Serum lncRNA H19/miR-675 /PPARα expression before middle gestation and their associations with macrosomia risk in singleton pregnancies without gestational diabetes mellitus: a preliminary study.

The roles of maternal serum lncRNA H19, miR-675, and PPARα protein levels before mid-pregnancy in predicting macrosomia remain unclear. This study aimed to investigate whether the expression of these serum molecules is associated with the risk of macrosomia in singleton pregnancies without gestational diabetes mellitus.

A nested case-control study was conducted within a prospective cohort study of 898 women with singleton pregnancies. Mothers of liveborn macrosomic newborns constituted the case group, and a random sample of mothers of the normal-birthweight newborns, matched on gestational age at blood collection and delivery date, served as controls. Serum levels of lncRNA H19, miR-675, PPARα protein, and serum lipids were measured before 20 weeks' gestation. Logistic regression, restricted cubic spline analysis, and stratified analysis were used to assess the associations. Predictive performance was explored using area under the receiver operating characteristic curve, net reclassification index (NRI), and integrated discrimination improvement (IDI).

No significant differences were observed in lncRNA H19 (Z =  - 0.344, P = 0.731), miR-675 (Z =  - 1.376, P = 0.169), or PPARα protein levels (Z < 0, P = 0.999) between macrosomia and control groups. However, in women with pre-pregnancy BMI < 24 kg/m2, lower PPARα protein levels (tertile 2 vs. tertile 3) were associated with a 70% reduced risk of macrosomia (OR = 0.30, 95% CI [0.09-0.99], P = 0.049). The NRI and IDI of the combined model incorporating serum lncRNA H19, miR-675, and PPARα protein levels were statistically superior to lipid-based models (P < 0.05).

Serum lncRNA H19 and miR-675 were not associated with macrosomia risk. Lower serum PPARα protein levels in early pregnancy may be associated with a reduced risk of macrosomia, particularly in non-obese women. The combined biomarkers demonstrated preliminary predictive potential in exploratory analysis, but validation in larger cohorts is required.
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Authors

Yu Yu, Jin Jin, Ding Ding, Cheng Cheng, He He, Yang Yang
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