p = .026), but not recency scores (b = ‐.02, p = .901), were associated with lower levels of p‐tau217 but not p‐tau202 in middle frontal cortex. Higher delayed recall (b = ‐.08, p = .007), but not immediate recall (b = ‐.01, p = .071), was also associated with lower p‐tau217.ConclusionPrimacy scores measured years before death were associated with the outcome of post‐mortem brain levels of p‐tau217, but not p‐tau202. The differential associations of serial position scores with p‐tau suggest they may add complementary information about early neuropathological changes when used in conjunction with routine delayed recall scores. These findings further contribute to evidence for p‐tau217 as a sensitive biomarker of AD.

Clinical Manifestations.

Subjective cognitive complaints (SCC) in the elderly may represent an early cognitive marker of Alzheimer's disease (AD). Currently, there is no recommended gold standard for evaluating SCC. In addition, available questionnaires were originally developed to identify individuals at later stages of AD. Based on previous research, we constructed the Subjective Cognitive Changes Questionnaire (SCC-Q), which includes items potentially sensitive to early cognitive decline. The study aimed to analyse reliability of the individual items and construct and convergent validity of the SCC-Q. A total of 211 non-demented participants over the age of 55 from the Czech Brain Aging Study (CBAS) underwent a comprehensive neuropsychological examination, based on which they were classified into two groups: patients with amnestic mild cognitive impairment (n = 88) and those with subjective cognitive decline (SCD) (n = 88). Further, we included cognitively healthy volunteers without SCC (n = 35). All participants completed the novel 26-item SCC-Q in which they evaluated change in specific cognitive abilities during the last 5 years on a 5-point Likert scale. The structure of the SCC-Q was explored using the principal component analysis (PCA) with varimax rotation. To analyse associations between the components and cognitive performance (convergent validity), non-parametric partial rank correlations controlled for sex, age and education were performed. Cognitive performance was expressed as composite z-scores representing memory, attention and working memory, language, executive, and visuospatial function. Item analysis showed that all included items were highly reliable (McDonald's Ω > 0.9, Cronbach's α > 0.9). Using the PCA, four components explaining 57.6% of the variance were identified. Two of them were significantly associated with memory, attention and working memory, and executive or visuospatial function, respectively (all ps ≤ 0.048). The component more closely associated with cognitive domains includes items related to spatial orientation changes. The SCC-Q has the potential to become a valuable method for clinical practice in identifying individuals at risk of developing cognitive deficits. Further analyses are needed to confirm its validity.

MRI or 18F-FDG PET for Brain Age Gap Estimation: Links to Cognition, Pathology, and Alzheimer Disease Progression.

Deviations of brain age from chronologic age, known as the brain age gap (BAG), have been linked to neurodegenerative diseases such as Alzheimer disease (AD). Here, we compare the associations of MRI-derived (atrophy) or 18F-FDG PET-derived (brain metabolism) BAG with cognitive performance, neuropathologic burden, and disease progression in cognitively normal individuals (CNs) and individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI). Methods: Machine learning pipelines were trained to estimate brain age from 185 matched T1-weighted MRI or 18F-FDG PET scans of CN from the Alzheimer's Disease Neuroimaging Initiative and validated in external test sets from the Open Access of Imaging and German Center for Neurodegenerative Diseases-Longitudinal Cognitive Impairment and Dementia studies. BAG was correlated with measures of cognitive performance and AD neuropathology in CNs, SCD subjects, and MCI subjects. Finally, BAG was compared between cognitively stable and declining individuals and subsequently used to predict disease progression. Results: MRI (mean absolute error, 2.49 y) and 18F-FDG PET (mean absolute error, 2.60 y) both estimated chronologic age well. At the SCD stage, MRI-based BAG correlated significantly with beta-amyloid1-42 (Aβ1-42) in cerebrospinal fluid, whereas 18F-FDG PET BAG correlated with memory performance. At the MCI stage, both BAGs were associated with memory and executive function performance and cerebrospinal fluid Aβ1-42, but only MRI-derived BAG correlated with phosphorylated-tau181/Aβ1-42 Lastly, MRI-estimated BAG predicted MCI-to-AD progression better than 18F-FDG PET-estimated BAG (areas under the curve, 0.73 and 0.60, respectively). Conclusion: Age was reliably estimated from MRI or 18F-FDG PET. MRI BAG reflected cognitive and pathologic markers of AD in SCD and MCI, whereas 18F-FDG PET BAG was sensitive mainly to early cognitive impairment, possibly constituting an independent biomarker of brain age-related changes.

Neuroprotective Effects of Moderate Hypoxia: A Systematic Review.

Emerging evidence highlights moderate hypoxia as a candidate treatment for brain disorders. This systematic review examines findings and the methodological quality of studies investigating hypoxia (10-16% O2) for ≥14 days in humans, as well as the neurobiological mechanisms triggered by hypoxia in animals, and suggests optimal treatment protocols to guide future studies. We followed the preferred reporting items for systematic reviews and meta-analysis (PRISMA) 2020. Searches were performed on PubMed/MEDLINE, PsycInfo, EMBASE, and the Cochrane Library, in May-September 2023. Two authors independently reviewed the human studies with the following tools: (1) revised Cochrane collaboration's risk of bias for randomized trials 2.0; (2) the risk of bias in nonrandomized studies of interventions. We identified 58 eligible studies (k = 8 human studies with N = 274 individuals; k = 48 animal studies) reporting the effects of hypoxia on cognition, motor function, neuroimaging, neuronal/synaptic morphology, inflammation, oxidative stress, erythropoietin, neurotrophins, and Alzheimer's disease markers. A total of 75% of human studies indicated cognitive and/or neurological benefits, although all studies were evaluated ashigh risk of bias due to a lack of randomization and assessor blinding. Low-dose intermittent or continuous hypoxia repeated for 30-240 min sessions, preferably in combination with motor-cognitive training, produced beneficial effects, and high-dose hypoxia with longer (≥6 h) durations and chronic exposure produced more adverse effects. Larger and methodologically stronger translational studies are warranted.

Application of bi-directional long-short-term memory network in cognitive age prediction based on EEG signals

Electroencephalography (EEG) measures changes in neuronal activity and can reveal significant changes from infancy to adulthood concomitant with brain maturation, making it a potential physiological marker of brain maturation and cognition. To investigate a promising deep learning tool for EEG classification, we applied the bidirectional long short-term memory (BLSTM) algorithm to analyze EEG data from the pediatric EEG laboratory of Taipei Tzu Chi Hospital. The trained BLSTM model was 86% accurate when identifying EEGs from young children (8 months–6 years) and adolescents (12–20 years). However, there was only a modest classification accuracy (69.3%) when categorizing EEG samples into three age groups (8 months–6 years, 6–12 years, and 12–20 years). For EEG samples from patients with intellectual disability, the prediction accuracy of the trained BLSTM model was 46.4%, which was significantly lower than its accuracy for EEGs from neurotypical patients, indicating that the individual’s intelligence plays a major role in the age prediction. This study confirmed that scalp EEG can reflect brain maturation and the BLSTM algorithm is a feasible deep learning tool for the identification of cognitive age. The trained model can potentially be applied to clinical services as a supportive measurement of neurodevelopmental status.

Short-Term Memory Deficit Associates with miR-153-3p Upregulation in the Hippocampus of Middle-Aged Mice

The early stages of ageing are a critical time window in which the ability to detect and identify precocious molecular and cognitive markers can make the difference in determining a healthy vs unhealthy course of ageing. Using the 6-different object task (6-DOT), a highly demanding hippocampal-dependent recognition memory task, we classified a population of middle-aged (12-month-old) CD1 male mice in Impaired and Unimpaired based on their short-term memory. This approach led us to identify a different microRNAs expression profile in the hippocampus of Impaired mice compared to Unimpaired ones. Among the dysregulated microRNAs, miR-153-3p was upregulated in the hippocampus of Impaired mice and appeared of high interest for its putative target genes and their possible implication in memory-related synaptic plasticity. We showed that intra-hippocampal injection of the miR-153-3p mimic in adult (3-month-old) mice is sufficient to induce a short-term memory deficit similar to that observed in middle-aged Impaired mice. Overall, these findings unravel a novel role for hippocampal miR-153-3p in modulating short-term memory that could be exploited to prevent early cognitive deficits in ageing.

Comprehension of irony in autistic children: The role of theory of mind and executive function.

