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Background Mayo Test DRIVE (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web‐based multi‐device (smartphone, tablet, personal computer) platform optimized for remote self‐administered cognitive assessment that includes a computer‐adaptive word list memory test (Stricker Learning Span; SLS), a measure of processing speed/executive functioning (Symbols Test) and a score combining both the memory and processing speed/executive functioning measures (MTD Composite). We aimed to determine the reliability of MTD measures across follow‐up sessions. Method Individuals participating in this ancillary study who completed at least two and up to four complete MTD sessions were included, resulting in 1,293 participants (mean age = 70.6, SD = 11.6; mean education = 15.6, SD = 2.3; 48.6% male; 96.9% White; 99.1% non‐Hispanic; 97.1% cognitively unimpaired) from parent studies (see Table 1). MTD raw scores were winsorized at 1% and 99% to minimize the impact of outliers. Test‐retest reliability was assessed using single‐rating, absolute‐agreement, and two‐way mixed ICCs and results are described using descriptives from Koo et al. (2016). ICCs for in‐person‐administered traditional neuropsychological measures are also reported alongside MTD for a subset of participants newly enrolled into the MCSA (to ensure participants were test naïve to both MTD and in‐person tests). Result Reliability was good for the MTD Composite raw [total ICC = 0.78; see Table 2 for session‐to‐session ICCs and 95% CIs], and moderate‐to‐good for the primary outcome variables for each subtest [total ICC = 0.74 for both SLS and Symbols]. Weighting by accuracy negatively impacted reliability of Symbols and the Composite; without this weighting, MTD Composite and Symbols variables showed higher reliability (MTD Composite z total ICC = 0.80; Symbols response time total ICC = 0.84; see Table 2). Alternative methods of defining response time on Symbols showed nearly identical reliability values. SLS sum of trials (primary variable) had subtly higher reliability than separate measures of learning (1‐5 correct, max span) or delay. Reliability of remote MTD and in‐person‐administered measures and select comparisons are provided in Table 3. Conclusion MTD showed moderate to good reliability, similar to in‐person‐administered traditional neuropsychological tests. Future work will examine the effect of demographics, device type, and session interference on reliability.

Background Digital cognitive tools offer novel ways to detect early cognitive changes associated with preclinical Alzheimer’s disease (AD). A digital version of the maze test (dMaze) was recently developed using a digital pen (12 ms temporal precision) to uniquely capture the process of test completion, reflecting the thinking effort, potentially more sensitive to early cognitive deficits in preclinical AD. The sensitivity of these novel digital maze test variables—Wall Penetration Count and Speed Standard Deviation (Speed SD)—to detect early amyloid‐β burden was evaluated, hypothesizing that greater amyloid accumulation would be associated with greater variability of speed, and more wall penetration errors while completing the task, reflecting a greater thinking effort. Method A cohort of 221 participants (CN = 208, MCI = 9, Dementia = 4) completed dMaze pairs possessing the same motor solutions but differing in cognitive loads: simple path following “no‐choice” (NC) and “choice” (CH) containing decision points that necessitate selecting path alternatives, thus adding elements of strategic problem‐solving. Wall Penetration Count tallied invasions into maze boundaries, and Speed SD quantified speed variability. Global amyloid‐β burden was assessed using [11C]Pittsburgh‐Compound‐B (PiB) PET, estimated as distribution volume ratio (DVR) in neocortical aggregate regions. Separate linear regression models examined the associations between the digital maze test variables and global amyloid‐β, adjusting for age and education. Analyses were conducted for NC and CH conditions separately. Result In the CH conditions, higher amyloid‐β burden was significantly associated with a higher Wall Penetration Count (b = 2.26, p = 0.03, R2 = 0.03) and greater Speed SD (b = 1.65, p = 0.04, R2 = 0.20). In the NC conditions, Wall Penetration Count and Speed SD were not significantly associated with amyloid‐β burden(b = 1.10, p = .12; (b = 0.99, p = .23). Conclusion Speed variability and wall penetration errors in the completion of the more challenging maze test choice condition were associated with higher amyloid‐β burden in a largely cognitively normal sample. This association was not observed in the NC conditions, suggesting that the higher cognitive demands of the CH mazes may unmask subtle, amyloid‐related disruptions in navigational strategies. These findings support the potential utility of the dMaze tests as sensitive tools for detecting early pathophysiological deficits in AD.

