Downstream Biomarker Effects of Gantenerumab or Solanezumab in Dominantly Inherited Alzheimer Disease: The DIAN-TU-001 Randomized Clinical Trial.

Importance: Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD). Objective: To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment. Design, Setting, and Participants: From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed. Interventions: In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks. Main Outcomes and Measures: Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3-like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL. Results: Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] ß = -242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] ß = -0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] ß = -0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] ß = -0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] ß = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] ß = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] ß = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo. Conclusions and Relevance: This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification. Trial Registration: ClinicalTrials.gov Identifier: NCT04623242.

Pick a PACC: Comparing domain-specific and general cognitive composites in Alzheimer disease research.

OBJECTIVE: We aimed to illustrate how complex cognitive data can be used to create domain-specific and general cognitive composites relevant to Alzheimer disease research. METHOD: Using equipercentile equating, we combined data from the Charles F. and Joanne Knight Alzheimer Disease Research Center that spanned multiple iterations of the Uniform Data Set. Exploratory factor analyses revealed four domain-specific composites representing episodic memory, semantic memory, working memory, and attention/processing speed. The previously defined preclinical Alzheimer disease cognitive composite (PACC) and a novel alternative, the Knight-PACC, were also computed alongside a global composite comprising all available tests. These three composites allowed us to compare the usefulness of domain and general composites in the context of predicting common Alzheimer disease biomarkers. RESULTS: General composites slightly outperformed domain-specific metrics in predicting imaging-derived amyloid, tau, and neurodegeneration burden. Power analyses revealed that the global, Knight-PACC, and attention and processing speed composites would require the smallest sample sizes to detect cognitive change in a clinical trial, while the Alzheimer Disease Cooperative Study-PACC required two to three times as many participants. CONCLUSIONS: Analyses of cognition with the Knight-PACC and our domain-specific composites offer researchers flexibility by providing validated outcome assessments that can equate across test versions to answer a wide range of questions regarding cognitive decline in normal aging and neurodegenerative disease. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Disease staging of Alzheimer's disease using a CSF-based biomarker model.

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aß42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aß-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.

Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging.

BACKGROUND: Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD. METHODS: 445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants. FINDINGS: We found both tau metrics significantly elevated across increasing disease stages (p < 0.0001) and as a function of increasing amyloid burden for participants with preclinical (p < 0.0001, p = 0.0056) and symptomatic (p = 0.010, p = 0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p = 0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (ß = 0.59), but then tau burden elevated relative to spread (ß = 0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R = 0.83). INTERPRETATION: Tau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design. FUNDING: This research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund.

Timing of Biomarker Changes in Sporadic Alzheimer's Disease in Estimated Years from Symptom Onset.

OBJECTIVE: A clock relating amyloid positron emission tomography (PET) to time was used to estimate the timing of biomarker changes in sporadic Alzheimer disease (AD). METHODS: Research participants were included who underwent cerebrospinal fluid (CSF) collection within 2 years of amyloid PET. The ages at amyloid onset and AD symptom onset were estimated for each individual. The timing of change for plasma, CSF, imaging, and cognitive measures was calculated by comparing restricted cubic splines of cross-sectional data from the amyloid PET positive and negative groups. RESULTS: The amyloid PET positive sub-cohort (n = 118) had an average age of 70.4 ± 7.4 years (mean ± standard deviation) and 16% were cognitively impaired. The amyloid PET negative sub-cohort (n = 277) included individuals with low levels of amyloid plaque burden at all scans who were cognitively unimpaired at the time of the scans. Biomarker changes were detected 15-19 years before estimated symptom onset for CSF Aß42/Aß40, plasma Aß42/Aß40, CSF pT217/T217, and amyloid PET; 12-14 years before estimated symptom onset for plasma pT217/T217, CSF neurogranin, CSF SNAP-25, CSF sTREM2, plasma GFAP, and plasma NfL; and 7-9 years before estimated symptom onset for CSF pT205/T205, CSF YKL-40, hippocampal volumes, and cognitive measures. INTERPRETATION: The use of an amyloid clock enabled visualization and analysis of biomarker changes as a function of estimated years from symptom onset in sporadic AD. This study demonstrates that estimated years from symptom onset based on an amyloid clock can be used as a continuous staging measure for sporadic AD and aligns with findings in autosomal dominant AD. ANN NEUROL 2024;95:951-965.

Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double-blind phase 3 DIAN-TU-001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab. METHODS: We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker. RESULTS: LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid-no-change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid-reduction class exhibited reductions in the annual decline rates compared to the amyloid-growth class across multiple biomarker, clinical, and cognitive outcomes. DISCUSSION: LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials. HIGHLIGHTS: We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker. Despite similar baseline characteristics, the amyloid-reduction class exhibited remarkably better outcomes compared to the amyloid-growth class across multiple measures. LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects.

Antecedents of mind wandering states in healthy aging and mild cognitive impairment.

OBJECTIVE: Mind wandering refers to periods of internally directed attention and comprises up to 30% or more of our waking thoughts. Frequent mind wandering can be detrimental to ongoing task performance. We aim to determine whether rates of mind wandering change in healthy aging and mild cognitive impairment and how differences in mind wandering contribute to differences in attention and working memory. METHOD: We administered a standard behavioral task, the Sustained Attention to Response Test, to measure mind wandering in healthy younger adults (N = 66), healthy older adults (N = 51), and adults with cognitive impairment (N = 38), that was completed daily for 3 weeks. The N-back test was also administered at a reduced frequency as a measure of working memory performance. RESULTS: Generally speaking, averaged across 3 weeks of testing, relative to healthy older adults, mind wandering was higher in younger adults and in cognitive impairment, although the specific patterns varied across mind wandering states. Multiple states of mind wandering also predicted working memory performance; however, reaction time variability tended to be the best predictor based on model comparisons. Each state was also modestly associated with different dispositional factors including mood and Agreeableness. CONCLUSIONS: Patterns of mind wandering change across healthy aging and cognitive impairment and are related to individual differences in multiple dispositional factors and also working memory performance. These results suggest that different states of mind wandering should be measured and accounted for when modeling cognitive change in healthy and pathological aging. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Naturalistic assessment of reaction time variability in older adults at risk for Alzheimer's disease.

OBJECTIVE: Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer's disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD. METHOD: Three hundred and seventy older adults (aged 75.8 +/- 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials. RESULTS: Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites. CONCLUSIONS: Attentional fluctuations over 20-40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.

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

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

Investigation of sex differences in mutation carriers of the Dominantly Inherited Alzheimer Network.

INTRODUCTION: Studies suggest distinct differences in the development, presentation, progression, and response to treatment of Alzheimer's disease (AD) between females and males. We investigated sex differences in cognition, neuroimaging, and fluid biomarkers in dominantly inherited AD (DIAD). METHODS: Three hundred twenty-five mutation carriers (55% female) and one hundred eighty-six non-carriers (58% female) of the Dominantly Inherited Alzheimer Network Observational Study were analyzed. Linear mixed models and Spearman's correlation explored cross-sectional sex differences in cognition, cerebrospinal fluid (CSF) biomarkers, Pittsburgh compound B positron emission tomography (11 C-PiB PET) and structural magnetic resonance imaging (MRI). RESULTS: Female carriers performed better than males on delayed recall and processing speed despite similar hippocampal volumes. As the disease progressed, symptomatic females revealed higher increases in MRI markers of neurodegeneration and memory impairment. PiB PET and established CSF AD markers revealed no sex differences. DISCUSSION: Our findings suggest an initial cognitive reserve in female carriers followed by a pronounced increase in neurodegeneration coupled with worse performance on delayed recall at later stages of DIAD.

Predicting cognitive decline: Which is more useful, baseline amyloid levels or longitudinal change?

