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ObjectiveTo determine the relationship between sleep quality and CSF markers of Alzheimer disease (AD) pathology in late midlife.MethodsWe investigated the relationship between sleep quality and CSF AD biomarkers in a cohort enriched for parental history of sporadic AD, the Wisconsin Registry for Alzheimer's Prevention. A total of 101 participants (mean age 62.9 ± 6.2 years, 65.3% female) completed sleep assessments and CSF collection and were cognitively normal. Sleep quality was measured with the Medical Outcomes Study Sleep Scale. CSF was assayed for biomarkers of amyloid metabolism and plaques (β-amyloid 42 [Aβ42]), tau pathology (phosphorylated tau [p-tau] 181), neuronal/axonal degeneration (total tau [t-tau], neurofilament light [NFL]), neuroinflammation/astroglial activation (monocyte chemoattractant protein-1 [MCP-1], chitinase-3-like protein 1 [YKL-40]), and synaptic dysfunction/degeneration (neurogranin). To adjust for individual differences in total amyloid production, Aβ42 was expressed relative to Aβ40. To assess cumulative pathology, CSF biomarkers were expressed in ratio to Aβ42. Relationships among sleep scores and CSF biomarkers were assessed with multiple regression, controlling for age, sex, time between sleep and CSF measurements, and CSF assay batch.ResultsWorse subjective sleep quality, more sleep problems, and daytime somnolence were associated with greater AD pathology, indicated by lower CSF Aβ42/Aβ40 and higher t-tau/Aβ42, p-tau/Aβ42, MCP-1/Aβ42, and YKL-40/Aβ42. There were no significant associations between sleep and NFL or neurogranin.ConclusionsSelf-report of poor sleep was associated with greater AD-related pathology in cognitively healthy adults at risk for AD. Effective strategies exist for improving sleep; therefore sleep health may be a tractable target for early intervention to attenuate AD pathogenesis.

Midlife may be an ideal window for intervention in Alzheimer's disease (AD). To determine whether sleep is associated with early signs of AD neuropathology (amyloid deposition) in late midlife, we imaged brain amyloid deposits using positron emission tomography with [C-11]Pittsburgh Compound B (PiB), and assessed sleep with the Epworth Sleepiness Scale and the Medical Outcomes Study Sleep Scale in 98 cognitively healthy adults (aged 62.4 ± 5.7 years) from the Wisconsin Registry for Alzheimer's Prevention. We used multiple regressions to test the extent to which sleep scores predicted regional amyloid burden. Participants reporting less adequate sleep, more sleep problems, and greater somnolence on the Medical Outcomes Study had greater amyloid burden in AD-sensitive brain regions (angular gyrus, frontal medial orbital cortex, cingulate gyrus, and precuneus). Amyloid was not associated with reported sleep amount, symptoms of sleep-disordered breathing, trouble falling asleep, or Epworth Sleepiness Scale. Poor sleep may be a risk factor for AD and a potential early marker of AD or target for preventative interventions in midlife.

(1) Smoking is the most significant preventable health hazard in the modern world. It increases the risk of vascular problems, which are also risk factors for dementia. In addition, toxins in cigarettes increase oxidative stress and inflammation, which have both been linked to the development of Alzheimer's disease and related dementias (ADRD). This study identified potential mechanisms of the smoking–cognitive function relationship using metabolomics data from the longitudinal Wisconsin Registry for Alzheimer's Prevention (WRAP). (2) 1266 WRAP participants were included to assess the association between smoking status and four cognitive composite scores. Next, untargeted metabolomic data were used to assess the relationships between smoking and metabolites. Metabolites significantly associated with smoking were then tested for association with cognitive composite scores. Total effect models and mediation models were used to explore the role of metabolites in smoking-cognitive function pathways. (3) Plasma N-acetylneuraminate was associated with smoking status Preclinical Alzheimer Cognitive Composite 3 (PACC3) and Immediate Learning (IMM). N-acetylneuraminate mediated 12% of the smoking-PACC3 relationship and 13% of the smoking-IMM relationship. (4) These findings provide links between previous studies that can enhance our understanding of potential biological pathways between smoking and cognitive function. [ABSTRACT FROM AUTHOR]

