|
[1]
|
Gach O, El HZ, Lancellotti P. (2018) [Acute Coronary Syndrome]. Revue Médicale de Liège, 73, 243-250.
|
|
[2]
|
Puri, R. and Nissen, S. (2013) The Complementary Roles of Imaging and ‘Omics’ for Future Anti-Atherosclerotic Drug Development. Current Pharmaceutical Design, 19, 5963-5971. [Google Scholar] [CrossRef] [PubMed]
|
|
[3]
|
Wishart, D.S., Guo, A., Oler, E., Wang, F., Anjum, A., Peters, H., Dizon, R., Sayeeda, Z., Tian, S., Lee, B.L., Berjanskii, M., Mah, R., Yamamoto, M., Jovel, J., Torres-Calzada, C., Hiebert-Giesbrecht, M., Lui, V.W., Varshavi, D., Varshavi, D., Allen, D., Arndt, D., Khetarpal, N., Sivakumaran, A., Harford, K., Sanford, S., Yee, K., Cao, X., Budinski, Z., Liigand, J., Zhang, L., Zheng, J., Mandal, R., Karu, N., Dambrova, M., Schiöth, H.B., Greiner, R. and Gautam, V. (2021) HMDB 5.0: The Human Metabolome Database for 2022. Nucleic Acids Research, 50, D622-D631. [Google Scholar] [CrossRef] [PubMed]
|
|
[4]
|
Hunter, W.G., Kelly, J.P., McGarrah, R.W., Khouri, M.G., Craig, D., Haynes, C., Ilkayeva, O., Stevens, R.D., Bain, J.R., Muehlbauer, M.J., Newgard, C.B., Felker, G.M., Hernandez, A.F., Velazquez, E.J., Kraus, W.E. and Shah, S.H. (2016) Metabolomic Profiling Identifies Novel Circulating Biomarkers of Mitochondrial Dysfunction Differentially Elevated in Heart Failure with Preserved versus Reduced Ejection Fraction: Evidence for Shared Metabolic Impairments in Clinical Heart Failure. Journal of the American Heart Association, 5, e003190. [Google Scholar] [CrossRef] [PubMed]
|
|
[5]
|
Sun, H., Olson, K.C., Gao, C., Prosdocimo, D.A., Zhou, M., Wang, Z., Jeyaraj, D., Youn, J., Ren, S., Liu, Y., Rau, C.D., Shah, S., Ilkayeva, O., Gui, W., William, N.S., Wynn, R.M., Newgard, C.B., Cai, H., Xiao, X., Chuang, D.T., Schulze, P.C., Lynch, C., Jain, M.K. and Wang, Y. (2016) Catabolic Defect of Branched-Chain Amino Acids Promotes Heart Failure. Circulation, 133, 2038-2049. [Google Scholar] [CrossRef] [PubMed]
|
|
[6]
|
Lanfear, D.E., Gibbs, J.J., Li, J., She, R., Petucci, C., Culver, J.A., Tang, W.H.W., Pinto, Y.M., Williams, L.K., Sabbah, H.N. and Gardell, S.J. (2017) Targeted Metabolomic Profiling of Plasma and Survival in Heart Failure Patients. JACC: Heart Failure, 5, 823-832. [Google Scholar] [CrossRef] [PubMed]
|
|
[7]
|
Pouralijan Amiri, M., Khoshkam, M., Salek, R.M., Madadi, R., Faghanzadeh Ganji, G. and Ramazani, A. (2019) Metabolomics in Early Detection and Prognosis of Acute Coronary Syndrome. Clinica Chimica Acta, 495, 43-53. [Google Scholar] [CrossRef] [PubMed]
|
|
[8]
|
Dunn, W.B., Goodacre, R., Neyses, L. and Mamas, M. (2011) Integration of Metabolomics in Heart Disease and Diabetes Research: Current Achievements and Future Outlook. Bioanalysis, 3, 2205-2222. [Google Scholar] [CrossRef] [PubMed]
