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      Low-Density Lipoprotein Cholesterol and Alzheimer's Disease: A Systematic Review and Meta-Analysis

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          Abstract

          Objective: To assess the association between low-density lipoprotein cholesterol (LDL-c) and risk of Alzheimer's disease (AD).

          Methods: Embase, Pubmed, and Web of Science were searched until June 2019. Standard mean difference (SMD) with 95% confidence intervals (CI) was estimated using random-effects models.

          Results: Our meta-analysis of 26 studies revealed higher levels of LDL-c in AD than that of non-dementia controls (SMD = 0.35, 95% CI 0.12–0.58, p < 0.01). The meta-regression analysis on confounders showed that age ( p < 0.01, Adj R-squared = 92.41%) and cardiovascular disease ( p = 0.01, Adj R-squared = 85.21%), but not the body mass index, education, smoking, hypertension and diabetes mellitus, exerted an impact on the relationship between LDL-c and risk of ICH. Further subgroup analysis of age showed LDL-c levels in AD patients aged 60–70 were higher than that of non-dementia (60 ≤ age < 70: SMD = 0.80, 95% CI 0.23–1.37, p < 0.01); but no association between the SMD of AD in LDL-c and age over 70 was noted across the studies (70 ≤ age < 77: SMD = −0.02, 95% CI −0.39~0.34, p = 9.0; 77 ≤ age < 80: SMD = 0.15, 95% CI −0.17~0.47, p = 0.35; ≥80: SMD = 0.53, 95% CI −0.04~1.11, p = 0.07). The concentrations of LDL-c during the quintile interval of 3~4 were positively associated with AD (121 ≤ concentration < 137: SMD = 0.98, 95% CI 0.13~1.82, p = 0.02; ≥137: SMD = 0.62, 95% CI 0.18~1.06, p < 0.01); whereas there was no correlation between AD and LDL-c within the quintile interval of 1~2 (103.9 ≤ concentration < 112: SMD = 0.08, 95% CI −0.20~0.35, p = 0.59; 112 ≤ concentration < 121: SMD = −0.26, 95% CI −0.58~0.06, p = 0.11).

          Conclusions: Elevated concentration of LDL-c (>121 mg/dl) may be a potential risk factor for AD. This association is strong in patients aged 60–70 years, but vanishes with advancing age.

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          Most cited references47

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          Convergence of atherosclerosis and Alzheimer's disease: inflammation, cholesterol, and misfolded proteins.

          Late-onset sporadic Alzheimer's disease is a heterogeneous disorder. In elderly patients, increasing evidence suggests a link between this neurodegenerative disease, and vascular risk factors and atherosclerosis. The nature of this link remains speculative. Some investigators have suggested that the disease arises as a secondary event related to atherosclerosis of extracranial or intracranial vessels. A toxic effect of vascular factors on the microvasculature of susceptible brain regions has also been argued. An alternative explanation is that atherosclerosis and Alzheimer's disease are independent but convergent disease processes. This hypothesis is lent support by observations of shared epidemiology, pathophysiological elements, and response to treatment in both disorders. It provides a potential framework for an improved understanding of the pathogenesis of Alzheimer's disease, especially in elderly patients with vascular risk factors, and offers some promise toward the search for preventive and therapeutic treatments.
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            Relation of plasma lipids to Alzheimer disease and vascular dementia.

            The relation between plasma lipid levels and Alzheimer disease (AD) and vascular dementia (VaD), and the impact of drugs to lower lipid levels remains unclear. To investigate the relation between plasma lipid levels and the risk of AD and VaD and the impact of drugs to lower lipid levels on this relationship. Cross-sectional and prospective community-based cohort studies. Random sample of 4316 Medicare recipients, 65 years and older, residing in northern Manhattan, NY. Vascular dementia and AD according to standard criteria. Elevated levels of non-high-density lipoprotein (HDL-C) and low-density lipoprotein cholesterol (LDL-C) and decreased levels of HDL-C were weak risk factors for VaD in either cross-sectional or prospective analyses. Higher levels of total cholesterol were associated with a decreased risk of incident AD after adjustment for demographics, apolipoprotein E genotype, and cardiovascular risk factors. Treatment with drugs to lower lipid levels did not change the disease risk of either disorder. We found a weak relation between non-HDL-C, LDL-C, and HDL-C levels and the risk of VaD. Lipid levels and the use of agents to lower them do not seem to be associated with the risk of AD.
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              Association of Extracellular Vesicle Biomarkers With Alzheimer Disease in the Baltimore Longitudinal Study of Aging

