Comprehensive MicroRNAome Analysis of the Relationship Between Alzheimer Disease and Cancer in Double-Knockout Mice

Purpose Presenilins are functionally important components of γ-secretase, which cleaves a number of transmembrane proteins. Manipulations of PSEN1 and PSEN2 have been separately studied in Alzheimer disease (AD) and cancer because both involve substrates of γ-secretase. However, numerous clinical studies have reported an inverse correlation between AD and cancer. Interestingly, AD is a neurodegenerative disorder, whereas cancer is characterized by the proliferation of malignant cells. However, this inverse correlation in the PSEN double-knockout (PSEN dKO) mouse model of AD has been not elucidated, although doing so would shed light onto the relationship between AD and cancer. Methods To investigate the inverse relationship of AD and cancer under conditions of PSEN loss, we used the hippocampus of 7-month-old and 18-month-old PSEN dKO mice for a microRNA (miRNA) microarray analysis, and explored the tumorsuppressive or oncogenic role of differentially-expressed miRNAs. Results The total number of miRNAs that showed changes in expression level was greater at 18 months of age than at 7 months. Most of the putative target genes of the differentially-expressed miRNAs involved Cancer pathways. Conclusions Based on literature reviews, many of the miRNAs involved in Cancer pathways were found to be known tumorsuppressive miRNAs, and their target genes were known or putative oncogenes. In conclusion, the expression levels of known tumor-suppressive miRNAs increased at 7 and 18 months, in the PSEN dKO mouse model of AD, supporting the negative correlation between AD and cancer

Big Data Analysis of Genes Associated With Neuropsychiatric Disorders in an Alzheimer’s Disease Animal Model

Alzheimer’s disease is a neurodegenerative disease characterized by the impairment of cognitive function and loss of memory, affecting millions of individuals worldwide. With the dramatic increase in the prevalence of Alzheimer’s disease, it is expected to impose extensive public health and economic burden. However, this burden is particularly heavy on the caregivers of Alzheimer’s disease patients eliciting neuropsychiatric symptoms that include mood swings, hallucinations, and depression. Interestingly, these neuropsychiatric symptoms are shared across symptoms of bipolar disorder, schizophrenia, and major depression disorder. Despite the similarities in symptomatology, comorbidities of Alzheimer’s disease and these neuropsychiatric disorders have not been studied in the Alzheimer’s disease model. Here, we explore the comprehensive changes in gene expression of genes that are associated with bipolar disorder, schizophrenia, and major depression disorder through the microarray of an Alzheimer’s disease animal model, the forebrain specific PSEN double knockout mouse. To analyze the genes related with these three neuropsychiatric disorders within the scope of our microarray data, we used selected 1207 of a total of 45,037 genes that satisfied our selection criteria. These genes were selected on the basis of 14 Gene Ontology terms significantly relevant with the three disorders which were identified by previous research conducted by the Psychiatric Genomics Consortium. Our study revealed that the forebrain specific deletion of Alzheimer’s disease genes can significantly alter neuropsychiatric disorder associated genes. Most importantly, most of these significantly altered genes were found to be involved with schizophrenia. Taken together, we suggest that the synaptic dysfunction by mutation of Alzheimer’s disease genes can lead to the manifestation of not only memory loss and impairments in cognition, but also neuropsychiatric symptoms

mRNA microarray within hippocampus and cortex brain regions of PSEN12 double knockout mice

The wild type and PSEN dKO mice were sacrificed at the ages of 7 and 18 months. The complete mouse brain structure was removed and immediately prepared by being frozen on dry ice. The cortex and hippocampus were dissected and stored at -80°C until RNA isolation. Total RNA was isolated using the Trizol reagent. Messenger RNA expression profiling was performed using Affymetrix Mouse Genome 430 2.0 array chip containing 764,885 probe sets from 28,132 genes (Ensembl) or from 19,734 putative full-length transcripts (GenBank and Ref Seq)

Data from: Comprehensive MicroRNAome analysis of the relationship between Alzheimer disease and cancer in PSEN double-knockout mice

Purpose: Presenilins are functionally important components of γ-secretase, which cleaves a number of transmembrane proteins. Manipulations of PSEN1 and PSEN2 have been separately studied in Alzheimer disease (AD) and cancer because both involve substrates of γ-secretase. However, numerous clinical studies have reported an inverse correlation between AD and cancer. Interestingly, AD is a neurodegenerative disorder, whereas cancer is characterized by the proliferation of malignant cells. However, this inverse correlation in the PSEN double-knockout (PSEN dKO) mouse model of AD has been not elucidated, although doing so would shed light onto the relationship between AD and cancer. Methods: To investigate the inverse relationship of AD and cancer under conditions of PSEN loss, we used the hippocampus of 7-month-old and 18-month-old PSEN dKO mice for a microRNA (miRNA) microarray analysis, and explored the tumorsuppressive or oncogenic role of differentially-expressed miRNAs. Results: The total number of miRNAs that showed changes in expression level was greater at 18 months of age than at 7 months. Most of the putative target genes of the differentially-expressed miRNAs involved Cancer pathways. Conclusions: Based on literature reviews, many of the miRNAs involved in Cancer pathways were found to be known tumorsuppressive miRNAs, and their target genes were known or putative oncogenes. In conclusion, the expression levels of known tumor-suppressive miRNAs increased at 7 and 18 months, in the PSEN dKO mouse model of AD, supporting the negative correlation between AD and cancer

Data_Sheet_2_Big Data Analysis of Genes Associated With Neuropsychiatric Disorders in an Alzheimer’s Disease Animal Model.XLSX

