rs12420205 - DRD2 - TMPRSS5

Magnitude 4.5 · 3 studies on file

Reported associations

• Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. - Nature genetics (2019) · Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, Savage JE, Hammerschlag AR, Skene NG, Muñoz-Manchado AB, White T, Tiemeier H, Linnarsson S, Hjerling-Leffler J, Polderman TJC, Sullivan PF, van der Sluis S, Posthuma D · PubMed 29942085

  Neuroticism is an important risk factor for psychiatric traits, including depression , anxiety , and schizophrenia . At the time of analysis, previous genome-wide association studies (GWAS) reported 16 genomic loci associated to neuroticism . Here we conducted a large GWAS meta-analysis (n = 449,484) of neuroticism and identified 136 independent genome-wide significant loci (124 new at the time of analysis), which implicate 599 genes. Functional follow-up analyses showed enrichment in several brain regions and involvement of specific cell types, including dopaminergic neuroblasts (P = 3.49 × 10 ), medium spiny neurons (P = 4.23 × 10 ), and serotonergic neurons (P = 1.37 × 10 ). Gene set analyses implicated three specific pathways: neurogenesis (P = 4.43

• Item-level analyses reveal genetic heterogeneity in neuroticism - Unknown journal (n.d.) · Unknown authors · PubMed 29500382

  ABSTRACT: Genome-wide association studies (GWAS) of psychological traits are generally conducted on (dichotomized) sums of items or symptoms (e.g., case-control status), and not on the individual items or symptoms themselves. We conduct large-scale GWAS on 12 neuroticism items and observe notable and replicable variation in genetic signal between items. Within samples, genetic correlations among the items range between 0.38 and 0.91 (mean rg = .63), indicating genetic heterogeneity in the full item set. Meta-analyzing the two samples, we identify 255 genome-wide significant independent genomic regions, of which 138 are item-specific. Genetic analyses and genetic correlations with 33 external traits support genetic differences between the items. Hierarchical clustering analysis identifi

• Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study - Unknown journal (n.d.) · Unknown authors · PubMed 37156939

  ABSTRACT: Background and Aims: Genome-wide association studies (GWAS) of opioid use disorder (OUD) and cannabis use disorder (CUD) have lagged behind those of alcohol use disorder (AUD) and smoking, where many more loci have been identified. We sought to identify novel loci for substance use traits (SUTs) in both African- (AFR) and European- (EUR) ancestry individuals to enhance our understanding of the traits' genetic architecture. Design: We used multi-trait analysis of GWAS (MTAG) to analyze four SUTs in EUR subjects (OUD, CUD, AUD and smoking initiation [SMKinitiation]), and three SUTs in AFR subjects (OUD, AUD and smoking trajectory [SMKtrajectory]). We conducted gene-set and protein-protein interaction analyses and calculated polygenic risk scores (PRS) in two independent samples

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