Evidence map›Paper›PMID 35777578›Full record

SynthesisNeuroscience and biobehavioral reviews2022

Insulin resistance in depression: A large meta-analysis of metabolic parameters and variation.

Brisa S Fernandes, Estela Salagre, Nitesh Enduru, Iria Grande, Eduard Vieta, Zhongming Zhao

Open access · greenAbstract readMeta-AnalysisReview
In one paragraph

Synthesis in Neuroscience and biobehavioral reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed, 2 pooled it
17.0field-weighted citation impact, top 1% of its field
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

89 citing papers in PubMed, 2 syntheses or guidelines pooled it, 130 citations in OpenAlex.

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29 more citing papers are in PubMed but not listed here.

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

6 authors at 3 institutions in 3 countries.

Brisa S FernandesCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Estela SalagreBipolar and Depressive Disorders Unit, Institute of Neurosciences, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Affective Disorders, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.
Nitesh EnduruCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Iria GrandeBipolar and Depressive Disorders Unit, Institute of Neurosciences, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain.
Eduard VietaBipolar and Depressive Disorders Unit, Institute of Neurosciences, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain.
Zhongming ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston (UTHealth), Houston, TX 77030, USA; Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA. Electronic address: zhongming.zhao@uth.tmc.edu.
The University of Texas Health Science Center at Houston · USUniversitat de Barcelona · ESAarhus University Hospital · DK

Funding

Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
NLM NIH HHS R01 LM012806
6 · The paper itself

Abstract

Increased insulin resistance is recognized in psychiatric disorders, such as schizophrenia and bipolar disorder, but its occurrence in depression is less clear. Our aims were to verify if insulin resistance is altered in depression, to test the metabolic subgroup hypothesis of depression and if there are changes with antidepressants. Inclusion criteria were studies including adult subjects with depression and either a control group or follow-up after treatment with antidepressants, and assessing fasting insulin or glucose levels or the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index. Seventy studies with 240,704 participants were included. Both insulin levels and the HOMA-IR index were increased in acute depression. Neither insulin nor the HOMA-IR index were altered during remission. Insulin was increased in atypical, but not typical depression. There was higher variation in insulin in individuals with depression than in controls. Insulin resistance did not change with antidepressant treatment. Insulin resistance is increased in depression during acute episodes. Heterogeneity was high in most of the analyses. Laboratory assessment of insulin resistance might have clinical utility in people with depression for diagnosis of the metabolic subtype and treatment selection, following precision psychiatry standards.

Indexed as

Bipolar DisorderInsulin ResistanceAdultAntidepressive AgentsDepressionHumansInsulinAntidepressive AgentsInsulinBiomarkerDepressionMajor depressive disorderMeta-analysisPrecision psychiatrySystematic review

Identifiers

PMID35777578
PMCPMC11056930
OpenAlexW4283689928

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.