ReviewCurrent diabetes reports2020
Integrating Genetics and the Plasma Proteome to Predict the Risk of Type 2 Diabetes.
Review in Current diabetes reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 14 citations in OpenAlex.
- Large-scale multi-omics enhance risk prediction for type 2 diabetes.Cardiovascular diabetology · 2026Article
- Multi-omics signatures of chronic inflammation across immune-related disease states.Frontiers in immunology · 2026Article
- Plasma proteomic signatures for type 2 diabetes and related traits in the UK Biobank cohort.Diabetes research and clinical practice · 2025Article
- A plasma proteomic signature for atherosclerotic cardiovascular disease risk prediction in the UK Biobank cohort.medRxiv : the preprint server for health sciences · 2024Article
- Multi-omic prediction of incident type 2 diabetes.Diabetologia · 2024Article
- Plasma proteomic signatures of a direct measure of insulin sensitivity in two population cohorts.Diabetologia · 2023Article
- The Proteome of Circulating Large Extracellular Vesicles in Diabetes and Hypertension.International journal of molecular sciences · 2023Article
- Personalised prevention of type 2 diabetes.Diabetologia · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of the reviewProteins are the central layer of information transfer from genome to phenome and represent the largest class of drug targets. We review recent advances in high-throughput technologies that provide comprehensive, scalable profiling of the plasma proteome with the potential to improve prediction and mechanistic understanding of type 2 diabetes (T2D). RECENT
findingsTechnological and analytical advancements have enabled identification of novel protein biomarkers and signatures that help to address challenges of existing approaches to predict and screen for T2D. Genetic studies have so far revealed putative causal roles for only few of the proteins that have been linked to T2D, but ongoing large-scale genetic studies of the plasma proteome will help to address this and increase our understanding of aetiological pathways and mechanisms leading to diabetes. Studies of the human plasma proteome have started to elucidate its potential for T2D prediction and biomarker discovery. Future studies integrating genomic and proteomic data will provide opportunities to prioritise drug targets and identify pathways linking genetic predisposition to T2D development.
Indexed as
Identifiers
What Socratic 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 Socratic graph.