Hassenstab, Jason

AbstractBackgroundThe balance between production, clearance, and toxicity of Ab peptides is central to AD pathobiology. Though highly variable in terms of age of symptom onset (AAO), hundreds of pathogenic variants in Presenilin‐1 (PSEN1) cause autosomal dominant forms of AD (ADAD). PSEN1 forms the catalytic core of the γ‐secretase complex and thereby directly mediates the production of longer, aggregation‐prone Aβ peptides relative to shorter, non‐aggregating peptides. We hypothesized that the broad AAO and biomarker heterogeneity seen across ADAD would be predictable based on mutation‐specific differences in γ‐secretase function, as measured by a ratio of production of shorter vs. longer Aβ species.MethodsAβ‐37, 38, 40, 42, and 43 production was quantified from 162 unique PSEN1 variants expressed in HEK293 cells engineered to lack endogenous wild‐type PSEN1/2 (Figure 1). Prediction of AAO was carried out in 107 PSEN1 variants (characterized by Liu et al, 2022) and then replicated with a set 55 unique PSEN1 variants represented in the Dominantly Inherited Alzheimer Network (DIAN; n = 190 corresponding variant carriers with detailed cognitive and biomarker data; Figure 2).ResultsMutation‐level variations in Aβ production, including a novel composite representing γ‐secretase function (lower score = less g‐processivity), from the cellular model were highly predictive of actual AAO across the 162 mutants examined (Non‐DIAN variants [N = 107]: r = 0.71, p <2.2e‐16; DIAN variants [N = 55]: r = 0.61, p = 6.10e‐07). Our cell‐based γ‐secretase function composite was strongly associated with cerebral PiB‐PET β‐amyloid burden (B[SE] = ‐0.03[0.01], p = 4.06e‐07), MRI gray matter volume (B[SE] = 44.22[6.4], p = 5.15e‐01), cerebrospinal fluid Aβ42/40 (B[SE] = 6.3e‐04[1.5e‐04], p = 4.46e‐05) and phosphorylated tau‐217 (B[SE] = ‐0.01[0.002], p = 1.98e‐05), Clinical Dementia Rating®‐ Sum of Boxes (B[SE] = ‐0.07[0.02], p = 4.86e‐05), and Mini‐Mental State Exam (B[SE] = 0.11[.03], p = 2.17e‐04).ConclusionsBiochemical variations in γ‐secretase function across PSEN1 pathogenic variants broadly predicted the cross‐sectional clinical, cognitive, and biomarker course of ADAD, including AAO. These findings elucidate the critical link between γ‐secretase function, Aβ production, and severity of AD. The novel approach designed here also represents a tool to account for heterogeneity in ADAD clinical trials and to assess the pathogenicity of PSEN1 variants of unknown significance or with limited family history.

AbstractBackgroundThere has been a rise in remote cognitive testing for neurodegenerative diseases. The ALLFTD Mobile App is designed to capture clinical features of frontotemporal dementia (FTD) through repeated remote assessment on smartphones. This is a departure from traditional neuropsychological practice in which a single examiner‐led assessment occurs in a controlled setting. When participants complete tasks on their own, those with greater disease severity may be more variable in their performance for a variety of reasons (e.g. greater distractibility, less engagement). Here we study whether intraindividual cognitive variability (IIV) is associated with older age and increasing disease severity.MethodParticipants were 279 (mean age = 54.9) healthy controls and participants with sporadic FTD or from familial FTD kindreds with a range of disease severities based on FTLD Clinical Dementia Rating scale (CDR®+NACC‐FTLD Global) scores: 0 (n = 132), 0.5 (n = 54), and ≥1 (n = 47). Participants completed three cognitive tasks at least two times across twelve days. Measures included an adaptive memory task and gamified versions of Flanker and Go/no‐go tasks. IIV was operationalized as the standard deviation in performance on each task. Regression analyses investigated the relationship of IIV with CDR®+NACC‐FTLD group, and with age in those without symptoms. Education and gender were included as covariates in all analyses.ResultGreater disease severity (CDR®+NACC‐FTLD) was associated with greater variability on Flanker (p<.001) and Go/No‐go (p = .02) tasks; a positive but non‐significant association was seen with memory testing (p = .16). Post‐hoc comparisons found that those with CDR®+NACC‐FTLD of 0.5 had significantly more IIV on the Flanker task (𝛃 = .39, p = .004) than those with CDR®+NACC‐FTLD’s of 0. Moreover, those with a CDR®+NACC‐FTLD ≥1 had significantly greater IIV on the Flanker (𝛃 = .85, p<.001) and Go/No‐go tasks (𝛃 = .51, p = .007) than those with a CDR®+NACC‐FTLD of 0. In those without symptoms (CDR®+NACC‐FTLD = 0), age was associated with increased IIV on the Flanker (𝛃 = .27, p<.001) and Go/no‐go (𝛃 = .23, p<.001) tasks.ConclusionIncreased IIV, particularly on processing speed/executive functioning tasks, was associated with greater age and greater functional impairment, even in the mildest stages. Future investigations exploring predictors of IIV and the prognostic value of IIV are warranted.

