Table 1.

Overview of omics technologies: summary of strengths, limitations and clinical utility for each technology

Omics	Strengths	Limitations	Clinical utility
Genomics
SNP	• Unbiased approach when using GWAS	• Difficult to find functional and structural gene variants	• Theragnostic approach
	• Cost-effective large-scale genetic screening	• Only regulatory or coding regions are included	• Risk stratification
	• Well-established analysis tools	• Tissue-specific alterations
Epigenetics	• Unbiased approach when using epigenome-wide association studies	• Different composition of cell types during sepsis	• Epigenetic signatures for sepsis diagnosis and/or prognosis
	• Can elucidate the interplay between genetic and environmental factors	• Frequency of epigenetic changes not known	• Prediction of therapeutic response
		• Reverse causation
Transcriptomics
Expression profiling	• Can generate global view transcriptome alterations	• Tissue-specific expression of genes	• mRNA expression signatures for sepsis diagnosis and/or prognosis
	• Provide good coverage of genome	• Fails to measure low-expression genes with good sensitivity	• Prediction of therapeutic response
	• Can elucidate alterations in signal transduction pathways during sepsis
High-throughput gene sequencing (for example, RNA-seq)	• Comprehensive sequence information	• Tissue-specific expression of genes	• No clinical utility
	• Unbiased approach
	• Estimates abundance of genes in term of copies
miRNA	• Stable in blood	• Functions not completely understood	• Novel diagnostic and/or prognostic biomarkers in sepsis.
	• Suggestive evidence that miRNAs play an important role in regulation of networks		• Necessary for correctly interpretation of gene expression
	• The inclusion of miRNA when interpreting mRNA expression
Proteomics	• Provides global or unbiased alteration	• Needs large amount of preprocessing or fractions	• Novel diagnostic and/or prognostic biomarkers in sepsis
	• Highly sensitive	• Current instruments unable to measure all proteins from complex biological fluids	• Prediction of therapeutic response
	• No need for antibody-based technologies for measuring proteins	• Inefficient quantification of low expression proteins
Metabolomics	• Relatively few targets	• Difficulty in identifying small molecules	• Novel diagnostic and/or prognostic biomarkers in sepsis
	• Good translation to existing laboratory technology	• Diverse physical and chemical properties and thus no single extraction tool	• Prediction of therapeutic response
			• Disease progression

GWAS, genome-wide association studies.