Evidence map›Paper›PMID 39586851›Full record

ArticleDiscover oncology2024

Genetic insights into blood protein correlations with colorectal cancer: a Mendelian randomization study.

Wenjing Xu, Wei Li, Yaqiang Li, Dayu Kuai, Wei Sun, Xian Liu, Baohong Xu

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Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Wenjing XuDepartment of Gastroenterology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 100000, China.
Wei LiDepartment of Gastroenterology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 100000, China.
Yaqiang LiDepartment of Gastroenterology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 100000, China.
Dayu KuaiDepartment of Gastroenterology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 100000, China.
Wei SunDepartment of Gastroenterology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 100000, China.
Xian LiuDepartment of Gastroenterology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 100000, China.
Baohong XuDepartment of Gastroenterology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 100000, China. bhxu22@ccmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral blood proteins might be associated with the development of colorectal cancer (CRC), but many studies on this topic are often biased. By using genetic variation data, which is less influenced by environmental factors, we can better determine the causal relationship between specific blood proteins and the occurrence of colorectal cancer.

methodsData from a genome-wide association study (GWAS) on blood proteins, encompassing 1,478 proteins, and colorectal cancer (CRC) GWAS data, covering 637,693 subjects, were collected and organized. Additionally, GWAS data for obesity, diabetes mellitus (DM), and smoking were obtained for further analysis. Single nucleotide polymorphisms (SNPs) significantly associated with the exposure factors (blood proteins) were selected to ensure their independence from other confounding factors and outcomes (CRC onset), and that they only affected outcomes through blood proteins. The causal effects of Mendelian Randomization (MR) were primarily estimated using the inverse variance weighted (IVW) method, with other methods serving as supplementary approaches. The Cochran's Q-test assessed heterogeneity among SNP estimates; the MR Egger method evaluated pleiotropy; and the leave-one-out test examined the sensitivity of individual SNPs. Obesity, DM, and smoking were included in the multivariate MR analysis.

resultA total of 31 SNPs and 8 blood protein exposure factors were identified, specifically TNFRSF16 (4 SNPs), RNF8 (4 SNPs), MRM3 (4 SNPs), ST6GALNAC1 (4 SNPs), TIE1 (4 SNPs), CBP (4 SNPs), DNAJB9 (4 SNPs), and EDN2 (3 SNPs). The IVW results showed a significant causal relationship between all 8 exposure factors and colorectal cancer (P < 0.05). Among these, TNFRSF16, TIE1, and EDN2 were identified as risk factors, while the remaining five served as protective factors. The causal inference in this study was not influenced by pleiotropy or environmental factors such as obesity, diabetes, and smoking. Therefore, the results were both stable and reliable.

conclusionEight blood proteins (or genes) have been identified as having a causal relationship with the onset of colorectal cancer, suggesting their potential use as screening biomarkers and treatment targets.

Indexed as

Blood proteinsCausal relationshipColorectal cancerGenetic variationScreening biomarkersTreatment targets

Identifiers

PMID39586851
PMCPMC11589031

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.