Association between Periodontitis and nonalcoholic fatty liver disease: A two-sample Mendelian randomization study

doi:10.21203/rs.3.rs-4802910/v1

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Association between Periodontitis and nonalcoholic fatty liver disease: A two-sample Mendelian randomization study

https://doi.org/10.21203/rs.3.rs-4802910/v1

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Purpose

Previous epidemiological studies have shown significant associations between periodontitis disease (PD) and nonalcoholic fatty liver disease (NAFLD), but the causal relationship remains uncertain. We carried out a bidirectional two-sample Mendelian randomization (MR) analysis using a variety of MR techniques to investigate the causal relationship between these two diseases.

Materials and Methods

We performed a two-sample MR analysis using publicly released genome-wide association studies (GWAS) statistics. The main analysis used the inverse-variance weighted (IVW) method. To identify and account for the impact of horizontal pleiotropy, we used complementary techniques such as weighted median, weighted mode, simple mode, MR-Egger regression, and MR-pleiotropy residual sum and outlier.

Results

Genetically determined NAFLD did not have a causal effect on PD (OR = 0.958, 95% CI: 0.838–1.096, P = 0.539). Furthermore, we did not find a significant causal effect of PD on NAFLD in the reverse MR analysis. The results of MR-Egger regression, Weighted Median, and Weighted Mode methods were consistent with those of the IVW method. Horizontal pleiotropy was unlikely to distort the causal estimates according to the sensitivity analysis.

Clinical Significance

Despite observational studies finding a link between periodontitis and NAFLD, our MR analysis demonstrates a non-causal association between NAFLD and PD.

Health sciences/Diseases/Oral diseases/Periodontitis

Periodontitis disease (PD) is a chronic inflammatory condition that eventually destroys the periodontal tissue support, including the bone surrounding the teeth.¹ The clinical effects of periodontitis, such as tooth loss, have a significant detrimental impact on oral health-related quality of life.² Severe periodontitis was the sixth most common condition in the world, with an estimated 11% prevalence on average.³ According to the National Health and Nutrition Examination Survey from 2009 to 2014, periodontitis is a very common oral illness in US adults, which In the US, periodontitis affected 42% of dentate people aged 30 or older, with severe periodontitis affecting 7.8% of cases.⁴ According to reports, Periodontitis has been linked to a variety of diseases, including cardiovascular diseases,⁵ type II diabetic patients,⁶ chronic migraine,⁷ pneumonia mortality in hemodialysis patients,⁸ preeclampsia and nonalcoholic fatty liver disease.^{9, 10}

Nonalcoholic fatty liver disease (NAFLD) is a catch-all term for a wide range of lesions ranging from steatosis without necroinflammatory injury to active lesions of hepatocyte injury, cell death, and inflammation.¹¹ According to a survey, the combined global prevalence of NAFLD identified by imaging was predicted to be 25.24%.¹² NAFLD is a multisystem disease that affects extra-hepatic organs and regulatory pathways, so its clinical burden extends beyond liver-related morbidity and mortality.¹³

Some epidemiological studies have shown a relationship between Periodontitis and Nonalcoholic fatty liver disease. In a population-based study including 8,513 NHANES Ⅲ participants, Alazawi et al.¹⁰ discovered that NAFLD is related to PD, and the association is stronger with significant liver fibrosis. According to Masato et al.¹⁴, Porphyromonas gingivalis, a common bacterium with periodontal disease, may play a role in the development of nonalcoholic fatty liver disease. The causal relationship between PD and NAFLD, on the other hand, has yet to be established, which is extremely important and could improve our current understanding of PD and NAFLD pathogeneses.

Data Sources

This study utilized periodontitis information from the European samples of the FinnGen project (https://www.finngen.fi/en). NAFLD data from GWAS Catalog (https://www.ebi.ac.uk/), a database of publicly available datasets. The FinnGen Project is run by the University of Helsinki, and each study that was a part of it received approval from the regional institutional review board and ethics committee. To investigate the relationship between PD and NAFLD at the causal level, we carried out a bidirectional two-sample MR study. For the study, GWAS data were used to identify 3,837 cases and 242,518 control cases of PD, 8434 cases, and 770,180 control samples of NAFLD. All of these samples came from individuals with European ancestry, which can minimize potential bias due to demographic heterogeneity.

Statistical analysis for Mendelian randomization

Mendelian randomization (MR) is a statistical technique that can reveal causality and is based on whole genome sequencing data, which can effectively reduce bias, similar to RCT.¹⁵ MR uses genetic variants as instrumental variables (IVs) to determine whether risk factors have a causal effect on health outcomes.¹⁶ For MR, the inverse-variance weighted (IVW) method is used as the primary analytical method to examine the relationship between PD and NAFLD.¹⁷ We also estimated the effects using other statistical tests (the weighted median, MR-Egger regression methods, weighted mode method, and simple mode method).

