| Title: | Genetic epidemiology of psoriasis and other inflammatory skin diseases |
| Lead Institution: | King's College London |
| Principal investigator: | Dr Nick Dand |
Application 15147
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
We aim to identify and compare DNA sequence variants predisposing to psoriasis and other inflammatory skin diseases. The proposed analysis will integrate UK Biobank?s population-based cohort with our international consortia-derived case-control datasets (including 8,000 severe psoriasis cases). We aim to improve understanding of the genetic factors underlying disease development and outcome. Our group has a longstanding interest in the genetic basis of psoriasis, playing a leading role in many recent pioneering genomewide studies. This study aligns with our research objectives: seeking new insights into the biology of skin inflammation and translating these into healthcare innovations. Long-term disfiguring skin diseases including psoriasis and eczema are common and associated with poor quality of life, multiple comorbidities and reduced life expectancy. These stigmatising diseases have a large impact on the emotional health and wellbeing of patients, hence pose a major social and economic burden on society. There are very significant direct and indirect health care costs. Current treatments are non-curative and may result in serious side effects. It is vitally important to understand the molecular processes underlying these diseases so that efficacious, targeted novel therapies, personalised to the individual needs of patients, can be developed. We will undertake genomewide association analysis for each inflammatory skin disease of interest, to identify statistical association between individual genetic variants and disease status/severity. This is an established technique in which we have substantial experience. Additionally, medication and relevant clinical data will be used to assess the utility of self-reported disease data compared to traditionally ascertained datasets. We will use more detailed statistical models to examine the interaction between genetic and environmental risk factors (including modifiable lifestyle factors), and perform cross-phenotype analysis to study the shared genetic basis of skin diseases and general inflammatory disease processes. Full cohort5 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 11031 | Comorbidities of Keloid and Hypertrophic Scars Among Participants in UK Biobank | Chuin Y. Ung (+7) | 2023 | JAMA Dermatology |
| 11957 | Gene-Environment Interaction Between CYP1B1 and Oral Contraception on Frontal Fibrosing Alopecia | Tuntas Rayinda (+8) | 2024 | JAMA Dermatology |
| 7918 | Genetic Validation of Psoriasis Phenotyping in UK Biobank Supports the Utility of Self-Reported Data and Composite Definitions for Large Genetic and Epidemiological Studies | Jake R. Saklatvala (+8) | 2023 | Journal of Investigative Dermatology |
| 9597 | Genome-wide meta-analysis implicates variation affecting mast cell biology in urticaria | Sheila Mary McSweeney (+11) | 2023 | Journal of Allergy and Clinical Immunology |
| 11464 | Shared Genetic Risk Variants in Both Male and Female Frontal Fibrosing Alopecia | Tuntas Rayinda (+31) | 2023 | Journal of Investigative Dermatology |
Enabling scientific discoveries that improve human health