Background: Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan. Objective: In this study, we leveraged longitudinal data from the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways. Methods: PRS and p-PRSs with and without APOE were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers in a subset. Replication analyses were performed in an independent sample. Results: We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of PRS/p-PRSs on rate of change in cognition, amyloid-β, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded. Conclusion: In addition to APOE, the p-PRSs can predict age-dependent changes in amyloid-β, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating amyloid-β and tau, long before the onset of clinical symptoms. [ABSTRACT FROM AUTHOR]

Alzheimer's disease biomarkers are becoming increasingly important for characterizing the longitudinal course of disease, predicting the timing of clinical and cognitive symptoms, and for recruitment and treatment monitoring in clinical trials. In this work, we develop and evaluate three methods for modelling the longitudinal course of amyloid accumulation in three cohorts using amyloid PET imaging. We then use these novel approaches to investigate factors that influence the timing of amyloid onset and the timing from amyloid onset to impairment onset in the Alzheimer's disease continuum. Data were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Baltimore Longitudinal Study of Aging (BLSA) and the Wisconsin Registry for Alzheimer's Prevention (WRAP). Amyloid PET was used to assess global amyloid burden. Three methods were evaluated for modelling amyloid accumulation using 10-fold cross-validation and holdout validation where applicable. Estimated amyloid onset age was compared across all three modelling methods and cohorts. Cox regression and accelerated failure time models were used to investigate whether sex, apolipoprotein E genotype and e4 carriage were associated with amyloid onset age in all cohorts. Cox regression was used to investigate whether apolipoprotein E (e4 carriage and e3e3, e3e4, e4e4 genotypes), sex or age of amyloid onset were associated with the time from amyloid onset to impairment onset (global clinical dementia rating ≥1) in a subset of 595 ADNI participants that were not impaired before amyloid onset. Model prediction and estimated amyloid onset age were similar across all three amyloid modelling methods. Sex and apolipoprotein E e4 carriage were not associated with PET-measured amyloid accumulation rates. Apolipoprotein E genotype and e4 carriage, but not sex, were associated with amyloid onset age such that e4 carriers became amyloid positive at an earlier age compared to non-carriers, and greater e4 dosage was associated with an earlier amyloid onset age. In the ADNI, e4 carriage, being female and a later amyloid onset age were all associated with a shorter time from amyloid onset to impairment onset. The risk of impairment onset due to age of amyloid onset was non-linear and accelerated for amyloid onset age >65. These findings demonstrate the feasibility of modelling longitudinal amyloid accumulation to enable individualized estimates of amyloid onset age from amyloid PET imaging. These estimates provide a more direct way to investigate the role of amyloid and other factors that influence the timing of clinical impairment in Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Background. The psychosocial effects on parents of infants with abnormal results in cystic fibrosis (CF) newborn screening (NBS) that uses genetic testing remain unclear. Methods. Twenty-eight individuals representing 14 families participated in grounded theory interviews ~6 months after their child's positive NBS results for CF. Participants also completed the Center for Epidemiologic Studies Depression Scales (CES-D) at their infant's sweat-test appointment (n = 51) and/or ~6 months after the sweat test (n = 35). Results. Most parents experienced high levels of emotional distress during their wait for the sweat-test appointment (CES-D score, mean [+ or -] SD: 16.5 [+ or -] 6.7; 43.1% in the clinical range; median wait: 7 days; range: 3-35 days). CES-D scores of these parents were also significantly higher than those of comparison parents. Interviews showed that parental cognitive uncertainty and emotional distress were influenced by the parents' prior knowledge of NBS, CF, and their carrier status; parents' adjustment to their new baby; and the physicians' approach to informing parents. Parents' coping strategies involved requesting a sweat test as soon as possible, searching for information, assessing the infant's risk/ health, seeking support, praying, or not talking with others. Conclusions. The waiting period from notification regarding positive NBS results to diagnostic test results can be psychologically distressing to parents, causing depressive symptoms that vary depending on their perceptions about the likelihood that their infant has CF. Implications for future research examining psychosocial interventions for NBS are discussed. Pediatrics 2005;115:1692-1703; cystic fibrosis, newborn screening, psychosocial risk. ABBREVIATIONS. CES-D, Center for Epidemiological Studies Depression Scales; CF, cystic fibrosis; CFTR, cystic fibrosis transmembrane conductance regulator; NBS, newborn screening., Since the inception of screening programs in the 1960s, there have been reports of adverse psychosocial events associated with the initial implementation of screening. Negative consequences have been attributed generally [...]

