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. Author manuscript; available in PMC: 2011 Oct 1.
Published in final edited form as: Genes Brain Behav. 2010 Jun 29;9(7):673–680. doi: 10.1111/j.1601-183X.2010.00601.x

A Genome-wide Association Study of Bipolar Disorder and Co-morbid Migraine

K J Oedegaard 1,2,3, T A Greenwood 1,6, S Johansson 4,8, K K Jacobsen 4,8, A Halmoy 4, O B Fasmer 2,3, H S Akiskal 1,5; The Bipolar Genome Study (BiGS)6, J Haavik 4,7, J R Kelsoe 1,5,6
PMCID: PMC2970709  NIHMSID: NIHMS208150  PMID: 20528957

Abstract

Both migraine and Bipolar Disorder (BPAD) are complex phenotypes with significant genetic and non-genetic components. Epidemiological and clinical studies have demonstrated a high degree of co-morbidity between migraine and BPAD, and overlapping regions of linkage have been shown in numerous genome-wide linkage studies.

To identify susceptibility factors for the BPAD/migraine phenotype, we conducted a genome-wide association study (GWAS) in 1001 cases with bipolar disorder collected through the NIMH Genetics Initiative for Bipolar Disorder and genotyped at 1M SNPs as part of the Genetic Association Information Network (GAIN). We compared BPAD patients without any headache (n=699) to BPAD patients with doctor diagnosed migraine (n=56). The strongest evidence for association was found for several SNPs in a 317 kb region encompassing the uncharacterized gene KIAA0564 (e.g. rs9566845 (OR=4.98 (95%CI: 2.6–9.48), p= 7.7 ×10−8) and rs9566867 (p= 8.2 × 10−8)). Although the level of significance was significanlty reduced when using the Fisher’s Exact test (due to the low count of cases with migraine); rs9566845 p= 1.4 ×10−5 and rs9566867 p= 1.5 × 10−5, this region remained the most prominent finding. Furthermore, marker rs9566845 was genotyped and found associated with migraine in an independent Norwegian sample of adult ADHD patients with and without co-morbid migraine (n=131 and n=324 respectively), OR=2.42 (1.18–4.97), p=0.013.

This is the first GWAS examining patients with bipolar disorder and co-morbid migraine. These data suggest that genetic variants in the KIAA0564 gene region may predispose to migraine headaches in subgroups of patients with both BPAD and ADHD.

Keywords: Bipolar disorder, migraine, whole genome association study, ADHD, KIAA0564, GAIN

1. Introduction

Bipolar affective disorder (BPAD [MIM 125480]) affects about 1 % of the population, increasing morbidity and mortality (APA, 2000). It is characterized by episodes of depression and mania, and there is strong support for a genetic basis with heritability of at least 60% (Craddock & Jones, 1999, Smoller & Finn, 2003). Although BPAD is highly heritable, the identification of specific genetic variations has yielded limited findings (Baum et al., 2008a, Baum et al., 2008b, Sklar et al., 2008, Wtccc, 2007), and sub-grouping patients with BPAD according to clinical sub-phenotypes has been suggested as a fruitful approach for further genetic studies in BPAD (Mcqueen et al., 2005).

Migraine (MIM 157300) affects approximately 18% women, 6% men, and 4% children, and is characterized by recurrent headache, nausea, emesis, phonophobia and photophobia (Headache classification committee, 2004). The heritability in migraine is estimated between 40–65% (Gervil et al., 1999, Honkasalo et al., 1995, Larsson et al., 1995). Linkage studies have not been consistent, and no genes associated with common forms of migraine have been recognized (Fasmer, 2009a, Oedegaard et al., 2010) However, three genes for the autosomal dominant disorder Familial Hemiplegic Migraine (FHM1–3, MIMs 141500, 602481, and 609634, respectively) have been identified. These genes are involved in ion-transport (CACNA1A (MIM 601011) (Ophoff et al., 1996), SCN1A (MIM 182389) (Dichgans et al., 2005), and ATP1A2 (MIM 182340) (De Fusco et al., 2003), and the identified mutations can lead to increased extra cellular glutamate and potassium levels, and through that mechanism affect neuronal membrane thresholds and cause hyperexcitability of neurons (Van De Ven et al., 2007).

There is a substantial co-morbidity between migraine and bipolar disorders documented in clinical and epidemiological studies. Both disorders have been linked to disturbances in the serotonergic, dopaminergic and glutamatergic systems, and alterations in ion channels may be involved in the pathophysiology of migraine and bipolar disorders (Fasmer, 2009a, Oedegaard et al., 2010). Population studies have revealed that there is a two to three fold increased prevalence of migraine in patients with bipolar disorders (Hirschfeld et al., 2003, Mcintyre et al., 2006).

The relationship might be particularly strong in patients with bipolar II disorder (Fasmer, 2001, Low et al., 2003), and an increased risk of having migraine has been associated with having a family history of bipolar disorder (Dilsaver et al., 2009). Some pharmacological treatments are successful in the prevention of both disorders, most notably valproate (Bowden et al., 2000, Mulleners & Chronicle, 2008).

We recently used BPAD with co-morbid migraine as an alternative phenotype definition in a genome-wide linkage study (a re-analysis of the NIMH Bipolar Genetics Initiative wave 4 data set) (Oedegaard et al., 2010) and identified a locus on chromosome 20p11 with overlapping elevated LOD scores for both migraine (LOD=1.95) and BPAD (LOD=1.67) phenotypes.

In order to validate our results we used genetic information from an available sample of patients with attention deficit hyperactivity disorder (ADHD). This a neuropsychiatric disorder strongly associated with bipolar disorder (Halmoy et al., 2010), and the sample had also been assessed for migraine headache.

We hypothesized that the BPAD/migraine symptom complex could be a meaningful alternative phenotype/endophenotype for the identification of genetic susceptibility regions in a genome-wide association study.

To the best of our knowledge this study is also the first GWAS in migraine in any sample (NHGRI catalog of published GWA studies: http://www.genome.gov/gwastudies/; updated Feb. 16th 2010).

2. Methods and Materials

The GAIN Study

The study population and subject characteristics are described elsewhere (Smith et al., 2009). In brief, this is a genome-wide association case-control study including a European American sample of 1001 Bipolar cases and 1033 controls. The final dataset (after study subjects, genotyping and quality control) consisted of 724,067 SNPs. The patients were recruited at 11 data collection sites across the U.S. Patients were interviewed with the Diagnostic Interview for Genetic Studies DIGS (APA, 2000, Nurnberger et al., 1994). Medical records were obtained, and a consensus final best estimate diagnosis was made using DSM-IV criteria. (APA, 2000).

Bipolar cases

Bipolar cases were selected from those collected and characterized by the NIMH Genetics Initiative for Bipolar Disorder Consortium over the past 18 years. These subjects were collected in 5 waves. Waves 1–4 were families collected for linkage studies, while wave 5 was a large set of primarily unrelated cases collected for large-scale association studies. The study sample includes 175 unrelated subjects from waves 1 and 2 and 396 unrelated subjects from waves 3 and 4. In addition, the sample includes 430 subjects from the wave 5 data collection. The subjects abstracted from waves 1–5 totalled 1041 individuals. Forty subjects were removed due to a non-BPAD I/SABP (Schizo-Affective Bipolar Disorder) best estimate diagnosis or low diagnostic confidence. The final sample included 1001 cases of which 951 had a diagnosis of BPAD 1 and 50 had a diagnosis of SABP.

Migraine cases

In waves 1–2 information regarding doctor diagnosed migraine was not assessed. Patients were asked whether they suffered from migraine headaches, but not whether the diagnosis had been affirmed by a medical doctor. In waves 3–5 all patients were asked whether they suffered from migraine headaches and also if the diagnosis had been confirmed by a medical doctor. Since there is a substantial overlap between symptoms of tension type headache and migraine headaches (Davidoff, 2002), we only included those patients who reported that their diagnosis had been verified by a medical doctor in the current analyses. Furthermore, in order to avoid possible contamination of migraine headaches by other types of headache, all patients with self-reported migraine only were excluded from this GWAS.

Genotyping

Genotyping was carried out by The Broad Institute Center for Genotyping and Analysis (http://www.broad.mit.edu/node/306), using the Affimetrix Genome-Wide Human SNP Array 6.0 (Mccarroll et al., 2008). Samples for which fewer than 86% of the quality control (FQC) SNPs produced genotypes were rerun. Allele calling was performed using the BirdSeed algorithm (Korn et al., 2008) Affymetrics Power Tools version apt- 1.8.6 (http://www.affymetrix.com/partners_programs/programs/developer/tools/powertools.affx#1_3) and cluster models file (http://www.broad.mit.edu/dbmirel/ncbi/affy6.0_birdseed1.31.priors.tsv). Further quality control was performed on SNPs to remove duplicate samples, poorly genotyped and/or contaminated samples, and poorly-performing SNPs, as part of standard quality control measures used for the whole-genome association study of the same sample (Smith et al., 2009). The genotype data are available through dbGaP (phs000017.v1.p1).

Statistical Analyses

All genetic analyses were conducted using PLINK version 1.07 (Purcell et al., 2007) for the BPAD with migraine vs. BPAD without migraine phenotypes. The distribution of expected p-values under the null hypothesis (i.e., no association), and genomic inflation value (λ) was calculated in PLINK using the adjust command.

Power and statistical significance

In the current study, we have employed a significance of 5 ×10 −8 threshold, as this has been commonly used in previous GWA studies. One region had two SNPs that were close to this threshold, but since the strongest test of association lies in follow-up replication studies we conducted a study in order to replicate this BPAD/migraine finding in an available sample of patients with ADHD and co-morbid migraine. In addition we list all SNPs with a p value < 10 × 10− 5 (table S2).

The ADHD Study

The patients were recruited in a genetic study using a national registry of adults diagnosed with ADHD in Norway during 1997 through 2005, as recently described (Halmoy et al., 2010). The diagnostic evaluation of the patients in the registry was made by 1 of 3 national expert commissions for ADHD/hyperkinetic disorder by systematic assessment of information records (including information from informants) provided by the referring psychiatrists. The diagnosis of ADHD was made according to the ICD-10 research criteria. In addition, to increase recruitment and to also include patients diagnosed later than May 2005, clinicians nationwide were asked to recruit formally diagnosed adult patients with ADHD. These patients were assessed by specialists in clinical psychiatry according to national guidelines based on the criteria described above, though without the mandatory evaluation of the committees yielding a total sample of 466 adults with persistent ADHD diagnosis. Information on co-morbid migraine and bipolar disorder was extracted from questionnaire data obtained in the primary study. In the ADHD sample only self-reported migraine data were available. Genomic DNA was extracted either from whole blood, or from saliva using the Oragene DNA Self-Collection Kit from DNA Genotek (DNA Genotek Inc, Ontario, Canada) at the HUNT biobank (Levanger, Norway).

BPAD and migraine co-morbidity in the ADHD study

A life-time history of bipolar disorder was reported by 12.3% of the adult ADHD patients and 1.7% of controls (p<0.001). Bipolar disorder in first degree family members was reported by 11.3% and 2.7% of patients and controls, respectively (p<0.001). Using the Mood Disorder Questionnaire (MDQ), 50.6 % of the ADHD patients screened positive for a bipolar spectrum disorder (BSD)(Halmoy et al., 2010).

Among adult ADHD patients, 27.9% reported a life-time history of migraine compared to 18.6 % in the control group (p=0.001). Migraine in first degree family members was reported by 35.2% of the patients and 28.1% of controls (p = 0.001).

The ADHD study included 466 patients with ADHD and 133 of these had a co-morbid migraine diagnosis. This represented the replication sample.

Genotyping

Marker rs9566845 which tagged the entire associated haplotype in the GWA-analysis was selected for replication in the ADHD-samples. Genotyping was carried out by the multiplex MassARRAY®iPLEX™ System (SEQUENOM, Inc.) at the Norwegian national technology platform CIGENE as part of a bigger ADHD-genotyping study including 55 markers. Genotyping call rate in the 484 patients was 99.6% and concordance rate was 100% (38 duplicates) for marker rs9566845. A total of 18 ADHD patients were subsequently excluded based on strict QC-measures in the total data set (>10 % missing genotypes) yielding a final data set of 466 ADHD patients.

Statistical analyses

Data-analyses were performed using the PLINK software, and the single point allelic association test was performed with the chi-square test and Fisher’s Exact test.

Results

Descriptive statistics of the BPAD and ADHD samples

Demographic variables for the study population, for the migraine phenotypes and for the replication sample are presented in table 1. The study population included 699 individuals without migraine and 56 individuals who reported having a doctor diagnosed migraine; 233 individuals were excluded from the study since they reported having headache that had not been diagnosed by a doctor. The demographic data revealed that the proportion of women was significantly higher in the BPAD/migraine group compared to the group without migraine (76.8% vs. 43.9%). The mean age was similar for both groups in both men and women. In the ADHD group the proportion of women was also higher in the ADHD/migraine group compared to the ADHD group without migraine (58.8% vs. 42.9%), and also here the mean age was similar in both genders. In the ADHD sample 11 subjects were excluded due to genotyping errors.

Table 1.

Demographic data for the BPAD and ADHD sample

Bipolar affective disorder (BPAD) (n=1001) Attention deficit Hyperactivity Disorder (ADHD) (n= 466)
Migraine (n=56) No migraine (n=699) Excluded (n=232) Migraine (n=131) No migraine (n=324) Excluded (n=11)
N Age N Age N Age N Age N Age N Age
Men 13 43.1 392 42.4 94 39.9 54 34.9 185 33.5 8 28.8
Women 43 45.4 307 42.0 151 42.2 77 35.5 139 34.6 3 23
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BPAD GWA analyses

Fig. 1 is a Manhattan plot of all SNPs in the analyses, displaying the p-values of the comparisons between the BPAD with migraine and those without migraine. SNPs with p-values below 10 × 10− 5 (blue line) are highlighted (117 SNPs). We report a list of these top associated SNPs in table S1. The SNP with the lowest p-value (rs11031481; p< 9.4 ×10− 9) is located in a gene desert and surrounding SNPs were not genotyped in the current study. The most noticeable peak was located in a 317 kb region on chromosome 13 with several SNPs approaching the proposed 5×10−8 threshold for GWA-significance, e.g. rs9566845 (OR=4.98 (95% CI: 2.6–9.48), p= 7.7 ×10−8) and rs9566867 (p= 8.2 × 10−8), with additional support from numerous surrounding SNPs. The rare allele of rs9566845 was significantly more frequent in patients with migraine headache compared to patients without migraine headaches (12.5% vs. 2.8%). This region harbours an uncharacterized gene, KIAA0564 (chr13:41,191,473-41,433,221) (Fig. 2). An in depth analyses of this region revealed that the association is best explained by one relatively rare haplotype which involves the top 10 associated SNPs of the region (see Supplementary Tables X, Y, Z and Supplementary Figure XX). The haplotype has an allele frequency of 2.3 % among bipolar patients without migraine and 12.7 % of patients with doctor diagnosed migraine (the haplotype is indicated by a blue line in Figure 2). This haplotype spans at least 315 kb and covers the entire associated region and is fully tagged by markers rs9566845 and rs9566876.

Fig 1.

Fig 1

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shows a Manhattan plot of all SNPs, organized by chromosome. The blue line represents p = 10 × 10e-5, the red line 10 × 10e-8. Genes in regions with p<10 × 10e-5 are indicated.

Figure 2.

Figure 2

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Regional plot of chromosome 13, (40,800–41,400 kb) showing the association signal for bipolar patients with comorbid migraine versus bipolar patients without comorbid migraine from the GWA-scan. The physical positions are indicated on the x-axis and on the Y-axis is the P-value for association (expressed as −logP). Grey diamonds represents the −logP of the association for each genotyped SNP. The right hand axis presents the estimated recombination rates in cM/Mb from the HapMap samples (Build 35). The yellow diamond corresponds to the top hit SNP rs9566845 (P= 7.7 ×10−8) which was also genotyped in the follow up study using Norwegian ADHD patients with and without migraine. The blue line represents the minimal associated haplotype which contains the top 10 ranked SNPs in the region.

Furthermore we include a report on all chromosomal regions that had at least two SNPs with p-values < 10 × 10−5. A list of these regions including information regarding support from SNPs with p-values < 10 × 10−4 and possible candidate genes in these regions are presented in table S2. As can be seen from this list, these regions harbour numerous genes of theoretical interest both in migraine and BPAD. However, these results should be interpreted with caution before firm replications have been reported.

Since the number of patients with co-morbid migraine was small (n=56) and was compared to a relatively much larger sample of patents without migraine (n=699), we calculated the p-values for all markers (with P-values from chisquare test less than 1×10-5) by the use of the Fisher’s Exact test as well. These results are presented in Supplementary table S3. As can be seen the p-values for all single point allelic association results are reduced significantly when using Fisher’s Exact test. As can also be seen, the region encompassing the six most significant SNPs on chr. 13 still stands out as the most prominent finding, although these p-values are no longer approaching genome-wide significance.

Replication analyses in the ADHD-study

Although the nominal p-values presented for the chromosome 13 haplotype are nearly GWA-significant we appreciate that the number of bipolar cases with migraine in the initial study was small and that we therefore cannot exclude chance effects (as indicated by the use of Fisher’s Exact test). We therefore decided to genotype a sample of adult Norwegian patients with ADHD, a group of patients who share many symptoms with BPAD. To maximize power and minimize multiple testing problems we only genotyped the single most associated marker in the chromosome 13 haplotype, rs9566845. A total of 466 ADHD patients were genotyped of which 133 had migraine. We again found that the rare allele of rs9566845 was significantly more frequent in patients with migraine headache ((5.6% vs. 2.4%, p=0.013, OR=2.42 (95% CI 1.18–4.97)).

Table 2 shows allelic association results for rs9566845 in the BPAD GWA study and the follow up replication in a Norwegian ADHD sample, comparing subjects with and without comorbid migraine.

Table 2.

Allelic association results for rs9566845 in the BPAD GWAS and the follow up replication in a Norwegian ADHD sample. Comparisons between subjects with (Migr.+) and without (Migr.−) comorbid migraine.

Population (study design) N (Migr+/−) MAF OR P
Migr.+ Migr.−
BPAD US (GWAS) (56/699) 0.125 0.028 4.98 (2.61–9.48) 7.7e-08
ADHD Norway (single SNP) (133/332) 0.056 0.024 2.42 (1.18–4.97) 0.013
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Discussion

