Results remained unaffected after exclusion of any single study. Subgroup analysis revealed significantly decreased FMD in NAFLD subjects diagnosed with liver ultrasound or liver biopsy compared with method combination or other methods, while no differences were observed according to the chosen cuff inflation threshold, the presence of a significant difference in obesity measures between the groups, or the type of the control group (age- and sex-matched vs. other). Funnel plot asymmetry was not observed. Finally, compared with patients with pure steatosis, individuals with nonalcoholic steatohepatitis had significantly lower FMD . In conclusion, FMD of the brachial artery, indicative of endothelial dysfunction, was significantly reduced in subjects with nonalcoholic fatty liver disease. Patients with nonalcoholic steatohepatitis might be facing a more pronounced endothelial impairment.Individuals with nonalcoholic fatty liver disease (NAFLD) are characterized by increased cardiovascular risk. Endothelial dysfunction, a mechanism implicated in those processes, may constitute the missing link in this interaction. Therefore, this systematic review and meta-analysis aims to evaluate the association of endothelial dysfunction, assessed by flow-mediated dilation (FMD) of the brachial artery, with NAFLD. We conducted a systematic literature search for studies assessing the difference in FMD between patients with NAFLD and controls. Exclusion criteria consisted of preclinical studies, studies in children/adolescents, no FMD assessment, and the absence of an NAFLD/control group. The database search identified 96 studies. Following the application of the exclusion criteria, 22 studies were included in the meta-analysis . Compared with controls, patients with NAFLD had significantly lower FMD% values (SMD: −1.37, 95% CI −1.91 to −0.83,  Nonalcoholic fatty liver disease (NAFLD) is a heterogeneous entity with rising incidence worldwide, as evidenced by reported contemporary epidemiologic trends . This maNAFLD terminology has been recently questioned, as experts presented significant drawbacks of this entity . To begiImportantly, NAFLD and NASH appear to confer a higher risk of incident cardiovascular events, independently of their known risk factors, as noted by the latest systematic review and meta-analysis conducted by Montovani et al. . MoreoveThis systematic review and meta-analysis was conducted in accordance to the guidelines of the 2020 Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) statement , as showWe performed a literature search in PubMed from inception to 27 February 2022 in order to detect studies assessing the brachial artery FMD in patients with NAFLD and a control group. The following search terms were used:  AND . The difference between the FMD of NAFLD patients and the control group was the primary outcome of interest. We excluded studies performed in preclinical models, children, or adolescents. Moreover, studies not using brachial FMD as the endothelial function assessment method, as well as those lacking an NAFLD group and/or a control group, were also excluded.The full text of the eligible studies was assessed by two independent review authors (P.T. and A.V.), who then proceeded to the data extraction that consisted of the FMD value (in %) in the NAFLD and the control group, publication year, method of NAFLD diagnosis , cuff inflation threshold during the FMD measurement procedure, study group features , and control group features . Consequently, the extracted data was cross-checked in a meeting. In the case of discrepancies in the data extraction, a third review author (R.G.K.), blinded to the initial data, was responsible for the reevaluation of the studies in question and making the final decision. Whenever significant information regarding FMD values was not included in the articles, we contacted corresponding authors via email. However, no replies were received after an attempt to contact the authors of two papers.Numerical values of data represented graphically were extrapolated using Adobe Photoshop CS6 whenever they were not reported in the text. All numerical continuous data were transformed to mean ± standard deviation for the final analysis, as previously described . Moreove2, with values of 25%, 50%, and 75% indicating mild, moderate, and substantial heterogeneity, respectively. A sensitivity analysis was conducted using the leave-one-out method and we additionally performed an influence analysis followed by an updated meta-analysis with the exclusion of the influential studies. Furthermore, graphic display of study heterogeneity (GOSH) plots were created, consisting of a combinatorial meta-analysis including 2k−1 analyses, with k representing the number of interventions. By using a κ-means algorithm and the Cook’s distance, studies were considered influential in cases where their Cook’s distance was over the calculated threshold. An