Correlation between the first-trimester non-traditional lipid parameters with the risk of gestational diabetes mellitus in pregnancy

doi:10.21203/rs.3.rs-4946619/v1

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Correlation between the first-trimester non-traditional lipid parameters with the risk of gestational diabetes mellitus in pregnancy

https://doi.org/10.21203/rs.3.rs-4946619/v1

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Introduction: Gestational diabetes mellitus (GDM) is a common complication in pregnancy, linked to adverse outcomes for mothers and infants. Elevated levels of non-traditional lipid parameters have been associated with metabolic disorders. This study investigates these lipid parameters' role in predicting GDM in the first trimester.

Methods: A retrospective study involving 1197 patients from The Third Affiliated Hospital of Wenzhou Medical University (January 2019 - August 2023) examined the correlation between non-traditional lipid parameters and GDM using logistic regression and stratified analyses. The diagnostic performance of the lipid parameters was evaluated using the area under the curve (AUC) method. Pearson correlation analysis clarified the relationship between non-traditional lipid parameters and neonatal birth weight, as well as their association with oral glucose tolerance test (OGTT) glycemic measures.

Results: Among 1197 participants, 201 were diagnosed with GDM. The GDM group exhibited significantly higher levels of non-traditional lipid parameters. Multivariate analysis identified these lipid measures, particularly Non-HDL-C with an AUC of 64.0% (95% CI: 59.6%-68.4%), as independent predictors of GDM across all models (P < 0.05), except for RC/HDL-C in model3. Most non-traditional lipid parameters demonstrated a linear relationship with GDM, with the exception of Non-HDL-C. Strong positive correlations were observed between fasting blood glucose levels and lipid ratios such as Non-HDL-C/HDL-C, LDL/HDL-C, TG/HDL-C, TC/HDL-C, and RC/HDL-C in patients with GDM. No significant differences were found in non-traditional lipid parameters among the single, double, and triple positive groups.

Discussion: First-trimester non-traditional lipid parameters are significant predictors of GDM, particularly when considering fasting blood glucose levels from the OGTT. These parameters offer potential value for early diagnosis.

Non-traditional lipid parameters

Oral glucose tolerance test

Neonatal birth weight

First-trimester

Gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a condition characterized by varying levels of carbohydrate intolerance that begins or is first identified during pregnancy [1]. It is a common obstetric complication, affecting 17.8% of pregnancies, with incidence rates ranging from 9.3–25.5% [2]. Women with GDM face higher risks of both short-term and long-term adverse outcomes for themselves and their offspring. Short-term risks include preeclampsia, cesarean section, perinatal mortality, preterm birth, and adverse fetal outcomes such as macrosomia, shoulder dystocia, birth trauma, and neonatal hypoglycemia [3–5]. Long-term complications involve a higher likelihood of developing type 2 diabetes (T2D) and obesity in both the mother and child [6, 7].

It is well-known that impaired glucose metabolism, abnormal circulating lipid levels, and worsening glucose intolerance are interconnected[8]. GDM, as a metabolic disorder during pregnancy, is associated with abnormal traditional lipid metabolism. Many studies show that women with GDM often exhibit higher levels of total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C), and lower levels of high-density lipoprotein cholesterol (HDL-C)[9, 10]. Non-traditional lipid parameters, calculated from TC, TG, LDL-C, and HDL-C, are also reported to be related to metabolic disorders[11–14]. Song et al. [11] found that higher non-HDL-C, TC/HDL-C, and TG/HDL-C ratios, and lower HDL-C levels were individually associated with type 2 diabetes in multivariate analyses (all P < 0.05). Wang et al. [13] showed a positive association between blood glucose levels and TG/HDL-C (β = 0.28, 95% CI: 0.09–0.46, p < 0.01) and LDL-C/HDL-C (β = 0.11, 95% CI: 0.04–0.18, P < 0.01) in type 2 diabetes patients.

Limited research exists on the association between changes in non-traditional lipid indicators and GDM. The relationship between fluctuations in these lipid parameters and oral glucose tolerance test (OGTT) results is also not well understood. Our study aims to investigate this association and assess the diagnostic value of these lipid indicators for predicting GDM in the first trimester.

