The cause-and-effect relationship between gut microbiota abundance and carcinoid syndrome: a bidirectional Mendelian randomization study

Abstract

ObjectiveCarcinoid syndrome (CS) commonly results from neuroendocrine tumors. While active substances are recognized as the main causes of the typical symptoms such as diarrhea and skin flush, the cause-and-effect relationship between gut microbiota abundance and CS remains unclear.MethodsThe Single Nucleotide Polymorphisms (SNPs) related to gut microbiota abundance and CS were obtained from the GWAS summary data. The inverse variance weighted (IVW) method was used to assess the causal relationship between gut microbiota abundance and CS. Additionally, the MR-Egger, Weighted Median model, and Weighted model were employed as supplementary approaches. The heterogeneity function of the TwoSampleMR package was utilized to assess whether SNPs exhibit heterogeneity. The Egger intercept and Presso test were used to assess whether SNPs exhibit pleiotropy. The Leave-One-Out test was employed to evaluate the sensitivity of SNPs. The Steiger test was utilized to examine whether SNPs have a reverse causal relationship. A bidirectional mendelian randomization (MR) study was conducted to elucidate the inferred cause-and-effect relationship between gut microbiota abundance and CS.ResultsThe IVW results indicated a causal relationship between 6 gut microbiota taxa and CS. Among the 6 gut microbiota taxa, the genus Anaerofilum (IVW OR: 0.3606, 95%CI: 0.1554–0.8367, p-value: 0.0175) exhibited a protective effect against CS. On the other hand, the family Coriobacteriaceae (IVW OR: 3.4572, 95%CI: 1.0571–11.3066, p-value: 0.0402), the genus Enterorhabdus (IVW OR: 4.2496, 95%CI: 1.3314–13.5640, p-value: 0.0146), the genus Ruminiclostridium6 (IVW OR: 4.0116, 95%CI: 1.2711–12.6604, p-value: 0.0178), the genus Veillonella (IVW OR: 3.7023, 95%CI: 1.0155–13.4980, p-value: 0.0473) and genus Holdemanella (IVW OR: 2.2400, 95%CI: 1.0376–4.8358, p-value: 0.0400) demonstrated a detrimental effect on CS. The CS was not found to have a reverse causal relationship with the above 6 gut microbiota taxa.ConclusionSix microbiota taxa were found to have a causal relationship with CS, and further randomized controlled trials are needed for verification.

DataSheet2.CSV

“…In addition, linkage disequilibrium is not allowed in MR analysis, which will challenge the reliability of the results. Therefore, we also screened for IVs by setting r 2 = 0.001 and kb = 10,000 (Zhang et al, 2023). We also used the Steiger test to remove the IVs with reverse causality.…”

DataSheet7.PDF

“…In addition, linkage disequilibrium is not allowed in MR analysis, which will challenge the reliability of the results. Therefore, we also screened for IVs by setting r 2 = 0.001 and kb = 10,000 (Zhang et al, 2023). We also used the Steiger test to remove the IVs with reverse causality.…”

“…The data on intestinal flora come from Kurilshikov A, published in Nature Genetics in 2021 (Kurilshikov et al, 2021). Our previously published article describes the data and screening thresholds (Zhang et al, 2023). The data on lipid metabolism come from Ottensmann L, published in Nature Communications in 2023 (Ottensmann et al, 2023).…”

DataSheet5.CSV

“…In addition, linkage disequilibrium is not allowed in MR analysis, which will challenge the reliability of the results. Therefore, we also screened for IVs by setting r 2 = 0.001 and kb = 10,000 (Zhang et al, 2023). We also used the Steiger test to remove the IVs with reverse causality.…”

“…The data on intestinal flora come from Kurilshikov A, published in Nature Genetics in 2021 (Kurilshikov et al, 2021). Our previously published article describes the data and screening thresholds (Zhang et al, 2023). The data on lipid metabolism come from Ottensmann L, published in Nature Communications in 2023 (Ottensmann et al, 2023).…”