HIV-1 acquisition consists of behavioral risk parameters moderating exposure as well as biological factors controlling viral entry and replication. However, the genetic aspects of HIV-1 acquisition (outside of the CCR5 Δ32 mutation) have been understudied, in part because no robust genome-wide significant variants were found in early studies10,11,12,13,14,15,16, which led to the premature assumption that acquisition was not substantially moderated by common genetic variants. The GWAS analyzed here, by McLaren and colleagues (2013), did not identify genome-wide significant polymorphisms associated with HIV-1 acquisition (after correcting association signals for frailty bias), but population genetic methods have advanced considerably in recent years, now allowing for powerful inferences about genetic traits using GWAS summary statistics19,22,24,27, even in moderately powered studies. For instance, we calculated heritability estimates of HIV-1 acquisition using cutting edge methods like LDSC and LDAK, which would otherwise be challenging using traditional twin and family methods. The level of SNP h2 observed for acquisition (LDSC: 0.28 ± 0.05; LDAK: 0.42 ± 0.08) was greater or comparable to that of traits considered highly heritable, such as body mass index (LDSC: 0.09 ± 0.01; LDAK: 0.33 ± 0.03), height (LDSC: 0.20 ± 0.02; LDAK: 0.46 ± 0.04), and schizophrenia (LDSC: 0.19 ± 0.01; LDAK: 0.42 ± 0.02)20. Overall, these results highlight the contribution of common variants to HIV-1 acquisition risk, showing this is a heritable trait.

To understand the underlying genetic factors associated with HIV-1 acquisition, we performed genetic correlation analyses in LD Hub, which leverages on data from ~500,000 individuals from the UK Biobank, to investigate how acquisition genetics correlates with heritable traits assessed in this large population sample. We observed genetic correlations between HIV-1 acquisition and heritable phenotypes associated with socio-economic factors, corroborating previous epidemiological work, and further highlighting the need for prevention strategies tailored to individuals who most need it28. We further validated the genetic correlations using the independent SumHer-GC method, supporting these results.

Our results also validate and expand the current understanding of the biological basis of HIV-1 acquisition. In a preliminary enrichment analysis that aimed to identify the cell types that mediate HIV-1 acquisition susceptibility throughout the body, we observed that polymorphisms implicated in acquisition were enriched for genes expressed in T-cells, which are the main targets for HIV-1 replication29. We further tested the enrichment of HIV-1 variants for genes expressed across a range of neural cell types, since these cells mediate behavior and could explain certain genetic correlations observed with HIV-1 acquisition. We observed a significant enrichment for striatal and hippocampal neurons in association with HIV-1 acquisition, which is particularly striking considering they are brain areas implicated in the regulation of reward and pleasure30,31. Alternatively, these cell types may represent those which harbor HIV-1 and most effectively hide it from the immune system, propagating a sustained infection. Furthermore, the gene-level enrichment analysis identified EFCAB14 as a susceptibility gene for HIV-1 acquisition, on chromosome 1p33. This gene is ubiquitously expressed in the body, and the risk allele of rs8851 is known to reduce expression of EFCAB14 across multiple tissues. Proteins containing EF-Hand Calcium Binding domains in general are implicated in functions ranging from intracellular calcium buffering, signal transduction and muscle contraction32, but future studies are warranted to investigate the function of EFCAB14 specifically, particularly in the context of HIV-1 acquisition.

Another emerging method in population genetics is polygenic risk scoring33,34. We modelled how genetic risk for HIV-1 acquisition expresses itself in the pre-exposed immune profile using a cohort of HIV-1 negative individuals. By considering genetic risk as a continuous trait in a population setting, we can more powerfully determine the influences of the genetic risk signal on innate biological systems such as inflammatory marker expression, without confounders (e.g. drug use, other infections) more commonly associated with individuals from high-risk groups. Moreover, previous studies that have compared high-risk individuals who do not acquire HIV-1, with those that do, are likely confounded by the fact that HIV-1 has an influence on the immune system and inflammatory profile of the individual, which may not correspond to the pre-exposed immune profile associated with risk or resilience. In particular, we studied how genetic predisposition to HIV-1 acquisition affects inflammatory cytokines, which are immune messengers that are relatively easy to assay, can be modified via pharmacological intervention, and are thought to be key moderators of HIV-1 infection25,26. We observed that PRS for HIV-1 acquisition inversely correlated with CCL17 levels in the blood of HIV-1 negative individuals, suggesting that levels of this chemokine should be considered in clinical trials for biomarker, drug and vaccine development. CCL17 is known to regulate the development and maturation of T-cells in the thymus, as well as their trafficking during inflammation35,36,37. Neutralization of this chemokine by antibody treatment has been shown to block the recruitment of T-cells in the lung (ameliorating respiratory allergy)38. We hypothesize that increased CCL17 levels may increase the influx of inflammatory cells, which could help eliminate HIV-1-infected cells before the establishment of a systemic infection. However, CCL17 levels may represent only one of many biological mechanisms implicated in, or co-occurring with, HIV-1 acquisition susceptibility, and further research is needed to better understand this relationship.

Despite the insights provided, our study has limitations, including the modest cohort size of European-only individuals in the GWAS analyzed. Analyses of larger cohorts from different ancestry groups and well-characterized infection routes have the potential to improve our understanding of HIV-1 acquisition, by improving the identification of specific SNPs and genes involved. Future well-powered GWAS of HIV-1 acquisition comparing high risk individuals who are infected versus those who are not will more likely tease apart the biological risk mechanisms implicated in viral resilience from the behavioral risk factors. This could be studied in areas where the risk for HIV-1 is already relatively high in the general population (e.g. South Africa), and where viral entry and replication may represent more important components of acquisition than risk behaviors. Furthermore, although we validated our estimates of heritability and genetic correlations by using two independent methods, additional cohorts are needed to replicate our findings, including those obtained with the PRS analysis. Moreover, our genetic correlation analysis relies on self-report information from the UK Biobank, where individuals (aged 40+) are probably older than the average age of individuals diagnosed with HIV-1. Consequently, behaviors relevant to HIV-1 acquisition that may be more common in a younger cohort (e.g. drug use), could have been absent (or not reported) in the UK Biobank. Where we do find genetic correlations with HIV-1 risk, we cannot currently infer cause and effect, but this is something which may be achievable in the future via a Mendelian randomization design, once larger GWAS are able to detect robust genome-wide significant predictors of HIV-1 acquisition. Finally, the cytokine panel we investigated in association with PRS for acquisition was limited to 35 proteins, and it is possible that other inflammatory markers which we did not assess may be more relevant to this trait.

To conclude, our results show that HIV-1 acquisition genetics impinges upon behavioral, cellular, and immune factors. By leveraging on modern population genetic methods, our work provides a novel framework to study HIV-1 acquisition as a complex phenotype, advancing our understanding of the underlying risk factors. Our results suggest that in addition to environmental risk factors, there is a polygenic component to HIV-1 acquisition that should be explored further in clinical studies. In addition, our work supports the investigation of future intervention strategies surrounding education and smoking behavior. In particular, there needs to be studies investigating whether smoking simply represents a proxy for unhealthy behaviors, or whether it actively influences biological processes linked to HIV-1 acquisition. Similarly, CCL17 and EFCAB14 should also be investigated with respect to their potential role as biomarkers for HIV-1 acquisition and as drug targets. As demonstrated here, GWAS can be very informative even when analyzing moderately sized cohorts, but its true potential to unveil the host genetic mechanisms influencing HIV-1 acquisition will likely only be unlocked with the creation of collaborative initiatives and analyses of larger cohorts.