2.1 Patient Population

This study retrospectively included 1197 patients from The Third Affiliated Hospital of Wenzhou Medical University, covering the period from January 2019 to August 2023. The inclusion criteria required participants to have an ultrasound-confirmed intrauterine pregnancy in the first trimester (before 14 weeks of gestation based on the last menstrual period) and a live birth in the third trimester. Exclusion criteria included: a) incomplete clinical records; b) use of medications affecting insulin secretion; c) hormonal or metabolic disorders (e.g., prediabetes, type 1 or 2 diabetes, polycystic ovary syndrome); d) loss to follow-up; e) history of GDM or pre-eclampsia; f) multiple pregnancies. The study involved a 2-hour, 75-gram OGTT administered after an overnight fast, conducted between 24 and 28 weeks of gestation to screen for GDM. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) guidelines [15], based on the following criteria: fasting blood glucose ≥ 5.1 mmol/L (91.90 mg/dL), 1-hour blood glucose ≥ 10.0 mmol/L (180.20 mg/dL), or 2-hour blood glucose ≥ 8.5 mmol/L (153.17 mg/dL). GDM classification: - Single positive: one of the blood glucose levels met or exceeded the threshold. - Double positive: two of the levels met or exceeded the threshold. - Triple positive: all three levels met or exceeded the threshold. Informed consent was obtained from all participants, and the study was approved by the Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University.

2.2 Clinical features record

The demographic and clinical data recorded for study subjects included age, weight, height, reproductive history, systolic blood pressure (SBP), diastolic blood pressure (DBP), gestational week at examination, and follow-up pregnancy outcomes. These outcomes included neonatal birth weight and OGTT results, measuring fasting, 1-hour, and 2-hour blood glucose levels.

2.3 Biochemical indicators measurements

The chemiluminescence assay (Siemens IM1600) was used to measure blood lipid markers, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). Other biochemical parameters assessed were fasting blood glucose (FBG), uric acid (UA), total bilirubin (TBil), direct bilirubin (DBil), indirect bilirubin (IBil), total bile acid (TBA), alanine transaminase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), serum creatinine (Scr), 25-hydroxyvitamin D (25(OH)D), and homocysteine (Hcy).

2.4 Immune and endocrine biomarker measurements

Triiodothyronine (T3), thyroxine (T4), and thyroid-stimulating hormone (TSH) levels were measured using a chemiluminescence assay (Siemens IM1600). Complement C3, C4, and C1q levels were determined using rate turbidimetry with an automatic biochemical analyzer (Siemens CH930, Shanghai, China). All tests adhered to the manufacturer's protocols and were performed by experienced technicians. Blood samples, collected from pregnant women in a fasting state between the 4th and 8th weeks of pregnancy, were used for these laboratory tests.

2.5 Calculation formulas of related parameters

The aspartate aminotransferase-to-alanine transaminase ratio (AST/ALT) is calculated as follows: AST/ALT = AST (U/L)/ALT (U/L) ; The blood urea nitrogen to creatinine ratio (BUN/Scr) is calculated as follows: BUN/Scr = BUN (mmol/L)/Scr (µmol/L) ×1000; BMI = weight (kg)/height (m²); TG/HDL-C = TG (mmol/L)/HDL-C (mmol/L); TC/HDL-C = TC (mmol/L)/HDL-C (mmol/L); LDL-C/HDL-C = LDL-C (mmol/L)/HDL-C (mmol/L); Non-HDL-C = TC (mmol/L) − HDL-C (mmol/L); Non-HDL-C/HDL-C(NHHR) = Non-HDL-C (mmol/L)/HDL-C (mmol/L); RC = HDL-C (mmol/L)- LDL-C (mmol/L); RC/HDL-C = RC (mmol/L)/ HDL-C (mmol/L).

2.6 Statistical analysis

The Shapiro–Wilk test was used to determine if the data followed a normal distribution. Normally distributed continuous variables are presented as mean and standard deviation (X ± SD), while non-normally distributed continuous variables are shown as medians (Q1, Q3). Categorical data are reported as numbers and proportions. Means were compared using the Student t-test, medians with the Mann–Whitney U test, and proportions with the χ2 test.

Multivariate-adjusted models were employed to examine the association between non-traditional lipid parameters and the incidence of GDM. Variables for adjustment were chosen based on two criteria: a change in the effect estimate exceeding 10% or a clinically significant relationship. The initial model was unadjusted. Model 1 adjusted for age, SBP, and DBP. Model 2 added C3, C1q, TBil, DBil, IBil, ALT and AST/ALT to Model 1. Model 3 further included FBG and UA. The results are presented as odds ratios (OR) with 95% confidence intervals (CI). Non-linearity was assessed using a likelihood ratio test, comparing a model with only a linear term to one with both linear and cubic spline terms. Subgroup analyses were conducted as well. Continuous variables were initially converted into categorical variables based on clinically established cut-off points or median values. To evaluate the diagnostic effectiveness of the variables for GDM, receiver operating characteristic (ROC) curves were used, and the area under the ROC curve (AUC) was calculated to quantify the screening value. Pearson correlation analysis was utilized to examine associations between neonatal birth weight and non-traditional lipid parameters. Additionally, the relationships between these lipid parameters and glycemic parameters measured by the OGTT were analyzed.

