Abstract
Background
The study assessed replicative human immunodeficiency virus-(HIV-) infection and replicative co-infections as well as molecular determinants of reduced susceptibility towards anti-retroviral therapy in a Ghanaian population of known HIV patients and a control group.
Methods
Real-time PCRs for HIV-1, HIV-2, hepatitis B virus (HBV) and hepatitis C virus (HCV) were run with serum samples from known Ghanaian HIV-patients (n = 975) and control individuals (n = 105). For 108 individuals, HIV-sequence analysis was performed.
Results
Prevalence of replicative HIV-1 infection was 59.8% (583/975) in the known HIV-positive population and 2.9% (3/105) in the controls. Prevalences of replicative HBV-infection were comparable with 3.4% (33/975) in the HIV-positive individuals and 3.8% (4/105) in the controls. HIV-2 and HCV sequences were not recorded. Almost perfect concordance between two compared HIV-1-PCR assays was indicated by Fleiss' Kappa >0.8. Sanger sequencing indicated CRF_02AG, G and A3 as the quantitatively dominating HIV-1 subtypes, a minority of 3.4% CXCR4 tropism and high detection rates of mutations mediating reduced susceptibility towards nucleoside reverse transcriptase inhibitors (71.9%, 64/89), non-nucleoside reverse transcriptase inhibitors (95.5%, 85/89), protease inhibitors (95.9%, 93/97) and integrase inhibitors (22.4%, 22/98).
Conclusions
The assessment did not suggest HIV-triggered increased replication of HBV and HCV in the investigated Ghanaian population.
Introduction
Infections with the human immunodeficiency virus (HIV) and parenterally transmitted hepatitis viruses like the hepatitis B virus (HBV), the hepatitis C virus (HCV) and the hepatitis D virus (HDV) are generally known to frequently co-occur in human patients and partly to facilitate each other's replication [1–15]. The primary reason for co-occurrence is the comparable mode of transmission [8, 16, 17], resulting in 15% HIV-HCV-coinfections in Germany, 30% in the USA and even higher rates in Eastern Europe as well as immunologically proven contact of up-to 95% of HIV-infected individuals with HBV globally. Beyond the transmission mode, however, pathophysiological and immunologic interactions of the viruses have been described as well as interactions regarding the replication behavior. In particular, mortality of HBV-associated liver disease is 15× as high in HIV-positive compared to HIV-negative individuals, HBV replication, disease progression and risk of cirrhosis are increased due to HIV infection-induced pro-inflammatory and apoptosis-facilitating factors [9, 18]. In turn, HBV is associated with increased HIV-related mortality and an increased number of AIDS (acquired immunodeficiency syndrome)-defining medical conditions [19, 20]. HIV-induced immunosuppression can facilitate the progress of HCV infection with decreased latency periods until liver failure or hepatic carcinoma, while a potential impact of HCV on the course of the HIV infection is considered as uncertain [11, 13, 21, 22].
While HIV, HBV and HCV infections are generally considered as well treatable, resistance mutations in HIV remain a challenge to consider. Sequence-guided HIV resistance assessment has recently shifted towards next-generation-sequencing-(NGS-)based protocols [23] including highly standardized commercial products [24–28]. While NGS-approaches are generally considered to provide deeper insights into mutations occurring in smaller proportions of virus variants compared to traditional Sanger sequencing [29, 30], the clinical impact of this increased sensitivity in terms of associated therapy failure is a matter of debate [31]. Sequencing also provides a global view on the distribution of HIV variants and their resistance mutations as reported elsewhere [32]. Such resistance mechanisms and their local prevalence are collected in specific databases [33–35]. Irrespective of the region of assessment, however, the choice of antimicrobial treatment is the primary determinant of resistance selection and distribution, with typical resistance-associated mutations as recently summarized freely-accessible elsewhere [36] for interested readers.
In the study provided here, we focused on viral co-infections and HIV-1 resistance mutations in Ghanaian HIV-1-infected individuals. Ghana is a west African country considerably affected by the HIV/AIDS pandemic. The prevalence of HIV infections in the Ghanaian populations is estimated to be 1.6% with female sex workers (FSW), male clients of FSW as well as men-having-sex-with-men (MSM) accounting for 28% of new infections [37]. The high incidence in risk groups can partly be attributed to low health literacy [38] in spite of existing prevention programs [39]. Thereby, the Ghanaian health system is generally considered as prepared for the diagnostic and therapeutic challenge of the HIV/AIDS pandemic. The time is long gone since blood transfusion was still a major risk factor for HIV transmission in Ghana [40], short timelines of registration facilitate broad availability of antiretroviral combination therapy [41] and the option of therapeutic adaptations [42] is well established. Governmental response to the HIV/AIDS pandemic was enforced early in Ghana [43]. In spite of repeatedly reported supply shortages [44], facilities for the diagnosis and treatment of HIV infections and associated opportunistic infections are broadly available [45–47]. Nevertheless, considerable mortality of 35.5% was recently reported for people-living-with-HIV (PLWH) admitted as in-patients to a Ghanaian hospital with tuberculosis and neurological disorders being identified as major risk factors [48]. Late presentation of HIV-infected men to medical care [49] is a potential reason for the above-mentioned unfavorable outcomes [48], but also Ghanian children are often diagnosed with HIV associated with inpatient care due to severe co-occurring infectious diseases [50]. Further, missed opportunities for maternal testing accounts for avoidable mother-to-child transmission events [51] and maternal knowledge on HIV is considered as a factor influencing the birth-associated transmission risk in Ghana [52].
Adherence rates with antiretroviral therapy (ART) still leave room for improvement, facilitating the spread of the infection among Ghanaians. In adults, adherence has been estimated to be 70% (58%–81%), in adolescents and young adults even as low as 66% (48%–84%) [53]. In line with this, a reduced viral suppression rate of 76% has been reported for PLWH on anti-retroviral therapy in the Ghanaian town of Kumasi [54]. In contrast, high viral response rates could be achieved in case of adequate adherence with antiretroviral medication intake [55]. Factors affecting adherence with antiretroviral therapy in Ghana comprise the stage of the HIV infection and the choice of the antiretroviral therapy, forgetfulness, secrecy, waiting time, religious beliefs, sleepiness, pill fatigue, repeated stock out of medicines, long waiting times, and worrying side-effects [56–59]. Further and non-surprisingly, therapy-interruption has been identified as a relevant factor associated with the accumulation of resistance associated mutations (RAMs) and thus virological failure of ART in Ghana [60]. Further identified factors associated with HIV non-suppression in Ghanaian patients comprise female sex, history of treatment of tuberculosis, severe depletion of CD4+ T-lymphocytes, use of old substances like the non-nucleoside reverse transcriptase inhibitor (NNRTI) nevirapine, limited compliance and restricted access to virus load assessment under therapy [61, 62]. Consequently, same-day point-of-care viral load testing was suggested as an option to increase therapeutic effectiveness in Ghana [63]. In HIV-positive Ghanaian children, factors associated with unfavorable therapeutic outcomes comprised high viral load, age at initiation of therapy, child's sex, not having a parent as a primary care giver, severity of illness, and type of therapeutic regimen [64, 65].
