case study of someone with depression

Mental Health Case Study: Understanding Depression through a Real-life Example

Imagine feeling an unrelenting heaviness weighing down on your chest. Every breath becomes a struggle as a cloud of sadness engulfs your every thought. Your energy levels plummet, leaving you physically and emotionally drained. This is the reality for millions of people worldwide who suffer from depression, a complex and debilitating mental health condition.

Understanding depression is crucial in order to provide effective support and treatment for those affected. While textbooks and research papers provide valuable insights, sometimes the best way to truly comprehend the depths of this condition is through real-life case studies. These stories bring depression to life, shedding light on its impact on individuals and society as a whole.

In this article, we will delve into the world of mental health case studies, using a real-life example to explore the intricacies of depression. We will examine the symptoms, prevalence, and consequences of this all-encompassing condition. Furthermore, we will discuss the significance of case studies in mental health research, including their ability to provide detailed information about individual experiences and contribute to the development of treatment strategies.

Through an in-depth analysis of a selected case study, we will gain insight into the journey of an individual facing depression. We will explore their background, symptoms, and initial diagnosis. Additionally, we will examine the various treatment options available and assess the effectiveness of the chosen approach.

By delving into this real-life example, we will not only gain a better understanding of depression as a mental health condition, but we will also uncover valuable lessons that can aid in the treatment and support of those who are affected. So, let us embark on this enlightening journey, using the power of case studies to bring understanding and empathy to those who need it most.

Understanding Depression

Depression is a complex and multifaceted mental health condition that affects millions of people worldwide. To comprehend the impact of depression, it is essential to explore its defining characteristics, prevalence, and consequences on individuals and society as a whole.

Defining depression and its symptoms

Depression is more than just feeling sad or experiencing a low mood. It is a serious mental health disorder characterized by persistent feelings of sadness, hopelessness, and a loss of interest in activities that were once enjoyable. Individuals with depression often experience a range of symptoms that can significantly impact their daily lives. These symptoms include:

1. Persistent feelings of sadness or emptiness. 2. Fatigue and decreased energy levels. 3. Significant changes in appetite and weight. 4. Difficulty concentrating or making decisions. 5. Insomnia or excessive sleep. 6. feelings of guilt, worthlessness, or hopelessness. 7. Loss of interest or pleasure in activities.

Exploring the prevalence of depression worldwide

Depression knows no boundaries and affects individuals from all walks of life. According to the World Health Organization (WHO), an estimated 264 million people globally suffer from depression. This makes depression one of the most common mental health conditions worldwide. Additionally, the WHO highlights that depression is more prevalent among females than males.

The impact of depression is not limited to individuals alone. It also has significant social and economic consequences. Depression can lead to impaired productivity, increased healthcare costs, and strain on relationships, contributing to a significant burden on families, communities, and society at large.

The impact of depression on individuals and society

Depression can have a profound and debilitating impact on individuals’ lives, affecting their physical, emotional, and social well-being. The persistent sadness and loss of interest can lead to difficulties in maintaining relationships, pursuing education or careers, and engaging in daily activities. Furthermore, depression increases the risk of developing other mental health conditions, such as anxiety disorders or substance abuse.

On a societal level, depression poses numerous challenges. The economic burden of depression is significant, with costs associated with treatment, reduced productivity, and premature death. Moreover, the social stigma surrounding mental health can impede individuals from seeking help and accessing appropriate support systems.

Understanding the prevalence and consequences of depression is crucial for policymakers, healthcare professionals, and individuals alike. By recognizing the significant impact depression has on individuals and society, appropriate resources and interventions can be developed to mitigate its effects and improve the overall well-being of those affected.

The Significance of Case Studies in Mental Health Research

Case studies play a vital role in mental health research, providing valuable insights into individual experiences and contributing to the development of effective treatment strategies. Let us explore why case studies are considered invaluable in understanding and addressing mental health conditions.

Why case studies are valuable in mental health research

Case studies offer a unique opportunity to examine mental health conditions within the real-life context of individuals. Unlike large-scale studies that focus on statistical data, case studies provide a detailed examination of specific cases, allowing researchers to delve into the complexities of a particular condition or treatment approach. This micro-level analysis helps researchers gain a deeper understanding of the nuances and intricacies involved.

The role of case studies in providing detailed information about individual experiences

Through case studies, researchers can capture rich narratives and delve into the lived experiences of individuals facing mental health challenges. These stories help to humanize the condition and provide valuable insights that go beyond a list of symptoms or diagnostic criteria. By understanding the unique experiences, thoughts, and emotions of individuals, researchers can develop a more comprehensive understanding of mental health conditions and tailor interventions accordingly.

How case studies contribute to the development of treatment strategies

Case studies form a vital foundation for the development of effective treatment strategies. By examining a specific case in detail, researchers can identify patterns, factors influencing treatment outcomes, and areas where intervention may be particularly effective. Moreover, case studies foster an iterative approach to treatment development—an ongoing cycle of using data and experience to refine and improve interventions.

By examining multiple case studies, researchers can identify common themes and trends, leading to the development of evidence-based guidelines and best practices. This allows healthcare professionals to provide more targeted and personalized support to individuals facing mental health conditions.

Furthermore, case studies can shed light on potential limitations or challenges in existing treatment approaches. By thoroughly analyzing different cases, researchers can identify gaps in current treatments and focus on areas that require further exploration and innovation.

In summary, case studies are a vital component of mental health research, offering detailed insights into the lived experiences of individuals with mental health conditions. They provide a rich understanding of the complexities of these conditions and contribute to the development of effective treatment strategies. By leveraging the power of case studies, researchers can move closer to improving the lives of individuals facing mental health challenges.

Examining a Real-life Case Study of Depression

In order to gain a deeper understanding of depression, let us now turn our attention to a real-life case study. By exploring the journey of an individual navigating through depression, we can gain valuable insights into the complexities and challenges associated with this mental health condition.

Introduction to the selected case study

In this case study, we will focus on Jane, a 32-year-old woman who has been struggling with depression for the past two years. Jane’s case offers a compelling narrative that highlights the various aspects of depression, including its onset, symptoms, and the treatment journey.

Background information on the individual facing depression

Before the onset of depression, Jane led a fulfilling and successful life. She had a promising career, a supportive network of friends and family, and engaged in hobbies that brought her joy. However, a series of life stressors, including a demanding job, a breakup, and the loss of a loved one, began to take a toll on her mental well-being.

Jane’s background highlights a common phenomenon – depression can affect individuals from all walks of life, irrespective of their socio-economic status, age, or external circumstances. It serves as a reminder that no one is immune to mental health challenges.

Presentation of symptoms and initial diagnosis

Jane began noticing a shift in her mood, characterized by persistent feelings of sadness and a lack of interest in activities she once enjoyed. She experienced disruptions in her sleep patterns, appetite changes, and a general sense of hopelessness. Recognizing the severity of her symptoms, Jane sought help from a mental health professional who diagnosed her with major depressive disorder.

Jane’s case exemplifies the varied and complex symptoms associated with depression. While individuals may exhibit overlapping symptoms, the intensity and manifestation of those symptoms can vary greatly, underscoring the importance of personalized and tailored treatment approaches.

By examining this real-life case study of depression, we can gain an empathetic understanding of the challenges faced by individuals experiencing this mental health condition. Through Jane’s journey, we will uncover the treatment options available for depression and analyze the effectiveness of the chosen approach. The case study will allow us to explore the nuances of depression and provide valuable insights into the treatment landscape for this prevalent mental health condition.

The Treatment Journey

When it comes to treating depression, there are various options available, ranging from therapy to medication. In this section, we will provide an overview of the treatment options for depression and analyze the treatment plan implemented in the real-life case study.

Overview of the treatment options available for depression

Treatment for depression typically involves a combination of approaches tailored to the individual’s needs. The two primary treatment modalities for depression are psychotherapy (talk therapy) and medication. Psychotherapy aims to help individuals explore their thoughts, emotions, and behaviors, while medication can help alleviate symptoms by restoring chemical imbalances in the brain.

Common forms of psychotherapy used in the treatment of depression include cognitive-behavioral therapy (CBT), interpersonal therapy (IPT), and psychodynamic therapy. These therapeutic approaches focus on addressing negative thought patterns, improving relationship dynamics, and gaining insight into underlying psychological factors contributing to depression.

In cases where medication is utilized, selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed. These medications help rebalance serotonin levels in the brain, which are often disrupted in individuals with depression. Other classes of antidepressant medications, such as serotonin-norepinephrine reuptake inhibitors (SNRIs) or tricyclic antidepressants (TCAs), may be considered in specific cases.

Exploring the treatment plan implemented in the case study

In Jane’s case, a comprehensive treatment plan was developed with the intention of addressing her specific needs and symptoms. Recognizing the severity of her depression, Jane’s healthcare team recommended a combination of talk therapy and medication.

Jane began attending weekly sessions of cognitive-behavioral therapy (CBT) with a licensed therapist. This form of therapy aimed to help Jane identify and challenge negative thought patterns, develop coping strategies, and cultivate more adaptive behaviors. The therapeutic relationship provided Jane with a safe space to explore and process her emotions, ultimately helping her regain a sense of control over her life.

In conjunction with therapy, Jane’s healthcare provider prescribed an SSRI medication to assist in managing her symptoms. The medication was carefully selected based on Jane’s specific symptoms and medical history, and regular follow-up appointments were scheduled to monitor her response to the medication and adjust the dosage if necessary.

Analyzing the effectiveness of the treatment approach

The effectiveness of treatment for depression varies from person to person, and it often requires a period of trial and adjustment to find the most suitable intervention. In Jane’s case, the combination of cognitive-behavioral therapy and medication proved to be beneficial. Over time, she reported a reduction in her depressive symptoms, an improvement in her overall mood, and increased ability to engage in activities she once enjoyed.

It is important to note that the treatment journey for depression is not always linear, and setbacks and challenges may occur along the way. Each individual responds differently to treatment, and adjustments might be necessary to optimize outcomes. Continuous communication between the individual and their healthcare team is crucial to addressing any concerns, monitoring progress, and adapting the treatment plan as needed.

By analyzing the treatment approach in the real-life case study, we gain insights into the various treatment options available for depression and how they can be tailored to meet individual needs. The combination of psychotherapy and medication offers a holistic approach, addressing both psychological and biological aspects of depression.

The Outcome and Lessons Learned

After undergoing treatment for depression, it is essential to assess the outcome and draw valuable lessons from the case study. In this section, we will discuss the progress made by the individual in the case study, examine the challenges faced during the treatment process, and identify key lessons learned.

Discussing the progress made by the individual in the case study

Throughout the treatment process, Jane experienced significant progress in managing her depression. She reported a reduction in depressive symptoms, improved mood, and a renewed sense of hope and purpose in her life. Jane’s active participation in therapy, combined with the appropriate use of medication, played a crucial role in her progress.

Furthermore, Jane’s support network of family and friends played a significant role in her recovery. Their understanding, empathy, and support provided a solid foundation for her journey towards improved mental well-being. This highlights the importance of social support in the treatment and management of depression.

Examining the challenges faced during the treatment process

Despite the progress made, Jane faced several challenges during her treatment journey. Adhering to the treatment plan consistently proved to be difficult at times, as she encountered setbacks and moments of self-doubt. Additionally, managing the side effects of the medication required careful monitoring and adjustments to find the right balance.

Moreover, the stigma associated with mental health continued to be a challenge for Jane. Overcoming societal misconceptions and seeking help required courage and resilience. The case study underscores the need for increased awareness, education, and advocacy to address the stigma surrounding mental health conditions.

Identifying the key lessons learned from the case study

The case study offers valuable lessons that can inform the treatment and support of individuals with depression:

1. Holistic Approach: The combination of psychotherapy and medication proved to be effective in addressing the psychological and biological aspects of depression. This highlights the need for a holistic and personalized treatment approach.

2. Importance of Support: Having a strong support system can significantly impact an individual’s ability to navigate through depression. Family, friends, and healthcare professionals play a vital role in providing empathy, understanding, and encouragement.

3. Individualized Treatment: Depression manifests differently in each individual, emphasizing the importance of tailoring treatment plans to meet individual needs. Personalized interventions are more likely to lead to positive outcomes.

4. Overcoming Stigma: Addressing the stigma associated with mental health conditions is crucial for individuals to seek timely help and access the support they need. Educating society about mental health is essential to create a more supportive and inclusive environment.

By drawing lessons from this real-life case study, we gain insights that can improve the understanding and treatment of depression. Recognizing the progress made, understanding the challenges faced, and implementing the lessons learned can contribute to more effective interventions and support systems for individuals facing depression.In conclusion, this article has explored the significance of mental health case studies in understanding and addressing depression, focusing on a real-life example. By delving into case studies, we gain a deeper appreciation for the complexities of depression and the profound impact it has on individuals and society.

Through our examination of the selected case study, we have learned valuable lessons about the nature of depression and its treatment. We have seen how the combination of psychotherapy and medication can provide a holistic approach, addressing both psychological and biological factors. Furthermore, the importance of social support and the role of a strong network in an individual’s recovery journey cannot be overstated.

Additionally, we have identified challenges faced during the treatment process, such as adherence to the treatment plan and managing medication side effects. These challenges highlight the need for ongoing monitoring, adjustments, and open communication between individuals and their healthcare providers.

The case study has also emphasized the impact of stigma on individuals seeking help for depression. Addressing societal misconceptions and promoting mental health awareness is essential to create a more supportive environment for those affected by depression and other mental health conditions.

Overall, this article reinforces the significance of case studies in advancing our understanding of mental health conditions and developing effective treatment strategies. Through real-life examples, we gain a more comprehensive and empathetic perspective on depression, enabling us to provide better support and care for individuals facing this mental health challenge.

As we conclude, it is crucial to emphasize the importance of continued research and exploration of mental health case studies. The more we learn from individual experiences, the better equipped we become to address the diverse needs of those affected by mental health conditions. By fostering a culture of understanding, support, and advocacy, we can strive towards a future where individuals with depression receive the care and compassion they deserve.