|
|
[9]
|
McGarrah, R.W., Crown, S.B., Zhang, G., Shah, S.H. and Newgard, C.B. (2018) Cardiovascular Metabolomics. Circulation Research, 122, 1238-1258. [Google Scholar] [CrossRef] [PubMed]
|
|
[10]
|
Wang, Z., Klipfell, E., Bennett, B.J., Koeth, R., Levison, B.S., DuGar, B., Feldstein, A.E., Britt, E.B., Fu, X., Chung, Y., Wu, Y., Schauer, P., Smith, J.D., Allayee, H., Tang, W.H.W., DiDonato, J.A., Lusis, A.J. and Hazen, S.L. (2011) Gut Flora Metabolism of Phosphatidylcholine Promotes Cardiovascular Disease. Nature, 472, 57-63. [Google Scholar] [CrossRef] [PubMed]
|
|
[11]
|
Teul, J., Garcia, A., Tuñón, J., Martin-Ventura, J.L., Tarín, N., Bescós, L.L., Egido, J., Barbas, C. and Rupérez, F.J. (2011) Targeted and Non-Targeted Metabolic Time Trajectory in Plasma of Patients after Acute Coronary Syndrome. Journal of Pharmaceutical and Biomedical Analysis, 56, 343-351. [Google Scholar] [CrossRef] [PubMed]
|
|
[12]
|
Oakman, C., Tenori, L., Biganzoli, L., Santarpia, L., Cappadona, S., Luchinat, C. and Di Leo, A. (2011) Uncovering the Metabolomic Fingerprint of Breast Cancer. The International Journal of Biochemistry & Cell Biology, 43, 1010-1020. [Google Scholar] [CrossRef] [PubMed]
|
|
[13]
|
Krone, N., Hughes, B.A., Lavery, G.G., Stewart, P.M., Arlt, W. and Shackleton, C.H.L. (2010) Gas Chromatography/Mass Spectrometry (GC/MS) Remains a Pre-Eminent Discovery Tool in Clinical Steroid Investigations Even in the Era of Fast Liquid Chromatography Tandem Mass Spectrometry (LC/MS/MS). The Journal of Steroid Biochemistry and Molecular Biology, 121, 496-504. [Google Scholar] [CrossRef] [PubMed]
|
|
[14]
|
Sabatine, M.S., Liu, E., Morrow, D.A., Heller, E., McCarroll, R., Wiegand, R., Berriz, G.F., Roth, F.P. and Gerszten, R.E. (2005) Metabolomic Identification of Novel Biomarkers of Myocardial Ischemia. Circulation, 112, 3868-3875. [Google Scholar] [CrossRef] [PubMed]
|
|
[15]
|
Drexler, D.M., Reily, M.D. and Shipkova, P.A. (2010) Advances in Mass Spectrometry Applied to Pharmaceutical Metabolomics. Analytical and Bioanalytical Chemistry, 399, 2645-2653. [Google Scholar] [CrossRef] [PubMed]
|
|
[16]
|
Boulesteix, A.L. and Strimmer, K. (2006) Partial Least Squares: A Versatile Tool for the Analysis of High-Dimensional Genomic Data. Briefings in Bioinformatics, 8, 32-44. [Google Scholar] [CrossRef] [PubMed]
|
|
[17]
|
Posma, J.M., Robinette, S.L., Holmes, E. and Nicholson, J.K. (2013) MetaboNetworks, an Interactive Matlab-Based Toolbox for Creating, Customizing and Exploring Sub-Networks from KEGG. Bioinformatics, 30, 893-895. [Google Scholar] [CrossRef] [PubMed]
|
|
[18]
|
Chong, J., Soufan, O., Li, C., Caraus, I., Li, S., Bourque, G., Wishart, D.S. and Xia, J. (2018) MetaboAnalyst 4.0: Towards More Transparent and Integrative Metabolomics Analysis. Nucleic Acids Research, 46, W486-W494. [Google Scholar] [CrossRef] [PubMed]