AbstractBackgroundEasily accessible and self‐administered cognitive assessments that can aide early identification of individuals at risk for Alzheimer’s disease (AD) dementia are critical for timely intervention. Mayo Test Drive (MTD) is a remote, self‐administered, multi‐device compatible, web‐based cognitive assessment (Stricker et al., 2022). We investigated continuous associations between MTD and amyloid and tau PET biomarkers and compared the strength of association to PET biomarkers and in‐person cognitive measures.Method556 adults from the Mayo Clinic Study of Aging participated (mean age = 70.6; mean education = 16.0 years; 50.7% female; 97.5% white). Participants were predominantly cognitively unimpaired (95.3%; 4.7% had a consensus diagnosis of mild cognitive impairment). Participants completed (1) brain amyloid and tau PET scans, (2) in‐person neuropsychological assessment including Mayo Preclinical Alzheimer’s disease Cognitive Composite (Mayo‐PACC) and Global‐z, and (3) remote MTD comprised of the Stricker Learning Span (SLS) and the Symbols test, which are combined into an MTD composite. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers [amyloid meta‐region of interest (ROI), tau meta‐ROI, and tau entorhinal cortex (EC)‐ROI)] and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites.ResultLower performances on MTD composite and Mayo‐PACC were associated with higher amyloid meta‐ROI (p’s<.05; Table 1). MTD composite was also negatively associated with tau meta‐ROI and EC‐ROI (p’s<.05). For memory measures, SLS sum of trials was negatively associated with tau meta‐ROI (p = .01) and EC‐ROI (p<.001) with no associations between AVLT sum of trials and PET (p’s≥.06; Table 2). Among processing speed/executive function measures, worse Trails B performance was associated with higher amyloid meta‐ROI (p<.001). Symbols and Digit Symbol Coding were not associated with PET (p’s≥.29). A multivariable model with MTD explained significantly less variance (p = .04) for amyloid meta‐ROI (adjusted R‐squared = 0.165) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.176); remote and in‐person composite measures were comparable for other associations (p’s>.05).ConclusionMTD is associated with continuous measures of amyloid and tau PET biomarkers of AD, demonstrating criterion validity for MTD. Several associations were comparable to relationships between gold‐standard in‐person neuropsychological tests and imaging biomarkers.

