Assessing transmissibility of HIV-1 drug resistance mutations from treated and from drug-naive individuals.
OBJECTIVE
Surveillance drug resistance mutations (SDRMs) in drug-naive patients are typically used to survey HIV-1-transmitted drug resistance (TDR). We test here how SDRMs in patients failing treatment, the original source of TDR, contribute to assessing TDR, transmissibility and transmission source of SDRMs.


METHODS
This is a retrospective observational study analyzing a Portuguese cohort of HIV-1-infected patients.


METHODS
The prevalence of SDRMs to protease inhibitors, nucleoside reverse transcriptase inhibitors (NRTIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs) in drug-naive and treatment-failing patients was measured for 3554 HIV-1 subtype B patients. Transmission ratio (prevalence in drug-naive/prevalence in treatment-failing patients), average viral load and robust linear regression with outlier detection (prevalence in drug-naive versus in treatment-failing patients) were analyzed and used to interpret transmissibility.


RESULTS
Prevalence of SDRMs in drug-naive and treatment-failing patients were linearly correlated, but some SDRMs were classified as outliers - above (PRO: D30N, N88D/S, L90 M, RT: G190A/S/E) or below (RT: M184I/V) expectations. The normalized regression slope was 0.073 for protease inhibitors, 0.084 for NRTIs and 0.116 for NNRTIs. Differences between SDRMs transmission ratios were not associated with differences in viral loads.


CONCLUSIONS
The significant linear correlation between prevalence of SDRMs in drug-naive and in treatment-failing patients indicates that the prevalence in treatment-failing patients can be useful to predict levels of TDR. The slope is a cohort-dependent estimate of rate of TDR per drug class and outlier detection reveals comparative persistence of SDRMs. Outlier SDRMs with higher transmissibility are more persistent and more likely to have been acquired from drug-naive patients. Those with lower transmissibility have faster reversion dynamics after transmission and are associated with acquisition from treatment-failing patients.
aKU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics biMinds Medical IT cKU Leuven, University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium dPortuguese Society of Rheumatology eLaboratório de Microbiologia Clínica e Biologia Molecular, Serviço de Patologia Clínica, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Rua da Junqueira, Lisbon fCentro de Investigação Interdisciplinar Egas Moniz (CiiEM), Instituto Superior de Ciências da Saúde Sul, Campus Universitário, Quinta da Granja, Monte de Caparica, Caparica, Portugal gDepartment of Biomathematics hDepartment of Human Genetics, David Geffen School of Medicine at UCLA iDepartment of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, California, USA jGlobal Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lsboa, Portugal.
Raf
R
Winand
Kristof
K
Theys
Mónica
M
Eusébio
Jan
J
Aerts
Ricardo J
RJ
Camacho
Perpetua
P
Gomes
Marc A
MA
Suchard
Anne-Mieke
AM
Vandamme
Ana B
AB
Abecasis
D000328:Adult; D018562:Disease Transmission, Infectious; D024882:Drug Resistance, Viral; D062665:Epidemiological Monitoring; D005260:Female; D060005:Genotyping Techniques; D015658:HIV Infections / Q000453:epidemiology / Q000635:transmission* / Q000821:virology*; D015497:HIV-1 / Q000187:drug effects* / Q000235:genetics / Q000302:isolation & purification; D054298:Human Immunodeficiency Virus Proteins / Q000235:genetics; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D020125:Mutation, Missense; D011174:Portugal / Q000453:epidemiology; D015995:Prevalence; D012189:Retrospective Studies
D054298:Human Immunodeficiency Virus Proteins