An adaptationist perspective on the etiology of depression
Zachary Durisko1, Benoit H Mulsant2, Paul W Andrews3
1Social Aetiology of Mental Illness (SAMI) CIHR Training Program, Centre for Addiction and Mental Health (CAMH), Suite 1111, 33 Russell Street, Toronto, Ontario, Canada M5S 3B1; Evolutionary Ecology of Health Research Laboratories, Department of Psychology, Neuroscience & Behaviour, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4K1.
Abstract:
Major depressive disorder (MDD) presents with a variety of symptoms and responds to a wide range of treatment interventions. Diagnostic criteria collapse multiple syndromes with distinct etiologies into the same disorder. MDD is typically understood as a malfunction of neurotransmission or brain circuitry regulating mood, pleasure and reward, or executive function. However, research from an evolutionary perspective suggests that the "normal" functioning of adaptations may also generate symptoms meeting diagnostic criteria. Functioning adaptations may be an underappreciated etiological pathway to MDD. Many adaptive functions for depressive symptoms have been suggested: biasing cognition to avoid losses, conserving energy, disengaging from unobtainable goals, signaling submission, soliciting resources, and promoting analytical thinking. We review the potential role of these adaptive functions and how they can lead to specific clusters of depressive symptoms. Understanding MDD from such a perspective reduces the heterogeneity of cases and may help to select the best intervention for each patient. We discuss the implications of different adaptive and maladaptive etiological pathways for the use of antidepressants and various modes of psychotherapy. In particular, instances of MDD caused by functioning adaptations may benefit most from treatments that support the adaptive function, or that target the precipitating causal stressor. We conclude that an evolutionary approach to the study of MDD may be one of the more promising approaches to reduce its heterogeneity and to better match patients and treatment.
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