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INTRODUCTION: The current study evaluated the relationship between habitual physical activity (PA) levels and brain amyloid beta (Aβ) over 15 years in a cohort of cognitively unimpaired older adults. METHODS: PA and Aβ measures were collected over multiple timepoints from 731 cognitively unimpaired older adults participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Aging. Regression modeling examined cross‐sectional and longitudinal relationships between PA and brain Aβ. Moderation analyses examined apolipoprotein E (APOE) ε4 carriage impact on the PA‐Aβ relationship. RESULTS: PA was not associated with brain Aβ at baseline (β = –0.001, p = 0.72) or over time (β = –0.26, p = 0.24). APOE ε4 status did not moderate the PA‐Aβ relationship over time (β = 0.12, p = 0.73). Brain Aβ levels did not predict PA trajectory (β = –54.26, p = 0.59). DISCUSSION: Our study did not identify a relationship between habitual PA and brain Aβ levels. Highlights: Physical activity levels did not predict brain amyloid beta (Aβ) levels over time in cognitively unimpaired older adults (≥60 years of age).Apolipoprotein E (APOE) ε4 carrier status did not moderate the physical activity–brain Aβ relationship over time.Physical activity trajectories were not impacted by brain Aβ levels. [ABSTRACT FROM AUTHOR]

Introduction: The current study investigated the association between objectively measured physical activity and cognition in older adults over approximately 8 years. Methods: We utilized data from 199 cognitively unimpaired individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, aged ≥60. Actigraphy was used to measure physical activity (intensity, total activity, and energy expenditure) at baseline. Cognition was assessed using a comprehensive cognitive battery every 18‐months. Results: Higher baseline energy expenditure predicted better episodic recall memory and global cognition over the follow‐up period (p = 0.031; p = 0.047, respectively). Those with higher physical activity intensity and greater total activity also had better global cognition over time (both p = 0.005). Finally, higher total physical activity predicted improved episodic recall memory over time (p = 0.022). Discussion: These results suggest that physical activity can preserve cognition and that activity intensity may play an important role in this association. Highlights: Greater total physical activity predicts preserved episodic memory and global cognition.Moderate intensity physical activity (>3.7 metabolic equivalents of task [MET]) predicts preserved global cognition.Expending > 373 kilocalories per day may benefit episodic memory and global cognition. [ABSTRACT FROM AUTHOR]

Introduction: Plasma amyloid beta (Aβ)1‐42/Aβ1‐40 ratio, phosphorylated‐tau181 (p‐tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) are putative blood biomarkers for Alzheimer's disease (AD). However, head‐to‐head cross‐sectional and longitudinal comparisons of the aforementioned biomarkers across the AD continuum are lacking. Methods: Plasma Aβ1‐42, Aβ1‐40, p‐tau181, GFAP, and NfL were measured utilizing the Single Molecule Array (Simoa) platform and compared cross‐sectionally across the AD continuum, wherein Aβ‐PET (positron emission tomography)–negative cognitively unimpaired (CU Aβ−, n = 81) and mild cognitive impairment (MCI Aβ−, n = 26) participants were compared with Aβ‐PET–positive participants across the AD continuum (CU Aβ+, n = 39; MCI Aβ+, n = 33; AD Aβ+, n = 46) from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) cohort. Longitudinal plasma biomarker changes were also assessed in MCI (n = 27) and AD (n = 29) participants compared with CU (n = 120) participants. In addition, associations between baseline plasma biomarker levels and prospective cognitive decline and Aβ‐PET load were assessed over a 7 to 10‐year duration. Results: Lower plasma Aβ1‐42/Aβ1‐40 ratio and elevated p‐tau181 and GFAP were observed in CU Aβ+, MCI Aβ+, and AD Aβ+, whereas elevated plasma NfL was observed in MCI Aβ+ and AD Aβ+, compared with CU Aβ− and MCI Aβ−. Among the aforementioned