literature review on mood disorder

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• April 01, 2024 | VOL. 181, NO. 4 CURRENT ISSUE pp.255-346
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Advances in Understanding and Treating Mood Disorders

• Ned H. Kalin , M.D.

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Mood disorders, primarily major depression and bipolar disorder, are among the most debilitating psychiatric illnesses. Although significant progress has been made, there is much to be learned about their pathophysiology and much to be improved upon regarding their treatment. It is important to acknowledge that considerable work in the past has enhanced our understanding and treatment of mood disorders as evidenced by currently available effective treatments, which range from specific psychotherapies to psychopharmacology to neuromodulation. Still, many of our patients fail to fully respond to treatment or stay chronically ill.

Significant advances have been made in relation to the neurobiology underlying emotion, cognition, and behavior, and multitudes of studies have been performed in clinically ill populations; however, we are still far away from applying most of these findings to the clinical setting. From neuroimaging studies, we have developed a reasonable understanding of the circuity underlying negative emotion, reward, fear, anxiety, cognition, and behavior and have characterized various abnormalities in task and “resting-state” brain function in populations of patients with depression and bipolar disorder. Replicability of many of these findings, especially those in patient populations, has become an issue. Genetic studies are identifying structural genetic variants associated with the likelihood of developing mood disorders. However, the effect size of the influence of any one single-nucleotide polymorphism is quite small, and as with most psychiatric illness, we are understanding that many genes interact to increase susceptibility or provide protection. The use of polygenic risk scores appears to be an effective way to capture the complex genetics of these disorders, and over time this approach has potential to inform clinical care. Environmental factors also play a prominent role in the expression of mood disorders: advances are being made at the molecular level in understanding how environmental events are epigenetically programmed to result in altered gene expression that is informative for understanding the gene-by-environment interactions relevant to mood disorders. Most in the field believe that new effective treatment development depends on elucidating a fundamental understanding of mood disorder–related alterations in specific neural circuits and the molecules within these circuits. In addition, the use of machine learning to capitalize on combining critical components of large data sets (i.e., genetic, epigenetic, circuit function, and environmental events) holds promise for personalized psychiatric treatment approaches.

This issue of the Journal is devoted to providing our readership with a better understanding of where the field is in relation to our understanding and treatment of mood disorders, as well as introducing our readers to new promising findings. The centerpiece of this issue is a broad overview on depression by Dr. Charles Nemeroff, chair of the Department of Psychiatry and Behavioral Sciences at the University of Texas Dell Medical School in Austin. In his insightful and thought-provoking overview ( 1 ), Dr. Nemeroff provides his perspective on how we can conceptualize and integrate the multitude of findings and issues relevant to understanding the heterogeneity of depression, diagnostic criteria, mechanisms associated with depression-related pathophysiology, and insights into current and future treatments. This overview is followed by a comprehensive review focused on the use of hormonal treatment strategies for major depression ( 2 ). Dysregulated hormonal systems (e.g., pituitary-adrenal, thyroid, and gonadal) have long been associated with mood alterations and have been a focus of a vast number of studies investigating the potential role of specific hormonal systems in the pathophysiology and treatment of depression. This review, a product of the APA Council of Research Task Force on Novel Biomarkers and Treatments, synthesizes findings from the existing literature to provide clinicians and researchers with a resource for the evidence underlying hormonal treatment strategies. I particularly want to acknowledge the two co-first authors of this review, Dr. Jennifer Dwyer and Dr. Awais Aftab, who at the time were trainee members on the research council. I had the privilege of working closely with Drs. Dwyer and Aftab on this review and personally thank them for their insights and considerable efforts, which they relate in further detail in this month’s AJP Audio podcast episode.

This issue of the Journal also presents original research articles that address topics related to the treatment of bipolar disorder, the use of a new transcranial magnetic stimulation (TMS) strategy for treatment of refractory depression, and the effects of gender-affirming interventions on the treatment of mood and anxiety disorders in transgender individuals.

Using data from the National Ambulatory Medical Care Survey from 1997 to 2016, Rhee et al. ( 3 ) statistically characterize 20-year trends in the pharmacological treatment of bipolar disorder. Although it is probably not a surprise to somewhat older practitioners who have lived these changes, an important finding from this study is documenting the dramatic increase in the use of second-generation antipsychotics with the co-occurrence of a large reduction in the use of traditional mood stabilizers, such as lithium or valproic acid. The authors also report a considerable decrease in the use of psychotherapy, which may be problematic given the considerable psychosocial issues faced by patients with bipolar disorder. Dr. Michael Thase, from the University of Pennsylvania and an expert in the development and evaluation of new treatments for mood disorders, contributes an editorial that provides further historical context for these changes in treatment as well as the implications of these changes ( 4 ).

In another article, the Stanford group presents extremely promising data toward improving TMS methods for treatment-resistant depression ( 5 ). Capitalizing on intermittent theta-burst stimulation (iTBS), which is approved for the treatment of depression, Cole and coworkers report findings from an open-label trial of 22 patients who underwent an intensive iTBS treatment over the course of 5 consecutive days. Importantly, this early study used resting-state functional connectivity MRI to individualize the treatment target region within the left dorsolateral prefrontal cortex, such that stimulation was placed over the area that was most negatively correlated with the functional MRI signal in the subgenual anterior cingulate cortex (sgACC). This targeting strategy was used as the sgACC is a neural hub that receives the confluence of prefrontal cortical and subcortical information that is relevant to emotion and mood regulation, as well as to depression. One important outcome of the study is the demonstration that this intensive theta-burst treatment protocol was safe for patients. Treatment efficacy was rapid, with a remarkable remission rate of approximately 90%. Drs. Carpenter and Philip, from the Brown Department of Psychiatry and Human Behavior and experts in TMS neuromodulation, provide an editorial emphasizing the exciting treatment prospects supported by the data from this study (6). They also discuss these findings in relation to existing TMS treatment strategies and study design issues, including the small sample size and open-label nature of the study.

Also in this issue, along with an accompanying editorial by Dr. Sven Mueller from Ghent University ( 7 ), is an article that addresses the very important concern regarding the mental well-being of transgender individuals, specifically the effects of gender-affirming treatments on their mental health ( 8 ). In their article, Bränström and Pachankis use Swedish registries to assess mental health visits and outcomes after hormonal and surgical gender-affirming interventions. Compared with the general population, the results demonstrate that transgender individuals had higher numbers of clinical visits for the treatment of depression and anxiety prior to the interventions. The authors initially concluded, and presented in their article, that gender-affirming surgery, and not hormonal treatment, was associated with a subsequent reduction in the need for mental health intervention. However, when the article was initially available online, concerns were raised by some of our readers regarding the conclusions. Based on these concerns, we solicited secondary reviews of the article, including statistical consultation that recommended additional analyses. Among these analyses, the authors compared matched groups of gender identity patients who did and did not receive gender-affirming surgery, which resulted in the revised conclusion that gender-affirming surgery did not provide an advantage in relation to mental health outcomes. A robust discussion of this issue, and other methodologic and interpretive concerns, can be found in the numerous accompanying letters to the editor ( 9 – 15 ), published along with Bränström and Pachankis’ response to these letters ( 16 ) and a note from myself regarding the corrections and the process the Journal followed to vet the concerns that were raised ( 17 ). In addition to a published erratum notice, the Bränström and Pachankis article now includes an addendum referring to this postpublication discussion.

Two articles in this issue address environmental influences on mental health and depression, though in very different ways. One article examines the effects of air pollution on increasing hospital admissions for depression in China, and another article focuses on mechanisms involved in the intergenerational transmission of the effects of trauma. In their article, Gu et al. ( 18 ) present information building on earlier work that draws an association between short-term ambient air pollutant concentration and hospital admissions for depression. Using daily assessments of air pollutant concentrations across 75 cities and admission data from more than 111,000 hospitals, the authors found that from 2013 to 2017, increasing exposure to fine particles (<2.5 μm) and inhalable particles (<10 μm) was associated with increased rates of hospitalization. This association was demonstrated to be present within 7 days of increasing pollutant exposure, and the effects appeared to be particularly strong for nitrogen dioxide. It should be emphasized that in interpreting these findings, there are important methodologic issues that the authors discuss in the limitations paragraph of the article’s Discussion section. Furthermore, these findings represent associational data, which do not address causality. Nonetheless, the authors speculate on the possibility that pollutant-induced oxidative stress and inflammation may be underlying factors that could mediate this interesting and troubling association with depression.

Moving from an epidemiological level of analysis toward a molecular one, the article in this issue by Bierer et al. ( 19 ) characterizes epigenetic changes associated with the intergenerational transfer of traumatic experiences. This article focuses on the FKBP5 gene, which makes a protein that regulates glucocorticoid receptor responsivity. In addition, variation in the FKBP5 gene has been shown to be associated with posttraumatic stress disorder. This article speaks to how traumatic experiences in parents prior to conception may influence the biology and behavior of their offspring. Specifically, the authors replicate and extend an earlier finding in which they demonstrated reduced methylation at a specific site of the FKBP5 gene when measured in blood from the offspring of mothers who survived the Holocaust. The authors show that this effect was strongest in the offspring of mothers who were exposed to the Holocaust at younger ages and that reduced methylation of this site on the FKBP5 gene was associated with lower levels of anxiety and higher levels of basal cortisol levels. Because of the association between reduced anxiety and decreased FKBP5 methylation, the authors speculate that this epigenetic alteration may serve to protect offspring from the influences of stress exposure. The article also provides a helpful, in-depth discussion of the function of the FKBP5 gene and its protein and how this gene may be causally related to the effects of trauma and to pituitary-adrenal function. The present finding, which is an important replication of earlier work, along with other numerous relevant discoveries involving the FKBP5 gene, supports further serious attention to FKBP5 as a risk factor and mediator of stress-related psychopathology.

The disruption of hedonic processes is a cardinal feature of depression, and it is well established that depression is associated with alterations in the activation of reward-related circuits. The article by Rappaport and coauthors ( 20 ) addresses depression at a neural systems level of analysis by focusing on reward-related circuitry and development. This circuitry is complex and brain-wide, including regions such as brainstem dopaminergic nuclei, the ventral and dorsal striatum (i.e., the nucleus accumbens and caudate, respectively), the prefrontal cortex, and limbic structures (e.g., the amygdala, hypothalamus, and hippocampus). In the study presented here, the researchers used a monetary reward task to examine activation of reward-related neural circuitry in adolescents in relation to current symptoms of depression as well as in relation to their lifetime history of depression. The sample used is unique in that prospective assessments of symptoms began at between 3 and 5 years of age. The findings demonstrate the importance of examining both the state and “trait-like” aspects of depression, as the data revealed different patterns of neural alterations in relation to current symptoms compared with an individual’s life history of depression. Specifically, current depression was characterized by blunted activation of the nucleus accumbens when anticipating reward, whereas a cumulative history of depression involved a blunted response across a broader network of cortical and striatal regions. These findings are intriguing and potentially very important. Above and beyond the specific findings, the analytic strategy used in this study emphasizes the value of parsing current symptoms from illness history when characterizing the biology of our patients. The findings suggest that different mechanisms, even within the same general circuitry, may be at play in relation to understanding current symptoms in contrast to longer-term vulnerabilities. The developmental nature of this study is also highly important, as the findings shed light on the earliest manifestations of depression and its potential cumulative effects over development on neural circuit dysfunction. In her accompanying editorial ( 21 ), Dr. Erika Forbes, an expert in mechanisms underlying adolescent depression, highlights the importance of neurodevelopmental research while reviewing and discussing the relevance of these new findings.

In conclusion, this issue presents an in-depth view into important clinical and research issues relevant to mood disorders. The overview on depression presents our readership with where we are in the field and the challenges we face in improving outcomes for patients with depression. The review on the use of hormonal treatments and the articles on treatment trends in bipolar disorder and on gender-affirming interventions in transgender individuals provide information that is immediately applicable to clinical practice. Other exciting findings reveal insights into alterations in reward processing in adolescents with depression, an understanding of how environmental influences affect the risk for developing stress-related psychopathology, and groundbreaking new neuromodulation strategies that may significantly impact treatment outcomes in patients with treatment-resistant depression. It is my hope that this issue of the Journal will enthuse, and provide optimism to, readers about the potential for further advances that will benefit our patients suffering from mood disorders.

Disclosures of Editors’ financial relationships appear in the April 2020 issue of the Journal .