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• Published: 03 April 2019

Prognosis and improved outcomes in major depression: a review

• Christoph Kraus   ORCID: orcid.org/0000-0002-7144-2282 1 , 2 ,
• Bashkim Kadriu   ORCID: orcid.org/0000-0002-3809-9451 2 ,
• Rupert Lanzenberger   ORCID: orcid.org/0000-0003-4641-9539 1 ,
• Carlos A. Zarate Jr. 2 &
• Siegfried Kasper   ORCID: orcid.org/0000-0001-8278-191X 1  

Translational Psychiatry volume  9 , Article number:  127 ( 2019 ) Cite this article

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Treatment outcomes for major depressive disorder (MDD) need to be improved. Presently, no clinically relevant tools have been established for stratifying subgroups or predicting outcomes. This literature review sought to investigate factors closely linked to outcome and summarize existing and novel strategies for improvement. The results show that early recognition and treatment are crucial, as duration of untreated depression correlates with worse outcomes. Early improvement is associated with response and remission, while comorbidities prolong course of illness. Potential biomarkers have been explored, including hippocampal volumes, neuronal activity of the anterior cingulate cortex, and levels of brain-derived neurotrophic factor (BDNF) and central and peripheral inflammatory markers (e.g., translocator protein (TSPO), interleukin-6 (IL-6), C-reactive protein (CRP), tumor necrosis factor alpha (TNFα)). However, their integration into routine clinical care has not yet been fully elucidated, and more research is needed in this regard. Genetic findings suggest that testing for CYP450 isoenzyme activity may improve treatment outcomes. Strategies such as managing risk factors, improving clinical trial methodology, and designing structured step-by-step treatments are also beneficial. Finally, drawing on existing guidelines, we outline a sequential treatment optimization paradigm for selecting first-, second-, and third-line treatments for acute and chronically ill patients. Well-established treatments such as electroconvulsive therapy (ECT) are clinically relevant for treatment-resistant populations, and novel transcranial stimulation methods such as theta-burst stimulation (TBS) and magnetic seizure therapy (MST) have shown promising results. Novel rapid-acting antidepressants, such as ketamine, may also constitute a paradigm shift in treatment optimization for MDD.

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Major depressive disorder (MDD) is the most common psychiatric disease and a worldwide leading cause of years lived with disability 1 , 2 . In addition, the bulk of suicides are linked to a diagnosis of MDD. Despite the high prevalence rate of MDD and ongoing efforts to increase knowledge and skills for healthcare providers, the illness remains both underdiagnosed and undertreated 3 . Many novel strategies with potentially broad impact are not yet ready for ‘prime time’, as they are either in early experimental stages or undergoing regulatory processes for approval. This review sought to: (1) provide a synopsis of key factors associated with outcomes in MDD, and (2) synthesize the existing literature on novel treatment strategies for depression. A literature search was conducted using the search terms ‘depression’, ‘antidepressant’, ‘outcome’, ‘predictor’, ‘(bio)marker’, ‘treatment-resistant depression (TRD)’, and ‘chronic depression’ in addition to combinations of these terms. The search was conducted in PubMed, Scopus, and Google Scholar with no restrictions on time period and concluded in October 2018. Notably, we defined ‘outcomes’ loosely, as either disease course (i.e., treatment resistance, chronic depression) or response/remission to treatment.

Prognostic variables for treatment outcomes in MDD

Clinical variables.

Clear evidence of an inverse relationship between duration of episode and treatment outcome (either response or remission) underscores the importance of early intervention in MDD 4 (Table 1 ). In particular, replicable prospective and retrospective studies indicate that shorter duration of untreated disease—both in terms of first and recurrent episodes—is a prognostic factor indicating better treatment response and better long-term outcomes 5 , 6 , 7 , 8 , 9 , 10 , although not all studies have found such an association 11 . Another important clinical variable is time to antidepressant response. For instance, one meta-analysis found that early improvement was positively linked to antidepressant treatment outcome in 15 of 16 studies 9 . Early response to antidepressant treatment appears to occur independently of treatment modality 12 , 13 or outcome parameters 14 , 15 . Another study found that early improvement in work productivity was a significant positive predictor of higher remission rates after three and seven months of treatment 16 . Similarly, imaging studies found that early response to treatment correlated with default mode network deactivation in the posterior cingulate 17 , as well as thickening of gray matter in the anterior cingulate cortex (ACC) 18 . Interestingly, two recent meta-analyses found that initial improvement was linked to response and outcome but failed to be associated with treatment resistance 19 , 20 . This suggests that TRD—defined loosely here as non-response to at least two adequate antidepressant trials—and chronic depression (roughly defined here as non-response to any treatment) may have similar response slopes in the earliest treatment stages.

In addition, lower baseline function and quality of life—including longer duration of the current index episode—have been associated with lower remission rates to various types of antidepressant treatments 21 , 22 . This is in line with results from a previous study that found that baseline function predicted antidepressant response in TRD patients 23 . Worse outcomes in more severely ill patients at baseline were also reported in elderly patients treated in primary-care settings 24 . In contrast, several controlled clinical studies found that elevated baseline severity correlated with improved response and remission rates 25 . Two naturalistic studies with broad inclusion criteria similarly found that remission correlated with higher baseline scores 4 , 26 . However, this discrepancy might be explained by variations in outcome according to parameter. It was noted earlier that studies that defined remission as percent change of baseline values might be biased in favor of higher baseline scores, while absolute endpoints (e.g., remission defined below a cutoff score) favor less sick patients 4 .

Psychosocial variables

The influence of sociodemographic factors such as age, age of onset, gender, and number of previous episodes on treatment outcome has been investigated with mixed results 4 , 27 , 28 . One study found that females had higher remission rates 21 , but this was not confirmed by another prospective study 27 . Others have found that stress related to high occupational levels might impair outcomes 29 . The European “Group for the Study of Resistant Depression” (GSRD) multi-site study found that age at first treatment (i.e., early-onset and early treatment), age, timespan between first and last episode (i.e., duration of illness), suicidality, and education level were all important variables for outcome 30 . Notably, authors of long-lasting longitudinal studies have suggested that recall bias may influence the age of onset variable 31 , 32 ; given the cognitive deficits associated with acute episodes of MDD, retrospective studies must hence address the factor of memory bias in data collection.

Environmental stress and stressful life events (SLEs)

High stress levels significantly influence outcomes in MDD patients who are prone to vulnerable states, such as those with high levels of neuroticism 33 , 34 . A meta-analysis found that history of childhood maltreatment was associated with elevated risk of developing recurrent and persistent depressive episodes, as well as with lack of response or remission during treatment 35 . Another meta-analysis confirmed the detrimental impact of childhood maltreatment (emotional physical or sexual maltreatment or neglect) as a predisposing risk factor for severe, early-onset, and treatment-resistant depression 36 , 37 . Studies also found gender-specific effects; in particular, at lower stress levels females were at higher risk of MDD than males 34 . Moreover, twin studies have suggested a differential reactivity of gender in response to type of SLE 38 . For instance, a treatment study using escitalopram and nortriptyline investigated the association between number of SLEs (e.g., job loss, psychological trauma, loss of a loved one) and antidepressant treatment. Subjects with more SLEs exhibited greater cognitive symptoms at baseline but not significantly more mood or neurovegetative symptoms. These patients also had greater cognitive symptom reduction in response to escitalopram but not nortriptyline 39 . This suggests that SLEs may have a cognitive domain-specific impact in MDD, but more data are needed to elucidate this issue.

Psychiatric and physical comorbidities

Psychiatric comorbidity has been shown to influence outcome in both treated and untreated patients 40 , 41 . Studies have found that elevated baseline anxiety symptoms or comorbid anxiety disorder are associated with worse antidepressant response to first-line selective serotonin reuptake inhibitors (SSRIs) or second-line treatment strategies 42 , 43 . Worse outcomes have also been reported for MDD patients with comorbid drug or alcohol use disorders, post-traumatic stress disorder (PTSD), and “double depression” (depression and dysthymia) 26 , 41 . Data from the Sequential Treatment Alternatives to Relieve Depression (STAR*D) study, which included patients who were seeking medical care in routine medical or psychiatric outpatient treatment, indicate that roughly one-third (34.8%) of all MDD patients are free of any comorbidity; the most frequent comorbid Axis-I disorders are social phobia (31.3%), generalized anxiety disorder (23.6%), PTSD (20.6%), and obsessive-compulsive disorder (14.3%) 21 . A large recent study found that clinically diagnosed personality disorder was associated with negative outcomes (with regard to remission and persistent depressive symptoms) six months after diagnosis in MDD subjects enrolled in primary care 44 . Moreover, meta-analytic studies indicate that comorbid personality disorder increases the likelihood of poorer outcomes 45 , 46 ; it should be noted, though, that negative studies have also been reported 40 .

MDD and several physical diseases—including cardiovascular disease and diabetes—appear to have bidirectional effects on disease trajectory 47 , 48 , yet pathophysiologic links are most likely complex and have to be elucidated. In addition, depression appears to be linked to hormonal diseases, including hypothyroidism 49 . A number of physical disabilities and medical comorbidities have been shown to significantly impact outcome measures in MDD 50 , particularly in elderly subjects 51 . This connection appears to be relevant at any stage of the disease, as number of physical comorbidities did not separate TRD from non-TRD patients 52 . Links between MDD and pain have also been noted; subjects with elevated levels of baseline pain due to chronic conditions had longer depressive episodes, delayed remission 53 and, most importantly, elevated suicide risk 54 , 55 . Interestingly, a prospective, 12-month study of older patients found that elderly patients with atrial fibrillation exhibited better remission rates 56 . Patients with chronic pulmonary diseases had worse outcomes in uncontrolled treatment settings than those without these diseases. This difference was absent in the intervention group, in which depression care managers helped physicians with guideline-concordant recommendations and helped patients adhere to treatment 56 . Further longitudinal studies on shared pathophysiology with physical diseases are needed to confirm such associations.

Neuroimaging markers of treatment outcomes

Structural markers of antidepressant treatment outcomes suggest that hippocampal volumes are related to response and remission 57 , 58 . One study found that low baseline hippocampal volumes were related to impaired treatment outcomes after 3 years 59 ; a meta-analysis confirmed that low baseline hippocampal volumes are associated with negative outcomes 60 . However, negative studies have also been reported 61 , 62 . The volume of other brain regions, including the anterior cingulate or orbitofrontal cortices, have also been shown to be decreased in MDD subjects 63 , but more longitudinal neuroimaging trials with antidepressants are needed to clarify this association. Interestingly, several studies, including one meta-analysis 64 , found significant hippocampal volume increases after ECT 65 , 66 , 67 , although the relationship to antidepressant response has yet to be confirmed 64 , 68 .

The largest functional magnetic resonance imaging (fMRI) study of MDD patients conducted to date reported neurophysiological subtypes based on connectivity patterns within limbic and frontostriatal brain areas 69 . In subset analyses, connectivity patterns plus subtype classifications predicted response to repetitive transcranial magnetic stimulation (rTMS) treatment with higher accuracy (89.6%) than clinical characteristics alone. Other task-based and resting-state fMRI studies found that ACC activity (including pregenual activity) predicted treatment response 70 , a finding corroborated by an expanded electroencephalography study 71 as well as a meta-analysis 60 . While these interesting results suggest that fMRI measures could ultimately help classify biological subtypes of depression, these methods are far from ready for clinical application and results will have to be reproduced. However, given its easy implementation and the short time needed to acquire measurements, fMRI appears to be a promising tool for identifying imaging biomarkers.

Positron emission tomography (PET) studies have identified altered serotonin-1A (5-HT 1A ) receptor and 5-HT transporter (SERT) binding potentials, an index of protein concentration, at baseline and in TRD patients 72 , 73 , 74 , 75 . Most of these results found reduced baseline SERT levels and elevated baseline 5-HT 1A heteroreceptors in MDD patients (depending on PET methodology for 5-HT 1A ); non-remitters had lower 5-HT 1A autoreceptor binding in the serotonergic raphe nuclei 75 , as well as lower SERT 76 . Reduced global 5-HT 1A receptor binding has also been observed after ECT 77 . High costs, technical and methodological challenges, lack of dedicated PET centers with 11 C-radiochemistry, small sample sizes, small effect sizes, and unclear cutoff values have heretofore prevented the broader clinical application of these tools in MDD compared to disorders such as Alzheimer’s and Parkinson’s disease. An earlier [ 18 F]FDG PET study of unmedicated MDD patients was consistent with the aforementioned fMRI results, demonstrating increased glucose turnover in the orbitofrontal and posterior cingulate cortices and amygdala and decreased turnover in the subgenual ACC and dorsolateral prefrontal cortex 78 . A later study corroborated these results and found that glucose turnover was differentially affected by cognitive behavioral therapy or venlafaxine 79 . Interestingly, several studies detected microglial activation by labeling translocator protein (TSPO) with PET, using TSPO radioligands like 18 F-FEPPA. Microglial activation is closely linked to brain tissue damage, traumatic brain injury, neuroinflammation, and increased metabolic demands. Increased TSPO binding in MDD patients has been observed in the ACC, insula, and prefrontal cortex 80 . In addition, TSPO binding has also been shown to positively correlate with length of illness and time without antidepressant treatment, and to negatively correlate with SSRI treatment 80 . Elevated TSPO levels in unmedicated, acutely ill MDD patients have now been reported in at least two independent datasets 81 , 82 . However, TSPO-positive MDD patients may reflect a specific subtype (i.e., associated with neuroinflammation) and may, thus, respond better to treatments that target neuroinflammation. For a graphical summary of these findings see Fig. 1 .

Imaging findings exhibiting unidirectional (left) relationships with outcome in MDD vs. bidirectional (right). fMRI, functional magnetic resonance imaging; PET, positron emission tomography; EEG electroencephalography; 5-HT1A, serotonin-1A receptor; SERT, serotonin transporter; MAO-A monoamine oxidase-A; BP ND , nondisplaceable binding potential; V T , volume of distribution

Blood-based markers of disease outcomes

Consistent with neuroinflammatory processes, elevated levels of C-reactive protein (CRP), tumor necrosis factor alpha (TNFα), and interleukin-6 (IL-6) have been reported in a subset of MDD patients. In particular, elevated levels of CRP, a well-established marker of increased proinflammatory state in blood, was shown to be associated with MDD and increased risk for psychological distress in cross-sectional samples of the general population 83 . A longitudinal study found that lower CRP levels were associated with quicker response to SSRIs, an association not observed for SSRI-bupropion combination therapy 84 . Interestingly, elevated CRP levels have been shown to be more pronounced in female versus male MDD patients 85 . Similar findings have been observed for IL-6 and TNFα. One meta-analysis found that all three were significantly elevated at baseline in MDD patients, but their treatment trajectories differed 86 ; IL-6 levels decreased with antidepressant treatment, but outcomes were indistinguishable. In the same meta-analysis, persistingly high TNFα levels identified TRD patients 86 . Notably, heterogeneity was high within the pooled studies. Another study noted that levels of acute phase protein complement C3 significantly differentiated between atypical and melancholic MDD subtypes 87 . MDD patients have also been shown to have altered levels of peripheral adipokines and bone inflammatory markers; these deficits were corrected with ketamine treatment 88 , 89 .