AbstractBackgroundBrief self‐administered cognitive assessments deployed remotely and combined with plasma biomarkers of Alzheimer’s disease (AD) are well suited to assess clinical symptoms and underlying biology in large‐scale decentralized studies. We investigated whether associations of self‐administered cognitive measures and plasma biomarkers were comparable to associations of in‐person cognitive measures and plasma biomarkers.MethodParticipants included 327 adults from the Mayo Clinic Study of Aging (mean age = 70.8; 48% female; mean education = 16.0 years; 96.9% white). Most (94.5%) were cognitively unimpaired; 5.5% had consensus diagnosis of mild cognitive impairment. Participants completed Mayo Test Drive (MTD; Stricker et al., 2022), a remote, self‐administered, multi‐device compatible web‐based cognitive assessment comprised of the Stricker Learning Span (SLS) and Symbols test that are combined into a MTD composite. Participants also completed in‐person neuropsychological assessment (global‐z; Mayo Preclinical Alzheimer’s disease Cognitive Composite [Mayo‐PACC]) and fasting venipuncture. Plasma was assayed via HD‐X simoa platform for amyloid‐beta (Aβ)‐42 and Aβ‐40 to create an Aβ42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) using the N4PE Quanterix kit as well as phosphorylated‐tau protein 181 (p‐tau181). P‐tau181, GFAP, and NfL were log10‐transformed. Multiple regression analyses adjusting for age, sex, and education examined associations between plasma biomarkers and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites.ResultLower performances on MTD, global‐z, and Mayo‐PACC (Table 1) were associated with higher GFAP (p’s≤.02), NfL (p’s≤.003), and p‐tau181 (p’s = .04). For memory, worse SLS and AVLT sum of trials were associated with higher GFAP (p’s≤.01) and NfL (p’s≤.03). For processing speed/executive function, worse Symbols and Trails B were associated with higher p‐tau181 (p’s≤.02). Worse Trails B and Digit Symbol Coding were associated with higher NfL (p’s≤.02), and worse Digit Symbol Coding was associated with lower Aβ42/40 (p = 0.03; Table 2). A multivariable model with MTD explained significantly more variance (p = .04) for NfL (adjusted R‐squared = 0.461) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.447); remote and in‐person composite measures were comparable for other associations (p’s>.05).ConclusionRemote and in‐person composite measures showed comparable associations with AD‐related plasma biomarkers, supporting MTD’s criterion validity.

AbstractBackgroundTriplication of the APP allele in Down syndrome (DS) leads to excess amyloid production and Alzheimer’s disease (AD) related cognitive decline. Key biomarkers (amyloid, tau, neurodegeneration) can identify pathological processes that occur before clinical symptoms and more precisely stage adults with DS along the AD continuum. Previous research has used changes in cortical thickness (CT) as an indicator of neurodegeneration in autosomal‐dominant AD1, but not DS‐related AD. It is unclear when and where cortical thinning occurs along the AD continuum in DS and if these differences are associated with increasing AD pathology.MethodCross‐sectional analysis compared DS participants from the Alzheimer Biomarkers Consortium‐Down Syndrome (106 amyloid‐/cognitively unimpaired, nonclinical, 20% reserved for receiver‐operating characteristic, ROC, analyses; 45 amyloid+/cognitively unimpaired, preclinical; 27 amyloid+/cognitively impaired, clinical) who had amyloid positron emission tomography and magnetic resonance imaging (MRI). Amyloid positivity was defined using standardized uptake value ratio (partial volume corrected) cortical mean values (1.42/1.19 for PIB/AV452) and impairment was based on consensus diagnosis. CT differences between nonclinical and clinical groups were calculated in FreeSurfer v5.3 for multiple thresholds (p<.05/.01/.005/.001/.0005/.0001) using a cluster‐wise false discovery rate of .001, corrected across hemispheres, after controlling for age and sex. CT values were extracted for each threshold and used in ROC analyses (nonclinical reserved participants compared against preclinical and preclinical compared against clinical) to identify key cortical regions that best discriminated amyloid positivity and between unimpaired and impaired.ResultSignificant decreases in parietal and inferior temporal CT were observed between nonclinical and clinical (Figures 1 and 2). ROC analyses identified regions in the left (threshold .05) and right (threshold .005) hemispheres that best differentiated nonclinical from preclinical. Observed area under the curves (AUCs) of .772 and .830 exceeded those previously reported for autosomal‐dominant AD (.547/.540)1. Analyses differentiating preclinical from clinical observed AUCs of .786 for left (threshold .0005) and .770 for right (threshold .0005) hemispheres.ConclusionCT differences primarily within posterior cortical regions differentiated adults with DS by amyloid status and cognitive impairment. CT differences were more diffuse for amyloid positivity but more focal for impairment.1. Dincer (2020). NeuroImage: Clinical, 28, 102491.2. Su (2019). Alzheimer’s Dement, 11, 180‐190.

