Plasma proteins predict conversion to dementia from prodromal disease.
Ontology highlight
ABSTRACT: Background
The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia.Methods
Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays.Results
Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%).Conclusions
We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.
SUBMITTER: Hye A
PROVIDER: S-EPMC4240530 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Glial fibrillary acidic protein (GFAP) has been suggested as a biomarker for reactive astrogliosis. We measured the levels of plasma GFAP by Simoa in 60 patients with PD with normal cognition, 63 with mild cognitive impairment (PD-MCI), 24 with dementia (PDD) and 15 healthy controls. A subgroup of patients with PD-MCI (n = 31) was followed up for 4.1 ± 2.3 years. Compared with healthy controls, plasma GFAP levels were elevated in patients with PDD (adjusted P < 0.001) and PD-MCI (adjusted P = 0.013) and were negatively correlated with the Mini Mental State Examination (MMSE) score in PD participants. Plasma GFAP predicted MCI-to-dementia conversion with an AUC of 0.90, higher than NfL, Tau and pTau181. Our results support that plasma GFAP has potential value for distinguishing patients with PDD, and predicting MCI-to-dementia conversion in PD.
| S-EPMC9911758 | biostudies-literature
Project description:BackgroundIncreased beta-secretase 1 (BACE1) activity has consistently been detected in brain tissue and cerebrospinal fluid of subjects with mild cognitive impairment (MCI) and probable Alzheimer's disease (AD) compared with control subjects. The collection of cerebrospinal fluid by lumbar puncture is invasive. We sought to identify the presence of plasma BACE1 activity and determine potential alterations in subjects with MCI with clinical follow-up examinations for 3 years using patients with diagnosed probable AD dementia compared with healthy control subjects.MethodsSeventy-five patients with probable AD, 96 individuals with MCI, and 53 age-matched and sex-matched healthy control subjects were recruited from three independent international academic memory clinics and AD research expert centers. Plasma BACE1 activity was measured by a synthetic fluorescence substrate enzyme-linked immunosorbent assay. BACE1 protein expression was assessed by Western blotting using three different antibodies that recognize the epitopes of the N-terminus, C-terminus, and full-length BACE1.ResultsCompared with healthy control subjects, plasma BACE1 activity (Vmax) significantly increased by 53.2% in subjects with MCI and by 68.9% in patients with probable AD. Subjects with MCI who converted to probable AD dementia at follow-up examinations exhibited significantly higher BACE1 activity compared with cognitively stable MCI nonconverters and showed higher levels of BACE1 activity than patients with AD.ConclusionsPlasma BACE1 activity is significantly increased in MCI converters and patients with probable AD. The sensitivities and specificities of BACE1 activity for the patients were 84% and 88%, respectively. Our results indicate that plasma BACE1 activity may be a biomarker for AD risk and could predict progression from prodromal to probable AD dementia.
| S-EPMC5656540 | biostudies-literature
Project description:Cognitive impairment in Parkinson's disease (PD) severely affects patients' prognosis, and early detection of patients at high risk of dementia conversion is important for establishing treatment strategies. We aimed to investigate whether multiparametric MRI radiomics from basal ganglia can improve the prediction of dementia development in PD when integrated with clinical profiles. In this retrospective study, 262 patients with newly diagnosed PD (June 2008-July 2017, follow-up >5 years) were included. MRI radiomic features (n = 1284) were extracted from bilateral caudate and putamen. Two models were developed to predict dementia development: (1) a clinical model-age, disease duration, and cognitive composite scores, and (2) a combined clinical and radiomics model. The area under the receiver operating characteristic curve (AUC) were calculated for each model. The models' interpretabilities were studied. Among total 262 PD patients (mean age, 68 years ± 8 [standard deviation]; 134 men), 51 (30.4%), and 24 (25.5%) patients developed dementia within 5 years of PD diagnosis in the training (n = 168) and test sets (n = 94), respectively. The combined model achieved superior predictive performance compared to the clinical model in training (AUCs 0.928 vs. 0.894, P = 0.284) and test set (AUCs 0.889 vs. 0.722, P = 0.016). The cognitive composite scores of the frontal/executive function domain contributed most to predicting dementia. Radiomics derived from the caudate were also highly associated with cognitive decline. Multiparametric MRI radiomics may have an incremental prognostic value when integrated with clinical profiles to predict future cognitive decline in PD.
