Chhatwal, Jasmeer P.

Abstract INTRODUCTION Cognition is reduced at low and high glucose, reflecting cognitive vulnerability to glucose (CVG) fluctuations. The impact of glucose fluctuations on the aging brain remains unclear. We examined whether CVG is associated with plasma biomarkers of Alzheimer's disease (AD) pathology and neurodegeneration. METHODS Participants included N = 114 adults with type 1 diabetes assessed for processing speed and sustained attention using ecological momentary assessment (EMA) combined with continuous glucose monitoring (CGM). We characterized associations between CVG and amyloid beta (Aβ) 42/40, phosphorylated tau (p‐tau) 181 and 217, neurofilament light chain, and glial fibrillary acidic protein. RESULTS CVG was associated with all plasma biomarkers, except Aβ 42/40. CVG for sustained attention exhibited strong associations with p‐tau biomarkers that persisted across covariate specifications. DISCUSSION CVG may be a useful digital phenotype of AD. It remains unclear whether CVG contributes to versus arises from neurodegeneration. We consider possible mechanisms linking cognitive vulnerability and long‐term glucose variability to the development of neuropathology. Highlights Cognitive vulnerability to glucose (CVG) may be a useful digital phenotype of neurodegeneration. We used cognitive ecological momentary assessment and continuous glucose monitoring to investigate CVG's associations with plasma biomarkers. Associations of CVG for sustained attention and phosphorylated tau 181 remained significant across covariates. We discuss possible mechanisms relating glucose variability, cognition, and neurodegeneration.

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.

AbstractBackgroundThe residual approach has found wide application in researching cognitive resilience, a phenomenon conceptually understood as cognitive performance being better‐than‐typical for an individual, despite apparent AD pathology. The standard residual approach extracts information about an individual’s resilience from the residuals of a linear model predicting cognition. This approach is subject to several limiting assumptions. Here, we explore the implications of these assumptions and propose an alternative predictive modeling approach which circumvents them.MethodsOur alternative approach relies on training a machine learning model on a sample of participants who follow a “typical” clinical progression (Fig. 1A). Residuals are then extracted for a heterogeneous dataset that potentially includes resilient participants by comparing observed cognitive outcomes to those predicted by the “typical” model (Fig. 1B). Additionally, our estimate can be refined by effectively estimating and removing model error from the extracted residual by leveraging a second predictive model (Fig. 1C). Using simulated data, we explore the assumptions made by the standard approach and the consequences of their violation. We then contrast this against our approach.ResultsOur simulations demonstrated that the standard residual approach only extracted accurate resilience estimates if the predictors used in the model explained cognition sufficiently well, while being unrelated to resilience itself. That is, as the predictors explain more of the resilience, the residuals became increasingly determined by model error (Fig. 2). We found that residuals achieved with our approach are more precise and provide individualized estimates that are unaffected by the aforementioned trade‐off (Fig. 3).ConclusionsOur approach holds several advantages over the standard approach: The definition of resilience can be freely adjusted and enforced via different definitions of “typical”, it allows for incorporating complex, non‐linear models without removing relevant information from the residual, the error component of the residual can be estimated through cross‐validation, and all predictors that potentially explain cognition can be included into the model without losing resilience information from the residual. Our approach can be used to measure any phenomenon that can be operationalized as a deviation from a typical outcome and, thus, is also applicable for researching resistance to pathology.

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

Abstract The grey matter of the brain develops and declines in coordinated patterns during the lifespan. Such covariation patterns of grey matter structure can be quantified as grey matter networks, which can be measured with magnetic resonance imaging. In Alzheimer’s disease, the global organization of grey matter networks becomes more random, which is captured by a decline in the small-world coefficient. Such decline in the small-world value has been robustly associated with cognitive decline across clinical stages of Alzheimer’s disease. The biological mechanisms causing this decline in small-world values remain unknown. Cerebrospinal fluid (CSF) protein biomarkers are available for studying diverse pathological mechanisms in humans and can provide insight into decline. We investigated the relationships between 10 CSF proteins and small-world coefficient in mutation carriers (N = 219) and non-carriers (N = 136) of the Dominantly Inherited Alzheimer Network Observational study. Abnormalities in Amyloid beta, Tau, synaptic (Synaptosome associated protein-25, Neurogranin) and neuronal calcium-sensor protein (Visinin-like protein-1) preceded loss of small-world coefficient by several years, while increased levels in CSF markers for inflammation (Chitinase-3-like protein 1) and axonal injury (Neurofilament light) co-occurred with decreasing small-world values. This suggests that axonal loss and inflammation play a role in structural grey matter network changes.

