Elevated Plasma microRNA-206 Levels Predict Cognitive Decline and Progression to Dementia from Mild Cognitive Impairment.
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ABSTRACT:
SUBMITTER: Kenny A
PROVIDER: S-EPMC6920950 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
Publications
Elevated Plasma microRNA-206 Levels Predict Cognitive Decline and Progression to Dementia from Mild Cognitive Impairment.
Kenny Aidan A McArdle Hazel H Calero Miguel M Rabano Alberto A Madden Stephen F SF Adamson Kellie K Forster Robert R Spain Elaine E Prehn Jochen H M JHM Henshall David C DC Medina Miguel M Jimenez-Mateos Eva M EM Engel Tobias T
Biomolecules 20191113 11
The need for practical biomarkers for early diagnosis of Alzheimer's disease (AD) remains largely unmet. Here we investigated the use of blood-based microRNAs as prognostic biomarkers for AD and their application in a novel electrochemical microfluidic device for microRNA detection. MicroRNA transcriptome was profiled in plasma from patients with mild cognitive impairment (MCI) and AD. MicroRNAs Let-7b and microRNA-206 were validated at elevated levels in MCI and AD, respectively. MicroRNA-206 d ...[more]
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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:IntroductionBiomarker discovery of dementia and cognitive impairment is important to gather insight into mechanisms underlying the pathogenesis of these conditions.MethodsIn 997 adults from the InCHIANTI study, we assessed the association of 1301 plasma proteins with dementia and cognitive impairment. Validation was conducted in two Alzheimer's disease (AD) case-control studies as well as endophenotypes of AD including cognitive decline, brain amyloid burden, and brain volume.ResultsWe identified four risk proteins that were significantly associated with increased odds (peptidase inhibitor 3 (PI3), trefoil factor 3 (TFF3), pregnancy associated plasma protein A (PAPPA), agouti-related peptide (AGRP)) and two protective proteins (myostatin (MSTN), integrin aVb5 (ITGAV/ITGB5)) with decreased odds of baseline cognitive impairment or dementia. Of these, four proteins (MSTN, PI3, TFF3, PAPPA) were associated cognitive decline in subjects that were cognitively normal at baseline. ITGAV/ITGB5 was associated with lower brain amyloid burden, MSTN and ITGAV/ITGB5 were associated with larger brain volume and slower brain atrophy, and PI3, PAPPA, and AGRP were associated with smaller brain volume and/or faster brain atrophy.DiscussionThese proteins may be useful as non-invasive biomarkers of dementia and cognitive impairment.
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Project description:ObjectiveWe examined whether sarcopenia is associated with the occurrence of late-life cognitive impairment.MethodsNondemented older adults (N = 1175) underwent annual testing with 17 cognitive tests summarized as a global cognitive score. A composite sarcopenia score was constructed based on muscle mass measured with bioelectrical impedance and muscle function based on grip strength. Cox proportional hazard models were employed to examine associations of sarcopenia with incident Alzheimer's dementia (AD) and incident mild cognitive impairment (MCI). Linear mixed-effect models determined the association of sarcopenia with cognitive decline. All models controlled for age, sex, education, race, and height squared.ResultsAverage follow-up was 5.6 years. More severe sarcopenia at baseline was associated with a higher risk of incident AD (hazard ratio [HR], 1.50 [95% confidence interval 1.20-1.86]; p < 0.001) and of MCI (1.21 [1.01-1.45]; 0.04) and a faster rate of cognitive decline (estimate = -0.013; p = 0.01). Analyses of the individual components of sarcopenia showed that muscle function was associated with incident AD, incident MCI, and cognitive decline with and without a term for lean muscle mass in the model. In contrast, lean muscle mass was not associated with incident cognitive impairment or cognitive decline when a term for muscle function was included in the model.ConclusionsPoor muscle function, but not reduced lean muscle mass, drives the association of sarcopenia with late-life cognitive impairment. Further work is needed to identify features of muscle structure, which may increase the specificity of sarcopenia for identifying older adults at risk for late-life cognitive impairment.
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Project description:To determine the relationship between psychological stress with cognitive outcomes in a multi-centre longitudinal study of people with amnestic mild cognitive impairment (aMCI) we assessed three parameters of psychological stress (Recent Life Changes Questionnaire (RLCQ); the Perceived Stress Scale (PSS) and salivary cortisol) and their relationship with rates of cognitive decline over an 18 month follow up period and conversion to dementia over a 5.5 year period. In 133 aMCI and 68 cognitively intact participants the PSS score was higher in the aMCI compared with control group but neither the RLCQ scores nor salivary cortisol measures were different between groups. In the aMCI group the RLCQ and the PSS showed no significant association with cognitive function at baseline, cognitive decline or with conversion rates to dementia but high salivary cortisol levels were associated with RLCQ scores and poorer cognitive function at baseline and lower rates of cognitive decline. No relationship was found between salivary cortisol levels and conversion rate to dementia. We conclude that psychological stress as measured by the RLCQ or PSS was not associated with adverse cognitive outcomes in an aMCI population and hypothesise that this may reflect diminished cortisol production to psychological stress as the disease progresses.
