Lipid Targets for Benign Colon Neoplasm through Mendelian Randomization Analysis

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Abstract

Background: Colon neoplasm (CN) is a complex disease, and a variety of therapies have been developed and widely used to treat colon neoplasm. However, colon neoplasm is usually diagnosed at an advanced stage, making the prognosis worse. Benign colon neoplasm (BCN) often has serious health consequences and is prone to transformation into malignancy. Therefore, it is essential to explore novel targets for CN, including BCN. The human lipidome is currently a primary therapeutic intervention. In contrast to conventional lipids, a recent study has meticulously categorized lipids into 179 variations across 13 distinct categories. This refined classification promises enhanced disease risk evaluation and is anticipated to result in the availability of more precise resources. Nevertheless, additional research is needed to delve deeper into the connection between lipids and BCN. Methods: To assess the causal association between lipids and BCN, we conducted a Mendelian randomization (MR) study utilizing genetic variants as an instrumental variable, with plasma lipids as exposure and BCN as an outcome. Sensitivity analyses were performed to detect heterogeneity and horizontal pleiotropy, and causal direction detection techniques were used to assess the potential causal relation of lipids with BCN. Primary findings were validated using a GWAS dataset derived from the UK Biobank. Finally, colocalization and multivariable Mendelian randomization (MVMR) analyses were conducted to further identify significant targets associated with BCN. Results: In this study, the MR analysis revealed that five out of 179 lipids were significantly associated with BCN at the Bonferroni significance criterion ( P < 2.79 × 10 -4 ), including phosphatidylcholine (20:4_0:0) levels, phosphatidylcholine (16:0_20:4) levels, phosphatidylcholine (18:0_20:5) levels, phosphatidylcholine (O-16:0_20:4) levels and phosphatidylethanolamine (18:0_18:2) levels. The significant causal relationship was ensured by heterogeneity, horizontal pleiotropy, and direction detection analyses. Furthermore, an external validation MR analysis confirmed the consistency of a significant potential causal effect between levels of phosphatidylcholine (16:0_20:4) and phosphatidylcholine (O-16:0_20:4) with BCN ( P < 0.05). Finally, colocalization analysis and multivariable MR analysis ultimately determined that elevated phosphatidylcholine (16:0_20:4) levels contribute to the risk of BCN. Conclusions: Phosphatidylcholine (16:0_20:4) levels positively contribute to BCN and are potential lipid targets in colon tumors. The research identified these lipid biomarkers causally associated with BCN risk, offering new insights into its causes and promising directions for discovering biomarkers and effective medications.

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