Depressive symptoms and CSF Alzheimer's disease biomarkers in relation to clinical symptom onset of mild cognitive impairment
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ABSTRACT:
SUBMITTER: Chan C
PROVIDER: S-EPMC7513625 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Project description:ABSTRACTObjective:There is increasing evidence of an association between depressive symptoms and mild cognitive impairment (MCI) in cross-sectional studies, but the longitudinal association between depressive symptoms and risk of MCI onset is less clear. The authors investigated whether baseline symptom severity of depression was predictive of time to onset of symptoms of MCI.MethodThese analyses included 300 participants from the BIOCARD study, a cohort of individuals who were cognitively normal at baseline (mean age = 57.4 years) and followed for up to 20 years (mean follow-up = 2.5 years). Depression symptom severity was measured using the Hamilton Depression Scale (HAM-D). The authors assessed the association between dichotomous and continuous HAM-D and time to onset of MCI within 7 years versus after 7 years from baseline (reflecting the mean time from baseline to onset of clinical symptoms in the cohort) using Cox regression models adjusted for gender, age, and education.ResultsAt baseline, subjects had a mean HAM-D score of 2.2 (SD = 2.8). Higher baseline HAM-D scores were associated with an increased risk of progression from normal cognition to clinical symptom onset ≤ 7 years from baseline (p = 0.043), but not with progression > 7 years from baseline (p = 0.194). These findings remained significant after adjustment for baseline cognition.ConclusionsThese results suggest that low levels of depressive symptoms may be predictive of clinical symptom onset within approximately 7 years among cognitively normal individuals and may be useful in identifying persons at risk for MCI due to Alzheimer's disease.
| S-EPMC6458104 | biostudies-literature
Project description:ObjectiveThis study evaluated longitudinal CSF biomarker measures collected when participants were cognitively normal to determine the magnitude and time course of biomarker changes before the onset of clinical symptoms in subjects with mild cognitive impairment (MCI).MethodsLongitudinal CSF collection and cognitive assessments were performed on a cohort of 265 participants who were cognitively normal at their baseline assessment and subsequently developed MCI or dementia. CSF ?-amyloid 1-42 (A?1-42), total tau (t-tau), and phosphorylated tau (p-tau) were determined longitudinally. Consensus diagnoses were completed annually. Cox regression analyses were performed, with baseline CSF values and time-dependent rate of change in CSF values as covariates (adjusted by baseline age, race, and education), in relation to time to onset of mild cognitive symptoms.ResultsThe mean time from baseline to onset of mild cognitive symptoms was 5.41 years. Increased risk of progressing from normal cognition to onset of clinical symptoms was associated with baseline values of A?1-42, p-tau, and the ratios of p-tau/A?1-42 and t-tau/A?1-42 (p < 0.002). Additionally, the rate of change in the ratios of t-tau/A?1-42 (p < 0.004) and p-tau/A?1-42 (p < 0.02) was greater among participants who were subsequently diagnosed with MCI.ConclusionsBaseline differences in CSF values were predictive of clinical symptoms that were a harbinger of a diagnosis of MCI more than 5 years before symptom onset, and continue to show longitudinal changes as cognitive symptoms develop, demonstrating that baseline and longitudinal changes in CSF biomarkers are evident during the preclinical phase of Alzheimer disease.
| S-EPMC3821715 | biostudies-literature
Project description:Altered levels of cerebrospinal fluid (CSF) peptides related to Alzheimer's disease (AD) are associated with pathologic AD diagnosis, although cognitively normal subjects can also have abnormal levels of these AD biomarkers. To identify novel CSF biomarkers that distinguish pathologically confirmed AD from cognitively normal subjects and patients with other neurodegenerative disorders, we collected antemortem CSF samples from 66 AD patients and 25 patients with other neurodegenerative dementias followed longitudinally to neuropathologic confirmation, plus CSF from 33 cognitively normal subjects. We measured levels of 151 novel analytes via a targeted multiplex panel enriched in cytokines, chemokines and growth factors, as well as established AD CSF biomarkers (levels of Abeta42, tau and p-tau(181)). Two categories of biomarkers were identified: (1) analytes that specifically distinguished AD (especially CSF Abeta42 levels) from cognitively normal subjects and other disorders; and (2) analytes altered in multiple diseases (NrCAM, PDGF, C3, IL-1alpha), but not in cognitively normal subjects. A multi-prong analytical approach showed AD patients were best distinguished from non-AD cases (including cognitively normal subjects and patients with other neurodegenerative disorders) by a combination of traditional AD biomarkers and novel multiplex biomarkers. Six novel biomarkers (C3, CgA, IL-1alpha, I-309, NrCAM and VEGF) were correlated with the severity of cognitive impairment at CSF collection, and altered levels of IL-1alpha and TECK associated with subsequent cognitive decline in 38 longitudinally followed subjects with mild cognitive impairment. In summary, our targeted proteomic screen revealed novel CSF biomarkers that can improve the distinction between AD and non-AD cases by established biomarkers alone.
