Evidence map›Paper›PMID 41518412›Full record

ReviewMetabolic brain disease2026

The adiponectin-depression nexus: a brief review of mechanisms and therapeutic opportunities.

Weifen Li, Iram Murtaza, Tahir Ali

Abstract readReview
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In one paragraph

Review in Metabolic brain disease, 2026. 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

3 authors.

Weifen LiSchool of Pharmacy, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518055, China. liweifen@szu.edu.cn.
Iram MurtazaDepartment of Biochemistry, Faculty of Biological Sciences, Quaid-I-Azam University, Islamabad, Pakistan.
Tahir AliState Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 518055, China. tali@bs.qau.edu.pk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The understanding of Major Depressive Disorder (MDD) has evolved beyond the classic monoamine hypothesis to include significant immune-inflammatory and metabolic dysfunction. At the intersection of these systems, adiponectin (APN), an adipokine with potent anti-inflammatory, insulin-sensitizing, and neuroprotective properties, has emerged as a key molecular link. Clinical evidence reveals a complex association, where hypoadiponectinemia is most consistent in medication-naïve MDD patients with metabolic comorbidities, though this relationship is confounded by antidepressant use and clinical heterogeneity. By contrast, preclinical studies robustly demonstrate that adiponectin signaling exerts antidepressant-like effects by modulating hypothalamic–pituitary–adrenal (HPA) axis hyperactivity, reducing neuroinflammation, and promoting hippocampal neurogenesis. This review critically synthesizes this evidence, exploring paradoxical findings that underscore a context-dependent role for adiponectin. We also assess the translational potential of this knowledge, evaluating how antidepressants modulate its signaling and discussing promising adiponectin-centric therapeutics, including receptor agonists and lifestyle interventions, for metabolically-defined subgroups of MDD.

Indexed as

AdiponectinDepressionMajor Depressive DisorderAnimalsAntidepressive AgentsHumansHypothalamo-Hypophyseal SystemPituitary-Adrenal SystemReceptors, AdiponectinSignal TransductionAdiponectinAntidepressive AgentsReceptors, AdiponectinAdiponectinAntidepressantsDepressionHPA AxisInflammationNeurogenesis

Identifiers

What OpenQuestion holds

Textmetadata
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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.