Depression - Clinical Case Series #3
Adapted by Prof. Henry O'Connell from "Evolution and Psychiatry: Clinical Cases" - Edited by Dr Gurjot Brar
Welcome to the third of our clinical case series, exploring common mental disorders through the lens of evolutionary psychiatry. A ‘problem-based learning’ (PBL) approach is taken with learning outcomes defined at the outset, followed by several clinical encounters with fictional scenarios, interspersed with theory responding to the learning objectives. This method has emerged globally in medical curricula and has a good evidence base in medical education promoting self-directed learning. We hope you enjoy this format and look forward to your feedback.
This case series will often refer to key principles defined in the following article published in July 2023 which serves as a primer:
Evolution – basic principles & applications to health and illness
"Evolution and Psychiatry: Clinical Cases" is available hereThanks for reading Evolution and Psychiatry! Subscribe for free to receive new posts and support my work.
Depression
Learning Objectives
Outline the key facts about depressive disorders including clinical features and diagnostic criteria, epidemiology, aetiology, pathophysiology and management.
Describe how an evolutionary perspective can enhance research and treatment strategies for people with depression.
Describe what the evolutionary perspective tells us about why mood and mood disorders exist
Briefly outline the basis for a research proposal to test evolutionary theories on depression.
Note: this article should be read in conjunction with the article on Bipolar Affective Disorder as there is considerable overlap in material:
Bipolar Affective Disorder (BPAD) - Clinical Case Series #2
Welcome to the second of our clinical case series, exploring common mental disorders through the lens of evolutionary psychiatry. A ‘problem-based learning’ (PBL) approach is taken with learning outcomes defined at the outset, followed by several clinical encounters with fictional scenarios, interspersed with theory resp…
Dr Walsh moves to the Mood Disorders Research Institute (MDRI)
We have already met Dr Walsh in the chapter on BPAD and many of the principles covered in that chapter are also of relevance here. Dr Walsh has now left clinical psychiatry and embarked on a career in research, focused on mood disorders. He has started a research fellowship with the Mood Disorders Research Institute (MDRI) in Dublin.
The lead researcher for the MDRI is Professor Moody and he has been the key driver of research at the institute for over twenty years. The MDRI has secured millions of Euro in research funding over the years and engaged with multiple clinical trials on medications for both BPAD and unipolar depression. In recent years, Professor Moody has taken an interest in treatment resistant depression and is currently running three separate but interrelated clinical trials. The focus is on ‘real world’ clinical populations and the overall sample size is 1,000 individuals. The MDRI team are examining the impact of antidepressant augmentation strategies (using atypical antipsychotics and mood stabilizers), ECT and cognitive behavioural therapy in patients with treatment resistant depression who have already failed to respond to standard antidepressant treatments. Dr Walsh is a ‘foot soldier’ in the research programme, recruiting patients, performing assessments of mood and assessing their responses to various interventions.
Because of the multiple interviews he has conducted with patients and treating clinicians, Dr Walsh can now rattle off the clinical criteria for depression without even thinking, and he is starting to feel truly immersed in the world of depression treatment research.
Learning Objective 1: Outline the key facts about depressive illness including clinical features and diagnostic criteria, epidemiology, aetiology, pathophysiology and management.
The core clinical features of depression include pervasively depressed mood and reduced enjoyment or anhedonia. In addition, patients may experience reduced energy levels, disturbed sleep with insomnia or hypersomnia, appetite change with loss or gain in weight, psychomotor agitation or retardation, feelings of worthlessness or guilt, impaired concentration or indecisiveness and ideas of suicide.
Depression is remarkably common with lifetime prevalence rates of up to 15% and females twice as likely to be affected as males. Aetiology is multifactorial and includes genetic factors, medical comorbidities and environmental factors such as adverse and traumatic experiences in early life and psychosocial stressors such as bereavement and other losses.
Treatment of mild depression is focused on brief psychological interventions while moderate to severe depression generally requires medication treatment with antidepressants and, in treatment resistant cases, the addition of mood stabilizers, atypical antipsychotics and even ECT. Medication treatment for once off episodes is generally discontinued after 6-12 months but those with a history of recurrent depressive episodes may require lifelong prophylaxis.
