Elgeta Hysaj, P Jahołkowski, Alexey Shadrin, Jacob Bergstedt, Yi Lu, Elizabeth Bertone-Johnson, Cynthia M. Bulik, Mikael Landén, Sven Sandin, Kaarina Kowalec, Sara Hägg, Arianna Di Florio, David Goldman, Schmidt Pj, Unnur A. Valdimarsdóttir, Ole A. Andreassen, Donghao Lu
ABSTRACT Background Premenstrual disorders (PMDs) are characterized by affective and physical symptoms before menses, likely due to abnormal sensitivity to normal hormone fluctuations. While sizable heritability has been indicated in twin studies, there are no genome-wide association studies (GWAS) to inform the genetic architecture of PMDs. Methods We conducted a GWAS of 17,511 women with premenstrual symptoms (PS) and 54,786 controls of European ancestry from two Nordic population-based cohorts. PS were assessed using questionnaire or identified as a clinical diagnosis of PMDs in the nationwide healthcare registers. GWAS was performed in each study before meta-analysis, followed by analyses of single nucleotide polymorphism (SNP)-based heritability (h 2 SNP ) and genetic correlations to psychosocial and gynecological phenotypes. Results In the meta-analysis, one locus at 12p13.3 (rs758170, CACNA1C , P=1.53x10 -8 , OR=0.93, 95% CI 0.90-0.95) was associated with PS; while the effect sizes were comparable between cohorts (LifeGene OR=0.95 vs MoBa OR=0.92, P het =0.59), the association was not significant in LifeGene (P=0.242). Moreover, we identified six loci with borderline significance, among which three were nominally significant in both cohorts (rs76665457, rs147346386, and rs4773561). The SNP-based heritability was estimated as 0.072 (SE=0.01, P=2.46 x10 -12 ). The strongest correlation was with major depression (rg=0.62, CI 0.49-0.74, P=3.04x10 -22 ). Conclusion This study provides initial genetic insights into the biology of PS by identifying a SNP associated with PS and genetic correlations to a range of psychosocial and gynecological traits. If confirmed in larger independent populations, these findings may advance our understanding of the underlying mechanisms of PMDs.