Evidence map›Paper›PMID 42827770›Full record

Observational studyFrontiers in immunology2026

Multi-omics reveals regulatory networks and critical early-warning factors for severe disease progression in diabetic patients infected with SARS-CoV-2.

Lei Dong, Dongshan Yu, Yunfeng Xiao, Jianjie Zhou, Jinhua Tang, Ying Li, Shijie Qin, Yueyun Ma, Yanhua Li

Abstract readObservational Study
In one paragraph

Observational study 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
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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

9 authors.

Lei Dong *Department of Clinical Laboratory, Air Force Medical Center, Air Force Medical University, Beijing, China.
Dongshan Yu *Department of Infectious Diseases, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Yunfeng Xiao *Department of Pharmacy, Hospital of the Shaanxi Provincial Corps of The Chinese People's Armed Police Force, Xi´an, China.
Jianjie Zhou *Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Jinhua TangDepartment of Clinical Laboratory, Air Force Medical Center, Air Force Medical University, Beijing, China.
Ying LiDepartment of Infectious Diseases, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Shijie QinInnovative Vaccine and Immunotherapy Research Center, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China.
Yueyun MaDepartment of Clinical Laboratory, Air Force Medical Center, Air Force Medical University, Beijing, China.
Yanhua LiDepartment of Clinical Laboratory, Air Force Medical Center, Air Force Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetic patients face elevated risks of severe COVID-19, yet the molecular underpinnings of disease progression, particularly for Omicron subvariants, which have predominated since late 2021, remain poorly defined. This observational study leverages a cohort recruited during China's Omicron peak (December 2022-February 2023) to delineate multi-omic signatures underlying severe diabetic COVID-19. Methods: We enrolled 55 patients across five clinical strata: non-diabetic mild/severe, diabetic mild/severe/fatal. Integrated 4D-DIA proteomics and LC/GC-MS metabolomics were applied, adjusting for confounders while retaining secondary infections as integral disease features. Results: Diabetic patients exhibited immune exhaustion with elevated IL-6/IL-10, blunted antiviral responses, and high secondary infection rates. We identified 62 diabetes-unique molecules associated with coordinated dysregulation across six pathways: oxidative stress, ferroptosis, glycolytic dysfunction, lipid remodeling, insulin signaling, and endothelial injury. A graded molecular signature tracked clinical deterioration: progressive depletion of GP1BB and PRG3, coupled with stepwise elevation of MMP-3/LOXL1 and Dl-Xylose. Fatal cases further revealed a metabolic substrate misalignment, glycolytic flux adduct accumulation paradoxically coexisting with glucose, lactate, ornithine depletion, suggesting terminal fuel utilization failure. Stage-dependent shifts of stress mediators (e.g., GSK3B, ALDH9A1) distinguished severe from fatal outcomes, implying transition from compensatory adaptation to homeostatic exhaustion. Conclusions: Severe diabetic COVID-19 is characterized by progressive immune-metabolic collapse. GP1BB, MMP-3, and Dl-Xylose warrant evaluation as early-warning biomarkers, while ornithine and PC(18:2) may track homeostatic reserve depletion in terminal disease. Together, these findings identify candidate biomarkers and pathway nodes that, with further validation, could contribute to risk-stratification and therapeutic strategies for diabetic patients with severe viral infections.

Indexed as

COVID-19Diabetes ComplicationsDiabetes MellitusSARS-CoV-2AgedBiomarkersDisease ProgressionFemaleHumansMaleMetabolomicsMiddle AgedMultiomicsProteomicsSeverity of Illness IndexBiomarkersbiomarkersCOVID-19diabetes mellitusdisease progressionmulti-omicsOmicron variant

Identifiers

PMID42827770
PMCPMC13630745

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.