updated meta-analysis was consequently conducted.We performed a meta-analysis to assess the difference in brachial FMD between individuals with NAFLD and a control group. Effect sizes were pooled via random-effect model and the results are expressed as uncorrected standardized mean difference (SMD), using the Cohen’s d as the effect size metric, with 95% confidence intervals (CI). Between-study heterogeneity was assessed through the calculation of Ip values of less than 0.05 signified statistical significance. All meta-analyses were generated using the meta and dmetar packages in R studio v.1.4.1106.The existence of publication bias was assessed by funnel plot inspection and Egger’s test. Furthermore, we carried out a subgroup analysis according to NAFLD diagnostic method, cuff inflation threshold, the presence of age- and sex-matched controls, and the presence of a significant difference in obesity prevalence across the examined groups. Last but not least, a meta-analysis of studies presenting FMD values in an NAFLD (pure steatosis) group and a NASH group was also performed, to assess the difference in FMD according to NAFLD severity. Database search provided 96 results . After eThe characteristics of the included studies are presented in p < 0.001) (2 = 98%). Omission of any single study did not alter the outcome of the results (2 = 61%) with little influence on the overall effect  . No indication of asymmetry was present upon funnel plot inspection and Egger’s regression test   . Substan results , while t< 0.001) . GOSH pl< 0.001) . After e = 0.17) . Most of = 0.17) .p for interaction = 0.23). When categorizing the studies according to the presence of an age- and sex-matched control group, no significant differences were observed (p for interaction = 0.60). Furthermore, although studies where nonsignificant differences in obesity measures had a lower effect size, this did not reach statistical significance (p for interaction = 0.38). Finally, we performed an analysis of studies involving participants with either histologically confirmed NASH or pure steatosis .A subgroup analysis was also conducted . Studiesteatosis . Based oThrough this systematic review and meta-analysis, based on 22 studies in adult humans, we tried to explore the association of NAFLD with endothelial dysfunction, a common pathophysiologic mechanism in cardiovascular diseases. Our results confirmed the hypothesis, highlighting the link between NAFLD and endothelial dysfunction, assessed via FMD of the brachial artery. Despite the substantial between-study heterogeneity that was noted, results were robust even after multiple sensitivity analyses. Moreover, the advanced form of the disease, NASH, may be associated with an even more severe endothelial impairment.NAFLD represents a pathologic state with increasing incidence rates across the past decades. Initially evident as pure steatosis, NAFLD may progress to NASH and later to liver fibrosis. Diagnosis of NAFLD is based mostly on ultrasound investigation of the liver or characteristic histologic changes in the absence of notable alcohol consumption or other etiologies of chronic liver diseases . Risk scFrequent reevaluation of patients with NAFLD is important, since a significant proportion will develop NASH and fibrosis, while others may exhibit disease regression . The timThe components of metabolic syndrome are the most frequent risk factors associated with its occurrence. This fact has urged experts to reconsider the previously set terminology in order to stress the metabolic abnormalities that surround it. Therefore, future studies are needed to unveil novel diagnostic criteria and therapeutic interventions towards the MAFLD . The undConcerning the cardiovascular complications, a recently reported meta-analysis of 34,043 patients presented a 64% higher risk of developing major adverse cardiovascular events for NAFLD patients compared with those without NAFLD, with a median follow-up of 7 years . The sevThe relationship between NAFLD and endothelial dysfunction may be important regarding the cardiovascular manifestations of NAFLD patients. This metabolic liver disease might be an independent aggravating factor towards endothelial impairment . Such anAn inverse association between endothelial dysfunction and NAFLD has also been suggested. Preexisting endothelial impairment could promote metabolic hepatopathy owing to lower nitric oxide bioavailability and, consequently, hepatic stellate cell activation and sinusoidal thrombosis . The rolThe promotion of endothelial dysfunction in cases of NAFLD, as indicated by our study results, may mediate the excess cardiovascular-related morbidity and mortality. Thus, our study may have important implications, suggesting the evaluation of FMD in patients with NAFLD. Initially, ultrasonographic evaluation of steatosis, a cardinal feature of NAFLD, together with impaired FMD, could efficiently and reliably