Evidence mapPaperPMID 41821013Full record

ArticleReproductive health2026

Identifying serum amino acid as biomarkers of gestational diabetes mellitus in second-trimester among Chinese pregnant women: a machine learning-based cross-sectional study.

Lingling Cui, Ruijie Sun, Xiaoli Fu, Yibo Wang, Linpu Ji, Qiaorui Liu, Xiyue Zheng, Xinqian Li, Mengru Song, Haojie Zhao and 3 more

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Article in Reproductive health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

13 authors.

Lingling CuiCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Ruijie SunCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Xiaoli FuHenan Vocational College of Tuina, Zhengzhou, Henan, 471023, China.
Yibo WangCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Linpu JiCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Qiaorui LiuCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Xiyue ZhengCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Xinqian LiCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Mengru SongCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Haojie ZhaoCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Hua YeCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Dongmei XuDepartment of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Luying QinSchool of Nursing and Health , Zhengzhou University, No.100 Science Avenue, Zhengzhou, Henan, 450001, China. qinluying761@126.com.

Funding

Research and development of key technology for personalized assessment of nutritional genetic risk and precise nutritional intervention assessment based on the Central Plains population 231111311200The association between red blood cell folate concentrations in early/mid-pregnancy and maternal and child health outcomes 252102311111
6 · The paper itself

Abstract

backgroundLevels of plasma branched-chain and aromatic amino acids in pregnancy have been associated with gestational diabetes mellitus (GDM), but the metabolic role of serum amino acid (AA) profiles in its pathogenesis remains insufficiently elucidated.

objectiveThis study evaluated the diagnostic potential of second-trimester serum AA profiles, including Cys, Met, Val, Lys, Cit, Tau, Asp, Ile and Ala, for distinguishing GDM patients from healthy controls.

methodsA total of 189 women with GDM and 189 healthy women at 24-28 weeks of gestation were enrolled in the study, recruited from 2019 to 2022. Serum levels of 21 amino acids were precisely measured using automatic amino acid analyzer. Three machine learning methods were employed to select the most significant variables. Generalized linear models (GLMs) were established to evaluate the association between Serum AAs and GDM.

resultsSerum cysteine (Cys) and lysine (Lys) were inversely associated with GDM risk, whereas methionine (Met) and citrulline (Cit) showed positive associations. Notably, Met demonstrated an inverted U-shaped relationship, with an inflection at 239.9 µmol/L. The adjusted model achieved higher discrimination than the crude model. Sensitivity and subgroup analyses confirmed robust associations for Cys, while associations for Met, Lys, and Cit varied by pre-pregnancy body mass index (BMI).

conclusionsMid-pregnancy serum AAs, particularly Cys, Lys, Met, and Cit, were associated with GDM risk. These findings highlighted the heterogeneity of GDM metabolic signatures and support AAs as potential biomarkers for diagnosis of GDM.

Indexed as

Amino AcidsDiabetes, GestationalMachine LearningPregnancy Trimester, SecondAdultBiomarkersCase-Control StudiesChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansPregnancyAmino AcidsBiomarkersAmino acids profileGestational diabetes mellitusMachine learning

Identifiers

PMID41821013
PMCPMC12980925

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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 Socratic graph.