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- Din, Lennox, et al.
(författare)
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Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes
- 2019
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Ingår i: Genetic Epidemiology. - : WILEY. - 0741-0395 .- 1098-2272. ; 43:7, s. 844-863
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Tidskriftsartikel (refereegranskat)abstract
- Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p =.0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.
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| 3. |
- Helle, Emmi, et al.
(författare)
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Loss of function, missense, and intronic variants in NOTCH1 confer different risks for left ventricular outflow tract obstructive heart defects in two European cohorts
- 2019
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Ingår i: Genetic Epidemiology. - : Wiley. - 0741-0395 .- 1098-2272. ; 43:2, s. 215-226
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Tidskriftsartikel (refereegranskat)abstract
- Loss of function variants in NOTCH1 cause left ventricular outflow tract obstructive defects (LVOTO). However, the risk conferred by rare and noncoding variants in NOTCH1 for LVOTO remains largely uncharacterized. In a cohort of 49 families affected by hypoplastic left heart syndrome, a severe form of LVOTO, we discovered predicted loss of function NOTCH1 variants in 6% of individuals. Rare or low-frequency missense variants were found in 16% of families. To make a quantitative estimate of the genetic risk posed by variants in NOTCH1 for LVOTO, we studied associations of 400 coding and noncoding variants in NOTCH1 in 1,085 cases and 332,788 controls from the UK Biobank. Two rare intronic variants in strong linkage disequilibrium displayed significant association with risk for LVOTO amongst European-ancestry individuals. This result was replicated in an independent analysis of 210 cases and 68,762 controls of non-European and mixed ancestry. In conclusion, carrying rare predicted loss of function variants in NOTCH1 confer significant risk for LVOTO. In addition, the two intronic variants seem to be associated with an increased risk for these defects. Our approach demonstrates the utility of population-based data sets in quantifying the specific risk of individual variants for disease-related phenotypes.
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| 10. |
- Sofer, Tamar, et al.
(författare)
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A fully adjusted two-stage procedure for rank-normalization in genetic association studies
- 2019
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 43:3, s. 263-275
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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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