rs10830220 - GRM5 - TYR

Magnitude 4.5 · 4 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

  • Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism - Unknown journal (n.d.) · Unknown authors · PubMed 29255261

    ABSTRACT: Neuroticism is a relatively stable personality trait characterised by negative emotionality (e.g., worry, guilt); twin study heritability ranges 30 to 50%, and SNP-based heritability ranges 6 to 15%. Increased neuroticism is associated with poorer mental and physical health, translating to high economic burden. Genome-wide association (GWA) studies of neuroticism have identified up to 11 genetic loci. Here we report 116 significant independent loci from a GWA of neuroticism in 329,821 UK Biobank participants; 15 of these replicated at P<.00045 in an unrelated cohort (N = 122,867). Genetic signals were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (rg = .82, SE=.03), major depr

  • Multi-trait analysis for genome-wide association study of five psychiatric disorders - Unknown journal (n.d.) · Unknown authors · PubMed 32606422

    ABSTRACT: We conducted a cross-trait meta-analysis of genome-wide association study on schizophrenia (SCZ) (n = 65,967), bipolar disorder (BD) (n = 41,653), autism spectrum disorder (ASD) (n = 46,350), attention deficit hyperactivity disorder (ADHD) (n = 55,374), and depression (DEP) (n = 688,809). After the meta-analysis, the number of genomic loci increased from 14 to 19 in ADHD, from 3 to 10 in ASD, from 45 to 57 in DEP, from 8 to 54 in BD, and from 64 to 87 in SCZ. We observed significant enrichment of overlapping genes among different disorders and identified a panel of cross-disorder genes. A total of seven genes were found being commonly associated with four out of five psychiatric conditions, namely GABBR1, GLT8D1, HIST1H1B, HIST1H2BN, HIST1H4L, KCNB1, and DCC.


Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.