Computational protocol: BMI-Associated Alleles Do Not Constitute Risk Alleles for Polycystic Ovary Syndrome Independently of BMI: A Case-Control Study

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Protocol publication

[…] Association analyses were initially carried out within each case-control set separately. The additive genetic model was tested using PLINK (v.1.07) and IBM SPSS version 20 (IBM Statistical Package for the Sociological Sciences Inc., Chicago, USA). The combined effect of the BMI-increasing alleles in the two populations was evaluated using a fixed-effects meta-analysis in GWAMA for SNPs with heterogeneity (I2) less than 25%. When I2 exceeded 25%, a random effect meta-analysis was performed using statistical software package R (http://www.r-project.org). Moreover, we studied the association of BMI-increasing alleles with PCOS when only including individuals with a BMI ≥30 kg/m2 and in a second analysis when only including individuals with a BMI <30 kg/m2.Using Genetic Power Calculator software we determined that with the sample size of the total case control set (cases: n = 1073; controls: n = 3511), we reached approximately 95% power to detect association of a risk allele of frequency ≥0.2 having an odds ratio of ≥1.3 and an alpha of 0.05 (http://pngu.mgh.harvard.edu/~purcell/gpc/). Since we selected the genetic variants, we did not correct for multiple testing and a P value <0.05 was considered statistically significant.To test for the combined effect of all the BMI-associated alleles on PCOS susceptibility and to estimate the genetic risk of having PCOS for these women dependent on the number of BMI-increasing alleles present, we calculated the Genetic Risk Score (GRS). The GRS was modeled as a continuous variable and the calculation was carried out using R (http://www.r-project.org/). Using the GRS we assume that each SNP in the panel contributes equally to PCOS risk and that each individual allele has an equal and additive effect on risk. To obtain accurate counts of BMI-increasing alleles, only individuals with genotypes for at least 90% of SNPs (11 out of 12) were included. Based on this criterion, a total of 1264 individuals, i.e., 512 cases and 752 controls, from the UK and 3150 individuals from the Netherlands, i.e., 502 cases and 2648 controls, were included in the GRS-analysis. This method was described previously. , Missing genotypes were replaced with the average risk score for each SNP in the total population. The maximum attainable score was 24 BMI-increasing alleles (12 SNPs * 2 alleles). The reference group was defined as 12 to 13 BMI-increasing alleles, which was the mean number of BMI-increasing alleles present in the controls. Analyses were carried out within the separate case-control sets as well as in the combined set. Finally, we calculated the overall trend across the GRS-groups using the Kruskal Wallis trend test (IBM SPSS version 20). […]

Pipeline specifications

Software tools PLINK, GWAMA
Application GWAS
Organisms Homo sapiens
Diseases Polycystic Ovary Syndrome