Molecular Epidemiology of Hepatitis C Virus Genotypes Among Chronically Infected Patients in Pakistan

A number of studies on the distribution of hepatitis C virus (HCV) genotypes among the chronically HCV-infected people have reported different patterns from various geographical regions of Pakistan. A relatively large scale epidemiological study was needed in order to figure out the distribution pattern of HCV genotypes. This research study was carried out to investigate the distribution pattern of hepatitis C virus genotypes in different geographical regions of Pakistan. In the current study, 5259 randomly selected patients with different genders, ethnicity, age groups, belonging to 24 geographical locations of Pakistan were included. Blood samples from patients with a positive history of active HCV infection were collected from various healthcare units from February 2016 to September 2018. Hepatitis C virus RNA was detected in serum samples by qualitative PCR and confirmed by real-time PCR. Hepatitis C virus genotyping analysis was performed by type specific PCR. Our study revealed that out of 5259 HCV infected patients, HCV genotype 3a was the most frequent one (n = 4203, 79.9%) in all of the 24 regions of Pakistan, especially in Rawalpindi and Islamabad (Twin cities). Untypeable genotype (n = 415, 7.9%) was the second most frequent one after 3a followed by 3a3b co-infection (n = 355, 6.7%), 3b (n = 182, 3.5%), 2a (n = 92, 1.7%), 2b (n = 10, 0.2%), and 1b (n = 2, 0.03%). Interestingly, rarely detectable genotype 4 (n = 1, 0.01%) was also reported. The overall distribution pattern of HCV genotypes was the same in both the genders. Comparatively higher HCV chronic infection was reported among patientwith age group (41 - 55). Currently the existing distribution pattern of HCV genotypes in Pakistan is similar to slight variations in some regions. Comparative analysis of the HCV genotype distribution indicated that the dynamics of HCV genotypes has changed in different areas with the emergence of a relatively uniform pattern across the country.