Dataset Information

Role of Fluid Biomarkers and PET Imaging in Early Diagnosis and its Clinical Implication in the Management of Alzheimer's Disease.

ABSTRACT: Clinical diagnosis of Alzheimer's disease (AD) is based on symptoms; however, the challenge is to diagnose AD at the preclinical stage with the application of biomarkers and initiate early treatment (still not widely available). Currently, cerebrospinal fluid (CSF) amyloid-? 42 (A?42) and tau are used in the clinical diagnosis of AD; nevertheless, blood biomarkers (A?42 and tau) are less predictive. Amyloid-positron emission tomography (PET) imaging is an advancement in technology that uses approved radioactive diagnostic agents (florbetapir, flutemetamol, or florbetaben) to estimate A? neuritic plaque density in adults with cognitive impairment evaluated for AD and other causes of cognitive decline. There is no cure for AD to date-the disease progression cannot be stopped or reversed; approved pharmacological agents (donepezil, galantamine, and rivastigmine; memantine) provide symptomatic treatment. However, the disease-modifying therapies are promising; aducanumab and CAD106 are in phase III trials for the early stages of AD. In conclusion, core CSF biomarkers reflect pathophysiology of AD in the early and late stages; the application of approved radiotracers have potential in amyloid-PET brain imaging to detect early AD.

SUBMITTER: Hameed S

PROVIDER: S-EPMC7081089 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Role of Fluid Biomarkers and PET Imaging in Early Diagnosis and its Clinical Implication in the Management of Alzheimer's Disease.

Hameed Shahul S Fuh Jong-Ling JL Senanarong Vorapun V Ebenezer Esther Gunaseli M EGM Looi Irene I Dominguez Jacqueline C JC Park Kyung Won KW Karanam Ananda Krishna AK Simon Oliver O

Journal of Alzheimer's disease reports 20200212 1

Clinical diagnosis of Alzheimer's disease (AD) is based on symptoms; however, the challenge is to diagnose AD at the preclinical stage with the application of biomarkers and initiate early treatment (still not widely available). Currently, cerebrospinal fluid (CSF) amyloid-β 42 (Aβ<sub>42</sub>) and tau are used in the clinical diagnosis of AD; nevertheless, blood biomarkers (Aβ<sub>42</sub> and tau) are less predictive. Amyloid-positron emission tomography (PET) imaging is an advancement in tec ...[more]

PMID: 32206755

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Project description:ObjectiveWe analyzed the longitudinal profile of Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in early Parkinson's disease (PD) compared with healthy controls (HCs) and tested baseline CSF biomarkers for prediction of clinical decline in PD.MethodsAmyloid-β 1 to 42 (Aβ42 ), total tau (t-tau) and phosphorylated tau (p-tau) at the threonine 181 position were measured using the high-precision Roche Elecsys electrochemiluminescence immunoassay in all available CSF samples from longitudinally studied patients with PD (n = 416) and HCs (n = 192) followed for up to 3 years in the Parkinson's Progression Markers Initiative (PPMI). Longitudinal CSF and clinical data were analyzed with linear-mixed effects models.ResultsWe found patients with PD had lower CSF t-tau (median = 157.7 pg/mL; range = 80.9-467.0); p-tau (median = 13.4 pg/mL; range = 8.0-40.1), and Aβ42 (median = 846.2 pg/mL; range = 238.8-3,707.0) than HCs at baseline (CSF t-tau median = 173.5 pg/mL; range = 82.0-580.8; p-tau median = 15.4 pg/mL; range = 8.1-73.6; and Aβ42 median = 926.5 pg/mL; range = 239.1-3,297.0; p < 0.05-0.001) and a moderate-to-strong correlation among these biomarkers in both patients with PD and HCs (Rho = 0.50-0.97; p < 0.001). Of the patients with PD, 31.5% had pathologically low levels of CSF Aβ42 at baseline and these patients with PD had lower p-tau levels (median = 10.8 pg/mL; range = 8.0-32.8) compared with 27.7% of HCs with pathologically low CSF Aβ42 (CSF p-tau median = 12.8 pg/mL; range 8.2-73.6; p < 0.03). In longitudinal CSF analysis, we found patients with PD had greater decline in CSF Aβ42 (mean difference = -41.83 pg/mL; p = 0.03) and CSF p-tau (mean difference = -0.38 pg/mL; p = 0.03) at year 3 compared with HCs. Baseline CSF Aβ42 values predicted small but measurable decline on cognitive, autonomic, and motor function in early PD.InterpretationOur data suggest baseline CSF AD biomarkers may have prognostic value in early PD and that the dynamic change of these markers, although modest over a 3-year period, suggest biomarker profiles in PD may deviate from healthy aging. ANN NEUROL 2020;88:574-587.

Project description:Alzheimer's disease (AD), including its mild cognitive impairment (MCI) phase that may or may not progress into the AD, is the most ordinary form of dementia. It is extremely important to correctly identify patients during the MCI stage because this is the phase where AD may or may not develop. Thus, it is crucial to predict outcomes during this phase. Thus far, many researchers have worked on only using a single modality of a biomarker for the diagnosis of AD or MCI. Although recent studies show that a combination of one or more different biomarkers may provide complementary information for the diagnosis, it also increases the classification accuracy distinguishing between different groups. In this paper, we propose a novel machine learning-based framework to discriminate subjects with AD or MCI utilizing a combination of four different biomarkers: fluorodeoxyglucose positron emission tomography (FDG-PET), structural magnetic resonance imaging (sMRI), cerebrospinal fluid (CSF) protein levels, and Apolipoprotein-E (APOE) genotype. The Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset was used in this study. In total, there were 158 subjects for whom all four modalities of biomarker were available. Of the 158 subjects, 38 subjects were in the AD group, 82 subjects were in MCI groups (including 46 in MCIc [MCI converted; conversion to AD within 24 months of time period], and 36 in MCIs [MCI stable; no conversion to AD within 24 months of time period]), and the remaining 38 subjects were in the healthy control (HC) group. For each image, we extracted 246 regions of interest (as features) using the Brainnetome template image and NiftyReg toolbox, and later we combined these features with three CSF and two APOE genotype features obtained from the ADNI website for each subject using early fusion technique. Here, a different kernel-based multiclass support vector machine (SVM) classifier with a grid-search method was applied. Before passing the obtained features to the classifier, we have used truncated singular value decomposition (Truncated SVD) dimensionality reduction technique to reduce high dimensional features into a lower-dimensional feature. As a result, our combined method achieved an area under the receiver operating characteristic (AU-ROC) curve of 98.33, 93.59, 96.83, 94.64, 96.43, and 95.24% for AD vs. HC, MCIs vs. MCIc, AD vs. MCIs, AD vs. MCIc, HC vs. MCIc, and HC vs. MCIs subjects which are high relative to single modality results and other state-of-the-art approaches. Moreover, combined multimodal methods have improved the classification performance over the unimodal classification.

Dataset Information

Role of Fluid Biomarkers and PET Imaging in Early Diagnosis and its Clinical Implication in the Management of Alzheimer's Disease.

Publications

Role of Fluid Biomarkers and PET Imaging in Early Diagnosis and its Clinical Implication in the Management of Alzheimer's Disease.

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