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. 2024 Dec 6;103(49):e40738. doi: 10.1097/MD.0000000000040738

The relationship between cereal intake and 3 common inflammatory joint diseases: A 2-sample Mendelian randomization study

Xujing Yuan a, Weiwei Wang a, Wenxun Lin a, Jiajia Wu a, Rong Du a,*
PMCID: PMC11630992  PMID: 39654226

Abstract

The association between cereal intake and inflammatory joint disease remains controversial. This study aims to use Mendelian randomization to comprehensively evaluate the causal relationship between cereal grain intake and Inflammatory joint diseases, including rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis. This investigation used publicly available data from genome-wide association studies to aggregate statistics on the association between cereal intake and inflammatory joint disease. Several methods were employed to estimate 2-sample causality. The results of the random-effects inverse variance-weighted method analysis indicated that higher cereal intake reduced the risk of developing rheumatoid arthritis (odds ratio [OR] = 0.554; 95% confidence interval [CI]: 0.324–0. 948; P = .031) and psoriatic arthritis (OR = 0.336; 95% CI: 0.123–0.918; P = .033), and the results of the Mendelian randomization-Egger regression analysis showed no horizontal pleiotropy (P > .05) for the included single nucleotide polymorphisms. Using the leave-one-out method, no single nucleotide polymorphism was found to affect the overall effect estimate significantly, and there was no heterogeneity. Cereal intake had no causal effect on the risk of developing ankylosing spondylitis (OR = 0.636; 95% CI: 0.236–1.711; P = .370). There is genetic evidence that cereal consumption reduces the risk of developing Inflammatory joint diseases such as rheumatoid arthritis and psoriatic arthritis.

Keywords: ankylosing spondylitis, cereal, Mendelian randomization, psoriatic arthritis, rheumatoid arthritis

1. Introduction

Inflammatory joint disease is a chronic inflammatory condition that affects the joints and surrounding tissues and is characterized by joint pain and stiffness, with symptoms typically worsening over time. It is estimated that hundreds of millions of people worldwide suffer from arthritis each year.[1] Rheumatoid arthritis (RA), ankylosing spondylitis (AS), and psoriatic arthritis (PsA) are the most common immune-mediated inflammatory diseases affecting the joints, all of which have a significant impact on quality of life. Several studies have shown that, in addition to genetic and environmental factors, diet plays a key role as a potential modulator of immune and inflammatory responses.[2] A well-considered diet is of paramount importance in both the early prevention and restorative treatment of arthritis.

Cereals, such as wheat, rice, oats, barley, and sorghum, are grown and consumed worldwide. Numerous previous studies have shown that higher cereal intake is associated with reduced mortality and incidence of chronic diseases, including cardiovascular disease,[3] type 2 diabetes,[4] cancers,[3] and metabolic syndrome.[5] Cereals are particularly rich in bioactive compounds, including phenolic compounds, dietary fiber, trace minerals, and antioxidants. These components have been shown to regulate inflammation, inhibit hyperimmunity and oxidative stress, and contribute significantly to maintaining normal immune homeostasis in the body. RA, AS, and PsA have long been recognized as being closely related to autoimmune diseases, with diet playing a key role in the development of these conditions. Numerous studies have shown that moderate grain consumption is beneficial, not only by reducing circulating C-reactive protein (CRP) levels but also by reducing overall inflammation. However, it is important to acknowledge that there are conflicting studies suggesting that certain compounds in wheat and other cereals may activate pro-inflammatory pathways. This discrepancy introduces a degree of uncertainty regarding the exact nature of the association between cereal intake and inflammatory joint disease. Given these conflicting findings, there is currently uncertainty about the relationship between cereal intake and inflammatory joint disease.[6]

Inherent limitations of observational studies include reverse causation, measurement error, and potential bias. Mendelian randomization (MR) is an analytic approach involving genetic variables that adheres to the Mendelian laws of inheritance. It uses single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) to identify causal relationships between modifiable exposures and clinically relevant outcomes. Because alleles segregate randomly during meiosis, MR serves to reduce bias due to confounding factors. In addition, MR minimizes the effects of reverse causation by exploiting genetic variants that precede disease onset and prevent reversal of temporal order. In the present study, we used Mendelian randomization to investigate the potential causal relationship between cereal intake and inflammatory joint disease. We aim to provide improved dietary guidance for people with inflammatory joint disease, potentially contributing to more effective clinical management.

2. Methods

2.1. Exposure and outcome GWAS data sources

To mitigate potential bias from overlapping exposure to outcome samples, a rigorous approach was adopted, with exposure and outcome samples sourced from different databases. The selection process for exposure and outcome genome-wide association study (GWAS) datasets took into account several critical factors to ensure a robust and comprehensive analysis. Key considerations included the European origin of the population, a diverse range of disease types, a large population sample size, a large number of SNPs, a balanced gender composition, and careful consideration of the timing of data publication. The Cereal Intake GWAS dataset, identified by the ID number “ukb-b-15926,” has a substantial sample size of 441,640 individuals and includes a large number of SNPs, totaling 9851,867 (https://gwas.mrcieu.ac.uk/). The rheumatoid arthritis GWAS dataset, ID number “ieu-a-833,” includes 19,234 cases (ncase), a sample size of 80,799, and an extensive set of 9739,304 SNPs, along with 61,565 controls (ncontrol). The Ankylosing Spondylitis GWAS dataset, named “finn-b-M13_ANKYLOSPON,” includes 1462 samples and an impressive 16,380,022 SNPs. Similarly, the arthropathic psoriasis GWAS dataset, codenamed “finn-b-L12_PSORI_ARTHRO,” has a sample size of 1637, comprising 16,380,462 SNPs, with a substantial number of controls (ncontrol: 212,242). Importantly, all individuals in these studies, both cases and controls, were of European ancestry, ensuring homogeneity of genetic background.

2.2. Mendelian randomization analysis

A 2-sample Mendelian randomization analysis was used in this study. MR analysis uses instrumental variables as mediators between exposure factors and outcomes, allowing for the exploration of causal relationships. Typically, genetic variants serve as IVs, with SNPs commonly used in this role. To ensure unbiased results, 3 fundamental assumptions of MR must be met: the instrumental variable IVs should have a robust association with the exposure; the instrumental variable IVs must be independent of confounders related to the selected exposure and outcome; and the instrumental variable IVs should exert their effect on the outcome solely through the exposure and not through alternative pathways.[7] The schematic of MR analysis is illustrated in Figure 1.

Figure 1.

Figure 1.

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Schematic of an MR analysis. β₁ represents the association between the instrumental variables (IVs) and the exposure, β₂ represents the association between the IVs and the outcome, β represents the causal association between the exposure and the outcome, and can be calculated using the formula β = β₂/β₁. AS = ankylosing spondylitis, IVs = instrumental variables, MR = Mendelian randomization, PsA = psoriatic arthritis, RA = rheumatoid arthritis.

2.3. Instrumental variables

First, independent SNPs strongly associated with exposure were identified within a 10,000 kb window around the lead SNP, using a stringent filtering criterion of P < 5 × 10−8. These selected SNPs were then queried in PhenoScanner (www.phenoscanner.medschl.cam.ac.uk), excluding SNPs correlated with confounders and outcomes. Confounders primarily refer to potential risk factors other than exposure that may contribute to the observed outcomes. SNPs corresponding to phenotypes associated with outcomes were eliminated, leaving only the relevant SNPs for subsequent analysis.

Subsequently, SNPs with an effect minor allele frequency (Maf) >0.01 were extracted from the outcome GWAS dataset using specific filtering criteria. The F statistic was used to determine the robust association of IVs with exposure. A threshold of F > 10 was set to consider the association between IVs and exposure to be strong enough to ensure that the results of the Mendelian randomization analyses were resistant to weak instrumental bias. A matching process was then performed to harmonize exposure and outcome effects, eliminating SNPs with F statistics < 10 or those that did not match. The resulting set of valid IVs included palindromic sequences with incompatible alleles and intermediate allele frequencies.

2.4. Statistical analysis

Prior to performing the Mendelian randomization analysis, the alleles of each SNP were matched to ensure concordance between exposure and outcome. The MR analysis used the inverse variance weighting (IVW) method as the primary analytical approach, utilizing various models based on heterogeneity. In particular, the IVW model, which is recognized for its robustness, was selected as the primary method for detecting causality in 2-sample MR analysis.[8] Subsequently, additional assessment of valid instrumental variables was performed using simple model, weighted median, and MR-Egger regression methods.[9] Each method makes different assumptions about the validity of the instrumental variables. For example, MR-Egger analysis is used to assess whether instrumental variables have a directional horizontal pleiotropic effect on the outcome. The weighted median method, on the other hand, provides reliable causal estimates when more than 50% of the information is derived from valid instrumental variables. Despite their effectiveness, the weighted median and MR-Egger methods tend to produce wider confidence intervals than IVW. Therefore, they were used in this study as complementary methods that provide greater robustness when the 3 models produce consistent results. All of these methods were used systematically to explore causality in a comprehensive manner, ensuring a thorough examination of the relationships under consideration.