Given the importance of neuroplasticity in the pathophysiology and treatment of depression, interest has grown in studying brain-derived neurotrophic factor (BDNF), a neurotrophin involved in the structural adaptation of neuronal networks and a prerequisite for neuronal reactions to stressors. BDNF blood levels most likely stem from peripheral tissue. While these peripheral levels are linked to central levels, the question of whether BDNF is actively transported through the blood–brain barrier remains controversial 90 . Compelling evidence suggests that BDNF levels are decreased at baseline in MDD patients and elevated in response to pharmacological 90 , 91 treatments as well as ECT 92 . A meta-analysis found that increased BDNF levels in response to treatment successfully stratified responders and remitters compared to non-responders 93 .

Outcome and genetic and epigenetic links

Heritable risk for MDD is between 30 and 40%, with higher rates in women. A large, collaborative genome-wide association study (GWAS) detected 44 significant loci associated with MDD 94 . Specific analyses identified neuronal genes (but not microglia or astrocytes), gene-expression regulating genes (such as RBFOX1 ), genes involved in gene-splicing, as well as genes that are the targets of antidepressant treatment. The authors suggested that alternative splicing could lead to shifts in the proportion of isoforms and altered biological functions of these proteins 94 .

Hypothesis-driven approaches with candidate genes have provided initial insights into the influence of single-nucleotide polymorphisms (SNPs). It is beyond the scope of this manuscript to review the large number of candidate genes; here, we outline only several representative genes (see Table 1 for meta-analytic evidence of treatment outcomes). These include synaptic proteins involved in stress response, antidepressant binding structures, or neuroplasticity (e.g., CRH receptor 1 ( CRHR1 )), the sodium-dependent serotonin transporter ( SLC6A4 ), and BDNF 95 . The aforementioned multicenter GSRD study also found that combining clinical and genetic variables explained antidepressant response better than SNPs alone in a random forest algorithm 96 . In that study, regulatory proteins such as ZNF804A (associated with response) and CREB1 (associated with remission), as well as a cell adhesion molecule (CHL1, associated with lower risk of TRD), were linked to antidepressant treatment outcomes. Another interesting candidate gene is FK506 binding protein 5 ( FKBP5 ), which was found to moderate the influence of standard treatments in an algorithm lasting up to 14 weeks 97 ; FKBP5 is known to influence HPA axis reactivity 98 , treatment response 99 , and epigenetic mechanisms in response to environmental stressors 100 . Another relevant avenue of research is drug-drug interactions and gene isoforms in the cytochrome P450 pathway (CYP450), which could account for insufficient amounts of a given drug reaching the brain or, conversely, result in exceedingly high plasma values, making subjects more vulnerable to treatment side effects 101 , 102 . Several commercially available kits categorize patients according to their phenotypic status (e.g., CYP2D6, 2C19, CYP3A4). This led to the introduction of phenotype categories—“poor”, “intermediate”, “extensive (normal)”, and “ultrarapid” metabolizers—based on CYP450 isoenzyme status and their relationship to plasma levels at fixed doses 102 . A large naturalistic study of CYP2C19 isoforms found that treatment success with escitalopram was less frequent in “poor” (CYP2C19Null/Null) and “ultrarapid” metabolizers (CYP2C19*1/*17 or CYP2C19*17/*17) 103 .

Clinical subgroups, TRD, and treatment outcomes

While some studies have suggested that depressive subtypes in MDD—including anxious, mixed, melancholic, atypical, and psychotic depression—respond differently to antidepressant treatment, this literature is mixed. For instance, some studies found that melancholic patients initially present with high levels of severity and may respond less well to SSRI treatment than to venlafaxine or tricyclic antidepressants 104 , but other studies did not support this finding 105 . No association was found between subgroups and clinical outcomes in a parallel design, uncontrolled study investigating sertraline, citalopram, and venlafaxine 106 , which found that near equal percentages of patients who met criteria for a pure-form subtype (39%) also had more than one subtype (36%), making these psychopathological subtypes difficult to classify.

It should be noted that treatment success might have more discriminatory power for identifying subgroups than psychopathological subgroup stratification. Although a wide range of definitions exists specifying the number of failed trials necessary to diagnose TRD 107 , the core definition of TRD centers around a lack of improvement in response to consecutive, adequate antidepressant treatments. Resistance occurs at alarmingly high rates and is thought to affect 50–60% of all treated patients 107 . Unsurprisingly, this group of patients has dramatically worse outcomes than those who respond to antidepressants, and factors that are associated with TRD overlap with many of those presented above 28 . Cross-sectional data from the GSRD 108 identified a number of risk factors linked to TRD, including comorbidity (particularly anxiety and personality disorders), suicide risk, episode severity, number of hospitalizations, episode recurrence, early-onset, melancholic features, and non-response at first treatment 28 . Most importantly, TRD is life-threatening, and associated with a two- to threefold increased risk of suicide attempts compared to responding patients, and a 15-fold increased risk compared to the general population 109 . Taken together, the evidence indicates that TRD patients need special attention, as outcomes in these individuals are significantly worse.

Novel and existing strategies to improve treatment outcomes

Early identification, prevention, and early treatment.

Numerous programs for suicide prevention exist 110 , and recognizing acute depressive symptoms is just one of many important facets of such work. Screening tools for early identification of depressed patients can be helpful 111 , and such instruments can start with as few as two items—for instance, the Patient Health Questionnaire-2 112 or Ask Suicide-Screening Questions (asQ’em) 113 —and proceed to more detailed instruments if initial screens are positive. Positive screening should be followed by a diagnostic interview to determine whether patients meet criteria for MDD 111 . In the general population, two large independent studies that used only clinical variables were nevertheless able to accurately predict depression within 1–3 years 114 . In addition, long-term monitoring of vulnerable subjects with known SLEs may further improve the ability to identify at-risk individuals early in their course of illness. As noted above, duration of untreated disease is a negative predictor of treatment outcomes. Because the advantages of early intervention in MDD have been demonstrated 115 , efforts to achieve early treatment might also help slow disease progression in individuals with TRD; however, this hypothesis has not been sufficiently tested.

Modeling environmental impact on predisposition

As noted above, severe SLEs constitute an important risk factor. Elegantly designed studies have demonstrated that genetic predisposition, in concert with SLEs, might account for increased vulnerability to MDD 100 . In this manner, the presence of ‘weak alleles’ in candidate genes such as BDNF, SERT , and others would be increasingly detrimental in the presence of SLEs 116 , 117 . However, studies have been quite inconsistent and yielded small effect sizes, including a negative result in 252 patients enrolled in the GSRD study 118 . It should be noted that counter-regulatory mechanisms or resilience factors, such as social support, may exist that counter SLEs. Nevertheless, preliminary research suggests that the impact of SLEs on MDD may depend on measurable factors such as gender and the timing of exposure 119 . Both genes and the environment are complex systems with frequent opportunity for interaction and elaborate compensatory mechanisms. While the complexity of genetic susceptibility in MDD can be tackled through enormous collaborative projects 94 , the interactions between genetic susceptibility and environmental factors have yet to be determined. Properly powered gene×environment interaction projects may exceed current research capabilities, and large longitudinal studies will certainly be needed 120 .

Developing markers for subgroup identification and disease course

Pioneering research on biological differences—for instance, between patients with atypical versus melancholic depression—suggests differential HPA axis or autonomous nervous system reactivity 121 , 122 , though the subtype results have been only moderately consistent across time and are prone to low group specificity 123 , 124 , 125 . However, at least one study demonstrated the more reliable stability of extreme types over a 2-year period 87 . Interestingly, one study found that individuals with atypical depression had significantly higher body-mass index, waist circumference, levels of inflammatory markers, and triglyceride levels, and lower levels of high-density lipid cholesterol than those with melancholic depression or controls 126 . Using fMRI and biological variables, another study found that MDD subjects could be divided into low/high appetite groups with distinctive correlations between neuronal activity and endocrine, metabolic, and immune states 127 . Other research groups have tried to overcome conventional psychopathological subgroups and model biotypes using resting-state fMRI 69 . Molecular and functional neuroimaging, as well as epigenetic studies, are promising approaches for separating subgroups and may be better suited to identifying screening markers (see Fig. 2 ) that are exclusively valid in certain subgroups with higher predictive power.

These approaches highlight the feasibility of linking and stratifying psychopathological categories with biological variables, a goal further supported by the Research Domain Criteria (RDoc), which seek to link dimensions of observable behavior with neurobiological systems 128 . In the search for biomarkers, subgroup- or domain-specific classifications using unidimensional variables might improve subgroup stratification 129 . Moreover, applying markers to other categories could boost the utility of existing markers that have failed in any given category (see Fig. 2 for established markers). As a field, the focus is largely on staging and prediction markers, but ‘predisposition’ or ‘recurrence’ markers may equally be worth investigating. Presently, however, the relative lack of biologically defined MDD subgroups and their stratification are key obstacles to finding and establishing treament outcome predictors appropriate for broader clinical applications.

Candidate disease markers can be applied in clinically meaningful ways. While only candidate markers are presently available, sorting these according to their potential applications may facilitate the development of clinically applicable disease markers. The outline follows the classification of markers as suggested by others 200 (modified and reprinted with permission from Springer)

The most important outcome of successful subgroup stratification and staging markers would be that patients and their relatives would receive valuable information at treatment onset about how their disease is likely to improve or worsen. Toward this end, the development of staging methods provides promising solutions. Currently, at least five different methods exist 130 that, to date, have not been evaluated thoroughly enough for clinical implementation. Continuous variables—as obtained by the Maudsley Method and Massachusetts General Hospital Staging Model—appear to provide greater staging advantages than categorical variables. It should be noted here that data indicate that research in severely ill, suicidal, and TRD subjects is safe to conduct in controlled inpatient settings 131 . Presently, patients in various stages of disease and/or treatment history are lumped together and compared in statistical analyses. We propose that staging should be more thoroughly integrated into clinical trial design.

Algorithm- and guideline-based treatments

Despite the availability and distribution of a variety of expert-based guidelines, only a fraction of patients are actually treated according to guidelines 132 (see Table 2 for current guidelines (≤10 years)). New guidelines – particularly for TRD – and more rigorous implementation of guideline-based care are needed. Improvements in currently available treatments have been conducted using treatment algorithms and following sequential treatment strategies, with standardized instructions for therapeutic decision-making. In the past two decades, large, collaborative studies using treatment-based algorithms have introduced standardized, sequential treatments; these include the Texas Medication Algorithm Project 133 , the STAR*D trial 21 , and the German algorithm project 134 . Indeed, evidence suggests that algorithm-based treatments improve treatment outcomes 135 and are cost effective 136 . Here, we considered current clinical treatment guidelines to create a sequential treatment optimization scheme of recommended treatments. While there is no fixed time-frame, first- and second-line treatments are recommended sequentially during the first episode and within 3 months (see Fig. 3 , which also illustrates the need for more third- and fourth-stage treatment options). Figure 4 , illustrates potential reasons for “pseudoresistance” 42 that should be ruled out during this time-frame.

A sequential treatment optimization scheme was generated based on antidepressant treatment guidelines (see Table 2 ). Treatment optimization is possible for patients being treated for the first time but also for patients with insufficient response to first- or second-stage therapies. a Treatment response curves for four common types of patients highlight the importance of sequentially introducing the next step upon non-response to previous steps. b Currently available treatments are listed in neuroscience-based nomenclature 201 with treatment lines corresponding to improvement curves in a . Although current classifications vary, patients classified as having treatment-resistant depression (TRD) are eligible for second- or third-stage therapies. 5-HT1A and similar: serotonin receptor subtypes; DBS: deep brain stimulation; DAT: dopamine transporter; D2: dopamine receptor D2; ECT: electroconvulsive therapy; MAO: monoamine oxidase; NET: noradrenaline transporter; SERT: serotonin transporter; TBS: theta-burst stimulation; rTMS: repetitive transcranial magnetic stimulation; DA: dopamine; NE: norepinephrine.

Points—in random order—follow earlier suggestions by Dold and Kasper (2017) 202

Reducing placebo response in clinical trials while harnessing placebo effects in clinical treatment

The issue of placebo response in antidepressant trials has become increasingly important 137 , 138 . Indeed, the contribution of placebo effects to early response needs to be systematically studied in order to disentangle biological therapy-induced effects from psychologically induced effects. Strikingly, in the brain, anatomically similar regions that mediate placebo response are affected by MDD (for a comprehensive review, see ref. 139 ). Several mechanisms contribute to placebo response, including patients’ expectations of benefits, behavioral conditions, and the quality of patient-physician interactions 139 . Strategies for reducing placebo response could lead to better discrimination between effective treatments in clinical trials; such strategies include extending trial duration, excluding placebo responders by including a placebo run-in, or using randomized run-in and withdrawal periods 138 , 139 . Others have suggested using more thorough criteria to select study participants 140 . On the other hand, when antidepressant agents are used clinically, placebo effects must be taken advantage of by harnessing patients’ expectations and learning mechanisms to improve treatment outcomes 141 .

Novel antidepressant treatments

The recent discovery that glutamatergic-based drugs are uniquely capable of rapidly and robustly treating mood disorders has ushered in a new era in the quest to develop novel and effective antidepressants 142 , 143 , 144 . In this regard, the prototypic glutamatergic modulator ketamine has catalyzed research into new mechanistic approaches and offered hope for the development of novel, fast-acting antidepressants. While ketamine’s underlying mechanism of action remains the subject of active investigation, several theories have been propsed 144 . These include N-methyl- d -aspartate receptor (NMDAR)-dependent mechanisms, such as the inhibition of NMDARs on gamma aminobutyric acid (GABA)-ergic interneurons, the inhibition of spontaneous NMDAR-mediated transmission, the inhibition of extrasynaptic NMDARs, the inhibition of lateral habenula neurons, and GABA B receptor expression/function 144 . Substantial evidence also supports additional NMDAR-independent mechanisms, including the stabilization of glutamate release/excitatory transmission, active metabolites such as hydroxynorketamine, regulation of the dopaminergic system, G-alpha subunit translocation, and activation of cyclic adenosine monophosphate, as well as potential sigma-1 and mu-opioid receptor activation 145 . Among those theories, a leading hypothesis remains that NMDAR antagonism increases BDNF synthesis, a process mediated by decreased phosphorylation of eukaryotic elongation factor-2 and the subsequent activation of the mammalian target of rapamycin pathway by BDNF activation of the TrkB receptor 146 , 147 . These putative mechanisms of action are not mutually exclusive and may complement each other to induce potentiation of excitatory synapses in affective-regulating brain circuits, resulting in improved depressive symptoms.

