Keywords: migraine, sex hormone receptors, polymorphisms, meta-analysis

Selection of studies

We followed the guidelines for systematic reviews of genetic association studies (13). Two investigators (M.S., P.M.R.) independently searched MEDLINE, EMBASE, and Science Citation Index from inception to August 2009 combining text words and MESH terms, were appropriate, for sex hormones (“hormones” or “sex hormones” or “estrogen” or “progesterone”) with terms for genetic variations (“gene” or “polymorphism” or “genetic variation”) and terms for headache and migraine (“headache” or “headache disorders” or “migraine” or “migraine disorders”). The search terms were combined with the “explode” feature where applicable. We did not use any language restrictions. In addition, we manually searched the reference list of all primary articles and review articles.

A priori, we defined the following criteria for inclusion:

1. Studies must have a cross-sectional, case-control or cohort design.

2. Authors must investigate patients with migraine and healthy control subjects.

3. Authors must provide information on genotype frequencies of the investigated polymorphisms or sufficient data to calculate these.

4. In studies with overlapping cases and/or controls the largest study with extractable data was included.

5. Studies must be published as full articles.

In a first step, two investigators (M.S., T.K.) by consensus identified all studies not meeting any of the pre-specified criteria by screening the title and abstracts. These studies were excluded. In a second step, the same investigators evaluated the remaining studies in their entirety. Studies were excluded if they did not meet all criteria.

Data extraction

Two investigators (M.S., P.M.R.) independently extracted data from the published studies and entered them in a customized database. Disagreements were resolved by consensus. The extracted data included authors and title of study, year of publication, country of origin, ethnicity of population investigated, setting (clinic vs. population), study design, genotyping method, migraine status (any migraine, MA, MO), age and gender of study individuals, study size, allele and genotype frequencies, and information on additional genetic variants as well as gene-gene and gene-environment interactions, if investigated. If not given, genotype frequencies were calculated where possible. We did not contact the authors to collect further information.

Statistical analysis

We first used logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between sex hormone receptor polymorphisms and migraine assuming additive, dominant, and recessive genetic models. We calculated these for polymorphisms which were investigated in at least two independent study populations. The additive model assumes that the risk for migraine among carriers of the heterozygous genotype is half way between carriers of the homozygous genotypes. While the dominant model assumes that carriers of the heterozygous and homozygous variant genotypes have the same risk of developing migraine compared with carriers of the homozygous wild-type genotype, a recessive model assumes that carrying the homozygous variant genotype is necessary to alter the risk for migraine compared with carriers of the heterozygous and homozygous wild-type genotype. We also determined Hardy-Weinberg Equilibrium (HWE) for the control group in each study. We investigated any migraine, MA, and MO.

We then pooled results from all studies and subsequently stratified analyses by ethnicity and gender where applicable.

We weighted the log of the ORs by the inverse of their variance to obtain pooled relative risk estimates. We ran random-effects models which include assumptions on potential variability across studies. We performed the DerSimonian and Laird Q test for heterogeneity and also calculated theI² statistic for each analysis (14). This statistic describes the percentage of total variation across studies that is due to heterogeneity rather than chance (25%: low, 50%: medium, 75%: high heterogeneity). We used Galbraith plots to visually examine the impact of individual studies on the overall homogeneity test statistic. We evaluated potential publication bias visually by examining for possible skewness in funnel plots (15) and statistically with the methods described by Begg and Mazumdar (15) and Egger (16). The latter method uses a weighted regression approach to investigate the association between outcome effects (log odds ratio) and its standard error in each study.

We considered a p-value<0.05 as statistically significant.

All analyses were performed using SAS version 9.1 (SAS Institute Inc, Cary, NC) and STATA 10.1 (Stata, College Station, Texas, USA).

Since we only utilized previously published data, we did not obtain approval of an ethics committee or written informed consent.