1 Nemeroff CB : The state of our understanding of the pathophysiology and optimal treatment of depression: glass half full or half empty? Am J Psychiatry 2020 ; 177:671–685 Link ,  Google Scholar

2 Dwyer JB, Aftab A, Widge A, et al. : Hormonal treatments for major depressive disorder: state of the art . Am J Psychiatry 2020 ; 177:686–705 Link ,  Google Scholar

3 Rhee TG, Olfson M, Nierenberg AA, et al. : 20-year trends in the pharmacologic treatment of bipolar disorder by psychiatrists in outpatient care settings . Am J Psychiatry 2020 ; 177:706–715 Link ,  Google Scholar

4 Thase ME : Charting sea changes in outpatient pharmacotherapy of bipolar disorder (editorial). Am J Psychiatry 2020 ; 177:651–653 Abstract ,  Google Scholar

5 Cole EJ, Stimpson KH, Bentzley BS, et al. : Stanford Accelerated Intelligent Neuromodulation Therapy for treatment-resistant depression . Am J Psychiatry 2020 ; 177:716–726 Link ,  Google Scholar

6 Carpenter LL, Philip NS : The future is now? Rapid advances by brain stimulation innovation (editorial). Am J Psychiatry 2020 ; 177:654–656 Abstract ,  Google Scholar

7 Mueller SC : Mental health treatment utilization in transgender persons: what we know and what we don’t know (editorial). Am J Psychiatry 2020 ; 177:657–659 Abstract ,  Google Scholar

8 Bränström R, Pachankis JE : Reduction in mental health treatment utilization among transgender individuals after gender-affirming surgeries: a total population study . Am J Psychiatry 2020 ; 177:727–734 Abstract ,  Google Scholar

9 Anckarsäter H, Gillberg C : Methodological shortcomings undercut statement in support of gender-affirming surgery (letter). Am J Psychiatry 2020 ; 177:764–765 Abstract ,  Google Scholar

10 Van Mol A, Laidlaw MK, Grossman M, et al. : Gender-affirmation surgery conclusion lacks evidence (letter). Am J Psychiatry 2020 ; 177:765–766 Abstract ,  Google Scholar

11 Curtis D : Study of transgender patients: conclusions are not supported by findings (letter). Am J Psychiatry 2020 ; 177:766 Abstract ,  Google Scholar

12 Malone WJ, Roman S : Calling into question whether gender-affirming surgery relieves psychological distress (letter). Am J Psychiatry 2020 ; 177:766–767 Abstract ,  Google Scholar

13 Landén M : The effect of gender-affirming treatment on psychiatric morbidity is still undecided (letter). Am J Psychiatry 2020 ; 177:767–768 Abstract ,  Google Scholar

14 Wold A : Gender-corrective surgery promoting mental health in persons with gender dysphoria not supported by data presented in article (letter). Am J Psychiatry 2020 ; 177:768 Abstract ,  Google Scholar

15 Ring A, Malone WJ : Confounding effects on mental health observations after sex reassignment surgery (letter). Am J Psychiatry 2020 ; 177:768–769 Abstract ,  Google Scholar

16 Bränström R, Pachankis JE : Toward rigorous methodologies for strengthening causal inference in the association between gender-affirming care and transgender individuals’ mental health: response to letters (letter). Am J Psychiatry 2020 ; 177:769–772 Abstract ,  Google Scholar

17 Kalin NH : Reassessing mental health treatment utilization reduction in transgender individuals after gender-affirming surgeries: a comment by the editor on the process (letter). Am J Psychiatry 2020 ; 177:764 Abstract ,  Google Scholar

18 Gu X, Guo T, Si Y, et al. : Association between ambient air pollution and daily hospital admissions for depression in 75 Chinese cities . Am J Psychiatry 2020 ; 177:735–743 Link ,  Google Scholar

19 Bierer LM, Bader HN, Daskalakis NP, et al. : Intergenerational effects of maternal Holocaust exposure on FKBP5 methylation . Am J Psychiatry 2020 ; 177:744–753 Link ,  Google Scholar

20 Rappaport BI, Kandala S, Luby JL, et al. : Brain reward system dysfunction in adolescence: current, cumulative, and developmental periods of depression . Am J Psychiatry 2020 ; 177:754–763 Link ,  Google Scholar

21 Forbes EE : Chasing the Holy Grail: developmentally informed research on frontostriatal reward circuitry in depression (editorial). Am J Psychiatry 2020 ; 177:660–662 Abstract ,  Google Scholar

• Cited by None

• Second-Generation Antipsychotics
• Bipolar and Related Disorders
• Depressive Disorders
• Environmental Risk Factors
• Inflammation
• Transgender (LGBT) Issues
• Neurostimulation
• Pharmacotherapy

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• Published: 20 August 2018

The neuropathology of bipolar disorder: systematic review and meta-analysis

• Paul J. Harrison   ORCID: orcid.org/0000-0002-6719-1126 1 , 2 ,
• Lucy Colbourne 1 , 2 &
• Charlotte H. Harrison   ORCID: orcid.org/0000-0003-3772-219X 3  

Molecular Psychiatry volume  25 ,  pages 1787–1808 ( 2020 ) Cite this article

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• Bipolar disorder
• Neuroscience

Various neuropathological findings have been reported in bipolar disorder (BD). However, it is unclear which findings are well established. To address this gap, we carried out a systematic review of the literature. We searched over 5000 publications, identifying 103 data papers, of which 81 were eligible for inclusion. Our main findings can be summarised as follows. First, most studies have relied on a limited number of brain collections, and have used relatively small sample sizes (averaging 12 BD cases and 15 controls). Second, surprisingly few studies have attempted to replicate closely a previous one, precluding substantial meta-analyses, such that the latter were all limited to two studies each, and comprising 16–36 BD cases and 16–74 controls. As such, no neuropathological findings can be considered to have been established beyond reasonable doubt. Nevertheless, there are several replicated positive findings in BD, including decreased cortical thickness and glial density in subgenual anterior cingulate cortex, reduced neuronal density in some amygdalar nuclei, and decreased calbindin-positive neuron density in prefrontal cortex. Many other positive findings have also been reported, but with limited or contradictory evidence. As an important negative result, it can be concluded that gliosis is not a feature of BD; neither is there neuropathological evidence for an inflammatory process.

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Introduction.

Like other ‘functional’ psychiatric disorders, bipolar disorder (BD) lacks any diagnostic neuropathology of the kind which characterises and defines the dementias, but this does not mean that BD has no morphological correlates. Magnetic resonance imaging (MRI) studies show small but robust differences in the volumes of some brain structures, notably decreases in hippocampus, amygdala and thalamus, and reduced cortical thickness [ 1 , 2 ]. There is also increasing evidence for white matter decrements [ 3 , 4 ] with anatomical and functional dysconnectivity of specific pathways and circuits [ 5 , 6 ]. Presumably these neuroimaging findings are reflected in alterations at the histological and cellular level. However, a review covering the period up to 1999 noted the remarkable lack of data [ 7 ]. By the definition of neuropathology adopted here (see Methods and Materials), the literature at that time comprised only nine publications. Vawter and colleagues [ 7 ] drew attention to some preliminary findings, notably a report of decreased glial density in the subgenual anterior cingulate cortex (sgACC) in BD and major depressive disorder [ 8 ], and a pilot study describing decreased interneuron density in the hippocampal CA2 subfield [ 9 ].

Öngür et al. (1998) [ 8 ] remains by some distance the most cited paper on the neuropathology of BD (Supplementary Table  1 ), and it was soon followed by a series of other morphometric studies. Many took advantage of the brain series collected by the Stanley Foundation (subsequently the Stanley Medical Research Institute), called the Stanley Neuropathology Consortium [ 10 ]. For the first time, this provided brain tissue specifically designed to allow comparison of BD, schizophrenia and major depressive disorder with healthy comparison subjects ( n  = 15 in each group) [ 10 ]. Moreover, tissue was provided blind to diagnosis such that researchers had to include BD, even if their primary interest lay in one of the other diagnoses.

An updated narrative review of the neuropathology of mood disorder was reported by Harrison (2002) [ 11 ], by which time the BD literature extended to 27 papers. More recently, Price and Drevets (2010) [ 12 ] reviewed mood disorder neuropathology in the context of neuroimaging findings and normative brain connectivity, and Savitz et al. (2014) [ 13 ] focused on the prefrontal cortex. To our knowledge, there has been no substantive review covering BD neuropathology since then, and there has never been a systematic review. Here, we report the latter, accompanied by meta-analyses where possible. The review was registered on the PROSPERO international prospective register of systematic reviews (CRD42018089740).

Methods and Materials

Scope of systematic review.

We adopted a pragmatic definition of neuropathology to comprise studies which measured ‘visible’ parameters such the density, number, size or shape of cells (neurons, glia or subpopulations thereof), cellular constituents (e.g. synapses, dendrites and mitochondria), or cytopathological elements (e.g. neurofibrillary tangles, amyloid plaques), in patients with BD compared to control subjects. We included studies which identified neuronal and glial populations using antigens generally recognised for this purpose (e.g. parvalbumin [PV], glial fibrillary acidic protein [GFAP], ionised calcium-binding adaptor molecule 1 [Iba-1]). We also included studies which measured the size of a brain structure (e.g. cortical thickness, hippocampal volume). We excluded studies which used messenger RNAs to delineate cell populations or which used proteins as proxy markers of sub-cellular compartments (e.g. synaptophysin as a marker of presynaptic terminals, or spinophilin for dendritic spines). We also excluded studies using brain homogenates.

Literature search and data extraction

We identified publications by searching the Web of Science Core Collection (1945 to 8th June 2018) and MEDLINE (1950 to 8 th June 2018) using the following search terms: (‘bipolar disorder’ or ‘bipolar affective’ or ‘bipolar illness’ or ‘bipolar disease’ or ‘manic-depressi*’ or ‘manic depressi*’) and (‘neuropatholog*’ or ‘morphometr*’ or ‘neuron*’ or ‘glia*’ or ‘pyramidal’ or ‘oligodendro*’ or ‘astrocyt*’ or ‘astrogli*’ or ‘microgli*’ or ‘*gliosis’). We also searched papers’ reference lists and PJH’s reprint collection to identify additional studies meeting our criteria. We did not consider papers including less than three BD cases, conference abstracts, non-peer reviewed publications (e.g. book chapters), nor data papers not published in English. Two authors (PJH, with either LC or CHH) independently conducted the searches and the data extraction, and all authors met to resolve any divergent results. Graphical data were extracted using Webplotter ( https://apps.automeris.io/wpd/ ).

We decided a priori to meta-analyse studies where at least two datasets were available, and which had measured the same parameter in the same brain region. In practice, this required judgement about what constituted meta-analysable data. Only data presented in the form of group means together with a measure of variance were considered for meta-analysis; this excluded several studies (e.g. which used medians and interquartile ranges). Meta-analyses were conducted with a fixed effects model, using Review Manager (RevMan) 5.3. Standardised mean differences (SMD) were used except where stated. Where necessary, standard errors were converted to standard deviations. If subgroups needed to be combined for meta-analysis (e.g. if a paper analysed males and females separately, or presented data for both right and left hemisphere), we used the formulae for weighted means and standard deviations in the Cochrane Handbook [ 14 ]. For studies reporting data for individual cortical layers or hippocampal subfields, a summary statistic for an overall diagnostic effect across all layers/subfields was also computed by RevMan; this statistic uses the number of observations not the number of subjects to calculate significance, and so should be interpreted with caution.

The literature search found 5388 publications meeting our criteria, and an additional 15 papers were found from other sources. Of the 5403 papers, 103 were selected for detailed inspection based on the abstract. 81 proved to have eligible original data [ 8 , 9 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 ], and form the focus of the systematic review. The 22 excluded papers are listed in Supplementary Table  2 together with the reason for their omission. The PRISMA diagram is shown as Supplementary Figure  1 .

Characteristics of included studies

The basic demographics of the 81 studies are shown in Table  1 .

Most studies utilised tissue from recognised brain collections, notably the Stanley Neuropathology Consortium ( n  = 35 studies), Harvard/McLean brain bank ( n  = 17), and Magdeburg brain collection ( n  = 11). The remainder came from a range of other sources; some studies used more than one series. Most studies used diagnostic criteria for BD: DSM-IV ( n  = 59), DSM-III-R ( n  = 13), and ICD-10 ( n  = 4); the remaining studies used other criteria or did not specify. Reflecting the fact that the brain collections mentioned above also include schizophrenia and/or major depressive disorder, many studies also included one or both diagnostic groups (schizophrenia [ n  = 58], major depressive disorder [ n  = 57]). In terms of anatomical focus, a range of brain regions have been studied: prefrontal cortex (PFC; n  = 19), especially dorsolateral (DLPFC; n  = 15); ACC, including sgACC ( n  = 17); other neocortical regions ( n  = 10); hippocampus ( n  = 13); amygdala ( n  = 8); entorhinal cortex ( n  = 7); white matter ( n  = 10); thalamus ( n  = 6); other ( n  = 18). Fourteen studies included more than one region. We rated 28 studies as adhering broadly to stereological principles (e.g. random sampling, 3D counting), 24 did so partially, and 29 either did not or could not be rated. Sixty five studies were carried out blind to diagnosis; no information about blinding was given for 16 studies.

Results are discussed region by region, and summarised in Tables  2 – 6 and Supplementary Tables  3 and 4 . The Tables highlight, for each study, the main results which the authors reported as being statistically significant, as well as important negative findings. Studies which we meta-analysed and their findings are described in the text, summarised in Supplementary Table  5 , and illustrated in Figs.  1 – 4 and Supplementary Figures  2 – 7 . In the event, only two datasets for any given parameter in any one brain region were amenable to meta-analysis.

Meta-analysis of volume, glial density, and glial number in subgenual ACC. Data are taken from the two cohorts included in Öngür et al. [ 8 ]. ‘Ongur 1998a’ refers to their pilot study; ‘Ongur 1998b’ refers to the main study, which used brains from the Stanley Foundation. Results are presented as mean differences. Glial density (cells/mm 3 x 10 3 ) is reduced, with a borderline reduction in glial number (x10 6 ), but no difference in sgACC volume (mm 3 )

Meta-analysis of layer thickness in subgenual ACC. Meta-analysis of Bouras et al. [ 26 ] and Williams et al. [ 82 ] reveals decreased thickness in BD of sgACC layer III (SMD −0.67, p  = 0.002), layer 5 (SMD −0.59, p  = 0.005) and layer VI (SMD −0.61, p  = 0.004). Thickness is also decreased across all four layers considered together (SMD −0.45, p  < 0.0001). The data in ref. 82 were originally analysed separately for men and women; they are combined here as described in the text

Meta-analysis of calbindin-immunoreactive neuron density in DLPFC. Meta-analysis of Beasley et al. [ 32 ] and Sakai et al. [ 62 ]. We used the data for the ‘medium’ size class of neuron reported in ref. 62 . Density of CB-positive neurons is reduced in BD in layer II (SMD −0.98, p  = 0.004) and layer III (SMD −0.92, p  = 0.006), and with an overall significant reduction if all 5 layers are considered together (SMD −0.59 p  < 0.0001)

Meta-analysis of neuronal density in lateral, basal and accessory basal nuclei of the amygdala. Meta-analysis of Berretta et al. [ 53 ] and Bezchlibnyk et al. [ 54 ]. For the accessory basal nucleus, we combined data from parvocellular and magnocellular subnuclei reported in [ 54 ]. Neuronal density is reduced in BD in the lateral nucleus (SMD −0.81, p  = 0.008), basal nucleus (SMD −0.85, p  = 0.005) and accessory basal nucleus (SMD −0.97, p  = 0.002). SMDs should be interpreted taking into account the fact that ref. 53 used 3D counting (neurons per unit volume) whereas ref. 54 used 2D counting (neurons per unit area)

Anterior cingulate cortex (ACC)

The ACC is an anatomically and functionally heterogeneous structure at the interface of cognition, emotion and behaviour [ 94 , 95 , 96 ]. It became of great interest in mood disorders after a study showing a focal decreased volume, and reduced metabolism, in the sgACC [ 97 ]. The same group then sought an anatomical correlate of these findings. They reported (in a pilot study and in a second, larger cohort) a reduction of glial density, using unbiased stereological methods on Nissl-stained sections, present in BD and in subjects with major depressive disorder [ 8 ]. Neuronal density and number were unchanged, and sgACC volume non-significantly reduced. Glial density was unaltered in the parietal cortex, suggesting a degree of anatomical localisation, and glial density was unchanged in the sgACC in schizophrenia, indicating a degree of diagnostic specificity.

