Amyloid-β aggregates activate peripheral monocytes in mild cognitive impairment.
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ABSTRACT:
SUBMITTER: Juul-Madsen K
PROVIDER: S-EPMC10858199 | biostudies-literature | 2024 Feb
REPOSITORIES: biostudies-literature
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Amyloid-β aggregates activate peripheral monocytes in mild cognitive impairment.
Juul-Madsen Kristian K Parbo Peter P Ismail Rola R Ovesen Peter L PL Schmidt Vanessa V Madsen Lasse S LS Thyrsted Jacob J Gierl Sarah S Breum Mihaela M Larsen Agnete A Andersen Morten N MN Romero-Ramos Marina M Holm Christian K CK Andersen Gregers R GR Zhao Huaying H Schuck Peter P Nygaard Jens V JV Sutherland Duncan S DS Eskildsen Simon F SF Willnow Thomas E TE Brooks David J DJ Vorup-Jensen Thomas T
Nature communications 20240209 1
The peripheral immune system is important in neurodegenerative diseases, both in protecting and inflaming the brain, but the underlying mechanisms remain elusive. Alzheimer's Disease is commonly preceded by a prodromal period. Here, we report the presence of large Aβ aggregates in plasma from patients with mild cognitive impairment (n = 38). The aggregates are associated with low level Alzheimer's Disease-like brain pathology as observed by <sup>11</sup>C-PiB PET and <sup>18</sup>F-FTP PET and l ...[more]
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Project description:BackgroundSeveral positron emission tomography (PET) studies have explored the relationship between amyloid-β (Aβ), glucose metabolism, and the APOEɛ4 genotype. It has been reported that APOEɛ4, and not aggregated Aβ, contributes to glucose hypometabolism in pre-clinical stages of Alzheimer's disease (AD) pathology.ObjectiveWe hypothesize that typical measurements of Aβ taken either from composite regions-of-interest with relatively high burden actually cover significant patterns of the relationship with glucose metabolism. In contrast, spatially weighted measures of Aβ are more related to glucose metabolism in cognitively normal (CN) aging and mild cognitive impairment (MCI).MethodsWe have generated a score of amyloid burden based on a joint singular value decomposition (SVD) of the cross-correlation structure between glucose metabolism, as measured by [18F]2-fluoro-2-deoxyglucose (FDG) PET, and Aβ, as measured by [18F]florbetapir PET, from the Alzheimer's Disease Neuroimaging Initiative study. This SVD-based score reveals cortical regions where a reduced glucose metabolism is maximally correlated with distributed patterns of Aβ.ResultsFrom an older population of CN and MCI subjects, we found that the SVD-based Aβ score was significantly correlated with glucose metabolism in several cortical regions. Additionally, the corresponding Aβ network has hubs that contribute to distributed glucose hypometabolism, which, in turn, are not necessarily foci of Aβ deposition.ConclusionsOur approach uncovered hidden patterns of the glucose metabolism-Aβ relationship. We showed that the SVD-based Aβ score produces a stronger relationship with decreasing glucose metabolism than either APOEɛ4 genotype or global measures of Aβ burden.
| S-EPMC7029335 | biostudies-literature
Project description:IntroductionPractical algorithms predicting the probability of amyloid pathology among patients with subjective cognitive decline or mild cognitive impairment may help clinical decisions regarding confirmatory biomarker testing for Alzheimer's disease.MethodsAlgorithm feature selection was conducted with Alzheimer's Disease Neuroimaging Initiative and Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing data. Probability algorithms were developed in Alzheimer's Disease Neuroimaging Initiative using nested cross-validation accompanied by stratified subsampling to obtain 1000 internally validated decision trees. Semi-independent validation was conducted using Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing. Independent external validation was conducted in the population-based Mayo Clinic Study of Aging.ResultsTwo algorithms were developed using age and normalized immediate recall z-scores, with or without apolipoprotein E ε4 carrier status. Both algorithms had robust performance across data sets and when substituting different recall memory tests.DiscussionThe statistical framework resulted in robust probability estimation. Application of these algorithms may assist in clinical decision-making for further testing to diagnose amyloid pathology.
