Early predictive biomarkers for postpartum depression point to a role for estrogen receptor signaling D. Mehta 1 *, D. J. Newport 2 , G. Frishman 3 , L. Kraus 1 , M. Rex-Haffner 1 , J. C. Ritchie 4 , A. Lori 5 , B. T. Knight 6 , E. Stagnaro 2 , A. Ruepp 3 , Z. N. Stowe 6 and E. B. Binder 1,2 * 1 Max Planck Institute of Psychiatry, Munich, Germany 2 Emory University School of Medicine, Department of Psychiatry and Behavioral Sciences, Atlanta, GA, USA 3 Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany 4 Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA 5 Department of Human Genetics, Emory University, Atlanta, GA, USA 6 Psychiatry Research Institute, University of Arkansas for Medical Sciences, Little Rock, AR, USA Background. Postpartum depression (PPD) affects approximately 13% of women and has a negative impact on mother and infant, hence reliable biological tests for early detection of PPD are essential. We aimed to identify robust predictive biomarkers for PPD using peripheral blood gene expression profiles in a hypothesis-free genome-wide study in a high-risk, longitudinal cohort. Method. We performed a genome-wide association study in a longitudinal discovery cohort comprising 62 women with psychopathology. Gene expression and hormones were measured in the first and third pregnancy trimesters and early postpartum (201 samples). The replication cohort comprised 24 women with third pregnancy trimester gene expression measures. Gene expression was measured on Illumina-Human HT12 v4 microarrays. Plasma estradiol and estriol were measured. Statistical analysis was performed in R. Results. We identified 116 transcripts differentially expressed between the PPD and euthymic women during the third trimester that allowed prediction of PPD with an accuracy of 88% in both discovery and replication cohorts. Within these transcripts, significant enrichment of transcripts implicated that estrogen signaling was observed and such enrichment was also evident when analysing published gene expression data predicting PPD from a non-risk cohort. While plasma estrogen levels were not different across groups, women with PPD displayed an increased sensitivity to estrogen signal- ing, confirming the previously proposed hypothesis of increased sex-steroid sensitivity as a susceptibility factor for PPD. Conclusions. These results suggest that PPD can be robustly predicted in currently euthymic women as early as the third trimester and these findings have implications for predictive testing of high-risk women and prevention and treatment for PPD. Received 12 June 2013; Revised 10 December 2013; Accepted 11 December 2013 Key words: Biomarkers, depression, estrogen, postpartum. Introduction The WHO has predicted that by 2030, major depressive disorder will be the top disability causing illness with a high disease burden across the world (WHO, 2008). The incidence of depressive disorders in men and women is similar up to adolescence; however, after menarche, women are twice as likely to suffer from de- pression (Kessler & Walters, 1998). While the relative risk of depression changes throughout the female reproductive life cycle, the windows of increased vul- nerability for depression occur during periods of sig- nificant hormonal fluctuations (Lokuge et al. 2011). One of the most vulnerable periods for a woman to become depressed is after childbirth (Kendler et al. 1992). Postpartum depression (PPD) affects approxi- mately 13% of women and has a negative impact on the lives of the mother and infant. PPD typically has symptom onset within 6–12 weeks after delivery (Leung & Kaplan, 2009). PPD, like other complex traits, is thought to involve both genetic and environmental factors (Craddock & Forty, 2006). Genetic predisposi- tion together with social, psychological and biological * Address for correspondence: E. B. Binder, M.D., Max Planck Institute of Psychiatry, Kraepelinstrasse 2, Munich 80804, Germany. (Email: binder@mpipsykl.mpg.de) [E. B. Binder] (Email: mehta@mpipsykl.mpg.de) [D. Mehta] Psychological Medicine, Page 1 of 14. © Cambridge University Press 2014 doi:10.1017/S0033291713003231 ORIGINAL ARTICLE