plasma biomarkers, for models with and without AD risk factors (age, sex, and apolipoprotein E (APOE) ε4 carrier status), p‐tau181 performed equivalent to or better than other biomarkers in predicting a brain Aβ−/+ status across the AD continuum. However, for models with and without the AD risk factors, a biomarker panel of Aβ1‐42/Aβ1‐40, p‐tau181, and GFAP performed equivalent to or better than any of the biomarkers alone in predicting brain Aβ−/+ status across the AD continuum. Longitudinally, plasma Aβ1‐42/Aβ1‐40, p‐tau181, and GFAP were altered in MCI compared with CU, and plasma GFAP and NfL were altered in AD compared with CU. In addition, lower plasma Aβ1‐42/Aβ1‐40 and higher p‐tau181, GFAP, and NfL were associated with prospective cognitive decline and lower plasma Aβ1‐42/Aβ1‐40, and higher p‐tau181 and GFAP were associated with increased Aβ‐PET load prospectively. Discussion: These findings suggest that plasma biomarkers are altered cross‐sectionally and longitudinally, along the AD continuum, and are prospectively associated with cognitive decline and brain Aβ‐PET load. In addition, although p‐tau181 performed equivalent to or better than other biomarkers in predicting an Aβ−/+ status across the AD continuum, a panel of biomarkers may have superior Aβ−/+ status predictive capability across the AD continuum. HIGHLIGHTS: Area under the curve (AUC) of p‐tau181 ≥ AUC of Aβ42/40, GFAP, NfL in predicting PET Aβ−/+ status (Aβ−/+). AUC of Aβ42/40+p‐tau181+GFAP panel ≥ AUC of Aβ42/40/p‐tau181/GFAP/NfL for Aβ−/+. Longitudinally, Aβ42/40, p‐tau181, and GFAP were altered in MCI versus CU. Longitudinally, GFAP and NfL were altered in AD versus CU. Aβ42/40, p‐tau181, GFAP, and NfL are associated with prospective cognitive decline. Aβ42/40, p‐tau181, and GFAP are associated with increased PET Aβ load prospectively. [ABSTRACT FROM AUTHOR]

Background: Plasma amyloid‐β (Aβ) 1‐42/Aβ1‐40 ratio, phosphorylated‐tau181 (p‐tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NFL) are putative blood‐based biomarkers for Alzheimer's disease (AD). However, head‐to‐head comparisons of the afore‐mentioned biomarkers across the AD continuum are lacking. Method: Plasma Aβ1‐42, Aβ1‐40, p‐tau181, GFAP and NFL were measured using the Single Molecule Array platform and compared cross‐sectionally in models with and without AD risk factors (age, sex and APOE ε4 status) across the AD continuum in Aβ PET positive confirmed participants (CU Aβ+, n = 39; MCI Aβ+, n = 33; AD Aβ+, n = 46) and Aβ PET negative confirmed participants (CU Aβ‐, n = 81; MCI Aβ‐, n = 26) from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) cohort. Area under the receiver operating characteristic curves (AUCs) for predicting Aβ PET‐/+ status were compared using DeLong test. Associations between plasma biomarker levels at baseline and prospective cognitive decline (CDR‐SOB) and brain Aβ load were also assessed. Result: Lower plasma Aβ1‐42/Aβ1‐40 ratio and higher p‐tau181 and GFAP were observed in preclinical AD (Aβ1‐42/Aβ1‐40 ratio: ∼19%; p‐tau181: ∼70%; GFAP: ∼52%), prodromal AD (Aβ1‐42/Aβ1‐40 ratio: ∼14%; p‐tau181: ∼69%; GFAP: ∼45%) and AD (Aβ1‐42/Aβ1‐40 ratio: ∼16%; p‐tau181: ∼91%; GFAP: ∼85%), and higher plasma NFL was observed in prodromal AD (∼27%) and AD (∼45%) (Figure 1). Based on the AUCs, p‐tau181 performed equivalent to or better than (≥) other biomarkers, in predicting Aβ PET‐/+ status across the AD continuum (p‐tau AUCs for CU Aβ‐ vs CU Aβ+ ∼81%/ MCI Aβ+ ∼86%/ AD ∼92%). A biomarker panel of Aβ1‐42/Aβ1‐40 ratio, p‐tau181 and GFAP performed ≥ the biomarkers alone in predicting Aβ PET‐/+ status across the AD continuum (biomarker panel AUCs for CU Aβ‐ vs CU Aβ+ 90%/ MCI Aβ+ 89%/ AD 96%). Higher p‐tau181 (β = 0.531, p = 3.18E‐08), GFAP (β = 0.530, p = 5.07E‐08) and NFL (β = 0.487, p = 4.76E‐06) were associated with cognitive decline prospectively and lower plasma Aβ1‐42/Aβ1‐40 ratio (β = ‐6.035, p = 1.56E‐04) and higher p‐tau181 (β = 2.823, p = 4.72E‐05) and GFAP (β = 2.075, p = 0.003) were associated with increased Aβ PET load prospectively. Conclusion: These findings suggest that plasma biomarkers are altered across the AD continuum and are associated with cognitive decline and increased brain Aβ load prospectively. [ABSTRACT FROM AUTHOR]

