title: A comparison of interpretation by three different HIV type 1 genotypic drug resistance algorithms using sequences from non-clade B HIV type 1 strains.
abstract: The advent of affordable ART has benefited HIV-infected individuals. Prospective studies have shown that the availability of drug resistance reports for infected individuals has allowed more effective regimens to be prescribed as compared to a control group whose physicians had no access to drug resistance reports. There is a paucity of information on the performance of genotypic algorithms on non-clade B HIV-1 strains, especially clade C. In this study the results obtained on submission of HIV-1 RT and PR sequences of non-clade B strains to the Stanford University HIV drug resistance database (SHDB) were compared to the results obtained from Geno2Pheno (G2P) and DR_Seqan (DS). For the study, we took samples from 93 treatment-naive individuals and 21 samples from 19 infected individuals showing detectable viral load while on ART. There were discrepancies in the clade identification results obtained from the SHDB and G2P databases. This feature was not available in DS. The mean observed concordance between SHDB and G2P was 85.6% while between SHDB and DC it was 37%. When the level of concordance was determined based on exposure to ART, the G2P was found to have a better level of concordance (76.8%) to SHDB as compared to SHDB versus DS (36%). We do not have phenotypic data for the strains included in this study and hence we are not in a position to assign a particular algorithm as being superior. These results also show a possible need for a subtype-specific algorithm for interpretation of HIV-1 genotypic drug resistance.
authors.affiliation: Department of Clinical Virology, Christian Medical College, Vellore, India. rajeshkannangai@hotmail.com
authors.forename: Abraham Joseph
authors.initials: AJ
authors.lastname: Kandathil
authors.forename: Rajesh
authors.initials: R
authors.lastname: Kannangai
authors.forename: Oriapadickal Cherian
authors.initials: OC
authors.lastname: Abraham
authors.forename: Susanne Alexander
authors.initials: SA
authors.lastname: Pulimood
authors.forename: Mark A
authors.initials: MA
authors.lastname: Jensen
authors.forename: Gopalan
authors.initials: G
authors.lastname: Sridharan
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D024882:Drug Resistance, Viral; D005838:Genotype; D015658:HIV Infections / Q000821:virology*; D016333:HIV Protease / Q000235:genetics; D054303:HIV Reverse Transcriptase / Q000235:genetics; D015497:HIV-1 / Q000187:drug effects* / Q000235:genetics*; D006801:Humans; D008826:Microbial Sensitivity Tests / Q000379:methods*; D008969:Molecular Sequence Data; D017422:Sequence Analysis, DNA
chemical_list: C514824:reverse transcriptase, Human immunodeficiency virus 1; D054303:HIV Reverse Transcriptase; D016333:HIV Protease; C514803:p16 protease, Human immunodeficiency virus 1