| S-EPMC6827360 | biostudies-literature
Project description:How beta-amyloid accumulation influences brain atrophy in Alzheimer's disease remains contentious with conflicting findings. We aimed to elucidate the correlations of regional longitudinal atrophy with cross-sectional regional and global amyloid in individuals with mild cognitive impairment and no cognitive impairment. We hypothesized that greater cortical thinning over time correlated with greater amyloid deposition, particularly within Alzheimer's disease characteristic regions in mild cognitive impairment, and weaker or no correlations in those with no cognitive impairment. 45 patients with mild cognitive impairment and 12 controls underwent a cross-sectional [11C]-Pittsburgh Compound B PET and two retrospective longitudinal structural imaging (follow-up: 23.65 ± 2.04 months) to assess global/regional amyloid and regional cortical thickness, respectively. Separate linear mixed models were constructed to evaluate relationships of either global or regional amyloid with regional cortical thinning longitudinally. In patients with mild cognitive impairment, regional amyloid in the right banks of the superior temporal sulcus was associated with longitudinal cortical thinning in the right medial orbitofrontal cortex (P = 0.04 after False Discovery Rate correction). In the mild cognitive impairment group, greater right banks amyloid burden and less cortical thickness in the right medial orbitofrontal cortex showed greater visual and verbal memory decline over time, which was not observed in controls. Global amyloid was not associated with longitudinal cortical thinning in any locations in either group. Our findings indicate an increasing influence of amyloid on neurodegeneration and memory along the preclinical to prodromal spectrum. Future multimodal studies that include additional biomarkers will be well-suited to delineate the interplay between various pathological processes and amyloid and memory decline, as well as clarify their additive or independent effects along the disease deterioration.
| S-EPMC10358322 | biostudies-literature
Project description:IntroductionPrevious studies have examined the predictive accuracy of plasma amyloid beta (Aβ) biomarkers in clinical cohorts. However, their accuracy for predicting amyloid-positive patients in community-based cohorts is unclear. This study aimed to determine the predictive accuracy of Aβ precursor protein 669-711/Aβ1-42, Aβ1-40/1-42 and their composite biomarkers for brain amyloid deposition or the clinical progression in community-dwelling older adults with mild cognitive impairment (MCI).MethodsThis prospective cohort study was conducted from August 2015 to September 2019. Subsequently, the participants underwent follow-up cognitive assessments up to 8 years after the start of the study. Blood samples were collected from older adults aged ≥ 65 years with MCI at baseline. Plasma Aβ biomarkers were analyzed using immunoprecipitation-mass spectrometry. The accuracy of plasma biomarkers for brain amyloid status was evaluated using receiver operating characteristic curve analysis. Relationships between comorbidities and plasma Aβ markers were examined using multiple linear regression analysis. Associations of plasma biomarkers with clinical conversion to Alzheimer's disease (AD) dementia were evaluated using Kaplan‒Meier curves.ResultsThe participants included 107 patients (57 [53.3%] females, median age: 76.0 [72.0-80.0] years). Plasma biomarkers correlated with cortical amyloid uptake (ρ = 0.667-0.754). The composite biomarker had the best area under the curve (0.943, 95% confidence interval [CI]: 0.901 to 0.985) for predicting amyloid positivity. Apolipoprotein ε4 status showed significant correlations with increased plasma amyloid biomarker levels. Participants with high composite biomarker levels at baseline had a greater risk of conversion to AD dementia (hazard ratio 10.74, 95% CI: 3.51 to 32.84, P < 0.001). The higher composite biomarker was associated with a faster rate of cognitive decline (ρ = -0.575, P < 0.001).DiscussionPlasma Aβ composite biomarker may serve as a surrogate measure for amyloid deposition and a predictor of disease progression in a community-based cohort.HighlightsPlasma amyloid beta (Aβ) biomarkers correlated with 11C-Pittsburgh compound B uptake, mainly in the frontal/parietotemporal cortices and posterior cingulate gyrus.The amyloid composite biomarker can predict amyloid positron emission tomography positivity with a high area under the curve of 0.943 in a community-based mild cognitive impairment cohort.The higher amyloid composite biomarker at baseline was significantly associated with worsening Mini-Mental State Examination score and a high risk for developing Alzheimer's disease (AD) dementia over 8 years.The amyloid composite biomarker can predict clinical progression to AD dementia with a high area under the curve of 0.860.Apolipoprotein E ε4 status influenced the plasma Aβ biomarker levels.
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Project description:BackgroundAmyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease (AD), particularly in trials for amyloid-targeted therapy. Predicting Aβ positivity prior to PET imaging can decrease unnecessary patient burden and costs of running these trials.ObjectiveThe aim of this study was to evaluate the performance of a machine learning model in estimating the individual risk of Aβ+ based on gold-standard of PET imaging.MethodsWe used data from an amnestic mild cognitive impairment (aMCI) subset of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to develop and validate the models. The predictors of Aβ status included demographic and ApoE4 status in all models plus a combination of neuropsychological tests (NP), MRI volumetrics, and cerebrospinal fluid (CSF) biomarkers.ResultsThe models that included NP and MRI measures separately showed an area under the receiver operating characteristics (AUC) of 0.74 and 0.72, respectively. However, using NP and MRI measures jointly in the model did not improve prediction. The models including CSF biomarkers significantly outperformed other models with AUCs between 0.89 to 0.92.ConclusionsPredictive models can be effectively used to identify persons with aMCI likely to be amyloid positive on a subsequent PET scan.
