Association study for genes at chromosome 5p13-q11 in attention deficit hyperactivity disorder.код для вставкиСкачать
American Journal of Medical Genetics Part B (Neuropsychiatric Genetics) 147B:600 –605 (2008) Association Study for Genes at Chromosome 5p13-q11 in Attention Deficit Hyperactivity Disorder Nancy Laurin,1 Jonghun Lee,1,2 Abel Ickowicz,3 Tejaswee Pathare,3 Molly Malone,3 Rosemary Tannock,3 James L. Kennedy,4 Russell J. Schachar,3 and Cathy L. Barr1,3* 1 Genetics and Development Division, The Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada Department of Psychiatry, Catholic University of Daegu, Daegu, South Korea 3 Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada 4 Neurogenetics Section, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada 2 Linkage of attention deficit hyperactivity disorder (ADHD) to the short arm-centromeric region of chromosome 5 has been reported in multiple studies. The overlapping region (5p13-q11) contains a number of strong candidate genes for ADHD, based on their role in brain function or neurodevelopment. The aim of this study was to investigate some of the top candidates among these genes in relation to ADHD in a sample of 245 nuclear families from the Toronto area. We investigated the genes for the glial cell-derived neurotropic factor (GDNF), the fibroblast growth factor 10 (FGF10), islet-1 (ISL1), the hyperpolarized potassium channel (HCN1) and the integrin alpha 1 (ITGA1). In addition to these genes, we assessed the 30 region of the SLC1A3 gene, a glutamate transporter implicated in ADHD by a previous association study. A total of 36 polymorphisms were selected across the six genes. We performed family-based association and haplotype analyses. ADHD is a dimensional disorder, with symptoms of inattention and hyperactivity-impulsivity therefore, we also conducted quantitative analysis in relation to symptom scores for both dimensions. Single marker and haplotype analyses yielded little evidence of association for any of the genes tested in this study. Moreover, we were unable to replicate the positive association findings reported for SLC1A3. Our results suggest that these six genes are unlikely to be susceptibility genes in the chromosome 5p13-q11 region and other genes should now be considered for priority study. ß 2007 Wiley-Liss, Inc. KEY WORDS: ADHD; genetics; TDT; 5p13-q11; candidate genes Please cite this article as follows: Laurin N, Lee J, Ickowicz A, Pathare T, Malone M, Tannock R, Kennedy JL, Schachar RJ, Barr CL. 2008. Association Study Grant sponsor: Canadian Institutes of Health Research; Grant numbers: MT14336, MOP14336, MOP64277. *Correspondence to: Cathy L. Barr, Room MP14-302, Genetics and Development Division, The Toronto Western Hospital, 399 Bathurst St., Toronto, Ont., Canada M5T 2S8. E-mail: CBarr@uhnres.utoronto.ca Received 29 May 2007; Accepted 20 September 2007 DOI 10.1002/ajmg.b.30654 ß 2007 Wiley-Liss, Inc. for Genes at Chromosome 5p13-q11 in Attention Deficit Hyperactivity Disorder. Am J Med Genet Part B 147B:600–605. INTRODUCTION Attention deficit hyperactivity disorder (ADHD) is a prevalent behavioral disorder with onset in childhood, affecting between 4% and 12% of children worldwide [Faraone et al., 2003]. The disorder is characterized by age-inappropriate and impairing levels of inattention, hyperactivity, and impulsivity, with symptoms often persisting into adolescence and adulthood [Clarke et al., 2005]. Twin, adoption and family studies have shown that genetic factors substantially contribute to the etiology of ADHD. The heritability estimates according to most twin studies vary between 60% and 90% [Faraone et al., 2005; Thapar et al., 2005]. Involvement of multiple genes with minor to