Skip to main content

2022 | OriginalPaper | Buchkapitel

Linear Predictive Modeling for Immune Metabolites Related to Other Metabolites

verfasst von : Jana Schwarzerova, Iro Pierides, Karel Sedlar, Wolfram Weckwerth

Erschienen in: Bioinformatics and Biomedical Engineering

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Metabolite analysis reveals new challenges in human health care. This human health care connects to the immune system and presents opportunities for the prevention and detection of early hidden disease symptoms. Predicting the concentration of immune metabolites and confirming relationships between concentrations of individual metabolites have the potential to create breakthroughs in diagnostic techniques. This early detection of serious diseases plays a major role in overall recovery. Moreover, metabolite analysis linked to biomedical applications could provide an ideal tool for preventive healthcare and the pharmaceutical industry.
This study presents the linear prediction of selected metabolites involved in the immune system. The evaluation relied on accurate linear prediction modeling and subsequent comparison. This is the first step toward determining the relationship of metabolites and immune system using computational biomedical analysis.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
3.
Zurück zum Zitat Zmora, N., Bashiardes, S., Levy, M., Elinav, E.: The role of the immune system in metabolic health and disease. Cell Metab. 25(3), 506–521 (2017)CrossRefPubMed Zmora, N., Bashiardes, S., Levy, M., Elinav, E.: The role of the immune system in metabolic health and disease. Cell Metab. 25(3), 506–521 (2017)CrossRefPubMed
4.
5.
Zurück zum Zitat Kim, I., He, Y.-Y.: Targeting the AMP-activated protein kinase for cancer prevention and therapy. Front. Oncol. 3, 175 (2013)PubMedPubMedCentral Kim, I., He, Y.-Y.: Targeting the AMP-activated protein kinase for cancer prevention and therapy. Front. Oncol. 3, 175 (2013)PubMedPubMedCentral
6.
7.
Zurück zum Zitat Buttgereit, F., Burmester, G.-R., Brand, M.D.: Bioenergetics of immune functions: fundamental and therapeutic aspects. Immunol. Today 21(4), 194–199 (2000)CrossRef Buttgereit, F., Burmester, G.-R., Brand, M.D.: Bioenergetics of immune functions: fundamental and therapeutic aspects. Immunol. Today 21(4), 194–199 (2000)CrossRef
8.
9.
Zurück zum Zitat Arts, R.J.W., et al.: Glutaminolysis and fumarate accumulation integrate immunometabolic and epigenetic programs in trained immunity. Cell Metab. 24(6), 807–819 (2016)CrossRefPubMedPubMedCentral Arts, R.J.W., et al.: Glutaminolysis and fumarate accumulation integrate immunometabolic and epigenetic programs in trained immunity. Cell Metab. 24(6), 807–819 (2016)CrossRefPubMedPubMedCentral
10.
Zurück zum Zitat Gu, C., et al.: Isoleucine plays an important role for maintaining immune function. Curr. Protein Pept. Sci. 20(7), 644–651 (2019)CrossRefPubMed Gu, C., et al.: Isoleucine plays an important role for maintaining immune function. Curr. Protein Pept. Sci. 20(7), 644–651 (2019)CrossRefPubMed
11.
Zurück zum Zitat Cruzat, V., Rogero, M.M., Keane, K.N., Curi, R., Newsholme, P.: Glutamine: metabolism and immune function, supplementation and clinical translation. Nutrients 10(11), 1564 (2018)CrossRefPubMedCentral Cruzat, V., Rogero, M.M., Keane, K.N., Curi, R., Newsholme, P.: Glutamine: metabolism and immune function, supplementation and clinical translation. Nutrients 10(11), 1564 (2018)CrossRefPubMedCentral
12.
Zurück zum Zitat Iyer, A., Fairlie, D.P., Brown, L.: Lysine acetylation in obesity, diabetes and metabolic disease. Immunol. Cell Biol. 90(1), 39–46 (2012)CrossRefPubMed Iyer, A., Fairlie, D.P., Brown, L.: Lysine acetylation in obesity, diabetes and metabolic disease. Immunol. Cell Biol. 90(1), 39–46 (2012)CrossRefPubMed
13.
Zurück zum Zitat Moffett, J.R., Namboodiri, M.A.A.: Tryptophan and the immune response. Immunol. Cell Biol. 81(4), 247–265 (2003)CrossRefPubMed Moffett, J.R., Namboodiri, M.A.A.: Tryptophan and the immune response. Immunol. Cell Biol. 81(4), 247–265 (2003)CrossRefPubMed
