Intrapatient Diversity and Its Correlation with Viral Setpoint in Human Immunodeficiency Virus Type 1 CRF02_A/G-IbNG Infection

Abstract

ABSTRACT The human immunodeficiency virus type 1 (HIV-1) viral setpoint during the disease-free interval has been strongly associated with future risk of disease progression. An awareness of the correlation between viral setpoint and HIV-1 genetic evolution over time is important in the understanding of viral dynamics and infection. We examined genetic diversity in HIV-1 CRF02_A/G-IbNG-infected seroincident women in Dakar, Senegal; determined whether a viral setpoint kinetic pattern existed for CRF02_A/G-IbNG during the disease-free interval; and correlated viral load level and diversity. Samples were drawn during the disease-free interval from consenting CRF02_A/G-IbNG-infected, antiretroviral therapy-naïve female commercial sex workers in Dakar, Senegal. Based on sequential plasma RNA values, low and high viral setpoint groups were established. Intrapatient diversity and divergence over time was determined from earlier and later time point DNA samples from each person. Most individuals followed the viral setpoint paradigm. For each 1|−|log 10 copy/ml of plasma increase in viral load, intrapatient diversity increased by 1.4% ( P = 0.028). A greater diversification rate was observed in the high viral setpoint group than in the low viral setpoint group ( P = 0.01). Greater nucleotide ( P = 0.015) and amino acid ( P = 0.048) divergences and a greater nucleotide divergence rate ( P = 0.03) were found in the high viral setpoint group. There was no difference between the groups in the ratio of the number of nonsynonymous substitutions per nonsynonymous site to the number of synonymous substitutions per synonymous site. The greater intrapatient diversity, divergence, and diversification rates observed in the high viral setpoint group supports the notion that diversity is driven by cycles of viral replication resulting in accumulated mutations. Recognizing diversity potential based on viral load levels in individuals may inform the design of vaccines and therapies.