|
|
[19]
|
Lynch, M., Barallobre‐Barreiro, J., Jahangiri, M. and Mayr, M. (2016) Vascular Proteomics in Metabolic and Cardiovascular Diseases. Journal of Internal Medicine, 280, 325-338. [Google Scholar] [CrossRef] [PubMed]
|
|
[20]
|
Soppert, J., Lehrke, M., Marx, N., Jankowski, J. and Noels, H. (2020) Lipoproteins and Lipids in Cardiovascular Disease: From Mechanistic Insights to Therapeutic Targeting. Advanced Drug Delivery Reviews, 159, 4-33. [Google Scholar] [CrossRef] [PubMed]
|
|
[21]
|
Ferreira-Divino, L.F., Suvitaival, T., Rotbain Curovic, V., Tofte, N., Trošt, K., Mattila, I.M., Theilade, S., Winther, S.A., Hansen, T.W., Frimodt-Møller, M., Legido-Quigley, C. and Rossing, P. (2022) Circulating Metabolites and Molecular Lipid Species Are Associated With Future Cardiovascular Morbidity and Mortality in Type 1 Diabetes. Cardiovascular Diabetology, 21, Article No. 153. [Google Scholar] [CrossRef] [PubMed]
|
|
[22]
|
Surendran, A., Atefi, N., Zhang, H., Aliani, M. and Ravandi, A. (2021) Defining Acute Coronary Syndrome through Metabolomics. Metabolites, 11, Article 685. [Google Scholar] [CrossRef] [PubMed]
|
|
[23]
|
Tran, D.H. and Wang, Z.V. (2019) Glucose Metabolism in Cardiac Hypertrophy and Heart Failure. Journal of the American Heart Association, 8, e012673. [Google Scholar] [CrossRef] [PubMed]
|
|
[24]
|
Wende, A.R., Brahma, M.K., McGinnis, G.R. and Young, M.E. (2017) Metabolic Origins of Heart Failure. JACC: Basic to Translational Science, 2, 297-310. [Google Scholar] [CrossRef] [PubMed]
|
|
[25]
|
Tian, R. and Abel, E.D. (2001) Responses of GLUT4-Deficient Hearts to Ischemia Underscore the Importance of Glycolysis. Circulation, 103, 2961-2966. [Google Scholar] [CrossRef] [PubMed]
|
|
[26]
|
Szablewski, L. (2017) Glucose Transporters in Healthy Heart and in Cardiac Disease. International Journal of Cardiology, 230, 70-75. [Google Scholar] [CrossRef] [PubMed]
|
|
[27]
|
Heather, L.C., Pates, K.M., Atherton, H.J., Cole, M.A., Ball, D.R., Evans, R.D., Glatz, J.F., Luiken, J.J., Griffin, J.L. and Clarke, K. (2013) Differential Translocation of the Fatty Acid Transporter, FAT/CD36, and the Glucose Transporter, GLUT4, Coordinates Changes in Cardiac Substrate Metabolism during Ischemia and Reperfusion. Circulation: Heart Failure, 6, 1058-1066. [Google Scholar] [CrossRef] [PubMed]
|
|
[28]
|
Taegtmeyer, H. (1978) Metabolic Responses to Cardiac Hypoxia. Increased Production of Succinate by Rabbit Papillary Muscles. Circulation Research, 43, 808-815. [Google Scholar] [CrossRef] [PubMed]
|
|
[29]
|
Chouchani, E.T., Pell, V.R., Gaude, E., Aksentijević, D., Sundier, S.Y., Robb, E.L., Logan, A., Nadtochiy, S.M., Ord, E.N.J., Smith, A.C., Eyassu, F., Shirley, R., Hu, C., Dare, A.J., James, A.M., Rogatti, S., Hartley, R.C., Eaton, S., Costa, A.S.H., Brookes, P.S., Davidson, S.M., Duchen, M.R., Saeb-Parsy, K., Shattock, M.J., Robinson, A.J., Work, L.M., Frezza, C., Krieg, T. and Murphy, M.P. (2014) Ischaemic Accumulation of Succinate Controls Reperfusion Injury Through Mitochondrial ROS. Nature, 515, 431-435. [Google Scholar] [CrossRef] [PubMed]
|
|
[30]
|
Rauckhorst, A.J., Borcherding, N., Pape, D.J., Kraus, A.S., Scerbo, D.A. and Taylor, E.B. (2022) Mouse Tissue Harvest-Induced Hypoxia Rapidly Alters the in Vivo Metabolome, Between-Genotype Metabolite Level Differences, and 13c-Tracing Enrichments. Molecular Metabolism, 66, Article ID: 101596. [Google Scholar] [CrossRef] [PubMed]
|
|
[31]
|
Kohlhauer, M., Dawkins, S., Costa, A.S.H., Lee, R., Young, T., Pell, V.R., Choudhury, R.P., Banning, A.P., Kharbanda, R.K., Saeb‐Parsy, K., Murphy, M.P., Frezza, C., Krieg, T., Channon, K.M. and Oxford Acute Myocardial Infarction (OxAMI) Study (2018) Metabolomic Profiling in Acute ST‐Segment-Elevation Myocardial Infarction Identifies Succinate as an Early Marker of Human Ischemia-Reperfusion Injury. Journal of the American Heart Association, 7, e007546. [Google Scholar] [CrossRef] [PubMed]
|
|
[32]
|
Hart, G.W. and Copeland, R.J. (2010) Glycomics Hits the Big Time. Cell, 143, 672-676. [Google Scholar] [CrossRef] [PubMed]
|
|
[33]
|
Wittenbecher, C., Štambuk, T., Kuxhaus, O., Rudman, N., Vučković, F., Štambuk, J., Schiborn, C., Rahelić, D., Dietrich, S., Gornik, O., Perola, M., Boeing, H., Schulze, M.B. and Lauc, G. (2020) Plasma N-Glycans as Emerging Biomarkers of Cardiometabolic Risk: A Prospective Investigation in the EPIC-Potsdam Cohort Study. Diabetes Care, 43, 661-668. [Google Scholar] [CrossRef] [PubMed]
|
|
[34]
|
Lim, S.Y., Hendra, C., Yeo, X.H., Tan, X.Y., Ng, B.H., Laserna, A.K.C., Tan, S.H., Chan, M.Y., Khan, S.H., Chen, S. and Li, S.F.Y. (2021) N-Glycan Profiles of Acute Myocardial Infarction Patients Reveal Potential Biomarkers for Diagnosis, Severity Assessment and Treatment Monitoring. Glycobiology, 32, 469-482. [Google Scholar] [CrossRef] [PubMed]
|
|
[35]
|
Barba, I., de León, G., Martín, E., Cuevas, A., Aguade, S., Candell‐Riera, J., Barrabés, J.A. and Garcia‐Dorado, D. (2008) Nuclear Magnetic Resonance‐Based Metabolomics Predicts Exercise‐induced Ischemia in Patients with Suspected Coronary Artery Disease. Magnetic Resonance in Medicine, 60, 27-32. [Google Scholar] [CrossRef] [PubMed]
|
|
[36]
|
Dhillon, O.S., Narayan, H.K., Quinn, P.A., Squire, I.B., Davies, J.E. and Ng, L.L. (2011) Interleukin 33 and ST2 in Non—ST-Elevation Myocardial Infarction: Comparison with Global Registry of Acute Coronary Events Risk Scoring and NT-proBNP. American Heart Journal, 161, 1163-1170. [Google Scholar] [CrossRef] [PubMed]
|
|
[37]
|
Barderas, M.G., Laborde, C.M., Posada, M., de la Cuesta, F., Zubiri, I., Vivanco, F. and Alvarez-Llamas, G. (2011) Metabolomic Profiling for Identification of Novel Potential Biomarkers in Cardiovascular Diseases. Journal of Biomedicine and Biotechnology, 2011, Article ID: 790132. [Google Scholar] [CrossRef] [PubMed]
|
|
[38]
|
Roberts, L.D., McCombie, G., Titman, C.M. and Griffin, J.L. (2008) A Matter of Fat: An Introduction to Lipidomic Profiling Methods. Journal of Chromatography B, 871, 174-181. [Google Scholar] [CrossRef] [PubMed]
|
|
[39]
|
Diehl, P., Nienaber, F., Zaldivia, M.T.K., Stamm, J., Siegel, P.M., Mellett, N.A., Wessinger, M., Wang, X., McFadyen, J.D., Bassler, N., Puetz, G., Htun, N.M., Braig, D., Habersberger, J., Helbing, T., Eisenhardt, S.U., Fuller, M., Bode, C., Meikle, P.J., Chen, Y.C. and Peter, K. (2019) Lysophosphatidylcholine Is a Major Component of Platelet Microvesicles Promoting Platelet Activation and Reporting Atherosclerotic Plaque Instability. Thrombosis and Haemostasis, 119, 1295-1310. [Google Scholar] [CrossRef] [PubMed]
|
|
[40]
|
Schober, A. and Siess, W. (2012) Lysophosphatidic Acid in Atherosclerotic Diseases. British Journal of Pharmacology, 167, 465-482. [Google Scholar] [CrossRef] [PubMed]
|
|
[41]
|
Chorell, E., Olsson, T., Jansson, J. and Wennberg, P. (2020) Lysophospholipids as Predictive Markers of ST-Elevation Myocardial Infarction (STEMI) and Non-St-Elevation Myocardial Infarction (NSTEMI). Metabolites, 11, Article 25. [Google Scholar] [CrossRef] [PubMed]
|
|
[42]
|
Walker, A.K., Jacobs, R.L., Watts, J.L., Rottiers, V., Jiang, K., Finnegan, D.M., Shioda, T., Hansen, M., Yang, F., Niebergall, L.J., Vance, D.E., Tzoneva, M., Hart, A.C. and Näär, A.M. (2011) A Conserved SREBP-1/Phosphatidylcholine Feedback Circuit Regulates Lipogenesis in Metazoans. Cell, 147, 840-852. [Google Scholar] [CrossRef] [PubMed]
|
|
[43]
|
Yin, X., de Carvalho, L.P., Chan, M.Y. and Li, S.F.Y. (2017) Integrated Metabolomics and Metallomics Analyses in Acute Coronary Syndrome Patients. Metallomics, 9, 734-743. [Google Scholar] [CrossRef] [PubMed]
|
|
[44]
|
He, X. and Schuchman, E.H. (2018) Ceramide and Ischemia/Reperfusion Injury. Journal of Lipids, 2018, Article ID: 3646725. [Google Scholar] [CrossRef] [PubMed]
|
|
[45]
|
Chatterjee, S. (1998) Sphingolipids in Atherosclerosis and Vascular Biology. Arteriosclerosis, Thrombosis, and Vascular Biology, 18, 1523-1533. [Google Scholar] [CrossRef] [PubMed]
|
|
[46]
|
Bielawska, A.E., Shapiro, J.P., Jiang, L., et al. (1997) Ceramide Is Involved in Triggering of Cardiomyocyte Apoptosis Induced by Ischemia and Reperfusion. The American Journal of Pathology, 151, 1257-1263.
|
|
[47]
|
Chen, H., Wang, Z., Qin, M., Zhang, B., Lin, L., Ma, Q., Liu, C., Chen, X., Li, H., Lai, W. and Zhong, S. (2021) Comprehensive Metabolomics Identified the Prominent Role of Glycerophospholipid Metabolism in Coronary Artery Disease Progression. Frontiers in Molecular Biosciences, 8, Article 632950. [Google Scholar] [CrossRef] [PubMed]
|
|
[48]
|
Laaksonen, R., Ekroos, K., Sysi-Aho, M., Hilvo, M., Vihervaara, T., Kauhanen, D., Suoniemi, M., Hurme, R., März, W., Scharnagl, H., Stojakovic, T., Vlachopoulou, E., Lokki, M., Nieminen, M.S., Klingenberg, R., Matter, C.M., Hornemann, T., Jüni, P., Rodondi, N., Räber, L., Windecker, S., Gencer, B., Pedersen, E.R., Tell, G.S., Nygård, O., Mach, F., Sinisalo, J. and Lüscher, T.F. (2016) Plasma Ceramides Predict Cardiovascular Death in Patients with Stable Coronary Artery Disease and Acute Coronary Syndromes beyond LDL-cholesterol. European Heart Journal, 37, 1967-1976. [Google Scholar] [CrossRef] [PubMed]
|
|
[49]
|
White, P.J., McGarrah, R.W., Herman, M.A., Bain, J.R., Shah, S.H. and Newgard, C.B. (2021) Insulin Action, Type 2 Diabetes, and Branched-Chain Amino Acids: A Two-Way Street. Molecular Metabolism, 52, Article ID: 101261. [Google Scholar] [CrossRef] [PubMed]
|
|
[50]
|
Arany, Z. and Neinast, M. (2018) Branched Chain Amino Acids in Metabolic Disease. Current Diabetes Reports, 18, Article No. 76. [Google Scholar] [CrossRef] [PubMed]
|
|
[51]
|
Neinast, M., Murashige, D. and Arany, Z. (2019) Branched Chain Amino Acids. Annual Review of Physiology, 81, 139-164. [Google Scholar] [CrossRef] [PubMed]
|
|
[52]
|
McGarrah, R.W. and White, P.J. (2022) Branched-Chain Amino Acids in Cardiovascular Disease. Nature Reviews Cardiology, 20, 77-89. [Google Scholar] [CrossRef] [PubMed]
|
|
[53]
|
Xu, Y., Jiang, H., Li, L., Chen, F., Liu, Y., Zhou, M., Wang, J., Jiang, J., Li, X., Fan, X., Zhang, L., Zhang, J., Qiu, J., Wu, Y., Fang, C., Sun, H. and Liu, J. (2020) Branched-Chain Amino Acid Catabolism Promotes Thrombosis Risk by Enhancing Tropomodulin-3 Propionylation in Platelets. Circulation, 142, 49-64. [Google Scholar] [CrossRef] [PubMed]
|
|
[54]
|
Li, Z., Liu, X., Wang, J., Gao, J., Guo, S., Gao, K., Man, H., Wang, Y., Chen, J. and Wang, W. (2015) Analysis of Urinary Metabolomic Profiling for Unstable Angina Pectoris Disease Based on Nuclear Magnetic Resonance Spectroscopy. Molecular BioSystems, 11, 3387-3396. [Google Scholar] [CrossRef] [PubMed]
|
|
[55]
|
Turer, A.T., Stevens, R.D., Bain, J.R., Muehlbauer, M.J., van der Westhuizen, J., Mathew, J.P., Schwinn, D.A., Glower, D.D., Newgard, C.B. and Podgoreanu, M.V. (2009) Metabolomic Profiling Reveals Distinct Patterns of Myocardial Substrate Use in Humans with Coronary Artery Disease or Left Ventricular Dysfunction during Surgical Ischemia/Reperfusion. Circulation, 119, 1736-1746. [Google Scholar] [CrossRef] [PubMed]
|
|
[56]
|
Lee, J.W., Miyawaki, H., Bobst, E.V., Hester, J.D., Ashraf, M. and Bobst, A.M. (1999) Improved Functional Recovery of Ischemic Rat Hearts Due to Singlet Oxygen Scavengers Histidine and Carnosine. Journal of Molecular and Cellular Cardiology, 31, 113-121. [Google Scholar] [CrossRef] [PubMed]
|
|
[57]
|