Öngür et al. [ 8 ] was arguably the first significant neuropathological study of BD, and the first to use contemporary methods. It has been followed by 16 further studies of ACC neuropathology in BD (Table  2 ); 4 include sgACC, 13 examined other parts of the ACC. However, there have been no direct replications of the design or methods used by Öngür et al., precluding any meta-analysis of their data beyond simply combining the two datasets in their original paper. This confirms the reduction in glial density in BD in sgACC, and also shows a borderline significant decrease in glial number, but no difference in sgACC volume (Fig.  1 ). The findings strengthen the conclusions drawn by Öngür and colleagues, not least since their paper used one-tailed tests for some analyses.

The largest BD ACC study is by Bouras et al. [ 26 ], who reported reduced neuronal density in layers III, V, and VI of sgACC. These laminae were also thinner than in controls, as was the grey matter as a whole. The changes were similar but less pronounced in schizophrenia, and not seen in major depression. They state that no differences between BD and controls were seen in occipital cortex, but do not present the data. Glia were not measured. In a much smaller study of sgACC, Sinka et al. [ 78 ], who only measured layers III and V, found a non-significant trend towards decreased thickness of layer III, but no difference in neuronal density in BD in either lamina. Again, glia were not measured. Williams et al. [ 82 ] found a thinner grey matter in the sgACC crown in BD, with a reduced layer V thickness in the right hemisphere. Meta-analysis of sgACC layer thickness using data from refs. 26 and 82 shows a decrease in layers III, V, and VI in BD (Fig.  2 ). In a companion paper, Williams et al. (2013b) [ 83 ] counted sgACC oligodendrocytes using a Nissl stain, and astrocytes using GFAP immunohistochemistry, and found no differences in BD.

Studies of the non-subgenual parts of ACC provide a mixed picture (Table  2 ). Bouras et al. [ 26 ] measured the same parameters as noted above in sgACC, and found no differences between BD and controls in the dorsal ACC. However, when their layer thickness data were meta-analysed together with Benes et al. [ 25 ], the trend reduction seen in both studies for a thinner layer V became significant (Supplementary Figure  2 ).

The main finding of Benes et al. [ 25 ], who studied the rostral ACC, was a marked reduction in the density of non-pyramidal neurons in layer II, which remained significant after Abercrombie correction for cell size. The latter point is relevant since the neurons were larger in BD than in controls. The authors found no differences in pyramidal neuron density, or in glial density, in BD. The same group later used a different (three-dimensional, stereological) counting method in a subset of the same brains, and found modest but significant reductions in the density of non-pyramidal and pyramidal neurons, and glia, in BD, mostly in layer V [ 50 ]. In contrast, Cotter et al. [ 27 ] found no differences in glial density, neuronal density, or neuronal size in BD in the supra-callosal ACC (Brodmann area [BA] 24b) using a stereological approach. This group later used an adjacent part of the supragenual ACC (BA24c) of the same subjects for a two-dimensional study of density, size, and clustering of neurons and glia; in BD, neuronal size was decreased in layer V, and neuronal density increased in layer VI [ 40 ]. Neither study could be included in a meta-analysis because data were presented as medians [ 27 ] or as means but without any measure of variance [ 40 ].

Connor et al. [ 64 ] studied the white matter below the caudal ACC to study the density of white matter neurons (stained by NeuN) since altered distribution of these neurons in schizophrenia had been reported, and viewed as indicative of disordered neurodevelopment. In this relatively large study, they reported an increased density of ACC white matter neurons in BD, with a similar finding in PFC white matter.

In summary, there have been intriguing findings in the sgACC in BD, notably the glial deficits identified by Öngür et al. [ 8 ] and a thinning of the cortex found in two independent studies [ 26 , 82 ]. In other regions of the ACC, the findings are less prominent and not well replicated for either glial or neuronal alterations, though there is moderate evidence for a thinner layer V.

Prefrontal cortex (PFC)

The PFC has been the most studied brain region in BD. Virtually all studies have been carried out in the DLPFC (BA9 and 46). This neuropathological focus can be traced in part to the prominence of this region in studies of schizophrenia at the time when the Stanley Neuropathology Consortium tissue was being made available (see Introduction) [ 98 , 99 ]. There had also been emerging interest in cognitive aspects of BD which suggested potential involvement of the PFC [ 100 , 101 ].

Neuropathological studies of PFC in BD are summarised in Table  3 . The first report was by Guidotti et al. (2000) [ 23 ]. Amongst other parameters, they reported a marked decrease in the density of reelin-positive neurons in layer I (wherein most such cells are located) of BA9, with no change in overall neuronal density. The first dedicated, three-dimensional counting study of PFC was by Rajkowska et al. [ 24 ], again in BA9. Neuronal density was reduced in layer III, and pyramidal neuron density reduced in layers III and V. Glial density was decreased in layer III, with glial size increases. These authors noted the similarity of the glial findings to those of Öngür et al. [ 8 ], and their own findings in major depressive disorder in BA9, and contrasted them with the gliosis which would have been expected were BD a neurodegenerative disorder. Cotter et al. [ 36 ], using a two-dimensional counting method, did not replicate the findings of Rajkowska et al. [ 24 ], with no differences in neuronal density and only a trend reduction in glial density, limited to layer VI; Cotter et al. [ 36 ] did find a significant reduction in neuronal size in layers V and VI. Using the same tissue, Uranova et al. (2004) counted putative oligodendrocytes, and reported that density of these glial cells was decreased in layer VI [ 44 ]; the same group later described a reduction of perineuronal oligodendrocytes in layer III [ 58 ]. In the only study of its kind in BD, Golgi staining was used to quantify dendritic parameters of deep layer III pyramidal neurons, and a reduction in dendritic spine number and density, and dendritic length, were identified [ 85 ].

Two studies have counted sub-populations of DLPFC interneurons defined by immunoreactivity for the calcium binding proteins calbindin (CB), calretinin (CR) or PV [ 32 , 62 ]. Beasley et al. [ 32 ] found a reduced density of CB-immunoreactive neurons in layers II and III, with no significant differences in CR- or PV-positive neuron. When these data were meta-analysed together with findings from a much smaller study [ 62 ], there was a reduction in BD of CB-positive neurons, significant in layers II and III, and overall if all five layers are considered together (Fig.  3 ). Meta-analysis of these papers also showed a reduction of PV-positive neurons across all layers, but with no significant difference in any one layer (Supplementary Figure  3 ); CR-positive neurons were unaffected (Supplementary Figure  4 ). We also meta-analysed studies of DLPFC grey matter thickness (Supplementary Figure  5 ) and the  density of oligodendrocytes in DLPFC white matter (Supplementary Figure  6 ): neither showed alterations in BD.

In summary, a range of alterations in neuronal and glial morphometry have been reported in DLPFC in BD, but apart from a decrease in density of CB-positive neurons, no specific finding has been replicated.

The central role of the amygdala in arousal and affect [ 102 , 103 ], its strong connections with the prefrontal cortex [ 5 ], and imaging data in BD [ 1 , 5 ], has made it a structure of neuropathological interest in the disorder [ 5 , 12 , 102 , 103 ]. Table  4 summarises the eight studies to date; three considered the amygdala as a single structure, whilst the others focused on one or more amygdaloid nuclei or groupings thereof [ 104 ].

The first study, by Bowley et al. in 2002 [ 34 ], was conducted to determine whether the amygdala shared the glial reductions seen in ACC and DLPFC. The result was negative, as were subsequent counts of glial subpopulations [ 43 , 54 , 65 , 70 ]. Berretta et al. [ 53 ] reported a decreased volume of the lateral nucleus, which was confirmed by Pantazopoulos et al. [ 92 ] in an expanded sample, and who also described a decreased volume of the cortical nucleus. Accompanying the decreased size of the lateral nucleus, reduced neuronal size [ 54 ], and a lower neuronal number and density [ 53 ] was found. The neuronal reduction in the lateral nucleus is in part due to a loss of somatostatin (SS)-positive neurons [ 92 ], whereas in the cortical nucleus, neuropeptide Y-immunoreactive neurons were decreased [ 92 ]. The number and density of PV-immunoreactive neurons were not changed in either nucleus [ 70 ]. We were able to meta-analyse the two independent studies which measured neuronal density in lateral, basal and accessory basal nuclei [ 53 , 54 ]. This revealed significant reductions in all three nuclei in BD (Fig.  4 ). However, this conclusion is weakened by the fact that Altshuler et al. [ 65 ], studying the same material as ref. 53 but with a different delineation of the ‘basolateral’ amygdala, found no diagnostic effect.

In summary, studies of the amygdala are consistent in showing no alterations in glia in BD, with moderate evidence for reduced density of neurons in lateral, basal and accessory basal nuclei.

Hippocampus

Neuropathological studies of the hippocampus (including the subicular complex) in BD are summarised in Table  5 .

Like PFC, the hippocampus was studied in BD in part because it had been a major focus in schizophrenia [ 105 , 106 ]. Indeed, the first such study in BD, by Benes et al. [ 9 ], primarily reported schizophrenia data but also included four BD subjects, and found a reduction of neuronal density (in both disorders), selective to CA2 subfield, and affecting non-pyramidal neurons (i.e. interneurons) but not pyramidal neurons. Non-pyramidal neurons in BD were also slightly smaller. Zhang and Reynolds [ 39 ] found a markedly reduced density of PV-positive interneurons in all subfields, and a reduced size of these neurons. The next substantive report was in 2011, when Konradi and colleagues carried out a larger, stereological study to measure hippocampal volume and the number and size of neurons, including interneurons labelled by PV or SS [ 73 ]. They found a selective reduction in the volume, and the somal volume, of the non-pyramidal sector of CA2/3, The numbers of both neuropeptide-delineated interneurons were reduced in BD, across all CA fields; pyramidal neurons were unaffected. In a related study, Wang et al. [ 74 ] reported PV and SS neuron reductions in the parasubiculum. In a stereological study of the posterior hippocampus, Malchow et al. [ 88 ] found no differences in hippocampal subfield volumes in BD (including CA2/3), and an increased number and density of neurons in CA1 and in subiculum; they did not distinguish pyramidal from non-pyramidal neurons. In CA1, oligodendrocyte number was also increased. Meta-analysing the two studies of hippocampal neuron number [ 73 , 88 ] revealed no differences in any subfield in BD (Supplementary Figure  7 ; see also Supplementary Table  5 ).

In summary, there is consistent albeit inconclusive evidence in the hippocampus for reductions of non-pyramidal neurons, especially of PV-positive neurons, although differences in methodology and subfields measured precluded meta-analysis. Evidence for involvement of other cell types, or for an altered hippocampal volume, is not compelling.

Other brain regions

Seven neuropathological studies have examined the entorhinal cortex in BD (Supplementary Table  3 ). The only replicated positive finding is that the density of PV-immunoreactive neurons is reduced [ 57 , 74 ]. An unchanged density of GFAP-positive astrocytes has been reported in two studies [ 28 , 70 ], complementing a lack of alteration in overall glial density [ 34 ].

Neuropathological investigations of other neocortical regions, sometimes included to determine the anatomical selectivity of changes found in ACC or DLPFC, are essentially negative, as summarised in Supplementary Table  4 . This includes a lack of alterations in the density of neurons or glia; the only exception is Brauch et al. (2007) who reported a modest increase in neuronal density in an unspecified region of temporal cortex [ 51 ].

In addition to the amygdala, several other subcortical nuclei and regions have been investigated in BD (Table  6 ). Various differences have been reported, particularly in the hypothalamus [ 18 , 47 , 49 , 79 ], but no specific finding has been replicated.

The existence and nature of the neuropathology of psychiatric disorders has been debated for well over a century. Contemporary studies began in earnest in the 1980s, with a focus on schizophrenia, with findings in that disorder informing and encouraging equivalent investigations of other psychiatric disorders, including BD. The latter literature now extends to over 100 empirical studies, of which 81 met our criteria for inclusion in this systematic review. Our findings can be summarised as follows. First, although this is a significant body of work, most studies have relied on a limited number of brain collections, and have used relatively small sample sizes (Table  1 ) and are thus vulnerable to both type I and type II errors. Second, surprisingly few studies have attempted to replicate closely a previous one, precluding substantial meta-analyses; such that the latter were all limited to analysis of two studies each, comprising 16–36 BD cases and 16–74 controls (summarised in Supplementary Table  5 ). Hence, no neuropathological findings in BD can be considered to have been unequivocally established. Nevertheless, several findings are significant after meta-analysis of the available data, and merit brief discussion. We also consider the evidence against the presence of gliosis.

Key positive findings

The sgACC remains of interest, with the findings of glial deficits (Fig.  1 ) and a thinning of grey matter (Fig.  2 ) being significant after meta-analysis. Indeed, the latter finding is probably the most robust positive result, given that it is based on two independent studies [ 26 , 82 ], both using relatively large samples (and comprising the largest combined sample), coupled with a third study showing a similar albeit non-significant trend [ 78 ], and the absence of any contradictory reports. The results mean that further neuropathological investigations of the sgACC are warranted, especially given the continuing focus on this region for the pathophysiology and therapeutics of mood disorder [ 107 , 108 ]. Whether a similar pathology is seen in other parts of the ACC is unclear, since whilst there is some evidence for a thinner layer V (Supplementary Figure  2 ), glial and neuronal density data are inconsistent, as discussed earlier.

The finding of a reduced density of CB-positive neurons in some layers of DLPFC is significant by meta-analysis (Fig.  3 ), albeit based on a modest sample size. Caution is also needed when interpreting the summary statistic which arises from considering the cortical layers together, such as the finding of reduced PV-positive neuron density (Supplementary Figure  6 ), especially given the lack of significant reduction of PV neurons in any one layer. On the other hand, these preliminary indications that interneurons may be affected in BD are supported by findings of a decreased density or number of interneurons, defined by a range of markers, in several brain regions [ 22 , 23 , 39 , 57 , 74 , 92 , 93 ]. No firm conclusions can be drawn regarding these disparate observations, but they do merit further investigation, and complement the well-established involvement of some interneuron populations in schizophrenia [ 109 , 110 , 111 , 112 ].