The initial serendipitous discovery that a single, subanesthetic-dose ketamine infusion has rapid-acting antidepressant effects in MDD 148 , a finding subsequently confirmed by numerous randomized trials, has been hailed as one of the most important discoveries in psychiatry in the last decades 149 . The initial proof-of-concept studies demonstrated that a single dose of ketamine (0.5 mg/kg, IV) administered over 40 min led to rapid, robust, and relatively sustained antidepressant effects in TRD—both MDD 150 , 151 , 152 , 153 and bipolar depression 154 , 155 . In research settings, studies of TRD patients found response rates of >70% within 24 h post-infusion 153 , with about 50–70% of participants exhibiting a variable duration of response 156 , 157 . Ketamine has also been shown to be superior to any blinding counterpart 158 . Off-label ketamine use has also been associated with significant and rapid (one to four hours) antisuicidal effects 150 , 159 , 160 , a finding supported by a large, recent metanalysis showing that ketamine exerted rapid (within hours) and sustained (up to 7 days) improvements in suicidal thoughts compared to placebo 161 .

Esketamine hydrochloride

The ketamine enantiomer esketamine received approval by the FDA for TRD and is currently undergoing further Phase III clinical trials. A Phase II, 10-week, clinical trial of flexibly dosed intranasal esketamine (28 mg/56 mg or 84 mg) found that, in TRD patients, this agent demonstrated rapid and clinically relevant improvements in depressive symptoms compared to placebo 162 . Strikingly, 65% of TRD patients met response criteria through Day 57. In another Phase II proof-of-concept, multi-site, 4-week, double-blind study, standard treatment plus intranasal esketamine (84 mg) was compared to standard treatment plus placebo in individuals with MDD at imminent risk of suicide 163 . The authors found a rapid antisuicidal effect, as assessed via the Montgomery-Åsberg Depression Rating Scale Suicide Item score at 4 h.

Other rapid acting and novel antidepressants

Based on the success of ketamine, other rapid-acting or novel antidepressant substances within the glutamatergic/GABA neurotransmitter systems are being developed, several of which are in Phase III clinical trials. A prototype novel substance is AV-101 (L-4-cholorkynurenine). This is a potent selective antagonist at the glycine-binding site of the NMDAR NR1 subunit and has demonstrated antidepressant-like effects in animal models, while human Phase II studies are currently ongoing 164 . Brexanolone is a formulation of the endogenous neurosteroid allopregnanolone, which modulates neuronal activation of GABA A receptors and has met positive endpoints in Phase III, leading to FDA approval for postpartum depression. A comparable substance is under development for MDD 165 . In addition, serotonergic agonists have been studied as our understanding of their mechanism of action (e.g., their effects on glutamate release or plasticity) has increased 166 . Encouraging results have been seen for the serotonin 2A receptor agonist psilocybin 167 , but these findings need to be replicated in larger systematic clinical trials. Initial positive trials of add-on agents—such as buprenorphine 168 , 169 , rapastinel 170 , or scopolamine 145 —have also been conducted. However, it is beyond the scope of this manuscript to review all of these findings, and we refer the interested reader to recent comprehensive reviews of this subject 144 , 145 , 165 , 171 .

Transcranial stimulation paradigms

In contrast to pharmaceutical treatments that exert their efficacy at the molecular level, electrical stimulation techniques target entire neuronal circuits. TMS of the (left) dorsolateral prefrontal cortex has been FDA-approved since 2008 to treat depression in patients who failed to respond to one standard antidepressant treatment. Apart from transient local skin and muscle irritation at the stimulation site and headaches, it is a very safe technique with few side effects. Studies have repeatedly demonstrated the superiority of rTMS over sham procedures, though effect sizes have been moderate 172 , 173 , 174 . Initial studies suggest that rTMS is also effective in TRD but the data are too few to draw definitive conclusions 175 , 176 . Improvements in rTMS techniques known as theta-burst stimulation (TBS) provide significantly shortened treatment times (3 min for TBS versus 37 min for rTMS) and hence allow more patients to be treated per day. A large non-inferiority trial of 414 moderately resistant MDD patients found that TBS was at least as effective as rTMS in reducing depressive symptoms 177 .

Electroconvulsive therapy (ECT)

Regarded as the ‘gold standard’, ECT has been successfully used for many years to treat severe TRD and exhibits both relatively rapid and sustained onset of efficacy; approximately 50% of all patients reach response criteria at the third treatment, typically within 1 week. It is also one of the most effective antidepressant therapies 178 , yielding response rates of ~80%, remission rates of ~75% 179 , and antisuicidal effects 180 . Remission is achieved by about 30% of patients within six ECT sessions 179 . ECT also reduces the risk of readmission 181 and is likewise safe to use in depressed elderly subjects 182 . The side effects of ECT include intermediate disorientation, impaired learning, and retrograde amnesia, all of which usually resolve 183 . The optimal anatomic location of the stimulus electrodes is a topic of current debate 184 , 185 . Recent evidence suggests that all three methods for electrode placement (bifrontal, bitemporal, and unilateral) show clinically significant effects 186 . While no difference in cognitive side effects was observed, bitemporal placement should be considered the first-line choice for urgent clinical situations. Despite its clinical efficacy, ECT remains underutilized. Its use is declining 187 because it needs to be administered in hospital settings under anesthesia, and partly because of misleading portrayals of the procedure itself. Adjusting the dose of electrical stimuli (e.g., through refined electrode placement or individually adjusted pulse amplitudes) may improve ECT’s side effect profile.

Magnetic seizure therapy (MST)

MST uses high doses of rTMS to induce seizures 188 . The electromagnetically induced electrical field generated by MST is unifocal and variable, as there are individual differences in the degree to which the skull provides electrical resistance 189 . As an advantage over ECT, MST is associated with a more superficial stimulation, which exerts less impact on the medial-temporal lobe where cognitive side effects are thought to be elicited. To date, few research sites across the world have used MST, with a concomitant dearth of open-label trials. Nevertheless, the preliminary treatment data suggest that results obtained with MST are similar to those obtained with ECT but with a more favorable side effect profile 190 , 191 .

Vagus nerve stimulation (VNS)

VNS is a surgically implanted pacemaker-like device attached to a stimulating wire threaded along the left vagus nerve. Since 2005, the FDA has approved VNS use for the adjunctive long-term treatment of long-lasting recurrent depression in patients 18 years and older who are experiencing a major depressive episode and have failed to respond to four or more previous adequate standard antidepressant treatment trials. In such cases, it has been shown to have superior long-term effects over conventional psychopharmacological treatment 192 . A recent, large, observational, adjunctive, open-label, naturalistic study followed TRD patients over 5 years 193 . In this group, adjunctive VNS led to significantly better clinical outcomes and higher remission rates than treatment as usual (67.6% vs. 40.9%, respectively).

Deep-brain stimulation (DBS)

DBS involves the neurosurgical implantation of electrodes and has become clinically routine in the treatment of Parkinson’s disease and Dystonia. The technique is safe, removable, and does not cause lasting neuronal lesions. In TRD, anatomical targets include the subgenual cingulate, nucleus accumbens, habenula, and medial forebrain bundle. Clinical trials typically only enroll severely ill TRD patients whose current episode has lasted >12 months, whose age of onset is <45 years, and who have failed to respond to at least four adequate prior treatment trials of standard antidepressants, ECT, and/or psychotherapy. Initial open-label or single-blind trials found that DBS had both rapid and sustained antidepressant effects 194 , 195 , 196 . In contrast, one large and one smaller sham-controlled clinical study both failed to achieve their primary endpoints of symptom reduction 197 , 198 . To date, the number of MDD patients treated with DBS has been very small compared to other treatment options, including ECT and TMS. Nevertheless, brain-electrode interfaces are evolving quickly and it is possible that next generation brain-responsive stimulation devices will be able to adjust stimulation on-demand only when abnormal biological marker impulses (e.g., pulse amplitude) are detected 199 .

Conclusions

Although enormous progress has been made in measuring, predicting, and improving outcomes, depression remains a relentless disease that places a heavy burden on both individuals and society. The research reviewed above indicates that early recognition and early adequate treatment at illness onset are preferable to watch-and-wait strategies. The studies reviewed above also underscore the manner in which SLEs, as well as physical and psychiatric comorbidities, contribute to impaired outcomes. Together, these factors contribute toward treatment resistance, which has gained a substantial amount of importance as a patient-stratifying variable.

This paper also reviewed biological markers, where research has grown exponentially to encompass enormous projects with potentially tens of thousands of subjects enrolled in real world studies. In parallel, studies exploring the underlying genetics of depression have evolved from early candidate gene studies of neurotransmitters, stress, or gene-regulatory systems to large GWAS that help reveal potential new pathways and treatment targets. Moreover, the burgeoning field of proteomics has found promising target molecules. Nevertheless, despite the wealth of recent work in this area, no single biomarker has yet been used in clinical applications. A substantial need exists for replication and, because many biomarker studies are currently open-label, for controlled studies. In combination with neuroimaging techniques such as fMRI, genes or blood-based markers have a high potential of future implementation in stratification of MDD or serve as prognostic marker on treatment outcome.

Above, we also outlined efforts to optimize outcomes. We argue that disease-inherent heterogeneity, in concert with inaccurate group stratification tools, might have contributed to the lack of clinically applicable stratification and response prediction markers. Successful subgroup identification, and the ability to use this information in clinical settings, is crucial to improving future treatment paradigms. While recent research has increasingly focused on TRD, we wish to reiterate that no standard definition of TRD presently exists. Thus, based on currently available guidelines, we have outlined a sequential treatment optimization scheme that includes options for TRD; such work highlights the substantial need to develop and improve “third-line-and-beyond” therapeutics. In this context, this manuscript also reviews novel treatments and brain stimulation techniques that have demonstrated rapid antidepressant effects in TRD, including ketamine, esketamine, ECT, MST, TMS/TBS, VNS, DBS, and others. When treating TRD patients, physicians should consider illness severity, the chronicity of past and recent depressive episodes, the side effect profile of available treatment options, as well as previous refractoriness to particular treatment approaches. If acuity supersedes chronicity, one could consider fast-acting interventions such as ketamine or ECT/MST.

This review, though comprehensive, was not able to consider several lines of evidence on outcome prediction and treatment improvement. In particular, we focused on clinical outcomes in humans and were, thus, unable to fully explore the highly valuable advances made in translational science. Similarly, it was beyond the scope of this manuscript to review the richness of results from animal research and their relevance to MDD. Moreover, given the amount of literature, we were not able to incorporate many proteomic, genetic, or psychopharmacological findings.

Taken together, this review outlines important clinical, psychosocial, and biological factors associated with response and remission to antidepressant treatment (see Table 3 ). Recent studies have led to important insights into neurobiological disease markers that could result in improved disease stratification and response prediction in the near future. Key discoveries into novel rapid-acting substances, in concert with improvements in brain stimulation techniques, may also result in significantly improved treatment outcomes in formerly hard-to-treat patients.

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Acknowledgements

We thank the 7SE research unit and staff for their support. Ioline Henter (NIMH) provided invaluable editorial assistance. We also thank E. Acevedo-Diaz, Z.D. Deng, and J.W. Evans for scientific input.

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Christoph Kraus, Rupert Lanzenberger & Siegfried Kasper

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Funding for this work was supported in part by the Intramural Research Program at the National Institute of Mental Health, National Institutes of Health (IRP-NIMH-NIH; ZIA MH002927). All support given to authors was not related to the design of the manuscript or the ideas stated in this review. Dr. Kasper received grants/research support, consulting fees, and/or honoraria within the last 3 years from Angelini, AOP Orphan Pharmaceuticals AG, AstraZeneca, Eli Lilly, Janssen, KRKA-Pharma, Lundbeck, Neuraxpharm, Pfizer, Pierre Fabre, Schwabe, and Servier. Dr. Lanzenberger received travel grants and/or conference speaker honoraria from AstraZeneca, Lundbeck A/S, Dr. Willmar Schwabe GmbH, Orphan Pharmaceuticals AG, Janssen-Cilag Pharma GmbH, and Roche Austria GmbH. Dr. Kraus has received travel grants from Roche Austria GmbH and AOP Orphan. Dr. Zarate is a full-time U.S government employee. He is listed as a co-inventor on a patent for the use of ketamine in major depression and suicidal ideation; as a co-inventor on a patent for the use of (2 R ,6 R )-hydroxynorketamine, ( S )-dehydronorketamine, and other stereoisomeric dehydro and hydroxylated metabolites of ( R,S )-ketamine metabolites in the treatment of depression and neuropathic pain; and as a co-inventor on a patent application for the use of (2 R ,6 R )-hydroxynorketamine and (2 S ,6 S )-hydroxynorketamine in the treatment of depression, anxiety, anhedonia, suicidal ideation, and post-traumatic stress disorders. He has assigned his patent rights to the U.S. government but will share a percentage of any royalties that may be received by the government.

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Kraus, C., Kadriu, B., Lanzenberger, R. et al. Prognosis and improved outcomes in major depression: a review. Transl Psychiatry 9 , 127 (2019). https://doi.org/10.1038/s41398-019-0460-3

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151 Case Studies: Real Stories Of People Overcoming Struggles of Mental Health

At Tracking Happiness, we’re dedicated to helping others around the world overcome struggles of mental health.

In 2022, we published a survey of 5,521 respondents and found:

• 88% of our respondents experienced mental health issues in the past year.
• 25% of people don’t feel comfortable sharing their struggles with anyone, not even their closest friends.

In order to break the stigma that surrounds mental health struggles, we’re looking to share your stories.

