Epigenetic role of LINE-1 methylation and key genes in pregnancy maintenance

Abstract

Spontaneous abortion is a pregnancy complication characterized by complex and multifactorial etiology. About 5% of childbearing women are globally affected by early pregnancy loss (EPL) and most of them experience recurrence (RPL). Epigenetic mechanisms and controlled inflammation are crucial for pregnancy maintenance and genetic predispositions may increase the risk affecting the maternal-fetal crosstalk. Combined analyses of global methylation, inflammation and inherited predispositions may contribute to define pregnancy loss etiopathogenesis. LINE-1 epigenetic regulation plays crucial roles during embryo implantation, and its hypomethylation has been associated with senescence and several complex diseases. By analysing a group of 230 women who have gone through pregnancy interruption and comparing those experiencing spontaneous EPL (n = 123; RPL, 54.5%) with a group of normal pregnant who underwent to voluntary interruption (VPI, n = 107), the single statistical analysis revealed significant lower (P < 0.00001) LINE-1 methylation and higher (P < 0.0001) mean cytokine levels (CKs: IL6, IL10, IL17A, IL23) in EPL. Genotyping of the following SNPs accounted for different EPL/RPL risk odds ratio: F13A1 rs5985 (OR = 0.24; 0.06-0.90); F13B rs6003 (OR = 0.23; 0.047-1.1); FGA rs6050 (OR = 0.58; 0.33-1.0); CRP rs2808635/rs876538 (OR = 0.15; 0.014-0.81); ABO rs657152 (OR = 0.48; 0.22-1.08); TP53 rs1042522 (OR = 0.54; 0.32-0.92); MTHFR rs1801133/rs1801131 (OR = 2.03; 1.2-3.47) and FGB rs1800790 (OR = 1.97; 1.01-3.87), although Bonferroni correction did not reach significant outputs. Principal Component Analysis (PCA) and logistic regression disclosed further SNPs positive/negative associations (e.g. APOE rs7412/rs429358; FGB rs1800790; CFH rs1061170) differently arranged and sorted in four significant PCs: PC1 (F13A, methylation, CKs); PC3 (CRP, MTHFR, age, methylation); PC4 (F13B, FGA, FGB, APOE, TP53, age, methylation); PC6 (F13A, CFH, ABO, MTHFR, TP53, age), yielding further statistical power to the association models. In detail, positive EPL risk association was with PC1 (OR = 1.81; 1.33-2.45; P < 0.0001) and negative associations with PC3 (OR = 0.489; 0.37-0.66; P < 0.0001); PC4 (OR = 0.72; 0.55-0.94; P = 0.018) and PC6 (OR = 0.61; 0.46-0.81; P = 0.001). Moreover, significant inverse associations were detected between methylation and CKs levels in the whole group (r_IL10 = - 0.22; r_IL17A = - 0.25; r_IL23 = - 0.19; r_IL6 = - 0.22), and methylation with age in the whole group, EPL and RPL subgroups (r²_TOT = 0.147; r²_EPL = 0.136; r² _RPL = 0.248), while VPI controls lost significance (r²_VPI = 0.011). This study provides a valuable multilayer approach for investigating epigenetic abnormalities in pregnancy loss suggesting genetic-driven dysregulations and anomalous epigenetic mechanisms potentially mediated by LINE-1 hypomethylation. Women with unexplained EPL might benefit of such investigations, providing new insights for predicting the pregnancy outcome and for treating at risk women with novel targeted epidrugs.

Keywords: Cytokines; Epidrugs, LINE-1 methylation; Epigenetics; Epigenomics; Inflammation; Pregnancy maintenance; Retrotransposons; Spontaneous miscarriage.

Figure 1

Methylation-age correlation analysis. (a) Correlation between methylation and age distribution in the whole cohort stratified by VPI controls (green dots) and EPL cases (red dots). Regression lines are shown (green line and red line for VPI controls and EPL respectively). (b) Correlation between methylation and age distribution in the EPL group stratified by single event (non-recurrent) cases (sEPL, grey dots) and recurrent EPL (RPL, dark dots). Regression lines are shown (continuous and dotted line for RPL and sEPL respectively). Each panel shows the r²-coefficient for the regression lines.

Figure 2

CKs levels distribution. Circulating IL6 (a), IL10 (b), IL17A (c) and IL23 (d) levels in VPI controls and EPL cases. Box plots show median and IQR. P values are indicated on top of each panel.

Figure 3

Pearson correlation heatmap between methylation and CKs in the whole group. Red and green indicate a positive and a negative association, respectively. Colour intensity represents the strength of the correlation.

Figure 4

Principal component analysis result for the computed 18 variables: PC1, PC2 and PC3 loadings. Abbreviations: CRP_1 (rs876538); CRP_2 (rs2808635); MTHFR_1 (rs1801133); MTHFR_2 (rs1801131); APOE (rs7412/rs429358) accounts for ε3/ε4 haplotypes; Methyl: methylation. Plotted by SPSS (Statistics Version 22).

Figure 5

3D-loading plot of the scores of the whole cohort (n = 230) based on PC1, PC2 and PC3. Red dots: n = 123 EPL; green dots: n = 107 VPI controls. Plotted by bioinformatics.com.cn/srplot.