Literature DB >> 26776179

METABOLOMICS DIFFERENTIAL CORRELATION NETWORK ANALYSIS OF OSTEOARTHRITIS.

Ting Hu1, Weidong Zhang, Zhaozhi Fan, Guang Sun, Sergei Likhodi, Edward Randell, Guangju Zhai.   

Abstract

Osteoarthritis (OA) significantly compromises the life quality of affected individuals and imposes a substantial economic burden on our society. Unfortunately the pathogenesis of the disease is till poorly understood and no effective medications have been developed. OA is a complex disease that involves both genetic and environmental influences. To elucidate the complex interlinked structure of metabolic processes associated with OA, we developed a differential correlation network approach to detecting the interconnection of metabolite pairs whose relationships are significantly altered due to the diseased process. Through topological analysis of such a differential network, we identified key metabolites that played an important role in governing the connectivity and information flow of the network. Identification of these key metabolites suggests the association of their underlying cellular processes with OA and may help elucidate the pathogenesis of the disease and the development of novel targeted therapies.

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Year:  2016        PMID: 26776179

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  11 in total

1.  Immunodeficiency in Pancreatic Adenocarcinoma with Diabetes Revealed by Comparative Genomics.

Authors:  Yuanqing Yan; Ruli Gao; Thao L P Trinh; Maria B Grant
Journal:  Clin Cancer Res       Date:  2017-07-06       Impact factor: 12.531

Review 2.  From correlation to causation: analysis of metabolomics data using systems biology approaches.

Authors:  Antonio Rosato; Leonardo Tenori; Marta Cascante; Pedro Ramon De Atauri Carulla; Vitor A P Martins Dos Santos; Edoardo Saccenti
Journal:  Metabolomics       Date:  2018-02-27       Impact factor: 4.290

3.  An evolutionary learning and network approach to identifying key metabolites for osteoarthritis.

Authors:  Ting Hu; Karoliina Oksanen; Weidong Zhang; Ed Randell; Andrew Furey; Guang Sun; Guangju Zhai
Journal:  PLoS Comput Biol       Date:  2018-03-01       Impact factor: 4.475

4.  Measuring the importance of vertices in the weighted human disease network.

Authors:  Seyed Mehrzad Almasi; Ting Hu
Journal:  PLoS One       Date:  2019-03-22       Impact factor: 3.240

5.  Differential metabolomics networks analysis of menopausal status.

Authors:  Xiujuan Cui; Xiaoyan Yu; Guang Sun; Ting Hu; Sergei Likhodii; Jingmin Zhang; Edward Randell; Xiang Gao; Zhaozhi Fan; Weidong Zhang
Journal:  PLoS One       Date:  2019-09-18       Impact factor: 3.240

Review 6.  Can joint fluid metabolic profiling (or "metabonomics") reveal biomarkers for osteoarthritis and inflammatory joint disease?: A systematic review.

Authors:  Pouya Akhbari; Urvi Karamchandani; Matthew K J Jaggard; Goncalo Graça; Rajarshi Bhattacharya; John C Lindon; Horace R T Williams; Chinmay M Gupte
Journal:  Bone Joint Res       Date:  2020-05-16       Impact factor: 5.853

7.  Disparity-filtered differential correlation network analysis: a case study on CRC metabolomics.

Authors:  Silvia Sabatini; Amalia Gastaldelli
Journal:  J Integr Bioinform       Date:  2021-11-19

8.  Differential correlation network analysis identified novel metabolomics signatures for non-responders to total joint replacement in primary osteoarthritis patients.

Authors:  Christie A Costello; Ting Hu; Ming Liu; Weidong Zhang; Andrew Furey; Zhaozhi Fan; Proton Rahman; Edward W Randell; Guangju Zhai
Journal:  Metabolomics       Date:  2020-04-25       Impact factor: 4.290

9.  Metabolic networks of plasma and joint fluid base on differential correlation.

Authors:  Bingyong Xu; Hong Su; Ruya Wang; Yixiao Wang; Weidong Zhang
Journal:  PLoS One       Date:  2021-02-22       Impact factor: 3.240

10.  Guidelines for correlation coefficient threshold settings in metabolite correlation networks exemplified on a potato association panel.

Authors:  David Toubiana; Helena Maruenda
Journal:  BMC Bioinformatics       Date:  2021-03-10       Impact factor: 3.169

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