2.5. Sensitivity analysis

This study incorporated several sensitivity analysis methods to increase the robustness of the results. First, Cochrane’s Q statistic was used to assess the heterogeneity among individual SNP estimates, which aided in the selection of an appropriate analysis method. Depending on the significance of the Cochrane Q statistic, either a random effects model (P < .05) or a fixed effects model (P > .05) was used.[10] Second, the MR-Egger intercept test was performed to assess horizontal pleiotropy. The intercept in the MR-Egger test estimates the mean horizontal pleiotropic effect of SNPs. A P value <.05 indicates potential bias in the IVW estimate. Third, the leave-one-out method systematically removed individual SNPs and recalculated effect sizes for the remaining instrumental variables to assess the influence of each SNP on the Mendelian randomization estimates. The MRE-IVW method was used to clarify whether the exclusion of specific instrumental variables significantly altered the MR results.[11] If the distribution of the “ALL” line remains consistent with the MR estimation results, it suggests stability and reliability of the MR results. Fourth, scatter plots, funnel plots, and forest plots were generated to visually present the MR results.[7] These graphical representations provide a comprehensive overview of the data and aid in the interpretation and visualization of the MR results.

3. Results

3.1. Characterization and results of selected SNPs

SNPs strongly associated with cereal intake were identified as IVs in the GWAS. Subsequently, linkage disequilibrium (LD) analysis was performed, filtering out SNPs with linkage disequilibrium (LDr2) <0.001 and a cluster distance >10,000 kb. A total of 43 SNPs (Table S1, Supplemental Digital Content, http://links.lww.com/MD/O83), exhibiting strong LD with cereal intake, were retained. To enhance the precision of the instrumental variable selection, a meticulous process was undertaken. We conducted a comprehensive search for phenotypes associated with each SNP using PhenoScanner (http://www.phenoscanner.medschl.cam.ac.uk/). We identified that SNPs rs9987289, rs9846396, and rs56131196 are associated with potential confounding factors such as C-reactive protein levels,[12] cholesterol,[13] and cancer.[14] Since these factors may be linked to the 3 inflammatory joint diseases investigated in our study, we excluded these SNPs from the analysis. Additionally, palindromic variants prone to chain ambiguity, such as rs10837531, rs1104608, rs3859193, rs627185, and others, were removed from consideration. After this comprehensive screening process, a total of 36 SNPs were included in the MR analysis for the relationship between cereal intake and RA and PA. Simultaneously, 37 SNPs were included in the MR analysis exploring the association between cereal intake and AS. These carefully selected SNPs served as the basis for further analysis. To ensure the robustness of the instrumental variables, a test of instrument strength (F statistic > 10) was conducted, revealing no evidence of weak instrumental bias. This stringent criterion was applied to affirm the reliability and validity of the instrumental variables chosen for the MR analysis.

3.2. Causal estimates of genetic susceptibility to cereal intake and risk of inflammatory arthritis

Regarding the relationship between cereal intake and the prevalence of RA (Fig. 2), the IVW method showed a significant result (OR = 0.554; 95% CI: 0.324–0.948; P = .031), indicating that higher cereal intake is associated with a reduced risk of RA (Figs. 3A and S1A, Supplemental Digital Content, http://links.lww.com/MD/O84). This finding is consistent with the results from the weighted median method (OR = 0.423; 95% CI: 0.214–0.837; P = .013), further supporting the protective effect of cereal intake against RA. However, the simple mode (95% CI: 0.099–1.279; P = .124) and weighted mode (95% CI: 0.109–1.493; P = .185) did not demonstrate statistical significance. When exploring the relationship between cereal intake and the prevalence of PsA, the IVW method similarly revealed a consistent protective association at the genetic level. The results indicated that cereal intake is a protective factor for PsA, with an odds ratio of 0.336 (95% CI: 0.123–0.918; P = .033), confirming the potential benefits of cereal consumption in reducing the risk of PsA (Figs. 3C and S1C, Supplemental Digital Content, http://links.lww.com/MD/O84). However, the weighted median (95% CI: 0.130–1.907; P = .309), simple mode (95% CI: 0.006–2.017; P = .146), and weighted mode (95% CI: 0.036–3.347; P = .365) did not show significant results. Overall, while only the IVW method demonstrated significant statistical relevance in these 2 analyses, the direction of results across all methods was consistent with that of the IVW, indicating that our findings are valid and reliable.

