Inhibition of Histone Acetylation by ANP32A Induces Memory Deficits

Chai, Gaoshang; Feng, Qiong; Ma, Rong-Hong; Qian, Xiaohang; Luo, Danju; Wang, Zhi-Hao; Hu, Yu; Sun, Dongsheng; Zhang, Junfei; Li, Xiao; Li, Xiaoguang; Ke, Dan; Wang, Jian‐Zhi; Yang, Xifei; Liu, Gongping

doi:10.3233/jad-180090

Cited by 16 publications

(10 citation statements)

References 44 publications

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“…In a mouse model of this disease, ANP32A elevation in the hippocampus correlates with learning deficits, and downregulating ANP32A rescues synaptic plasticity and memory loss (Chai et al, 2017; Feng et al, 2017). Conversely, overexpression of ANP32A in hippocampus induced memory deficits in mice (Chai et al, 2018). Loss of Wnt signaling plays a critical role in the pathogenesis of Alzheimer’s disease and emerging studies suggest that restoring Wnt signaling may be a promising therapeutic strategy (De Ferrari et al, 2014; Jia et al, 2019; Tapia-Rojas & Inestrosa, 2018).…”

Section: Resultsmentioning

confidence: 99%

“…In line with ANP32A’s pathological involvement in Alzheimer’s disease, ANP32A is reported to be increased in brain of Alzheimer’s disease patients and in disease mouse models (Tanimukai et al, 2005; Tsujio et al, 2005). In addition, overexpression of ANP32A in hippocampus induced memory impairments in mice (Chai et al, 2018). However, ANP32A’s pathological roles were not previously linked to a deficit in Wnt signaling, which has been extensively demonstrated to contribute to cognitive decline in Alzheimer’s disease (De Ferrari et al, 2014; Tapia-Rojas & Inestrosa, 2018).…”

Section: Discussionmentioning

confidence: 99%

Section: Anp32a Negatively Regulates Wnt Signaling In Heart and Hippocampusmentioning

confidence: 99%

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ANP32A represses Wnt signaling across tissues tissues thereby protecting against joint and heart disease

Monteagudo

Cornelis²,

Wang³

et al. 2021

Preprint

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Wnt signaling is key to diverse homeostatic and pathological processes. This cascade is hyper-activated in osteoarthritis, the most common joint disease. Yet, fundamental aspects of Wnt signaling remain undiscovered. Here, we report that ANP32A negatively regulates Wnt signaling across tissues. In cartilage, loss of Anp32a triggered Wnt hyper-activation. Mechanistically, ANP32A directly interacted with Wnt pathway components and inhibited Wnt target genes via histone acetylation masking. Wnt antagonist treatment reduced severity of osteoarthritis in Anp32a-deficient mice preventing osteophyte formation, contrasting with cartilage-protective effects of ANP32A on oxidative stress. Hence, dual therapy targeting Wnt signaling and oxidative stress in Anp32a-deficient mice ameliorated more osteoarthritis features than individual treatments. Anp32a loss also resulted in Wnt hyper-activation in the heart with cardiac hypertrophy, and in the hippocampus, shedding light on mechanisms for reported links between ANP32A and Alzheimer's disease. Collectively, this work reveals that ANP32A is a translationally relevant repressor of Wnt signaling, impacting homeostasis and disease across tissues.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Anp32a Negatively Regulates Wnt Signaling In Heart and Hippocampusmentioning

confidence: 99%

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ANP32A represses Wnt signaling across tissues tissues thereby protecting against joint and heart disease

Monteagudo

Cornelis²,

Wang³

et al. 2021

Preprint

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“…ANP32A is implicated in neurons differentiation, brain development, and neuritogenesis. Modulating ANP32A signaling could help manage oxidative stress in brain [67] and restore cognitive function [68] with therapeutic implications for neurological disease. To our best knowledge, no study has reported therole of RUNX1-IT1 and ANP32A-IT1 in stroke.…”

Section: Discussionmentioning

confidence: 99%

Hub Genes of Stroke Identified by Weighted Gene Co-expression Network Analysis

Zhai

et al. 2020

Preprint

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BACKGROUD: Microarray-based gene expression profiling is widely used in biomedical research. Weighted gene co-expression network analysis (WGCNA) links microarray data directly to clinical traits and identifies rules for predicting pathological stage and prognosis of disease.WGCNA is useful in understandingmany biological processes. Stroke is a common disease worldwide, however, molecular mechanisms of its pathogenesis are largely unknown. The aim of this study was to construct gene co-expression networks for identification of key modules and hub genes associated with stroke pathogenesis.METHODS: Gene microarray expression profiles of stroke samples were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by the limma package in R software. WGCNA was used to construct free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify key modules and hub genes. Subsequently, functional enrichment analyses were performed. Further, receiver operating characteristic (ROC) curve analysis was carried out to validate expression of hub genes and literature validation was performed as well.RESULTS: A total of 11,747 most variant genes were used for co-expression network construction. Pink and yellow modules were significantly correlated to stroke pathogenesis. Functional enrichment analysis showed that the pink module was mainly involved in regulation of neuron regeneration, and repair of DNA damage.On the other hand, yellow module was mainly enriched in ion transport system dysfunction which was correlated with neuron death. A total of eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) were identified and validated at transcriptional levels and through existing literature.CONCLUSION: The eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) identified in the study are potentialbiomarkers and therapeutic targets for effective diagnosis and treatment of stroke.

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“…ANP32A has multiple functions involved in neurons differentiation, brain development, and neuritogenesis. Modulating ANP32A signaling could help manage oxidative stress in brain [55] and restore cognitive function [56] with therapeutic implications for neurological disease. To our best knowledge, no study focusing on the function of RUNX1-IT1 and ANP32A-IT1 has been published in stroke until now.…”

Section: Discussionmentioning

confidence: 99%

Hub genes of stroke identified by weighted gene co-expression network analysis

Zhai²,

et al. 2019

Preprint

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Background Microarray-based gene expression profiling has been widely used in biomedical research. Weighted gene co-expression network analysis (WGCNA) can link microarray data directly to clinical traits and to identify rules for predicting pathological stage and prognosis of disease, it has been found useful in many biological processes. Stroke is one of the most common diseases worldwide, yet molecular mechanisms of its pathogenesis are largely unknown. We aimed to construct gene co-expression networks to identify key modules and hub genes associated with the pathogenesis of stroke.Results In this study, we screened out the differentially expressed genes from gene microarray expression profiles, then constructed the free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify key modules and hub genes. Subsequently, functional enrichment and the receiver operating characteristic (ROC) curve analysis were performed. And the results show that a total of 11,747 most variant genes were used for co-expression network construction. Pink and yellow modules were found to be the most significantly related to stroke. Functional enrichment analysis showed that the pink module was mainly involved in regulation of neuron regeneration, and the repair of DNA damage, while the yellow module was mainly enriched in ion transport system dysfunction which were correlated with neuron death. A total of 8 hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) were identified and validated at transcriptional levels (other datasets) and by existing literatures.Conclusions Eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) may serve as biomarkers and therapeutic targets for precise diagnosis and treatment of stroke in the future.

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Inhibition of Histone Acetylation by ANP32A Induces Memory Deficits

Cited by 16 publications

References 44 publications

ANP32A represses Wnt signaling across tissues tissues thereby protecting against joint and heart disease

ANP32A represses Wnt signaling across tissues tissues thereby protecting against joint and heart disease

Hub Genes of Stroke Identified by Weighted Gene Co-expression Network Analysis

Hub genes of stroke identified by weighted gene co-expression network analysis

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