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ABSTRACT: Background
Despite MN being one of the most common causes of nephrotic syndrome worldwide, its biological and environmental determinants are poorly understood in large-part due to it being a rare disease. Making use of the UK Biobank, a unique resource holding a clinical dataset and stored DNA, serum and urine for ~500,000 participants, this study aims to address this gap in understanding.Methods
The primary outcome was putative MN as defined by ICD-10 codes occurring in the UK Biobank. Univariate relative risk regression modelling was used to assess the associations between the incidence of MN and related phenotypes with sociodemographic, environmental exposures, and previously described increased-risk SNPs.Results
502,507 patients were included in the study of who
SUBMITTER: Hamilton P
PROVIDER: S-EPMC10138203 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature