scholarly journals Cognitive ability, Socioeconomic Status, and Depressive Symptoms: A Gene-Environment-Trait Correlation

2019 ◽  
Author(s):  
Reut Avinun
Keyword(s):  
Socioeconomic Status ◽  
Depressive Symptoms ◽  
Cognitive Ability ◽  
Genetic Correlation ◽  
Association Studies ◽  
Genetic Influences ◽  
Environmental Mediation ◽  
Gene Environment ◽  
Polygenic Scores ◽  
Two Samples

AbstractPurposeDepression is genetically influenced, but the mechanisms that underlie these influences are largely unknown. Recently, shared genetic influences were found between depression and both cognitive ability and educational attainment (EA). Although genetic influences are often thought to represent direct biological pathways, they can also reflect indirect pathways, including modifiable environmental mediations (gene-environment-trait correlations). Here, I tested whether the genetic correlation between cognitive ability and depressive symptoms partly reflects an environmental mediation involving socioeconomic status (SES).MethodsAs previously done to increase statistical power, and due to their high phenotypic and genetic correlation, EA was used as a proxy for cognitive ability. Summary statistics from a recent genome-wide association study of EA were used to calculate EA polygenic scores. Two independent samples were used: 522 non-Hispanic Caucasian university students from the Duke Neurogenetics Study (277 women, mean age 19.78±1.24 years) and 5,243 white British volunteers (2,669 women, mean age 62.30±7.41 years) from the UK biobank.ResultsMediation analyses in the two samples indicated that higher proxy-cognitive ability polygenic scores predicted higher SES, which in turn predicted lower depressive symptoms.ConclusionCurrent findings suggest that some of the genetic correlates of depressive symptoms depend on an environmental mediation and consequently that modifying the environment, specifically through social and economic policies, can affect the genetic influences on depression. Additionally, these results suggest that findings from genetic association studies of depression may be context-contingent and reflect social, cultural, and economic processes in the examined population.

scholarly journals Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status

2021 ◽  
Author(s):  
Joëlle A. Pasman ◽  
Perline A. Demange ◽  
Sinan Guloksuz ◽  
A. H. M. Willemsen ◽  
Abdel Abdellaoui ◽  
...  
Keyword(s):  
Mental Health ◽  
Socioeconomic Status ◽  
The Netherlands ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Neighborhood Socioeconomic Status ◽  
Gene Environment ◽  
Genome Wide ◽  
Polygenic Scores

AbstractThis study aims to disentangle the contribution of genetic liability, educational attainment (EA), and their overlap and interaction in lifetime smoking. We conducted genome-wide association studies (GWASs) in UK Biobank (N = 394,718) to (i) capture variants for lifetime smoking, (ii) variants for EA, and (iii) variants that contribute to lifetime smoking independently from EA (‘smoking-without-EA’). Based on the GWASs, three polygenic scores (PGSs) were created for individuals from the Netherlands Twin Register (NTR, N = 17,805) and the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2, N = 3090). We tested gene–environment (G × E) interactions between each PGS, neighborhood socioeconomic status (SES) and EA on lifetime smoking. To assess if the PGS effects were specific to smoking or had broader implications, we repeated the analyses with measures of mental health. After subtracting EA effects from the smoking GWAS, the SNP-based heritability decreased from 9.2 to 7.2%. The genetic correlation between smoking and SES characteristics was reduced, whereas overlap with smoking traits was less affected by subtracting EA. The PGSs for smoking, EA, and smoking-without-EA all predicted smoking. For mental health, only the PGS for EA was a reliable predictor. There were suggestions for G × E for some relationships, but there were no clear patterns per PGS type. This study showed that the genetic architecture of smoking has an EA component in addition to other, possibly more direct components. PGSs based on EA and smoking-without-EA had distinct predictive profiles. This study shows how disentangling different models of genetic liability and interplay can contribute to our understanding of the etiology of smoking.

