Evidence map›Paper›PMID 38726387›Full record

ArticleFrontiers in psychiatry2024

Identification of gene networks jointly associated with depressive symptoms and cardiovascular health metrics using whole blood transcriptome in the Young Finns Study.

Binisha H Mishra, Emma Raitoharju, Nina Mononen, Aino Saarinen, Jorma Viikari, Markus Juonala, Nina Hutri-Kähönen, Mika Kähönen, Olli T Raitakari, Terho Lehtimäki and 1 more

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Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Binisha H MishraDepartment of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Emma RaitoharjuMolecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Nina MononenDepartment of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Aino SaarinenDepartment of Psychology and Logopedics, Faculty of Medicine, University of Helsinki. Helsinki, Finland.
Jorma ViikariDepartment of Medicine, University of Turku, Turku, Finland.
Markus JuonalaDepartment of Medicine, University of Turku, Turku, Finland.
Nina Hutri-KähönenDepartment of Paediatrics, Tampere University Hospital, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Mika KähönenFinnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Olli T RaitakariResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
Terho LehtimäkiDepartment of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Pashupati P MishraDepartment of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Studies have shown that cardiovascular health (CVH) is related to depression. We aimed to identify gene networks jointly associated with depressive symptoms and cardiovascular health metrics using the whole blood transcriptome. Materials and methods: We analyzed human blood transcriptomic data to identify gene co-expression networks, termed gene modules, shared by Beck's depression inventory (BDI-II) scores and cardiovascular health (CVH) metrics as markers of depression and cardiovascular health, respectively. The BDI-II scores were derived from Beck's Depression Inventory, a 21-item self-report inventory that measures the characteristics and symptoms of depression. CVH metrics were defined according to the American Heart Association criteria using seven indices: smoking, diet, physical activity, body mass index (BMI), blood pressure, total cholesterol, and fasting glucose. Joint association of the modules, identified with weighted co-expression analysis, as well as the member genes of the modules with the markers of depression and CVH were tested with multivariate analysis of variance (MANOVA). Results: We identified a gene module with 256 genes that were significantly correlated with both the BDI-II score and CVH metrics. Based on the MANOVA test results adjusted for age and sex, the module was associated with both depression and CVH markers. The three most significant member genes in the module were Conclusions: The identified gene module and its members can provide new joint biomarkers for depression and CVH.

Indexed as

cardiovascular healthcomorbiditydepressive symptomsgene networksmultimorbiditytranscriptome

Identifiers

PMID38726387
PMCPMC11079127

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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.