Deciphering the genetic basis of systemic sclerosis

Abstract

Systemic sclerosis, or scleroderma (SSc), is a complex immunemediated inflammatory disorder. SSc pathogenesis involves a triad of factors: immunological imbalance characterized by the presence of autoantibodies. pronounced vascular damage and extensive fibrosis of the skin and the internal organs. Clinically, SSc can be classified based on the extension of fibrosis. When it primarily affects the face and limbs, it is referred to as limited cutaneous SSc (lcSSc), while when it involves internal organs, it is defined as diffuse cutaneous SSc (dcSSc). Additionally, SSc can be classified by the autoantibodies generated by the patient, the predominant types being anti-topoisomerase (ATA+) and anti-centromere (ACA+), that correlate with dcSSc and lcSSC, respectively. SSc has a clear genetic component and the role of common genetic variants in the susceptibility to SSc has been explored by using high throughput genotyping techniques such as genome-wide association studies (GWAS) arrays. The latest GWAS in the disease, published in 2019, identified 27 loci associated with SSc, discovering 13 new ones and providing new insights into the molecular pathways and specific cell types implicated in the pathogenesis of the disease. In addition, the mentioned large genomic study established solid grounds for comprehensive follow-up studies and data mining strategies. Consequently, the main aim of this doctoral thesis research was to further understand the biological mechanisms involved in SSc by applying novel analysis strategies on GWAS datasets and to generate and analyze the gene expression profiles of relevant cell subtypes at the single cell level. A straightforward application of the identification of genetic risk factors and the estimation of their effects in large GWASs is the generation of polygenic or genomic risk scores (PRS or GRS, respectively). This method enabled us to identify individuals at risk of developing the disease based on the presence of specific alleles in known disease-associated loci. In this doctoral thesis, we developed a 33 single nucleotide polymorphism (SNP) GRS that was proven to be able to differentiate between healthy individuals and SSc patients. Moreover, the generated GRS showed a relevant clinical management potential, as it could distinguish between individuals with SSc and those with two related immune-mediated disorders such as rheumatoid arthritis and Sjögren's syndrome, especially when genetic information was combined with immune cell count data. On the other hand, two-sample Mendelian randomization methods allowed the scientific community to combine GWAS results for diseases and environmental risk factors to address the causality of risk factors on disease onset. High levels of body fat or obesity are known risk factors for numerous diseases, including immune-mediated diseases. Obesity is associated with a state of chronic low-level inflammation, in which adipocytes release proinflammatory cytokines. Therefore, this thesis included the study of the causal contribution of body fat distribution to the SSc. We utilized GWAS data from public repositories for anthropometric measures of body fat distribution, including body mass index (BMI), waist-to-hip ratio, and BMI adjusted for waist-to-hip ratio. However, our analyses did not reveal a causal relationship between SSc and any of these obesity-related anthropometric measures. Finally, based on previous knowledge, monocytes were selected as targets cells to study in order to better understand the SSc pathogenesis. Monocytes are myeloid cells that circulate in the blood with various functions in innate immunity, ranging from direct action against threats to the activation of other cell types and chemotaxis. Therefore, we isolated monocytes from peripheral blood in patients and controls and using singlecell transcriptome analysis (scRNA-seq), we identified aberrant gene expression profiles in SSc patients. Briefly, non-classical monocytes (ncMos) were found in higher proportions in SSc patients, and SSc ncMos also expressed increased levels of PTGES and interferon-mediated activation. PTGES encodes a prostaglandin E2 synthase, which was previously proposed as a therapeutic target in inflammation and may also be relevant for SSc patients. A SSc-related cluster of IRF7+ STAT1+ intermediate monocyte subset with an aberrant interferon response was also described. Additionally, we identified a M2-polarized population of classical monocytes that was depleted in patients. Considering that M2 macrophages are profibrotic, we hypothesized that these monocyte subset is being activated and migrating to tissues in SSc patients. The results presented in this doctoral thesis signify a step forward in the genetic exploration of SSc from various perspectives. First, we employed previously published GWAS data to predict SSc onset based on genetic variants. Second, we utilized the same GWAS data to establish body fat distribution as a predisposing risk factor for the disease. Third, we employed cutting-edge techniques like scRNA-seq to describe circulating blood monocytes and their potential role in the disease.