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Association study for genes at chromosome 5p13-q11 in attention deficit hyperactivity disorder.

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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. [2004]). 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.
[2002]). 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. [2005]
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.
[2005] 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. [2005] 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. [2007] 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. [2006] 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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