moderate effect sizes was indicated by molecular studies of candidate genes and genome-wide linkage studies. The candidate gene approach has been particularly successful in ADHD. Molecular genetic studies have targeted specific candidate genes based on pharmacologic, animal studies and neuroimaging findings. The genes most consistently found to be associated with ADHD include the dopamine receptors D4 (DRD4) and D5 (DRD5), the dopamine transporter (DAT1), the synaptosomal protein of 25kD (SNAP25) and the serotonin receptor 1B (HTR1B) [Faraone et al., 2005; Thapar et al., 2005], but the odd ratio associated with each of these genes is low [Faraone et al., 2005]. Also, the candidate gene investigations are limited by our understanding of the biological pathways involved in the disorder, as well as by our knowledge of the molecular components of a given pathway. A complementary approach screens the whole genome for regions linked or associated to the condition. The genome scan approach has the potential to identify novel genes through position as opposed to prior knowledge of molecular mechanisms underlying a disorder. Three genome-wide scans on independent samples have been conducted to date using affected sibling pairs (ASPs) [Fisher et al., 2002; Bakker et al., 2003; Hebebrand et al., 2006] and one with multigenerational families from a Colombian population isolate [Arcos-Burgos et al., 2004]. The first scan was conducted on 126 American ASPs and identified nominal evidence for linkage to regions at 5p12, 10q26, 12q23, and 16p13 with maximum multipoint LOD scores (MLS) >1.5 [Fisher et al., 2002]. After extending the sample to 270 ASPs, suggestive evidence of linkage (MLS > 1.0) was still observed for 5p12–13 and 16p13–14 regions, together with novel regions at 6q14, 11q25, 17p11, and 20q13 [Ogdie et al., 2003]. Fine mapping with a further extended sample (308 ASPs) supported linkage at 5p13, 6q12, 16p13, and 17p11 [Ogdie et al., 2004]. An independent genome scan, conducted on Chromosome 5p13-q11 Genes and ADHD 164 Dutch ASPs with ADHD, reported different chromosomal loci (7p13, 9q33, 13q33, and 15q15) [Bakker et al., 2003]. The only overlapping region consisted of the 5p13, demonstrating nominally significant evidence of linkage in the Dutch genome scan. Finally, a third group of investigators performed a genome scans on 155 German ASPs and the chromosome 5p region demonstrated the highest non-parametric multipoint LOD score values [Hebebrand et al., 2006]. They also obtained nominal evidence of linkage (MLS > 1.0) to chromosomes 6q, 7p, 9q, 11q, 12q, and 17p. The results from the population isolate showed some overlaps with one or another of the previous screens with their strongest findings on chromosomes 5q33, 11q22, and 17p11 [Arcos-Burgos et al., 2004]. These data support the presence of several regions containing loci of moderate effect involved in ADHD susceptibility. The detection of suggestive or nominal evidence of linkage in the centromeric region of the chromosome 5 in all scans conducted to date with ADHD ASPs strongly support this region as potentially harboring a susceptibility gene for ADHD. Moreover, when the Dutch and American samples were pooled together, the only detected overlap between the samples was in the 5p13 region [Ogdie et al., 2006]. Interestingly, the marker D5S418 at the core of the linkage region on chromosome 5 yielded a nonparametric two-point MSL > 2.0 in the population isolate [Arcos-Burgos et al., 2004]. The smallest overlapping linkage region on chromosome 5 between the different scans spans approximately 7 cM (15.5 Mb) at 5p13-q11 and is delimited by D5S2105 and D5S1968 (LOD > 1.0 in Ogdie et al. ). This region comprises numerous genes, several of which