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study is a prospective study collecting extensive cognitive, clinical, fluid, and imaging biomarkers data from older adults living in Australia. Integration of outcomes between large prospective studies of AD will provide greater precision in models of AD brain‐behavior relationships, so it is important to align composite scores for cognitive domains between such studies. Methods: Detailed methods for AIBL, the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the National Alzheimer's Coordinating Center (NACC) have been published. Briefly, AIBL participants had cognition assessed with an extensive neuropsychological test battery alongside health and biomarker assessments at entry and each 18‐months thereafter. Granular‐level cognitive data were obtained and an expert panel of two neuropsychologists and a behavioral neurologist categorized each element as assessing memory, executive functioning, language, visuospatial, or none of these, exactly as we have done previously. We also identified elements we had previously calibrated from other studies; after careful quality control and confirmation these served as anchors enabling co‐calibration. We used confirmatory factor analysis bi‐factor models to calibrate the AIBL battery with other studies. We used those calibrations to obtain co‐calibrated scores for all AIBL participants at every study visit. Here we show descriptive statistics for baseline visits, separately by diagnosis (normal cognition, mild cognitive impairment (MCI), dementia) for two enrollment waves for AIBL as well as for each phase of ADNI and across the Uniform Data Set (UDS) 1 & 2 (UDS1/2) and UDS3 time periods for NACC. Results: Box plots for memory, executive functioning, language, and visuospatial for people with normal cognition are in Figure 1, MCI in Figure 2, and dementia in Figure 3. These figures show there is substantial cognitive variation across waves within these disease stage groups and across studies. Conclusion: Co‐calibrated neuropsychological domain scores provide a common metric for integrating cognitive data across studies. Co‐calibrated scores aggregated across large prospective AD studies such as AIBL, ADNI, and NACC provide a foundation for large‐scale models of the development of AD and can serve as phenotypes for genetics studies. Co‐calibrated scores are available from AIBL, ADNI, and from NACC. [ABSTRACT FROM AUTHOR]

Background: Animal studies have consistently shown that physical activity reduces brain levels of beta‐amyloid (Aβ). However, human studies of physical activity and Alzheimer's disease (AD)‐related brain biomarkers have produced somewhat inconsistent findings. To date, most human studies examining physical activity and Aβ have utilised cross‐sectional analyses and relatively small sample sizes. As brain Aβ is detectable decades prior to the onset of clinical symptoms, examination using longitudinal brain imaging is vital to provide insight into how ongoing physical activity levels impact the progression of AD. In addition, the causal direction of these relationships requires further investigation; some research suggests physical activity levels may decline prior to dementia diagnosis. Method: Habitual physical activity and Aβ measures were collected over 15 years from 731 cognitively normal older adults (60 years and over) participating in the Australian Imaging, Biomarkers and Lifestyle Study of Ageing. Physical activity was assessed via the self‐reported International Physical Activity Questionnaire and brain Aβ measures obtained via PET imaging. Regression modelling examined the cross‐sectional and longitudinal relationships between physical activity and brain Aβ. Moderation analyses examined the impact of apolipoprotein (APOE) ε4 carriage on the physical activity‐Aβ relationship. To further examine the causal nature of this relationship, the trajectory of physical activity levels for individuals as a predictor of either