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Characterizing the mechanism by which endogenous negative regulators of osteoclasts control bone homeostasis under physiological and pathological conditions in mouse models

Characterizing the mechanism by which endogenous negative regulators of osteoclasts control bone homeostasis under physiological and pathological conditions in mouse models
表征小鼠模型生理和病理条件下破骨细胞内源性负调节因子控制骨稳态的机制
批准号:
9307517
负责人:
Wei Chen
金额:
$32.67万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-04-01 至 2022-03-31

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中文摘要
翻译
本应用程序的直接目标是了解破骨细胞(OC)分化是如何通过
英文摘要
The immediate goal of this application is to understand how osteoclast (OC) differentiation is regulated through negative endogenous regulators, which may provide novel therapeutic targets for bone diseases, such as osteoporosis and rheumatoid arthritis (RA). Although positive regulators of OC differentiation through the receptor activator of nuclear factor kB (RANK) ligand (RANKL)-RANK signaling axis have been extensively studied, understanding of negative regulators of OC differentiation is elusive. To identify key negative regulators of OC differentiation, we utilized microarray, gene downregulation, and osteoclastogenesis assays, leading to the isolation of guanine protein alpha subunit 13 (Gα13, encoded by the Gna13 gene) as a potential OC negative regulator. To enable in vivo investigation of the role of Gα13 in OC differentiation, we generated an OC-lineage specific Gna13 conditional knockout (CKO) mouse model by crossing Gna13f/f mice with LysM-Cre (OC precursor specific) mice. Our preliminary data showed that Gna13f/fLysM-Cre mice exhibited a severe osteoporosis from a drastic increase in OC differentiation. We also noted that Gα13 deficiency attenuates RhoA activity and promotes Akt activity in OCs. Consistently, we showed that, as a proof of principle strategy, local constitutively active Gα13 overexpression can protect against bone and cartilage loss while also attenuating inflammation in a mouse model of RA. Based on our preliminary data, we hypothesize that Gα13 is a key negative regulator of OC that controls OC cell lineage commitment and differentiation for bone homeostasis under physiological and pathological conditions through activating RhoA and attenuating AKT signaling pathway. Three specific aims are proposed to test our hypothesis. In Aim 1, we will characterize the bone phenotypes of Gnα13f/fLysM-Cre mice and elucidate the mechanism underlying how Gα13 activates RhoA signaling and attenuates Akt signaling to negatively regulate OC cell lineage commitment and differentiation. In Aim 2 we will determine the upstream Gα13 signaling cascade in OCs through characterization of G protein coupled receptors (GPCRs) coupled with Gα13. We will characterize the mechanism underlying the roles of Gα13 in bone remodeling and pathological bone loss by using dendritic cell (DC)-, monocyte- and OC-specific Gna13 CKO and overexpression transgenic mice in the loss-of-function and gain-of-function analysis, respectively. This study may provide important insights into the roles of negative regulators of OC differentiation in bone homeostasis and osteolytic bone diseases of excessive OC differentiation. Knowledge gained from this study may generate potential therapeutic targets, through characterization of Gα13 signaling in OCs that may be targeted in treating osteolytic bone diseases by mimicking normal OC inhibitory signaling pathway to control OC formation. A multidisciplinary research team, including a bone biologist with expertise in OC biology and animal models of bone diseases; a bone biologist with expertise in OC biology and cell signaling; and an immunologist with expertise in autoimmunity diseases including RA has been established to achieve the research goal.
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An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.
  • 批准号:
    10564824
  • 项目类别:
  • 资助金额:
    $54.37万
  • 财政年份:
    2023
  • 负责人:
    Wei Chen
  • 依托单位:
Establishing translational neuroimaging tools for quantitative assessment of energy metabolism and metabolic reprogramming in healthy and diseased human brain at 7T
  • 批准号:
    10714863
  • 项目类别:
  • 资助金额:
    $63.02万
  • 财政年份:
    2023
  • 负责人:
    Wei Chen
  • 依托单位:
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
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