The use of biomarkers for the early detection of Alzheimer's disease (AD) is crucial for developing potential therapeutic treatments. Positron Emission Tomography (PET) is a well-established tool used to detect ß-amyloid (Aß) plaques in the brain. Previous studies have shown that cross-sectional biomarkers can predict cognitive decline (Schindler et al.,2021). However, it is still unclear whether longitudinal Aß-PET may have additional value for predicting time to cognitive impairment in AD. The current study aims to evaluate the ability of baseline- versus longitudinal rate of change in-11C-Pittsburgh compound B (PiB) Aß-PET to predict cognitive decline. A cohort of 153 participants who previously underwent PiB-PET scans and comprehensive clinical assessments were used in this study. Our analyses revealed that baseline Aß is significantly associated with the rate of change in cognitive composite scores, with cognition declining more rapidly when baseline PiB Aß levels were higher. In contrast, no signification association was identified between the rate of change in PiB-PET Aß and cognitive decline. Additionally, the ability of the rate of change in the PiB-PET measures to predict cognitive decline was significantly influenced by APOE ε4 carrier status. These results suggest that a single PiB-PET scan is sufficient to predict cognitive decline and that longitudinal measures of Aß accumulation do not improve the prediction of cognitive decline once someone is amyloid positive.

Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer's disease.

Approximately 5% of Alzheimer's disease cases have an early age at onset (<65 years), with 5-10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer's disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer's disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer's disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer's disease enrolled at the University of California San Francisco Alzheimer's Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer's disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P < 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P < 0.001), Trail Making Test Part B (P < 0.001) and digit span (P < 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer's disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer's disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.

Novel CSF tau biomarkers can be used for disease staging of sporadic Alzheimer's disease.

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic work-up of dementia in clinical practice and the design of clinical trials. Here, we created a staging model using the Subtype and Stage Inference (SuStaIn) algorithm by evaluating cerebrospinal fluid (CSF) amyloid-ß (Aß) and tau biomarkers in 426 participants from BioFINDER-2, that represent the entire spectrum of AD. The model composition and main analyses were replicated in 222 participants from the Knight ADRC cohort. SuStaIn revealed in the two cohorts that the data was best explained by a single biomarker sequence (one subtype), and that five CSF biomarkers (ordered: Aß42/40, tau phosphorylation occupancies at the residues 217 and 205 [pT217/T217 and pT205/T205], microtubule-binding region of tau containing the residue 243 [MTBR-tau243], and total tau) were sufficient to create an accurate disease staging model. Increasing CSF stages (0-5) were associated with increased abnormality in other AD-related biomarkers, such as Aß- and tau-PET, and aligned with different phases of longitudinal biomarker changes consistent with current models of AD progression. Higher CSF stages at baseline were associated with higher hazard ratio of clinical decline. Our findings indicate that a common pathophysiologic molecular pathway develops across all AD patients, and that a single CSF collection is sufficient to reliably indicate the presence of both AD pathologies and the degree and stage of disease progression.

Increased cognitive effort costs in healthy aging and preclinical Alzheimer's disease.

Life-long engagement in cognitively demanding activities may mitigate against declines in cognitive ability observed in healthy or pathological aging. However, the "mental costs" associated with completing cognitive tasks also increase with age and may be partly attributed to increases in preclinical levels of Alzheimer's disease (AD) pathology, specifically amyloid. We test whether cognitive effort costs increase in a domain-general manner among older adults, and further, whether such age-related increases in cognitive effort costs are associated with working memory (WM) capacity or amyloid burden, a signature pathology of AD. In two experiments, we administered a behavioral measure of cognitive effort costs (cognitive effort discounting) to a sample of older adults recruited from online sources (Experiment 1) or from ongoing longitudinal studies of aging and dementia (Experiment 2). Experiment 1 compared age-related differences in cognitive effort costs across two domains, WM and speech comprehension. Experiment 2 compared cognitive effort costs between a group of participants who were rated positive for amyloid relative to those with no evidence of amyloid. Results showed age-related increases in cognitive effort costs were evident in both domains. Cost estimates were highly correlated between the WM and speech comprehension tasks but did not correlate with WM capacity. In addition, older adults who were amyloid positive had higher cognitive effort costs than those who were amyloid negative. Cognitive effort costs may index a domain-general trait that consistently increases in aging. Differences in cognitive effort costs associated with amyloid burden suggest a potential neurobiological mechanism for age-related differences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

To BYOD or not: Are device latencies important for bring-your-own-device (BYOD) smartphone cognitive testing?

