Analysis of GWAS top hits in ADHD suggests association to two polymorphisms located in genes expressed in the cerebellum.код для вставкиСкачать
RAPID PUBLICATION Neuropsychiatric Genetics Analysis of GWAS Top Hits in ADHD Suggests Association to Two Polymorphisms Located in Genes Expressed in the Cerebellum Francesca Lantieri,1,2 Joseph T. Glessner,3 Hakon Hakonarson,3,4,5,6 Josephine Elia,1,7* and Marcella Devoto4,6,8,9 1 Department of Child and Adolescent Psychiatry, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania 2 Dipartimento di Scienze della Salute, Sezione Biostatistica, Universita degli Studi di Genova, Genova, Italy 3 Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania 4 5 Division of Pulmonary Medicine, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania 6 Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 7 Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania CCEB, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 8 9 Dipartimento di Medicina Sperimentale, Universita’ La Sapienza, Roma, Italy Received 20 April 2010; Accepted 2 June 2010 Attention deﬁcit/hyperactivity disorder (ADHD) is a common psychiatric disorder inﬂuenced by genetic factors. Several chromosomal regions with potential linkage and candidate genes associations have been reported, but ﬁndings are often inconsistent and non-replicated. The few genome-wide association studies (GWAS) carried out so far differ for study design and phenotypes analyzed, and did not detect any association signiﬁcant at the genome-wide level. In the present study we examined the top SNPs reported in the GWAS by Neale et al.  in an independent cohort. Although our sample size is smaller (415 trios vs. 909), the power was sufﬁcient to conﬁrm the role of candidate markers in ADHD if a true association exists. Two out of 36 top SNPs were signiﬁcant at a ¼ 0.05 in our sample, although none was still signiﬁcant after correction for multiple tests. These two SNPs are both located in genes coding for as yet uncharacterized proteins expressed in the cerebellum, XKR4 in 8q12.1, and FAM190A in 4q22.1. Three other FAM190A SNPs have TDT P-values of <105 in our sample, a level of signiﬁcance only reached by a total of ﬁve SNPs in our genomewide data. While these ﬁndings could be due to chance, we cannot exclude that these markers are indeed associated to disease risk. Remarkably, brain imaging studies have shown reduction of the posterior inferior cerebellar lobules volume of ADHD boys and girls compared to controls, persistent with age and not present in unaffected siblings, suggesting that the cerebellum may be directly related to pathophysiology of ADHD. 2010 Wiley-Liss, Inc. Key words: ADHD; GWAS; cerebellum 2010 Wiley-Liss, Inc. How to Cite this Article: Lantieri F, Glessner JT, Hakonarson H, Elia J, Devoto M. 2010. Analysis of GWAS Top Hits in ADHD Suggests Association to Two Polymorphisms Located in Genes Expressed in the Cerebellum. Am J Med Genet Part B 153B:1127–1133. Attention deﬁcit/hyperactivity disorder (ADHD) is a common psychiatric disorder with a prevalence of 5–10% in school age children [Scahill and Schwab-Stone, 2000], that causes signiﬁcant behavioral and social impairment throughout the life span [Greenﬁeld et al., 1988; Nigg et al., 2005; Barkley et al., 2006]. Family, twin, and adoption studies have demonstrated that ADHD Grant sponsor: NIMH; Grant number: K23MH066275-01; Grant sponsor: National Center for Research Resources; Grant number: UL1-RR-024134; Grant sponsor: The Center for Applied Genomics at The Children’s Hospital of Philadelphia. *Correspondence to: Dr. Josephine Elia, M.D., The Children’s Hospital of Philadelphia, Science Center, 3440 Market St. Suite 200, Philadelphia, PA 19104. E-mail: email@example.com Published online 6 July 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ajmg.b.31110 1127 1128 is inﬂuenced by genetic factors [Thapar et al., 1995], with an overall heritability of 0.76 [Biederman and Faraone, 2005]. The initial search for ADHD genetic risk factors followed the candidate gene