Expressive

rs11072811 - MORF4L1

Magnitude 2.0 · 3 studies on file

Reported associations

  • Genome‐Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases - Journal of the American Heart Association (2024) · Guo Y, Chung W, Shan Z, Zhu Z, Costenbader KH, Liang L · PubMed 37947095

    ABSTRACT: Background Patients with rheumatoid arthritis (RA) have a 2‐ to 10‐fold increased risk of cardiovascular disease (CVD), but the biological mechanisms and existence of causality underlying such associations remain to be investigated. We aimed to investigate the genetic associations and underlying mechanisms between RA and CVD by leveraging large‐scale genomic data and genetic cross‐trait analytic approaches. Methods and Results Within UK Biobank data, we examined the genetic correlation, shared genetics, and potential causality between RA (Ncases=6754, Ncontrols=452 384) and cardiovascular diseases (CVD, Ncases=44 238, Ncontrols=414 900) using linkage disequilibrium score regression, cross‐trait meta‐analysis, and Mendelian randomization. We observed significant

  • Multi‐phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations - Journal of thrombosis and haemostasis : JTH (2022) · Temprano-Sagrera G, Sitlani CM, Bone WP, Martin-Bornez M, Voight BF, Morrison AC, Damrauer SM, de Vries PS, Smith NL, Sabater-Lleal M · PubMed 35285134

    ABSTRACT: Abstract Background Multi‐phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods Summary statistics from genome wide‐association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI

  • Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies - Nature genetics (2019) · Zhou W, Nielsen JB, Fritsche LG, Dey R, Gabrielsen ME, Wolford BN, LeFaive J, VandeHaar P, Gagliano SA, Gifford A, Bastarache LA, Wei WQ, Denny JC, Lin M, Hveem K, Kang HM, Abecasis GR, Willer CJ, Lee S · PubMed 30104761

    ABSTRACT: In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, linear mixed model and the recently proposed logistic mixed model, perform poorly - producing large type I error rates - in the analysis of unbalanced case-control phenotypes. Here we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation to calibrate the distribution of score test statistics. This method, SAIGE, provides accurate p-values even when case-control ratios are extremely unbalanced. It utilizes state-of-art optimization strategies to reduce computational cost, and hence is applicable to GWAS for thousands of phenotypes by la

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