ADVANCEMENTS IN BIOTECHNOLOGY FOR EARLY DISEASE DETECTION: INTEGRATING BIOSENSORS AND GENOMIC TECHNOLOGIES TO IMPROVE HEALTH OUTCOMES
Keywords:
Biotechnology, Disease Detection, Biosensors, Genomics, CRISPR-based Diagnostics, Biomedicine, HealthcareAbstract
Early disease detection plays a crucial role in improving patient outcomes by enabling timely interventions, reducing healthcare costs, and increasing survival rates. Biotechnology has made significant strides in enhancing early detection through the integration of biosensors and genomic technologies. This review explores advancements in these two fields, focusing on how biosensors allow for real-time, non-invasive monitoring of biomarkers, and how genomic technologies, such as next-generation sequencing and CRISPR-based diagnostics, are transforming disease detection at the molecular level. These advancements promise to revolutionize healthcare, providing more accurate, faster, and cost-effective tools for diagnosing diseases such as cancer, infectious diseases, and genetic disorders.
References
Murray, C.J., et al., The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. Jama, 2013. 310(6): p. 591-606.
Crosby, D., et al., Early detection of cancer. Science, 2022. 375(6586): p. eaay9040.
Leopold, J.A. and J. Loscalzo, Emerging role of precision medicine in cardiovascular disease. Circulation research, 2018. 122(9): p. 1302-1315.
Martin-Yken, H., Yeast-based biosensors: current applications and new developments. Biosensors, 2020. 10(5): p. 51.
de Oliveira, W.F., et al., Biomarkers, biosensors and biomedicine. Current Medicinal Chemistry, 2020. 27(21): p. 3519-3533.
Grieshaber, D., et al., Electrochemical biosensors-sensor principles and architectures. Sensors, 2008. 8(3): p. 1400-1458.
Teymourian, H., A. Barfidokht, and J. Wang, Electrochemical glucose sensors in diabetes management: an updated review (2010–2020). Chemical Society Reviews, 2020. 49(21): p. 7671-7709.
Damborský, P., J. Švitel, and J. Katrlík, Optical biosensors. Essays in biochemistry, 2016. 60(1): p. 91-100.
Castillo-Henríquez, L., et al., Biosensors for the detection of bacterial and viral clinical pathogens. Sensors, 2020. 20(23): p. 6926.
Ermolaeva, T. and E. Kalmykova, Capabilities of piezoelectric immunosensors for detecting infections and for early clinical diagnostics. Adv. Immunoass. Technol, 2012. 81(10.5772): p. 35630.
Campuzano, S., P. Yáñez-Sedeño, and J.M. Pingarrón, Carbon dots and graphene quantum dots in electrochemical biosensing. Nanomaterials, 2019. 9(4): p. 634.
Sharma, A., et al., Wearable biosensors: an alternative and practical approach in healthcare and disease monitoring. Molecules, 2021. 26(3): p. 748.
Anbuselvam, B., et al., Wearable biosensors in cardiovascular disease. Clinica Chimica Acta, 2024: p. 119766.
Chu, S.S., et al., Towards Multiplexed and Multimodal Biosensor Platforms in Real-Time Monitoring of Metabolic Disorders. Sensors, 2022. 22(14): p. 5200.
Bohunicky, B. and S.A. Mousa, Biosensors: the new wave in cancer diagnosis. Nanotechnology, science and applications, 2010: p. 1-10.
Nakhjavani, S.A., et al., Biosensors for prostate cancer detection. Trends in Biotechnology, 2023. 41(10): p. 1248-1267.
Hu, T., et al., Next-generation sequencing technologies: An overview. Human Immunology, 2021. 82(11): p. 801-811.
Elazezy, M. and S.A. Joosse, Techniques of using circulating tumor DNA as a liquid biopsy component in cancer management. Computational and structural biotechnology journal, 2018. 16: p. 370-378.
Zhao, H., et al., Role of circulating tumor DNA in the management of early‐stage lung cancer. Thoracic cancer, 2018. 9(5): p. 509-515.
Uppada, V., M. Gokara, and G.K. Rasineni, Diagnosis and therapy with CRISPR advanced CRISPR based tools for point of care diagnostics and early therapies. Gene, 2018. 656: p. 22-29.
Tian, Y., et al., Pathogen detection strategy based on CRISPR. Microchemical Journal, 2022. 174: p. 107036.
Mustafa, M.I. and A.M. Makhawi, SHERLOCK and DETECTR: CRISPR-Cas systems as potential rapid diagnostic tools for emerging infectious diseases. Journal of Clinical Microbiology, 2021. 59(3): p. 10.1128/jcm. 00745-20.
Kim, S., S. Ji, and H.R. Koh, CRISPR as a Diagnostic Tool. Biomolecules, 2021. 11(8): p. 1162.
Palaz, F., et al., CRISPR-based tools: Alternative methods for the diagnosis of COVID-19. Clinical biochemistry, 2021. 89: p. 1-13.
Puckelwartz, M.J. and E.M. McNally, Genetic profiling for risk reduction in human cardiovascular disease. Genes, 2014. 5(1): p. 214-234.
Aragam, K.G. and P. Natarajan, Polygenic scores to assess atherosclerotic cardiovascular disease risk: clinical perspectives and basic implications. Circulation research, 2020. 126(9): p. 1159-1177.
Pashayan, N., et al., Personalized early detection and prevention of breast cancer: ENVISION consensus statement. Nature reviews Clinical oncology, 2020. 17(11): p. 687-705.
Kabay, G., et al., Emerging biosensing technologies for the diagnostics of viral infectious diseases. Advanced Materials, 2022. 34(30): p. 2201085.
Ahmed, M.U., et al., Personalized diagnostics and biosensors: a review of the biology and technology needed for personalized medicine. Critical Reviews in Biotechnology, 2014. 34(2): p. 180-196.
Rasooly, A. and J. Jacobson, Development of biosensors for cancer clinical testing. Biosensors and Bioelectronics, 2006. 21(10): p. 1851-1858.
Serratì, S., et al., Next-generation sequencing: advances and applications in cancer diagnosis. OncoTargets and therapy, 2016: p. 7355-7365.
Godman, B., et al., Personalizing health care: feasibility and future implications. BMC medicine, 2013. 11: p. 1-23.
Shamim, M.Z.M., et al., Diagnostic accuracy of smartphone-connected electrophysiological biosensors for prediction of blood glucose level in a type-2 diabetic patient using machine learning: A pilot study. IEEE Embedded Systems Letters, 2021. 14(1): p. 27-30.
Addissouky, T., et al., Revolutionary innovations in diabetes research: from biomarkers to genomic medicine. Iranian journal of diabetes and obesity, 2023.
Badillo-Ramírez, I., et al., Graphene-based biosensors for molecular chronic inflammatory disease biomarker detection. Biosensors, 2022. 12(4): p. 244.
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Copyright (c) 2024 Ifunanya Emmanuella Ezeumeh, Matthew O. Akindoyin, Adepeju Olowookere, Osinubi Morenike, Temitope Ruth Folorunso , Ilori Gbenga John (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
