GWAS-MA of persistent ADHD in adults

The GWAS-MA of persistent ADHD in adults included 6,532 adult ADHD cases and 15,874 controls. Minimal population stratification or other systematic biases were detected (LD score regression intercept = 1.01, Fig. S1a). The proportion of heritability of persistent ADHD attributable to common single-nucleotide polymorphisms on the liability scale (SNP-h2) was 0.19 (SE = 0.024), with a nominally significant enrichment in the heritability of variants located in conserved genomic regions (P = 5.18E−03) and in the cell-specific histone mark H3K4me1 (P = 3.17E−02) (Fig. S2a). The gene-based analysis revealed six genes in four loci (ST3GAL3, FRAT1/FRAT2, CGB1, and RNF225/ZNF584) significantly associated with persistent ADHD, with ST3GAL3 being the most significant one (P = 8.72E−07) (Table S2a). The single-marker analysis showed no variants exceeding genome-wide significance, with the most significant signal being rs3923931 (P = 1.69E−07) (Fig. 1a and Table S3a). Similarly, no significant gene sets were identified in the pathway analysis after correction for multiple comparisons (Table S4a [excel file]).

Fig. 1: Manhattan plots of the three GWAS meta-analyses conducted. (a) GWAS-MA of nine cohorts of persistent ADHD in adults, (b) GWAS-MA of ten cohorts of ADHD in childhood, and (c) GWAS-MA of all datasets of ADHD across the lifespan (ADHD in childhood + persistent ADHD). Horizontal lines indicate suggestive (P value = 5.00E−06) and genome-wide significant (P = 5.00E−08) thresholds in a-b, and c, respectively. Full size image

GWAS-MA of ADHD in childhood

To compare the genetic background between persistent ADHD in adults and ADHD in childhood (that may include future remittent and persistent forms of the disorder), we conducted a GWAS-MA on children with ADHD in a total of 10,617 ADHD cases and 16,537 controls. We found no evidence of genomic inflation or population stratification (LD score regression intercept = 1.02, Fig. S1b). The liability-scale SNP-h2 for ADHD in childhood was 0.19 (SE = 0.021), with a significant enrichment in the heritability of variants located in conserved genomic regions after Bonferroni correction (P = 1.21E−06) (Fig. S2b). The gene-based analysis highlighted a significant association between FEZF1 and ADHD in childhood (P = 5.42E−07) (Table S2b). No single genetic variant exceeded genome-wide significance, with the top signal being in rs55686778 (P = 1.67E−07) (Fig. 1b and Table S3b), and no significant gene sets were identified in the pathway analysis after correction for multiple comparisons (Table S4b [excel file]).

Comparison of the genetic background of persistent ADHD in adults and ADHD in childhood

We found a strong genetic correlation between persistent ADHD in adults and ADHD in childhood (rg = 0.81, 95% CI: 0.64–0.97), significantly different from 0 (P = 2.13E−21) and from 1 (P = 0.02). Sign test results provided evidence of a consistent direction of effect of genetic variants associated with ADHD in childhood in persistent ADHD and vice versa (P = 6.60E−04 and P = 4.47E−03, respectively, for variants with P < 5.00E−05 in each dataset) (Table S5). In addition, PRS analyses showed that childhood ADHD PRSs were associated with persistent ADHD at different predefined P value thresholds, with the P = 0.40 threshold (N SNPs = 20,398) explaining the most variance (r2 = 0.0041 and P = 1.20E−27) (Fig. 2a). The quintiles of the PRS built using this threshold showed the expected trend of higher ADHD risk for individuals in higher quintiles (Fig. 2b, Table S6).

Fig. 2: Polygenic risk scores for ADHD in childhood tested on persistent ADHD as target sample. a Bar plot and b quintile plot of meta-analysis odds ratios (OR meta) with 95% confidence intervals for P value threshold = 0.4 using the third quintile as baseline. Full size image

We then tested whether the genetic correlation between persistent ADHD and ADHD in childhood was driven by a subset of children enriched for persistent ADHD-associated alleles using the Breaking Up Heterogeneous Mixture Based On Cross-locus correlations (BUHMBOX) analysis. We found no evidence of subgroup genetic heterogeneity in children, supporting that the sharing of persistent ADHD-associated alleles between children and adults was driven by the whole group of children, with a statistical power of 98.4 and 100% for thresholds of P < 5.00E−05 and P < 1.00E−03, respectively (Table S7).

GWAS-MA of ADHD across the lifespan

Given the strong genetic correlation between persistent ADHD in adults and in childhood, we performed a GWAS-MA of ADHD across the lifespan considering all datasets included in the GWAS-MAs. In total, 17,149 ADHD cases and 32,411 controls were included, and no evidence of genomic inflation or population stratification was found (LD score regression intercept = 1.03, Fig. S1c). The liability-scale SNP-h2 for ADHD across the lifespan was 0.17 (SE = 0.013), and a significant enrichment in the heritability of variants located in conserved genomic regions was observed after Bonferroni correction (P = 1.53E−06) (Fig. S2c). We identified four genome-wide significant variants (Figs. 1c and 3, Table 1a, and Fig. S3) and nine genes in seven loci (FEZF1, DUSP6, ST3GAL3/KDM4A, SEMA6D, C2orf82/GIGYF2, AMN, and FBXL17) significantly associated with ADHD across the lifespan (Table 1b). The most significantly associated locus was on chromosome 6 (index variant rs183882582-T, OR = 1.43 (95% CI: 1.26–1.60), P = 1.57E−08), followed by loci on chromosome 7 (index variant rs3958046), chromosome 4 (index variant rs200721207), and chromosome 3 (index variant rs1920644) (Table 1a, Fig. 3). The gene-set analysis showed a significant association of the “ribonucleoprotein complex” GO term with ADHD across the lifespan (P.adj = 0.021) (Table S4c [excel file]).

