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. 2025 Aug 29;16:1654. doi: 10.1007/s12672-025-03480-5

Dietary factors causally affect the risk of kidney cancer: a two-sample Mendelian randomization study

Congcong Zhu 2,3,#, Tonghu Liu 1,3,#, Zhengyi Jiang 1,3, Hui Wang 1,3, Mengran Zhang 3,4,✉, Weibo Sun 3,5,✉, Zechen Yan 1,5,✉
PMCID: PMC12397012  PMID: 40879705

Abstract

Background

Previous observational studies have indicated potential associations between certain dietary factors and the incidence of kidney cancer. However, the causal relationship between these elements remains unknown. This study is aimed to investigate the causal relationship between dietary factors and the incidence of kidney cancer through Mendelian randomization (MR) analysis.

Methods

The study utilized genome-wide association study (GWAS) summary data from the GWAS Catalog and the IEU Open GWAS project databases. The exposure factors included consumption of dessert (n = 20,622), fruit (n = 421,155), alcohol (n = 462,346), and salt (n = 323,995). The outcomes were based on GWAS data for kidney cancer (cases = 1,103, controls = 455,245). Three MR methods, including Inverse Variance Weighted (IVW), MR-Egger, and Weighted Median, were used in the study, with IVW serving as the primary method. Sensitivity analyses such as the MR-Egger intercept test, Cochran’s Q test, and leave-one-out analysis were performed to detect heterogeneity and pleiotropy.

Results

The IVW method demonstrated a significant causal relationship between frequent alcohol consumption (OR = 1.61, 95% CI: 1.02–2.54, P = 0.040) and kidney cancer. In contrast, no causal associations were found with the consumption of alcohol (OR = 1.12, 95% CI: 0.91–1.37, P = 0.280), dessert (OR = 1.23, 95% CI: 0.71–2.12, P = 0.465), fruit (OR = 1.33, 95% CI: 0.59-3.00, P = 0.494) or salt (OR = 0.01, 95% CI: 0.00-1.49, P = 0.073). The sensitivity analyses did not reveal any evidence of pleiotropy.

Conclusion

This MR study suggests that frequent alcohol consumption can increase the risk of kidney cancer, whereas no significant causal relationships were detected between the consumption of dessert, fruit or salt and the risk of kidney cancer.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-025-03480-5.

Keywords: Mendelian randomization, Causal inference, Dietary factors, Kidney cancer, Genome-wide association study

Introduction

Kidney cancer is one of the top ten most common malignant tumors in adults, accounting for 3–5% of all malignant tumors in adults and ranking third in incidence among urological cancers [1, 2]. Early-stage kidney cancer is preferably treated with nephron-sparing surgery or radical nephrectomy. Despite the ongoing development of targeted therapies and the emergence of novel immunotherapeutic drugs, the effectiveness of treatments for advanced kidney cancer has not shown significant improvement. Over the past few decades, the incidence of kidney cancer has been on a rising trend, particularly in Europe [3]. Patients with kidney cancer not only have a lower survival rate but also face high recurrence rate of 20%−40%, with an increasing incidence among younger individuals [4]. Therefore, early prevention and diagnosis of kidney cancer are particularly crucial in clinical practice.

Previous observational studies have indicated that daily dietary habits and lifestyles are associated with the onset and progression of diseases, with certain diets altering the risk of various diseases [5, 6]. A case-control study by Handa et al. [7] investigated the impact of dietary factors on the risk of kidney cancer and found that the consumption of dessert and juices might be risk factors for kidney cancer. SONG et al. [8] discovered that alcohol consumption could affect the risk of kidney cancer. The latest guidelines from the European Association of Urology (EAU) also suggest that moderate alcohol consumption may reduce the risk of kidney cancer. Thus, the influence of daily dietary habits such as alcohol and dessert consumption on the risk of tumor development has attracted widespread attention among researchers. However, previous observational studies and meta-analyses struggle to avoid confounders such as hypertension and hyperglycemia, often have limited sample sizes, and can lead to poor stability in statistical results and insufficient evidence quality [9]. Therefore, the causal relationship between daily dietary habits and the risk of kidney cancer requires more systematic and comprehensive research.

Mendelian randomization (MR) utilizes genetic variants as instrumental variables to reveal the causal relationships between exposure factors and outcomes [10]. This approach is not influenced by confounding factors or reverse causation, resulting in more stable statistical outcomes [11]. This study uses GWAS summary data to perform a two-sample MR analysis, systematically exploring the causal relationships between specific dietary components such as alcohol, dessert, salt, and fruit, and the risk of kidney cancer. It aims to aid in the early prevention, diagnosis, and treatment of kidney cancer.

Methods

Study design

This study employs a two-sample MR approach to systematically explore the causal relationships between various dietary factors, such as alcohol, salt, dessert, and fruit, and the risk of kidney cancer. The study adheres to the three core assumptions of MR: (1) The selected instrumental variables are closely associated with the exposure factors; (2) The instrumental variables are not associated with any known confounding factors; (3) The exposure factors affect the outcome solely through the risk factor and not through any other direct causal pathways [12, 13](Fig. 1).

Fig. 1.

Fig. 1

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The three assumptions of Mendelian randomization

GWAS summary data sources

The GWAS summary data used in this two-sample MR study were all sourced from public databases. Dietary factors were considered as exposure factors, including alcohol consumption, dessert consumption, added salt consumption, and fruit consumption, with kidney cancer as the outcome. Specifically, frequent alcohol consumption data were obtained from the IEU Open GWAS project (https://gwas.mrcieu.ac.uk/) and included 462,346 cases; dessert consumption data were sourced from the GWAS Catalog database (https://www.ebi.ac.uk/gwas/) and included 20,622 participants; added salt consumption data were also from the GWAS Catalog database, including 323,995 participants; fruit consumption data were obtained from the GWAS Catalog database, including 421,155 participants. GWAS summary data related to kidney cancer were also sourced from the GWAS Catalog database, including 1,103 cases and 455,245 controls.

Instrumental variable selection

To ensure the credibility and robustness of the results of this MR study, we conducted stringent selection of IVs. The process is as follows: Firstly, we set different genome-wide significance thresholds for selecting genetic variants closely related to the exposure factors, based on sample size and sequencing depth of the different exposures. The thresholds were set at 5 × 10−9 for frequent alcohol consumption, 5 × 10−8 for fruit and salt, and 5 × 10−6 for dessert. The linkage disequilibrium threshold was uniformly set at R2 < 0.001 with a clumping window size of 10,000 kb [14, 15]. Secondly, genetic variants with an F-statistic less than 10 were excluded to ensure there was no weak instrument bias in our included instrumental variables [16]. The F-statistic for each instrumental variable is calculated using the formula: F = beta2/se2 [17]. Thirdly, SNPs with inconsistent alleles and palindromic SNPs with uncertain strands were removed during the harmonization process. Finally, we used the MR pleiotropy residual sum and outlier (MR-PRESSO) to detect and remove outlier SNPs, with the remaining SNPs used for the final MR analysis [18]. Additionally, we conducted a systematic screening of all candidate SNPs using PhenoScanner (www.phenoscanner.medschl.cam.ac.uk) to exclude genetic variants significantly associated with potential confounders such as BMI, smoking, and diabetes.

Statistical analyses

In this study, we utilized three MR methods: IVW, MR-Egger, and Weighted Median, to explore the causal relationship between dietary factors and kidney cancer [12]. IVW was employed as our primary analytical method to primarily assess the causal impact of various exposure phenotypes on the outcome [19]. Weighted Median and MR-Egger were used as supplementary methods to validate the robustness of the MR results. Multiple sensitivity analysis methods were employed to verify the stability of the MR findings. The MR-Egger intercept test was used to detect pleiotropy [20]; an associated P-value greater than 0.05 indicates no pleiotropy [21], suggesting high credibility of the MR results. Cochran’s Q test was used to detect heterogeneity [22]; a related P-value less than 0.5 indicates the presence of heterogeneity [23]. Leave-one-out analysis and funnel plots were used to detect heterogeneity in SNPs [24].

All related analyses in this study were conducted using R software (version 4.2.1), with MR analysis performed using the TwoSampleMR package (version 0.5.7).

Results

Based on the instrumental variable selection methods described above, we identified four sets of instrumental variables (IVs) to systematically explore the causal relationship between dietary factors and kidney cancer risk. A total of 59 SNPs were identified as IVs related to frequent alcohol consumption, with their F-values ranging from 34.28 to 811.86, all indicating strong instruments (Supplementary File: Table S1). A total of 66 SNPs were identified as IVs related to salt consumption, with F-values ranging from 30.10 to 182.91, showing no weak instrument bias (Supplementary File : Table S2). A total of 9 SNPs were identified as IVs related to dessert consumption, with F-values ranging from 20.96 to 26.01 (Supplementary File : Table S3). A total of 54 SNPs were identified as IVs related to fruit consumption, with F-values ranging from 29.95 to 144.02, indicating no weak instrument bias (Supplementary File : Table S4).

In this MR analysis, the IVW assessment showed that frequent alcohol consumption causally affects kidney cancer risk (OR = 1.61, 95% CI: 1.02–2.54, P = 0.040) (Figs. 2 and 3). The related P-values for MR-Egger intercept test and Cochran’s Q test were both above 0.05, indicating strong robustness of the MR results, with no heterogeneity or pleiotropy observed (Table 1). However, no significant causal relationships were observed between alcohol consumption (OR = 1.12, 95% CI: 0.91–1.37, P = 0.280), dessert consumption (OR = 1.23, 95% CI: 0.71–2.12, P = 0.465), added salt consumption (OR = 0.01, 95% CI: 0.00-1.49, P = 0.073), or fruit consumption (OR = 1.33, 95% CI: 0.59-3.00, P = 0.494) and kidney cancer (Fig. S1, Figs. 2 and 3), with sensitivity analyses revealing no pleiotropy or heterogeneity (Table 1). Scatter plots, leave-one-out plots and funnel plots are shown in Figs. 4, 5 and 6. These findings suggest that dietary factors can influence the risk of kidney cancer, with frequent alcohol consumption increasing the risk.

Fig. 2.

Fig. 2

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The potential relationship between four dietary factors and kidney cancer

Fig. 3.

Fig. 3

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Forest plot of the two-sample bidirectional Mendelian randomization estimates for the association between genetically predicted dietary factors and kidney cancer. IVW: Inverse Variance Weighted; SNP: Single Nucleotide Polymorphisms

Table 1.

The Mendelian randomisation estimates for genetically predicted risk of outcome based on the exposure

Exposure Outcome SNPs P IVW Or (95% CI) P MR−PRESSO P Cochran’s Q P MR−Egger
Dessert consumption kidney cancer 9 0.465 1.226(0.710 to 2.117) 0.271 0.259 0.932
Fruit consumption kidney cancer 54 0.494 1.329(0.588 to 3.001) 0.239 0.224 0.814
Frequent alcohol consumption kidney cancer 59 0.040 1.612(1.022 to 2.541) 0.402 0.397 0.709
Added salt consumption kidney cancer 66 0.073 0.014(0 to 1.490) 0.911 0.904 0.936
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IVW: Inverse Variance Weighted. MR: Mendelian randomization. SNP: Single Nucleotide Polymorphisms. MR-PRESSO: MR-Pleiotropy Residual Sum and Outlier. PMR-Egger intercept: p-value from the MR-Egger intercept test

Fig. 4.

Fig. 4

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Scatter plots for the causal association between dietary factors and kidney cancer. A: Added salt consumption and kidney cancer; B: Frequent alcohol consumption and kidney cancer; C: fruit consumption and kidney cancer; D: dessert consumption and kidney cancer

Fig. 5.

Fig. 5

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Leave-one-out plots for the causal association between dietary factors and kidney cancer. A: Added salt consumption and kidney cancer; B: Frequent alcohol consumption and kidney cancer; C: fruit consumption and kidney cancer; D: dessert consumption and kidney cancer

Fig. 6.

Fig. 6

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Funnel plots for the causal association between dietary factors and kidney cancer. A: Added salt consumption and kidney cancer; B: Frequent alcohol consumption and kidney cancer; C: fruit consumption and kidney cancer; D: dessert consumption and kidney cancer

Discussion

To our knowledge, this is the first study to systematically explore the causal relationships between dietary factors such as alcohol, dessert, salt, and fruit, and the risk of kidney cancer using a two-sample MR approach. The IVW estimate suggests that frequent alcohol consumption increases the risk of kidney cancer, while no significant causal relationships were found between the consumption of dessert, added salt, or fruit and kidney cancer.

Kidney cancer, a common malignancy within the urinary system, poses significant challenges due to its increasing incidence and the decreasing age of onset for patients and healthcare providers alike [3]. In recent years, early prevention and screening of kidney cancer have garnered extensive attention from researchers [25–27]. Studies indicate that poor lifestyle habits, such as smoking, obesity, and hypertension, can influence the risk of kidney cancer [3, 28]. However, the causal relationships between some daily dietary factors like alcohol, salt, and fruit, and kidney cancer remain unclear.

Research shows that alcohol consumption is associated with the occurrence of various cancers, such as liver cancer, pancreatic cancer, prostate cancer, etc. Alcohol metabolism in the human body is influenced by enzymes like alcohol dehydrogenase and cytochrome P450, among other ethanol-metabolizing enzymes [29]. Metabolic products such as acetaldehyde and reactive oxygen species can promote inflammation, tissue damage, and carcinogenesis in various tissues by inducing stem cell differentiation defects and DNA damage [30, 31] However, the causal relationship between alcohol consumption and the risk of kidney cancer still requires further study. Our two-sample Mendelian randomization study found no causal relationship between alcohol consumption alone and the risk of renal cancer. However, frequent alcohol consumption was associated with an increased risk of renal cancer, which is consistent with the findings reported by Huang et al. [28], who noted a positive correlation between alcohol frequency rates and the age-standardized rates (ASR) of kidney cancer incidence and mortality through an analysis of data on over one million cancer cases. Multivariate regression analysis indicated that frequent alcohol consumption is a significant risk factor for both the incidence and mortality of kidney cancer patients. Interestingly, a retrospective study by Song et al. [8] suggested that moderate frequent alcohol consumption could reduce the risk of kidney cancer, unaffected by gender, smoking status, or hypertension. A meta-analysis by Xu et al. [32] indicated that an increase of 5 g/day in alcohol consumption could reduce the risk of kidney cancer by 5% in men and 9% in women. It is evident that the relationship between alcohol consumption and the risk of kidney cancer is complex. frequent alcohol consumption is not solely associated with an increased risk of kidney cancer; moderate alcohol consumption may potentially reduce the risk of kidney cancer occurrence. This view is also supported by the latest guidelines from the EAU.

Fruits are rich sources of vitamin C, dietary fiber, and minerals, essential for human nutrition and known for their anti-cancer properties [33, 34]. A prospective cohort study by Wu et al. [35] demonstrated an association between increased fruit consumption and reduced risk of colorectal polyps in patients with colorectal cancer. The high dietary fiber content in fruits has been linked to a decreased risk of several site-specific cancers, including kidney cancer [36]. Additionally, a study in Canada also found a negative correlation between high fruit consumption and the risk of kidney cancer in women. Furthermore, a case-control study on the risk of kidney cancer in the United States [37] indicated that low fruit consumption is associated with an increased risk of kidney cancer among non-smokers. In the European Prospective Investigation into Cancer and Nutrition (EPIC) study, higher consumption of natural fruit juice was associated with higher mortality rates from kidney cancer in women [38]. However, observational studies conducted by BERTOIA et al. [39] suggested no association between fruit consumption and the risk of kidney cancer. Therefore, to further investigate the relationship between fruit consumption and kidney cancer, we conducted a MR analysis. However, the IVW assessment did not reveal a clear causal relationship between fruit consumption and the risk of kidney cancer.