The research meeting
It is now one year into his research fellowship. During that time, Dr Walsh has assessed several hundred patients with depressive symptoms and assessed their response to various medication and psychotherapy interventions. Dr Walsh has also co-authored some key papers with Professor Moody and the MDRI group that have led to pragmatic clinical recommendations on the use of medication in treatment resistant depression.
However, Dr Walsh has also started to ask himself and his colleagues some deeper questions about the nature and causes of depression. For one thing, he is conscious that the clinical criteria for depression (see earlier learning objective) are highly heterogenous and vary widely between individuals. He is also conscious that, while the medication and psychotherapy options recommended by the group have considerable efficacy, that his group is not asking wider questions about aetiology and the potential ‘function’ of depression, considering its high prevalence rates.
He decides to put some questions to Professor Moody at the monthly research meeting. Professor Moody acknowledges Dr Walsh’s concerns regarding the diagnostic criteria for depression and the fact that little heed is paid to ultimate causes for low mood and clinical depression. ‘I’ve been researching medications and psychotherapy in this area for twenty years’, he tells Dr Walsh and the research meeting, ‘But we’ve never asked deep questions about the aetiology of depression or indeed the reasons why ‘normal’ low mood is so common. Our funders are mainly pharmaceutical companies and I guess they’re more interested in medication solutions. However, I have had lots of discussions about the potential role for low mood and depression in our species and the discussions never get beyond some interesting ideas. I have never been able to apply evolutionary principles to treatment of depression. Furthermore, many of the evolutionary theories for depression are nice and plausible but largely untested. Maybe Dr Walsh for your second year here with us you could draw up a list of researchable evolutionary theories on depression and attempt to get some funding to look into them?’
Learning objective 2: Describe how an evolutionary perspective can enhance research and treatment strategies for people with depressive illness.
Abed and St John-Smith (2022) have outlined a number of theories based on evolutionary perspectives on depression as listed below:
1. Social competition and rank theories (Price et al, 1994) propose that depression is an adaptive strategy for coping with a decline in social standing or rank. The depressed state is thus conceptualized as a subordinate state that signals both submission to more powerful adversaries and may help in eliciting help from others.
2. Attachment theory (Bowlby, 1980) suggests that low mood in the context of depression is similar to the response seen in a child on prolonged separation from a parent, suggesting that depression is an evolved strategy for dealing with disruption of attachment bonds.
3. The social risk theory (Allen & Badcock, 2003) conceptualises low mood and depression as strategies for conserving energy and building up social value, thus helping avoid the potentially harmful effects of social exclusion.
4. The analytical rumination hypothesis (Andrews & Anderson Thomson, Jr, 2010) proposes that the depressed state may facilitate solving social dilemmas and decision making.
5. Nesse (2019) has proposed that depression facilitates withdrawal and disengagement from unattainable goals with clinical depression arising when the goals are too important to be abandoned.
6. Rantala et al (2018) have addressed the clinical heterogeneity within depression and suggested that, based on an evolutionary framework, major depressive disorder consists of twelve different conditions with proximate and ultimate causes, including infection, long-term stress, hierarchy conflict, grief, loneliness, traumatic experiences, post-partum events, romantic rejection, seasonal factors, chemicals, somatic disease and starvation.
7. Finally, Raison & Miller (2013) have proposed that clinical depression may be a modern manifestation of evolved illness behaviour and sickness responses to bacterial infection.