Reduced neuronal density has been identified in three nuclei of the amygdala (lateral, basal and accessory basal), arising from two reasonably sized samples by independent investigators using different methodologies ([ 53 , 54 ]; Fig.  4 ). The findings support an involvement of the amygdala in the key circuits of BD [ 5 , 12 ]. Data in other nuclei are insufficient to determine whether the findings reflect a broader distribution of amygdala changes, although the unaltered neuronal density seen in the amygdala as a whole [ 34 ] suggests that connections and functions of the laterobasal group of the amygdala may be particularly involved in BD [ 113 , 114 , 115 , 116 ]. However, as noted earlier, Altshuler et al. [ 65 ], using the same brains as Bezchilbnyk et al. [ 54 ], found no difference in neuronal density in BD in the basolateral nucleus. They do not define this structure, but the term conventionally refers to the lateral subdivision of the basal nucleus [ 104 ], and hence would have been subsumed within the latter region as measured in refs. 53 and 54 .

Absence of gliosis

Set against these positive findings, all of which remain to be confirmed beyond doubt, it is worth noting perhaps the clearest conclusion from this systematic review. That is, gliosis (an increase in the density, number or size of glia, especially astrocytes) is not a feature of BD. As summarised in Supplementary Table  6a , no increase in overall glial density has been reported in any of the 19 studies which have measured this parameter (and 4 of them reported reductions). Similarly, of the 12 studies which counted astrocytes (either as identified on Nissl stains, or using immunostaining), 10 reported no differences in BD, and 2 found a reduction (Supplementary Table  6b ). Data for oligodendrocytes and microglia are fewer, but again show no consistent pattern of alteration (Supplementary Table  6c and 6d ). Since astrocytic gliosis is usually considered to be indicative of a neurodegenerative process [ 117 , 118 ], this negative profile of results suggests strongly that BD is not a disorder of that kind. Similarly, the unchanged density of microglia provides no support for the presence of an underlying neuroinflammatory process. When drawing these conclusions, it should be noted that psychiatric brain banks usually exclude subjects if formal neuropathological examination revealed specific abnormalities,  because they are viewed as coincidental and confounding findings. For example, the Stanley Foundation brain collection, used in almost half the studies included here, screened brains ‘to rule out Alzheimer’s disease and other cerebral pathology’ [ 10 ]. Nevertheless, as noted by others, the cumulative evidence is strong that BD, like other major psychiatric disorders, is not neurodegenerative in nature [ 7 , 11 , 24 , 105 , 117 , 119 ]. By default, these disorders are often viewed as being neurodevelopmental in origin, although the positive evidence in favour of that conclusion comes primarily from epidemiology and functional genomics rather than from neuropathology [ 120 , 121 , 122 , 123 , 124 ].

Interpreting the neuropathological findings

MRI studies show reductions in grey matter thickness in several cortical regions in BD, including ACC [ 2 , 125 ]. As noted, there is also good neuropathological evidence for a thinning of sgACC (Fig.  2 ). However, in all other cortical areas examined, post mortem studies show minimal or no difference in grey matter thickness in BD [ 24 , 25 , 26 , 32 , 40 , 42 , 48 , 66 ], in contrast to the anatomically widespread MRI findings. There is also a divergence between the robust MRI evidence for decreased volumes of the hippocampus [ 1 ] and most of its constituent subfields [ 126 ], and the neuropathological studies which are divided, with two reporting reduced hippocampal size [ 47 , 73 ] and two which do not [ 9 , 88 ]. When reconciling observations from the two modalities, it should be borne in mind that the imaging data are based on findings from over 1700 BD patients and 2500 controls, and the differences between BD and controls for each parameter are only 1–2% [ 1 , 2 ]. Hence the neuropathological studies (which are about two orders of magnitude smaller; Table  1 ) are grossly underpowered to detect such differences. It is also possible that the group differences seen on neuroimaging are not exclusively reflective of brain structure, but have other potential interpretations and confounders [ 127 ], including the effects of lithium [ 128 , 129 ].

The diagnostic status of BD and its relationships with schizophrenia and major depressive disorder continue to be under active debate clinically and genetically. This issue also has a neuropathological dimension. As noted earlier, the majority of BD studies also include one or both of these other disorders. Although it is beyond the scope of this systematic review to perform a comparative analysis, it is apparent that there is no consistent pattern of similarities or differences between these disorders (with the exception of the absence of gliosis, which is a common observation). Thus, some reported positive findings are specific to BD (e.g. [ 54 ]), some are common to all three disorders (e.g. [ 40 , 44 ]), some affect BD and schizophrenia (e.g [ 26 ]), and others are shared by BD and major depressive disorder (e.g. [ 48 ]). Equally, other parameters are altered in schizophrenia and/or major depressive disorder but not in BD (e.g. [ 27 , 63 ]). Overall, therefore, the neuropathological data are in line with the view, supported strongly by genomic findings [ 130 , 131 ], that BD, schizophrenia and major depressive disorder are not distinct disorders, but have many features in common as well as some which distinguish them. It is also possible that some of the heterogeneity in the neuropathological data reflects the fact that there are morphological correlates of the genetic predisposition to BD as well as to the syndrome itself [ 132 , 133 ].

This latter point relates to perhaps the most fundamental interpretational issue. The nature of the findings – modest reductions in volume, and in the content of neurons or glia, in certain brain regions – cannot be assumed to be pathological in the sense that lesions such as neurofibrillary tangles or infarcts are. They might instead reflect pre-existing (and partly genetically-mediated) differences in brain structure and connectivity which render the person vulnerable to BD. Or, the extant morphometric findings could be secondary to the illness in some way, e.g. cell loss or atrophy secondary to chronic stress, reduced neurotrophic factor support, etc. These issues are impossible to disentangle using post mortem studies alone, and require triangulation of neuropathological data with other findings, such as neuroimaging and relevant model systems.

Limitations

In addition to the diagnostic issues and power considerations mentioned earlier, the literature has several other limitations to consider. The first concerns clinical phenotyping. For most studies, there is sparse information available, for example regarding the age of onset and main features of BD; the mood state at death; the presence of comorbid disorders, etc. In any event, the small sample sizes preclude any meaningful attempts at subdividing BD or correlating clinical or demographic variables with neuropathological parameters. Even the clinical diagnosis of BD itself is not straightforward when made on retrospective review of case notes or interview with relatives: Deep-Soboslay et al. [ 134 ] found that only about half of cases referred to their brain bank as BD met (DSM-IV) diagnostic criteria, with the remainder having inadequate documentation and/or substantial comorbid substance abuse. Other variables such as family history, brain hemisphere and sex could also influence neuropathological findings (e.g., refs. [ 8 , 82 , 88 ]), but have not been reported consistently or in sufficient detail to allow us to examine these factors. There may also be confounding by medications used in BD, since mood stabilisers, antipsychotics and antidepressants can all impact on neuronal and glial indices; such effects may either contribute to, or mitigate, the reported alterations [ 135 , 136 , 137 , 138 , 139 ]. Finally, the neuropathological studies of BD have been of variable methodological quality. For example, only the minority unequivocally meet stereological criteria; the remainder are subject to the limitations and potential biases of studies which do not adhere to these principles [ 140 , 141 ]. Also, studies differ in the statistical approaches taken, such as whether significance values were adjusted for multiple comparisons (e.g. for the number of cortical layers examined).

Conclusions

There remain no neuropathological correlates of BD of sufficient robustness, magnitude, and specificity, to be of clinical or diagnostic value. Clearly, this does not rule out the possibility, but it is unlikely that a neuropathology - in the conventional sense of the term - exists and which has avoided discovery. Nevertheless, the key findings of this systematic review do merit further study to either confirm or refute them. This would require research of a much larger scale and scope than has occurred to date, to ensure the results are conclusive, and to allow assessment of potential clinico-pathological correlates and subgroupings. This would be a challenging undertaking, but transcriptomic and other molecular studies of psychiatric disorders, including BD, now routinely include many hundreds of brains (e.g. refs. [ 123 , 142 , 143 ]). Neuropathological research should have similar aspirations.

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Acknowledgements

We thank Andrea Cipriani for expert advice and assistance. LC is funded by the Wellcome Trust Oxford Clinical Doctoral Fellowship Programme. PJH’s research is supported by the Wellcome Trust, Medical Research Council, and Oxford Health National Institute for Health Research (NIHR) Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the National Health Service, NIHR or the Department of Health.

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Harrison, P.J., Colbourne, L. & Harrison, C.H. The neuropathology of bipolar disorder: systematic review and meta-analysis. Mol Psychiatry 25 , 1787–1808 (2020). https://doi.org/10.1038/s41380-018-0213-3

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Article Contents

Introduction, part i: mood disorders and fertility, rates of mood disorders in female patients with infertility.

The influence of mood disorders on infertility treatment

Part II: Directions for future research

Conclusions.

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Mood disorders and fertility in women: a critical review of the literature and implications for future research

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Katherine E. Williams, Wendy K. Marsh, Natalie L. Rasgon, Mood disorders and fertility in women: a critical review of the literature and implications for future research, Human Reproduction Update , Volume 13, Issue 6, November/December 2007, Pages 607–616, https://doi.org/10.1093/humupd/dmm019

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A medline literature review of fertility and mood disorder articles published since 1980 was performed in order to critically review the literature regarding a relationship between mood disorders, fertility and infertility treatment. Previous studies suggests that mood disorders, both in the bipolar and unipolar spectrum, may be associated with decreased fertility rates. Most studies report that women seeking treatment for infertility have an increased rate of depressive symptoms and possibly major depression (none showed evaluated mood elevations). Many, but not all, studies found that depressive symptoms may decrease the success rate of fertility treatment. Treatments for infertility may independently influence mood through their effects on estrogen and progesterone, which have been shown to influence mood through their actions on serotonin. Studies are limited in scope and confounding variables are many, limiting the strength of the results. In conclusion, a range of existing studies suggests that fertility and mood disorders are related in a complex way. Future studies should use clinical interviews and standardized and validated measures to confirm the diagnosis of mood disorders and control for the variables of medication treatment, desire for children, frequency of sexual intercourse, age, FSH levels, menstrual cycle regularity in assessing an interrelationship between mood disorders and fertility.

Women are at their greatest lifetime risk for mood disorders during their childbearing years ( Weissman and Olfson, 1995 ). Mood, or affective, disorders include unipolar depression and bipolar disorder ( American Psychiatric Association, 2000 ). The lifetime prevalence of major depression is 16.6% and bipolar disorder 3.9%. Adult women are at significantly greater risk, up to one and a half times that of men, of having a mood disorder ( Maciejewski et al ., 2001 ; Kessler et al ., 2005 ). Infertility, clinically defined as the inability to conceive a child within one year, is also a common problem, affecting an estimated 5–10% of women ( Abma et al ., 1997 ). The question of whether mood disorders influence or contribute to infertility in women is an area in need of further research.

The goals of this paper are to critically review the literature regarding the relationship between mood disorders and fertility in women and identify variables that need further investigation. We examine primary studies found in a Pub-Med literature search on women, fertility status and mood from 1980 onwards. We used the following key words in combination: depression, depressive disorder, major depression, depressive episode, mania, bipolar disorder, psychiatric disorders, or mood disorder, with menstrual cycle, infertility, fertility, conception, in vitro fertilization (IVF), menstrual cycle, functional hypothalamic amenorrhea, hypothalamic-pituitary-gonadal axis (HPG) or pregnancy.

Several reviews address stress, depressive symptoms and anxiety in relation to fertility ( Edelmann and Connolly, 1986 ; Wright et al ., 1989 ; Golombok, 1997; Greil, 1997 ). However, in this review, we focus our analysis on clearly defined mood disorders. In part one, we investigate and analyze the interrelationship of mood disorders and fertility by reviewing the literature under the following domains: studies of fertility rates in women with mood disorders, including pregnancy rates in IVF patients with major depression, and rates of mood disorders in women with the diagnosis of infertility. In part two, we provide recommendations for future research.

Epidemiological studies of fertility in women with the diagnosis of mood disorders

Only five studies of fertility rates in women with clearly diagnosed mood disorders have been published since 1980 (Table  1 ) ( Odergard, 1980 ; Baron et al ., 1982 ; Calzeroni et al ., 1990 ; Jonsson, 1991 , Harlow et al ., 2003 ). Two studies were excluded, see Table  2 , Lapane et al ., 1995 , Grodstein et al ., 1993 . The definition of fertility varies among the studies, as does the point at which fertility is evaluated, since some studies only investigate fertility before the onset of the first psychiatric episode ( Odergard, 1980 ; Jonsson, 1991 ), and others after the first episode ( Baron et al ., 1982 ; Calzeroni et al ., 1990 ; Harlow et al ., 2003 ). Age, an important factor in infertility, is often not controlled ( Odergard, 1980 ; Calzeroni et al ., 1990 ; Jonsson, 1991 ; Harlow et al ., 2003 ), nor are occult causes of decreased fertility evaluated, such as male factor infertility, number of years married, desire and attempts to conceive, infertility evaluation or infertility treatment.

Epidemiological studies of fertility rates in women with mood disorders

Excluded studies of fertility rates in women with mood disorders

Odergard (1980) analyzed the number of children born prior to the first psychiatric admission of married women hospitalized for serious mental illness in Norway between 1936 and 1975. The 30 438 women evaluated had 60 916 children, and Odergard reported that the relative fertility, (here defined as number of children observed per 100 expected) was not statistically significantly different from the general population for patients within the diagnostic categories evaluated: affective disorders, bipolar disorder and major depression. This study is limited by the fact that it only investigates fertility of women prior to the first psychiatric admission, leaving unclear the timing of onset of the affective disorder in relationship to childbirth.