Background Cognitive decline in Alzheimer’s disease (AD) continuum is knowingly associated with degenerative neurobiological features; however, reliable markers for the early detection of the preclinical stages of AD are not fully established. The main goal of this study was to track ongoing brain neurodegeneration across the AD continuum by combining neuropsychological data, brain MRI features, and plasmatic ‐ brain‐derived circulating cell‐free DNA (b‐cfDNA) biomarkers. Method A total of 91 participants were included in this study including 28 healthy controls (HC) (mean age 66.4±9.2), 21 participants with Subjective Cognitive Decline (SCD) (mean age 70.4±8.5), 18 participants with Mild Cognitive Impairment (MCI) (mean age 72.3±7.1) and 24 patients with AD dementia (mean age 71.5±8.3). All participants underwent a neuropsychological evaluation, a brain MRI and a blood sample test to quantify the levels of brain‐derived cfDNA in plasma. ANCOVAs were used to test differences across participants. In addition, the median value of b‐cfDNA levels was set as a threshold to categorize participants into b‐cfDNA‐positive or negative. Pearson’s correlations were carried out between all variables. Results were corrected for multiple comparisons and statistical significance was set at p<0.05. Result Several regions in frontal, temporal and inferior parietal lobes showed progressively lower volumes going from HC to AD dementia. Although no statistical differences between mean b‐cfDNA levels were observed among groups, we found a trend of increased values in SCD and MCI participants. In addition, volumes of specific temporal regions differed significantly between b‐cfDNA‐positive and b‐cfDNA‐negative participants. Moreover, b‐cfDNA values correlated with semantic fluency scores in the AD dementia group (p = 0.038) and with the Stroop test scores in the HC group (p = 0.007). Conclusion These results suggest that active neurodegeneration in the early phases of AD can be associated with a release of b‐cfDNA in plasma. Thus, this blood‐based biomarker might reveal early neurodegenerative processes even in the pre‐clinical dementia stage, when the neuropsychological and MRI changes are very subtle and difficult to detect at the individual level. Acknowledgement: This study is supported by funding obtained under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3 ‐Project code PE0000006, CUP D93C22000930002, MNESYS

Background It is imperative to identify underrepresented populations (URPs) at risk for progression to Mild Cognitive Impairment (MCI) and dementia due to Alzheimer’s disease (AD), yet substantial heterogeneity exists in the presentation and risk of AD among URPs. Previous research with predominantly non‐Latinx White participants indicates early functional decline is associated with increased risk and can be effectively evaluated by participants and study partners (SPs). This study aims to understand the association between subjective functional/cognitive decline and objectively‐measured cognitive decline in URPs. Specifically, we hypothesize that SP‐reported decline predicts diagnostic progression over time better than participant‐reported decline in URPs. Method A sample of 283 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participant‐study partner dyads (Mage69.6 at baseline (±8.1), 62.1% female, 48.4% Black/African American, 29.0% Latinx, 15.5% Asian American, 0.4% Native Hawaiian/Pacific Islander, 1.4% American Indian/Alaska Native, and 8.8% of more than one race), completed the Everyday Cognition Questionnaire (ECog), which assesses real‐world functioning related to specific neuropsychological domains, and received consensus neurocognitive diagnoses. An autoregressive, cross‐lagged panel analysis examined whether ECog and diagnostic conversion from cognitively normal to MCI or MCI to AD were concurrently associated, whether participant‐reported ECog predicted future diagnostic conversion, and whether SP‐reported ECog predicted future diagnostic conversion across 3 time points (baseline, 12‐months, and 24‐months). Result All autoregressive paths of ECog and diagnostic progression were positive and significant (ps < .05). Cross‐lagged paths of SP‐reported ECog more strongly predicted diagnostic progression than participant‐reported ECog, and significantly predicted diagnostic progression from Time 2 (n = 130) to Time 3 (n = 92) (b = 2.03, SE = 0.64, p = .002). Cross‐lagged paths of participant‐reported ECog were not a significant predictor of diagnostic progression across three time points (ps > .05). Both models including SP‐reported ECog were significantly stronger at predicting diagnostic progression. Conclusion Early functional decline reported by SPs may be an independent predictor for cognitive decline in URPs. SPs also more accurately predicted cognitive decline cross‐sectionally and longitudinally than their participant counterparts. Further characterization of the relationships between URP participants and their SPs and their involvement in AD research should be prioritized.

