Evidence map›Paper›PMID 22110171›Full record

ReviewDiabetes care2011

Emerging applications of metabolomic and genomic profiling in diabetic clinical medicine.

Aine M McKillop, Peter R Flatt

Registry-linked trialOpen access · hybridAbstract readReview
In one paragraph

Review in Diabetes care, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04257877 (Targeted Proteomic Analysis in the Plasma of Children With Diabetes Type 1 and Its Association With Peripheral Diabetic Neuropathy), which is not on this map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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.

NCT04257877 unknown statusnot on this mapstarted 2018, after this paper: background citation

Targeted Proteomic Analysis in the Plasma of Children With Diabetes Type 1 and Its Association With Peripheral Diabetic Neuropathy

TypeobservationalSponsorAristotle University Of ThessalonikiRan2018 to 2025Enrolled50ConditionsDiabetes Type 1, Proteomics, Diabetic Peripheral NeuropathyArmsBlood sampling
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 49 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. A Pilot Study on Characteristics of Metabolomics and Lipidomics according to Sasang Constitution.Evidence-based complementary and alternative medicine : eCAM · 2018
    Article
  12. Article
  13. Article
  14. Diabetes Associated Metabolomic Perturbations in NOD Mice.Metabolomics : Official journal of the Metabolomic Society · 2015
    Article
  15. Article
  16. Introduction to personalized medicine in diabetes mellitus.Rambam Maimonides medical journal · 2014
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

2 authors at 1 institution in 1 country.

Aine M McKillopAAD Centre for Pharmacy and Diabetes, School of Biomedical Sciences, University of Ulster, Coleraine, Northern Ireland, UK. am.mckillop@ulster.ac.uk
Peter R Flatt
University of Ulster · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Clinical and epidemiological metabolomics provides a unique opportunity to look at genotype-phenotype relationships as well as the body\x{2019}s responses to environmental and lifestyle factors. Fundamentally, it provides information on the universal outcome of influencing factors on disease states and has great potential in the early diagnosis, therapy monitoring, and understanding of the pathogenesis of disease. Diseases, such as diabetes, with a complex set of interactions between genetic and environmental factors, produce changes in the body\x{2019}s biochemical profile, thereby providing potential markers for diagnosis and initiation of therapies. There is clearly a need to discover new ways to aid diagnosis and assessment of glycemic status to help reduce diabetes complications and improve the quality of life. Many factors, including peptides, proteins, metabolites, nucleic acids, and polymorphisms, have been proposed as putative biomarkers for diabetes. Metabolomics is an approach used to identify and assess metabolic characteristics, changes, and phenotypes in response to influencing factors, such as environment, diet, lifestyle, and pathophysiological states. The specificity and sensitivity using metabolomics to identify biomarkers of disease have become increasingly feasible because of advances in analytical and information technologies. Likewise, the emergence of high-throughput genotyping technologies and genome-wide association studies has prompted the search for genetic markers of diabetes predisposition or susceptibility. In this review, we consider the application of key metabolomic and genomic methodologies in diabetes and summarize the established, new, and emerging metabolomic and genomic biomarkers for the disease. We conclude by summarizing future insights into the search for improved biomarkers for diabetes research and human diagnostics.

Indexed as

GenomicsMetabolomicsAdipokinesAlanine TransaminaseAntioxidantsBiomarkersBlood GlucoseC-Reactive ProteinDiabetes MellitusDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2gamma-GlutamyltransferaseGenetic Predisposition to DiseaseGenome-Wide Association StudyGlycated HemoglobinHistocompatibility Antigens Class IIAdipokinesAlanine TransaminaseAntioxidantsBiomarkersBlood GlucoseC-Reactive Proteingamma-GlutamyltransferaseGlycated Hemoglobinhemoglobin A1c protein, humanHistocompatibility Antigens Class IIInsulin

Identifiers

PMID22110171
PMCPMC3220869
OpenAlexW2096647851

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.