Study characteristics

Seven genes involved in sex hormone receptor pathways and metabolism have been investigated in the identified studies: estrogen receptor 1 gene (ESR-1) (5–11), estrogen receptor 2 gene (ESR-2) (11), progesterone receptor gene (PGR) (7,8,12), androgen receptor gene (AR) (12), follicle stimulating hormone receptor gene (FSHR) (11), nuclear receptor interacting protein 1 (NRIP1) (11), cytochrome P450, family 19, subfamily A, polypeptide 1 gene (CYP19A1) (11). One study further investigated the methylenetetrahydrofolate reductase gene (MTHFR) (9). This gene will not be considered for the present analysis.

Table 1a summarizes the characteristics of the 8 studies included according to the polymorphisms investigated. Four studies (5 study populations: 2 populations from 1 study (6)) have investigated theESR-1 594 G>A (rs2228480) (6,7,9,10), 6 theESR-1 325 C>G (rs1801132) (5,7–11), 2 theESR-1 Pvu II C>T (rs2234693) (5,8), 2 theESR-1 30 T>C (rs2077647) (7,9), and 3 (4 study populations: 2 populations from 1 study (12)) thePGR PROGINS insert (Alu insert) polymorphism (7,8,12).

Additional polymorphisms have only been looked at in single studies (Table 1b): variousESR-1 polymorphisms (7,9),AR CAG repeat (12),FSHR rs6166 (11),ESR-2 rs4986938 (11),CYP19A1 rs10046 (11),NRIP1 rs2229741 (11).

For the meta-analysis we will only consider polymorphisms that have been investigated in at least two independent study populations. The data given in 1 (9) of the 2 (7,9) studies investigating theESR-1 30 T>C polymorphism did not allow calculating genotype frequencies. Hence, we could not determine pooled relative risk estimates and we did not include this polymorphism in our meta-analysis.

Almost all studies were performed in Caucasian populations. One study was in an Indian population (8). Further, most (5,6,8,10–12), but not all studies (7,9), presented results stratified by gender in addition to results for the overall study population.

The allele and genotype frequencies for the investigated polymorphisms for migraineurs and controls in each of the studies are summarized inTable 2.

Table 3 summarizes for each of the studies the p-value for the Hardy-Weinberg Equilibrium (HWE) in the controls as well as ORs (95% CI) for the association between the polymorphisms and migraine assuming additive, dominant, and recessive genetic models.

Table 4 summarizes the pooled effect estimates, measures for heterogeneity, and tests for publication bias for each of the polymorphisms.

Association between theESR-1 594 G>A polymorphism and migraine

Among the 5 study populations from 4 studies investigating the association between theESR-1 594 G>A polymorphism and migraine, there was a statistically significant positive association in two study populations (6) suggesting an increased risk for migraine among carriers of the A allele, which did not appear in the other studies (7,9,10) (Table 3).

The pooled effect estimates among all studies suggest that the A allele is associated with an increased risk for any migraine (additive mode: pooled OR 1.37; 95% CI 1.02–1.83) (Table 4). The association appeared most pronounced for carriers of the GA/AA genotype (dominant mode: pooled OR 1.50; 95% CI 1.10–2.06). However, there was medium heterogeneity across all studies (dominant mode:I²=64.5%). Further, the increased risk for the GA/AA genotype appeared to be slightly higher among men (dominant mode: pooled OR 1.80; 95% CI 1.16–2.80) than among women (dominant mode: pooled OR 1.56; 95% CI 0.98–2.48), where it did not reach statistical significance. In addition, heterogeneity was medium among studies investigating women (dominant mode:I²=73.5%) and absent among studies investigating men. The results for MA and MO were very similar. Neither Begg’s test nor Egger’s test indicated publication bias for the dominant model.

Association between theESR-1 325 C>G polymorphism and migraine

Among the 6 studies investigating theESR-1 325 C>G polymorphism, 2 suggested an increased risk for migraine among carriers of the GG genotype (recessive mode), which appeared to be strongest among women (10,11), while the others did not find an altered risk (5,7–9) (Table 3).

