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Review
. 2022 Nov 12;13(4):561-580.
doi: 10.1007/s13167-022-00304-2. eCollection 2022 Dec.

Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements

Neha Jain  1 , Upendra Nagaich  1 , Manisha Pandey  2 , Dinesh Kumar Chellappan  3 , Kamal Dua  4   5
Affiliations
Review

Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements

Neha Jain et al. EPMA J. .

Abstract

In the current era of medical revolution, genomic testing has guided the healthcare fraternity to develop predictive, preventive, and personalized medicine. Predictive screening involves sequencing a whole genome to comprehensively deliver patient care via enhanced diagnostic sensitivity and specific therapeutic targeting. The best example is the application of whole-exome sequencing when identifying aberrant fetuses with healthy karyotypes and chromosomal microarray analysis in complicated pregnancies. To fit into today's clinical practice needs, experimental system biology like genomic technologies, and system biology viz., the use of artificial intelligence and machine learning is required to be attuned to the development of preventive and personalized medicine. As diagnostic techniques are advancing, the selection of medical intervention can gradually be influenced by a person's genetic composition or the cellular profiling of the affected tissue. Clinical genetic practitioners can learn a lot about several conditions from their distinct facial traits. Current research indicates that in terms of diagnosing syndromes, facial analysis techniques are on par with those of qualified therapists. Employing deep learning and computer vision techniques, the face image assessment software DeepGestalt measures resemblances to numerous of disorders. Biomarkers are essential for diagnostic, prognostic, and selection systems for developing personalized medicine viz. DNA from chromosome 21 is counted in prenatal blood as part of the Down's syndrome biomarker screening. This review is based on a detailed analysis of the scientific literature via a vigilant approach to highlight the applicability of predictive diagnostics for the development of preventive, targeted, personalized medicine for clinical application in the framework of predictive, preventive, and personalized medicine (PPPM/3 PM). Additionally, targeted prevention has also been elaborated in terms of gene-environment interactions and next-generation DNA sequencing. The application of 3 PM has been highlighted by an in-depth analysis of cancer and cardiovascular diseases. The real-time challenges of genome sequencing and personalized medicine have also been discussed.

Keywords: Personalized medicine; Pharmacogenomics; Precision medicine; Predictive biomarkers; Vaccines.

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Conflict of interest statement

Competing interestsThe authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Diagrammatic illustration of application of distinct next-generation sequencing technologies adopted with permission from Klein et al.[91]
Fig. 2
Fig. 2
Comparison of tissue and liquid biopsy in diagnosis adopted with permission from Palacín-Aliana et al. [92]
Fig. 3
Fig. 3
List of biomarkers associated with the heart failure
See this image and copyright information in PMC

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