scholarly journals Deciphering cellular transcriptional alterations in Alzheimer’s disease brains

2020 ◽  
Author(s):  
Xue Wang ◽  
Mariet Allen ◽  
Shaoyu Li ◽  
Zachary S. Quicksall ◽  
Tulsi A. Patel ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Complex Disease ◽  
Individual Cell ◽  
Cell Types ◽  
Brain Regions ◽  
Bioinformatics Pipeline ◽  
Dorsolateral Prefrontal ◽  
Transcriptional Alterations

AbstractLarge-scale brain bulk-RNAseq studies identified molecular pathways implicated in Alzheimer’s disease (AD), however these findings can be confounded by cellular composition changes in bulk-tissue. To identify cell intrinsic gene expression alterations of individual cell types, we designed a bioinformatics pipeline and analyzed three AD and control bulk-RNAseq datasets of temporal and dorsolateral prefrontal cortex from 685 brain samples. We detected cell-proportion changes in AD brains that are robustly replicable across the three independently assessed cohorts. We applied three different algorithms including our in-house algorithm to identify cell intrinsic differentially expressed genes in individual cell types (CI-DEGs). We assessed the performance of all algorithms by comparison to single nucleus RNAseq data. We identified consensus CI-DEGs that are common to multiple brain regions. Despite significant overlap between consensus CI-DEGs and bulk-DEGs, many CI-DEGs were absent from bulk-DEGs. Consensus CI-DEGs and their enriched GO terms include genes and pathways previously implicated in AD or neurodegeneration, as well as novel ones. We demonstrated that the detection of CI-DEGs through computational deconvolution methods is promising and highlight remaining challenges. These findings provide novel insights into cell-intrinsic transcriptional changes of individual cell types in AD and may refine discovery and modeling of molecular targets that drive this complex disease.

scholarly journals Deciphering cellular transcriptional alterations in Alzheimer’s disease brains

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Xue Wang ◽  
Mariet Allen ◽  
Shaoyu Li ◽  
Zachary S. Quicksall ◽  
Tulsi A. Patel ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Complex Disease ◽  
Individual Cell ◽  
Cell Types ◽  
Brain Regions ◽  
Bioinformatics Pipeline ◽  
Dorsolateral Prefrontal ◽  
Transcriptional Alterations

Abstract Large-scale brain bulk-RNAseq studies identified molecular pathways implicated in Alzheimer’s disease (AD), however these findings can be confounded by cellular composition changes in bulk-tissue. To identify cell intrinsic gene expression alterations of individual cell types, we designed a bioinformatics pipeline and analyzed three AD and control bulk-RNAseq datasets of temporal and dorsolateral prefrontal cortex from 685 brain samples. We detected cell-proportion changes in AD brains that are robustly replicable across the three independently assessed cohorts. We applied three different algorithms including our in-house algorithm to identify cell intrinsic differentially expressed genes in individual cell types (CI-DEGs). We assessed the performance of all algorithms by comparison to single nucleus RNAseq data. We identified consensus CI-DEGs that are common to multiple brain regions. Despite significant overlap between consensus CI-DEGs and bulk-DEGs, many CI-DEGs were absent from bulk-DEGs. Consensus CI-DEGs and their enriched GO terms include genes and pathways previously implicated in AD or neurodegeneration, as well as novel ones. We demonstrated that the detection of CI-DEGs through computational deconvolution methods is promising and highlight remaining challenges. These findings provide novel insights into cell-intrinsic transcriptional changes of individual cell types in AD and may refine discovery and modeling of molecular targets that drive this complex disease.

scholarly journals Single-cell transcriptomic analysis elucidates APOE genotype specific changes across cell types in two brain regions in Alzheimer’s disease

2021 ◽  
Author(s):  
Stella Belonwu ◽  
Yaqiao Li ◽  
Daniel Bunis ◽  
Arjun Arkal Rao ◽  
Caroline Warly Solsberg ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Cell ◽  
Molecular Mechanisms ◽  
Apoe Genotype ◽  
Cell Types ◽  
Brain Regions ◽  
Single Cell Level ◽  
Cell Level ◽  
Single Nucleus