Figure 2.

Figure 2.

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A forest plot of 2-sample MR analysis. The MR estimates derived from different MR methods for the causal effect of exposure (cereal intake) on outcome (RA, AS, and PsA) are presented in a forest plot. The green square represents the estimated effect size, while the horizontal line extending from the square indicates the confidence interval for that effect size, typically the 95% confidence interval. AS = ankylosing spondylitis, CI = confidence interval, IVW = inverse variance weighted, MR = Mendelian randomization, MR-PRESSO = Mendelian random pleiotropy residual sum and outliers, OR = odds ratio, PsA = psoriatic arthritis, RA = rheumatoid arthritis, SNPs = single nucleotide polymorphisms, WME = weighted median estimate.

Figure 3.

Figure 3.

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Scatter plots of cereal intake associated with 3 common inflammatory joint diseases. (A) RA with cereal intake, (B) AS with cereal intake, and (C) PsA with cereal intake. The dashed lines in the figure show the 95% confidence intervals for each association. The upward sloping line from left to right indicates that the X-axis is positively associated with the Y-axis, indicating a pathogenic causal effect. The downward sloping lines indicate protective causal effects. Horizontal bars: These typically represent the confidence intervals for the effect estimates of the exposure (X-axis). They indicate the range within which the true effect size of the exposure is likely to fall. Vertical bars: These typically represent the confidence intervals for the effect estimates of the outcome (Y-axis). AS = ankylosing spondylitis, MR = Mendelian randomization, PsA = psoriatic arthritis, RA = rheumatoid arthritis.

However, our study could not establish a causal relationship between cereal intake and the incidence of AS. The IVW method yielded an odds ratio of 0.636 (95% CI: 0.236–1.711; P = .370), while the weighted median (95% CI: 0.090–1.473; P = .157), simple mode (95% CI: 0.019–5.573; P = .441), and weighted mode (95% CI: 0.021–2.494; P = .235) did not indicate a significant effect (Figs. 3B and S1B, Supplemental Digital Content, http://links.lww.com/MD/O84). This result underscores the specificity of the association between cereal intake and different forms of inflammatory arthritis (Fig. S2, Supplemental Digital Content, http://links.lww.com/MD/O84).

3.3. Horizontal multiplicity and heterogeneity tests

In the RA group (95% CI: 0.009–1.027; P = .063) and the PsA group (95% CI: 0.003–19.724; P = .541), the MR-Egger method did not indicate significant horizontal pleiotropy (P > .05). Notably, a P value >.05 suggests the absence of significant horizontal pleiotropy, further indicating that no bias was observed due to directional pleiotropic effects. In contrast, the MR-Egger method revealed significant horizontal pleiotropy in the AS subgroup (95% CI: 0.001–0.238; P = .013), which aligns with our conclusion that there is no significant association between cereal intake and AS.

At the same time, Cochran’s Q test did not identify significant heterogeneity in the results within each group. This consistent lack of heterogeneity across RA, AS, and PsA subgroups supports the robustness and internal consistency of the results (Table 1). The absence of significant heterogeneity enhances the reliability of the MR estimates within these subgroups, thereby strengthening the credibility of the observed associations between genetic susceptibility to cereal intake and the risk of inflammatory arthritis.

Table 1.

Heterogeneity and pleiotropy tests of 2-sample MR analysis.

Heterogeneity test Pleiotropic test
Exposure Methods Q Q_df P value Methods SE P value
RA MR Egger 35.317 28 .160 Egger_intercept 0.017 .149
IVW 38.095 29 .120
AS MR Egger 26.433 35 .850 Egger_intercept 0.030 .018
IVW 32.578 36 .632
PSA MR Egger 37.821 34 .299 Egger_intercept 0.031 .897
IVW 37.840 35 .341
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AS = ankylosing spondylitis, IVW = inverse variance weighting, MR = Mendelian randomization, PsA = psoriatic arthritis, RA = rheumatoid arthritis, SE = standard error.

