Benchmarking omics-based prediction of asthma development in children.

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.

Epigenome-wide association study reveals a molecular signature of response to phylloquinone (vitamin K1) supplementation.

Evidence suggests there are roles for vitamin K in various chronic disease outcomes, but population-level diet and supplement recommendations are difficult to determine due to high levels of variability in measures of status and response to intake compared to other nutrients. In this preliminary investigation, a blood-based epigenome-wide association study (EWAS) comparing responders and non-responders to phylloquinone (vitamin K1) supplementation (NCT00183001) was undertaken in order to better understand the molecular underpinnings of this observed variability. Responders (n = 24) and non-responders (n = 24) were identified in a prior 3-year phylloquinone supplementation trial based on their changes in plasma phylloquinone concentrations. Differential DNA methylation was identified in multiple regions with previously unknown relationships to phylloquinone absorption and metabolism, such as at the TMEM263 locus. A hypothesis-driven analysis of lipid-related genes highlighted a site in the NPC1L1 gene, supplementing existing evidence for its role in phylloquinone absorption. Furthermore, an EWAS for baseline plasma phylloquinone concentrations revealed a strong correlation between the epigenomic signatures of phylloquinone baseline status and response to supplementation. This work can guide future epigenomic research on vitamin K and contributes to the development of more personalized dietary recommendations for vitamin K.