Acknowledgement
This study was supported by a National Research Foundation of Korea grant funded by the Korean government (NRF-2018R1A2A3075397) and by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI19C1178).
References
- Susser M, Susser E. Choosing a future for epidemiology: II. From black box to Chinese boxes and eco-epidemiology. Am J Public Health 1996;86(5):674-677. https://doi.org/10.2105/AJPH.86.5.674
- Hu FB. Metabolic profiling of diabetes: from black-box epidemiology to systems epidemiology. Clin Chem 2011;57(9):1224-1226. https://doi.org/10.1373/clinchem.2011.167056
- Weed DL. Beyond black box epidemiology. Am J Public Health 1998;88(1):12-14. https://doi.org/10.2105/AJPH.88.1.12
- Laszlo A, Krippner S. Chapter 3: systems theories: their origins, foundations, and development. In: Jordan JS, editor. Systems theories and a priori aspects of perception. Amsterdam: Elsevier; 1998, p. 47-74.
- Lund E, Dumeaux V. Systems epidemiology in cancer. Cancer Epidemiol Biomarkers Prev 2008;17(11):2954-2957. https://doi.org/10.1158/1055-9965.EPI-08-0519
- Haring R, Wallaschofski H. Diving through the "-omics": the case for deep phenotyping and systems epidemiology. OMICS 2012;16(5):231-234. https://doi.org/10.1089/omi.2011.0108
- Cornelis MC, Hu FB. Systems epidemiology: a new direction in nutrition and metabolic disease research. Curr Nutr Rep 2013;2(4):10.1007/s13668-013-0052-4.
- Dammann O, Gray P, Gressens P, Wolkenhauer O, Leviton A. Systems epidemiology: what's in a name? Online J Public Health Inform 2014;6(3):e198. https://doi.org/10.5210/ojphi.v6i3.5571
- Yan J, Risacher SL, Shen L, Saykin AJ. Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data. Brief Bioinform 2018;19(6):1370-1381.
- Barabasi AL, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet 2011;12(1):56-68. https://doi.org/10.1038/nrg2918
- Hevey D. Network analysis: a brief overview and tutorial. Health Psychol Behav Med 2018;6(1):301-328. https://doi.org/10.1080/21642850.2018.1521283
- Batushansky A, Toubiana D, Fait A. Correlation-based network generation, visualization, and analysis as a powerful tool in biological studies: a case study in cancer cell metabolism. Biomed Res Int 2016;2016:8313272.
- Epskamp S, Fried EI. A tutorial on regularized partial correlation networks. Psychol Methods 2018;23(4):617-634. https://doi.org/10.1037/met0000167
- Perez De Souza L, Alseekh S, Brotman Y, Fernie AR. Network-based strategies in metabolomics data analysis and interpretation: from molecular networking to biological interpretation. Expert Rev Proteomics 2020;17(4):243-255. https://doi.org/10.1080/14789450.2020.1766975
- Kohl M, Wiese S, Warscheid B. Cytoscape: software for visualization and analysis of biological networks. Methods Mol Biol 2011;696:291-303. https://doi.org/10.1007/978-1-60761-987-1_18
- Kolaczyk ED, Csardi G. Statistical analysis of network data with R. New York: Springer; 2014, p. 29-41.
- Epskamp S, Borsboom D, Fried EI. Estimating psychological networks and their accuracy: a tutorial paper. Behav Res Methods 2018;50(1):195-212. https://doi.org/10.3758/s13428-017-0862-1
- Langfelder P, Horvath S. Fast R functions for robust correlations and hierarchical clustering. J Stat Softw 2012;46(11):i11.
- Kim S. ppcor: an R package for a fast calculation to semi-partial correlation coefficients. Commun Stat Appl Methods 2015;22(6):665-674. https://doi.org/10.5351/CSAM.2015.22.6.665
- Pedersen TL. Package 'ggraph'; 2021 [cited 2021 Jul 1]. Available from: https://mirror.uned.ac.cr/cran/web/packages/ggraph/ggraph.pdf.
- Csardi G. Package 'igraph'; 2015 [cited 2021 Jul 1]. Available from: https://cran.microsoft.com/snapshot/2017-05-27/web/packages/igraph/igraph.pdf.
- Epskamp S, Cramer AO, Waldorp LJ, Schmittmann VD, Borsboom D. qgraph: network visualizations of relationships in psychometric data. J Stat Softw 2012;48(4):1-18.
- Gentry J, Gentleman R, Huber W. How to plot a graph using Rgraphviz; 2021 [cited 2021 May 1]. Available from: http://www.bioconductor.org/packages/release/bioc/vignettes/Rgraphviz/inst/doc/Rgraphviz.pdf.
- Riaz MR, Preston GM, Mithani A. MAPPS: a web-based tool for metabolic pathway prediction and network analysis in the postgenomic era. ACS Synth Biol 2020;9(5):1069-1082. https://doi.org/10.1021/acssynbio.9b00397
- Zhou D, Zhu W, Sun T, Wang Y, Chi Y, Chen T, et al. iMAP: a web server for metabolomics data integrative analysis. Front Chem 2021;9:659656. https://doi.org/10.3389/fchem.2021.659656
- Fukushima A. DiffCorr: an R package to analyze and visualize differential correlations in biological networks. Gene 2013;518(1):209-214. https://doi.org/10.1016/j.gene.2012.11.028
- Li Z, Zhang Y, Hu T, Likhodii S, Sun G, Zhai G, et al. Differential metabolomics analysis allows characterization of diversity of metabolite networks between males and females. PLoS One 2018;13(11):e0207775. https://doi.org/10.1371/journal.pone.0207775
- Wang Y, Wang G, Jing RN, Hu T, Likhodii S, Sun G, et al. Metabolomics analysis of human plasma metabolites reveals the age-and sex-specific associations. Liq Chromatogr Relat Technol 2020;43(5-6):185-194. https://doi.org/10.1080/10826076.2019.1701016
- Costello CA, Hu T, Liu M, Zhang W, Furey A, Fan Z, et al. Differential correlation network analysis identified novel metabolomics signatures for non-responders to total joint replacement in primary osteoarthritis patients. Metabolomics 2020;16(5):61. https://doi.org/10.1007/s11306-020-01683-1
- Huang T, Glass K, Zeleznik OA, Kang JH, Ivey KL, Sonawane AR, et al. A network analysis of biomarkers for type 2 diabetes. Diabetes 2019;68(2):281-290. https://doi.org/10.2337/db18-0892
- Floegel A, Wientzek A, Bachlechner U, Jacobs S, Drogan D, Prehn C, et al. Linking diet, physical activity, cardiorespiratory fitness and obesity to serum metabolite networks: findings from a population-based study. Int J Obes (Lond) 2014;38(11):1388-1396. https://doi.org/10.1038/ijo.2014.39
Cited by
- Network Analysis of Demographics, Dietary Intake, and Comorbidity Interactions vol.13, pp.10, 2021, https://doi.org/10.3390/nu13103563