Abstract Alzheimer’s Disease (AD) is a complex neurodegenerative disease that gravely affects patients and imposes an immense burden on caregivers. Apolipoprotein E4 (APOE4) has been identified as the most common genetic risk factor for AD, yet the molecular mechanisms connecting APOE4 to AD are not well understood. Past transcriptomic analyses in AD have revealed APOE genotype-specific transcriptomic differences; however, these differences have not been explored at a single-cell level. Here, we leverage the first two single-nucleus RNA sequencing AD datasets from human brain samples, including nearly 55,000 cells from the prefrontal and entorhinal cortices. We observed more global transcriptomic changes in APOE4 positive AD cells and identified differences across APOE genotypes primarily in glial cell types. Our findings highlight the differential transcriptomic perturbations of APOE isoforms at a single-cell level in AD pathogenesis and have implications for precision medicine development in the diagnosis and treatment of AD.

Estrogenic Regulation of Synaptic Health and Cognition in Aging Rhesus Monkeys

2020 ◽  
pp. 303-334
Author(s):  
Johanna L. Crimins ◽  
Yuko Hara ◽  
John H. Morrison
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Aging ◽  
Rhesus Monkeys ◽  
Memory Systems ◽  
Brain Regions ◽  
Clinical Literature ◽  
Menopausal Women ◽  
Dorsolateral Prefrontal ◽  
Estrogenic Regulation

A compelling case can be made for estrogen’s role in maintaining synaptic health in the context of cognitive aging. This chapter first reviews clinical literature pertinent to estrogenic actions on cognition in menopausal women. Next, the authors provide a comprehensive summary of recent investigations in aging rhesus monkeys, which have emerged as a particularly powerful model for the study of synaptic and cognitive effects of both natural and surgical menopause. In particular, we focus on hippocampal and dorsolateral prefrontal cortex neurons and circuits that degenerate in normal aging and Alzheimer’s disease. The responsiveness of these brain regions to estrogen and implications for their related memory systems are discussed. Finally, the chapter highlights work that needs to be done to more fully understand the molecular basis for the complex interplay between menopause, aging, and vulnerability to Alzheimer’s disease in higher cognitive function and synaptic health.

scholarly journals Molecular and cellular pathology of monogenic Alzheimer’s disease at single cell resolution

2020 ◽  
Author(s):  
Federica Marinaro ◽  
Moritz Haneklaus ◽  
Zhechun Zhang ◽  
Alessio Strano ◽  
Lewis Evans ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Cell Types ◽  
Brain Cell ◽  
Metabolic Reprogramming ◽  
Brain Atlas ◽  
Transcriptional Changes ◽  
Single Nucleus ◽  
Cellular Pathology

AbstractCell and molecular biology analyses of sporadic Alzheimer’s disease brain are confounded by clinical variability, ageing and genetic heterogeneity. Therefore, we used single-nucleus RNA sequencing to characterize cell composition and gene expression in the cerebral cortex in early-onset, monogenic Alzheimer’s disease. Constructing a cellular atlas of frontal cortex from 8 monogenic AD individuals and 8 matched controls, provided insights into which neurons degenerate in AD and responses of different cell types to AD at the cellular and systems level. Such responses are a combination of positively adaptive and deleterious changes, including large-scale changes in synaptic transmission and marked metabolic reprogramming in neurons. The nature and scale of the transcriptional changes in AD emphasizes the global impact of the disease across all brain cell types.One Sentence SummaryAlzheimer’s disease brain atlas provides insights into disease mechanisms

scholarly journals Cell type-specific histone acetylation profiling of Alzheimer’s Disease subjects and integration with genetics

2020 ◽  
Author(s):  
Easwaran Ramamurthy ◽  
Gwyneth Welch ◽  
Jemmie Cheng ◽  
Yixin Yuan ◽  
Laura Gunsalus ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Cell Types ◽  
Brain Cell ◽  
Nucleotide Polymorphisms ◽  
Risk Genes ◽  
Genome Wide ◽  
Dorsolateral Prefrontal ◽  
Genomic Regions