Overcoming struggles

They say that everyone you meet is engaged in a great struggle. No matter how well someone manages to hide it, there’s always something to overcome, a struggle to deal with, an obstacle to climb.

And when someone is engaged in a struggle, that person is looking for others to join him. Because we, as human beings, don’t thrive when we feel alone in facing a struggle.

Let’s throw rocks together

Overcoming your struggles is like defeating an angry giant. You try to throw rocks at it, but how much damage is one little rock gonna do?

Tracking Happiness can become your partner in facing this giant. We are on a mission to share all your stories of overcoming mental health struggles. By doing so, we want to help inspire you to overcome the things that you’re struggling with, while also breaking the stigma of mental health.

Which explains the phrase: “Let’s throw rocks together”.

Let’s throw rocks together, and become better at overcoming our struggles collectively. If you’re interested in becoming a part of this and sharing your story, click this link!

Case studies

May 14, 2024

I’m Finding Luck After Trauma and Abuse Through Mindfulness

“I never mentioned the accident to anyone until I met my future husband at 22. He was sympathetic and supportive, and helped me understand the enormity of what I had been through.I still have not talked to my siblings about it.”

Struggled with: Abuse Depression Eating disorder Suicidal

Helped by: Meditation Mindfulness Reinventing yourself

May 7, 2024

My Journey From Hitting Rock Bottom to Overcoming Abuse, Addiction, and Eating Disorder

“Then something happened. On about day 3 or 4, the group spoke and I realized that their way of thinking around food, their rituals, and their tendencies, were all the same as the things I would do. It was wild because I thought I had made these things up myself and here I was with a room full of people who did the same things.”

Struggled with: Abuse Bullying Depression Divorce Eating disorder PTSD

Helped by: Self-Care Social support Therapy Treatment

May 2, 2024

How Yoga Became My Lifeline in Navigating Depression and Building Self-Love

“My relationship with myself was pretty broken and I had no self-belief, I had low self-esteem and I resented my family. It was through yoga that I found the truest feeling of comfort, self-compassion, and courage to move forward, grow as a person, and fall back in love with myself and life again.”

Struggled with: Depression Insomnia Stress Suicidal

Helped by: Exercise Meditation Mindfulness Self-Care

April 30, 2024

Finding Clarity After an ADHD Diagnosis and Bettering Myself With CBT and Medication

“Now as I was getting older, I felt I couldn’t trust my own thoughts in the same way as before, and self-doubt would creep in. I would constantly ask myself whether my emotions and thoughts were accurate or not when reacting to social situations. As you can imagine this was a huge challenge and draining emotionally.”

Struggled with: ADHD Autism

Helped by: Medication Social support Therapy

April 25, 2024

How I’m Seeking Moments of Happiness Despite Struggling With Depression

“The diagnosis I longed for finally arrived, but it didn’t bring the expected empowerment. While it sheds light on my struggles, it also serves as a reminder that this is a part of me that won’t simply vanish. Though mental health can be managed, I know it will always leave its mark. The most challenging part is not always pinpointing why I feel the way I do.”

Struggled with: Depression Negative body image

Helped by: Medication Therapy

April 24, 2024

How Boxing and Therapy Help Me Recover My Identity After Extreme Weight Loss

“When my body changed so drastically and rapidly, it broke my sense of self-identity. About a year into my weight loss, I began to experience early dissociation, depersonalization, and dissociative amnesia. I broke into two people. Me of now and her of before.”

Struggled with: Depression Dissociative amnesia

Helped by: Exercise Self-improvement Therapy

April 18, 2024

How Therapy, Medication and Baking Help Me Navigate Depression and OCD

“I was hospitalized for my eating disorder and my depression several times throughout my college career struggling with the will to live… I was desperate to be “normal” but my brain really got in the way of that.”

Struggled with: Anxiety Depression Eating disorder OCD Suicidal

Helped by: Medication Self-improvement Therapy Treatment

April 16, 2024

How I Found My Self-Worth After Battling Chronic Pain, Anxiety and Panic Attacks

“I remember being floored with a horrible throat infection, and I was just crying. I was done suffering, I couldn’t do it anymore, I was really broken down. That was about 2 years ago now, and it shifted something in my brain. Instead of going down the drain – and keeping that negativity going – it suddenly hit me that I’m the only one responsible for how I feel.”

Struggled with: Anxiety Chronic pain Panic attacks Stress

Helped by: Medication Self-Care Self-improvement Therapy

April 11, 2024

How a Mindset Change Helped Me Break Free From Childhood Trauma and Toxicity

“My mother said she wanted to end it in bloodshed and she waited for him to come home from his late-night meeting. She thought better of it when he was late arriving home. She was overwhelmed with thoughts of her in prison and me in foster care. To say that she made the right decision in achieving the goal of a good life is an answer I struggled to answer for many years.”

Struggled with: Abuse Anxiety Childhood CPTSD Depression

Helped by: Mindfulness Reinventing yourself Self-improvement Therapy

April 9, 2024

Healing From Postpartum Depression With Therapy, Friends & Exercise

“I wasn’t sure how to feel better for a while. People talk about ‘getting help’ but that’s a blanket term and unfortunately it’s not a band-aid you can just put on and suddenly be yourself again. It takes time to find the right therapist, medication if that’s what you decide to do, to find a new rhythm with family, and in my case, I really needed friends locally.”

Struggled with: Postpartum depression

Helped by: Exercise Social support Therapy

Scaremongering About Living Alone: A Case Study

People who live alone are very unlikely to be depressed..

Posted February 27, 2024 | Reviewed by Michelle Quirk

• What Is Depression?
• Find a therapist to overcome depression
• A misleading NPR headline implied that people living alone are especially likely to be depressed.
• In a CDC study, people living alone had significantly higher rates of depression only if living in poverty.
• Negative portrayals in the media can make people who love living alone doubt themselves.

An article on the NPR website, about a segment on Morning Edition, came with this headline: “Americans who live alone report depression at higher rates, but social support helps.” What were those “higher rates”? Just guessing, maybe about 70 percent? Surely more than half?

In the Facebook group, The Community of Single People, Monica Pignotti flagged that article. Wisely, she did not stop at the headline. She looked for the actual percentage of people living alone who feel depressed. The answer: 6 percent! A more accurate headline would be something like, “Americans who live alone report very low rates of depression.”

The actual headline referred to “higher rates,” a comparative claim. People living alone, we are led to believe, are more likely to be depressed than people living with others. But the rates of depression for people not living alone were 4 percent. With the large number of people in the study (nearly 30,000), that was a statistically significant difference from 6 percent, but as Monica suggested, it may not be a meaningful difference. I doubt that anyone reading just the headline would guess that the difference was just two percentage points.

People Living Alone Are More Depressed Only if They Get Almost No Social Support

The headline does include the qualifier that “social support helps.” I went to the original research report from the Centers for Disease Control and Prevention (CDC) to see the numbers. Participants—a nationally representative sample of adults in the United States aged 18 years and older—were asked, “How often do you get the social and emotional support you need?” They could answer rarely or never, sometimes, usually, or always. Only if the participants rarely or never got the emotional support they needed were the people living alone more likely to be depressed than the people living with others (20 percent vs. 12 percent).

People Living Alone Are More Depressed Only if They Are Impoverished

The CDC study also reported rates of depression by four levels of income: below the federal poverty level, up to twice the poverty level, from twice to four times the poverty level, and the highest level of income, more than four times the poverty level. The people living alone reported significantly higher rates of depression than those living with others only if they were living in poverty, 14 percent versus 9 percent.

Income also mattered in a previous study of loneliness among more than 16,000 Germans ranging in age from 18 to 103 years. When the researchers simply compared all the people living alone with all the people living with others, the people living alone were lonelier. But when they matched people on income so that they were comparing people living alone with people living with others when both groups had the same income, then they found that the people living alone were actually less lonely. (I discussed those findings in greater detail here at Living Single.)

Older People Are Very Unlikely to Be Depressed When Living Alone

The stereotype of old people living alone is that they are sad and lonely. But, according to the CDC study, that caricature may be exactly wrong. Among those 65 and older who were living alone, only 5 percent reported feeling depressed. People between the ages of 45 and 64 had the highest rate of depression when living alone, though at 9 percent, even that wasn’t very high. (For the other two age groups, 18-29 and 30-44, the rate was 6 percent, close to the rate for the oldest group.)

Why This Matters

Media messages matter. We should be able to trust in what we read, even if we read no more than a headline, especially from prestige media such as NPR. Typically, we can. But when it comes to matters such as living alone, we are at greater risk of scaremongering.

Unjustifiably negative portrayals of solo living, or of being single, are evident in other domains, too, such as popular culture and even in reports of scientific research . The cumulative effect is that people who love living alone, or love being single (such as the single at heart ), come to doubt themselves. Or worse—they worry that something is wrong with them. Think about that: They have what we all want, a life that they love. But instead of feeling encouraged to embrace their most fulfilling and authentic way of living, they wonder whether they should instead live the way they are expected to live. That’s unfair to them, especially when the actual findings are not at all what they have been led to believe. It undermines their potential to fully flourish.

Rhitu Chatterjee. Americans who live alone report depression at higher rates, but social support helps . NPR. February 15, 2024.

Bella DePaulo, Ph.D. , an expert on single people, is the author of Single at Heart and other books. She is an Academic Affiliate in Psychological & Brain Sciences, UCSB.

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A New Study Is Finally Attempting to Pin Down The Root Causes of Depression

Most experts agree that depression is not one thing.

The core experiences of depression — changes in energy, activity, thinking, and mood — have been described for more than 10,000 years. The word “depression” has been used for about 350 years.

Given this long history, it may surprise you that experts don’t agree about what depression is, how to define it, or what causes it.

However, many experts do agree that depression is not one thing . It’s a large family of illnesses with different causes and mechanisms. This makes choosing the best treatment for each person challenging.

Reactive vs endogenous depression

One strategy is to search for sub-types of depression and see whether they might do better with different kinds of treatments. One example is contrasting “reactive” depression with “endogenous” depression.

Reactive depression (also thought of as social or psychological depression) is presented as being triggered by exposure to stressful life events. These might be being assaulted or losing a loved one — an understandable reaction to an outside trigger.

Endogenous depression (also thought of as biological or genetic depression) is proposed to be caused by something inside , such as genes or brain chemistry.

Many people working clinically in mental health accept this sub-typing. You might have read about this online .

But we think this approach is way too simple.

While stressful life events and genes may, individually, contribute to causing depression, they also interact to increase the risk of someone developing depression. And evidence shows that there is a genetic component to being exposed to stressors. Some genes affect things such as personality. Some affect how we interact with our environments.

What we did and what we found

Our team set out to look at the role of genes and stressors to see if classifying depression as reactive or endogenous was valid.

In the Australian Genetics of Depression Study , people with depression answered surveys about exposure to stressful life events. We analyzed DNA from their saliva samples to calculate their genetic risk for mental disorders.

Our question was simple. Does genetic risk for depression, bipolar disorder, schizophrenia, ADHD, anxiety, and neuroticism (a personality trait) influence people’s reported exposure to stressful life events?

You may be wondering why we bothered calculating the genetic risk for mental disorders in people who already have depression. Every person has genetic variants linked to mental disorders. Some people have more, some less. Even people who already have depression might have a low genetic risk for it. These people may have developed their particular depression from some other constellation of causes.

We looked at the genetic risk of conditions other than depression for a couple of reasons. First, genetic variants linked to depression overlap with those linked to other mental disorders. Second, two people with depression may have completely different genetic variants. So, we wanted to cast a wide net to look at a wider spectrum of genetic variants linked to mental disorders.

If reactive and endogenous depression sub-types are valid, we’d expect people with a lower genetic component to their depression (the reactive group) to report more stressful life events. And we’d expect those with a higher genetic component (the endogenous group) would report fewer stressful life events.

But after studying more than 14,000 people with depression, we found the opposite.

We found people at higher genetic risk for depression, anxiety, ADHD, or schizophrenia say they’ve been exposed to more stressors .

Assault with a weapon, sexual assault, accidents, legal and financial troubles, and childhood abuse and neglect were all more common in people with a higher genetic risk of depression, anxiety, ADHD, or schizophrenia.

These associations were not strongly influenced by people’s age, sex, or relationships with family. We didn’t look at other factors that may influence these associations, such as socioeconomic status. We also relied on people’s memory of past events, which may not be accurate.

How do genes play a role?

Genetic risk for mental disorders changes people’s sensitivity to the environment.

Imagine two people, one with a high genetic risk for depression and one with a low risk. They both lose their jobs. The genetically vulnerable person experiences the job loss as a threat to their self-worth and social status. There is a sense of shame and despair. They can’t bring themselves to look for another job for fear of losing it, too. For the other, the job loss feels less about them and more about the company. These two people internalize the event differently and remember it differently.

Genetic risk for mental disorders also might make it more likely people find themselves in environments where bad things happen. For example, a higher genetic risk for depression might affect self-worth, making people more likely to get into dysfunctional relationships, which then go badly.

What does our study mean for depression?

First, it confirms genes and environments are not independent. Genes influence the environments we end up in and what then happens. Genes also influence how we react to those events.

Second, our study doesn’t support a distinction between reactive and endogenous depression. Genes and environments have a complex interplay. Most cases of depression are a mix of genetics, biology, and stressors.

Third, people with depression who appear to have a stronger genetic component to their depression report their lives are punctuated by more serious stressors.

So, clinically, people with higher genetic vulnerability might benefit from learning specific techniques to manage their stress. This might help some people reduce their chance of developing depression in the first place. It might also help some people with depression reduce their ongoing exposure to stressors.

This article was originally published on The Conversation by Jacob Crouse and Ian Hickie at the University of Sydney . Read the original article here .

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Biological, Psychological, and Social Determinants of Depression: A Review of Recent Literature

Olivia remes.