              This case-control study examines neuronal-enriched extracellular vesicles as predictors of Alzheimer disease. Can blood extracellular vesicle biomarkers diagnose Alzheimer disease at the preclinical and clinical stages? In a large case-control study examining 887 longitudinal samples from 128 Baltimore Longitudinal Study of Aging participants (split into training and test sets), combining extracellular vesicle biomarkers predicted Alzheimer disease with high discrimination accuracy and specificity about 4 years before symptom onset; individual biomarkers were associated with cognitive performance. Biomarkers were further validated in a case-control cohort from Johns Hopkins. Further development of extracellular vesicle biomarkers may establish them as a blood test for Alzheimer disease. Blood biomarkers able to diagnose Alzheimer disease (AD) at the preclinical stage would enable trial enrollment when the disease is potentially reversible. Plasma neuronal-enriched extracellular vesicles (nEVs) of patients with AD were reported to exhibit elevated levels of phosphorylated (p) tau, Aβ42, and phosphorylated insulin receptor substrate 1 (IRS-1). To validate nEV biomarkers as AD predictors. This case-control study included longitudinal plasma samples from cognitively normal participants in the Baltimore Longitudinal Study of Aging (BLSA) cohort who developed AD up to January 2015 and age- and sex-matched controls who remained cognitively normal over a similar length of follow-up. Repeated samples were blindly analyzed over 1 year from participants with clinical AD and controls from the Johns Hopkins Alzheimer Disease Research Center (JHADRC). Data were collected from September 2016 to January 2018. Analyses were conducted in March 2019. Neuronal-enriched extracellular vesicles were immunoprecipitated; tau, Aβ42, and IRS-1 biomarkers were quantified by immunoassays; and nEV concentration and diameter were determined by nanoparticle tracking analysis. Levels and longitudinal trajectories of nEV biomarkers between participants with future AD and control participants were compared. Overall, 887 longitudinal plasma samples from 128 BLSA participants who eventually developed AD and 222 age and sex-matched controls who remained cognitively normal were analyzed. Participants were followed up (from earliest sample to AD symptom onset) for a mean (SD) of 3.5 (2.31) years (range, 0-9.73 years). Overall, 161 participants were included in the training set, and 80 were in the test set. Participants in the BLSA cohort with future AD (mean [SD] age, 79.09 [7.02] years; 68 women [53.13%]) had longitudinally higher p-tau181, p-tau231, pSer312-IRS-1, pY-IRS-1, and nEV diameter than controls (mean [SD] age, 76.2 [7.36] years; 110 women [50.45%]) but had similar Aβ42, total tau, TSG101, and nEV concentration. In the training BLSA set, a model combining preclinical longitudinal data achieved 89.6% area under curve (AUC), 81.8% sensitivity, and 85.8% specificity for predicting AD. The model was validated in the test BLSA set (80% AUC, 55.6% sensitivity, 88.7% specificity). Preclinical levels of nEV biomarkers were associated with cognitive performance. In addition, 128 repeated samples over 1 year from 64 JHADRC participants with clinical AD and controls were analyzed. In the JHADRC cohort (35 participants with AD: mean [SD] age, 74.03 [8.73] years; 18 women [51.43%] and 29 controls: mean [SD] age, 72.14 [7.86] years; 23 women [79.31%]), nEV biomarkers achieved discrimination with 98.9% AUC, 100% sensitivity, and 94.7% specificity in the training set and 76.7% AUC, 91.7% sensitivity, and 60% specificity in the test set. We validated nEV biomarker candidates and further demonstrated that their preclinical longitudinal trajectories can predict AD diagnosis. These findings motivate further development of nEV biomarkers toward a clinical blood test for AD.
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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                30 January 2020
                2020
                : 12
                : 5
                Affiliations
                [1] 1Department of Geriatrics, The First Affiliated Hospital, China Medical University , Shenyang, China
                [2] 2Department of Neurology, The First Affiliated Hospital, China Medical University , Shenyang, China
                [3] 3Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University , Shenyang, China
                [4] 4Department of Emergency, Zhongshan Hospital Xiamen University , Xiamen, China
                [5] 5Department of Cardiology, The Shengjing Affiliated Hospital, China Medical University , Shenyang, China
                Author notes

                Edited by: Kenjiro Ono, Showa University, Japan

                Reviewed by: Vasileios-Arsenios Lioutas, Harvard Medical School, United States; Hayato Tada, Kanazawa University, Japan

                *Correspondence: Chuansheng Zhao cszhao@ 123456mail.cmu.edu.cn
                Article
                10.3389/fnagi.2020.00005
                7002548
                32082137
                067e41a7-4c5f-4dda-b963-2841d96cda5a
                Copyright © 2020 Zhou, Liang, Zhang, Xu, Lin, Zhang, Kang, Liu, Zhao and Zhao.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 October 2019
                : 09 January 2020
                Page count
                Figures: 5, Tables: 3, Equations: 0, References: 72, Pages: 11, Words: 7797
                Categories
                Neuroscience
                Systematic Review

                Neurosciences
                ldl-c,alzheimer's disease,risk factor,meta-analysis,association
                Neurosciences
                ldl-c, alzheimer's disease, risk factor, meta-analysis, association

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