Objective. Patients who have cystic fibrosis (CF) and experience delayed diagnosis by traditional methods have greater nutritional insult compared with peers diagnosed via neonatal screening. The objective of this study was to evaluate cognitive function in children with CF and the influence of both early diagnosis through neonatal screening and the potential effect of early malnutrition. Methods. Cognitive assessment data were obtained for 89 CF patients (aged 7.3-17 years) during routine clinic visits. Patients had been enrolled in either the screened (N = 42) or traditional diagnosis (control) group (N = 47) of the Wisconsin CF Neonatal Screening Project. The Test of Cognitive Skills, Second Edition was administered to generate the Cognitive Skills Index (CSI) and cognitive factor scores (Verbal, Nonverbal, and Memory). Results. Cognitive scores in the overall study population were similar to normative data (CSI mean [standard deviation]: 102.5 [16.6]; 95% confidence interval: 99.1-105.9). The mean (standard deviation) CSI scores for the screened and control groups were 104.4 (14.4) and 99.8 (18.5), respectively. Significantly lower cognitive scores correlated with indicators of malnutrition and unfavorable family factors such as single parents, lower socioeconomic status, and less parental education. Our analyses revealed lower cognitive scores in patients with low plasma [alpha]-tocopherol ([alpha]-T) levels at diagnosis. In addition, patients in the control group who also had vitamin E deficiency at diagnosis ([alpha]-T < 300 [micro]g/dl) showed significantly lower CSI scores in comparison with [alpha]-T sufficient control subjects and both deficient and sufficient [alpha]-T subsets of screened patients. Conclusion. Results suggest that prevention of prolonged malnutrition by early diagnosis and nutritional therapy, particularly minimizing the duration of vitamin E deficiency, is associated with better cognitive functioning in children with CF. Pediatrics 2004;113:1549-1558; cognitive function; cystic fibrosis; malnutrition; neonatal screening; vitamin E deficiency., ABBREVIATIONS. CF, cystic fibrosis; SES, socioeconomic status; [alpha]-T, [alpha]-tocopherol; TCS/2, Test of Cognitive Skills, Second Edition; CSI, Cognitive Skills Index; MI, meconium ileus; PS, pancreatic sufficient; PI, pancreatic insufficient. It [...]

Introduction: While it is generally appreciated that amyloid precedes symptomatic Alzheimer's disease (AD) by decades, a greater understanding of this timeline may increase prognostic accuracy, planning, and care of persons who are on the AD continuum. Methods: We examined trajectories of Clinical Dementia Rating–Sum of Boxes (CDR‐SB) relative to estimated years of amyloid positivity (A+) in n = 123 participants who were all A+ based on [C‐11]Pittsburgh compound B positron emission tomography. Results: The average amyloid chronicity at CDR‐SB of 2.5 was 20.1 years. The average trajectory of CDR‐SB accelerated after 10 years of elevated amyloid and varied greatly between 10 and 30 years. Exploratory analyses suggested that older age and higher volume of white matter hyperintensities shortened the interval between amyloid onset and cognitive impairment. Discussion: The recontextualization of amyloid burden into the time domain will facilitate studies of disease progression, the influence of co‐pathology, and factors that hasten or slow cognitive impairment. [ABSTRACT FROM AUTHOR]

