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. 2023 Dec 20:14:1291445.
doi: 10.3389/fendo.2023.1291445. eCollection 2023.

Assessment of causal association between differentiated thyroid cancer and disordered serum lipid profile: a Mendelian randomization study

Qiang Ma  1 , Yu Li  1 , Lijuan An  1 , Liang Guo  1 , Xiaokang Liu  1
Affiliations

Assessment of causal association between differentiated thyroid cancer and disordered serum lipid profile: a Mendelian randomization study

Qiang Ma et al. Front Endocrinol (Lausanne). .

Abstract

Background: Research has shown that the disordered serum lipid profile may be associated with the risk of differentiated thyroid cancer (DTC). Whether this association reflect causal effect is still unclear. The aim of this study was to evaluate the causality of circulating lipoprotein lipids on DTC.

Methods: Mendelian randomization (MR) analysis was conducted to evaluate the relationship between the circulating lipoprotein lipids and DTC risk using single-nucleotide polymorphisms (SNPs) from a genome-wide association (GWA) study containing a high-incidence Italian population of 690 cases samples with DTC and 497 controls.

Results: Univariate and multivariate mendelian randomization analysis demonstrated that 'total cholesterol', 'HDL cholesterol', 'apolipoprotein B' and 'ratio of apolipoprotein B to apolipoprotein A1' were correlated with DTC. According to sensitivity analysis, our results were reliable. Furthermore, multivariate analysis revealed that there is no causative association between DTC and any of the many cause factors when they interact with one another, suggesting that there was a deep interaction between the four factors, which could affect each other. Finally, the mechanism of the related effects each other as well as the target genes with significant SNP regulatory effects in DTC was explored by conducting functional enrichment analysis and constructing the regulatory networks.

Conclusions: We obtained four exposure factors (total cholesterol, HDL cholesterol, apolipoprotein B and ratio of apolipoprotein B to apolipoprotein A1) closely related to DTC, which laid a theoretical foundation for the treatment of DTC.

Keywords: Mendelian randomization; differentiated thyroid cancer; disordered serum lipid profile; exposure factors; single-nucleotide polymorphisms.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of this study.
Figure 2
Figure 2
Scatter plots of Mendelian randomization (MR) analysis for the relationship of six exposure factors (total cholesterol, LDL cholesterol, HDL cholesterol, apolipoprotein A, apolipoprotein B, and ratio of apolipoprotein B to apolipoprotein A1) and outcomes (thyroid cancer). The X-axes show the SNP-exposure effect and the Y-axes show the SNP-outcome effect. The inverse variance weighted method is mainly concerned. The small intercept indicates that the analysis is less affected by confounding factors to ensure reliability. The slope of each line shows the estimated causal effect of cholesterol-related factor on thyroid cancer, where a positive slope reflects a positive link with the risk of thyroid cancer (risk factor), and a negative slope reflects a reverse causality (protective factor).
Figure 3
Figure 3
Forest plots of Mendelian randomization analysis for the relationship of six exposure factors and thyroid cancer combining a Wald ratio method for each SNP effect (horizontal black solid line) and inverse variance weighted for fixed-effects (horizontal red solid line). The solid line completely on the left side of 0 indicates that this SNP estimates that exposure factors can reduce the risk of disease, the solid line completely on the right side of 0 indicates that this SNP estimates that exposure factors can increase the risk of disease, and the results of those crossing 0 are not significant.
Figure 4
Figure 4
Funnel plots of Mendelian randomization (MR) analysis for six exposure factors. The SNPs are symmetrically distributed along both sides of the inverse variance weighted line, indicating MR links to Mendel’s second law.
Figure 5
Figure 5
Forest plot of the leave-one-out (LOO) test for sensitivity tests. Calculate the Mendelian randomization (MR) results of the remaining SNPs after removing the SNPs one by one. The smooth black dot line reflects the robustness of the MR results.
Figure 6
Figure 6
Forest plot for multivariable Mendelian randomization analyses by adjusting four exposure factors associated to the probability of thyroid cancer (“total cholesterol”, “HDL cholesterol”, “apolipoprotein B”, and “ratio of apolipoprotein B to apolipoprotein A1”) together for the risk of thyroid cancer. OR, odds ratio; CI, confidence intervals. According to the P-values of four factors, which had no significance.
Figure 7
Figure 7
Gene Ontology analysis of the target genes. (A) ieu-b-4843: HDL cholesterol. (B) met-d-ApoB_by_ApoA1: ratio of apolipoprotein B to apolipoprotein A1. (C) met-d-Total_C: total cholesterol. (D) ukb-d-30640_raw: apolipoprotein B.
Figure 8
Figure 8
Kyoto Encyclopedia of Genes and Genomes enrichment analysis of the target genes. (A) ieu-b-4843: HDL cholesterol. (B) met-d-ApoB_by_ApoA1: ratio of apolipoprotein B to apolipoprotein A1. (C) met-d-Total_C: total cholesterol. (D) ukb-d-30640_raw: apolipoprotein B.
Figure 9
Figure 9
Protein–protein interaction network of target genes and identity of core key genes. (A) ieu-b-4843: HDL cholesterol. (B) met-d-ApoB_by_ApoA1: ratio of apolipoprotein B to apolipoprotein A1. (C) met-d-Total_C: total cholesterol. (D) ukb-d-30640_raw: apolipoprotein B.
Figure 10
Figure 10
Prediction of the transcription factor networks targeting key genes. (A) ieu-b-4843: HDL cholesterol. (B) met-d-ApoB_by_ApoA1: ratio of apolipoprotein B to apolipoprotein A1. (C) met-d-Total_C: total cholesterol. (D) ukb-d-30640_raw: apolipoprotein B.
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