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Sökning: WFRF:(Grinde Kelsey)

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1.
  • Shungin, Dmitry, et al. (författare)
  • Genome-wide analysis of dental caries and periodontitis combining clinical and self-reported data
  • 2019
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health.
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2.
  • Sofer, Tamar, et al. (författare)
  • A fully adjusted two-stage procedure for rank-normalization in genetic association studies
  • 2019
  • Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 43:3, s. 263-275
  • Tidskriftsartikel (refereegranskat)abstract
    • When testing genotype–phenotype associations using linear regression, departure of the trait distribution from normality can impact both Type I error rate control and statistical power, with worse consequences for rarer variants. Because genotypes are expected to have small effects (if any) investigators now routinely use a two‐stage method, in which they first regress the trait on covariates, obtain residuals, rank‐normalize them, and then use the rank‐normalized residuals in association analysis with the genotypes. Potential confounding signals are assumed to be removed at the first stage, so in practice, no further adjustment is done in the second stage. Here, we show that this widely used approach can lead to tests with undesirable statistical properties, due to both combination of a mis‐specified mean–variance relationship and remaining covariate associations between the rank‐normalized residuals and genotypes. We demonstrate these properties theoretically, and also in applications to genome‐wide and whole‐genome sequencing association studies. We further propose and evaluate an alternative fully adjusted two‐stage approach that adjusts for covariates both when residuals are obtained and in the subsequent association test. This method can reduce excess Type I errors and improve statistical power.
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