Research Review: A guide to computing and implementing polygenic scores in developmental research

Associations between polygenic risk scores for cardiometabolic phenotypes and adolescent depression and body dissatisfaction

BACKGROUND

Adolescents with elevated body mass index (BMI) are at an increased risk for depression and body dissatisfaction. Type 2 diabetes (T2D) is an established risk factor for depression. However, shared genetic risk between cardiometabolic conditions and mental health outcomes remains understudied in youth.

METHODS

The current study examined associations between polygenic risk scores (PRS) for BMI and T2D, and symptoms of depression and body dissatisfaction, in a sample of 827 community adolescents (Mage = 13.63, SDage = 1.01; 76% girls). BMI, depressive symptoms, and body dissatisfaction were assessed using validated self-report questionnaires.

RESULTS

BMI-PRS was associated with phenotypic BMI (β = 0.24, p < 0.001) and body dissatisfaction (β = 0.17, p < 0.001), but not with depressive symptoms. The association between BMI-PRS and body dissatisfaction was significantly mediated by BMI (indirect effect = 0.10, CI [0.07-0.13]). T2D-PRS was not associated with depression or body dissatisfaction.

CONCLUSIONS

The results suggest phenotypic BMI may largely explain the association between genetic risk for elevated BMI and body dissatisfaction in adolescents. Further research on age-specific genetic effects is needed, as summary statistics from adult discovery samples may have limited utility in youth.

IMPACT

The association between genetic risk for elevated BMI and body dissatisfaction in adolescents may be largely explained by phenotypic BMI, indicating a potential pathway through which genetic predisposition influences body image perception. Furthermore, age-specific genetic research is needed to understand the unique influences on health outcomes during adolescence. By identifying BMI as a potential mediator in the association between genetic risk for elevated BMI and body dissatisfaction, the current findings offer insights that could inform interventions targeting body image concerns and mental health in this population.

Growing Up Together in Society (GUTS): A team science effort to predict societal trajectories in adolescence and young adulthood

Our society faces a great diversity of opportunities for youth. The 10-year Growing Up Together in Society (GUTS) program has the long-term goal to understand which combination of measures best predict societal trajectories, such as school success, mental health, well-being, and developing a sense of belonging in society. Our leading hypothesis is that self-regulation is key to how adolescents successfully navigate the demands of contemporary society. We aim to test these questions using socio-economic, questionnaire (including experience sampling methods), behavioral, brain (fMRI, sMRI, EEG), hormonal, and genetic measures in four large cohorts including adolescents and young adults. Two cohorts are designed as test and replication cohorts to test the developmental trajectory of self-regulation, including adolescents of different socioeconomic status thereby bridging individual, family, and societal perspectives. The third cohort consists of an entire social network to examine how neural and self-regulatory development influences and is influenced by whom adolescents and young adults choose to interact with. The fourth cohort includes youth with early signs of antisocial and delinquent behavior to understand patterns of societal development in individuals at the extreme ends of self-regulation and societal participation, and examines pathways into and out of delinquency. We will complement the newly collected cohorts with data from existing large-scale population-based and case-control cohorts. The study is embedded in a transdisciplinary approach that engages stakeholders throughout the design stage, with a strong focus on citizen science and youth participation in study design, data collection, and interpretation of results, to ensure optimal translation to youth in society.

Alcohol Use Disorder Polygenic Risk Scores and Trajectories of Early Adolescent Externalizing Behaviors: Examining the Role of Parenting and Family Conflict in the Racially/Ethnically Diverse ABCD Sample

This study examined the independent and interactive effects of alcohol use disorder genome-wide polygenic scores (AUD-PGS) and parenting and family conflict on early adolescent externalizing behaviors. Data were drawn from White (N = 6181, 46.9% female), Black/African American (N = 1784, 50.1% female), and Hispanic/Latinx (N = 2410, 48.0% female) youth from the adolescent brain cognitive development Study (ABCD). Parents reported on youth externalizing behaviors at baseline (T1, age 9/10), 1-year (T2, age 10/11) and 2-year (T3, age 11/12) assessments. Youth reported on parenting and family environment at T1 and provided saliva or blood samples for genotyping. Results from latent growth models indicated that in general externalizing behaviors decreased from T1 to T3. Across all groups, higher family conflict was associated with more externalizing behaviors at T1, and we did not find significant associations between parental monitoring and early adolescent externalizing behaviors. Parental acceptance was associated with lower externalizing behaviors among White and Hispanic youth, but not among Black youth. Results indicated no significant main effect of AUD-PGS nor interaction effect between AUD-PGS and family variables on early adolescent externalizing behaviors. Post hoc exploratory analysis uncovered an interaction between AUD-PGS and parental acceptance such that AUD-PGS was positively associated with externalizing rule-breaking behaviors among Hispanic youth, but only when parental acceptance was very low. Findings highlight the important role of family conflict and parental acceptance in externalizing behaviors among early adolescents, and emphasize the need to examine other developmental pathways underlying genetic risk for AUD across diverse populations.

