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      Identification of candidate genes associated with clinical onset of Alzheimer’s disease

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          Abstract

          Background and objective

          Alzheimer’s disease (AD) is the most common type of dementia, with its pathology like beta-amyloid and phosphorylated tau beginning several years before the clinical onset. The aim is to identify genetic risk factors associated with the onset of AD.

          Methods

          We collected three microarray data of post-mortem brains of AD patients and the healthy from the GEO database and screened differentially expressed genes between AD and healthy control. GO/KEGG analysis was applied to identify AD-related pathways. Then we distinguished differential expressed genes between symptomatic and asymptomatic AD. Feature importance with logistic regression analysis is adopted to identify the most critical genes with symptomatic AD.

          Results

          Data was collected from three datasets, including 184 AD patients and 132 healthy controls. We found 66 genes to be differently expressed between AD and the control. The pathway enriched in the process of exocytosis, synapse, and metabolism and identified 19 candidate genes, four of which (VSNL1, RTN1, FGF12, and ENC1) are vital.

          Conclusion

          VSNL1, RTN1, FGF12, and ENC1 may be the essential genes that progress asymptomatic AD to symptomatic AD. Moreover, they may serve as genetic risk factors to identify high-risk individuals showing an earlier onset of AD.

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          Most cited references30

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          Alzheimer's disease

          In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies.
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            Prevalence and architecture of de novo mutations in developmental disorders

            (2017)
            Summary Individuals with severe, undiagnosed developmental disorders (DDs) are enriched for damaging de novo mutations (DNMs) in developmentally important genes. We exome sequenced 4,293 families with individuals with DDs, and meta-analysed these data with another 3,287 individuals with similar disorders. We show that the most significant factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and parental ages. We identified 94 genes enriched for damaging DNMs, including 14 without previous compelling evidence. We have characterised the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences, and approximately half disrupt gene function, with the remainder resulting in altered-function. We estimate that developmental disorders caused by DNMs have an average birth prevalence of 1 in 213 to 1 in 448, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year.
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              Biomarkers for Alzheimer’s Disease Diagnosis

              Objective: The dramatic increase in the population with dementia expected in the next decades is accompanied by the establishment of novel and innovated methods that will offer accurate and efficient detection of the disease in its early stages. While Alzheimer’s disease is the most common cause of dementia, by the time it is typically diagnosed, substantial neuronal loss and neuropathological lesions can damage many brain regions. The aim of this study is to investigate the main risk factors that affect and increase Alzheimer’s disease progression over time even in cases with no significant memory impairment present. Several potential markers are discussed such as oxidative stress, metal ions, vascular disorders, protein dysfunctions and alterations in the mitochondrial populations. Conclusion: A multiparametric model of Alzheimer’s biomarkers is presented according to the latest classification of the disease.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                20 December 2022
                2022
                : 16
                : 1060111
                Affiliations
                [1] 1Department of Neurology, The Second Affiliated Hospital, Guangzhou Medical University , Guangzhou, China
                [2] 2Department of Rehabilitation, The Second Affiliated Hospital, Guangzhou Medical University , Guangzhou, China
                [3] 3Guangzhou Medical University , Guangzhou, China
                [4] 4School of Basic Medical Sciences, Guangzhou Medical University , Guangzhou, China
                Author notes

                Edited by: Guangzhi Ning, Tianjin Medical University General Hospital, China

                Reviewed by: Li-Ching Wu, National Central University, Taiwan; Jihu Sun, Jiangsu Vocational College of Medicine, China; Wenzhen He, The First Affiliated Hospital of Shantou University Medical College, China; Junliang Yuan, Peking University Sixth Hospital, China

                *Correspondence: Jun Liu, liujun@ 123456gzhmu.edu.cn

                These authors have contributed equally to this work

                This article was submitted to Translational Neuroscience, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2022.1060111
                9808086
                36605552
                35302422-f557-45ce-bd64-59e254aaa5d1
                Copyright © 2022 Liao, Luo, Ruan, Mai, Liu, Chen, Yang, Xuan and Liu.

                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
                : 02 October 2022
                : 30 November 2022
                Page count
                Figures: 5, Tables: 6, Equations: 0, References: 30, Pages: 12, Words: 5749
                Categories
                Neuroscience
                Original Research

                Neurosciences
                alzheimer’s disease,genes,transcriptomic analysis,geo,dementia
                Neurosciences
                alzheimer’s disease, genes, transcriptomic analysis, geo, dementia

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