Polygenic scores for smoking and educational attainment have independent influences on academic success and adjustment in adolescence and educational attainment in adulthood

Dissecting the polygenic contribution of attention-deficit/hyperactivity disorder and autism spectrum disorder on school performance by their relationship with educational attainment

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) are strongly associated with educational attainment (EA), but little is known about their genetic relationship with school performance and whether these links are explained, in part, by the genetic liability of EA. Here, we aim to dissect the polygenic contribution of ADHD and ASD to school performance, early manifestation of psychopathology and other psychiatric disorders and related traits by their relationship with EA. To do so, we tested the association of polygenic scores for EA, ADHD and ASD with school performance, assessed whether the contribution of the genetic liability of ADHD and ASD to school performance is influenced by the genetic liability of EA, and evaluated the role of EA in the genetic overlap between ADHD and ASD with early manifestation of psychopathology and other psychiatric disorders and related traits in a sample of 4,278 school-age children. The genetic liability for ADHD and ASD dissected by their relationship with EA show differences in their association with school performance and early manifestation of psychopathology, partly mediated by ADHD and ASD symptoms. Genetic variation with concordant effects in ASD and EA contributes to better school performance, while the genetic variation with discordant effects in ADHD or ASD and EA is associated with poor school performance and higher rates of emotional and behavioral problems. Our results strongly support the usage of the genetic load for EA to dissect the genetic and phenotypic heterogeneity of ADHD and ASD, which could help to fill the gap of knowledge of mechanisms underlying educational outcomes.

Associations between polygenic scores for cognitive and non-cognitive factors of educational attainment and measures of behavior, psychopathology, and neuroimaging in the adolescent brain cognitive development study

BACKGROUND

Educational attainment (EduA) is correlated with life outcomes, and EduA itself is influenced by both cognitive and non-cognitive factors. A recent study performed a 'genome-wide association study (GWAS) by subtraction,' subtracting genetic effects for cognitive performance from an educational attainment GWAS to create orthogonal 'cognitive' and 'non-cognitive' factors. These cognitive and non-cognitive factors showed associations with behavioral health outcomes in adults; however, whether these correlations are present during childhood is unclear.

METHODS

Using data from up to 5517 youth (ages 9-11) of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and cognition, risk tolerance, decision-making & personality, substance initiation, psychopathology, and brain structure (e.g. volume, fractional anisotropy [FA]). Within-sibling analyses estimated whether observed genetic associations may be consistent with direct genetic effects.

RESULTS

Both PGSs were associated with greater cognition and lower impulsivity, drive, and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk tolerance, increased odds of choosing delayed reward, and decreased likelihood of ADHD and bipolar disorder; the non-cognitive PGS was associated with lack of perseverance and reward responsiveness. Cognitive PGS were more strongly associated with larger regional cortical volumes; non-cognitive PGS were more strongly associated with higher FA. All associations were characterized by small effects.

CONCLUSIONS

While the small sizes of these associations suggest that they are not effective for prediction within individuals, cognitive and non-cognitive PGS show unique associations with phenotypes in childhood at the population level.

Does Tobacco Smoking Increase Social Isolation? A Mendelian Randomization Study

In this study, we aimed to investigate the causal effect of smoking on social isolation among older adults in England. Data from older adults of European ancestry who participated in 1 or more waves of the English Longitudinal Study of Ageing, from wave 1 (2002/2003) to wave 9 (2018/2019), were analyzed (n = 43,687 observations from 7,008 individuals; mean age = 68.50 years). The effect of current smoking on social isolation (ranging from 0 to 5) was estimated by 2-stage least squares regression using a polygenic score (PGS) for smoking cessation as the instrument. A low PGS for smoking cessation predicted current smoking (per 1-standard-deviation lower PGS, coefficient = 0.023, 95% confidence interval (CI): 0.015, 0.030; F = 36.420). The second-stage regression showed that current smoking increased social isolation by 1.205 points (95% CI: 0.308, 2.101). The association was larger for persons with higher socioeconomic backgrounds: 2.501 (95% CI: -0.024, 5.026) and 0.696 (95% CI: -0.294, 1.686) for those with higher and lower educational levels, respectively. This study showed that current smoking instrumented by a PGS for smoking cessation was associated with social isolation. Assuming that the PGS served as a valid instrument in this study, the findings support an effect of smoking on social isolation.

Disentangling the interplay between genes, cognitive skills, and educational level in adolescent and young adult smoking - The TRAILS study

Recent studies suggest that smoking and lower educational attainment may have genetic influences in common. However, little is known about the mechanisms through which genetics contributes to educational inequalities in adolescent and young adult smoking. Common genetic liabilities may underlie cognitive skills associated with both smoking and education, such as IQ and effortful control, in line with indirect health-related selection explanations. Additionally, by affecting cognitive skills, genes may predict educational trajectories and hereby adolescents' social context, which may be associated with smoking, consistent with social causation explanations. Using data from the Dutch TRAILS Study (N = 1581), we estimated the extent to which polygenic scores (PGSs) for ever smoking regularly (PGSSMOK) and years of education (PGSEDU) predict IQ and effortful control, measured around age 11, and whether these cognitive skills then act as shared predictors of smoking and educational level around age 16, 19, 22, and 26. Second, we assessed if educational level mediated associations between PGSs and smoking. Both PGSs were associated with lower effortful control, and PGSEDU also with lower IQ. Lower IQ and effortful control, in turn, predicted having a lower educational level. However, neither of these cognitive skills were directly associated with smoking behaviour after controlling for covariates and PGSs. This suggests that IQ and effortful control are not shared predictors of smoking and education (i.e., no indirect health-related selection related to cognitive skills). Instead, PGSSMOK and PGSEDU, partly through their associations with lower cognitive skills, predicted selection into a lower educational track, which in turn was associated with more smoking, in line with social causation explanations. Our findings suggest that educational differences in the social context contribute to associations between genetic liabilities and educational inequalities in smoking.

Timing of lifespan influences on brain and cognition

Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.

Educational Attainment Polygenic Scores: Examining Evidence for Gene-Environment Interplay with Adolescent Alcohol, Tobacco and Cannabis Use

Genes associated with educational attainment may be related to or interact with adolescent alcohol, tobacco and cannabis use. Potential gene-environment interplay between educational attainment polygenic scores (EA-PGS) and adolescent alcohol, tobacco, and cannabis use was evaluated with a series of regression models fitted to data from a sample of 1871 adult Australian twins. All models controlled for age, age2, cohort, sex and genetic ancestry as fixed effects, and a genetic relatedness matrix was included as a random effect. Although there was no evidence that adolescent alcohol, tobacco or cannabis use interacted with EA-PGS to influence educational attainment, there was a significant, positive gene-environment correlation with adolescent alcohol use at all PGS thresholds (ps <.02). Higher EA-PGS were associated with an increased likelihood of using alcohol as an adolescent (ΔR2 ranged from 0.5% to 1.1%). The positive gene-environment correlation suggests a complex relationship between educational attainment and alcohol use that is due to common genetic factors.