AbstractBackgroundAdults with Down Syndrome (DS) develop Alzheimer disease (AD)‐like pathology and dementia as they age. This is attributed to triplication of the amyloid precursor protein gene. Recent work demonstrated that amyloid is elevated in DS and accumulates in a similar topography to autosomal dominant AD (ADAD). Tau accumulation is the second hallmark of AD and may be measured using tau positron emission tomography (PET) imaging. The pattern of tau accumulation remains unknown in DS.MethodIn a cross‐sectional analysis we evaluated amyloid and tau positron emission tomography (PET) in 124 participants with DS (109 cognitively stable, 8 symptomatic, 7 no consensus), 29 ADAD mutation carriers (26 asymptomatic, 3 symptomatic), and 201 cognitively normal non‐mutation carriers (CN). Regional cortical standard uptake value ratios (SUVR) for tau imaging were obtained and compared by cognitive status. Similarly, regional cortical amyloid SUVR were obtained and converted to centiloids. We then compared the magnitude of tau burden as well as spatial spread of tau across groups relative to amyloid burden.ResultCompared to CN, tau PET binding was elevated in participants with (µDS = 2.12 ± 0.22 SUVR, µADAD = 2.52 ± 0.37 SUVR) and without (µDS = 1.24 ± 0.15 SUVR, µADAD = 1.16 ± 0.19 SUVR) cognitive changes. For both groups, tau increased with increasing amyloid (centiloids). In some regions, DS had greater tau burden for a given amyloid level (centiloids) (Figure 1). There was increased spatial distribution of tau throughout the brain for participants with DS compared to CN. In contrast, tau burden was more focal in participants with ADAD with tau primarily elevated in posterior regions (Figure 2).ConclusionWhile tau burden was higher with symptomatic disease for both groups, significant differences existed in the overall amount and spatial spread. Tau spread was greatest in participants with DS and more diffuse compared to ADAD. These results indicate a substantial tau burden is present in DS, and suggest not only anti‐amyloid but also tau‐reducing agents should be considered for treating cognitive decline in adults with DS.

AbstractBackgroundDisease‐modifying therapies for Alzheimer’s Disease (AD) are likely most beneficial when initiated in the pre‐symptomatic phase. To track success of such interventions fluid biomarkers became instrumental, with neurofilament light chain (NfL) showing particular promise. We previously reported that serum NfL increases in pre‐symptomatic phases of familial (autosomal‐dominantly inherited) AD (fAD) and that within‐person rate‐of‐change in NfL is an earlier predictor of fAD symptom onset compared to cross‐sectional levels. The aim of the study at hand was to extend these initial findings in a larger cohort.MethodParticipants enrolled in the Dominantly Inherited Alzheimer Network (DIAN) with matched cross‐sectional and longitudinal cerebrospinal fluid (CSF; n = 962) as well as plasma (n = 1294) samples were used. NfL measurements have been performed on the SIMOA platform using commercially available assay‐kits. To investigate the influence of physiological factors independent from AD, we first analyzed whether age and body mass index (BMI) could account for observed variation in inter‐individual CSF and plasma NfL levels considering non‐carrier family‐members (NC) as a healthy control group. Next, utilizing estimated years to symptom onset (EYO) and previously published methods (Preische et al., 2019), we determined the point in disease course when baseline and longitudinal CSF and plasma NfL concentrations started to increase in mutation carriers (MC) relative to NC, after adjusting for age and BMI.ResultOur results reveal a tight correlation of CSF and blood NfL values within MC as well as NC (figure 1A‐B). However, within NC, after correction for age and BMI, some unexplained variability remained (figure 1C). Further, a decrease of the NfL plasma/CSF ratio over age was found after correcting for BMI (figure 1D). The discrimination of MC from NC was equally good for plasma compared to CSF, being possible on the group level as early as around ‐15 to almost ‐20 EYO depending on the modelling (figure 2).ConclusionOur results support plasma equivalently to CSF NfL as a clinically useful biomarker to longitudinally track neurodegeneration in fAD. The systemic factors influencing physiological NfL values in blood should be investigated in future studies to further improve interpretation of this biomarker.