In contrast, Baron et al .'s (1982) study of fertility rates in male and female bipolar patients controlled for several of these variables, including age of subjects, and investigated fertility rates before and after illness onset. Baron et al .'s population included 60 males and 74 females admitted to the Lithium Clinic of the New York State Psychiatric Institute between 1968 and 1974. Strict diagnostic criteria for bipolar affective disorder were used, and the age at evaluation, age at illness onset (not just the first psychiatric admission), the number and age of all children per person regardless of marital status were computed. The authors referenced a reduced fertility rate in both genders in comparison to US population norms by age. Most importantly, they found that fertility was reduced even prior to the onset of illness and stayed lower than expected in women. Men, in contrast, had an even greater reduction in fertility after the onset psychiatric illness.

Similarly decreased fertility rates were observed for those with severe mental illness in a small comparison study of patients hospitalized in 1925 ( Jonsson, 1991 ). Irrespective of marital status, 40 women with the diagnosis of a mood disorder had birth rates significantly less than the age matched population norm. The fertility rate of these women was 71.2% of the expected frequency. As in Baron et al .'s study, fertility was decreased in women with mood disorders even before the first psychiatric admission.

Lower rates of fertility in women with a history of major depression were also found in the Harvard study of moods and cycles, a unique prospective study of women in the transition to menopause ( Harlow et al ., 2003 ). Women with a current diagnosis or lifetime history of major depression were significantly more likely than women without to have fewer live births. Although the study reported that women with a lifetime history of major depression had higher rates of divorce, separation and widowhood, it did not report important variables regarding potential for fertility, such as number of years married, desire and attempts to conceive, infertility evaluation or infertility treatment.

Calzeroni et al ., (1990) studied fertility rates of 186 male and female patients with DSMIII-R diagnosed major depression with psychotic features and compared patients with mood congruent delusions or suicidal behavior to those without. Fertility was determined only in married subjects under 45 years old and expressed as mean number of legitimate children born alive, as a percentage of childless patients and as high (more than two children) or low fertility (less than two children). Patients who had attempted suicide had significantly fewer children than that of non-attempters (1.5 + 0.9 versus 1.9 + 1.1) and there was lower frequency of high fertility cases, despite similar rates of childless patients in the two groups. There was no significant difference between patients with and without delusions in rates of childlessness (12/99 versus 4/29) but patients without psychotic symptoms were 2.4 times more likely to show a condition of high fertility. These non-psychotic patients had a non-significant trend for an increased mean number of children, thus suggesting differential fertility within the members of this group.

To make conclusions about the fertility rate in women with mood disorders is difficult because of the variability of the studies, although the above findings are suggestive of a potential reduced fertility rate when fertility is defined as observed versus expected number of children. Two questions that do emerge from these studies are whether fertility is diminished prior to the first mood episode, and therefore may be a sign of a greater risk for later onset of a mood disorder and whether specific phenotypes of mood disorders are associated with greater reductions in fertility.

Menstrual abnormalities in unipolar and bipolar disorders

Depressive symptoms have been associated with changes in the menstrual cycle that may lead to reduced female fertility. Six studies are listed in Table  3 and three excluded studies in Table  4 . In a large, carefully controlled cross-sectional study of adolescent girls, Bisaga et al ., (2002) reported that depressive symptoms (defined as a Beck Depression Inventory > 16) were associated with late menarche, secondary amenorrhea and irregular menstrual cycles. Two large cross-sectional studies of women have also reported that women with a current or past history of depression report a history of early menstrual irregularity. However, both studies are limited by recall problems inherent in retrospective diagnosis as well as a lack of control groups ( Rowland et al ., 2002 ; Harlow et al ., 2004 ).

Menstrual cycle characteristics in women with a mood disorder diagnosis

Excluded studies, menstrual cycle in women with a mood disorder

Joffe et al ., (2006) did include a control group in a study comparing 245 women with major depression to 619 healthy controls, and found no statistical significance between the two groups regarding history of menstrual abnormalities prior to the diagnosis and treatment of a mood disorder. However, in the 295 bipolar women in this study, a history of menstrual abnormalities was more common (34%) than in the depressed women (24.5%) or the control women (21%). Rasgon et al ., (2005) also found that in women with bipolar disorder, menstrual abnormalities frequently preceded treatment with a mood stabilizer. These studies, while limited by recall bias, are intriguing because they suggest that if a higher rate of menstrual abnormalities exists in women with mood disorders, then the hypothalamic gonadal axis (HPG) may be affected by the disorder even prior to, or in conjunction with the hypothalamic adrenal axis.

Surprisingly, there are few studies which have carefully evaluated the presence of major depressive disorder in women with functional hypothalamic amenorrhea (FHA). FHA is characterized by disturbances in GnRH pulsatility and this disturbance appears to be mediated by increased cortisol, since basal ACTH and cortisol levels have been found to be higher in FHA patient compared with controls ( Meczekalski et al ., 2000 ). In their comparison of women with FHA, women with organic amenorrhea and eumenorrheic control women, Marcus et al ., (2001) found that women with FHA reported more depressive symptoms and dysfunctional attitudes than eumenorrheic women, but not significantly more than women with organic amenorrhea. Since standardized depression scales were not used, it is not clear whether the women met criteria for an affective disorder. Thus, we recommended that future studies of FHA characterize depressive phenotype, including whether patients meet criteria for the subtypes most classically associated with hypercortisolemia in mood disorders, such as melancholic and psychotic depression.

Phenotypic differences in depression and potential influence on fertility

One mechanism by which depressive disorders may influence fertility is by the symptoms of decreased energy, libido, self-esteem, increased guilt and psychomotor retardation. Suicidal ideation also would be expected to decrease motivation for a new life and this was found in Calzeroni et al .'s study (1990).

Bipolar disorder may also influence fertility, since increased libido is a common experience during mood elevations. However, other symptoms that occur during hypomania or mania, such as an increase in behaviors that may cause self harm or injury and a decline in self-care, would not be expected to improve fertility.

Future studies should examine the relationship between fertility and specific depressive or manic phenotypes since not all patients with a mood disorder experience the same severity of symptoms that may influence fertility. Future epidemiological studies of mood disorders and fertility should attempt to assess for frequency of sexual intercourse, desire for children and presence or absence of birth control as well.

Psychopharmacologic considerations

Antidepressants and fertility.

The use of psychotropic medications needs to be critically assessed in studies of fertility rates in patients with mood disorders, since several treatment medications may impact fertility. For example, the decreased libido seen with serotonin selective reuptake inhibitors (SSRIs) has not been assessed specifically in relation to fertility in mood disorders. Furthermore, these medications may affect fertility rates by potentially increasing spontaneous abortion rates. A recent meta-analysis of six cohort studies of 1534 antidepressant exposed women and 2033 non-exposed women found that exposure to antidepressants was associated with a significant increase in rates of spontaneous abortion (3.9%). No differences were found among classes of drug ( Hemels et al ., 2005 ). Klock et al .'s (2004) recent pilot study, a retrospective chart review of the IVF outcome of women taking SSRIs and women not taking SSRIs, found that 40% of women taking SSRIs had ongoing pregnancies compared with 51% not taking SSRIs. The study is unique in that it controlled for key variables that could affect fertility, and reported that there were no differences in number of ooctyes fertilized, percentage of eight cell blastocystes developed or initial hCG values.

Although it is an apparently uncommon phenomenon, antidepressants have been associated with the onset of hyperprolactinemia. Hyperprolactinemia could be an independent variable that influences menstrual cycle function, and consequently fertility, in depressed women. ( Emiliano and Fudge, 2004 ).

Mood stabilizers and fertility

No studies exist for the influence of the mood stabilizers, lithium, valproic acid, carbamazepine and lamotrigine, on fertility rates in women with mood disorders. Several investigations have suggested that valproic acid may decrease fertility in women since it has been associated with hyperandrogenism, hyperinsulinemia and dyslipidemia and menstrual abnormalities ( Morrell et al ., 2003 , 2005,Rasgon et al ., 2004). Valproic acid is a well documented teratogen, but the impact of this medication on fertility is currently unknown ( Holmes et al ., 2001 ).

Atypical antipsychotics are increasingly used in the treatment of mood disorders, as mood stabilizers ( Malhi et al ., 2003 ), to treat mania ( Perlis et al ., 2006 ) and to augment antidepressant response ( Nemeroff, 2005 ). These medications, especially risperidone, may increase prolactin levels in women even at low doses ( Haddad and Wieck, 2004 ). The associated hyperprolactinemia may lead to menstrual cycle abnormalities and thereby independently influence fertility. The only existing prospective study of pregnancy outcome of women using atypical antipsychotics includes both mood and psychotic disorder patients. This study found that olanzapine, risperidone and quetiapine are not associated with an increased risk of spontaneous abortions ( McKenna et al ., 2005 ).

Another approach to evaluating whether mood disorders lead to decreased fertility is to review the prevalence of these disorders in infertility patients. An increased prevalence of depressive symptoms in infertility patients compared with a variety of control groups has been found in most ( Link and Darling, 1986 ; Reading et al ., 1989 ; Stewart et al ., 1992 ; Domar et al ., 1992 , 1993 ; Merari et al ., 1992 ; Thiering et al ., 1993 ; Chiba et al ., 1997 ; Beutel et al ., 1999 ; Lukse et al ., 1999; Oddens et al ., 1999 ; Matsubyashi et al ., 2001; Fassino et al ., 2002 ) but not all studies ( Paulson et al ., 1988 ; Downey et al ., 1989 ; Connolly et al ., 1992 ; Downey et al ., 1992; Hynes et al ., 1992 ; Beuarepaire et al ., 1994; Visser et al ., 1994 ; Bringhenti et al ., 1997 ; Slade et al ., 1997 ; Emery et al ., 2003 ; Guz et al ., 2003 ). The differing findings regarding rates of depression result from several methodological differences and problems. Most of the studies only used questionnaires to assess psychiatric symptoms. Also, the control groups vary and include no controls (Beuarepaire et al ., 1994; Yong et al ., 2000 ; Chen et al ., 2004 ), age matched gynecology out patient controls ( Kee et al ., 2000 ; Fassino et al ., 2002 ), pregnant patient controls ( Matsubayashi et al ., 2001 ; Fido and Saheed, 2004), medical patient controls ( Domar et al ., 1993 ) and population controls ( Domar et al ., 1992 ; Merari et al ., 1992 ; Thiering et al ., 1993 ; Oddens et al ., 1999 ).

Furthermore, most of these studies are cross-sectional, not prospective, and the differing rates of mood disorders may be due to the timing of the psychiatric evaluation. It is important to assess women at the beginning of their infertility evaluation and treatment process since most ( Thiering et al ., 1993 ; Beaurepaire et al ., 1994 ; Slade et al ., 1997 ; Chiba et al ., 1997 ; Guerra et al ., 1998 ; Beutel et al ., 1999 ; Lok et al ., 2002 ; Ramezanzadeh et al ., 2004 ) but not all ( Stewart et al ., 1992 ; Domar et al ., 1992 ; Kee et al ., 2000 ; Smeenk et al ., 2001 ) studies have shown that depressive symptoms are related to duration of treatment. However, even when patients are assessed at the beginning of infertility evaluation and treatment, they may have struggled with difficulty conceiving for a long time. Thus it remains difficult to assess the relationship between the onset of the affective episode and fertility problems.

Prevalence of major depression in infertility patients

Only a few of the studies that investigate depressive symptoms in newly diagnosed infertility patients actually use diagnostically valid and reliable criteria for confirming a mood disorder ( Downey et al ., 1989 ; Fassino et al ., 2002 ; Meller et al ., 2002 ) and they have conflicting results. Downey et al ., (1989) compared 59 women who were in the initial stages of infertility treatment to a control group of women presenting for routine gynecological care. The Schedule for Affective Disorders and Schizophrenia-Life-time Version (SADS-L) was used to diagnose major depression. Downey et al ., reported no significant difference between patients and controls in rates of current or past major depressive disorder. About 8.5% of the infertility patients met criteria for a current major depressive episode, compared with 2.9% of the control women. About 32.2% of infertility patients had experienced a past episode of MDE compared with 48.6% of the controls.

In contrast, Fassino et al ., (2002) did find a significant difference in Hamilton depression (Ham-D) scores between two groups of women who had been attempting pregnancy for less than 2 years and fertile controls. Despite the fact that this study used Axis I psychopathology as an exclusion criteria, both infertility groups reported a significantly higher Ham-D than controls and both groups averaged above cutoff scores for mild depression ( Hamilton, 1960 ). Mean Ham-D scores for women with organic infertility (infertility clearly related to an medical cause) was 15.4 and for women with ‘functional’ infertility was 11.72. ‘Functional’ or unexplained infertility was carefully evaluated with a 3 month diagnostic evaluation which included gynecological and andrological clinical examination, seminal liquid evaluation, post-coital test, progesterone assay, hysterosalpingography and, in some cases, biopsy of the endometrium and laparoscopy.

Chen et al ., (2004) carefully assessed psychiatric diagnoses in women with varying years since infertility diagnosis. This study used the Mini International Neuropsychiatric Interview as well as Hospital Anxiety and Depression Scale (HADS) to assess the prevalence of psychiatric disorders in 112 women consecutively presenting for infertility treatment. 26.8% of the women met criteria for a mood disorder, 17% for major depression and 9.8% for dysthymia. These results are consistent with previous questionnaire only studies which have found rates of mild to moderate clinical depression ranging from 8–54% in women diagnosed as infertile ( Newton et al ., 1990 ; Domar et al ., 1992 ; Demyttenaere et al ., 1998 ; Lukse et al ., 1999; Matsubayashi et al ., 2001 ; Lok et al ., 2002 ; Anderson et al ., 2003 ).

Another approach to assessing whether mood disorders influence fertility is to investigate whether the presence of depression influences the outcome of infertility treatment. Although several studies report on depressive or anxiety symptoms and their relationship to IVF outcome, few studies have focused on women who met full criteria for a mood disorder. Included and excluded studies are listed in Tables  5 and 6 . Thiering et al ., (1993) used the Center for Epidemiological Studies Depression Scale (CES-D) to evaluate mood state prior to initiating an IVF cycle in 113 first time participants (inductees) and 217 repeat cycle participants (veterans). In both groups, women with major depression (defined as CES-D > 16) had lower rates of pregnancy than non-depressed subjects. However, the important variables of age, FSH, oocyte or embryo status were not assessed in this study.