scholarly journals Socioeconomic status and genetic influences on cognitive development

2017 ◽  
Vol 114 (51) ◽  
pp. 13441-13446 ◽  
Author(s):  
David N. Figlio ◽  
Jeremy Freese ◽  
Krzysztof Karbownik ◽  
Jeffrey Roth
Keyword(s):  
Socioeconomic Status ◽  
Cognitive Development ◽  
Test Scores ◽  
Genetic Influence ◽  
Genetic Influences ◽  
Gene Environment ◽  
School Records

Accurate understanding of environmental moderation of genetic influences is vital to advancing the science of cognitive development as well as for designing interventions. One widely reported idea is increasing genetic influence on cognition for children raised in higher socioeconomic status (SES) families, including recent proposals that the pattern is a particularly US phenomenon. We used matched birth and school records from Florida siblings and twins born in 1994–2002 to provide the largest, most population-diverse consideration of this hypothesis to date. We found no evidence of SES moderation of genetic influence on test scores, suggesting that articulating gene-environment interactions for cognition is more complex and elusive than previously supposed.

scholarly journals Comparison of adopted and non-adopted individuals reveals gene-environment interplay for education in the UK Biobank

2019 ◽  
Author(s):  
Rosa Cheesman ◽  
Avina Hunjan ◽  
Jonathan R. I. Coleman ◽  
Yasmin Ahmadzadeh ◽  
Robert Plomin ◽  
...  
Keyword(s):  
Home Environment ◽  
Adoptive Parents ◽  
Genetic Influences ◽  
Uk Biobank ◽  
Rearing Environment ◽  
Individual Level ◽  
Gene Environment ◽  
Polygenic Scores ◽  
The Uk ◽  
Difference Test

AbstractIndividual-level polygenic scores can now explain ∼10% of the variation in number of years of completed education. However, associations between polygenic scores and education capture not only genetic propensity but information about the environment that individuals are exposed to. This is because individuals passively inherit effects of parental genotypes, since their parents typically also provide the rearing environment. In other words, the strong correlation between offspring and parent genotypes results in an association between the offspring genotypes and the rearing environment. This is termed passive gene-environment correlation. We present an approach to test for the extent of passive gene-environment correlation for education without requiring intergenerational data. Specifically, we use information from 6311 individuals in the UK Biobank who were adopted in childhood to compare genetic influence on education between adoptees and non-adopted individuals. Adoptees’ rearing environments are less correlated with their genotypes, because they do not share genes with their adoptive parents. We find that polygenic scores are twice as predictive of years of education in non-adopted individuals compared to adoptees (R2= 0.074 vs 0.037, difference test p= 8.23 × 10−24). We provide another kind of evidence for the influence of parental behaviour on offspring education: individuals in the lowest decile of education polygenic score attain significantly more education if they are adopted, possibly due to educationally supportive adoptive environments. Overall, these results suggest that genetic influences on education are mediated via the home environment. As such, polygenic prediction of educational attainment represents gene-environment correlations just as much as it represents direct genetic effects.

scholarly journals Polygenic predictors of age-related decline in cognitive ability

2019 ◽  
Vol 25 (10) ◽  
pp. 2584-2598 ◽  
Author(s):  
Stuart J. Ritchie ◽  
W. David Hill ◽  
Riccardo E. Marioni ◽  
Gail Davies ◽  
Saskia P. Hagenaars ◽  
...  
Keyword(s):  
Cognitive Ability ◽  
Association Studies ◽  
Cognitive Change ◽  
Genome Wide Association ◽  
General Factor ◽  
Genome Wide Association Studies ◽  
Cognitive Ageing ◽  
Health Lifestyle ◽  
Genome Wide ◽  
Polygenic Scores

