Background: Hepatitis B (HB) and Hepatitis C (HC) viral infections, with 328 million cases globally, represent a significant disease burden. Currently, Pakistan has 3.88 million HB and 9.31 million HC cases. High-risk populations like refugees are disproportionately affected by these infections. The objectives of this study were to determine the seroprevalence of hepatitis B surface antigen (HBsAg) and hepatitis C virus antibody (anti-HCV) among Kashmiri refugees in Muzaffarabad, Pakistan, and to identify the key demographic and educational risk factors associated with the seroprevalence in this population. Methods: A cross-sectional study was conducted across eight refugee camps in the Muzaffarabad division, Pakistan. A six-membered team visited each camp to collect blood samples through venipuncture. The seroprevalence of HBsAg and anti-HCV was determined using rapid immunochromatographic test (ICT) kits. Results: A total of 550 sera samples were collected from the refugee population in Muzaffarabad. The overall seroprevalence was 5.82% (32/550) for HBsAg and 4.73% (26/550) for anti-HCV. A higher seroprevalence of HBsAg and anti-HCV was recorded among females 6.12% (15/245), and 6.53% (16/245), respectively, compared to males 5.75% (17/305), and 3.28% (10/305), respectively. A marked increase in seroprevalence of HBsAg and anti-HCV was noted with an increase in age: 1–10 (2.44%) and (2.44%), 41–50 (8.20%) and (6.56%), and 51–60 (8.93%) and (8.93%), respectively. Chi-square test revealed a statistically significant association between age and seroprevalence of HBsAg χ² (degrees of freedom (df):6, N = 550) = 27.22, p = 0.000, and HC χ² (df:6, N = 550) = 15.23, p = 0.019.The level of education impacted the seroprevalence of HBsAg and anti-HCV, resulting in a higher seroprevalence of HBsAg (6.9%) and anti-HCV (5.4%) among uneducated individuals compared to educated individuals (4.71%) and (3.99%), respectively. Conclusion: The seroprevalence of HBsAg and anti-HCV is high among the refugee population of Muzaffarabad, Pakistan. There is a need for the implementation of a robust vaccination program for HB as well as the establishing a hepatitis micro-elimination program among the Kashmiri refugee population of Muzaffarabad, Pakistan.

Background Diabetes mellitus (DM) affects hundreds of millions of people worldwide. Genetic research plays a cru-cial role in managing diabetes by providing valuable insights into genetic predispositions, facilitating early diagno-sis, and enabling personalized treatment strategies. Identification of important genetic markers has paved the way for the creation of targeted therapies, enhancing treatment outcomes and promoting preventive care for both type 1 diabetes mellitus ( T1DM) and type 2 diabetes mellitus ( T2DM). The aim of this study is to explore the role of different genes in the development of DM and its related complications. Methodology A comprehensive literature search was conducted from October 27 to November 14, 2024, to enlist articles related to genes involved in development of DM and its complications in search engines including PubMed, Medline, Google Scholar, and Scopus. We included original articles, case–control studies, cohort studies, review arti-cles, systematic review, and meta-analysis published between January 1, 2014, and November 14, 2024 in our study. Results In T1DM; research has historically concentrated on the role of HLA class II genes. However, recent studies have brought attention to the role of HLA class I genes in the disease’s development, suggesting a broader role of genetics than previously understood. CTLA4, IL2RA, and PTPN22, genes were also significantly linked to T1DM. In T2DM; TCF7L2 was found to be the most potent gene for its development among others genes such as LCAT, APOE, FTO. For gesta-tional diabetes mellitus (GDM), MTNR1B, CDKAL1, and IRS1 genes played an important role. Conclusion Genetics played an important role in the understanding of DM. Researchers have identified new genetic loci that can serve as diagnostic markers for DM and its associated compilations such as diabetic kidney disease (DKD), diabetic neuropathy (DN), diabetic retinopathy (DR) and cardiovascular diseases (CVDs). TCF7L2 and HLA class II are the strongest risk factors for T2DM and T1DM, respectively. Understanding the genetics of DM and its complications is essential for improving early detection, enhancing treatment outcomes, and developing targeted therapies for DM patients.

Background: Hypertension (HTN) impacts approximately 1.28 billion individuals globally and poses a great burden of disease. The objectives of this study are to explore the role of genetics, epigenetics, microbiome, and artificial intelligence (AI) in the management of HTN. A thorough literature search was conducted across various databases including PubMed, Google Scholar, Web of Science (WoS), and Medline to retrieve articles related to the role of genetics, epigenetics, microbiome, and AI in the precision medicine of HTN. Genes—including ACE, NOS3, ADD1, CYP11B2, NPPA, and NPPB—have a profound impact on blood pressure (BP) regulation in our body and polymorphism in these key genes can lead to HTN. Up or down-regulation of genes by epigenetic factors such as miRNA-155, miRNA-210, and miRNA-122 can significantly contribute to the development of HTN. These genetic and epigenetic factors can also be used as specific targets for gene editing and gene therapy for long-term management of HTN. However, the implementation of these techniques has not been possible in clinical settings due to lack of human studies and safety concerns related to unpredictable DNA alterations, nucleotide deletions, and loss of allele-specific chromosomes. Modulation of gut microbiome through oral supplements, fecal microbiota transplant (FMT), and dietary interventions has emerged as one the most effective and safe techniques for managing HTN in human models. AI-based cutting-edge models have helped curate personalized diet plans based on an individual’s unique microbiome, genomic information, and physiological conditions leading to a reduction in BMI, fat, BP, and heart rate while improving overall cardiac health and gut microbial diversity. Despite the significant advantages offered by AI-based medicine, ethical concerns—related to data privacy, bias, and discrimination—and ineffective models have led to limited integration of AI in precision medicine of HTN. The integration of genetics, epigenetics, microbiome, and AI-based models can play a key role in improving the current landscape of precision medicine of HTN. These cutting-edge techniques can lead to a shift from the current one-size-fits all approach to more personalized treatment plan however further research in human models is needed to determine the safety and true efficacy of these techniques. Additionally, new AI-models need to be developed that address ethical concerns and are effective in real-world clinical settings.