indicate a patient at an already increased risk for incident cardiovascular events who might benefit from early lifestyle modifications and pharmacological treatment for the strict control of risk factors. Moreover, adequate staging with imaging-based or histologic evaluation of hepatic inflammation and fibrosis represents an essential approach in high-risk patients with NAFLD . TherefoSeveral limitations of our study should be stressed. To begin with, the use of formulas for approximation of means and standard deviations from other summary measures, as well as the combination of means and standard deviations of different groups, may have had an influence on the overall findings. In addition, the overall results of our meta-analysis should be interpreted with caution on the basis of the considerable between-study heterogeneity. Sensitivity analyses attenuated the degree of heterogeneity to an extent. Moreover, the studies with nonsignificant differences in obesity measures were few, an observation which may have underestimated the importance of this factor in the NAFLD-related endothelial dysfunction.Our systematic review and meta-analysis highlights the association of nonalcoholic fatty liver disease with endothelial dysfunction, assessed by the flow-mediated dilation of the brachial artery. Patients with nonalcoholic steatohepatitis might be facing a more pronounced endothelial impairment. Our findings provide the rationale for endothelial dysfunction screening in this patient population, since the degree of endothelial impairment might indicate an advanced form of the disease, related to an adverse hepatic and cardiovascular prognosis.


Rheumatoid arthritis (RA) and Parkinson's disease (PD) are two common chronic diseases worldwide, and any potential link between the two would significantly impact public health practice. Considering the current inconsistent evidence, we conducted a meta-analysis and systematic review to examine the risk of PD in patients with RA.Two investigators (DL and XH) conducted a comprehensive search of PubMed, Embase, and Web of Science using medical subject headings terms combined with free words to identify relevant papers published from inception through December 31, 2021. All studies that explored the relationship between RA and PD were included for quantitative analysis and qualitative review. Random- and fixed-effects models were used to pool the risk ratios (RRs) of PD in patients with RA. The Newcastle-Ottawa scale was used to assess the quality of included studies. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guideline.P = 0.034). No apparent effects of gender, age, region, follow-up time, or study design on PD risk were observed. Sensitivity analysis showed that pooled results were relatively stable, and no publication bias was detected. The Mendelian randomization study indicated a significant inverse association between RA and PD  and that each one standard deviation increase in the risk of RA was significantly associated with a lower risk of PD. Of note, the current study is limited by the relatively small number of included studies and unmeasured confounding factors, especially for RA-related anti-inflammatory agents.Four population-based studies involving 353,246 patients and one Mendelian randomized study were included in our study. The pooled result showed a significantly reduced risk of PD in patients with RA than in the general population (RR = 0.74, 95% CI: 0.56-0.98, This study supports that people with RA had a lower PD risk than those without RA. Further studies are needed to explore the underlying molecular mechanisms of the interaction between the two diseases. Parkinson's disease (PD) is a chronic progressive motor dysfunction characterized by static tremor, rigidity, and bradykinesia –4. As thRheumatoid arthritis (RA) is an inflammatory autoimmune disease. Similar to PD, RA is a common chronic disease that affects approximately 1% of people worldwide . RA can Both RA and PD are highly prevalent diseases worldwide, and any correlation between the two would have important implications for public health practice and potentially provide new targets and ideas for the management of PD. Considering the current conflicting evidence and the lack of a study comprehensively summarizing current data, we conducted this meta-analysis and systematic review to elucidate the impact of RA on PD risk and provide higher quality evidence.This study was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines . The proTwo investigators (DL and XH) independently searched PubMed, Embase, and Web of Science databases for relevant literature published from inception through December 31, 2021. The search strategy consisted of subject terms  and synonyms  for RA and PD; the medical subject headings terms were linked by “AND” and the synonyms by “OR.” No language restrictions or filters were used. The specific search strategy for