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Project description:BackgroundIn cognitively normal individuals, subjective cognitive decline (SCD) has been reported to predict MCI and dementia (MCI/dementia). However, prior studies mostly captured SCD at single time-points without considering the longitudinal course of SCD. This study examined whether the trajectories of SCD provide any added information-beyond one-time assessments of SCD-on the risk of MCI/dementia.MethodsThis cohort study included 5661 participants from the Alzheimer's Disease Centers across the USA, who were ≥ 50 years and had normal cognition in the first-four annual visits (year 1 to year 4). The participants were evaluated for SCD in the first-four annual visits (year 1 to year 4), and followed-up almost annually (year 4 up to year 14) for incident MCI/dementia. SCD trajectories (as identified from latent-class-growth-curve-analysis) were included in Cox regression to estimate their risks of MCI/dementia, with analyses further stratified by age (< 75 years versus ≥ 75 years; based on median-split).ResultsCompared to those without SCD (in the first-four annual visits), Intermittent SCD (i.e., reported in 1-2 of the first-four annual visits) predicted a higher risk (HR 1.4) and Persistent SCD (i.e., reported in 3-4 of the first-four annual visits) predicted the highest risk (HR 2.2), with the results remaining significant even after adjusting for baseline SCD. Age-stratified analysis revealed that the risk associated with Intermittent SCD was only present in older individuals, while risk related to Persistent SCD was consistently present across the younger and older age groups. Age compounded the effects of the trajectories, whereby older individuals with Persistent SCD had > 75% probability of developing MCI/dementia by 10 years, in contrast to < 25% probability by 10 years in younger individuals with No SCD.ConclusionsThe findings demonstrate the utility of SCD trajectories-especially when used in combination with age strata-in identifying high-risk populations for preventive interventions and trials. They also suggest a potential modification in the current SCD criteria, with the inclusion of "persistent SCD over several years" as a feature of SCD plus.
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Project description:Plasma-based biomarkers present a promising approach in the research and clinical practice of Alzheimer's disease as they are inexpensive, accessible and minimally invasive. In particular, prognostic biomarkers of cognitive decline may aid in planning and management of clinical care. Although recent studies have demonstrated the prognostic utility of plasma biomarkers of Alzheimer pathology or neurodegeneration, such as pTau-181 and NF-L, whether other plasma biomarkers can further improve prediction of cognitive decline is undetermined. We conducted an observational cohort study to determine the prognostic utility of plasma biomarkers in predicting progression to dementia for individuals presenting with mild cognitive impairment due to probable Alzheimer's disease. We used the Olink™ Proximity Extension Assay technology to measure the level of 460 circulating proteins in banked plasma samples of all participants. We used a discovery data set comprised 60 individuals with mild cognitive impairment (30 progressors and 30 stable) and a validation data set consisting of 21 stable and 21 progressors. We developed a machine learning model to distinguish progressors from stable and used 44 proteins with significantly different plasma levels in progressors versus stable along with age, sex, education and baseline cognition as candidate features. A model with age, education, APOE genotype, baseline cognition, plasma pTau-181 and 12 plasma Olink protein biomarker levels was able to distinguish progressors from stable with 86.7% accuracy (mean area under the curve = 0.88). In the validation data set, the model accuracy was 78.6%. The Olink proteins selected by the model included those associated with vascular injury and neuroinflammation (e.g. IL-8, IL-17A, TIMP-4, MMP7). In addition, to compare these prognostic biomarkers to those that are altered in Alzheimer's disease or other types of dementia relative to controls, we analyzed samples from 20 individuals with Alzheimer, 30 with non-Alzheimer dementias and 34 with normal cognition. The proteins NF-L and PTP-1B were significantly higher in both Alzheimer and non-Alzheimer dementias compared with cognitively normal individuals. Interestingly, the prognostic markers of decline at the mild cognitive impairment stage did not overlap with those that differed between dementia and control cases. In summary, our findings suggest that plasma biomarkers of inflammation and vascular injury are associated with cognitive decline. Developing a plasma biomarker profile could aid in prognostic deliberations and identify individuals at higher risk of dementia in clinical practice.
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