In Ghana, PLWH show considerable proportions of co-infections with other blood-borne viruses like HBV and HCV [66–68] with a high proportion of HBV genotype E but also abundance of A and D genotypes as well as A/E and D/E recombinant viruses [69]. In a meta-analysis from 2016, it was estimated that about every 7th Ghanaian individuum living with HIV might also be HBV-co-infected [66]. Overall, HBV-seroprevalence in Ghana considerably varies depending on factors like geographic region and sex of the assessed individual [70–72] while overall HBV surface antigen prevalence indicative of transcription-active infection was slightly lower with 8.5% [73]. Of note, HBV-positivity is associated with anti-HDV-seroprevalence in the 7%–10% range in Ghana [74]. Lamivudine resistance is common in lamivudine-treated Ghanaian HBV patients. Locally identified lamivudine resistance mutations comprised rtV173L, rtL180M and rtM204V in recent assessments [75, 76]. Ghanaian prevalence of chronic HCV infections is estimated in the 3% range with higher prevalence in rural (5.7%) than in urban settings (2.6%) and about 2.8% HCV prevalence in PLWH [67]. Co-infections of HIV with non-viral infectious diseases play a role in Ghana as well. In nearly every fifth Ghanaian tuberculosis patient, HIV-coinfection can be expected [77]; children and females are particularly affected [78].
Several cross-sectional studies have reported on resistance mutations in HIV in Ghanaian patients [60, 79–87]. Resistance against NNRTIs has been described as most common with 12% resistance in treatment-naïve PWLH, while integrase inhibitor (INST) resistance was least common with about 2% [79]. In HIV-1 patients under therapy, resistance was reported in more than 40% or even 70% of assessed PLWH [81, 82] with therapy duration being associated with the risk of antiretroviral resistance [82] compared to low resistance rates in non-treated individuals [83, 84]. Described local HIV-1 resistance associated mutations (RAMs) comprised RAMs mediating reduced susceptibility against nucleoside reverse transcriptase inhibitors (NRTIs) like M41L, K65R, D67N, T69N, K70R/E, M184V/I and T215Y/F [55, 79–81, 83, 84], against NNRTIs like V90I, A98G, K103N, V106A, E138A, V179E, Y181C, G190S, and F227L [24, 45–47, 49–51] and against protease inhibitors (PIs) like L10I, L10V, V11I, E35G, M46I, I54 V, V82A, L90M and I471 V [82, 86, 87]. Combined NRTI/NNRTI-resistance via the M184V/K103N pattern was identified as a frequent cause of failure of early treatment schemes in Ghana [65]. For HIV-2, resistance information in Ghana is scarce, but RAMs affecting NRTI susceptibility (K65R, Y115F and M184V) have been reported for Ghanaian HIV-2 patients [88].
Predominant HIV-1 subtypes in Ghana comprise the circulating recombinant form CRF02_AG [60, 79], mosaics containing CRF02_AG and/or CRF06_cpx as well as other unique recombinant forms, but the subtypes A, A1, A3, B, G, K, the complex circulating recombinant form CRF09_cpx as well as recombinant forms with CRF01_AE, CRF02_AG/A3, CRF02_AG/A3/CRF06_cpx and CRF02_AG/A3/CRF09_cpx mosaics are also locally abundant [80–82, 87, 89]. HIV-1 showing CXCR4-tropismus was demonstrated with a prevalence of 23% in a recent assessment of treatment-naïve Ghanaian individuals [79]. Focusing on HIV-2 patients, the HIV-2 groups A and B are known to be prevalent in Ghana [88].
The study presented here was conducted to contribute to the understanding of the epidemiology of HIV and replicative viral co-infections in Ghana. In a population of known HIV-positive individuals from Ghana and a small Ghanaian control cohort without known HIV-infection, replicative infection as indicated by positive real-time PCR was assessed for HIV-1, HIV-2, HBV, and HCV. In addition to the search for replicative co-infections, a subpopulation of 108 samples with the highest viral load for HIV-1 were assessed for RAMs applying Sanger sequencing. As a minor aim of the assessment, two published in-house real-time PCR assays for HIV-1 were comparatively assessed for their diagnostic accuracy.
Methods
Study type
The study was conducted as a retrospective cross-sectional assessment with serum-samples from a fully anonymized historic cohort of Ghanaian PLWH as well as a control cohort of Ghanaian individuals without known HIV infection.
Study population
From 1083 assessed residual serum samples, 3 were excluded due to PCR inhibition. Consequently, the study population comprised 1080 residual serum samples collected previously [90] from 975 known Ghanian PLWH as well as 105 samples from Ghanian individuals without known HIV infection. The samples were blinded prior to the assessment not allowing assignments to specific patients, as correlation with patient-specific characteristics like immune parameters or HIV-specific medication was not the study purpose of this holistic investigation. On population level, the mean age (± standard deviation (±SD)) was 39.6 (±9.9) with a male-to-female ratio of 3:1. When focusing on the subpopulation of included PLWH, median CD4+ T-cell count/μL (interquartile range (IRQ)) of 392.5 (189, 610), median CD4+/CD8+ T-cell ratio of 0.4 (0.2, 0.7) and median viral load in log10 copies/mL of 4.0 (1.6, 5.2) had been recorded. The relation of treatment-naïve PWLH and HIV-positive individuals under antiretroviral therapy was 1:1 with a dominance of NRTI/NNRTI-based therapy regiments (96.7%) compared to NRTI/PI-based schemes (3.3%).
Real-time PCR-based screening for HIV-1, HIV-2, HBV and HCV
Prior to the assessments, the analyzed serum samples had been stored at −80°C. Nucleic acid extraction was performed automatically using the EZ1 Virus Mini Kit v2.0 assay (Qiagen, Hilden, Germany) on an EZ1 Advanced (Qiagen, Hilden, Germany) automate according to the manufacturer's instructions. Again, eluates were stored at −80 °C prior to subsequent real-time PCR based screening for nucleic acid sequences of HIV-1, HIV-2, HBV and HCV. For HIV-1, two published real-time PCR assays were applied targeting either the LTR (long terminal repeat) region based on the protocol by Candotti et al. (referred to as the “Candotti HIV-1 PCR” in the following) [91] or the gag p24-region based on the protocol by Yamazaki et al. (referred to as the “Yamazaki HIV-1 PCR” in the following) [92]. HIV-2 screening was based upon a protocol by Yamazaki et al. targeting a HIV-2-specific LTR-region [92], HBV-screening upon a protocol by Weinberger et al. and Candotti et al. targeting a conserved region of the HBV surface gene [91, 93] and HCV-screening upon a protocol by Candotti et al. targeting HCV's 5′-UTR (untranslated region) [91, 94]. The assays were run on Corbett Q (Qiagen, Hilden, Germany) cyclers applying the QuantiNova Pathogen +IC (Qiagen, Hilden, Germany) kit including a commercial RNA-based internal control. Next to the internal controls, a plasmid-based positive control and a PCR-grade water-based negative control were included in each run. Details on the PCR reactions including technical detection thresholds as defined applying 10-fold dilution steps of the positive control plasmids are shown in Tables 1 and 2. As indicated in Table 1, the HIV-specific real-time PCR assays' detection thresholds do not match detection thresholds typical for modern commercial assays, indicating substantial replication in case of positive signals. Quantification was not performed in this study.
