| Title: | Physician-Confirmed and Administrative Definitions of Stroke in UK Biobank Reflect the Same Underlying Genetic Trait |
| Journal: | Frontiers in Neurology |
| Published: | 2 Feb 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35185750/ |
| DOI: | https://doi.org/10.3389/fneur.2021.787107 |
| URL: | https://www.frontiersin.org/articles/10.3389/fneur.2021.787107/pdf |
Publication 13863
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Abstract
BACKGROUND: Stroke in UK Biobank (UKB) is ascertained via linkages to coded administrative datasets and self-report. We studied the accuracy of these codes using genetic validation.</p>
METHODS: We compiled stroke-specific and broad cerebrovascular disease (CVD) code lists (Read V2/V3, ICD-9/-10) for medical settings (hospital, death record, primary care) and self-report. Among 408,210 UKB participants, we identified all with a relevant code, creating 12 stroke definitions based on the code type and source. We performed genome-wide association studies (GWASs) for each definition, comparing summary results against the largest published stroke GWAS (MEGASTROKE), assessing genetic correlations, and replicating 32 stroke-associated loci.</p>
RESULTS: The stroke case numbers identified varied widely from 3,976 (primary care stroke-specific codes) to 19,449 (all codes, all sources). All 12 UKB stroke definitions were significantly correlated with the MEGASTROKE summary GWAS results (rg.81-1) and each other (rg.4-1). However, Bonferroni-corrected confidence intervals were wide, suggesting limited precision of some results. Six previously reported stroke-associated loci were replicated using ≥1 UKB stroke definition.</p>
CONCLUSIONS: Stroke case numbers in UKB depend on the code source and type used, with a 5-fold difference in the maximum case-sample size. All stroke definitions are significantly genetically correlated with the largest stroke GWAS to date.</p>
13 Authors
- Kristiina Rannikmäe
- Konrad Rawlik
- Amy C. Ferguson
- Nikos Avramidis
- Muchen Jiang
- Nicola Pirastu
- Xia Shen
- Emma Davidson
- Rebecca Woodfield
- Rainer Malik
- Martin Dichgans
- Albert Tenesa
- Cathie Sudlow
1 Application
| Application ID | Title |
|---|---|
| 2532 | UK Biobank Stroke Study (UKBiSS): developing an in-depth understanding of the determinants of stroke and its subtypes |
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