15.
Zurück zum Zitat Opitz, C.A., Wick, W., Steinman, L., Platten, M.: Tryptophan degradation in autoimmune diseases. Cell. Mol. Life Sci. 64(19–20), 2542–2563 (2007)CrossRefPubMed Opitz, C.A., Wick, W., Steinman, L., Platten, M.: Tryptophan degradation in autoimmune diseases. Cell. Mol. Life Sci. 64(19–20), 2542–2563 (2007)CrossRefPubMed
16.
Zurück zum Zitat Tantawy, A.A., Naguib, D.M.: Arginine, histidine and tryptophan: a new hope for cancer immunotherapy. PharmaNutrition 8, 100149 (2019)CrossRef Tantawy, A.A., Naguib, D.M.: Arginine, histidine and tryptophan: a new hope for cancer immunotherapy. PharmaNutrition 8, 100149 (2019)CrossRef
17.
Zurück zum Zitat Bronte, V., Zanovello, P.: Regulation of immune responses by L-arginine metabolism. Nat. Rev. Immunol. 5(8), 641–654 (2005)CrossRefPubMed Bronte, V., Zanovello, P.: Regulation of immune responses by L-arginine metabolism. Nat. Rev. Immunol. 5(8), 641–654 (2005)CrossRefPubMed
18.
Zurück zum Zitat Lovelace, M.D., et al.: Recent evidence for an expanded role of the kynurenine pathway of tryptophan metabolism in neurological diseases. Neuropharmacology 112, 373–388 (2017)CrossRefPubMed Lovelace, M.D., et al.: Recent evidence for an expanded role of the kynurenine pathway of tryptophan metabolism in neurological diseases. Neuropharmacology 112, 373–388 (2017)CrossRefPubMed
19.
Zurück zum Zitat Saha, S.B., Prasanna, J., Chandrasekar, B., Nandi, D.: Gene modulation and immunoregulatory roles of Interferonγ. Cytokine 50(1), 1–14 (2010)CrossRefPubMed Saha, S.B., Prasanna, J., Chandrasekar, B., Nandi, D.: Gene modulation and immunoregulatory roles of Interferonγ. Cytokine 50(1), 1–14 (2010)CrossRefPubMed
22.
Zurück zum Zitat Poon, I.K.H., Patel, K.K., Davis, D.S., Parish, C.R., Hulett, M.D.: Histidine-rich glycoprotein: the Swiss Army knife of mammalian plasma. Blood 117(7), 2093–2101 (2011)CrossRefPubMed Poon, I.K.H., Patel, K.K., Davis, D.S., Parish, C.R., Hulett, M.D.: Histidine-rich glycoprotein: the Swiss Army knife of mammalian plasma. Blood 117(7), 2093–2101 (2011)CrossRefPubMed
23.
Zurück zum Zitat Chu, X., et al.: Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease. Genome Biol. 22(1), 1–22 (2021)CrossRef Chu, X., et al.: Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease. Genome Biol. 22(1), 1–22 (2021)CrossRef
24.
Zurück zum Zitat Hanusz, Z., Tarasińska, J.: Normalization of the Kolmogorov–Smirnov and Shapiro–Wilk tests of normality. Biometrical Lett. 52(2), 85–93 (2015)CrossRef Hanusz, Z., Tarasińska, J.: Normalization of the Kolmogorov–Smirnov and Shapiro–Wilk tests of normality. Biometrical Lett. 52(2), 85–93 (2015)CrossRef
25.
Zurück zum Zitat Ranstam, J., Cook, J.A.: LASSO regression. J. Br. Surg. 105(10), 1348 (2018)CrossRef Ranstam, J., Cook, J.A.: LASSO regression. J. Br. Surg. 105(10), 1348 (2018)CrossRef
26.
Zurück zum Zitat McDonald, G.C.: Ridge regression. Wiley Interdisc. Rev. Comput. Stat. 1(1), 93–100 (2009)CrossRef McDonald, G.C.: Ridge regression. Wiley Interdisc. Rev. Comput. Stat. 1(1), 93–100 (2009)CrossRef
27.
Zurück zum Zitat Marquardt, D.W., Snee, R.D.: Ridge regression in practice. Am. Stat. 29(1), 3–20 (1975) Marquardt, D.W., Snee, R.D.: Ridge regression in practice. Am. Stat. 29(1), 3–20 (1975)
28.
Zurück zum Zitat Ridgeway, G.: Generalized Boosted Models: A guide to the gbm package. Update, 2007, 1 January 2007 Ridgeway, G.: Generalized Boosted Models: A guide to the gbm package. Update, 2007, 1 January 2007
29.
Zurück zum Zitat de los Campos, G., Pataki, A., Pérez, P.: The BGLR (Bayesian Generalized Linear Regression) R-Package (2015) de los Campos, G., Pataki, A., Pérez, P.: The BGLR (Bayesian Generalized Linear Regression) R-Package (2015)
30.
Zurück zum Zitat Hastie, T., Qian, J., Tay, K.: An Introduction to glmnet (2016) Hastie, T., Qian, J., Tay, K.: An Introduction to glmnet (2016)
31.
Zurück zum Zitat Engebretsen, S., Bohlin, J.: Statistical predictions with glmnet. Clin. Epigenetics 11(1), 1–3 (2019)CrossRef Engebretsen, S., Bohlin, J.: Statistical predictions with glmnet. Clin. Epigenetics 11(1), 1–3 (2019)CrossRef
