To BYOD or Not: Are Device Latencies Important for Bring Your Own Device (BYOD) Smartphone Cognitive Testing?
Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer disease
Avoid or Embrace? Practice Effects
in Alzheimer’s Disease Prevention
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.
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 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 disease
Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer 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. We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65-97) and 22 individuals with very mild dementia (ages 61-88). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau PET, and structural MRI studies. First, results indicated that 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. 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.
Bridging the technological divide: Stigmas and challenges with technology in clinical studies of older adults
The COVID-19 pandemic has increased adoption of remote assessments in clinical research. However, longstanding stereotypes persist regarding older adults’ technology familiarity and their willingness to participate in technology-enabled remote studies. We examined the validity of these stereotypes using a novel technology familiarity assessment (n = 342) and with a critical evaluation of participation factors from an intensive smartphone study of cognition in older adults (n = 445). The technology assessment revealed that older age was strongly associated with less technology familiarity, less frequent engagement with technology, and higher difficulty ratings. Despite this, the majority (86.5%) of older adults elected to participate in the smartphone study and showed exceptional adherence (85.7%). Furthermore, among those enrolled, neither technology familiarity, knowledge, perceived difficulty, nor gender, race, or education were associated with adherence. These results suggest that while older adults remain significantly less familiar with technology than younger generations, with thoughtful study planning that emphasizes participant support and user-centered design, they are willing and capable participants in technology-enabled studies. And once enrolled, they are remarkably adherent.
Sharper in the morning: Cognitive time of day effects revealed with high-frequency smartphone testing
Decades of research has established a shift from an “eveningness” preference to a “morningness” preference with increasing age. Accordingly, older adults typically have better cognition in morning hours compared to evening hours. We present the first known attempt to capture circadian fluctuations in cognition in individuals at risk for Alzheimer disease (AD) using a remotely administered smartphone assessment that samples cognition rapidly and repeatedly over several days. Older adults (N = 169, aged 61–94 years; 93% cognitively normal) completed four brief smartphone-based testing sessions per day for 7 consecutive days at quasi-random time intervals, assessing associate memory, processing speed, and visual working memory. Scores completed during early hours were averaged for comparison with averaged scores completed during later hours. Mixed effects models evaluated time of day effects on cognition. Additional models included clinical status and cerebrospinal fluid (CSF) biomarkers for beta amyloid (Aβ42) and phosphorylated tau181 (pTau). Models with terms for age, gender, education, APOE ε4 status, and clinical status revealed significantly worse performance on associate memory in evening hours compared to morning hours. Contemporaneously reported mood and fatigue levels did not moderate relationships. Using CSF data to classify individuals with and without significant AD pathology, there were no group differences in performance in morning hours, but subtle impairment emerged in associate memory in evening hours in those with CSF-confirmed AD pathology. These findings indicate that memory is worse in evening hours in older adults, that this pattern is consistent across several days, and is independent of measures of mood and fatigue. Further, they provide preliminary evidence of a “cognitive sundowning” in the very earliest stages of AD. Time of day may be an important consideration for assessments in observational studies and clinical trials in AD populations.
Undetected neuropathology biases estimates of cognitive change in older adults
Neurodegenerative disease is highly prevalent among older adults and, if undetected, may obscure estimates of cognitive change among aging samples. Our aim in this study was to determine the nature and magnitude of cognitive change in the absence of common neuropathologic markers of neurodegenerative disease. Cognitively normal older adults (ages 65–89 years, N = 199) were classified as normal or abnormal using neuroimaging and cerebrospinal-fluid biomarkers of β-amyloid, tau, and neurodegeneration. When cognitive change was modeled without accounting for biomarker status, significant decline was evident for semantic memory, processing speed, and working memory. However, after adjusting for biomarker status, we found that the rate of change was attenuated and that the biomarker-normal group demonstrated no decline for any cognitive domain. These results indicate that estimates of cognitive change in otherwise healthy older adults will be biased toward decline when the presence of early neurodegenerative disease is not accounted for.
