SUPR
Genetic studies in UK biobank
Dnr:

sens2017538

Type:

SNIC SENS

Principal Investigator:

Åsa Johansson

Affiliation:

Uppsala universitet

Start Date:

2017-11-29

End Date:

2025-01-01

Primary Classification:

30107: Medical Genetics

Allocation

Abstract

Genome-wide association studies (GWAS) have identified thousands of common single nucleotide polymorphisms (SNPs) associated with complex traits and diseases. However, GWAS have also highlighted that only a small proportion of the genetic contribution to complex diseases can be explained by the SNPs identified. It is likely that much of the remaining genetic contribution to complex traits, the missing heritability, is due to: a) the effect of rare genetic variants not assessed in GWAS, b) common variants with small effects that are not detected in the GWAS studies performed so far, and c) interactions between genes and environment, or between pairs of genes. The purpose of this project is to study the effect of genetic variants and the effect of gene-environment interactions on complex traits using a large population based study cohort, the UK biobank. The UK biobank has recruited 500,000 people aged 40-69 years from across the UK and genotyping of all samples (N=500,000) is expected to be finished by Q2 end of 2016. Most participants have undergone a physical examination including e.g. blood pressure, pulse rate, ECG, weight and height measurements. Participants were also interviewed about smoking, medications, disease history, and filled in a diet questionnaire. Death and cancer registry, as well as in-patient hospital data is available and the intention is to performed yearly updates on this data. Genotyping in UK biobank is performed in collaboration with Affymetrix and will include approximately 821,000 SNP in total. Unassayed genotypes ahs been imputed using the 1000 genome reference database resulting in over 10 million SNPs per participant. Applications for using data from UK biobank has been approved for three projects entitled: “Using Mendelian randomization to evaluate the causal effect of disease related biomarkers on clinical outcomes “, “Interaction between diet, food preference and lifestyle with genetic factors influencing body mass, body adiposity and obesity”, “Genetic architecture of immune diseases and allergies”.