Evidence map›Paper›PMID 41878314›Full record

ReviewFrontiers in aging neuroscience2026

Brain insulin resistance: a key pathological hub linking metabolic and neuropsychiatric comorbidities.

Shanwen Tang, Yifan Liao, Maoyi Yang, Rensong Yue

Abstract readReview
In one paragraph

Review in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

4 authors.

Shanwen TangHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Yifan LiaoHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Maoyi YangHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Rensong YueHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high rate of comorbidity between metabolic diseases and neuropsychiatric disorders suggests a shared underlying pathogenic mechanism. However, the biological basis of this relationship remains unclear. This study aims to clarify the role of brain insulin resistance (BIR) in linking metabolic dysfunction to neuropsychiatric symptoms based on existing evidence. The analysis shows that BIR disrupts limbic system function through two primary molecular pathways: (1) impairment of the PI3K/Akt/mTOR pathway, which decreases the expression of synaptic plasticity-related proteins and causes deficits in long-term potentiation (LTP); (2) activation of the TLR4/MyD88 inflammatory axis, promoting pro-inflammatory cytokine release from glial cells. These changes result in characteristic neuropsychiatric phenotypes, including amygdala hyperactivity (emotional disorders), hippocampal atrophy (memory impairment), and decreased prefrontal cortex (PFC) function (executive dysfunction). This review highlights that interventions targeting BIR might simultaneously improve metabolic outcomes and neuropsychiatric symptoms, providing a theoretical foundation for trans-diagnostic treatment models. The findings support the view of BIR as a modifiable interface for metabolic- neuropsychiatric comorbidities and advocate for the development of a multidisciplinary collaborative framework to facilitate mechanism-based precision therapy.

Indexed as

Alzheimer’s diseaseanxiety disordersbrain insulin resistance (BIR)depressive disordersdiabetes-associated cognitive decline

Identifiers

PMID41878314
PMCPMC13006599

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.