Evidence map›Paper›PMID 37069659›Full record

ArticleBMC medicine2023

Liver biomarkers, lipid metabolites, and risk of gestational diabetes mellitus in a prospective study among Chinese pregnant women.

Ping Wu, Yi Wang, Yi Ye, Xue Yang, Yichao Huang, Yixiang Ye, Yuwei Lai, Jing Ouyang, Linjing Wu, Jianguo Xu and 7 more

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
11.4field-weighted citation impact, top 1% 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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. [Early detection of Insuline Resistence in Pregnant Women].Revista medica del Instituto Mexicano del Seguro Social · 2026
    Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. 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

17 authors at 6 institutions in 1 country.

Ping WuDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Yi WangDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Yi YeDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Xue YangDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Yichao HuangDepartment of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China.
Yixiang YeDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Yuwei LaiDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Jing OuyangDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Linjing WuDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Jianguo XuDepartment of Clinical Laboratories, Shuangliu Maternal and Child Health Hospital, Chengdu, 610200, Sichuan, China.
Jiaying YuanDepartment of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu, 610200, Sichuan, China.
Yayi HuDepartment of Obstetrics and Gynecology & Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Yi-Xin WangDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Gang LiuDepartment of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Da ChenSchool of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, 511436, Guangdong, China.
An PanDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China. panan@hust.edu.cn.ORCID 0000-0002-1089-7945
Xiong-Fei PanSection of Epidemiology and Population Health & Department of Obstetrics and Gynecology, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Sichuan, Chengdu, 610041, China. pxiongfei@scu.edu.cn.ORCID 0000-0002-9350-9230
Huazhong University of Science and Technology · CNMaternal and Child Health Hospital of Sichuan Province · CNNational Medical Products Administration · CNSichuan University · CNAnhui Medical University · CNJinan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLiver plays an important role in maintaining glucose homeostasis. We aimed to examine the associations of liver enzymes and hepatic steatosis index (HSI, a reliable biomarker for non-alcoholic fatty liver disease) in early pregnancy with subsequent GDM risk, as well as the potential mediation effects of lipid metabolites on the association between HSI and GDM.

methodsIn a birth cohort, liver enzymes were measured in early pregnancy (6-15 gestational weeks, mean 10) among 6,860 Chinese women. Multivariable logistic regression was performed to examine the association between liver biomarkers and risk of GDM. Pearson partial correlation and least absolute shrinkage and selection operator (LASSO) regression were conducted to identify lipid metabolites that were significantly associated with HSI in a subset of 948 women. Mediation analyses were performed to estimate the mediating roles of lipid metabolites on the association of HSI with GDM.

resultsLiver enzymes and HSI were associated with higher risks of GDM after adjustment for potential confounders, with ORs ranging from 1.42 to 2.24 for extreme-quartile comparisons (false discovery rate-adjusted P-trend ≤0.005). On the natural log scale, each SD increment of alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, and HSI was associated with a 1.15-fold (95% CI: 1.05, 1.26), 1.10-fold (1.01, 1.20), 1.21-fold (1.10, 1.32), 1.15-fold (1.04, 1.27), and 1.33-fold (1.18, 1.51) increased risk of GDM, respectively. Pearson partial correlation and LASSO regression identified 15 specific lipid metabolites in relation to HSI. Up to 52.6% of the association between HSI and GDM risk was attributed to the indirect effect of the HSI-related lipid score composed of lipid metabolites predominantly from phospholipids (e.g., lysophosphatidylcholine and ceramides) and triacylglycerol.

conclusionsElevated liver enzymes and HSI in early pregnancy, even within a normal range, were associated with higher risks of GDM among Chinese pregnant women. The association of HSI with GDM was largely mediated by altered lipid metabolism.

Indexed as

Diabetes, GestationalBiomarkersEast Asian PeopleFemaleHumansLipidsLiverPregnancyPregnant PeopleProspective StudiesRisk FactorsBiomarkersLipidsBirth cohortGestational diabetes mellitusHepatic steatosis indexLipidomicsLiver enzyme

Identifiers

PMID37069659
PMCPMC10111672
OpenAlexW4366086093

What OpenQuestion holds

Textmetadata
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.