Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome
Metabolic syndrome (MetS) is a subclinical disease, resulting in increased risk of type 2 diabetes (T2D), cardiovascular diseases, cancer, and mortality. Dynamical network biomarkers (DNB) theory has been developed to provide early-warning signals of the disease state during a preclinical stage. To...
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2025-03-01
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| author | Kazutaka Akagi Ying-Jie Jin Keiichi Koizumi Makito Oku Kaisei Ito Xun Shen Jun-ichi Imura Kazuyuki Aihara Shigeru Saito |
| author_facet | Kazutaka Akagi Ying-Jie Jin Keiichi Koizumi Makito Oku Kaisei Ito Xun Shen Jun-ichi Imura Kazuyuki Aihara Shigeru Saito |
| author_sort | Kazutaka Akagi |
| collection | DOAJ |
| description | Metabolic syndrome (MetS) is a subclinical disease, resulting in increased risk of type 2 diabetes (T2D), cardiovascular diseases, cancer, and mortality. Dynamical network biomarkers (DNB) theory has been developed to provide early-warning signals of the disease state during a preclinical stage. To improve the efficiency of DNB analysis for the target genes discovery, the DNB intervention analysis based on the control theory has been proposed. However, its biological validation in a specific disease such as MetS remains unexplored. Herein, we identified eight candidate genes from adipose tissue of MetS model mice at the preclinical stage by the DNB intervention analysis. Using <i>Drosophila</i>, we conducted RNAi-mediated knockdown screening of these candidate genes and identified <i>vasa</i> (also known as <i>DDX4</i>), encoding a DEAD-box RNA helicase, as a fat metabolism-associated gene. Fat body-specific knockdown of <i>vasa</i> abrogated high-fat diet (HFD)-induced enhancement of starvation resistance through up-regulation of triglyceride lipase. We also confirmed that DDX4 expressing adipocytes are increased in HFD-fed mice and high BMI patients using the public datasets. These results prove the potential of the DNB intervention analysis to search the therapeutic targets for diseases at the preclinical stage. |
| format | Article |
| id | doaj-art-034ad11ae6564604bddc669c4e6b09aa |
| institution | DOAJ |
| issn | 2073-4409 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
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| series | Cells |
| spelling | doaj-art-034ad11ae6564604bddc669c4e6b09aa2025-08-20T02:42:42ZengMDPI AGCells2073-44092025-03-0114641510.3390/cells14060415Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic SyndromeKazutaka Akagi0Ying-Jie Jin1Keiichi Koizumi2Makito Oku3Kaisei Ito4Xun Shen5Jun-ichi Imura6Kazuyuki Aihara7Shigeru Saito8Division of Presymptomatic Disease, Institute of Natural Medicine, University of Toyama, Toyama 930-0194, JapanGraduate School of Pharma-Medical Sciences, University of Toyama, Toyama 930-0194, JapanDivision of Presymptomatic Disease, Institute of Natural Medicine, University of Toyama, Toyama 930-0194, JapanResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, JapanDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, JapanGraduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo 184-8588, JapanDepartment of Systems and Control Engineering, School of Engineering, Institute of Science Tokyo, Tokyo 152-8552, JapanInternational Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo 113-0033, JapanResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, JapanMetabolic syndrome (MetS) is a subclinical disease, resulting in increased risk of type 2 diabetes (T2D), cardiovascular diseases, cancer, and mortality. Dynamical network biomarkers (DNB) theory has been developed to provide early-warning signals of the disease state during a preclinical stage. To improve the efficiency of DNB analysis for the target genes discovery, the DNB intervention analysis based on the control theory has been proposed. However, its biological validation in a specific disease such as MetS remains unexplored. Herein, we identified eight candidate genes from adipose tissue of MetS model mice at the preclinical stage by the DNB intervention analysis. Using <i>Drosophila</i>, we conducted RNAi-mediated knockdown screening of these candidate genes and identified <i>vasa</i> (also known as <i>DDX4</i>), encoding a DEAD-box RNA helicase, as a fat metabolism-associated gene. Fat body-specific knockdown of <i>vasa</i> abrogated high-fat diet (HFD)-induced enhancement of starvation resistance through up-regulation of triglyceride lipase. We also confirmed that DDX4 expressing adipocytes are increased in HFD-fed mice and high BMI patients using the public datasets. These results prove the potential of the DNB intervention analysis to search the therapeutic targets for diseases at the preclinical stage.https://www.mdpi.com/2073-4409/14/6/415dynamical network biomarkers theoryDNB intervention analysismetabolic syndrome<i>Drosophila melanogaster</i> |
| spellingShingle | Kazutaka Akagi Ying-Jie Jin Keiichi Koizumi Makito Oku Kaisei Ito Xun Shen Jun-ichi Imura Kazuyuki Aihara Shigeru Saito Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome Cells dynamical network biomarkers theory DNB intervention analysis metabolic syndrome <i>Drosophila melanogaster</i> |
| title | Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome |
| title_full | Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome |
| title_fullStr | Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome |
| title_full_unstemmed | Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome |
| title_short | Integration of Dynamical Network Biomarkers, Control Theory and <i>Drosophila</i> Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome |
| title_sort | integration of dynamical network biomarkers control theory and i drosophila i model identifies vasa ddx4 as the potential therapeutic targets for metabolic syndrome |
| topic | dynamical network biomarkers theory DNB intervention analysis metabolic syndrome <i>Drosophila melanogaster</i> |
| url | https://www.mdpi.com/2073-4409/14/6/415 |
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