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

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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.

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Authors and Affiliations

  1. Department of Pharmaceutics, Amity Institute of Pharmacy, Amity University, Noida, 201303, UP, India

    Neha Jain & Upendra Nagaich

  2. Department of Pharmaceutical Sciences, Central University of Haryana, Mahendergarh, 123031, India

    Manisha Pandey

  3. Department of Life Sciences, School of Pharmacy, International Medical University, Bukit Jalil 57000, Kuala Lumpur, Malaysia

    Dinesh Kumar Chellappan

  4. Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW, 2007, Australia

    Kamal Dua

  5. Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW, 2007, Australia

    Kamal Dua

Authors
  1. Neha Jain
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  2. Upendra Nagaich
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  3. Manisha Pandey
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  4. Dinesh Kumar Chellappan
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  5. Kamal Dua
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Contributions

All authors contributed to the study’s conception and design. Literature survey, collection, and analysis were performed by Neha Jain, Upendra Nagaich, and Manisha Pandey. The first draft of the manuscript was written by Neha Jain and Upendra Nagaich. Further modifications in subsequent drafts were done by Dinesh Kumar Chellappan and Kamal Dua. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Neha Jain.

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The authors declare no competing interests.

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Highlights

• Technical advancements in the fields of genomics in predictive, preventive, and personalized medicine have been on the rise.

• Predictive information on modifications in genetic makeup or any gene mutation can prevent disease manifestation.

• Personalized medicine (PM) is a medical approach for patient classification based on illness subtypes, risks, diagnoses, or therapy responses using specialized diagnostic tests.

• Personalized medicine based on genome analysis aims to enhance therapeutic outcomes and decrease adverse effects important to physicians and patients.

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Jain, N., Nagaich, U., Pandey, M. et al. Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements. EPMA Journal 13, 561–580 (2022). https://doi.org/10.1007/s13167-022-00304-2

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  • DOI: https://doi.org/10.1007/s13167-022-00304-2

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