Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer’s Disease

Abstract Alzheimer’s disease (AD) brains are characterized by progressive neuron loss and gliosis. Previous studies comparing AD versus control using bulk brain tissue samples have not considered cell composition changes in AD brains that can cause transcriptional changes not due to transcriptional regulation.Using five large transcriptomic datasets, we mined conserved gene co-expression network modules, and applied differential expression and differential co-expression analysis on the modules in AD versus control brains. Combined with cell type deconvolution analysis, we addressed the question of whether the module expression changes are due to altered cellular composition or transcriptional regulation. Our findings were validated using four additional datasets.We discovered that the increased expression of microglia modules can be explained by increased microglia population in AD brains rather than gene upregulation. In contrast, the decreased expression and perturbed co-expression in AD neuron modules are due to both neuron loss and regulation of neuronal pathways and several transcriptional factors are identified for such regulation. Similarly, the strong changes in expression and co-expression in astrocyte modules can also be attributed to a combinatory effect from astrogliosis and astrocyte gene activation in AD brains. The astrocyte modules expressions also strongly correlated with the clinicopathological biomarkers.In summary, we demonstrated that combinatorial analysis is a powerful approach to delineate the origin of transcriptomic changes in bulk tissue data, which leads to a deeper understanding of key genes/pathways in AD.

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Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer’s Disease

10.21203/rs.3.rs-26385/v2 ◽

2020 ◽

Author(s):

Travis S. Johnson ◽

Shunian Xiang ◽

Tianhan Dong ◽

Zhi Huang ◽

Michael Cheng ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Gene Activation ◽

Cellular Composition ◽

Cell Type ◽

Tissue Samples ◽

Deconvolution Analysis ◽

Neuron Loss ◽

Transcriptomic Changes ◽

Composition Changes

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Combinatorial analyses reveal that cellular composition changes have different impact on transcriptomic changes of cell type specific genes in Alzheimer’s Disease brains

10.21203/rs.3.rs-26385/v1 ◽

2020 ◽

Author(s):

Shunian Xiang ◽

Travis Johnson ◽

Tianhan Dong ◽

Zhi Huang ◽

Michael Cheng ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Transcriptional Regulation ◽

Brain Tissue ◽

Cellular Composition ◽

Cell Type ◽

Tissue Samples ◽

Cell Type Specific ◽

Transcriptomic Changes ◽

Composition Changes

Abstract Background Alzheimer’s disease (AD) brains are characterized by progressive neuron loss and gliosis which involves mostly microglia and astrocytes. Comparative transcriptomic analysis on AD vs. normal brain tissues helps to identify key genes/pathways involved in AD initiation and progression. However, many such studies using bulk brain tissue samples have not considered cell composition changes in AD brains, which may lead to expression changes that are not due to transcriptional regulation. Methods Using five large transcriptomic datasets including 1,681 brain tissue samples (882 AD, 799 normal) in total, we first mined frequent co-expression network modules across them, then combined differential expression and differential co-expression analysis on the mined modules in AD versus normal brains. Integrated with cell type deconvolution analysis, we addressed the question of whether the module expression changes are due to altered cellular composition or transcriptional regulation. We then used four additional large AD/normal transcriptomic datasets to validate our findings. Results The integrative analysis revealed highly elevated expression level of microglia modules in AD without co-expression change. Decreased expression and elevated co-expression are observed for neuron modules in AD, while significant over-expression and co-expression perturbation are observed in astrocyte modules, all of which has not been previously reported. The expression levels of astrocyte modules also show the strongest correlation with the clinicopathological biomarkers among all cell type specific modules. Conclusion Further analysis indicated that the overall increased expression of the core microglia modules can be well explained by the increased microglia cell population in AD brains instead of bona fide microglia genes’ upregulation. In contrast, the decreased expression and perturbed co-expression in AD neuron modules are due to both neuron cell loss and expression regulation of neuronal pathways including differentially expressed transcription factors such as BCL6 and STAT3, which previous study was not able to identify from the shadow of the cellular composition change. Similarly, the strong changes in expression and co-expression in the astrocyte modules may be also due to a combinatory effect from astrogliosis and astrocyte gene activation in AD brains. In this work, we demonstrated that the combinatorial analyses not only provide a powerful approach to delineate the origin of transcriptomic changes in bulk tissue data, but also lead to a deeper understanding of genes in AD.

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Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structure

10.1101/266296 ◽

2018 ◽

Cited By ~ 1

Author(s):

Zeran Li ◽

Jorge L Del-Aguila ◽

Umber Dube ◽

John Budde ◽

Rita Martinez ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cerebral Cortex ◽

Genetic Risk ◽

Molecular Mechanisms ◽

Neuronal Loss ◽

Reference Panel ◽

Cellular Composition ◽

Cell Type ◽

Large Bulk

AbstractAlzheimer’s disease (AD) is characterized by neuronal loss and astrocytosis in the cerebral cortex. However, the effects of brain cellular composition are often ignored in high-throughput molecular studies. We developed and optimized a cell-type specific expression reference panel and employed digital deconvolution methods to determine brain cellular distribution in three independent transcriptomic studies. We found that neuronal and astrocyte proportions differ between healthy and diseased brains and also among AD cases that carry specific genetic risk variants. Brain carriers of pathogenic mutations in APP, PSEN1 or PSEN2 presented lower neurons and higher astrocytes proportions compared to sporadic AD. Similarly, the APOE ε4 allele also showed decreased neurons and increased astrocytes compared to AD non-carriers. On the contrary, carriers of variants in TREM2 risk showed a lower degree of neuronal loss than matched AD cases in multiple independent studies. These findings suggest that genetic risk factors associated with AD etiology have a specific imprinting in the cellular composition of AD brains. Our digital deconvolution reference panel provides an enhanced understanding of the fundamental molecular mechanisms underlying neurodegeneration, enabling the analysis of large bulk RNA-seq studies for cell composition, and suggests that correcting for the cellular structure when performing transcriptomic analysis will lead to novel insights of AD.