AbstractPolygenic scores can be used to distil the knowledge gained in genome-wide association studies for prediction of health, lifestyle, and psychological factors in independent samples. In this preregistered study, we used fourteen polygenic scores to predict variation in cognitive ability level at age 70, and cognitive change from age 70 to age 79, in the longitudinal Lothian Birth Cohort 1936 study. The polygenic scores were created for phenotypes that have been suggested as risk or protective factors for cognitive ageing. Cognitive abilities within older age were indexed using a latent general factor estimated from thirteen varied cognitive tests taken at four waves, each three years apart (initialn = 1091 age 70; finaln = 550 age 79). The general factor indexed over two-thirds of the variance in longitudinal cognitive change. We ran additional analyses using an age-11 intelligence test to index cognitive change from age 11 to age 70. Several polygenic scores were associated with the level of cognitive ability at age-70 baseline (range of standardizedβ-values = –0.178 to 0.302), and the polygenic score for education was associated with cognitive change from childhood to age 70 (standardizedβ = 0.100). No polygenic scores were statistically significantly associated with variation in cognitive change between ages 70 and 79, and effect sizes were small. However,APOEe4 status made a significant prediction of the rate of cognitive decline from age 70 to 79 (standardizedβ = –0.319 for carriers vs. non-carriers). The results suggest that the predictive validity for cognitive ageing of polygenic scores derived from genome-wide association study summary statistics is not yet on a par withAPOEe4, a better-established predictor.

scholarly journals Comparison of Adopted and Nonadopted Individuals Reveals Gene–Environment Interplay for Education in the UK Biobank

2020 ◽  
Vol 31 (5) ◽  
pp. 582-591 ◽  
Author(s):  
Rosa Cheesman ◽  
Avina Hunjan ◽  
Jonathan R. I. Coleman ◽  
Yasmin Ahmadzadeh ◽  
Robert Plomin ◽  
...  
Keyword(s):  
Educational Attainment ◽  
Home Environment ◽  
Family Environment ◽  
Adoptive Parents ◽  
Genetic Influences ◽  
Uk Biobank ◽  
Gene Environment ◽  
Polygenic Scores ◽  
The Family ◽  
The Uk

Polygenic scores now explain approximately 10% of the variation in educational attainment. However, they capture not only genetic propensity but also information about the family environment. This is because of passive gene–environment correlation, whereby the correlation between offspring and parent genotypes results in an association between offspring genotypes and the rearing environment. We measured passive gene–environment correlation using information on 6,311 adoptees in the UK Biobank. Adoptees’ genotypes were less correlated with their rearing environments because they did not share genes with their adoptive parents. We found that polygenic scores were twice as predictive of years of education in nonadopted individuals compared with adoptees ( R2s = .074 vs. .037, p = 8.23 × 10−24). Individuals in the lowest decile of polygenic scores for education attained significantly more education if they were adopted, possibly because of educationally supportive adoptive environments. Overall, these results suggest that genetic influences on education are mediated via the home environment.

scholarly journals Mental Health, Schooling Attainment and Polygenic Scores: Are There Significant Gene-Environment Associations?

2019 ◽  
Author(s):  
Vikesh Amin ◽  
Jere R. Behrman ◽  
Jason M. Fletcher ◽  
Carlos A. Flores ◽  
Alfonso Flores-Lagunes ◽  
...  
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Longitudinal Study ◽  
Statistical Power ◽  
College Education ◽  
Add Health ◽  
Fixed Effect ◽  
Older Individuals ◽  
Gene Environment ◽  
Polygenic Scores