Relationships between big‐five personality factors and Alzheimer’s disease pathology in autosomal dominant Alzheimer’s disease
Changes in personality characteristics are associated with the onset of symptoms in Alzheimer’s disease (AD) and may even precede clinical diagnosis. However, personality changes caused by disease progression can be difficult to separate from changes that occur with normal aging. The Dominantly Inherited Alzheimer Network (DIAN) provides a unique cohort in which to relate measures of personality traits to in vivo markers of disease in a much younger sample than in typical late onset AD. Personality traits measured with the International Personality Item Pool at baseline from DIAN participants were analyzed as a function of estimated years to onset of clinical symptoms and well‐established AD biomarkers. Both neuroticism and conscientiousness were correlated with years to symptom onset and markers of tau pathology in the cerebrospinal fluid. Self‐reported conscientiousness and both neuroticism and conscientiousness ratings from a collateral source were correlated with longitudinal rates of cognitive decline such that participants who were rated as higher on neuroticism and lower on conscientiousness exhibited accelerated rates of cognitive decline. Personality traits are correlated with the accumulation of AD pathology and time to symptom onset, suggesting that AD progression can influence an individual’s personality characteristics. Together these findings suggest that measuring neuroticism and conscientiousness may hold utility in tracking disease progression in AD.
Neurofilament Light Predicts Decline in Attention but Not Episodic Memory in Preclinical Alzheimer’s Disease.
Cerebrospinal fluid tau and neurofilament light (NfL) are two biomarkers of neurodegeneration in Alzheimer’s disease. Previous reports have shown that the influence of tau on cognitive decline depends on levels of amyloid burden whereas NfL predicts decline independently of amyloid. Most studies use a global cognitive composite as the primary outcome, and it is unknown if critical cognitive domain scores are similarly sensitive to rates of decline due to neurodegeneration. Objective: To examine the unique contribution of amyloid, tau, and NfL to rates of cognitive decline in multiple cognitive composites in a cognitively healthy, middle-aged to older adult cohort. Methods: A total of 255 participants (55% female; mean age = 66.2 years, range = 42.5-86.7 years) completed CSF studies and serial cognitive assessments to measure global cognition, episodic memory, and attentional control. Linear mixed effects models were used to examine rates of change on each composite score as a function of baseline biomarker levels. Results: Total tau predicted decline in attention regardless of amyloid status, but the relationship to global cognition and episodic memory was dependent on amyloid, replicating prior literature. NfL predicted decline in attention and global cognition, but not memory, and this effect was independent of amyloid status. Conclusions: These findings suggest that NfL can be used to monitor cognitive decline in aging and Alzheimer’s disease and that an attentional control composite may be a better outcome for tracking general neurodegenerative effects on cognition.
Enabling Technologies for Personalized and Precision Medicine
Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care.
Cognitive trajectory in mild cognitive impairment due to primary age-related tauopathy
Primary age-related tauopathy is increasingly recognized as a separate neuropathological entity different from Alzheimer’s disease. Both share the neuropathological features of tau aggregates and neuronal loss in the temporal lobe, but primary age-related tauopathy lacks the requisite amyloid plaques central to Alzheimer’s disease. While both have similar clinical presentations, individuals with symptomatic primary age-related tauopathy are commonly of more advanced ages with milder cognitive dysfunction. Direct comparison of the neuropsychological trajectories of primary age-related tauopathy and Alzheimer’s disease has not been thoroughly evaluated and thus, our objective was to determine how cognitive decline differs longitudinally between these two conditions after the onset of clinical symptoms. Data were obtained from the National Alzheimer’s Coordinating Center on participants with mild cognitive impairment at baseline and either no neuritic plaques (i.e. primary age-related tauopathy) or moderate to frequent neuritic plaques (i.e. Alzheimer neuropathological change) at subsequent autopsy. For patients with Alzheimer’s disease and primary age-related tauopathy, we compared rates of decline in the sum of boxes score from the CDR Dementia Staging Instrument and in five cognitive domains (episodic memory, attention/working memory, executive function, language/semantic memory, and global composite) using z-scores for neuropsychological tests that were calculated based on scores for participants with normal cognition. The differences in rates of change were tested using linear mixed-effects models accounting for clinical centre clustering and repeated measures by individual. Models were adjusted for sex, age, education, baseline test score, Braak stage, apolipoprotein e4 (APOE e4) carrier status, family history of cognitive impairment, and history of stroke, hypertension, or diabetes. We identified 578 participants with a global CDR of 0.5 (i.e. mild cognitive impairment) at baseline, 126 with primary age-related tauopathy and 452 with Alzheimer’s disease. Examining the difference in rates of change in CDR sum of boxes and in all domain scores, participants with Alzheimer’s disease had a significantly steeper decline after becoming clinically symptomatic than those with primary age-related tauopathy. This remained true after adjusting for covariates.