Excluded studies on the influence of mood disorders on infertility treatment

Smeenk et al ., (2001) did control for the variables of age, number of previous pregnancies and number of embryos transferred in their analysis of pregnancy rates in relation to mood state in 291 women undergoing the first IVF/ICSI cycle. Prior to the subject's first IVF medication treatment, the standardized Beck Depression Inventory (BDI) and State and Trait Anxiety Inventory measures were given. Smeenk et al ., (2001) found that depression had an independent and significant correlation with lower pregnancy rates; however, state anxiety had an even stronger negative correlation with pregnancy rates.

Demyttenaere et al ., (1998) evaluated even more variables that may independently affect pregnancy rates, in their study of depression and coping in 98 women about to begin an IVF cycle for a either male subfertility, female subfertility or combined male and female infertility. About 54.1% of the women had Zung scores higher than the cutoff score for mild depression, 19.4% for moderate depression and 2% for severe depression. A higher Zung Depression score and greater depressive coping style were associated with lower pregnancy rates. When subfertile women who became pregnant were compared with women who did not, no statistically significant differences were found between the women in terms of age, duration of infertility, number of previous IVF attempts, number of injected ampules of hMG, estradiol concentrations on day 6, number of retrieved ooctyes and number of mature oocytes and number of fertilized and transferred embryos.

Not all studies found depressive symptoms associated with decreased pregnancy rates, but is important to note that these studies did not control for age, duration of infertility treatment, FSH, oocyte or embryo status. Slade et al ., (1997) did not find BDI depressive symptoms at intake to predict a decrease in pregnancy rates in women seeking infertility treatment. Mild depression scores at intake were not different between women who subsequently became pregnant (26%) and women who did not become pregnant (21%). Moderately depressed women at intake subsequently accounted for both 7% of the pregnancy and 7% of the non-pregnancy groups. Likewise, Mindes et al ., (2003) reported no significant difference in initial depression scores (measured by the CES-D) in women with infertility problems who became pregnant and those who did not at 6–12 months follow-up. Neither study controlled for age, duration of infertility treatment, FSH, oocyte or embryo status.

The relationship between affective disorders and fertility is extremely complex and a biospsychosocial multimodal approach is needed to tease out the many independent variables.

Recommendation 1: investigate the hypothalamic pituitary gonadal axis in mood disorder patients

More studies are needed examining the HPG axis in both unipolar and bipolar populations. Cortisol releasing hormone (CRH) induced propiomelanocortin peptides inhibit GnRH secretion and CRH has been found to be dysregulated in major depressive disorder ( Gold and Chrousus, 2002 ). Only a few studies have focused exclusively on the hypothalamic pituitary gonadal axis in premenopausal women with the diagnosis of major depressive disorder ( Young and Korzun, 2002 ). Baisher et al ., (1995) reported that untreated premenopausal depressed women had higher testosterone levels than controls, but no differences in basal and GnRH stimulated LH, FSH, estradiol or progesterone levels. O'Toole et al ., (1995) reported that in contrast to a sample of post-menopausal and perimenopausal patients, premenopausal depressed patients showed no differences in diurnal or nocturnal basal gonadotropin concentrations compared with non-depressed controls. Similiarly, Young et al ., (2000) matched 25 women with major depression to healthy controls of same age and menstrual cycle day and sampled FSH, estradiol and LH every 10 min for 12 h. No differences were found between the groups on any measures except lower mean estrogen levels in the follicular phase and a shorter half-life of LH in the depressed group.

In contrast, Meller et al ., (2001) compared LH pulses in 26 women with current or past history of DSM IV diagnosed affective disorder (23 recurrent unipolar major depression and 3 bipolar II, currently depressed) and 24 control women. No women were on medications and there was no difference between groups regarding age, weight or day of LH sampling. All women were admitted for 8 h and LH was sampled every 10 min. Depressed patients showed slower frequency and decreased rhythmicity of LH pulses but no change in amplitude compared with controls. The clinical significance of these differences is currently not understood, since the study did not report whether these differences affected ovarian follicular development or ovulation. Further research should focus on comparing the HPG axis characteristics in women with major depression and infertility and euthymic women with infertility and the clinical outcomes of these differences.

Recommendation 2: investigate the psychopharmacologic effects of infertility medications

The psychopharmacologic effects of the infertility medication may be an important independent risk factor for the development of depression in infertility patients. Most studies have not controlled for this and have not clarified type and dose of medication. There are only a few studies and case reports investigating the effects of infertility medications on mood ( Blenner, 1991 ; Williams and Casper, 1995 ; Choi et al ., 2005 ). However, it makes theoretical sense that these medications may influence the development of mood disorders, since these medications acutely and dramatically alter serum levels of estrogen and progesterone, and research has shown that some women are especially vulnerable to the onset of mood disorders at times of hormonal change, such as postpartum and perimenopause ( Rapkin et al ., 2002 ; Chaudron et al ., 2003).

For instance, many women report that clomiphene citrate is associated with mood changes, including irritability, emotionality, and increased symptoms of premenstrual syndrome ( Blenner, 1991 ). In a small pilot study, Williams and Casper (1995) reported that clomiphene citrate is associated with fatigue at midcycle, at the time when the estradiol levels are highest. Future studies should investigate whether clomiphene and human menopausal gonadotropins, including menotropins (Humegon, Pergonal and Pregova) and urofollotropin (e.g. Metrodin), are associated with more mood changes in women with a history of mood lability at times of hormonal change, such as women with a history of premenstrual dysphoric disorder or bipolar disorder.

Recommendation 3: investigate rates of mood disorders in specific infertility populations

The prevalence of mood disorders in female infertility patients may be independently and differentially related to certain causes of infertility and future studies should control for this important independent variable. Since male factors, such as sperm motility problems, are a common cause of infertility, future studies that investigate the possibility of shared biological pathways between mood and infertility in women should clearly study female infertility separately. In so doing, the importance of biological versus psychological factors in depressive symptoms and disorders in female infertility can be elucidated, since the diagnosis of a fertility problems, even if male factor related, may itself independently affect mood.

Specific female infertility related disorders should be studied separately. For instance, Weiner et al ., (2004) recently reported that women with polycystic ovarian syndrome (PCOS) experienced more depression than a matched control group and that the most negative mood scores were associated with higher free testosterone values. Similarly, Rasgon et al ., (2003) reported a high prevalence of major depression in 32 women with PCOS and noted that depressive symptoms were related to BMI and insulin resistance. Rasgon et al ., (2002) also described a case of a woman with treatment resistant major depression and PCOS whose mood disorder finally remitted once her insulin resistance and hyperandrogenism were treated with metformin and spironolactone.

Mood disorders and fertility in women have a complex relationship. This review of the literature suggests that mood disorders may be associated with decreased fertility rates, but the direction of causality is still unclear and likely variable, depending on independent factors, such as female infertility subtype, that need further investigation. Future epidemiological studies should use standardized, validated measures of major depression and bipolar disorder. Fertility should be clearly defined and infertility carefully evaluated prior to the diagnosis of ‘unexplained’ infertility. Studies should control for such confounding variables as birth control use, frequency and timing of sexual intercourse and desire for children. Studies investigating pregnancy outcome in depressed female infertility patients should control for comorbid anxiety disorders and stress levels, medication use, and report important variables such as FSH levels, number and quality of ooctyes, number of embryos transferred and the quality of these embryos and rates of spontaneous abortion when comparing patients and controls. It is recommended that further research focus on the HPG axis function in women with mood disorders and the clinical correlates of dysregulation, such as differences in menstrual cycle characteristics in depressed and non-depressed patients or patients with bipolar disorder.

The influence of decreased fertility on mood disorders is also complex. Future studies should focus on specific variables and risk factors for the onset of a mood disorder, such as the effect of the hormonal manipulations associated with the assisted reproductive technology process on mood. Such research would provide information for not only the field of fertility but also for women's greater psychiatric health, since the subtle and complex relationship between HPG function and mood remains an important area of investigation across the female life cycle, from puberty to menopause.

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• PMC10613459

A Comprehensive Review of Motherhood and Mental Health: Postpartum Mood Disorders in Focus

Anushree modak.

1 Obstetrics and Gynaecology, Srimati Radhikabai Meghe Memorial College of Nursing, Datta Meghe Institute of Higher Education & Research, Wardha, IND

Vaishnavi Ronghe

Kavita p gomase, manjusha g mahakalkar, vaishali taksande.

The journey of motherhood encompasses a profound array of emotions, experiences, and challenges that extend beyond the surface of joy and elation. This review delves into the crucial yet often underexplored realm of postpartum mood disorders, aiming to illuminate their significance and foster understanding. Postpartum mood disorders, including postpartum depression, anxiety disorders, and psychosis, impact the mental well-being of mothers during a pivotal phase of their lives. Through a comprehensive exploration, this review elucidates the various dimensions of these disorders, from their definitions and classifications to their prevalence and impact on both mothers and families. Identifying and diagnosing postpartum mood disorders is discussed in detail, shedding light on the emotional, cognitive, and physical symptoms that warrant attention. Screening and assessment tools are highlighted as essential instruments for early detection, while challenges in diagnosis, including the overlap with typical postpartum experiences and the influence of stigma, are explored. The review further delves into treatment and intervention, underscoring the importance of psychotherapy, pharmacological interventions, and individualised treatment plans. The roles of healthcare providers and mental health professionals in offering support and guidance are emphasised, emphasising the significance of a collaborative approach. Cultural and societal influences are crucial in shaping perceptions of motherhood and mental health. The review explores how these influences can create barriers to seeking help and highlights the importance of destigmatising postpartum mood disorders. It underscores the urgency of raising awareness and fostering a supportive environment that empowers mothers to seek assistance without fear of judgment. Looking toward the future, the review points to potential research directions, such as advances in understanding hormonal influences and exploring the long-term effects on maternal mental health. The overarching call to action resonates - increased awareness, support, and dismantling stigma are imperative. A hopeful vision is presented: a future where all mothers receive appropriate mental health care, no mother stands alone in her motherhood journey, and societal understanding and compassion thrive.

Introduction and background

Motherhood is a transformative journey that brings joy, challenges, and profound changes to a woman’s life. Amid the joyous moments and new beginnings, it is essential to acknowledge the less-discussed aspects of motherhood, particularly those related to mental health. This review delves into a critical dimension of motherhood-postpartum mood disorders and sheds light on their significance, highlighting the pressing need to address mental health during this pivotal phase of a woman’s life [ 1 ].

The transition to motherhood is marked by hormonal fluctuations, sleep deprivation, and adjustments to a new role, potentially impacting a woman’s mental well-being. Postpartum mood disorders, including postpartum depression (PPD), anxiety disorders, and even rare but severe cases of postpartum psychosis, can cast a shadow over what is meant to be a joyous time. The significance of this topic lies in the potential long-term consequences of untreated postpartum mood disorders, affecting not only the mother but also her family unit [ 2 ].

Maternal mental health is not just an individual concern but has far-reaching implications for the child’s emotional, cognitive, and social development. Research has established the interplay between a mother’s mental well-being and her ability to provide responsive caregiving. Unaddressed postpartum mood disorders can disrupt the formation of a secure mother-child attachment and hinder the child’s emotional regulation and overall mental health. Furthermore, the effects of maternal mental health reverberate through the family, influencing partner relationships, sibling dynamics, and the overall family environment [ 3 ].

The purpose of this review is twofold: first, to deepen our understanding of postpartum mood disorders by exploring their various forms, causes, and prevalence, and second, to emphasise the significance of timely intervention and support for mothers experiencing these disorders. By delving into the complexities of these disorders, we aim to provide healthcare practitioners, mental health professionals, families, and society with insights into practical strategies for prevention, early detection, and management. Additionally, we will explore the role of cultural and societal factors in shaping perceptions of maternal mental health and help bridge the gap between awareness and destigmatisation.

Understanding postpartum mood disorders

Definition and Classification of Postpartum Mood Disorders

The spectrum of postpartum mood disorders encompasses a range of emotional and psychological challenges that can affect mothers after childbirth. These disorders are not only diverse in their manifestations but also differ in their severity and duration [ 2 ]. The following classifications shed light on the multifaceted nature of these disorders:

Postpartum depression (PPD): PPD is characterised by persistent sadness, hopelessness, and a loss of interest or pleasure in previously enjoyed activities. It often manifests within the first few weeks after childbirth but can emerge up to a year later. Physical symptoms such as changes in appetite and sleep patterns might accompany emotional distress [ 2 ].

Postpartum anxiety disorders: These disorders encompass a range of anxiety-related conditions, including generalised anxiety disorder (GAD), panic disorder, and obsessive-compulsive disorder (OCD). New mothers with postpartum anxiety may experience excessive worry, restlessness, and intrusive thoughts about their baby’s safety [ 4 ].

Postpartum psychosis: Although relatively rare, postpartum psychosis is a severe disorder characterised by hallucinations, delusions, and disorganised thinking. It typically emerges within the first few weeks after childbirth and requires immediate medical intervention [ 5 ].

Baby blues vs. more severe disorders: Distinguishing between the “baby blues” and more severe postpartum mood disorders is crucial. Baby blues are common, short-lived mood fluctuations affecting up to 80% of new mothers and generally resolve independently within a couple of weeks. In contrast, postpartum mood disorders involve persistent and often worsening symptoms that require professional attention [ 2 ].

Prevalence and Statistics

Postpartum mood disorders are more prevalent than commonly perceived. PPD alone affects around 10-20% of new mothers worldwide. Postpartum anxiety disorders and psychosis are less common but still demand attention due to their potential severity. The prevalence varies across cultures, highlighting the complex interplay of biological, psychological, and sociocultural factors [ 6 ].

Risk Factors and Contributing Factors

Hormonal changes: The journey of pregnancy and childbirth is accompanied by dramatic hormonal shifts. The abrupt decline in oestrogen and progesterone levels after delivery is of particular significance. These hormonal changes can profoundly impact mood regulation mechanisms within the brain. The intricate interrelationship between these hormonal fluctuations and neurotransmitter activity can potentially render individuals susceptible to mood disorders during the postpartum period. The abruptness of these hormonal changes further underscores their potential influence on mood regulation [ 7 ].

Psychological factors: Personal mental health history plays a pivotal role in developing postpartum mood disorders. Individuals with a prior history of depression or anxiety may exhibit heightened vulnerability during this phase. Pregnancy and childbirth’s physiological and psychological challenges can act as triggers, exacerbating these preexisting tendencies. Furthermore, unresolved emotional issues, compounded by the stress and uncertainty of new motherhood, can fuel the onset of mood disorders. Unrealistic expectations surrounding the experience of motherhood, often shaped by societal norms and personal perceptions, can add another layer of psychological strain [ 8 ].

