rs10484565 - TAP2

Magnitude 2.8 · 4 studies on file

Reported associations

• An Immunochip-based interaction study of contrasting interaction effects with smoking in ACPA-positive versus ACPA-negative rheumatoid arthritis. - Rheumatology (Oxford, England) (2016) · Jiang X, Källberg H, Chen Z, Ärlestig L, Rantapää-Dahlqvist S, Davila S, Klareskog L, Padyukov L, Alfredsson L · PubMed 26272072

  To investigate the gene-environment interaction between smoking and single nucleotide polymorphisms (SNPs), using Immunochip material, on the risk of developing either of two serologically defined subsets of RA. Interaction between smoking and 133,648 genetic markers from the Immunochip was examined for two RA subsets, defined by the presence or absence of ACPA. A total of 1590 ACPA-positive and 891 ACPA-negative cases were compared with 1856 controls in the Swedish Epidemiological Investigation of RA (EIRA) case-control study. Logistic regression models were used to determine the presence of interaction. The proportion attributable to interaction was calculated for each smoking-SNP pair. Replication was carried out in an independent dataset from northern Sweden. To further validate and ex

• A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286

  ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

• A saturated map of common genetic variants associated with human height - Unknown journal (n.d.) · Unknown authors · PubMed 36224396

  ABSTRACT: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation

• Identifying shared genetic loci and common risk genes of rheumatoid arthritis associated with three autoimmune diseases based on large-scale cross-trait genome-wide association studies - Unknown journal (n.d.) · Unknown authors · PubMed 37377963

  ABSTRACT: Introduction Substantial links between autoimmune diseases have been shown by an increasing number of studies, and one hypothesis for this comorbidity is that there is a common genetic cause. Methods In this paper, a large-scale cross-trait Genome-wide Association Studies (GWAS) was conducted to investigate the genetic overlap among rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease and type 1 diabetes. Results and discussion Through the local genetic correlation analysis, 2 regions with locally significant genetic associations between rheumatoid arthritis and multiple sclerosis, and 4 regions with locally significant genetic associations between rheumatoid arthritis and type 1 diabetes were discovered. By cross-trait meta-analysis, 58 independent loci associate

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