Evidence map›Paper›PMID 26846149›Full record

ArticleEndocrine connections2016

Central and peripheral pathogenetic forms of type 2 diabetes: a proof-of-concept study.

Dmitry M Davydov, Malik K Nurbekov

Abstract read
In one paragraph

Article in Endocrine connections, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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.

Dmitry M DavydovLaboratory of NeuroimmunopathologyInstitute of General Pathology and Pathophysiology, Russian Academy of Medical Sciences, Moscow, Russia d.m.davydov@gmail.com.
Malik K NurbekovLaboratory of SociogenomicsMoscow State Pedagogical University, Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

hypothesisPrevious studies provide evidence that glycated haemoglobin (HbA1c) and fasting plasma glucose (FPG) should not be considered as interchangeable alternatives in the diagnosis of the same type 2 diabetes, but as indicators of its different pathogenetic subtypes. This study was conducted to determine whether a particularly high amount of glucose in either HbA1c form or in fasting plasma would be found in diabetic patients genetically predisposed for either intensive cognitive or intensive muscle metabolic activity, respectively.

methodsHbA1c and FPG levels, polymorphisms of genes indicating the predisposition to different cognitive activity (the dopamine D2 receptor (DRD2/ANKK1)), muscle activity (peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PGC1A(PPARGC1A))), and vascular regulation of general metabolic activity (the angiotensin 1 converting enzyme (ACE)) were assessed in diabetic patients and nondiabetic controls.

resultsDRD2/ANKK1 polymorphism that affects baseline central arousal determined HbA1c variations uncorrelated with FPG in total and clinical groups. The mutation of PGC1A mainly affecting peripheral glucose metabolism had an effect on FPG correlated or uncorrelated with HbA1c depending on the effect assessment in the total sample or in the nondiabetic group, respectively. ACE insertion/deletion (I/D) gene polymorphism was associated with both HbA1c and FPG fluctuations, but only in diabetic patients.

conclusionThe findings provide evidence that the HbA1c and FPG may predict the risks for different subtypes of type 2 diabetes associated with either brain or muscle metabolic activity in genetically vulnerable people.

Indexed as

ACEcentral arousalDRD2/ANKK1fasting plasma glucosegene polymorphismglycated haemoglobinmuscle activityPGC1Atype 2 diabetesvascular resistance

Identifiers

PMID26846149
PMCPMC8450667

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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.