Social support and environment: The support network and environment in which a new mother finds herself are influential determinants of her mental well-being. Adequate social support can act as a protective buffer against developing postpartum mood disorders. Conversely, a lack of support or strained relationships can magnify a new mother’s challenges, making her more vulnerable to emotional distress. Isolation, whether physical or emotional, can compound the risk, as it restricts the availability of sources to seek comfort, understanding, and guidance. The absence of a strong support network can amplify the feelings of inadequacy and overwhelm that often accompany the transition into motherhood [ 9 ].

Impact on mothers and families

Effects on Maternal Well-being

Emotional distress and mood fluctuations: Mothers grappling with postpartum mood disorders often find themselves caught in a tumultuous whirlwind of emotions. These emotions can span from overwhelming sadness that engulfs their days to heightened irritability and restlessness. The unpredictable mood fluctuations can be likened to an emotional rollercoaster, rendering even simple tasks a challenge and robbing them of the ability to savour life’s ordinary moments. The weight of these emotions can be paralysing, making it difficult to engage in daily activities, interact with loved ones, and find joy in things that once brought happiness [ 2 ].

Impact on self-esteem and self-image: Postpartum mood disorders can profoundly distort a mother’s sense of self. The internal dialogue becomes clouded by negative self-perceptions, leading to a sense of inadequacy and self-doubt. Mothers may internalise their struggles as personal failings, viewing themselves as incapable of meeting motherhood’s demands. This negative self-image can magnify emotional challenges, forming a self-reinforcing cycle that perpetuates emotional distress [ 10 ].

Relationship with the baby and partner: One of the most poignant consequences of postpartum mood disorders is their impact on the mother’s relationship with her infant and her partner. Emotional distress can hinder a mother’s ability to form a strong, nurturing bond with her baby, impairing her capacity to provide the responsive care crucial for the infant’s healthy development. This can lead to feelings of guilt and inadequacy, further intensifying her emotional turmoil. Simultaneously, strained emotional states can reverberate into the mother’s partnership, causing communication breakdowns and emotional distance. Partners might struggle to comprehend the changes they observe, leading to a sense of helplessness in providing support [ 11 ].

Effects on Family Dynamics

Role of the partner and extended family: Partners emerge as critical sources of support during the postpartum period, offering understanding, assistance, and emotional connection. However, the challenges posed by a mother’s mood disorder can create strains that ripple across the family unit. The partner’s emotional well-being might be impacted as they navigate how to best provide the necessary care and support while managing their emotional responses. Equally important are extended family members, whose empathy and involvement can significantly lighten the load on the mother. Their understanding and contributions can help create a more conducive environment for the mother’s recovery and family well-being [ 12 ].

Sibling relationships and family bonding: Families with older children face unique challenges when a mother struggles with a postpartum mood disorder. These struggles can impact her capacity to engage fully with all her children, leading to feelings of neglect or even resentment among her siblings. The emotional turbulence can affect the overall family bonding experience, potentially introducing tensions and imbalances that disrupt the equilibrium of familial relationships [ 13 ].

Long-term implications if left untreated: The consequences of untreated postpartum mood disorders can cast long shadows, profoundly affecting not only the mother but also the development and dynamics of her family. Children raised by mothers grappling with unaddressed mood disorders might encounter developmental delays from disrupted caregiving and emotional engagement. These children could also face difficulties regulating their emotions and may have a heightened vulnerability to their mental health issues later in life. The foundations of family dynamics might be reshaped as the mother’s unmet emotional needs continue reverberating, potentially leading to persistent imbalances and strained relationships in the long run [ 11 ].

Identifying and diagnosing postpartum mood disorders

Recognising Symptoms

Accurate identification of postpartum mood disorders is paramount as it is the foundation for timely and effective intervention. By recognising the myriad symptoms that encompass these disorders, healthcare professionals can facilitate early diagnosis and thereby prevent potential escalation of the condition.

Emotional symptoms: The emotional toll of postpartum mood disorders can be profound and wide-ranging. Mothers grappling with these disorders might find themselves immersed in persistent sadness, emptiness, or hopelessness that extends beyond what is commonly expected during the postpartum period. Unexplained and uncontrollable crying spells and intense irritability are further indications of emotional distress. A particularly concerning manifestation is emotional numbness, where mothers might describe feeling disconnected from themselves, their surroundings, or even their newborns [ 2 ].

Cognitive symptoms: Postpartum mood disorders often cast a shadow on cognitive functioning. Mothers might experience notable difficulty in concentrating on tasks, making decisions, or even thinking clearly. This cognitive fog can exacerbate feelings of frustration and inadequacy. A striking hallmark is the emergence of intrusive thoughts - distressing and unwanted ideas or mental images that might be distressing or terrifying. These thoughts might revolve around themes of harm to the baby or oneself despite having no intent or desire for such actions [ 14 ].

Physical symptoms: The physical toll postpartum mood disorders take on mothers is tangible and impactful. Overwhelming fatigue, beyond the expected sleep deprivation associated with caring for an infant, is a common symptom. Changes in appetite and sleep patterns can further compound the physical strain. Many mothers may also experience unexplained physical aches and pains, which often intensify their already grappling with emotional distress. Notably, losing interest in previously enjoyable activities can be a critical indicator that something needs to be corrected [ 15 ].

Screening and assessment tools

Screening and assessment tools constitute a fundamental component in the landscape of postpartum mood disorders. In the delicate period following childbirth, when the emotional well-being of mothers is especially vulnerable, these tools act as essential gateways to early detection and intervention. Two prominent examples of such tools, the Edinburgh Postnatal Depression Scale (EPDS) and the Postpartum Depression Screening Scale (PDSS), are crucial instruments in this endeavour [ 16 ].

The EPDS is widely recognised as a reliable self-report questionnaire that aids healthcare providers in identifying mothers who might be at risk of PPD. The EPDS is designed to explore various mood dimensions, including emotional symptoms such as sadness, anxiety, and irritability. By evaluating responses to specific questions, the EPDS quantifies the severity of these symptoms, effectively gauging the likelihood of a mother experiencing depressive symptoms. Its user-friendly format allows for straightforward administration and interpretation, making it a valuable tool for healthcare providers [ 17 ].

The PDSS is another notable instrument tailored to assess PPD. The PDSS encompasses a broader range of emotional, cognitive, and physical symptoms. Through carefully crafted questions, it captures the nuances of a mother’s emotional experience, aiding healthcare providers in understanding the complexity of her emotional state. This multidimensional approach enhances assessment accuracy, ensuring a more comprehensive evaluation of a mother’s mental well-being [ 18 ].

Both of these screening tools serve a dual purpose. They identify mothers who might be at risk of postpartum mood disorders, thereby facilitating timely intervention. Furthermore, they offer a crucial means of differentiation-helping healthcare providers distinguish between the more transient “baby blues” and the potentially more severe mood disorders that demand specialised attention.

Challenges in Diagnosis

Overlap with typical postpartum experiences: One of the primary challenges lies in the overlap between symptoms of postpartum mood disorders and those considered within the realm of typical postpartum experiences. Fatigue, mood swings, and appetite changes are expected postpartum. Distinguishing between transient mood changes often accompanying the adjustment to new motherhood and persistent symptoms indicative of a disorder requires a nuanced understanding. Healthcare providers must carefully evaluate these symptoms’ duration, intensity, and impact to make an accurate diagnosis. A clear differentiation is vital to avoid either underdiagnosis, which may lead to untreated disorders, or overdiagnosis, which could cause unnecessary distress [ 19 ].

Stigma and cultural considerations: Stigma surrounding mental health issues can create substantial barriers to accurate diagnosis. Women experiencing postpartum mood disorders might be hesitant to acknowledge their struggles due to the fear of judgment or societal misconceptions about mental health. This reluctance to seek help delays intervention and exacerbates the emotional burden. Additionally, cultural norms and expectations related to motherhood vary widely across societies. Some cultures idealise the image of the “strong” and “selfless” mother, which might discourage women from admitting their emotional challenges. Cultural differences can also influence how symptoms are perceived and reported. Expressions of distress might be framed differently or downplayed due to cultural norms, leading to potential inaccuracies in diagnosis [ 19 ].

Treatment and intervention

Psychotherapy Options

Psychotherapy emerges as a fundamental cornerstone in the comprehensive treatment of postpartum mood disorders, pivotal in addressing the intricate emotional landscape experienced by new mothers. This therapeutic approach offers a range of practical strategies designed to alleviate emotional distress and foster overall well-being, tailored to the unique needs of each individual.

Cognitive-behavioural therapy (CBT): Among the prominent psychotherapeutic modalities, CBT stands out as a structured and goal-oriented approach. CBT operates on the premise that our thoughts, emotions, and behaviours are interconnected. CBT provides a roadmap for identifying negative thought patterns and behaviours contributing to emotional distress for mothers grappling with postpartum mood disorders. Mothers learn to challenge and reframe these negative cognitions through collaborative work with trained therapists, replacing them with healthier and more constructive alternatives. This empowerment equips them with valuable coping skills, enabling them to manage their symptoms more effectively and cultivate a more optimistic outlook on their journey through motherhood [ 20 ].

Interpersonal therapy (IPT): IPT is another instrumental psychotherapeutic approach tailored to the challenges of postpartum life. It recognises the profound shifts in interpersonal relationships accompanying motherhood and targets these dynamics as a central focus of therapy. IPT assists mothers in enhancing their communication skills and improving their interpersonal relationships. It equips them with tools to navigate the changes that motherhood introduces into their relationships with partners, family members, and friends. By addressing these shifts head-on, IPT empowers mothers to strengthen their support systems and cultivate healthier, more fulfilling relationships, thus alleviating some of the emotional burdens associated with postpartum mood disorders [ 21 ].

Support groups and peer counselling: In addition to individual therapy modalities, the power of communal support cannot be underestimated. Support groups and peer counselling offer a unique and invaluable space for mothers to connect, share their experiences, and find solace in knowing they are not alone in their struggles. Support groups provide a haven for mothers to express their thoughts and feelings without judgment, receiving validation and understanding from peers who have traversed similar challenges. This shared journey helps reduce feelings of isolation and provides a platform for learning effective coping strategies from those who have firsthand experience. Peer counselling, within this context, fosters an even more profound sense of connection and empathy as mothers provide support for one another guided by their shared experiences [ 22 ].

Pharmacological Interventions

Pharmacological treatments play a crucial role in managing postpartum mood disorders, particularly in cases where symptoms are severe or unresponsive to psychotherapy. Among the most commonly prescribed pharmacological interventions are antidepressants and anti-anxiety medications, with Selective Serotonin Reuptake Inhibitors (SSRIs) taking the forefront. These medications regulate neurotransmitter levels in the brain, effectively mitigating emotional distress and ameliorating the symptoms associated with PPD and anxiety [ 15 ].

However, initiating pharmacological treatment is not without careful consideration, particularly for breastfeeding mothers. Healthcare providers face the delicate task of balancing the potential benefits of medication with the potential risks posed to both the mother and the infant through breast milk. This complex decision-making process considers several factors, including the severity of the mother’s condition, the specific medication’s safety profile for breastfeeding, and the potential impact on the baby’s development [ 23 ].

It’s important to note that many antidepressants and anti-anxiety medications are deemed safe for breastfeeding mothers. This assurance stems from extensive research that has evaluated the passage of these medications into breast milk and their potential effects on infants. In this context, healthcare providers are pivotal in guiding mothers through this decision-making process, providing information about the benefits and potential risks, and working collaboratively to determine the most suitable course of action for the mother’s well-being and the baby’s health.

Importance of Individualized Treatment Plans

Recognising the unique nature of each mother’s experience when dealing with postpartum mood disorders is paramount in providing adequate care. The cookie-cutter approach doesn’t suffice, given the broad spectrum of symptoms, backgrounds, and circumstances that mothers bring to the table. This is where the significance of individualised treatment plans comes into play [ 24 ].

Understanding the complexity: Postpartum mood disorders can manifest differently in each woman. Some might primarily experience emotional turmoil, while others struggle with cognitive symptoms or physical manifestations. Furthermore, factors such as the severity of symptoms, personal medical history, and existing support networks all contribute to the complexity of each case [ 14 ].

Personalised assessment: An effective treatment plan starts with a thorough and personalised assessment. Healthcare professionals must delve into the specific symptoms a mother faces, her medical history (including any preexisting mental health conditions), her personal preferences, and the context in which she’s navigating motherhood [ 25 ].

Tailored approaches: Psychotherapy and pharmacological interventions are powerful tools, but their efficacy dramatically depends on how well they align with an individual’s needs. Some mothers might resonate more with CBT, while others might find relief through IPT. Similarly, when it comes to medications, considering factors like potential side effects, breastfeeding compatibility, and personal comfort with medication use is crucial [ 26 ].

Maximising outcomes: An individualised approach considers each mother’s specific symptoms and needs and ensures that treatment is more likely to be accepted and adhered to. When mothers feel their care plan respects their uniqueness and aligns with their values, they are more likely to engage wholeheartedly in the healing process [ 26 ].

Holistic well-being: Motherhood is a multidimensional journey beyond just the emotional realm. It encompasses physical changes, shifts in roles and responsibilities, and adjustments to daily routines. An individualised treatment plan acknowledges and addresses these interconnected aspects, aiming to restore holistic well-being [ 27 ].

The power of collaboration: The beauty of individualised treatment plans lies in the collaboration between healthcare professionals and mothers. By engaging mothers in the decision-making process and valuing their input, the treatment plan becomes a joint effort to achieve better mental health outcomes [ 28 ].

Role of Healthcare Providers and Mental Health Professionals

The role of healthcare providers and mental health professionals is of paramount importance in addressing postpartum mood disorders. This multidisciplinary approach brings together the expertise of various professionals to ensure the well-being of both mothers and their newborns [ 29 ].

Healthcare providers, encompassing obstetricians, paediatricians, and general practitioners, are often the frontline observers during the postpartum period. Routine postpartum check-ups provide crucial opportunities to assess a mother’s mental well-being alongside her physical health. These encounters allow healthcare providers to establish open lines of communication, creating an environment where mothers feel comfortable sharing their emotional experiences. By incorporating mental health assessments into routine postpartum care, healthcare providers can effectively identify early signs of distress or disorder, enabling timely intervention [ 30 ].

