Evidence map›Paper›PMID 26796761›Full record

ArticleThe Journal of clinical endocrinology and metabolism2016

Impact of Long-Term Poor and Good Glycemic Control on Metabolomics Alterations in Type 1 Diabetic People.

Tumpa Dutta, Yogish C Kudva, Xuan-Mai T Persson, Louis A Schenck, G Charles Ford, Ravinder J Singh, Rickey Carter, K Sreekumaran Nair

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in The Journal of clinical endocrinology and metabolism, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
5.2field-weighted citation impact, top 4% 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

47 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.

  1. Pooled it
  2. Trial
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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

8 authors at 2 institutions in 1 country.

Tumpa DuttaDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
Yogish C KudvaDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
Xuan-Mai T PerssonDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
Louis A SchenckDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
G Charles FordDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
Ravinder J SinghDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
Rickey CarterDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
K Sreekumaran NairDivisions of Endocrinology and Endocrine Research Unit (Y.C.K., K.S.N.) and Biomedical Statistics and Informatics (L.A.S., R.C.), Mayo Clinic Metabolomics Resource Core (T.D., X.-M.T.P., G.C.F., K.S.N.), and Department of Laboratory Medicine and Pathology (R.J.S.), Mayo Clinic, Rochester, Minnesota 55905.
Mayo Clinic · USUniversity of Minnesota Rochester · US

Funding

Mayo Clinic Center for Translational Science ActivitiesUL1TR000135 · NCATS · MAYO CLINIC ROCHESTER · PI KHOSLA, SUNDEEP · 2012 to 2015
$41.2M
TECHNOLOGY NMR SPECTROSCOPYU24DK100469 · NIDDK · MAYO CLINIC ROCHESTER · PI NAIR, K SREEKUMARAN · 2013 to 2017
$9.0M
IN VIVO REGULATION OF PROTEIN TURNOVER BY HORMONESR01DK041973 · NIDDK · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI NAIR, K SREEKUMARAN · 1989 to 2014
$7.3M
NCATS NIH HHS UL1 TR000135NIDDK NIH HHS R01 DK041973NIDDK NIH HHS R01 DK41973NIDDK NIH HHS U24 DK100469
6 · The paper itself

Abstract

contextPoor glycemic control in individuals with type 1 diabetes (T1D) is associated with both micro- and macrovascular complications, but good glycemic control does not fully prevent the risk of these complications.

objectiveThe objective of the study was to determine whether T1D with good glycemic control have persistent abnormalities of metabolites and pathways that exist in T1D with poor glycemic control.

designWe compared plasma metabolites in T1D with poor (glycated hemoglobin ≥ 8.5%, T1D[-] and good (glycated hemoglobin < 6.5%, T1D[+]) glycemic control with nondiabetic controls (ND).

settingThe study was conducted at the clinical research unit. PATIENTS OR OTHER

participantsT1D with poor (n = 14), T1D(-) and good, T1D(+) (n = 15) glycemic control and matched (for age, sex, and body mass index) ND participants were included in the study. INTERVENTION(S): There were no intervention. MAIN OUTCOME MEASURE(S): Comparison of qualitative and quantitative profiling of metabolome was performed.

resultsIn T1D(-), 347 known metabolites belonging to 38 metabolic pathways involved in cholesterol, vitamin D, tRNA, amino acids (AAs), bile acids, urea, tricarboxylic acid cycle, immune response, and eicosanoids were different from ND. In T1D(+),154 known metabolites belonging to 26 pathways including glycolysis, gluconeogenesis, bile acids, tRNA biosynthesis, AAs, branch-chain AAs, retinol, and vitamin D metabolism remained altered from ND. Targeted measurements of AA metabolites, trichloroacetic acid, and free fatty acids showed directional changes similar to the untargeted metabolomics approach.

conclusionsComprehensive metabolomic profiling identified extensive metabolomic abnormalities in T1D with poor glycemic control. Chronic good glycemic control failed to normalize many of these perturbations, suggesting a potential role for these persistent abnormalities in many complications in T1D.

Indexed as

MetabolomicsAdultAmino AcidsBlood GlucoseDiabetes Mellitus, Type 1Fatty Acids, NonesterifiedFemaleGlycated HemoglobinHumansLipid MetabolismMaleMetabolic Networks and PathwaysMiddle AgedRisk FactorsVitamin DAmino AcidsBlood GlucoseFatty Acids, NonesterifiedGlycated HemoglobinVitamin D

Identifiers

PMID26796761
PMCPMC4803168
OpenAlexW2277846589

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.