Statistical analyses were performed using R software (version 4.2.2; The R Foundation), SPSS Statistics (version 22.0; IBM Corp.), and Free Statistics (version 1.9; Beijing, China). All tests were two-tailed, and a P-value of less than 0.05 was considered statistically significant.

3.1 Baseline Clinical and Laboratory Characteristics of Study Participants

The study included 1176 participants, with 201 diagnosed with GDM (mean age: 30.52 ± 4.81 years; BMI: 22.67 ± 3.41 kg/m²), and 773 non-GDM participants (mean age: 28.7 ± 4.26 years; BMI: 21.19 ± 3.04 kg/m²). Compared to the non-GDM group, the GDM group had significantly higher levels of age, BMI, SBP, DBP, FBG, UA, ALT, C3, C1q, TC, TG, and LDL-C (P < 0.05). Additionally, the GDM group had elevated levels of Non-HDL-C (2.72 ± 0.83 vs. 2.35 ± 0.72 mmol/L, P < 0.001), Non-HDL-C/HDL-C (2.21 ± 0.87 vs. 1.87 ± 0.65 mmol/L, P < 0.001), RC (0.48 ± 0.27 vs. 0.40 ± 0.19 mmol/L, P < 0.001), LDL/HDL-C (1.99 ± 0.72 vs. 1.75 ± 0.65 mmol/L, P < 0.001), TG/HDL-C (0.86 (0.59, 1.25) vs. 0.70 (0.52, 1.01) mmol/L, P < 0.001), TC/HDL-C (3.38 ± 0.81 vs. 3.07 ± 0.69 mmol/L, P < 0.001), and RC/HDL-C (0.35 (0.23, 0.47) vs. 0.30 (0.21, 0.40) U/ml, P < 0.001). The GDM group also exhibited lower levels of TBil, DBil, IBil, and ALT/AST compared to the non-GDM group. There were no significant differences between the groups in terms of pregnancy history, previous miscarriage, AST, BUN, Scr, BUN/Scr, 25(OH)D, Hcy, C4, T3, T4, TSH, and HDL-C (Table 1).

Table 1

Baseline demographic characteristics and laboratory indicators of the study population
Variables	GDM (n = 201)	Non-GDM (n = 996)	t/Z/χ²	P-Value
Age (years)	30.52 ± 4.81	28.70 ± 4.26	4.994	< 0.001
BMI (kg/m²)	22.67 ± 3.41	21.19 ± 3.04	5.714	< 0.001
Pregnancy history			0.931	0.335
Nulliparous	135 (67.2%)	703 (70.6%)
Multiparous	66(32.8%)	293 (29.4%)
Previous miscarriage			7.413	0.060
0	68 (33.8%)	360 (36.1%)
1	79 (39.3%)	403 (40.5%)
2	26(12.9%)	153 (15.4%)
≥ 3	28(13.9%)	80 (8.0%)
SBP (mmHg)	117.51 ± 11.49	115.25 ± 12.03	2.451	0.014
DBP (mmHg)	72.33 ± 9.92	69.85 ± 9.01	3.287	0.001
FBG (mmol/L)	5.14 ± 1.22	4.53 ± 0.81	6.778	< 0.001
UA (µmol/L)	268.16 ± 72.75	248.08 ± 62.55	3.651	< 0.001
TBil (µmol/L)	10.27 ± 4.27	11.45 ± 4.46	3.387	0.004
DBil (µmol/L)	3.90 ± 1.57	4.61 ± 1.97	3.170	0.006
IBil (µmol/L)	6.37 ± 2.99	7.14 ± 3.72	2.769	0.006
ALT (U/L)	15.00 (11.00, 23.00)	14.00 (10.00, 21.75)	2.363	0.018
AST (U/L)	15.00 (13.00, 19.50)	16.00 (13.00, 19.00)	0.541	0.588
ALT/AST	1.06 ± 0.42	1.23 ± 0.60	4.934	< 0.001
BUN (mmol/L)	3.80 ± 1.24	3.67 ± 1.05	1.457	0.145
Scr (µmol/L)	52.12 ± 7.02	51.83 ± 8.24	0.525	0.600
BUN/Scr	73.57 ± 23.23	71.99 ± 21.44	0.942	0.346
25(OH)D (ng/mL)	21.11 ± 7.77	20.80 ± 7.88	0.504	0.614
Hcy (µmol/L)	6.08 ± 1.36	6.28 ± 1.47	1.801	0.072
C3 (mg/dL)	9.98 ± 2.33	9.29 ± 2.00	3.924	< 0.001
C4 (mg/dL)	2.23 ± 0.77	2.12 ± 0.74	1.885	0.060
C1q (g/L)	181.48 ± 30.75	175.60 ± 32.39	1.368	0.018
T3 (pmol/L)	1.70 ± 0.39	1.73 ± 0.38	0.829	0.407
T4 (pmol/L)	118.95 ± 8.40	123.16 ± 27.76	1.955	0.051
TSH (mIU/L)	1.78 (1.18, 2.37)	1.66 (1.04, 2.40)	0.705	0.481
TC (mmol/L)	4.22 ± 0.81	3.89 ± 0.75	5.565	< 0.001
TG (mmol/L)	1.32 ± 0.91	1.03 ± 0.51	4.463	< 0.001
HDL-C (mmol/L)	1.30 ± 0.35	1.31 ± 0.30	0.163	0.871
LDL-C (mmol/L)	2.44 ± 0.66	2.18 ± 0.65	5.111	< 0.001
Non-HDL-C (mmol/L)	2.72 ± 0.83	2.35 ± 0.72	5.803	< 0.001
Non-HDL-C/HDL-C (mmol/L)	2.21 ± 0.87	1.87 ± 0.65	6.326	< 0.001
RC (mmol/L)	0.48 ± 0.27	0.40 ± 0.19	3.758	< 0.001
LDL/HDL-C (mmol/L)	1.99 ± 0.72	1.75 ± 0.65	4.738	< 0.001
TG/HDL-C (mmol/L)	0.86 (0.59, 1.25)	0.70 (0.52, 1.01)	4.467	< 0.001
TC/HDL-C (mmol/L)	3.38 ± 0.81	3.07 ± 0.69	5.129	< 0.001
RC/HDL-C (mmol/L)	0.35 (0.23, 0.47)	0.30 (0.21, 0.40)	3.463	< 0.001
GDM: gestational diabetes mellitus; BMI: body mass index; SBP: systolic blood pressure; DBP: diastolic blood pressure; TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein; LDL-C: low-density lipoprotein; RC: remnant cholesterol; FBG: fasting blood glucose; UA: uric acid; TBil: total bilirubin; DBil: direct bilirubin; IBil: indirect bilirubin; TBA: total bile acid; ALT: alanine transaminase; AST: aspartate aminotransferase; AST/ALT: aspartate aminotransferase-to-alanine transaminase ratio; BUN: blood urea nitrogen; Scr: Serum creatinine; BUN/Scr: blood urea nitrogen to creatinine ratio; 25(OH)D: 25-hydroxyvitamin D; Hcy: homocysteine; C3: complement C3; C4: complement C4; C1q: complement C1q; T3: triiodothyronine; T4: thyroxine; TSH: thyroid stimulating hormone;

3.2 Associated between non-traditional lipid parameters and GDM in pregnancies

In the multivariate regression analysis (Table 2), a positive association was observed between non-traditional lipid parameters and the risk of GDM across all models, except for RC/HDL-C in Model 3, where the P value was 0.050. In the unadjusted model, the OR for GDM were as follows: Non-HDL-C (1.835), Non-HDL-C/HDL-C (1.855), RC (4.785), LDL/HDL-C (1.627), TG/HDL-C (1.865), TC/HDL-C (1.717), and RC/HDL-C (5.628). In the fully adjusted main model (Model 3), which included adjustments for age, BMI, SBP, DBP, C3, C1q, TBil, Dbil, IBil, ALT, AST/ALT, FGB, and UA, the ORs were: Non-HDL-C (1.561, 95% CI: 1.270–1.919; P < 0.001), Non-HDL-C/HDL-C (1.589, 95% CI: 1.279–1.976; P < 0.001), RC (2.205, 95% CI: 1.044–4.659; P = 0.038), LDL/HDL-C (1.476, 95% CI: 1.155–1.887; P = 0.002), TG/HDL-C (1.334, 95% CI: 1.011–1.760; P = 0.042), TC/HDL-C (1.496, 95% CI: 1.190–1.881; P = 0.001), and RC/HDL-C (2.264, 95% CI: 0.999–5.129; P = 0.050).

