Skip to main content
Download PDF
Download ePub

The role of gut microbiota in the pathogenesis and treatment of postpartum depression

Annals of General Psychiatry volume 22, Article number: 36 (2023) Cite this article

Abstract

Postpartum depression (PPD) is a common complication of pregnancy in women, and its pathogenesis mainly involves disturbances of the neuroendocrine regulation, immune system, neurotransmitters, hormone secretion, and the gut microbiome. Gut microbes play essential physiological and pathological roles in the gut-brain axis’ pathways which are involved in various central nervous system (CNS) and psychiatric disorders, including PPD. Numerous studies have identified the fundamental role of the gut-brain axis in the pathogenesis and treatment of PPD patients and also correlates with other pathogenic mechanisms of PPD. Disturbances in gut microbes are associated with the disruption of multiple signaling pathways and systems that ultimately lead to PPD development. This review aimed to elucidate the potential connections between gut microbes and the established PPD network, and this might serve as a guide for the development of new efficient diagnostic, therapeutic, and prognostic strategies in the management of PPD.

Introduction

Postpartum depression (PPD) is one of the common complications of childbirth occurring in 10%–15% of women and is mainly characterized by depression, sadness, frustration, crying, irritability, hallucinations, suicide drives, and a series of symptoms of mental disorders[1, 2]. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR) assigns a “postpartum depression” specifier to episodes of depression that begin within six months of delivery. PPD has been variously defined as depression occurring between 4 weeks and 12 months after childbirth [2]. Predictors of PPD include perinatal anxiety, psychiatric illness, life stress, social isolation, low self-esteem, low socioeconomic status, obstetric complications, history of physical abuse, postpartum medical complications, and family history of PPD [3,4,5,6]. As many as 70% of pregnant women experience mild depression or depressive episodes, mainly in early and mid-pregnancy [2, 7]. The prevalence of PPD is also influenced by medical and economic conditions, ranging from 10% in high-income countries to more than 20% in some low- or middle-income countries. Additionally, PPD may also be aggregated in families, with women more likely to develop PPD if a sister or mother had the disorder [8, 9].

PPD is not limited to mothers but extends to fathers as supported by a recent meta-analysis of 74 studies which revealed the prevalence of PPD in fathers to be 8.4% [10]. Some of the risk factors for paternal PPD appear to be similar to those for maternal PPD, including primarily financial stress and a past history of depression [10,11,12]. The natural duration of PPD is variable, with most cases subsiding with treatment within a few months, but 24% and 13% of women diagnosed with PPD remain depressed 1 and 2 years after delivery, respectively [13]. PPD is often distinguished from other complications of childbirth. Shortly after delivery, women usually experience a mild transient syndrome of depressed mood or irritability often referred to as “postpartum blues” or “postpartum psychosis”, which often lasts less than a few weeks and may progress to postpartum depression [14, 15].

In addition, PPD is not only a source of huge economic and medical burden to the society and individuals but also a source of familial conflicts. Children of mothers with PPD often suffer adverse consequences in the long-term [16,17,18] which among others include decreased feeding, lack of verbal communication and emotional bonding, which can lead to reduced language competence and activity levels, increasing family conflicts and thereby affecting the harmony of the whole family [19]. Moreover, PPD-related suicide has been reported to be the second most common cause of death in postpartum women [20]. There is still a lack of safe and effective therapeutic options, both Traditional Chinese medicine (TCM) and Western medicine, due to the sensitivity of pregnant women to medications. Therefore, the exploration of new treatments for PPD has become extremely urgent. In recent years, gut microbiota has been shown to play an important role in the onset and progression of the central nervous system and psychiatric disorders. Interestingly, PPD occurs mainly after delivery, and dramatic changes in gut microbiota are also major postpartum events [21]. This, together with the fact that gut microbiota plays a key regulatory role in depression progression, lets us speculate that gut microbiota is likely an additional key causative factor in PPD.

There are about 3 million genes of intestinal microorganisms in the human body, which is more than 100 times the number of the human genome [22]. The Firmicutes and Bacteroides are the most prominent phyla in the human gut and constitute more than 75% of the intestinal microorganisms [23]. The ability of intestinal microorganisms to play a wide range of biological roles depends largely on their quality and quantity. It has been first observed that gut microbiota exhibit differences in terms of microbial composition and abundance between obese and lean individuals [24]. Subsequent studies have gradually highlighted the link between gut microbes and various systemic disorders, including CNS disorders, immune system disorders, and PPD.

The pathogenesis of PPD has not been fully elucidated but it is believed to involve four aspects including brain dysfunction, the hypothalamic–pituitary–adrenal (HPA) axis, immune response, and the brain-gut axis [25]. The causal relationship between gut microbes and mental illness through the gut-brain axis has attracted much attention in recent years. The bidirectional regulation of the gut-brain axis has been investigated for many years and includes the autonomic nervous system (ANS), neuroendocrine system, and metabolism-related pathways, and disturbances in these pathways have been found to be associated with PPD [26, 27]. This is supported by a recent meta-analysis study which showed changes in gut microbiota in patients with depression at phylum and genus levels compared to controls [28], suggesting the important role of gut microbes in the pathophysiology of depression. Differences in gut microbiota are also evident between pregnant women with PPD and those without PPD [29]. In addition to the altered gut flora, the microbial-derived metabolites, including those associated with bile acids and tryptophan metabolism, were also reported to be altered accordingly and thus have an impact on the host organism [30]. Therefore, this implies that intestinal microorganisms play an important role in regulating the homeostatic balance of the PPD.

PPD presents with unique features including altered immune, endocrine, and nervous systems, and epigenetic alterations. Interestingly, changes in any of these systems can alter the homeostasis of microbial composition and structure, suggesting that the gut microbiome might be a pivotal point among the above-mentioned systems [31]. Moreover, several studies reported numerous changes in gut microbes throughout pregnancy [32, 33], hence, gut microbes might serve as a biomarker for PPD. The next sections will highlight the current evidence on the changes in gut microbes in the PPD model and their possible association with other pathogenic factors. Search procedures and study selection Relevant studies were identified by searching Web of Science and PubMed using postpartum depression and gut microbiota as keywords to search terms. Existing meta-analyses, relevant reviews and reference lists of retrieved articles were examined for further relevant studies. DSM-5-TR criteria defined disorders were also used as review disease references. This review belongs to an inductive review, which focuses on the introduction of postpartum depression and gut microbiota and the direct regulatory.

Gut microbiota and postpartum depression

Function of normal gut microbiota

A vast amount of research has led to a better understanding of the role of gut microbes in human health and disease development. It is clearly known that metabolic molecules from the gut microbiota can cross the intestinal epithelium into the internal circulatory system to act on the central nervous system. Microbial metabolism produces short-chain fatty acids (SCFA), catecholamines, histamines, gamma-aminobutyric acid (GABA), and other microbial neuromolecules that may directly or indirectly affect brain metabolism and function [34, 35]. Gut microbes are key regulators of the gut-brain axis, and different gut microbes can influence the production of neurotransmitters and precursors such as serotonin, GABA, and tryptophan and regulate the secretion of metabolites including neuropeptides, brain-derived neurotrophic factor (BDNF), and short-chain fatty acids [36,37,38]. In turn, external stress stimuli can influence the brain to regulate cortisol release and control gut enteric nervous system function and gut mucosal protein production [39, 40]. In addition, the bidirectional signaling of the gut-brain axis not only influences the CNS but also involves both arms of the ANS, including sympathetic and parasympathetic, and regulates the enteric nervous system (ENS) [41]. Therefore, the gut microbiota is a central component of the immune and metabolic system of the host and also can influence the etiopathogenesis of enteric and CNS diseases such as motility, behavioral, and neurodegenerative disorders [42]. The interrelation of gut microbiota and the nervous system via the gut-brain axis suggests that alterations in the gut microbes could be associated with the etiopathogenesis of PPD.

Changes in gut microbiota and its related metabolites in PPD

Gut microbes are highly associated with molecules related to pathophysiological mechanisms involved in PPD. Recent studies have shown that gut microbes can be involved in multisystem regulation to cause the development of depression-like phenotypes in hosts [43,44,45,46]. The PPD phenotype mainly includes anxiety- and depression-like symptoms, and changes in gut microbiota are highly correlated with these phenotypes, suggesting that the gut microbiota is likely to be implicated in the development of PPD after childbirth [47]. Gut microbes are an important regulator of the host homeostasis, and are subjected to drastic changes after delivery. However, when these changes become uncontrollable, they can easily lead to gut microbiota disorders, which, in turn, increase the risk of PPD. Although changes in gut microbiota vary between different PPD models, in general, the variation mainly involves the Bacteroides, Firmicutes, and Lactobacillus phyla [48, 49].