AbstractINTRODUCTIONWe investigated longitudinal associations between self‐reported exercise and Alzheimer's disease (AD)‐related biomarkers in individuals with autosomal dominant AD (ADAD) mutations.METHODSParticipants were 308 ADAD mutation carriers aged 39.7 ± 10.8 years from the Dominantly Inherited Alzheimer's Network. Weekly exercise volume was measured via questionnaire and associations with brain volume (magnetic resonance imaging), cerebrospinal fluid biomarkers, and brain amyloid beta (Aβ) measured by positron emission tomography were investigated.RESULTSGreater volume of weekly exercise at baseline was associated with slower accumulation of brain Aβ at preclinical disease stages β = –0.16 [–0.23 to –0.08], and a slower decline in multiple brain regions including hippocampal volume β = 0.06 [0.03 to 0.08].DISCUSSIONExercise is associated with more favorable profiles of AD‐related biomarkers in individuals with ADAD mutations. Exercise may have therapeutic potential for delaying the onset of AD; however, randomized controlled trials are vital to determine a causal relationship before a clinical recommendation of exercise is implemented.Highlights Greater self‐reported weekly exercise predicts slower declines in brain volume in autosomal dominant Alzheimer's disease (ADAD). Greater self‐reported weekly exercise predicts slower accumulation of brain amyloid beta in ADAD. Associations varied depending on closeness to estimated symptom onset.

Abstract This study explored the role of the ubiquitin-proteasome system (UPS) in dominantly inherited Alzheimer’s disease (DIAD) by examining changes in cerebrospinal fluid (CSF) levels of UPS proteins along with disease progression, AD imaging biomarkers (PiB PET, tau PET), neurodegeneration imaging measures (MRI, FDG PET), and Clinical Dementia Rating® (CDR®). Using the SOMAscan assay, we detected subtle increases in specific ubiquitin enzymes associated with proteostasis in mutation carriers (MCs) up to two decades before the estimated symptom onset. This was followed by more pronounced elevations of UPS-activating enzymes, including E2 and E3 proteins, and ubiquitin-related modifiers. Our findings also demonstrated consistent correlations between UPS proteins and CSF biomarkers such as Aβ42/40 ratio, total tau, various phosphorylated tau species to total tau ratios (ptau181/T181, ptauT205/T205, ptauS202/S202, ptauT217/T217), and MTBR-tau243, alongside Neurofilament light chain (NfL) and the CDR®. Notably, a positive association was observed with imaging markers (PiB PET, tau PET) and a negative correlation with markers of neurodegeneration (FDG PET, MRI), highlighting a significant link between UPS dysregulation and neurodegenerative processes. The correlations suggest that the increase in multiple UPS proteins with rising tau levels and tau-tangle associated markers, indicating a potential role for the UPS in relation to misfolded tau/neurofibrillary tangles (NFTs) and symptom onset. These findings indicate that elevated CSF UPS proteins in DIAD MCs could serve as early indicators of disease progression and suggest a link between UPS dysregulation and amyloid plaque, tau tangles formation, implicating the UPS as a potential therapeutic target in AD pathogenesis.

Abstract Approximately 5% of Alzheimer’s disease patients develop symptoms before age 65 (early-onset Alzheimer’s disease), with either sporadic (sporadic early-onset Alzheimer’s disease) or dominantly inherited (dominantly inherited Alzheimer’s disease) presentations. Both sporadic early-onset Alzheimer’s disease and dominantly inherited Alzheimer’s disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer’s disease and dominantly inherited Alzheimer’s disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer’s disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer’s Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer’s disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50–70 cerebellar grey reference and FDG30–60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer’s disease, sporadic early-onset Alzheimer’s disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen’s d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer’s V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer’s disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer’s disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer’s disease versus sporadic early-onset Alzheimer’s disease. Sporadic early-onset Alzheimer’s disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer’s disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer’s disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer’s disease.