Target genes, calculated detection limits and oligonucleotides used for the applied real-time PCR screening assays for HIV-1, HIV-2, HBV and HCV. Hyphens in the oligonucleotide sequences have been inserted to increase the readability, not to delineate codon triplets
PCR target | HIV-1 (Candotti HIV-1 PCR) |
Target gene | LTR (long terminal repeat) region |
Detection limit | 3.2 × 102/µL |
Forward primer | 5′-TAA-AGC-TTG-CCT-TGA-GTG-CT-3′ |
Reverse primer | 5′-GTC-TGA-GGG-ATC-TCT-AGT-TAC-CAG-3′ |
Probe and modifications | 5′-FAM-AGT-AGT-GTG-TGC-CCG-TCT-GTT-GTG-TG-TAMRA-3′ |
Positive control plasmid insert | 5′-TAA-GCC-TCAA-TAA-AGC-TTG-CCT-TGA-GTG-CTT-CAA-GTA-GTG-TGT-GCC-CGT-CTG-TTG-TGT-GAC-TCT-GGT-TTG-ACT-CTG-GTA-ACT-AGA-GAT-CCC-TCA-GAC-CAA-TTT-AGT-CGA-ATT-CGA-ATT-CTA-CGC-GAG-ACT-GCT-AGC-CGA-GTA-GTG-TTG-GGT-CGC-GAA-AGG-CCT-TGT-GGT-ACT-GCC-TGA-TAG-GGT-GCT-TGC-GAG-TGC-AGA-CTA-TCT-CGC-GAT-CCC-CAA-CCT-CCA-ATC-ACT-CAC-CAA-CCT-CCT-GTC-CTC-CAA-TTT-GTC-CTG-GTT-ATC-GCT-GGA-TGT-GTC-TGC-GGC-GTT-TTA-TCA-TAT-TCC-TCT-TCA-T-3′ |
GenBank accession number used for the insert | OR246504.1 |
Reference | [91] |
PCR target | HIV-1 (Yamazaki HIV-1 PCR) |
Target gene | gag p24-region |
Detection limit | 8.4 × 102/µL |
Forward primer | 5′-AGT-RGG-GGG-ACA-YCA-RGC-AGC-HAT-GCA-RAT-3′ |
Reverse primer | 5′-TAC-TAG-TAG-TTC-CTG-CTA-TRT-CAC-TTC-C-3′ |
Probe and modifications* | 5′-6-FAM-ATC-AAT-GAR-GAR-GCT-GCA-GAA-TGG-GA-MGB-CDPl3-3′ |
Positive control plasmid insert | 5′-TGC-TAA-ACA-CAG-TGG-GGG-GAC-ATC-AAG-CAG-CCA-TGC-AAA-TGT-TAA-AAG-AGA-CCA-TCA-ATG-AGG-AAG-CTG-CAG-AAT-GGG-ATA-GAG-TGC-ATC-CAG-TGC-ATG-CAG-GGC-CTA-TTG-CAC-CAG-GCC-AGA-TGA-GAG-AAC-CAA-GGG-GAA-GTG-ACA-TAG-CAG-GAA-CTA-CTA-GTA-CCC-TTC-AGG-A-3′ |
GenBank accession number used for the insert | K03455.1 |
Reference | [92] |
PCR target | HIV-2 |
Target gene | HIV-2-specific LTR-region |
Detection limit | 5.6 × 102/µL |
Forward primer | 5′-GCG-GAG-AGG-CTG-GCA-GAT-3′ |
Reverse primer | 5′-TCT-TTA-AGC-AAG-CAA-GCG-TGG-3′ |
Probe and modifications | 5′-FAM-AGC-AGG-TAG-AGC-CTG-TAMRA-3′ |
Positive control plasmid insert | 5′-CGA-CAG-CAC-GGG-CGG-AAT-AGA-GTG-GCT-TAA-TTC-TCA-ATC-TAT-CCC-CAC-GTA-TGC-ATC-TGA-ATT-AAC-AAA-TGA-ACT-TCT-TAA-AAA-AGA-CGG-TAA-AGT-ACA-AGC-TAA-AAA-TTC-ATT-TAG-CGG-AG-3′ |
GenBank accession number used for the insert | M15390.1 |
Reference | [92] |
PCR target | HBV |
Target gene | conserved region of the HBV surface gene |
Detection limit | 3.2 × 101/µL |
Forward primer | 5′-CAA-CCT-CCA-ATC-ACT-CAC-CAA-C-3′ |
Reverse primer | 5′-ATA-TGA-TAA-AAC-GCC-GCA-GAC-AC-3′ |
Probe and modifications | 5′-ROX-TCCTCCAATTTGTCCTGGTTATCGCT-BHQ2-3′ |
Positive control plasmid insert | 5′-TAA-GCC-TCAA-TAA-AGC-TTG-CCT-TGA-GTG-CTT-CAA-GTA-GTG-TGT-GCC-CGT-CTG-TTG-TGT-GAC-TCT-GGT-TTG-ACT-CTG-GTA-ACT-AGA-GAT-CCC-TCA-GAC-CAA-TTT-AGT-CGA-ATT-CGA-ATT-CTA-CGC-GAG-ACT-GCT-AGC-CGA-GTA-GTG-TTG-GGT-CGC-GAA-AGG-CCT-TGT-GGT-ACT-GCC-TGA-TAG-GGT-GCT-TGC-GAG-TGC-AGA-CTA-TCT-CGC-GAT-CCC-CAA-CCT-CCA-ATC-ACT-CAC-CAA-CCT-CCT-GTC-CTC-CAA-TTT-GTC-CTG-GTT-ATC-GCT-GGA-TGT-GTC-TGC-GGC-GTT-TTA-TCA-TAT-TCC-TCT-TCA-T-3′ |
GenBank accession number used for the insert | X51970.1 |
Reference | [91, 93] |
PCR target | HCV |
Target gene | 5′-UTR (untranslated region) |
Detection limit | 3.2 × 102/µL |
Forward primer | 5′-TGC-TAG-CCG-AGT-AGY-GTT-GG-3′ |
Reverse primer | 5′-ACT-CGC-AAG-CAC-CCT-ATC-AG-3′ |
Probe and modifications | 5′-Cy5-ACC-ACA-AGG-CCT-TTC-GCG-AC-BHQ2-3′ |
Positive control plasmid insert | 5′-TAA-GCC-TCAA-TAA-AGC-TTG-CCT-TGA-GTG-CTT-CAA-GTA-GTG-TGT-GCC-CGT-CTG-TTG-TGT-GAC-TCT-GGT-TTG-ACT-CTG-GTA-ACT-AGA-GAT-CCC-TCA-GAC-CAA-TTT-AGT-CGA-ATT-CGA-ATT-CTA-CGC-GAG-ACT-GCT-AGC-CGA-GTA-GTG-TTG-GGT-CGC-GAA-AGG-CCT-TGT-GGT-ACT-GCC-TGA-TAG-GGT-GCT-TGC-GAG-TGC-AGA-CTA-TCT-CGC-GAT-CCC-CAA-CCT-CCA-ATC-ACT-CAC-CAA-CCT-CCT-GTC-CTC-CAA-TTT-GTC-CTG-GTT-ATC-GCT-GGA-TGT-GTC-TGC-GGC-GTT-TTA-TCA-TAT-TCC-TCT-TCA-T-3′ |
GenBank accession number used for the insert | OQ676935.1 (modified) |
Reference | [91, 94] |
*Internally modified 5. BMN-Q535.
