Psycodex #1: Depression
SIG E CAPS, Neurobiological Hypotheses, Antidepressants, and everything in-between.
This is the first post in a series of weekly primers on what Australian medical students learn in psychiatry. “[]” indicates further commentary beyond the medical curriculum. See here for the introductory post.
Across 2023-24, 1 in 7 Australians (3.9 million people) were prescribed antidepressants [1].
In medical school, psychiatry does not hide the primacy of the biopsychosocial model; that mental distress is not purely a biological phenomenon, but intimately intertwined with psychological and social variables. In the acute hospital setting, the psychiatrist manages people through this model - working with social workers and psychologists to determine what protective factors can be addressed.
Psychiatrists are acutely aware of the sociological underpinnings of distress [2]; but of course, the expertise of the psychiatrist is biological. And this is reflected in our teaching.
The Construct of Depression
The psychiatry-keen student needs a systematic system to recognise depression. After all, the particular symptom cluster of the DSM-V Major Depressive Disorder (MDD) is entangled with all the clinical literature on antidepressant efficacy [3]. One is taught to be aware of its limitations, but understand that this is what embeds psychiatry as ‘evidence-based medicine’.
Thus, we learn the acronym of SIG E CAPS - Sleep changes, lack of Interest, Guilt, low Energy, low Concentration, altered Appetite, Psychomotor changes, Suicidal ideation - that a 2 week period with 5 or more of these symptoms (one being low mood or lack of interest) defines MDD. We rote memorise this to act as a guide for history-taking; not as a bible of truth.
The biomedical theoretical framework we are taught goes something akin to the following:
The monoamine hypothesis (1960s) describes low mood as a deficiency of serotonin or noradrenaline in neural circuits related to emotion regulation and reward. Debates in this area centre around the therapeutic lag between antidepressant effects (4-6 weeks) and the expected biological time of onset of these medications (7-10 days), as well as how serotonin deficits in ‘normal’ individuals did not predict depression.
The neuroendocrine hypothesis (1980s) grew given studies showing links between cortisol and inflammatory markers with depression, suggesting links to the hypothalamic-pituitary-adrenal axis and chronic stress physiology, emphasising the role of early life stressors.
Now, the neurotrophic hypothesis (1990s) suggests it is not the deficiency of serotonin, but rather the promoted neurogenesis and thus creation of new pathways that leads to an antidepressant effect. [4]
The final nuances in clinical considerations are related to separating depression from other clinical disorders, and treatment choice. For instance, a more biological or ‘melancholic’ depression which has more psychomotor and weight changes may be referred for treatments typically reserved later in the treatment pathway. Speaking of…
‘Antidepressants’ and other biological treatments
In an ideal world, medications would only be considered after psychological, behavioural, and social interventions have already been attempted. But realistically, in the hospital and in the community, drugs represent a much cheaper and pragmatic ‘fix’.
The group of drugs known as ‘antidepressants’ is incredibly broad. The conventional story goes a deficit in serotonin and noradrenaline - thus explaining the mechanism of SSRIs (Selective Serotonin Reuptake Inhibitors) and SNRIs (Serotonin-Noradrenaline Reuptake Inhibitors), and to an extent even older drugs like TCAs (Tricyclic Antidepressants) and MAOIs (Monoamine Oxidase inhibitors). Yet despite this, even as early as 1953 it was recognised that drugs classed as mood stabilisers, antipsychotics, and anxiolytics were also beneficial in depression - with widely varying mechanisms.
From a guideline-based perspective (RANZCP, 2020), we are given the following protocol:
First-Line Drugs: SSRIs, (with some specific indications using Mirtazepine, Agomelatine and Buproprion)
Second-Line Drugs: SNRIs, TCAs
Third-Line Drugs: MAOIs
Drugs are titrated up to a therapeutic dose, and attempted for at least 4 weeks. The key consideration of switching drugs comes from either lack of improvement or intolerance of side effects - which represents a key part of our learning.
To paint an example picture using SSRIs - on starting the medication, a ‘somatic storm’ of symptoms can cause nausea, headaches, and agitation. The largest reported side effect is sexual dysfunction, with more critical studies reporting up to 70%. Finally, the withdrawal effects of SSRIs are extensively reported, ranging from nausea, to akathisia, to ironically increased suicidal ideation [5].
Non-pharmacological biological treatment typically comes after pharmacological has failed; depression is defined as ‘treatment-resistant’ when two or more antidepressant trials haven’t worked, where other options like Electroconvulsive Therapy and emerging treatments like Transcranial Magnetic Stimulation are considered.
Finally, the emerging discourse in psychiatry centres around the re-emergence of drugs previously limited by political resistance: psychedelics like Psilocybin or LSD, Ketamine, and MDMA.
