Depression, Estrogens, and Neuroinflammation: A Preclinical Review of Ketamine Treatment for Mood Disorders in Womens

Szewczyk and colleagues open by situating the problem: women experience major depressive disorder at roughly twice the rate of men during adolescence and early adulthood, and ovarian steroid hormones (principally 17β-estradiol and progesterone) are implicated in that sex difference. The introduction reviews clinical phenomena linking hormone fluxes to mood—post-partum depression, premenstrual dysphoric disorder and menopause-related mood change—and notes that simple models that equate low ovarian hormones with depression are inadequate because some conditions involve heightened hormone sensitivity rather than absolute deficits. Against this background, the review sets out to synthesise preclinical evidence about how ketamine exerts antidepressant effects in the female brain, with particular attention to interactions with estrogens, progesterone and neuroinflammatory processes (especially microglia and the kynurenine pathway). The authors frame the neuroinflammatory hypothesis of depression as a potentially useful lens for understanding sex-specific ketamine effects and identify the hippocampus as a candidate brain region for hormone–ketamine interactions.

The extracted text presents this work as a narrative, preclinical review that integrates animal, in vitro and selected clinical findings to explore mechanistic interactions among ketamine, ovarian hormones and neuroinflammation. However, the extraction does not clearly report a formal methods section: no search strategy, databases, date range, inclusion/exclusion criteria or explicit quality assessment method are provided in the available text. Instead, the authors draw on a body of basic-science studies (rodent behavioural and molecular work, cell-culture experiments), selected clinical trial and biomarker studies, and prior meta-analyses to assemble mechanistic arguments. Where sample sizes or study details are given in the source text (for example, a clinical trial of racemic versus S-ketamine with N = 63, a meta-analysis of 24 studies with N = 1,877, and a small TRD cohort with N = 15), those data are reported within the Results synthesis rather than in a methods protocol. Because the review appears to be synthetic and conceptual rather than a systematic review, methodological transparency about literature selection is limited in the extracted text.

Epidemiology and ovarian hormones: The review reiterates that depression prevalence is approximately two-fold higher in women aged about 14–25, with sex differences diminishing in late adulthood. Clinical syndromes tied to hormone changes are summarised: post-partum depression affects an estimated 7–20% of women after childbirth, and premenstrual dysphoric disorder affects about 3–8% of premenopausal women. A meta-analysis cited in the text reported an effect size of d = 0.69 for estradiol (E) reducing depressed mood in menopausal women, whereas progesterone (P) alone or combined with E had smaller effects. The authors stress that hormonal effects are complex—some conditions reflect heightened sensitivity to normal hormone profiles rather than simple deficiency. Theories of depression: Multiple mechanistic frameworks are reviewed. The monoamine hypothesis is presented as incomplete, given the delayed clinical action of monoaminergic antidepressants. The glutamate hypothesis links excessive glutamatergic transmission, impaired glial clearance and excitotoxicity to brain atrophy observed in MDD. The neurotrophic hypothesis emphasises stress-induced reductions in neurogenesis and trophic factors such as brain-derived neurotrophic factor (BDNF), with evidence that antidepressant interventions increase BDNF and neurogenesis. The neuroinflammatory (cytokine) hypothesis is highlighted for integrating immune, monoamine and neurotrophic pathways: pro-inflammatory cytokines and microglial activation can decrease neurogenesis and shift tryptophan metabolism toward neurotoxic kynurenine metabolites such as quinolinic acid (QUIN), thereby linking inflammation to glutamatergic dysfunction and serotonin depletion. Ketamine mechanisms: The review covers several proposed mechanisms for ketamine's rapid antidepressant effects. The glutamate burst (disinhibition) hypothesis posits that ketamine preferentially blocks NMDA receptors on fast-firing GABA interneurons, causing disinhibition of pyramidal cells, a presynaptic glutamate surge, postsynaptic AMPA receptor activation, BDNF release and subsequent mTORC1-dependent increases in spine density and synaptogenesis. Alternative mechanisms are described: an eEF2-kinase model in which NMDA blockade reduces eEF2 phosphorylation and thereby permits rapid protein translation including BDNF; and a metabolite-centred model in which ketamine's antidepressant actions are mediated by hydroxynorketamine (2R-6R/2S-6S HNK) metabolites acting at AMPA receptors. The authors note enantiomeric affinity differences (reported Ki values in the text: R-ketamine Ki ≈ 2.57, S-ketamine Ki ≈ 0.69) and preclinical evidence that deuterated (non-metabolised) ketamine lacks antidepressant-like effects, supporting a role for metabolites. Sex differences in ketamine effects: Preclinical studies show sex-specific differences. Female rodents often display different behavioural and synaptic responses to stress and to ketamine than males: for example, social isolation stress decreased medial prefrontal cortex (mPFC) spine density and synaptic proteins in both sexes but produced anhedonia (sucrose preference reduction) that ketamine reversed in males but not females in the cited rodent model. Females reportedly require about half the minimum dose of ketamine compared with males to achieve antidepressant-like effects in some rodent paradigms, but this greater sensitivity depended on the presence of both estradiol and progesterone. Some molecular responses to ketamine differ by sex—for instance, ketamine did not decrease eEF2 levels in the hippocampus and PFC of female rats while it consistently did so in males. Metabolite production also differs: females produce higher levels of 2R/6R and 2S/6S HNK than males, which may relate to higher expression of CYP2A6 and CYP2B6 enzymes; E2 and P can induce these enzymes. By contrast, clinical meta-analyses cited in the text generally did not find robust sex differences in ketamine’s antidepressant efficacy, or found only modest male advantages at day 7 post-infusion; however, the review emphasises that clinical trials and meta-analyses have largely not stratified or tested sex differences comprehensively. Microglia, kynurenine pathway and ketamine: Several preclinical lines link ketamine with attenuation of microglial-driven neuroinflammation. Lipopolysaccharide (LPS) models induce microglial QUIN production; higher QUIN has been observed in cerebrospinal fluid of suicide victims and in microglia of severely depressed post-mortem brains. Ketamine reversed LPS-induced depressive-like behaviour in rodents even when given after inflammation had been established, and in some studies ketamine reduced QUIN in brain parenchyma without altering peripheral cytokine levels. In a small clinical cohort (N = 15) with treatment-resistant depression, the pre-treatment KYNA:QUIN ratio and QUIN plasma concentrations predicted response to ketamine, with QUIN levels being the strongest predictor of change in Montgomery–Åsberg Depression Rating Scale (MADRS) scores. In vitro and animal studies further show that ketamine can reduce microglial pro-inflammatory cytokine release and blunt LPS-induced microglial activation. Ovarian hormones and microglia: The review summarises evidence that estradiol (E2) and progesterone (P) modulate microglial phenotype via multiple receptors. E2 acts via nuclear ERα and membrane-associated receptors including GPER1 to produce broadly anti-inflammatory and neuroprotective effects in microglia (reducing phagocytic markers, cytokine release and reactive morphology). GPER1 agonism attenuates LPS-induced TNF-α and IL-1β increases in rodent models, and GPER1 antagonism blocks E2’s anti-inflammatory effects. Progesterone acts via classical nuclear progesterone receptors and via membrane-associated progesterone receptor components such as PGRMC1; evidence is mixed because PGRMC1 activation by P has been reported to induce microglial activation and inhibit neurite outgrowth, while other studies report P attenuating LPS-induced pro-inflammatory markers and NF-κB activation. Thus, the data suggest potential antagonistic interactions between E2 and P on microglial activation depending on receptor context and experimental conditions. Interactions between ketamine and ovarian-hormone systems: Notably, in vitro binding assays and surface plasmon resonance experiments cited in the review indicate that ketamine and its HNK metabolites can bind to ERα in cultured astrocytes, promote ERα nuclear trafficking and additively induce AMPA receptor subunit expression; ERα knockdown abolished the AMPA induction. The authors hypothesise a potential positive feedback loop whereby ERα-driven transcription upregulates CYP2A6 and CYP2B6 (ketamine-metabolising enzymes) and AMPA subunits, thereby increasing metabolite formation and AMPA-mediated signalling. The hippocampus is highlighted as a promising locus for these interactions because it shows volume reductions in MDD, is a site of adult neurogenesis influenced by BDNF and estrogens, and is sensitive to both inflammatory signalling and ketamine’s synaptogenic effects.