The results of this analysis corroborate previous studies showing that primary age-related tauopathy has slower cognitive decline than Alzheimer’s disease across multiple neuropsychological domains, thus adding to the understanding of the neuropsychological burden in primary age-related tauopathy. The study provides further evidence to support the hypothesis that primary age-related tauopathy has distinct neuropathological and clinical features compared to Alzheimer’s disease.
Predicting sporadic Alzheimer’s disease progression via inherited Alzheimer’s disease‐informed machine‐learning
Introduction: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer’s disease (AD) is a critical yet unmet clinical challenge.
Methods: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer’s disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated.
Results: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50%–75%.
Discussion: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD.
Association of longitudinal changes in cerebrospinal fluid total tau and phosphorylated tau 181 and babin atrophy with disease progression in patients with Alzheimer disease
Importance: The amyloid/tau/neurodegeneration (A/T/N) framework uses cerebrospinal fluid (CSF) levels of total tau (tTau) as a marker of neurodegeneration and CSF levels of phosphorylated tau 181 (pTau181) as a marker of tau tangles. However, it is unclear whether CSF levels of tTau and pTau181 have similar or different trajectories over the course of Alzheimer disease.
Objectives: To examine the rates of change in CSF levels of tTau and pTau181 across the Alzheimer disease course and how the rates of change are associated with brain atrophy as measured by magnetic resonance imaging.
Design, Setting, and Participants: This cohort study was set in tertiary research clinics. Each participant was a member of a pedigree with a known mutation for dominantly inherited Alzheimer disease. Participants were divided into 3 groups on the basis of the presence of a mutation and their Clinical Dementia Rating score. Data analysis was performed in June 2019.
Main Outcomes and Measures: Rates of change of CSF tTau and pTau181 levels and their association with the rate of change of brain volume.
Results: Data from 465 participants (283 mutation carriers and 182 noncarriers) were analyzed. The mean (SD) age of the cohort was 37.8 (11.3) years, and 262 (56.3%) were women. The mean (SD) follow-up duration was 2.7 (1.5) years. Two or more longitudinal CSF and magnetic resonance imaging assessments were available for 160 and 247 participants, respectively. Sixty-five percent of mutation carriers (183) did not have symptoms at baseline (Clinical Dementia Rating score, 0). For mutation carriers, the annual rates of change for CSF tTau and pTau181 became significantly different from 0 approximately 10 years before the estimated year of onset (mean [SE] rates of change, 5.5 [2.8] for tTau [P = .05] and 0.7 [0.3] for pTau 181 [P = .04]) and 15 years before onset (mean [SE] rates of change, 5.4 [3.9] for tTau [P = .17] and 1.1 [0.5] for pTau181 [P = .03]), respectively. The rate of change of pTau181 was positive and increased at the early stages of the disease, showing a positive rate of change starting at 15 estimated years before onset until 5 estimated years before onset (mean [SE], 0.4 [0.3]), followed by a positive but decreasing rate of change at year 0 (mean [SE], 0.1 [0.3]) and then negative rates of change at 5 years (mean [SE], −0.3 [0.4]) and 10 years (mean [SE], −0.6 [0.6]) after symptom onset. In individuals without symptoms (Clinical Dementia Rating score, 0), the rates of change of CSF tTau and pTau181 were negatively associated with brain atrophy (high rates of change in CSF measures were associated with low rates of change in brain volume in asymptomatic stages). After symptom onset (Clinical Dementia Rating score, >0), an increased rate of brain atrophy was not associated with rates of change of levels of both CSF tTau and pTau181.
