Dataset Information

CSF Proteomic Alzheimer's Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals.

ABSTRACT: We recently discovered three distinct pathophysiological subtypes in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics: one with neuronal hyperplasticity, a second with innate immune system activation, and a third subtype with blood-brain barrier dysfunction. It remains unclear whether AD proteomic subtype profiles are a consequence of amyloid aggregation, or might exist upstream from aggregated amyloid. We studied this question in 127 older individuals with intact cognition and normal AD biomarkers in two independent cohorts (EMIF-AD MBD and ADNI). We clustered 705 proteins measured in CSF that were previously related to AD. We identified in these cognitively intact individuals without AD pathology three subtypes: two subtypes were seen in both cohorts (n = 49 with neuronal hyperplasticity and n = 44 with blood-brain barrier dysfunction), and one only in ADNI (n = 12 with innate immune activation). The proteins specific for these subtypes strongly overlapped with AD subtype protein profiles (overlap coefficients 92%-71%). Longitudinal p₁₈₁-tau and amyloid β 1-42 (Aβ42) CSF analysis showed that in the hyperplasticity subtype p₁₈₁-tau increased (β = 2.6 pg/mL per year, p = 0.01) and Aβ42 decreased over time (β = -4.4 pg/mL per year, p = 0.03), in the innate immune activation subtype p₁₈₁-tau increased (β = 3.1 pg/mL per year, p = 0.01) while in the blood-brain barrier dysfunction subtype Aβ42 decreased (β = -3.7 pg/mL per year, p = 0.009). These findings suggest that AD proteomic subtypes might already manifest in cognitively normal individuals and may predispose for AD before amyloid has reached abnormal levels.

SUBMITTER: Tijms BM

PROVIDER: S-EPMC8396164 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Research shows that gamma activity changes in Alzheimer's disease (AD), revealing synaptic pathology and potential therapeutic applications. We aim to explore whether cognitive challenge combined with quantitative EEG (qEEG) can unmask abnormal gamma frequency power in healthy individuals at high risk of developing AD. We analyzed low (30-50 Hz) and high gamma (50-80 Hz) power over six brain regions at EEG sensor level (frontal/central/parietal/left temporal/right temporal/occipital) in a dataset collected from an aging cohort during N-back working memory (WM) testing at two different load conditions (N = 0 or 2). Cognitively healthy (CH) study participants (≥60 years old) of both sexes were divided into two subgroups: normal amyloid/tau ratios (CH-NAT, n = 10) or pathological amyloid/tau (CH-PAT, n = 14) in cerebrospinal fluid (CSF). During low load (0-back) challenge, low gamma is higher in CH-PATs than CH-NATs over frontal and central regions (p = 0.014∼0.032, effect size (Cohen's d) = 0.95∼1.11). However, during high load (2-back) challenge, low gamma is lower in CH-PATs compared to CH-NATs over the left temporal region (p = 0.045, Cohen's d = -0.96), and high gamma is lower over the parietal region (p = 0.035, Cohen's d = -1.02). Overall, our studies show a medium to large negative effect size across the scalp (Cohen's d = -0.51∼-1.02). In addition, low gamma during 2-back is positively correlated with 0-back accuracy over all regions except the occipital region only in CH-NATs (r = 0.69∼0.77, p = 0.0098∼0.027); high gamma during 2-back correlated positively with 0-back accuracy over all regions in CH-NATs (r = 0.68∼0.78, p = 0.007∼0.030); high gamma during 2-back negatively correlated with 0-back response time over parietal, right temporal, and occipital regions in CH-NATs (r = -0.70∼-0.66, p = 0.025∼0.037). We interpret these preliminary results to show: (1) gamma power is compromised in AD-biomarker positive individuals, who are otherwise cognitively healthy (CH-PATs); (2) gamma is associated with WM performance in normal aging (CH-NATs) (most significantly in the frontoparietal region). Our pilot findings encourage further investigations in combining cognitive challenges and qEEG in developing neurophysiology-based markers for identifying individuals in the prodromal stage, to help improving our understanding of AD pathophysiology and the contributions of low- and high-frequency gamma oscillations in cognitive functions.

Project description:Observations in animal models suggest that amyloid can cause network hypersynchrony in the early preclinical phase of Alzheimer's disease (AD). The aim of this study was (a) to obtain evidence of paroxysmal hypersynchrony in cognitively intact subjects (CN) with increased brain amyloid load from task-free fMRI exams using a dynamic analysis approach, (b) to investigate if and how hypersynchrony interferes with memory performance, and (c) to describe its relationship with gray and white matter connectivity. Florbetapir-F18 PET and task-free 3T functional and structural MRI were acquired in 47 CN (age = 70.6 ± 6.6), 17 were amyloid pos (florbetapir SUVR >1.11). A parcellation scheme encompassing 382 regions of interest was used to extract regional gray matter volumes, FA-weighted fiber tracts and regional BOLD signals. Graph analysis was used to characterize the gray matter atrophy profile and the white matter connectivity of each subject. The fMRI data was processed using a combination of sliding windows, graph and hierarchical cluster analysis. Each activity cluster was characterized by identifying strength dispersion (difference between pos and neg strength) their maximal and minimal pos and neg strength rois and by investigating their distribution and association with memory performance and gray and white matter connectivity using spearman rank correlations (FDR p < 0.05). The cluster analysis identified eight different activity clusters. Cluster 8 was characterized by the largest strength dispersion indicating hypersynchrony. Its duration/subject was positively correlated with amyloid load (r = 0.42, p = 0.03) and negatively with memory performance (CVLT delayed recall r = -0.39 p = 0.04). The assessment of the regional strength distribution indicated a functional disconnection between mesial temporal structures and the rest of the brain. White matter connectivity was increased in left lateral and mesial temporal lobe and was positively correlated with strength dispersion in the cross-modality analysis suggesting that it enables widespread hypersynchrony. In contrast, precuneus, gray matter connectivity was decreased in the right fusiform gyrus and negatively correlated with high degrees of strength dispersion suggesting that progressing gray matter atrophy could prevent the generation of paroxysmal hypersynchrony in later stages of the disease.

Project description:BackgroundGrowing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis.MethodsWe performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ42, phosphorylated tau181 (pTau181), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset.ResultsWe identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker.ConclusionsOur study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.

Dataset Information

CSF Proteomic Alzheimer's Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets