Evidence map›Paper›PMID 41005771›Full record

ArticleBMJ open2025

Identifying mood disorder subgroups at early risk of metabolic dysfunction: a cross-sectional cohort study in young people at early intervention services.

Sarah McKenna, Mirim Shin, Shin Ho Park, Alissa Nichles, Natalia Zmicerevska, Jacob Crouse, Connie Janiszewski, Minji Park, Elizabeth Phung, Frank Iorfino and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Sarah McKennaBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia sarah.mckenna@sydney.edu.au.ORCID http://orcid.org/0000-0002-8560-6399
Mirim ShinBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.
Shin Ho ParkBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.
Alissa NichlesBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.ORCID http://orcid.org/0000-0001-6404-7199
Natalia ZmicerevskaBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.ORCID http://orcid.org/0000-0001-7649-4711
Jacob CrouseBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.ORCID http://orcid.org/0000-0002-3805-2936
Connie JaniszewskiBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.
Minji ParkBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.
Elizabeth PhungBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.
Frank IorfinoBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.ORCID http://orcid.org/0000-0003-1109-0972
Mathew VaridelBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.
Elizabeth M ScottBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.
Joanne Sarah CarpenterBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.ORCID http://orcid.org/0000-0002-9766-6700
Ian B HickieBrain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSevere mental disorders are associated with increased risk of metabolic dysfunction. Identifying those subgroups at higher risk may help to inform more effective early intervention. The objective of this study was to compare metabolic profiles across three proposed pathophysiological subtypes of common mood disorders ('hyperarousal-anxious depression', 'circadian-bipolar spectrum' and 'neurodevelopmental-psychosis').

methods751 young people (aged 16-25 years; mean age 19.67±2.69) were recruited from early intervention mental health services between 2004 and 2024 and assigned to two mood disorder subgroups (hyperarousal-anxious depression (n=656) and circadian-bipolar spectrum (n=95)). We conducted cross-sectional assessments and between-group comparisons of metabolic and immune risk factors. Immune-metabolic markers included body mass index (BMI), fasting glucose (FG), fasting insulin, Homeostasis Model Assessment-Insulin Resistance (HOMA2-IR), C reactive protein and blood lipids.

resultsIndividuals in the circadian-bipolar spectrum subgroup had significantly elevated FG (

conclusionsCircadian disturbance may be driving increased rates of metabolic dysfunction among youth with emerging mood disorders, while increased BMI also remains a key determinant. Implications for assessment and early interventions are discussed.

Indexed as

Metabolic DiseasesMood DisordersAdolescentAdultBiomarkersBlood GlucoseBody Mass IndexC-Reactive ProteinCross-Sectional StudiesEarly Medical InterventionFemaleHumansInsulinInsulin ResistanceMaleRisk FactorsBiomarkersBlood GlucoseC-Reactive ProteinInsulinAdolescentsChild & adolescent psychiatryPrimary Health CarePSYCHIATRYPUBLIC HEALTH

Identifiers

PMID41005771
PMCPMC12481334

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.