Conclusions and Relevance: These findings suggest that CSF tTau and pTau181 may have different associations with brain atrophy across the disease time course. These results have implications for understanding the dynamics of disease pathobiology and interpreting neuronal injury biomarker concentrations in response to Alzheimer disease progression and disease-modifying therapies.
Use of an experimental language acquisition paradigm for standardized neuropsychological assessment of learning: A pilot study in young and older adults
Introduction: Despite the numerous episodic memory tasks used in neuropsychological assessment, relatively few learning tasks are available, with methods lacking the complexity and sophistication to capture very subtle changes in information acquisition.
Method: We adapted a previously validated associative learning task for use within an online framework, utilizing real-world stimuli, in which learning of audio-visual pairs of Chinese characters and English words occurs over 5 days. The aim of this study was to validate our adaptation to the task, provide estimates of rates of learning in both young and older adults, as well as provide a methodological framework for further adaptation and development of the paradigm. A total of 30 young adults and 30 older adults completed 5 days of the Chinese Characters Learning Task (CCLT).
Results: Results indicated that rates of learning on the adapted task were comparable to the original paradigm and consistent across variations to testing frequency and duration. Our results also indicate the presence of a significant age-related impairment in the rate and accuracy of learning, with young adults aged 18–45 years performing significantly better than older adults aged 65–85 years, that was not due to differences in reaction time.
Conclusions: These findings suggest that daily measurement of cognition via an online platform can detect age-related impairments in learning and is therefore applicable for use within the context of age-related disorders of memory and learning.
Two‐period linear mixed effects models to analyze clinical trials with run‐in data when the primary outcome is continuous: Applications to Alzheimer’s disease
Introduction: Study outcomes can be measured repeatedly based on the clinical trial protocol before randomization during what is known as the “run-in” period. However, it has not been established how best to incorporate run-in data into the primary analysis of the trial.
Methods: We proposed two-period (run-in period and randomization period) linear mixed effects models to simultaneously model the run-in data and the postrandomization data.
Results: Compared with the traditional models, the two-period linear mixed effects models can increase the power up to 15% and yield similar power for both unequal randomization and equal randomization.
Discussion: Given that analysis of run-in data using the two-period linear mixed effects models allows more participants (unequal randomization) to be on the active treatment with similar power to that of the equal-randomization trials, it may reduce the dropout by assigning more participants to the active treatment and thus improve the efficiency of AD clinical trials.
A harmonized longitudinal biomarkers and cognition database for assessing the natural history of preclinical Alzheimer’s disease from young adulthood and for designing prevention trials
Introduction: Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer’s disease (AD) prevention.
Methods: Data for cerebrospinal fluid analytes, molecular imaging of cerebral fibrillar β-amyloid with positron emission tomography, magnetic resonance imaging–based brain structures, and clinical/cognitive outcomes were harmonized across eight AD biomarker studies. Statistical power was estimated.
Results: The harmonized database included 7779 participants with clinical/cognitive data: 3542 were 18∼65 years at the baseline, 5865 had longitudinal cognitive data for a median of 4.7 years, 2473 participated in the cerebrospinal fluid studies (906 had longitudinal data), 2496 participated in the magnetic resonance imaging studies (1283 had longitudinal data), and 1498 participated in the positron emission tomography amyloid studies (849 had longitudinal data). The database provides adequate power for detecting early biomarker changes, and demonstrates the feasibility of AD prevention trials on middle-aged individuals.
Discussion: The harmonized database is an optimum resource to design AD prevention trials decades before symptomatic onset.
Vascular risk factors are associated with longitudinal changes in cerebrospinal fluid tau markers and cognition in preclinical Alzheimer’s disease
Introduction: Vascular factors increase the risk of Alzheimer’s disease (AD). We investigated the associations between such factors, longitudinal AD cerebrospinal fluid biomarkers, and cognition.
