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Background: Sphingomyelin (SM) levels have been associated with Alzheimer’s disease (AD), but the association direction has been inconsistent and research on cerebrospinal fluid (CSF) SMs has been limited by sample size, breadth of SMs examined, and diversity of biomarkers available. Objective: Here, we seek to build on our understanding of the role of SM metabolites in AD by studying a broad range of CSF SMs and biomarkers of AD, neurodegeneration, and neuroinflammation. Methods: Leveraging two longitudinal AD cohorts with metabolome-wide CSF metabolomics data (n = 502), we analyzed the relationship between the levels of 12 CSF SMs, and AD diagnosis and biomarkers of pathology, neurodegeneration, and neuroinflammation using logistic, linear, and linear mixed effects models. Results: No SMs were significantly associated with AD diagnosis, mild cognitive impairment, or amyloid biomarkers. Phosphorylated tau, neurofilament light, α-synuclein, neurogranin, soluble triggering receptor expressed on myeloid cells 2, and chitinase-3-like-protein 1 were each significantly, positively associated with at least 5 of the SMs. Conclusion: The associations between SMs and biomarkers of neurodegeneration and neuroinflammation, but not biomarkers of amyloid or diagnosis of AD, point to SMs as potential biomarkers for neurodegeneration and neuroinflammation that may not be AD-specific.

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.

IMPORTANCE: Characterization of early tau deposition in individuals with preclinical Alzheimer disease (AD) is critical for prevention trials that aim to select individuals at risk for AD and halt the progression of disease. OBJECTIVE: To evaluate the prevalence of cortical tau positron emission tomography (PET) heterogeneity in a large cohort of clinically unimpaired older adults with elevated β-amyloid (A+). DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study examined prerandomized tau PET, amyloid PET, structural magnetic resonance imaging, demographic, and cognitive data from the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study from April 2014 to December 2017. Follow-up analyses used observational tau PET data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Harvard Aging Brain Study (HABS), and the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center (together hereinafter referred to as Wisconsin) to evaluate consistency. Participants were clinically unimpaired at the study visit closest to the tau PET scan and had available amyloid and tau PET data (A4 Study, n = 447; ADNI, n = 433; HABS, n = 190; and Wisconsin, n = 328). No participants who met eligibility criteria were excluded. Data were analyzed from May 11, 2021, to January 25, 2022. MAIN OUTCOMES AND MEASURES: Individuals with preclinical AD with heterogeneous cortical tau PET patterns (A+T cortical(+)) were identified by examining asymmetrical cortical tau signal and disproportionate cortical tau signal relative to medial temporal lobe (MTL) tau. Voxelwise tau patterns, amyloid, neurodegeneration, cognition, and demographic characteristics were examined. RESULTS: The 447 A4 participants (A+ group, 392; and normal β-amyloid group, 55), with a mean (SD) age of 71.8 (4.8) years, included 239 women (54%). A total of 36 individuals in the A+ group (9% of the A+ group) exhibited heterogeneous cortical tau patterns and were further categorized into 3 subtypes: asymmetrical left, precuneus dominant, and asymmetrical right. A total of 116 individuals in the A+ group (30% of the A+ group) showed elevated MTL tau (A+T MTL(+)). Individuals in the A+T cortical(+) group were younger than those in the A+T MTL(+) group (t(61.867) = –2.597; P = .03). Across the A+T cortical(+) and A+T MTL(+) groups, increased regional tau was associated with reduced hippocampal volume and MTL thickness but not with cortical thickness. Memory scores were comparable between the A+T cortical(+) and A+T MTL(+) groups, whereas executive functioning scores were lower for the A+T cortical(+) group than for the A+T MTL(+) group. The prevalence of the A+T cortical(+) group and tau patterns within the A+T cortical(+) group were consistent in ADNI, HABS, and Wisconsin. CONCLUSIONS AND RELEVANCE: This study suggests that early tau deposition may follow multiple trajectories during preclinical AD and may involve several cortical regions. Staging procedures, especially those based on neuropathology, that assume a uniform trajectory across individuals are insufficient for disease monitoring with tau imaging.

