The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) were followed throughout the search of this research as shown in Fig. 1a–c. Prospective registration with PROSPERO (Id no. 441920) attests to the reliability of the review methodology.

a Flowchart of literature screening of rs1801132 gene polymorphism. b Flowchart of literature screening of rs2228480 gene polymorphism. c Flowchart of literature screening of rs2234693 gene polymorphism

The examination was performed individually by SBS under the guidance of the corresponding author (GK). In the event of any disagreements, a consensus was reached. The search was improved by using Boolean operators like “AND” and “OR” to combine search topics in the advanced search builder. Extensive electronic database searches were performed by using Scopus, Google Scholar, Web of Science, Embase, PubMed, and MEDLINE from 2004 of the period till June 2023. This search used medical subheading terms and text words from the following lists: migraine, headache, and ESR-1 gene polymorphism. Screening reviews, new research publications, and past meta-analyses have been employed to update the database and get rid of duplicate entries.

Articles were selected for the meta-analysis based on certain criteria. The ESR-1 gene polymorphism and migraine risk had to be investigated in three different ways for the study to meet these criteria: i) through a case vs. control study, ii) through a case vs. control study that included allele and genotype information, and iii) through case vs control studies that used genetic information. On the other hand, research was not included if it met any of the following criteria: i) it relied solely on case data; ii) it did not provide enough information to determine a 95% confidence interval or odds ratio; iii) it was an animal study that overlapped with other research; or iv) it involved duplicated data.

The data-collecting process was standardized according to the inclusion criteria. Under the direction of the corresponding author (GKS), the authors (SBS) built a pooled database in which pertinent features were retrieved from each eligible research like First author, year of publication, country, allele, genotype frequency and characteristics of participants for each SNPs like race, sample size, age, sex (Supplementary material-1). Divergences were discussed and settled by mutual agreement. The Newcastle–Ottawa scale was used to evaluate the potential for bias in these observational studies. Data related to the first author, year of publication, population source, ethnicity, country of origin, research design, outcomes, and clinical subject characteristics were supplied for each study that met the inclusion criteria.

The risk of bias for each study was evaluated using the Newcastle–Ottawa Quality Assessment Scale (NOS), which assesses the quality of non-randomized studies. The NOS uses a “star system” to judge studies in three areas: the selection of study groups, the comparability of groups, and the ascertainment of exposure or outcome. Studies with a score of five or higher are considered low risk of bias and high quality. The overall quality of evidence for each risk factor in the pooled analysis was assessed using the ROB 2 tool to strengthen the evidence and generate a summary table for all three gene polymorphism variants.

The metadata obtained underwent power analysis under conditions with a 95% confidence interval (0.05 α error). The power of each study sample size (both case and control) was aggregated and individually assessed for each chosen gene using GPower 3.1 software.

Three polymorphisms in the ESR-1 gene (rs1801132, rs2228480, and rs2234693) were analysed in this research to determine their potential role in the development of migraine. Statistical significance is assumed to exist when the p-value of a study is lesser than 0.05 when the 95% confidence interval (CI) and odds ratio (OR) are calculated and evaluated. Allele comparison, genetic regression for recessive characteristics, genetic regression for dominant traits, and genetic regression for over-dominant traits were the four genetic models used. Each study’s findings were compared using the inconsistency index (I2), whose values, from 0 to 100%, indicated the level of heterogeneity between the studies. In our study, fixed effects were used when I2 is less than 50%, while random effects are used when I2 is greater than 50%. It is also considered statistically significant when the OR ratio is greater than one, the lower limit of the CI is greater than one, or when the OR ratio is less than one, the upper limit of the CI is less than one with p < 0.05. A Chi-squared Q-statistic test was used to examine consistency. To assess diversity, we performed subgroup analysis by ethnicity by publishing year and ethnicity. Sensitivity analysis was conducted to check the relationship between the gene and migraine by excluding the specific investigation, we were able to examine no heterogeneity study had a substantial impact on the entire study’s conclusion and egger’s linear regression analysis and funnel plots were used to determine the presence of publication bias. I2 statistics and Egger’s test were performed at a significance level of p < 0.05. For statistical data analysis, we used MetaGenyo for data administration and analysis.