Methods: 433 cognitively normal participants were classified into four biomarker groups using their baseline amyloid (A+/−) and tau status (T+/−). 184 participants had undergone serial cerebrospinal fluid collection. Frequencies of risk factors and the Framingham Risk Score (FRS) were compared, and we tested the influence of risk factors on change in biomarker concentrations and cognition.
Results: The absence of obesity, presence of hypertension, and a high FRS were associated with an increase in tau levels, particularly in A+T+ individuals. Risk factors were not associated with amyloid. Depression was associated with higher cognitive scores, whereas high FRS was associated with lower scores and a faster decline.
Discussion: Our results demonstrate that vascular risk factors may enhance neurodegeneration but not amyloid accumulation in preclinical AD.
Clinical, pathophysiological and genetic features of motor symptoms in autosomal dominant Alzheimer’s disease
Owing to an early and marked deposition of amyloid-β in the basal ganglia, autosomal dominant Alzheimer’s disease could distinctly involve motor symptoms. Therefore, we aimed to assess the prevalence and characteristics of motor signs in autosomal dominant Alzheimer’s disease. Baseline Unified Parkinson Disease Rating Scale part three scores (UPDRS-III) from 433 participants of the Dominantly Inherited Alzheimer’s Network observational study were analysed. Motor symptoms were scrutinized with respect to associations with mutation carrier status, mutation site within PSEN1, basal ganglia amyloid-β as measured by Pittsburgh compound B PET, estimated years to symptom onset and Clinical Dementia Rating Scale-Sum of Boxes. Motor findings in mutation carriers were compared to patients with sporadic Alzheimer’s disease using data of the National Alzheimer’s Coordination Center. Mutation carriers showed motor findings at a higher frequency (28.4% versus 12.8%; P < 0.001) and severity (mean UPDRS-III scores 2.0 versus 0.4; P < 0.001) compared to non-carriers. Eleven of the 27 UPDRS-III items were statistically more frequently affected in mutation carriers after adjustment for multiple comparisons. Ten of these 11 items were subscale components of bradykinesia. In cognitively asymptomatic mutation carriers, dysdiadochokinesia was more frequent compared to non-carriers (right hand: 3.8% versus 0%; adjusted P = 0.023; left: 4.4% versus 0.6%; adjusted P = 0.031). In this cohort, the positive predictive value for mutation carrier status in cognitively asymptomatic participants (50% a priori risk) of dysdiadochokinesia was 100% for the right and 87.5% for the left side. Mutation carriers with motor findings more frequently were basal ganglia amyloid-β positive (84% versus 63.3%; P = 0.006) and showed more basal ganglia amyloid-β deposition (Pittsburgh compound B-standardized uptake value ratio 2.472 versus 1.928; P = 0.002) than those without. Frequency and severity of motor findings were greater in post-codon 200 PSEN1 mutations (36%; mean UPDRS-III score 3.03) compared to mutations pre-codon 200 PSEN1 (19.3%, P = 0.022; 0.91, P = 0.013). In mutation carriers, motor symptom severity was significantly positively correlated with basal ganglia amyloid-β deposition, Clinical Dementia Rating scores and estimated years to symptom onset. Mutation carriers with a Clinical Dementia Rating global score of 2 exhibited more pronounced motor symptoms than sporadic Alzheimer’s disease patients with the same Clinical Dementia Rating global score (mean UPDRS-III scores 20.71 versus 5.96; P < 0.001). With a prevalence of approximately 30% and increasing severity with progression of dementia, motor symptoms are proven as a clinically relevant finding in autosomal dominant Alzheimer’s disease, in particular in advanced dementia stages, that correlates with deposition of amyloid-β in the basal ganglia. In a very small per cent of cognitively asymptomatic members of families with autosomal dominant Alzheimer’s disease, dysdiadochokinesia may increase the chance of an individual’s status as mutation carrier.
