Application of Machine Learning Ensemble Super Learner for analysis of the cytokines transported by high density lipoproteins (HDL) of smokers and nonsmokers.

Autor:	Saharan SS; Department of Statistics, University of Rajasthan, Jaipur, India.; UCSF Kane Lab, San Francisco, USA.; UC Berkeley Extension, Berkeley, USA., Nagar P; Department of Statistics, University of Rajasthan, Jaipur, India., Creasy KT; Cardiovascular Research Institute, Department of Medicine, University of California, San Francisco, USA., Stock EO; Cardiovascular Research Institute, Department of Medicine, University of California, San Francisco, USA., Feng J; Cardiovascular Research Institute, Department of Medicine, University of California, San Francisco, USA., Malloy MJ; Cardiovascular Research Institute, Department of Medicine, University of California, San Francisco, USA., Kane JP; Cardiovascular Research Institute, Department of Medicine, University of California, San Francisco, USA.
Jazyk:	angličtina
Zdroj:	Proceedings. International Conference on Computational Science and Computational Intelligence [Proc (Int Conf Comput Sci Comput Intell)] 2021 Dec; Vol. 2021, pp. 370-375. Date of Electronic Publication: 2022 Jun 22.
DOI:	10.1109/csci54926.2021.00133
Abstrakt:	Smoking is a major cause of cardiac and pulmonary disease, cancer, and other inflammation related diseases. Smoking impairs lipid and lipoprotein metabolism. The observed modification and reduction in levels of HDL in smokers has adverse effects on atheroprotective properties. It has been hypothesized that HDL transports inflammatory cytokines which accelerate tobacco-related diseases. To investigate the role of HDL in the transport of inflammatory cytokines and their detrimental effects on the immune response, it is paramount to compare cytokine levels in HDL for Smoker versus Nonsmoker groups. We isolated HDL from plasma using selected affinity immunosorption of apolipoprotein A-I-bearing lipoproteins, followed by quantitative ELISA of cytokines. We implemented a powerful stacked ensemble Machine Learning algorithm, namely Super Learner (SL) with base-learners: Decision Tree classifier, AdaBoost classifier, Bagging classifier, Extra Tree classifier, Logistic Regression and Random Forest classifier and meta learner: Logistic Regression. Prediction Accuracy metric was used to ascertain the separability efficacy of Smoker versus Nonsmoker based on cytokine levels. Super Learner composed of a Logistic Regression meta learner, achieved a 100% prediction accuracy, outperforming all the base learners. Machine learning-enabled Precision Medicine allows the investigation of the role of novel biomarkers such as HDL-transported cytokines which have a potential to generate valuable molecular insights. The discovery that cytokines are transported by HDL presents a new dimension in understanding inflammatory disorders and the potential for therapeutic intervention. The outstanding classification and prediction performance of Ensemble learning can be leveraged to revolutionize the biomarker discoveries, enabling insight that can lead to novel treatment modalities. Competing Interests: Competing interests The authors report no conflicts of interest.
Databáze:	MEDLINE
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