Table 2

Relationship between different non‑traditional blood lipid parameters levels and gestational diabetes mellitus in different models
	Crude Model		Model 1		Model 2		Model 3
Variable	OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)	P
Non-HDL-C	1.835 (1.509 ~ 2.230)	< 0.001	1.700 (1.395 ~ 2.072)	< 0.001	1.680 (1.374 ~ 2.054)	< 0.001	1.561 (1.270 ~ 1.919)	< 0.001
Non-HDL-C/HDL-C	1.855 (1.521 ~ 2.262)	< 0.001	1.690 (1.369 ~ 2.086)	< 0.001	1.680 (1.359 ~ 2.078)	< 0.001	1.589 (1.279 ~ 1.976)	< 0.001
RC	4.785 (2.436 ~ 9.399)	< 0.001	3.125 (1.555 ~ 6.280)	0.001	2.625 (1.281 ~ 5.376)	0.008	2.205 (1.044 ~ 4.659)	0.038
LDL/HDL-C	1.627 (1.320 ~ 2.006)	< 0.001	1.413 (1.125 ~ 1.774)	0.003	1.476 (1.167 ~ 1.868)	0.001	1.476 (1.155 ~ 1.887)	0.002
TG/HDL-C	1.865 (1.480 ~ 2.351)	< 0.001	1.438 (1.127 ~ 1.835)	0.003	1.392 (1.074 ~ 1.805)	0.012	1.334 (1.011 ~ 1.760)	0.042
TC/HDL-C	1.717 (1.412 ~ 2.088)	< 0.001	1.481 (1.196 ~ 1.834)	< 0.001	1.515 (1.216 ~ 1.887)	< 0.001	1.496 (1.190 ~ 1.881)	0.001
RC/HDL-C	5.628 (2.695 ~ 11.752)	< 0.001	3.009 (1.406 ~ 6.439)	0.005	2.601 (1.193 ~ 5.673)	0.016	2.264 (0.999 ~ 5.129)	0.050
Crude model: adjusted for none.
Model 1: Adjusted for Age, BMI, SBP and DBP.
Model 2: Adjusted for the variables in Model 1 plus C3, C1q, TBil, Dbil, Ibil, ALT and AST/ALT.
Model 3: Adjusted for the variables in Model 2 plus FBG and UA
BMI: body mass index; TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein; LDL-C: low-density lipoprotein; RC: remnant cholesterol; FBG: fasting blood glucose; UA: uric acid; C3: complement C3; C1q: complement C1q; TBil: total bilirubin; DBil: direct bilirubin; IBil: indirect bilirubin; ALT: alanine transaminase; AST/ALT: aspartate aminotransferase-to-alanine transaminase ratio; SBP: systolic blood pressure; DBP: diastolic blood pressure;

3.3 Diagnostic performance of non-traditional lipid parameters in identifying GDM

Table 3 summarizes the diagnostic accuracy of non-traditional lipid parameters in distinguishing GDM from non-GDM cases. The AUC was highest for Non-HDL-C at 0.640, with a sensitivity of 56.7% and specificity of 69.2%. Other lipid parameters showed lower AUCs: Non-HDL-C/HDL-C at 0.617, RC at 0.580, LDL/HDL-C at 0.607, TG/HDL-C at 0.600, TC/HDL-C at 0.623, and RC/HDL-C at 0.577, the latter being the lowest.

Table 3

Results of ROC analysis for non-traditional blood lipid parameters predicting the development of gestational diabetes mellitus
Variables	AUC (95% CI), %	Specificity (%)	Sensitivity (%)	PPV (%)	NPV (%)	Youden index	Cutoff
Non-HDL-C	64.0 (59.6 ~ 68.4)	69.2	56.7	26.8	88.7	0.259	2.620
Non-HDL-C/HDL-C	61.7 (57.2 ~ 66.2)	78.1	46.8	27.5	86.5	0.219	2.220
RC	58.0 (53.5 ~ 62.6)	70.7	46.3	23.8	87.4	0.17	0.480
LDL/HDL-C	60.7 (56.5 ~ 65.0)	54.2	663.2	30.0	85.2	0.174	1.699
TG/HDL-C	60.0 (55.6 ~ 64.4)	50.4	66.7	22.7	88.2	0.171	0.701
TC/HDL-C	62.3 (58.0 ~ 66.5)	66.2	54.2	24.4	84.5	0.204	3.219
RC/HDL-C	57.7 (53.2 ~ 62.3)	69.6	46.3	21.6	86.5	0.159	0.372
TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein; LDL-C: low-density lipoprotein; RC: remnant cholesterol; AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value; ROC: receiver operating characteristic;

3.4 Nonlinear relationship between non-traditional blood lipid parameters and GDM

After adjusting for multiple covariates, the relationship between Non-HDL-C and GDM showed a nonlinear association (P for non-linearity = 0.005) in restricted cubic spline (RCS) analysis. In the threshold analysis, the OR for GDM was 3.069 (95% CI 2.015–4.676, P < 0.001) among participants with a Non-HDL-C level between 1.956 and 3.76. Notably, there was no association between Non-HDL-C and GDM when the Non-HDL-C level was below 1.956 or above 3.76 (Table 4). In contrast, other non-traditional blood lipid parameters exhibited linear associations, with P-values for non-linearity as follows: Non-HDL-C/HDL-C (0.586), RC (0.42), LDL/HDL-C (0.392), TG/HDL-C (0.865) and TC/HDL-C (0.425), as illustrated in Fig. 1.

Table 4

Threshold effect analysis of Non-HDL-C and gestational diabetes mellitus
	OR	95% CI	P-Value
Non-HDL-C < 1.956	0.73	0.157 ~ 3.39	0.688
3.76 > Non-HDL-C ≥ 1.956	3.069	2.015 ~ 4.676	< 0.001
Non-HDL-C ≥ 3.76	25.84	0.687 ~ 971.336	0.079
Likelihood Ratio test			0.176
Notes: Data presented are HRs and 95% CIs.
Adjusted for age, BMI, SBP, DBP, C3, C1q, TBil, Dbil, Ibil, ALT, AST/ALT, FBG and UA.
BMI: body mass index; HDL-C: high-density lipoprotein; FBG: fasting blood glucose; UA: uric acid; C3: complement C3; C1q: complement C1q; TBil: total bilirubin; DBil: direct bilirubin; IBil: indirect bilirubin; ALT: alanine transaminase; AST/ALT: aspartate aminotransferase-to-alanine transaminase ratio; SBP: systolic blood pressure; DBP: diastolic blood pressure;

3.5 Subgroup analyses

The stratified analyses of the associations between non-traditional lipid parameters and GDM are shown in Fig. 2. Across different subgroups, including age, SBP, DBP, BMI, FBG, and UA, most non-traditional lipid parameters showed no significant association with GDM. However, BMI demonstrated significant interactions with RC in relation to GDM, while age showed significant interactions with LDL/HDL-C in relation to GDM.

3.6 Relationship between fasting, 1-hour, or 2-hour blood glucose levels and the non-traditional blood lipid parameters in patients with GDM

Among the 201 patients with GDM, OGTT results showed that 114 had a single positive result, 62 had double positives, and 25 had triple positive results. Scatter plots revealed a strong positive correlation between fasting blood glucose and several lipid ratios: Non-HDL-C/HDL-C (r = 0.185, P = 0.008), LDL/HDL-C (r = 0.161, P = 0.022), TG/HDL-C (r = 0.197, P = 0.005), TC/HDL-C (r = 0.196, P = 0.005), and RC/HDL-C (r = 0.162, P = 0.021). No significant correlations were observed between Non-HDL-C or RC with fasting blood glucose. Furthermore, no significant correlations were found between any non-traditional lipid parameters and 1-hour or 2-hour blood glucose levels (Table 5). Bar graphs showed no significant differences in non-traditional lipid parameters among the single, double, and triple positive groups (P < 0.05) (Fig. 3).