Dr Walsh’s Presentation
Halfway through his 2nd year with the MDRI, Dr Walsh is asked whether he might be interested in giving a presentation to psychiatry trainees on the evolutionary aspects of mood disorders. He is now well prepared to give this presentation after having spent time with hundreds of patients and reading the literature on evolutionary psychiatry. There is a good mix of psychiatry trainees and a few consultants in in the lecture room. Dr Walsh shuffles his prompts and catches Professor Moody in attendance towards the back row. After exchanging a brief smile, he begins:
Learning Objective 3: Describe what the evolutionary perspective tells us about why mood and mood disorders exist
“Thank you for coming today. I want to begin by emphasising that today’s lecture will be slightly different to what you are used to. I will be talking about ultimate explanations for mood disorders, not just the proximate mechanisms. I’m sure many of you like me have a curiosity that is not satisfied at stopping at diagnostic criteria, and instead want to delve deeper and understand why mood disorders are so common. Before discussing mood disorders, it first makes sense to understand why we evolved to have mood and a mood regulating system. Mood, in contrast to acute emotions, is defined as ‘a more pervasive state, partly detached from immediate environmental stimuli’ (Nettle & Bateson, 2012). Having a mood system allows us to direct attention towards situations that increase our reproductive fitness (rewards) and away from threats and punishments. For example, the repeated absence of reward causes low mood which then raises the threshold for reward-seeking behaviour. Similarly unbounded reward can drive hypomania and mania (Wilson, 1998). The relevance of a phylogenetically conserved mood system becomes apparent when we take into consideration the ‘environment of evolutionary adaptedness’ (EEA) (Tooby & Cosmides, 1990), which is not one specific timepoint but a wide range of similar contexts. Conditions in these historic environments exposed our ancestors to many threats to which they evolved a broad range of adaptive defence mechanisms, including for example, cough, fever, and inflammatory responses evolved to fight infectious disease.
Pertinent to mood, strategies involving social withdrawal and submission allowed minimisation of damage from social threats whereas social dominance in propitious situations gave access to mates, resources, and status (Brune & Wilson, 2022). It makes sense that mood fluctuates in response to our changing internal and external environment, where appraising a threat as a false negative may be life-threatening but a false positive may cost only a few calories (Nesse, 2005). We continually take in cues from our external environment which allows us to make predictions on our reproductive success, thus a particular experience produces an acute mood shift which allows an adjustment of expectations and informs our subsequent actions. The mood system must also contend with our internal state, in other words our functional ability, generally indicated by our physical condition. Integrating these two interacting inputs produces the necessary shifts in mood to orient ourselves towards appropriate actions (or inactions) (Nettle & Bateson, 2012).”
For more on signal detection theory based on reward and punishment see ‘The evolutionary origins of mood and its disorders’ (Nettle & Bateson, 2012).
“Consistent with these theories, particular life-events correlate with mood disorders. Loss and depression (Kendler et al., 2003); marriage and re-employment with antidepressant effects (Luhmann et al., 2012); and finally; physical infirmity (Lenze et al., 2001), poverty and social isolation (Brown & Moran, 1997; Galea et al., 2007; Rimehaug & Wallander, 2010) with depression. Cognitive bias towards negative appraisals further perpetuates the dysfunction in mood. For example, depressed individuals are more likely to rate ambiguous stimuli as negative than non-depressed controls (Gotlib & Krasnoperova, 1998).”
“Genetic variance in the responsiveness of mood systems and phenotypic plasticity can explain much of the variance observed in mood disorders (Caspi et al., 2003; Kendler et al., 2005), giving rise to ‘polymorphism of mood’ (Nettle & Bateson, 2012). This allows appreciation of variable selection pressures acting on these systems in differing environments, producing a ‘design compromise’ in terms of alleles that are positively selected, despite their potential to skew towards disorder and dysfunction. It must be emphasised however that the heritability of mood disorders is polygenic, and thus mediated by several genes contributing small effects to the overall expression. The persistence of these genes suggests, compromises of opposing selective pressures, or as mediators of positive effects yet unknown (Brune & Wilson, 2008).”
“Despite the belief that psychiatric disorders are arbitrarily agreed upon, the justification to treat can be based on suffering rather than demonstrating dysfunction, as is the basis for pain treatment (Nettle & Bateson, 2012).”
“Humans observe a slow life history strategy in general, but considerable ‘within-species’ variation occurs (Stearns, 1992), largely mediated by attachment (Bowlby, 1969). Insecure attachment is associated with a faster life trajectory based on unpredictable early environments. This is conceptualised as a proximate adaptive strategy for survival and reproduction, observed as exploitation of others, more risk-prone behaviours and early mating efforts (Belsky,1999). Fast life history strategies predict an increased risk of psychopathology including depression and mania (Brune 2016; Del Giudice, 2014; Hurst & Kavanagh, 2017) and depression is more likely in individuals who experienced neglectful or inconsistent parenting as children (insecure attachment) (Gilbert, 2006) and carries an unfavourable prognosis if associated with poor maternal care (Geerts & Brune, 2009).”
