Mood disorders are more common in persons with medical illness than in the general population, and add to suffering, morbidity, and mortality. As to diagnosis, emotional states seen in the context of illness range from denial to bland indifference to “normal” sadness, to pathological anxiety and depressive or manic syndromes. Within this range fall both primary mood disorders and mood disorders secondary to the primary illness and its treatment.Treatment is complicated by difficulties with patient engagement and retention, limited clinical trial data, illness-related sensitivity to medications and alterations in drug metabolism, drug side effects, and drug interactions. Limited data are available about potentially valuable treatments such as exercise, transcranial magnetic stimulation, ketamine and psychedelics. Collaborative care models for depression treatment in medical settings are effective but demanding to implement and sustain. Special considerations apply to treatment of patients near the end of life and those requesting hastened death. Psychiatric treatment of the medically ill patient can evoke strong feelings in the treatment provider.

The concept of abnormal mood has been a matter of a millennia-long debate in philosophy and medicine, while the diagnosis and classification of mood disorders remains a complex and controversial issue even in modern psychiatry. A centrepiece of this debate is the conceptualisation of mood and, by extension, mood disorders as a multi-dimensional spectrum with transdiagnostic symptoms (i.e., a continuous diagnostic classification) or as discrete nosological entities (i.e., a categorical diagnostic classification). Theoretical models and arguments based on empirical evidence have been proposed for both the distinct categorisation of abnormal mood states and the affective continuum perspective, which may also encompass psychosis and psychotic disorders. Although the conceptualisation of mood as a spectrum ranging from unipolar depression to unipolar mania may be the most suitable, this approach requires further evidence before it can replace the categorical classifications firmly employed in clinical practice for more than a century.

This chapter outlines the current research on the stress response and how chronic stress can lead to the dysfunction of neuroendocrine and immune responses and ultimately contribute to the development of psychiatric disorders. The chapter aims to provide an understanding of the pathways involved in the stress response, in particular the HPA axis and the role of cortisol, exploring the role of HPA hyperactivity as a contributor to major depressive disorder. The chapter reviews the impact of the stress response in bipolar and post-traumatic stress disorder, concluding with a summary of our current understanding of the interplay of mood disorders with early life stress.

Cultural background influences multiple aspects of human experience, including perceptions of mental illness and symptom expression. Incidence and prevalence of mood disorders appear to differ between cultures, with higher rates reported for developing compared to developed areas, although this is limited by differences diagnostic classification, as well as methodological inconsistencies in epidemiological studies. Social constructs about the self and others, beliefs, norms, and customs may affect not only the occurrence but also shape the profile of mood disorders and the extent of help seeking. The impact of culture on illness presentation may even extend to treatment selection and service use. Culture plays an important role in treatment outcomes, with racial disparities in antidepressant efficacy and fewer talking therapy referrals for minorities being prominent examples. Access to health services may also vary between cultural groups, even within regions and countries. A personalised approach matching patients with clinicians may provide a framework for shared understanding and experiences of illness to improve provided care.

In his book General Psychopathology, first published in 1913, Jaspers presented a methodological framework for exploring the phenomenology of symptoms of psychiatric disorders as well as relating experimental psychology and nosology to phenomenology. This chapter briefly introduces the phenomenological approach to symptoms and how this has influenced symptom- as opposed to diagnostic criterion-based assessment instruments, such as those based on the diagnostic statistical manual. A transcultural and historical perspective is employed to identify relevant symptoms of mood disorders and their temporal course. Descriptions and definitions of classical symptoms are provided and extended based on modern evidence to include changes in self-imagery, moral emotions, self-blame-related action tendencies, as well as mood-congruent biases in the representation of the past and future. Lastly the contribution of psychopathology to future subsyndrome discovery, translational cognitive neuroscience, and network-based approaches to the psychopathology of mood disorders is discussed.