Studies using remote cognitive testing must make a critical decision: whether to allow participants to use their own devices or to provide participants with a study-specific device. Bring-your-own-device (BYOD) studies have several advantages including increased accessibility, potential for larger sample sizes, and reduced participant burden. However, BYOD studies offer little control over device performance characteristics that could potentially influence results. In particular, response times measured by each device not only include the participant's true response time, but also latencies of the device itself. The present study investigated two prominent sources of device latencies that pose significant risks to data quality: device display output latency and touchscreen input latency. We comprehensively tested 26 popular smartphones ranging in price from < $100 to $1000+ running either Android or iOS to determine if hardware and operating system differences led to appreciable device latency variability. To accomplish this, a custom-built device called the Latency and Timing Assessment Robot (LaTARbot) measured device display output and capacitive touchscreen input latencies. We found considerable variability across smartphones in display and touch latencies which, if unaccounted for, could be misattributed as individual or group differences in response times. Specifically, total device (sum of display and touch) latencies ranged from 35 to 140 ms. We offer recommendations to researchers to increase the precision of data collection and analysis in the context of remote BYOD studies.

Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer's disease.

OBJECTIVE: Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer's disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants' personal devices in their everyday environments. METHODS: We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65-97 years) and 22 individuals with very mild dementia (ages 61-88 years). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau positron emission tomography, and structural magnetic resonance imaging studies. RESULTS: First, ARC tasks were reliable as between-person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants. CONCLUSIONS: Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.

Evaluation of dose-dependent treatment effects after mid-trial dose escalation in biomarker, clinical, and cognitive outcomes for gantenerumab or solanezumab in dominantly inherited Alzheimer's disease.

Introduction: While the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) was ongoing, external data suggested higher doses were needed to achieve targeted effects; therefore, doses of gantenerumab were increased 5-fold, and solanezumab was increased 4-fold. We evaluated to what extent mid-trial dose increases produced a dose-dependent treatment effect. Methods: Using generalized linear mixed effects (LME) models, we estimated the annual low- and high-dose treatment effects in clinical, cognitive, and biomarker outcomes. Results: Both gantenerumab and solanezumab demonstrated dose-dependent treatment effects (significant for gantenerumab, non-significant for solanezumab) in their respective target amyloid biomarkers (Pittsburgh compound B positron emission tomography standardized uptake value ratio and cerebrospinal fluid amyloid beta 42), with gantenerumab demonstrating additional treatment effects in some downstream biomarkers. No dose-dependent treatment effects were observed in clinical or cognitive outcomes. Conclusions: Mid-trial dose escalation can be implemented as a remedy for an insufficient initial dose and can be more cost effective and less burdensome to participants than starting a new trial with higher doses, especially in rare diseases. Highlights: We evaluated the dose-dependent treatment effect of two different amyloid-specific immunotherapies.Dose-dependent treatment effects were observed in some biomarkers.No dose-dependent treatment effects were observed in clinical/cognitive outcomes, potentially due to the fact that the modified study may not have been powered to detect such treatment effects in symptomatic subjects at a mild stage of disease exposed to high (or maximal) doses of medication for prolonged durations.

Comparison of plasma and CSF biomarkers in predicting cognitive decline.