with potential relevance to ADHD. The aim of the present study was to test six strong candidate genes localized within or nearby the overlapping interval for their involvement in ADHD in a sample of nuclear families from the Toronto area. We selected five genes within the region of interest according to their role in brain functions. These include the genes for glial cell-derived neurotrophic factor (GDNF), the fibroblast growth factor 10 (FGF10), islet-1 (ISL1), the hyperpolarized potassium channel 1 (HCN1), and the integrin alpha 1 (ITGA1). We also included SLC1A3, a glutamate transporter found close to the 50 boundary, that was previously implicated in ADHD [Turic et al., 2005]. We conducted categorical and quantitative TDT analyses for single markers and haplotypes. MATERIALS AND METHODS Study Sample and Diagnostic Assessment The methods of assessment, characteristics of the subjects, and inclusion/exclusion criteria have been described previously, including the instruments used to collect information for the diagnosis of ADHD and co-morbid conditions [Quist et al., 2000; Laurin et al., 2005]. Briefly, probands and their siblings between 7 and 16 years old were included if they met DSM-IV criteria for one of the three ADHD subtypes (predominantly inattentive, predominantly hyperactive/ impulsive, or combined). The study sample was comprised of 245 nuclear families from the Toronto area, including 35 affected siblings. This gave a total of 280 affected children (224 boys and 56 girls). The sample consists of 179 parents-child trios and 66 families in which a single parent was genotyped. The distribution of the affected children among the DSM-IV ADHD subtypes was 14% of the predominantly hyperactive/impulsive subtype, 24% of the predominantly inattentive subtype and 62% of the combined subtype. All children were free of medication for 24 hr before assessment. The majority of the families reported their ethnic background to be of European Caucasian descent, while 10% of families were of other or mixed background, including Chinese, African, Indian, and Native-Canadians. 601 This protocol was approved by the Hospital for Sick Children’s Research Ethics Board and informed written consent or verbal assent was obtained for all participants. For the quantitative analyses, symptom scores based on the nine DSM-IV criteria for both inattention and hyperactivity/ impulsivity dimensions were obtained using semi-structured interviews for parents (Parent Interview for Child Symptoms: PICS-IV) [Ickowicz et al., 2006] and teachers (Teacher Telephone Interview: TTI-IV) [Tannock et al., 2002]. SNPs Selection and Genotyping Information on linkage disequilibrium (LD) obtained from HapMap (CEU population) [TIHMC, 2003] suggest high LD between markers across FGF10, ISL1, GDNF, and HCN1 and a consequently low number of LD blocks for these genes (according to the confidence-interval method of Gabriel et al. ). In order to reduce the number of markers for genotyping, we selected validated SNPs from public databases necessary to capture haplotypes with frequency above 10% for these genes. For ITGA1, the LD pattern is not as strong; therefore, we selected 14 variants across the 166 kb-region of the gene. Finally, in an attempt to replicate Turic et al.  findings for SLC1A3, we also included the three markers implicated in their positive association results. This yielded a total of 36 SNPs that were genotyped in this study. Details on primer and probe sequences are available on request. DNA was isolated from blood lymphocytes using a standard high salt extraction method [Miller et al., 1988]. SNPs were genotyped using the TaqMan 50 nuclease assays for allelic discrimination [Livak, 1999] implemented on a ABI 