Dataset Information

Depressive symptoms and CSF Alzheimer's disease biomarkers in relation to clinical symptom onset of mild cognitive impairment.

ABSTRACT:

Introduction

We sought to examine whether depressive symptoms and level of Alzheimer's disease (AD) pathology are independently or interactively associated with the risk of progression to mild cognitive impairment (MCI).

Methods

The study included a total of 216 participants from the Biomarkers for Older Controls at Risk for Alzheimer's Disease study, a cohort of individuals who were cognitively normal at baseline (mean age = 57) and followed for more than 20 years (mean = 12.7 years), who had baseline Hamilton Depression Scale (HAM-D) scores and cerebrospinal fluid (CSF) amyloid beta (Aβ)_1-42 , t-tau, and p-tau measures available.

Results

Cox regression demonstrated that baseline HAM-D and CSF AD biomarkers were both associated with time to onset of MCI. There was an interaction between HAM-D scores and markers of AD pathology, in which depression was associated with time of onset in participants with low levels of AD pathology (hazard ratio = 0.64; 95% confidence interval = 0.43-0.95; P= .026).

Discussion

The effect of depressive symptoms on progression to clinical symptoms of MCI may be most evident among individuals with low levels of AD pathology.

SUBMITTER: Chan CK

PROVIDER: S-EPMC7513625 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Depressive symptoms and CSF Alzheimer's disease biomarkers in relation to clinical symptom onset of mild cognitive impairment.

Chan Carol K CK Soldan Anja A Pettigrew Corinne C Wang Jiangxia J Albert Marilyn M Rosenberg Paul B PB

Alzheimer's & dementia (Amsterdam, Netherlands) 20200924 1

<h4>Introduction</h4>We sought to examine whether depressive symptoms and level of Alzheimer's disease (AD) pathology are independently or interactively associated with the risk of progression to mild cognitive impairment (MCI).<h4>Methods</h4>The study included a total of 216 participants from the Biomarkers for Older Controls at Risk for Alzheimer's Disease study, a cohort of individuals who were cognitively normal at baseline (mean age = 57) and followed for more than 20 years (mean = 12.7 ye ...[more]

PMID: 33005725

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Project description:Research shows that late mild cognitive impairment (LMCI) has a high risk of turning into Alzheimer's disease (AD). Due to the invasion of detection methods and physical damage to the patients, it is not a convenient way to diagnose and detect early AD and LMCI by cerebrospinal fluid (CSF) data. So there is an urgent need to find the correlation between peripheral biological data and CSF data in the brain, and to find new diagnostic methods through changes in the peripheral biological data. Studies have shown that during the pathogenesis of LMCI and AD, peripheral immune cells specifically infiltrate into the brain through the blood-brain barrier, causing an imbalance in the brain's immune response and dysregulating the clearance of Aβ in CSF. Therefore, in this paper, canonical correlation analysis (CCA) algorithm is presented to derive the correlation between peripheral and CSF biomarkers based on LMCI peripheral gene expression data and plasma marker information. Firstly, to explore the influence of the infiltration of peripheral blood immune cells on the brain, the abundance of 28 immune cells were calculated by using the gene set enrichment analysis algorithm of LMCI samples. Then, to identify the correlation between biomarkers inside and outside of the brain, we performed CCA to calculate the relationship between CSF and peripheral biomarkers. Results of CCA showed significant correlations between the variable sets of 8 peripheral biomarkers and the variable sets of CSF biomarkers (at 0.794). Finally, according to Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis, it was found that the obtained peripheral biomarkers are involved in many immune-related pathways and functions which can be activated in peripheral blood of LMCI patients. Most related genes enriched in immune-related pathways and functions were up-regulated. Through receiver operating characteristic curve (ROC) analysis, it was also found that FP40/FP42 and type 1 T helper can accurately predict the pathological changes of LMCI (at 0.747).

Dataset Information

Depressive symptoms and CSF Alzheimer's disease biomarkers in relation to clinical symptom onset of mild cognitive impairment.

Introduction

Methods

Results

Discussion

Publications

Depressive symptoms and CSF Alzheimer's disease biomarkers in relation to clinical symptom onset of mild cognitive impairment.

Similar Datasets

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