Mental health specialists, mainly those skilled in perinatal and postpartum care, offer a unique and specialised support layer. Their expertise is finely attuned to the emotional intricacies of the transition to motherhood. With comprehensive knowledge of the hormonal, psychological, and sociocultural factors, these specialists possess the insight to diagnose and treat postpartum mood disorders accurately. Their guidance is instrumental in tailoring treatment plans, whether that involves psychotherapy, pharmacological intervention, or a combination of both [ 31 ].

Moreover, mental health professionals provide a safe space for mothers to discuss their feelings, fears, and challenges openly. The non-judgmental and empathetic environment they foster encourages mothers to seek help without stigma. This therapeutic alliance between mental health professionals and mothers ensures that emotional struggles are met with understanding and that appropriate strategies for managing and overcoming these challenges are implemented [ 32 ].

Preventive measures

Prenatal Education and Preparation

Engaging in proactive measures during pregnancy can be pivotal in mitigating the risk of postpartum mood disorders. Among these measures, prenatal education is a cornerstone, offering expectant mothers a valuable tool to enhance their emotional resilience and well-being.

Prenatal education is a compass, guiding mothers through the labyrinth of emotions that can arise postpartum. This educational process equips expectant mothers with a comprehensive understanding of the emotional challenges that might await them after childbirth. It’s an opportunity to shed light on the diverse feelings they might encounter, ranging from the elation of new motherhood to the potential strains and anxieties that can emerge. With this knowledge, mothers are better prepared to recognise the natural variations in their emotional states, helping them avoid unnecessary distress or confusion [ 33 ].

Crucially, prenatal education empowers mothers by equipping them with strategies to manage and navigate these emotions effectively. Understanding that it’s entirely normal to experience a range of positive and challenging feelings reduces the stigma often associated with mood fluctuations. Expectant mothers can learn practical coping techniques like relaxation exercises, mindfulness practices, and stress-reduction strategies. This arsenal of coping tools enhances their emotional well-being and equips them to respond constructively to the emotional challenges that can emerge during the postpartum period [ 34 ]. Furthermore, prenatal education offers a roadmap to creating a solid and supportive postpartum network. Mothers gain insights into the importance of seeking assistance, not as a sign of weakness, but as a proactive step towards ensuring their well-being. They become familiar with the available resources, from mental health professionals to support groups, enabling them to reach out for help without hesitation when needed. By understanding where to turn and who to talk to, mothers are better positioned to seek timely support, preventing isolated struggles from escalating into more severe mood disorders.

Lifestyle Modifications

Exercise and physical well-being: Engaging in regular physical activity during both pregnancy and postpartum holds the potential for significant positive impacts on mental well-being. Exercise acts as a natural mood enhancer, promoting the release of endorphins, commonly referred to as “feel-good” hormones. These endorphins help alleviate feelings of stress, anxiety, and even depression. Engaging in activities such as yoga, walking, swimming, or other low-impact exercises helps maintain physical fitness and contributes to mental rejuvenation [ 35 ].

Moreover, exercise offers more than just a physiological boost. It can provide a valuable opportunity for new mothers to engage in self-care and carve out time for themselves amidst their caregiving responsibilities. Participating in group classes or outdoor activities can also foster social interaction, combating feelings of isolation that some mothers might experience during this transition period. By incorporating regular physical activity into their routines, new mothers can cultivate a sense of empowerment, confidence, and emotional resilience [ 36 ].

Nutrition and sleep: The significance of maintaining a balanced diet during the postpartum period cannot be overstated. Adequate nutrition provides the necessary fuel for physical recovery, especially after the demands of childbirth. But beyond physical health, a balanced diet rich in nutrients can directly impact emotional well-being. Certain nutrients, such as omega-3 fatty acids and B vitamins, are linked to improved mood regulation and mental clarity [ 37 ].

Equally crucial is prioritising sufficient sleep. New mothers face sleep deprivation due to the demands of round-the-clock care for their newborns. However, deliberate efforts to improve sleep quality can substantially affect mental health. Even if it means catching naps during the day, establishing a consistent sleep schedule can help regulate circadian rhythms and promote better sleep patterns. Creating a conducive sleep environment by minimising noise, dimming lights, and ensuring comfort further supports better sleep quality [ 38 ].

Social Support Systems

Partner involvement: The involvement of partners in a mother’s journey through postpartum mood disorders is paramount. Partners not only provide a vital emotional anchor but also offer practical assistance that can significantly alleviate the challenges faced by new mothers. Open and honest communication between partners fosters an environment where mothers feel comfortable expressing their feelings and seeking help when needed. Sharing responsibilities in caregiving, household chores, and other daily tasks can significantly reduce the burden on the mother, allowing her the time and space to focus on her well-being and recovery. Partners who consciously try to understand the emotional turmoil accompanying postpartum mood disorders strengthen the relationship, forging a more profound bond built on empathy and mutual support [ 9 ].

Family and friends as a support network: The presence of a robust support network, comprising not only partners but also extended family and friends, can serve as a lifeline for mothers grappling with postpartum mood disorders. People willing to lend a listening ear, offer reassurance, and assist when needed can make an immense difference in a mother's emotional well-being. Confiding in someone who understands and empathises with her struggles can alleviate the sense of isolation that often accompanies these disorders. Family and friends can offer a safe space for mothers to share their feelings without judgment, helping them process their emotions and navigate the challenges of motherhood. Additionally, practical help, such as babysitting, preparing meals, or running errands, can lighten the load and allow mothers the time and energy to focus on their recovery. The support of loved ones eases the emotional strain and reinforces the sense of community and belonging, reminding mothers that they are not alone on this journey [ 9 ].

Cultural and societal influences

Cultural Variations in Perceptions of Motherhood and Mental Health

The diverse tapestry of cultures across the globe contributes to a fascinating array of perspectives on motherhood and mental health. Cultural norms, traditions, and beliefs play an influential role in shaping how these topics are understood, discussed, and approached. Such cultural intricacies profoundly affect how different societies perceive and manage postpartum mood disorders [ 39 ].

In the realm of motherhood, cultural variations become evident in the expectations set for women as they embark on this transformative journey. Some cultures uphold a view of motherhood that idealises self-sacrifice and unconditional devotion to the family unit. In these societies, the role of a mother might be perceived as secondary to the well-being of her children and partner. Conversely, other cultures adopt a more holistic approach that recognises the importance of a mother’s well-being alongside her caregiving responsibilities. Here, the balance between self-care and caregiving is emphasised, acknowledging that a mother’s emotional and mental health directly impacts her ability to nurture her family effectively [ 40 ].

However, cultural norms can also give rise to challenges when acknowledging and addressing postpartum mood disorders. The stigmatisation of mental health issues might prevail in certain cultures, rendering discussions about emotional struggles taboo. This stigma can create a barrier that discourages mothers from openly expressing their symptoms or seeking professional help. The fear of being labelled as “weak” or “unfit” may lead to the underreporting of symptoms and a reluctance to access necessary support systems [ 41 ].

Understanding these cultural variations is pivotal for delivering effective and culturally sensitive care. Healthcare providers must be attuned to the nuances of each culture, recognising how perceptions of motherhood and mental health intersect. This awareness allows for developing strategies that break down barriers, encourage open conversations, and provide tailored support to mothers in a way that respects their cultural backgrounds. By embracing these diversities, we can bridge the gap between awareness and destigmatisation, ensuring that all mothers receive the comprehensive care they need while respecting their cultural contexts [ 42 ].

Barriers to Seeking Help in Different Societies

Cultural and societal factors can create significant barriers to seeking help for postpartum mood disorders, impeding the well-being of mothers and hindering timely interventions. These barriers are shaped by prevailing attitudes, norms, and expectations within specific societies, impacting how women perceive and address their mental health challenges [ 43 ].

Stigma around mental health issues: The mental health stigma is deeply entrenched in certain societies. Mental health issues may be misunderstood or associated with personal weakness or instability. Consequently, women experiencing postpartum mood disorders might feel ashamed or afraid of being judged by their communities. The fear of being labelled “mentally ill” can discourage women from acknowledging their struggles and seeking professional support [ 44 ].

Cultural notions of womanhood and caregiving: A woman’s role as a primary caregiver is often central in many cultures. Women are expected to prioritise the needs of their families and children, often at the expense of their well-being. Admitting emotional difficulties might be perceived as a deviation from this role, and women might worry that seeking help would be seen as a failure to fulfil their societal obligations. This clash between cultural expectations and emotional challenges can deter women from seeking desperately needed support [ 45 ].

These barriers highlight the complexity of addressing maternal mental health globally. Healthcare systems, governments, and communities must acknowledge and address these cultural and societal factors when designing interventions and support networks. By promoting awareness, education, and destigmatisation, we can gradually break down these barriers and create an environment where women feel empowered to seek help without fear of judgment or reproach.

Importance of Destigmatizing Postpartum Mood Disorders

The significance of destigmatising postpartum mood disorders cannot be overstated, as it holds profound implications for both individual well-being and the broader societal fabric. This process is crucial for a multitude of reasons that resonate deeply with the challenges faced by mothers:

Stigma prevents mothers from seeking help, delaying intervention and exacerbating emotional distress: The stigma surrounding mental health issues often casts a shadow of shame and embarrassment, leading mothers to internalise their struggles and refrain from seeking professional help. This delay in seeking intervention can prolong their emotional turmoil, potentially worsening symptoms and impeding their ability to care for themselves and their newborns effectively [ 46 ].

Promoting open conversations around mental health reduces isolation and fosters community support: Destigmatization paves the way for open discussions about postpartum mood disorders. When mothers feel empowered to share their experiences without fear of judgment, it breaks down the isolation that often accompanies these disorders. Open conversations foster a sense of belonging and validate the experiences of countless mothers who may be silently grappling with similar challenges [ 19 ].

Breaking down stigma encourages governments, healthcare systems, and communities to allocate resources for maternal mental health support: The weight of stigma extends beyond individual experiences. It obstructs progress on a systemic level, hindering governments, healthcare systems, and communities from prioritising maternal mental health support. By destigmatising these disorders, society can channel resources toward comprehensive and accessible care, ranging from awareness campaigns to specialised healthcare services catering to mothers’ unique needs [ 47 ].

Future directions and research

Advances in Understanding Hormonal Influences

As research continues, advances in understanding the intricate hormonal changes that occur during pregnancy and the postpartum period can shed light on the links between these fluctuations and mood disorders. A more profound comprehension of how hormonal shifts affect neurotransmitter regulation and brain function may pave the way for more targeted interventions and treatments.

Long-Term Effects on Maternal Mental Health

Exploring the long-term impact of untreated postpartum mood disorders on maternal mental health is an emerging area of research. Understanding how these disorders can influence a woman’s emotional well-being can highlight the necessity of early intervention and comprehensive support during the postpartum period.

Development of Targeted Interventions

A dvancements in personalised medicine offer the potential for tailoring interventions to individual needs. Genetic markers, hormonal profiles, and other factors can guide the development of more effective treatments for specific individuals, increasing the likelihood of positive outcomes.

Conclusions

This comprehensive exploration underscores a vital call to action. Increased awareness and support are imperative to shatter the stigma enveloping postpartum mood disorders, encouraging mothers to seek assistance without hesitation. Collaborative efforts involving healthcare providers, communities, and governments are necessary to establish accessible and culturally sensitive support networks. Partners, family, and friends are pivotal in nurturing open dialogues and actively participating in the well-being of new mothers. Ultimately, a hopeful vision emerges - a future where maternal mental health is paramount. A future where no mother stands alone, where comprehensive resources and care empower them to navigate the complexities of motherhood with resilience. Through collective dedication, we can foster healthier mothers, strengthen familial bonds, and create communities that embody empathy and understanding. This review asserts that with concerted endeavours, we can transform this vision into reality, ensuring that every mother receives the appropriate mental health care she deserves.

The authors have declared that no competing interests exist.

Cannabis use and mood disorders: a systematic review

Affiliations.

• 1 Institute for Mental Health Policy and Research at CAMH, Toronto, ON, Canada.
• 2 Department of Psychiatry, Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
• 3 Department of Psychology, McGill University, Montreal, QC, Canada.
• PMID: 38655516
• PMCID: PMC11035759
• DOI: 10.3389/fpubh.2024.1346207

Background: Problematic cannabis use is highly prevalent among people with mood disorders. This underscores the need to understand the effects of cannabis and cannabinoids in this population, especially considering legalization of recreational cannabis use.

Objectives: We aimed to (1) systematically evaluate cross-sectional and longitudinal studies investigating the interplay between cannabis use, cannabis use disorder (CUD), and the occurrence of mood disorders and symptoms, with a focus on major depressive disorder (MDD) and bipolar disorder (BD) and; (2) examine the effects of cannabis on the prognosis and treatment outcomes of MDD and BD.

Methods: Following PRISMA guidelines, we conducted an extensive search for English-language studies investigating the potential impact of cannabis on the development and prognosis of mood disorders published from inception through November 2023, using EMBASE, PsycINFO, PubMed, and MEDLINE databases.

Results: Our literature search identified 3,262 studies, with 78 meeting inclusion criteria. We found that cannabis use is associated with increased depressive and manic symptoms in the general population in addition to an elevated likelihood of developing MDD and BD. Furthermore, we observed that cannabis use is linked to an unfavorable prognosis in both MDD or BD.

Discussion: Our findings suggest that cannabis use may negatively influence the development, course, and prognosis of MDD and BD. Future well-designed studies, considering type, amount, and frequency of cannabis use while addressing confounding factors, are imperative for a comprehensive understanding of this relationship.

Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023481634.

Keywords: bipolar disorder; cannabis; depression; major depressive disorder; mania; suicidality.

Copyright © 2024 Sorkhou, Dent and George.

Publication types

• Systematic Review
• Research Support, Non-U.S. Gov't
• Bipolar Disorder
• Cross-Sectional Studies
• Depressive Disorder, Major*
• Longitudinal Studies
• Marijuana Abuse / complications
• Marijuana Abuse / epidemiology
• Marijuana Use / epidemiology
• Mood Disorders

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