Omic Medicine and Precision Medicine

- The Omic Era

The "Omics" era begins at the end of the twentieth century, when the technological advance in biochemistry, molecular biology and analytical chemistry enables the development of genomics, transcriptomics, proteomics, metabolomics and metobonomic.

These new areas of knowledge are currently recognised as disciplines with their own entity, which are responsible for the detailed study of the genome, transcriptome, proteome, metabolome and metabonome, respectively.

- Omic Medicine and Precision Medicine

Omic medicine is the term for the next generation of laboratory tools that provide insights into an individual’s molecular makeup. Omics approaches include proteomics, transcriptomics, genomics, metabolomics, lipidomics, and epigenomics. These methods analyze proteins, RNA, genes, metabolites, lipids, and methylated DNA or modified histones in chromosomes.

Precision medicine is an innovative approach that takes into account individual differences in a patient’s genes, environment and lifestyle. Precision medicine can provide precise prevention, diagnosis and treatment options.

Omics approaches have been used to investigate more specific and accurate markers to predict treatment response. During the COVID-19 pandemic, it became apparent that precision medicine relies heavily on biological multi-omic discovery.

- Omics Approaches

The branches of science known informally as omics are various disciplines in biology whose names end in the suffix -omics, such as genomics, proteomics, metabolomics, and glycomics. Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. Omics approaches have changed the landscape of different diseases including stroke, diabetes, and cancer. 

The related suffix -ome is used to address the objects of study of such fields, such as the genome, proteome or metabolome respectively. The suffix -ome as used in molecular biology refers to a totality of some sort; it is an example of a "neo-suffix" formed by abstraction from various Greek terms in -ωμα, a sequence that does not form an identifiable suffix in Greek. 

Functional genomics aims at identifying the functions of as many genes as possible of a given organism. It combines different -omics techniques such as transcriptomics and proteomics with saturated mutant collections. 

- Genomic Approaches

Genomic approaches such as genome wide association studies have led to the identification of 30 loci, which were used in swaying body mass index and the risk of obesity. At mRNA levels, transcriptomic profiling using cDNA microarrays has helped not only in detecting the downregulation of significant tumor suppressors in breast cancer metastasis but also enabled medical practitioners to discriminate patients with activated B-like diffuse large B-cell lymphoma (DLBCL) from those with germinal center B-like DLBCL. 

High-throughput studies focused on microRNAs (miRNAs or miRs) in early stage breast cancer have led to the identification of unique predictive miR signatures specific to ER, PR, and HER2 status. At the protein level, an in vivo labeling technique like stable isotope labeling with amino acids in animal cell culture, coupled with a mass-spectrometry based proteomic approach, has allowed for the comparison of different mutations in lung adenocarcinoma cell lines in relation to EGFR signaling.

[Budapest, Hungary - Civil Engineering Discoveries]

- Assimilation and Integration of Omic Technologies

Assimilation and integration of omic technologies, including genomics, epigenomics, proteomics, and metabolomics has readily altered the landscape of medical research in the last decade. The vast and complex nature of omics data can only be interpreted by linking molecular information at the organismic level, forming the foundation of systems biology. 

For example, research in pulmonary biology/medicine has necessitated integration of omics, network, systems and computational biology data to differentially diagnose, interpret, and prognosticate pulmonary diseases, facilitating improvement in therapy and treatment modalities. This research topic describes how to leverage this emerging technology in understanding pulmonary diseases at the systems level called a systemic approach. 

Considering the operational wholeness of cellular and organ systems, diseased genome, proteome, and the metabolome needs to be conceptualized at the systems level to understand disease pathogenesis and progression. Currently available omics technology and resources require a certain degree of training and proficiency in addition to dedicated hardware and applications, making them relatively less user friendly for the pulmonary biologist and clinicians. Herein, The various strategies, computational tools and approaches are required to study pulmonary diseases at the systems level for biomedical scientists and clinical researchers. 

- Muliomic Approaches

Multiomics is a new approach where the data sets of different omic groups are combined during analysis. The different omic strategies employed during multiomics are genome, proteome, transcriptome, epigenome, and microbiome.