Atlas of RNA editing events affecting protein expression in aged and Alzheimer’s disease human brain tissue

AbstractRNA editing is a feature of RNA maturation resulting in the formation of transcripts whose sequence differs from the genome template. Brain RNA editing may be altered in Alzheimer’s disease (AD). Here, we analyzed data from 1,865 brain samples covering 9 brain regions from 1,074 unrelated subjects on a transcriptome-wide scale to identify inter-regional differences in RNA editing. We expand the list of known brain editing events by identifying 58,761 previously unreported events. We note that only a small proportion of these editing events are found at the protein level in our proteome-wide validation effort. We also identified the occurrence of editing events associated with AD dementia, neuropathological measures and longitudinal cognitive decline in: SYT11, MCUR1, SOD2, ORAI2, HSDL2, PFKP, and GPRC5B. Thus, we present an extended reference set of brain RNA editing events, identify a subset that are found to be expressed at the protein level, and extend the narrative of transcriptomic perturbation in AD to RNA editing.

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ADeditome provides the genomic landscape of A-to-I RNA editing in Alzheimer’s disease

Briefings in Bioinformatics ◽

10.1093/bib/bbaa384 ◽

2021 ◽

Author(s):

Sijia Wu ◽

Mengyuan Yang ◽

Pora Kim ◽

Xiaobo Zhou

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rna Editing ◽

Memory Loss ◽

Brain Regions ◽

Disease Stage ◽

Mirna Regulation ◽

Annotation Database ◽

Functional Annotations ◽

Genomic Landscape

Abstract A-to-I RNA editing, contributing to nearly 90% of all editing events in human, has been reported to involve in the pathogenesis of Alzheimer’s disease (AD) due to its roles in brain development and immune regulation, such as the deficient editing of GluA2 Q/R related to cell death and memory loss. Currently, there are urgent needs for the systematic annotations of A-to-I RNA editing events in AD. Here, we built ADeditome, the annotation database of A-to-I RNA editing in AD available at https://ccsm.uth.edu/ADeditome, aiming to provide a resource and reference for functional annotation of A-to-I RNA editing in AD to identify therapeutically targetable genes in an individual. We detected 1676 363 editing sites in 1524 samples across nine brain regions from ROSMAP, MayoRNAseq and MSBB. For these editing events, we performed multiple functional annotations including identification of specific and disease stage associated editing events and the influence of editing events on gene expression, protein recoding, alternative splicing and miRNA regulation for all the genes, especially for AD-related genes in order to explore the pathology of AD. Combing all the analysis results, we found 108 010 and 26 168 editing events which may promote or inhibit AD progression, respectively. We also found 5582 brain region-specific editing events with potentially dual roles in AD across different brain regions. ADeditome will be a unique resource for AD and drug research communities to identify therapeutically targetable editing events. Significance: ADeditome is the first comprehensive resource of the functional genomics of individual A-to-I RNA editing events in AD, which will be useful for many researchers in the fields of AD pathology, precision medicine, and therapeutic researches.

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DECODER: A probabilistic approach to integrate big data reveals mitochondrial Complex I as a potential therapeutic target for Alzheimer’s disease

10.1101/302737 ◽

2018 ◽

Cited By ~ 1

Author(s):

Safiye Celik ◽

Josh C. Russell ◽

Cezar R. Pestana ◽

Ting-I Lee ◽

Shubhabrata Mukherjee ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Complex I ◽

Meta Analysis ◽

Probabilistic Approach ◽

Amyloid Β ◽

Brain Regions ◽

Mitochondrial Complex I ◽

Mitochondrial Complex ◽

Human Brain Tissue

AbstractIdentifying gene expression markers for Alzheimer’s disease (AD) neuropathology through meta-analysis is a complex undertaking because available data are often from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. Here we introduce a novel probabilistic model-based framework, DECODER, leveraging these discrepancies to identify robust biomarkers for complex phenotypes. Our experiments present: (1) DECODER’s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD and cancer) and phenotypes (e.g., Amyloid-β (Aβ) pathology, tau pathology, and survival), (2) our results from a meta-analysis using 1,746 human brain tissue samples from nine brain regions in three studies — the largest expression meta-analysis for AD, to our knowledge —, and (3)in vivovalidation of identified modifiers of Aβ toxicity in a transgenicCaenorhabditis elegansmodel expressing AD-associated Aβ, which pinpoints mitochondrial Complex I as a critical mediator of proteostasis and a promising pharmacological avenue toward treating AD.

