Unveiling the Causal Links Between Lipid Traits and Pregnancy Complications

Pregnancy complications often pose significant risks to both maternal and fetal health. Among these complications, preeclampsia, gestational diabetes mellitus (GDM), and intrahepatic cholestasis of pregnancy (ICP) are particularly prevalent. These conditions have substantial negative impacts, yet their underlying mechanisms remain poorly understood.

The Importance of Understanding Lipid Traits in Pregnancy

Recent research highlights the role of dyslipidemia in these conditions. Studies show that total cholesterol (TC) and triglyceride (TG) levels are elevated in both preeclampsia and GDM. Additionally, lower high-density lipoprotein cholesterol (HDL-C) levels correlate with higher incidences of preeclampsia and GDM. Patients with ICP exhibit elevated TC, TG, and low-density lipoprotein cholesterol (LDL-C) compared to healthy pregnant women.

The Potential Benefits of Lipid-Modifying Drugs

Exploring the potential benefits of lipid-modifying drugs for affected individuals is gathering interest. Currently, several drugs are popular, including statins, cholesterol absorption inhibitors, bile acid sequestrants, niacin, fibrates, omega-3 fatty acids, and their derivatives. Statins, which reduce LDL-C levels and exhibit anti-inflammatory properties, are the most commonly used.

Statin use in preeclampsia has shown mixed results, with some early reports indicating improved outcomes, while a more recent study found potential harm. This discrepancy underscores the need for further investigation into the efficacy of these drugs in managing pregnancy complications.

Mendelian Randomization Approach

To explore these research gaps and inconsistencies, a study used a two-sample Mendelian Randomization (MR) approach. This method uses genetic variants as instrumental variables to establish stronger causal evidence by minimizing confounding factors and reverse causation. MR provides a more robust way to clarify causal relationships than traditional observational studies.

The study aimed to examine the causal relationships between lipid traits and the incidence of preeclampsia, GDM, and ICP. It also assessed how lipid-modifying drug targets could inform clinical strategies. These findings could offer valuable insights for developing targeted and effective treatments to prevent and manage pregnancy complications.

Study Design and Methodology

The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology-Mendelian Randomization (STROBE-MR) framework. All studies had been approved by relevant institutional review boards and participants had provided informed consent.

Data sources included GWAS data for lipid levels from the Global Lipids Genetics Consortium and GWAS data for the three diseases — preeclampsia, GDM, and ICP — from the FinnGen consortium.

Genetic instrumental variable selection focused on drug target genes significantly associated with pregnancy complications, using eQTL data from the eQTLGen Consortium and the Genotype-Tissue Expression project. Summary-data-based MR (SMR) analysis further validated these drug targets.

Statistical analysis involved the inverse-variance weighted MR method, adjusting odds ratios to reflect a 1-mmol/L change in genetically predicted lipid levels. Multiple testing was adjusted using the Benjamini-Hochberg false-discovery rate (FDR) procedure.

Sensitivity analyses included weighted median and MR-Egger regression to test the robustness of the IVW-MR analysis. Cochran’s Q test, MR-PRESSO, and MR-Egger intercepts were used to assess heterogeneity and detect potential pleiotropy.

Results

Causal Effect of Lipid Traits on Pregnancy Complications

Sensitivity analyses including MR Egger and weighted median methods provided evidence for the robustness of the results. Leave-one-out analysis also confirmed the robustness, demonstrating no single SNP disproportionately influenced the overall causal estimates. The MR-Egger test and MR-PRESSO confirmed no pleiotropies in this MR analysis.

A significant association was found between increased HDL-C levels and reduced risks of preeclampsia and GDM, indicating each unit increase in HDL-C was linked to a 24.5% lower risk of preeclampsia and a 16.5% lower risk of GDM. Lower HDL-C levels in observational studies align with this finding.

Causal Effect of Lipid-Modifying Drug Targets on Pregnancy Complications

The drug-target MR analysis indicated that genetic proxies for CETP inhibition were associated with a reduced risk of preeclampsia. Genetic enhancement of LPL showed a significant reduced risk of GDM. However, no causal relationship was found between genetic mimicries of other drug targets and ICP.

