Evidence map›Paper›PMID 25986611›Full record

ArticleCardiovascular diabetology2015

Sex influenced association of directly measured insulin sensitivity and serum transaminase levels: Why alanine aminotransferase only predicts cardiovascular risk in men?

Barbara Buday, Peter Ferenc Pach, Botond Literati-Nagy, Marta Vitai, Gyorgyi Kovacs, Zsuzsa Vecsei, Laszlo Koranyi, Csaba Lengyel

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

18 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
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  6. Article
  7. Influence of Gender in Diabetes Mellitus and Its Complication.International journal of molecular sciences · 2022
    Review
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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.

Barbara BudayDrug Research Center, Department of Metabolism, Balatonfüred, Hungary. budaybarb@hotmail.com.
Peter Ferenc PachTritoo Informatics Ltd., Balatonfűzfő, Hungary. drpachpeter@gmail.com.
Botond Literati-NagyDrug Research Center, Department of Metabolism, Balatonfüred, Hungary. botond.literati@drc.hu.
Marta VitaiDrug Research Center, Department of Metabolism, Balatonfüred, Hungary. marta.vitai@drc.hu.
Gyorgyi KovacsDrug Research Center, Department of Metabolism, Balatonfüred, Hungary. gyoree@hotmail.vom.
Zsuzsa VecseiDrug Research Center, Department of Metabolism, Balatonfüred, Hungary. vecsei@drc.hu.
Laszlo KoranyiDrug Research Center, Department of Metabolism, Balatonfüred, Hungary. laszlo.koranyi@drc.hu.
Csaba LengyelFaculty of Medicine, First Department of Internal Medicine, University of Szeged, Szeged, Hungary. lecs.in1st@gmail.com.
HUN-REN Balaton Limnological Research Institute · HUUniversity of Szeged · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon alcoholic fatty liver disease (NAFLD) is an independent cardiovascular (CV) risk factor which is closely associated with insulin resistance measured by both direct or indirect methods. Gender specific findings in the relationship between alanine aminotransferase (ALT) and CV disease, the prevalence of NAFLD and type 2 diabetes (T2DM) have been published recently. The aim of the present study was to explore the gender aspects of the association between insulin sensitivity, liver markers and other metabolic biomarkers in order to elucidate the background behind the sex influenced difference in both NAFLD, T2DM and their association with CV risk. PATIENTS AND

methods158 female (47 normal and 111 impaired glucose intolerant) and 148 male (74 normal and 74 impaired glucose tolerant) subjects were included (mean age: 46.5 ± 8.31 vs. 41.6 ± 11.3, average Hba1c < 6.1 %, i.e. prediabetic population, drug naive at the time of the study). Subjects underwent a hyperinsulinemic normoglycemic clamp to determine muscle glucose uptake (M3), besides liver function tests and other fasting metabolic and anthropometric parameters were determined.

resultsSignificant bivariate correlations were found between clamp measured M3 and all three liver enzymes (ALT, aspartate aminotransferase and gamma-glutamyl transferase) in both sexes. When data were adjusted for possible metabolic confounding factors correlations ceased in the male population but stayed significant in the female group. Feature selection analysis showed that ALT is an important attribute for M3 in the female but not in male group (mean Z: 3.85 vs. 0.107). Multiple regression analysis confirmed that BMI (p < 0.0001) and ALT (p = 0.00991) significantly and independently predicted clamp measured muscle glucose uptake in women (R(2) = 0.5259), while in men serum fasting insulin (p = 0.0210) and leptin levels (p = 0.0294) but none of the liver enzymes were confirmed as significant independent predictors of M3 (R(2) = 0.4989).

conclusionThere is a gender specific association between insulin sensitivity, metabolic risk factors and liver transaminase levels. This might explain the sex difference in the predictive role of ALT elevation for CV disease. Moreover, ALT may be used as a simple diagnostic tool to identify insulin resistant subjects only in the female population according to our results.

Indexed as

AdultAlanine TransaminaseAspartate AminotransferasesCardiovascular DiseasesCase-Control StudiesFemalegamma-GlutamyltransferaseGlucoseGlucose Clamp TechniqueGlucose IntoleranceHumansInsulin ResistanceLinear ModelsMaleMiddle AgedMultivariate AnalysisAlanine TransaminaseAspartate Aminotransferasesgamma-GlutamyltransferaseGlucose

Identifiers

PMID25986611
PMCPMC4492083
OpenAlexW1858689059

What OpenQuestion holds

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LicenceCC BY
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.