scholarly journals A Meta-Analysis of Alzheimer’s Disease Brain Transcriptomic Data

2018 ◽  
Author(s):  
Hamel Patel ◽  
Richard J.B Dobson ◽  
Stephen J Newhouse
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Frontal Lobe ◽  
Temporal Lobe ◽  
Parietal Lobe ◽  
Meta Analysis ◽  
Differential Expression Analysis ◽  
Brain Regions ◽  
Biological Pathways ◽  
Transcriptomic Changes

ABSTRACTBackgroundMicroarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer’s disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations. We are yet to identify robust transcriptomic changes specific to AD brains.Methods and ResultsTwenty-two AD, eight Schizophrenia, five Bipolar Disorder, four Huntington's disease, two Major Depressive Disorder and one Parkinson’s disease dataset totalling 2667 samples and mapping to four different brain regions (Temporal lobe, Frontal lobe, Parietal lobe and Cerebellum) were analysed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction. This identified 323, 435, 1023 and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe and cerebellum brain regions respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. Biological pathways involved in the “metabolism of proteins” and viral components were significantly enriched across AD brains.ConclusionThis study solely relied on publicly available microarray data, which too often lacks appropriate phenotypic information for robust data analysis and needs to be addressed by future studies. Nevertheless, with the information available, we were able to identify specific transcriptomic changes in AD brains which could make a significant contribution towards the understanding of AD disease mechanisms and may also provide new therapeutic targets.

scholarly journals Changes of Regional Neural Activity Homogeneity in Preclinical Alzheimer’s Disease: Compensation and Dysfunction

2021 ◽  
Vol 15 ◽  
Author(s):  
Zhen Zhang ◽  
Liang Cui ◽  
Yanlu Huang ◽  
Yu Chen ◽  
Yuehua Li ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Function ◽  
Frontal Lobe ◽  
Temporal Lobe ◽  
Neural Activity ◽  
Neuropsychological Tests ◽  
Parietal Lobe ◽  
Neuropsychological Test ◽  
Potential Biomarker

IntroductionSubjective cognitive decline (SCD) is the preclinical stage of Alzheimer’s disease and may develop into amnestic mild cognitive impairment (aMCI). Finding suitable biomarkers is the key to accurately identifying SCD. Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies on SCD patients showed functional connectivity disorders. Our goal was to explore whether local neurological homogeneity changes in SCD patients, the relationship between these changes and cognitive function, and similarities of neurological homogeneity changes between SCD and aMCI patients.Materials and Methods37 cases of the healthy control (HC) group, 39 cases of the SCD group, and 28 cases of the aMCI group were included. Participants underwent rs-fMRI examination and a set of neuropsychological test batteries. Regional homogeneity (ReHo) was calculated and compared between groups. ReHo values were extracted from meaningful regions in the SCD group, and the correlation between ReHo values with the performance of neuropsychological tests was analyzed.ResultsOur results showed significant changes in the ReHo among groups. In the SCD group compared with the HC group, part of the parietal lobe, frontal lobe, and occipital lobe showed decreased ReHo, and the temporal lobe, part of the parietal lobe and the frontal lobe showed increased ReHo. The increased area of ReHo was negatively correlated with the decreased area, and was related to decrease on multiple neuropsychological tests performance. Simultaneously, the changed areas of ReHo in SCD patients are similar to aMCI patients, while aMCI group’s neuropsychological test performance was significantly lower than that of the SCD group.ConclusionThere are significant changes in local neurological homogeneity in SCD patients, and related to the decline of cognitive function. The increase of neurological homogeneity in the temporal lobe and adjacent area is negatively correlated with cognitive function, reflecting compensation for local neural damage. These changes in local neurological homogeneity in SCD patients are similar to aMCI patients, suggesting similar neuropathy in these two stages. However, the aMCI group’s cognitive function was significantly worse than that of the SCD group, suggesting that this compensation is limited. In summary, regional neural activity homogeneity may be a potential biomarker for identifying SCD and measuring the disease severity.

Identification of a Pathogenic PSEN1 Ala285Val Mutation Associated with Early-Onset Alzheimer’s Disease

2020 ◽  
Vol 17 (5) ◽  
pp. 438-445
Author(s):  
Van Giau Vo ◽  
Jung-Min Pyun ◽  
Eva Bagyinszky ◽  
Seong S.A. An ◽  
Sang Y. Kim
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Temporal Lobe ◽  
Early Onset ◽  
Parietal Lobe ◽  
Disease Diagnosis ◽  
Random Coil ◽  
Magnetic Resonance Imaging Scan ◽  
Preclinical Ad ◽  
Early Onset Alzheimer’S Disease