This chapter outlines some of the most widely used clinician-rated (e.g., HAM-D, MADRS, YMRS) and self-rated (e.g., BDI, PHQ-9, QIDS, ISS, ASRM) tools for depression and bipolar disorder and summarises the evidence to date on their psychometric properties and practicality for use in research and clinical practice. The chapter also discusses the emerging research surrounding affective instability (AI), a core trait-like feature known to underpin the development and emergence of mood disorder symptoms and describes how digital technologies can aid in the monitoring of both mood and AI. A novel mood-monitoring methodology, called experience sampling method, is introduced and its benefits over traditional approaches are discussed. The chapter concludes with a summary of the current and upcoming mood rating tools, as well as their future role and potential applications in clinical practice.

Mood disorders constitute a substantial burden to patients, including a significant risk of suicide. In this chapter, the multidisciplinary components of services for mood disorders are delineated. Areas of special difficulty for service providers are recognised. Service development for mood disorders is necessary to meet existing treatment guidelines and to offer new evidence-based treatments, as they emerge. The elements of a general business case for local service development are outlined. The premise that early, correct diagnosis and effective treatment can produce savings in direct service costs and in indirect costs to society is explored briefly. The needs for co-production in partnership with service users and consultation with clinical stakeholders and managers are emphasised. Examples of service development are discussed, including a national programme to improve access to psychological treatments, a bipolar psychoeducation programme, and local specialist bipolar services. Finally, the need for rigorous planning of clinician recruitment, training and retention is highlighted.

Patients with mood disorders experience substantial challenges in their lives, often over long-term periods and despite receiving treatment. Provision of clinical care for mood disorders involves direct monetary costs. Illness also leads to indirect socioeconomic costs due to reduced work capacity. The absence of these patients from wider economic activity within society is another indirect cost. Estimating the impact of mood disorders in monetary terms mainly relies on administrative records, patient surveys, and mathematical models. Although estimations may vary between studies depending on methodology, annual economic cost of major depressive disorder and bipolar disorder in the UK may exceed £8 billion and £7 billion, respectively, with the majority of this cost accounted for by lost production rather than provided healthcare. Other indirect costs are commonly ignored and require further research. Cost of illness studies may serve as the basis for economic evaluations (e.g., cost-effectiveness analyses) of interventions targeting mood disorders.

Accurate diagnoses are crucial in choosing the most appropriate evidence-based treatment for mood disorders. Structured clinical interviews are the gold standard to assess unipolar (UD) and bipolar disorders (BD); however, they require time, financial, and training resources that are often unavailable. As this is especially true outside of specialty clinics or tertiary care settings, self-ratings can be used for screening to facilitate the diagnostic process. Such tools have both strengths and weaknesses, but it is essential that a detailed clinical assessment still follows before providing a valid diagnosis for mood disorders. In this chapter, we review several screening tools for UD and BD that have substantial empirical support and/or are widely used. We list measures that have been used for other types of screening, for example, to assess severity of symptoms or focus on specific populations. Gaps, recent developments, such as digital approaches, and final conclusions for clinical practice are also discussed.

Progress in developing new treatments for people with Major Depressive Disorder (MDD) and other mental disorders is hampered by the inability to apply standardized diagnostic tools to supplement clinical findings from DSM-5 or other recognized diagnostic systems. In the absence of tissue biopsies as a source of ‘solid’ biomarkers, mental health researchers have access to ‘liquid’ biopsies as well as neuroimaging, electroencephalography (EEG), and other techniques. Integration of clinical and biomarker features derived from large integrated datasets using machine-learning techniques provides a future for better classification and treatment selection to improve outcomes.

Mood disorders, including bipolar disorder (BD) and major depressive disorder (MDD), are known to have a significant genetic component based on familial and twin studies. Tremendous efforts from the scientific community and technical advancements have led to the discovery of multiple genes associated with the heritability of these disorders over the last years. Nonetheless, our knowledge of the exact genetic basis of BD and MDD is still fairly limited. Recent genome-wide association studies with massive sample sizes have started to characterize the polygenicity of these disorders, although future studies have yet to explore how genetic variants may interact with the environment to modulate one’s risk of disease. As our understanding of the genetics of mood disorders increases (with increasing sample sizes, a more significant shift from candidate gene studies to microarray and sequencing strategies, and integration of findings with environmental measures), many clinical opportunities may arise. This may include the future use of polygenic risk scores for risk assessment, predicting response to medications based on genotype, among others.