Introduction: Modifiable health and lifestyle factors increase risk of dementia, but whether modifiable factors, when measured in late‐midlife, impact the emergence or progression of Alzheimer's disease (AD) pathophysiologic or cognitive changes remains unresolved. Methods: In initially cognitively unimpaired, late middle‐aged participants (N = 1215; baseline age, M [standard deviation] = 59.3 [6.7] years) from the Wisconsin Registry for Alzheimer's Prevention (WRAP), we investigated the influence of the Lifestyle for Brain Health (LIBRA) index, a lifestyle‐based dementia risk score, on AD‐related cognitive trajectories and amyloid beta (Aβ) plaque accumulation. Results: Overall, lower baseline LIBRA, denoting healthier lifestyle and lower dementia risk, was related to better overall cognitive performance, but did not moderate apolipoprotein E ε4 or Aβ‐related longitudinal cognitive trajectories. LIBRA was not significantly associated with Aβ accumulation or estimated age of Aβ onset. Discussion: In WRAP, late‐midlife LIBRA scores were related to overall cognitive performance, but not AD‐related cognitive decline or Aβ accumulation in the preclinical timeframe. Highlights: The Lifestyle for Brain Health (LIBRA) index was associated with cognitive performance in late‐midlife.LIBRA did not moderate apolipoprotein E ε4 or amyloid‐related cognitive decline.LIBRA was not associated with the onset or accumulation of amyloid plaques. [ABSTRACT FROM AUTHOR]

Background: Insulin resistance (IR) and hyperglycemia have been linked to increased dementia risk. In some animal studies IR and hyperglycemia have been associated with tau hyperphosphorylation. In a sample of predominantly healthy middle‐aged and older adults, we examined whether higher IR and fasting glucose were related to increased odds of tau PET positivity assessed using [F‐18]MK‐6240 positron emission tomography (PET). We also explored whether relationships to tau PET positivity were moderated by global amyloid pathology measured using [C‐11]PiB PET. Method: Participants were enrolled in the Wisconsin Registry for Alzheimer's Prevention (WRAP) and the Wisconsin Alzheimer's Disease Research Center (ADRC) Clinical Core (Table 1). In the IR study, n=231 WRAP participants had homeostatic model assessment of insulin resistance (HOMA2‐IR) and PET. Twenty‐eight (12.1%) were tau PET positive (entorhinal MK‐6240 SUVR > 1.27; Betthauser et al., 2020) and 59 (25.5%) were amyloid PET positive (global PiB DVR > 1.19; Racine et al., 2016). In the Glucose study, n=332 participants (n=239 WRAP; n=93 Wisconsin‐ADRC) had fasting glucose and PET. Forty‐nine (14.8%) exhibited tau PET positivity and 81 (24.4%) were amyloid PET positive. Binary logistic regression tested whether HOMA2‐IR and glucose were related to odds of tau PET positivity. Global PiB DVR was explored as a moderator of HOMA2‐IR and glucose in separate logistic regressions. Result: HOMA2‐IR and glucose were not significantly related to odds of tau PET positivity (ps >.37), controlling for age, sex and global PiB DVR (Figure 1). Higher global PiB DVR (standardized using cut‐point to center) was significantly related to greater odds of tau PET positivity [IR study: Exp(2.8), p <.001, 95%CI: 1.9‐4.1; Glucose study: Exp(3.1), p <.001, 95%CI: 2.3‐4.4]. Global PiB DVR was not a significant moderator of insulin or glucose (ps >.81; Figure 2). Conclusion: HOMA2‐IR and glucose may not be related to tau pathology in cognitively unimpaired adults. The low proportion of participants who were tau PET positive likely limited the detection of significant interaction effects. Additional research is needed in samples with a greater proportion of diabetic and cognitively impaired participants to determine potential pathways linking IR and glucose to dementia. [ABSTRACT FROM AUTHOR]