| S-EPMC2880811 | biostudies-literature
Project description:Depression has been associated with higher conversion rates from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and may be a marker of prodromal AD that can be used to identify individuals with MCI who are most likely to progress to AD. Thus, we examined the neuroanatomical changes associated with depressive symptoms in MCI.Two-hundred forty-three MCI subjects from the Alzheimer's Disease Neuroimaging Initiative who had brain magnetic resonance imaging scans at baseline and 2-year follow-up were classified into depressed (n = 44), nondepressed with other neuropsychiatric symptoms (n = 93), and no-symptom (NOSYMP; n = 106) groups based on the Neuropsychiatric Inventory Questionnaire. Tensor-based morphometry was used to create individual three-dimensional maps of 2-year brain changes that were compared between groups.Depressed subjects had more frontal (p = .024), parietal (p = .030), and temporal (p = .038) white matter atrophy than NOSYMP subjects. Those whose depressive symptoms persisted over 2 years also had higher conversion to AD and more decline on measures of global cognition, language, and executive functioning compared with stable NOSYMP subjects. Nondepressed with other neuropsychiatric symptoms and NOSYMP groups exhibited no differences in rates of atrophy.Depressive symptoms were associated with greater atrophy in AD-affected regions, increased cognitive decline, and higher rates of conversion to AD. Depression in individuals with MCI may be associated with underlying neuropathological changes, including prodromal AD, and may be a potentially useful clinical marker in identifying MCI patients who are most likely to progress to AD.
| S-EPMC3322258 | biostudies-literature
Project description:Brain atrophy and altered CSF levels of amyloid beta (Abeta(42)) and the microtubule-associated protein tau are potent biomarkers of Alzheimer's disease (AD)-related pathology. However, the relationship between CSF biomarkers and brain morphometry is poorly understood. Thus, we addressed the following questions. (1) Can CSF biomarker levels explain the morphometric differences between normal controls (NC) and patients with mild cognitive impairment (MCI) or AD? (2) How are CSF biomarkers related to atrophy across the brain? (3) How closely are CSF biomarkers and morphometry related to clinical change [clinical dementia rating sum of boxes (CDR-sb)]? Three hundred seventy participants (105 NC, 175 MCI, 90 AD) from the Alzheimer's Disease Neuroimaging Initiative were studied, of whom 309 were followed for 1 year and 176 for 2 years. Analyses were performed across the entire cortical surface, as well as for 30 cortical and subcortical regions of interest. Results showed that CSF biomarker levels could not account for group differences in brain morphometry at baseline but that CSF biomarker levels showed moderate relationships to longitudinal atrophy rates in numerous brain areas, not restricted to medial temporal structures. Baseline morphometry was at least as predictive of atrophy as were CSF biomarkers. Even MCI patients with levels of Abeta(42) comparable with controls and of p-tau lower than controls showed more atrophy than the controls. Morphometry predicted change in CDR-sb better than did CSF biomarkers. These results indicate that morphometric changes in MCI and AD are not secondary to CSF biomarker changes and that the two types of biomarkers yield complementary information.
| S-EPMC2828879 | biostudies-literature
Project description:IntroductionBile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer's disease (AD) including neuroinflammation and amyloid-β deposition.MethodSerum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n = 1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD: cerebrospinal fluid (CSF) biomarkers, atrophy (magnetic resonance imaging), and brain glucose metabolism ([18F]FDG PET).ResultsOf 23 BAs and relevant calculated ratios after quality control procedures, three BA signatures were associated with CSF Aβ1-42 ("A") and three with CSF p-tau181 ("T") (corrected P < .05). Furthermore, three, twelve, and fourteen BA signatures were associated with CSF t-tau, glucose metabolism, and atrophy ("N"), respectively (corrected P < .05).DiscussionThis is the first study to show serum-based BA metabolites are associated with "A/T/N" AD biomarkers, providing further support for a role of BA pathways in AD pathophysiology. Prospective clinical observations and validation in model systems are needed to assess causality and specific mechanisms underlying this association.
