Neurogenetic mechanisms of risk for ADHD: Examining associations of polygenic scores and brain volumes in a population cohort.

BACKGROUND: ADHD polygenic scores (PGSs) have been previously shown to predict ADHD outcomes in several studies. However, ADHD PGSs are typically correlated with ADHD but not necessarily reflective of causal mechanisms. More research is needed to elucidate the neurobiological mechanisms underlying ADHD. We leveraged functional annotation information into an ADHD PGS to (1) improve the prediction performance over a non-annotated ADHD PGS and (2) test whether volumetric variation in brain regions putatively associated with ADHD mediate the association between PGSs and ADHD outcomes. METHODS: Data were from the Philadelphia Neurodevelopmental Cohort (N = 555). Multiple mediation models were tested to examine the indirect effects of two ADHD PGSs-one using a traditional computation involving clumping and thresholding and another using a functionally annotated approach (i.e., AnnoPred)-on ADHD inattention (IA) and hyperactivity-impulsivity (HI) symptoms, via gray matter volumes in the cingulate gyrus, angular gyrus, caudate, dorsolateral prefrontal cortex (DLPFC), and inferior temporal lobe. RESULTS: A direct effect was detected between the AnnoPred ADHD PGS and IA symptoms in adolescents. No indirect effects via brain volumes were detected for either IA or HI symptoms. However, both ADHD PGSs were negatively associated with the DLPFC. CONCLUSIONS: The AnnoPred ADHD PGS was a more developmentally specific predictor of adolescent IA symptoms compared to the traditional ADHD PGS. However, brain volumes did not mediate the effects of either a traditional or AnnoPred ADHD PGS on ADHD symptoms, suggesting that we may still be underpowered in clarifying brain-based biomarkers for ADHD using genetic measures.

A Gene-Environment Interaction Study of Polygenic Scores and Maltreatment on Childhood ADHD.

This study explored whether maltreatment moderates the association of polygenic risk for ADHD. Because individuals with low polygenic scores (PGS) for ADHD were previously shown to have better than expected functional outcomes (i.e., cognitive, mental health, social-emotional) than individuals with middle or high ADHD PGS, we hypothesized low ADHD PGS may confer a protective effect from maltreatment in the development of ADHD. Data were from participants with phenotypic and genotypic data in the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 4,722). ADHD PGS were generated from the most recent genome-wide association study on ADHD and categorized into three groups (i.e., low, medium, high) using empirically determined cut-points. A maltreatment factor score was derived from five forms of self-reported maltreatment experiences prior to age 18. ADHD PGS and maltreatment were positively associated with ADHD symptoms, as expected. However, no interaction between ADHD PGS and maltreatment on ADHD symptoms was detected. Despite the increase in predictive power afforded by PGS, the lack of an interaction between ADHD PGS and maltreatment on ADHD symptoms converges with an emerging body of PGS studies that have also failed to detect PGS-environment interplay in mental disorders. We discuss possible reasons for this pattern of results and offer alternative methods for future research in understanding gene-environment interactions.

Childhood exposure to interpersonal violence is associated with greater transdiagnostic integration of psychiatric symptoms.

BACKGROUND: Childhood exposure to interpersonal violence (IPV) may be linked to distinct manifestations of mental illness, yet the nature of this change remains poorly understood. Network analysis can provide unique insights by contrasting the interrelatedness of symptoms underlying psychopathology across exposed and non-exposed youth, with potential clinical implications for a treatment-resistant population. We anticipated marked differences in symptom associations among IPV-exposed youth, particularly in terms of 'hub' symptoms holding outsized influence over the network, as well as formation and influence of communities of highly interconnected symptoms. METHODS: Participants from a population-representative sample of youth (n = 4433; ages 11-18 years) completed a comprehensive structured clinical interview assessing mental health symptoms, diagnostic status, and history of violence exposure. Network analytic methods were used to model the pattern of associations between symptoms, quantify differences across diagnosed youth with (IPV+) and without (IPV-) IPV exposure, and identify transdiagnostic 'bridge' symptoms linking multiple disorders. RESULTS: Symptoms organized into six 'disorder' communities (e.g. Intrusive Thoughts/Sensations, Depression, Anxiety), that exhibited considerably greater interconnectivity in IPV+ youth. Five symptoms emerged in IPV+ youth as highly trafficked 'bridges' between symptom communities (11 in IPV- youth). CONCLUSION: IPV exposure may alter mutually reinforcing symptom co-occurrence in youth, thus contributing to greater psychiatric comorbidity and treatment resistance. The presence of a condensed and unique set of bridge symptoms suggests trauma-enriched nodes which could be therapeutically targeted to improve outcomes in violence-exposed youth.