4. Discussion

In recent decades, dietary modification has received increasing attention due to its practical feasibility as a potential preventive measure against joint inflammation. Epidemiologic and human intervention studies have been pivotal in investigating the role of cereal-based diets in modulating inflammatory biomarkers, albeit with mixed results. Andersson et al[15] conducted a randomized crossover trial to evaluate the effects of grain-based diets on inflammatory markers. Their investigation of a 6-week cereal intake in healthy, moderately overweight adults (22 women and 8 men) concluded that plasma levels of IL-6 and CRP were unaffected. Similar results were observed in another 3-week crossover study with 15 healthy subjects and in a comparable study with 21 healthy subjects.[16,17] In addition, Zevallos and colleagues[18] found that wheat amylase-trypsin inhibitors (ATIs) activated by toll-like receptor 4 (TLR4) on myeloid cells were unaffected by consumption of wheat ATIs within a normal daily gluten-containing diet. Conversely, a cohort study of 259 healthy women aged 18 to 44 years showed a negative correlation between whole grain (WG) intake and hs-CRP concentrations. In addition to the randomized controlled trials (RCTs) mentioned above, a prospective study from the United Kingdom suggested a reduced risk of rheumatoid arthritis associated with breakfast cereal consumption.[19] Lefevre and Jonnalagadda,[20] based on a review of 13 epidemiologic and 5 interventional studies, reported a 7% reduction in serum CRP levels per serving of whole grain. In addition, supplementation of morbidly obese subjects with ground flaxseed, a source of omega-3 fatty acids, resulted in reduced CRP and serum amyloid A (SAA) concentrations in a study by Dangardt et al.[21] Omar et al[22] found a negative correlation between a whole grain diet and markers of inflammation in the body, such as cathepsin S (histoproteinase). Oats, which are rich in dietary fiber, were the subject of a randomized controlled meta-analysis that found that adding oat products to the diet resulted in lower LDL and total cholesterol levels, with soluble fiber identified as the primary active ingredient.[23] Taken together, these studies suggest that sustained adherence to a grain-rich diet may contribute to the reduction of inflammatory markers.

In contrast to previous prospective or cohort studies, our investigation examines the potential causal relationship between grain consumption and various inflammatory joint diseases at the genetic level. This approach complements and strengthens the findings of previous studies. Chronic systemic autoimmune diseases such as RA, AS, and PsA have been extensively studied for etiologic factors, including genetics and hormone levels. However, the focus on dietary factors and rehabilitative therapies has been relatively limited. In the context of this Mendelian randomization study, our results indicate the absence of a potential risk association between a grain-based diet and AS. Conversely, consistent consumption of grain-rich foods appears to be a protective factor, significantly reducing the incidence of RA and PsA. These findings provide strong evidence to support early prevention and dietary management of these diseases.

Numerous studies have consistently confirmed the significant role of bioactive compounds found in cereals, particularly trace elements, dietary fiber and polyphenols, in both the pathogenesis and therapeutic processes associated with inflammatory joint disease.[24] These bioactive compounds are absorbed and exert influence on systemic energy metabolism, including regulation of lipid-glucose metabolism,[25] modulation of the immune microenvironment,[26] and composition of the gut microbiota.[27,28] In addition, cereal intake undergoes metabolic transformations in the body, resulting in the formation of trace elements that play key roles in various cellular communications and biosynthesis. The homeostasis of intestinal flora, recognized as a critical determinant of systemic inflammatory immune responses, has been shown to be positively influenced by dietary fiber. Increased fiber intake has been associated with increased production of short-chain fatty acids, known for their anti-inflammatory properties.[29] In addition, polyphenolic compounds present in cereals exhibit targeted regulation of inflammatory pathways through their antioxidant properties, metal chelation mechanisms, and modulation of gene activity.[30,31] Studies have demonstrated that cereal polyphenols have the ability to attenuate pro-inflammatory and oxidative stress-induced barrier dysfunction by inhibiting NF-kB and stimulating Nrf2.[32,33] β-Glucans, which constitute a significant portion of cereal foods, not only contribute to the reduction of cholesterol levels, but also affect cytokine secretion, complement system activation, phagocytic activity, and overall toxicity.[34,35] Together, these effects contribute to the maintenance of in vivo homeostasis and a reduced incidence of associated inflammatory diseases. Similarly, cereal-derived arabinoxylans have been shown to enhance various immune responses both in vivo and in vitro.[36] The large body of evidence strongly suggests that grain intake serves as a key determinant in the development of inflammatory joint disease.