AbstractIt is well-established that (1) there is a large genetic component to mental health, and (2) higher schooling attainment is associated with better mental health. Given these two observations, we test the hypothesis that schooling may attenuate the genetic predisposition to poor mental health. Specifically, we estimate associations between a polygenic score (PGS) for depressive symptoms, schooling attainment and gene-environment (GxE) interactions with mental health (depressive symptoms and depression), in two distinct United States datasets at different adult ages-29 years old in the National Longitudinal Study of Adolescent Health (Add Health) and 54 years old in the Wisconsin Longitudinal Study (WLS). OLS results indicate that the association of the PGS with mental health is similar in Add Health and the WLS, but the association of schooling attainment is much larger in Add Health than in the WLS. There is some suggestive evidence that the association of the PGS with mental health is lower for more-schooled older individuals in the WLS, but there is no evidence of any significant GxE associations in Add Health. Quantile regression estimates also show that in the WLS the GxE associations are statistically significant only in the upper parts of the conditional depressive symptoms score distribution. We assess the robustness of the OLS results to omitted variable bias by using the siblings samples in both datasets to estimate sibling fixed-effect regressions. The sibling fixed-effect results must be qualified, in part due to low statistical power. However, the sibling fixed-effect estimates show that college education is associated with fewer depressive symptoms in both datasets.

scholarly journals Evidence for Recent Polygenic Selection on Educational Attainment Inferred from GWAS Hits

2016 ◽  
Author(s):  
Davide Piffer
Keyword(s):  
Educational Attainment ◽  
Cognitive Ability ◽  
Association Studies ◽  
Meta Analysis ◽  
Significant Snps ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Model Average ◽  
Polygenic Scores ◽  
Polygenic Selection

The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment were used to test a polygenic selection model. Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. The PS of 161 GWAS significant SNPs in a recent meta-analysis was highly correlated to population IQ (r=0.863) and to the polygenic score of four alleles independently associated with general cognitive ability. High  correlations with PISA scores for a subsample were observed.SNP p value predicted correlation to population IQ and factors from the two previous GWAS (r= -.25). Factor analysis produced similar estimates of selection pressure for educational attainment across the three datasets. Polygenic and factor scores computed using the top 20 significant SNPs showed very high correlation to population IQ (r=0.88; 0.9). Similar findings were obtained using 52 populations from another database (ALFRED). The results together constitute a replication of preliminary findings and provide strong evidence for recent diversifying polygenic selection on educational attainment and underlying cognitive ability.

scholarly journals Mental Health, Schooling Attainment and Polygenic Scores: Are There Significant Gene-Environment Associations?

2019 ◽  
Author(s):  
Vikesh Amin ◽  
Jason Fletcher ◽  
Jere Behrman ◽  
Carlos A Flores ◽  
Carlos A Flores ◽  
...  
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Longitudinal Study ◽  
Statistical Power ◽  
College Education ◽  
Add Health ◽  
Fixed Effect ◽  
Older Individuals ◽  
Gene Environment ◽  
Polygenic Scores

It is well-established that (1) there is a large genetic component to mental health, and (2) higher schooling attainment is associated with better mental health. Given these two observations, we test the hypothesis that schooling may attenuate the genetic predisposition to poor mental health. Specifically, we estimate associations between a polygenic score (PGS) for depressive symptoms, schooling attainment and gene-environment (GxE) interactions with mental health (depressive symptoms and depression), in two distinct United States datasets at different adult ages- 29 years old in the National Longitudinal Study of Adolescent Health (Add Health) and 54 years old in the Wisconsin Longitudinal Study (WLS). OLS results indicate that the association of the PGS with mental health is similar in Add Health and the WLS, but the association of schooling attainment is much larger in Add Health than in the WLS. There is some suggestive evidence that the association of the PGS with mental health is lower for more-schooled older individuals in the WLS, but there is no evidence of any significant GxE associations in Add Health. Quantile regression estimates also show that in the WLS the GxE associations are statistically significant only in the upper parts of the conditional depressive symptoms score distribution. We assess the robustness of the OLS results to omitted variable bias by using the siblings samples in both datasets to estimate sibling fixed-effect regressions. The sibling fixed-effect results must be qualified, in part due to low statistical power. However, the sibling fixed-effect estimates show that college education is associated with fewer depressive symptoms in both datasets.

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