Several studies have reported changes in the gut microbiota in humans and rodents with PPD (Table 1). In a high-fat-diet (HFD)-induced PPD mice model, it was found that at the phylum level, increased abundance of p_Actinobacteria, p_Proteobacteria, p_Deferribacteres, p_unkunown_Unassigned, and p_Verrucomicrobia was accompanied by decreased abundance of p_Bacteroidetes, p_Cyanobacteria, and p_TM7 in PPD mice [29]. At the genus level, increased abundance of g_Lactobacillus, g_Desulfovibrionaceae, and g_Christensenellaceae was accompanied by decreased abundance of g_unknown_S24-7, g_F16, and g_Flexispira compared to the control mice [29]. A similar trend was found in rats in a gestational diabetes mellitus (GDM)-induced PPD model. In this study, an increase in the abundance of f_Prevotellaceae, f_Ruminococccaceae, f_Peptococciaceae, f_Coriobacteriaceae, g_Prevotella, g_Lactobacillus, and g_Paraprevotella and a decrease in the abundance of p_Actinobacteria, p_Clostridiales, f_Lachnospirnaceae, g_Helicobacter, g_Clostridium XlVa, and g_Ruminococcus was reported in the PPD group compared to the control [50]. In addition to rodents, direct evidence of changes in gut microbiota has been found in human PPD patients. In a study examining 16 healthy and 28 patients with PPD, an increase in the abundance of p_Actinobacteria, p_Bacteroidetes, and f_Enterobacteriaceae was found to be accompanied by a decrease in the abundance of p_Firmicutes, f_Faecalibacterium, f_Phascolarctobacterium, f_Butyricicoccus, f_Lachnospiraceae, g_Faecalibacterium, g_Phascolarctobacterium, g_Butyricicoccus, and g_Megasphaera in PPD patients [51]. Moreover, prenatal and postnatal stress in rhesus monkeys has been shown to alter the composition and the total number of gut microbes, with the greatest variation in Lactobacillus [52, 53]. Interestingly, the ratios of Firmicutes and Bacteroidetes (F/B) significantly increased in the postpartum depressive subjects in the above-described studies [52, 53]. These changes in the gut microbiota in the depressed subjects provide direct evidence of the relationship between gut microbiota and PPD, suggesting that alterations in gut microbiota might likely play a major role in the development of PPD in both rodents and humans.

Table 1 Changes in gut microbiota in different animal models and humans with postpartum depression (PPD)
Full size table

In different models of PPD, the changes in gut microbiota are accompanied by other molecular changes. For example, in rodent PPD models, perturbations in the microbiome have been associated with a decrease in 5-hydroxytryptamine (5-HT, also known as serotonin), and norepinephrine (NE), and inflammatory response, in combination with cognitive deficits and depressive-like behaviors [29, 50]. However, in human PPD patients, changes in certain gut microbiota have been linearly related to age, weight, body mass index, and sex hormones [55]. The molecular changes in the PPD models are very variable according to the model, but gut flora disorders occur in all the above-mentioned PPD models. From this perspective, it is likely that gut microbiota is probably a major factor in PPD pathogenesis. This is supported by the fact that external interventions, including high-dietary fiber intake or 919 syrup, were able to reverse gut microbiota disorders and their corresponding depressive-like symptoms [29, 54]. It has also been reported that the decrease in the endogenous anti-inflammatory mediators as well as a decrease in the omega-polyunsaturated fatty acids (PUFA), which are observed after parturition, might play a role in the development of PPD [56]. Interestingly, the gut microbiota is central to the host lipid metabolism [57] suggesting that alterations in the gut microbes following child birth could be related to these changes. Moreover, many studies have reported that fecal microbiota transplantation (FMT) can induce or reverse gut microbiota disorders and the accompanying cognitive impairment and depression-like symptoms in the CNS and psychiatric disorders. Varying microbiome levels from phylum to genus are likely to correlate with the microbiome abundance and diversity of the species [58,59,60]. It is also clear from the above-described studies that gut microbiota might be a critical player in the study of mechanisms related to PPD. Thus, we would further describe the interrelation between gut microbiota and the molecular alterations that occur in PPD in the next section.

Mechanisms of gut microbiota implication in PPD pathogenesis

Also defined as the second brain of the human body, gut microbiota might play a central role in psychiatric disorders, including PPD. Previous studies have demonstrated that alterations in the gut microbiota occur in PPD, and these changes simultaneously modulate multiple systemic molecules including estrogen and progesterone, 5-HT, SCFA, and amino acids (AAs) and the HPA axis to jointly induce PPD (Fig. 1).

Fig. 1
figure 1

A variety of factors including genes and the external environment can affect the internal HPA axis, immune system, and metabolic disorders through the gut-brain axis and thus contribute to PPD

Full size image

Estrogen and progesterone

Estrogen is a protein produced by the ovaries and placenta that promotes the development of secondary sexual characteristics and the maturation of sexual organs in females. Natural estrogens mainly include estradiol, estrone, and estriol. Oxytocin is a hormone associated with delivery, maternal attachment, and breastfeeding. Mothers with low oxytocin levels during pregnancy show a lower frequency of interaction with their infants, and low maternal oxytocin levels during pregnancy are significantly associated with an increased risk of postpartum pregnancy and susceptibility to PPD development [61]. During pregnancy dynamic, physiological changes affecting the reproductive, immune, nervous, and metabolic systems occur in all pregnant women and these are expected to resolve to a pre-pregnancy state after delivery. Unsuccessful return to normal pre-pregnancy state added to other risk factors has been shown to be associated with the onset of PPD [62]. Therefore, pregnant women undergo dramatic and sudden changes in hormonal levels, such as a decrease in steroid hormones (estradiol and progesterone) following parturition. Studies in this field have provided some evidence that PPD tends to be accompanied by low allopregnanolone and high cortisol concentrations, suggesting that hormonal alterations are closely related to PPD [63, 64]. For instance, the hormone withdrawal theory states that the dramatic postpartum drop in estradiol and progesterone is critical for the development of PPD [65, 66]. Interestingly, the certain gut microbiota is associated with the secretion of β-glucuronidase, an enzyme that breaks down estrogen into its most biologically active form [55, 67] suggesting that gut microbiota might be associated with systemic estrogen and progesterone levels. The disturbance of gut microbiota after delivery might, therefore, cause a dramatic decrease in both estrogens and progesterone by affecting key enzymes (e.g., β-glucuronidase) related to the production of hormones, thus, causing PPD onset. In the postpartum hypoestrogenic state, estrogen production is also a possible mechanism by which the microbiota is involved in PPD onset.

In PPD subjects, fluctuations in estrogen and progesterone levels can trigger changes in the HPA axis, causing women with PPD to be more insensitive to adrenocorticotropin-releasing hormone (CRH) and adrenocorticotropic hormone (ACTH) postpartum, relative to normal women [68, 69]. Sex steroid hormones, such as estradiol and progesterone, can modulate neurotransmitter systems, including the serotoninergic, GABAergic, and dopaminergic systems. In line with this, several studies have shown that an acute decrease in allopregnanolone levels after delivery might promote PPD through GABA receptors [70,71,72]. Although both estrogen and progesterone are significantly decreased in PPD, administration of both hormones was clinically unsuccessful in reversing PPD symptoms. This is supported by results from a study that showed that women with a history of PPD exhibited increased depressive symptoms after hormone supplementation compared to women without PPD [68]. However, another trial found that estrogen treatment might reduce PPD symptoms, but that synthetic progestin application increased the risk of PPD probably due to the complexity of the body’s biological systems and the fact that progestin supplementation might be influenced by other organismal systems, such as the gut-brain axis [73]. The wide variety and function of intestinal microorganisms can be involved in the estrogen and progesterone disorder of PPD through various biological enzymes.

Hypothalamic–pituitary–adrenal axis

As a classical pathway, the HPA axis plays a key role in the regulation of cortisol levels through the neuroendocrine system. The activation of the HPA axis stimulates the CRH release from neurosecretory cells in the hypothalamus which in turn stimulates ACTH secretion from the anterior pituitary, which enters the circulation and stimulates the production of glucocorticoids from the adrenal cortex, most notably cortisol [74].

Many researchers have investigated the implication of the HPA axis in depression. For instance, the HPA axis was shown to be activated in response to internal and external stresses causing increased cortisol in depressed subjects [75]. Interestingly, cortisol is the major stress hormone that affects intestinal integrity, motility, and mucus production and might cause changes in the composition of the gut microbiota. Upregulation of this pathway has been reported in depressed patients, ultimately resulting in irritable bowel syndrome and disruption of the gut microbiota [76]. Interestingly, pregnant women with PPD exhibit more pronounced changes in cortisol after social stress [77]. Moreover, women who developed PPD after delivery have elevated CRH levels in mid-pregnancy, and the severity of PPD positively correlates with CRH levels, compared to women who did not develop PPD after delivery, however, ACTH, another protein in the HPA axis, was not correlated with PPD [78, 79].

The gut microbiota is believed to be one of the potential mechanisms regulating the HPA axis via both the activation and inhibition of the HPA axis. Consistently, a study examining the relationship between the HPA axis and stress has found that germ-free (GF) mice showed significantly elevated plasma ACTH and corticosterone levels with a decreased expression of BDNF in the hippocampus and cortex after undergoing restraint stress compared to specific pathogen-free (SPF) mice [40]. Interestingly, the HPA axis activation exhibited by the GF mice could be reversed by Bifidobacterium remodeling [40]. In a rat PPD model, the disturbance of gut microbiota was also accompanied by changes in cortisol, suggesting a regulatory role of gut microbiota in the activation of the HPA axis [50]. Together, the data reviewed here provided experimental evidence for the role of gut microbiota in the modulation of PPD through the HPA axis.

5-hydroxytryptamine (5-HT)

The discovery in the middle of the last century that the anti-hypertensive reserpine triggered major depression and reduced monoamines raised interest in monoamine neurotransmitters (serotonin, norepinephrine, and dopamine) research. These pathological changes are thought to underlie many neurological and psychiatric disorders, including PPD [80]. Serotonin is one of the most significant neurotransmitters involved in mood generation, and years of clinical research support the central role of 5-HT in the pathophysiology of depression. Consistent with this, a reduced affinity for serotonin and platelet receptors and a reduced action of serotonin in the brains of women with PPD were reported [81]. Moreover, in PPD, a decline in 5-HT production was observed and this is thought to be among the main causes of depressive episodes. In addition to changes in serotonin, tryptophan, the sole precursor of serotonin, is also disturbed during pregnancy [82, 83]. Interestingly, many studies have highlighted the role of gut microbiota in the metabolism of both serotonin and tryptophan.

The regulation of host 5-HT has been reported to be influenced by different gut microbiota. For example, the spore-forming bacteria (Sp) and their specific metabolites were found to promote 5-HT biosynthesis in colonic enterochromaffin cells (ECs) and increase blood, mucosal, and lumen 5-HT levels [84]. In addition, the regulation and production of 5-HT have been reported to be influenced by other microbes including s_Candida, s_Streptococcus, and s_Escherichia [85]. Interestingly, it was found that colonic colonization levels and 5-HT levels have been significantly decreased in GF mice, whereas tryptophan hydroxylase 1, the rate-limiting enzyme in 5-HT biosynthesis, was significantly increased in GF mice after microbiota transplantation from normal mice [86], suggesting a pivotal role of commensal gut microbiota in regulating 5-HT homeostasis. In a chronic unpredictable mild stress (CUMS) depression mouse model, Clostridium butyricum was found to attenuate depressive-like behavior by increasing 5-HT, Glucagon-like peptide-1 (GLP-1), and Glucagon-like peptide 1 receptor (GLP-1R) concentrations and upregulating BDNF expression [87]. Similarly, Lactobacillus was used to examine the alleviating effects in the CUMS depression model, and Bifidobacterium E41 and Bifidobacterium breve M2CF22M7 significantly reduced depression-like behaviors in forced swimming and sugar-water preference experiments in mice. Further investigation of the underlying mechanisms revealed that these microbes increased 5-HT and BDNF levels in the mouse brain [88], suggesting that E41 and M2CF22M7 exert antidepressant-like effects in depressed mice in a 5-HTP-dependent and microbially regulated manner. In a study examining the effect of gut microbiota and antidepressants, Bifidobacteria was found to reduce depression-like phenotypes through the 5-HT reuptake pathway compared to antidepressants [89]. In the HFD-induced PPD mice model, disruption of gut microbiota was accompanied by depressive-like behavior, while high dietary fiber (inulin) intake prevented disruption of gut microbiota and depressive-like behavior in PPD through the microbial-gut-brain axis [29]. Further analysis indicates that an increase in microorganisms such as Lactobacillus and S24-7 as well as 5-HT tryptophan regulation play a major role in the improvement of depression-like symptoms. In another study, FMT intervention on the early gut microbiota of neonatal piglets was able to regulate serotonin and tryptophan metabolism in the host [90], providing a new basis for the regulation of depression-like phenotypes by the gut microbiota through the regulation of tryptophan metabolism.

Short-chain fatty acids (SCFAs)

Some of the gut microbiota-derived metabolites include SCFAs which are important mediators in the gut-brain axis. SCFAs can reduce chronic inflammation through direct consumption producing local and systemic effects through host cells, or binding to host cell receptors, which is a common marker of PPD [91]. This suggests that the level of SCFA intake and production during pregnancy might also impact the PPD status in pregnant women, indicating the role of SCFAs in PPD.

The depressive symptoms in PPD could be affected by the composition as well as the structure of the individual microbiome through the gut-brain axis. In an HFD-induced mouse model of PPD, high dietary fiber intake prevented gut microbiota disturbances and depression-like behaviors by remodeling gut microbiota and increasing SCFA levels, including acetate, propionate, butyrate, and isovalerate [29]. Also, it was found that in depression patients the production of gut-associated microbial metabolites, such as tryptophan and SCFA, is associated with serotonin metabolism and HPA axis regulation [92, 93]. Consistent with this, it was reported that bacterial end-products such as acetate, propionate, and butyrate, all increase the expression of tyrosine and tryptophan hydroxylases which are involved in the synthesis of dopamine, norepinephrine, and serotonin, and thus, are critical for neurotransmission processes [94,95,96]. Moreover, it has been identified that gut microbiota can regulate kynurenic acid by affecting tryptophan production, and steroid and glucocorticoid levels by SCFA-mediated stimulation of the serotonin synthesis in the intestinal endothelium [86, 97]. Some microorganisms present in our gut, e.g., Akkermansia muciniphila and Ruminococcus obeum, can degrade fiber into SCFA such as acetic acid, propionic acid, and butyric acid [98], which might explain the ameliorative effect of high dietary fiber intake in HFD-induced PPD in mice. Some reports have suggested that butyrate might have antidepressant-like properties [91, 98]. Particularly, sodium butyrate was reported to significantly improve depression-like behaviors in CUMS-induced mice at least in part via increasing brain 5-HT level, BDNF expression, and improving Blood–brain barrier (BBB) impairments [91]. Moreover, sodium butyrate was reported to improve aversive memory impairment, depression-like behaviors, and hippocampal microglial activation via inhibiting histone deacetylase and increasing the levels of Ten-Eleven Translocation 1 (TET1), 5-HT, and BDNF expression [99,100,101]. Lipophilic SCFAs readily cross the blood–brain barrier to reach the brain and directly interact with neurons. The application of sodium butyrate has restored normal levels of the prefrontal cortex, hippocampus, striatum, and amygdala and reversed depressive- and manic-like behaviors in rats [102]. The above-mentioned evidence indicates that SCFA is an intermediate molecule in the depression-like phenotype and could be modulated by gut microbiota.

Amino acids

Recently, disruptions in AA in both GDM-induced rat PPD and stress-induced mouse PPD models were reported. In the rat PPD model, a decrease in the ratio of Firmicutes to Bacteroidetes as well as a decrease in the expression of tryptophan hydroxylase (TPH), a key enzyme in the 5-HT production pathway, resulted in a significant decrease in 5-HT, while in the mouse PPD model, the disruption of the gut microbiota was accompanied by a significant decrease in 4-aminobutyric acid [50, 54]. Meanwhile, blood levels of the AA serine, methionine, asparagine, glutamine, and tryptophan were reported to be reduced in depressed patients, whereas elevated plasma levels of phenylalanine, aspartate, serine, and γ-glutamyl AAs were found in such patients [103, 104]. Importantly, these studies demonstrated that the changes in plasma AA levels correlate with changes in AAs observed with gut microbial metabolism which might be the pathological basis for gut microbial-induced depression. These studies indicate that some of these AAs and their bacterial-derived metabolites might serve as biomarkers of PPD in clinical practice. Glutamate (or glutamine) is another disturbed AAs and their levels are significantly elevated in the brain, cerebrospinal fluid, and plasma of patients with depression [105]. Glutamate is an agonist of the N-methyl-d-aspartate (NMDA) receptor, and interestingly, NMDA receptor antagonists such as ketamine have been reported to show rapid antidepressant properties in animal models of depression as well as in depressed patients, by inhibiting glutamatergic neurotransmission [106].

In agreement with the data reviewed above, the metabolic interaction of AAs in the host and the microbes as biomarkers of PPD is present in many gut bacterial species. Such interactions between bacteria and hosts occur at both local and systemic levels. AA metabolites involved in branched-chain AA synthesis, namely leucine, isoleucine, threonine, and methionine, have been shown to be dysregulated in patients with major depressive disorder (MDD) [107]. The main members of the AA-producing gut microbiotas are s_Streptococcus, Staphylococcus aureus, Escherichia coli, s_Klebsiella, s_Ruminomonas, Ehrlichia megaterium, s_Proteus, s_Synechococcus, and s_Clostridium [108]. These gut microbes can directly influence the onset of PPD through AA production and modulation. Among these AA, alanine, arginine, glutamine, leucine, methionine, serine, tryptophan, and tyrosine have all been shown to exert some varying degrees of antidepressant effects in different experimental systems [109]. The microbe L. reuteri 3 was reported to increase the expression of serotonin biosynthesis enzymes while inhibiting the expression of enzymes involved in tryptophan metabolism in the kynurenine pathway in the frontal cortex, ultimately improving depression-like behavior [110]. Moreover, clinical studies have revealed that d-serine is one of many AAs with antidepressant effects similar to ketamine, as demonstrated in animal studies conducted in rodent models of depression [111, 112]. Therefore, the data reviewed here strongly suggest that disturbance of gut microbiota as seen in the PPD model as well as in PPD patients could often be reflected by changes in AAs as well suggesting that AAs play a critical role in PPD and could serve as potential biomarkers.