Desserts contain high levels of sugar, sucrose, fructose, glucose, and maltose [40]. A previous Italian case-control study mentioned an association between sweet consumption and the risk of disease in both men and women. Excessive consumption of desserts can lead to elevated blood sugar levels. The safe range of sugar consumption has always been a concern for healthcare professionals and the general public, as excessive consumption can pose significant health risks due to hyperglycemia. High sugar consumption has been shown to independently promote chronic activation of the insulin signaling pathway, oxidative stress, and increased inflammatory markers, thereby increasing the risk of cancer [41]. The disease most closely associated with blood sugar is diabetes, which is a leading cause of death in many countries. Research by Li et al. [42] indicates that the younger the age at diagnosis of diabetes, the higher the risk of kidney cancer, and compared to the general population, patients with type 2 diabetes mellitus (T2DM) have a higher incidence of kidney cancer. Diet is a key modifiable factor affecting diabetes. To investigate whether dessert can directly influence the occurrence of kidney cancer and to eliminate the influence of confounding factors, we conducted a MR analysis, which showed no significant causal relationship between dessert consumption and the risk of kidney cancer according to the IVW assessment.

Epidemiological studies in the general population indicate that dietary salt consumption is associated with an increased risk of hypertension and kidney-related diseases [43]. The groundbreaking work of Dr. Lewis K. Dahl established the relationship between the kidneys, salt, and hypertension. Excessive salt consumption can lead to elevated blood pressure, which is the most common health complication worldwide. Increased levels of aldosterone and angiotensin II in hypertensive patients may exert genotoxic effects in vitro, potentially leading to carcinogenesis. A prospective study by Deckers [44] assessing kidney cancer found that high sodium consumption increases the risk of kidney cancer in healthy individuals. Both the World Health Organization and other organizations recommend limiting salt consumption to reduce the incidence of kidney and cardiovascular diseases. Added salt consumption has been shown to have a negative correlation with chronic kidney disease and kidney cancer. To confirm the relationship between added salt consumption and kidney cancer with high-level evidence, we conducted MR analysis, which did not support a causal relationship between salt consumption and kidney cancer.

Overall, the influence of diabetes and hypertension on the risk of kidney cancer is widely recognized by researchers, yet our MR study did not find a causal relationship between dessert and salt consumption and the risk of kidney cancer. This may be because sugar and added salt consumption cannot be equated with diabetes and hypertension, and an increase in dessert and salt consumption within a certain range may not alter the risk of kidney cancer. This also underscores the need for more comprehensive and clearly categorized GWAS-related data to systematically explore the causal relationship between varying levels of dessert and salt consumption and kidney cancer.