Fig. 3: Regional association plots for genome-wide significant loci identified in the GWAS meta-analysis of ADHD across the lifespan. Each plot includes information about the locus, the location and orientation of the genes in the region, the local estimates of recombination rate (in the right corner), and the LD estimates of surrounding SNPs with the index SNP (r2 values are estimated based on 1000 Genomes European reference panel), which is indicated by color (in the upper left corner). Full size image

Table 1 Genome-wide significant loci in the GWAS meta-analysis of ADHD across the lifespan identified through (A) single-variant analysis and (B) gene-based analysis. Full size table

One of the four loci identified in the single-variant analysis also reached genome-wide significance in the previous GWAS-MA on ADHD [6], and all of them showed consistent direction of the effect in that study (Table S8a). Significant loci reported by Demontis et al. [6] showed nominal association with ADHD across the lifespan in our study (Table S8b, c), with single variant hits showing the same direction of the effect (Table S8b).

Analyses conditioning on the index variant for the four ADHD-associated loci did not reveal new independent markers. These four significant loci were functionally characterized by obtaining Bayesian credible sets and searching for expression quantitative trait loci (eQTL) using available data in blood or brain [54, 55]. We found that credible sets for three of the four loci contained at least one eQTL within 1 Mb of the index variant. The credible set on chromosome 6 included the index variant (rs183882582) and rs12197454. This variant, in LD with the index variant (r2 = 0.56), was associated with the expression of RSPH3 in blood and brain (P.adj < 1.65E−05 and P.adj = 2.36E−07, respectively), and with the expression of VIL2 in blood (P.adj = 3.21E−03). The credible set for the second most associated locus on chromosome 7 included 24 variants. The index variant, rs3958046, and other variants in this set, were eQTLs for CADPS2 in brain (maximum P.adj = 2.91E−03). The credible set for the locus on chromosome 4 contained 50 variants, most of them located in or near PCDH7, but no eQTLs were identified. In the credible set for the locus on chromosome 3, which included 98 variants, the index variant, rs1920644, was associated with the expression of KPNA4, IFT80, and KRT8P12 in brain (P.adj = 1.16E−04, P.adj = 1.40E−03, and P.adj = 1.77E−03, respectively). Many other variants in this set were eQTLs for these genes and also for TRIM59, OTOL1, and/or C3orf80 in brain (P.adj < 0.05) (Table S9 [excel file]).

In a summary-data-based Mendelian randomization (SMR) analysis, we used summary data from the GWAS-MA of ADHD across the lifespan and the eQTL data in blood and brain from Westra et al. [54] and Qi et al. [55] to identify gene expression levels associated with ADHD. We found a significant association between ADHD across the lifespan and RMI1 expression in blood (P SMR = 5.36E−06) (Table S10 [in excel]), finding not likely to be an artifact due to LD between eQTL and other ADHD-associated variants given that the P HEIDI was 0.47.

Genetic correlation with other ADHD datasets and phenotypes

We found significant genetic correlations of ADHD in children and adults from the previous GWAS-MA [6] (N = 53,296) and persistent ADHD (rg = 0.85, SE = 0.04, P = 5.49E−99), ADHD in childhood (rg = 0.99, SE = 0.03, P = 5.02E−273), and ADHD across the lifespan (rg = 0.98, SE = 0.01, P < 2.23E−308) (Table S11). When removing sample overlap (LD score genetic covariance intercept = 0.75) and considering only the subset of new samples included in our GWAS-MA on ADHD across the lifespan (N = 7086), a significant genetic correlation was also obtained between their sample and ours (rg = 0.91, SE = 0.35, P = 8.70E−03).

We also observed significant genetic correlations between childhood ADHD symptom scores from a GWAS-MA in a population of children reported by the EAGLE consortium [52] (N = 17,666) and persistent ADHD (rg = 0.65, SE = 0.20, P = 1.10E−03), ADHD in childhood (rg = 0.98, SE = 0.21, P = 2.76E−06), and ADHD across the lifespan (rg = 0.87, SE = 0.19, P = 4.80E−06). Similarly, significant genetic correlations between GWAS of self-reported ADHD status from 23andMe (N = 952,652) and persistent ADHD (rg = 0.75, SE = 0.05, P = 2.49E−45), ADHD in childhood (rg = 0.63, SE = 0.05, P = 1.39E−42), and ADHD across the lifespan (rg = 0.72, SE = 0.04, P = 4.86E−88) were observed (Table S11).

We also estimated the genetic correlation of persistent ADHD in adults, ADHD in childhood, and ADHD across the lifespan with all available phenotypes in LD-hub. Results for 139 phenotypes passed the QC parameters and 41 genetic correlations were significant after Bonferroni correction in both children and adults with persistent ADHD (Table S12 [excel file]). Again, the genetic correlations with ADHD were consistent across the lifespan, with similar patterns found in adulthood and childhood (Pearson’s r = 0.89) (Fig. 4a, Table S12 [excel file]). The strongest genetic correlations with ADHD were found for traits related to academic performance, intelligence, and risk-taking behaviors, including smoking and early pregnancy (Fig. 4b).