Genetically determined cheese intake and risk of arterial diseases, frailty, and oral disease: a Mendelian randomized study

doi:10.21203/rs.3.rs-3131350/v1

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Genetically determined cheese intake and risk of arterial diseases, frailty, and oral disease: a Mendelian randomized study

https://doi.org/10.21203/rs.3.rs-3131350/v1

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Background

Observational studies suggest a possible correlation between cheese intake and certain arterial diseases, frailty, and oral disease. However, the causal relationship between them is unclear.

Objective

The aim of this study was to investigate the possible causal effects of genetic prediction of cheese intake with certain arterial diseases, frailty, and oral disease.

Methods

This study explored possible causal effects of exposure and outcome based on data from genome-wide association studies in a two-sample Mendelian randomization (MR) study.

Results

The findings showed that genetically predicted cheese intake was associated with coronary atherosclerosis (odds ratio (OR) = 0.986; 95% confifidence interval (CI): 0.976–0.996; P = 0.0048), peripheral atherosclerosis (OR = 0.558; 95% CI: 0.369–0.843; P = 0.0056), atherosclerosis (excluding cerebral, coronary, and peripheral arteries) (OR = 0.803; 95% CI: 0.741–0.871; P = 0.0427), frailty index (OR = 0.803; 95%CI: 0.746–0.865; P = 9.36E-08), chronic periodontitis (OR = 0.558; 95% CI: 0.349–0.890; P = 0.0145 ) and acute periodontitis(OR = 0.235; 95% CI: 0.062–0.893; P = 0.0335) were negatively associated. Also, no association was observed between cheese intake and cerebral atherosclerosis (OR = 0.909; 95% CI: 0.073–11.288; P = 0.9408) and dental caries (OR = 1.018; 95% CI: 0.676–1.533; P = 0.9337).

Conclusion

This MR study found a negative association between cheese intake and coronary atherosclerosis, peripheral atherosclerosis, atherosclerosis (excluding cerebral, coronary, and peripheral arteries), frailty, and periodontitis.

cheese intake

atherosclerosis

frailty

dental caries

periodontitis

Mendelian randomization

Cheese is a fermented milk product and is constituted by solidification and precipitation of casein after acidification or fermentation. And cheese is rich in saturated fatty acids, which may be related to certain artery diseases, such as atherosclerosis. Correspondingly, the European Society of Cardiology's dietary guidelines recommend reducing saturated fat intake^[1]. However, moderate intake of whole- and low-fat dairy products was not found to increase the risk of cardiovascular disease. And small amounts of cheese and regular consumption of yogurt have even been linked to a protective effect^[2]. Not only that, fermented food has anti-atherosclerosis, anti-oxidation, anti-inflammatory, anti-diabetes, antibacterial and other effects^[3]. A recent research indicated that cheese intake was connected with a lower incidence of coronary heart disease (CHD) ^[4]. Meanwhile, a meta-analysis study showed that subjects who consumed high amounts of cheese had a 6% lower risk of stroke compared with those who consumed low amounts^[5]. According to 8 cohort studies, consuming more fermented dairy products was linked to a substantial 17% lower risk of cardiovascular disease than consuming less of them ^[6]. Milk, cheese, and yogurt seem to have a negative relationship with the risk of cardiovascular disease based on the evidence currently available ^[7].

Intake of cheese is not linked to a decreased incidence of periodontitis, despite the fact that it is a significant source of medium- and odd-chain saturated fats, trans fatty acids, branched-chain amino acids, vitamins, and calcium^{[8, 9]}. Consistently, cheese intake was negatively associated with dental caries and diets containing cheese increased calcium concentrations in dental plaque, so cheese may have a caries-preventive effect^{[10, 11]}. However, low cheese intake is associated with a reduced risk of dental caries in children and adolescents in the United States^[12]. A study has shown no substantial association between cheese, bread and butter, or milk intake and caries prevalence^[13]. Frailty is a geriatric syndrome that is strongly related with disability, mortality, and hospitalization and is generally measured using the frailty index (FI). Frailty involves multiple systemic impairments, but its association with cardiometabolic health is particularly prominent ^{[14, 15]}. In order to reduce frailty in elderly people, it is crucial to discover frailty preventive strategies. Protein intake is thought to be associated with the prevention of frailty^{[16, 17]}. Despite the fact that cheese is rich in high-quality protein, some scholarly studies have suggested that cheese intake may not be associated with frailty in adults ^{[18, 19]}. However, recent reports suggest that aged people who consume dairy products may experience a reduction in the risk of frailty ^[20].

Due to the potential for selectivity bias in conventional observational studies, we should nevertheless proceed with care when interpreting the aforementioned results. Because of confounding variables or reverse causation, observational studies may produce biased relationships ^[21]. However, the Mendelian randomization (MR) method uses genetic variation as instrumental variables (IVs) to provide unconfounded estimates ^[22] and is used to explore the causal effects of both factors. MR Research is not only not affected by traditional confounding, but its causal association also satisfies the time series. This study used extensive genome-wide association study (GWAS) data to examine possible causal links between cheese consumption and certain arterial diseases, frailty, and oral disease.

2.1.Study design

Single nucleotide polymorphisms (SNPs) significantly associated with cheese consumption were used as the IVs, and atherosclerosis, frailty, periodontitis, and dental caries were used as the outcome variables. Among them, IVs in MR studies are required to satisfy three core assumptions: (1) correlation assumption: strong correlation with exposure; (2) exclusivity assumption: independent of outcome; (3) independence assumption: independent of confounding factors ^{[23, 24]}.

2.2.Data sources

The data used in this study were obtained from the IEU OpenGWAS project (https://gwas.mrcieu.ac.uk/). The study on cheese intake included 451,486 European participants with 9,851,867 SNPs. The GWAS of coronary atherosclerosis included 14,334 cases versus 346,860 controls. Gwas of peripheral atherosclerosis included 6,631 cases versus 162,201 controls. Gwas of cerebral atherosclerosis included 104 cases versus 218,688 controls. Gwas of atherosclerosis (excluding cerebral, coronary and peripheral arteries) contained 6,599 cases versus 206,541 controls. Gwas of frailty index contained 175,226 participants. Gwas of chronic periodontitis contained 3,046 cases versus 195,395 controls. Gwas of acute periodontitis contained 367 cases versus 195,395 controls. Gwas of dental caries contained 4,170 cases with 195,395 controls.

2.3.Selection of instrumental variables

As tools for the MR analysis, all genetic variations with genome-wide significance (P < 5 × 10^− 8) were chosen. By removing SNPs within a 10,000 kb region with a r² < 0.001 threshold, the matching linkage disequilibrium was examined to see whether any SNPs were in a linkage disequilibrium state and the SNPs were independent. In addition, the F statistic was calculated to quantify the strength of genetic variation, while F > 10 was used as a strong correlation criterion to hopefully attenuate the effect of potential bias. Meanwhile, instrumental variable screening should eliminate confounding, extract information from outcomes, and eliminate palinemical SNPS after combining data sets. Finally, MR-PRESSO analysis was performed in this study to exclude any outliers with potential pleiotropy to ensure the reliability of MR estimates.

2.4.Mendelian randomization analysis

The MR methods used in this study were mainly inverse variance weighted (IVW), MR-Egger regression (MR-Egger regression), median weighting, maximum likelihood estimation, and robust adjusted profile score (MR.RAPS). The IVW method uses the ratio method to calculate the causality of individual genetic variance instrumental variables estimates, and the total estimates obtained by weighted linear regression for each set of estimates ^[25]. Because IVW method has relatively high testing ability, the IVW method was used as the preferred method for causal effect estimation in this study^[26].

2.5.Sensitivity analysis

Cochran's Q test was employed in this work to assess the heterogeneity of the IVW model; heterogeneity was present when P < 0.05, at which point the random effects IVW model was applied. The MR-Egger test for directional pleiotropy was used to determine whether the key MR assumptions had been violated as a result of this phenomenon. When the value of the intercept in MR-Egger is different from zero, the IVW estimate is considered biased. The intercept estimates the average pleiotropic effect across genetic variations. After eliminating each IV one at a time, the leave-one-out method is mostly utilized to calculate the MR results for the remaining IVs.

All analyses were performed using the package “Two-Sample-MR” (version 0.5.6) and “MR-PRESSO” (version 1.0) in R (version 4.2.3).

3.1. Inclusion of instrumental variables

In this study, 65 SNPs associated with cheese intake were included, all of which met the genome-wide significance threshold. F-values were all greater than 10 (14.011-14.212), suggesting that there were no potential weak instrumental variable bias. (Table 1). The detailed information is presented in TableS 1.

3.2. Results of two-sample Mendelian randomization

Table 1 displays the findings of the MR analysis, while Figures 1 and 2 respectively display the scatter and forest plots. The results of IVW analysis showed that genetic prediction of cheese intake was negatively associated with coronary atherosclerosis (OR = 0.986, 95%CI: 0.976-0.996, P = 0.0048), peripheral atherosclerosis (OR=0.558, 95% CI:0.369-0.843, P=0.0056), atherosclerosis (excluding cerebral, coronary and peripheral arteries) (OR = 0.803, 95% CI: 0.741-0.871, P = 0.0427), frailty index (OR =0.803, 95%CI: 0.746-0.865, P =9.36E-08), chronic periodontitis (OR = 0.558, 95% CI: 0.349-0.890, P = 0.0145 ) and acute periodontitis(OR = 0.235, 95% CI: 0.062-0.893, P = 0.0335). Conversely, there was no connection found between cheese intake and dental caries or cerebral atherosclerosis (all P > 0.05). When partial outcome heterogeneity was high (P > 0.05), IVW analysis under a random effects model was used to mitigate the effect of heterogeneity (Table 1).

