Hassenstab, Jason

AbstractINTRODUCTIONThis study investigated the role of the ubiquitin–proteasome system (UPS) in dominantly inherited Alzheimer's disease (DIAD) by examining cerebrospinal fluid (CSF) levels of UPS proteins.METHODThe SOMAscan assay was used to detect changes in UPS proteins in mutation carriers (MCs) relative to disease progression; imaging and CSF biomarkers of amyloid, tau, and neurodegeneration measures; and Clinical Dementia Rating scale.RESULTSSubtle increases in specific ubiquitin enzymes were detected in MCs up to two decades before symptom onset, with more pronounced elevations in UPS‐activating enzymes near symptom onset. Significant correlations were found between UPS proteins and Alzheimer's disease (AD) biomarkers, especially between autophagy markers and late‐stage tau biomarkers, microglia, and axonal degeneration.DISCUSSIONThe rise in UPS proteins alongside tau‐related markers suggests UPS involvement in tau neurofibrillary tangles. Elevated CSF UPS proteins in DIAD MCs may serve as indicators of disease progression, and may support the UPS as a therapeutic target in AD.Highlights This study investigates the ubiquitin‐proteasome system (UPS) in Dominantly Inherited Alzheimer's Disease (DIAD), highlighting early molecular changes linked to disease progression. Using SOMAscan proteomics, we identified significant UPS protein alterations in cerebrospinal fluid of mutation carriers, notably up to 20 years before clinical symptom onset. Correlations between UPS protein levels and Alzheimer's biomarkers, particularly tau and neurodegeneration markers, suggest a strong association between UPS dysregulation and tau pathology in DIAD. Dynamic UPS changes align with A/T biological staging: UPS proteins were shown to increase across Aβ/tau (A/T) groups, with largest increases in the A+/T+ group, reinforcing their role in late‐stage tau pathology and disease progression. These findings underscore the potential of UPS proteins as early biomarkers for Alzheimer's disease progression and as novel therapeutic targets, especially in tau‐pathology‐driven neurodegeneration. This work contributes to understanding AD pathogenesis, by emphasizing the importance of protein quality control systems and by offering avenues for future biomarker discovery and therapeutic development in Alzheimer's disease.

Abstract We present a comprehensive global analysis of genetic variants associated with autosomal-dominant Alzheimer’s disease (ADAD). A total of 550 variants in the APP, PSEN1 and PSEN2 genes were identified, of which 279 were classified as pathogenic or likely pathogenic based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria, utilizing data from the Dominantly Inherited Alzheimer Network (DIAN), literature and public databases. Symptomatic age at onset (AAO) data were estimated for 227 of these variants, allowing detailed characterization of their frequency, pathogenicity and AAO. Importantly, 226 variants met eligibility criteria for inclusion in disease-modifying clinical trials. Furthermore, we demonstrated the predictive value of mean variant AAO and parental AAO in predicting symptomatic AAO, validated against converters who became symptomatic during follow-up in the DIAN Observational Study. This dataset provides critical insights into the global landscape of ADAD and reveals the genetic and AAO heterogeneity of ADAD variants while refining variant trial eligibility criteria.