Reaction mixes and run conditions for the real-time screening PCR assays for HIV-1, HIV-2, HBV and HCV
Candotti HIV-1 assay, HBV assay, HCV assay | Yamazaki HIV-1 assay, HIV-2 assay | |
Reaction chemistry | ||
Master Mix | QuantiNova Pathogens (Qiagen) | QuantiNova Pathogens (Qiagen) |
Reaction volume (µL) | 20.0 | 20.0 |
Forward primer concentration (pmol µL−1) | 20.0 for HIV-1 and HCV, 25.0 for HBV | 20.0 |
Reverse primer concentration (pmol µL−1) | 20.0 for HIV-1 and HCV, 25.0 for HBV | 20.0 |
Probe concentration (pmol µL−1) | 5.0 | 16.0 |
Final Mg2+ concentration (mM) | 5.0 | 4.0 |
Internal control reaction mix | QuantiNova IC Probe Assay | QuantiNova IC Probe Assay |
Internal control | QN IC RNA | QN IC RNA |
Eluate volume (µL) | 5.0 | 5.0 |
Run conditions | ||
Reverse transcription | 50°C, 10 min. | 50 °C, 10 min. |
Initial denaturation | 95°C, 2 min. | 95 °C, 2 min. |
Cycle numbers | 45 | 50 |
Denaturation | 95°C, 30 s. | 94°C, 1 s. |
Annealing | Combined with amplification | 60°C, 10 s. |
Amplification | 60°C, 60 s. | 72°C, 15 s. |
Hold | 40°C, 20 s. | 40°C, 20 s. |
min. = minute, sec. = second.
Sequence assessment of HIV-1 resistance mutations, subtypes and tropism
Amplification of amplicons for Sanger sequencing-based HIV-1 resistance assessment, subtype assignment and tropism assessment with nested PCR were performed with primers adapted from the protocols (version 2022.1) of the French National Agency for AIDS Research (ANRS) [95]. The 108 samples with the lowest cycle threshold (Ct) values in HIV-1 PCR were subjected to sequence analysis. For the first PCR of the nested approach, a QuantiNova Pathogen +IC (Qiagen, Hilden, Germany) master mix was used, while a HotStar master mix (Qiagen, Hilden, Germany) was applied for the second PCR. Protocols are shown in more details in Tables 3 and 4. As shown there, a primary and a secondary assay were used for reverse transcriptase inhibitor resistance assessment, a primary, secondary and tertiary assay for integrase inhibitor resistance. The assays were applied in declining order in case of failure of an assay ranked higher in the assigned order. For protease inhibitor resistance assessment and tropism assignment, only one assay each was used. Amplicons were visualized using a Lonza FlashGel system (Lonza Group, Basel, Switzerland) and – in case of appropriate bands - sent for nucleic acid extraction of the amplicons and subsequent Sanger sequencing to the commercial company Microsynth Seqlab GmbH (Göttingen, Germany). The inner primers of the nested PCRs were applied as sequencing primers as well. Forward and reverse strand sequences were manually aligned and quality-controlled using the software Finch TV (Geospiza Inc., 2004–2012, Seattle, Washington, USA). As sequencing was solely diagnostically performed and not associated with sample-associated characteristics, no sequence files were deposited at international databases. Instead, aligned sequence raw reads are provided as supplementary material 1 together with this article. Identification of resistance-associated mutations and assignment of HIV-1 subtypes based on the obtained sequences were conducted using the online tools “Geno2Pheno” [96], “HIV-Grade” [97] and “Stanford Database” [98]. While every mutation associated with likely reduced anti-retroviral drug susceptibility was counted, consensus results were derived from the different database assessments regarding subtype- and tropism-assignment.