Tau PET in autosomal dominant Alzheimer’s disease: relationship with cognition, dementia and other biomarkers
Tauopathy is a hallmark pathology of Alzheimer’s disease with a strong relationship with cognitive impairment. As such, understanding tau may be a key to clinical interventions. In vivo tauopathy has been measured using cerebrospinal fluid assays, but these do not provide information about where pathology is in the brain. The introduction of PET ligands that bind to paired helical filaments provides the ability to measure the amount and distribution of tau pathology. The heritability of the age of dementia onset tied to the specific mutations found in autosomal dominant Alzheimer’s disease families provides an elegant model to study the spread of tau across the course of the disease as well as the cross-modal relationship between tau and other biomarkers. To better understand the pathobiology of Alzheimer’s disease we measured levels of tau PET binding in individuals with dominantly inherited Alzheimer’s disease using data from the Dominantly Inherited Alzheimer Network (DIAN). We examined cross-sectional
measures of amyloid-b, tau, glucose metabolism, and grey matter degeneration in 15 cognitively normal mutation non-carriers, 20 asymptomatic carriers, and 15 symptomatic mutation carriers. Linear models examined the association of pathology with group, estimated years to symptom onset, as well as cross-modal relationships. For comparison, tau PET was acquired on 17 older adults
with sporadic, late onset Alzheimer disease. Tau PET binding was starkly elevated in symptomatic DIAN individuals throughout the cortex. The brain areas demonstrating elevated tau PET binding overlapped with those seen in sporadic Alzheimer’s disease, but with a greater cortical involvement and greater levels of binding despite similar cognitive impairment. Tau PET binding was elevated in the temporal lobe, but the most prominent loci of pathology were in the precuneus and lateral parietal regions. Symptomatic mutation carriers also demonstrated elevated tau PET binding in the basal ganglia, consistent with prior work with amyloid-b. The degree of tau tracer binding in symptomatic individuals was correlated to other biomarkers, particularly markers of neurodegeneration. In addition to the differences seen with tau, amyloid-b was increased in both asymptomatic and symptomatic groups relative to non-carriers. Glucose metabolism showed decline primarily in the symptomatic group. MRI indicated structural degeneration in both asymptomatic and symptomatic cohorts. We demonstrate that tau PET binding is elevated in symptomatic individuals with dominantly inherited Alzheimer’s disease. Tau PET uptake was tied to the onset of cognitive dysfunction, and there was a higher amount, and different regional pattern of binding compared to late onset, nonfamilial Alzheimer’s disease.
The BDNF Val66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer’s disease
In Alzheimer’s disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aβ) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In
seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Aβ, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Aβ-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medialfrontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.
Emerging cerebrospinal fluid biomarkers in autosomal dominant Alzheimer’s disease
Introduction: Four less well-studied but promising “emerging” cerebrospinal fluid (CSF) biomarkers are elevated in late-onset Alzheimer disease (AD): neurogranin, synaptosomal-associated protein-25 (SNAP-25), visinin-like protein 1 (VILIP-1), and chitinase-3-like protein 1 (YKL-40). Methods: CSF neurogranin, SNAP-25, VILIP-1, and YKL-40 were measured in families carrying autosomal-dominant AD mutations. Results: The four emerging CSF biomarkers were significantly elevated in the mutation carriers (n = 235) versus noncarriers (n = 145). CSF SNAP-25, VILIP-1, and YKL-40 were altered very early in the AD time course, approximately 15-19 years before estimated symptom onset. All CSF biomarkers predicted important AD-related outcomes including performance on a cognitive composite, brain amyloid burden as measured by amyloid positron emission tomography, and the estimated years from symptom onset. Discussion: Early abnormalities in CSF tTau, pTau, SNAP-25, VILIP-1, and YKL-40 suggest that synaptic damage, neuronal injury, and neuroinflammation begin shortly after the commencement of brain amyloid accumulation.
Staging biomarkers in preclinical autosomal dominant Alzheimer’s disease by estimated years to symptom onset
Introduction: Staging preclinical Alzheimer disease (AD) by the expected years to symptom onset (EYO) in autosomal dominant AD (ADAD) through biomarker correlations is important.
Methods: We estimated the correlation matrix between EYO/cognition and imaging/CSF biomarkers, and searched for the EYO cutoff where a change in the correlations occurred before and after the cutoff among the asymptomatic mutation carriers of ADAD. We then estimated the longitudinal rate of change for biomarkers/cognition within each preclinical stage defined by the EYO.