7900-HT Sequence Detection System1 (Applied Biosystems, Foster City, CA) as described previously [Feng et al., 2005; Laurin et al., 2005]. Statistical Analysis For the analysis of ADHD as a categorical trait, the PDTphase program from the UNPHASED package [Dudbridge, 2003] was used to test for biased transmission of individual marker alleles while the TRANSMIT program [Clayton, 1999] was used for the haplotype analysis, with the robust estimator of variance (-ro option). Quantitative trait TDT analyses, examining the transmission of individual alleles or haplotypes in relation to inattentive and hyperactive symptom scores were carried out using the FBAT program v1.5.5, with the additive model of inheritance and the use of population-based mean scores as offset values to mean centre the trait [Laird et al., 2000; Horvath et al., 2001]. LD between marker alleles and Hardy–Weinberg equilibrium (HWE) were assessed using Haploview v2.03 [Barrett et al., 2005]. No deviation from the HWE was observed at significant level a ¼ 0.01 for any of the marker genotypes. Two-sided P values were used and are not corrected for multiple testing. RESULTS Figure 1 shows the location of the six genes studied within the 15.5 Mb region of chromosome 5 overlapping in the genome-wide screens [Bakker et al., 2003; Ogdie et al., 2004; Hebebrand et al., 2006]. Strong pairwise LD was observed for the markers genotyped in the FGF10, GDNF, ISL1, and HCN1 genes in this sample set, while markers in SCL1A3 and ITGA1 showed a more punctate LD pattern (Fig. 1). No evidence of LD was detected between the genes. Table I shows the categorical and quantitative analyses for single markers genotyped for the six genes. No significant evidence of association was observed for the individual markers when ADHD was analyzed as a categorical trait. 602 Laurin et al. Fig. 1. Location of the SLC1A3, GDNF, FGF10, HCN1, ISL1, and ITGA1 genes across the chromosome 5p13-q11 region and pairwise LD pattern for markers genotyped for each gene. The five-color scheme (white to red) represents the increasing strength of LD. Values of D0 are shown. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.] When analyzed in relation to the dimensional symptom scores for inattention or hyperactivity and impulsivity, rs10513003 in ITGA1 intronic sequence was the only marker showing marginal evidence of association for the parent’s report (parent’s rated inattention P ¼ 0.013; and hyperactivity/ impulsivity P ¼ 0.008). Because high LD was observed across FGF10, ISL1, HCN1, and GDNF, we conducted a haplotype analysis for these genes (Table II). No evidence of association was suggested by the global analysis (global w2 and P values) for these genes. However, two GDNF low frequency haplotypes demonstrated marginal evidence of association (P ¼ 0.011 and P ¼ 0.049). This was not supported by the quantitative analyses for these haplotypes. Globally, the quantitative analyses did not yield evidence for significant relationships between any of the observed haplotypes for these genes and both dimensions of ADHD. Finally, in their investigation of SLC1A3, Turic et al.  reported association between ADHD and a single marker (rs2269272), as well as with two two-marker haplotpes (involving rs2269272-rs3776581 and rs2269272-rs2032893). We were unable to detect significant evidence of association with the same single markers or haplotypes (Table II). A three marker-haplotype analysis yielded similar results (data not shown). DISCUSSION Linkage to the chromosome 5p13-q11 has been repeatedly found in ADHD [Fisher et al., 2002; Bakker et al., 2003; Hebebrand et al., 2006]. Although the LOD score values for each study are low, these findings appear robust because evidence of