EPIGENETIC BIOMARKERS OF POSTPARTUM DEPRESSION IDENTIFY PREMENSTRUAL DYSPHORIC DISORDER (PMDD) AND POST-MENOPAUSAL DEPRESSION (PMD)

Abstract Background Postpartum depression (PPD) occurs following periods of major hormonal flux and experiments modulating gonadal hormone levels in the humans pharmacologically can lead to the onset of depressive phenotypes(Bloch et al., 2000). Together the data suggest a class of depression driven by hormonal change, here termed ‘hormonal depression’ (Payne, Palmer and Joffe, 2009; Payne, 2019).Previous work out of our laboratories have identified epigenetic variation at the TTC9B and HP1BP3 loci that is prospectively predictive of PPD risk, validated in over 5 cohorts(Guintivano et al., 2014; Osborne et al., 2016; Kaminsky et al., 2020; Lapato et al., 2020; Payne et al., 2020). Objectives The primary objective was to assess the predictive efficacy of epigenetic PPD biomarkers for other hormonally driven depressions including premenstrual dysphoric disorder (PMDD) and post-menopausal depression (PMD). The secondary objective was to assess the influence of antidepressant medications and serum hormones and neuroactive metabolites on biomarker outcomes. Methods We applied our published PPD biomarker linear model to DNA methylation generated by targeted pyrosequencing at TTC9B and HP1BP3 in a cohort of N=55 women with and without premenstrual dysphoric disorder (PMDD). The model was evaluated in a convenience sample of publicly available DNA methylation data from N=128 women to predict current depression in post-menopausal women. Results In the PMDD sample, Luteal but not follicular phase samples generated an AUC of 0.71 (95% CI: 0.49-0.93 ) to distinguish N= 10 PMDD cases from N=18 controls and generated an AUC of 0.86 (95% CI: 0.70-0.86). In the PMD sample, the PPD model predicted depression status with an AUC of 0.71 (95% CI: 0.61-0.81) in N=80 women with current depression and N=48 controls. In the PMDD sample, model application to luteal phase samples distinguished between N=5 SSRI responders from N=5 non-responders (AUC= 0.80, 95% CI: 0.50-0.80). HP1BP3 DNA methylation was significantly positively associated with levels of pregnenolone (rho= 0.35, p=0.014), suggesting it may be a marker of progesterone pathway precursor levels. Additionally, follicular phase TTC9B methylation was associated with the change in log(allopregnanolone) levels from follicular to luteal phases (rho= -0.53, p=0.02), suggesting it may be a marker of altered neuroactive steroid metabolism in the progesterone pathway. Conclusions This study suggests epigenetic PPD biomarkers can predict other hormonal depressions like PMDD and PMD. Furthermore, they may mark a biology related to variation of gonadal hormones like pregnenolone, the precursor to progesterone, and allopregnanolone, a neuroactive steroid important for modulating mood. Allopregnanolone, a target of recently approved PPD medications like Zuranolone(Althaus et al., 2020; Deligiannidis et al., 2021), can interact with the serotonin system and may be important for antidepressant medication response(Lovick, 2013; Lü scher and Mö hler, 2019). Future work should investigate the interaction of PPD biomarkers with medication response in hormonal depressions. References Althaus, A.L. et al. (2020) ‘Preclinical characterization of zuranolone (SAGE-217), a selective neuroactive steroid GABAA receptor positive allosteric modulator’, Neuropharmacology [Preprint]. doi:10.1016/j.neuropharm.2020.108333. Bloch, M. et al. (2000) ‘Effects of gonadal steroids in women with a history of postpartum depression’, American Journal of Psychiatry [Preprint]. doi:10.1176/appi.ajp.157.6.924.Deligiannidis, K.M. et al. (2021) ‘Effect of Zuranolone vs Placebo in Postpartum Depression’, JAMA Psychiatry [Preprint]. doi:10.1001/jamapsychiatry.2021.1559. Guintivano, J. et al. (2014) ‘Antenatal prediction of postpartum depression with blood DNA methylation biomarkers’, Molecular Psychiatry [Preprint]. doi:10.1038/mp.2013.62. Kaminsky, Z.A. et al. (2020) ‘Postpartum depression biomarkers predict exacerbation of OCD symptoms during pregnancy’, Psychiatry Research [Preprint]. doi:10.1016/j.psychres.2020.113332. Lapato, D.M. et al. (2020) ‘Predictive validity of a DNA methylation-based screening panel for postpartum depression’, medRxiv [Preprint].Lovick, T. (2013) ‘SSRIs and the female brain - Potential for utilizing steroid-stimulating properties to treat menstrual cycle-linked dysphorias’, Journal of Psychopharmacology [Preprint]. doi:10.1177/0269881113490327. Lü scher, B. and Mö hler, H. (2019) ‘Brexanolone, a neurosteroid antidepressant, vindicates the gabaergic deficit hypothesis of depression and may foster resilience.’, F1000Research [Preprint]. doi:10.12688/f1000research.18758.1. Osborne, L. et al. (2016) ‘Replication of epigenetic postpartum depression biomarkers and variation with hormone levels’, Neuropsychopharmacology [Preprint]. doi:10.1038/npp.2015.333. Payne, J.L. (2019) ‘Reproductive psychiatry: giving birth to a new subspecialty’, International Review of Psychiatry [Preprint]. doi:10.1080/09540261.2018.1579991. Payne, J.L. et al. (2020) ‘DNA methylation biomarkers prospectively predict both antenatal and postpartum depression’, Psychiatry Research, 285. doi:10.1016/j.psychres.2019.112711. Payne, J.L., Palmer, J.T. and Joffe, H. (2009) ‘A reproductive subtype of depression: Conceptualizing models and moving toward etiology’, Harvard Review of Psychiatry [Preprint]. doi:10.1080/10673220902899706.

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