Abstract Background Easily accessible and self‐administered cognitive assessments that can aide early identification of individuals at risk for Alzheimer’s disease (AD) dementia are critical for timely intervention. Mayo Test Drive (MTD) is a remote, self‐administered, multi‐device compatible, web‐based cognitive assessment (Stricker et al., 2022). We investigated continuous associations between MTD and amyloid and tau PET biomarkers and compared the strength of association to PET biomarkers and in‐person cognitive measures. Method 556 adults from the Mayo Clinic Study of Aging participated (mean age = 70.6; mean education = 16.0 years; 50.7% female; 97.5% white). Participants were predominantly cognitively unimpaired (95.3%; 4.7% had a consensus diagnosis of mild cognitive impairment). Participants completed (1) brain amyloid and tau PET scans, (2) in‐person neuropsychological assessment including Mayo Preclinical Alzheimer’s disease Cognitive Composite (Mayo‐PACC) and Global‐z, and (3) remote MTD comprised of the Stricker Learning Span (SLS) and the Symbols test, which are combined into an MTD composite. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers [amyloid meta‐region of interest (ROI), tau meta‐ROI, and tau entorhinal cortex (EC)‐ROI)] and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites. Result Lower performances on MTD composite and Mayo‐PACC were associated with higher amyloid meta‐ROI (p’s<.05; Table 1). MTD composite was also negatively associated with tau meta‐ROI and EC‐ROI (p’s<.05). For memory measures, SLS sum of trials was negatively associated with tau meta‐ROI (p = .01) and EC‐ROI (p<.001) with no associations between AVLT sum of trials and PET (p’s = .06; Table 2). Among processing speed/executive function measures, worse Trails B performance was associated with higher amyloid meta‐ROI (p<.001). Symbols and Digit Symbol Coding were not associated with PET (p’s = .29). A multivariable model with MTD explained significantly less variance (p = .04) for amyloid meta‐ROI (adjusted R‐squared = 0.165) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.176); remote and in‐person composite measures were comparable for other associations (p’s>.05). Conclusion MTD is associated with continuous measures of amyloid and tau PET biomarkers of AD, demonstrating criterion validity for MTD. Several associations were comparable to relationships between gold‐standard in‐person neuropsychological tests and imaging biomarkers.

Abstract Background Brief self‐administered cognitive assessments deployed remotely and combined with plasma biomarkers of Alzheimer’s disease (AD) are well suited to assess clinical symptoms and underlying biology in large‐scale decentralized studies. We investigated whether associations of self‐administered cognitive measures and plasma biomarkers were comparable to associations of in‐person cognitive measures and plasma biomarkers. Method Participants included 327 adults from the Mayo Clinic Study of Aging (mean age = 70.8; 48% female; mean education = 16.0 years; 96.9% white). Most (94.5%) were cognitively unimpaired; 5.5% had consensus diagnosis of mild cognitive impairment. Participants completed Mayo Test Drive (MTD; Stricker et al., 2022), a remote, self‐administered, multi‐device compatible web‐based cognitive assessment comprised of the Stricker Learning Span (SLS) and Symbols test that are combined into a MTD composite. Participants also completed in‐person neuropsychological assessment (global‐z; Mayo Preclinical Alzheimer’s disease Cognitive Composite [Mayo‐PACC]) and fasting venipuncture. Plasma was assayed via HD‐X simoa platform for amyloid‐beta (Aß)‐42 and Aß‐40 to create an Aß42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) using the N4PE Quanterix kit as well as phosphorylated‐tau protein 181 (p‐tau181). P‐tau181, GFAP, and NfL were log10‐transformed. Multiple regression analyses adjusting for age, sex, and education examined associations between plasma biomarkers and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites. Result Lower performances on MTD, global‐z, and Mayo‐PACC (Table 1) were associated with higher GFAP (p’s = .02), NfL (p’s = .003), and p‐tau181 (p’s = .04). For memory, worse SLS and AVLT sum of trials were associated with higher GFAP (p’s = .01) and NfL (p’s = .03). For processing speed/executive function, worse Symbols and Trails B were associated with higher p‐tau181 (p’s = .02). Worse Trails B and Digit Symbol Coding were associated with higher NfL (p’s = .02), and worse Digit Symbol Coding was associated with lower Aß42/40 (p = 0.03; Table 2). A multivariable model with MTD explained significantly more variance (p = .04) for NfL (adjusted R‐squared = 0.461) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.447); remote and in‐person composite measures were comparable for other associations (p’s>.05). Conclusion Remote and in‐person composite measures showed comparable associations with AD‐related plasma biomarkers, supporting MTD’s criterion validity.

Abstract Approximately 5% of Alzheimer’s disease cases have an early age at onset (&lt;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 &lt; 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 &lt; 0.001), Trail Making Test Part B (P &lt; 0.001) and digit span (P &lt; 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.