SynthesisPloS one2016
A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature.
Synthesis in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 3 of them syntheses that pooled it.
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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.
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Who cites it
39 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Tools for assessing quality and risk of bias in Mendelian randomization studies: a systematic review.International journal of epidemiology · 2023Pooled it
- Non-genetic biomarkers and colorectal cancer risk: Umbrella review and evidence triangulation.Cancer medicine · 2020Pooled it
- Decision models of prediabetes populations: A systematic review.Diabetes, obesity & metabolism · 2019Pooled it
- CT-based radiomics nomogram of vertebral bodies and paravertebral muscles for differential diagnosis of type 2 diabetes mellitus.Frontiers in endocrinology · 2026Article
- An inflammatory biomarker panel for prediabetes classification using interpretable machine learning.PloS one · 2026Article
- Omics Approach for Personalised Prevention of Type 2 Diabetes Mellitus for African and European Populations (OPTIMA): a protocol paper.BMJ open · 2025Article
- The relationship between hepatic enzymes, prediabetes, and diabetes in the Azar cohort population.BMC endocrine disorders · 2025Article
- Longitudinal metabolite and protein trajectories prior to diabetes mellitus diagnosis in Danish blood donors: a nested case-control study.Diabetologia · 2024Article
- BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus.PLoS computational biology · 2023Article
- Longitudinal changes in vitamin D concentrations and the association with type 2 diabetes mellitus: the Tromsø Study.Acta diabetologica · 2023Article
- Association between neutrophil-to-lymphocyte ratio and diabetic kidney disease in type 2 diabetes mellitus patients: a cross-sectional study.Frontiers in endocrinology · 2023Article
- Predicting the Risk of Incident Type 2 Diabetes Mellitus in Chinese Elderly Using Machine Learning Techniques.Journal of personalized medicine · 2022Article
- Longitudinal changes in blood biomarkers and their ability to predict type 2 diabetes mellitus-The Tromsø study.Endocrinology, diabetes & metabolism · 2022Article
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- Article
- Therapeutic Potential of miRNAs for Type 2 Diabetes Mellitus: An Overview.Epigenetics insights · 2022Review
- Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes.International journal of molecular sciences · 2021Review
- A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population.The Journal of clinical endocrinology and metabolism · 2021Article
- Clinical and predictive significance of Plasma Fibrinogen Concentrations combined Monocyte-lymphocyte ratio in patients with Diabetic Retinopathy.International journal of medical sciences · 2021Observational
- Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundBlood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. METHODS AND
findingsWe systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of meta-analyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia.
conclusionsThis study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context.
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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.