Background: Studies of anticholinergic (AC) medications (drugs that block acetylcholine neurotransmitter action) have shown associations between the AC medications use, cognitive impairment, and increased dementia risk. Associations between AC medication and AD biomarkers among cognitively normal late middle‐aged adults are unclear. This study examined associations between AC use, cognition, physical health, and amyloid PET measures. Methods: Wisconsin Registry for Alzheimer's Prevention (WRAP) participants with >=3 cognitive composite scores, free of dementia at baseline cognition (n=1262) were included in analyses of cognitive and general health measures; PET amyloid measures were examined in a subset with Pittsburgh Compound B PET imaging (PiB; n=299). Participants were classified as either taking or not taking at least one AC medication at baseline (AC+, n=437; AC‐, n=825; Table 1). Cross‐sectional analysis of baseline associations examined AC+/AC‐ differences in AD‐related cognitive composites (e.g., memory, PACC) and health markers (e.g., depression, comorbidities). Linear mixed‐effects models (LME) examined whether AC modified age‐related cognitive trajectories in APOE ε4 carriers or non‐carriers and PiB positive or negative group. Sensitivity analyses repeated models only in the high AC+ (AC score > 1) group (n=191) relative to the AC‐ group. The statistical threshold for significance was set at P <.05. Results: Mean(sd) age for AC+ and AC‐ participants was 55.4(6.4) and 53.7(6.6). The AC+ group was significantly higher than the AC‐ group on depression scores, BMI, total medications, total comorbidities, and cardiovascular problems (Table 2). The AC groups did not differ on amyloid PET measures (Table 3). At baseline cognition, the AC+ group (n=437) showed lower executive function and PACC3 scores (Figure 1). Longitudinal analyses indicated that AC+ predicted a steeper decline slope in executive function and PACC3 with effects exacerbated in individuals with AD risk factors (Fig. 2‐3, respectively). The slopes of AC + group differed significantly after age 65. Conclusion: AC medication use was associated with faster cognitive decline, particularly among APOE4 carriers and those with PET‐based evidence of amyloid plaques, suggesting AC use may exacerbate AD‐related cognitive decline in the preclinical time frame. The results have implications for AC usage in older adults with AD risk or biomarker positivity. [ABSTRACT FROM AUTHOR]

Clinical assessments often use complex picture description tasks to elicit natural speech patterns and magnify changes occurring in brain regions implicated in Alzheimer's disease and dementia. As The Cookie Theft picture description task is used in the largest Alzheimer's disease and dementia cohort studies available, we aimed to create algorithms that could characterize the visual narrative path a participant takes in describing what is happening in this image. We proposed spatio-semantic graphs, models based on graph theory that transform the participants' narratives into graphs that retain semantic order and encode the visuospatial information between content units in the image. The resulting graphs differ between Cognitively Impaired and Unimpaired participants in several important ways. Cognitively Impaired participants consistently scored higher on features that are heavily associated with symptoms of cognitive decline, including repetition, evidence of short-term memory lapses, and generally disorganized narrative descriptions, while Cognitively Unimpaired participants produced more efficient narrative paths. These results provide evidence that spatio-semantic graph analysis of these tasks can generate important insights into a participant's cognitive performance that cannot be generated from semantic analysis alone. [ABSTRACT FROM AUTHOR]

Background: Previous studies suggest associations between self‐reported poor sleep and relevant health markers and AD‐related outcomes including cognition and AD pathology. It is important to understand how sleep, a modifiable risk factor, may be related to cognition and other measures of aging in late midlife when AD pathology may be accruing. The study objectives included examining whether sleep profiles were associated with concurrent health and cognition, and positron emission tomography (PET) measures of amyloid. Methods: Dementia‐free participants from the Wisconsin Registry for Alzheimer's Prevention (WRAP) who had completed sleep questionnaires were eligible (n=619); questionnaires included the Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), and Medical Outcomes Study Sleep Scale (MOS). K‐means clustering analysis identified three clusters. We compared concurrent health markers (e.g., depression and insulin resistance) and cognitive composite scores across the sleep profile clusters. In the subset with Pittsburgh Compound B (PiB; n=107) PET imaging, we also compared amyloid measures (estimated global PiB distribution volume ratio (DVR), PiB chronicity, and PiB(+) (DVR>=1.2) at sleep assessment. Significant omnibus tests (p<.05) were followed with pairwise comparisons. Results: Mean(sd) sample baseline age was 62.6(6.7). Cluster analysis identified 3 groups: Healthy Sleepers (HS, n=262(42.3%)), Intermediate Sleepers (IS, n=229(37.0%)), and Poor Sleepers (PS, n=128(20.7%); Fig. 1, Fig. 2, Table 1). All omnibus tests comparing demographics and health measures across sleep groups were significant except age, gender, and APOE e4 carriers; the PS group was worse than HS and/or IS on all other measures, including self‐reported depression, health, and memory complaints (Table 2). PS performed worse than HS and/or IS on measured body mass index, waist‐hip ratio and insulin resistance (Fig. 3a); and after adjusting for covariates, PS performed worse on all cognitive outcomes except working memory (Fig. 4). There were no differences between sleep groups on measures of amyloid (Fig. 3b). Conclusion: Sleep profiles were associated with differences in additional modifiable risk factors and concurrent cognition, but not amyloid. Further analysis was needed in the association between the sleep constructs and amyloid clearance/accumulation. Management of sleep and related factors may provide an opportunity for early intervention that could ultimately delay or prevent clinical impairment. [ABSTRACT FROM AUTHOR]

Background: Subjective memory complaints (SMC) in the absence of impaired performance on objective measures increases risk for dementia among some individuals. Connected Speech Language (CSL) is language produced in a continuous sequence as in conversations. Subtle, yet detectable, changes in CSL have been shown to predict cognitive decline, suggesting that changes in discourse are an early clinical symptom of dementia. Here we examined whether a baseline assessment of SMC was associated prospectively with longitudinal CSL age‐related trajectories. Method: N=1039 participants who completed SMC and CSL assessment were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of preclinical AD, in middle‐aged adults. SMC reflects the average rating (1‐7) across the Memory Functioning Questionnaire frequency of forgetting subscale. To ensure SMC did not reflect transient memory problems, participants were grouped into no self‐reported problems, persistent self‐reported problems, or inconsistent self‐reported problems (Figure 1) across time. Participants in the inconsistent group (n = 237) and those with fewer than three SMC assessments (n=54) were excluded from analyses. Participant's speech was recorded while describing the "Cookie Theft" picture from the Boston Diagnostic Aphasia Examination. CSL outcomes included content information units (CIU density), content units per minute (CIU minutes), types‐tokens ratio, and filled pauses. We tested the moderation of CSL age related trajectories by baseline SMC. Linear mixed models included a random intercept, gender, reading ability, and practice effects as fixed covariates. Result: Sample characteristics are shown in Table 1 by SMC group. The persistent problem group had fewer years of education and lower WRAT reading scores than the no problems group, but were otherwise comparable. Baseline SMC did not moderate age‐related changes in CIU density, types‐tokens ratio or filled pauses. Baseline SMC moderated changes in CIU Minutes at trend level (Table 2 and Figure 2). Greater memory complaints at baseline were associated with faster age‐related decline in the contents unit/minute compared to those with fewer complaints. Conclusion: SMC modestly, prospectively related to difficulties expressing ideas. Self‐reported may precede subtle cognitive changes. Future work will examine whether SMC predicts declines in standard cognitive tests of verbal ability. [ABSTRACT FROM AUTHOR]