Background Neuropsychiatric symptoms (NPS) including depression and apathy, are common in dementia and profoundly affect both patients and caregivers. These symptoms can manifest early and can be indicative of the disease progression. The existing tools for measuring NPS lack objectivity and are not sensitive enough to detect subtle changes in the earlier stages of dementia. Here, we report a preliminary analysis of the associations of speech markers with NPS in older adults from the Mount Sinai Alzheimer’s Disease Research Center (ADRC). Method Participants aged 60 and above were recruited through the Mount Sinai ADRC. Cognition was measured by the Montreal Cognitive Assessment (MOCA), and NPS by the Geriatric Depression Scale (GDS) and the Neuropsychiatric Inventory (NPI‐Q). Speech samples, collected during description of the “cookie theft” picture. Samples were then transcribed manually and processed using automated acoustic and lexical pipelines. Nonparametric partial correlation analysis was used to examine the relationship of the speech markers with the behavioral measures, adjusting for age, sex, education and MOCA score. Result Participants (N = 54) averaged 79 ± 7.73 years of age, 55.6% were female. They had a mean MOCA score of 24.91 (±4.08), GDS score of 2.6 (±2.59) and NPI‐Q score of 2.17(±3.21). Higher GDS scores, indicative of more severe depression, were associated with higher mean pitch values (r = +0.376, p = 0.015). Higher NPI‐Q scores, reflecting greater NPS severity, were associated with reduced speech complexity, including using more incomplete (r = + 0.350, P = 0.025) and less‐novel (r = +0.313, p = 0.046) words. Higher NPI‐Q scores were also correlated with words with higher valence (i.e., more pleasant content, r = +0.363, p = 0.02) and a tendency toward more dominant speech (r = +0.297, p = 0.059). Conclusion Our preliminary results so far show the potential of speech (both acoustic and lexical features) as a marker for NPS. Specifically, we observed relationships between speech characteristics and self‐reported depression symptoms, as well as NPI scores reflecting symptom severity. Further research is necessary to validate and refine these associations, ultimately paving the way of speech analysis as a promising non‐invasive objective method for detecting subtle behavioral changes in the early stages of dementia.

Background Apathy in Alzheimer’s disease improves with methylphenidate (MPH) but treatment response was found to vary depending on clinical factors. Here, we explored whether underlying biological factors assessed by blood‐based biomarkers of neurodegeneration, inflammation and oxidative stress affect apathy treatment response. Method A subset of participants from the Apathy in Dementia Methylphenidate Trial 2 (ADMET 2) were included in this study whose blood samples were available at baseline and at the 6‐month treatment completion. Apathy was assessed with the Neuropsychiatric Inventory apathy subscale (NPI‐A, range: 0‐12). Blood concentrations of (i) neuronal damage: neurofilament light (NFL) and S‐100B (available at baseline only), (ii) inflammation: interleukin (IL)‐6, IL‐10, Tumor Necrosis Factor‐alpha (TNFα), and (iii) oxidative stress: lipid hydroperoxide (LPH), 4‐hydroxynonenal (4‐HNE), 8‐isoprostane (8‐ISO) were obtained with ELISA assays. Biomarkers were normalized by log transformation and pareto scaling. Predictive value of biomarkers was assessed by examining differences in treatment response between each biomarker tertile level. We also assessed whether biomarkers improved predictive models for established clinical predictors. Monitoring value was assessed by linear mixed models with NPI‐A as the dependent variable and interaction between biomarker and time or biomarker and treatment as the independent variable. Result Among 55 participants (MPH: 24, age: 75.4 years [standard deviation (SD): 7.6], MMSE: 19.9 [SD: 4.9]) at baseline and 49 at the 6 month end point, the change in NPI‐A showed a greater than 2‐point difference between tertiles of NFL (6.8 points), TNFα (4.2 points) and 8‐ISO (5.5 points) (Fig. 1). Treatment response prediction improved by adding NFL with cholinesterase use (likelihood ratio test[lrt]: 4.6, p: 0.03), presence of agitation (lrt: 4.4, p: 0.04) or presence of anxiety (lrt: 4.5, p: 0.04); no added value was found with TNFα and 8‐ISO. As a monitoring biomarker, TNFα (but not NFL and 8‐ISO) levels over time were associated with NPI‐A score (t: 2.69, p: 0.009). Conclusion Blood‐based biomarkers of neurodegeneration, inflammation and oxidative stress are associated with apathy and affect treatment response, indicating potential predictive and monitoring value. Peripheral inflammation (TNFα) may have added value along with clinical predictors of response.

