Expressive

rs11656665 - SREBF1

Magnitude 2.0 · 2 studies on file

Reported associations

  • Shared genetics of psychiatric disorders and type 2 diabetes:a large-scale genome-wide cross-trait analysis. - Journal of psychiatric research (2023) · Ding H, Xie M, Wang J, Ouyang M, Huang Y, Yuan F, Jia Y, Zhang X, Liu N, Zhang N · PubMed 36738649

    Individuals with psychiatric disorders have elevated rates of type 2 diabetes comorbidity. Although little is known about the shared genetics and causality of this association. Thus, we aimed to investigate shared genetics and causal link between different type 2 diabetes and psychiatric disorders. We conducted a large-scale genome-wide cross-trait association study(GWAS) to investigate genetic overlap between type 2 diabetes and anorexia nervosa, attention deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, schizophrenia, anxiety disorders and Tourette syndrome. By post-GWAS functional analysis, we identify variants genes expression in various tissues. Enrichment pathways, potential protein interaction and m

  • A powerful method for pleiotropic analysis under composite null hypothesis identifies novel shared loci between Type 2 Diabetes and Prostate Cancer - Unknown journal (n.d.) · Unknown authors · PubMed 33290408

    ABSTRACT: There is increasing evidence that pleiotropy, the association of multiple traits with the same genetic variants/loci, is a very common phenomenon. Cross-phenotype association tests are often used to jointly analyze multiple traits from a genome-wide association study (GWAS). The underlying methods, however, are often designed to test the global null hypothesis that there is no association of a genetic variant with any of the traits, the rejection of which does not implicate pleiotropy. In this article, we propose a new statistical approach, PLACO, for specifically detecting pleiotropic loci between two traits by considering an underlying composite null hypothesis that a variant is associated with none or only one of the traits. We propose testing the null hypothesis based on the

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