Genetic overlap between self-assessed intelligence, measured IQ and personality

2011 ◽  
Author(s):  
Denis Bratko
Keyword(s):  
2021 ◽  
pp. 108705472110201
Author(s):  
Douglas Teixeira Leffa ◽  
Bernardo Horta ◽  
Fernando C. Barros ◽  
Ana M. B. Menezes ◽  
Thais Martins-Silva ◽  
...  

Objective: Shared genetic mechanisms have been hypothesized to explain the comorbidity between ADHD and asthma. To evaluate their genetic overlap, we relied on data from the 1982 Pelotas birth cohort to test the association between polygenic risk scores (PRSs) for ADHD (ADHD-PRSs) and asthma, and PRSs for asthma (asthma-PRSs) and ADHD. Method: We analyzed data collected at birth, 2, 22, and 30 years from 3,574 individuals. Results: Subjects with ADHD had increased risk of having asthma (OR 1.92, 95% CI 1.01–3.66). The association was stronger for females. Our results showed no evidence of association between ADHD-PRSs and asthma or asthma-PRSs and ADHD. However, an exploratory analysis suggested that adult ADHD might be genetically associated with asthma. Conclusion: Our results do not support a shared genetic background between both conditions. Findings should be viewed in light of important limitations, particularly the sample size and the self-reported asthma diagnosis. Studies in larger datasets are required to better explore the genetic overlap between adult ADHD and asthma.


Author(s):  
Emma E.M. Knowles ◽  
Juan M. Peralta ◽  
Laura Almasy ◽  
Vishwajit Nimgaonkar ◽  
Francis J. McMahon ◽  
...  

2018 ◽  
Vol 48 (6) ◽  
pp. 432-439 ◽  
Author(s):  
Megan Flom ◽  
Manjie Wang ◽  
Kendra J. Uccello ◽  
Kimberly J. Saudino

2021 ◽  
Author(s):  
Jennifer Monereo Sánchez ◽  
Miranda T. Schram ◽  
Oleksandr Frei ◽  
Kevin O’Connell ◽  
Alexey A. Shadrin ◽  
...  

ABSTRACTBackgroundAlzheimer’s disease (AD) and depression are debilitating brain disorders that are often comorbid. Shared brain mechanisms have been implicated, yet findings are inconsistent, reflecting the complexity of the underlying pathophysiology. As both disorders are (partly) heritable, characterizing their genetic overlap may provide etiological clues. While previous studies have indicated negligible genetic correlations, this study aims to expose the genetic overlap that may remain hidden due to mixed directions of effects.MethodsWe applied Gaussian mixture modelling, through MiXeR, and conjunctional false discovery rate (cFDR) analysis, through pleioFDR, to genome-wide association study (GWAS) summary statistics of AD (n=79,145) and depression (n=450,619). The effects of identified overlapping loci on AD and depression were tested in 403,029 participants of the UK Biobank (mean age 57.21 52.0% female), and mapped onto brain morphology in 30,699 individuals with brain MRI data.ResultsMiXer estimated 98 causal genetic variants overlapping between the two disorders, with 0.44 concordant directions of effects. Through pleioFDR, we identified a SNP in the TMEM106B gene, which was significantly associated with AD (B=-0.002, p=9.1×10−4) and depression (B=0.007, p=3.2×10−9) in the UK Biobank. This SNP was also associated with several regions of the corpus callosum volume anterior (B>0.024, p<8.6×10−4), third ventricle volume ventricle (B=-0.025, p=5.0×10−6), and inferior temporal gyrus surface area (B=0.017, p=5.3×10−4).DiscussionOur results indicate there is substantial genetic overlap, with mixed directions of effects, between AD and depression. These findings illustrate the value of biostatistical tools that capture such overlap, providing insight into the genetic architectures of these disorders.


2019 ◽  
Vol 3 ◽  
pp. 11 ◽  
Author(s):  
Toni-Kim Clarke ◽  
Yanni Zeng ◽  
Lauren Navrady ◽  
Charley Xia ◽  
Chris Haley ◽  
...  

Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r2=1.1%, p=2.5 x 10-25) and neuroticism (β =0.13, r2=1.9%, p=1.04 x 10-37) at the phenotypic level.  Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r2=0.3%, p=3 x 10-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (rG=0.33, S.E.=0.08 ) and neuroticism (rG=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.


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