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A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials

Current Alzheimer Research ◽

10.2174/1567205014666171106150309 ◽

2018 ◽

Vol 15 (5) ◽

pp. 429-442 ◽

Cited By ~ 3

Author(s):

Nishant Verma ◽

S. Natasha Beretvas ◽

Belen Pascual ◽

Joseph C. Masdeu ◽

Mia K. Markey ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Clinical Trials ◽

Cognitive Impairment ◽

Latent Variable ◽

Brain Regions ◽

Disease Assessment ◽

Latent Variable Analysis ◽

The Relationship ◽

Selection Of

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.

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Characteristics of Insulin-degrading Enzyme in Alzheimer's Disease: A Meta-Analysis

Current Alzheimer Research ◽

10.2174/1567205015666180119105446 ◽

2018 ◽

Vol 15 (7) ◽

pp. 610-617 ◽

Cited By ~ 4

Author(s):

Huifeng Zhang ◽

Dan Liu ◽

Huanhuan Huang ◽

Yujia Zhao ◽

Hui Zhou

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Enzyme Activity ◽

Protein Level ◽

Senile Plaque ◽

Meta Analysis ◽

Cochrane Library ◽

Insulin Degrading Enzyme ◽

Degrading Enzyme ◽

Significant Difference

Background: β-amyloid (Aβ) accumulates abnormally to senile plaque which is the initiator of Alzheimer's disease (AD). As one of the Aβ-degrading enzymes, Insulin-degrading enzyme (IDE) remains controversial for its protein level and activity in Alzheimer's brain. Methods: The electronic databases PubMed, EMBASE, The Cochrane Library, OVID and Sinomed were systemically searched up to Sep. 20th, 2017. And the published case-control or cohort studies were retrieved to perform the meta-analysis. Results: Seven studies for IDE protein level (AD cases = 293; controls = 126), three for mRNA level (AD cases = 138; controls = 81), and three for enzyme activity (AD cases = 123; controls = 75) were pooling together. The IDE protein level was significantly lower in AD cases than in controls (SMD = - 0.47, 95% CI [-0.69, -0.24], p < 0.001), but IDE mRNA and enzyme activity had no significant difference (SMD = 0.02, 95% CI [-0.40, 0.43] and SMD = 0.06, 95% CI [-0.41, 0.53] respectively). Subgroup analyses found that IDE protein level was decreased in both cortex and hippocampus of AD cases (SMD = -0.43, 95% CI [-0.71, -0.16], p = 0.002 and SMD = -0.53, 95% CI [-0.91, -0.15], p = 0.006 respectively). However, IDE mRNA was higher in cortex of AD cases (SMD = 0.71, 95% CI [0.14, 1.29], p = 0.01), not in hippocampus (SMD = -0.26, 95% CI [-0.58, 0.06]). Conclusions: Our results indicate that AD patients may have lower IDE protease level. Further relevant studies are still needed to verify whether IDE is one of the factors affecting Aβ abnormal accumulation and throw new insights for AD detection or therapy.

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Genome-wide analysis identifies a novel LINC-PINT splice variant associated with vascular amyloid pathology in Alzheimer’s disease

Acta Neuropathologica Communications ◽

10.1186/s40478-021-01199-2 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Joseph S. Reddy ◽

Mariet Allen ◽

Charlotte C. G. Ho ◽

Stephanie R. Oatman ◽

Özkan İş ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Genome Wide Association Study ◽

Transcriptome Profiling ◽

Brain Regions ◽

Common Finding ◽

Amyloid Angiopathy ◽

Genome Wide ◽

A Genome ◽

Male Sex

AbstractCerebral amyloid angiopathy (CAA) contributes to accelerated cognitive decline in Alzheimer’s disease (AD) dementia and is a common finding at autopsy. The APOEε4 allele and male sex have previously been reported to associate with increased CAA in AD. To inform biomarker and therapeutic target discovery, we aimed to identify additional genetic risk factors and biological pathways involved in this vascular component of AD etiology. We present a genome-wide association study of CAA pathology in AD cases and report sex- and APOE-stratified assessment of this phenotype. Genome-wide genotypes were collected from 853 neuropathology-confirmed AD cases scored for CAA across five brain regions, and imputed to the Haplotype Reference Consortium panel. Key variables and genome-wide genotypes were tested for association with CAA in all individuals and in sex and APOEε4 stratified subsets. Pathway enrichment was run for each of the genetic analyses. Implicated loci were further investigated for functional consequences using brain transcriptome data from 1,186 samples representing seven brain regions profiled as part of the AMP-AD consortium. We confirmed association of male sex, AD neuropathology and APOEε4 with increased CAA, and identified a novel locus, LINC-PINT, associated with lower CAA amongst APOEε4-negative individuals (rs10234094-C, beta = −3.70 [95% CI −0.49—−0.24]; p = 1.63E-08). Transcriptome profiling revealed higher LINC-PINT expression levels in AD cases, and association of rs10234094-C with altered LINC-PINT splicing. Pathway analysis indicates variation in genes involved in neuronal health and function are linked to CAA in AD patients. Further studies in additional and diverse cohorts are needed to assess broader translation of our findings.