Further analyses using weighted median and MR-Egger methods consistently supported these findings, indicating robust causal associations. Genetic proxies of HMGCR inhibition were associated with an increased risk of preeclampsia.

Summary-Data-Based Mendelian Randomization (SMR) Analysis

SMR analysis with genetic variations associated with CETP, HMGCR, and LPL expression further validated their unique associations with the risks of preeclampsia and GDM. Higher LPL expression in subcutaneous adipose tissue was linked to a reduced risk of GDM.

Mediation Analysis

Mediation analysis revealed that the WHRadjBMI and WC were likely to partially mediate LPL enhancement on the reduced risk of GDM. This mediation effect accounted for approximately 5.7% and 4.2% through WHRadjBMI and WC, respectively.

Discussion

This MR study provides convincing evidence of causal relationships between lipid traits and pregnancy complications, highlighting potential therapeutic targets in preeclampsia and GDM. Understanding these pathophysiological relationships can guide therapeutic interventions.

The study found a significant association between increased HDL-C levels and reduced risks of preeclampsia and GDM, supporting the role of HDL-C in vascular health and inflammation reduction.

CETP inhibition shows promise in reducing the risk of preeclampsia, while genetic enhancement of LPL appears protective against GDM. The study cautions against HMGCR inhibition, linked to increased risk of preeclampsia.

Further research is needed to fully elucidate the underlying mechanisms and validate these findings in diverse populations.

Conclusion

The study provides novel insights into the causal relationships between lipid traits and pregnancy complications, highlighting potential therapeutic targets. Elevated HDL-C and genetic inhibition of CETP show promise in reducing the risk of preeclampsia, while LPL enhancement appears protective against GDM. These findings indicate potential for lipid-targeting interventions to improve maternal and fetal health.

Abbreviations

LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; TC, total cholesterol; HDL-C, high density lipoprotein cholesterol; HMGCR, HMG-CoA reductase; NPC1L1, Niemann-Pick C1-like protein 1; PCSK9, proprotein convertase subtilisin/kexin type 9; ABCG5, ATP Binding Cassette Subfamily G Member 5; ABCG8, ATP Binding Cassette Subfamily G Member 8; APOB, Apolipoprotein B-100; LDLR, LDL Receptor; ANGPTL3, angiopoietin-like 3; APOC3, Apolipoprotein C-III; LPL, lipoprotein lipase; CETP, cholesteryl ester transfer protein; BMI, body mass index; WHR, waist-to-hip ratio; WHRadjBMI, WHR adjusted for BMI; WC, waist circumference; HC, hip circumference; GDM, gestational diabetes mellitus; and ICP, intrahepatic cholestasis of pregnancy; FDR, false discovery rate; SMR, summary-data-based Mendelian Randomization.

Figure 2 Association of four lipid traits with the risk of pregnancy complications in IVW-MR analysis. (A) The forest plot shows the correlation between the four lipid traits and the risk of preeclampsia; (B) and risk of GDM; (C) and risk of ICP; (D) Scatter plot showing the correlation between the effects of SNPs on HDL-C level and the effects of SNPs on preeclampsia; (E) Scatter plot showing the correlation between the effects of SNPs on HDL-C level and the effects of SNPs on GDM.

Figure 3 Association of nine drug targets with the risk of pregnancy complications in IVW-MR analysis. (A) The forest plot shows the correlation between a 1-mmol/L alteration in the lipid levels of ten lipid-modifying drug targets and the risk of preeclampsia; (B) and risk of GDM; (C) and risk of ICP.

Figure 4 Mediation analysis of the effect of LPL on GDM via potential mediators. (A) LPL effect on GDM mediated by WC; (B) LPL effect on GDM mediated by WC. Abbreviations: βEM, effects of exposure on mediator; βMO, effects of mediator on outcome; βEO, effects of exposure on outcome.

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