<p>Alzheimer’s disease is a neurodegenerative disease characterized by the impairment of cognitive function and loss of memory, affecting millions of individuals worldwide. With the dramatic increase in the prevalence of Alzheimer’s disease, it is expected to impose extensive public health and economic burden. However, this burden is particularly heavy on the caregivers of Alzheimer’s disease patients eliciting neuropsychiatric symptoms that include mood swings, hallucinations, and depression. Interestingly, these neuropsychiatric symptoms are shared across symptoms of bipolar disorder, schizophrenia, and major depression disorder. Despite the similarities in symptomatology, comorbidities of Alzheimer’s disease and these neuropsychiatric disorders have not been studied in the Alzheimer’s disease model. Here, we explore the comprehensive changes in gene expression of genes that are associated with bipolar disorder, schizophrenia, and major depression disorder through the microarray of an Alzheimer’s disease animal model, the forebrain specific PSEN double knockout mouse. To analyze the genes related with these three neuropsychiatric disorders within the scope of our microarray data, we used selected 1207 of a total of 45,037 genes that satisfied our selection criteria. These genes were selected on the basis of 14 Gene Ontology terms significantly relevant with the three disorders which were identified by previous research conducted by the Psychiatric Genomics Consortium. Our study revealed that the forebrain specific deletion of Alzheimer’s disease genes can significantly alter neuropsychiatric disorder associated genes. Most importantly, most of these significantly altered genes were found to be involved with schizophrenia. Taken together, we suggest that the synaptic dysfunction by mutation of Alzheimer’s disease genes can lead to the manifestation of not only memory loss and impairments in cognition, but also neuropsychiatric symptoms.</p

Data_Sheet_1_Big Data Analysis of Genes Associated With Neuropsychiatric Disorders in an Alzheimer’s Disease Animal Model.XLSX

<p>Alzheimer’s disease is a neurodegenerative disease characterized by the impairment of cognitive function and loss of memory, affecting millions of individuals worldwide. With the dramatic increase in the prevalence of Alzheimer’s disease, it is expected to impose extensive public health and economic burden. However, this burden is particularly heavy on the caregivers of Alzheimer’s disease patients eliciting neuropsychiatric symptoms that include mood swings, hallucinations, and depression. Interestingly, these neuropsychiatric symptoms are shared across symptoms of bipolar disorder, schizophrenia, and major depression disorder. Despite the similarities in symptomatology, comorbidities of Alzheimer’s disease and these neuropsychiatric disorders have not been studied in the Alzheimer’s disease model. Here, we explore the comprehensive changes in gene expression of genes that are associated with bipolar disorder, schizophrenia, and major depression disorder through the microarray of an Alzheimer’s disease animal model, the forebrain specific PSEN double knockout mouse. To analyze the genes related with these three neuropsychiatric disorders within the scope of our microarray data, we used selected 1207 of a total of 45,037 genes that satisfied our selection criteria. These genes were selected on the basis of 14 Gene Ontology terms significantly relevant with the three disorders which were identified by previous research conducted by the Psychiatric Genomics Consortium. Our study revealed that the forebrain specific deletion of Alzheimer’s disease genes can significantly alter neuropsychiatric disorder associated genes. Most importantly, most of these significantly altered genes were found to be involved with schizophrenia. Taken together, we suggest that the synaptic dysfunction by mutation of Alzheimer’s disease genes can lead to the manifestation of not only memory loss and impairments in cognition, but also neuropsychiatric symptoms.</p

p Dysfunction of striatal MeCP2 is associated with cognitive decline in a mouse model of Alzheimer&apos;s disease

Rationale: Cerebral Methyl-CpG binding Protein 2 (MeCP2) is involved in several psychiatric disorders that are concomitant with cognitive dysfunction. However, the regulatory function of striatal MeCP2 and its association with Alzheimer&apos;s disease (AD) has been largely neglected due to the absence of amyloid plaque accumulation in the striatal region until the later stages of AD progression. Considerable evidence indicates that neuropsychiatric symptoms related to cognitive decline are involved with striatal dysfunction. To this respect, we investigated the epigenetic function of striatal MeCP2 paralleling the pathogenesis of AD. Methods: We investigated the brain from amyloid precursor protein (APP)/presenilin1 (PS1) transgenic mice and postmortem brain samples from normal subjects and AD patients. The molecular changes in the brain, particularly in the striatal regions, were analyzed with thioflavin S staining, immunohistochemistry, immunoblotting, and MeCP2 chromatin immunoprecipitation sequencing (ChIP-seq). The cognitive function of APP/PS1 mice was assessed via three behavioral tests: 3-chamber test (3CT), Y-maze test (YMT), and passive avoidance test (PA). A multi-electrode array (MEA) was performed to analyze the neuronal activity of the striatum in APP/PS1 mice. Results: Striatal MeCP2 expression was increased in the younger (6 months) and older (10 months) ages of APP/PS1 mice, and the genome-wide occupancy of MeCP2 in the younger APP/PS1 showed dysregulated binding patterns in the striatum. Additionally, we confirmed that APP/PS1 mice showed behavioral deficits in multiple cognitive behaviors. Notably, defective cognitive phenotypes and abnormal neuronal activity in old APP/PS1 mice were rescued through the knock-down of striatal MeCP2. Conclusion: We found that the MeCP2-mediated dysregulation of the epigenome in the striatum is linked to the defects in cognitive behavior and neuronal activity in the AD animal model, and that this alteration is initiated even in the very early stages of AD pathogenesis. Together, our data indicates that MeCP2 may be a potential target for the diagnosis and treatment of AD at asymptomatic and symptomatic stages.N