The choice of IVs is crucial to the outcome of an MR research. A good IVs needs to satisfy three fundamental presumptions in order to allow impartial evaluation of the causal effect of the exposure on the result.¹⁸ (Fig. 1)

Correlation hypothesis: IVs are strongly correlated with exposure factors.

Exclusivity hypothesis: IV is independent of outcome.

Independence hypothesis: IV is not related to confounding factors.

We used the Two Sample MR (0.5.6) package and MRPRESSO (1.0) package in R for data analysis.¹⁹ The general process is as follows. First, the correlation settings are carried out, and the p < 5e-06 and F > 10 of the instrumental variables are extracted to the instrumental variables that have a strong correlation with the outcome.^{20, 21} Second, palindromic SNPs and SNPs with intermediate allele frequencies should be removed in a coordinated manner (LDr² < 0.001, distance = 10000kb). Third, the extracted instrumental variables (IVs) are compared to the outcome's SNPS. Finally, execute the Two Sample MR package as well as the other packages.

$$\:\text{F}=\frac{{\text{R}}^{2}(\text{n}-1-\text{k})}{(1-{\text{R}}^{2})\text{k}}$$

Detecting data heterogeneity and horizontal pleiotropy are additional tasks. The heterogeneity of IVs is defined as the presence of a difference between the two-sample data. In this study, the heterogeneity of IVs is primarily tested using the IVW analysis method; if the P value of the test result is greater than 0.05, it is thought that there is no heterogeneity between these IVs and there is good confidence. To identify potential heterogeneous SNPs, we performed a leave-one-out analysis. Assuming that instrumental variables can only affect outcomes through exposure, MR analysis assumes that horizontal pleiotropy of causal relationships between exposure and outcomes should be tested.²² We can evaluate directional pleiotropy by performing "MR-Egger regression". The intercept of MR-Ager will explain horizontal pleiotropy and a non-0 intercept indicates horizontal pleiotropy, indicating that the outcome existed before it was exposed.²³

Causal effects of NAFLD on PD

With NAFLD as the exposure and periodontitis as the outcome, 12 SNPs were extracted for the MR analysis. The findings showed that the weighted median had an OR of (OR=, 95%CI=, P=), as did the IVW (OR=, 95%CI=, P=). It showed that periodontitis and NAFLD were unrelated (Table 1 and Fig. 4). Heterogeneity among these IVs is revealed by Cochran's Q report (p < 0.05).

Table 1

Mendelian randomization estimates for the relationship between genetically instrumented PD and NAFLD
Outcome	Exposure	Method	OR	95%CI	P-value
PD	NAFLD	MR Egger	0.819	0.621–1.079	0.199
		Weighted median	0.903	0.765–1.067	0.233
		Inverse variance weighted	0.958	0.838–1.096	0.539
		Simple mode	0.844	0.606–1.174	0.344
		Weighted mode	0.875	0.726–1.056	0.203
NAFLD	PD	MR Egger	0.956	0.721–1.269	0.765
		Weighted median	0.918	0.816–1.033	0.157
		Inverse variance weighted	0.960	0.879–1.048	0.368
		Simple mode	0.900	0.746–1.086	0.296
		Weighted mode	0.904	0.757–1.079	0.288

Table 2 displays the relationship between NAFLD and periodontitis risk. The intercept = 0.0234 and p = 0.24 indicate that there is no horizontal pleiotropy among these IVs. Figure 2 (a and b) displays scatter plots of SNP effect sizes for PD and NAFLD. 20,165,507 people made up the total sample for PD, while 6,797,908 people made up the total sample for NAFLD. To determine the strength of IVs when an effector allele frequency (EAF) value was present, we computed R2 and F-statistics based on the EAF and effect estimate (BETA). The following equation was used to calculate the F statistics, which are used to test the strength of the association between the SNPs as instrumental variables and NAFLD, to evaluate the strength of the chosen SNPs.²⁴ The F-statistic values in this study are all greater than 10(Fig. 6), and the leave-one-out analysis did not reveal any high-impact points.

Table 2

Heterogeneity of Wald ratios and MR-Egger test for directional pleiotropy
Exposure	Heterogeneity
	Outcome	Q	df	P-value	I²
NAFLD	PD	7.4307	8	0.5645
PD	NAFLD	5.5593	11	0.9010
Exposure	MR-Egger test for directional pleiotropy
	Outcome	Intercept	SE	P-value
NAFLD	PD	0.0234	0.0183	0.2409
PD	NAFLD	0.0005	0.0202	0.9776

Causal effects of periodontitis on breast cancer

12 SNPs were extracted with PD as the exposure and NAFLD as the outcome. The results showed that IVW (OR = 0.9588, 95%CI = 0.8383–1.0966, P = 0.5396), MR-egger (OR = 0.8190, 95%CI = 0.6215–1.0793, P = 0.1992), and weighted median (OR = 0.9037, 95% CI = 0.7650–1.0675, P = 0.2338), which indicated that there was no causal association for PD and NAFLD (Table 1 and Figs. 2b and Figs. 3b). The F-statistic values are all greater than 10 (Fig. 6). The MR-Egger analysis revealed no horizontal pleiotropy (periodontitis and nonalcoholic fatty liver disease risk: intercept = 0.0005, P = 0.9776). (Table 2 and Fig. 3). The findings of the leave-one-out analysis did not reveal any evident irregularities(Fig. 3). Our findings refute the existence of a bidirectional genetic link between periodontitis and nonalcoholic fatty liver disease (Fig. 5).