We conducted a GWA study in a sample of patients with BPAD using co-morbid migraine as an alternative phenotype. This is the first GWAS using this phenotype, and to the best of our knowledge, the first GWAS in any sample of patients with information regarding migraine headaches. We here report a finding on chromosome 13q14.1 characterizing the patients with BPAD and comorbid migraine. The region counted 9 SNPs with p-values < 10 × 10−5 (chr13:41192397-41388566), including two SNPs with p-values, approaching genome-wide significance (5×10−8). This finding was however considerably weaker when analyses were repeated using the Fisher’s Exact test which is more robust to small cell counts. In order to further qualify our most interesting result, we therefore performed a successful replication analyses in a sample of patients with ADHD and comorbid migraine. This replication analyses included only the most significant SNP from the primary analyses (rs9566845), and the analyses demonstrated a 2.4 fold increase of the rare allele among ADHD patients with migraine headache (p=0.013). Interestingly, the region of association harbours an uncharacterized gene (KIAA0564; chr13:41191473-41433221). Little is known about the gene which has a complex structure with several putative transcripts. The longest transcript consists of 45 exons and is estimated to encode a protein of 1905 amino acids with putative ATPase activity. The expression pattern appears to vary between transcripts, for example one transcript which is encoded by 26 exons (NM_001009814) shows a particularly interesting pattern of expression (found in cDNA clones from whole brain, substantia nigra, amygdala, hypothalamus etc). It is also possible that the associated variant act as a regulator of other nearby genes. Recently, a genome-wide Dutch migraine linkage study reported linkage to a genomic region in close proximity the region of association in the current study (Ligthart et al., 2008), giving further support that this genomic region could be implicated in migraine headaches. In the Dutch study a broad peak covering a wide area of chromosome 13 with a maximum LOD score of 1.63 was identified. However, the subtype with pulsating headache produced even higher LOD scores (LOD > 2 from 40–100cM), encompassing the region enclosing the KIAA 0564 gene. Also a genome-wide linkage screen of 13 bipolar affective disorder pedigrees has provided evidence for susceptibility on chromosome 13q14 (LOD score of 2.29 at marker D13S153) in close proximity to KIAA0564 (Badenhop et al., 2002)). The gene KIAA0564 has putative ATPase activity expressed in the brain, as seen in patients with familial hemiplegic migraine (FHM II), where are found mutations in ATP1A2 which encodes the 2 subunit of Na+/K+ ATPases that are expressed in astrocytes in the adult brain (De Fusco et al., 2003). In this regard, it is interesting that the gene identified to cause familial hemiplegic migraine (FHM I), CACNA1A) (Ophoff et al., 1996), has overlapping functional similarities to CACNA1C, a gene that was recently associated with bipolar disorder in a collaborative genome-wide association analysis of 4387 cases (Ferreira et al., 2008). Both these genes encode an alpha-1 subunit of a voltage-dependant calcium channel.

One SNP (SNP_A-8530612; 4252795) on chromosome 11 showed significant association after correction for genome-wide testing (p= 9.4×10−9, p= 4.21×10−7 when using Fisher’s Exact test). This SNP seems to be located in a gene desert, and the GAIN GWAS did not include analyses of SNPs in close proximity to this SNP. It is therefore not possible to exclude this as a potentially interesting region, since the lack of supporting SNPs is based on an absence of SNPs in this region in the GAIN study.

No single SNP from other genomic regions showed significant association after correction for genome–wide testing, but as many as 117 SNPs showed p values < 10 × 10−5 (Table S1), and many of these clustered together in genomic regions containing genes of potential interest. Table S2 displays the 20 regions that had at least two SNPs with p values < 10 × 10−5, most of these with good support from surrounding SNPs. A list of genes that are of potential interest in both migraine and bipolar disorder based on interesting functions and characteristics are presented in Table 3:

Table 3.

A list of genes that are of potential interest in both migraine and bipolar disorder based on interesting functions and characteristics (genes in regions that had at least 2 SNPs p< 10 × 10−5)

  • ZFYVE16 (chr5:79739639-79810477), (6 SNPs p< 10 × 10−6, 2 SNPs p< 10 × 10−5). Endofin, an endosomal protein implicated in regulating membrane trafficking.