Although previous studies have examined irony comprehension in autistic children and potential impact factors, the relationship between theory of mind (ToM), executive function (EF), symptoms of autism, and comprehension of irony in this population remains largely unknown. This study explored irony comprehension in autistic children and examined the roles of ToM and EF in linking autism symptoms to deficits in irony comprehension. Twenty autistic children were compared with 25 typically developing (TD) children in an irony story picture task, ToM task, and EF task. The results showed that autistic children had impaired comprehension of irony compared with TD children, and performance on ironic stories showed a significant moderate discriminatory effect in predicting autistic children. A ToM deficit has also been proposed for autistic children. Comprehension of irony was significantly correlated with second-order ToM (2nd ToM) but was not significantly correlated with any components of EF. Moreover, 2nd ToM can predict the level of irony comprehension and mediate the relationship between symptoms of autism and irony comprehension. Taken together, these findings suggest that irony comprehension may offer a potential cognitive marker for quantifying syndrome manifestations in autistic children, and 2nd ToM may provide insight into the theoretical mechanism underlying the deficit in irony comprehension in this population.

Exploring the Potential of the Corpus Callosum Area as a Predictive Marker for Impaired Information Processing in Multiple Sclerosis

Early cognitive impairment (CI) detection is crucial in multiple sclerosis (MS). However, it can progress silently regardless of relapse activity and reach an advanced stage. We aimed to determine whether the corpus callosum area (CCA) is a sensitive and feasible marker for CI in MS compared to other neuroimaging markers. We assessed cognitive function in 77 MS patients using the Symbol Digit Modalities Test, Paced Auditory Serial Additions Task, Wechsler Adult Intelligence Scale-IV, and Wechsler Memory Scale-Revised. The neuroimaging markers included manually measured CCA, two diffusion tensor imaging markers, and nine volumetric measurements. Apart from volumes of the hippocampus and cerebellum, ten markers showed a significant correlation with all neuropsychological tests and significant differences between the groups. The normalized CCA demonstrated a moderate-to-strong correlation with all neuropsychological tests and successfully differentiated between the CI and cognitively normal groups with 80% sensitivity and 83% specificity. The marker had a large area under the curve and a high Youden index (0.82 and 0.63, respectively) and comparability with established cognitive markers. Therefore, the normalized CCA may serve as a reliable marker for CI in MS and can be easily implemented in clinical practice, providing a supportive diagnostic tool for CI in MS.

Symposium 04: Innovative Ways of Applying Digital Technology in Neuropsychology - A Sneak Peak into the Future

Summary Abstract:The explosion of digital technology in the past decade has led to unprecedented possibilities towards improving cognitive assessment and understanding brain health. Digital technology encompasses using a multitude of devices, such as laptops, smartphones, etc, to collect health-related data. The settings can be varied to include in-clinic, remote/virtual, or a combination of hybrid models for data collection. Data can be collected at a single time point or over a continued period of time. Furthermore, the unique combination of devices used, settings, and methods of collecting digital data can become even more exclusive against the backdrop of the 'purpose’ for conducting the digital study. This symposium, consisting of four abstracts, brings together the unique combination of digital studies with exclusive devices, methodologies, settings, and purposes. The topics range from how smartphone-based assessments can be applied to understand the interaction between day-to-day variability in sleep and cognition, to the use of computerized testing to investigate the associations between cognitive performance and markers of brain pathology (e.g. amyloid and tau status), to understanding cognition from an open-source smartphone application to passively and continuously capture sensor data including global positioning system trajectories, to the development and validation of an online simulated money management credit card task, and to determining the effects of cognitive rehabilitation via digital technology on cognition, neuropsychiatric symptoms, and memory strategies.

Explainable Machine Learning with Pairwise Interactions for Predicting Conversion from Mild Cognitive Impairment to Alzheimer's Disease Utilizing Multi-Modalities Data.

