Background
Migraine is a highly prevalent neurological disorder involving multiple susceptibility genes and environmental factors [
1,
2]. The current clinical classification follows the International Criteria for Headache Disorders (ICHD-II), with the two main categories of migraine without aura (MO) and migraine with aura (MA) [
3]. The pathophysiology of migraine is not entirely understood, but a role for dopamine (DA) was already suggested thirty years ago [
4]. The DA hypothesis relies on the observed signs of central DA hypersensitivity in migraine patients and the known capacity of DA receptors to regulate nociception, vascular tone and autonomic responses [
5]. Studies in animal models revealed that DA receptors are present in the trigeminovascular pathway and showed that DA can act as an inhibitor of nociceptive trigeminovascular transmission in the rat brain [
6]. Along this line, DA antagonists have proved useful in aborting migraine headache or associated symptoms [
5]. However, DA antagonists are not always selective and may act through DA receptor-independent mechanisms [
7]. Also, a review of pharmacological and therapeutic studies in migraine could not provide convincing evidence of a direct role of DA in migraine pathogenesis [
8].
Several association studies in different populations have focused on genes encoding proteins of the dopaminergic neurotransmission system, including DA receptors, the DA transporter, and enzymes involved in the synthesis and catabolism of DA. These studies provided conflicting results [
7], although a recent, most comprehensive analysis of 10 dopamine-related genes in MA suggested that
DBH and
SLC6A3, at least, might be involved in migraine pathogenesis [
9].
In a previous study that evaluated the contribution of 19 serotonin-related genes to migraine susceptibility in our cohort of Spanish migraineurs, we reported risk haplotypes in
MAOA for migraine without aura and in
DDC for migraine with aura [
10], both genes being key players in the serotonin and dopamine metabolic pathways. In order to further elucidate the involvement of the dopaminergic system in migraine liability, nine dopamine-related genes were selected for a two-stage case-control association study in the Spanish population.
Results
Initially, 64 SNPs from nine candidate genes encoding proteins related with DA neurotransmission were genotyped [see Additional File
1]. Fourteen SNPs were excluded from statistical analysis after data depuration in the first population: ten had genotype call rates <90%, one was monomorphic and three were in strong LD with other SNPs (r
2 > 0.85, [see Additional File
1]). The 50 remaining SNPs had MAF>0.12 and were in HWE in control population 1 (P > 0.01; [see Additional File
2]). After the exclusion of individuals with low genotyping rate, population 1 consisted of 263 patients and 274 controls, and population 2 was composed of 259 patients and 287 controls. No evidence of population stratification was found in any of the two populations studied by applying the STRUCTURE software [see Additional File
3], the Fst coefficient (theta = 0, 99%CI = 0.000-0.001 for population 1 and theta = 0, 99%CI = 0.000-0.002 for population 2) and the method by Pritchard and Rosenberg (P = 0.57 for population 1 and P = 0.05 for population 2).
In the single-marker analysis, genotype and allele frequencies were compared between patients and controls in population 1 [see Additional File
2]. Six SNPs within five genes (
DRD1,
DRD2,
DRD3,
DBH and
TH) displayed P-values < 0.05 (table
1). Two of them, rs2283265 in
DRD2 and rs2070762 in
TH, remained significant after applying a FDR of 10% (Table
1A) and were further considered for the multiple-marker analysis. No SNP withstood the restrictive Bonferroni correction for multiple testing. For these two SNPs we sought to detect a specific association with either one of the clinical subtypes, MO or MA. We found that in population 1,
DRD2 rs2283265 was associated wit both MO and MA, while
TH rs2070762 was only associated with MO (Table 1B).