Other mechanisms

In addition to the above-discussed common pathophysiological mechanisms, many genetic and environmental factors are involved in the etiopathogenesis of PPD. For example, Specific genes encoding female reproductive hormones, stress, inflammation-related components, and neuropeptides were reported to be altered in PPD [113]. Genetic alterations in the serotonin transporter gene (SERT) oxytocin receptor (OXTR) gene, the oxytocin peptide gene, the glucocorticoid receptor gene, and the CRH receptor 1 gene have been associated with PPD [114]. Estrogen-induced DNA methylation is also associated with PPD development, suggesting a genetic component in PPD pathogenesis [115], and DNA methylation biomarkers were revealed to predict both antenatal and postpartum depression [116].

Numerous negative environmental factors can also exacerbate PPD onset. For instance, family misfortune, internal isolation, lack of cultural background, and low social status are all risk factors for PPD. Particularly, studies have highlighted that women who are in economic distress have a 2–3 times higher risk of developing PPD than women who are economically independent [117,118,119]. Although there are studies exploring the potential mechanisms of the external environment in PPD, more evidence is needed to understand its impact.

The immune system is also an integral part of the pathogenesis of depression. This is supported by the studies that indicate that prolonged HPA axis hyperactivity due to increased proinflammatory cytokines such as IL-1, IL-6, and TNF-α is one of the underlying mechanisms of cytokine-induced depression [120]. Moreover, a recent study also revealed that alteration in B-cell activation and insulin resistance might also be implicated in PPD [121]. Other factors like zinc, vitamin D, high-density lipoprotein (HDL)-cholesterol, and omics biomarker have all been reported to play a role in the development of PPD [114]. A lot of studies on PPD related to genetic, environmental, and other factors are ongoing, and many reviews have been published on the implications of genetic factors in the pathophysiology of PPD [114, 115, 122].

Treatment of PPD

Current prevention, diagnosis, and treatment strategies around PPD are severely underdeveloped, largely due to limited reporting by patients with PPD and reluctance to seek outside help, care, and pharmacological interventions, especially during breastfeeding. Screening after delivery is a key to early detection and diagnosis of PPD, and clinicians can improve the detection and diagnosis of PPD using a reliable screening tool, such as the Edinburgh Postpartum Depression Scale (EPDS) [123]. Given the specificity of maternal conditions, women with PPD tend to prefer psychotherapy to medication and want to avoid medication, especially while breastfeeding [124]. This occurs in form of counseling in one-on-one or group therapy. Moderate to severe PPD often requires medication administration to have a positive effect, and this usually results in the reduction of gut microbiota disturbances and depressive-like symptoms. The main antidepressants used in clinical practice are serotonin reuptake inhibitors (SSRIs), tricyclic antidepressants, serotonin–norepinephrine reuptake inhibitors (SNRIs), and monoamine oxidase inhibitors [125]. Among them, selective SSRIs have become the first-line drugs. The safety profile of SSRIs in breastfeeding is relatively high, with few reports of maternal and infant adverse effects [126]. SNRIs or mirtazapine are usually administered when SSRIs are ineffective or when these drugs were previously indicated for women, as the available data have suggested that SNRIs are rarely introduced into breast milk [127]. Monoamine oxidase inhibitors are used less frequently because of their potential side effects, and their safety during breastfeeding is also unknown. Unlike the above-preferred medications, tricyclic antidepressants are usually avoided during breastfeeding because of their potential entry into the breast milk and cardiac side effects [128]. Recently, an allopregnanolone-based PPD treatment brexanolone has been approved by the Food and Drug Administration (FDA) in the United States as a fast-acting and long-lasting antidepressant [114]. Widely used antidepressant therapeutic regimens still have a high number of drawbacks, including drug tolerance, delayed action, suboptimal efficacy, and various adverse effects [129]. Therefore, the search for new potential treatments for PPD is significant, and gut microbiota treatment might be a promising option.

Gut microbiota have a wide range of physiological roles, including nutritional delivery, engagement in human metabolism, immunity, regulation of brain function, regulation of bone density, and anticancer. Dysregulation of gut flora is closely associated with many diseases such as autoimmunity, metabolism, neurological disorders and even cancer, such as obesity, diabetes, inflammatory bowel disease, colorectal cancer and Alzheimer's disease [130]. Interestingly, normal microbiota can be restored through probiotics, prebiotics, diet, and fecal microbial transplantation in animal models [131,132,133]. Metabolite tryptophol acetate produced by probiotic yeast blocks group sensing of several pathogenic gram-negative bacteria, thereby inhibiting bacterial virulence [134]. Several studies in rodent and macaque models of depression have found that transplantation of normal microbiota to depressed animals reversed the host depression-like phenotype [60, 135]. These studies provide experimental evidence for the clinical application of gut microbiota therapy; however, it has not been yet performed in human PPD subjects.

Conclusion and perspective

PPD is one of the most common complications of childbirth, and if left untreated, it can have far-reaching negative effects on the mother, child, and the whole family. Thus, safer and more effective treatments are urgently needed. Research has revealed that disruptions in the gut microbiota, the “second brain” can lead to the development of multisystem diseases, including PPD. In this study, we reviewed data from both experimental and clinical research that indicate the implication of gut microbiota dysregulation in the pathogenesis of PPD. Direct evidence revealed gut microbiota disorders in patients with PPD, which are mainly clustered in phyla Firmicute, Bacteroide, and Actinobacteria in PPD. The molecular changes are highly variable in different types of PPD subjects, however, there are always gut microbiota disturbances. The application of gut microbiota remodeling in a PPD model can reverse gut microbiota disorders and their accompanying depressive-like symptoms. This suggests that gut microbiota plays a causative role in the bidirectional communication of the “gut-brain axis”, in which gut microbiota dysregulation might play a key role in PPD pathogenesis through various mechanisms including serotonin, hormones, and the HPA axis modulation.

Although a huge number of articles have been published on the link between gut microbiota and many diseases including depression, most of them are animal studies, especially fecal microbiota transplantation to treat depressive animals. While treatments for depression or postpartum depression have mostly focused on interventions with small clusters of metabolites, such as SSRIs, SNRIs, etc., those aimed at improving the gut microbiota environment for the treatment of depression have mostly focused on probiotics. However, there is still a long way to go in the research field of gut microbiota and its application in PPD patients. For example, the changes in gut microbiota in different PPD populations with disorders are slightly different, and there is no specific gut microbiota or a more convincing change pattern. The application of gut microbiota to clinical treatment will still take a long time to be realized due to the limitations of human experiments and the sensitive condition of pregnant women. Overall, there have been inspiring advances in the study of gut microbiota, and the corresponding specific changes in gut microbiota can be used as biomarkers of PPD risk for diagnosis, treatment, and prognosis. Most current reviews or articles focus on the etiology, pathogenesis, consequences, and treatment approaches of postpartum depression. This review provides a comprehensive and detailed overview of the role played by gut microbiota in the pathology of postpartum depression from the perspective of gut microbiota on postpartum depression. Gut microbiota therapy is a non-invasive and therefore, a more promising treatment modality, providing a desirable blueprint for the future clinical treatment of PPD patients. The development of specific biomarkers, genetic and epigenetic, for early and better diagnosis of PPD is a prerequisite for management of women with PPD.

Availability of data and materials

This manuscript, including all relevant raw data, will be freely available to any researcher wishing to use them for non-commercial purposes, without breaching participant confidentiality.

Abbreviations

AAs:

Amino acids

ACTH:

Adrenocorticotropic hormone

ANS:

Autonomic nervous system

BDNF:

Brain-derived neurotrophic factor

CNS:

Central nervous system

CRH:

Adrenocorticotropin-releasing hormone

CUMS:

Chronic unpredictable mild stress

ECs:

Enterochromaffin cells

ENS:

Enteric nervous system

EPDS:

Edinburgh Postpartum Depression Scale

FDA:

Food and Drug Administration

FMT:

Fecal microbiota transplantation

GABA:

Gamma-aminobutyric acid

GDM:

Gestational diabetes mellitus

GF:

Germ free

GLP:

Glucagon-like peptide-1

HFD:

High-fat-diet

HPA:

Hypothalamic–pituitary–adrenal

MDD:

Major depressive disorder

NMDA:

N-Methyl-d-aspartate

OXTR:

Oxytocin receptor

PPD:

Postpartum depression

PPP:

Postpartum psychosis

PUFA:

Omega-polyunsaturated fatty acids

SCFA:

Short-chain fatty acids

SERT:

Serotonin transporter gene

SNRIs:

Serotonin-norepinephrine reuptake inhibitors

SPF:

Specific pathogen free

SSRIs:

Serotonin reuptake inhibitors

TET-1:

Ten–Eleven Translocation 1

TPH:

Tryptophan hydroxylase

5-HT:

5-Hydroxytryptamine

References

  1. O’Hara MW, McCabe JE. Postpartum depression: current status and future directions. Annu Rev Clin Psychol. 2013;9:379–407.

    PubMed  Google Scholar 

  2. Pearlstein T, Howard M, Salisbury A, Zlotnick C. Postpartum depression. Am J Obstet Gynecol. 2009;200:357–64.

    PubMed  PubMed Central  Google Scholar 

  3. Beck CT. Predictors of postpartum depression: an update. Nurs Res. 2001;50:275–85.

    CAS  PubMed  Google Scholar 

  4. Gaillard A, Le Strat Y, Mandelbrot L, Keïta H, Dubertret C. Predictors of postpartum depression: prospective study of 264 women followed during pregnancy and postpartum. Psychiatry Res. 2014;215:341–6.