The pooled effect estimates suggest that the G allele is associated with a slightly increased risk for having any migraine (additive mode: pooled OR 1.16; 95% CI 1.03–1.32) (Table 4). The association was most pronounced for carriers of the GG genotype (recessive mode: pooled OR 1.40; 95% CI 0.93–2.11); however, this result did not reach statistical significance. Further, the effect estimates among studies in Caucasian populations were very similar to the overall result, which included a study in the Indian population. The association between the GG genotype and any migraine was stronger among women than men. Heterogeneity among the studies was low (recessive mode:I²=38.9%). The overall association was the same for MA (recessive mode: pooled OR 1.60; 95% CI 1.19–2.17) and MO (recessive mode: pooled OR 1.44; 95% CI 0.97–2.13). In addition, the pattern of a stronger association among women than men also occurred for MA and MO. Neither Begg’s test nor Egger’s test indicated publication bias when assuming a recessive model.

Association between theESR-1 Pvu II C>T polymorphism and migraine

Among the 2 studies investigating theESR-1 Pvu II C>T polymorphism, 1 found an increased risk for migraine among carriers of the T allele (8), while the other did not (5) (Table 3).

The pooled effect estimates between the 2 studies neither suggest an association for any of the genotypes with any migraine, MA or MO nor a difference between women and men when looking at any migraine. One study provided gender specific effect estimates for MA and MO, which suggested a higher risk among women than men (8). Heterogeneity between the 2 studies was high. This is most likely due to the low number of studies and remaining uncertainties which may include genotypic ethnic differences. Formal investigation using Begg’s test did not indicate publication bias.

Association between thePGR PROGINS insert polymorphism and migraine

Among the 4 study populations investigating thePGR PROGINS insert polymorphism, 2 found an increased risk among carriers of the “2” allele (=Alu insert) (12), 1 found a protective association (8), and 1 did not find an association (7) (Table 3).

The pooled effect estimates among all studies do not suggest an association between any of the genotypes and any migraine (additive mode: pooled OR 1.02; 95% CI 0.55–1.87) (Table 4). This finding did not differ between MA (additive mode: pooled OR 1.11; 95% CI 0.68–1.81) and MO (additive mode: pooled OR 1.01; 95% CI 0.48–2.13). However, further analyses suggested that there may be a moderately increased association for having any migraine among Caucasians, which appeared strongest in a dominant model (pooled OR 1.49; 95% CI 0.98–2.26). While the direction and association of the effect estimates among Caucasians were similar for both migraine subgroups, they only reached statistical significance in MA (dominant mode: pooled OR 1.49; 95% CI 1.10–2.01), but not MO (dominant mode: pooled OR 1.56; 95% CI 0.79–3.09). Heterogeneity across all studies was medium to high for any migraine, MA, and MO, it was low among the studies investigating MA among Caucasians (dominant mode:I²=4.3%). This may support the significant results for Caucasians among MA.

Sensitivity analyses

For some of our analyses, Galbraith plots identified individual studies as important sources of heterogeneity. We performed sensitivity analyses by excluding studies that fell outside the margin set by the z score ±2 standard deviations.

For the association between theESR-1 594 G>A polymorphism and migraine Galbraith plots did not identify individual studies as significant sources of heterogeneity for any migraine and MO (dominant model). One study (6) was excluded when looking at MA, which lowered the effect estimates, however, the association remained statistically significant (dominant mode: pooled OR 1.18; 95% CI 1.01–1.38).

For the association betweenESR-1 325 C>G polymorphism and any migraine, MA, and MO, Galbraith plots did not identify individual studies as important sources of heterogeneity in any of the models.

For the association between theESR-1 Pvu II C>T polymorphism and migraine we did not perform a formal sensitivity analysis, because 1) only 2 studies were pooled and 2) the heterogeneity index was high, already suggesting that pooled results need to interpreted with caution.

Effect estimates from the sensitivity analysis did not change the association between thePGR PROGINS insert polymorphism and migraine. They were all slightly higher for any migraine, MA, and MO assuming additive or dominant models. For example, after excluding 2 studies (8,12) the pooled OR for the association with any migraine assuming a dominant model was 1.34 (95% CI 0.74–2.41).

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