30 research outputs found

    Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife

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    The ability to detect preclinical Alzheimer’s disease is of great importance, as this stage of the Alzheimer’s continuum is believed to provide a key window for intervention and prevention. As Alzheimer’s disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer’s disease; (ii) mixed Alzheimer’s disease and vascular aetiology; (iii) suspected non-Alzheimer’s disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials

    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

    Pathway-Specific Polygenic Risk Scores as Predictors of Amyloid-beta Deposition and Cognitive Function in a Sample at Increased Risk for Alzheimer's Disease

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    Polygenic risk scores (PRSs) have been used to combine the effects of variants with small effects identified by genome-wide association studies. We explore the potential for using pathway-specific PRSs as predictors of early changes in Alzheimer’s disease (AD)-related biomarkers and cognitive function. Participants were from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of adults who were cognitively asymptomatic at enrollment and enriched for a parental history of AD. Using genes associated with AD in the International Genomics of Alzheimer’s Project’s meta-analysis, we identified clusters of genes that grouped into pathways involved in amyloid-β (Aβ) deposition and neurodegeneration: Aβ clearance, cholesterol metabolism, and immune response. Weighted pathway-specific and overall PRSs were developed and compared to APOE alone. Mixed models were used to assess whether each PRS was associated with cognition in 1,200 individuals, cerebral Aβ deposition measured using amyloid ligand (Pittsburgh compound B) positron emission imaging in 168 individuals, and cerebrospinal fluid Aβ deposition, neurodegeneration, and tau pathology in 111 individuals, with replication performed in an independent sample. We found that PRSs including APOE appeared to be driven by the inclusion of APOE, suggesting that the pathway-specific PRSs used here were not more predictive than an overall PRS or APOE alone. However, pathway-specific PRSs could prove to be useful as more knowledge is gained on the genetic variants involved in specific biological pathways of AD

    Cerebrospinal fluid biomarkers of neurofibrillary tangles and synaptic dysfunction are associated with longitudinal decline in white matter connectivity: A multi-resolution graph analysis

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    In addition to the development of beta amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) involves the loss of connecting structures including degeneration of myelinated axons and synaptic connections. However, the extent to which white matter tracts change longitudinally, particularly in the asymptomatic, preclinical stage of AD, remains poorly characterized. In this study we used a novel graph wavelet algorithm to determine the extent to which microstructural brain changes evolve in concert with the development of AD neuropathology as observed using CSF biomarkers. A total of 118 participants with at least two diffusion tensor imaging (DTI) scans and one lumbar puncture for CSF were selected from two observational and longitudinally followed cohorts. CSF was assayed for pathology specific to AD (Aβ42 and phosphorylated-tau), neurodegeneration (total-tau), axonal degeneration (neurofilament light chain protein; NFL), and synaptic degeneration (neurogranin). Tractography was performed on DTI scans to obtain structural connectivity networks with 160 nodes where the nodes correspond to specific brain regions of interest (ROIs) and their connections were defined by DTI metrics (i.e., fractional anisotropy (FA) and mean diffusivity (MD)). For the analysis, we adopted a multi-resolution graph wavelet technique called Wavelet Connectivity Signature (WaCS) which derives higher order representations from DTI metrics at each brain connection. Our statistical analysis showed interactions between the CSF measures and the MRI time interval, such that elevated CSF biomarkers and longer time were associated with greater longitudinal changes in white matter microstructure (decreasing FA and increasing MD). Specifically, we detected a total of 17 fiber tracts whose WaCS representations showed an association between longitudinal decline in white matter microstructure and both CSF p-tau and neurogranin. While development of neurofibrillary tangles and synaptic degeneration are cortical phenomena, the results show that they are also associated with degeneration of underlying white matter tracts, a process which may eventually play a role in the development of cognitive decline and dementia

    Measurement batch differences and between-batch conversion of Alzheimer's disease cerebrospinal fluid biomarker values