Target genes, assay priorities and oligonucleotides used for the applied nested PCR assays for Sanger sequence-based resistance, subtype and tropism assessment of HIV-1. Hyphens in the oligonucleotide sequences have been inserted to increase the readability, not to delineate codon triplets. Inner primers were also used as sequencing primers
PCR mix name | HIV RT A/B MIX |
Target | reverse transcriptase |
Assay priority | first |
PCR order | first PCR (outer primers), followed by HIV RT E/F MIX |
Forward primer HIV RT-A (MJ3) | 5′-AGT-AGG-ACC-TAC-ACC-TGT-CA-3′ |
Reverse primer HIV RT-B (MJ4) | 5′-CTG-TTA-GTG-CTT-TGG-TTC-CTC-T-3′ |
PCR mix name | HIV RT E/F MIX |
Target | reverse transcriptase |
Assay priority | first |
PCR order | nested PCR (inner primers), subsequent to HIV RT A/B MIX |
Forward primer HIV RT-E (A(35)) | 5′-TTG-GTT-GCA-CTT-TAA-ATT-TTC-CCA-TTA-GTC-CTA-TT-3′ |
Reverse primer HIV RT-F (NE1(35)) | 5′-CCT-ACT-AAC-TTC-TGT-ATG-TCA-TTG-ACA-GTC-CAG-CT-3′ |
PCR mix name | HIV RT C/I MIX |
Target | reverse transcriptase |
Assay priority | second |
PCR order | first PCR (outer primers), followed by HIV RT G/J MIX |
Forward primer HIV RT-C (RT18) | 5′-GGA-AAC-CAA-AAA-TGA-TAG-GGG-GAA-TTG-GAG-G-3′ |
Reverse primer HIV RT-I (JPH4M) | 5′-TGA-ATG-ATT-CCT-AAT-GCA-TAY-TGT-GAG-TCT-GT-3′ |
PCR mix name | HIV RT G/J MIX |
Target | reverse transcriptase |
Assay priority | second |
PCR order | nested PCR (inner primers), subsequent to HIV RT C/I MIX |
Forward primer HIV RT-G (RT1) | 5′-CCA-AAA-GTT-AAA-CAA-TGG-CCA-TTG-ACA-GA-3′ |
Reverse primer HIV RT-J (PL1M) | 5′-CYT-GYT-TCT-GTA-TTT-CTG-CTA-YTA-AGT-CTT-TTG-3′ |
PCR mix name | HIV Prot A/B MIX |
Target | protease |
Assay priority | not applicable (only one assay used) |
PCR order | first PCR (outer primers), followed by HIV Prot E/F MIX |
Forward primer HIV Prot-A (5'PROT1) | 5′-TAA-TTT-TTT-AGG-GAA-GAT-CTG-GCC-TTC-C-3′ |
Reverse primer HIV Prot-B (3′PROT1) | 5′-GCA-AAT-ACT-GGA-GTA-TTG-TAT-GGA-TTT-TCA-GG-3′ |
PCR mix name | HIV Prot E/F MIX |
Target | protease |
Assay priority | not applicable (only one assay used) |
PCR order | nested PCR (inner primers), subsequent to HIV Prot A/B MIX |
Forward primer HIV Prot-E (5′PROT2) | 5′-TCA-GAG-CAG-ACC-AGA-GCC-AAC-AGC-CCA-A-3′ |
Reverse primer HIV Prot-F (3′PROT2) | 5′-AAT-GCT-TTT-ATT-TTT-TCT-TCT-GTC-AAT-GGC-3′ |
PCR mix name | HIV INT A/B MIX |
Target | integrase |
Assay priority | first |
PCR order | first PCR (outer primers), followed by HIV INT C/D MIX |
Forward primer HIV Int-A (IN12) | 5′-GCA-GGA-TTC-GGG-ATT-AGA-AG-3′ |
Reverse primer HIV Int-B (IN13) | 5′-CTT-TCT-CCT-GTA-TGC-AGA-CC-3′ |
PCR mix name | HIV INT C/D MIX |
Target | integrase |
Assay priority | first |
PCR order | nested PCR (inner primers), subsequent to HIV INT A/B MIX |
Forward primer HIV Int-C (IN1) | 5′-AAG-GTC-TAT-CTG-GCA-TGG-GTA-3′ |
Reverse primer HIV Int-D (BH4) | 5′-TCC-CCT-AGT-GGG-ATG-TGT-ACT-TC-3′ |
PCR mix name | HIV INT I/J MIX |
Target | integrase |
Assay priority | second |
PCR order | first PCR (outer primers), followed by HIV INT K/L MIX |
Forward primer HIV Int-I (INPS1) | 5′-TAG-TAG-CCA-GCT-GTG-ATA-AAT-GTC-3′ |
Reverse primer HIV Int-J (INPR8) | 5′-TTC-CAT-GTT-CTA-ATC-CTC-ATC-CTG-3′ |
PCR mix name | HIV INT K/L MIX |
Target | integrase |
Assay priority | second |
PCR order | nested PCR (inner primers), subsequent to HIV INT I/J MIX |
Forward primer HIV Int-K (INPS3) | 5′-GAA-GCC-ATG-CAT-GGA-CAA-G-3′ |
Reverse primer HIV Int-L (INPR9) | 5′-ATC-CTC-ATC-CTG-TCT-ACT-TGC-C-3′ |
PCR mix name | HIV INT M/N MIX |
Target | integrase |
Assay priority | third |
PCR order | first PCR (outer primers), followed by HIV INT O/P MIX |
Forward primer HIV Int-M (HP4149) | 5′-CAT-GGG-TAC-CAG-CAC-ACA-AAG-GAA-TT-3′ |
Reverse primer HIV Int-N (IN-PCRBD) | 5′-GCT-YTC-TTT-GAA-AYA-TAC-ATA-TGR-T-3′ |
PCR mix name | HIV INT O/P MIX |
Target | integrase |
Assay priority | third |
PCR order | nested PCR (inner primers), subsequent to HIV INT M/N MIX |
Forward primer HIV Int-O (IN-PCRA) | 5′-GGA-GGA-AAT-GAA-CAA-GTA-GAT-3′ |
Reverse primer HIV Int-P (IN-SEQ2) | 5′-TAC-TGC-TGT-CTT-AAG-RTG-TTC-AG-3′ |
PCR mix name | HIV Trop A/B MIX |
Target | tropism-related envelope sequence |
Assay priority | not applicable (only one assay used) |
PCR order | first PCR (outer primers), followed by HIV Trop C/D MIX |
Forward primer HIV Trop-A (ENV_31) | 5′-CAG-TAC-AAT-GTA-CAC-ATG-G-3′ |
Reverse primer HIV Trop-B (ENV_8) | 5′-ATG-GGA-GGG-GCA-TAC-ATT-G-3′ |
PCR mix name | HIV Trop C/D MIX |
Target | tropism-related envelope sequence |
Assay priority | not applicable (only one assay used) |
PCR order | nested PCR (inner primers), subsequent to HIV Trop A/B MIX |
Forward primer HIV Trop-C (ENV_7) | 5′-AAT-GGC-AGT-CTA-GCA-GAA-G-3′ |
Reverse primer HIV Trop-D (ED_33) | 5′-TTA-CAG-TAG-AAA-AAT-TCC-CCT-C-3′ |
Reaction mixes and run conditions for the nested PCR assays generating the amplicons for the HIV-1 sequence analyses
first PCR (outer primers) | nested PCR (inner primers) | |
Reaction chemistry | ||
Master Mix | QuantiNova Pathogens (Qiagen) | HotStarTaq (Qiagen) |
Reaction volume (µL) | 25.0 | 50.0 |
Forward primer concentration (pmol µL−1) | 20.0 | 20.0 |
Reverse primer concentration (pmol µL−1) | 20.0 | 20.0 |
Final Mg2+ concentration (mM) | 1.5 | 3.0 |
Internal control reaction mix | QuantiNova IC Probe Assay | not applicable |
Internal control | QN IC RNA | not applicable |
Eluate volume (µL) | 5.0 | 10.0 (product of the first PCR) |
Run conditions | ||
Reverse transcription | 50°C, 30 min. | not applicable |
Initial denaturation | 94°C, 2 min. | 94°C, 2 min. |
Cycle numbers | 40 | 40 |
Denaturation | 94°C, 30 s. | 94°C, 30 s. |
Annealing | 55°C, 30 s. | 55°C, 30 s. |
Amplification | 68°C, 60 s. | 72°C, 90 s. |
Hold | 8°C, unlimited | 4°C, unlimited |
Min. = minute, sec. = second.