Table 5

The relationship between non‑traditional blood lipid parameters and various glycemic parameters measured by the OGTT
Variables	fasting blood glucose		1-hour blood glucose		2-hour blood glucose
	r	P	r	P	r	P
Non-HDL-C	0.050	0.478	-0.020	0.773	-0.047	0.503
Non-HDL-C/HDL-C	0.185	0.008*	-0.036	0.615	-0.074	0.298
RC	0.092	0.196	-0.067	0.347	-0.098	0.168
LDL/HDL-C	0.161	0.022*	0.019	0.790	-0.052	0.460
TG/HDL-C	0.197	0.005*	0.000	0.997	-0.071	0.313
TC/HDL-C	0.196	0.005*	-0.007	0.919	-0.085	0.229
RC/HDL-C	0.162	0.021*	-0.075	0.292	-0.119	0.092
TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein; LDL-C: low-density lipoprotein; RC: remnant cholesterol; * P < .05;

3.7 Relationship between neonatal birth weight and the non-traditional blood lipid parameters

Pearson correlation analysis examined the relationship between neonatal birth weight and non-traditional blood lipid parameters. For the entire cohort, a weak positive correlation was observed with LDL/HDL-C (r = 0.060, P = 0.037). In the GDM subgroup, Non-HDL-C showed a negative correlation (r = -0.167, P = 0.018). In the non-GDM subgroup, both LDL/HDL-C (r = 0.070, P = 0.026) and TC/HDL-C (r = 0.067, P = 0.034) showed weak positive correlations (Table 6).

Table 6

The relationship between non‑traditional blood lipid parameters and various glycemic parameters measured by the OGTT
Variables	All participants		GDM		Non-GDM
	r	P	r	P	r	P
Non-HDL-C	-0.056	0.051	-0.167	0.018*	-0.023	0.467
Non-HDL-C/HDL-C	0.001	0.984	-0.048	0.498	0.022	0.496
RC	-0.031	0.289	-0.084	0.238	-0.010	0.763
LDL/HDL-C	0.060	0.037*	0.041	0.566	0.070	0.026*
TG/HDL-C	-0.033	0.259	-0.029	0.684	-0.029	0.355
TC/HDL-C	0.055	0.059	0.031	0.664	0.067	0.034*
RC/HDL-C	-0.006	0.837	-0.017	0.809	0.003	0.925
TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein; LDL-C: low-density lipoprotein; RC: remnant cholesterol; GDM: gestational diabetes mellitus; * P < .05;

The prevalence of GDM is highest in the South-East Asia Region at 25.0%, while it is 10.4% in the North America and Caribbean Region [16]. GDM is associated with increased risks of preeclampsia, macrosomia, perinatal complications, and mortality. Therefore, in East Asia, it is crucial to highlight the importance of early detection and management. Although older maternal age and specific ethnicities are known high-risk factors for GDM [17], numerous studies have shown that blood lipid levels also play a critical role in the development of GDM [18–20]. Lipid levels rise slightly in early pregnancy and significantly in later stages [21, 22], These changes in lipid metabolism promote maternal fat accumulation in early and mid-pregnancy, allow fat mobilization as an energy source in late pregnancy, and facilitate lipid transport across the placenta [23], If these adaptive changes exceed a certain threshold, GDM can develop.

Recent studies suggest that non-traditional lipid parameters may serve as simple, reliable, and cost-effective indicators for assessing metabolic diseases (MS) [14, 24]. Zhang et al. [14] found that TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, and non-HDL-C were associated with MS (all P < 0.05). The odds ratios were 4.075 (0.891, 1.107), 3.121 (1.844, 5.282), 3.106 (1.734, 5.561), and 2.238 (1.302, 3.848), respectively, suggesting these are effective predictors of MS in polycystic ovary syndrome (PCOS). Similarly, Golabi et al. [25] revealed that non-traditional lipids (TG/HDL-C, TC/HDL-C) are associated with cardiometabolic risk factors in patients with T2D. Consistent with previous studies, our research showed that all the first-trimester parameters, except RC/HDL-C, were effective indicators for predicting GDM. Among the seven indicators, Non-HDL-C had the best predictive performance, with a sensitivity of 56.7% and specificity of 69.2% in predicting GDM. Although the p-value of RC/HDL-C with GDM was 0.05 after full adjustment, showing no significant difference in our study, other studies have shown that the RC/HDL-C ratio is the best lipid parameter for reflecting diabetes risk (HR: 6.75, 95% CI 2.40-18.98) [26].

The mechanisms of non-traditional lipid profiles are unclear and speculative. One hypothesis is that increased insulin resistance reduces lipoprotein lipase activity, preventing the adequate hydrolysis of very low-density lipoprotein, leading to elevated LDL and TG levels [27, 28]. This suggests that comprehensive lipid indices may better predict GDM risk than single indices. Additionally, because Non-HDL-C includes all apolipoprotein-B-containing lipoproteins, this hypothesis explains why Non-HDL-C is the best predictor of GDM among the seven parameters. Further large-scale research is needed to investigate the specific mechanisms involved.

