The effect of common and rare variants on inflammatory traits and diseases

Sammanfattning: Genome wide association studies (GWAS) have identified thousands of loci associated to an immense number of traits and diseases. Most associations have been to common variants, but rare variant associations are progressively being reported. Common genetic variants often have a small effect individually but can contribute to disease risk when being several, whereas rare genetic variants often have a large effect individually. In so-called complex diseases, a number of variants together contribute to alterations in disease risk. However, to what extent common and rare variants contribute in combination or separately, still needs to be characterized for many types of diseases.In Paper I, we performed a GWAS on whole-genome sequence (WGS) data from a Swedish cohort (NSPHS, Northern Swedish Population Health Study). The same cohort have previously been genotyped, and our aim was to assess the differences and possible gains of analysing WGS data instead of genotyped data. We demonstrated that we were able to gain both power and precision in increasing the support for previous associations as well as detecting novel ones.In Paper II, we assessed the ABO blood grouping system by analysing the ABO genotypes in UK Biobank. We genetically determined the ABO genotypes of all participates and investigated whether individuals with different ABO genotypes pose different risks for cardiovascular and inflammatory disease. We were able to fine-map previous associations between the ABO blood groups and cardiovascular disease, including proteins involved in coagulation. We confirmed that non-O individuals have a higher risk of blood clots, even heterozygous carriers of A and B. These results show the potential importance of implementing ABO genotypes in the clinic.In Paper III, we used whole-exome sequence (WES) data from UK Biobank to assess the genetic contribution to changes in eosinophil count. We performed gene-based analyses with five different analysis models and found novel associations to eosinophil count. We further found associations that appears to be mainly driven by rare variants in previously known eosinophil loci. Even if WES analysis is limited to coding variation, these are promising results for further validation.In Paper IV, we built upon Paper I and performed gene-based tests in relation to more than 400 protein levels measured in NSPHS. We utilised several different models, including only coding variation, only regulatory and others and used these variant-sets in different models. By taking common GWAS variants into account, we demonstrated that novel findings could still be found. We further demonstrated that the majority of all variants in NSPHS are rare but the majority of variants carried by each individual are common.This thesis has highlighted the utilisation of different kinds of genetic data, and how it can aid in both improving, fine-mapping and increasing associations to complex diseases. This work had aided in the advancements in genetic epidemiology and medical genetics. It has explored both genotyped, WGS and WES variants, highlighting how rare and common variants can be detected and characterise in relation to inflammatory disease, both as single variants and in aggregate.