Budu-Aggrey, A. | bioRxiv Science

bioRxiv2018

Common genetic variants and health outcomes appear geographically structured in the UK Biobank sample: Old concerns returning and their implications.

Introductory paragraphThe inclusion of genetic data in large studies has enabled the discovery of genetic contributions to complex traits and their application in applied analyses including those using genetic risk scores (GRS) for the prediction of phenotypic variance. If genotypes show structure by location and coincident structure exists for the trait of interest, analyses can be biased. Having illustrated structure in an apparently homogeneous collection, we aimed to a) test for geographical stratification of genotypes in UK Biobank and b) assess whether stratification might induce bias in genetic association analysis.\n\nWe found that single genetic variants are associated with birth location within UK Biobank and that geographic structure in genetic data could not be accounted for using routine adjustment for study centre and principal components (PCs) derived from genotype data. We found that GRS for complex traits do appear geographically structured and analysis using GRS can yield biased associations. We discuss the likely origins of these observations and potential implications for analysis within large-scale population based genetic studies.

genetics↗

bioRxiv2018

Evidence of a common causal relationship between body mass index and inflammatory skin disease: a Mendelian Randomization study

ObjectivePsoriasis and eczema are common inflammatory skin diseases that have been reported to be associated with obesity. However, causality has not yet been established. We aimed to investigate the possible causal relationship between body mass index (BMI) and psoriasis or eczema.\n\nMethodsFollowing a review of published epidemiological evidence of the association between obesity and either psoriasis or eczema, Mendelian Randomization (MR) was used to test for a causal relationship between BMI and these inflammatory skin conditions. We used a genetic instrument comprising 97 single nucleotide polymorphisms (SNPs) associated with BMI. One-sample MR was conducted using individual-level data (401,508 individuals) from the UK Biobank and the Nord-Trondelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (731,021 individuals) from published BMI, psoriasis and eczema GWAS. The one-sample and two-sample MR estimates were meta-analysed using a fixed effect model. To explore the reverse causal direction, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis and eczema were used to test if inflammatory skin disease has a causal effect on BMI.\n\nResultsPublished observational data show an association of greater BMI with both psoriasis and eczema case status. The observational associations were confirmed in UK Biobank and HUNT datasets. MR analyses provide evidence that higher BMI causally increases the odds of psoriasis (by 53% per 5 units higher BMI; OR= 1.09 (1.06 to 1.12) per 1 kg/m2; P=4.67x10-9) and eczema (by 8% per 5 units higher BMI; OR=1.02 (1.00 to 1.03) per 1 kg/m2; P=0.09). When investigating causality in the opposite direction, MR estimates provide little evidence for an effect of either psoriasis or eczema influencing BMI.\n\nConclusionOur study, using genetic variants as instrumental variables for BMI, shows that higher BMI leads to a higher risk of inflammatory skin disease. The causal relationship was stronger for psoriasis than eczema. Therapies and life-style interventions aimed at controlling BMI or targeting the mechanisms linking obesity with skin inflammation may offer an opportunity for the prevention or treatment of these common skin diseases.

genetics↗