Predicting cognition decline in patients with mild cognitive impairment (MCI) is crucial for identifying high-risk individuals and implementing effective management. To improve predicting MCI-to-AD conversion, it is necessary to consider various factors using explainable machine learning (XAI) models which provide interpretability while maintaining predictive accuracy. This study used the Explainable Boosting Machine (EBM) model with multimodal features to predict the conversion of MCI to AD during different follow-up periods while providing interpretability. This retrospective case-control study is conducted with data obtained from the ADNI database, with records of 1042 MCI patients from 2006 to 2022 included. The exposures included in this study were MRI biomarkers, cognitive scores, demographics, and clinical features. The main outcome was AD conversion from aMCI during follow-up. The EBM model was utilized to predict aMCI converting to AD based on three feature combinations, obtaining interpretability while ensuring accuracy. Meanwhile, the interaction effect was considered in the model. The three feature combinations were compared in different follow-up periods with accuracy, sensitivity, specificity, and AUC-ROC. The global and local explanations are displayed by importance ranking and feature interpretability plots. The five-years prediction accuracy reached 85% (AUC = 0.92) using both cognitive scores and MRI markers. Apart from accuracies, we obtained features' importance in different follow-up periods. In early stage of AD, the MRI markers play a major role, while for middle-term, the cognitive scores are more important. Feature risk scoring plots demonstrated insightful nonlinear interactive associations between selected factors and outcome. In one-year prediction, lower right inferior temporal volume (<9000) is significantly associated with AD conversion. For two-year prediction, low left inferior temporal thickness (<2) is most critical. For three-year prediction, higher FAQ scores (>4) is the most important. During four-year prediction, APOE4 is the most critical. For five-year prediction, lower right entorhinal volume (<1000) is the most critical feature. The established glass-box model EBMs with multimodal features demonstrated a superior ability with detailed interpretability in predicting AD conversion from MCI. Multi features with significant importance were identified. Further study may be of significance to determine whether the established prediction tool would improve clinical management for AD patients.

Association between cerebrospinal fluid clusterin and biomarkers of Alzheimer's disease pathology in mild cognitive impairment: a longitudinal cohort study.

Clusterin, a glycoprotein implicated in Alzheimer's disease (AD), remains unclear. The objective of this study was to analyze the effect of cerebrospinal fluid (CSF) clusterin in relation to AD biomarkers using a longitudinal cohort of non-demented individuals. We gathered a sample comprising 86 individuals under cognition normal (CN) and 134 patients diagnosed with MCI via the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. To investigate the correlation of CSF clusterin with cognitive function and markers of key physiological changes, we employed multiple linear regression and mixed-effect models. We undertook a causal mediation analysis to inspect the mediating influence of CSF clusterin on cognitive abilities. Pathological characteristics associated with baseline Aβ42, Tau, brain volume, exhibited a correlation with initial CSF clusterin in the general population, Specifically, these correlations were especially prominent in the MCI population; CSF Aβ42 (PCN = 0.001; PMCI = 0.007), T-tau (PCN < 0.001; PMCI < 0.001), and Mid temporal (PCN = 0.033; PMCI = 0.005). Baseline CSF clusterin level was predictive of measurable cognitive shifts in the MCI population, as indicated by MMSE (β = 0.202, p = 0.029), MEM (β = 0.186, p = 0.036), RAVLT immediate recall (β = 0.182, p = 0.038), and EF scores (β = 0.221, p = 0.013). In MCI population, the alterations in brain regions (17.87% of the total effect) mediated the effect of clusterin on cognition. It was found that variables such as age, gender, and presence of APOE ε4 carrier status, influenced some of these connections. Our investigation underscored a correlation between CSF clusterin concentrations and pivotal AD indicators, while also highlighting clusterin's potential role as a protective factor for cognitive abilities in MCI patients.

Prefrontal event-related potential markers in association with mild cognitive impairment.

Alzheimer's disease (AD) is among the leading contributors of dementia globally with approximately 60-70% of its cases. Current research is focused on the mild cognitive impairment (MCI), which is associated with cognitive decline but does not disrupt routine activities. Event-related potential (ERP) research is essential in screening patients with MCI. Low-density channel electroencephalography (EEG) is frequently used due to its convenience, portability, and affordability, making it suitable for resource-constrained environments. Despite extensive research on neural biomarkers for cognitive impairment, there is a considerable gap in understanding the effects on early stages of cognitive processes, particularly when combining physiological and cognitive markers using portable devices. The present study aimed to examine cognitive shortfalls and behavioral changes in patients with MCI using prefrontal selective attention ERP recorded from a prefrontal two-channel EEG device. We assessed cognitive decline using the Mini-Mental State Examination (MMSE) and the Seoul Neuropsychological Screening Battery (SNSB). We administered auditory selective attention tasks to 598 elderly participants, including those with MCI (160) and cognitively normal (CN) individuals (407). We conducted statistical analyses such as independent t-tests, Pearson's correlations, and univariate and multiple logistic regression analyses to assess group differences and associations between neuropsychological tests, ERP measures, behavioral measures, and MCI prevalence. Our findings revealed that patients with MCI demonstrated slower information-processing abilities, and exhibited poorer task execution, characterized by reduced accuracy, increased errors, and higher variability in response time, compared to CN adults. Multiple logistic regression analyses confirmed the association between some ERP and behavioral measures with MCI prevalence, independent of demographic and neuropsychological factors. A relationship was observed between neuropsychological scores, ERP, and behavioral measures. The slower information processing abilities, and poor task execution in the MCI group compared to the CN individuals suggests flawed neurological changes and reduced attentional maintenance during cognitive processing, respectively. Hence, the utilization of portable EEG devices to capture prefrontal selective attention ERPs, in combination with behavioral assessments, holds promise for the identification of mild cognitive deficits and neural alterations in individuals with MCI. This approach could potentially augment the traditional neuropsychological tests during clinical screening for MCI.

