NEURAL CORRELATES OF THE DUAL-PATHWAY MODEL FOR ADHD IN ADOLESCENTS FIGURE1 Significa ain clusters asso ciated with ADHD total score in a population-based cohort had reduced ra matter vol umes of both the prefrontal as compared with the [SD=103]comparedwith6.23 mL[SD119:F=6.37,df ter (2.06 mL SD=0.351 com. paredwith2.19mL[SD=0.28]; ng the onata9e14Nl26i000 nificant results with even of005 larger effect sizes were found ster 9.5 95.2 29. 1950 4.32 0.001 asing matchcd-group 0251 No clust supplement). f=1949,p=0.002,95%CI=-0.03,-0.1 ate Phenotypes With mical Correlates of Inattention Selectively In the IMAGEN sample,we found that higher PRS for ADHD was associated with higher ADHD total score at baseline Variability,or Delay Discounting In IMAGEN at baseline,we found that a larger number of working memory errors was CL-02007.95%C002L0109 d0.6 matter volume of the posterior occipital cluster only (r=-0.07,df=1831,p=0.005)(Table 2).Similar to working .06,df=1777,p=0.009,95%C1=-0106,-0.015) memory,increased intrasubject variability was associate lower gray matte Validation using an adHd clinical cohort In the ADHD-200 sample,we confirmed that patients had delay discounting (r=0.05.df=1831.p=0.027(Table 2). ower gray matter volumes in both the prefrontal (3.86 mL SD-167 compared wi 40m king memory ith 1.28 ml SD0.291r928.dfL.49Lp-0.002:,0.019 (Figure2B. ter:r=-0.05,df=1831,p=0.049)(Table2). ese volumetric reductions were nonsignificant in patients ective Associations With Inattention 2 Ye sLate onding ADHD sympto clister:F=1292 dfl 354 00020035 age 14,working memory and delay discountingat age 14were xccipital cluster:F=729,df=1 354.p=0.007:p0.20) selectively associated with inattention (t=2.35, d1505 (Figure 2C-D). and hyperactivity-impulsivity(24. y-204d404.AR2-0002 p=0.042)and gray matter volume of the posterior oc cipital cluster (t=-3.55,df=1404,AR2=0.005,P<0.001) olumes of both clusters,the medicated patients(N56)had associate with inattention 2 years late lumes,and the never-medicated gray matter volumes 848 aip psychiatryonline.oro AmJPsychiatry 177:9.September 2020df=1949, p,0.001, 95% CI=20.03, 20.13; posterior occipital cluster: r=20.07, df=1949, p=0.002, 95% CI=20.03, 20.11). Neuroanatomical Correlates of Inattention Selectively Associated With Working Memory, Intrasubject Variability, or Delay Discounting In IMAGEN at baseline, we found that a larger number of working memory errors was associated with lower gray matter volume of the posterior occipital cluster even after controlling for intrasubject variability and delay discounting (r=20.07, df=1831, p=0.005) (Table 2). Similar to working memory, increased intrasubject variability was associated with lower gray matter volume of the posterior occipital cluster even after controlling for working memory and delay discounting (r=20.05, df=1831, p=0.027) (Table 2). Greater delay discounting rate was associated with lower graymatter volumes of both clusters even after controlling for working memory and intrasubject variability (prefrontal cluster: r=20.05, df=1831, p=0.042; posterior occipital clus￾ter: r=20.05, df=1831, p=0.049) (Table 2). Prospective Associations With Inattention 2 Years Later After controlling for the corresponding ADHD symptom at age 14, working memory and delay discounting at age 14 were selectively associated with inattention (t=2.35, df=1505, p=0.019) and hyperactivity-impulsivity (t=2.24, df=1505, p=0.025) at age 16. In the multivariate regression model, we found that bothworkingmemory (t=2.04, df=1404,DR2 =0.002, p=0.042) and gray matter volume of the posterior oc￾cipital cluster (t=23.55, df=1404, DR2 =0.005, p,0.001) at age 14 were associated with inattention 2 years later (Table 3). Adolescents with persis￾tent ADHD symptoms (N=29) had reduced gray matter vol￾umes of both the prefrontal cluster as compared with the typically developed control subjects (N=1,278; 5.63 mL [SD=1.03] compared with 6.23 mL [SD=1.19]; F=6.37, df=1, 1295, p-perm=0.012; partial eta-squared [h2 p]=0.005) and the posterior occipital clus￾ter (2.06 mL SD=0.35] com￾pared with 2.19mL [SD=0.28]; F=5.12,df=1,1295,p-perm=0.022; h2 p=0.004; see Figure S2 in the online supplement). Sig￾nificant results with even larger effect sizes were found using matched-group com￾parisons (29 compared with 58; see eResults 3 in the online supplement). Associations of Neuropsychological and Neuroanatomical Intermediate Phenotypes With Polygenic Risk for ADHD In the IMAGEN sample, we found that higher PRS for ADHD was associated with higher ADHD total score at baseline (r=0.14, df=1779, p,0.001, 95% CI=0.097, 0.188), more working memory errors ( r=0.07, df=1779, p=0.002, 95% CI=0.026, 0.121), greater delay discounting rate (r=0.06, df=1779, p=0.007, 95% CI=0.021, 0.109), and lower gray matter volume of the posterior occipital cluster only (r=20.06, df=1777, p=0.009, 95% CI=20.106, 20.015). Validation Using an ADHD Clinical Cohort In the ADHD-200 sample, we confirmed that patients had lower gray matter volumes in both the prefrontal (3.86 mL [SD=1.67] compared with 4.40 mL [SD=1.56]; F=12.18, df=1, 491, p,0.001; h2 p=0.024) (Figure 2A) and the posterior oc￾cipital clusters (1.21 mL [SD=0.30] compared with 1.28 mL [SD=0.29]; F=9.28, df=1, 491, p=0.002;h2 p=0.019) (Figure 2B). These volumetric reductions were nonsignificant in patients with the combined subtype (N=129) and significant only in patients with the inattentive subtype (N=96; prefrontal cluster: F=12.92, df=1, 354, p,0.001; h2 p=0.035; posterior occipital cluster: F=7.29, df=1, 354, p=0.007; h2 p=0.20) (Figure 2C–D). Medication Effects In the ADHD-200 sample, we found that the typically de￾veloped control subjects (N=267) had the highest gray matter volumes of both clusters, the medicated patients (N=56) had intermediate gray matter volumes, and the never-medicated patients (N=99) had the lowest gray matter volumes. FIGURE 1. Significant brain clusters associated with ADHD total score in a population-based cohorta a The results were given by a voxel-wise whole brain analysis using the IMAGEN cohort at age 14 (N=1,963). Age, sex, handedness, total intracranial volume, and site were used as covariates. An uncorrected p threshold of 0.001 at voxel level, with a cluster-level family-wise error (FWE) corrected p threshold of 0.05, was applied to identify significant clusters. Two clusters were found to be negatively associated with the ADHD total score: the prefrontal cluster (x=219.5, y=49.5, z=3; 3,357 voxels; peak t=24.29, df=1950, cluster-level pFWE,0.001) and the posterior occipital cortex (x=21.5, y=91.5, z=15; 1,295 voxels; peak t=24.32, df=1950, cluster-level pFWE=0.025). No clusters were found to be positively associated with the ADHD total score. 848 ajp.psychiatryonline.org Am J Psychiatry 177:9, September 2020 NEURAL CORRELATES OF THE DUAL-PATHWAY MODEL FOR ADHD IN ADOLESCENTS