| S-EPMC7376527 | biostudies-literature
Project description:BackgroundNon-alcoholic fatty liver disease (NAFLD) is a prevalent risk factor for cognitive impairment. Cerebral amyloid-β (Aβ) accumulation, as an important pathology of cognitive impairment, can be caused by impaired Aβ clearance in the periphery. The liver is the primary organ for peripheral Aβ clearance, but the role of peripheral Aβ clearance in NAFLD-induced cognitive impairment remains unclear.MethodsWe examined correlations between NAFLD severity, Aβ accumulation, and cognitive performance in female Sprague-Dawley rats. The impact of NAFLD on hepatic Aβ clearance and the involvement of low-density lipoprotein receptor-related protein 1 (LRP-1) were assessed in rat livers and cultured hepatocytes. Additionally, a case-control study, including 549 NAFLD cases and 549 controls (782 males, 316 females), investigated the interaction between NAFLD and LRP-1 rs1799986 polymorphism on plasma Aβ levels.FindingsThe severity of hepatic steatosis and dysfunction closely correlated with plasma and cerebral Aβ accumulations and cognitive deficits in rats. The rats with NAFLD manifested diminished levels of LRP-1 and Aβ in liver tissue, with these reductions inversely proportional to plasma and cerebral Aβ concentrations and cognitive performance. In vitro, exposure of HepG2 cells to palmitic acid inhibited LRP-1 expression and Aβ uptake, which was subsequently reversed by a peroxisome proliferator-activated receptor α (PPARα) agonist. The case-control study revealed NAFLD to be associated with an increment of 8.24% and 10.51% in plasma Aβ40 and Aβ42 levels, respectively (both P < 0.0001). Moreover, the positive associations between NAFLD and plasma Aβ40 and Aβ42 levels were modified by the LRP-1 rs1799986 polymorphism (P for interaction = 0.0017 and 0.0015, respectively).InterpretationLRP-1 mediates the adverse effect of NAFLD on peripheral Aβ clearance, thereby contributing to cerebral Aβ accumulation and cognitive impairment in NAFLD.FundingMajor International (Regional) Joint Research Project, National Key Research and Development Program of China, National Natural Science Foundation of China, and the Angel Nutrition Research Fund.
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Project description:Positron emission tomography (PET) studies using [18F]2-fluoro-2-deoxyglucose (FDG) have identified a well-defined pattern of glucose hypometabolism in Alzheimer's disease (AD). The assessment of the metabolic relationship among brain regions has the potential to provide unique information regarding the disease process. Previous studies of metabolic correlation patterns have demonstrated alterations in AD subjects relative to age-matched, healthy control subjects. The objective of this study was to examine the associations between β-amyloid, apolipoprotein E ɛ4 (APOE ɛ4) genotype, and metabolic correlations patterns in subjects diagnosed with mild cognitive impairment (MCI). Mild cognitive impairment subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were categorized into β-amyloid-low and β-amyloid-high groups, based on quantitative analysis of [18F]florbetapir PET scans, and APOE ɛ4 non-carriers and carriers based on genotyping. We generated voxel-wise metabolic correlation strength maps across the entire cerebral cortex for each group, and, subsequently, performed a seed-based analysis. We found that the APOE ɛ4 genotype was closely related to regional glucose hypometabolism, while elevated, fibrillar β-amyloid burden was associated with specific derangements of the metabolic correlation patterns.
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Project description:BackgroundBlood adiponectin and leptin are adipokines that emerged as potential biomarkers for predicting Alzheimer's disease (AD) owing to their strong connection with obesity. Although obesity affects the relation between beta-amyloid (Aβ) aggregation and cognitive decline, the longitudinal interactive effect of adipokines and Aβ on cognition and brain structures in humans remains unexplored. Hence, we investigated whether plasma levels of adiponectin and leptin are associated with future cognitive decline and cortical thinning across Aβ conditions (Aβ [+] and Aβ [-]) in individuals with mild cognitive impairment (MCI).MethodsOf 156 participants with MCI from the longitudinal cohort study of Alzheimer's Disease Neuroimaging Initiative (ADNI), 31 were Aβ (-) and 125 were Aβ (+) as determined by CSF analysis. The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) scores and the thickness of the parahippocampal and entorhinal cortices were used to evaluate cognition and brain structure, respectively. After stratifying groups by Aβ conditions, the association of cognitive and brain structural changes with baseline plasma levels of adiponectin and leptin was examined.ResultsOf the total 156 participants, 51 were women (32.7%). The mean age of participants was 74.5 (standard deviation 7.57), and the mean follow-up period was 54.3 months, without a difference between the Aβ (+) and (-) groups. After adjustment for confounders, higher plasma adiponectin levels were associated with a faster increase in ADAS-Cog scores, indicating faster cognitive decline under the Aβ (+) condition (beta = 0.224, p = 0.018). Likewise, participants with higher plasma adiponectin presented faster cortical thinning in the bilateral parahippocampal cortices under the Aβ (+) condition (beta = - 0.004, p = 0.012 for the right side; beta = - 0.004, p = 0.025 for the left side). Interestingly, plasma adiponectin levels were not associated with longitudinal ADAS-Cog scores or cortical thickness in the Aβ (-) condition. Plasma leptin levels were not predictive of cognition or cortical thickness regardless of Aβ status.ConclusionPlasma adiponectin can be a potential biomarker for predicting the speed of AD progression in individuals with Aβ (+) MCI.