The authors interpret the assembled evidence as indicating that ovarian hormones are likely to interact meaningfully with ketamine’s mechanisms of action, particularly via effects on microglia, BDNF signalling and ketamine metabolism. They argue that the neuroinflammatory hypothesis of depression provides a useful integrative framework: pro-inflammatory microglial activity and kynurenine-pathway shifts toward neurotoxic metabolites (for example QUIN) can link stress, monoamine changes and neurodegeneration, and ketamine appears capable of countering some of those processes in preclinical models. Szewczyk and colleagues emphasise that much of the mechanistic literature has been generated in male animals or male-biased experimental systems, so generalising those mechanisms to females is problematic. They note contradictory findings about progesterone’s role—some work implicates PGRMC1-mediated microglial activation, while other experiments show progesterone attenuates LPS-induced inflammatory signalling—highlighting receptor- and context-dependent effects. The authors also underscore preliminary evidence that ketamine and HNK metabolites interact with ERα and with CYP enzymes, raising the possibility of hormone-dependent modulation of ketamine metabolism and downstream AMPA/BDNF signalling. Key limitations acknowledged in the extracted text include the predominance of male-preclinical data, reliance on in vitro models for many receptor-level findings, small human biomarker studies, and the absence of a systematic literature-search method reported in the paper. For future research, the authors call for targeted in vivo experiments—particularly in the hippocampus—explicitly designed to evaluate ketamine–hormone–microglia interactions in females, and for clinical studies and meta-analyses that stratify and test sex differences. They frame this work as important for safely and effectively expanding ketamine-based treatments to women at scale, given the sex-specific biological complexity.

The conclusion reiterates that major depressive disorder has a complex, multifactorial aetiology and that ovarian hormones are plausibly implicated in the higher incidence of MDD in women. While ketamine is supported by multiple mechanistic hypotheses, evidence specific to female biology is sparse and sometimes contradictory. Considering neuroinflammatory mechanisms, and microglia in particular, may help clarify how ketamine interacts with estradiol and progesterone. The authors call for more in vivo hippocampal research in females to resolve these questions before ketamine or related compounds are widely applied in female patient populations.