This study describes the first meta-analysis of GWAS for population-based migraine, and contains a total of 2446 migraine cases and 8534 controls. The best P-value was obtained for SNP rs9908234, which is located in the NGFR gene. A replication study was performed in two Dutch replication cohorts that were available for wet replication; the GEM cohort (769 cases, 940 controls) and the NTR replication cohort (337 cases, 826 controls). In addition, the ATM GWA cohort (1851 cases, 1631 controls) was available for in silico replication. Although the NGFR gene is an interesting candidate gene for migraine, the association of NGFR with migraine could not be replicated in these cohorts. A total of 18 additional top SNPs (P-value<10−5) from the meta-analysis were tested in the GEM cohort and the ATM GWA cohort, but none could be replicated successfully.
There are several possible explanations for the lack of replication. First, several different genotyping platforms were used, which made imputation necessary to ensure sufficient overlap between the studies. Also, two different programs (MACH and IMPUTE) were used for imputation. However, given that MACH and IMPUTE use very similar imputation algorithms, and have been reported to be very similar in imputation accuracy,38
we do not expect this to have a major effect on our results. Second, there were some differences between the samples in the precision of the migraine diagnoses, and in most samples, a clinical migraine diagnosis was not available. This is often the case in population-based studies because, for reasons of efficiency, diagnoses are commonly made with (short) headache questionnaires. Unlike in clinic-based studies, they are not usually further evaluated with more extensive questionnaires or interviews by specialized physicians. Less accuracy of diagnosis may result in reduced power to detect association. The phenotypic differences also extend to the control groups, as all non-migraine individuals were included as controls. These differences between studies mean that effect sizes may not be directly comparable. To address this, a pooled Z
-score meta-analysis was performed. This type of analysis does not require a direct comparison of effect sizes.39
Third, population-based cohorts also include many patients who have less severe migraine and a lower attack frequency. This means that they might be a genetically more heterogeneous group than patients from clinic-based cohorts. In addition, they are likely to have a lower genetic risk of migraine than the more severely affected patients in clinic-based cohorts. As a consequence, population-based studies may require a larger number of patients for sufficient power. Given that this study replicates previous findings, but does not produce genome-wide significant results, insufficient power (possibly because of the reasons above) seems the most likely explanation for the lack of replication of our top results. A lack of power makes it difficult to distinguish between true associations and false-positive findings in the original meta-analysis. Therefore, when the discovery samples have insufficient power, SNPs selected for replication based on small P
-values may not replicate (even in sufficiently large replication samples) because they are false positives. Finally, it should be mentioned that the NESDA sample differed from the other samples because the majority of NESDA participants were selected for major depression. Because of the comorbidity of migraine and major depression, there is a higher prevalence of migraine in this sample than in the other samples. However, given that the percentage of MDD was similar in the migraine cases and the controls (94.3 vs
86.6%), any associations detected in this sample will be related to migraine and not to MDD.
In the present study, we also investigated SNP rs1835740 that was found to be significantly associated with MA in the first GWA study of clinic-based populations.17
This SNP is located on 8q21 between the MTDH
genes. The SNP itself was not associated with migraine in our study, but our gene-based analyses provided modest support for an association of MTDH
In summary, although this study does not provide genome-wide significant association of an SNP with migraine, it provides suggestive evidence for an association with the MTDH
gene, which is involved in the glutamate pathway, previously hypothesized to have a role in migraine based on findings in FHM.40
Clearly, even though a large number of patients and controls were included, the present study suffered from a lack of power. In addition to simply increasing the sample size, additional strategies aimed at minimizing phenotypic and genetic heterogeneity may be necessary. Strategies to achieve this can include the identification of reliable biomarkers or stratification of samples based on phenotypic similarity (eg, by looking at trait components,11
specific symptoms16, 41
and/or comorbid pathology). In addition, in future studies it may be worth focusing specifically on the glutamate pathway to assess whether genetic variants affecting glutamate levels are systematically associated with migraine.