مقالات پذیرفته شده در نهمین کنگره بین المللی زیست پزشکی
Towards Population-Specific Genomic Databases for Iranian Precision Medicine
Towards Population-Specific Genomic Databases for Iranian Precision Medicine
Nadiya Rahimi,1Mahoora Rahimi,2,*
1. Department of Biomedical Engineering, Faculty of Electrical Engineering and Biomedical Engineering, Sadjad University, Mashhad, Iran 2. Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
Introduction: Precision medicine uses genomic databases to tailor therapies to each patient's genetic profile. These databases store DNA sequences, genetic variations, and expression data to help researchers identify biomarkers, predict treatment outcomes, and enhance prevention strategies. Precision medicine represents a significant shift from traditional, one-size-fits-all therapy to personalized, individualized treatments that consider genetic, environmental, and lifestyle factors. Iran is significantly affected by this change. Genetic diversity in Iran is influenced by previous migrations and the presence of various ethnic groups, including the Persians, Kurds, Azeris, Baluchis, and others. This type causes thalassemia, familial Mediterranean fever, and some cancers. Contemporary global databases, largely influenced by European and North American data, fail to represent these differences, resulting in incorrect diagnoses and poor treatments in Iran. Thus, Iranian precision medicine requires population-specific solutions and datasets. These may help identify genetic predispositions in specific cultures, provide targeted screening, and offer culturally appropriate healthcare advice. Pharmacogenomics can also target Iranian gene–drug interactions to improve therapy. These datasets, combined with advancements in healthcare such as AI, machine learning, and telemedicine, may enhance Iranian healthcare equity and efficacy.
Methods: This research included a literature survey and comparative analysis. A thorough study was conducted on genomic datasets, including the 1000 Genomes Project, gnomAD, ExAC, and Iranome, to evaluate the representation of Iranian genetic diversity. Local Iranian research and healthcare records were compared with foreign data to identify discrepancies, particularly in disease-associated indicators. Online databases, including PubMed, Scopus, and Google Scholar, were examined. Relevant publications were reviewed to provide a broader clinical and population genetic background. This methodology underscored the need for cataloging existing information, accentuating overlooked data, and pinpointing domains necessitating more investigation to enhance precision medicine in Iran.
Results: The analysis of genetic databases has shown significant deficiencies, especially concerning the distinct health issues encountered by the Iranian people. Contemporary databases primarily derive from data of European and North American individuals, resulting in an insufficient representation of Iranians. This mismatch substantially affects the efficacy of precision medicine, which is crucial for comprehending the genetic determinants of illnesses common in certain populations. The substantial genetic variety of Iran, influenced by past migrations and cultural factors, is inadequately reflected in current genome collections, which often use a uniform model. Research indicates that illnesses such as thalassemia, cystic fibrosis, and familial Mediterranean fever (FMF) are more frequent among Iranians and are associated with unique genetic markers that have not been extensively examined in existing databases. Moreover, a lack of population-specific data hinders a thorough study of intricate illnesses, such as diabetes and cardiovascular disorders, which are prevalent in Iran. Research demonstrates that allele frequencies for genetic variations associated with Type 2 diabetes vary significantly between Iranians and groups represented in worldwide databases, potentially leading to erroneous genetic test results. The understanding of gene-environment interactions in Iran remains limited. Distinct environmental influences impacting local populations may modify genetic predispositions, confounding precision medicine initiatives. Recent studies have discovered significant genetic differences among the Iranian population. For example, notable SNPs associated with hereditary disorders, such as particular mutations in the MEFV gene linked to FMF, underscore the need for tailored databases that represent Iran's unique genetic profile. There is an urgent need to provide customized genetic resources to effectively address health needs and enhance precision medicine outcomes in Iran.
Conclusion: For healthcare equity, accuracy, and effectiveness, Iranian precision medicine genetic databases must be redefined. Iran's genetic diversity poses challenges and opportunities. Iranians require tailored genetic resources, as Western databases are often ineffective in addressing their specific needs. Population-specific databases provide an accurate representation of genetic diversity, enhance diagnostic tools, improve treatment methods, and facilitate the development of Iranian patient-specific pharmaceuticals. These databases enhance research, facilitate international collaboration, and improve Iran's genetic standing. Future aims include investments in technology and infrastructure, biobanks, public engagement to foster trust, and robust ethics regarding privacy and consent. AI, machine learning, and telemedicine may accelerate innovation, while political, scientific, and medical networks will promote unity. Redefining Iranian genomic databases becomes a public health and scientific endeavor. Iranian precision medicine has the potential to enhance health outcomes, reduce inequalities, and position the country as a leader in tailored, equitable, and innovative healthcare by embracing genetic variability, cultural context, and technological innovation.