Background: Presenilin 1 (PSEN1) was suggested as the most common causative gene of early onset Alzheimer’s Disease (AD). Methods: Patient who presented progressive memory decline in her 40s was enrolled in this study. A broad battery of neuropsychological tests and neuroimaging was applied to make the diagnosis. Genetic tests were performed in the patient to evaluate possible mutations using whole exome sequencing. The pathogenic nature of missense mutation and its 3D protein structure prediction were performed by in silico prediction programs. Results: A pathogenic mutation in PSEN1 (NM_000021.3: c.1027T>C p.Ala285Val), which was found in a Korean EOAD patient. Magnetic resonance imaging scan showed mild left temporal lobe atrophy. Hypometabolism appeared through 18F-fludeoxyglucose Positron Emission Tomography (FDG-PET) scanning in bilateral temporal and parietal lobe, and 18F-Florbetaben-PET (FBB-PET) showed increased amyloid deposition in bilateral frontal, parietal, temporal lobe and hence presumed preclinical AD. Protein modeling showed that the p.Ala285Val is located in the random coil region and could result in extra stress in this region, resulting in the replacement of an alanine residue with a valine. This prediction was confirmed previous in vitro studies that the p.Trp165Cys resulted in an elevated Aβ42/Aβ40 ratio in both COS-1 and HEK293 cell lines compared that of wild-type control. Conclusion: Together, the clinical characteristics and the effect of the mutation would facilitate our understanding of PSEN1 in AD pathogenesis for the disease diagnosis and treatment. Future in vivo study is needed to evaluate the role of PSEN1 p.Ala285Val mutation in AD progression.

scholarly journals Meta-analysis of epigenome-wide association studies in Alzheimer’s disease highlights novel differentially methylated loci across cortex

2020 ◽  
Author(s):  
Rebecca G. Smith ◽  
Ehsan Pishva ◽  
Gemma Shireby ◽  
Adam R. Smith ◽  
Janou A.Y. Roubroeks ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Studies ◽  
Meta Analysis ◽  
Brain Regions ◽  
Braak Stage ◽  
Combine Data ◽  
Online Data ◽  
Data Resource ◽  
Significance Threshold

ABSTRACTEpigenome-wide association studies of Alzheimer’s disease have highlighted neuropathology-associated DNA methylation differences, although existing studies have been limited in sample size and utilized different brain regions. Here, we combine data from six DNA methylomic studies of Alzheimer’s disease (N=1,453 unique individuals) to identify differential methylation associated with Braak stage in different brain regions and across cortex. We identified 236 CpGs in the prefrontal cortex, 95 CpGs in the temporal gyrus and ten CpGs in the entorhinal cortex at Bonferroni significance, with none in the cerebellum. Our cross-cortex meta-analysis (N=1,408 donors) identified 220 CpGs associated with neuropathology, annotated to 121 genes, of which 84 genes had not been previously reported at this significance threshold. We have replicated our findings using two further DNA methylomic datasets consisting of a > 600 further unique donors. The meta-analysis summary statistics are available in our online data resource (www.epigenomicslab.com/ad-meta-analysis/).

scholarly journals Alzheimer's Disease: Metabolic Uncoupling of Associative Brain Regions

1986 ◽  
Vol 13 (S4) ◽  
pp. 540-545 ◽  
Author(s):  
Stanley I. Rapoport ◽  
Barry Horwitz ◽  
James V. Haxby ◽  
Cheryl L. Grady
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Parietal Lobe ◽  
Brain Regions ◽  
Metabolic Abnormalities ◽  
Alzheimer Type ◽  
Positron Emission ◽  
Partial Correlations ◽  
Metabolic Uncoupling ◽  
Parietal Cortices

Abstract:Evidence indicates that Alzheimer's disease (AD) causes functional disconnection of neocortical association areas. In mildly demented AD patients without measurable neocortically-mediated cognitive abnormalities, positron emission tomography demonstrates reduced parietal lobe glucose metabolism and left/right metabolic asymmetries in neocortical association areas. Similar metabolic abnormalities occur in moderately demented patients, but are accompanied by appropriate language and visuospatial discrepancies. Left/right metabolic asymmetries correspond with reduced numbers of partial correlations between metabolic rates in homologous right and left regions, and in the frontal and parietal cortices, indicating metabolic uncoupling among these regions. The affected association regions are those which demonstrate Alzheimer-type neuropathology post-mortem.

scholarly journals A meta-analysis of epigenome-wide association studies in Alzheimer’s disease highlights novel differentially methylated loci across cortex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Rebecca G. Smith ◽  
Ehsan Pishva ◽  
Gemma Shireby ◽  
Adam R. Smith ◽  
Janou A. Y. Roubroeks ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Studies ◽  
Meta Analysis ◽  
Brain Regions ◽  
Braak Stage ◽  
Combine Data ◽  
Online Data ◽  
Data Resource ◽  
Significance Threshold

AbstractEpigenome-wide association studies of Alzheimer’s disease have highlighted neuropathology-associated DNA methylation differences, although existing studies have been limited in sample size and utilized different brain regions. Here, we combine data from six DNA methylomic studies of Alzheimer’s disease (N = 1453 unique individuals) to identify differential methylation associated with Braak stage in different brain regions and across cortex. We identify 236 CpGs in the prefrontal cortex, 95 CpGs in the temporal gyrus and ten CpGs in the entorhinal cortex at Bonferroni significance, with none in the cerebellum. Our cross-cortex meta-analysis (N = 1408 donors) identifies 220 CpGs associated with neuropathology, annotated to 121 genes, of which 84 genes have not been previously reported at this significance threshold. We have replicated our findings using two further DNA methylomic datasets consisting of a further >600 unique donors. The meta-analysis summary statistics are available in our online data resource (www.epigenomicslab.com/ad-meta-analysis/).

