Editorial: in search of environmental risk factors of Crohn's disease and ulcerative colitis with mendelian randomisation—authors' reply
Bibliographic record
Abstract
We thank Drs. Meyer, Amiot and Carbonnel for taking the time to consider in detail our research article and for sharing thoughts on its implications.1, 2 We agree that previous studies have not arrived at a consensus on the causal relationship of individual circulating antioxidants minerals, and vitamins with inflammatory bowel disease (IBD) and its subtypes. In the Mendelian randomization (MR) analysis based on three outcome datasets, we provided evidence that genetically determined higher levels of vitamin D were associated with decreased risk of Crohn's disease (CD). We also found a suggestive association between genetically determined higher levels of vitamin D and ulcerative colitis (UC) (p = 0.048). Consistent with our findings, a meta-analysis found that vitamin D deficiency was associated with increased risks of both CD and UC in Western populations based on 13 observational studies.3 However, a previous study found that high levels of plasma vitamin D were associated with high risks of UC in cross-sectional analysis, and reported a null finding on the association between vitamin D and IBD in MR analysis.4 The discrepancies could be explained by the residual confounding from unmeasured confounders or reverse causation, which could be a problem in a cross-sectional design. In addition, the weaker genetic association of vitamin D (captured by allele scores) and limited sample size in the previous study may have been factors in underestimating the potential association. Indeed, a previous MR study also failed to detect the association between vitamin D and IBD with a relatively limited sample size.5 We agree that MR usually examines nutrients individually, which means that it does not consider the complex interactions and relationships between different nutrients. Thus, more research on the interactions between different nutrients is essential. Nevertheless, evidence from MR has still provided new insights into the role of nutrients in disease pathophysiology. In our study, MR with adjustment for body mass index (BMI), smoking and body fat percentage was not performed, as these data were not available in the genome-wide association studies that we used. In the future, it will be beneficial to conduct MR studies with adjustments for these confounding factors, if more comprehensive genetic data become available. In conclusion, MR is a useful methodology for examining the causal relationship of circulating antioxidants, minerals and vitamins with IBD. Meanwhile, we agree with Drs. Meyer, Amiot and Carbonnel that it is important to acknowledge the complex nature of nutrient interactions and relationships in the context of overall dietary patterns, and that MR results must be interpreted with caution. In addition, more large-scale, publicly available genome-wide association studies of nutrients and IBD will help better understand the causal association between circulating nutrients and IBD. Jie Chen: Conceptualization (equal); writing – original draft (equal). Xixian Ruan: Conceptualization (equal); writing – original draft (equal). Shuai Yuan: Conceptualization (supporting); writing – review and editing (equal). Evropi Therdoratou: Conceptualization (supporting); writing – review and editing (equal). Jack Satsangi: Conceptualization (supporting); writing – review and editing (equal). Xue Li: Conceptualization (equal); writing – review and editing (lead). Declaration of personal interests: The authors' declarations of personal and financial interests are unchanged from those in the original article.1 XL is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001) and the National Nature Science Foundation of China (82204019). ET is supported by a CRUK Career Development Fellowship (C31250/A22804). This article is linked to Chen et al papers. To view these articles, visit https://doi.org/10.1111/apt.17392 and https://doi.org/10.1111/apt.17432
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.086 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.023 | 0.028 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".