Molecular Epidemiology of HIV-1 Virus in Egypt: A Major Change in the Circulating Subtypes

Abstract

Background: Human immunodeficiency virus type 1 (HIV-1) is characterized by high genetic diversity due to its high-mutation and recombination rates. Although, there is an increasing prevalence of circulating recombinant forms (CRFs) worldwide. Subtype B is still recognized as the predominant subtype in the Middle East and North Africa (MENA) region. There is a limited sampling of HIV in this region due to its low prevalence. The main purpose of this study is to provide a summary of the current status of the resident HIV subtypes and their distribution among Egyptian patients. Methodology: Forty-five HIV-1 patients were included in this study. Partial pol gene covering the protease (PR) and reverse transcriptase (RT) was successfully amplified in 21 HIV patients using nested PCR of cDNA of the viral genomic RNA, then sequenced. The sequence data were used for viral HIV-1 subtyping by 5 online subtyping tools: NCBI viral genotyping tool, Stanford University HIV database (HIVDB) subtyping program, REGA tool, Context-based modeling for expeditious typing (COMET) tool, and Recombinant identification program (RIP) tool. The final subtype assignment was based on molecular phylogenetic analysis. Results: Unexpectedly, non-B subtypes are dominating with the most common circulating one is CRF02_AG (57.1%) followed by subtype B (14.3%), subtype BG recombinant (9.5%), CRF35_AD (9.5%), subtype A1 and CRF06_cpx (4.8 % each). Conclusion: To the best of our knowledge, this is the first study to tackle HIV-1 subtyping among the group of HIV-1 patients in Egypt. CRF02_AG is the most prevalent subtype in Egypt.

Establishment and analysis of artificial neural network diagnosis model for coagulation-related molecular subgroups in coronary artery disease

“…In recent years, research on molecular subgroups and particular illness biomarkers has been intensively conducted due to the advancement of whole-genome sequencing technology and the demand for individualized treatment. For example, molecular characterization and typing of triple-negative breast cancer (Bareche et al, 2018;Zhao et al, 2020), colorectal cancer (Menter et al, 2019;Hu et al, 2021), lung adenocarcinoma (Wang et al, 2020), pancreatic ductal carcinoma (Topham et al, 2021), and other solid tumors based on tumor multi-omics datasets from the Cancer Genome Atlas (TCGA) database (Tomczak et al, 2015); molecular typing of non-neoplastic diseases are commonly used in immune-related diseases such as HIV (Patil et al, 2020;Amer et al, 2021). However, other diseases are limited by the lack of large-scale sequencing data, and molecular diagnosis and typing are still in the preliminary development.…”