1 Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK

João Francisco Mendes

2 NOVA Medical School, Universidade NOVA de Lisboa, 1099-085 Lisbon, Portugal; ku.ca.mac@94cfj

Peter Templeton

3 IfM Engage Limited, Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK; ku.ca.mac@32twp

4 The William Templeton Foundation for Young People’s Mental Health (YPMH), Cambridge CB2 0AH, UK

Associated Data

Depression is one of the leading causes of disability, and, if left unmanaged, it can increase the risk for suicide. The evidence base on the determinants of depression is fragmented, which makes the interpretation of the results across studies difficult. The objective of this study is to conduct a thorough synthesis of the literature assessing the biological, psychological, and social determinants of depression in order to piece together the puzzle of the key factors that are related to this condition. Titles and abstracts published between 2017 and 2020 were identified in PubMed, as well as Medline, Scopus, and PsycInfo. Key words relating to biological, social, and psychological determinants as well as depression were applied to the databases, and the screening and data charting of the documents took place. We included 470 documents in this literature review. The findings showed that there are a plethora of risk and protective factors (relating to biological, psychological, and social determinants) that are related to depression; these determinants are interlinked and influence depression outcomes through a web of causation. In this paper, we describe and present the vast, fragmented, and complex literature related to this topic. This review may be used to guide practice, public health efforts, policy, and research related to mental health and, specifically, depression.

1. Introduction

Depression is one of the most common mental health issues, with an estimated prevalence of 5% among adults [ 1 , 2 ]. Symptoms may include anhedonia, feelings of worthlessness, concentration and sleep difficulties, and suicidal ideation. According to the World Health Organization, depression is a leading cause of disability; research shows that it is a burdensome condition with a negative impact on educational trajectories, work performance, and other areas of life [ 1 , 3 ]. Depression can start early in the lifecourse and, if it remains unmanaged, may increase the risk for substance abuse, chronic conditions, such as cardiovascular disease, and premature mortality [ 4 , 5 , 6 , 7 , 8 ].

Treatment for depression exists, such as pharmacotherapy, cognitive behavioural therapy, and other modalities. A meta-analysis of randomized, placebo-controlled trials of patients shows that 56–60% of people respond well to active treatment with antidepressants (selective serotonin reuptake inhibitors, tricyclic antidepressants) [ 9 ]. However, pharmacotherapy may be associated with problems, such as side-effects, relapse issues, a potential duration of weeks until the medication starts working, and possible limited efficacy in mild cases [ 10 , 11 , 12 , 13 , 14 ]. Psychotherapy is also available, but access barriers can make it difficult for a number of people to get the necessary help.

Studies on depression have increased significantly over the past few decades. However, the literature remains fragmented and the interpretation of heterogeneous findings across studies and between fields is difficult. The cross-pollination of ideas between disciplines, such as genetics, neurology, immunology, and psychology, is limited. Reviews on the determinants of depression have been conducted, but they either focus exclusively on a particular set of determinants (ex. genetic risk factors [ 15 ]) or population sub-group (ex. children and adolescents [ 16 ]) or focus on characteristics measured predominantly at the individual level (ex. focus on social support, history of depression [ 17 ]) without taking the wider context (ex. area-level variables) into account. An integrated approach paying attention to key determinants from the biological, psychological, and social spheres, as well as key themes, such as the lifecourse perspective, enables clinicians and public health authorities to develop tailored, person-centred approaches.

The primary aim of this literature review: to address the aforementioned challenges, we have synthesized recent research on the biological, psychological, and social determinants of depression and we have reviewed research from fields including genetics, immunology, neurology, psychology, public health, and epidemiology, among others.

The subsidiary aim: we have paid special attention to important themes, including the lifecourse perspective and interactions between determinants, to guide further efforts by public health and medical professionals.

This literature review can be used as an evidence base by those in public health and the clinical setting and can be used to inform targeted interventions.

2. Materials and Methods

We conducted a review of the literature on the biological, psychological, and social determinants of depression in the last 4 years. We decided to focus on these determinants after discussions with academics (from the Manchester Metropolitan University, University of Cardiff, University of Colorado, Boulder, University of Cork, University of Leuven, University of Texas), charity representatives, and people with lived experience at workshops held by the University of Cambridge in 2020. In several aspects, we attempted to conduct this review according to PRISMA guidelines [ 18 ].

The inclusion and exclusion criteria are the following:

• - We included documents, such as primary studies, literature reviews, systematic reviews, meta-analyses, reports, and commentaries on the determinants of depression. The determinants refer to variables that appear to be linked to the development of depression, such as physiological factors (e.g., the nervous system, genetics), but also factors that are further away or more distal to the condition. Determinants may be risk or protective factors, and individual- or wider-area-level variables.
• - We focused on major depressive disorder, treatment-resistant depression, dysthymia, depressive symptoms, poststroke depression, perinatal depression, as well as depressive-like behaviour (common in animal studies), among others.
• - We included papers regardless of the measurement methods of depression.
• - We included papers that focused on human and/or rodent research.
• - This review focused on articles written in the English language.
• - Documents published between 2017–2020 were captured to provide an understanding of the latest research on this topic.
• - Studies that assessed depression as a comorbidity or secondary to another disorder.
• - Studies that did not focus on rodent and/or human research.
• - Studies that focused on the treatment of depression. We made this decision, because this is an in-depth topic that would warrant a separate stand-alone review.
• Next, we searched PubMed (2017–2020) using keywords related to depression and determinants. Appendix A contains the search strategy used. We also conducted focused searches in Medline, Scopus, and PsycInfo (2017–2020).
• Once the documents were identified through the databases, the inclusion and exclusion criteria were applied to the titles and abstracts. Screening of documents was conducted by O.R., and a subsample was screened by J.M.; any discrepancies were resolved through a communication process.
• The full texts of documents were retrieved, and the inclusion and exclusion criteria were again applied. A subsample of documents underwent double screening by two authors (O.R., J.M.); again, any discrepancies were resolved through communication.
• a. A data charting form was created to capture the data elements of interest, including the authors, titles, determinants (biological, psychological, social), and the type of depression assessed by the research (e.g., major depression, depressive symptoms, depressive behaviour).
• b. The data charting form was piloted on a subset of documents, and refinements to it were made. The data charting form was created with the data elements described above and tested in 20 studies to determine whether refinements in the wording or language were needed.
• c. Data charting was conducted on the documents.
• d. Narrative analysis was conducted on the data charting table to identify key themes. When a particular finding was noted more than once, it was logged as a potential theme, with a review of these notes yielding key themes that appeared on multiple occasions. When key themes were identified, one researcher (O.R.) reviewed each document pertaining to that theme and derived concepts (key determinants and related outcomes). This process (a subsample) was verified by a second author (J.M.), and the two authors resolved any discrepancies through communication. Key themes were also checked as to whether they were of major significance to public mental health and at the forefront of public health discourse according to consultations we held with stakeholders from the Manchester Metropolitan University, University of Cardiff, University of Colorado, Boulder, University of Cork, University of Leuven, University of Texas, charity representatives, and people with lived experience at workshops held by the University of Cambridge in 2020.

We condensed the extensive information gleaned through our review into short summaries (with key points boxes for ease of understanding and interpretation of the data).

Through the searches, 6335 documents, such as primary studies, literature reviews, systematic reviews, meta-analyses, reports, and commentaries, were identified. After applying the inclusion and exclusion criteria, 470 papers were included in this review ( Supplementary Table S1 ). We focused on aspects related to biological, psychological, and social determinants of depression (examples of determinants and related outcomes are provided under each of the following sections.

3.1. Biological Factors

The following aspects will be discussed in this section: physical health conditions; then specific biological factors, including genetics; the microbiome; inflammatory factors; stress and hypothalamic–pituitary–adrenal (HPA) axis dysfunction, and the kynurenine pathway. Finally, aspects related to cognition will also be discussed in the context of depression.

3.1.1. Physical Health Conditions

Studies on physical health conditions—key points:

• The presence of a physical health condition can increase the risk for depression
• Psychological evaluation in physically sick populations is needed
• There is large heterogeneity in study design and measurement; this makes the comparison of findings between and across studies difficult

A number of studies examined the links between the outcome of depression and physical health-related factors, such as bladder outlet obstruction, cerebral atrophy, cataract, stroke, epilepsy, body mass index and obesity, diabetes, urinary tract infection, forms of cancer, inflammatory bowel disorder, glaucoma, acne, urea accumulation, cerebral small vessel disease, traumatic brain injury, and disability in multiple sclerosis [ 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 ]. For example, bladder outlet obstruction has been linked to inflammation and depressive behaviour in rodent research [ 24 ]. The presence of head and neck cancer also seemed to be related to an increased risk for depressive disorder [ 45 ]. Gestational diabetes mellitus has been linked to depressive symptoms in the postpartum period (but no association has been found with depression in the third pregnancy trimester) [ 50 ], and a plethora of other such examples of relationships between depression and physical conditions exist. As such, the assessment of psychopathology and the provision of support are necessary in individuals of ill health [ 45 ]. Despite the large evidence base on physical health-related factors, differences in study methodology and design, the lack of standardization when it comes to the measurement of various physical health conditions and depression, and heterogeneity in the study populations makes it difficult to compare studies [ 50 ].

The next subsections discuss specific biological factors, including genetics; the microbiome; inflammatory factors; stress and hypothalamic–pituitary–adrenal (HPA) axis dysfunction, and the kynurenine pathway; and aspects related to cognition.

3.1.2. Genetics

Studies on genetics—key points:

There were associations between genetic factors and depression; for example:

• The brain-derived neurotrophic factor (BDNF) plays an important role in depression
• Links exist between major histocompatibility complex region genes, as well as various gene polymorphisms and depression
• Single nucleotide polymorphisms (SNPs) of genes involved in the tryptophan catabolites pathway are of interest in relation to depression

A number of genetic-related factors, genomic regions, polymorphisms, and other related aspects have been examined with respect to depression [ 61 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 ]. The influence of BDNF in relation to depression has been amply studied [ 117 , 118 , 141 , 142 , 143 ]. Research has shown associations between depression and BDNF (as well as candidate SNPs of the BDNF gene, polymorphisms of the BDNF gene, and the interaction of these polymorphisms with other determinants, such as stress) [ 129 , 144 , 145 ]. Specific findings have been reported: for example, a study reported a link between the BDNF rs6265 allele (A) and major depressive disorder [ 117 ].

Other research focused on major histocompatibility complex region genes, endocannabinoid receptor gene polymorphisms, as well as tissue-specific genes and gene co-expression networks and their links to depression [ 99 , 110 , 112 ]. The SNPs of genes involved in the tryptophan catabolites pathway have also been of interest when studying the pathogenesis of depression.

The results from genetics studies are compelling; however, the findings remain mixed. One study indicated no support for depression candidate gene findings [ 122 ]. Another study found no association between specific polymorphisms and major depressive disorder [ 132 ]. As such, further research using larger samples is needed to corroborate the statistically significant associations reported in the literature.

3.1.3. Microbiome

Studies on the microbiome—key points:

• The gut bacteria and the brain communicate via both direct and indirect pathways called the gut-microbiota-brain axis (the bidirectional communication networks between the central nervous system and the gastrointestinal tract; this axis plays an important role in maintaining homeostasis).
• A disordered microbiome can lead to inflammation, which can then lead to depression
• There are possible links between the gut microbiome, host liver metabolism, brain inflammation, and depression

The common themes of this review have focused on the microbiome/microbiota or gut metabolome [ 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 ], the microbiota-gut-brain axis, and related factors [ 152 , 162 , 163 , 164 , 165 , 166 , 167 ]. When there is an imbalance in the intestinal bacteria, this can interfere with emotional regulation and contribute to harmful inflammatory processes and mood disorders [ 148 , 151 , 153 , 155 , 157 ]. Rodent research has shown that there may be a bidirectional association between the gut microbiota and depression: a disordered gut microbiota can play a role in the onset of this mental health problem, but, at the same time, the existence of stress and depression may also lead to a lower level of richness and diversity in the microbiome [ 158 ].

Research has also attempted to disentangle the links between the gut microbiome, host liver metabolism, brain inflammation, and depression, as well as the role of the ratio of lactobacillus to clostridium [ 152 ]. The literature has also examined the links between medication, such as antibiotics, and mood and behaviour, with the findings showing that antibiotics may be related to depression [ 159 , 168 ]. The links between the microbiome and depression are complex, and further studies are needed to determine the underpinning causal mechanisms.

3.1.4. Inflammation

Studies on inflammation—key points:

• Pro-inflammatory cytokines are linked to depression
• Pro-inflammatory cytokines, such as the tumour necrosis factor (TNF)-alpha, may play an important role
• Different methods of measurement are used, making the comparison of findings across studies difficult

Inflammation has been a theme in this literature review [ 60 , 161 , 164 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 ]. The findings show that raised levels of inflammation (because of factors such as pro-inflammatory cytokines) have been associated with depression [ 60 , 161 , 174 , 175 , 178 ]. For example, pro-inflammatory cytokines, such as tumour necrosis factor (TNF)-alpha, have been linked to depression [ 185 ]. Various determinants, such as early life stress, have also been linked to systemic inflammation, and this can increase the risk for depression [ 186 ].

Nevertheless, not everyone with elevated inflammation develops depression; therefore, this is just one route out of many linked to pathogenesis. Despite the compelling evidence reported with respect to inflammation, it is difficult to compare the findings across studies because of different methods used to assess depression and its risk factors.

3.1.5. Stress and HPA Axis Dysfunction

Studies on stress and HPA axis dysfunction—key points:

• Stress is linked to the release of proinflammatory factors
• The dysregulation of the HPA axis is linked to depression
• Determinants are interlinked in a complex web of causation

Stress was studied in various forms in rodent populations and humans [ 144 , 145 , 155 , 174 , 176 , 180 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 , 195 , 196 , 197 , 198 , 199 , 200 , 201 , 202 , 203 , 204 , 205 , 206 , 207 , 208 , 209 , 210 , 211 ].

Although this section has some overlap with others (as is to be expected because all of these determinants and body systems are interlinked), a number of studies have focused on the impact of stress on mental health. Stress has been mentioned in the literature as a risk factor of poor mental health and has emerged as an important determinant of depression. The effects of this variable are wide-ranging, and a short discussion is warranted.

Stress has been linked to the release of inflammatory factors, as well as the development of depression [ 204 ]. When the stress is high or lasts for a long period of time, this may negatively impact the brain. Chronic stress can impact the dendrites and synapses of various neurons, and may be implicated in the pathway leading to major depressive disorder [ 114 ]. As a review by Uchida et al. indicates, stress may be associated with the “dysregulation of neuronal and synaptic plasticity” [ 114 ]. Even in rodent studies, stress has a negative impact: chronic and unpredictable stress (and other forms of tension or stress) have been linked to unusual behaviour and depression symptoms [ 114 ].

