A decade-long retrospective study of hepatitis C virus genetic diversity in Cameroon, 2013-2023: presence of a high proportion of unsubtypable and putative recombinant HCV strains.

While treatment options for hepatitis C virus (HCV) infection have expanded considerably over the past decade thanks to the development of pan-genotypic therapies, genotype testing remains a prerequisite for treatment in sub-Saharan African countries, including Cameroon, where multiple HCV genotypes and subtypes exist. The main objective of this study was to describe the trend in the distribution of HCV genotypes and subtypes from 2013 to 2023 in the Cameroonian population. Viral loads were determined using the Abbott real-time assay, and genotyping/subtyping was based on nested and semi-nested reverse transcription polymerase chain reaction (RT-PCR) amplification of the regions encoding the core and non-structural protein 5B (NS5B) regions, respectively, followed by sequencing and phylogenetic analysis. A total of 512 patients with NS5B and core sequencing results were included in our study. Genotyping revealed a predominance of both genotype 4 (38.48%) and genotype 1 (37.11%), followed by genotype 2, detected in 22.46% of patients. Interestingly, 10 samples (1.95%) had discordant genotypes in both regions, suggesting the presence of putative recombinant forms of HCV. Twelve different subtypes were detected during the study period, with a predominance of subtypes 4f (18.95%) and 1e (16.02%). Furthermore, phylogenetic analysis failed to assign a subtype to a relatively high proportion of sequences (38.67%) for the two genomic regions, and their classification was limited to genotype assignment. The frequency distribution of HCV genotypes did not show any statistical difference according to year or sex. These results confirm the genetic diversity of HCV in Cameroon and the potential for the generation of recombinant strains.

A cheap and open HIV viral load technique applicable in routine analysis in a resource limited setting with a wide HIV genetic diversity.

BACKGROUND: HIV infection in Cameroon is characterized by a great viral diversity with all HIV-1 groups (M, N, O, and P) and HIV-2 in circulation. HIV group determination is very important if tailored viral load analysis and treatments are to be applied. In our laboratory, HIV viral load is carried out using two platforms; Biocentric and Abbott depending on the HIV group identified. Biocentric which quantifies HIV-1 group M is a cheap and open system useful in resource limited settings. The objective of this study was to compare the viral load analyses of serologically group-indeterminate HIV samples using the two platforms with the view of reducing cost. METHODS: Consecutive samples received between March and May 2014, and between August and September 2014 in our laboratory for HIV viral load analysis were included. All these samples were analyzed for their HIV groups using an in-house ELISA serotyping test. All HIV-1 group M samples were quantified using the Biocentric test while all other known atypical samples (HIV-1 groups N, O and P) were analyzed using the Abbott technique. HIV group-indeterminate samples (by serotyping) were quantified with both techniques. RESULTS: Among the 6355 plasma samples received, HIV-1 group M was identified in 6026 (94.82%) cases; HIV-1 group O, in 20 (0.31%); HIV-1 group M + O, in 3 (0.05%) and HIV-2, in 3 (0.05%) case. HIV-group indeterminate samples represented about 4.76% (303/6355) and only 231 of them were available for analysis by Abbott Real-Time HIV-1 and Generic HIV Viral Load techniques. Results showed that 188 (81.39%) samples had undetectable viral load in both techniques. All the detectable samples showed high viral load, with a mean of 4.5 log copies/ml (range 2.1-6.5) for Abbott Real-Time and 4.5 log copies/ml (range 2-6.4) for Generic HIV Viral Load. The mean viral load difference between the two techniques was 0.03 log10 copies/ml and a good correlation was obtained (r 2 = 0.89; P < 0.001). CONCLUSION: Our results suggest that cheaper and open techniques such as Biocentric could be useful alternatives for HIV viral load follow-up quantification in resource limited settings like Cameroon; even with its high viral diversity.