high or low Aβ brain load was also examined. Result: Physical activity was not associated with brain Aβ at baseline (β = ‐0.001, p = 0.131) or over time (β = ‐0.101, p = 0.571). APOE ε4 status did not moderate the relationship between physical activity and brain Aβ over time (β = 0.04, p = 0.917). Brain Aβ levels were not associated with physical activity trajectory (β = ‐54.26, p = 0.590). Conclusion: Our study did not identify a relationship between habitual physical activity and brain Aβ levels. Future longitudinal studies should examine middle‐aged participants to assess whether physical activity influences Aβ accumulation earlier in life. [ABSTRACT FROM AUTHOR]

Background: The NHMRC‐funded Promoting Independence Through quality Care at Home (PITCH) project aimed to improve outcomes for people living with dementia and their paid and family carers via an evidence‐based dementia specialist training program for home care workers (HCWs). PITCH training was co‐designed with HCWs, family carers and people with dementia, consisting of 2×3.5 hour sessions, delivered face to face (F2F) or on‐line. Methods: Stepped‐wedge cluster RCT including 18 home care services in rural and urban VIC, NSW, and SA cluster‐randomised into one of two arms. Data collection from 18 July 2019 to 12 May 2022. Analyses included linear mixed models with intention to treat. Results: N = 213 HCWs completed baseline measures, N = 144 completed 6‐month follow‐ups, and N = 120 completed 12‐month follow‐ups. 172 HCWs completed the training program. N = 148 (86%) completed all training sessions; N = 81 F2F and 67 online. Primary outcome measure: HCWs' Sense of Competency in Dementia Care Staff (SCIDS) was higher after training (p = 0.04). This was driven by F2F training: SCIDS for HCWs completing F2F training was higher vs no training (p = 0.003) and online training (p = 0.015). There was no difference between online training and no training (control condition). Secondary outcome measures: Overall, HCW scores on the Dementia Attitudes Scale (DAS) showed no difference between training and no training. However, F2F training was associated with higher DAS compared to no training (p = 0.05) and online training (p = 0.05). Training improved scores on the Dementia Knowledge Assessment Scale (DKAS, p = 0.03). This was also driven by F2F training (F2F vs no training p = 0.024; F2F vs online p = 0.026). There was no difference between online training and no training for DAS and DKAS. Training had no effect on Strain in Dementia Care Scale (SDCS) scores. Discussion/Conclusion: Receiving F2F PITCH training improved dementia attitudes, dementia knowledge, and sense of competence in delivering dementia care for HCWs versus no training and online training. The HCW workforce has unique challenges to accessing and completing training and education to deliver evidence‐based dementia care. Minimising these challenges is critical to the delivery of quality home care. PITCH training now has evidence for its efficacy but only when delivered face‐to‐face. [ABSTRACT FROM AUTHOR]

Background: Early detection of brain‐related disorders is key to prevention of Alzheimer's disease (AD), and research on Hispanic populations is severely lacking. Obstacles to recruitment include the lack of trust in research and researchers and requirements for English proficiency, which excludes many potential Hispanic participants. Methods: Researchers from El Faro Health and Therapeutics in Starr County, Texas and the Framingham Heart Study are teaming up on a digital phenotyping study and incorporating "trust" as a central theme for recruitment/retention of Hispanic participants. Study materials are in both English and Spanish. The smartphone tasks are presented in two formats: "in‐clinic" using an iPad and "remote" utilizing participants' smartphones. Activities include voice tasks, gait and balance, and game‐like cognitive tasks. Longitudinal data will be collected every three months for one year. Participants: Recruitment is for anyone aged 18+ in Starr County, which is approximately 98% Hispanic. To maximize inclusivity, there are no other