Our study on viral dynamics and drug resistance testing among ART-naive perinatally-infected children aged between 2 and 16 years found that a substantial proportion of older children with CD4 T cell count in the ‘non-immunosuppressed’ category had high viremia. As expected subtype C is the most prevalent HIV-1 subtype in this study population. We also identified a low level of transmitted drug resistance in this population.
A recent study showed that a proportion of HIV-infected adults with horizontally-acquired subtype C infection in southern Africa maintained high viral loads for a prolonged period of time . A South African cohort of HIV-1-infected infants also demonstrated high viral load where HIV-1 subtype C is predominant . A comparative study between Malawi and US/Swiss study participants also showed a significant higher viral load in Malawians, suggesting the possibility that high viremia may occur more frequently in subtype C rather than subtype B infection . In our cohort, the duration of infection as measured by the age of these children, did not directly correlate with the degree of viremia, thus precluding viral load measurement as a prognostic marker of disease length; moreover, there was a substantial proportion of adolescents who maintained high CD4 T-cell count but had elevated viremia as well. Our findings imply that even in vertical transmission, a proportion of HIV-1 subtype C-infected children and adolescents have high viremia irrespective of their stable clinical and immunological status. To minimize horizontal transmission among youth, targeted interventions with treatment as prevention among adolescents with high viremia may be of public health benefit which could also be a cost-effective strategy to attain maximum population-level reductions in HIV-1 transmission .
The transmitted drug resistance prevalence was derived by using the SDRM 2009 list . The SDRM 2009 list was compiled keeping in mind four main concepts: (i) included mutations should be recognized as causing or contributing to drug resistance - by being present on ≥3 of five existing expert lists of drug resistance mutations, namely, Stanford university HIVdb drug resistance interpretation algorithm (http://hivdb.stanford.edu/). IAS-USA Mutations Associated With Drug Resistance (March/April 2008), ANRS drug resistance interpretation algorithm, Los Alamos National Laboratories HIV Sequence database (2007), or Rega Institute Drug Resistance Interpretation Algorithm (7.1.1) (ii) the mutations should not be polymorphisms or occur at highly polymorphic positions, (iii) the mutations should be applicable to the 8 most common HIV-1 subtypes globally and (iv) the list should be parsimonious, excluding mutations that are unlikely to result from drug pressure. These criteria have shaped the SDRM 2009 list to be especially relevant in our setting, and hence this list was used for our current interpretation. The TDRM level in our study population was very low which was consistent with our previous findings where the level of TDRMS and polymorphisms among ART-naïve adults did not exceed 10% . Other paediatric studies from India have revealed similar low TDRM prevalence; among a south Indian cohort of 48 perinatally infected children of mean age 5.7 years, none had major drug resistance mutations . In another study from north India where 25 ART-naïve children with mean age 6 years were studied, K103N was the only drug resistance mutation that was observed . Studies on ART-naïve adults from different parts of India with sample sizes ranging from 34 to 107 patients, have revealed low TDRM prevalence (<5%) [11, 12, 14–18].
Presence of K103N and K101E TDRM in our cohort sequences may be due to wide usage of nevirapine in this setting . Our data on prevalence of TDRM among children was significantly lower than other settings. Studies from Brazil reported 26.9% of TDRM in therapy-naïve children , while a report from Central African Republic identified 13.9% . A meta-analysis showed that approximately half of the children with PMTCT exposure (single-dose nevirapine) harboured TDRM . A recent study from Spain on PMTCT-exposed children identified 13% TDR , while another study from Western Cape Province of South Africa reported TDRM <5% among children who were exposed to PMTCT . A recent study also showed that the effect of viral fitness on HIV RNA level could be one of the determining factors for selective viral transmission; maternal presence of mutations such as K103N which promote viral fitness may be easily transmitted to infants .
Minor differences between the two lists used for TDRM interpretation can lead to contradictory prevalence results of drug resistance. In our study, we excluded minor NRTI mutations such as T215S and L74I which were included in the SDRM 2009 list. The SDRM 2009 WHO group recommends that the SDRM list should be “as parsimonious as possible without sacrificing sensitivity,” this can be accomplished by excluding “exceedingly rare drug-resistance mutations defined as those mutations present at a frequency below 0.5% among treated individuals in the subtype having the highest prevalence of that mutation” . Our analysis of previous RT sequences obtained from treatment-experienced patients from Indian subtype C patients [n = 606; downloaded from the Los Alamos database (n = 102); literature survey (n = 446) and unpublished from lab (n = 58)] revealed that T215S was not present in any of the sequences (data not shown). Although in vitro analysis showed that T215S represents revertants of T215Y , phenotypic characterisation did not show resistance to any nucleoside analogues including zidovudine . The L74I mutation was present in 0.3% (2/606) of sequences obtained from treatment-experienced patients infected with subtype C viruses. In addition, the analysis of global subtype C sequences in HIVseq program available in Stanford University HIV drug resistance database (http://hivdb.stanford.edu/; accessed 07 October 2012) also revealed absence of both mutations in 232 HIV-1 subtype C sequences from NRTI-treated patients. The low prevalence of T215S and L74I at a frequency of <0.5% in treatment-experienced patients harbouring subtype C HIV-1 provided the basis for our rationale for excluding these mutations from our analysis. F227C is another example of a mutation included in the IAS-USA panel that is not likely to be significant as a transmitted mutation, as F227C confers “minor” resistance to rilpivirine, a drug that is as yet unavailable in India. Other studies have observed differences in prevalence of TDRM within the same cohort when differing tools such as SDRM 2009 and IAS-USA 2009 are used . Current SDRM 2009 guidelines propose that such polymorphic drug resistance mutations which occur commonly in the absence of drug selective pressure, and are present in <0.5% of the treated population, could lead to falsely elevated estimates of TDRM, and hence, must not be included for surveillance of transmitted HIVDR .
Our study limitations include the cross-sectional design which restricts our ability to comment on kinetics of viral dynamics and evolution. Further, we have not been able to include samples from children below two years of age for this analysis as most of the children in our settings were diagnosed in their early and middle childhood. There may be an inherent survival bias since only these older children were included in the study. Thus, having only chronically infected children may actually underestimate the prevalence of transmitted drug resistance as the wild type virus with increased fitness may predominate and minor viral populations with drug resistant mutations may be too low to detect using population sequencing. However, our study is strengthened by the inclusion of a high proportion of children with age ≥10 years, which allowed us to study viral load and its associations in adolescents. Finally, the population-based genotyping method can only detect mutations that are present in 30% or more of the quasi-species constituting circulating virus population . It is possible that mutations carried by minor viral populations may be missed due to the limited sensitivity of population-based sequencing method.