  • NPAS3 (chr14:32754139-33219999), (1 SNPs p< 10 × 10−6, 3 SNPs p< 10 × 10−5, 1 SNPs p< 10 × 10−4). Neuronal PAS domain protein 3 isoform 2.

  • KCNG4 (Chr16:82813324-82830857), (5 SNPs p< 10 × 10−5, 3 SNPs p< 10 × 10−4). Potassium channel, voltage-gated, subfamily G.

  • SBF2 (chr11:9816182-10172110), (2 SNPs p< 10 × 10−5). Pseudophosphatase member of the myotubularin-related protein family. Defects in SBF2 are the cause of Charcot-Marie-Tooth disease type 4B2 (CMT4B2).

  • CNTP5 (chr2:124499334-125264188), (2 SNPs p< 10 × 10−5). This gene may play a role in the correct development and proper functioning of the peripheral and central nervous system and may be involved in cell adhesion and intercellular communication; it is expressed in the trigiminal ganglion [RefSeq].

  • KCNMB2 (chr3:179759312-180044911), (2 SNPs p< 110 × 10−5). MaxiK channels are large conductance, voltage and calcium-sensitive potassium channels which are fundamental to the control of smooth muscle tone and neuronal excitability. May participate in inactivation in chromaffin cells in hippocampal CA1 neurons.

  • TSHR (chr 14: 80491622-80682399), (2 SNPs p< 10 × 10−5, 8 SNPs p< 10 × 10−4). Thyroid stimulating hormone receptor. T Relationships to thyroid-stimulating hormone levels have been found in migraine and BPAD.

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The ADHD replication sample

ADHD is a common condition during childhood, adolescence, and adulthood with recent world wide prevalence estimates of 3–4% in adults (Kessler et al., 2006). Adult ADHD is associated with significant lifetime psychiatric comorbidity (Sobanski et al., 2007). Particularly, the relationship between ADHD and BPAD has been of interest since high rates of co-existence have been reported between ADHD and BPAD, both in childhood, adolescence and adulthood. Furthermore, current diagnostic criteria in both disorders include dysregulation of energy, activity and impulsivity (APA, 2000). For both conditions, the heritability has typically been estimated at 0.7–0.8 (Faraone et al., 2005, Smoller & Finn, 2003). The reported prevalence of ADHD in adult bipolar patients varies between 10–21%, whereas rates of BPAD in adult patients with ADHD vary from 5–47 %. The prevalence of BPAD in the current ADHD sample was reported at 12.3 %, but 50.6 % screened positive for a Bipolar spectrum disorder according to the Mood Disorder Questionnaire (Faraone et al., 1997, Halmoy et al., 2010). Furthermore, it has been suggested that co-morbid ADHD and BPAD may represent a distinct subtype of ADHD (Faraone et al., 1997).

To the best of our knowledge there is no information from epidemiological studies on co-morbidity of migraine with ADHD. However, a recent study, indirectly assessing the possible co-morbidity of these disorders, by using data from a prescription register covering the whole Norwegian population, found a positive connection between prescription of migraine drugs and drugs used to treat patients with ADHD (methylphenidate and atomoxetine), yielding OR’s between 1.6 and 2.7 in adults between 20 and 50 years (Fasmer, 2009b). Although headache in this prescription study may have been related to the intake of psycho-stimulants, the figures are still in line with the data from the current study where the prevalence of migraine in the ADHD sample was 28.6 %. This is similar to the proportions of comorbid migraine that have been reported in BPAD I samples previously (Mahmood et al., 1999, Mcintyre et al., 2006), and clearly higher than the prevalence in the general population (10–15%)(Davidoff, 2002).

