scholarly journals Inflammatory gene expression profiling in peripheral blood from patients with Alzheimer’s disease reveals key pathways and hub genes with potential diagnostic utility: a preliminary study

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12016
Author(s):  
Kelly Cardona ◽  
Javier Medina ◽  
Mary Orrego-Cardozo ◽  
Francia Restrepo de Mejía ◽  
Xabier Elcoroaristizabal ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Alzheimer Disease ◽  
Peripheral Blood ◽  
Map Kinases ◽  
Function Analysis ◽  
Expression Profiles ◽  
Rna Expression ◽  
Preliminary Study

Background Alzheimer’s disease (AD) is an age-related neurodegenerative disease caused by central nervous system disorders. Late-onset Alzheimer disease (LOAD) is the most common neurodegenerative disorder worldwide. Differences at the expression level of certain genes, resulting from either genetic variations or environmental interactions, might be one of the mechanisms underlying differential risks for developing AD. Peripheral blood genome transcriptional profiling may provide a powerful and minimally invasive tool for the identification of novel targets beyond Aβ and tau for AD research. Methods This preliminary study explores molecular pathogenesis of LOAD-related inflammation through next generation sequencing, to assess RNA expression profiles in peripheral blood from five patients with LOAD and 10 healthy controls. Results The analysis of RNA expression profiles revealed 94 genes up-regulated and 147 down-regulated. Gene function analysis, including Gene Ontology (GO) and KOBAS-Kyoto Encyclopedia of DEGs and Genomes (KEGG) pathways indicated upregulation of interferon family (INF) signaling, while the down-regulated genes were mainly associated with the cell cycle process. KEGG metabolic pathways mapping showed gene expression alterations in the signaling pathways of JAK/STAT, chemokines, MAP kinases and Alzheimer disease. The results of this preliminary study provided not only a comprehensive picture of gene expression, but also the key processes associated with pathology for the regulation of neuroinflammation, to improve the current mechanisms to treat LOAD.

Comprehensive Analysis of Differential Expression Profiles of Long Non-coding RNAs with Associated Co-expression and Competing Endogenous RNA Networks in the Hippocampus of Patients with Alzheimer's Disease

2021 ◽  
Vol 18 ◽  
Author(s):  
Jian-Jun Zhang ◽  
Ze-Xuan-Zhu ◽  
Guang-Min-Xu ◽  
Peng Su ◽  
Qian Lei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
Competing Endogenous Rna ◽  
Pathogenic Genes ◽  
Non Coding Rna ◽  
Using Data ◽  
Trans Regulation

Background: Alzheimer's disease (AD) is still one of the major threats to human health. Although a satisfactory treatment for AD has not yet been discovered, it is necessary to continue to search for novel approaches to deal with this insidious and debilitating disease. Although numerous studies have shown that long non-coding RNA (lncRNA) occupy a significant role in a variety of diseases, their roles in AD remain unclear. Objectives: Using data analysis to explore the role of lncRNA in the course of AD, to further our understanding of AD, and to look forward to finding a new breakthrough for the treatment of AD. Methods: We downloaded and screened expression data of the hippocampal regions of patients with AD from the Gene Expression Omnibus database. We generated lncRNA-miRNA-mRNA networks based on the competing endogenous RNA (ceRNA) hypothesis, and according to gene expression level, we constructed a coding-noncoding co-expression (CNC) network and then executed cis- and trans-regulation analyses. Results: Through comprehensive and systematic analyses, we found that lncRNAs MALAT1, OIP5-AS1, LINC00657, and lnc-NUMB-1 regulated the expression of the key AD pathogenic genes APP, PSEN1, BACE1; and that these lncRNAs may promote the distribution of β-amyloid (Aβ protein) in the brain through exosomes. In addition, lncRNAs were found to adjust viral transcriptional expression, thereby further supporting viral pathogenesis for AD. Conclusions: The lncRNAs MALAT1, OIP5-AS1, LINC00657, and lnc-NUMB-1 that are present in the hippocampus of AD patients exert an important influence on the development of this disease.

Muscarinic Receptors Expression in the Peripheral Blood Cells Differentiate Dementia with Lewy Bodies from Alzheimer’s Disease

2021 ◽  
pp. 1-8
Author(s):  
Marcella Reale ◽  
Claudia Carrarini ◽  
Mirella Russo ◽  
Fedele Dono ◽  
Laura Ferri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Dementia With Lewy Bodies ◽  
Mononuclear Cells ◽  
Lewy Bodies ◽  
Acetylcholinesterase Inhibitors ◽  
Operating Characteristics ◽  
Peripheral Blood Mononuclear

Background: Central nervous system disruption of cholinergic (ACh) signaling, which plays a major role in cognitive processes, is well documented in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). The expression of muscarinic ACh receptors type 1 and 4 (CHRM1 and CHRM4) has been reported to be altered in the brain of DLB patients. Objective: We aim to assess the peripheral gene expression of CHRM1 and 4 in DLB as a possible marker as compared to AD and healthy control (HC) subjects. Methods: Peripheral blood mononuclear cells were collected from 21 DLB, 13 AD, and 8 HC matched subjects. RT-PCR was performed to estimate gene expression of CHRM1 and CHRM4. Results: Peripheral CHRM1 expression was higher and CHRM4 was lower in DLB and AD compared to HC, whereas both CHRM1 and CHRM4 levels were higher in AD compared to DLB patients. Receiver operating characteristics curves, with logistic regression analysis, showed that combining peripheral CHRM1 and CHRM4 levels, DLB and AD subjects were classified with an accuracy of 76.0%. Conclusion: Alterations of peripheral CHRM1 and CHRM4 was found in both AD and DLB patients as compared to HC. CHRM1 and CHRM4 gene expression resulted to be lower in DLB patients compared to AD. In the future, peripheral CHRM expression could be studied as a possible marker of neurodegenerative conditions associated with cholinergic deficit and a possible marker of response to acetylcholinesterase inhibitors.

