Study population

The Child and Adolescent Twin Study in Sweden (CATSS) is an ongoing study targeting all 9-year-old (born after June 1995) and 12-year-old (born before July 1995) twins born in Sweden since July 1992. Parents were contacted for a telephone interview on the twins’ 9th or 12th birthdays. The overall response rate in CATSS is 80% [36]. Analyses comparing non-responders and responders have shown that participating families generally have higher socio-economic status, lower rates of parental psychiatric illness, and child clinical diagnosis for ADHD, autism spectrum disorder (ASD), and learning disabilities [36]. CATSS was approved by the ethics committee at Karolinska Institutet and all participants gave informed consent. The study has been described in detail elsewhere [36].

Genotyping and imputation

A total of 11,551 CATSS twins were genotyped using the Illumina Infinium PsychArray-24 BeadChip. Prior to analysis, stringent quality control (QC) procedures were performed on the genotyped markers and individuals using standardized procedures. After QC, 561,187 genotyped SNPs and 11,081 samples were retained. Genotypes for another 2495 monozygotic (MZ) twins were imputed from their genotyped co-twin, resulting in a sample size of 13,576 samples with genotype data. Details of the QC protocol, imputation, and principal components extraction are presented in supplementary note 1 and Figure S1. CATSS participants without available genetic data differed to those included in the current sample, in that they showed higher levels of parent-reported ADHD symptoms and clinical ADHD diagnosis were more likely to be male, and have parents with lower education levels (see supplementary Table S1).

Polygenic risk scores

ADHD polygenic risk scores (PRS) were generated in CATSS based on summary statistics from what should theoretically be the most powerful discovery sample available : a meta-analysis of the largest GWAS of clinically diagnosed ADHD (20,183 cases, 35,191 controls) [8] and the largest GWAS of ADHD symptoms (17,666 children from population-based samples). Details of the discovery sample are provided in supplementary note 2 [9]. We calculated standardized betas for each SNP, based on available z scores, effective sample size and allele frequency in the discovery GWAS [37]. After excluding individuals with parent-reported cerebral palsy, Down syndrome, brain injury, and chromosomal abnormalities (supplementary Figure S1), ADHD PRS were derived in CATSS from best-guess imputed genotypes across a range of seven p value thresholds (0.00001 ≤ P T ≤ 1). Indels, multi-allelic and symmetric/ambiguous SNPs were excluded. Autosomal SNPs with a minor allele frequency (MAF) ≥ 0.05 and good imputation quality (INFO score) ≥ 0.8 were clumped (linkage disequilibrium threshold R2 > 0.1, ± 1000 kb) using PLINK.v.1.9 [38]. Retained reference alleles were scored across the set of SNPs in PLINK (applying the command–score no-mean-imputation) using standard procedures [39, 40]. In line with previous publications, we used the PRS including SNPs at a threshold of P T ≤ 0.50 for the main analysis [20, 41]. Sensitivity analyses of PRS associations across other p value thresholds are presented in the supplementary materials.

Childhood psychiatric symptoms

Childhood psychiatric symptoms were assessed using the Autism-Tics, ADHD, and Other Comorbidities inventory (A-TAC). A-TAC is a 96-items questionnaire corresponding to DSM-IV definitions of childhood psychiatric disorders. Questions assess lifetime symptoms in relation to same-age peers [42]. We selected the 62 symptoms items measuring inattention (IA), hyperactivity/impulsivity (H/I), ASD, learning difficulties (LD), oppositional defiant disorder (ODD), conduct disorder (CD), depression (DEP) and anxiety (ANX). The A-TAC neurodevelopmental and externalizing scales have been validated, showing strong internal consistency and moderate to strong predictive validity [42,43,44,45]. A-TAC anxiety and depression items have not been validated and were only assessed in twins born from 1992 to 1997. For twins born after 1997, depression symptoms were instead assessed using the Short Mood and Feelings Questionnaire (SMFQ), a 13-item questionnaire measuring child depressive symptoms experienced in the last 2 weeks [46]. Anxiety symptoms were assessed using the Screen for Child Anxiety Related Emotional Disorders (SCARED), a 41-item questionnaire measuring symptoms experienced in the last three months across five anxiety dimensions: panic disorder (PD), generalized anxiety disorder (GAD), separation anxiety disorder (SAD), school anxiety (SA) and social phobia (SP) [47]. SMFQ and SCARED are validated questionnaires, with strong internal consistency and moderate predictive validity for clinical diagnoses [47,48,49,50,51].