We therefore believed that a sample of patients with ADHD including information on comorbid migraine would be interesting in order to perform replication analyses regarding the best finding from a migraine/BPAD phenotype GWA study. This is of course also a limitation, since the ADHD sample is obviously not identical to the BPAD sample. Furthermore, it is not possible to conclude whether this finding is related to migraine in general, but nevertheless, it is clearly interesting that the same finding was present across different disorders like BPAD and ADHD.

It is obviously a departure from the ideal that migraine diagnoses were not assessed according to IHS- defined criteria, but based on patients own reports (even when diagnosed by a doctor, this is still self-reported, and could very well be a false positive migraine identification). This represents a limitation to the current study. The present finding should be replicated in larger independent samples. This might also help to clarify whether KIAA0564 variants are primarily associated with common migraine, BPAD, or ADHD, and what is the biological foundation for the observed co-occurrence of these symptoms.

In conclusion, the results from the current study suggest that the region 13q14.1 harbouring the gene KIAA0564 is associated with migraine headaches both in a sample of patients with BPAD and in a sample of patients with ADHD.

Our GWA study of BPAD with co-morbid migraine supports the suggestion that this symptom constellation can reclassify some patients into a more homogeneous genetic subgroup. Co-morbid migraine is a phenomenon that appears to cluster in BPAD and could in the context of BPAD be either a sub-phenotype (illness-related phenomenon) or even an endophenotype (independent of the illness state), possibly related to a common genetic vulnerability.

We propose that information regarding a prevalent co-morbid neurological disorder (i.e. migraine) can provide an additional tool for stratifying a bipolar study sample. It is hoped that this approach will be a useful in future studies of the complex genetics of both migraine and bipolar disorder.

Supplementary Material

Supp Figs&Tables
Supp Table s1
Supp Table s2

Acknowledgments

These studies were supported by grants from the National Institute of Mental Health (MH078151, MH68503, MH59567), and by the Department of Veterans Affairs. JRK is a founder and holds equity in Psynomics, Inc.

Footnotes

Bipolar Genome Study Co-Authors

John R. Kelsoe, Tiffany A. Greenwood, Paul D. Shilling, Caroline M. Nievergelt –Department of Psychiatry, University of California, San Diego, USA; Dept of Psychiatry, Veterans Affairs San Diego Healthcare System, La Jolla, USA

Nicholas Schork, Erin N. Smith, Cinnamon S. Bloss - Scripps Genomic Medicine and Scripps Translational Science Institute, La Jolla, CA, USA; Dept of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA, USA; Scripps Health, La Jolla, CA, USA;

John I. Nurnberger, Jr., Howard J. Edenberg, Tatiana Foroud, Daniel L. Koller - Department of Psychiatry, Department of Biochemistry and Molecular Biology, Department of Medical and Molecular Genetics, Indiana Univ School of Medicine, Indianapolis, IN, USA;

Elliot S. Gershon, Chunyu Liu, Judith A. Badner - Dept of Psychiatry, University of Chicago, Chicago, IL, USA;

William Scheftner - Department of Psychiatry, Rush University Medical Center, Chicago, IL, USA;

William B. Lawson, Evaristus A. Nwulia, Maria Hipolito - Department of Psychiatry, Howard University, Washington, D.C., USA;

William Coryell - Dept of Psychiatry, University of Iowa, Iowa City, IA, USA;

John Rice - Division of Biostatistics, Washington University, St. Louis, MO, USA;

William Byerley - Department of Psychiatry, University of California, San Francisco, CA, USA;

Francis McMahon, Thomas G. Schulze - Genetic Basis of Mood and Anxiety Disorders Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD, USA;

Thomas B. Barrett - Department of Psychiatry, Portland Veterans Affairs Medical Center, Portland, OR, USA;

Wade Berrettini - Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA;

James B. Potash, Peter P. Zandi, Pamela B. Mahon - Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, USA;

Melvin G. McInnis, Sebastian Zöllner, Peng Zhang - Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA;

David Craig, Szabolics Szelinger - Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, AZ, USA.

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