| S-EPMC10468504 | biostudies-literature
Project description:In Parkinson's disease, electroencephalographic abnormalities during wakefulness and non-rapid eye movement sleep (spindles) were found to be predictive biomarkers of dementia. Because rapid eye movement sleep is regulated by the cholinergic system, which shows early degeneration in Parkinson's disease with cognitive impairment, anomalies during this sleep stage might mirror dementia development. In this prospective study, we examined baseline electroencephalographic absolute spectral power across three states of consciousness (non-rapid eye movement sleep, rapid eye movement sleep, and wakefulness) in 68 non-demented patients with Parkinson's disease and 44 healthy controls. All participants underwent baseline polysomnographic recordings and a comprehensive neuropsychological assessment. Power spectral analyses were performed on standard frequency bands. Dominant occipital frequency during wakefulness and ratios of slow-to-fast frequencies during rapid eye movement sleep and wakefulness were also computed. At follow-up (an average 4.5 years after baseline), 18 patients with Parkinson's disease had developed dementia and 50 patients remained dementia-free. In rapid eye movement sleep, patients with Parkinson's disease who later developed dementia showed, at baseline, higher absolute power in delta and theta bands and a higher slowing ratio, especially in temporal, parietal, and occipital regions, compared to patients who remained dementia-free and controls. In non-rapid eye movement sleep, lower baseline sigma power in parietal cortical regions also predicted development of dementia. During wakefulness, patients with Parkinson's disease who later developed dementia showed lower dominant occipital frequency as well as higher delta and slowing ratio compared to patients who remained dementia-free and controls. At baseline, higher slowing ratios in temporo-occipital regions during rapid eye movement sleep were associated with poor performance on visuospatial tests in patients with Parkinson's disease. Using receiver operating characteristic curves, we found that best predictors of dementia in Parkinson's disease were rapid eye movement sleep slowing ratios in posterior regions, wakefulness slowing ratios in temporal areas, and lower dominant occipital frequency. These results suggest that electroencephalographic slowing during sleep is a new promising predictive biomarker for Parkinson's disease dementia, perhaps as a marker of cholinergic denervation.
| S-EPMC5841211 | biostudies-literature
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.
| S-EPMC7210784 | biostudies-literature
Project description:ImportanceDetecting individuals at risk for Parkinson disease (PD) during the prodromal phase could clarify disease mechanisms and allow for treatment earlier in the disease process to possibly slow or prevent the onset of motor PD.ObjectiveTo determine if the combination of smell identification testing followed by dopamine transporter (DAT) imaging can accurately and efficiently identify individuals from the general population at risk for conversion to a clinical diagnosis of PD.Design, setting, and participantsParticipants were identified from the community by olfactory testing assessed longitudinally with DAT imaging 2 and 4 years after baseline and by annual clinical follow-up to determine whether they had clinical evidence to establish a PD diagnosis. Participants were contacted by mail and completed olfactory testing at home. Longitudinal follow-up of clinical measures and DAT imaging occurred at specialty centers. There were 203 hyposmic and 100 normosmic participants. A total of 185 hyposmic and 95 normosmic individuals had at least 1 follow-up visit, and 152 hyposmic participants (82.2%) were either observed for 4 years or converted to PD during follow-up.Main outcomes and measuresPercentage of individuals with hyposmia and a DAT deficit that converted to PD and the change in PD clinical scale scores (Unified Parkinson's Disease Rating Scale) and DAT imaging during 4-year follow-up.ResultsOf 280 total participants, 140 (50.0%) were male, and the mean (SD) age of the cohort was 63 (8.7) years. Among 21 participants with hyposmia and a DAT deficit (65% or less of age-expected lowest putamen binding ratio) at baseline, 14 (67%) converted to PD at 4 years compared with 2 of 22 participants (9%) with a DAT in an indeterminate range (greater than 65%-80%) and 3 of 109 participants (2.8%) with no DAT deficit (greater than 80%) at baseline. Individuals with a baseline DAT deficit experienced a 4-year decline in DAT binding of 20.23% (SD, 15.04%) compared with 3.68% (SD, 18.36%) and 5.45% (SD, 13.58%) for participants with an indeterminate and no DAT deficit, respectively (P = .002). The relative risk of conversion to a diagnosis of PD in hyposmic individuals with a DAT deficit was 17.47 (95% CI, 7.02-43.45) compared with individuals with either indeterminate or no DAT deficit.Conclusions and relevanceThe combination of hyposmia and DAT deficit was highly predictive of conversion to PD within 4 years of clinical follow-up. Individuals with hyposmia and a DAT deficit had a 5% reduction in DAT binding annually, similar to early PD. These results provide a framework for planning disease prevention studies in PD.