An accurate blood test for Alzheimer’s disease that is sensitive to preclinical proteinopathy and cognitive decline has clear implications for early detection and secondary prevention. We assessed the performance of plasma phosphorylated tau 217 (pTau217) against brain PET markers of amyloid [[11C]-labelled Pittsburgh compound B (PiB)] and tau ([18F]MK-6240) and its utility for predicting longitudinal cognition. Samples were analysed from a subset of participants with up to 8 years follow-up in the Wisconsin Registry for Alzheimer’s Prevention (WRAP; 2001–present; plasma 2011–present), a longitudinal cohort study of adults from midlife, enriched for parental history of Alzheimer’s disease. Participants were a convenience sample who volunteered for at least one PiB scan, had usable banked plasma and were cognitively unimpaired at first plasma collection. Study personnel who interacted with participants or samples were blind to amyloid status. We used mixed effects models and receiver–operator characteristic curves to assess concordance between plasma pTau217 and PET biomarkers of Alzheimer’s disease and mixed effects models to understand the ability of plasma pTau217 to predict longitudinal performance on WRAP’s preclinical Alzheimer’s cognitive composite (PACC-3). The primary analysis included 165 people (108 women; mean age = 62.9 ± 6.06; 160 still enrolled; 2 deceased; 3 discontinued). Plasma pTau217 was strongly related to PET-based estimates of concurrent brain amyloid (β^ = 0.83 (0.75, 0.90), P < 0.001). Concordance was high between plasma pTau217 and both amyloid PET (area under the curve = 0.91, specificity = 0.80, sensitivity = 0.85, positive predictive value = 0.58, negative predictive value = 0.94) and tau PET (area under the curve = 0.95, specificity = 1, sensitivity = 0.85, positive predictive value = 1, negative predictive value = 0.98). Higher baseline pTau217 levels were associated with worse cognitive trajectories (β^pTau×age = −0.07 (−0.09, −0.06), P < 0.001). In a convenience sample of unimpaired adults, plasma pTau217 levels correlate well with concurrent brain Alzheimer’s disease pathophysiology and with prospective cognitive performance. These data indicate that this marker can detect disease before clinical signs and thus may disambiguate presymptomatic Alzheimer’s disease from normal cognitive ageing.

Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer’s disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer’s disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer’s Prevention (n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests (P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [n = 262 (42.3%)], intermediate sleepers [n = 229 (37.0%)] and poor sleepers [n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist–hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment.

Age-related disease may be mediated by low levels of chronic inflammation (“inflammaging”). Recent work suggests that gut microbes may contribute to inflammation via degradation of the intestinal barrier. While aging and age-related diseases including Alzheimer’s disease (AD) are linked to altered microbiome composition and higher levels of gut microbial components in systemic circulation, the role of intestinal inflammation and permeability per se remains unclear. To test whether greater gut inflammation is associated with older age and AD pathology, we assessed fecal samples from older adults to measure calprotectin, an established marker of intestinal inflammation which is elevated in diseases of gut barrier integrity. Here we found that calprotectin levels are higher with age, and that higher calprotectin was associated with greater amyloid burden among participants with an amyloid-confirmed AD dementia diagnosis. Calprotectin was also associated with cerebrospinal fluid markers of AD pathology and axonal degeneration, as well as with lower verbal memory function among cognitively unimpaired participants. Together, these findings suggest that intestinal inflammation may play a role in pathology development, and that it may exacerbate the progression toward AD.SummaryIntestinal inflammation is correlated with older age, Alzheimer’s disease (AD) dementia, and greater amyloid burden in participants with AD.

Background and ObjectivesAn accurate blood test for Alzheimer’s disease (AD) that is sensitive to preclinical proteinopathy and cognitive decline has clear implications for early detection and secondary prevention of AD. We assessed the performance of plasma pTau against brain PET markers of amyloid ([11C]-PiB) and tau ([18F]MK-6240), and its utility for predicting longitudinal cognition.MethodsSamples were analyzed from a subset of participants with up to 8 years follow-up in the Wisconsin Registry for Alzheimer’s Prevention (WRAP; 2001-present; plasma 2011-present), a longitudinal cohort study of adults from midlife, enriched for parental history of AD. Participants were a convenience sample who volunteered for at least one PiB scan, had usable banked plasma, and were cognitively unimpaired at first plasma collection. Study personnel who interacted with participants or samples were blind to amyloid status. We used mixed effects models and receiver-operator characteristic curves to assess concordance between plasma pTau217 and PET biomarkers of AD, and mixed effects models to understand the ability of plasma pTau217 to predict longitudinal performance on WRAP’s preclinical Alzheimer’s cognitive composite (PACC-3).ResultsThe primary analysis included 165 people (108 women; mean age=62.9 ± 6.06; 160 still enrolled; 2 deceased; 3 discontinued). Plasma pTau217 was strongly related to PET-based estimates of concurrent brain amyloid (β̂DVR = 0.83 (0.75, 0.90), p217 and both amyloid PET (AUC=0.91, specificity=0.80, sensitivity=0.85, PPV=0.58, NPV=0.94, LR−=5.48) and tau PET (AUC=0.95, specificity=1, sensitivity=0.85, PPV=1, NPV=0.98, LR−=6.47). Higher baseline pTau217 levels were associated with worse cognitive trajectories (β̂pTau=age = -0.07 (-0.09, -0.06), pConclusions and RelevanceIn a convenience sample of unimpaired adults, plasma pTau217 levels correlate well with concurrent brain AD pathophysiology and with prospective cognitive performance. These data indicate that this marker can detect AD before clinical signs and thus may disambiguate presymptomatic AD from normal cognitive aging.Classification of EvidenceThis study meets Class III evidential criteria for diagnostic accuracy of plasma pTau217.