Biostatistics
Most results were just descriptively assessed and presented. The Candotti HIV-1 PCR and the Yamazaki HIV-1 PCR, however, were additionally investigated for their diagnostic accuracy with the Ghanaian samples applying latent class analysis (LCA) for a test comparison without a gold standard [99] and diagnostic accuracy-adjusted prevalence assignment. Calculation and interpretation of the agreement of positive results obtained with the Candotti HIV-1 PCR and the Yamazaki HIV-1 PCR according to Fleiss' kappa were conducted as detailed elsewhere [100]. In line with the postulates by Landis & Koch [100], kappa indicates the agreement between the qualitative real-time PCR results with the strata poor (below 0.00), slight (0.00–0.20), fair (0.21–0.40), moderate (0.41–0.60), substantial (0.61–0.80), and almost perfect (0.81–1.00). Student's T-test was used to compare Ct values of concordant and discordant results of the Candotti HIV-1 PCR and the Yamazaki HIV-1 PCR. For both statistical approaches, the software Stata/IC 15.1 for Mac 64-bit Intel (College Station, TX, USA) was applied.
Ethics
Sample collection and analysis were conducted under protocols approved by the Committee on Human Research of the Kwame Nkrumah University of Science and Technology in Kumasi, Ghana: CHRPE/AP/12/11 (on 8th September 2012) and by the ethics committee of the Medical Council in Hamburg, Germany: PV3771. Study participants or next-to-kin gave a written informed consent prior to enrolment. The study was conducted in accordance with the Declaration of Helsinki and all its amendments.
Results
Latent class analysis based diagnostic accuracy assessment of the Candotti HIV-1 PCR and the Yamazaki HIV-1 PCR with the assessed Ghanaian samples
Although almost perfect correlation between the Candotti HIV-1 PCR and the Yamazaki HIV-1 PCR as indicated by Fleiss' >0.8 could be shown, minor proportions of discordant real-time PCR screening results for HIV-1 yet resulted in imperfect diagnostic accuracy. The resulting diagnostic accuracy-corrected estimation of the prevalence of replicative HIV-1 infection was 0.5. Details are provided in Tables 5 and 6. As indicated in Table 7, significantly higher Ct values for discordantly positive samples could only be shown for the Yamazaki HIV-1 PCR but not for the Candotti HIV-1 PCR.
Agreement kappa between the compared real-time screening PCR assays Candotti HIV-1 PCR and Yamazaki HIV-1 PCR as well as sensitivity, specificity and accuracy-adjusted prevalence as calculated with latent class analysis (LCA) based on the assessment of 1,080 samples from both subpopulations of the study after exclusion of 4 samples showing PCR inhibition
Assay | n | Positives (%) | Sensitivity (0.95 CI) | Specificity (0.95 CI) | Kappa (0.95 CI) |
Candotti HIV-1 PCR | 1,080 | 507 (46.94) | 0.939 (n.e.) | 0.998 (0, 1) | 0.828 (0.795, 0.862) |
Yamazaki HIV-1 PCR | 1,080 | 572 (52.96) | 0.974 (0.09, 0.999) | 0.914(0.878, 0.940) | |
Prevalence | 0.4997 |
n = number included after exclusion of inhibited samples. n.e. = not estimable.
Cross-table detailing mismatches between the real-time screening PCRs Candotti HIV-1 PCR and Yamazaki HIV-1 PCR. Green = matching results. Red = mismatching results. Black = not filled in to avoid repetition
![]() |
Comparison of recorded Ct values of the real-time screening PCR assays Candotti HIV-1 PCR and Yamazaki HIV-1 PCR for samples showing concordant and discordant test results
n | Mean (SD) | Median (Min., Max.) | Significance P (T-test) | |
Candotti HIV-1 PCR – concordantly positive results | 493 | 26.41 (2.37) | 26 (19, 34) | Reference |
Candotti HIV-1 PCR – discordantly positive results | 14 | 27.50 (2.95) | 27 (24, 33) | 0.0941 (not significant) |
Yamazaki HIV-1 PCR – concordantly positive results | 493 | 25.82 (2.60) | 26 (19, 35) | Reference |
Yamazaki HIV-1 PCR – discordantly positive results | 79 | 29.95 (2.90) | 30 (21, 36) | <0.0001 (significant) |
Min. = minimum. Max. = maximum.
Co-infection assessment within the Ghanaian populations
While a total number of 586 assessed individuals showed replicative HIV-1 virus infection in at least one of the applied HIV-1 specific real-time PCR assays, numbers and proportions of recorded replicative infections were 0/1080 (0%) for HIV-2, 37/1080 (3.4%) for HBV (mean Ct value ± SD: 14.2 ± 4.8) and 0/1083 (0%) for HCV. Focusing on their distribution on the assessed subpopulations of known HIV-positive patients and control individuals, the proportions of replicative HBV co-infections in the known HIV-positive cohort and in the cohort of control individuals were nearly identical within the 3%–4% range. While replicative HIV-1 infection was recorded within 59.8% of the known HIV-positive cohort, a minority of 2.9% individuals within the control group without known HIV-infection showed replication of HIV-1 as well (Tables 8–10).