scholarly journals Multi-regional Neurodegeneration in Alzheimer’s disease: Meta-analysis and data integration of transcriptomics data

2018 ◽  
Author(s):  
Karbalaei Reza ◽  
Rezaei-Tavirani Mostafa ◽  
Torkzaban Bahareh ◽  
Azimzadeh Sadegh
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Metabolic Pathways ◽  
Analytical Study ◽  
Meta Analysis ◽  
Brain Regions ◽  
Regulatory Pathways ◽  
Transcriptomics Data ◽  
The Brain

AbstractAlzheimer’s disease (AD) is a complex neurodegenerative disease with various deleterious perturbations in regulatory pathways of various brain regions. Thus, it would be critical to understanding the role of different regions of the brain in initiation and progression of AD, However, owing to complex and multifactorial nature of this disease, the molecular mechanism of AD has yet to be fully elucidated. To confront with this challenge, we launched a meta-analytical study of current transcriptomics data in four different regions of the brain in AD (Entorhinal, Hippocampus, Temporal and Frontal) with systems analysis of identifying involved signaling and metabolic pathways. We found different regulatory patterns in Entorhinal and Hippocampus regions to be associated with progression of AD. We also identified shared versus unique biological pathways and critical proteins among different brain regions. ACACB, GAPDH, ACLY, and EGFR were the most important proteins in Entorhinal, Frontal, Hippocampus and Temporal regions, respectively. Moreover, eight proteins including CDK5, ATP5G1, DNM1, GNG3, AP2M1, ALDOA, GPI, and TPI1 were differentially expressed in all four brain regions, among which, CDK5 and ATP5G1 were enriched in KEGG Alzheimer’s disease pathway as well.

scholarly journals COMBINING MACHINE LEARNING WITH AUTOMATED NEMATODE LIFESPAN ANALYSIS TO IDENTIFY MODIFIERS OF ALZHEIMER’S DISEASE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S96-S96
Author(s):  
Joshua Russell ◽  
Matt Kaeberlein
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Meta Analysis ◽  
Brain Regions ◽  
Data Sets ◽  
Data Types ◽  
C Elegans

Abstract Here we present new computational and experimental methods to leverage the gene expression and neuropathology data collected from several large-scale studies of Alzheimer’s disease . These data sets include diverse data types, including transcriptomics, neuropathology phenotypes such as quantification of amyloid beta plaques and tau tangles in different brain regions, as well as assessments of dementia prior to death. This meta-analysis is a complex undertaking because the available data are from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. We have therefore taken neural network and probabilistic computational approaches that reduce the data dimensionality, allowing statistical comparison across all brain samples. These approaches identify gene expression changes that are significantly associated with clinical and neuropathological assessment of Alzheimer’s disease. We then conduct in vivo validation of the genes through genetic screening of C. elegans models of Alzheimer's disease utilizing our automated robotic lifespan analysis platform. This approach allows for the greater leverage of existing Alzheimer’s disease biobank data to identify deep genetic signatures that could help identify new clinical gene-expression markers and pharmacological targets for Alzheimer’s disease.

scholarly journals A core transcriptional signature of human microglia: derivation and utility in describing region-dependent alterations associated with Alzheimer's disease

2018 ◽  
Author(s):  
Anirudh Patir ◽  
Barbarah Shih ◽  
Barry McColl ◽  
Tom Freeman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Phenotypic Diversity ◽  
Meta Analysis ◽  
Gene Signature ◽  
Brain Regions ◽  
Core Gene ◽  
Human Microglia ◽  
Transcriptional Signature ◽  
Health And Disease

Growing recognition of the pivotal role microglia play in neurodegenerative and neuroinflammatory disorders has accentuated the need to better characterize their function in health and disease. Studies in mouse, have applied transcriptome-wide profiling of microglia to reveal key features of microglial ontogeny, functional profile and phenotypic diversity. Whilst similar in many ways, human microglia exhibit clear differences to their mouse counterparts, underlining the need to develop a better understanding of the human microglial profile. On examining published microglia gene signatures, little consistency was observed between studies. Hence, we set out to define a conserved microglia signature of the human central nervous system (CNS), through a comprehensive meta-analysis of existing transcriptomic resources. Nine datasets derived from cells and tissue, isolated from different regions of the CNS across numerous donors, were subjected independently to an unbiased correlation network analysis. From each dataset, a list of coexpressing genes corresponding to microglia was identified. Comparison of individual microglia clusters showed 249 genes highly conserved between them. This core gene signature included all known markers and improves upon published microglial signatures. The utility of this signature was demonstrated by its use in detecting qualitative and quantitative region-specific alterations in aging and Alzheimer's disease. These analyses highlighted the reactive response of microglia in vulnerable brain regions such as the entorhinal cortex and hippocampus, additionally implicating pathways associated with disease progression. We believe this resource and the analyses described here, will support further investigations in the contribution of human microglia towards the CNS in health and disease.

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