Bernstein, A.M., Willcox, B.J., Tamaki, H., Kunishima, N., Suzuki, M., Craig Willcox, D., Kristen Yoo, J.-S. and Perls, T.T. (2004) First Autopsy Study of an Okinawan Centenarian: Absence of Many Age-Related Diseases. The Journals of Gerontology: Series A, 59, 1195-1199. [Google Scholar] [CrossRef] [PubMed]
|
|
[58]
|
Vallejo, M., García, A., Tuñón, J., García-Martínez, D., Angulo, S., Martin-Ventura, J.L., Blanco-Colio, L.M., Almeida, P., Egido, J. and Barbas, C. (2009) Plasma Fingerprinting with GC-MS in Acute Coronary Syndrome. Analytical and Bioanalytical Chemistry, 394, 1517-1524. [Google Scholar] [CrossRef] [PubMed]
|
|
[59]
|
Karlstaedt, A. (2021) Stable Isotopes for Tracing Cardiac Metabolism in Diseases. Frontiers in Cardiovascular Medicine, 8, Article 734364. [Google Scholar] [CrossRef] [PubMed]
|
|
[60]
|
Sauer, U. (2006) Metabolic Networks in Motion: 13C‐Based Flux Analysis. Molecular Systems Biology, 2, Article 62. [Google Scholar] [CrossRef] [PubMed]
|
|
[61]
|
Jin, E.S., Lee, M.H. and Malloy, C.R. (2021) 13C NMR of Glutamate for Monitoring the Pentose Phosphate Pathway in Myocardium. NMR in Biomedicine, 34, e4533. [Google Scholar] [CrossRef] [PubMed]
|
|
[62]
|
Bakker, O.B., Aguirre-Gamboa, R., Sanna, S., Oosting, M., Smeekens, S.P., Jaeger, M., Zorro, M., Võsa, U., Withoff, S., Netea-Maier, R.T., Koenen, H.J.P.M., Joosten, I., Xavier, R.J., Franke, L., Joosten, L.A.B., Kumar, V., Wijmenga, C., Netea, M.G. and Li, Y. (2018) Integration of Multi-Omics Data and Deep Phenotyping Enables Prediction of Cytokine Responses. Nature Immunology, 19, 776-786. [Google Scholar] [CrossRef] [PubMed]
|
|
[63]
|
Ritchie, M.D., Holzinger, E.R., Li, R., Pendergrass, S.A. and Kim, D. (2015) Methods of Integrating Data to Uncover Genotype-Phenotype Interactions. Nature Reviews Genetics, 16, 85-97. [Google Scholar] [CrossRef] [PubMed]
|
|
[64]
|
Yao, Q., Xu, Y., Yang, H., Shang, D., Zhang, C., Zhang, Y., Sun, Z., Shi, X., Feng, L., Han, J., Su, F., Li, C. and Li, X. (2015) Global Prioritization of Disease Candidate Metabolites Based on a Multi-Omics Composite Network. Scientific Reports, 5, Article No. 17201. [Google Scholar] [CrossRef] [PubMed]
|
|
[65]
|
Yang, P., Humphrey, S.J., Cinghu, S., Pathania, R., Oldfield, A.J., Kumar, D., Perera, D., Yang, J.Y.H., James, D.E., Mann, M. and Jothi, R. (2019) Multi-Omic Profiling Reveals Dynamics of the Phased Progression of Pluripotency. Cell Systems, 8, 427-445.E10. [Google Scholar] [CrossRef] [PubMed]
|
|
[66]
|
Bodein, A., Scott-Boyer, M., Perin, O., Lê Cao, K. and Droit, A. (2021) Interpretation of Network-Based Integration from Multi-Omics Longitudinal Data. Nucleic Acids Research, 50, e27. [Google Scholar] [CrossRef] [PubMed]
|
|
[67]
|
Schüssler-Fiorenza Rose, S.M., Contrepois, K., Moneghetti, K.J., Zhou, W., Mishra, T., Mataraso, S., Dagan-Rosenfeld, O., Ganz, A.B., Dunn, J., Hornburg, D., Rego, S., Perelman, D., Ahadi, S., Sailani, M.R., Zhou, Y., Leopold, S.R., Chen, J., Ashland, M., Christle, J.W., Avina, M., Limcaoco, P., Ruiz, C., Tan, M., Butte, A.J., Weinstock, G.M., Slavich, G.M., Sodergren, E., McLaughlin, T.L., Haddad, F. and Snyder, M.P. (2019) A Longitudinal Big Data Approach for Precision Health. Nature Medicine, 25, 792-804. [Google Scholar] [CrossRef] [PubMed]
|