Posttraumatic Stress and Traumatic Brain Injury: Cognition, Behavior, and Neuroimaging Markers in Vietnam Veterans.

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are common in Veterans and linked to behavioral disturbances, increased risk of cognitive decline, and Alzheimer's disease. We studied the synergistic effects of PTSD and TBI on behavioral, cognitive, and neuroimaging measures in Vietnam war Veterans. Data were acquired at baseline and after about one-year from male Veterans categorized into: PTSD, TBI, PTSD+TBI, and Veteran controls without PTSD or TBI. We applied manual tractography to examine white matter microstructure of three fiber tracts: uncinate fasciculus (N = 91), cingulum (N = 87), and inferior longitudinal fasciculus (N = 95). ANCOVAs were used to compare Veterans' baseline behavioral and cognitive functioning (N = 285), white matter microstructure, amyloid-β (N = 230), and tau PET (N = 120). Additional ANCOVAs examined scores' differences from baseline to follow-up. Veterans with PTSD and PTSD+TBI, but not Veterans with TBI only, exhibited poorer behavioral and cognitive functioning at baseline than controls. The groups did not differ in baseline white matter, amyloid-β, or tau, nor in behavioral and cognitive functioning, and tau accumulation change. Progression of white matter abnormalities of the uncinate fasciculus in Veterans with PTSD compared to controls was observed; analyses in TBI and PTSD+TBI were not run due to insufficient sample size. PTSD and PTSD+TBI negatively affect behavioral and cognitive functioning, while TBI does not contribute independently. Whether progressive decline in uncinate fasciculus microstructure in Veterans with PTSD might account for cognitive decline should be further studied. Findings did not support an association between PTSD, TBI, and Alzheimer's disease pathology based on amyloid and tau PET.

A - 11 Cognitive and Clinical Correlates of Olfactory Function in Adults with Epilepsy.

Olfactory dysfunction is well-documented in epilepsy. We recently found that olfactory assessment may have clinical utility in identifying surgical candidates with intractable epilepsy who benefit from magnetic resonance-guided laser interstitial thermal therapy (MRgLiTT). However, the demographic, clinical, and cognitive correlates of olfaction in epilepsy remain unclear and could aid in understanding its potential utility in clinical examinations. We identified 60 outpatients with epilepsy (mean age = 38.22 ± 13.84years; 50% male; 89.3% right-handed; seizure location: 45.0% left, 33.3% right, 13.3% bilateral, 8.3% unspecified) referred for neuropsychological evaluation in the Johns Hopkins Division of Medical Psychology Clinic. Neuropsychological evaluation included the 16-item Sniffin' Sticks Odor Identification Test. Linear regression models were used to examine associations between 1) olfaction and demographic/clinical characteristics (age, sex, education, duration of illness, seizure laterality) and 2) olfaction and cognition (processing speed, language, auditory-verbal and visuospatial memory, executive functioning; adjusted for demographic/clinical characteristics). Olfactory performance was not significantly associated with demographic or clinical characteristics. Across all participants, better olfactory performance was associated with better auditory-verbal memory (B = 5.04, t(46) = 4.16, p < 0.001) and visual confrontation naming (B = 1.53, t(45) = 4.11, p < 0.001) with correction for multiple comparisons. In a subset with lateralizing epilepsy (n = 47), better odor identification performance remained a significant predictor of the aforementioned cognitive measures with adjustment for demographic and clinical characteristics. Consistent with work in other neurologic conditions, our preliminary findings indicate that olfactory function is associated with verbally-mediated neuropsychological measures in epilepsy. Future studies utilizing pre-surgical neuroimaging will examine the association between olfaction, cognition, and radiographic markers of tissue integrity in epilepsy.