Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 4 de 4
Filtrar
Mais filtros

Base de dados
Assunto principal
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
J Neurosci ; 2024 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-39327003

RESUMO

Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzheimer's disease (AD) facilitates the identification of new targets for effective treatments. Recently available large-scale multi-omics datasets provide opportunities to use computational approaches for such studies. Here, we devised a novel disease gene identification (digID) computational framework that consists of a semi-supervised deep learning classifier to predict AD-associated genes and a protein-protein interaction (PPI) network-based analysis to prioritize the importance of these predicted genes in AD. digID predicted 1,529 AD-associated genes and revealed potentially new AD molecular mechanisms and therapeutic targets including GNAI1 and GNB1, two G-protein subunits that regulate cell signaling, and KNG1, an upstream modulator of CDC42 small G-protein signaling and mediator of inflammation and candidate coregulator of amyloid precursor protein (APP). Analysis of mRNA expression validated their dysregulation in AD brains but further revealed the significant spatial patterns in different brain regions as well as among different sub-regions of frontal cortex and hippocampi. Super-resolution STochastic Optical Reconstruction Microscopy (STORM) further demonstrated their subcellular co-localization and molecular interactions with APP in a transgenic mouse model of both sexes with AD-like mutations. These studies support the predictions made by digID while highlighting the importance of concurrent biological validation of computationally identified gene clusters as potential new AD therapeutic targets.Significance Statement Powerful computational approaches such as machine learning (ML) can interrogate large-scale multi-omics datasets to predict disease-associated genes unbiasedly via systemic study. This study presents a new disease gene identification (digID) computational framework using semi-supervised deep learning classifier. Empowered by the super-resolution imaging and the spatial biology paradigm, we further revealed that the ML model predicted AD-related G-protein signaling is subject to spatial expression dysregulation. Therefore, computational discoveries require independent biological validation to yield medical insights and our data highlight three novel G-protein genes and their signaling networks to be potential new AD therapeutic targets.

2.
J Alzheimers Dis ; 95(4): 1643-1656, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37718806

RESUMO

BACKGROUND: RhoA signaling is widely reported to be dysregulated in Alzheimer's disease (AD), but its therapeutic targeting demonstrated mixed outcomes. We hypothesize that the activation and inactivation states of RhoA and LIMK are different in the cortex and in subregions of hippocampus along the rostral-caudal dimensions. OBJECTIVE: We intended to elucidate the plane and spatial dependent RhoA signaling in association with AD. METHODS: We applied antibody pRhoA that recognizes an inactive state of RhoA (S188 phosphorylation) and antibody pLIMK against an active state of LIMK (T508 phosphorylation) to investigate RhoA signaling in wildtype (WT) and triple transgenic AD (3xTg-AD) mouse model. We prepared serial sections from the rostral to caudal coronal planes of the entire mouse brain followed by immunofluorescence staining with pRhoA and pLIMK antibodies. RESULTS: Both pRhoA and pLIMK elicited a shift of expression pattern from rostral to caudal planes. Additionally, pRhoA demonstrated dynamic redistribution between the nucleus and cytoplasm. pLIMK did not show such nucleus and cytoplasm redistribution but the expression level was changed from rostral to caudal planes. At some planes, pRhoA showed an increasing trend in expression in the cortex but a decreasing trend in the dentate gyrus of the 3xTg-AD mouse hippocampus. pLIMK tends to decrease in the cortex but increase in the dentate gyrus of 3xTg-AD mouse hippocampus. CONCLUSIONS: RhoA activation is dysregulated in both human and mouse AD brains, and the RhoA-LIMK signaling axis reveals spatial dysregulation along the rostral-caudal plane dimensions.


Assuntos
Doença de Alzheimer , Animais , Humanos , Camundongos , Doença de Alzheimer/metabolismo , Encéfalo/metabolismo , Córtex Cerebral/metabolismo , Modelos Animais de Doenças , Hipocampo/metabolismo , Camundongos Transgênicos , Transdução de Sinais , Proteína rhoA de Ligação ao GTP/metabolismo , Quinases Lim/metabolismo
3.
Front Cell Neurosci ; 17: 1084769, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-36779014

RESUMO

Neurodegeneration is associated with defects in cytoskeletal dynamics and dysfunctions of the vesicular trafficking and sorting systems. In the last few decades, studies have demonstrated that the key regulators of cytoskeletal dynamics are proteins from the Rho family GTPases, meanwhile, the central hub for vesicle sorting and transport between target membranes is the Rab family of GTPases. In this regard, the role of Rho and Rab GTPases in the induction and maintenance of distinct functional and morphological neuronal domains (such as dendrites and axons) has been extensively studied. Several members belonging to these two families of proteins have been associated with many neurodegenerative disorders ranging from dementia to motor neuron degeneration. In this analysis, we attempt to present a brief review of the potential crosstalk between the Rab and Rho family members in neurodegenerative pathologies such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington disease, and amyotrophic lateral sclerosis (ALS).

4.
Front Med (Lausanne) ; 7: 626796, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33553219

RESUMO

Coronavirus disease 19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first emerged in late 2019 and has since rapidly become a global pandemic. SARS-CoV-2 infection causes damages to the lung and other organs. The clinical manifestations of COVID-19 range widely from asymptomatic infection, mild respiratory illness to severe pneumonia with respiratory failure and death. Autopsy studies demonstrate that diffuse alveolar damage, inflammatory cell infiltration, edema, proteinaceous exudates, and vascular thromboembolism in the lung as well as extrapulmonary injuries in other organs represent key pathological findings. Herein, we hypothesize that GPR4 plays an integral role in COVID-19 pathophysiology and is a potential therapeutic target for the treatment of COVID-19. GPR4 is a pro-inflammatory G protein-coupled receptor (GPCR) highly expressed in vascular endothelial cells and serves as a "gatekeeper" to regulate endothelium-blood cell interaction and leukocyte infiltration. GPR4 also regulates vascular permeability and tissue edema under inflammatory conditions. Therefore, we hypothesize that GPR4 antagonism can potentially be exploited to mitigate the hyper-inflammatory response, vessel hyper-permeability, pulmonary edema, exudate formation, vascular thromboembolism and tissue injury associated with COVID-19.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA