Evidence map›Paper›PMID 42741185›Full record

ArticleFrontiers in immunology2026

Comorbidity of anxiety and dry eye disease: shared biomarkers and immune responses.

Xi Long, Xin Peng, Guicheng Liu, Pengfei Jiang, Pei Liu, Jun Peng, Qinghua Peng

Abstract read
In one paragraph

Article in Frontiers in immunology, 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

7 authors.

Xi Long *Hunan University of Chinese Medicine, Changsha, China.
Xin Peng *Hunan University of Chinese Medicine, Changsha, China.
Guicheng LiuHunan University of Chinese Medicine, Changsha, China.
Pengfei JiangQuzhou Hospital of Zhejiang Medical and Health Group, Quzhou, China.
Pei LiuHunan University of Chinese Medicine, Changsha, China.
Jun PengThe First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China.
Qinghua PengHunan University of Chinese Medicine, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Dry eye disease (DED) and anxiety are prevalent disorders that often coexist, yet the molecular mechanisms underlying their comorbidity remain inadequately understood. This study sought to elucidate the convergent genes, pathways, and immune signatures that link DED and anxiety by employing integrated bioinformatics and experimental validation approaches. Methods: Datasets (GSE44101, GSE98793) were retrieved from the GEO database. Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and LASSO regression were utilized to identify candidate genes associated with comorbidity. Subsequently, functional enrichment analysis, protein-protein interaction network analysis, immune infiltration deconvolution, and single-cell RNA sequencing were conducted. A comorbid DED-anxiety mouse model was developed using a combination of desiccating stress, 0.2% benzalkonium chloride, and chronic unpredictable mild stress. The expression of hub genes was validated through reverse transcription quantitative polymerase chain reaction(RT-qPCR) and Western blotting. Results: Researchers identified 128 candidate genes enriched in pathways like circadian rhythm. Four key genes ( Conclusion: The study suggests

Indexed as

AnxietyDry Eye SyndromesAnimalsBiomarkersComorbidityComputational BiologyDisease Models, AnimalGene Expression ProfilingGene Regulatory NetworksHumansMiceProtein Interaction MapsBiomarkersanxietycircadian rhythmcomorbiditydry eye diseaseimmune response

Identifiers

PMID42741185
PMCPMC13572286

What Socratic holds

Textmetadata
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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 Socratic graph.