The Promise of Panomics: Decoding Biological Networks to Identify Pathways Involved in Complex Diseases

June 12, 2014
The Promise of Panomics: Decoding Biological Networks to Identify Pathways Involved in Complex Diseases
Cardiovascular computed tomography (CT) permits heart disease patients to be precisely separated using noninvasive imaging techniques. [G3]

Szilard Voros, M.D.

Technological advances such as high-throughput sequencing are transforming medicine from symptom-based diagnosis and treatment to personalized medicine as scientists employ novel rapid genomic methodologies to gain a broader comprehension of disease and disease progression. As next-generation sequencing becomes more rapid, researchers are turning toward large-scale pan-omics, the collective use of all omics such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics and lipoprotein proteomics, to better understand, identify, and treat complex disease.

Genomics has been a cornerstone in understanding disease, and the sequencing of the human genome has led to the identification of numerous disease biomarkers through genome-wide association studies (GWAS).1 It was the goal of these studies that these biomarkers would serve to predict individual disease risk, enable early detection of disease, help make treatment decisions, and identify new therapeutic targets. In reality, however, only a few have gone on to become established in clinical practice.1,2 For example in human GWAS studies for heart failure at least 35 biomarkers have been identified but only natriuretic peptides have moved into clinical practice, where they are limited primarily for use as a diagnostic tool.2

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