TABLE 1. The results of Mendelian randomization analyses. MR-Egger; WM, weighted median; IVW, inverse-variance weighted; Ml, Maximum likelihood; MR.RAPS robust adjusted profile scor；SE, Standard error; CI, confidence interval; OR, odds ratio.

3.3 Sensitivity analysis

The results of MR-Egger analysis are shown in Table 2, and the Egger-intercept was close to 0, and the p-values were not statistically significant (p>0.05), indicating that the results of MR analysis were not affected by multi-effectiveness and the assumption of exclusivity can be considered to be valid (Table 2).

Although Cochran's Q test (P<0.05) found heterogeneity in coronary atherosclerosis, frailty (Table 2), the existence of heterogeneity does not mean that the IVW model is necessarily invalid. The results of the random-effects IVW analysis method suggested a causal relationship between cheese intake and both. At the same time, Cochran's Q statistic did not reveal significant heterogeneity (P < 0.05) for peripheral atherosclerosis, atherosclerosis (excluding cerebral, coronary, and peripheral arteries), frailty, periodontitis, and dental caries (Table 2). Funnel plots showed that all SNPs included were roughly symmetrical (Figure 4), indicating small differences between instrumental variables. After the Leave-one-out test, each SNP was eliminated in turn, and the remaining SNPs were largely located to the right or left of the null line, indicating that the MR analysis results of this study were robust (Figure 3).

TABLE 2. Sensitivity analysis of the causal relationship between cheese intake and Outcome variable. NA, Not available.

This study comprehensively assessed the link of causality between genetic susceptibility to cheese intake and certain vascular diseases, frailty, periodontitis, and dental caries using large-scale GWAS pooled data and Mendelian randomization analysis. The findings of gene prediction revealed that cheese intake was connected with coronary atherosclerosis, peripheral atherosclerosis, atherosclerosis (excluding cerebral, coronary, and peripheral arteries), frailty, and periodontitis in negative ways.

These outcomes demonstrate the need for more study on how cheese affects atherosclerosis through its nutritional components or specific mechanisms. Intake of full-fat or low-fat dairy products did not significantly upgrade LDL cholesterol, according to a meta-analysis. ^[27]. This may be related to the following mechanisms. First, probiotics have antioxidant and anti-inflammatory properties and lower cholesterol and blood pressure levels ^[28]. Among these, the hypotensive effect of probiotics acts through several mechanisms, such as modulation of the renin-angiotensin system^[29]. Not only that, by lowering levels of CRP, VCAM-1, and ICAM-1, probiotics in conventionally fermented cheese whey may have considerable anti-atherogenic capability in atherosclerotic rabbits. ^[30]. Second, it has been found that consuming more fermented dairy products is linked to decrease LDL cholesterol.^[31]. Cheese provides rich calcium and protein ^[32], where more calcium binds to fatty acids in the gut to create insoluble detergent that cause bile acids to be regenerated from hepatic cholesterol, lowering plasma cholesterol levels. And some researchers have suggested that saturated fat may reduce the ability to penetrate the arterial wall by increasing LDL particle size ^[33]. Notably, hypertension plays an integral role in the pathology of atherosclerosis. Third, consumption of calcium and dairy products is connected with a lower incidence of hypertension. ^{[34, 35]}. At the same time, minerals in dairy products, such as magnesium and potassium, are of great benefit for blood pressure regulation. Surprisingly, antihypertensive peptides have been identified in some cheeses and the antihypertensive activity of some peptides has been demonstrated in spontaneously hypertensive rats. For example, Gouda cheeses were shown to have highly high DPP-IV and ACE inhibitory actions as well as significant antioxidant properties. ^[36].

Cheese intake was negatively associated with frailty and periodontitis. On the one hand dairy products with dietary calcium may have a preventive impact on periodontal disease ^{[37, 38]}, and on the other hand dairy products may enhance oral microbiome and lower the incidence of periodontal disease in both children and adults. Moreover, higher dietary protein intake was inversely associated with frailty in old age^[39]. Cheese may be beneficial in old age frailty due to its richness in protein (mainly casein), fat, minerals, as well as vitamins, and folic acid. A recent MR study revealed that higher levels of protein nutrition can help reduce the risk of frailty ^[40]. In addition to this, frail patients usually exhibit higher levels of oxidative stress ^[41], and the frail state is accompanied by elevated inflammatory and coagulation factors^[42]. However, the protein, probiotics in cheese may help reduce inflammation levels. The richness of cheese in saturated fat has led to the narrow view that it is not beneficial to health, which may not be appropriate. This is because different types of lipids may have different cardiometabolic effects. A complex physical structure combining different nutrients may affect digestion, absorption and metabolism and affect the food's overall nutritional qualities^[43]. Currently, it may be more accurate to assess the food matrix, rather than just single nutrients, to assess the health effects of dairy products ^[44]. In conclusion, the biological functions of all the components in the matrix structure of dairy products should be included in the nutritional value of dairy products^[45].