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Effects of tetrahydrocannabinol treatment on brain metabolism and neuron loss in a mouse model of sporadic Alzheimer's disease

10.1055/s-0039-1683689 ◽

2019 ◽

Cited By ~ 1

Author(s):

TN Franke ◽

C Irwin ◽

N Beindorff ◽

Y Bouter ◽

C Bouter

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Mouse Model ◽

Brain Metabolism ◽

Sporadic Alzheimer’S Disease ◽

Neuron Loss

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Integrative multi-omics analyses identify cell-type disease genes and regulatory networks across schizophrenia and Alzheimer’s disease

10.1101/2020.06.11.147314 ◽

2020 ◽

Author(s):

Mufang Ying ◽

Peter Rehani ◽

Panagiotis Roussos ◽

Daifeng Wang

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Regulatory Elements ◽

Disease Genes ◽

Omics Data ◽

Cell Type ◽

Cellular Resolution ◽

Gene Regulatory

AbstractStrong phenotype-genotype associations have been reported across brain diseases. However, understanding underlying gene regulatory mechanisms remains challenging, especially at the cellular level. To address this, we integrated the multi-omics data at the cellular resolution of the human brain: cell-type chromatin interactions, epigenomics and single cell transcriptomics, and predicted cell-type gene regulatory networks linking transcription factors, distal regulatory elements and target genes (e.g., excitatory and inhibitory neurons, microglia, oligodendrocyte). Using these cell-type networks and disease risk variants, we further identified the cell-type disease genes and regulatory networks for schizophrenia and Alzheimer’s disease. The celltype regulatory elements (e.g., enhancers) in the networks were also found to be potential pleiotropic regulatory loci for a variety of diseases. Further enrichment analyses including gene ontology and KEGG pathways revealed potential novel cross-disease and disease-specific molecular functions, advancing knowledge on the interplays among genetic, transcriptional and epigenetic risks at the cellular resolution between neurodegenerative and neuropsychiatric diseases. Finally, we summarized our computational analyses as a general-purpose pipeline for predicting gene regulatory networks via multi-omics data.

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Summary-Based Methylome-Wide Association Analyses Suggest Potential Genetically Driven Epigenetic Heterogeneity of Alzheimer’s Disease

Journal of Clinical Medicine ◽

10.3390/jcm9051489 ◽

2020 ◽

Vol 9 (5) ◽

pp. 1489

Author(s):

Alireza Nazarian ◽

Anatoliy I. Yashin ◽

Alexander M. Kulminski

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Neurodegenerative Disorder ◽

Tissue Samples ◽

Significance Level ◽

Association Analyses ◽

Functional Studies ◽

Genome Wide ◽

Summary Data

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with no curative treatment available. Exploring the genetic and non-genetic contributors to AD pathogenesis is essential to better understand its underlying biological mechanisms, and to develop novel preventive and therapeutic strategies. We investigated potential genetically driven epigenetic heterogeneity of AD through summary data-based Mendelian randomization (SMR), which combined results from our previous genome-wide association analyses with those from two publicly available methylation quantitative trait loci studies of blood and brain tissue samples. We found that 152 probes corresponding to 113 genes were epigenetically associated with AD at a Bonferroni-adjusted significance level of 5.49E-07. Of these, 10 genes had significant probes in both brain-specific and blood-based analyses. Comparing males vs. females and hypertensive vs. non-hypertensive subjects, we found that 22 and 79 probes had group-specific associations with AD, respectively, suggesting a potential role for such epigenetic modifications in the heterogeneous nature of AD. Our analyses provided stronger evidence for possible roles of four genes (i.e., AIM2, C16orf80, DGUOK, and ST14) in AD pathogenesis as they were also transcriptionally associated with AD. The identified associations suggest a list of prioritized genes for follow-up functional studies and advance our understanding of AD pathogenesis.

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Chronic Memantine Treatment Ameliorates Behavioral Deficits, Neuron Loss, and Impaired Neurogenesis in a Model of Alzheimer’s Disease

Molecular Neurobiology ◽

10.1007/s12035-020-02120-z ◽

2020 ◽

Vol 58 (1) ◽

pp. 204-216

Author(s):

Martina Stazi ◽

Oliver Wirths

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Mouse Model ◽

Recognition Task ◽

Hippocampal Neurogenesis ◽

Adult Hippocampal Neurogenesis ◽

Behavioral Deficits ◽

Neuron Loss ◽

Beneficial Effects ◽

Memantine Treatment

AbstractMemantine, a non-competitive NMDA receptor antagonist possessing neuroprotective properties, belongs to the small group of drugs which have been approved for the treatment of Alzheimer’s disease (AD). While several preclinical studies employing different transgenic AD mouse models have described beneficial effects with regard to rescued behavioral deficits or reduced amyloid plaque pathology, it is largely unknown whether memantine might have beneficial effects on neurodegeneration. In the current study, we assessed whether memantine treatment has an impact on hippocampal neuron loss and associated behavioral deficits in the Tg4-42 mouse model of AD. We demonstrate that a chronic oral memantine treatment for 4 months diminishes hippocampal CA1 neuron loss and rescues learning and memory performance in different behavioral paradigms, such as Morris water maze or a novel object recognition task. Cognitive benefits of chronic memantine treatment were accompanied by an amelioration of impaired adult hippocampal neurogenesis. Taken together, our results demonstrate that memantine successfully counteracts pathological alterations in a preclinical mouse model of AD.

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