ReviewWorld journal of diabetes2025
Illuminating diabetes
Review in World journal of diabetes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Global research trends and hotspots evolution in type 2 diabetes mellitus complicated with coronary heart disease: a bibliometric analysis from 2016 to 2026.Frontiers in endocrinology · 2026Review
- Research progress and application prospects of multi-omics integration strategies in precision risk stratification of type 1 diabetes mellitus.Frontiers in immunology · 2026Review
- Integrative multi-omics profiling for early diagnosis, stratification and personalized management of chronic kidney disease: a new paradigm.Clinical and experimental medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetes mellitus (DM) comprises distinct subtypes-including type 1 DM, type 2 DM, and gestational DM - all characterized by chronic hyperglycemia and substantial morbidity. Conventional diagnostic and therapeutic strategies often fall short in addressing the complex, multifactorial nature of DM. This review explores how multi-omics integration enhances our mechanistic understanding of DM and informs emerging personalized therapeutic approaches. We consolidated genomic, transcriptomic, proteomic, metabolomic, and microbiomic data from major databases and peer-reviewed publications (2015-2025), with an emphasis on clinical relevance. Multi-omics investigations have identified convergent molecular networks underlying β-cell dysfunction, insulin resistance, and diabetic complications. The combination of metabolomics and microbiomics highlights critical interactions between metabolic intermediates and gut dysbiosis. Novel biomarkers facilitate early detection of DM and its complications, while single-cell multi-omics and machine learning further refine risk stratification. By dissecting DM heterogeneity more precisely, multi-omics integration enables targeted interventions and preventive strategies. Future efforts should focus on data harmonization, ethical considerations, and real-world validation to fully leverage multi-omics in addressing the global DM burden.
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What OpenQuestion holds
Registered trials
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.