Preventive medicine is aimed at the preservation of health and well-being of people by prevention of diseases or death. Preventive medicine practices a range of methods from simple approaches such as modulation of lifestyle through exercise and diet[1]to utilize the most recent advanced ‘omics’ data which includes the use of genomic, epigenomics, transcriptomics, proteomics, and metabolomics[2]. The application of omics data in preventive medicine can also be a predictive medical practice as they mostly identify disease risk factors in a personalized manner or at the population level. The development of diagnostic and prognostic measures at the molecular level including genetic variations, epigenetic changes (DNA methylation, histone posttranslational modifications, and non-coding RNAs), protein level and metabolite changes have allowed the preventive medicine to be more efficient in clinical practices in many ways. The use of omics detection strategies requires smaller patient sample sizes, ability to run more replicates of the same test and robustly automated methodologies [3]. Prevention of patient death (mortality reduction) and early detection of the disease has been further improved by more sophisticated screening tests with minimal false positive detection. For instance, the omics approaches are currently being used to develop more effective molecular biomarkers for early detection of many disease conditions (example cancer, diabetes) and following the prognosis after treatments [4]. Metabolomics is currently being employed in the development of risk stratification strategies in the prevention of social health concerns such as spontaneous preterm birth [5], traumatic brain injury [6] and kidney diseases [7] through quantitative analysis of enzymes and metabolic products (the metabolome). Whole genome sequencing and whole exome sequencing have shown great promise in preventive medicine as they have been able to provide extensive information regarding personalized risk factors, susceptibility to disease conditions and current health status starting from newborn to adults [8-10]. Combinatorial or integrative use of two more of these methods (‘multi-omics’) is being explored currently, as risk prediction can be done more efficiently and accurately when analysis of DNA, RNA, protein and metabolite levels are analyzed in a synchronized passion [11,12]. Despite the advancements of the omics approaches and their applications in preventive medicine, there is still much to be explored regarding the interpretation of the vast amount of data generated by each method[13]. Moreover, the data produced by these methods are up for a broad range of interpretation from being highly clinically relevant to simply being personal changes that can occur in any person without being clinically relevant. For the same reason, there are much debated ethical issues associated with using omics data in health care practices regarding the extent of using this data and the consequences related to knowing the information [14]. Adding further complexity to this picture, the gene-environment interactions measured as nutrigenomics, economics, and microbiomes are being explored in clinic applications where the information can be used to predict and prevent associations between man and environment that can lead to health concerns[15,16]. The intricacy of this omics preventive medicine association warrants in-depth analysis of the strengths, weaknesses, ethical considerations and future perspectives of this field.
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