32.
Zurück zum Zitat Yachen, Y.: MLmetrics: Machine Learning Evaluation Metrics. R package version 1.1.1 (2016) Yachen, Y.: MLmetrics: Machine Learning Evaluation Metrics. R package version 1.1.1 (2016)
33.
Zurück zum Zitat Pérez, P., de los Campos, G.: Genome-wide regression and prediction with the BGLR statistical package. Genetics 198(2), 483–495 (2014) Pérez, P., de los Campos, G.: Genome-wide regression and prediction with the BGLR statistical package. Genetics 198(2), 483–495 (2014)
34.
Zurück zum Zitat Deutelmoser, H., et al.: Robust Huber-LASSO for improved prediction of protein, metabolite and gene expression levels relying on individual genotype data. Brief. Bioinform. 22(4), bbaa230 (2021)CrossRefPubMed Deutelmoser, H., et al.: Robust Huber-LASSO for improved prediction of protein, metabolite and gene expression levels relying on individual genotype data. Brief. Bioinform. 22(4), bbaa230 (2021)CrossRefPubMed
35.
Zurück zum Zitat Öllerer, V., Croux, C., Alfons, A.: The influence function of penalized regression estimators. Statistics 49(4), 741–765 (2015)CrossRef Öllerer, V., Croux, C., Alfons, A.: The influence function of penalized regression estimators. Statistics 49(4), 741–765 (2015)CrossRef
36.
Zurück zum Zitat Beaver, W.L., Wasserman, K., Whipp, B.J.: Improved detection of lactate threshold during exercise using a log-log transformation. J. Appl. Physiol. 59(6), 1936–1940 (1985)CrossRefPubMed Beaver, W.L., Wasserman, K., Whipp, B.J.: Improved detection of lactate threshold during exercise using a log-log transformation. J. Appl. Physiol. 59(6), 1936–1940 (1985)CrossRefPubMed
37.
Zurück zum Zitat Becker, R.A., Chambers, J.M., Wilks, A.R.: The New S Language. Wadsworth & Brooks/Cole (1988) Becker, R.A., Chambers, J.M., Wilks, A.R.: The New S Language. Wadsworth & Brooks/Cole (1988)
38.
Zurück zum Zitat Grueneberg, A., de los Campos, G.: BGData - a suite of R packages for genomic analysis with big data. G3 Genes Genomes Genet. 9(5), 1377–1383 (2019) Grueneberg, A., de los Campos, G.: BGData - a suite of R packages for genomic analysis with big data. G3 Genes Genomes Genet. 9(5), 1377–1383 (2019)
39.
Zurück zum Zitat van den Berg, R.A., Hoefsloot, H.C.J., Westerhuis, J.A., Smilde, A.K., van der Werf, M.J.: Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics 7(1), 1–15 (2006)CrossRef van den Berg, R.A., Hoefsloot, H.C.J., Westerhuis, J.A., Smilde, A.K., van der Werf, M.J.: Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics 7(1), 1–15 (2006)CrossRef
40.
Zurück zum Zitat Banerjee, P., Garai, B., Mallick, H., Chowdhury, S., Chatterjee, S.: A note on the adaptive LASSO for zero-inflated Poisson regression. J. Probab. Stat. 2018, 1–9 (2018)CrossRef Banerjee, P., Garai, B., Mallick, H., Chowdhury, S., Chatterjee, S.: A note on the adaptive LASSO for zero-inflated Poisson regression. J. Probab. Stat. 2018, 1–9 (2018)CrossRef
41.
Zurück zum Zitat Algamal, Z.Y.: Diagnostic in poisson regression models. Electron. J. Appl. Stat. Anal. 5(2), 178–186 (2012) Algamal, Z.Y.: Diagnostic in poisson regression models. Electron. J. Appl. Stat. Anal. 5(2), 178–186 (2012)
42.
Zurück zum Zitat Chai, T., Draxler, R.R.: Root mean square error (RMSE) or mean absolute error (MAE). Geosci. Model Dev. Discuss. 7(1), 1525–1534 (2014) Chai, T., Draxler, R.R.: Root mean square error (RMSE) or mean absolute error (MAE). Geosci. Model Dev. Discuss. 7(1), 1525–1534 (2014)
43.
Zurück zum Zitat Chicco, D., Warrens, M.J., Jurman, G.: The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Comput. Sci. 7, e623 (2021)CrossRefPubMedPubMedCentral Chicco, D., Warrens, M.J., Jurman, G.: The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Comput. Sci. 7, e623 (2021)CrossRefPubMedPubMedCentral
Metadaten
Titel
Linear Predictive Modeling for Immune Metabolites Related to Other Metabolites
verfasst von
Jana Schwarzerova
Iro Pierides
Karel Sedlar
Wolfram Weckwerth
Copyright-Jahr
2022
DOI
https://doi.org/10.1007/978-3-031-07704-3_2

Premium Partner