inclusion/exclusion criteria. Study procedures are customized to accommodate individuals. Recruitment goal is 500 participants within one year, with planned expansion to 5,000+ over 5 years. Results: Recruitment approach includes several components: (1) El Faro investigators have been providing clinical services to community members for decades, and are respected and trusted members of the community. (2) All participant‐facing study materials are available in both English and Spanish, with most translated into the specific local dialect. (3) Community fliers include text in both English and Spanish. (4) Social media outreach has sparked a great deal of interest for participating in research, and the team attends community events to further spread the word. (5) Multi‐generational families are encouraged given family decision‐making culture; (6) Word‐of‐mouth within the Starr County community is expected to be an important contributor to recruitment. Conclusions: Although data collection will begin in February 2023, already more than 150 participants have expressed interest in being involved. Leveraging resources to enable highly respected and trusted local researchers to conduct the research, and using participant‐centric design approaches will result in greater success in recruitment and retention of this underrepresented population. [ABSTRACT FROM AUTHOR]

Background: Mid‐life obesity is linked with increased risk for late‐life dementia, however relationships between later‐life body composition and dementia are less clear. Method: Using a combined cohort from two major observational studies (AIBL and ADNI) and categorising Body Mass Index (BMI) according to WHO criteria, we computed multivariable linear mixed‐effects models to determine association between BMI category and outcomes: brain beta‐amyloid PET quantification (centiloid); MRI (global, hippocampal and white matter hyperintensity volume); and cognition (PACC [preclinical Alzheimer cognitive composite], composite scores for attention, executive function and episodic memory). All models were adjusted by covariables age, gender, education, APOE ε4, and study (AIBL/ADNI). Results: The cohort included 4,668 observations from 2,828 individuals (49.4% male, mean age 73.8 years, 38.2% APOE ε4 carriage, 61.8% normal cognition [NC], 25.6% Mild Cognitive Impairment [MCI], 12.6% dementia due to Alzheimer's disease). The average BMI was 26.8 kg/m2 (0.6% underweight, 37.7% normal‐range, 41.7% overweight, 20.0% obese [BMI <18, 18‐25, 25‐30 and >30 kg/m2, respectively]). Relative to normal‐range BMI, those with overweight‐or‐obese range BMI had a significant negative association with PET centiloid level, beta = ‐0.150 (0.037 se) and ‐0.309 (0.042), respectively (i.e. greater BMI had lower amyloid level). This remained significant for obese‐range BMI in fully‐adjusted models when restricted to only NC participants. Also, obesity was associated with greater hippocampal volume, beta = 0.192 (0.046), but this was not significant when restricted to NC only. Associations with total grey matter/cortical volume and white matter hyperintensities were not significant. Obese‐range BMI was associated with stronger performance on attention and episodic memory composites, but not for PACC and executive function. For NC‐only, there was only significant negative association between obesity and attention performance. In multivariate analyses, neither obesity category nor BMI were associated with longitudinal change in cognitive scores. Conclusion: Presence of obesity in later life was associated with lower brain amyloid levels and less hippocampal atrophy in a mixed cohort including older adults with dementia, mild cognitive impairment and normal cognition. While mid‐life obesity is associated greater risk for AD, later life associations appear influenced by weight loss with emerging dementia. [ABSTRACT FROM AUTHOR]