OBJECTIVES: Concentrations of amyloid-ß peptides (Aß42/Aß40) and neurofilament light (NfL) can be measured in plasma or cerebrospinal fluid (CSF) and are associated with Alzheimer's disease brain pathology and cognitive impairment. This study directly compared plasma and CSF measures of Aß42/Aß40 and NfL as predictors of cognitive decline. METHODS: Participants were 65 years or older and cognitively normal at baseline with at least one follow-up cognitive assessment. Analytes were measured with the following types of assays: plasma Aß42/Aß40, immunoprecipitation-mass spectrometry; plasma NfL, Simoa; CSF Aß42/Aß40, automated immunoassay; CSF NfL plate-based immunoassay. Mixed effects models evaluated the global cognitive composite score over a maximum of 6 years as predicted by the fluid biomarkers. RESULTS: Analyses included 371 cognitively normal participants, aged 72.7 ± 5.2 years (mean ± standard deviation) with an average length of follow-up of 3.9 ± 1.6 years. Standardized concentrations of biomarkers were associated with annualized cognitive change: plasma Aß42/Aß40, 0.014 standard deviations (95% confidence intervals 0.002 to 0.026); CSF Aß42/Aß40, 0.020 (0.008 to 0.032); plasma Nfl, -0.018 (-0.030 to -0.005); and CSF NfL, -0.024 (-0.036 to -0.012). Power analyses estimated that 266 individuals in each treatment arm would be needed to detect a 50% slowing of decline if identified by abnormal plasma measures versus 229 for CSF measures. INTERPRETATION: Both plasma and CSF measures of Aß42/Aß40 and NfL predicted cognitive decline. A clinical trial that enrolled individuals based on abnormal plasma Aß42/Aß40 and NfL levels would require only a marginally larger cohort than if CSF measures were used.

Avoid or Embrace? Practice Effects in Alzheimer's Disease Prevention Trials.

Demonstrating a slowing in the rate of cognitive decline is a common outcome measure in clinical trials in Alzheimer's disease (AD). Selection of cognitive endpoints typically includes modeling candidate outcome measures in the many, richly phenotyped observational cohort studies available. An important part of choosing cognitive endpoints is a consideration of improvements in performance due to repeated cognitive testing (termed "practice effects"). As primary and secondary AD prevention trials are comprised predominantly of cognitively unimpaired participants, practice effects may be substantial and may have considerable impact on detecting cognitive change. The extent to which practice effects in AD prevention trials are similar to those from observational studies and how these potential differences impact trials is unknown. In the current study, we analyzed data from the recently completed DIAN-TU-001 clinical trial (TU) and the associated DIAN-Observational (OBS) study. Results indicated that asymptomatic mutation carriers in the TU exhibited persistent practice effects on several key outcomes spanning the entire trial duration. Critically, these practice related improvements were larger on certain tests in the TU relative to matched participants from the OBS study. Our results suggest that the magnitude of practice effects may not be captured by modeling potential endpoints in observational studies where assessments are typically less frequent and drug expectancy effects are absent. Using alternate instrument forms (represented in our study by computerized tasks) may partly mitigate practice effects in clinical trials but incorporating practice effects as outcomes may also be viable. Thus, investigators must carefully consider practice effects (either by minimizing them or modeling them directly) when designing cognitive endpoint AD prevention trials by utilizing trial data with similar assessment frequencies.

Neuropsychological Correlates of Changes in Driving Behavior Among Clinically Healthy Older Adults.

OBJECTIVES: To determine the extent to which cognitive domain scores moderate change in driving behavior in cognitively healthy older adults using naturalistic (Global Positioning System-based) driving outcomes and to compare against self-reported outcomes using an established driving questionnaire. METHODS: We analyzed longitudinal naturalistic driving behavior from a sample (N = 161, 45% female, mean age = 74.7 years, mean education = 16.5 years) of cognitively healthy, nondemented older adults. Composite driving variables were formed that indexed "driving space" and "driving performance." All participants completed a baseline comprehensive cognitive assessment that measured multiple domains as well as an annual self-reported driving outcomes questionnaire. RESULTS: Across an average of 24 months of naturalistic driving, our results showed that attentional control, broadly defined as the ability to focus on relevant aspects of the environment and ignore distracting or competing information as measured behaviorally with tasks such as the Stroop color naming test, moderated change in driving space scores over time. Specifically, individuals with lower attentional control scores drove fewer trips per month, drove less at night, visited fewer unique locations, and drove in smaller spaces than those with higher attentional control scores. No cognitive domain predicted driving performance such as hard braking or sudden acceleration. DISCUSSION: Attentional control is a key moderator of change over time in driving space but not driving performance in older adults. We speculate on mechanisms that may relate attentional control ability to modifications of driving behaviors.