We profile genome-wide histone 3 lysine 27 acetylation (H3K27ac) of 3 major brain cell types from hippocampus and dorsolateral prefrontal cortex (dlPFC) of subjects with and without Alzheimer’s Disease (AD). We confirm that single nucleotide polymorphisms (SNPs) associated with late onset AD (LOAD) prefer to reside in the microglial histone acetylome, which varies most strongly with age. We observe acetylation differences associated with AD pathology at 3,598 peaks, predominantly in an oligodendrocyte-enriched population. Strikingly, these differences occur at the promoters of known early onset AD (EOAD) risk genes (APP, PSEN1, PSEN2, BACE1), late onset AD (LOAD) risk genes (BIN1, PICALM, CLU, ADAM10, ADAMTS4, SORL1 and FERMT2), and putative enhancers annotated to other genes associated with AD pathology (MAPT). More broadly, acetylation differences in the oligodendrocyte-enriched population occur near genes in pathways for central nervous system myelination and oxidative phosphorylation. In most cases, these promoter acetylation differences are associated with differences in transcription in oligodendrocytes. Overall, we reveal deregulation of known and novel pathways in AD and highlight genomic regions as therapeutic targets in oligodendrocytes of hippocampus and dlPFC.

scholarly journals Large-Scale Functional Brain Network Abnormalities in Alzheimer’s Disease: Insights from Functional Neuroimaging

2009 ◽  
Vol 21 (1-2) ◽  
pp. 63-75 ◽  
Author(s):  
Bradford C. Dickerson ◽  
Reisa A. Sperling
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Medial Temporal Lobe ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Brain Regions ◽  
Memory System ◽  
Fmri Data ◽  
Therapeutic Monitoring ◽  
Functional Brain Network

Functional MRI (fMRI) studies of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) have begun to reveal abnormalities in large-scale memory and cognitive brain networks. Since the medial temporal lobe (MTL) memory system is a site of very early pathology in AD, a number of studies have focused on this region of the brain. Yet it is clear that other regions of the large-scale episodic memory network are affected early in the disease as well, and fMRI has begun to illuminate functional abnormalities in frontal, temporal, and parietal cortices as well in MCI and AD. Besides predictable hypoactivation of brain regions as they accrue pathology and undergo atrophy, there are also areas of hyperactivation in brain memory and cognitive circuits, possibly representing attempted compensatory activity. Recent fMRI data in MCI and AD are beginning to reveal relationships between abnormalities of functional activity in the MTL memory system and in functionally connected brain regions, such as the precuneus. Additional work with “resting state” fMRI data is illuminating functional-anatomic brain circuits and their disruption by disease. As this work continues to mature, it will likely contribute to our understanding of fundamental memory processes in the human brain and how these are perturbed in memory disorders. We hope these insights will translate into the incorporation of measures of task-related brain function into diagnostic assessment or therapeutic monitoring, which will hopefully one day be useful for demonstrating beneficial effects of treatments being tested in clinical trials.

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 Differential transcript usage unravels gene expression alterations in Alzheimer’s disease human brains

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Diego Marques-Coelho ◽  
◽  
Lukas da Cruz Carvalho Iohan ◽  
Ana Raquel Melo de Farias ◽  
Amandine Flaig ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Differential Expression ◽  
Cell Types ◽  
Brain Regions ◽  
Adult Brain ◽  
Gene Transcript ◽  
Comprehensive Overview ◽  
Gene Expression Alterations

