rs114400264 - EHMT2-AS1, SLC44A4
Magnitude 4.5 · 2 studies on file
Reported associations
-
Multi-ancestry genome-wide meta-analysis with 472,819 individuals identifies 32 novel risk loci for psoriasis. - Journal of translational medicine (2025) · Zhang M, Su W, Deng J, Zhai B, Zhu G, Gao R, Zeng Q, Qiu J, Bian Z, Xiao H, Luan G, Wang R · PubMed 39885523
Psoriasis is a common chronic, recurrent, immune-mediated disease involved in the skin or joints or both. However, deeper insight into the genetic susceptibility of psoriasis is still unclear. Here we performed the largest multi-ancestry meta-analysis of genome-wide association study including 28,869 psoriasis cases and 443,950 healthy controls. We identified 74 genome-wide significant loci for psoriasis. Of 74 loci, 32 were novel psoriasis risk loci. Across 74 loci, 801 likely causal genes are indicated and 164 causal genes are prioritized. SNP-based heritability analyses demonstrated that common variants explain 15% of genetic risk for psoriasis. Gene-set analyses and the genetic correlation revealed that psoriasis-related genes have the positive correlations with autoimmune diseases suc
-
Evaluate the effects of serum urate level on bone mineral density: a genome-wide gene-environment interaction analysis in UK Biobank cohort. - Endocrine (2021) · Yao Y, Chu X, Ma M, Ye J, Wen Y, Li P, Cheng B, Cheng S, Zhang L, Liu L, Qi X, Liang C, Kafle OP, Wu C, Wang S, Wang X, Ning Y, Zhang F · PubMed 34046847
Serum urate is associated with BMD and may be a protective factor. However, the exact association and mechanism are still unclear. We performed a genome-wide gene-environmental interaction study (GWGEIS) to explore the interaction effects between gene and urate on BMD, using data from the UK Biobank cohort. A total of 4575 participants for femur total BMD, 4561 participants for L1-L4 BMD, and 237799 participants for heel BMD were included in the present study. Linear regression models were used to test for associations between urate and BMD (femur total BMD, L1-L4 BMD, heel BMD) by R software. GWGEIS was conducted by PLINK 2.0 using a generalize linear model, adjusted for age, sex, weight, smoking behavior, drinking behavior, physical activity and 10 principle components for population str
Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.