Introduction This study examines the utility of a multipanel of cerebrospinal fluid (CSF) biomarkers complementing Alzheimer's disease (AD) biomarkers in a clinical research sample. We compared biomarkers across groups defined by clinical diagnosis and pTau181 /Aβ42 status (+/-) and explored their value in predicting cognition. Methods CSF biomarkers amyloid beta (Aβ)42 , pTau181 , tTau, Aβ40 , neurogranin, neurofilament light (NfL), α-synuclein, glial fibrillary acidic protein (GFAP), chitinase-3-like protein 1 (YKL-40), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), S100 calcium binding protein B (S100B), and interleukin 6 (IL6), were measured with the NeuroToolKit (NTK) for 720 adults ages 40 to 93 years (mean age = 63.9 years, standard deviation [SD] = 9.0; 50 with dementia; 54 with mild cognitive impairment [MCI], 616 unimpaired). Results Neurodegeneration and glial activation biomarkers were elevated in pTau181 /Aβ42 + MCI/dementia participants relative to all pTau181 /Aβ42 - participants. Neurodegeneration biomarkers increased with clinical severity among pTau181 /Aβ42 + participants and predicted worse cognitive performance. Glial activation biomarkers were unrelated to cognitive performance. Discussion The NTK contains promising markers that improve the pathophysiological characterization of AD. Neurodegeneration biomarkers beyond tTau improved statistical prediction of cognition and disease stages.

Although diagnosing the syndrome of dementia is largely a clinical endeavor, neuroimaging plays an increasingly important role in accurately determining the underlying etiology, which extends beyond its traditional role in excluding other causes of altered cognition. New neuroimaging methods not only facilitate the diagnosis of the most common neurodegenerative conditions (particularly Alzheimer Disease [AD]) after symptom onset, but also show diagnostic promise even in the very early or presymptomatic phases of disease. Positron emission tomography (PET) is increasingly recognized as a key clinical tool for differentiating normal age-related changes in brain metabolism (using 18F-fluorodeoxyglucose [FDG]) from those seen in the earliest stages of specific forms of dementia. However, FDG PET only demonstrates nonspecific changes in altered parenchymal glucose uptake and not the specific etiologic proteinopathy causing the abnormal glucose uptake. A growing class of radiotracers targeting specific protein aggregates for amyloid-β (Aβ) and tau are changing the way AD is diagnosed, as these radiotracers directly label the underlying disease pathology. As these pathology-specific radiotracers are currently making their way to the clinic, it is important for the clinical neuroradiologist to understand the underlying patterns of Aβ and tau deposition in the context of AD (across its clinical continuum) and in other causes of dementia, as well as understand the implications of current research.

Blood biomarkers indicative of Alzheimer’s disease (AD) pathology are altered in both preclinical and symptomatic stages of the disease. Distinctive biomarkers may be optimal for the identification of AD pathology or monitoring of disease progression. Blood biomarkers that correlate with changes in cognition and atrophy during the course of the disease could be used in clinical trials to identify successful interventions and thereby accelerate the development of efficient therapies. When disease-modifying treatments become approved for use, efficient blood-based biomarkers might also inform on treatment implementation and management in clinical practice. In the BioFINDER-1 cohort, plasma phosphorylated (p)-tau231 and amyloid-β42/40 ratio were more changed at lower thresholds of amyloid pathology. Longitudinally, however, only p-tau217 demonstrated marked amyloid-dependent changes over 4–6 years in both preclinical and symptomatic stages of the disease, with no such changes observed in p-tau231, p-tau181, amyloid-β42/40, glial acidic fibrillary protein or neurofilament light. Only longitudinal increases of p-tau217 were also associated with clinical deterioration and brain atrophy in preclinical AD. The selective longitudinal increase of p-tau217 and its associations with cognitive decline and atrophy was confirmed in an independent cohort (Wisconsin Registry for Alzheimer’s Prevention). These findings support the differential association of plasma biomarkers with disease development and strongly highlight p-tau217 as a surrogate marker of disease progression in preclinical and prodromal AD, with impact for the development of new disease-modifying treatments.

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.In initially cognitively unimpaired, late middle-aged participants (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.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.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.

Blood-based Alzheimer's disease (AD) biomarkers show promise, but pre-analytical protocol differences may pose problems. We examined seven AD blood biomarkers (amyloid beta [Plasma and serum were obtained from cerebrospinal fluid or amyloid positron emission tomography-positive and -negative participants (N = 38) in the Wisconsin Registry for Alzheimer's Prevention. We modeled AD biomarker values observed in EDTA plasma versus heparin plasma and serum, and assessed correspondence with brain amyloidosis.Results suggested bias due to tube type, but crosswalks are possible for some analytes, with excellent model fit for NfL (AD biomarker concentrations vary by tube type. However, correlations for some biomarkers support harmonization across types, suggesting cautious optimism for use in banked blood.

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.We examined trajectories of Clinical Dementia Rating-Sum of Boxes (CDR-SB) relative to estimated years of amyloid positivity (A+) inThe 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.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.