Polygenic Scores for ADHD: A Meta-Analysis.

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder that is known to have a polygenic (i.e., many genes of individually small effects) architecture. Polygenic scores (PGS), which characterize this polygenicity as a single score for a given individual, are considered the state-of-the-art in psychiatric genetics research. Despite the proliferation of ADHD studies adopting this approach and its clinical implications, remarkably little is known about the predictive utility of PGS in ADHD research to date, given that there have not yet been any systematic or meta-analytic reviews of this rapidly developing literature. We meta-analyzed 12 unique effect sizes from ADHD PGS studies, yielding an N = 40,088. These studies, which included a mixture of large population-based cohorts and case-control samples of predominantly European ancestry, yielded a pooled ADHD PGS effect size of rrandom = 0.201 (95% CI = [0.144, 0.288]) and an rfixed = 0.190 (95% CI = [0.180, 0.199]) in predicting ADHD. In other words, ADHD PGS reliably account for between 3.6% (in the fixed effects model) to 4.0% (in the random effects model) of the variance in broadly defined phenotypic ADHD. Findings provide important insights into the genetics of psychiatric outcomes and raise several key questions about the impact of PGS on psychiatric research moving forward. Our review concludes by providing recommendations for future research directions in the use of PGS, including new methods to account for comorbidities, integrating bioinformatics to elucidate biological pathways, and leveraging PGS to test mechanistic models of ADHD.

Factorial invariance in hierarchical factor models of mental disorders in African American and European American youths.

BACKGROUND: There is converging evidence that mental disorders are more optimally conceptualized in a hierarchical framework (i.e., the Hierarchical Taxonomy of Psychopathology, HiTOP) that transcends the categorical boundaries of the Diagnostic and Statistical Manual of Mental Disorders (DSM). However, the majority of this evidence comes from studies that draw upon predominantly European American or Caucasian populations. Whether a hierarchical conceptualization of mental disorders generalizes across racial-ethnic groups, including for African American (AA) populations, is unclear. METHODS: We tested multidimensional and bifactor models of 15 DSM diagnoses and psychiatric traits in two groups, including AA (n = 3,088) and European American (EA; n = 5,147) youths aged 8-21 from the Philadelphia Neurodevelopmental Cohort (PNC). We also conducted multigroup confirmatory factor analyses to test for factorial invariance between the best fitting AA and EA multidimensional and bifactor models. RESULTS: In the multidimensional model tests, a three-factor model, specifying internalizing, externalizing, and thought dimensions, emerged as the best fitting model for AAs and EAs. In the bifactor model tests, a three-factor model (i.e., internalizing, externalizing, and thought dimensions) that also specified a general factor emerged as the optimal for both AAs and EAs. The general factor accounted for a significant proportion of the covariation between the secondary factors and the individual disorders and traits. Furthermore, both models were factorially invariant, indicating no significant difference in the factor structure of mental disorders between AAs and EAs in PNC. CONCLUSIONS: Results suggest that the hierarchical factor structure of mental disorders may be racial-ethnically robust. This finding has implications for etiological and epidemiological studies focused on racial-ethnic subgroup comparisons, particularly with respect to identifying similarities and differences in prevalence rates or sociodemographic risk factors for mental disorders.