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    Introduction: Batch differences in cerebrospinal fluid (CSF) biomarker measurement can introduce bias into analyses for Alzheimer's disease studies. We evaluated and adjusted for batch differences using statistical methods. Methods: A total of 792 CSF samples from 528 participants were assayed in three batches for 12 biomarkers and 3 biomarker ratios. Batch differences were assessed using Bland-Altman plot, paired t test, Pitman-Morgan test, and linear regression. Generalized linear models were applied to convert CSF values between batches. Results: We found statistically significant batch differences for all biomarkers and ratios, except that neurofilament light was comparable between batches 1 and 2. The conversion models generally had high R2 except for converting P-tau between batches 1 and 3. Discussion: Between-batch conversion allows harmonized CSF values to be used in the same analysis. Such method may be applied to adjust for other sources of variability in measuring CSF or other types of biomarkers

    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

    Comparison of different MRI-based morphometric estimates for defining neurodegeneration across the Alzheimer's disease continuum

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    BACKGROUND: Several neurodegeneration (N) metrics using structural MRI are used for the purpose of Alzheimer's disease (AD)-related staging, including hippocampal volume, global atrophy, and an "AD signature" composite consisting of thickness or volumetric estimates derived from regions impacted early in AD. This study sought to determine if less user-intensive estimates of global atrophy and hippocampal volume were equivalent to a thickness-based AD signature from FreeSurfer for defining N across the AD continuum (i.e., individuals who are amyloid-positive (A+)). // METHODS: Cognitively unimpaired (CU) late middle-aged and older adults, as well as A+ mild cognitive impairment (MCI) and A+ AD dementia individuals, with available CSF and structural MRI scan <1.5 years apart, were selected for the study (n = 325, mean age = 62). First, in a subsample of A+ AD dementia and matched biomarker-negative (i.e., A- and tau tangle pathology (T)-) CU controls (n = 40), we examined ROC characteristics and identified N cut-offs using Youden's J for neurofilament light chain protein (NfL) and each of three MRI-based measures: a thickness-based AD signature from FreeSurfer, hippocampal volume (using FIRST), and a simple estimate of global atrophy (the ratio of intracranial CSF segmented volume to brain tissue volume, using SPM12). Based on the results from the ROC analyses, we then examined the concordance between NfL N positivity and N positivity for each MRI-based metric using Cohen's Kappa in the remaining subsample of 285 individuals. Finally, in the full sample (n = 325), we examined the relationship between the four measures of N and group membership across the AD continuum using Kruskal-Wallis tests and Cliff's deltas. // RESULTS: The three MRI-based metrics and CSF NfL similarly discriminated between the A-T- CU (n = 20) and A+ AD (n = 20) groups (AUCs ≥0.885; ps < 0.001). Using the cut-off values derived from the ROCs to define N positivity, there was weak concordance between NfL and all three MRI-derived metrics of N in the subsample of 285 individuals (Cohen's Kappas ≤0.429). Finally, the three MRI-based measures of N and CSF NfL showed similar associations with AD continuum group (i.e., Kruskal-Wallis ps < 0.001), with relatively larger effect sizes noted when comparing the A-T- CU to the A+ MCI (Cliff's deltas ≥0.741) and A+ AD groups (Cliff's deltas ≥0.810) than to the A+T- CU (Cliff's deltas = 0.112-0.298) and A + T+ CU groups (Cliff's deltas = 0.212-0.731). // CONCLUSIONS: These findings suggest that the three MRI-based morphometric estimates and CSF NfL similarly differentiate individuals across the AD continuum on N status. In many applications, a simple estimate of global atrophy may be preferred as an MRI marker of N across the AD continuum given its methodological robustness and ease of calculation when compared to hippocampal volume or a cortical thickness AD signature

    Cardiorespiratory Fitness Modifies Influence of Sleep Problems on Cerebrospinal Fluid Biomarkers in an At-Risk Cohort