Table 1
Results of dopamine-related genes association studies
DRD1
| rs251937 p1 | 133 (54.7) | 95 (39.1) | 15 (6.2) | 243 | 120 (45.5) | 119 (45.1) | 25 (9.4) | 264 | NS | 1.45a (1.02-2.08) | 0.0355 | 1.58a (0.82-3.12) | NS | 1.36 (1.04-1.79) | 0.0261 |
| p2 | 130 (53.0) | 95 (38.8) | 20 (8.2) | 245 | 144 (51.8) | 116 (41.7) | 18 (6.5) | 278 | NS | 1.05a (0.74-1.49) | NS | 1.29 (0.66-2.51) | NS | 1.01a (0.77-1.33) | NS |
DRD2
| rs12363125 p1 | 133 (51.8) | 97 (37.7) | 27 (10.5) | 257 | 108 (40.6) | 128 (48.1) | 30 (11.3) | 266 | 0.0304 | 1.56a (1.11-2.22) | 0.0102 | 1.07a (0.62-1.85) | NS | 1.31 (1.01-1.70) | 0.0401 |
| p2 | 112 (43.6) | 123 (47.9) | 22 (8.5) | 257 | 141 (49.5) | 112 (39.3) | 32 (11.2) | 285 | NS | 1.27 (0.90-1.78) | NS | 1.35a (0.76-2.38) | NS | 1.07 (0.83-1.39) | NS |
DRD2
| rs2283265 p1 | 210 (82.4) | 44 (17.3) | 1 (0.3) | 255 | 196 (72.3) | 69 (25.5) | 6 (2.2) | 271 | 0.0085 | 1.79a (1.18-2.70) | 0.0059 | 5.88a (0.68-50) | NS | 1.78 (1.20-2.63) | 0.0030* |
| p2 | 199 (77.7) | 54 (21.1) | 3 (1.2) | 256 | 226 (81.3) | 49 (17.6) | 3 (1.1) | 278 | NS | 1.24 (0.81-1.89) | NS | 1.09 (0.22-4.46) | NS | 1.2a (0.81-1.77) | NS |
DRD3
| rs3732790 p1 | 113 (44.0) | 119 (46.3) | 25 (9.7) | 257 | 104 (38.7) | 115 (42.7) | 50 (18.6) | 269 | 0.0131 | 1.25a (0.88-1.75) | NS | 2.12a (1.27-3.57) | 0.0033 | 1.36 (1.06-1.75) | 0.0169 |
| p2 | 101 (39.5) | 122 (47.7) | 33 (12.8) | 256 | 114 (40.3) | 125 (44.2) | 44 (15.5) | 283 | NS | 1.03 (0.73-1.46) | NS | 1.25a (0.76-2.04) | NS | 1.04 (0.81-1.33) | NS |
DBH
| rs1611131 p1 | 129 (56.6) | 76 (33.3) | 23 (10.1) | 228 | 129 (49.6) | 114 (43.8) | 17 (6.6) | 260 | 0.0400 | 1.33a (0.93-1.92) | NS | 1.57 (0.81-3.02) | NS | 1.09 (0.83-1.47) | NS |
| p2 | 124 (51.0) | 102 (42.0) | 17 (7.0) | 243 | 136 (52.7) | 107 (41.5) | 15 (5.8) | 258 | NS | 1.07 (0.76-1.52) | NS | 1.22 (0.60-2.50) | NS | 1.08a (0.82-1.42) | NS |
TH
| rs2070762 p1 | 51 (20.8) | 138 (56.3) | 56 (22.9) | 245 | 84 (32.2) | 129 (49.4) | 48 (18.4) | 261 | 0.0130 | 1.81 (1.21-2.72) | 0.0035* | 1.32 (0.85-2.03) | NS | 1.37a (1.08-1.75) | 0.0111 |
| p2 | 57 (23.4) | 119 (49.0) | 67 (27.6) | 243 | 78 (28.2) | 131 (47.3) | 68 (24.5) | 277 | NS | 1.28 (0.86-1.90) | NS | 1.17 (0.79-1.74) | NS | 1.16a (0.92-1.49) | NS |
B. Results of the association study of DRD2 rs2283265 and TH rs2070762 in the migraine without aura and migraine with aura subgroups of population 1 and population 2. |
| |
Cases
| |
Controls
| | |
Genotype
11 vs 12+22
| |
Genotype 11+12 vs 22
| |
Allele 2 vs allele 1
| |
Gene
|
SNP population
|
11
|
12
|
22
|
Sum
|
11
|
12
|
22
|
Sum
|
P value
|
OR (95% IC)
|
P value
|
OR (95% IC)
|
P value
|
OR (95% IC)
|
P value
|
Migraine without aura
| | | | | | | | | | | | | | | | |
DRD2
| rs2283265 p1 | 119 (82.6) | 25 (17.4) | 0 (0.0) | 144 | 196 (72.3) | 69 (25.5) | 6 (2.2) | 271 | 0.0097 | 1.81a (1.10-3.03) | 0.017 | 1.02 (1.004-1.04) | 0.023 | 1.85 (1.15-2.90) | 0.0081 |
| p2 | 115 (72.8) | 40 (25.3) | 3 (1.9) | 158 | 226 (81.3) | 49 (17.6) | 3 (1.1) | 278 | NS | 1.59 (1.00-2.53) | NS | 1.80 (0.36-9.05) | NS | 1.52a (1.00-2.32) | NS |
TH
