HIV host genomics in the era of effective antiretroviral therapy

The introduction and widespread use of antiretroviral therapy against Human Immunodefi-ciency Virus (HIV) has had a remarkable effect on disease progression and the longevity of infected individuals. However, the establishment of a latent viral reservoir and the inability of antiretroviral compounds to purge it has resulted in HIV infection becoming a chronic disease with a high preva-lence of comorbidities, adding significant strain to the healthcare systems as well as the affected pa-tients. Human genetic variation has previously been shown to influence HIV pathogenesis as well as the risk of developing multiple common diseases in the general population. However, the influence of genetic variation on HIV positive individuals under suppressive antiretroviral therapy remains largely unknown. This thesis examines the role of human genetic variation in determining the size and long-term dy-namics of the viral reservoir, genetic risk factors for developing HIV-related non-Hodgkin lymphoma (NHL), and how genetic risk scores (GRS) can improve the prediction of chronic kidney disease (CKD) in HIV-infected individuals. Taken together, these studies delineate the role of human genetic variation in phenotypic outcomes that are highly relevant in the era of suppressive antiretroviral treatment, while also suggesting that newly developed genetic risk scores will be capable of enhancing the pre-dictive power of current clinical risk scores.

The interplay between human genetic variation, chronic inflammation and persistent infection: relevance for cardiovascular morbidity

Flavia Aurelia Shoko Hodel

Contemporary genomic approaches allow us to seek answers to biological questions that were previously out of reach. Genome-wide association studies (GWAS) have identified numerous genetic polymorphisms associated with human diseases, providing new insight into the genes and pathways involved in pathogenesis. The work presented in this thesis aimed to harness the power of large-scale genomics, statistical methods and bioinformatic tools to explore the interactions between persistent infections, chronic low-grade inflammation, and coronary heart disease (CHD). To achieve this, we used data collected from large population-based studies of individuals of European ancestry.To identify human genetic determinants of the humoral immune response against persistent or frequently recurring infections, with a special focus on human polyomaviruses, we performed GWAS and meta-analyses of serostatus and quantitative immunoglobulin G responses. We identified NFKB1 as a common locus associated with antibody response to multiple pathogens. For polyomaviruses, we found strong associations of HLA class II, FUT2, STING1, and MUC1 genetic variants with the intensity of the humoral response. Together, these results demonstrate the modulating contribution of host genetic variation to the individual response against some of the most prevalent human viruses.Even when they are latent, chronic infections can trigger some degree of local or systemic immune response, resulting in low-grade inflammation. In an effort to better understand the variability of humoral immune response and inflammation patterns in response to pathogen exposure, we found evidence for an association between Chlamydia trachomatis and Helicobacter pylori seropositivity, and higher plasma levels of C-reactive protein (CRP), a sensitive indicator of inflammation. High polygenic risk was also significantly associated with CRP levels, confirming that human genetic variation plays a modulating role in systemic inflammation. These results improve our understanding of the relationship between persistent infections and chronic inflammation, an important determinant of long-term morbidity in humans.Finally, we developed statistical models to explore the influences of genetic variation, persistent infections and low-grade inflammation on incident CHD. We identified high polygenic risk and Fusobacterium nucleatum infection as associated with an increased risk of developing CHD, in addition to conventional risk factors. These results confirm that CHD is a multicomponent disease that is caused by demographic, genetic and environmental factors. Moreover, they might allow for better identification of individuals at high risk for CHD and provide a rationale for future anti-infective prevention trials.Together, this research demonstrates that current genomic and serological technology, bioinformatic analysis and functional follow-up studies have the potential to provide new insight into the molecular basis of host-pathogen interactions, and their role in chronic diseases. From a translational perspective, the results of this project include new targets for diagnosis and therapeutic development, new disease biomarkers, and better predictive models. Every advance in the understanding of complex disease has the potential to improve genomic and clinical medicine, and I am pleased to have had the opportunity to act at different levels to participate in this much needed transition to precision medicine.

EPFL2022

GuavaH: a compendium of host genomic data in HIV biology and disease

Istvan Bartha, Jacques Fellay, Amalio Telenti

Background: There is an ever-increasing volume of data on host genes that are modulated during HIV infection, influence disease susceptibility or carry genetic variants that impact HIV infection. We created GuavaH (Genomic Utility for Association and Viral Analyses in HIV, http://www.GuavaH.org), a public resource that supports multipurpose analysis of genome-wide genetic variation and gene expression profile across multiple phenotypes relevant to HIV biology. Findings: We included original data from 8 genome and transcriptome studies addressing viral and host responses in and ex vivo. These studies cover phenotypes such as HIV acquisition, plasma viral load, disease progression, viral replication cycle, latency and viral-host genome interaction. This represents genome-wide association data from more than 4,000 individuals, exome sequencing data from 392 individuals, in vivo transcriptome microarray data from 127 patients/conditions, and 60 sets of RNA-seq data. Additionally, GuavaH allows visualization of protein variation in similar to 8,000 individuals from the general population. The publicly available GuavaH framework supports queries on (i) unique single nucleotide polymorphism across different HIV related phenotypes, (ii) gene structure and variation, (iii) in vivo gene expression in the setting of human infection (CD4+ T cells), and (iv) in vitro gene expression data in models of permissive infection, latency and reactivation. Conclusions: The complexity of the analysis of host genetic influences on HIV biology and pathogenesis calls for comprehensive motors of research on curated data. The tool developed here allows queries and supports validation of the rapidly growing body of host genomic information pertinent to HIV research.

BioMed Central2014

The interplay between human genetic variation, chronic inflammation and persistent infection: relevance for cardiovascular morbidity

Flavia Aurelia Shoko Hodel

EPFL2022