Background Locus coeruleus (LC) is a primary source of noradrenalin in the brain and plays a complex role in human behavior. In healthy aging and Alzheimer’s disease (AD), LC cell loss has been linked to a decline in overall cognitive function. This study aimed to explore age‐ and AD‐related differences in a proxy measure of LC activity. Using pupil dilation (PD) as a non‐exclusive proxy measure of the LC‐NE system activity, we examined whether pupillometric recordings during cognitive tasks are possible in early AD and whether they reveal differences in attentional modulation in aging and AD. Method 37 subjects (14 healthy OA and 23 individuals with AD) completed an auditory and visual oddball task to assess attentional modulation; 62 subjects (22 healthy YA, 20 healthy OA, and 20 individuals with AD) completed a Simon task to assess attention and cognitive control. LC integrity was assessed using neuromelanin‐sensitive MRI. Result A larger PD response for oddball compared to standard stimuli was observed, with no difference between OA and AD participants. In the visual task, greater PD correlated with faster reaction times (RTs) for hits in both groups, indicating the interindividual differences in PD can reflect heightened attentional involvement in aging and AD. Similarly, a consistent Simon effect, i.e., lower accuracy and longer RTs for incongruent trials, was observed in all groups, suggesting cognitive effort in discriminating between congruences. PD was higher for incongruent than congruent trials across all age groups, yet YA exhibited a less pronounced Simon effect, indicating age‐related differences in attentional resource allocation with a potentially larger need in OA and AD for attentional control on incongruent stimuli. In YA, slower RTs correlated with smaller PD in incongruent trials. YA and AD individuals with a stronger Simon effect in PD showed faster processing for incongruent trials and better performance for congruent trials, respectively. Conclusion Using PD as a measure of attentional allocation and effort during cognitive control is possible in AD. Moreover, it allows for the assessment of interindividual differences in the extent of attentional modulation in AD. Assessing PD could be a useful tool for distinguishing between healthy aging and early AD.

Background The timely diagnosis of mild cognitive impairment (MCI) in Alzheimer’s disease is challenging in routine care due to the complexity and time burden of required cognitive assessments. New unsupervised digital remote assessment tools could adress this challenge. Method The multicentric healthcare study “re.cogni.ze” evaluated usability, adherence and acceptance of remote digital assessment (neotivCare, installed on private smartphone) over a period of 22 months with 27 specialist physicians (neurologists and psychiatrists), 13 GPs and 3 memory clinics in Germany. Result 765 persons with subjectively perceived memory problems were recommended neotivCare by their doctors. 574 patients (75%) followed the recommendation (mean age 67 ‐ SD 10; 50.2% female). 573 (93%) used the app at home (one visual memory test per week over a period 12 weeks). 496 patients (93%) completed the assessment and discussed the results using the in‐app generated findings letter with their doctor. Of these, 368 patients also completed a separate (independent from the app) survey about usability, difficulty, worries, experienced added value etc. 40% of the patients fell below the prevalidated cut‐off for MCI in the app‐tests. Specialists reported a higher satisfaction with the app compared to standard paper‐pencil tests (5.2 versus 4.4 on a 7 point Likert scale). There was no such difference for GPs. 71% of all doctors found that the app easy to use. 80% saw an added value in using the app. 71.5% of the patients thought that the app was easy to use. 67.6% reported an added value over paper pencil tests. Using the app reduced experienced worries in 51% of the patients and left worries unchanged in 29%. The patients rated the duration of the app‐use and the self‐testing at home favourably (both 8.5 scores on a Likert scale 0 ‐10). Conclusion The topline results of the re.cog.nize study show that remote digital self‐assessment in routine care is feasible and is accepted by health care providers and patients. The high adherence rates indicate that a timely assessment of MCI is possible with this type of digital technology.