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

AbstractBackgroundAutosomal dominant Alzheimer disease (ADAD) is characterized by genetic mutations affecting the beta‐amyloid (Aβ) pathway. However, vascular and immune factors play important roles which are not completely understood. Understanding the function of the neurovascular unit (NVU) comprised of neurons, glial cells, and vasculature, at different disease stages appears ideal to developing and evaluating therapeutics. Omics approaches can inform NVU changes and their disease associations.MethodsCSF proteomic data using the Somalogic® platform was generated from 485 participants in the DIAN study, who also had PiB‐PET and MRI assessing Aβ burden, white matter hyperintensity (WMH), and cerebral microhemorrhage (CMH). From previously published AD studies, we identified 33 NVU‐associated proteins with corresponding Somalogic aptamers (Figure 1). We used Principal Component Analysis (PCA) on participants with complete data (n=262, 166 mutation‐carriers and 96 non‐carriers) to find groups of proteins associated with mutation status and disease stage as measured with estimated year to symptom onset (EYO), PiB‐PET, and clinical status. Linear‐mixed effect models and two‐part zero‐inflated negative binomial mixed models further evaluated the link between significant principal components (PCs) and WMH and CMH, respectively. Models accounted for age, APOE‐e4 status, sex, and education.ResultsThe first ten PCs explained >60% of the variance in NVU‐related protein levels (Figure 2A) with only PC5 (4.8%) associated with mutation*EYO, suggesting relationship with ADAD‐specific disease progression (***p<0.0001, Figure 2B). While asymptomatic PiB‐negative individuals were not significantly different from non‐carriers, asymptomatic PiB‐positive individuals had higher PC5 scores than non‐carriers and symptomatic individuals scored still higher (**p<0.005, ***p<0.0001, Figure 2C). The main proteins composing PC5 were: neurofilament light‐chain, angiopoietin‐2, SMOC1, LRP1, E‐selectin, and sTREM2, suggesting strong association with proinflammatory glial response from neuronal injury (Figure 2D). PC5 was also associated with WMH volumes (*p<0.05, Figure 3A) and with CMH count in participants with CMH (**p<0.005, Figure 3B).ConclusionsThis PCA approach indicates that some groups of NVU‐associated proteins are related with mutation status and disease stage, and that they are differentially associated with features of ADAD such as white matter integrity as measured by WMH volume. Weighted Correlation Network Analysis will be of interest to further understand these associations.Funding: K01AG080123, RF1‐AG044546, UF1AG032438

AbstractBackgroundAlzheimer disease (AD) related cognitive decline occurs at relatively young ages in individuals with Down syndrome (DS, early‐mid 50s) and in those with autosomal dominant mutations (ADAD, 40‐50s). Both groups show similar patterns of amyloid accumulation. We examined if brain volumes are similarly affected by AD pathology in individuals with DS and ADAD.MethodData for cognitively stable and declining participants was obtained from the Alzheimer Biomarker Consortium‐Down Syndrome (ABC‐DS) and the Dominantly Inherited Alzheimer Network (DIAN). Stability/decline was identified based on cognitive testing and interview of individuals and caregivers by trained assessors. Cognitively stable family members without DS/ADAD mutations were recruited as controls from both studies. Participants underwent MRI and amyloid positron emission tomography (PET) scans from which brain volumes and amyloid (centiloids) were derived, respectively. Participants from DIAN had Pittsburgh Compound‐B (PIB) scans, ABC‐DS had PIB or florbetapir. Nonlinear cross‐sectional associations between regional brain volumes and estimated years to onset of cognitive decline (EYO, negative values before onset, positive after) and centiloid were evaluated using generalized additive models while controlling for sex and random effects of family. EYO was set to 52 for all participants with DS and based on parental decline/mutation type for participants with ADAD. EYO for controls was based on the EYO of their family member.ResultData from 239 participants with DS (47 declining), and 340 participants with ADAD (122 declining), and 263 familial controls were included. Higher EYO and centiloid values were associated with lower brain volumes in almost all regions. At earlier EYOs, individuals with DS typically had smaller regional volumes than ADAD or sibling controls, with volume declining linearly across the EYO range. By contrast, ADAD mutation carriers had similar volumes to non‐carriers at early EYOs, with volumes diverging as early as 10 years before decline. Brain volumes and centiloid values were inversely related in ADAD and DSAD. Volume in key cortical regions were similar by the expected year of onset in both groups.ConclusionADAD and DSAD demonstrated different temporal patterns of regional neurodegeneration prior to cognitive change despite being similarly affected by early onset amyloid.