| S-EPMC6454538 | biostudies-literature
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).
| S-EPMC7437457 | biostudies-literature
Project description:There is evidence of longitudinal atrophy in posterior brain areas in early-onset Alzheimer's disease (EOAD; aged < 65 years), but no studies have been conducted in an EOAD cohort with fluid biomarkers characterization. We used 3T-MRI and Freesurfer 6.0 to investigate cortical and subcortical gray matter loss at two years in 12 EOAD patients (A + T + N + ) compared to 19 controls (A-T-N-) from the Hospital Clínic Barcelona cohort. We explored group differences in atrophy patterns and we correlated atrophy and baseline CSF-biomarkers levels in EOAD. We replicated the correlation analyses in 14 EOAD (A + T + N + ) and 55 late-onset AD (LOAD; aged ≥ 75 years; A + T + N + ) participants from the Alzheimer's disease Neuroimaging Initiative. We found that EOAD longitudinal atrophy spread with a posterior-to-anterior gradient and beyond hippocampus/amygdala. In EOAD, higher initial CSF NfL levels correlated with higher ventricular volumes at baseline. On the other hand, higher initial CSF Aβ42 levels (within pathological range) predicted higher rates of cortical loss in EOAD. In EOAD and LOAD subjects, higher CSF t-tau values at baseline predicted higher rates of subcortical atrophy. CSF p-tau did not show any significant correlation. In conclusion, posterior cortices, hippocampus and amygdala capture EOAD atrophy from early stages. CSF Aβ42 might predict cortical thinning and t-tau/NfL subcortical atrophy.
| S-EPMC8405839 | biostudies-literature
Project description:A highly sensitive immunoassay, the immunomagnetic reduction, is used to measure several biomarkers for plasma that is related to Alzheimer's disease (AD). These biomarkers include Aβ-40, Aβ-42, and tau proteins. The samples are composed of four groups: healthy controls (n=66), mild cognitive impairment (MCI, n=22), very mild dementia (n=23), and mild-to-serve dementia, all due to AD (n=22). It is found that the concentrations of both Aβ-42 and tau protein for the healthy controls are significantly lower than those of all of the other groups. The sensitivity and the specificity of plasma Aβ-42 and tau protein in differentiating MCI from AD are all around 0.9 (0.88-0.97). However, neither plasma Aβ-42 nor tau-protein concentration is an adequate parameter to distinguish MCI from AD. A parameter is proposed, which is the product of plasma Aβ-42 and tau-protein levels, to differentiate MCI from AD. The sensitivity and specificity are found to be 0.80 and 0.82, respectively. It is concluded that the use of combined plasma biomarkers not only allows the differentiation of the healthy controls and patients with AD in both the prodromal phase and the dementia phase, but it also allows AD in the prodromal phase to be distinguished from that in the dementia phase.
| S-EPMC3867966 | biostudies-other
Project description:AIM:The objective is to develop a semi-mechanistic disease progression model for mild cognitive impairment (MCI) subjects. The model aims to describe the longitudinal progression of ADAS-cog scores from the Alzheimer's disease neuroimaging initiative trial that had data from 198 MCI subjects with cerebrospinal fluid (CSF) information who were followed for 3 years. METHOD:Various covariates were tested on disease progression parameters and these variables fell into six categories: imaging volumetrics, biochemical, genetic, demographic, cognitive tests and CSF biomarkers. RESULTS:CSF biomarkers were associated with both baseline disease score and disease progression rate in subjects with MCI. Baseline disease score was also correlated with atrophy measured using hippocampal volume. Progression rate was also predicted by executive functioning as measured by the Trail B-test. CONCLUSION:CSF biomarkers have the ability to discriminate MCI subjects into sub-populations that exhibit markedly different rates of disease progression on the ADAS-cog scale. These biomarkers can therefore be utilized for designing clinical trials enriched with subjects that carry the underlying disease pathology.
| S-EPMC3555054 | biostudies-literature