Individual Trajectories of Depressive Symptoms Within Racially-Ethnically Diverse Youth: Associations with Polygenic Risk for Depression and Substance Use Intent and Perceived Harm

There are distinct individual trajectories of depressive symptoms across adolescence which are most often differentiated into low, moderate/stable, and high/increasing groups. Research has found genetic predisposition for depression associated with trajectories characterized by greater depressive symptoms. However, the majority of this research has been conducted in White youth. Moreover, a separate literature indicates that trajectories with elevated depressive symptoms can result in substance use. It is critical to identify depressive symptom trajectories, genetic predictors, and substance use outcomes in diverse samples in early adolescence to understand distinct processes and convey equitable benefits from research. Using data from the Adolescent Cognitive Brain Development Study (ABCD), we examined parent-reported depressive symptom trajectories within Black/African American (AA, n = 1783), White/European American (EA, n = 6179), and Hispanic/Latinx (LX, n = 2410) youth across four annual assessments in early adolescence (age 9-10 to 12-13). We examined racially/ethnically aligned polygenic scores (Dep-PGS) as predictors of trajectories as well as substance use intent and perceived substance use harm as outcomes at age 12-13. Differential trajectories were found in AA, EA, and LX youth but low and high trajectories were represented within each group. In EA youth, greater Dep-PGS were broadly associated with membership in trajectories with greater depressive symptoms. Genetic effects were not significant in AA and LX youth. In AA youth, membership in the low trajectory was associated with greater substance use intent. In EA youth, membership in trajectories with higher depressive symptoms was associated with greater substance use intent and less perceived harm. There were no associations between trajectories and substance use intent and perceived harm in LX youth. These findings indicate that there are distinct depressive symptom trajectories in AA, EA, and LX youth, accompanied by unique associations with genetic predisposition for depressive symptoms and substance use outcomes.

Transdiagnostic biomarkers of mental illness across the lifespan: A systematic review examining the genetic and neural correlates of latent transdiagnostic dimensions of psychopathology in the general population

This systematic review synthesizes evidence from research investigating the biological correlates of latent transdiagnostic dimensions of psychopathology (e.g., the p-factor, internalizing, externalizing) across the lifespan. Eligibility criteria captured genomic and neuroimaging studies investigating general and/or specific dimensions in general population samples across all age groups. MEDLINE, Embase, and PsycINFO were searched for relevant studies published up to March 2023 and 46 studies were selected for inclusion. The results revealed several biological correlates consistently associated with transdiagnostic dimensions of psychopathology, including polygenic scores for ADHD and neuroticism, global surface area and global gray matter volume. Shared and unique associations between symptom dimensions are highlighted, as are potential age-specific differences in biological associations. Findings are interpreted with reference to key methodological differences across studies. The included studies provide compelling evidence that the general dimension of psychopathology reflects common underlying genetic and neurobiological vulnerabilities that are shared across diverse manifestations of mental illness. Substantive interpretations of general psychopathology in the context of genetic and neurobiological evidence are discussed.

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.

Something old, something new - can adding genomic data to family studies advance our understanding of the impact of nature and nurture on mental health? Commentary on McAdams et al. (2023)

In their annual research review, McAdams, Cheesman, and Ahmadzadeh (2023) provide a thorough overview of how the use of novel genetically informative approaches can increase our knowledge about the intergenerational transmission of psychopathology. Many JCPP readers will already be familiar with genetically sensitive family-based designs, such as twin and adoption studies, as well as with newer molecular-genetic approaches, such as polygenic-score studies. McAdams et al.'s (2023) review discusses the innovative combination of family-based and molecular-genetic methods, and what this combination can reveal about developmental psychopathology.

Epigenetics applied to child and adolescent mental health: Progress, challenges and opportunities

Background

Epigenetic processes are fast emerging as a promising molecular system in the search for both biomarkers and mechanisms underlying human health and disease risk, including psychopathology.