linkage is supported from independent samples, with different ethnicity, ascertainment procedures and phenotyping methods. In the present study, we tested six genes located in this region for association with ADHD. Using 245 nuclear families from Toronto, we did not observe strong evidence of association for any of the tested markers or for their haplotypes. We found nominal evidence of association between ADHD and two low frequency GDNF haplotypes and between one ITGA1 marker and symptom scores of inattention and hyperactivity/impulsivity. The genes selected in this study have been shown or suggested to play a role in different aspects of neurodevelopment including survival, cell proliferation, migration, differentiation, neuronal organization, neuronal excitability, axonal development, synaptogenesis, or synaptic plasticity [Lin et al., 1993; Bar-Peled et al., 1997; Santoro and Tibbs, 1999; Milner and Campbell, 2002; Umemori et al., 2004; Lujan et al., 2005]. These genes thus constitute good candidates for ADHD susceptibility. More specifically, some, like GDNF and islet 1, are involved in survival and differentiation of dopaminergic neurons [Pfaff et al., 1996; Thor and Thomas, 1997; Wang and Liu, 2001], and ITGA1 was shown to be expressed almost exclusively on catecholaminergic neurons [Murase and Hayashi, 1998]. The SLC1A3 and GDNF genes have previously been investigated in ADHD. Using a multi-step approach, Turic et al.  reported the genetic association of one coding two SNP in the 30 region of SLC1A3 with ADHD, as well as with two-marker haplotypes. Those markers and their haplotypes were tested in the current study and yielded negative results. As for GDNF, Syed et al.  were unable to detect evidence of association between ADHD and four SNPs (three intergenic and one intronic). However, the coverage of the gene remained low for that study. We used a different strategy to select markers across the GDNF gene based on LD pattern and found little evidence of association with ADHD in our sample. To our knowledge, none of the other genes reported here has been previously tested in relation to ADHD. Two distinct dimensions are thought to underlie the behavioral symptoms of ADHD, one reflecting inattentiveness, the other reflecting a combination of hyperactivity and impulsivity. Twin studies have shown that symptoms for either dimension are highly heritable and are primarily explained by shared genetic influences, however, each symptom dimension was also shown to be under unique genetic influence [Sherman et al., 1997; Levy et al., 2001; Rasmussen et al., 2004]. In the analysis of their genome-wide data, Hebebrand et al.  conducted a multipoint quantitative Chromosome 5p13-q11 Genes and ADHD 603 TABLE I. Categorical and Quantitative Analysis for Single-Markers Categorical Gene SLC1A3 GDNF FGF10 HCN1 ISL1 ITGA1 a b Quantitative Markers Allelesa MAF Zb P-value # Fam PICS inat P-value PICS HI P-value TTI inat P-value TTI HI P-value rs3776581 rs2269272 rs2032893 rs7731209 rs2973050 rs2910797 rs1549250 rs2216711 rs2973041 rs12518844 rs3812047 rs2290070 rs980510 rs11743802 rs16902086 rs994092 rs11743392 rs2589162 rs7722380 rs10491412 rs11954894 rs2288648 rs13188662 rs2406217 rs2860025 rs1391983 rs12110170 rs2126953 rs7732839 rs2456205 rs2406369 rs1478438 rs1478442 rs10513003 rs1421927 rs2193968 G/A C/T C/T C/T G/A C/T C/A A/G T/C G/A C/T C/G C/A T/C A/G T/C T/C A/G G/C C/T C/T T/C A/G C/G G/A T/A T/A T/G A/T G/T G/A T/A A/G C/T A/G A/G 0.309 0.192 0.376 0.157 0.356 0.259 0.431 0.219 0.178 0.408 0.148 0.189 0.352 0.128 0.379 0.190 0.413 0.416 0.241 0.079 0.214 0.370 0.352 0.461 0.251 0.110 0.237 0.189 0.227 0.217 0.487 0.204 0.228 0.229 0.284 0.417 0.562 0.047 0.324 0.322 0.264 0.341 0.464 0.853 