Background Network neuropsychology is an emergent field dedicated to analyzing cognitive functions as interconnected systems. Although previous studies have explored cognitive network reorganization across the Alzheimer’s disease (AD) continuum using comprehensive neuropsychological batteries, these approaches often overlook the potential of single screening tests used in routine clinical practice. This study innovatively applies graphical models to data from isolated neurocognitive tests, specifically the Alzheimer’s Disease Assessment Scale‐Cognitive Subscale (ADAS‐Cog), to construct cognitive networks. Our approach not only handles the challenges posed by the non‐normal, ordinal and discrete nature of test data but also provides a more detailed understanding of the AD continuum. Method We utilized ADAS‐Cog neuropsychological test scores from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, categorizing subjects into Cognitively Normal (CN, n = 662), Mild Cognitive Impairment (MCI, n = 705), and Dementia (n = 219). To construct cognitive networks for each group, we calculated Spearman’s correlations and applied BIC graphical LASSO regularization, quantifying network stability through non‐parametric and case‐drop bootstrapping. We then rigorously assessed differences in network structures across the disease spectrum using the Network Comparison Test, focusing on several key graph metrics. Result Our global connectivity analysis uncovered distinct variations in network densities across the AD spectrum, with notably higher density in the Dementia network. The most significant differences in node strengths were identified between the CN and Dementia groups, reinforcing ADAS‐Cog’s effectiveness in detecting various stages of Dementia. Furthermore, strength centrality analysis highlighted the growing relevance of ideational praxis, linked to the Visuospatial domain, in network reorganization across the AD continuum. In the Dementia networks, Immediate Memory and Language items emerged as predominant influencers, whereas Delayed Memory, Attention and Orientation were significantly more central in the MCI network. Conclusion Our research highlights that dynamic changes in cognitive networks across the AD continuum can be effectively mapped using isolated neurocognitive tests like the ADAS‐Cog. Notably, the Dementia network emphasized the critical roles of Immediate Memory, Language and Visuospatial functions. Conversely, the MCI network revealed pronounced impairments in Orientation and Attention. These insights demonstrate the capacity of streamlined cognitive assessments to identify key cognitive changes, offering a quicker, yet robust alternative for monitoring disease progression in clinical settings.

Background Despite women showing greater pathological tau burden than men in the preclinical and mild cognitive impairment (MCI) stages of Alzheimer’s disease (AD), they show a cognitive advantage, particularly in verbal memory, followed by a steeper decline. Thus, the question of sex differences in the clinical manifestation of AD pathology is important, but underexamined. Among preclinical AD and MCI participants, we examined sex differences in the relationship of changes in cerebrospinal fluid (CSF) pTau181/Aβ42 (pTau/Aβ) ratio to changes in verbal memory. Methods Participants included 504 older individuals (age range: 55‐90, mean age = 73.5±6.7, 95% non‐Hispanic White; mean follow‐up = 3.9±2.7 years) classified as preclinical AD (89 women, 88 men) or MCI (118 women, 176 men) at baseline in the Alzheimer’s Disease Neuroimaging Initiative. Preclinical AD was defined as cognitively normal but positive for CSF or PET Aβ or pTau biomarkers. MCI was defined by the Jak/Bondi criteria. Rey Auditory Verbal Learning Test‐Immediate and Delayed Recall z‐scores were averaged to create a verbal memory composite score. We applied latent class mixture modeling to trajectories of the verbal memory composite score, allowing for clustering of the growth trajectories into latent classes. We then examined the effect of sex, time‐varying pTau/Aβ ratio, time and disease stage (preclinical versus MCI) and their interactions on verbal memory composite while adjusting for education, age, and APOE4 status. Results At baseline, women showed significantly better verbal memory performance (p<.01) and higher CSF pTau levels (p = .003), but the pTau/Aβ ratio did not differ by sex (p = .33). A 1‐class, non‐linear model provided optimal fit. A significant time x sex x pTau/Aβ interaction (p = .016) revealed a sex‐dependent influence of the pTau181/Aβ42 ratio on verbal memory over time, whereby, among those with higher pTau/Aβ ratio levels (>1SD above mean), higher pTau/Aβ ratio levels predicted verbal memory decline more strongly in women than in men. Conclusions Findings suggest that, when AD pathology is more advanced, women show greater verbal memory decline as AD pathology progresses. Our findings provide insight into why sex differences in the clinical trajectory of AD vary by disease stage and raise questions as to the biological mechanisms underlying these sex differences.