| S-EPMC5710321 | biostudies-literature
Project description:IntroductionThe NIH Toolbox Cognition Battery (NIHTB-CB) is a computer-based protocol not yet validated for clinical assessment.MethodsWe administered the NIHTB-CB and traditional neuropsychological tests to 247 Memory Disorders and Alzheimer's Prevention Clinic patients with subjective cognitive decline, mild cognitive impairment, mild dementia due to Alzheimer's disease, and normal cognition. Principal component analysis, partial correlations, and univariate general linear model tests were performed to assess construct validity. Discriminant function analyses compared classification accuracy.ResultsPrincipal component analysis identified three conceptually coherent factors: memory (MEMNIH), executive function (EFNIH), and crystallized intelligence (CINIH). These factors were strongly associated with corresponding traditional tests and differed across diagnostic groups as expected. Both NIHTB and traditional batteries yielded strong overall discriminative ability (>80%).DiscussionThe NIHTB-CB is a valid method to assess neurocognitive domains pertinent to aging and dementia and has utility for applications in a memory clinic setting.
| S-EPMC6247399 | biostudies-literature
Project description:BackgroundAlzheimer's disease (AD) accompanied by psychotic symptoms (PS) has a poor prognosis and may be associated with imbalances in key neural proteins such as alpha-synuclein (AS).AimThe aim of the study was to evaluate the diagnostic validity of AS levels in the cerebrospinal fluid (CSF) as a predictor of the emergence of PS in patients with prodromal AD.Materials and methodsPatients with mild cognitive impairment were recruited between 2010 and 2018. Core AD biomarkers and AS levels were measured in CSF obtained during the prodromal phase of the illness. All patients who met the NIA-AA 2018 criteria for AD biomarkers received treatment with anticholinesterasic drugs. Follow-up evaluations were conducted to assess patients for the presence of psychosis using current criteria; the use of neuroleptic drugs was required for inclusion in the psychosis group. Several comparisons were made, taking into account the timing of the emergence of PS.ResultsA total of 130 patients with prodromal AD were included in this study. Of these, 50 (38.4%) met the criteria for PS within an 8-year follow-up period. AS was found to be a valuable CSF biomarker to differentiate between the psychotic and non-psychotic groups in every comparison made, depending on the onset of PS. Using an AS level of 1,257 pg/mL as the cutoff, this predictor achieved at least 80% sensitivity.ConclusionTo our knowledge, this study represents the first time that a CSF biomarker has shown diagnostic validity for prediction of the emergence of PS in patients with prodromal AD.
| S-EPMC10244520 | biostudies-literature
Project description:BackgroundBlood-based biomarkers for dementia are gaining attention due to their non-invasive nature and feasibility in regular healthcare settings. Here, we explored the associations between 249 metabolites with all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VaD) and assessed their predictive potential.MethodsThis study included 274,160 participants from the UK Biobank. Cox proportional hazard models were employed to investigate longitudinal associations between metabolites and dementia. The importance of these metabolites was quantified using machine learning algorithms, and a metabolic risk score (MetRS) was subsequently developed for each dementia type. We further investigated how MetRS stratified the risk of dementia onset and assessed its predictive performance, both alone and in combination with demographic and cognitive predictors.ResultsDuring a median follow-up of 14.01 years, 5274 participants developed dementia. Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD. Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance. Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile. When MetRS was combined with demographic and cognitive predictors, the model yielded the area under the receiver operating characteristic curve (AUC) values of 0.857 for ACD, 0.861 for AD, and 0.873 for VaD.ConclusionsWe conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.
| S-EPMC10802055 | biostudies-literature
Project description:Amnestic mild cognitive impairment (MCI) is a prodromal stage of dementia, with a higher incidence of these patients progressing to Alzheimer's disease (AD) than normal aging people. A biomarker for the early detection and prediction for this progression is important. We recruited MCI subjects in three teaching hospitals and conducted longitudinal follow-up for 5 years at one-year intervals. Cognitively healthy controls were recruited for comparisom at baseline. Plasma transthyretin (TTR) levels were measured by ELISA. Survival analysis with time to AD conversion as an outcome variable was calculated with the multivariable Cox proportional hazards models using TTR as a continuous variable with adjustment for other covariates and bootstrapping resampling analysis. In total, 184 MCI subjects and 40 sex- and age-matched controls were recruited at baseline. At baseline, MCI patients had higher TTR levels compared with the control group. During the longitudinal follow-ups, 135 MCI patients (73.4%) completed follow-up at least once. The TTR level was an independent predictor for MCI conversion to AD when using TTR as a continuous variable (p = 0.023, 95% CI 1.001-1.007). In addition, in MCI converters, the TTR level at the point when they converted to AD was significantly lower than that at baseline (328.6 ± 66.5 vs. 381.9 ± 77.6 ug/ml, p < 0.001). Our study demonstrates the temporal relationship between the plasma TTR level and the conversion from MCI to AD.
| S-EPMC6904474 | biostudies-literature