RA and PsA are typically classified as adaptive immune-mediated autoimmune diseases characterized by chronic joint inflammation, synovial immune cell infiltration, and fibroblast-like synovial cell proliferation.[37,38] In contrast to RA and PsA, AS results from abnormal activation of innate immune cells and innate-like immune cells, such as γδ T-cells and type 3 innate lymphoid cells.[39] Approximately half of patients with active arthritic disease in ankylosing spondylitis have normal erythrocyte sedimentation rate or CRP levels, and the absence of autoantibodies is generally accepted as a specific marker for AS. AS can be considered as a continuum between autoimmunity and autoinflammation, where innate immunity plays a predominant role in initiating the disease, while adaptive components are responsible for sustaining the inflammatory process.[40] In our study, we observed no significant association between cereal intake and AS. This finding supports the distinction in pathogenesis between AS and RA/PsA. In addition, it is plausible that the AS population experiences an earlier peak of disease onset, and the duration of exposure to cereal intake may not be sufficient to observe an effective protective effect in the short term.

In summary, a large body of evidence suggests that long-term grain-based diets are effective in both the prevention and treatment of inflammatory joint disease. Although previous studies have yielded conflicting results regarding the relationship between grains and inflammation, our current investigation using genetic tools robustly confirms that a grain-based diet serves as a protective factor against a broad spectrum of chronic inflammatory arthropathies. Regular, sustained grain consumption offers significant benefits for individuals susceptible to these conditions. However, our study has several limitations. First, the GWAS summary data used were derived from published studies that lacked categorization based on specific factors such as age and sex. As a result, our study could not detect age- or sex-related differences. Second, the analysis focused on the 3 most common inflammatory joint diseases and did not include other joint diseases. Third, the study focused primarily on a European population, limiting the generalizability of the findings to other racial or ethnic groups. Moreover, the currently available public databases have a relatively small sample size, which may contribute to the overall weak statistical significance. Finally, while the MR results suggest potential genetic correlations and causal associations at the gene level, further mechanistic experiments are essential to establish biological plausibility and elucidate the underlying mechanisms linking cereal grain consumption to disease development. Future GWAS studies in larger populations are expected to reveal important loci with increased genetic relevance. inflammatory joint diseases, providing an important avenue for early prevention of related diseases.

5. Conclusion

Genetic evidence indicates that the consumption of grains is associated with a reduced risk of developing inflammatory joint diseases, such as rheumatoid arthritis and psoriatic arthritis. We advocate for studies with larger sample sizes to more comprehensively elucidate the potential causality and precise underlying mechanisms of this protective effect.

Acknowledgments

We sincerely appreciate the FinnGen biobank and IEU Open GWAS project for providing the GWAS summary data.

Author contributions

Conceptualization: Xujing Yuan, Rong Du.

Data curation: Xujing Yuan.

Methodology: Weiwei Wang.

Software: Xujing Yuan, Wenxun Lin.

Visualization: Jiajia Wu.

Writing – original draft: Xujing Yuan.

Writing – review & editing: Rong Du.

Supplementary Material

medi-103-e40738-s001.xlsx (14.3KB, xlsx)
medi-103-e40738-s002.pdf (219.6KB, pdf)

Abbreviations:

AS
ankylosing spondylitis
CI
confidence interval
ESR
erythrocyte sedimentation rate
GWAS
genome-wide association study
IJD
inflammatory joint disease
IVs
instrumental variables
IVW
inverse variance weighted
LD
linkage disequilibrium
MR
Mendelian randomization
OR
odds ratio
PsA
psoriatic arthritis
RA
rheumatoid arthritis
SM
simple model
SNPs
single nucleotide polymorphisms

The authors have no funding and conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

Supplemental Digital Content is available for this article.

How to cite this article: Yuan X, Wang W, Lin W, Wu J, Du R. The relationship between cereal intake and 3 common inflammatory joint diseases: A 2-sample Mendelian randomization study. Medicine 2024;103:49(e40738).

Contributor Information

Xujing Yuan, Email: yyuanxujing@163.com.

Weiwei Wang, Email: wangweiweixh@163.com.

Wenxun Lin, Email: wenxunlinn@163.com.

Jiajia Wu, Email: wujiajiadw@163.com.

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