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.

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 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 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 A transcriptional signature of Alzheimer’s disease is associated with a metastable subproteome at risk for aggregation

2016 ◽  
Vol 113 (17) ◽  
pp. 4753-4758 ◽  
Author(s):  
Prajwal Ciryam ◽  
Rishika Kundra ◽  
Rosie Freer ◽  
Richard I. Morimoto ◽  
Christopher M. Dobson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Meta Analysis ◽  
Protein Homeostasis ◽  
Human Central Nervous System ◽  
Transcriptional Signature ◽  
Biochemical Pathways ◽  
Transcriptional Changes ◽  
Cellular Dysfunction

It is well-established that widespread transcriptional changes accompany the onset and progression of Alzheimer’s disease. Because of the multifactorial nature of this neurodegenerative disorder and its complex relationship with aging, however, it remains unclear whether such changes are the result of nonspecific dysregulation and multisystem failure or instead are part of a coordinated response to cellular dysfunction. To address this problem in a systematic manner, we performed a meta-analysis of about 1,600 microarrays from human central nervous system tissues to identify transcriptional changes upon aging and as a result of Alzheimer’s disease. Our strategy to discover a transcriptional signature of Alzheimer’s disease revealed a set of down-regulated genes that encode proteins metastable to aggregation. Using this approach, we identified a small number of biochemical pathways, notably oxidative phosphorylation, enriched in proteins vulnerable to aggregation in control brains and encoded by genes down-regulated in Alzheimer’s disease. These results suggest that the down-regulation of a metastable subproteome may help mitigate aberrant protein aggregation when protein homeostasis becomes compromised in Alzheimer’s disease.

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 Brain CHID1 Expression Correlates with NRGN and CALB1 in Healthy Subjects and AD Patients

Cells ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 882
Author(s):  
Paola Castrogiovanni ◽  
Cristina Sanfilippo ◽  
Rosa Imbesi ◽  
Grazia Maugeri ◽  
Debora Lo Furno ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Calcium Binding ◽  
Meta Analysis ◽  
Inverse Correlation ◽  
Brain Regions ◽  
Brain Disorder ◽  
Expression Levels ◽  
Healthy Control ◽  
The Brain

Alzheimer’s disease is a progressive, devastating, and irreversible brain disorder that, day by day, destroys memory skills and social behavior. Despite this, the number of known genes suitable for discriminating between AD patients is insufficient. Among the genes potentially involved in the development of AD, there are the chitinase-like proteins (CLPs) CHI3L1, CHI3L2, and CHID1. The genes of the first two have been extensively investigated while, on the contrary, little information is available on CHID1. In this manuscript, we conducted transcriptome meta-analysis on an extensive sample of brains of healthy control subjects (n = 1849) (NDHC) and brains of AD patients (n = 1170) in order to demonstrate CHID1 involvement. Our analysis revealed an inverse correlation between the brain CHID1 expression levels and the age of NDHC subjects. Significant differences were highlighted comparing CHID1 expression of NDHC subjects and AD patients. Exclusive in AD patients, the CHID1 expression levels were correlated positively to calcium-binding adapter molecule 1 (IBA1) levels. Furthermore, both in NDHC and in AD patient’s brains, the CHID1 expression levels were directly correlated with calbindin 1 (CALB1) and neurogranin (NRGN). According to brain regions, correlation differences were shown between the expression levels of CHID1 in prefrontal, frontal, occipital, cerebellum, temporal, and limbic system. Sex-related differences were only highlighted in NDHC. CHID1 represents a new chitinase potentially involved in the principal processes underlying Alzheimer’s disease.

scholarly journals A meta-analysis of brain DNA methylation across sex, age and Alzheimer’s disease points for accelerated epigenetic aging in neurodegeneration

2020 ◽  
Author(s):  
C Pellegrini ◽  
C Pirazzini ◽  
C Sala ◽  
L Sambati ◽  
I Yusipov ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Meta Analysis ◽  
Brain Regions ◽  
Epigenetic Aging ◽  
High Concordance ◽  
Males And Females ◽  
Cortical Regions ◽  
The Brain

AbstractAlzheimer’s disease (AD) is characterized by specific alterations of brain DNA methylation (DNAm) patterns. Age and sex, two major risk factors for AD, are also known to largely affect the epigenetic profiles in the brain, but their contribution to AD-associated DNAm changes has been poorly investigated. In this study we considered publicly available DNAm datasets of 4 brain regions (temporal, frontal, entorhinal cortex and cerebellum) from healthy adult subjects and AD patients, and performed a meta-analysis to identify sex-, age- and AD-associated epigenetic profiles. We showed that DNAm differences between males and females tend to be shared between the 4 brain regions, while aging differently affects cortical regions compared to cerebellum. We found that the proportion of sex-dependent probes whose methylation changes also during aging is higher than expected, but that differences between males and females tend to be maintained, with only few probes showing sex-by-age interaction. We did not find significant overlaps between AD- and sex-associated probes, nor disease-by-sex interaction effects. On the contrary, we found that AD-related epigenetic modifications are significantly enriched in probes whose DNAm changes with age and that there is a high concordance between the direction of changes (hyper or hypo-methylation) in aging and AD, supporting accelerated epigenetic aging in the disease.In conclusion, we demonstrated that age-associated, but not sex-associated DNAm concurs to the epigenetic deregulation observed in AD, providing new insight on how advanced age enables neurodegeneration.

scholarly journals A Meta-Analysis of Brain DNA Methylation Across Sex, Age, and Alzheimer's Disease Points for Accelerated Epigenetic Aging in Neurodegeneration

2021 ◽  
Vol 13 ◽  
Author(s):  
Camilla Pellegrini ◽  
Chiara Pirazzini ◽  
Claudia Sala ◽  
Luisa Sambati ◽  
Igor Yusipov ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Healthy Adult ◽  
Meta Analysis ◽  
Brain Regions ◽  
Epigenetic Aging ◽  
High Concordance ◽  
Males And Females ◽  
Cortical Regions

Alzheimer's disease (AD) is characterized by specific alterations of brain DNA methylation (DNAm) patterns. Age and sex, two major risk factors for AD, are also known to largely affect the epigenetic profiles in brain, but their contribution to AD-associated DNAm changes has been poorly investigated. In this study we considered publicly available DNAm datasets of four brain regions (temporal, frontal, entorhinal cortex, and cerebellum) from healthy adult subjects and AD patients, and performed a meta-analysis to identify sex-, age-, and AD-associated epigenetic profiles. In one of these datasets it was also possible to distinguish 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) profiles. We showed that DNAm differences between males and females tend to be shared between the four brain regions, while aging differently affects cortical regions compared to cerebellum. We found that the proportion of sex-dependent probes whose methylation is modified also during aging is higher than expected, but that differences between males and females tend to be maintained, with only a few probes showing age-by-sex interaction. We did not find significant overlaps between AD- and sex-associated probes, nor disease-by-sex interaction effects. On the contrary, we found that AD-related epigenetic modifications are significantly enriched in probes whose DNAm varies with age and that there is a high concordance between the direction of changes (hyper or hypo-methylation) in aging and AD, supporting accelerated epigenetic aging in the disease. In summary, our results suggest that age-associated DNAm patterns concur to the epigenetic deregulation observed in AD, providing new insights on how advanced age enables neurodegeneration.

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