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Project description:BACKGROUND:Determination of β-amyloid (Aβ) positivity and likelihood of underlying Alzheimer's disease (AD) relies on dichotomous biomarker cut-off values. Individuals with mild cognitive impairment (MCI) and Aβ within the normal range may still have a substantial risk of developing dementia, primarily of Alzheimer type. Their prognosis, as well as predictors of clinical progression, are not fully understood. The aim of this study was to explore the associations of cerebrospinal fluid (CSF) biomarkers (Aβ42, total tau, phosphorylated tau) and other characteristics, including modifiable vascular factors, with the risk of progression to dementia among patients with MCI and normal CSF Aβ42. METHODS:Three hundred eighteen memory clinic patients with CSF and clinical data, and at least 1-year follow-up, were included. Patients had normal CSF Aβ42 levels based on clinical cut-offs. Cox proportional hazard models with age as time scale and adjusted for sex, education, and cognition (Mini-Mental State Examination) were used to investigate predictors of progression to dementia and Alzheimer-type dementia. Potential predictors included CSF biomarkers, cognitive performance (verbal learning and memory), apolipoprotein E (APOE) ε4 genotype, medial temporal lobe atrophy, family history of dementia, depressive symptoms, and vascular factors, including the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) risk score. Predictive performance of patient characteristics was further explored with Harrell C statistic. RESULTS:Lower normal Aβ42 and higher total tau and phosphorylated tau were associated with higher dementia risk, and the association was not driven by Aβ42 values close to cut-off. Additional predictors included poorer cognition, APOE ε4 genotype, higher systolic blood pressure, and lower body mass index, but not the CAIDE dementia risk score. Aβ42 individually and in combination with other CSF biomarkers improved the risk prediction compared to age and cognition alone. Medial temporal lobe atrophy or vascular factors did not increase the predictive performance. CONCLUSIONS:Possibility of underlying AD pathology and increased dementia risk should not be ruled out among MCI patients with CSF Aβ42 within the normal range. While cut-offs may be useful in clinical practice to identify high-risk individuals, personalized risk prediction tools incorporating continuous biomarkers may be preferable among individuals with intermediate risk. The role of modifiable vascular factors could be explored in this context.
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Project description:Depressive symptoms are frequently seen in patients with dementia and mild cognitive impairment (MCI). Evidence suggests that there may be a link between current depressive symptoms and Alzheimer disease (AD)-associated pathological changes, such as an increase in cortical amyloid-β (Aβ). However, limited in vivo studies have explored the relationship between current depressive symptoms and cortical Aβ in patients with MCI and AD. Our study, using a large sample of 455 patients with MCI and 153 patients with AD from the Alzheimer's disease Neuroimaging Initiatives, investigated whether current depressive symptoms are related to cortical Aβ deposition. Depressive symptoms were assessed using the Geriatric Depression Scale and Neuropsychiatric Inventory-depression/dysphoria. Cortical Aβ was quantified using positron emission tomography with the Aβ probe(18)F-florbetapir (AV-45).(18)F-florbetapir standardized uptake value ratio (AV-45 SUVR) from the frontal, cingulate, parietal, and temporal regions was estimated. A global AV-45 SUVR, defined as the average of frontal, cingulate, precuneus, and parietal cortex, was also used. We observed that current depressive symptoms were not related to cortical Aβ, after controlling for potential confounds, including history of major depression. We also observed that there was no difference in cortical Aβ between matched participants with high and low depressive symptoms, as well as no difference between matched participants with the presence and absence of depressive symptoms. The association between depression and cortical Aβ deposition does not exist, but the relationship is highly influenced by stressful events in the past, such as previous depressive episodes, and complex interactions of different pathways underlying both depression and dementia.
| S-EPMC4870393 | biostudies-literature