Observational studies have inherent limitations such as reverse causation, measurement error, and underlying bias. To investigate the causal relationship between exposure phenotype and outcome phenotype, we used Mendelian randomization (MR) analysis, which includes germline genetic variants as instrumental variables (IVs) for exposure.²⁵ At the same time, three basic assumptions must be met by instrumental variables.²⁶ In this study, we conducted a bidirectional two-sample MR method to explore the causal relationship between PD and NAFLD in the population of European ancestry. In this study, there is no observed evidence to support the effect of NAFLD on PD risk in individuals of European descent, and vice versa.

The results of our MR analysis contradict the results of existing observational studies. There have been prior epidemiological studies that found a connection between PD and NAFLD. NAFLD and periodontitis share some risk factors, according to one study of Oral Diseases Associated with Nonalcoholic Fatty Liver Disease in the United States. It was discovered that those who had moderate-severe periodontitis had a higher risk of developing NAFLD (USON: OR = 1.54, 95% CI = 1.06 to 2.24; FS: OR = 3.10, 95% CI = 2.31 to 4.17; FLI: OR = 1.61, 95% CI = 1.13 to 2.28; US-FLI: OR = 2.21, 95% CI = 1.64 to 2.98).²⁷ A cross-sectional study conducted on the adult population of Korea at a national level has revealed that the existence of periodontal pockets could be associated independently with indicators of NAFLD.³⁰ Alazawi et al analyzed data from both a population-based survey and a patient-based study. Their findings indicate that NAFLD is linked to PD, and this association is particularly strong in cases where there is significant liver fibrosis.¹⁰

However, most of the evidence linking periodontitis and nonalcoholic fatty liver disease in humans comes from observational studies, which provide pathologic links. However, the causal relationship has not yet been established. one meta-analysis from the primary study found no correlation between NAFLD and PD, even after controlling for confounding variables like different metabolic parameters.²⁸ In another study, a systematic review and meta-analysis discovered a notable correlation between periodontitis and NAFLD. Nevertheless, the correlation lost its significance after adjusting for various metabolic parameters. This suggests that metabolic conditions, rather than periodontitis alone, are the predisposing factors for NAFLD.²⁹

Several possible reasons may explain the association between PD and NAFLD in observational studies. Firstly, it has been suggested that infection with high-virulence P. gingivalis may increase the risk of developing or worsening NAFLD/NASH. Studies have shown that the detection frequency of P. gingivalis in NAFLD patients is significantly higher than in non-NAFLD control subjects (46.7% vs. 21.7%, with an odds ratio of 3.16).¹⁴ Secondly, it has been reported that the development of NAFLD is promoted by the systemic inflammation and oxidative stress caused by PD.³⁰ Thirdly, Xu et al.³¹ discovered that genes associated with "dendritic cell migration" were found in modules highly relevant to both periodontitis and NAFLD. This suggests that the biological pathway of "dendritic cell migration" may indeed play a significant role in the development of both conditions. Fourthly, gut microbiome dysbiosis is strongly associated with closely associated with nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.³²

This MR study has certain limitations. Firstly, only European ancestry was represented in the sample population included in the MR analysis. Therefore, it is still necessary to confirm whether the results are truly representative of the population as a whole. Secondly, Participants in exposure and outcome studies may overlap, however, it is difficult to determine the degree of sample overlap. Therefore, the use of IVs in this study can reduce potential bias for sample overlap (F statistic considerably more than 10).³³ Thirdly, SNPs used as genetic tools have a weak correlation with PD and NAFLD, with P value thresholds < 1×10^− 6.

Current bidirectional MR studies have several advantages. Firstly, Bidirectional analysis ensures the inference of a bidirectional causal relationship between PD and arthritis. Secondly, MR analysis usually provides strong evidence in cases where the effect is, particularly small or non-existent.³⁴

Our data do not support either a genetically predicted causal correlation between NAFLD and PD or a genetically projected causal relationship between PD and NAFLD. To eventually obtain a more logical and effective outcome, updated MR analysis based on larger GWAS pooled data and additional genetic instruments is necessary to validate the findings of this work.

Conflict of interest

The authors have no conflict of interest to declare.

Author Contributions:

Both authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Yang Deng and Weiyue Kong. The first draft of the manuscript was written by Weiyue Kong, and all authors commented on previous versions of the manuscript. Yang Deng provided the methodology, reviewed the draft of the paper, and approved the final draft. Both authors read and approved the final manuscript.

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Association between Periodontitis and nonalcoholic fatty liver disease: A two-sample Mendelian randomization study

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