AbstractAlzheimer’s disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain could contribute for a better understanding of the AD pathology. In this work, we probed the differential expression of genes in different brain regions of healthy and AD adult subjects using data from three large transcriptomic studies: Mayo Clinic, Mount Sinai Brain Bank (MSBB), and ROSMAP. Using a combination of differential expression of gene and isoform switch analyses, we provide a detailed landscape of gene expression alterations in the temporal and frontal lobes, harboring brain areas affected at early and late stages of the AD pathology, respectively. Next, we took advantage of an indirect approach to assign the complex gene expression changes revealed in bulk RNAseq to individual cell types/subtypes of the adult brain. This strategy allowed us to identify previously overlooked gene expression changes in the brain of AD patients. Among these alterations, we show isoform switches in the AD causal gene amyloid-beta precursor protein (APP) and the risk gene bridging integrator 1 (BIN1), which could have important functional consequences in neuronal cells. Altogether, our work proposes a novel integrative strategy to analyze RNAseq data in AD and other neurodegenerative diseases based on both gene/transcript expression and regional/cell-type specificities.

scholarly journals Large-Scale Deep Multi-Layer Analysis of Alzheimer’s Disease Brain Reveals Strong Proteomic Disease-Related Changes Not Observed at the RNA Level

2021 ◽  
Author(s):  
Erik C.B. Johnson ◽  
E. Kathleen Carter ◽  
Eric B. Dammer ◽  
Duc M. Duong ◽  
Ekaterina S. Gerasimov ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Large Scale ◽  
Brain Regions ◽  
Mapk Signaling ◽  
Proteomic Data ◽  
Tandem Mass Tag ◽  
Within Subjects ◽  
Decline Disease

AbstractThe biological processes that are disrupted in the Alzheimer’s disease (AD) brain remain incompletely understood. We recently performed a proteomic analysis of >2000 brains to better understand these changes, which highlighted alterations in astrocytes and microglia as likely key drivers of disease. Here, we extend this analysis by analyzing >1000 brain tissues using a tandem mass tag mass spectrometry (TMT-MS) pipeline, which allowed us to nearly triple the number of quantified proteins across cases. A consensus protein co-expression network analysis of this deeper dataset revealed new co-expression modules that were highly preserved across cohorts and brain regions, and strongly altered in AD. Nearly half of the protein co-expression modules, including modules significantly altered in AD, were not observed in RNA networks from the same cohorts and brain regions, highlighting the proteopathic nature of AD. Two such AD-associated modules unique to the proteomic network included a module related to MAPK signaling and metabolism, and a module related to the matrisome. Analysis of paired genomic and proteomic data within subjects showed that expression level of the matrisome module was influenced by the APOE ε4 genotype, but was not related to the rate of cognitive decline after adjustment for neuropathology. In contrast, the MAPK/metabolism module was strongly associated with the rate of cognitive decline. Disease-associated modules unique to the proteome are sources of promising therapeutic targets and biomarkers for AD.

scholarly journals Dysregulation of the secretory pathway connects Alzheimer’s disease genetics to aggregate formation

2020 ◽  
Author(s):  
Chih-Chung Kuo ◽  
Austin WT Chiang ◽  
Nathan E. Lewis
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Secretory Pathway ◽  
Cell Types ◽  
Brain Regions ◽  
Support Network ◽  
Secreted Proteins ◽  
Amyloid Formation ◽  
Protein Protein Interaction ◽  
Endocytosis Pathway

AbstractA hallmark of amyloid disorders, such as Alzheimer’s disease, is aggregation of secreted proteins. However it is largely unclear how the hundreds of secretory pathway proteins contribute to amyloid formation. We developed a systems biology framework that integrates expression data with protein-protein interaction networks to successfully estimate a tissue’s fitness for producing specific secreted proteins. Using this framework, we analyzed the fitness of the secretory pathway of various brain regions and cell types for synthesizing the Alzheimer’s disease-associated amyloid-precursor protein (APP). While none of the key amyloidogenic pathway components were differentially expressed in AD brain, we found the deposition of Aβ is associated with repressed expression of the secretory pathway components proximal to APP. Concurrently, we detected systemic up-regulation of the secretory pathway components proximal to β- and γ-secretases in AD brains. Our analyses suggest that perturbations from 3 high confidence AD risk genes cascade through the secretory machinery support network for APP and into the endocytosis pathway. Thus, we present a model where amyloidogenesis is associated with dysregulation of dozens of secretory pathway components supporting APP, which could yield novel therapeutic targets for the treatment of AD.

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