approach, focusing on genes involved in neurotransmission, based on evidence from effective pharmacotherapeutic agents [Solanto, 1998], animal models [Viggiano et al., 2003], and neuroimaging studies [Volkow et al., 2007]. Dopaminergic and catecholaminergic pathways have been the most widely studied [Biederman and Faraone, 2005], but also the serotonergic [Biederman and Faraone, 2005] and the glutaminergic [Mick et al., 2008] neurotransmission pathways have been investigated, together with genes regulating vesicular neurotransmission. Although a few conﬁrmed associations have emerged from candidate gene analyses [Brookes et al., 2006; Elia et al., 2009], ﬁndings are often inconsistent and non-replicated across different studies. Genome-wide linkage studies carried out so far have showed several chromosomal regions with potential linkage [Smalley et al., 2002; Bakker et al., 2003; Arcos-Burgos et al., 2004; Ogdie et al., 2004; Hebebrand et al., 2006; Asherson et al., 2008; Romanos et al., 2008; Zhou et al., 2008]. However, none of the loci strongly replicated in additional studies [Bakker et al., 2003; Arcos-Burgos et al., 2004; Hebebrand et al., 2006], and some studies did not identify any signiﬁcant linkage at all [Faraone et al., 2008]. Recently, a few ADHD genome-wide association studies (GWAS) have been attempted [see Franke et al., 2009 for a review]. Two of them used samples collected by the GAIN/IMAGE collaborative group on 958 Caucasian ADHD probands aged 5–17 and their parents [Lasky-Su et al., 2008; Neale et al., 2008], partly overlapping with the samples analyzed in a previous candidate genes study [Brookes et al., 2006]. Neale et al. conducted a family-based GWAS on the categorical deﬁnition of ADHD, using the transmission disequilibrium test (TDT) on 909 complete trios with probands mainly with the combined subtype of ADHD. Although they calculated that their sample size was enough to detect at least one association signiﬁcant at genome-wide level (P < 5 108), for an odds ratio (OR) of 1.3 and a minor allele frequency (MAF) of 0.20, no SNP achieved this level of signiﬁcance indicating that an even larger sample may be required. However, they reported the top 25 SNPs based on the nominal P-values and the top 25 SNPs after genomic correction [Devlin and Roeder, 1999], for a total of 36 SNPs, 14 of which included in both lists. Lasky-Su et al. analyzed the same population treating ADHD symptoms as quantitative phenotypes, generated with two methods: one considering the total count of symptoms and the count of symptoms classiﬁed as hyperactive-impulsive or inattentive obtained through the Parental Account of Childhood Symptoms (PACS) interview, and the other based on the total count of symptoms and the count of hyperactive-impulsive or inattentive symptoms, using the principal component methodology implemented in the FamilyBased Association Test (FBAT-PC) [Lange et al., 2004] applied to the Long Version of Conners’ Parent Rating Scale (CPRS-R:L). For each of the six phenotypes thus generated, additive, dominant and recessive models were applied, for a total of 18 analyses [Lasky-Su et al., 2008]. The two most signiﬁcant markers were located in the CDH13 gene for the phenotype based on all symptoms under the additive genetic model (P-value ¼ 0.005) and in the GF0D1 gene for AMERICAN JOURNAL OF MEDICAL GENETICS PART B the inattentive symptoms under the dominant model, using the FBAT-PC method (P-value ¼ 0.004). A third GWAS was carried out on a pooled sample of 343 adults (18–65 years old) with persistent ADHD and 304 controls of German origin [Lesch et al., 2008]. In all three studies no marker was signiﬁcantly associated at the genome-wide level after appropriate correction for multiple testing, and there was scarce overlap of ﬁndings among them and even across the different analyses carried out by Lasky-Su et al. . At the Children’s Hospital of Philadelphia we are currently recruiting ADHD patients and their parents for an ongoing genetic study on the disorder. Our sample so far comprises 1,286 NorthAmerican