138 research outputs found

    Cerebral amyloid‐β load is associated with neurodegeneration and gliosis: Mediation by p‐tau and interactions with risk factors early in the Alzheimer's continuum

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    Introduction: The association between cerebral amyloid‐β accumulation and downstream CSF biomarkers is not fully understood, particularly in asymptomatic stages. / Methods: In 318 cognitively unimpaired participants, we assessed the association between amyloid‐β PET (Centiloid), and cerebrospinal fluid (CSF) biomarkers of several pathophysiological pathways. Interactions by Alzheimer's disease risk factors (age, sex and APOE‐ε4), and the mediation effect of tau and neurodegeneration were also investigated. / Results: Centiloids were positively associated with CSF biomarkers of tau pathology (p‐tau), neurodegeneration (t‐tau, NfL), synaptic dysfunction (neurogranin) and neuroinflammation (YKL‐40, GFAP, sTREM2), presenting interactions with age (p‐tau, t‐tau, neurogranin) and sex (sTREM2, NfL). Most of these associations were mediated by p‐tau, except for NfL. The interaction between sex and amyloid‐β on sTREM2 and NfL was also tau‐independent. / Discussion: Early amyloid‐β accumulation has a tau‐independent effect on neurodegeneration and a tau‐dependent effect on neuroinflammation. Besides, sex has a modifier effect on these associations independent of tau

    Identifying clinically useful biomarkers in neurodegenerative disease through a collaborative approach: the NeuroToolKit

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    BACKGROUND: Alzheimer’s disease (AD) is a complex and heterogeneous disease, which requires reliable biomarkers for diagnosis and monitoring disease activity. Preanalytical protocol and technical variability associated with biomarker immunoassays makes comparability of biomarker data across multiple cohorts difficult. This study aimed to compare cerebrospinal fluid (CSF) biomarker results across independent cohorts, including participants spanning the AD continuum. METHODS: Measured on the NeuroToolKit (NTK) prototype panel of immunoassays, 12 CSF biomarkers were evaluated from three cohorts (ALFA+, Wisconsin, and Abby/Blaze). A correction factor was applied to biomarkers found to be affected by preanalytical procedures (amyloid-β1–42, amyloid-β1–40, and alpha-synuclein), and results between cohorts for each disease stage were compared. The relationship between CSF biomarker concentration and cognitive scores was evaluated. RESULTS: Biomarker distributions were comparable across cohorts following correction. Correlations of biomarker values were consistent across cohorts, regardless of disease stage. Disease stage differentiation was highest for neurofilament light (NfL), phosphorylated tau, and total tau, regardless of the cohort. Correlation between biomarker concentration and cognitive scores was comparable across cohorts, and strongest for NfL, chitinase-3-like protein-1 (YKL40), and glial fibrillary acidic protein. DISCUSSION: The precision of the NTK enables merging of biomarker datasets, after correction for preanalytical confounders. Assessment of multiple cohorts is crucial to increase power in future studies into AD pathogenesis

    Comparative Analysis of Different Definitions of Amyloid-beta Positivity to Detect Early Downstream Pathophysiological Alterations in Preclinical Alzheimer

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    Amyloid-β (Aβ) positivity is defined using different biomarkers and different criteria. Criteria used in symptomatic patients may conceal meaningful early Aβ pathology in preclinical Alzheimer. Therefore, the description of sensitive cutoffs to study the pathophysiological changes in early stages of the Alzheimer’s continuum is critical. Here, we compare different Aβ classification approaches and we show their performance in detecting pathophysiological changes downstream Aβ pathology. We studied 368 cognitively unimpaired individuals of the ALFA+ study, many of whom in the preclinical stage of the Alzheimer’s continuum. Participants underwent Aβ PET and CSF biomarkers assessment. We classified participants as Aβ -positive using five approaches: (1) CSF Aβ42 12; (4) Aβ PET Centiloid > 30 or (5) Aβ PET Positive visual read. We assessed the correlations between Aβ biomarkers and compared the prevalence of Aβ positivity. We determined which approach significantly detected associations between Aβ pathology and tau/neurodegeneration CSF biomarkers. We found that CSF-based approaches result in a higher Aβ-positive prevalence than PET-based ones. There was a higher number of discordant participants classified as CSF Aβ-positive but PET Aβ-negative than CSF Aβ-negative but PET Aβ-positive. The CSF Aβ 42/40 approach allowed optimal detection of significant associations with CSF p-tau and t-tau in the Aβ-positive group. Altogether, we highlight the need for sensitive Aβ -classifications to study the preclinical Alzheimer’s continuum. Approaches that define Aβ positivity based on optimal discrimination of symptomatic Alzheimer’s disease patients may be suboptimal for the detection of early pathophysiological alterations in preclinical Alzheimer

