Back

Exploring the causal role of the human gut microbiome in colorectal cancer: Application of Mendelian randomization

Hatcher, C.; Richenberg, G.; Waterson, S.; Nguyen, L. H.; Joshi, A. D.; Carreras-Torres, R.; Moreno, V.; Chan, A. T.; Gunter, M.; Lin, Y.; Qu, C.; Song, M.; Casey, G.; Figueiredo, J. C.; Gruber, S. B.; Hampe, J.; Hampel, H.; Jenkins, M. A.; Keku, T. O.; Peters, U.; Tangen, C. M.; Wu, A. H.; Hughes, D. A.; Ruhlemann, M. C.; Raes, J.; Timpson, N. J.; Wade, K. H.

2022-10-17 epidemiology
10.1101/2022.10.14.22281077 medRxiv
Show abstract

AimThe role of the human gut microbiome in colorectal cancer (CRC) is unclear as most studies on the topic are unable to discern correlation from causation. We apply two-sample Mendelian randomization (MR) to estimate the causal relationship between the gut microbiome and CRC. Materials and methodsWe used summary-level data from independent genome-wide association studies to estimate the causal effect of 14 microbial traits (n=3,890 individuals) on overall CRC (55,168 cases, 65,160 controls) and site-specific CRC risk, conducting several sensitivity analyses to understand the nature of results. ResultsInitial MR analysis suggested that a higher abundance of Bifidobacterium and presence of an unclassified group of bacteria within the Bacteroidales order in the gut increased overall and site-specific CRC risk. However, sensitivity analyses suggested that instruments used to estimate relationships were likely complex and involved in many potential horizontal pleiotropic pathways, demonstrating that caution is needed when interpreting MR analyses with gut microbiome exposures. In assessing reverse causality, we did not find strong evidence that CRC causally affected these microbial traits. ConclusionsWhilst our study initially identified potential causal roles for two microbial traits in CRC, importantly, further exploration of these relationships highlighted that these were unlikely to reflect causality.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Cancer Epidemiology, Biomarkers & Prevention
17 papers in training set
Top 0.1%
23.2%
2
Scientific Reports
3102 papers in training set
Top 16%
6.5%
3
PLOS ONE
4510 papers in training set
Top 30%
5.0%
4
International Journal of Cancer
42 papers in training set
Top 0.2%
4.1%
5
F1000Research
79 papers in training set
Top 0.4%
3.8%
6
Clinical Infectious Diseases
231 papers in training set
Top 1%
3.7%
7
PeerJ
261 papers in training set
Top 4%
2.7%
8
BMC Medicine
163 papers in training set
Top 2%
2.2%
50% of probability mass above
9
Nature Communications
4913 papers in training set
Top 46%
2.1%
10
BMC Cancer
52 papers in training set
Top 1.0%
2.1%
11
Microbial Genomics
204 papers in training set
Top 1.0%
1.9%
12
Gut Microbes
70 papers in training set
Top 0.5%
1.9%
13
British Journal of Cancer
42 papers in training set
Top 0.8%
1.7%
14
JNCI Cancer Spectrum
10 papers in training set
Top 0.2%
1.7%
15
npj Precision Oncology
48 papers in training set
Top 0.5%
1.7%
16
mBio
750 papers in training set
Top 7%
1.7%
17
International Journal of Epidemiology
74 papers in training set
Top 2%
1.4%
18
Microorganisms
101 papers in training set
Top 2%
0.9%
19
Pediatric Research
18 papers in training set
Top 0.3%
0.8%
20
BMC Public Health
147 papers in training set
Top 5%
0.8%
21
BMC Infectious Diseases
118 papers in training set
Top 5%
0.8%
22
JNCI: Journal of the National Cancer Institute
16 papers in training set
Top 0.6%
0.8%
23
Open Forum Infectious Diseases
134 papers in training set
Top 2%
0.8%
24
Wellcome Open Research
57 papers in training set
Top 2%
0.8%
25
Frontiers in Oncology
95 papers in training set
Top 3%
0.8%
26
BMJ Open
554 papers in training set
Top 12%
0.8%
27
npj Biofilms and Microbiomes
56 papers in training set
Top 2%
0.8%
28
International Journal of Environmental Research and Public Health
124 papers in training set
Top 7%
0.8%
29
American Journal of Epidemiology
57 papers in training set
Top 1%
0.8%
30
Frontiers in Microbiology
375 papers in training set
Top 9%
0.8%