International Journal of Social Science & Economic Research
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Title:
Integration of Polygenic Risk Scores and Artificial Intelligence into Healthcare

Authors:
Shannon Victor

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Shannon Victor
Independent Researcher, USA

MLA 8
Victor, Shannon. "Integration of Polygenic Risk Scores and Artificial Intelligence into Healthcare." Int. j. of Social Science and Economic Research, vol. 9, no. 10, Oct. 2024, pp. 4864-4873, doi.org/10.46609/IJSSER.2024.v09i10.053. Accessed Oct. 2024.
APA 6
Victor, S. (2024, October). Integration of Polygenic Risk Scores and Artificial Intelligence into Healthcare. Int. j. of Social Science and Economic Research, 9(10), 4864-4873. Retrieved from https://doi.org/10.46609/IJSSER.2024.v09i10.053
Chicago
Victor, Shannon. "Integration of Polygenic Risk Scores and Artificial Intelligence into Healthcare." Int. j. of Social Science and Economic Research 9, no. 10 (October 2024), 4864-4873. Accessed October, 2024. https://doi.org/10.46609/IJSSER.2024.v09i10.053.

References

[1] . Chacko, M., Sarma, P. S., Harikrishnan, S., Zachariah, G., & Jeemon, P. (2020). Family history of cardiovascular disease and risk of premature coronary heart disease: A matched case-control study. Wellcome Open Research, 5(5), 70. https://doi.org/10.12688/wellcomeopenres.15829.2
[2] . CDC. (2024, January 17). Social Determinants of Health (SDOH). CDC. https://www.cdc.gov/about/priorities/why-is-addressing-sdoh-important.html
[3] . Choi, S. W., Mak, T. S.-H., & O’Reilly, P. F. (2020). Tutorial: a guide to performing polygenic risk score analyses. Nature Protocols, 15(9), 2759–2772. https://doi.org/10.1038/s41596-020-0353-1
[4] . Gene and Environment Interaction. (2018). National Institute of Environmental Health Sciences. https://www.niehs.nih.gov/health/topics/science/gene-env#:~:text=Introduction
[5] . Hernandez, L. M. (2016). Genetics and Health. Nih.gov; National Academies Press (US). https://www.ncbi.nlm.nih.gov/books/NBK19932
[6] . Krisela Steyn, & Albertino Damasceno. (2009). Lifestyle and Related Risk Factors for Chronic Diseases. Nih.gov; The International Bank for Reconstruction and Development / The World Bank. https://www.ncbi.nlm.nih.gov/books/NBK2290/
[7] . Lewis, C. M., & Vassos, E. (2020). Polygenic risk scores: from research tools to clinical instruments. Genome Medicine, 12(1). https://doi.org/10.1186/s13073-020-00742-5
[8] . Mostafavi, H., Harpak, A., Agarwal, I., Conley, D., Pritchard, J. K., & Przeworski, M. (2020). Variable prediction accuracy of polygenic scores within an ancestry group. ELife, 9. https://doi.org/10.7554/elife.48376
[9] . Norori, N., Hu, Q., Aellen, F. M., Faraci, F. D., & Tzovara, A. (2021). Addressing bias in big data and AI for health care: A call for open science. Patterns, 2(10), 100347. https://doi.org/10.1016/j.patter.2021.100347
[10] . National Human Genome Research Institute. (2020, August 11). Polygenic Risk Scores. Genome.gov. https://www.genome.gov/Health/Genomics-and-Medicine/Polygenic-risk-scores
[11] . Polygenic Risk Score (PRS). (n.d.). Genome.gov. https://www.genome.gov/genetics-glossary/Polygenic-Risk-Score
[12] . Polygenic Risk Scores in Complex Disease Research. (2020). Illumina.com. https://www.illumina.com/areas-of-interest/complex-disease-genomics/polygenic-risk-scores.html#:~:text=Polygenic%20risk%20scores%20
[13] . Social determinants of health. (n.d.). Www.who.int.
[14] . https://www.who.int/health-topics/social-determinants-of-health#tab=tab_
[15] . Uffelmann, E., Huang, Q. Q., Munung, N. S., de Vries, J., Okada, Y., Martin, A. R., Martin, H. C., Lappalainen, T., & Posthuma, D. (2021). Genome-wide association studies. Nature Reviews Methods Primers, 1(1). https://doi.org/10.1038/s43586-021-00056-9
[16] . Volk, H. E., Kerin, T., Lurmann, F., Hertz-Picciotto, I., McConnell, R., & Campbell, D. B. (2014). Autism Spectrum Disorder. Epidemiology, 25(1), 44–47. https://doi.org/10.1097/ede.0000000000000030
[17] . What are complex or multifactorial disorders?: MedlinePlus Genetics. (2021).
[18] . Medlineplus.gov. https://medlineplus.gov/genetics/understanding/mutationsanddisorders/complexdisord ers/#:~:text=Common%20health%20 problems%20such%20as
[19] . WHO. (2024). Social Determinants of Health. World Health Organization. https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1

ABSTRACT:
The introduction of artificial intelligence technology has been groundbreaking in increasing positive outcomes and simplifying processes for numerous industries. In recent years, the healthcare field has followed suit by leveraging advancements to allow for predictive analysis. The integration of artificial intelligence into scientific techniques has transformed the way we identify the population’s genetic predispositions to diseases. Polygenic risk scores (PRS) are a calculation of an individual’s risk for a certain genetic disease. However, since most complex diseases are also affected by environmental and lifestyle factors that these tests don’t take into consideration, utilizing artificial intelligence in addition to this provides a much more accurate approach. This will aid in identifying individuals at higher risk, usually because of family history, in order to provide a comprehensive diagnosis and treatment plan. While this combination holds significant promise in advancing personalized medicine, it’s important to be aware of the possible racial and socioeconomic underrepresentation present in the current development of these technologies.

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