Background/Objectives: Major Depressive Disorder (MDD) is a neuropsychiatric disorder affecting nearly 200 million people worldwide. While it has broad health effects, relatively little is known about how these vary across MDD ‘subtypes’, which reflect distinct symptom profiles. This systematic review examined the methods used to define several MDD subtypes and their associations with physical, cognitive, social, and functional health outcomes. Methods: A systematic search of PubMed was conducted in accordance with PRISMA 2020 guidelines to identify peer-reviewed studies published in English between 2014 and 2025. The final search was conducted on 21 January 2025. Studies were included if they examined adults with MDD subtypes and reported health-related outcomes. Risk of bias was assessed using the Newcastle–Ottawa Scale. A narrative synthesis was conducted due to heterogeneity in the subtype definitions and outcome measures. Results: Sixteen studies were included. Atypical and melancholic depression were most consistently associated with metabolic dysfunction, higher BMI, and a greater waist circumference. Melancholic depression was frequently associated with cognitive deficits, though results varied. Cognitive impairments were also observed in DSM-defined atypical depression, particularly in attention, vigilance, and social cognition. Anxious and melancholic depression may be associated with more severe social and functional impairment compared to other subtypes. However, the findings were limited by inconsistent definitions and outcome measures. Conclusions: Some subtypes, particularly atypical, melancholic, and anxious depression, are differentially associated with specific patterns of impairment, though inconsistencies limit firm conclusions. Registration: This review was retrospectively registered with the Open Science Framework (OSF): No specific funding was received.

Background: The Autism Spectrum Disorder (ASD) characteristic of difficulties in social communication and interaction has been previously associated with elevated anxiety and the degree of mental effort required to understand and respond to social cues. These associations have implications for the mental health of autistic youth, but they are usually based on correlational statistics between measures of anxiety and social interaction demands that are collected in formal psychological testing settings. Another index of mental effort that has been found to correlate with anxious arousal is gamma wave activity, which is measured via EEG. Methods: To compare data from both of these indicators of mental effort and anxiety, a two-stage study was conducted using (1) standardized test data and (2) in vivo EEG data in a low-demand social setting. Results: As well as significant associations between social cognition and anxiety from standardized scales, there were also meaningful relationships between social cognition and gamma wave activity. Conclusions: Because gamma wave activity represents the highest level of cognitive complexity for brain activity, is an index of hypervigilance under threatening conditions, and has been associated with anxiety in autistic youth, these findings suggest that even low-level demand social interaction settings may initiate high-level anxiety-related behaviour in autistic youth.

Depression remains one of the most widespread and costly mental disorders, with the current first-line treatment efficacy of about a third, possibly due to its heterogeneous nature. Consequently, there is a need to identify reliable biomarkers for specific subtypes of depression, particularly neurological signatures that may help with targeted treatments. This study aimed to explore the connectivity between two important networks in the brain: the dorsal and ventral attention networks and the salience network, to determine their potential as biomarkers of depression subtypes. From resting electroencephalogram (EEG) data collected on 54 males and 46 females aged between 18 and 75 yr (M = 33 yr), functional network connectivity data were examined for their relationships with four depression subtypes. Beta and gamma wave connectivity was significantly associated with Anhedonia and Cognitive depression subtypes across and within all three networks while no significant results were found for alpha wave activity connectivity, and only one result was found for either the Mood or Somatic depression subtypes. In conclusion, these results provide further support for the concept of depression as heterogeneous rather than homogeneous and identify the novel neurophysiological signatures of two depression subtypes.

This study aimed to assess the association between four depression subtypes and health-related symptoms. Although it was expected that there would be asymmetry across the associations between depression subtypes and health, that relationship had not been previously reported. Data on the core diagnostic symptoms of depression and four depression subtypes, plus health-related outcomes, were collected from a sample of 301 community participants who completed standardised self-report questionnaires. Results indicated that Somatic Depression and Depressed Mood were most consistently associated with poorer outcomes across physical, emotional, and social domains, while Cognitive Depression and Anhedonia subtypes showed weaker associations. An exploratory network analysis identified Social Functioning and Depressed Mood as central nodes, indicating that affective disturbance and social wellbeing are key pathways through which depression relates to wider health outcomes. In conclusion, these results confirmed the heterogeneity of depression, as well as indicating that certain symptom clusters carry disproportionate weight in predicting health outcomes, thus exhibiting an asymmetrical pattern of associations between depression and health.