Background: It has been proposed that tau deposition in the mesial temporal lobe (MTL) is an age‐related occurrence. We investigated the effects of high mesial temporal tau on age, cognition and neocortical tau in Aβ‐ cognitively unimpaired individuals (CU). Method: 187 Aβ‐ cognitively unimpaired older adults (≥60 years) from the AIBL cohort were included in this study. MK‐6240 retention was assessed in the amygdala, hippocampus, parahippocampus and entorhinal cortex and in a composite mesial temporal (Me) region. We assessed the association between regional and neocortical retention, age and cognition (MMSE, composite memory scores (CMS), composite non‐memory scores (CNMS) and the AIBL preclinical Alzheimer cognitive composite (AIBL‐PACC)). Two thresholds were used to stratify the cohort into two groups according to Me tau SUVR: 1) using the 95th percentile of the cohort; and 2) using two standard deviations (SD) above the mean. Results: MK‐6240 Me retention was correlated with age (rs = 0.19, p = 0.01). Those with higher Me retention also had higher retention in all other neocortical regions, as well as higher retention in all four Me sub‐regions. Using the 95th percentile cut‐point, those with higher Me retention performed significantly worse on the CMS (t = 1.89, p = 0.03, Cohen's d = 0.66) and the CNMS (t = ‐1.90, p=0.03, d = 0.69), which remained significant for the CMS after correction for age. There was a trend toward significance on the MMSE (t =‐1.40, p = 0.08, d =0.43) and PACC (‐1.37, p= 0.09, d = 0.47). These findings should be interpreted with caution, given the small sample of participants above the cut‐off (n =10). When stratified using the 2 SD cut‐point, the resulting sample size of the higher retention group was too small (n =5) to be reliably interpreted. Conclusion: These findings demonstrate an association between mesial temporal tau with age and neocortical tau deposition. The relationship to cognition should be further validated in a larger cohort. [ABSTRACT FROM AUTHOR]

Background: Physical inactivity is one of the greatest modifiable risk factors for dementia and research shows physical activity can delay cognitive decline in older adults. However, much of this research has used subjective physical activity data and a single follow‐up cognitive assessment. Further studies using objectively measured physical activity and comprehensive cognitive data measured at multiple timepoints are required. Methods: Participants were 199 community‐dwelling cognitively normal older adults (68.7 5.9 years) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Actigraphy was used to measure physical activity at baseline, yielding measures of intensity (peak counts), total activity (total counts) and energy expenditure (kilocalories; k/cal). Cognitive function was assessed using a cognitive battery administered every 18‐months from baseline (3‐11 years follow‐up), yielding composite scores for episodic memory, executive function, attention and processing speed, and global cognition. Results: Higher baseline energy expenditure predicted improvements in episodic memory and maintained global cognition over time (β = 0.011, SE = 0.005, p = 0.031; β = 0.009, SE = 0.004, p = 0.047, respectively). Both physical activity intensity and total activity predicted global cognition, such that those with higher peak and total counts had better cognition over time (β = 0.012, SE = 0.004, p = 0.005; β = 0.012, SE = 0.004, p = 0.005, respectively). Finally, higher total activity predicted improved episodic memory over time (β = 0.011, SE = 0.005, p =.022). Conclusion: These results suggest that physical activity is associated with preserved cognitive function over time, and that activity intensity may play an important role. This research further highlights the importance of early intervention to prevent cognitive decline and may aid in informing lifestyle interventions for dementia prevention. [ABSTRACT FROM AUTHOR]