| rs2070762 p1 | 27 (19.0) | 84 (59.2) | 31 (21.8) | 142 | 84 (32.2) | 129 (49.4) | 48 (18.4) | 261 | 0.0143 | 2.04 (1.24-3.34) | 0.0036 | 1.24 (0.74-2.05) | NS | 1.40a (1.04-1.88) | 0.023 |
| p2 | 37 (24.5) | 73 (48.3) | 41 (27.2) | 151 | 78 (28.2) | 131 (47.3) | 68 (24.5) | 277 | NS | 1.19 (0.76-1.88) | NS | 1.11 (0.71-1.76) | NS | 1.11a (0.84-1.47) | NS |
Migraine with aura
| | | | | | | | | | | | | | | | |
DRD2
| rs2283265 p1 | 91 (82.0) | 19 (17.1) | 1 (0.9) | 111 | 196 (72.3) | 69 (25.5) | 6 (2.2) | 271 | NS | 1.75a (1.00-3.03) | 0.042 | 2.5a (0.29-20.0) | NS | 1.69 (1.01-2.77) | 0.037 |
| p2 | 84 (85.7) | 14 (14.3) | 0 (0.0) | 98 | 226 (81.3) | 49 (17.6) | 3 (1.1) | 278 | NS | 1.37a (0.72-2.56) | NS | 1.01a (0.99-1.02) | NS | 1.41 (0.77-2.63) | NS |
TH
| rs2070762 p1 | 24 (23.3) | 54 (52.4) | 25 (24.3) | 103 | 84 (32.2) | 129 (49.4) | 48 (18.4) | 261 | NS | 1.57 (0.93-2.66) | NS | 1.44 (0.83-2.5) | NS | 1.35a (0.98-1.89) | NS |
| p2 | 20 (21.7) | 46 (50.0) | 26 (28.3) | 92 | 78 (28.2) | 131 (47.3) | 68 (24.5) | 277 | NS | 1.44 (0.82-2.52) | NS | 1.28 (0.75-2.20) | NS | 1.26a (0.90-1.75) | NS |
The analysis of all possible allelic combinations within the
DRD2 gene revealed a five-marker haplotype (rs12363125-rs2283265-rs2242592-rs1554929-rs2234689) associated with migraine (best adjusted P-value = 0.00889; Table
2), with an over-representation of the T-C-G-C-G allelic combination in cases (OR = 1.85, 95%CI = 1.13-3.04, P = 0.0139) and the C-A-A-C-C haplotype in controls (OR = 1.88, 95%CI = 1.25-2.82, P = 0.00199; Table
3). The T-C-G-C-G haplotype carriers displayed an OR of 1.74 (95%CI = 1.06-2.88, P = 0.0277). In order to investigate if the association was specific of MO or MA, we compared the risk haplotype carrier frequencies between controls and each migraine subgroup separately. Although the frequencies were different (10.6% controls, 17.7% MO, 16.4% MA), they only reached borderline significance in MO (P = 0.042), while no significant differences were found in MA (P = 0.12). We performed a second-stage replication study in an independent Spanish case-control cohort to test these positive findings. The frequency of the risk haplotype T-C-G-C-G (rs12363125-rs2283265-rs2242592-rs1554929-rs2234689) carriers in population 2 was compared between 259 patients and 287 controls. Control carrier frequencies were very similar to those obtained in population 1 (10.4% control population 2 and 10.8% control population 1), whereas case carriers were more frequent in population 1 (17.1%) than in population 2 (14.3%). Thereby, the differences between cases and controls in population 2 did not reach significance (P = 0.22).
Table 2
Haplotype analysis of DRD2 and TH SNPs in 263 migraine patients and 274 unrelated non-migraine controls using the UNPHASED software.
DRD2
| 6 7 | 0.00519 | 0.00178 (0.00450) | 1.37 (1.05-1.79) |
| 6 7 8 | 0.00175 | 9.74e-04 (0.00400) | 1.74 (1.08-2.80) |
| 6 7 8 10 | 0.00135 | 0.00100 (0.00460) | 1.84 (1.12-3.02) |
| 6 7 8 9 10b
| 0.00276 | 0.00199 (0.00889) | 1.85 (1.13-3.04) |
TH
| 1 2 | 0.0283 | 0.00573 (0.0150) | 1.34 (0.94-1.90) |
Table 3
Haplotype distributions of DRD2 in populations 1 and 2 using the UNPHASED software.