Gene expression profiles of metabolic enzyme transcripts in Alzheimer's disease

2007 ◽  
Vol 1127 ◽  
pp. 127-135 ◽  
Author(s):  
Wendy M. Brooks ◽  
Patrick J. Lynch ◽  
Catherine C. Ingle ◽  
Alexander Hatton ◽  
Piers C. Emson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Metabolic Enzyme

Gene Expression Profiles of Entorhinal Cortex in Alzheimer’s Disease

2014 ◽  
Vol 29 (6) ◽  
pp. 526-532 ◽  
Author(s):  
Bingqian Ding ◽  
Yan Xi ◽  
Ming Gao ◽  
Zhenjiang Li ◽  
Chenyang Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Entorhinal Cortex ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Altered neuronal gene expression in brain regions differentially affected by Alzheimer's disease: a reference data set

2008 ◽  
Vol 33 (2) ◽  
pp. 240-256 ◽  
Author(s):  
Winnie S. Liang ◽  
Travis Dunckley ◽  
Thomas G. Beach ◽  
Andrew Grover ◽  
Diego Mastroeni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Expression Profiles ◽  
Brain Regions ◽  
Elderly Persons ◽  
Data Set ◽  
Healthy Elderly ◽  
Neuronal Gene ◽  
Laser Capture

Alzheimer's Disease (AD) is the most widespread form of dementia during the later stages of life. If improved therapeutics are not developed, the prevalence of AD will drastically increase in the coming years as the world's population ages. By identifying differences in neuronal gene expression profiles between healthy elderly persons and individuals diagnosed with AD, we may be able to better understand the molecular mechanisms that drive AD pathogenesis, including the formation of amyloid plaques and neurofibrillary tangles. In this study, we expression profiled histopathologically normal cortical neurons collected with laser capture microdissection (LCM) from six anatomically and functionally discrete postmortem brain regions in 34 AD-afflicted individuals, using Affymetrix Human Genome U133 Plus 2.0 microarrays. These regions include the entorhinal cortex, hippocampus, middle temporal gyrus, posterior cingulate cortex, superior frontal gyrus, and primary visual cortex. This study is predicated on previous parallel research on the postmortem brains of the same six regions in 14 healthy elderly individuals, for which LCM neurons were similarly processed for expression analysis. We identified significant regional differential expression in AD brains compared with control brains including expression changes of genes previously implicated in AD pathogenesis, particularly with regard to tangle and plaque formation. Pinpointing the expression of factors that may play a role in AD pathogenesis provides a foundation for future identification of new targets for improved AD therapeutics. We provide this carefully phenotyped, laser capture microdissected intraindividual brain region expression data set to the community as a public resource.

scholarly journals Functional Genetic Biomarkers of Alzheimer’s Disease and Gene Expression from Peripheral Blood

2021 ◽  
Author(s):  
Andrew Ni ◽  
Amish Sethi ◽  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Genetic Variants ◽  
Cell Activation ◽  
Association Studies ◽  
Gene Set Enrichment Analysis ◽  
Machine Learning Techniques ◽  
Genome Wide Association Studies

AbstractDetecting Alzheimer’s Disease (AD) at the earliest possible stage is key in advancing AD prevention and treatment but is challenged by normal aging processes in addition to other confounding neurodegenerative diseases. Recent genome-wide association studies (GWAS) have identified associated alleles, but it has been difficult to transition from non-coding genetic variants to underlying mechanisms of AD. Here, we sought to reveal functional genetic variants and diagnostic biomarkers underlying AD using machine learning techniques. We first developed a Random Forest (RF) classifier using microarray gene expression data sampled from the peripheral blood of 744 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. After initial feature selection, 5-fold cross-validation of the 100-gene RF classifier achieved an accuracy of 99.04%. The high accuracy of the RF classifier supports the possibility of a powerful and minimally invasive tool for screening of AD. Next, unsupervised clustering was used to validate and identify relationships among differentially expressed genes (DEGs) the RF selected revealing 3 distinct AD clusters. Results suggest downregulation of global sulfatase and oxidoreductase activities in AD through mutations in SUMF1 and SMOX respectively. Then, we used Greedy Fast Causal Inference (GFCI) to find potential causes of AD within DEGs. In the causal graph, HLA-DPB1 and CYP4A11 emerge as hub genes, furthering the discussion of the immune system’s role in AD. Finally, we used Gene Set Enrichment Analysis (GSEA) to determine the biological pathways and processes underlying the DEGs that were highly correlated with AD. Cell activation in the immune system, glycosaminoglycan (GAG) binding, vascular dysfunction, oxidative stress, and the neuronal apoptotic process were revealed to be significantly enriched in AD. This study further advances the possibility of low-cost and noninvasive genetic screening for AD while also providing potential gene targets for further experimentation.

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