Detection of replicative infections with HIV-1 (as defined by a positive result in at least one out of two HIV-1-specific real-time real-time PCRs), HIV-2, HBV and HCV over the assessed study groups
Population of known HIV-positive individuals n/n (%) | Control population n/n (%) | |
HIV-1 | 583/975 (59.8%) | 3/105 (2.9%) |
HIV-2 | 0/0 (0%) | 0/0 (0%) |
HBV | 33/975 (3.4%) | 4/105 (3.8%) |
HCV | 0/975 (0.0%) | 0/105 (0.0%) |
Numbers and proportions of detected replicative co-infections within the subpopulation of known HIV-patients (control individuals excluded)
Detected replication | Numbers n/n and percentages (%) |
HIV-1 & HIV-2 & HBV & HCV | 0/975 (0.0%) |
HIV-1 & HIV-2 & HBV | 0/975 (0.0%) |
HIV-1 & HIV-2 & HCV | 0/975 (0.0%) |
HIV-1 & HBV & HCV | 0/975 (0.0%) |
HIV-2 & HBV & HCV | 0/975 (0.0%) |
HIV-1 & HIV-2 | 0/975 (0.0%) |
HIV-1 & HBV | 29/975 (3.0%) |
HIV-1 & HCV | 0/975 (0.0%) |
HIV-2 & HBV | 0/975 (0.0%) |
HIV-2 & HCV | 0/975 (0.0%) |
HBV & HCV | 0/975 (0.0%) |
HIV-1 | 583/975 (59.8%) |
HIV-2 | 0/975 (0.0%) |
HBV | 33/975 (3.4%) |
HCV | 0/975 (0.0%) |
Samples without detectable replication | 388/975 (39.8%) |
Numbers and proportions of detected replicative co-infections over both subpopulations
Detected replication | Numbers n/n and percentages (%) |
HIV-1 & HIV-2 & HBV & HCV | 0/1080 (0.0%) |
HIV-1 & HIV-2 & HBV | 0/1080 (0.0%) |
HIV-1 & HIV-2 & HCV | 0/1080 (0.0%) |
HIV-1 & HBV & HCV | 0/1080 (0.0%) |
HIV-2 & HBV & HCV | 0/1080 (0.0%) |
HIV-1 & HIV-2 | 0/1080 (0.0%) |
HIV-1 & HBV | 29/1080 (2.7%) |
HIV-1 & HCV | 0/1080 (0.0%) |
HIV-2 & HBV | 0/1080 (0.0%) |
HIV-2 & HCV | 0/1080 (0.0%) |
HBV & HCV | 0/1080 (0.0%) |
HIV-1 | 586/1080 (54.3%) |
HIV-2 | 0/1080 (0.0%) |
HBV | 37/1080 (3.4%) |
HCV | 0/1080 (0.0%) |
Samples without detectable replication | 486/1080 (45.0%) |
HIV-1 sub-type assessment and tropism assessment
Sequence-bases sub-type and tropism assignment of the 108 HIV-1 PCR positive samples succeeded in 108/108 (100.0%) and 89/108 (82.4%) cases, respectively. In detail, CRF02_AG, G and A3 were quantitatively dominating, while other subtypes were only inconsistently recorded. The majority of sequenced viruses showed CCR5-tropism, while CXCR4-tropism was recorded in case of a minority of 3.4% (Tables 11 and 12).
Numbers and proportions of sub-type assignments
Detected HIV-1 subtype | Numbers n/n and percentages (%) |
CRF02_AG | 92/108 (85.1%) |
G | 6/108 (5.6%) |
A3 | 4/108 (3.7%) |
D | 1/108 (0.9%) |
A/B | 1/108 (0.9%) |
A/A3 | 1/108 (0.9%) |
AE/K | 1/108 (0.9%) |
CRF06_cpx | 1/108 (0.9%) |
CRF09_cpx | 1/108 (0.9%) |
Numbers and proportions of tropism assignments
Tropism | Numbers n/n and percentages (%) |
CCR5 | 86/89 (96.6%) |
CXCR4 | 3/89 (3.4%) |
HIV-1 resistance assessment
Sequence-based resistance assessment succeeded for NRTI, NNRTI, PI and INSTI in in 89/108 (82.4%), 89/108 (82.4%), 97/108 (89.4%), and 98/108 (89.8%) cases. Recorded numbers of samples showing mutations associated with reduced susceptibility towards antiretroviral drugs as well as the distribution of detected mutations are shown in detail in Table 13. In short, mutations associated with reduced susceptibility towards NRTI, NNRTI, PI and INSTI were seen in 71.9%, 95.5%, 95.9% and 22.4% of the interpretable sequences, respectively. Details on the most frequently detection mutations with confirmed or likely effects on drug susceptibility are visualized in Table 13.
Numbers and proportions of samples with recorded mutations in the HIV-1 genome associated with reduced susceptibility towards antiretroviral drugs as well as the distribution of such mutations
Number and proportion of samples with mutations affecting antiretroviral susceptibility (n/n, (%)) | Recorded mutations and their distributions (n/n, (%)) | |
NRTIs | 64/89 (71.9%) | V118I (2/89 (2.2%)), T69N (1/89 ((1.1%)), M184V (2/89 (2.2%)), T215S (1/89 (1.1%)), T69S (1/89 (1.1%)), Y115*Y (1/89 (1.1%)) |
NNRTIs | 85/89 (95.5%) | V90I (5/89 (5.6%)), E138A (6/89 (6.7%)), K238R (2/89 (2.2%)), V179I (4/89 (4.5%)), V108I (1/89 (1.1%)), V179E (2/89 (2.2%)), K101Q (1/89 (1.1%)), K103N (2/89 (2.2%)), P225H (1/89 1.1%)), V106I (1/89 (1.1%)), K101E (1/89 (1.1%)), G190A (1/89 (1.1%)), Y181F/S (2/89 (2.2%)) |
PIs | 93/97 (95.9%) | H69L (89/97 (91.8%)), K20I (84/97 (86.6%)), L89M (85/97 (87.6%)), E35N (5/97 (5.2%)), L89I (5/97 (5.2%)), T74A (1/97 (1.0%)), N88K (1/97 (1.0%)), L10I (6/97 (6.2%)), E35K (1/97 (1.0%)), V11I (3/97 (3.1%)), E35Q (1/97 (1.0%)), H69R (2/97 (2.1%)), K20V (3/97 (3.1%)), L10I/V (1/97 (1.0%)), L10I/M (1/97 (1.0%)), L10V (9/97 (9.3%)), T74S (1/97 (1.0%)), K20R (5/97 (5.1%)), H69Q (3/97 (3.1%)), L33F (1/97 (1.0%)), V82I (7/97 (7.2%)), E35G (2/97 (2.1%)), T125V (1/97 (1.0%)), K43R (2/97 (2.1%)), |
INSTIs | 22/98 (22.4%) | M50T (7/97 (7.2%)), T125A (82/97 (84.5%)), M50I (22/97 (22.7%)), S119P (4/97 (4.1%)), S153F (5/97 (5.2%)), S230R (2/97 (2.1%)), M50R (1/97 (1%)), G163A (4/97 (4.1%)), L74V (1/97 (1.0%)), E92D (1/97 (1.0%)), G163E (7/97 (7.2%)), E157Q (9/97 (9.3%)), T125P (3/97 (3.1%)), S147N (3/97 (3.1%)), T97A (5/97 (5.2%)), G163V (2/97 (2.1%)), G118S (1/97 (1.0%)), F121L (1/97 (1.0%)), E157G (1/97 (1.0%)), G163Q (1/97 (1.0%)), S119T (2/97 (2.1%)), V165I (4/97 (4.1%)), S119A (1/97 (1.0%)), L74I (8/97 (8.2%)), E157H (1/97 (1.0%)), S230N (2/97 (2.1%)), V75E (1/97 (1.0%)), E92K (2/97 (2.1%)), G140E (1/97 (1.0%)), S147I (1/97 (1.0%)), L74M (1/97 (1.0%)), S153A (1/97 (1.0%)), G163T (1/97 (1.0%)), S119R (2/97 (2.1%)), S119G (1/97 (1.0%)), M50V (2/97 (2.1%)) |
*indicates a silent mutation without expression on amino acid level but nevertheless with an assumed effect on drug susceptibility. NRTI = nucleoside reverse transcriptase inhibitor. NNRTI = non-nucleoside reverse transcriptase inhibitor. PI = protease inhibitor. INSTI = integrase inhibitor.