The depression process and related brain changes, however, have also been linked to the hyperactivity or dysregulation of the HPA axis [ 127 , 130 , 131 , 182 , 212 ]. One review indicates that a potential underpinning mechanism of depression relates to “HPA axis abnormalities involved in chronic stress” [ 213 ]. There is a complex relationship between the HPA axis, glucocorticoid receptors, epigenetic mechanisms, and psychiatric sequelae [ 130 , 212 ].

In terms of the relationship between the HPA axis and stress and their influence on depression, the diathesis–stress model offers an explanation: it could be that early stress plays a role in the hyperactivation of the HPA axis, thus creating a predisposition “towards a maladaptive reaction to stress”. When this predisposition then meets an acute stressor, depression may ensue; thus, in line with the diathesis–stress model, a pre-existing vulnerability and stressor can create fertile ground for a mood disorder [ 213 ]. An integrated review by Dean and Keshavan [ 213 ] suggests that HPA axis hyperactivity is, in turn, related to other determinants, such as early deprivation and insecure early attachment; this again shows the complex web of causation between the different determinants.

3.1.6. Kynurenine Pathway

Studies on the kynurenine pathway—key points:

• The kynurenine pathway is linked to depression
• Indolamine 2,3-dioxegenase (IDO) polymorphisms are linked to postpartum depression

The kynurenine pathway was another theme that emerged in this review [ 120 , 178 , 181 , 184 , 214 , 215 , 216 , 217 , 218 , 219 , 220 , 221 ]. The kynurenine pathway has been implicated not only in general depressed mood (inflammation-induced depression) [ 184 , 214 , 219 ] but also postpartum depression [ 120 ]. When the kynurenine metabolism pathway is activated, this results in metabolites, which are neurotoxic.

A review by Jeon et al. notes a link between the impairment of the kynurenine pathway and inflammation-induced depression (triggered by treatment for various physical diseases, such as malignancy). The authors note that this could represent an important opportunity for immunopharmacology [ 214 ]. Another review by Danzer et al. suggests links between the inflammation-induced activation of indolamine 2,3-dioxegenase (the enzyme that converts tryptophan to kynurenine), the kynurenine metabolism pathway, and depression, and also remarks about the “opportunities for treatment of inflammation-induced depression” [ 184 ].

3.1.7. Cognition

Studies on cognition and the brain—key points:

• Cognitive decline and cognitive deficits are linked to increased depression risk
• Cognitive reserve is important in the disability/depression relationship
• Family history of cognitive impairment is linked to depression

A number of studies have focused on the theme of cognition and the brain. The results show that factors, such as low cognitive ability/function, cognitive vulnerability, cognitive impairment or deficits, subjective cognitive decline, regression of dendritic branching and hippocampal atrophy/death of hippocampal cells, impaired neuroplasticity, and neurogenesis-related aspects, have been linked to depression [ 131 , 212 , 222 , 223 , 224 , 225 , 226 , 227 , 228 , 229 , 230 , 231 , 232 , 233 , 234 , 235 , 236 , 237 , 238 , 239 ]. The cognitive reserve appears to act as a moderator and can magnify the impact of certain determinants on poor mental health. For example, in a study in which participants with multiple sclerosis also had low cognitive reserve, disability was shown to increase the risk for depression [ 63 ]. Cognitive deficits can be both causal and resultant in depression. A study on individuals attending outpatient stroke clinics showed that lower scores in cognition were related to depression; thus, cognitive impairment appears to be associated with depressive symptomatology [ 226 ]. Further, Halahakoon et al. [ 222 ] note a meta-analysis [ 240 ] that shows that a family history of cognitive impairment (in first degree relatives) is also linked to depression.

In addition to cognitive deficits, low-level cognitive ability [ 231 ] and cognitive vulnerability [ 232 ] have also been linked to depression. While cognitive impairment may be implicated in the pathogenesis of depressive symptoms [ 222 ], negative information processing biases are also important; according to the ‘cognitive neuropsychological’ model of depression, negative affective biases play a central part in the development of depression [ 222 , 241 ]. Nevertheless, the evidence on this topic is mixed and further work is needed to determine the underpinning mechanisms between these states.

3.2. Psychological Factors

Studies on psychological factors—key points:

• There are many affective risk factors linked to depression
• Determinants of depression include negative self-concept, sensitivity to rejection, neuroticism, rumination, negative emotionality, and others

A number of studies have been undertaken on the psychological factors linked to depression (including mastery, self-esteem, optimism, negative self-image, current or past mental health conditions, and various other aspects, including neuroticism, brooding, conflict, negative thinking, insight, cognitive fusion, emotional clarity, rumination, dysfunctional attitudes, interpretation bias, and attachment style) [ 66 , 128 , 140 , 205 , 210 , 228 , 235 , 242 , 243 , 244 , 245 , 246 , 247 , 248 , 249 , 250 , 251 , 252 , 253 , 254 , 255 , 256 , 257 , 258 , 259 , 260 , 261 , 262 , 263 , 264 , 265 , 266 , 267 , 268 , 269 , 270 , 271 , 272 , 273 , 274 , 275 , 276 , 277 , 278 , 279 , 280 , 281 , 282 , 283 , 284 , 285 , 286 , 287 , 288 , 289 , 290 ]. Determinants related to this condition include low self-esteem and shame, among other factors [ 269 , 270 , 275 , 278 ]. Several emotional states and traits, such as neuroticism [ 235 , 260 , 271 , 278 ], negative self-concept (with self-perceptions of worthlessness and uselessness), and negative interpretation or attention biases have been linked to depression [ 261 , 271 , 282 , 283 , 286 ]. Moreover, low emotional clarity has been associated with depression [ 267 ]. When it comes to the severity of the disorder, it appears that meta-emotions (“emotions that occur in response to other emotions (e.g., guilt about anger)” [ 268 ]) have a role to play in depression [ 268 ].

A determinant that has received much attention in mental health research concerns rumination. Rumination has been presented as a mediator but also as a risk factor for depression [ 57 , 210 , 259 ]. When studied as a risk factor, it appears that the relationship of rumination with depression is mediated by variables that include limited problem-solving ability and insufficient social support [ 259 ]. However, rumination also appears to act as a mediator: for example, this variable (particularly brooding rumination) lies on the causal pathway between poor attention control and depression [ 265 ]. This shows that determinants may present in several forms: as moderators or mediators, risk factors or outcomes, and this is why disentangling the relationships between the various factors linked to depression is a complex task.

The psychological determinants are commonly researched variables in the mental health literature. A wide range of factors have been linked to depression, such as the aforementioned determinants, but also: (low) optimism levels, maladaptive coping (such as avoidance), body image issues, and maladaptive perfectionism, among others [ 269 , 270 , 272 , 273 , 275 , 276 , 279 , 285 , 286 ]. Various mechanisms have been proposed to explain the way these determinants increase the risk for depression. One of the underpinning mechanisms linking the determinants and depression concerns coping. For example, positive fantasy engagement, cognitive biases, or personality dispositions may lead to emotion-focused coping, such as brooding, and subsequently increase the risk for depression [ 272 , 284 , 287 ]. Knowing the causal mechanisms linking the determinants to outcomes provides insight for the development of targeted interventions.

3.3. Social Determinants

Studies on social determinants—key points:

• Social determinants are the conditions in the environments where people are born, live, learn, work, play, etc.; these influence (mental) health [ 291 ]
• There are many social determinants linked to depression, such as sociodemographics, social support, adverse childhood experiences
• Determinants can be at the individual, social network, community, and societal levels

Studies also focused on the social determinants of (mental) health; these are the conditions in which people are born, live, learn, work, play, and age, and have a significant influence on wellbeing [ 291 ]. Factors such as age, social or socioeconomic status, social support, financial strain and deprivation, food insecurity, education, employment status, living arrangements, marital status, race, childhood conflict and bullying, violent crime exposure, abuse, discrimination, (self)-stigma, ethnicity and migrant status, working conditions, adverse or significant life events, illiteracy or health literacy, environmental events, job strain, and the built environment have been linked to depression, among others [ 52 , 133 , 235 , 236 , 239 , 252 , 269 , 280 , 292 , 293 , 294 , 295 , 296 , 297 , 298 , 299 , 300 , 301 , 302 , 303 , 304 , 305 , 306 , 307 , 308 , 309 , 310 , 311 , 312 , 313 , 314 , 315 , 316 , 317 , 318 , 319 , 320 , 321 , 322 , 323 , 324 , 325 , 326 , 327 , 328 , 329 , 330 , 331 , 332 , 333 , 334 , 335 , 336 , 337 , 338 , 339 , 340 , 341 , 342 , 343 , 344 , 345 , 346 , 347 , 348 , 349 , 350 , 351 , 352 , 353 , 354 , 355 , 356 , 357 , 358 , 359 , 360 , 361 , 362 , 363 , 364 , 365 , 366 , 367 , 368 , 369 , 370 , 371 ]. Social support and cohesion, as well as structural social capital, have also been identified as determinants [ 140 , 228 , 239 , 269 , 293 , 372 , 373 , 374 , 375 , 376 , 377 , 378 , 379 ]. In a study, part of the findings showed that low levels of education have been shown to be linked to post-stroke depression (but not severe or clinical depression outcomes) [ 299 ]. A study within a systematic review indicated that having only primary education was associated with a higher risk of depression compared to having secondary or higher education (although another study contrasted this finding) [ 296 ]. Various studies on socioeconomic status-related factors have been undertaken [ 239 , 297 ]; the research has shown that a low level of education is linked to depression [ 297 ]. Low income is also related to depressive disorders [ 312 ]. By contrast, high levels of education and income are protective [ 335 ].

A group of determinants touched upon by several studies included adverse childhood or early life experiences: ex. conflict with parents, early exposure to traumatic life events, bullying and childhood trauma were found to increase the risk of depression (ex. through pathways, such as inflammation, interaction effects, or cognitive biases) [ 161 , 182 , 258 , 358 , 362 , 380 ].

Gender-related factors were also found to play an important role with respect to mental health [ 235 , 381 , 382 , 383 , 384 , 385 ]. Gender inequalities can start early on in the lifecourse, and women were found to be twice as likely to have depression as men. Gender-related factors were linked to cognitive biases, resilience and vulnerabilities [ 362 , 384 ].

Determinants can impact mental health outcomes through underpinning mechanisms. For example, harmful determinants can influence the uptake of risk behaviours. Risk behaviours, such as sedentary behaviour, substance abuse and smoking/nicotine exposure, have been linked to depression [ 226 , 335 , 355 , 385 , 386 , 387 , 388 , 389 , 390 , 391 , 392 , 393 , 394 , 395 , 396 , 397 , 398 , 399 , 400 , 401 ]. Harmful determinants can also have an impact on diet. Indeed, dietary aspects and diet components (ex. vitamin D, folate, selenium intake, iron, vitamin B12, vitamin K, fiber intake, zinc) as well as diet-related inflammatory potential have been linked to depression outcomes [ 161 , 208 , 236 , 312 , 396 , 402 , 403 , 404 , 405 , 406 , 407 , 408 , 409 , 410 , 411 , 412 , 413 , 414 , 415 , 416 , 417 , 418 , 419 , 420 , 421 , 422 , 423 , 424 , 425 , 426 , 427 , 428 ]. A poor diet has been linked to depression through mechanisms such as inflammation [ 428 ].

Again, it is difficult to constrict diet to the ‘social determinants of health’ category as it also relates to inflammation (biological determinants) and could even stand alone as its own category. Nevertheless, all of these factors are interlinked and influence one another in a complex web of causation, as mentioned elsewhere in the paper.

Supplementary Figure S1 contains a representation of key determinants acting at various levels: the individual, social network, community, and societal levels. The determinants have an influence on risk behaviours, and this, in turn, can affect the mood (i.e., depression), body processes (ex. can increase inflammation), and may negatively influence brain structure and function.

3.4. Others

Studies on ‘other’ determinants—key points:

• A number of factors are related to depression
• These may not be as easily categorized as the other determinants in this paper

A number of factors arose in this review that were related to depression; it was difficult to place these under a specific heading above, so this ‘other’ category was created. A number of these could be sorted under the ‘social determinants of depression’ category. For example, being exposed to deprivation, hardship, or adversity may increase the risk for air pollution exposure and nighttime shift work, among others, and the latter determinants have been found to increase the risk for depression. Air pollution could also be regarded as an ecologic-level (environmental) determinant of mental health.

Nevertheless, we have decided to leave these factors in a separate category (because their categorization may not be as immediately clear-cut as others), and these factors include: low-level light [ 429 ], weight cycling [ 430 ], water contaminants [ 431 ], trade [ 432 ], air pollution [ 433 , 434 ], program-level variables (ex. feedback and learning experience) [ 435 ], TV viewing [ 436 ], falls [ 437 ], various other biological factors [ 116 , 136 , 141 , 151 , 164 , 182 , 363 , 364 , 438 , 439 , 440 , 441 , 442 , 443 , 444 , 445 , 446 , 447 , 448 , 449 , 450 , 451 , 452 , 453 , 454 , 455 , 456 , 457 , 458 , 459 , 460 , 461 , 462 , 463 , 464 , 465 , 466 , 467 , 468 , 469 ], mobile phone use [ 470 ], ultrasound chronic exposure [ 471 ], nighttime shift work [ 472 ], work accidents [ 473 ], therapy enrollment [ 226 ], and exposure to light at night [ 474 ].

4. Cross-Cutting Themes

4.1. lifecourse perspective.

Studies on the lifecourse perspective—key points:

• Early life has an importance on mental health
• Stress has been linked to depression
• In old age, the decline in social capital is important

Trajectories and life events are important when it comes to the lifecourse perspective. Research has touched on the influence of prenatal or early life stress on an individual’s mental health trajectory [ 164 , 199 , 475 ]. Severe stress that occurs in the form of early-life trauma has also been associated with depressive symptoms [ 362 , 380 ]. It may be that some individuals exposed to trauma develop thoughts of personal failure, which then serve as a catalyst of depression [ 380 ].

At the other end of the life trajectory—old age—specific determinants have been linked to an increased risk for depression. Older people are at a heightened risk of losing their social networks, and structural social capital has been identified as important in relation to depression in old age [ 293 ].