individuals of European descent from 428 families, and includes 426 complete trios from 386 nuclear families. Probands were recruited from pediatric and behavioral health centers in the Philadelphia area based on age range of 6–18 years, and KSADS-P IVR interview were administered to the parents and child separately. Details on the recruitment methods are described elsewhere [Elia et al., 2009]. The study was approved by the Institutional Review Boards of The Children’s Hospital of Philadelphia (Protocol #20031-3125) and the University of Pennsylvania School of Medicine (Protocol #707843). This research was performed in compliance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). Given that our study design is similar to the one by Neale et al.  (henceforth referred to simply as Neale), that is a familybased study of ADHD children and adolescents, and that we elected to perform the analysis on the categorical deﬁnition of ADHD based on the DSM-IV criteria, we examined in our sample the association with their 36 top SNPs. Although our current sample size is smaller than the one analyzed by Neale, and thus clearly underpowered for a genome-wide study, it should be sufﬁcient to conﬁrm the role of candidate markers in ADHD if a true association exists. We estimated the statistical power to conﬁrm the association reported by Neale for our ﬁnal sample size of 415 trios, for the values of OR reported by them, and the MAF observed in the HapMap CEU sample for each SNP, using the software Quanto [Gauderman and Morrison, 2006]. Fixing the prevalence of ADHD at 5%, assuming the log-additive genetic risk model, and setting one-side P-value of 0.05 as signiﬁcance threshold, we found that, with the exception of one case with a power of 72%, we had power above 85% for all markers (Table I). Lymphoblastoid cell lines were established from peripheral blood and DNA was extracted at Rutgers University Cell and DNA Repository in New Jersey (RUCDR). The Center for Applied Genomics at The Children’s Hospital of Philadelphia carried out the genotyping using the InﬁniumII HumanHap550 k BeadChip technology (Illumina, San Diego, CA) [Steemers et al., 2006]. Following genotyping, careful data cleaning was carried out checking for gender discrepancies, identity by descent (IBDs), and sample heterozygosity. To ensure genotyping quality we excluded from the analysis ﬁve individuals that had more than 10% of missing genotyping calls. None of the families showed Mendelian error rates of more than 1%. In fact, in all families except one the Mendelian error rate was <0.05%. Following quality control, 374 nuclear families with both parents (338 with one affected child, 31 with two, and 5 with three), for a total of 415 trios (comprising LANTIERI ET AL. 1129 TABLE I. Features of the SNPs Analyzed and Statistical Power to Detect Association in Our Sample Reference SNP rs# rs10807124 rs11221064 rs12505502 rs12772737 rs1427324 rs1539549 rs1541665 rs17673653 rs17689952 rs17722514 rs17754282 rs2295426 rs2311120 rs2323262 rs2439832 rs2678787 rs2747100 rs2939678 rs3782309 rs4241112 rs4913069 rs6570426 rs6657749 rs6919857 rs7187223 rs7528615 rs7657608 rs876477 rs922781 rs9389835 rs9484448 rs957795 rs9608617 rs964647 rs9676447 rs9973180 chr 6 11 4 10 14 13 5 5 4 13 11 14 18 4 15 18 14 8 12 2 5 6 1 6 16 1 4 4 15 6 6 21 22 6 19 18 Physical positiona 33512042 127192523 91787046 116731491 58434446 35349881 170075495 170099172 167158604 89511946 87622650 58446208 50628121 21753534 41566978 26436326 57534739 56409692 26750663 122378682 139525294 141239039 212643136 137182147 81015234 84505551 168390756 20766026 58857636 141312353 141260753 45583147 26236244 88993111 54116059 55105194 Alleles G>A G>C T>G C>G C>T C>T C>T A>T A>G C>T T>G T>C A>G G>A C>T T>C G>C G>A G>T C>T G>A A>T C>T C>T A>G T>C C>T C>T C>G T>C C>T G>A G>C A>T T>C C>T Lists of top SNPs from Neale u c Both c Both Both c u u c Both c c u u c u u Both Both u c c Both c u Both Both Both Both c u Both Both Both u Genotyped or imputed in our sample Imputed Imputed Imputed Imputed Genotyped Imputed