Microbiome and its implications in oncogenesis: a Mendelian randomization perspective

Abstract

The human microbiome, an intricate ecological network, has garnered significant attention due to its potential implications in oncogenesis. This paper delves into the multifaceted relationships between the microbiome, its metabolites, and cancer development, emphasizing the human intestinal tract as the primary microbial habitat. Highlighting the potential causative associations between microbial disturbances and cancer progression, we underscore the role of specific bacterial strains in various cancers, such as stomach and colorectal cancer. Traditional causality assessment methods, like randomized controlled trials (RCTs), have limitations. Therefore, we advocate using Mendelian Randomization (MR) as a powerful alternative to study causal relationships, leveraging genetic variants as instrumental variables. With the proliferation of genome-wide association studies, MR harnesses genetic variations to infer causality, which is especially beneficial when addressing confounders like diet and lifestyle that can skew microbial research. We systematically review MR's application in understanding the microbiome-cancer nexus, emphasizing its strengths and challenges. While MR offers a unique perspective on causality, it faces hurdles like horizontal pleiotropy and weak instrumental variable bias. Integrating MR with multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, holds promise for future research, potentially heralding groundbreaking discoveries in microbiology and genetics. This comprehensive review underscores the critical role of the human microbiome in oncogenesis and champions MR as an indispensable tool for advancing our understanding in this domain.

Keywords: Mendelian randomization; Microbiome; cancer.

Figure 1

Advantages, disadvantages, and application conditions of six research methodologies: Mendelian randomization, randomized controlled trials, systematic reviews and meta-analyses, bioinformatics and computational biology, observational studies, multi-omics sequencing, and animal models.

Figure 2

Mendelian randomization model and three key assumptions of a Mendelian randomization analysis. MR, Mendelian randomization.

Figure 3

Summary of current research on microbiome causality in relation to multiple cancers.