Methods

In this review, we discuss the application of epigenetics (specifically DNA methylation) to research in child and adolescent mental health, with a focus on the use of developmentally sensitive datasets, such as prospective, population-based cohorts. We look back at lessons learned to date, highlight current developments in the field and areas of priority for future research. We also reflect on why epigenetic research on child and adolescent mental health currently lags behind other areas of epigenetic research and what we can do to overcome existing barriers.

Results

To move the field forward, we advocate for the need of large-scale, harmonized, collaborative efforts that explicitly account for the time-varying nature of epigenetic and mental health data across development.

Conclusion

We conclude with a perspective on what the future may hold in terms of translational applications as more robust signals emerge from epigenetic research on child and adolescent mental health.

The next 10 years of behavioural genomic research

Background

The explosion caused by the fusion of quantitative genetics and molecular genetics will transform behavioural genetic research in child and adolescent psychology and psychiatry.

Methods

Although the fallout has not yet settled, the goal of this paper is to predict the next 10 years of research in what could be called behavioural genomics.

Results

I focus on three research directions: the genetic architecture of psychopathology, causal modelling of gene-environment interplay, and the use of DNA as an early warning system.

Conclusion

Eventually, whole-genome sequencing will be available for all newborns, which means that behavioural genomics could potentially be applied ubiquitously in research and clinical practice.

Research Review: How to interpret associations between polygenic scores, environmental risks, and phenotypes

BACKGROUND

Genetic influences are ubiquitous as virtually all phenotypes and most exposures typically classified as environmental have been found to be heritable. A polygenic score summarises the associations between millions of genetic variants and an outcome in a single value for each individual. Ever lowering costs have enabled the genotyping of many samples relevant to child psychology and psychiatry research, including cohort studies, leading to the proliferation of polygenic score studies. It is tempting to assume that associations detected between polygenic scores and phenotypes in those studies only reflect genetic effects. However, such associations can reflect many pathways (e.g. via environmental mediation) and biases.

METHODS

Here, we provide a comprehensive overview of the many reasons why associations between polygenic scores, environmental exposures, and phenotypes exist. We include formal representations of common analyses in polygenic score studies using structural equation modelling. We derive biases, provide illustrative empirical examples and, when possible, mention steps that can be taken to alleviate those biases.

RESULTS

Structural equation models and derivations show the many complexities arising from jointly modelling polygenic scores with environmental exposures and phenotypes. Counter-intuitive examples include that: (a) associations between polygenic scores and phenotypes may exist even in the absence of direct genetic effects; (b) associations between child polygenic scores and environmental exposures can exist in the absence of evocative/active gene-environment correlations; and (c) adjusting an exposure-outcome association for a polygenic score can increase rather than decrease bias.

CONCLUSIONS

Strikingly, using polygenic scores may, in some cases, lead to more bias than not using them. Appropriately conducting and interpreting polygenic score studies thus requires researchers in child psychology and psychiatry and beyond to be versed in both epidemiological and genetic methods or build on interdisciplinary collaborations.

Editorial: Does the polygenic revolution herald a watershed in the study of GE interplay in developmental psychopathology? Some considerations for the Special Issue reader

The primary goal motivating the scientific field of Developmental Psychopathology is to discover why some individuals develop mental health and neuro-developmental difficulties while others do not. This is not simply a 'blue skies' preoccupation: the underlying hope, of course, is to translate such discoveries to the benefit of individuals, families and communities, reducing poor outcomes for those at risk and - in the best case scenario - ensuring that they thrive. A core tenet of the bio-psycho-social framework within which this field of enquiry operates is that children's difficulties are determined by the interplay of predisposing genetic risk and resilience factors and the environments and experiences to which individuals are exposed. From this perspective, understanding gene-environment (GE) interplay is a necessary condition for explaining and, as importantly predicting, why one individual is at risk while another is not. If we believe this, then the risk calculators designed to show who will and will not get a particular disorder - all the rage at the moment - are doomed to fail until they can go beyond modelling the main effects of genes and environments, and reliably estimate GE processes too. Despite significant progress, we remain a considerable way off cracking this problem.

Commentary: Will genomics revolutionise research on gene-environment interplay?

The synthesis of quantitative genetics and molecular genetics is transforming research in the behavioural sciences. The ability to measure inherited DNA differences directly has led to polygenic scores and to new methods to estimate heritability and genetic correlations. This issue provides examples of how these advances can be appllied to research on gene-environment interplay in developmental psychopathology.