Evidence map›Paper›PMID 40599634›Full record

ArticleBiological psychiatry global open science2025

Immunometabolic Pathways: Investigating Mediators of Major Depressive Disorder and Atherosclerotic Cardiovascular Disease Comorbidity.

Angela Koloi, Nabila P R Siregar, Rick Quax, Antonis I Sakellarios, Femke Lamers, Arja Rydin, Kevin Dobretz, Costas Papaloukas, Dimitrios I Fotiadis, Jos A Bosch

Abstract read
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In one paragraph

Article in Biological psychiatry global open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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

10 authors.

Angela KoloiUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.
Nabila P R SiregarComputational Science Laboratory, Institute of Informatics, University of Amsterdam, Amsterdam, the Netherlands.
Rick QuaxComputational Science Laboratory, Institute of Informatics, University of Amsterdam, Amsterdam, the Netherlands.
Antonis I SakellariosUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.
Femke LamersDepartment of Psychiatry, Amsterdam University Medical Center, VU Amsterdam, Amsterdam, the Netherlands.
Arja RydinDepartment of Psychiatry, Amsterdam University Medical Center, VU Amsterdam, Amsterdam, the Netherlands.
Kevin DobretzCardiology, Geneva University Hospitals, Geneva, Switzerland.
Costas PapaloukasUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.
Dimitrios I FotiadisUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.
Jos A BoschDepartment of Clinical Psychology, University of Amsterdam, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Major depressive disorder (MDD) and cardiovascular diseases (CVDs) often co-occur whereby comorbidity results in poorer clinical outcomes, presumably due to shared immunometabolic pathways. Identifying shared biomarkers for MDD-CVD comorbidity may provide targets for prevention or treatment. Methods: Using data from the NESDA (Netherlands Study of Depression and Anxiety) ( Results: Network analysis identified stable direct paths from MDD to CVDs via tumor necrosis factor α (TNF-α), tyrosine, and fatty acids and indirect paths via acetate, high-density lipoprotein (HDL) diameter, interleukin 6, AGP, high-sensitivity C-reactive protein, and low-density lipoprotein triglycerides. Among these, acetate, tyrosine, AGP (α Conclusions: These analyses identified biomarkers shared in MDD and CVDs and may drive comorbid pathology risk.

Indexed as

BiomarkersCVDMachine learningMDDMediators

Identifiers

PMID40599634
PMCPMC12209949

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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.