Results: Based on the change in the correlations, the preclinical ADAD was divided by EYOs −7 and −13 years. Mutation carriers demonstrated a temporal ordering of biomarker/cognition changes across the three preclinical stages.
Discussion: Duration of each preclinical stage can be estimated in ADAD, facilitating better planning of prevention trials with the EYO cutoffs under the recently released FDA guidance. The generalization of these results to sporadic AD warrants further investigation.
Differences in cognitive impairment in primary age-related tauopathy versus Alzheimer disease
This study examined differences in neuropsychological test scores between individuals with primary age-related tauopathy (PART) and Alzheimer disease (AD) using cross-sectional data from the National Alzheimer’s Coordinating Center. Linear regression tested for differences in 4 cognitive domains stratified by cognitive status (global Clinical Dementia Rating [CDR]). The sample included 240 participants with no neuritic plaques (NP) (definite PART), 186 with sparse NP (possible PART), and 510 with moderate/frequent NP (AD). Four cognitive domain z-score outcome variables (memory, attention, executive function, and semantic memory/language) were calculated using 12 neuropsychological tests. Definite PART participants had a sparing of semantic memory/language compared to those with AD, with a mean adjusted z-score difference of 0.37 (95% confidence interval [CI]: 0.16–0.58) for those with CDR = 0.5 or 1 and of 0.92 (CI: 0.22–1.63) for those with CDR = 2 or 3. Compared to participants with AD, definite PART participants with CDR = 0.5 or 1 had sparing of memory (adjusted z-score difference: 0.61; CI: 0.39–0.84) and definite PART participants with CDR = 2 or 3 had sparing of attention (adjusted z-score difference: 0.76: CI: 0.09–1.43). Patterns of cognitive impairment differed between definite PART and AD, suggesting significant differences in clinical presentation between individuals from these 2 groups.
Awareness of genetic risk in the Dominantly Inherited Alzheimer Network (DIAN)
Introduction: Although some members of families with autosomal dominant Alzheimer’s disease mutations learn their mutation status, most do not. How knowledge of mutation status affects clinical disease progression is unknown. This study quantifies the influence of mutation awareness on clinical symptoms, cognition, and biomarkers.
Methods: Mutation carriers and non-carriers from the Dominantly Inherited Alzheimer Network (DIAN) were stratified based on knowledge of mutation status. Rates of change on standard clinical, cognitive, and neuroimaging outcomes were examined.
Results: Mutation knowledge had no associations with cognitive decline, clinical progression, amyloid deposition, hippocampal volume, or depression in either carriers or non-carriers. Carriers who learned their status mid-study had slightly higher levels of depression and lower cognitive scores.
Discussion: Knowledge of mutation status does not affect rates of change on any measured outcome. Learning of status mid-study may confer short-term changes in cognitive functioning, or changes in cognition may influence the determination of mutation status.
An atlas of cortical circular RNA expression in Alzheimer disease brains demonstrates clinical and pathological associations
Parietal cortex RNA-sequencing (RNA-seq) data were generated from individuals with and without Alzheimer disease (AD; ncontrol = 13; nAD = 83) from the Knight Alzheimer Disease Research Center (Knight ADRC). Using this and an independent (Mount Sinai Brain Bank (MSBB)) AD RNA-seq dataset, cortical circular RNA (circRNA) expression was quantified in the context of AD. Significant associations were identified between circRNA expression and AD diagnosis, clinical dementia severity and neuropathological severity. It was demonstrated that most circRNA–AD associations are independent of changes in cognate linear messenger RNA expression or estimated brain cell-type proportions. Evidence was provided for circRNA expression changes occurring early in presymptomatic AD and in autosomal dominant AD. It was also observed that AD-associated circRNAs co-expressed with known AD genes. Finally, potential microRNA-binding sites were identified in AD-associated circRNAs for miRNAs predicted to target AD genes. Together, these results highlight the importance of analyzing non-linear RNAs and support future studies exploring the potential roles of circRNAs in AD pathogenesis.