Discussion
The study was conducted to assess replicative viral co-infections in a cohort of HIV-positive Ghanaian patients as well as the abundance of mutations in the HIV-1 genomes associated with reduced susceptibility towards anti-retroviral drugs as well as with viral tropism and led to a number of results.
First of all, replicative HIV-2 infections and HCV infections were not recorded in the assessed cohort with the applied in-house assays, which is in contrast to previous reports on people-living-with-HIV in Ghana [67, 88] and elsewhere [8, 17]. Although the assays' detection thresholds, especially when applied with historic, deep-frozen stored samples, have to be considered when interpreting this result, at least substantial replication can be considered as unlikely. Further, in those previous assessments, the focus had not been specifically on replicative infections. For replicative HBV-infections, comparable infection rates ranging between 3% and 4% were recorded for both HIV-positive individuals and control individuals. This indirectly speaks in favor of a higher rate of such infections in HIV-positive individuals, because commonly applied NRTIs like lamivudine and tenofovir can suppress the replication of HBV as well [101], although lamivudine resistance is reported to be an issue of relevance in HBV in Ghana [75, 76]. Previously reported HBV surface antigen prevalence of 8.5% in Ghanaian individuals [73] further supports the hypothesis of partial suppression of HBV nucleic acid replication due to antiretroviral therapy, resulting in detectable surface antigen without co-circulating virus sequences. As multiple factors other than treatment also interfere with HBV and HCV replication in HIV infected individuals as stated above [1–22], the assessment had been conducted in an exploratory way and without a predefined hypothesis.
Regarding HIV-replication within the Ghanaian HIV-cohort, a replication rate round about 60% is not surprising, keeping in mind the abovementioned 1 : 1 ratio of treatment-naïve and treated HIV infections. Another reason for high replication rates, especially among PLWH on antiretroviral combination therapy, is failure of virologic suppression resulting from suboptimal adherence to treatment in Ghana [53, 54]. Interestingly, however, a small proportion of replicative HIV infection of 2.9% and thus a higher one compared to the Ghanaian standard population [37] was observed in the control population as well. Notably, the applied HIV-specific real-time PCRs were not optimized for sensitivity. Consequently, substantial replication is associated with positive PCR signals in the assessment provided here.
Second, as a side finding, almost perfect correlation between two applied HIV-1 real-time PCR assays was demonstrated. Of note, however, significance for Ct value differences between concordant and discordant real-time PCR results could be demonstrated for one out of two assays only. The result once more confirms the preference of dual-target PCR-assays to ensure improved sensitivity [102–104].
Third and focusing on the sequenced HIV-1-positive samples, the observed predominance of the mosaic CRF02_AG and the genotypes A and G is well in line with previous reports for Ghana [80–82, 87, 89]. In contrast, the recorded one-digit CXCR4 tropism rate is smaller than expected for this region [79]. In line with considerable HIV-1 resistance rates reported for Ghana, mutations associated with reduced susceptibility towards antiretroviral drugs were observed in the vast majority of assessed samples. Some of the recorded mutations like, e.g., T69N and M184V coding for reduced NRTI susceptibility, V90I, K103N, E138A, and V179E coding for reduced NNRTI susceptibility as well as L10I, L10V, V11I and E35G coding for reduced PI susceptibility had been reported to be frequently observed in Ghana before [60, 79–87]. As stated above [36], the observed mutation selection was most likely influenced by the choice of applied anti-retroviral drugs during the assessment period. As indicated in HIV sequence databases [33–35], resistance distribution can vary not only region-dependent but also period-dependent. In line with the common use of NRTIs, NNRTIs and PIs in Ghana during the assessment period as described for the study population in the methods section, most recorded mutations affected these substance classes.
The study has a number of limitations. First, the assessment of a historic sample collection might have been associated with reduced sensitivity due to RNA degradation in spite of appropriate deep-frozen storage. Second, the historic analysis is not necessarily representative for the present situation in Ghana. Third, the retrospective design of the study did not allow for sample size calculations in the course of this epidemiological assessment. Fourth, in-depth sequence analysis based on highly standardized NGS approaches [24–28] was unfeasible due to funding restrictions. Instead, traditional Sanger sequencing and subsequent comparison of the obtained sequences with internet-based reference databases [96–98] were applied.
Conclusions
In spite of the above-mentioned limitations, the study provides another piece in the puzzle of HIV epidemiology in Ghana, confirming high rates of mutations mediating reduced susceptibility towards antiretroviral drugs in HIV-1 viruses in Ghanaian patients. Further, it could show that replicative HBV co-infection rates in HIV-positive individuals were quite similar compared to a control group.
Conflicts of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Author contributions
Conceptualization, H.F., K.A.E., H.R., M.L.; methodology, H.F., M.L., A.H., L.G., F.W.; software, A.H., L.G.; validation, L.G., H.F.; formal analysis, L.G., A.H., H.F.; investigation, L.G., A.H., T.F., F.S.S., R.O.P., A.D., S.O.A., R.B., F.W., H.F., K.A.E.; resources, K.A.E., H.F.; data curation, L.G., A.H., H.F.; writing—original draft preparation, L.G., H.F.; writing—review and editing, L.G., A.H., H.R., M.L., T.F., F.S.S., R.O.P., A.D., S.O.A., R.B., F.W., H.F., K.A.E.; visualization, L.G., H.F.; supervision, H.F., H.R., K.A.E.; project administration, H.F., K.A.E.; funding acquisition, K.A.E. All authors have read and agreed to the published version of the manuscript.
Funding
The implementation of the study was supported by the ESTHER Alliance for Global Health Partnerships and the German Federal Ministry of Education and Research (Project No. 01KA1102).
Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1556/1886.2024.00103.
Abbreviations
AIDS | acquired immunodeficiency syndrome |
ANRS | French National Agency for AIDS Research |
ART | antiretroviral therapy |
CD | cluster of differentiation |
FSW | female sex worker |
HBV | hepatitis B virus |
HCV | hepatitis C virus |
HDV | hepatitis D virus |
HIV | human immunodeficiency virus |
IRQ | interquartile range |
LCA | latent class analysis |
LTR | long terminal repeat |
μL: | microliter |
MSM | men-having-sex-with-men |
NGS | next-generation-sequencing |
NNRTI | non-nucleoside reverse transcriptase inhibitor |
NRTI | nucleoside reverse transcriptase inhibitor |
PCR | polymerase chain reaction |
PI | protease inhibitor |
PLWH | people-living-with-HIV |
RAMS | resistance associated mutations |
SD | standard deviation |
USA | United States of America |
Acknowledgements
Annett Michel and Simone Priesnitz are gratefully acknowledged for excellent technical assistance.
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