AbstractBackgroundAutosomal dominant Alzheimer disease (ADAD) is characterized by genetic mutations affecting the beta‐amyloid (Aß) pathway. However, vascular and immune factors play important roles which are not completely understood. Understanding the function of the neurovascular unit (NVU) comprised of neurons, glial cells, and vasculature, at different disease stages appears ideal to developing and evaluating therapeutics. Omics approaches can inform NVU changes and their disease associations.MethodsCSF proteomic data using the Somalogic® platform was generated from 485 participants in the DIAN study, who also had PiB‐PET and MRI assessing Aß burden, white matter hyperintensity (WMH), and cerebral microhemorrhage (CMH). From previously published AD studies, we identified 33 NVU‐associated proteins with corresponding Somalogic aptamers (Figure 1). We used Principal Component Analysis (PCA) on participants with complete data (n = 262, 166 mutation‐carriers and 96 non‐carriers) to find groups of proteins associated with mutation status and disease stage as measured with estimated year to symptom onset (EYO), PiB‐PET, and clinical status. Linear‐mixed effect models and two‐part zero‐inflated negative binomial mixed models further evaluated the link between significant principal components (PCs) and WMH and CMH, respectively. Models accounted for age, APOE‐e4 status, sex, and education.ResultsThe first ten PCs explained >60% of the variance in NVU‐related protein levels (Figure 2A) with only PC5 (4.8%) associated with mutation*EYO, suggesting relationship with ADAD‐specific disease progression (***p<0.0001, Figure 2B). While asymptomatic PiB‐negative individuals were not significantly different from non‐carriers, asymptomatic PiB‐positive individuals had higher PC5 scores than non‐carriers and symptomatic individuals scored still higher (**p<0.005, ***p<0.0001, Figure 2C). The main proteins composing PC5 were: neurofilament light‐chain, angiopoietin‐2, SMOC1, LRP1, E‐selectin, and sTREM2, suggesting strong association with proinflammatory glial response from neuronal injury (Figure 2D). PC5 was also associated with WMH volumes (*p<0.05, Figure 3A) and with CMH count in participants with CMH (**p<0.005, Figure 3B).ConclusionsThis PCA approach indicates that some groups of NVU‐associated proteins are related with mutation status and disease stage, and that they are differentially associated with features of ADAD such as white matter integrity as measured by WMH volume. Weighted Correlation Network Analysis will be of interest to further understand these associations. Funding: K01AG080123, RF1‐AG044546, UF1AG032438

AbstractBackgroundMany treatments targeting frontotemporal lobar degeneration (FTLD) are in the developmental pipeline, but the rarity of the disease, coupled with the behavioral and motor features of FTLD, make it challenging to identify sufficient trial participants who can attend frequent in‐person visits. Decentralized clinical trial designs with remote evaluations are attractive alternatives but require validated tools for symptom tracking. Our previous cross‐sectional analyses showed that cognitive tasks deployed via the ALLFTD Mobile App are reliable and sensitive to early stages of disease. The current study seeks to evaluate whether unsupervised smartphone cognitive tests are sensitive to longitudinal changes that occur with increasing FTLD disease stage.MethodThe study included 194 participants (mean baseline age 54.30, SD = 15.66; mean education = 16.52, SD = 2.31; 55.2% women) who were asymptomatic (Clinical Dementia Rating plus FTLD (CDR®+NACC‐FTLD) = 0 [n = 109; 43 carriers of FTLD‐associated genetic variants]), prodromal (CDR®+NACC‐FTLD = 0.5 [n = 39]), or symptomatic (CDR®+NACC‐FTLD>0.5 [n = 46]) at baseline. Participants completed ALLFTD Mobile App smartphone versions of Stroop, flanker, and 2‐back tasks, as well as an adaptive associative memory task, every six months for up to two years. Linear‐mixed effects models investigated the effect of disease severity on cognitive trajectories by testing the interaction of baseline CDR®+NACC‐FTLD box score and time on smartphone test scores. Analyses were repeated in the subsample of asymptomatic/prodromal CDR®+NACC‐FTLD<1) familial FTLD mutation carriers (C9orf72, n = 27; MAPT, n = 16). All models controlled for age, education, and sex.ResultGreater baseline disease severity was associated with lower cognitive scores across all tasks (β range: ‐0.28 to ‐0.13; p’s < 0.001), and faster rates of decline on the memory and 2‐back tasks (β range: ‐0.15 to ‐0.07; p’s<0.04). When the sample was restricted to asymptomatic and prodromal individuals (CDR®+NACC FTLD<1), greater baseline disease severity was still associated with lower scores across most tasks (β range: ‐0.48 to ‐0.27; p’s<0.002; 2‐back: β = ‐0.19, p = 0.26). When the sample was restricted to asymptomatic/prodromal mutation carriers, disease severity remained associated with the memory and flanker tasks (β range: ‐0.85 to ‐0.45; p’s<0.01).ConclusionThis study provides initial evidence that longitudinal smartphone‐based cognitive measurements capture the accelerated cognitive worsening that accompanies increasing disease progression in FTLD.