Imputed Imputed Imputed Imputed Imputed Genotyped Imputed Genotyped Imputed Imputed Imputed Genotyped Genotyped Imputed Genotyped Imputed Imputed Imputed Imputed Genotyped Genotyped Imputed Imputed Genotyped Genotyped Imputed Imputed Imputed Imputed Imputed No. of polymorphicb SNPs in the 50 kb region around the ref. SNP in HapMapc 28 91 45 44 — 79 115 76 39 161 61 — 53 — 33 79 96 — — 20 — 48 74 32 112 — — 66 95 — — 46 136 60 41 76 No. of SNPs in the 50kb region around the ref. SNP in our dataset 6 16 16 4 — 19 15 15 8 18 17 — 9 — 7 15 16 — — 2 — 11 23 5 23 — — 15 27 — — 12 35 11 11 19 MAFd 0.27 0.16 0.47 0.32 0.27 0.26 0.17 0.17 0.22 0.07 0.19 0.27 0.23 0.19 0.06 0.23 0.58 0.20 0.14 0.25 0.13 0.31 0.17 0.63 0.04 0.35 0.31 0.07 0.54 0.35 0.34 0.08 0.19 0.07 0.07 0.28 ORs from Neale 0.744 1.439 1.303 0.725 0.724 0.731 0.634 0.661 0.722 1.648 1.441 0.710 0.680 0.697 0.657 0.723 0.764 0.722 1.527 0.721 0.648 0.735 0.664 0.749 0.446 0.756 1.356 1.903 1.315 0.731 0.739 0.619 1.376 1.717 2.078 0.749 Power 0.87 0.89 0.85 0.93 0.92 0.89 0.98 0.96 0.89 0.88 0.92 0.94 0.96 0.92 0.72 0.89 0.86 0.87 0.94 0.91 0.94 0.91 0.95 0.89 0.98 0.87 0.90 0.98 0.87 0.93 0.91 0.88 0.85 0.92 1.00 0.86 u, from the uncorrected list; c, from the corrected list; both, present on both lists.aPosition based on the human assembly NCBI B36, hg18. b MAF > 105. c Release 24 and 27 merged together. d For CEU sample from HapMap. 309 male and 106 female cases) were used in the analysis. Of these, 258 patients were combined-ADHD subtype (C), 126 inattentive subtypes (IA), 29 hyperactive (HI), and 2 not speciﬁed. We used all subtypes for the main association analysis, but we also repeated the analysis for the combined subtype alone, since the sample analyzed by Neale was mainly composed of patients with this subtype. Ten SNPs of the 36 reported by Neale were also genotyped in our sample (Table I). We imputed the 26 missing SNPs based on HapMap data from phase I þ II (release 24) merged with phase III (release 2 http://hapmap.ncbi.nlm.nih.gov/). To this aim, we selected from HapMap the SNPs included in the 50 kb genomic region around each SNP reported by Neale not genotyped in our sample (Table I), and used genotypes from the HapMap CEU sample as the reference panel to impute those SNPs in our sample. Imputation was done with Beagle version 3.0.4 [Browning and Browning, 2009], that reports phased genotypes for parents, deriving the sibling genotypes from the haplotypes transmitted from parents. Data obtained in this way were merged to the genotyped SNPs. Following standard SNP data quality procedures (checking for Hardy–Weinberg equilibrium in the parents with P > 105, call rate >90%, MAF >1%, Mendelian error rate <1%), only one SNP 1130 AMERICAN JOURNAL OF MEDICAL GENETICS PART B with MAF lower than 0.01 (rs7187223) and another that was not polymorphic at all (rs9676447), were excluded from the analysis. None of the 36 SNPs investigated showed Mendelian inconsistency in any of the families. At the genome-wide level, only 2,240 SNPs (<0.4%) had Mendelian error rates >1%, conﬁrming the overall good quality of our genotype data. Since our aim was to test association with the same alleles reported by Neale, we evaluated the probability of observing a distortion from random segregation of the 34 remaining SNPs in the same direction as they reported. To this aim we calculated the P-values using the binomial distribution on the transmitted:untransmitted (T:U) allele frequencies calculated by plink [Purcell et al., 2007] with respect to the expected ratio of 50:50 (Table II). Two SNPs were signiﬁcant at a ¼ 0.05 (rs12505502 and rs2939678). After correcting for the number of tests performed no SNP was still signiﬁcant. Overall, odd-ratios ranged between 0.821 and 1.455, and for 15 SNPS were opposite in direction to those reported by Neale (in italics in Table II). Since the sample analyzed by Neale presented a marked excess of children with the combined ADHD subtype, we also performed the same tests on the combined TABLE II. Results for the 36 Reference SNPs