A Novel Sample Selection Approach to Aid the Identification of Factors That Correlate With the Control of HIV-1 Infection - Makinde, Julia; Nduati, Eunice W.; Freni-Sterrantino, Anna; Streatfield, Claire; Kibirige, Catherine; Dalel, Jama; Black, S. Lucas; Hayes, Peter; Macharia, Gladys; Hare, Jonathan; McGowan, Edward; Abel, Brian; et al. (Frontiers in Immunology, 2021)
Individuals infected with HIV display varying rates of viral control and disease progression, with a small percentage of individuals being able to spontaneously control infection in the absence of treatment. In attempting to define the correlates associated with natural protection against HIV, extreme heterogeneity in the datasets generated from systems methodologies can be further complicated by the inherent variability encountered at the population, individual, cellular and molecular levels. Furthermore, such studies have been limited by the paucity of paucity of well characterized samples and linked epidemiological data, including duration of infection and clinical outcomes. To address this, we selected 10 volunteers who rapidly and persistently controlled HIV, and 10 volunteers each, from two control groups who failed to control (based on set point viral loads) from an acute and early HIV prospective cohort from East and Southern Africa. A propensity score matching approach was applied to control for the influence of five factors (age, risk group, virus subtype, gender, and country) known to influence disease progression on causal observations. Fifty-two plasma proteins were assessed at two timepoints in the first year of infection. We confirmed factors known to influence disease progression such as the B*57 HLA Class I allele, and infecting virus Subtype. We demonstrated associations between circulating levels of MIP-1α and IL-17C, and the ability to control infection. IL-17C has not been described previously within the context of HIV control, making it an interesting target for future studies to understand HIV infection and transmission. An in-depth systems analysis is now underway to fully characterise host, viral and immunological factors contributing to control.