Evidence mapPaperPMID 31802145Full record

ArticleDiabetologia2020

Metabolomic profiles associated with subtypes of prediabetes among Mexican Americans in Starr County, Texas, USA.

Goo Jun, David Aguilar, Charles Evans, Charles F Burant, Craig L Hanis

Open access · bronzeAbstract read
In one paragraph

Article in Diabetologia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 34% 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.

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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Application of Metabolomics and Traditional Chinese Medicine for Type 2 Diabetes Mellitus Treatment.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023
    Review
  8. 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

5 authors at 2 institutions in 1 country.

Goo JunHuman Genetics Center, University of Texas Health Science Center at Houston, P. O. Box 20186, Houston, TX, 77225, USA.ORCID http://orcid.org/0000-0003-0891-0204
David AguilarHuman Genetics Center, University of Texas Health Science Center at Houston, P. O. Box 20186, Houston, TX, 77225, USA.
Charles EvansMichigan Regional Comprehensive Metabolomics Resource Core, University of Michigan, Ann Arbor, MI, USA.
Charles F BurantMichigan Regional Comprehensive Metabolomics Resource Core, University of Michigan, Ann Arbor, MI, USA.
Craig L HanisHuman Genetics Center, University of Texas Health Science Center at Houston, P. O. Box 20186, Houston, TX, 77225, USA. Craig.L.Hanis@uth.tmc.edu.
The University of Texas Health Science Center at Houston · USUniversity of Michigan · US

Funding

Pilot and Feasibility (P and F) ProgramP30DK089503 · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2025 to 2025
$1.2M
Diabetes Progression with Metabolomic Profiling in Starr County Mexican AmericansR01DK118631 · NIDDK · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Goo Jun · 2023 to 2023
$579k
NIDDK NIH HHS P30 DK089503NIDDK NIH HHS R01 DK118631NIDDK NIH HHS U24 DK097153
6 · The paper itself

Abstract

aims/hypothesisTo understand the complex metabolic changes that occur long before the diagnosis of type 2 diabetes, we investigated differences in metabolomic profiles in plasma between prediabetic and normoglycaemic individuals for subtypes of prediabetes defined by fasting glucose, 2 h glucose and HbA

methodsUntargeted metabolomics data were obtained from 155 plasma samples from 127 Mexican American individuals from Starr County, TX, USA. None had type 2 diabetes at the time of sample collection and 69 had prediabetes by at least one criterion. We tested statistical associations of amino acids and other metabolites with each subtype of prediabetes.

resultsWe identified distinctive differences in amino acid profiles between prediabetic and normoglycaemic individuals, with further differences in amino acid levels among subtypes of prediabetes. When testing all named metabolites, several fatty acids were also significantly associated with 2 h glucose levels. Multivariate discriminative analyses show that untargeted metabolomic data have considerable potential for identifying metabolic differences among subtypes of prediabetes. CONCLUSIONS/

interpretationPeople with each subtype of prediabetes have a distinctive metabolomic signature, beyond the well-known differences in branched-chain amino acids. DATA AVAILABILITY: Metabolomics data are available through the NCBI database of Genotypes and Phenotypes (dbGaP, accession number phs001166; www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001166.v1.p1).

Indexed as

AdultAgedAmino Acids, Branched-ChainBlood GlucoseDiabetes Mellitus, Type 2FastingGlycated HemoglobinHumansMetabolomicsMexican AmericansMiddle AgedMultivariate AnalysisPrediabetic StateTexasUnited StatesYoung AdultAmino Acids, Branched-ChainBlood GlucoseGlycated HemoglobinAmino acidsImpaired fasting glucoseImpaired glucose toleranceMetabolomicsMexican AmericansPrediabetesType 2 diabetes

Identifiers

PMID31802145
PMCPMC7771728
OpenAlexW2991970338

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

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.