    PubMed  Google Scholar 

  5. Kimmel M, Hess E, Roy PS, Palmer JT, Meltzer-Brody S, Meuchel JM, Bost-Baxter E, Payne JL. Family history, not lack of medication use, is associated with the development of postpartum depression in a high-risk sample. Arch Womens Ment Health. 2015;18:113–21.

    PubMed  Google Scholar 

  6. Robertson E, Grace S, Wallington T, Stewart DE. Antenatal risk factors for postpartum depression: a synthesis of recent literature. Gen Hosp Psychiatry. 2004;26:289–95.

    PubMed  Google Scholar 

  7. ACOG Practice Bulletin: Clinical management guidelines for obstetrician-gynecologists number 92, April 2008 (replaces practice bulletin number 87, November 2007). Use of psychiatric medications during pregnancy and lactation. Obstetr Gynecol. 2008; 111: 1001–20.

  8. Forty L, Jones L, Macgregor S, Caesar S, Cooper C, Hough A, Dean L, Dave S, Farmer A, McGuffin P, Brewster S, Craddock N, Jones I. Familiality of postpartum depression in unipolar disorder: results of a family study. Am J Psychiatry. 2006;163:1549–53.

    PubMed  Google Scholar 

  9. Howard LM, Molyneaux E, Dennis CL, Rochat T, Stein A, Milgrom J. Non-psychotic mental disorders in the perinatal period. Lancet. 2014;384:1775–88.

    PubMed  Google Scholar 

  10. Cameron EE, Sedov ID, Tomfohr-Madsen LM. Prevalence of paternal depression in pregnancy and the postpartum: an updated meta-analysis. J Affect Disord. 2016;206:189–203.

    PubMed  Google Scholar 

  11. Kerstis B, Engström G, Edlund B, Aarts C. Association between mothers’ and fathers’ depressive symptoms, sense of coherence and perception of their child’s temperament in early parenthood in Sweden. Scand J Public Health. 2013;41:233–9.

    PubMed  Google Scholar 

  12. Leung BM, Letourneau NL, Giesbrecht GF, Ntanda H, Hart M. Predictors of postpartum depression in partnered mothers and fathers from a longitudinal cohort. Community Ment Health J. 2017;53:420–31.

    PubMed  Google Scholar 

  13. Sohr-Preston SL, Scaramella LV. Implications of timing of maternal depressive symptoms for early cognitive and language development. Clin Child Fam Psychol Rev. 2006;9:65–83.

    PubMed  Google Scholar 

  14. Sit D, Rothschild AJ, Wisner KL. A review of postpartum psychosis. J Womens Health (Larchmt). 2006;15:352–68.

    PubMed  Google Scholar 

  15. Henshaw C. Mood disturbance in the early puerperium: a review. Arch Womens Ment Health. 2003;6(Suppl 2):S33-42.

    PubMed  Google Scholar 

  16. Farías-Antúnez S, Xavier MO, Santos IS. Effect of maternal postpartum depression on offspring’s growth. J Affect Disord. 2018;228:143–52.

    PubMed  Google Scholar 

  17. Netsi E, Pearson RM, Murray L, Cooper P, Craske MG, Stein A. Association of persistent and severe postnatal depression with child outcomes. JAMA Psychiat. 2018;75:247–53.

    Google Scholar 

  18. Oh Y, Joung YS, Baek JH, Yoo N. Maternal depression trajectories and child executive function over 9 years. J Affect Disord. 2020;276:646–52.

    PubMed  Google Scholar 

  19. Goodman SH, Rouse MH, Connell AM, Broth MR, Hall CM, Heyward D. Maternal depression and child psychopathology: a meta-analytic review. Clin Child Fam Psychol Rev. 2011;14:1–27.

    PubMed  Google Scholar 

  20. Serati M, Carnevali G. Perinatal depression. In: Altamura AC, Brambilla P, editors. Clinical cases in psychiatry: integrating translational neuroscience approaches. Cham: Springer International Publishing; 2019. p. 155–70.

    Google Scholar 

  21. Simpson CA, Diaz-Arteche C, Eliby D, Schwartz OS, Simmons JG, Cowan CSM. The gut microbiota in anxiety and depression—a systematic review. Clin Psychol Rev. 2021;83: 101943.

    PubMed  Google Scholar 

  22. Yu Y, Raka F, Adeli K. The role of the gut microbiota in lipid and lipoprotein metabolism. J Clin Med. 2019;8:2227.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Diamant M, Blaak EE, de Vos WM. Do nutrient-gut-microbiota interactions play a role in human obesity, insulin resistance and type 2 diabetes? Obes Rev. 2011;12:272–81.

    CAS  PubMed  Google Scholar 

  24. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444:1027–31.

    PubMed  Google Scholar 

  25. Chaudhury D, Liu H, Han MH. Neuronal correlates of depression. Cell Mol Life Sci. 2015;72:4825–48.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Jiang H, Ling Z, Zhang Y, Mao H, Ma Z, Yin Y, Wang W, Tang W, Tan Z, Shi J, Li L, Ruan B. Altered fecal microbiota composition in patients with major depressive disorder. Brain Behav Immun. 2015;48:186–94.

    PubMed  Google Scholar 

  27. Rackers HS, Thomas S, Williamson K, Posey R, Kimmel MC. Emerging literature in the microbiota-brain axis and perinatal mood and anxiety disorders. Psychoneuroendocrinology. 2018;95:86–96.

    PubMed  PubMed Central  Google Scholar 

  28. Sanada K, Nakajima S, Kurokawa S, Barceló-Soler A, Ikuse D, Hirata A, Yoshizawa A, Tomizawa Y, Salas-Valero M, Noda Y, Mimura M, Iwanami A, Kishimoto T. Gut microbiota and major depressive disorder: a systematic review and meta-analysis. J Affect Disord. 2020;266:1–13.

    CAS  PubMed  Google Scholar 

  29. Liu Z, Li L, Ma S, Ye J, Zhang H, Li Y, Sair AT, Pan J, Liu X, Li X, Yan S, Liu X. High-dietary fiber intake alleviates antenatal obesity-induced postpartum depression: roles of gut microbiota and microbial metabolite short-chain fatty acid involved. J Agric Food Chem. 2020;68:13697–710.

    CAS  PubMed  Google Scholar 

  30. Ewelina M, Joanna G, Julita T, Joanna F, Aleksandra S, Beata F, Jacek R. The Role of the Microbiome–Brain–Gut Axis in the Pathogenesis of Depressive Disorder. Nutrients 2022;14(9):1921.

  31. Peñalver Bernabé B, Maki PM, Dowty SM, Salas M, Cralle L, Shah Z, Gilbert JA. Precision medicine in perinatal depression in light of the human microbiome. Psychopharmacology. 2020;237:915–41.

    PubMed  Google Scholar 

  32. Jašarević E, Howard CD, Misic AM, Beiting DP, Bale TL. Stress during pregnancy alters temporal and spatial dynamics of the maternal and offspring microbiome in a sex-specific manner. Sci Rep. 2017;7:44182.

    PubMed  PubMed Central  Google Scholar 

  33. Koren O, Goodrich JK, Cullender TC, Spor A, Laitinen K, Bäckhed HK, Gonzalez A, Werner JJ, Angenent LT, Knight R, Bäckhed F, Isolauri E, Salminen S, Ley RE. Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell. 2012;150:470–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Cheung SG, Goldenthal AR, Uhlemann AC, Mann JJ, Miller JM, Sublette ME. Systematic review of gut microbiota and major depression. Front Psychiatry. 2019;10:34.

    PubMed  PubMed Central  Google Scholar 

  35. Dalile B, Van Oudenhove L, Vervliet B, Verbeke K. The role of short-chain fatty acids in microbiota-gut-brain communication. Nat Rev Gastroenterol Hepatol. 2019;16:461–78.

    PubMed  Google Scholar 

  36. Bercik P, Verdu EF, Foster JA, Macri J, Potter M, Huang X, Malinowski P, Jackson W, Blennerhassett P, Neufeld KA, Lu J, Khan WI, Corthesy-Theulaz I, Cherbut C, Bergonzelli GE, Collins SM. Chronic gastrointestinal inflammation induces anxiety-like behavior and alters central nervous system biochemistry in mice. Gastroenterology. 2010;139:2102-2112.e1.

    CAS  PubMed  Google Scholar 

  37. O’Sullivan E, Barrett E, Grenham S, Fitzgerald P, Stanton C, Ross RP, Quigley EM, Cryan JF, Dinan TG. BDNF expression in the hippocampus of maternally separated rats: does Bifidobacterium breve 6330 alter BDNF levels? Benef Microbes. 2011;2:199–207.

    CAS  PubMed  Google Scholar 

  38. Parada Venegas D, De la Fuente MK, Landskron G, González MJ, Quera R, Dijkstra G, Harmsen HJM, Faber KN, Hermoso MA. Short chain fatty acids (SCFAs)-mediated gut epithelial and immune regulation and its relevance for inflammatory bowel diseases. Front Immunol. 2019;10:277.

    PubMed  PubMed Central  Google Scholar 

  39. Mackos AR, Maltz R, Bailey MT. The role of the commensal microbiota in adaptive and maladaptive stressor-induced immunomodulation. Horm Behav. 2017;88:70–8.

