Metabolic and inflammatory dysfunction is prevalent in middle-aged people with major mood disorders, but less is known about young people. We investigated the trajectories of sensitive metabolic (Homeostatic Model Assessment for Insulin Resistance [HOMA2-IR]) and inflammatory markers (C-reactive protein [CRP]) in 155 young people (26.9 ± 5.6 years) accessing mental health services. We examined demographic and clinical correlates, longitudinal trajectories and relationships with specific illness subtypes. Additionally, we compared the HOMA2-IR with fasting blood glucose (FBG) for sensitivity. We observed a significant increase in HOMA2-IR and CRP over time with higher baseline levels predicting greater increases, although the rate of increase diminished in those with higher baseline levels. Body mass index predicted increases in HOMA2-IR (p < 0.001), but not CRP (p = 0.135). Multinomial logistic regression revealed that higher HOMA2-IR levels were associated with 2.3-fold increased odds of the “circadian-bipolar spectrum” subtype (p = 0.033), while higher CRP levels were associated with a reduced risk of the “neurodevelopmental psychosis” subtype (p = 0.033). Standard FBG measures were insensitive in detecting early metabolic dysregulation in young people with depression. The study supports the use of more sensitive markers of metabolic dysfunction to address the longitudinal relationships between immune-metabolic dysregulation and mood disorders in young people.

Hickie et al. (2023) pose the question “Are sleep and circadian rhythm disturbances (SCRD) the cause or simply the consequence of depression or other mood disorder sub-types?” and suggest strategies to better understand the role of SCRD in depression. Here, we contribute to the discussion by highlighting state-of-the-art computational omics methods (and the data sets needed to use these methods) which have potential for improving our understanding of the role of circadian biology in mood disorders.

Climatic and atmospheric conditions impact mental health, including increased incidents of depression associated with air pollution. A growing body of research considers time-bound ‘snap-shots’ of climatic drivers and mental health outcomes. Less is known about the likely effects of future climate change on mental health. Research is often inhibited by data scarcity, the challenge of synthesising data across multiple geospatial and temporal scales, and the under-representation of hard-to-reach groups. Thus, research methods are needed to integrate and analyse complex environmental and mental health multi-datasets while improving the visibility of under-represented groups. In this methods paper we present a novel approach for investigating the impact of climate change on mental health and addressing some challenges with, a) invisibility of vulnerable groups, and b) integrating complex environmental and mental health multi-datasets. The research aim is to pilot a web-based and smartphone application (Methane Early Warning Network (ME-NET)) for investigating the role of methane as a precursor of on-ground ozone, and the impact of ozone on mental health outcomes to improve civic knowledge and health-protection behaviour in the United Kingdom and Ghana. The methods include exploring the feasibility of using machine learning to develop an ozone early warning system and application co-design.

There is considerable interest in the role of neuroimmune processes in neuropsychiatric presentations among young people seeking mental health, neurological, paediatric and rheumatological services. The increasing availability of new immunotherapies, particularly monoclonal antibodies, introduces challenges in effectively and appropriately selecting candidates for immunotherapies. Neuroimmune-mediated neuropsychiatric syndromes (NIMNPS) typically include two broad types: i) ‘autoimmune encephalitis’, characterised by acute or subacute onset, neurological signs such as seizures, delirium or motor features and severe psychotic or major mood phenomena. Anti-N-methyl-D-aspartate receptor encephalitis was a pioneering clinical example, but various other autoantibodies have since been associated with this phenotype; and ii) atypical mood or psychotic syndromes with sub-acute or insidious onset, moderately severe atypical mood or psychotic symptoms, autonomic dysregulation, narcolepsy-like features, poor response to conventional treatments and adverse (notably motor) effects from psychotropic medications. Diagnosis of NIMNPS requires clinical or laboratory evidence of direct brain involvement, though autoantibodies are not always detectable. Given the broad and controversial diagnostic criteria for NIMNPS, we propose standardised clinical criteria for identifying ‘possible cases’, followed by laboratory, neuropsychological and brain imaging tests to confirm ‘probable’ cases suitable for immunotherapy. We emphasise rapid clinical and informed co-decision-making with young people and their families and loved ones. While immunotherapy holds promise for symptom alleviation, highly-personalised approaches and long-term management are essential. Future research should validate our proposed criteria, establish optimal, standardised yet personalised immunotherapy strategies that balance between clinical benefit and risks, and identify predictive markers of treatment response.