0.068 0.186 0.926 0.582 0.498 0.042 0.377 0.275 0.461 0.000 1.144 0.776 1.756 0.681 1.405 0.879 0.969 0.962 0.091 1.765 1.555 0.905 0.436 0.618 0.699 1.659 0.155 0.196 0.574 0.963 0.746 0.747 0.792 0.733 0.643 0.394 0.946 0.852 0.354 0.560 0.619 0.967 0.706 0.783 0.645 1.000 0.253 0.438 0.079 0.496 0.160 0.380 0.333 0.336 0.928 0.078 0.120 0.366 0.663 0.536 0.485 0.097 0.877 0.844 132 110 111 73 143 97 155 122 85 147 85 88 126 60 125 98 148 154 127 57 117 143 121 122 104 50 96 81 87 90 131 95 97 97 101 119 0.772 0.757 0.624 0.530 0.673 0.719 0.445 0.963 0.325 0.756 0.490 0.633 0.455 0.564 0.497 0.630 0.758 0.976 0.370 0.108 0.277 0.877 0.507 0.781 0.846 0.448 0.330 0.155 0.011 0.044 0.947 0.350 0.182 0.013 0.883 0.905 0.369 0.979 0.723 0.354 0.816 0.821 0.357 0.532 0.281 0.566 0.461 0.387 0.943 0.503 0.897 0.713 0.371 0.733 0.398 0.277 0.214 0.940 0.698 0.287 0.557 0.695 0.951 0.063 0.203 0.078 0.983 0.932 0.164 0.008 0.580 0.659 0.531 0.467 0.862 0.613 0.905 0.708 0.783 0.697 0.425 0.912 0.831 0.257 0.435 0.465 0.858 0.746 0.862 0.841 0.543 0.266 0.290 0.705 0.190 0.250 0.175 0.339 0.477 0.065 0.260 0.634 0.907 0.490 0.096 0.071 0.761 0.778 0.776 0.708 0.964 0.301 0.485 0.552 0.466 0.825 0.777 0.772 0.447 0.780 0.922 0.485 0.562 0.386 0.899 0.988 0.706 0.966 0.756 0.983 0.650 0.497 0.736 0.152 0.560 0.074 0.488 0.418 0.595 0.399 0.422 0.169 0.561 0.701 The major and minor allele appear first and second, respectively. Z scores, as given by PDTphase for the minor allele. analysis using the dimensional symptom scores. They found that their linkage to chromosome 5p was improved when considering the inattention symptoms only. This suggests that the putative ADHD susceptibility gene(s) responsible for the linkage peak in this region contribute more to inattentive than to hyperactive-impulsive behavior. In the current study, we quantitatively assessed the relationship of inattentive symptoms for single-marker and haplotype analyses. We did not, however, observe any evidence of association with a specific dimension of the disorder for these genes. We believe it is unlikely to be due to differences in the sample phenotypic characteristics since similar proportions of the three ADHD subtypes are found in both Hebebrand’s and our samples. Our results do not suggest that common genetic variants in FGF10, GDNF, ISL1, and HCN1 play a major role in ADHD susceptibility in the current family sample, although adequate coverage of these genes was achieved with the SNPs analyzed in this study, as suggested by the LD observed between markers for each gene (Fig. 1). Moreover, our preliminary analysis of ITGA1 did not yield evidence of association with ADHD. It remains possible that not all genetic variations across the ITGA1 region has been captured by the set of markers tested in this study and analysis of additional SNPs will be needed before this locus can be confidently excluded. Finally, we could not replicate Turic et al. findings regarding SLC1A3. As we focused only in the 30 region of the gene, as it was the segment previously associated with ADHD, we cannot exclude the possibility of a susceptibility variant elsewhere in the gene in our sample. A possible reason for the failure to identify a susceptibility region in this study could be the heterogeneity between the dataset used in this study and the datasets used to determine linkage in the genome scan studies. However, considering the apparent robustness of the linkage findings, with the same region identified in different populations and the different ascertainment procedures, it seems more likely that the susceptibility gene for ADHD resides outside the regions tested in the present study. It is also possible that the susceptibility gene on 5p lies