    CAS  PubMed  Google Scholar 

  40. Sudo N, Chida Y, Aiba Y, Sonoda J, Oyama N, Yu XN, Kubo C, Koga Y. Postnatal microbial colonization programs the hypothalamic-pituitary-adrenal system for stress response in mice. J Physiol. 2004;558:263–75.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Wang SZ, Yu YJ, Adeli K. Role of gut microbiota in neuroendocrine regulation of carbohydrate and lipid metabolism via the microbiota-gut-brain-liver axis. Microorganisms. 2020;8:527.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Strandwitz P. Neurotransmitter modulation by the gut microbiota. Brain Res. 2018;1693:128–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Nuriel-Ohayon M, Neuman H, Koren O. Microbial changes during pregnancy, birth, and infancy. Front Microbiol. 2016;7:1031.

    PubMed  PubMed Central  Google Scholar 

  44. Sharon G, Sampson TR, Geschwind DH, Mazmanian SK. The central nervous system and the gut microbiome. Cell. 2016;167:915–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Smid MC, Ricks NM, Panzer A, McCoy AN, Azcarate-Peril MA, Keku TO, Boggess KA. Maternal gut microbiome biodiversity in pregnancy. Am J Perinatol. 2018;35:24–30.

    PubMed  Google Scholar 

  46. Wang Y, Kasper LH. The role of microbiome in central nervous system disorders. Brain Behav Immun. 2014;38:1–12.

    PubMed  Google Scholar 

  47. Bellavance MA, Rivest S. The HPA—immune axis and the immunomodulatory actions of glucocorticoids in the brain. Front Immunol. 2014;5:136.

    PubMed  PubMed Central  Google Scholar 

  48. Park AJ, Collins J, Blennerhassett PA, Ghia JE, Verdu EF, Bercik P, Collins SM. Altered colonic function and microbiota profile in a mouse model of chronic depression. Neurogastroenterol Motil. 2013;25:733-e575.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Yu M, Jia H, Zhou C, Yang Y, Zhao Y, Yang M, Zou Z. Variations in gut microbiota and fecal metabolic phenotype associated with depression by 16S rRNA gene sequencing and LC/MS-based metabolomics. J Pharm Biomed Anal. 2017;138:231–9.

    CAS  PubMed  Google Scholar 

  50. Zhao R, Zhou Y, Shi H, Ye W, Lyu Y, Wen Z, Li R, Xu Y. Effect of gestational diabetes on postpartum depression-like behavior in rats and its mechanism. Nutrients. 2022;14:1229.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Zhou Y, Chen C, Yu H, Yang Z. Fecal microbiota changes in patients with postpartum depressive disorder. Front Cell Infect Microbiol. 2020;10: 567268.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Bailey MT, Coe CL. Maternal separation disrupts the integrity of the intestinal microflora in infant rhesus monkeys. Dev Psychobiol. 1999;35:146–55.

    CAS  PubMed  Google Scholar 

  53. Bailey MT, Lubach GR, Coe CL. Prenatal stress alters bacterial colonization of the gut in infant monkeys. J Pediatr Gastroenterol Nutr. 2004;38:414–21.

    PubMed  Google Scholar 

  54. Tian XY, Xing JW, Zheng QQ, Gao PF. 919 syrup alleviates postpartum depression by modulating the structure and metabolism of gut microbes and affecting the function of the hippocampal GABA/glutamate system. Front Cell Infect Microbiol. 2021;11: 694443.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Flores R, Shi J, Fuhrman B, Xu X, Veenstra TD, Gail MH, Gajer P, Ravel J, Goedert JJ. Fecal microbial determinants of fecal and systemic estrogens and estrogen metabolites: a cross-sectional study. J Transl Med. 2012;10:253.

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Kim S, Soeken TA, Cromer SJ, Martinez SR, Hardy LR, Strathearn L. Oxytocin and postpartum depression: delivering on what’s known and what’s not. Brain Res. 2014;1580:219–32.

    CAS  PubMed  Google Scholar 

  57. Schoeler M, Caesar R. Dietary lipids, gut microbiota and lipid metabolism. Rev Endocr Metab Disord. 2019;20:461–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Li N, Wang Q, Wang Y, Sun A, Lin Y, Jin Y, Li X. Fecal microbiota transplantation from chronic unpredictable mild stress mice donors affects anxiety-like and depression-like behavior in recipient mice via the gut microbiota-inflammation-brain axis. Stress. 2019;22:592–602.

    CAS  PubMed  Google Scholar 

  59. Wei S, Peng W, Mai Y, Li K, Wei W, Hu L, Zhu S, Zhou H, Jie W, Wei Z, Kang C, Li R, Liu Z, Zhao B, Cai Z. Outer membrane vesicles enhance tau phosphorylation and contribute to cognitive impairment. J Cell Physiol. 2020;235:4843–55.

    CAS  PubMed  Google Scholar 

  60. Zheng P, Wu J, Zhang H, Perry SW, Yin B, Tan X, Chai T, Liang W, Huang Y, Li Y, Duan J, Wong ML, Licinio J, Xie P. The gut microbiome modulates gut-brain axis glycerophospholipid metabolism in a region-specific manner in a nonhuman primate model of depression. Mol Psychiatry. 2021;26:2380–92.

    CAS  PubMed  Google Scholar 

  61. Skrundz M, Bolten M, Nast I, Hellhammer DH, Meinlschmidt G. Plasma oxytocin concentration during pregnancy is associated with development of postpartum depression. Neuropsychopharmacology. 2011;36:1886–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Stewart DE, Vigod SN. Postpartum depression: pathophysiology, treatment, and emerging therapeutics. Annu Rev Med. 2019;70:183–96.

    CAS  PubMed  Google Scholar 

  63. Hellgren C, Åkerud H, Skalkidou A, Bäckström T, Sundström-Poromaa I. Low serum allopregnanolone is associated with symptoms of depression in late pregnancy. Neuropsychobiology. 2014;69:147–53.

    CAS  PubMed  Google Scholar 

  64. Zou Y, Fan F, Ma A, Yue Y, Mao W, Ma X. Hormonal changes and somatopsychologic manifestations in the first trimester of pregnancy and post partum. Int J Gynaecol Obstet. 2009;105:46–9.

    PubMed  Google Scholar 

  65. Ohara MW, Schlechte JA, Lewis DA, Wright EJ. Prospective study of postpartum blues. Biologic and psychosocial factors. Arch Gen Psychiatry. 1991;48:801–6.

    CAS  PubMed  Google Scholar 

  66. Workman JL, Barha CK, Galea LA. Endocrine substrates of cognitive and affective changes during pregnancy and postpartum. Behav Neurosci. 2012;126:54–72.

    CAS  PubMed  Google Scholar 

  67. Baker JM, Al-Nakkash L, Herbst-Kralovetz MM. Estrogen-gut microbiome axis: physiological and clinical implications. Maturitas. 2017;103:45–53.

    CAS  PubMed  Google Scholar 

  68. Bloch M, Schmidt PJ, Danaceau M, Murphy J, Nieman L, Rubinow DR. Effects of gonadal steroids in women with a history of postpartum depression. Am J Psychiatry. 2000;157:924–30.

    CAS  PubMed  Google Scholar 

  69. Mastorakos G, Ilias I. Maternal and fetal hypothalamic-pituitary-adrenal axes during pregnancy and postpartum. Ann N Y Acad Sci. 2003;997:136–49.

    CAS  PubMed  Google Scholar 

  70. Gu H, Hu D, Hong XR, Mao J, Cui Y, Hui N, Sha JY. Changes and significance of orphanin and serotonin in patients with postpartum depression. Zhonghua Fu Chan Ke Za Zhi. 2003;38:727–8.

    PubMed  Google Scholar 

  71. Mann JJ. Role of the serotonergic system in the pathogenesis of major depression and suicidal behavior. Neuropsychopharmacology. 1999;21:99s–105s.

    CAS  PubMed  Google Scholar 

  72. Schiller CE, Meltzer-Brody S, Rubinow DR. The role of reproductive hormones in postpartum depression. CNS Spectr. 2015;20:48–59.

    PubMed  Google Scholar 

  73. Dennis CL, Ross LE, Herxheimer A. Oestrogens and progestins for preventing and treating postpartum depression. Cochrane Database Syst Rev. 2008;2008:CD001690.

    PubMed  PubMed Central  Google Scholar 

  74. Engert V, Vogel S, Efanov SI, Duchesne A, Corbo V, Ali N, Pruessner JC. Investigation into the cross-correlation of salivary cortisol and alpha-amylase responses to psychological stress. Psychoneuroendocrinology. 2011;36:1294–302.

    CAS  PubMed  Google Scholar 

  75. Dean J, Keshavan M. The neurobiology of depression: an integrated view. Asian J Psychiatr. 2017;27:101–11.

    PubMed  Google Scholar 

  76. Mayer SE, Lopez-Duran NL, Sen S, Abelson JL. Chronic stress, hair cortisol and depression: a prospective and longitudinal study of medical internship. Psychoneuroendocrinology. 2018;92:57–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Nierop A, Bratsikas A, Klinkenberg A, Nater UM, Zimmermann R, Ehlert U. Prolonged salivary cortisol recovery in second-trimester pregnant women and attenuated salivary alpha-amylase responses to psychosocial stress in human pregnancy. J Clin Endocrinol Metab. 2006;91:1329–35.