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    Background: Previous studies indicate that cardiorespiratory fitness (CRF) and sleep are each favorably associated with Alzheimer’s disease (AD) pathophysiology, including reduced amyloid-β (Aβ) and tau pathology. However, few studies have examined CRF and sleep in the same analysis. Objective: To examine the relationship between sleep and core AD cerebrospinal fluid (CSF) biomarkers among at-risk healthy late-middle-aged adults and determine whether CRF modifies this association. Methods: Seventy-four adults (age = 64.38±5.48, 68.9% female) from the Wisconsin Registry for Alzheimer’s Prevention participated. Sleep was evaluated using the Medical Outcomes Study Sleep Scale, specifically the Sleep Problems Index I (SPI), which incorporates domains of sleep disturbance, somnolence, sleep adequacy, and shortness of breath. Higher scores indicate greater sleep problems. To assess CRF, participants underwent a graded exercise test. CSF was collected via lumbar puncture, from which Aβ42, total-tau (t-tau), and phosphorylated-tau (p-tau) were immunoassayed. Regression analyses examined the association between SPI and CSF biomarkers, and the interaction between SPI and CRF on these same biomarkers, adjusting for relevant covariates. Results: Higher SPI scores were associated with greater p-tau (p = 0.027) and higher t-tau/Aβ42 (p = 0.021) and p-tau/Aβ42 (p = 0.009) ratios. Analyses revealed significant SPI*CRF interactions for t-tau (p = 0.016), p-tau (p = 0.008), and p-tau/Aβ42 (p = 0.041); with a trend for t-tau/Aβ42 (p = 0.061). Specifically, the relationship between poorer sleep and these biomarkers was significant among less fit individuals, but not among those who were more fit. Conclusion: In a late-middle-aged at-risk cohort, CRF attenuated the association between poor sleep and levels of select CSF biomarkers. This suggests fitness may play an important role in preventing AD by protecting against pathology, even in impaired sleep

    Moderate intensity physical activity associates with CSF biomarkers in a cohort at risk for Alzheimer's disease

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    INTRODUCTION: Alzheimer's disease (AD) is characterized by the presence of amyloid β (Aβ) plaques, neurofibrillary tangles, and neurodegeneration, evidence of which may be detected in vivo via cerebrospinal fluid (CSF) sampling. Physical activity (PA) has emerged as a possible modifier of these AD-related pathological changes. Consequently, the aim of this study was to cross-sectionally examine the relationship between objectively measured PA and CSF levels of Aβ42 and tau in asymptomatic late-middle-aged adults at risk for AD. METHODS: Eighty-five cognitively healthy late-middle-aged adults (age = 64.31 years, 61.2% female) from the Wisconsin Registry for Alzheimer's Prevention participated in this study. They wore an accelerometer (ActiGraph GT3X+) for one week to record free-living PA, yielding measures of sedentariness and various intensities of PA (i.e., light, moderate, and vigorous). They also underwent lumbar puncture to collect CSF, from which Aβ42, total tau, and phosphorylated tau were immunoassayed. Regression analyses were used to examine the association between accelerometer measures and CSF biomarkers, adjusting for age, sex, and other relevant covariates. RESULTS: Engagement in moderate PA was associated with higher Aβ42 (P = .008), lower total tau/Aβ42 (P = .006), and lower phosphorylated tau/Aβ42 (P = .030). In contrast, neither light nor vigorous PA was associated with any of the biomarkers. Increased sedentariness was associated with reduced Aβ42 (P = .014). DISCUSSIONS: In this cohort, moderate PA, but not light or vigorous, was associated with a favorable AD biomarker profile, while sedentariness was associated with greater Aβ burden. These findings suggest that a physically active lifestyle may play a protective role against the development of AD

    Measuring longitudinal cognition: Individual tests versus composites

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    INTRODUCTION: Longitudinal cohort studies of cognitive aging must confront several sources of within-person variability in scores. In this article, we compare several neuropsychological measures in terms of longitudinal error variance and relationships with biomarker-assessed brain amyloidosis (Aβ). METHODS: Analyses used data from the Wisconsin Registry for Alzheimer's Prevention. We quantified within-person longitudinal variability and age-related trajectories for several global and domain-specific composites and their constituent scores. For a subset with cerebrospinal fluid or amyloid positron emission tomography measures, we examined how Aβ modified cognitive trajectories. RESULTS: Global and theoretically derived composites exhibited lower intraindividual variability and stronger age × Aβ interactions than did empirically derived composites or raw scores from single tests. For example, the theoretical executive function outperformed other executive function scores on both metrics. DISCUSSION: These results reinforce the need for careful selection of cognitive outcomes in study design, and support the emerging consensus favoring composites over single-test measures
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