Background: Reactive astrogliosis is an early event along the Alzheimer's disease (AD) continuum. We have shown that plasma glial fibrillary acidic protein (GFAP), reflecting reactive astrogliosis, is elevated in cognitively unimpaired individuals with preclinical AD (Chatterjee et al., 2021). We reported similar findings using 18F‐SMBT‐1, a PET tracer for monoamine oxidase B (MAO‐B) (Villemagne et al., 2022). To provide further evidence of their relationship with reactive astrogliosis we investigated the association between GFAP and 18F‐SMBT‐1 in the same participants. Method: Plasma GFAP, Aβ42 and Aβ40 levels were measured using the Single Molecule Array platform in 71 participants comprising 54 healthy controls (12 Aβ+ and 42 Aβ‐), 11 MCI(3 Aβ+ and 8 Aβ‐) and 6 probable AD(5 Aβ+ and 1 Aβ‐) patients from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing cohort. These participants also underwent 18F‐SMBT‐1 and Aβ PET imaging. Aβ imaging results were expressed in Centiloids (CL; ≥20 CL classified as Aβ+). 18F‐SMBT‐1 Standard Uptake Value Ratio (SUVR) were generated using the subcortical white matter as reference region. Linear regression analyses were carried out using plasma GFAP levels as the dependent variable and regional 18F‐SMBT‐1 SUVR as the independent variable, before and after adjusting for age, sex, soluble Aβ (plasma Aβ1‐42/Aβ1‐40 ratio) and insoluble Aβ (Aβ PET). Result: Plasma GFAP was significantly associated with 18F‐SMBT‐1 SUVR in brain regions of early Aβ deposition, such as the supramarginal gyrus (SG, β=.361, p=.002), posterior cingulate (PC, β=.308, p=.009), lateral temporal (LT, β=.299, p=.011), lateral occipital (LO, β=.313, p=.008) before adjusting for any covariates. After adjusting for covariates age, sex and soluble Aβ, GFAP was significantly associated with 18F‐SMBT‐1 PET signal in the SG (β=.333, p<.001), PC (β=.278, p=.005), LT (β=.256, p=.009), LO (β=.296, p=.004) and superior parietal (SP, β=.243, p=.016). On adjusting for age, sex and insoluble Aβ, GFAP was significantly associated with SMBT‐1 PET in the SG (β=.211, p=.037) however only a trend towards significance was observed in the PC (β=.186, p=.052) and LT (β=.171, p=.067) (Figure 1). Conclusion: There is an association between plasma GFAP and regional SMBT‐1 PET that is primarily driven by brain Aβ load. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is characterized pathologically by deposition of misfolded amyloid‐b and tau proteins. However, protein‐directed therapeutic strategies have shown limited clinical benefit, pointing to the need to examine pathogenesis from a broader lens. Neurons each harbor somatic single nucleotide variants (sSNV) in their genomes, which increase with age, at a rate of ∼15 sSNV per year. In AD, DNA damage is increased, with potentially significant effects on the genome of each cell. Method: We performed single‐cell whole‐genome sequencing on neurons from postmortem brain tissue from humans with AD and age‐matched controls, using two independent genome amplification methods (MDA and PTA), and analyzed the burden of somatic mutations. We also performed mutational signature analysis of the nucleotide changes and trinucleotide context to assess for mutagenic patterns. Result: We found significantly increased sSNV in AD, with each neuron carrying hundreds of additional somatic mutations, with a distinct mutation pattern. AD neurons show an increase in Signature C, which contains distinct nucleotide changes including C>A variants. We found elevated 8‐Oxoguanine DNA lesions, evidence that these mutations may result from oxidative damage to DNA. Mutations also show a mechanistic role for gene transcription in the generation of sSNV. Somatic mutations are predicted to produce deleterious effects on the neuron, including gene inactivation and neoantigen‐stimulated immune attack. Conclusion: Somatic mutations accumulate abundantly in Alzheimer's disease, distributed across the genome. Our findings implicate multiple mutagenic forces in sSNV generation in AD, illuminating multiple upstream components of disease pathogenesis including DNA oxidation and transcription‐coupled DNA repair. Furthermore, elevated somatic mutation levels appear to produce a toxic cellular state, positioning neurons for dysfunction and death. These findings therefore identify somatic mutation accumulation as a novel process in neurodegeneration, through which we can dissect the cascade of events in Alzheimer's disease pathogenesis. [ABSTRACT FROM AUTHOR]