    CAS  PubMed  Google Scholar 

  78. Glynn LM, Sandman CA. Evaluation of the association between placental corticotrophin-releasing hormone and postpartum depressive symptoms. Psychosom Med. 2014;76:355–62.

    CAS  PubMed  Google Scholar 

  79. Yim IS, Glynn LM, Dunkel-Schetter C, Hobel CJ, Chicz-DeMet A, Sandman CA. Risk of postpartum depressive symptoms with elevated corticotropin-releasing hormone in human pregnancy. Arch Gen Psychiatry. 2009;66:162–9.

    PubMed  PubMed Central  Google Scholar 

  80. Segal DS, Kuczenski R, Mandell AJ. Theoretical implications of drug-induced adaptive regulation for a biogenic amine hypothesis of affective disorder. Biol Psychiatry. 1974;9:147–59.

    CAS  PubMed  Google Scholar 

  81. Newport DJ, Owens MJ, Knight DL, Ragan K, Morgan N, Nemeroff CB, Stowe ZN. Alterations in platelet serotonin transporter binding in women with postpartum onset major depression. J Psychiatr Res. 2004;38:467–73.

    PubMed  Google Scholar 

  82. Badawy AA. Tryptophan metabolism, disposition and utilization in pregnancy. Biosci Rep. 2015;35:e00261.

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Smith KA, Fairburn CG, Cowen PJ. Relapse of depression after rapid depletion of tryptophan. Lancet. 1997;349:915–9.

    CAS  PubMed  Google Scholar 

  84. Yano JM, Yu K, Donaldson GP, Shastri GG, Ann P, Ma L, Nagler CR, Ismagilov RF, Mazmanian SK, Hsiao EY. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell. 2015;161:264–76.

    CAS  PubMed  PubMed Central  Google Scholar 

  85. O’Mahony SM, Clarke G, Borre YE, Dinan TG, Cryan JF. Serotonin, tryptophan metabolism and the brain-gut-microbiome axis. Behav Brain Res. 2015;277:32–48.

    CAS  PubMed  Google Scholar 

  86. Reigstad CS, Salmonson CE, Rainey JF 3rd, Szurszewski JH, Linden DR, Sonnenburg JL, Farrugia G, Kashyap PC. Gut microbes promote colonic serotonin production through an effect of short-chain fatty acids on enterochromaffin cells. Faseb j. 2015;29:1395–403.

    CAS  PubMed  Google Scholar 

  87. Sun J, Wang F, Hu X, Yang C, Xu H, Yao Y, Liu J. Clostridium butyricum attenuates chronic unpredictable mild stress-induced depressive-like behavior in mice via the gut-brain axis. J Agric Food Chem. 2018;66:8415–21.

    PubMed  Google Scholar 

  88. Tian P, Wang G, Zhao J, Zhang H, Chen W. Bifidobacterium with the role of 5-hydroxytryptophan synthesis regulation alleviates the symptom of depression and related microbiota dysbiosis. J Nutr Biochem. 2019;66:43–51.

    CAS  PubMed  Google Scholar 

  89. Savignac HM, Kiely B, Dinan TG, Cryan JF. Bifidobacteria exert strain-specific effects on stress-related behavior and physiology in BALB/c mice. Neurogastroenterol Motil. 2014;26:1615–27.

    CAS  PubMed  Google Scholar 

  90. Geng S, Cheng S, Li Y, Wen Z, Ma X, Jiang X, Wang Y, Han X. Faecal microbiota transplantation reduces susceptibility to epithelial injury and modulates tryptophan metabolism of the microbial community in a piglet model. J Crohns Colitis. 2018;12:1359–74.

    PubMed  Google Scholar 

  91. Sun J, Wang F, Hong G, Pang M, Xu H, Li H, Tian F, Fang R, Yao Y, Liu J. Antidepressant-like effects of sodium butyrate and its possible mechanisms of action in mice exposed to chronic unpredictable mild stress. Neurosci Lett. 2016;618:159–66.

    CAS  PubMed  Google Scholar 

  92. Dinan TG, Cryan JF. Regulation of the stress response by the gut microbiota: implications for psychoneuroendocrinology. Psychoneuroendocrinology. 2012;37:1369–78.

    CAS  PubMed  Google Scholar 

  93. Dinan TG, Cryan JF. Microbes, immunity, and behavior: psychoneuroimmunology meets the microbiome. Neuropsychopharmacology. 2017;42:178–92.

    CAS  PubMed  Google Scholar 

  94. Christiansen CB, Gabe MBN, Svendsen B, Dragsted LO, Rosenkilde MM, Holst JJ. The impact of short-chain fatty acids on GLP-1 and PYY secretion from the isolated perfused rat colon. Am J Physiol Gastrointest Liver Physiol. 2018;315:G53-g65.

    CAS  PubMed  Google Scholar 

  95. Nankova BB, Agarwal R, MacFabe DF, La Gamma EF. Enteric bacterial metabolites propionic and butyric acid modulate gene expression, including CREB-dependent catecholaminergic neurotransmission, in PC12 cells–possible relevance to autism spectrum disorders. PLoS ONE. 2014;9: e103740.

    PubMed  PubMed Central  Google Scholar 

  96. Pascale A, Marchesi N, Marelli C, Coppola A, Luzi L, Govoni S, Giustina A, Gazzaruso C. Microbiota and metabolic diseases. Endocrine. 2018;61:357–71.

    CAS  PubMed  Google Scholar 

  97. Clarke G, Grenham S, Scully P, Fitzgerald P, Moloney RD, Shanahan F, Dinan TG, Cryan JF. The microbiome-gut-brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Mol Psychiatry. 2013;18:666–73.

    CAS  PubMed  Google Scholar 

  98. Koh A, De Vadder F, Kovatcheva-Datchary P, Bäckhed F. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell. 2016;165:1332–45.

    CAS  PubMed  Google Scholar 

  99. Steckert AV, Comim CM, Igna DM, Dominguini D, Mendonça BP, Ornell F, Colpo GD, Gubert C, Kapczinski F, Barichello T, Quevedo J, Dal-Pizzol F. Effects of sodium butyrate on aversive memory in rats submitted to sepsis. Neurosci Lett. 2015;595:134–8.

    CAS  PubMed  Google Scholar 

  100. Yamawaki Y, Yoshioka N, Nozaki K, Ito H, Oda K, Harada K, Shirawachi S, Asano S, Aizawa H, Yamawaki S, Kanematsu T, Akagi H. Sodium butyrate abolishes lipopolysaccharide-induced depression-like behaviors and hippocampal microglial activation in mice. Brain Res. 2018;1680:13–38.

    CAS  PubMed  Google Scholar 

  101. Wei Y, Melas PA, Wegener G, Mathé AA, Lavebratt C. Antidepressant-like effect of sodium butyrate is associated with an increase in TET1 and in 5-hydroxymethylation levels in the Bdnf gene. Int J Neuropsychopharmacol. 2014;18:pyu032.

    PubMed  Google Scholar 

  102. Moretti M, Valvassori SS, Varela RB, Ferreira CL, Rochi N, Benedet J, Scaini G, Kapczinski F, Streck EL, Zugno AI, Quevedo J. Behavioral and neurochemical effects of sodium butyrate in an animal model of mania. Behav Pharmacol. 2011;22:766–72.

    CAS  PubMed  Google Scholar 

  103. Hashimoto K, Bruno D, Nierenberg J, Marmar CR, Zetterberg H, Blennow K, Pomara N. Abnormality in glutamine-glutamate cycle in the cerebrospinal fluid of cognitively intact elderly individuals with major depressive disorder: a 3-year follow-up study. Transl Psychiatry. 2016;6: e744.

    CAS  PubMed  PubMed Central  Google Scholar 

  104. Pu J, Liu Y, Zhang H, Tian L, Gui S, Yu Y, Chen X, Chen Y, Yang L, Ran Y, Zhong X, Xu S, Song X, Liu L, Zheng P, Wang H, Xie P. An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder. Mol Psychiatry. 2021;26:4265–76.

    CAS  PubMed  Google Scholar 

  105. Domin H, Szewczyk B, Woźniak M, Wawrzak-Wleciał A, Śmiałowska M. Antidepressant-like effect of the mGluR5 antagonist MTEP in an astroglial degeneration model of depression. Behav Brain Res. 2014;273:23–33.

    CAS  PubMed  Google Scholar 

  106. Gosek P, Chojnacka M, Bieńkowski P, Swiecicki Ł. Antidepressant effect of ketamine, a N-methyl-D-aspartate (NMDA) glutamate receptor antagonist, in the therapy of treatment-resistant depression. Psychiatr Pol. 2012;46:283–94.

    PubMed  Google Scholar 

  107. Baranyi A, Amouzadeh-Ghadikolai O, von Lewinski D, Rothenhäusler HB, Theokas S, Robier C, Mangge H, Reicht G, Hlade P, Meinitzer A. Branched-chain amino acids as new biomarkers of major depression—a novel neurobiology of mood disorder. PLoS ONE. 2016;11: e0160542.

    PubMed  PubMed Central  Google Scholar 

  108. Dai ZL, Wu G, Zhu WY. Amino acid metabolism in intestinal bacteria: links between gut ecology and host health. Front Biosci (Landmark edition). 2011;16:1768–86.

