瑞典卡罗林斯卡学院全奖博士招生

Project description

Rheumatoid arthritis (RA) is a lifelong autoimmune inflammatory disease, characterized with persistent synovitis, systemic inflammations, and autoantibodies. The disease strikes predominantly women, affecting small joints of hands and feet, leading to a high proportion of work disability. The overall aim of this PhD project is to provide novel insights into the risk factors, gene-environment interactions, and comorbid conditions of RA, leveraging large-scale genetic information and environmental data. The ultimate goal is to understand disease aetiology and to inform preventive strategy. This PhD project consists of five sub-projects, first a systemic review and meta-analysis to comprehensively summarize the roles of airborne occupational exposures in RA development; followed by a population-based case-control study comprising both European and Asian individuals to understand airborne occupational exposures, genetic predispositions, and their interactions in RA onset. Next, a project looking into the roles of stress at work and in life, as well as social support in RA development. Furthermore, an outcome-wide Mendelian randomization to explore the putative causal association of RA with its subsequent health outcomes; and finally a cross-phenotype design to understand shared and distinct risk factors between RA and other autoimmune disorders such as MS.

Selection criteria

Applicants must have a deep interest in computational medical research. Previous experience with genetic, epidemiological research (particularly, in the field of autoimmune disease), programming, application of advanced statistical methods and work in R programming environment is a merit. We expect the applicant to be familiar with the basic concepts of statistical analysis. Additionally, advanced knowledge of statistical genetics approaches such as genome-wide association analysis, functional annotations, G-by-E interactions, and Mendelian randomization is a merit. We require the applicant to be willing to develop intermediate programming skills and to work with open-source software using a command-line interface.

Information

Ingrid Kockum, Professor, ingrid.kockum@ki.se

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