Background: New methods have recently been developed to model longitudinal amyloid biomarkers in AD. This work compares three methods in three different cohorts, and investigates associations of APOE‐e4 status with amyloid onset age and amyloid accumulation rates. Method: Participants from ADNI (N=1213), BLSA (N=205) and WRAP (N=272) with available amyloid PET imaging and APOE genotype were included in the study (Table 1). Amyloid (A) burden was quantified using established methods (ADNI: BAI processed SUVR, WM reference region; BLSA: SRTM‐LRSC DVR, PVC, cerebellum GM reference region; WRAP: graphical analysis DVR, cerebellum GM reference region). Group‐based trajectory modeling (GBTM), ordinary differential equation‐Gaussian process (ODE‐GP) and sampled iterative local linear approximation (SILLA) methods were used to model longitudinal amyloid accumulation, estimate A+ onset age, and align amyloid values by years A+ for each cohort. Forward and backward SUVR/DVR prediction, estimated age of A+ onset, and associations of DVR/SUVR residuals with age, time from reference scan, and SUVR/DVR, were compared for each model and cohort. The impact of APOE genotype on A+ onset and amyloid PET accumulation trajectories was investigated using discrete rate sample, Kaplan‐Meier curves, and accelerated failure time models. Result: All methods produced similar amyloid vs. years A+ curves for each cohort (Figure 1) with most notable discrepancies occurring in the A‐ range. DVR/SUVR prediction performance was similar across methods and was better for retrospective vs. prospective prediction. Amyloid accumulation rates and trajectories were similar for APOE‐e4+ and APOE‐e4‐ genotypes (Figure 2). Kaplan‐Meier curves were different between the APOE groups (log‐rank test, p<0.005 for each test; Figure 3), with the e4+ group exhibiting earlier A+ onset ages compared to e4‐ (Table 2) for all methods and cohorts. Conclusion: This work demonstrates similar performance of three novel methods for modeling longitudinal amyloid PET burden and estimating individualized A+ onset age. Results suggest that APOE‐e4 status affects the A+ onset age, but not the rate of amyloid PET accumulation. Ongoing work is investigating potential differences in amyloid accumulation trajectories and A+ onset age between APOE genotypes (e.g. e3e3, e3e4, e4e4,...) and is investigating relationships between A+ onset, APOE genotype and onset of cognitive impairment. [ABSTRACT FROM AUTHOR]

Background: Asymmetric binding patterns in tau PET imaging are sometimes observed, but less is known about how this asymmetry might explain clinical phenotypes and AD variants, especially in a longitudinal context. Previous work has demonstrated that unilateral tau deposition in left frontal and temporal regions is common in logopenic progressive aphasia (lvPPA), an atypical AD variant. This work presents two descriptive case studies of participants with opposing laterality of [18F]MK‐6240, a PET radioligand for AD neurofibrillary tangles. Method: Two participants from the Wisconsin Registry for Alzheimer’s Prevention (WRAP), an ongoing, longitudinal cohort study of late middle‐aged adults enriched for AD risk, were identified based on unilateral MK‐6240 deposition. Topographic amyloid and tau burden was assessed with [11C]PiB and [18F]MK‐6240 PET imaging, respectively. Demographic data, cognitive diagnoses, health histories, and APOE status are described. Longitudinal neuropsychological assessments and digitally recorded connected speech samples were analyzed to create a descriptive profile of cognition and connected speech‐language (CSL). Cognitive test scores and language measures were then compared against the scores of the full WRAP sample, using a robust normative approach previously described by our group. Result: MK‐6240 tau‐PET imaging revealed right‐lateralized tau in Participant A and left‐lateralized tau in Participant B (Figure 1). Participants were identical on all demographics except age and APOE risk of developing AD (though both participants were ApoE‐4 allele carriers) (Table 1). Cognitive assessment Z‐scores (0=mean of demographically similar cognitively stable WRAP participants; Figs 2‐4) depict considerable between visit variability for Participant A on all measures, including language and CSL, with decline from baseline on all but letter fluency. Participant B showed isolated baseline deficits on memory tests (AVLT and story recall) at two standard deviations below the mean, which declined further across visits, whereas performances on Trails, naming, category fluency, and all measures of CSL remained stable and within normal expectations. Conclusion: In this case study, right>left tau PET signal was associated with greater decline in language, particularly connected speech and naming. Future work will examine associations between volumetric MRI and asymmetric regional tau deposition, as well as additional relationships to language and cognition. [ABSTRACT FROM AUTHOR]