6 7 8 9 10
| | | | | | |
C C G C G | 49 (9.9) | 58 (11.5) | 0.423 | 66 (13.9) | 47 (9.1) | 0.018 |
C C G C C | 47 (10.1) | 40 (7.9) | 0.233 | 42 (8.8) | 55 (10.7) | 0.331 |
C A A C C | 40 (8.6) | 76 (15.1) | 0.00199; 1.88 (1.25-2.82)
c
| 53 (11.1) | 53 (10.3) | 0.660 |
T C G C G | 44 (9.4) | 27 (5.4) | 0.0139; 1.85 (1.13-3.04) | 37 (7.8) | 28 (5.4) | 0.136 |
T C A T C | 287 (62.0) | 303 (60.1) | 0.581 | 278 (58.4) | 333 (64.5) | 0.047 |
TH
| | | | | | |
|
Population 1 Overall P-value = 0.0283
|
Population 2 Overall P-value = 0.2
|
Marker
b
Haplotype
|
Cases (%)
|
Controls (%)
|
Haplotype-specific P; OR (CI)
|
Cases (%)
|
Controls (%)
|
Haplotype-specific P
|
1 2
| | | | | | |
A C | 82 (17.4) | 68 (13.5) | 0.0370; 1.34 (0.94-1.90) | 100 (20.9) | 86 (15.7) | 0.129 |
A T | 108 (23.0) | 118 (23.7) | 0.674 | 82 (17.2) | 123 (22.4) | 0.141 |
G C | 162 (34.6) | 149 (29.9) | 0.127 | 147 (30.8) | 178 (32.5) | 0.935 |
G T | 118 (25.0) | 165 (32.9) | 0.00573; 1.47 (1.11-1.94)
c
| 149 (31.1) | 161 (29.4) | 0.953 |
Multiple-marker analysis of the two SNPs (rs6356 and rs2070762) in
TH showed a different overall distribution between cases and controls (best adjusted P-value = 0.015, Table
2), due to an over-representation the A-C allelic combination in cases (P = 0.037, OR = 1.34, 95%CI = 0.94-1.90), and G-T in controls (P = 0.00573, OR = 1.47, 95%IC = 1.11-1.94; Table
3). However, individual haplotype assignation did not identify differences in the frequency of risk haplotype carriers between cases and controls. Moreover, the analysis of rs6356-rs2070762 haplotype distributions in cases and controls of population 2 found no evidence of association with migraine (table
3).
Finally, we aimed to determine whether those variants nominally associated with the disease phenotype in population 1 after the single-marker analysis, could be replicated in population 2, especially rs2283265 in the
DRD2 gene and rs2070762 in the
TH gene, which maintained significance after FDR correction in the initial analysis. The comparison of genotype and allele frequencies between cases - either the whole group of migraineurs, or MO or MA subgroups- and controls did not reveal significant differences for rs2283265 (codominant genotypes P = 0.62 and alleles P = 0.36), rs2070762 (codominant genotypes P = 0.44 and alleles P = 0.22) nor for any other SNP (table
1).
Discussion
We performed a two-stage case-control association study of eight dopamine-related genes in the Spanish population. In order to capture the common haplotype variation of these genes in the European population, we selected haplotype-tagging SNPs which covered each gene and its flanking regions. In population 1, a five-marker risk haplotype in the
DRD2 gene and a single variant in the
TH gene were found to be associated with migraine, and both remained significant after applying correction for multiple comparisons. In the initial single-marker analysis, pointing at five genes including the two above, no SNP withstood the Bonferroni correction. However, it is well known that this correction is often over-conservative as it assumes independence of all the tests performed, whereas many SNPs within the genes studied, although not in strong LD, are not independent. When markers found associated in population 1 were analyzed in the follow-up population, the results could not be replicated. As special attention was paid to rule out the existence of stratification and both populations were comparable in terms of size, gender distribution, ethnicity (Caucasians), geographical origin (Spain) and diagnostic criteria, failure to replicate the results suggests that the associations identified in population 1 may be spurious and that the genes analyzed here would not be involved in migraine susceptibility. However, these findings should be taken with caution, as the genetic coverage of some of the studied genes is not optimal for several reasons: First, SNPs with low frequencies, which would require very large sample sizes to produce significant results, were not selected. Second, some SNPs within the studied genes, for which no LD data were available in the HapMap database, were not included. And third, SNPlex design constraints and low genotyping call rates of some specific SNPs forced additional exclusions that left the
DRD4 gene out of the study. Of note, the same Spanish cohort analyzed in the present work was previously scrutinized by us to detect association of MA or MO with genes related with serotonin neurotransmission [
10]. Among the three genes that displayed significant association, two belong to the dopamine metabolic pathway:
MAOA, found to be associated with MO, and
DDC, which was associated with MA. However, these findings still await replication.
