LRLSHMDA: Laplacian Regularized Least Squares for Human Microbe–Disease Association prediction

• Published in: Scientific reports Vol. 7; no. 1; pp. 7601 - 11
• Main Authors: Wang, Fan, Huang, Zhi-An, Chen, Xing, Zhu, Zexuan, Wen, Zhenkun, Zhao, Jiyun, Yan, Gui-Ying
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 08.08.2017; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/2397; 631/337/384; 631/553/2695; Actinobacteria - classification; Actinobacteria - genetics; Actinobacteria - isolation & purification; Algorithms; Asthma; Asthma - diagnosis; Asthma - microbiology; Asthma - pathology; Bacteria; Carcinoma - diagnosis; Carcinoma - microbiology; Carcinoma - pathology; Chronic obstructive pulmonary disease; Cloning; Clostridiaceae - classification; Clostridiaceae - genetics; Clostridiaceae - isolation & purification; Colorectal cancer; Colorectal carcinoma; Colorectal Neoplasms - diagnosis; Colorectal Neoplasms - microbiology; Colorectal Neoplasms - pathology; Comamonadaceae - classification; Comamonadaceae - genetics; Comamonadaceae - isolation & purification; Computer applications; Databases, Factual; Disease; Drug discovery; Drug resistance; Firmicutes - classification; Firmicutes - genetics; Firmicutes - isolation & purification; Gastrointestinal Microbiome - genetics; Gene expression; Humanities and Social Sciences; Humans; Least-Squares Analysis; Lung diseases; Medical diagnosis; Medical research; Metabolism; Microbiota; Microorganisms; Mining; Models, Statistical; multidisciplinary; Obstructive lung disease; Oxalobacteraceae - classification; Oxalobacteraceae - genetics; Oxalobacteraceae - isolation & purification; Physiology; Prognosis; Pulmonary Disease, Chronic Obstructive - diagnosis; Pulmonary Disease, Chronic Obstructive - microbiology; Pulmonary Disease, Chronic Obstructive - pathology; R&D; Research & development; Science; Science (multidisciplinary); Sphingomonadaceae - classification; Sphingomonadaceae - genetics; Sphingomonadaceae - isolation & purification
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-08127-2

An increasing number of evidences indicate microbes are implicated in human physiological mechanisms, including complicated disease pathology. Some microbes have been demonstrated to be associated with diverse important human diseases or disorders. Through investigating these disease-related microbes, we can obtain a better understanding of human disease mechanisms for advancing medical scientific progress in terms of disease diagnosis, treatment, prevention, prognosis and drug discovery. Based on the known microbe-disease association network, we developed a semi-supervised computational model of L aplacian R egularized L east S quares for H uman M icrobe– D isease A ssociation (LRLSHMDA) by introducing Gaussian interaction profile kernel similarity calculation and Laplacian regularized least squares classifier. LRLSHMDA reached the reliable AUCs of 0.8909 and 0.7657 based on the global and local leave-one-out cross validations, respectively. In the framework of 5-fold cross validation, average AUC value of 0.8794 +/−0.0029 further demonstrated its promising prediction ability. In case studies, 9, 9 and 8 of top-10 predicted microbes have been manually certified to be associated with asthma, colorectal carcinoma and chronic obstructive pulmonary disease by published literature evidence. Our proposed model achieves better prediction performance relative to the previous model. We expect that LRLSHMDA could offer insights into identifying more promising human microbe-disease associations in the future.