Background: Quantifying the temporal progression of key pathophysiological events in Alzheimer's disease is crucial for staging disease, dementia risk assessment, and informing clinical trials. This work extends a novel algorithm (sampled iterative local linear approximation; SILLA) developed for modeling PET trajectories to: 1) generate a unified CSF and PET amyloid accumulation timeline, and 2) characterize the temporal progression of biomarker and cognitive changes in AD. Method: 941 participants from the Wisconsin Registry of Alzheimer's Prevention, Wisconsin Alzheimer's Disease Research Center, and Statins in Healthy, At‐Risk Adults: Impact on Amyloid and Regional Perfusion studies underwent [C‐11]PiB PET and/or lumbar puncture; and a subset underwent [F‐18]MK‐6240 PET and anatomical MRI using standardized protocols (Table 1). Amyloid burden was quantified from cortical PiB DVR and CSF Aβ42/40. Amyloid Time, quantified as years from CSF Aβ42/40 positivity, was estimated by simultaneously modeling Aβ42/40 and PiB DVR using an extension of the SILLA method in a subset of 248 participants with both measurements. CSF biomarkers measured using the exploratory Roche NeuroToolKit assays, imaging biomarkers, and cognitive impairment (global CDR, CDR SOB, and diagnosis) were plotted as a function of Amyloid Time. Time between key AD events was estimated using LOWESS curves and positivity thresholds for each AD biomarker and CDR scores. Result: Figure 1 depicts biomarker thresholds. Amyloid Time suggested PET Aβ+, CSF T+, PET T+, CDR=0.5, and CDR=1 occurred 4.0, 12.0, 13.8, 17.7, and 22.0 years following Aβ42/40 positivity (Figure 2, Table 2). Heterogeneity was observed in tau levels relative to Amyloid Time for individual cases. Those with worsening CDR generally had high amyloid and at least one T+ biomarker. Conclusion: Amyloid Time based on combined CSF and PET amyloid biomarkers and the SILLA algorithm provides a novel way to quantify the duration of amyloid exposure from the earliest pathophysiologic CSF changes to dementia onset in AD within individuals. This enables characterization of the time between key AD events, which could inform prognosis, identify intervention timing for novel therapies, and enable exploration of mechanisms related to resistance and/or resilience. [ABSTRACT FROM AUTHOR]

Background: This work examined heterogeneity in cognitive trajectories between amyloid(A) and tau(T) cerebrospinal fluid (CSF) stratified biomarker groups in late‐middle‐aged, initially cognitively unimpaired individuals. Additionally, candidate biomarkers of neurodegeneration were investigated for potential added value in predicting cognitive decline. Method: Individuals (N=535) recruited from Wisconsin Alzheimer's Disease Research Center (n=301) and Wisconsin Registry for Alzheimer's Prevention (n=234) underwent a lumbar puncture and serial (1 to 9) cognitive assessments (Table 1). CSF biomarkers were measured using the exploratory Roche NeuroToolKit assays (Roche Diagnostics International Ltd). Four biomarker groups (A‐T‐, A‐T+, A+T‐ and A+T+) were established based on combinations of CSF Aβ42/40 and p‐tau biomarker positivity, where (A) and (T) positivity was determined as CSF Aβ42/40≤0.046 and CSF p‐tau≥24.8 pg/mL. Decline on a Preclinical Alzheimer's Cognitive Composite (PACC‐3) was investigated using linear mixed effects models (including subject‐specific random intercepts and age‐related slopes) adjusting for sex, education, cohort, and the number of prior exposures to the cognitive battery. In primary analyses, the predictors of interest included the biomarker group and its interaction with age to investigate whether longitudinal PACC‐3 trajectories differed between biomarker groups. Secondary models added one of the following biomarkers for neurodegeneration and its interaction with age: neurofilament light chain (NfL), neurogranin, or alpha‐synuclein. Models were compared against the primary model using the Akaike information criterion and log likelihood ratio tests. Result: The results from the primary model indicated a significant biomarker group×time interaction (P<.001, Figure 2). Tukey‐adjusted pairwise comparisons indicated that the A+ groups (A+T‐ and A+T+) had significantly different PACC‐3 trajectories compared with the A‐T‐ group (P<.0001, Figure 2). Comparison of the simple age‐related slopes suggest that the A+T+ group was declining approximately 3.6 times faster compared with those without elevated biomarkers. Higher NfL, but not neurogranin or alpha‐synuclein, was associated with PACC‐3 decline after accounting for AT(+/‐) status (Table 2). Conclusion: In this preclinical sample, cognitive decline was evident in A+ groups. Secondary analyses suggest that NfL may contribute additional value to the AT(neurodegeneration) framework in explaining cognitive decline before the onset of dementia. [ABSTRACT FROM AUTHOR]