A number of association studies have focused on dopamine-related genes. The first susceptibility polymorphism identified in this system was the
NcoI variant in the
DRD2 gene (rs6275), with an over-representation of the C allele in MA [
24]. Subsequent studies failed to replicate this association [
25‐
28] or that with other
DRD2 polymorphisms [
27,
29]. It is worth mentioning, however, that a (TG)n repeat variant in
DRD2 was found associated with yawning and nausea in a small subgroup of migraine patients [
30]. We analyzed
DRD2 rs2242592, in strong LD with rs6275, that belonged to a risk haplotype identified in population 1 but not confirmed in population 2. Subsequent studies found association between migraine phenotypes and polymorphisms in
DRD4 [
31,
32] and
DBH [
9,
25,
33,
34], although negative associations have also been described [
9,
30,
31,
33]. No associations have been identified in any of the polymorphisms analyzed in genes
DRD1,
DRD3,
DRD5 or
COMT [
9,
27,
30,
35‐
38]. The genetic marker set selected in the present analysis is in many respects not comparable with the polymorphisms analyzed in the previous studies. However, our results agree with previous negative findings in
DRD1,
DRD3 and one polymorphism in
DBH.
A recent study carried in two German populations [
9], analyzed the contribution of the nine dopamine-related genes we have examined, plus
DDC, to MA susceptibility. In that study, MA was associated with three SNPs,
SLC6A3 rs40184,
DRD2 rs7131056 and
DBH rs2097629. Overall, they analyzed 43 SNPs belonging to the nine genes studied in our work; of them, 23 SNPs are coincident or in strong LD (r
2 > 0.85) with the ones we analyzed. The remaining 20 markers were not included in our analysis because their MAFs values were under the selected cut off (n = 13), lacked genotyping in the HapMap sample (n = 3), had SNPlex design constraints (n = 2) or failed in the genotyping step (n = 2). Conversely, our study included 27 SNPs with MAF>0.15 that were not analyzed by Todt et al. Three out of five nominal associations identified in our population 1, not replicated in population 2, also showed P-values > 0.05 in the first German population, thus reinforcing the likelihood of a spurious association in our population 1. Our study did not reveal association with rs7131056 in
DRD2 or rs40184 in
SLC6A3 at variance with the German study, while rs2097629 in
DBH was not included in our study because of design constraints. In addition to differences in the respective SNP sets, our samples were composed of both MO and MA patients, and therefore a comparison of our results with those of Todt et al. is not altogether straightforward. Also, our analytical design set that the two population samples could only be grouped for analysis in case nominal associations were found in both populations 1 and 2, while in the German study their two samples were analyzed as a single group for all SNPs within the three genes that showed nominal association in only one population. This strategy produced significant associations despite lack of replication in their follow-up sample. Future studies combining both marker sets might help to reconcile these apparently discordant findings.
Much evidence points to dopamine hypersensitivity in migraineurs, particularly those displaying the premonitory symptoms of yawning or nausea. In our study, such specific symptoms could not be analyzed, since they were not available in the whole sample. To our knowledge, no well-powered association study has addressed the relationship between endophenotypes based on dopaminergic symptoms and genetic susceptibility using a pathway-based approach. Alternatively, latent class analysis of migraine symptoms, as used to enhance clinical homogeneity in genetic linkage analysis [
39,
40], might define migraine phenotypes, not necessarily related to ICHD-II migraine subtype diagnoses, and thus uncover specific genetic susceptibility factors.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
RC carried out the genotyping, analyzed the data and drafted the manuscript. MC, EC-L and MJS participated in genotyping. BC and AM designed the study and had the primary responsibility for writing the manuscript. MR helped in study design and supervised all the statistical analysis. JP, SB, MJS and AM were responsible for selecting and evaluating the patients in the respective centers. EC-L, MJS and RC participated in control recruitment. All authors have read and approved the final manuscript.