From Neale SNP rs10807124 rs11221064 rs12505502 rs12772737 rs1427324 rs1539549 rs1541665 rs17673653 rs17689952 rs17722514 rs17754282 rs2295426 rs2311120 rs2323262 rs2439832 rs2678787 rs2747100 rs2939678 rs3782309 rs4241112 rs4913069 rs6570426 rs6657749 rs6919857 rs7187223 rs7528615 rs7657608 rs876477 rs922781 rs9389835 rs9484448 rs957795 rs9608617 rs964647 rs9676447 rs9973180 A1:A2a A:G C:G G:T G:C T:C T:C T:C T:A G:A T:C G:T C:T G:A A:G T:C C:T G:C A:G T:G T:Cc A:G T:A T:C C:T G:A C:T T:C T:C C:G C:T T:C A:G C:G T:A C:T T:C T:Ua 313:421 305:212 525:403 292:403 301:416 328:449 135:213 160:242 270:374 178:108 294:204 304:428 229:337 207:297 153:233 279:386 391:512 273:378 223:146 277:384 136:210 344:468 184:277 370:494 37:83 353:467 434:320 118:62 493:375 350:479 353:478 117:189 399:290 170:99 106:51 328:438 ORs 0.74 1.44 1.30 0.72 0.72 0.73 0.63 0.66 0.72 1.65 1.44 0.71 0.68 0.70 0.66 0.72 0.76 0.72 1.53 0.72 0.65 0.74 0.66 0.75 0.45 0.76 1.36 1.90 1.32 0.73 0.74 0.62 1.38 1.72 2.08 0.75 Whole sample (415 trios) TDT corrected (uncorrected) P-value (6.71E 05) 3.89E 05 5.62E 05 (6.21E 05) 4.96E 05 3.50E 05 (1.75E 05) 2.88E 05 (1.42E 05) 5.60E 05 (4.32E 05) (4.16E 05) 3.14E 05 4.97E 05 (5.51E 05) 1.00 E 05 1.22 E 05 (6.10E 05) (4.66E 05) 6.36 E 05 (5.66E 05) (3.87E 05) 5.53E 05 (6.11E 05) 6.06E 05 (3.16E 05) (6.94E 05) 2.74 E 05 2.99 E 05 4.79E 05 (2.46E 05) 5.21 E 05 (6.86E 05) 2.96E 05 (3.30E 05) 2.69E 05 (2.99E 05) 5.62E 05 (6.20E 05) 1.58E 05 (7.45E 06) 2.94 E 05 (3.86E 05) 2.96E 05 (3.29E 05) 1.34E 05 (1.50E 05) 1.01E 05 (1.14E 05) (7.05E 05) T:Ua 168:147 114:127 229:194 184:159 163:166 134:118 104:113 106:113 139:144 62:56 105:101 162:167 155:136 110:100 83:78 163:163 215:220 128:156 96:98 164:188 77:78 168:165 81:79 200:195 — 198:170 173:191 43:37 211:205 170:179 166:170 64:44 157:176 57:49 — 168:175 ORsb 1.14 0.90 1.18 1.16 0.98 1.14 0.92 0.94 0.97 1.11 1.04 0.97 1.14 1.10 1.06 1.00 0.98 0.82 0.98 0.87 0.99 1.02 1.03 1.03 — 1.17 0.91 1.16 1.03 0.95 0.98 1.46 0.89 1.16 — 0.96 Binomial P-value 0.89 0.82 0.05 0.92 0.46 0.86 0.29 0.34 0.41 0.32 0.42 0.41 0.88 0.78 0.68 0.52 0.42 0.05 0.59 0.11 0.50 0.59 0.59 0.62 — 0.93 0.84 0.29 0.40 0.33 0.44 0.98 0.86 0.25 — 0.37 C-subtype (257 trios) T:Ua 104:93 65:87 140:115 109:107 99:103 75:73 69:64 71:64 80:94 42:34 71:67 99:102 95:80 66:60 48:50 108:106 131:140 86:94 63:62 116:97 52:48 101:98 53:47 121:120 — 137:108 109:115 22:21 135:118 104:102 102:108 43:29 92:110 36:32 — 108:102 ORsb 1.12 0.75 1.22 1.02 0.96 1.03 1.08 1.11 0.85 1.24 1.06 0.97 1.19 1.10 0.96 1.02 0.94 0.91 1.02 0.84 1.08 1.03 1.13 1.01 — 1.27 0.95 1.05 1.14 1.02 0.94 1.48 0.84 1.13 — 1.06 Binomial P-value 0.80 0.97 0.07 0.58 0.42 0.60 0.70 0.75 0.16 0.21 0.40 0.44 0.89 0.73 0.46 0.58 0.31 0.30 0.50 0.91 0.69 0.61 0.76 0.55 — 0.97 0.68 0.50 0.16 0.58 0.37 0.96 0.91 0.36 — 0.69 Binomial P-values are reported for the allele over-transmitted (or under-transmitted) in Neale et al. .aA1 is the minor allele, while A2 is the major allele for Neale et al. . The transmitted:untransmitted rate refers to the minor allele. b In italics ORs with opposite sign to those found by Neale et al. . c In our sample the minor allele was C (MAF ¼ 0.4365). LANTIERI ET AL. subset only, comprised of 258 trios. In this analysis, no SNP had Pvalues below 0.05, likely due to the small sample size. The smallest P-value of 0.07 was observed for rs12505502. Our results did not show any evident bias in the distribution of association test statistics calculated on the genome-wide data, with a lambda factor of 1.015. However, we also applied the genomic correction, without any difference in the results, as expected (data not shown). The two SNPs signiﬁcant at a ¼ 0.05 in our sample are both located in genes coding for as yet uncharacterized proteins. rs2939678 is in the XKR4 gene (XK, Kell blood group complex subunit-related family, member 4), in 8q12.1, a gene expressed in the cerebellum. In a recent GWAS, a SNP upstream of this gene has been described as associated to the efﬁcacy of the antipsychotic iloperidone in schizophrenia treatment [Lavedan et al., 2009]. rs12505502 is in the FAM190A gene (family with sequence similarity 190 member A), in 4q22.1, a gene highly expressed in ovary and testis but also expressed in brain and cerebellum. Notably, three other FAM190A SNPs, namely rs11097273, rs7683787, and rs1551773, have TDT P-values of <105 in our sample, a level of signiﬁcance only reached by a total of ﬁve SNPs in our genome-wide data. In conclusion, hundreds of genes have been reported as associated to ADHD [Bobb et al., 2005; Khan and Faraone, 2006], but, despite strong evidence for a large genetic contribution, there is a high rate of inconsistency and lack of replication across different studies. These ﬁndings suggest that many genes contribute to the disorder in a modest way and therefore extremely large sample sizes will be necessary to reach a deﬁnite conclusion about their role. Very few GWAS have been published so far, and they generally differ for study design and phenotypes analyzed [Franke et al., 2009]. In the present study we examined the top SNPs reported by Neale et al.  in a group of ADHD trios of European descent, using a similar study design and the same phenotype deﬁnition. We could not unequivocally conﬁrm any of the SNPs among their top signiﬁcant ones as associated to the disorder in our independent sample after correction for multiple tests. However, two markers, rs12505502 and rs2939678, had nominal P-value ¼ 0.05. These SNPs are located in genes whose function is still unknown, but that are expressed in cerebellum, known to play a role in a variety of cognitive processes, such as executive functioning, memory, learning, attention, visuo-spatial regulation, language and behavioralaffective modulation [Baillieux et al., 2008]. Remarkably, the most consistent ﬁndings in ADHD brain imaging studies are decreases in total cerebral volume [Castellanos et al., 1996, 2001, 2002; Filipek et al., 1997; Kates et al., 2002; Mostofsky et al., 2002; Hill et al., 2003; Durston et al., 2004], and in posterior inferior cerebellar vermis (lobes VIII–X) volume [Castellanos et al., 1996, 2001, 2002; Berquin et al., 1998; Bussing et al., 2002; Hill et al., 2003; Durston et al., 2004]. The reduction of the posterior inferior lobes of the vermis, conﬁrmed in both males and females [Castellanos et al., 2001, 2002; Hill et al., 2003], persisted with age in a longitudinal study that scanned each patient one to four times between ages 5 and 18 and was found to correlate with parent- and clinician-rated severity measures of ADHD [Castellanos et al., 2002]. The only imaging study that also included unaffected siblings of ADHD boys reported intracranial volume reduction as well as reductions in right prefrontal gray matter and left occipital gray and 1131 white matter also in the unaffected siblings. The right cerebellar volume was the only measure reduced in the ADHD children but not in the unaffected siblings [Durston et al., 2004], suggesting that the cerebellum may be more directly related to pathophysiology. While the ﬁnding of a genetic association with SNPs located in genes expressed in the cerebellum may be due to chance, we cannot exclude that these markers are indeed associated to the disease albeit exerting a low risk. ACKNOWLEDGMENTS This research is supported by NIMH (K23MH066275-01), UL1-RR -024134 from the National Center for Research Resources, and The Center for Applied Genomics at The Children’s Hospital of Philadelphia. We want to thank all the families that have participated, the referring clinicians, our research coordinator Tamika Scott, and the technical staff in the Center for Applied Genomics at The Children’s Hospital of Philadelphia for generating the genotypes used in this study. REFERENCES Arcos-Burgos M, Castellanos FX, Pineda D, Lopera F, Palacio JD, Palacio LG, Rapoport JL, Berg K, Bailey-Wilson JE, Muenke M. 2004. Attention-deﬁcit/hyperactivity disorder in a population isolate: Linkage to loci at 4q13.2, 5q33.3, 11q22, and 17p11. Am J Hum Genet 75:998–1014. 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