The following principles provide an understanding of how evolution has influenced the development of traits that leave us vulnerable to mood disorders:
Environmental Mismatch and Phenotypic Plasticity
Selection of genes favours reproductive success over all else
Design compromises are the rule, not the exception (even in psychological features)
Moods and their regulating systems have evolved as defense mechanisms to orientate us towards rewards and away from punishment
“In social competition theory, humans compete for mates, resources and status. This is invariably mediated by our mood system (Price et al., 1994). For example, ingratiation and dominance allow for chances of higher reproductive success via the social hierarchy. Typically, this produces a higher mood and in some cases mania (Sloman et al., 2011). Indeed, mania has been described as ‘an unconstrained acquisitive drive which is activated by evolutionary ancient systems involved in the regulation of arousal and ambition’ (Wilson, 1998).”
“Coming back to depression there are a number of theories (see previous learning objective above) and it is likely that depressive disorder represents a heterogeneous condition brought on by myriad causes. Some authors have called for subtyping of depression, which in theory would allow for better stratification of treatment regimes and research questions.”
“That being said, one of the most serious traps of a misguided evolutionary perspective is to view all mental states and disorders as being potentially useful and adaptive. Evolutionary psychiatry makes the case that although depressive disorder in the individual is unlikely to have adaptive benefits, the population having mood and a related mood regulating system is adaptive in specific contexts.”
The Research Proposal
Dr Walsh meets with Professor Moody in his office some weeks after the presentation. “Dr Walsh I’ve had a number of trainees who are interested in becoming involved in a research project at the MDRI and I wondered if we could further explore the evolutionary perspective for mood disorders, say depression?”. Dr Walsh has recently read some of Randy Nesse’s work and has been particularly drawn to the SOCIAL acronym. “Of course, my thoughts would be that different aspects of e.g. Nesse's SOCIAL system are disrupted differently for all of us at various times in our lives and the specific nature of the SOCIAL disturbance may colour the particular depressive episode, with implications for how that is assessed and treated.” replies Dr Walsh.
“Yes I believe that could have some merit, could you draw up a research proposal by next week and I can then apply for funding and put these keen trainees to work?” says Professor Moody.
Learning Objective. Briefly outline the basis for a research proposal to test evolutionary theories on depression.
Evolutionary perspectives can allow for broader and more pragmatic measures of health and illness, placing individuals in their wider social context. A notable example being the SOCIAL acronym (social situation, occupation, children and family, income, abilities, love, and sex) developed by Nesse (2019), which can be used to guide a broader definition of health and wellbeing, allowing psychiatry to pivot away from changes in rating scales and questionnaires with arbitrarily defined cut-off scores for levels of illness severity. The SOCIAL review of systems outlined by Nesse adds quality to the assessment and helps inform a bespoke treatment plan for individual patients. Thus, resources relating to Social (friends, groups, social influence, etc.), Occupation, Children and family, Income, Abilities and other personal resources and Love and sex should be considered in how they colour the current presentation and in their importance for future prognosis. Deficits or challenges in specific areas should be addressed through targeted psychosocial interventions and supports.
A study looking at stratifying depressed patients according to their ‘SOCIAL’ status could provide meaningful information about the context and environment. This information can lead to subtyping of depression which can allow for stratification to specific treatment regimes and interventions. E.g. a particular patient may be depressed and has recently suffered through a loss of occupation, income and social influence. Targeted interventions using employment support specialists and social workers could lead to an improvement in the depression. Another example could be a depressed patient who has lost their functional abilities due to a spine injury. Optimising treatment here would involve a comprehensive multidisciplinary team including physiotherapists, psychologists and occupational therapists.
In summary, a detailed personal history in conjunction with Nesse’s SOCIAL model could be essential for understanding the types of psychosocial factors that may elicit different types of depressive episodes in individuals. For example, individuals who are recently unemployed or bereaved may have a different symptom profile compared to those who are struggling to attain a challenging goal. These differences in symptom profile and psychosocial factors can potentially influence our choice of medications and therapies. By considering the unique circumstances and challenges faced by each individual, healthcare providers can tailor treatment approaches to address specific needs and optimise outcomes.
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Fantastic, thanks.