    CSF metabolites associated with biomarkers of Alzheimer’s disease pathology

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    INTRODUCTION: Metabolomics technology facilitates studying associations between small molecules and disease processes. Correlating metabolites in cerebrospinal fluid (CSF) with Alzheimer’s disease (AD) CSF biomarkers may elucidate additional changes that are associated with early AD pathology and enhance our knowledge of the disease. METHODS: The relative abundance of untargeted metabolites was assessed in 161 individuals from the Wisconsin Registry for Alzheimer’s Prevention. A metabolome-wide association study (MWAS) was conducted between 269 CSF metabolites and protein biomarkers reflecting brain amyloidosis, tau pathology, neuronal and synaptic degeneration, and astrocyte or microglial activation and neuroinflammation. Linear mixed-effects regression analyses were performed with random intercepts for sample relatedness and repeated measurements and fixed effects for age, sex, and years of education. The metabolome-wide significance was determined by a false discovery rate threshold of 0.05. The significant metabolites were replicated in 154 independent individuals from then Wisconsin Alzheimer’s Disease Research Center. Mendelian randomization was performed using genome-wide significant single nucleotide polymorphisms from a CSF metabolites genome-wide association study. RESULTS: Metabolome-wide association study results showed several significantly associated metabolites for all the biomarkers except Aβ42/40 and IL-6. Genetic variants associated with metabolites and Mendelian randomization analysis provided evidence for a causal association of metabolites for soluble triggering receptor expressed on myeloid cells 2 (sTREM2), amyloid β (Aβ40), α-synuclein, total tau, phosphorylated tau, and neurogranin, for example, palmitoyl sphingomyelin (d18:1/16:0) for sTREM2, and erythritol for Aβ40 and α-synuclein. DISCUSSION: This study provides evidence that CSF metabolites are associated with AD-related pathology, and many of these associations may be causal

    The recency ratio assessed by story recall is associated with cerebrospinal fluid levels of neurodegeneration biomarkers

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    Recency refers to the information learned at the end of a study list or task. Recency forgetting, as tracked by the ratio between recency recall in immediate and delayed conditions, i.e., the recency ratio (Rr), has been applied to list-learning tasks, demonstrating its efficacy in predicting cognitive decline, conversion to mild cognitive impairment (MCI), and cerebrospinal fluid (CSF) biomarkers of neurodegeneration. However, little is known as to whether Rr can be effectively applied to story recall tasks. To address this question, data were extracted from the database of the Alzheimer's Disease Research Center at the University of Wisconsin – Madison. A total of 212 participants were included in the study. CSF biomarkers were amyloid-beta (Aβ) 40 and 42, phosphorylated (p) and total (t) tau, neurofilament light (NFL), neurogranin (Ng), and α-synuclein (a-syn). Story Recall was measured with the Logical Memory Test (LMT). We carried out Bayesian regression analyses with Rr, and other LMT scores as predictors; and CSF biomarkers (including the Aβ42/40 and p-tau/Aβ42 ratios) as outcomes. Results showed that models including Rr consistently provided best fits with the data, with few exceptions. These findings demonstrate the applicability of Rr to story recall and its sensitivity to CSF biomarkers of neurodegeneration, and encourage its inclusion when evaluating risk of neurodegeneration with story recall

    A comparison of diagnostic performance of word-list and story recall tests for biomarker-determined Alzheimer’s disease

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    BACKGROUND: Wordlist and story recall tests are routinely employed in clinical practice for dementia diagnosis. In this study, our aim was to establish how well-standard clinical metrics compared to process scores derived from wordlist and story recall tests in predicting biomarker determined Alzheimer’s disease, as defined by CSF ptau/Aβ42 ratio. METHODS: Data from 295 participants (mean age = 65 ± 9.) were drawn from the University of Wisconsin – Madison Alzheimer’s Disease Research Center (ADRC) and Wisconsin Registry for Alzheimer’s Prevention (WRAP). Rey’s Auditory Verbal Learning Test (AVLT; wordlist) and Logical Memory Test (LMT; story) data were used. Bayesian linear regression analyses were carried out with CSF ptau/Aβ42 ratio as outcome. Sensitivity analyses were carried out with logistic regressions to assess diagnosticity. RESULTS: LMT generally outperformed AVLT. Notably, the best predictors were primacy ratio, a process score indexing loss of information learned early during test administration, and recency ratio, which tracks loss of recently learned information. Sensitivity analyses confirmed this conclusion. CONCLUSIONS: Our study shows that story recall tests may be better than wordlist tests for detection of dementia, especially when employing process scores alongside conventional clinical scores

    Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

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    Background: Alzheimer’s disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. Methods: Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). Results: Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. Conclusion: Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged

    Association of weight change with cerebrospinal fluid biomarkers and amyloid positron emission tomography in preclinical Alzheimer's disease

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    BACKGROUND: Recognizing clinical manifestations heralding the development of Alzheimer's disease (AD)-related cognitive impairment could improve the identification of individuals at higher risk of AD who may benefit from potential prevention strategies targeting preclinical population. We aim to characterize the association of body weight change with cognitive changes and AD biomarkers in cognitively unimpaired middle-aged adults. METHODS: This prospective cohort study included data from cognitively unimpaired adults from the ALFA study (n = 2743), a research platform focused on preclinical AD. Cognitive and anthropometric data were collected at baseline between April 2013 and November 2014. Between October 2016 and February 2020, 450 participants were visited in the context of the nested ALFA+ study and underwent cerebrospinal fluid (CSF) extraction and acquisition of positron emission tomography images with [18F]flutemetamol (FTM-PET). From these, 408 (90.1%) were included in the present study. We used data from two visits (average interval 4.1 years) to compute rates of change in weight and cognitive performance. We tested associations between these variables and between weight change and categorical and continuous measures of CSF and neuroimaging AD biomarkers obtained at follow-up. We classified participants with CSF data according to the AT (amyloid, tau) system and assessed between-group differences in weight change. RESULTS: Weight loss predicted a higher likelihood of positive FTM-PET visual read (OR 1.27, 95% CI 1.00-1.61, p = 0.049), abnormal CSF p-tau levels (OR 1.50, 95% CI 1.19-1.89, p = 0.001), and an A+T+ profile (OR 1.64, 95% CI 1.25-2.20, p = 0.001) and was greater among participants with an A+T+ profile (p < 0.01) at follow-up. Weight change was positively associated with CSF Aβ42/40 ratio (β = 0.099, p = 0.032) and negatively associated with CSF p-tau (β = - 0.141, p = 0.005), t-tau (β = - 0.147 p = 0.004) and neurogranin levels (β = - 0.158, p = 0.002). In stratified analyses, weight loss was significantly associated with higher t-tau, p-tau, neurofilament light, and neurogranin, as well as faster cognitive decline in A+ participants only. CONCLUSIONS: Weight loss predicts AD CSF and PET biomarker results and may occur downstream to amyloid-β accumulation in preclinical AD, paralleling cognitive decline. Accordingly, it should be considered as an indicator of increased risk of AD-related cognitive impairment. TRIAL REGISTRATION: NCT01835717 , NCT02485730 , NCT02685969

    Insulin resistance is related to cognitive decline but not change in CSF biomarkers of Alzheimer's disease in non-demented adults

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    Introduction: We investigated whether insulin resistance (IR) was associated with longitudinal age-related change in cognition and biomarkers of Alzheimer's disease (AD) pathology and neurodegeneration in middle-aged and older adults who were non-demented at baseline. Methods: IR was measured with homeostatic model assessment of insulin resistance (HOMA2-IR). Core AD-related cerebrospinal fluid (CSF) biomarkers and cognition were assessed, respectively, on n = 212 (1 to 5 visits) and n = 1299 (1 to 6 visits). Linear mixed models tested whether HOMA2-IR moderated age-related change in CSF biomarkers and cognition. Linear regressions tested whether HOMA2-IR x apolipoprotein E ε4 allele (APOE ε4) carrier status predicted amyloid beta [Aβ] chronicity (estimated duration of amyloid positron emission tomography [PET] positivity) (n = 253). Results: Higher HOMA2-IR was associated with greater cognitive decline but not with changes in CSF biomarkers. HOMA2-IR x APOE4 was not related to Aβ chronicity but was significantly associated with CSF phosphorylated tau (P-tau)181/Aβ42 level. Discussion: In non-demented adults IR may not be directly associated with age-related change in AD biomarkers. Additional research is needed to determine mechanisms linking IR to cognitive decline

    Neuropathology-based APOE genetic risk score better quantifies Alzheimer's risk

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    Introduction: Apolipoprotein E (APOE) ε4-carrier status or ε4 allele count are included in analyses to account for the APOE genetic effect on Alzheimer's disease (AD); however, this does not account for protective effects of APOE ε2 or heterogeneous effect of ε2, ε3, and ε4 haplotypes. Methods: We leveraged results from an autopsy-confirmed AD study to generate a weighted risk score for APOE (APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers on APOE variables from the Wisconsin Registry for Alzheimer's Prevention (WRAP), Wisconsin Alzheimer's Disease Research Center (WADRC), and Alzheimer's Disease Neuroimaging Initiative (ADNI). Results: The APOE-npscore explained more variance and provided a better model fit for all three CSF measures than APOE ε4-carrier status and ε4 allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired (CU) participants. Discussion: The APOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account for APOE in AD-related analyses
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