outside of the region overlapping between genome scans, that we targeted in the current study, as linkage boundaries are rarely strictly defined. Alternatively a number of genes with known and unknown function reside in this region and fine mapping across the entire region may be required to identify the putative susceptibility gene. 0.642 0.152 0.123 0.075 ISL1: ISL1: ISL1: ISL1: 0.456 0.351 0.172 SLC1A3: -11 SLC1A3: -12 SLC1A3: -21 248.6 201.9 103.5 357.0 164.4 91.3 39.3 397.5 87.5 79.7 49.0 172.6 62.3 49.8 45.7 36.2 37.2 22.3 262.5 77.4 95.6 68.4 159.5 93.0 57.0 51.6 23.5 21.4 15.0 17.0 Observedc 255.0 200.0 100.2 363.4 160.4 92.4 35.8 390.6 97.6 77.5 45.5 175.7 59.8 48.6 44.6 41.2 36.0 18.5 265.7 85.8 85.1 64.9 165.4 91.2 50.5 41.6 25.8 26.9 14.5 12.0 Expectedd c b 47.001 42.233 19.009 15.481 11.197 13.170 7.783 6.363 Globale: 60.250 36.170 28.655 18.297 Globale: 52.595 24.231 20.623 21.438 21.296 17.808 6.393 Globale: 67.362 41.723 34.006 20.739 Globale: 65.107 54.224 27.664 14.348 Globale: 54.871 58.194 31.287 Globale: Var/O-Eb Major allele ¼ 1, minor allele ¼ 2. Haplotypes with Var(O-E) >5.00 in the TRANSMIT analysis are listed. Test statistic representing the observed number of transmissions. d Expected value of the test statistic under the null hypothesis of no association. e Global w2 for haplotypes with frequency >0.05. a 0.558 0.251 0.137 0.054 SLC1A3: 11SLC1A3: 21SLC1A3: 12SLC1A3: 22- 111 112 122 222 0.356 0.124 0.100 0.080 0.079 0.077 0.035 HCN1: 11211 HCN1: 11111 HCN1: 21121 HCN1: 11122 HCN1: 22121 HCN1: 22122 HCN1: 21122 0.375 0.201 0.100 0.094 0.061 0.057 0.031 0.024 0.525 0.180 0.167 0.120 11111121 12122111 11221211 21211112 12121211 21211111 12121112 12111121 Haplotype frequency FGF10: 111 FGF10: 221 FGF10: 121 FGF10: 112 GDNF: GDNF: GDNF: GDNF: GDNF: GDNF: GDNF: GDNF: Haplotypea Transmission Categorical 0.747 0.074 2.161 6.509 0.506 2.346 0.033 3.862 12.401 (6 df) 0.170 1.962 3.827 0.647 8.004 (4 df) 0.185 0.247 0.064 0.054 1.195 0.074 2.299 2.131 (6 df) 0.699 2.410 0.171 0.578 5.843 (4 df) 0.625 0.308 0.049 0.833 1.336 (3 df) 0.736 0.066 0.361 1.009 (3 df) w2 (1 df) 0.386 0.785 0.142 0.011 0.477 0.126 0.856 0.049 0.054 0.681 0.161 0.050 0.421 0.091 0.667 0.619 0.801 0.816 0.274 0.786 0.129 0.907 0.403 0.121 0.679 0.447 0.211 0.429 0.579 0.825 0.361 0.721 0.391 0.797 0.548 0.799 P-value 115.1 111.8 79.2 157.0 124.0 84.1 41.9 131.9 81.0 70.9 51.0 95.9 62.0 45.0 40.0 40.0 41.9 20.1 118.0 80.6 71.8 55.5 102.0 90.9 47.9 42.0 29.0 33.0 19.0 13.0 # Fam. TABLE II. Categorical and Quantitative Haplotype Analysis 0.908 0.424 0.466 0.880 0.669 0.575 0.218 0.953 0.349 0.828 0.032 0.481 0.444 0.561 0.788 0.331 0.833 0.142 0.409 0.872 0.052 0.843 0.318 0.405 0.170 0.344 0.636 0.143 0.722 0.623 PICS inat P-value 0.635 0.909 0.695 0.865 0.893 0.466 0.202 0.901 0.113 0.508 0.129 0.084 0.236 0.974 0.849 0.194 0.978 0.854 0.413 0.461 0.157 0.346 0.322 0.513 0.151 0.324 0.334 0.063 0.912 0.976 PICS HI P-value Quantitative 0.804 0.552 0.461 0.560 0.975 0.892 0.324 0.808 0.523 0.712 0.160 0.338 0.114 0.357 0.662 0.239 0.929 0.916 0.822 0.336 0.507 0.212 0.466 0.497 0.166 0.228 0.780 0.076 0.519 0.364 TTI inat P-value 0.732 0.816 0.807 0.436 0.568 0.546 0.837 0.836 0.674 0.747 0.710 0.600 0.220 0.576 0.878 0.726 0.779 0.917 0.285 0.505 0.851 0.227 0.640 0.489 0.462 0.982 0.780 0.236 0.845 0.337 TTI HI P-value Chromosome 5p13-q11 Genes and ADHD ACKNOWLEDGMENTS This work was supported by Postdoctoral Fellowship from the Canadian Institutes of Health Research (NL) and by grants from The Hospital for Sick Children Psychiatric Endowment Fund (CLB), and the Canadian Institutes of Health Research MT14336 and MOP14336 (CLB) and MOP64277 (RJS). 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