Beyond the Psychiatry of Depression
Depression, as in most of psychiatry, is a multi-faceted subject. As I will explore in the rest of the series, understanding these topics requires a pluralistic approach; no single psychiatrist, psychologist, epidemiologist, sociologist, neuroscientist will have a perfect understanding. In the spirit of pluralism, below I share a limited selection of additional learnings from various interdisciplinary readings.
[1] There is no single mental health crisis.
The epidemiology of depression is an intensely multifactorial topic. The numbers are: 10% Australians aged over 15 had depression/anxiety in 2009, compared with 18% in 2021 (AIHW, 2022). ~0.56% of Australian 12-24yo females had overnight psychiatric emergency presentations, compared with ~1% in 2020 - an 81% relative increase (After Babel).
Two lenses for understanding these changes are diagnostic inflation and concept heterogeneity.
The diagnostic inflation argument asks whether we are pathologising normal behaviour, and argues the Szasian idea that mental illness is a myth; driven both by well intentioned mental health awareness, but also social and political factors (further expanded in [2]). Are we overdiagnosing, or do humans today feel more distress than previously?
Concept heterogeneity questions the utility of this category to begin with. The MDD diagnosis does not separate the melancholic, severe biological depression from the mild-depression crisis, nor the acutely suicidal teenager from the burnt-out worker. One writer considers three separate mental health crises, each of which may need different types of solutions.
[2] Social factors as driving forces for mental distress
To give two examples of social drivers for mental health epidemiology;
James Davies in Sedated (2021) argues for how entrenched financial, regulatory, and political systems create incentives to overdiagnose and reduce mental distress issues. He argues that financial ties between clinicians, pharmaceutical companies, and regulators, along with governmental and economic philosophies, places the mental health burden on individuals, rather than the system which has caused it.
“Our mental health system has, like most other major social institutions, simply come to embrace those ideas and practices that have best secured its own perpetuation.”
Jonathan Haidt in The Anxious Generation (2024) argues for how technology, particularly social media, is a strong driver for the rise in the depression/anxiety in the youth. His blog, After Babel, details his argument, and is a key driver for political movements to ban phone usage in schools.
[3] Depression-rating scales are the ground truth of psychiatric research
Beyond the DSM-V (discussed more here), to trust the randomly controlled trials and meta-analyses of antidepressants, one needs to appreciate what they all hinge on: Scales. These are questionnaires, administered by the research or self-reported by the patient, which pin a numerical number on the extent of depression. To report a patient as having ‘remitted’ or ‘responded’, is to report a percentage reduction of these symptoms.
McPherson (2021) summarises the history of the scales nicely - having been born from the note card categorisation from Kraepelin in the 19th century, to the post-war questionnaires of the Hamilton Depression Rating Scale (1960), Beck Depression Inventory (1961), and the modern efficient primary scales of the Patient Health Questionnaire (2001). To be clear here - Hamilton himself mentions in his article that his scale has “considerable room for improvement”. Criticisms of these scales suggest that they do not effectively capture improvement, reducing it numerically, and that they were biased out of necessity to prove antidepressant efficacy. I believe they are better than nothing, but leave much to be desired.
[4] Emerging modern models of antidepressants and depression
Although the above arguments paint the depression epidemic as a social phenomenon which necessitates social change, there are still foundational questions in how depression in individuals manifest, and how biological treatments can reduce suffering. To give two perspectives:
Aftab (2024) integrates existing biological hypotheses with psychological models, the cognitive neuropsychological hypothesis - that antidepressants induce a positive shift in emotional processing, increase emotional flexibility (get unstuck from rigid behaviours), reduce neuroticism, and generally inhibits emotions and thus sensitivity. I think this gives much more tangible explanatory power.
Li et al. (2018) presents the neuroimaging perspective, linking multiple circuits in the brain to produce a more powerfully explanatory model for the constellation of symptoms in depression. In particular, the authors tie dysphoria to the ventral limbic affective network, anhedonia to the frontal-striatal reward network, rumination with the default mode network, and cognitive deficits to the dorsal cognitive control network. Those neuroscientifically inclined may nod along - but to summarise that jargon; we are starting to build understandable models for how depression works. The broader field exploring this space is known as computational psychiatry, which seeks to translate neuroscientific ideas into clinical applications.
[5] The war against antidepressant side-effects
The first figure on antidepressant usage in Australia may be surprising - but the kicker is even more; the average duration of antidepressant use is 4 years. This is despite guidelines suggesting use for 6-12mth for mild episodes of anxiety/depression. Mark Horowitz, an Australian-born psychiatrist, is a co-author of the Maudsley Deprescribing Guidelines, which aims to reduce the key withdrawal symptoms from antidepressant discontinuation. Stories of being unable to stop antidepressants, eroding trust in the medical institution (see Horowitz, 2024 for a detailed presentation).
P.S. I’d love to hear what you found interesting, and what you’d like more of in the comments.
It's interesting how you navigate the complexity here. I'm curious, how do med students reconcile the clear biological focus in teaching with the acute awareness of sociological underpinnings? That seems like a very difficult balance to strike in practise.