rs10244364 - CTTNBP2 - LSM8

Magnitude 4.5 · 5 studies on file

Reported associations

• Multivariate genome-wide analyses of the well-being spectrum. - Nature genetics (2019) · Baselmans BML, Jansen R, Ip HF, van Dongen J, Abdellaoui A, van de Weijer MP, Bao Y, Smart M, Kumari M, Willemsen G, Hottenga JJ, Boomsma DI, de Geus EJC, Nivard MG, Bartels M · PubMed 30643256

  We introduce two novel methods for multivariate genome-wide-association meta-analysis (GWAMA) of related traits that correct for sample overlap. A broad range of simulation scenarios supports the added value of our multivariate methods relative to univariate GWAMA. We applied the novel methods to life satisfaction, positive affect, neuroticism, and depressive symptoms, collectively referred to as the well-being spectrum (N = 2,370,390), and found 304 significant independent signals. Our multivariate approaches resulted in a 26% increase in the number of independent signals relative to the four univariate GWAMAs and in an ~57% increase in the predictive power of polygenic risk scores. Supporting transcriptome- and methylome-wide analyses (TWAS and MWAS, respectively) uncovered an addition

• Minimal phenotyping yields genome-wide association signals of low specificity for major depression - Unknown journal (n.d.) · Unknown authors · PubMed 32231276

  ABSTRACT: Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be

• 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 of genome-wide association summary statistics using MTAG - Unknown journal (n.d.) · Unknown authors · PubMed 29292387

  ABSTRACT: We introduce Multi-Trait Analysis of GWAS (MTAG), a method for joint analysis of summary statistics from GWASs of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (Neff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). Compared to 32, 9, and 13 genome-wide significant loci in the single-trait GWASs (most of which are themselves novel), MTAG increases the number of loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase variance explained by polygenic scores by approximately 25%, matching theoretical expectations. FULL TEXT: [INTRO] INTRODUCTION [INTRO] The standard approach in genetic-association studi

• Genetic variants associated with subjective well-being, depressive symptoms and neuroticism identified through genome-wide analyses - Unknown journal (n.d.) · Unknown authors · PubMed 27089181

  ABSTRACT: We conducted genome-wide association studies of three phenotypes: subjective well-being (N = 298,420), depressive symptoms (N = 161,460), and neuroticism (N = 170,910). We identified three variants associated with subjective well-being, two with depressive symptoms, and eleven with neuroticism, including two inversion polymorphisms. The two depressive symptoms loci replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes strengthen the overall credibility of the findings, and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are strongly enriched for association. FULL TEXT: [INTRO] Introduction [INTRO] Subjectiv

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