Evidence map›Paper›PMID 36869375›Full record

SynthesisJournal of neuroinflammation2023

Effects of diabetes on microglial physiology: a systematic review of in vitro, preclinical and clinical studies.

María Vargas-Soria, Mónica García-Alloza, Miriam Corraliza-Gómez

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of neuroinflammation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 2 pooled it
10.9field-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

56 citing papers in PubMed, 2 syntheses or guidelines pooled it, 87 citations in OpenAlex.

  1. Pooled it
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  11. iRhom2 deletion protects against diabetic neuropathy by suppressing neuroinflammation.The Journal of pharmacology and experimental therapeutics · 2026
    Article
  12. Review
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  20. Mechanisms of action of retinal microglia in diabetic retinopathy (Review).International journal of molecular medicine · 2025
    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

3 authors at 2 institutions in 1 country.

María Vargas-SoriaDivision of Physiology, School of Medicine, Universidad de Cadiz, Cadiz, Spain.
Mónica García-AllozaDivision of Physiology, School of Medicine, Universidad de Cadiz, Cadiz, Spain.
Miriam Corraliza-GómezDivision of Physiology, School of Medicine, Universidad de Cadiz, Cadiz, Spain. miriam.corraliza@uca.es.
Instituto de Investigación Biomédica de A Coruña · ESBiomedical Research and Innovation Institute of Cadiz · ES

Funding

Agencia Estatal de Investigacion. Ministerio de Ciencia e Innovación PID2020-115499RB-I00Junta de Andalucía P20-00928
6 · The paper itself

Abstract

Diabetes mellitus is a heterogeneous chronic metabolic disorder characterized by the presence of hyperglycemia, commonly preceded by a prediabetic state. The excess of blood glucose can damage multiple organs, including the brain. In fact, cognitive decline and dementia are increasingly being recognized as important comorbidities of diabetes. Despite the largely consistent link between diabetes and dementia, the underlying causes of neurodegeneration in diabetic patients remain to be elucidated. A common factor for almost all neurological disorders is neuroinflammation, a complex inflammatory process in the central nervous system for the most part orchestrated by microglial cells, the main representatives of the immune system in the brain. In this context, our research question aimed to understand how diabetes affects brain and/or retinal microglia physiology. We conducted a systematic search in PubMed and Web of Science to identify research items addressing the effects of diabetes on microglial phenotypic modulation, including critical neuroinflammatory mediators and their pathways. The literature search yielded 1327 records, including 18 patents. Based on the title and abstracts, 830 papers were screened from which 250 primary research papers met the eligibility criteria (original research articles with patients or with a strict diabetes model without comorbidities, that included direct data about microglia in the brain or retina), and 17 additional research papers were included through forward and backward citations, resulting in a total of 267 primary research articles included in the scoping systematic review. We reviewed all primary publications investigating the effects of diabetes and/or its main pathophysiological traits on microglia, including in vitro studies, preclinical models of diabetes and clinical studies on diabetic patients. Although a strict classification of microglia remains elusive given their capacity to adapt to the environment and their morphological, ultrastructural and molecular dynamism, diabetes modulates microglial phenotypic states, triggering specific responses that include upregulation of activity markers (such as Iba1, CD11b, CD68, MHC-II and F4/80), morphological shift to amoeboid shape, secretion of a wide variety of cytokines and chemokines, metabolic reprogramming and generalized increase of oxidative stress. Pathways commonly activated by diabetes-related conditions include NF-κB, NLRP3 inflammasome, fractalkine/CX3CR1, MAPKs, AGEs/RAGE and Akt/mTOR. Altogether, the detailed portrait of complex interactions between diabetes and microglia physiology presented here can be regarded as an important starting point for future research focused on the microglia-metabolism interface.

Indexed as

DementiaDiabetes MellitusHyperglycemiaCentral Nervous SystemHumansMicrogliaBrainCytokinesDiabetes mellitusHyperglycemiaMicrogliaNeuroinflammationOxidative stressRetina

Identifiers

PMID36869375
PMCPMC9983227
OpenAlexW4323047274

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.