Our investigation revealed a significant positive correlation between most non-traditional lipid parameters and fasting blood glucose levels, but no discernible association with 1-hour and 2-hour blood glucose levels. These results suggest that non-traditional lipids could potentially serve as biomarkers for isolated impaired fasting glucose (hepatic insulin resistance and inadequate insulin secretion), rather than impaired glucose tolerance.

The maternal lipid profile is associated with fetal growth and neonatal birth weight during pregnancy [29–31]. Clinck Isabel et al. [30] reported that for each 1 mmol/L increment in triglycerides, birth weight increased significantly by 81.7 g, indicating a positive correlation between TG levels and neonatal birth weight. Similarly, our study found positive correlations between LDL/HDL-C and TC/HDL-C with neonatal birth weight in the non-GDM group. Notably, in the GDM subgroup, Non-HDL-C showed a negative correlation with neonatal birth weight. This may be attributed to not excluding preterm infants and not adjusting for confounding factors such as gestational weight gain, lifestyle, and dietary control during pregnancy [32, 33].

This study has several limitations that should be considered. First, its retrospective design and restriction to a single center may limit the generalizability of the findings. Second, blood lipid levels were measured only once during early pregnancy, without subsequent monitoring, potentially missing fluctuations in non-traditional lipid parameters throughout gestation. Third, the study lacks data on lifestyle factors, economic status, dietary habits, physical activity, and sleep patterns, which could act as confounders and influence the results. Further research is needed to explore the mechanisms linking non-traditional lipid parameters and GDM, including the roles of adipokines, oxidative stress, inflammation, and insulin resistance.

In conclusion, our study identifies that elevated first-trimester non-traditional blood lipid parameters, including Non-HDL-C, Non-HDL-C/HDL-C, RC, LDL/HDL-C, TG/HDL-C, and TC/HDL-C, are independent predictors of GDM. Although no significant differences were found in these lipid parameters among the single, double, and triple positive groups, a positive correlation was observed between Non-HDL-C/HDL-C, LDL/HDL-C, TG/HDL-C, TC/HDL-C, RC/HDL-C, and fasting blood glucose levels in GDM patients. These findings suggest that first-trimester non-traditional lipid parameters could be useful in predicting GDM early in pregnancy. However, further research is needed to fully establish the prognostic value of these lipid parameters for early GDM risk prediction.

GDM Gestational diabetes mellitus

TC Cholesterol

TG Triglycerides

LDL-C Low-density lipoprotein cholesterol

HDL-C High-density lipoprotein cholesterol

OGTT Oral glucose tolerance test

Conflict of interest

The authors declare that they have no competing interests.

Consent for publication

Before participating in the study, all participants signed up with informed permission.

Ethics approval and consent to participate

This study was reviewed and approved by the Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University. The patients/participants provided written informed consent to participate in this study.

Funding

This work was supported by Foundation of Wenzhou Municipal Health Commission (2020041)

Author Contribution

Junmiao Xiang: Conceptualization, Methodology, Software, Investigation, Formal Analysis, Funding Acquisition, Writing - Original Draft; Ruru Bao: Data Curation, Writing - Original Draft; Yundong Pan: Visualization, Validation, Writing - Original Draft; Zhuhua Cai: Conceptualization, Resources, Supervision, Writing - Review & Editing.

Acknowledgement

The authors thank the Department of Gynecology of The Third Affiliated Hospital of Wenzhou Medical University, for their continuous support during the study

Data Availability

Data available on request from the authors

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Correlation between the first-trimester non-traditional lipid parameters with the risk of gestational diabetes mellitus in pregnancy

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Abstract

Figures

1. Introduction

2. Material and Methods

2.1 Patient Population

2.2 Clinical features record

2.3 Biochemical indicators measurements

2.4 Immune and endocrine biomarker measurements

2.5 Calculation formulas of related parameters

2.6 Statistical analysis

3. Results

3.1 Baseline Clinical and Laboratory Characteristics of Study Participants

3.2 Associated between non-traditional lipid parameters and GDM in pregnancies

3.3 Diagnostic performance of non-traditional lipid parameters in identifying GDM

3.4 Nonlinear relationship between non-traditional blood lipid parameters and GDM

3.5 Subgroup analyses

3.7 Relationship between neonatal birth weight and the non-traditional blood lipid parameters

4. Discussion

5. Conclusion

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Funding

Author Contribution

Acknowledgement

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