The study has several strengths. Firstly, to our knowledge, this is the first investigation into the causal relationship between dietary factors (dessert, salt, alcohol, fruit) and the risk of kidney cancer using a two-sample MR approach. Secondly, utilizing genetic variation as IVs to explore the causal relationship between exposure factors and outcomes is not influenced by confounding factors (such as diabetes, hypertension) or reverse causation. Thirdly, we employed three MR methods to study the causal relationship between dietary factors and kidney cancer and validated the stability of the results through various sensitivity analyses. However, there are also some limitations to this study. Firstly, the distribution of kidney cancer patients shows significant geographical variations, with the highest incidence rates in developed Western countries such as North America and Western Europe, and the lowest rates in developing countries such as Africa and Asia. Since the data primarily came from Europe in this study, the causal relationship between these dietary factors and the risk of kidney cancer in other populations remains unknown. This is especially relevant considering the strong correlation between diet, environmental exposure, lifestyle, socioeconomic status, and education [45]. Secondly, the related GWAS data are not comprehensive enough to systematically study the causal relationship between different levels of alcohol consumption (moderate, excessive) and different levels of dessert and salt consumption and the risk of kidney cancer. Moreover, the use of GWAS summary-level data limited our ability to explore potential non-linear relationships, such as threshold effects of alcohol consumption on kidney cancer risk. Individual-level data or more refined genetic instruments are needed to capture the full spectrum of dose–response associations. Thirdly, due to the limitations of the GWAS summary data used, we were unable to conduct stratified analyses by renal cell carcinoma subtypes, such as clear cell and non-clear cell carcinoma, which may have different etiologies. Future studies with subtype-specific data are needed to address this gap. Additionally, the GWAS data on salt consumption in this study were primarily based on self-reported measures, which may involve measurement error. Future studies should adopt more objective assessments, such as urinary sodium biomarkers or dietary records, to improve data accuracy. What is more, this study did not explore potential interactions between different dietary factors. Future research combining individual-level data or employing multivariable MR models with interaction terms will be necessary to better understand the synergistic effects of complex dietary patterns on kidney cancer risk.

Conclusion

In conclusion, we conducted the first two-sample MR analysis to assess the causal relationship between dietary factors (dessert, salt, fruit, alcohol) and kidney cancer. We found that frequent alcohol consumption increases the risk of kidney cancer, while there is no clear causal relationship between the consumption of dessert, salt, fruit, and kidney cancer. This discovery not only paves the way for early prevention and screening diagnosis of kidney cancer but also contributes to the advancement of human health endeavors.

Supplementary Information

Supplementary Material 1 (25.5KB, xlsx)
Supplementary Material 2 (18.4MB, tif)

Acknowledgements

We sincerely gratitude the IEU Open GWAS project and GWAS Catalog database sharing the GWAS summary statistics.

Author contributions

Conceptualization: C.Z. and T.L.; Investigation and resources: C.Z., Z.J., and H.W.; Methodology and data analysis: C.Z. and T.L.; Writing—original draft: C.Z. and T.L.; Critical revision: Z.Y., W.S. and M.Z.; Funding acquisition: W.S.; All authors have reviewed, revised, and approved the final manuscript.

Funding

This study was funded by the Joint Co-construction Project of Henan Medical Science and Technology Tackling Program (LHGJ20230060).

Data availability

The Genome-Wide Association Studies (GWAS) summary data utilized in this study are publicly accessible. Specifically, alcohol intake data were obtained from the IEU Open GWAS project (https://gwas.mrcieu.ac.uk/); dessert intake data and added salt intake data and fruit intake data were sourced from the GWAS Catalog database (https://www.ebi.ac.uk/gwas/).

Declarations

Ethics approval

The GWAS summary data used in this study were sourced from public databases, therefore, it does not require ethical approval.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Congcong Zhu and Tonghu Liu contributed equally.

Contributor Information

Mengran Zhang, Email: 609186531@qq.com.

Weibo Sun, Email: gorph1@163.com.

Zechen Yan, Email: yanzechen@foxmail.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Sanderson E. Multivariable mendelian randomization and mediation. Cold Spring Harb Perspect Med. 2021. 10.1101/cshperspect.a038984. [DOI] [PMC free article] [PubMed]

Supplementary Materials

Supplementary Material 1 (25.5KB, xlsx)
Supplementary Material 2 (18.4MB, tif)

Data Availability Statement

The Genome-Wide Association Studies (GWAS) summary data utilized in this study are publicly accessible. Specifically, alcohol intake data were obtained from the IEU Open GWAS project (https://gwas.mrcieu.ac.uk/); dessert intake data and added salt intake data and fruit intake data were sourced from the GWAS Catalog database (https://www.ebi.ac.uk/gwas/).

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