    CAS  Google Scholar 

  109. Averina OV, Zorkina YA, Yunes RA, Kovtun AS, Ushakova VM, Morozova AY, Kostyuk GP, Danilenko VN, Chekhonin VP. Bacterial metabolites of human gut microbiota correlating with depression. Int J Mol Sci. 2020;21:9234.

    CAS  PubMed  PubMed Central  Google Scholar 

  110. Yang Z, Li J, Gui X, Shi X, Bao Z, Han H, Li MD. Updated review of research on the gut microbiota and their relation to depression in animals and human beings. Mol Psychiatry. 2020;25:2759–72.

    PubMed  Google Scholar 

  111. Malkesman O, Austin DR, Tragon T, Wang G, Rompala G, Hamidi AB, Cui Z, Young WS, Nakazawa K, Zarate CA, Manji HK, Chen G. Acute D-serine treatment produces antidepressant-like effects in rodents. Int J Neuropsychopharmacol. 2012;15:1135–48.

    CAS  PubMed  Google Scholar 

  112. Otte DM, Barcena de Arellano ML, Bilkei-Gorzo A, Albayram O, Imbeault S, Jeung H, Alferink J, Zimmer A. Effects of chronic D-serine elevation on animal models of depression and anxiety-related behavior. PLoS ONE. 2013;8: e67131.

    CAS  PubMed  PubMed Central  Google Scholar 

  113. Landsman A. Chapter 3—gene expression in depression: Molecular aspects of postpartum depression. In: Martin CR, Hunter L-A, Patel VB, Preedy VR, Rajendram R, editors. The neuroscience of depression. Academic Press; 2021. p. 25–35.

    Google Scholar 

  114. Yu Y, Liang HF, Chen J, Li ZB, Han YS, Chen JX, Li JC. Postpartum depression: current status and possible identification using biomarkers. Front Psychiatry. 2021;12: 620371.

    PubMed  PubMed Central  Google Scholar 

  115. Guintivano J, Arad M, Gould TD, Payne JL, Kaminsky ZA. Antenatal prediction of postpartum depression with blood DNA methylation biomarkers. Mol Psychiatry. 2014;19:560–7.

    CAS  PubMed  Google Scholar 

  116. Payne JL, Osborne LM, Cox O, Kelly J, Meilman S, Jones I, Grenier W, Clark K, Ross E, McGinn R, Wadhwa PD, Entringer S, Dunlop AL, Knight AK, Smith AK, Buss C, Kaminsky ZA. DNA methylation biomarkers prospectively predict both antenatal and postpartum depression. Psychiatry Res. 2020;285: 112711.

    CAS  PubMed  Google Scholar 

  117. Corbani IE, Rucci P, Iapichino E, Quartieri Bollani M, Cauli G, Ceruti MR, Gala C, Bassi M. Comparing the prevalence and the risk profile for antenatal depressive symptoms across cultures. Int J Soc Psychiatry. 2017;63:622–31.

    PubMed  Google Scholar 

  118. Goyal D, Gay C, Lee KA. How much does low socioeconomic status increase the risk of prenatal and postpartum depressive symptoms in first-time mothers? Womens Health Issues. 2010;20:96–104.

    PubMed  PubMed Central  Google Scholar 

  119. Pao C, Guintivano J, Santos H, Meltzer-Brody S. Postpartum depression and social support in a racially and ethnically diverse population of women. Arch Womens Ment Health. 2019;22:105–14.

    PubMed  Google Scholar 

  120. Schiepers OJ, Wichers MC, Maes M. Cytokines and major depression. Prog Neuropsychopharmacol Biol Psychiatry. 2005;29:201–17.

    CAS  PubMed  Google Scholar 

  121. Guintivano J, Aberg KA, Clark SL, Rubinow DR, Sullivan PF, Meltzer-Brody S, van den Oord E. Transcriptome-wide association study for postpartum depression implicates altered B-cell activation and insulin resistance. Mol Psychiatry. 2022;27:2858–67.

    CAS  PubMed  PubMed Central  Google Scholar 

  122. Couto TC, Brancaglion MY, Alvim-Soares A, Moreira L, Garcia FD, Nicolato R, Aguiar RA, Leite HV, Corrêa H. Postpartum depression: a systematic review of the genetics involved. World J Psychiatry. 2015;5:103–11.

    PubMed  PubMed Central  Google Scholar 

  123. Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry. 1987;150:782–6.

    CAS  PubMed  Google Scholar 

  124. Walton GD, Ross LE, Stewart DE, Grigoriadis S, Dennis CL, Vigod S. Decisional conflict among women considering antidepressant medication use in pregnancy. Arch Womens Ment Health. 2014;17:493–501.

    PubMed  Google Scholar 

  125. Leucht S, Hierl S, Kissling W, Dold M, Davis JM. Putting the efficacy of psychiatric and general medicine medication into perspective: review of meta-analyses. Br J Psychiatry. 2012;200:97–106.

    PubMed  Google Scholar 

  126. Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, Leucht S, Ruhe HG, Turner EH, Higgins JPT, Egger M, Takeshima N, Hayasaka Y, Imai H, Shinohara K, Tajika A, Ioannidis JPA, Geddes JR. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet. 2018;391:1357–66.

    CAS  PubMed  PubMed Central  Google Scholar 

  127. Lundorff M, Holmgren H, Zachariae R, Farver-Vestergaard I, O’Connor M. Prevalence of prolonged grief disorder in adult bereavement: A systematic review and meta-analysis. J Affect Disord. 2017;212:138–49.

    PubMed  Google Scholar 

  128. Möller HJ, Bandelow B, Volz HP, Barnikol UB, Seifritz E, Kasper S. The relevance of “mixed anxiety and depression” as a diagnostic category in clinical practice. Eur Arch Psychiatry Clin Neurosci. 2016;266:725–36.

    PubMed  PubMed Central  Google Scholar 

  129. Bennabi D, Aouizerate B, El-Hage W, Doumy O, Moliere F, Courtet P, Nieto I, Bellivier F, Bubrovsky M, Vaiva G, Holztmann J, Bougerol T, Richieri R, Lancon C, Camus V, Saba G, Haesbaert F, d’Amato T, Charpeaud T, Llorca PM, Leboyer M, Haffen E. Risk factors for treatment resistance in unipolar depression: a systematic review. J Affect Disord. 2015;171:137–41.

    CAS  PubMed  Google Scholar 

  130. Zhang F, Aschenbrenner D, Yoo JY, Zuo T. The gut mycobiome in health, disease, and clinical applications in association with the gut bacterial microbiome assembly. Lancet Microb. 2022;3:e969–83.

    CAS  Google Scholar 

  131. Cammarota G, Ianiro G, Bibbò S, Gasbarrini A. Gut microbiota modulation: probiotics, antibiotics or fecal microbiota transplantation? Intern Emerg Med. 2014;9:365–73.

    PubMed  Google Scholar 

  132. Liu X, Cao S, Zhang X. Modulation of gut microbiota-brain axis by probiotics, prebiotics, and diet. J Agric Food Chem. 2015;63:7885–95.

    CAS  PubMed  Google Scholar 

  133. Sandhu KV, Sherwin E, Schellekens H, Stanton C, Dinan TG, Cryan JF. Feeding the microbiota-gut-brain axis: diet, microbiome, and neuropsychiatry. Transl Res. 2017;179:223–44.

    CAS  PubMed  Google Scholar 

  134. Malka O, Kalson D, Yaniv K, Shafir R, Rajendran M, Ben-David O, Kushmaro A, Meijler MM, Jelinek R. Cross-kingdom inhibition of bacterial virulence and communication by probiotic yeast metabolites. Microbiome. 2021;9:70.

    CAS  PubMed  PubMed Central  Google Scholar 

  135. Lv WJ, Wu XL, Chen WQ, Li YF, Zhang GF, Chao LM, Zhou JH, Guo A, Liu C, Guo SN. The gut microbiome modulates the changes in liver metabolism and in inflammatory processes in the brain of chronic unpredictable mild stress rats. Oxid Med Cell Longev. 2019;2019:7902874.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Appreciation for the translation services with the help of Charlesworth Author Services.

Funding

This work was supported by the Health and Health Research of Wuhan Fund (Grant Number WX21D67).

Author information

Author notes

  1. Sheng Zhang and Baili Lu contributed equally to this work.

Authors and Affiliations

  1. Wuhan Mental Health Center, Wuhan, China

    Sheng Zhang, Baili Lu & Gang Wang

Authors
  1. Sheng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Baili Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SZ and BL performed the manuscript writing. GW reviewed and gave professional advice on the manuscript.

Corresponding author

Correspondence to Gang Wang.

Ethics declarations

Ethics approval and consent to participate

All authors have read and approved the full manuscript. The manuscript is original and not published or submitted for publication elsewhere in any language.

Human ethics

This review does not cover human subjects.

Consent for publication

All authors agreed to the publication of the review in the Annals of General Psychiatry.

Competing interests

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, S., Lu, B. & Wang, G. The role of gut microbiota in the pathogenesis and treatment of postpartum depression. Ann Gen Psychiatry 22, 36 (2023). https://0-doi-org.brum.beds.ac.uk/10.1186/s12991-023-00469-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12991-023-00469-8

Keywords

Annals of General Psychiatry

ISSN: 1744-859X