Evidence map›Paper›PMID 40885996›Full record

ArticleEuropean journal of medical research2025

Mechanisms of IGF1R signaling in type 2 diabetes-related neurodegeneration and therapeutic implications of exercise.

Zhenlin Mao, Ming Gong, Xinyue Sun, Canhong Yang

Abstract read
In one paragraph

Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Zhenlin Mao *Department of Neurology, Jinan University Affiliated Guangzhou Red Cross Hospital, Guangzhou, Guangdong, China.
Ming Gong *Department of Neurology, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Institute of Neuroscience, Guangzhou, China.
Xinyue SunHeilongjiang University of Chinese Medicine, Harbin, Heilongjiang Province, China.
Canhong YangDepartment of Neurology, The Third Affiliated Hospital of Southern Medical University, No. 183, Zhongshan Road West, Guangzhou, Guangdong, China. 916487904@qq.com.

Funding

Guangzhou Science and Technology Plan Project No. 2024A04J4728
6 · The paper itself

Abstract

backgroundType 2 diabetes (T2D) is a chronic metabolic disorder associated with an elevated risk of neurodegenerative diseases (NDs), notably Alzheimer's disease (AD). The insulin-like growth factor 1 receptor (IGF1R) plays a key role in both T2D and ND pathogenesis by regulating neuroinflammation and neuronal survival. However, the precise molecular mechanisms linking T2D to NDs remain unclear.

objectivesThis study investigates how IGF1R-mediated immunomodulatory pathways could be leveraged for therapeutic purposes in T2D-related neurodegeneration. It further explores the combined effects of Traditional Chinese Medicine (TCM) and structured exercise on IGF1R signaling and their potential to mitigate T2D-induced neurodegenerative changes.

methodsBioinformatics analyses and in vitro experiments were conducted using SH-SY5Y neuronal cells and primary mouse cortical neurons exposed to amyloid-beta (Aβ) toxicity. IGF1R was overexpressed, and cells were treated with CS at varying concentrations. Cell viability, apoptosis, inflammatory cytokines, oxidative stress markers, and macrophage polarization were assessed using CCK-8, flow cytometry, ELISA, fluorescence microscopy, and related methods.

resultsElevated IGF1R expression reduced Aβ-induced neuronal death and inflammation. CS administration increased IL-10 levels, suppressing pro-inflammatory cytokines (IL-1β, TNF-α), and promoted M2-like macrophage polarization, enhancing neurotrophic factors, such as brain-derived neurotrophic factor (BDNF) and anti-inflammatory responses.

conclusionsIGF1R is pivotal in regulating neuroinflammation and neuronal apoptosis in T2D-associated neurodegeneration. Combined TCM and structured exercise may beneficially modulate IGF1R-dependent signaling and protect neurons. Further clinical studies are needed to validate these findings and assess their therapeutic potential.

Indexed as

Alzheimer DiseaseDiabetes Mellitus, Type 2ExerciseNeuroinflammatory DiseasesReceptor, IGF Type 1Signal TransductionAmyloid beta-PeptidesAnimalsApoptosisCell SurvivalCerebral CortexComputational BiologyDatasets as TopicDisease Models, AnimalGene Expression ProfilingGene Expression RegulationAmyloid beta-PeptidesIgf1r protein, mouseReceptor, IGF Type 1ExerciseIGF1RNeurodegenerationNeuroinflammationTraditional Chinese MedicineType 2 diabetes

Identifiers

PMID40885996
PMCPMC12398044

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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.