All scales were rated according to three response categories: “no” (coded 0), “yes, to some extent” (coded 1), and “yes” (coded 2). As the A-TAC internalizing scales, SCARED, and SMFQ are not directly comparable measures, we used a split-sample approach based on the available internalizing assessments. The final sample sizes with genotype and phenotype data were 6603 (3483 unrelated individuals) for the A-TAC subsample, and 6854 (3634 unrelated individuals) in the SMFQ/SCARED subsample. Based on previous simulation studies, this sample size is more than adequate for estimating complex structural equation models (SEM) and PRS associations [52, 53].

Statistical analyses

We estimated associations between ADHD PRS and ADHD symptom dimensions (IA, H/I) and related neurodevelopmental (ASD, LD), externalizing (ODD, CD), and internalizing (DEP, ANX) symptom dimensions, using confirmatory factor analysis and regression analyses implemented via SEM. Path diagrams of the models are presented by subsample in Fig. 1.

Fig. 1 Path diagram of the general factor model in the A-TAC subsample A and the SMFQ/SCARED subsample B. Path diagram for the general factor models, presented by study subsample. Latent factors are depicted as circles. For clarity, covariates (age, sex and the six principal components) and correlations across latent trait factors are omitted in the above graphical representation. The models consisted of a latent general psychopathology factor (GP) and specific latent trait factors reflecting symptoms dimensions of inattention (IA), hyperactivity/impulsivity (H/I), autism spectrum disorder (ASD), learning difficulties (LD), oppositional defiant disorder (ODD), conduct disorder (CD), depression (DEP), and anxiety (ANX) or panic disorder (PD), generalized anxiety (GAD), separation anxiety (SAD), school anxiety (SA), and social phobia (SP). Variances for all latent factors were fixed at 1. Measured variables are depicted as squares, and include the ADHD PRS and all symptoms items from the Autism-Tics, ADHD, and Other Comorbidities inventory (A-TAC), the Short Mood and Feelings Questionnaire (SMFQ), and the Screen for Child Anxiety Related Emotional Disorders (SCARED). Numbers 1…X indicate the number of symptom items loading onto each specific latent trait factor. β 1 –β x represent the regression coefficients, regressing each latent variable onto ADHD PRS. Note that the corresponding path diagrams for the correlated factors models are identical, excluding the general psychopathology factor Full size image

We first fitted a correlated factors model where symptoms from each subscale were set to load onto a corresponding single latent trait factor. All the latent trait factors were allowed to correlate. In the A-TAC subsample, a correlated factors model with eight latent trait factors was fitted, corresponding to symptoms dimensions of IA, H/I, ASD, LD, ODD, CD, DEP, and ANX. In the SMFQ/SCARED subsample, we fitted a correlated factors model with 12 latent trait factors, including the first six factors outlined above, one DEP factor measured via SMFQ, and five latent anxiety factors corresponding to the SCARED subscales of PD, GAD, SAD, SA, and SP. Previous studies of the SCARED have shown that this five-factor structure has the best psychometric properties for the questionaire [54,55,56].

Second, we fitted a general factor (or bifactor) model, which in addition to the latent trait factors, included a general psychopathology factor. The general factor model quantifies the extent to which covariance among symptom dimensions reflects both a general factor (on which all assessed symptoms load), and a number of specific latent trait factors (on which only a subset of the symptoms load) [57, 58]. Correlations between the specific latent trait factors and the general factor are fixed at zero, whereas correlations between the specific latent trait factors are free to vary.

In both models, the latent factors were regressed on ADHD PRS using SEM, with sex, age and the first six PCs (to account for population stratification) included as covariates. We evaluated whether the models provided a good fit to the underlying data using the comparative fit index, and the root mean square error of approximation (RMSEA) [59]. A likelihood ratio test was used to test whether the exclusion of the general psychopathology factor from the correlated factors model led to a significant decrease in model fit. To account for the non-independence of twin data, family clusters were specified and standard errors were estimated using a sandwich estimator. All models were run using Mplus [60].

Sensitivity analyses

We performed several sensitivity analyses to test the robustness of results from the general factor model (see supplementary note 3 for details). First, to test whether observed associations were driven by ADHD cases, we re-ran analyses excluding children with an ADHD diagnosis (ICD and/or ≥ 8 A-TAC DSM-based symptoms). For completeness, we present the number children with an ICD diagnosis corresponding to the any of the assessed symptoms dimensions in supplementary Table S2. Second, we excluded one twin in every monozygotic pair to confirm that estimates were not inflated by the inclusion of genetically identical individuals. Third, we tested for sex differences in the association between ADHD PRS and the latent factors. Finally, we tested whether ADHD PRS showed similar associations with the latent factors across a range of seven p value thresholds (0.00001 ≤ PT ≤ 1).

Code availability

Computer codes are available upon request from the corresponding author.