The current study has the following advantages. First, compared with observational studies, MR studies overcome the bias caused by reverse causality and confounding risks. Second, to make sure the MR results in the initial analysis were accurate, sensitivity and pleiotropy evaluations were performed. This study does, however, have certain shortcomings. First off, the fact that our datasets comprised only European people restricted the application of the findings to groups outside of Europe. More research is required to confirm the relevance of these findings in future demographics and ethnicities. Second, the GWAS aggregate data utilized in the two-sample MR analysis made it challenging to stratify the study by gender and age since there was a lack of specific individual data. Further investigation may have been hampered by the wide variety in the content of the various varieties of cheese and the absence of data on the kind and frequency of cheese consumption. At last, notwithstanding the lack of indication of directional pleiotropy in the analysis, we should no longer rule out the association, which is almost completely mediated through different causal pathways.

The results of this study, which used MR approach to examine the causal relationships between cheese consumption and arterial diseases, frailty, and oral disease, revealed that genetically predicted cheese intake was negatively associated with coronary atherosclerosis, peripheral atherosclerosis, atherosclerosis (excluding cerebral, coronary, and peripheral arteries), frailty, and periodontitis. Additionally, there is no connection between cheese intake and cerebral atherosclerosis or dental decay. Future research is required to pinpoint the precise mechanism by which consuming cheese lowers the risk of atherosclerosis, frailty, and periodontitis.

ACE Angiotensin-converting enzyme

CI confifidence interval

CRP C-reactive protein

DPP-IV Dipeptidyl peptidase-4

GWAS genome-wide association study

HDL high-density lipoprotein

IV instrumental variable

IVW inverse-variance weighted

ICAM-1 Inter-Cellular adhesion molecule-1

LDL low-density lipoprotein

MR Mendelian randomization

OR odds ratio

RR relative ratio

SNP single-nucleotide polymorphism

VCAM-1 vascular cell adhesion molecule-1

Supplementary Materials: Table S1: The R2 and F-statistics for the genetic instruments.

Acknowledgments: We would especially like to thank The MRC Integrative Epidemiology Unit (IEU) at the University of Bristol for developing the IEU open GWAS study.

Funding: International Science and Technology Cooperation Program of Gansu Province, China ( 20YF3WA011) supported this study.

Availability of data and materials ：The datasets generated and analysed during the current study are available in the IEU open gwas project [https://gwas.mrcieu.ac.uk/], and the GWAS ID are ukb-b-1489, ukb-d-I9_CORATHER, finn-b-I9_CEREBATHER, finn-b-DM_PERIPHATHERO, finn-b-I9_ATHSCLE, ebi-a-GCST90020053, finn-b-K11_CARIES, finn-b-K11_PERIODON_CHRON and finn-b-K11_PERIODON_ACUTE, respectively.

Author Contributions: Conceptualization, Z.-Z. and P.-X.; methodology, Z.-Z.and J.-F.L.; software, C.-L.L.Z.A.W; validation, X.-H.L. and B.-W.W.; formal analysis, Y.-L.L. and R.-W.; investigation, Z.-Z., J.-F.L., and R.-Z.L.; resources, P.-X.; data curation, Z.-Z.; writing— original draft preparation, Z.-Z.; writing—review and editing, Z.-Z.and J.-F.L.; visualization, Z.-Z.; supervision, P.-X.; project administration, P.-X.; funding acquisition, P.-X.. Z.-Z. and J.-F.L. contribute equally and are co-fifirst authors of the article. P.-X. is corresponding authors of the article. All authors have read and agreed to the published version of the manuscript.

Corresponding author: Ping Xie.

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Conflflicts of Interest: All authors declare no conflflict of interest.

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No competing interests reported.

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Genetically determined cheese intake and risk of arterial diseases, frailty, and oral disease: a Mendelian randomized study

Status:

Version 1

Abstract

Figures

1. INTRODUCTION

2. MATERIALS AND METHODS

2.1.Study design

2.2.Data sources

2.3.Selection of instrumental variables

2.4.Mendelian randomization analysis

2.5.Sensitivity analysis

3. Results

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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