Year: 2023
Type: article
Abstract: BACKGROUND: Asthma is a heterogeneous disease with high morbidity. Advancement in high-throughput multi-omics approaches has enabled the collection of molecular assessments at different layers, providing a complementary perspective of complex diseases. Numerous computational methods have been developed for the omics-based patient classification or disease outcome prediction. Yet, a systematic benchmarking of those methods using various combinations of omics data for the prediction of asthma development is still lacking. OBJECTIVE: We aimed to investigate the computational methods in disease status prediction using multi-omics data. METHOD: We systematically benchmarked 18 computational methods using all the 63 combinations of six omics data (GWAS, miRNA, mRNA, microbiome, metabolome, DNA methylation) collected in The Vitamin D Antenatal Asthma Reduction Trial (VDAART) cohort. We evaluated each method using standard performance metrics for each of the 63 omics combinations. RESULTS: Our results indicate that overall Logistic Regression, Multi-Layer Perceptron, and MOGONET display superior performance, and the combination of transcriptional, genomic and microbiome data achieves the best prediction. Moreover, we find that including the clinical data can further improve the prediction performance for some but not all the omics combinations. CONCLUSIONS: Specific omics combinations can reach the optimal prediction of asthma development in children. And certain computational methods showed superior performance than other methods.
Source: Respiratory Research
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,190
Awards: Multi-omic approaches to mechanisms of vitamin D, environmental influences, and the microbiome on asthma, Mechanistic insights into asthma pathogenesis through the integration of asthma genes, risk exposures, and metabolomics, Long-term health consequences of birth by cesarean section, Integrative Metabolomics of Asthma Severity, Functional Redundancy of Human Microbiome and its Implication in Fecal Microbiota Transplantation, Prospective Study of the Gut Microbiome in Aging, (2 of 2) Genetic Epidemiology of COPD, Randomized Trial: Maternal Vitamin D Supplementation to Prevent Childhood Asthma, Pathophysiologic and Therapeutic Mechanisms of Aspirin Exacerbated Respiratory Disease, Environmental Agents as Modulators of Disease Processes, Immune development in early life (IDEAL) shapes vaccine response, respiratory infectious diseaseand asthma, Omic Determinants of Longitudinal Lung Function in Asthma
OpenAlex ID: W4322109835