Commentary - (2022) Volume 8, Issue 8
Received: 01-Aug-2022, Manuscript No. IPBM-22-14590; Editor assigned: 03-Aug-2022, Pre QC No. IPBM-22-14590 (PQ); Reviewed: 17-Aug-2022, QC No. IPBM-22-14590; Revised: 22-Aug-2022, Manuscript No. IPBM-22-14590 (R); Published: 29-Aug-2022, DOI: 10.35841/2472-1646-8.8.149
For decades, biomarkers have been used in clinical medicine. Biomarker studies have entered a new era with the rise of genomic information and other breakthroughs in molecular biology, holding promise for early diagnosis and effective treatment of many diseases. A biomarker is a distinctive feature that can be measured and evaluated objectively as an indicator of regular biochemical functions, pathogenic processes, or pharmacologic reactions to a therapeutic intervention. They are divided into five categories based on their application in various stages of disease antecedent biomarkers to identify the risk of developing an illness, screening biomarkers to detect sub-clinical disease, diagnostic biomarkers to detect overt disease, and staging biomarkers to classify patients. Prognostic biomarkers to help predict disease course, such as recurrence, response to therapy, and monitoring’s important. Genetic markers can indicate a variety of health or disease processes, such as the level or type of ecological footprint exposure, genetic susceptibility, genetic reactions to environmental exposures, markers of subclinical or clinical disease, or indicators of therapy response. This chapter will examine how these genetic markers have been utilized in preventive medicine, diagnostics, therapeutics, and prediction, as well as population health, and their existing medical status. The biomedical sciences have seen a shift away from inhabitant’s approaches and toward individualised care. Individualization could improve the efficiency of public health strategies by allowing professionals to direct assets to those in greatest need. However, the continued identification of biological markers that reflect an individual’s health status and risk at key time points, as well as the full implementation of these biological markers into medical practise, will be critical to the success of these efforts. To be clinically useful, metabolomics tests must be highly predictive, easily measurable and reproducible, non-invasive, and acceptable to patients and physicians. When a suggested biomarker is validated, can be used to evaluate disease risk in a general public, confirm diagnosis of diseases in an individual patient, and tailor treatment to an individual (choice of drug treatment or administration regimes). A biomarker may be used as a surrogate for a natural endpoint, such as survival or irreversible mortality, when evaluating potential drug therapies. If a treatment changes a biomarker that is directly related to improved health, the biomarker serves as a surrogate endpoint for assessing clinical benefit. Recent advances in molecular strategies to biology, genetics, biochemistry, and medicine, particularly the rise of genomic information, transcriptomics, proteomics, and metabolic engineering, appear to hold the promise of transforming medical practise into personalised medicine the right treatment at the right time. Blood lead density, for example, has been used as a marker for exposure to lead saliva cotinine (a nicotine metabolite level) has been employed as a marker in studies of adolescent cigarette consumption. A biomarker of effect is a substantial difference in an endogenous factor that has been linked to impairment or disease as a result of exposure to an exogenous agent. A biosensor of effect, for instance, is a change in pulmonary function tests in children after exposure to environmental tobacco smoke. Caused by mutations have been employed as biomarkers of effect following carcinogen exposure. A susceptibility biomarker identifies individual factors that can influence the response to environmental agents.
These reflect differences in genetic structure among individual people, some of which make the individual more vulnerable. The TYR gene variant that encodes an R402Q amino acid replacement, which has previously been shown to affect eye colour and bronzing response, was associated with an increased risk of developing Cutaneous Melanoma (CM) a and medullary cell carcinoma (BCC); variations in a haplogroup (set of closely associated genes) near the ASIP gene.
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The author’s declared that they have no conflict of interest.
Citation: Liu X (2022) Role of Biomarkers in Preventive and Clinical Medicine. Biomark J. 8:149.
Copyright: © 2022 Liu X. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