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Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography

Neural Computing and Applications ◽

10.1007/s00521-021-06105-4 ◽

2021 ◽

Author(s):

Antonio Giovannetti ◽

Gianluca Susi ◽

Paola Casti ◽

Arianna Mencattini ◽

Sandra Pusil ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Brain Regions ◽

Ensemble Classification ◽

The Novel ◽

Ensemble Classifiers ◽

Deep Convolutional Neural Networks ◽

Early Signs ◽

Data Representations ◽

The Brain

AbstractIn this paper, we present the novel Deep-MEG approach in which image-based representations of magnetoencephalography (MEG) data are combined with ensemble classifiers based on deep convolutional neural networks. For the scope of predicting the early signs of Alzheimer’s disease (AD), functional connectivity (FC) measures between the brain bio-magnetic signals originated from spatially separated brain regions are used as MEG data representations for the analysis. After stacking the FC indicators relative to different frequency bands into multiple images, a deep transfer learning model is used to extract different sets of deep features and to derive improved classification ensembles. The proposed Deep-MEG architectures were tested on a set of resting-state MEG recordings and their corresponding magnetic resonance imaging scans, from a longitudinal study involving 87 subjects. Accuracy values of 89% and 87% were obtained, respectively, for the early prediction of AD conversion in a sample of 54 mild cognitive impairment subjects and in a sample of 87 subjects, including 33 healthy controls. These results indicate that the proposed Deep-MEG approach is a powerful tool for detecting early alterations in the spectral–temporal connectivity profiles and in their spatial relationships.

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Microcanonical and Canonical Ensembles for fMRI Brain Networks in Alzheimer’s Disease

Entropy ◽

10.3390/e23020216 ◽

2021 ◽

Vol 23 (2) ◽

pp. 216 ◽

Cited By ~ 1

Author(s):

Jianjia Wang ◽

Xichen Wu ◽

Mingrui Li ◽

Hui Wu ◽

Edwin Hancock

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Ensemble Methods ◽

Brain Regions ◽

Fmri Data ◽

Thermal Systems ◽

Network Construction ◽

Network Characteristics ◽

Network Entropy ◽

Canonical Ensembles

This paper seeks to advance the state-of-the-art in analysing fMRI data to detect onset of Alzheimer’s disease and identify stages in the disease progression. We employ methods of network neuroscience to represent correlation across fMRI data arrays, and introduce novel techniques for network construction and analysis. In network construction, we vary thresholds in establishing BOLD time series correlation between nodes, yielding variations in topological and other network characteristics. For network analysis, we employ methods developed for modelling statistical ensembles of virtual particles in thermal systems. The microcanonical ensemble and the canonical ensemble are analogous to two different fMRI network representations. In the former case, there is zero variance in the number of edges in each network, while in the latter case the set of networks have a variance in the number of edges. Ensemble methods describe the macroscopic properties of a network by considering the underlying microscopic characterisations which are in turn closely related to the degree configuration and network entropy. When applied to fMRI data in populations of Alzheimer’s patients and controls, our methods demonstrated levels of sensitivity adequate for clinical purposes in both identifying brain regions undergoing pathological changes and in revealing the dynamics of such changes.

