Dataset Information

CCL23: A Chemokine Associated with Progression from Mild Cognitive Impairment to Alzheimer's Disease.

ABSTRACT: CCL23 is a chemokine implicated in inflammation and host defense responses. It has been recently associated with acquired brain damage and stroke outcomes. In this study, we reported the role of CCL23 in Alzheimer's disease (AD). We evaluated the levels of CCL23 in 659 individuals: cognitively normal, mild cognitive impaired (MCI), and AD patients. Two cross-sectional (study 1, n = 53; study 2, n = 200) and two longitudinal (study 3, n = 74; study 4, n = 332) studies were analyzed separately. CCL23 levels in the blood and/or cerebrospinal fluid (CSF) of each study were measured by immunoassays. Globally, our results suggest a predictive role of CCL23 protein levels both in the plasma in study 3 (hazard ratio (HR) = 2.5 (confidence interval (CI) 95% : 1.2-5.3), p = 0.02) and in the CSF in study 4 (HR = 3.05 (CI 95% : 1.02-5), p = 0.04) in cases of MCI that progress to AD. Moreover, we observed that the APOEɛ4 allele was associated with higher levels of CCL23 in study 2 (470.33 pg/mL (interquartile range (IQR): 303.33-597.76) versus 377.94 pg/mL (IQR: 267.16-529.19), p = 0.01) (APOE genotypes were available in studies 2 and 4). Together, these findings support the role of CCL23 in neuroinflammation in the early stages of AD, suggesting that CCL23 might be a candidate blood biomarker for MCI to AD progression.

SUBMITTER: Faura J

PROVIDER: S-EPMC8010612 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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CCL23: A Chemokine Associated with Progression from Mild Cognitive Impairment to Alzheimer's Disease.

Faura Júlia J Bustamante Alejandro A Penalba Anna A Giralt Dolors D Simats Alba A Martínez-Sáez Elena E Alcolea Daniel D Fortea Juan J Lleó Alberto A Teunissen Charlotte E CE van der Flier Wiesje M WM Ibañez Laura L Harari Oscar O Cruchaga Carlos C Hernández-Guillamón Mar M Delgado Pilar P Montaner Joan J

Journal of Alzheimer's disease : JAD 20200101 4

CCL23 is a chemokine implicated in inflammation and host defense responses. It has been recently associated with acquired brain damage and stroke outcomes. In this study, we reported the role of CCL23 in Alzheimer's disease (AD). We evaluated the levels of CCL23 in 659 individuals: cognitively normal, mild cognitive impaired (MCI), and AD patients. Two cross-sectional (study 1, n = 53; study 2, n = 200) and two longitudinal (study 3, n = 74; study 4, n = 332) studies were analyzed separately. CC ...[more]

PMID: 31958084

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Project description:Predicting progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) is clinically important. In this study, we propose a dual-model radiomic analysis with multivariate Cox proportional hazards regression models to investigate promising risk factors associated with MCI conversion to AD. T1 structural magnetic resonance imaging (MRI) and 18F-Fluorodeoxyglucose (FDG) positron emission tomography (PET) data, from the AD Neuroimaging Initiative database, were collected from 131 patients with MCI who converted to AD within 3 years and 132 patients with MCI without conversion within 3 years. These subjects were randomly partition into 70% training dataset and 30% test dataset with multiple times. We fused MRI and PET images by wavelet method. In a subset of subjects, a group comparison was performed using a two-sample t-test to determine regions of interest (ROIs) associated with MCI conversion. 172 radiomic features from ROIs for each individual were established using a published radiomics tool. Finally, L1-penalized Cox model was constructed and Harrell's C index (C-index) was used to evaluate prediction accuracy of the model. To evaluate the efficacy of our proposed method, we used a same analysis framework to evaluate MRI and PET data separately. We constructed prognostic Cox models with: clinical data, MRI images, PET images, fused MRI/PET images, and clinical variables and fused MRI/PET images in combination. The experimental results showed that captured ROIs significantly associated with conversion to AD, such as gray matter atrophy in the bilateral hippocampus and hypometabolism in the temporoparietal cortex. Imaging model (MRI/PET/fused) provided significant enhancement in prediction of conversion compared to clinical models, especially the fused-modality Cox model. Moreover, the combination of fused-modality imaging and clinical variables resulted in the greatest accuracy of prediction. The average C-index for the clinical/MRI/PET/fused/combined model in the test dataset was 0.69, 0.73, 0.73 and 0.75, and 0.78, respectively. These results suggested that a combination of radiomic analysis and Cox model analyses could be used successfully in survival analysis and may be powerful tools for personalized precision medicine patients with potential to undergo conversion from MCI to AD.

Project description:IntroductionHeterogeneity in risk of conversion to Alzheimer's disease (AD) among individuals with mild cognitive impairment (MCI) is well known. Novel statistical methods that are based on partially ordered set (poset) models can be used to create models that provide detailed and accurate information about performance with specific cognitive functions. This approach allows for the study of direct links between specific cognitive functions and risk of conversion to AD from MCI. It also allows for further delineation of multi-domain amnestic MCI, in relation to specific non-amnestic cognitive deficits, and the modeling of a range of episodic memory functioning levels.MethodsFrom the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, conversion at 24 months of 268 MCI subjects was analyzed. It was found that 101 of those subjects (37.7%) converted to AD within that time frame. Poset models were then used to classify cognitive performance for MCI subjects. Respective observed conversion rates to AD were calculated for various cognitive subgroups, and by APOE e4 allele status. These rates were then compared across subgroups.ResultsThe observed conversion rate for MCI subjects with a relatively lower functioning with a high level of episodic memory at baseline was 61.2%. In MCI subjects who additionally also had relatively lower perceptual motor speed functioning and at least one APOE e4 allele, the conversion rate was 84.2%. In contrast, the observed conversion rate was 9.8% for MCI subjects with a relatively higher episodic memory functioning level and no APOE e4 allele. Relatively lower functioning with cognitive flexibility and perceptual motor speed by itself also appears to be associated with higher conversion rates.ConclusionsAmong MCI subjects, specific baseline cognitive profiles that were derived through poset modeling methods, are clearly associated with differential rates of conversion to AD. More precise delineation of MCI by such cognitive functioning profiles, including notions such as multidomain amnestic MCI, can help in gaining further insight into how heterogeneity arises in outcomes. Poset-based modeling methods may be useful for providing more precise classification of cognitive subgroups among MCI for imaging and genetics studies, and for developing more efficient and focused cognitive test batteries.

Dataset Information

CCL23: A Chemokine Associated with Progression from Mild Cognitive Impairment to Alzheimer's Disease.

Publications

CCL23: A Chemokine Associated with Progression from Mild Cognitive Impairment to Alzheimer's Disease.

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