4.2. Gene–Environment Interactions

Studies on gene–environment interactions—key points:

• The environment and genetics interact to increase the risk of depression
• The etiology of depression is multifactorial
• Adolescence is a time of vulnerability

A number of studies have touched on gene–environment interactions [ 72 , 77 , 82 , 119 , 381 , 476 , 477 , 478 , 479 , 480 , 481 ]. The interactions between genetic factors and determinants, such as negative life events (ex. relationship and social difficulties, serious illness, unemployment and financial crises) and stressors (ex. death of spouse, minor violations of law, neighbourhood socioeconomic status) have been studied in relation to depression [ 82 , 135 , 298 , 449 , 481 ]. A study reported an interaction of significant life events with functional variation in the serotonin-transporter-linked polymorphic region (5-HTTLPR) allele type (in the context of multiple sclerosis) and linked this to depression [ 361 ], while another reported an interaction between stress and 5-HTTLPR in relation to depression [ 480 ]. Other research reported that the genetic variation of HPA-axis genes has moderating effects on the relationship between stressors and depression [ 198 ]. Another study showed that early-life stress interacts with gene variants to increase the risk for depression [ 77 ].

Adolescence is a time of vulnerability [ 111 , 480 ]. Perceived parental support has been found to interact with genes (GABRR1, GABRR2), and this appears to be associated with depressive symptoms in adolescence [ 480 ]. It is important to pay special attention to critical periods in the lifecourse so that adequate support is provided to those who are most vulnerable.

The etiology of depression is multifactorial, and it is worthwhile to examine the interaction between multiple factors, such as epigenetic, genetic, and environmental factors, in order to truly understand this mental health condition. Finally, taking into account critical periods of life when assessing gene–environment interactions is important for developing targeted interventions.

5. Discussion

Depression is one of the most common mental health conditions, and, if left untreated, it can increase the risk for substance abuse, anxiety disorders, and suicide. In the past 20 years, a large number of studies on the risk and protective factors of depression have been undertaken in various fields, such as genetics, neurology, immunology, and epidemiology. However, there are limitations associated with the extant evidence base. The previous syntheses on depression are limited in scope and focus exclusively on social or biological factors, population sub-groups, or examine depression as a comorbidity (rather than an independent disorder). The research on the determinants and causal pathways of depression is fragmentated and heterogeneous, and this has not helped to stimulate progress when it comes to the prevention and intervention of this condition—specifically unravelling the complexity of the determinants related to this condition and thus refining the prevention and intervention methods.

The scope of this paper was to bring together the heterogeneous, vast, and fragmented literature on depression and paint a picture of the key factors that contribute to this condition. The findings from this review show that there are important themes when it comes to the determinants of depression, such as: the microbiome, dysregulation of the HPA axis, inflammatory reactions, the kynurenine pathway, as well as psychological and social factors. It may be that physical factors are proximal determinants of depression, which, in turn, are acted on by more distal social factors, such as deprivation, environmental events, and social capital.

The Marmot Report [ 291 ], the World Health Organization [ 482 ], and Compton et al. [ 483 ] highlight that the most disadvantaged segments of society are suffering (the socioeconomic context is important), and this inequality in resources has translated to inequality in mental health outcomes [ 483 ]. To tackle the issue of egalitarianism and restore equality in the health between the groups, the social determinants need to be addressed [ 483 ]. A wide range of determinants of mental health have been identified in the literature: age, gender, ethnicity, family upbringing and early attachment patterns, social support, access to food, water and proper nutrition, and community factors. People spiral downwards because of individual- and societal-level circumstances; therefore, these circumstances along with the interactions between the determinants need to be considered.

Another important theme in the mental health literature is the lifecourse perspective. This shows that the timing of events has significance when it comes to mental health. Early life is a critical period during the lifespan at which cognitive processes develop. Exposure to harmful determinants, such as stress, during this period can place an individual on a trajectory of depression in adulthood or later life. When an individual is exposed to harmful determinants during critical periods and is also genetically predisposed to depression, the risk for the disorder can be compounded. This is why aspects such as the lifecourse perspective and gene–environment interactions need to be taken into account. Insight into this can also help to refine targeted interventions.

A number of interventions for depression have been developed or recommended, addressing, for example, the physical factors described here and lifestyle modifications. Interventions targeting various factors, such as education and socioeconomic status, are needed to help prevent and reduce the burden of depression. Further research on the efficacy of various interventions is needed. Additional studies are also needed on each of the themes described in this paper, for example: the biological factors related to postpartum depression [ 134 ], and further work is needed on depression outcomes, such as chronic, recurrent depression [ 452 ]. Previous literature has shown that chronic stress (associated with depression) is also linked to glucocorticoid receptor resistance, as well as problems with the regulation of the inflammatory response [ 484 ]. Further work is needed on this and the underpinning mechanisms between the determinants and outcomes. This review highlighted the myriad ways of measuring depression and its determinants [ 66 , 85 , 281 , 298 , 451 , 485 ]. Thus, the standardization of the measurements of the outcomes (ex. a gold standard for measuring depression) and determinants is essential; this can facilitate comparisons of findings across studies.

5.1. Strengths

This paper has important strengths. It brings together the wide literature on depression and helps to bridge disciplines in relation to one of the most common mental health problems. We identified, selected, and extracted data from studies, and provided concise summaries.

5.2. Limitations

The limitations of the review include missing potentially important studies; however, this is a weakness that cannot be avoided by literature reviews. Nevertheless, the aim of the review was not to identify each study that has been conducted on the risk and protective factors of depression (which a single review is unable to capture) but rather to gain insight into the breadth of literature on this topic, highlight key biological, psychological, and social determinants, and shed light on important themes, such as the lifecourse perspective and gene–environment interactions.

6. Conclusions

We have reviewed the determinants of depression and recognize that there are a multitude of risk and protective factors at the individual and wider ecologic levels. These determinants are interlinked and influence one another. We have attempted to describe the wide literature on this topic, and we have brought to light major factors that are of public mental health significance. This review may be used as an evidence base by those in public health, clinical practice, and research.

This paper discusses key areas in depression research; however, an exhaustive discussion of all the risk factors and determinants linked to depression and their mechanisms is not possible in one journal article—which, by its very nature, a single paper cannot do. We have brought to light overarching factors linked to depression and a workable conceptual framework that may guide clinical and public health practice; however, we encourage other researchers to continue to expand on this timely and relevant work—particularly as depression is a top priority on the policy agenda now.

Acknowledgments

Thank you to Isla Kuhn for the help with the Medline, Scopus, and PsycInfo database searches.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/brainsci11121633/s1 , Figure S1: Conceptual framework: Determinants of depression, Table S1: Data charting—A selection of determinants from the literature.

Appendix A.1. Search Strategy

Search: ((((((((((((((((“Gene-Environment Interaction”[Majr]) OR (“Genetics”[Mesh])) OR (“Genome-Wide Association Study”[Majr])) OR (“Microbiota”[Mesh] OR “Gastrointestinal Microbiome”[Mesh])) OR (“Neurogenic Inflammation”[Mesh])) OR (“genetic determinant”)) OR (“gut-brain-axis”)) OR (“Kynurenine”[Majr])) OR (“Cognition”[Mesh])) OR (“Neuronal Plasticity”[Majr])) OR (“Neurogenesis”[Mesh])) OR (“Genes”[Mesh])) OR (“Neurology”[Majr])) OR (“Social Determinants of Health”[Majr])) OR (“Glucocorticoids”[Mesh])) OR (“Tryptophan”[Mesh])) AND (“Depression”[Mesh] OR “Depressive Disorder”[Mesh]) Filters: from 2017—2020.

Ovid MEDLINE(R) and Epub Ahead of Print, In-Process, In-Data-Review & Other Non-Indexed Citations, Daily and Versions(R)

• exp *Depression/
• exp *Depressive Disorder/
• exp *”Social Determinants of Health”/
• exp *Tryptophan/
• exp *Glucocorticoids/
• exp *Neurology/
• exp *Genes/
• exp *Neurogenesis/
• exp *Neuronal Plasticity/
• exp *Kynurenine/
• exp *Genetics/
• exp *Neurogenic Inflammation/
• exp *Gastrointestinal Microbiome/
• exp *Genome-Wide Association Study/
• exp *Gene-Environment Interaction/
• exp *Depression/et [Etiology]
• exp *Depressive Disorder/et
• or/4-16   637368
• limit 22 to yr = “2017–Current”
• “cause* of depression”.mp.
• “cause* of depression”.ti.
• (cause adj3 (depression or depressive)).ti.
• (caus* adj3 (depression or depressive)).ti.

Appendix A.2. PsycInfo

(TITLE ( depression OR “ Depressive Disorder ”) AND TITLE (“ Social Determinants of Health ” OR tryptophan OR glucocorticoids OR neurology OR genes OR neurogenesis OR “ Neuronal Plasticity ” OR kynurenine OR genetics OR “ Neurogenic Inflammation ” OR “ Gastrointestinal Microbiome ” OR “ Genome-Wide Association Study ” OR “ Gene-Environment Interaction ” OR aetiology OR etiology )) OR TITLE ( cause* W/3 ( depression OR depressive )).

Author Contributions

O.R. was responsible for the design of the study and methodology undertaken. Despite P.T.’s involvement in YPMH, he had no role in the design of the study; P.T. was responsible for the conceptualization of the study. Validation was conducted by O.R. and J.F.M. Formal analysis (data charting) was undertaken by O.R. O.R. and P.T. were involved in the investigation, resource acquisition, and data presentation. The original draft preparation was undertaken by O.R. The writing was conducted by O.R., with review and editing by P.T. and J.F.M. Funding acquisition was undertaken by O.R. and P.T. All authors have read and agreed to the published version of the manuscript.

This research was funded by The William Templeton Foundation for Young People’s Mental Health, Cambridge Philosophical Society, and the Aviva Foundation.

Conflicts of Interest

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Up to 40pc of mental health conditions are linked to child abuse and neglect, study finds

In 1996, Ange McAuley was just 11 years old when ABC's Four Corners profiled her family living on Brisbane's outskirts.

At the time her mother was pregnant with her sixth child and her father had long ago moved back to Perth.

WARNING: This story contains details that may be distressing to some readers.

It was a story about child protection and the program was profiling the role of community volunteers helping her mother, who had been in and out of mental health wards.

Ange was the eldest and it fell to her to get her younger siblings ready for school.

By the time the new baby arrived, she would stay home and change nappies.

"It was pretty crazy back then — I wasn't going to school a lot," she said.

By that age she was already holding a secret — she'd been sexually abused at age six by her stepfather, who would later be convicted of the crime.

"Back in the nineties, a lot of people kept stuff hidden and it wasn't spoken about outside of the family," she said.

"I've carried all these big burdens that weren't even mine. Sexual abuse happened to me. I didn't ask for it."

She says the trauma triggered a lifetime of mental health problems from substance abuse and self-harm as a teen, right through to post-natal depression.

Hidden source of our mental health crisis

A new study from the University of Sydney's Matilda Centre has established just how much Australia's mental health crisis can be traced back to this kind of childhood abuse and neglect.

The research has found that childhood maltreatment is responsible for up to 41 per cent of common mental health conditions including anxiety, depression, substance abuse, self-harm and suicide attempts.

The research, which draws on a 2023 meta-analysis of 34 research studies covering 54,000 people, found maltreatment accounted for 41 per cent of suicide attempts in Australia, 35 per cent of self-harm cases and 21 per cent of depression episodes.

It defined childhood maltreatment as physical, sexual, emotional abuse, emotional or physical neglect and domestic violence before the age of 18.

Lead researcher Lucy Grummitt said it is the first piece of work to quantify the direct impact of child abuse on long-term mental health. 

It found if childhood maltreatment was eradicated it would avert more than 1.8 million cases of depression, anxiety and substance use disorders.

"It shows just how many people in Australia are suffering from mental health conditions that are potentially preventable," she said.

Dr Grummitt said they found in the year 2023 child maltreatment in Australia accounted for 66,143 years of life lost and 118,493 years lived with disability because of the associated mental health conditions.

"We know that when a child is exposed to this level of stress or trauma, it does trigger a lot of changes in the brain and body," Dr Grummitt said.

"Things like altering the body's stress response will make a child hyper-vigilant to threat. It can lead to difficulties with emotion regulation, being able to cope with difficult emotions."

While some areas of maltreatment are trending down, figures from the landmark Australian child maltreatment study last year show rising rates of sexual abuse by adolescents and emotional abuse.

That study found more than one in three females and one in seven males aged 16 to 24 had experienced childhood sexual abuse.

Dr Grummit says childhood trauma can affect how the brain processes emotions once children become teens.

"It could be teenagers struggling to really cope with difficult emotions and certainly trauma can play a huge role in causing those difficult emotions," she said.

Mental health scars emerge early

For Ange, the trauma of her early years first showed itself in adolescence when she started acting out — she remembers punching walls and cars, binge drinking and using drugs.

"I would get angry and just scream," she said.

"I used to talk back to the teachers. I didn't finish school. Mum kicked me out a lot as a teenager. I was back and forth between mum and dad's."

By the time she disclosed her abuse, she was self-harming and at one point tried to take her own life.

"I was just done," she said.

"I was sick of having to get up every day. I didn't want to do it anymore."

Later on, she would have inappropriate relationships with much older men and suffered from depression, including post-natal depression.

"It's definitely affected relationships, it's affected my friendships, it's affected my intimate relationships," she said.

"Flashbacks can come in at the most inappropriate times — you're back in that moment and you feel guilt and shame.

"I feel like it's held me back a lot."

Calls for mental health 'immunisation'

Dr Grummitt said childhood abuse and neglect should be treated as a national public health priority.

In Australia, suicide is the leading cause of death for young people. 

"It's critical that we are investing in prevention rather than putting all our investments into treatment of mental health problems," she said.

Her team has suggested child development and mental health check-ins become a regular feature across a person's lifetime and have proposed a mental health "immunisation schedule".

Chief executive of mental health charity Prevention United, Stephen Carbone, said they estimate that less than 1 per cent of mental health funding goes toward prevention.

"There's been a big steady increase in per capita funding for mental health over the last 30 years but that hasn't translated into reductions," Dr Carbone, a GP, said. 

"You're not going to be able to prevent mental health conditions unless you start to tackle some of these big causes, in particular child maltreatment."

He said most of Australia's child protection system was about reacting to problems rather than trying to prevent them.

"If you're not tackling the upstream risk factors or putting in place protective factors you just keep getting more and more young people experiencing problems and services being overwhelmed," he said.

Now a mother of two teens herself, Ange says she wants to break the cycle and has been going to therapy regularly to help identify and avoid destructive patterns that she's seen herself fall into.

"I love my girls so much and I want better for them."

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