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The extracellular chaperone Clusterin enhances Tau aggregate seeding in a cellular model

Nature Communications ◽

10.1038/s41467-021-25060-1 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Patricia Yuste-Checa ◽

Victoria A. Trinkaus ◽

Irene Riera-Tur ◽

Rahmi Imamoglu ◽

Theresa F. Schaller ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Disease Progression ◽

Frontotemporal Dementia ◽

Brain Regions ◽

Model System ◽

Cellular Model ◽

Tau Pathology ◽

Extracellular Chaperone ◽

Tau Aggregate

AbstractSpreading of aggregate pathology across brain regions acts as a driver of disease progression in Tau-related neurodegeneration, including Alzheimer’s disease (AD) and frontotemporal dementia. Aggregate seeds released from affected cells are internalized by naïve cells and induce the prion-like templating of soluble Tau into neurotoxic aggregates. Here we show in a cellular model system and in neurons that Clusterin, an abundant extracellular chaperone, strongly enhances Tau aggregate seeding. Upon interaction with Tau aggregates, Clusterin stabilizes highly potent, soluble seed species. Tau/Clusterin complexes enter recipient cells via endocytosis and compromise the endolysosomal compartment, allowing transfer to the cytosol where they propagate aggregation of endogenous Tau. Thus, upregulation of Clusterin, as observed in AD patients, may enhance Tau seeding and possibly accelerate the spreading of Tau pathology.

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Learning Deficits Accompanied by Microglial Proliferation After the Long-Term Post-Injection of Alzheimer’s Disease Brain Extract in Mouse Brains

Journal of Alzheimer s Disease ◽

10.3233/jad-201002 ◽

2021 ◽

Vol 79 (4) ◽

pp. 1701-1711

Author(s):

Tetsuo Hayashi ◽

Shotaro Shimonaka ◽

Montasir Elahi ◽

Shin-Ei Matsumoto ◽

Koichi Ishiguro ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Mouse Brain ◽

Functional Decline ◽

Brain Regions ◽

Insoluble Fraction ◽

Brain Extract ◽

Post Injection ◽

Learning Deficits

Background: Human tauopathy brain injections into the mouse brain induce the development of tau aggregates, which spread to functionally connected brain regions; however, the features of this neurotoxicity remain unclear. One reason may be short observational periods because previous studies mostly used mutated-tau transgenic mice and needed to complete the study before these mice developed neurofibrillary tangles. Objective: To examine whether long-term incubation of Alzheimer’s disease (AD) brain in the mouse brain cause functional decline. Methods: We herein used Tg601 mice, which overexpress wild-type human tau, and non-transgenic littermates (NTg) and injected an insoluble fraction of the AD brain into the unilateral hippocampus. Results: After a long-term (17–19 months) post-injection, mice exhibited learning deficits detected by the Barnes maze test. Aggregated tau pathology in the bilateral hippocampus was more prominent in Tg601 mice than in NTg mice. No significant changes were observed in the number of Neu-N positive cells or astrocytes in the hippocampus, whereas that of Iba-I-positive microglia increased after the AD brain injection. Conclusion: These results potentially implicate tau propagation in functional decline and indicate that long-term changes in non-mutated tau mice may reflect human pathological conditions.

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Defining early changes in Alzheimer’s disease from RNA sequencing of brain regions differentially affected by pathology

Scientific Reports ◽

10.1038/s41598-021-83872-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Boris Guennewig ◽

Julia Lim ◽

Lee Marshall ◽

Andrew N. McCorkindale ◽

Patrick J. Paasila ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rna Sequencing ◽

Neuronal Loss ◽

Brain Regions ◽

Post Mortem ◽

Tau Pathology ◽

Membrane Spanning ◽

Immune Related Genes ◽

Vesicle Secretion

AbstractTau pathology in Alzheimer’s disease (AD) spreads in a predictable pattern that corresponds with disease symptoms and severity. At post-mortem there are cortical regions that range from mildly to severely affected by tau pathology and neuronal loss. A comparison of the molecular signatures of these differentially affected areas within cases and between cases and controls may allow the temporal modelling of disease progression. Here we used RNA sequencing to explore differential gene expression in the mildly affected primary visual cortex and moderately affected precuneus of ten age-, gender- and RNA quality-matched post-mortem brains from AD patients and healthy controls. The two regions in AD cases had similar transcriptomic signatures but there were broader abnormalities in the precuneus consistent with the greater tau load. Both regions were characterised by upregulation of immune-related genes such as those encoding triggering receptor expressed on myeloid cells 2 and membrane spanning 4-domains A6A and milder changes in insulin/IGF1 signalling. The precuneus in AD was also characterised by changes in vesicle secretion and downregulation of the interneuronal subtype marker, somatostatin. The ‘early’ AD transcriptome is characterised by perturbations in synaptic vesicle secretion on a background of neuroimmune dysfunction. In particular, the synaptic deficits that characterise AD may begin with the somatostatin division of inhibitory neurotransmission.

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