each database is available in the Studies that fulfilled all of the following criteria would be considered for inclusion in meta-analysis: (1) RA and PD were clearly defined or met diagnostic criteria, such as the readable codes or standard clinical diagnostic criteria; (2) correlations between RA and risk of PD were explored; (3) studies reported relative risk estimates and corresponding 95% confidence intervals (CIs), such as risk ratio (RR), hazard ratio (HR), odds ratio (OR), and standardized incidence ratio (SIR), or provided sufficient data to calculate these ratios; and (4) the study design was a longitudinal observational study, including case-control and cohort studies, whether prospective or retrospective.Studies meeting any of the following criteria would be excluded: (1) studies that did not generate original data, such as reviews, meta-analyses, commentaries; (2) non-human studies, such as cellular or animal model experiments; (3) case reports or case series of fewer than 10 patients; (4) overlapping study participants; for multiple studies from the same population, the study with the largest sample size and the most complete outcomes would be included.Studies that did not fully meet the above criteria but explored the association between RA and risk of PD would be qualitatively analyzed as part of the systematic review.Two investigators (DL and XH) independently screened the titles and abstracts of the initially retrieved records according to the eligibility criteria. Potentially eligible papers were read in full, and reasons for exclusion would be recorded.For included studies, two researchers independently (DL and TC) extracted the following information: first author, publication year, study period, age, gender, population source, sample size, study design, effect size, methods of PD and RA identification, adjusted/matched confounders, and follow-up time.The Newcastle-Ottawa scale (NOS) was used to assess the quality of included studies, and three main aspects were involved:  selectioQ-test and Higgins' I2 statistics; pooled results of the fixed-effects model were reported when I2 <50% and P > 0.1, otherwise, heterogeneity between the included studies was considered significant and results of the random-effects model were reported. We performed sensitivity analyses by excluding one study at a time and comparing the results of the fixed- and random-effects models. Publication bias was assessed by observing the symmetry of the funnel plot and performing Egger's and Begg's tests. We performed subgroup analyses according to age, sex, follow-up, region, and study design to explore the effects of these variables on the pooled results. Data for this study were analyzed using STATA/MP 16.0 . All P-values were two-tailed, and the statistical significance threshold was 0.05.We used fixed- and random-effects models to calculate pooled risk estimates of PD in RA patients compared to the non-RA population . For stuThe predeveloped database search strategies and browsing the reference lists of relevant papers yielded 2,295 records. After removing 875 duplicates and excluding 1,382 apparently irrelevant papers, 38 papers were read in full. Among them, 15 did not report results of interest, 9 were case reports or case series, 5 were cellular or animal model studies, and 4 had duplicate data. A total of five studies were finally included in this review .Of the eligible studies, four were population-based studies, and one was the Mendelian randomization study , 25, 26.The NOS scores of the included studies ranged from 7 to 9, indicating a high level of overall quality. These studies had clear exposure and outcome definitions, appropriate adjustment for confounders, and sufficiently long follow-up .2 = 87.9%, P < 0.001), so the random-effects model was used . Mendelian randomization analysis was performed in two samples and showed that each one standard deviation increase in the risk of RA was significantly associated with a lower risk of PD  .We performed stratified analyses according to sex, age (<65 vs. ≥65 years old), duration of follow-up (<5 vs. ≥5 years), region, and study design.No significant differences in effect sizes were observed between the above subgroups, and RA was associated with a reduced risk of PD in all conditions. However, the pooled results for age subgroups , European region , and cohort studies  were not statistically significant; this may be due to the small number and substantial heterogeneity of the included studies resulting in conservative confidence intervals .We performed sensitivity analyses to test the robustness of the combined results by two methods. First, the impact of individual studies on the overall pooled result was assessed by excluding one study at a time. Although the statistical significance of the pooled result disappeared after excluding certain studies, patients with RA still tended to have a lower risk of PD . In addiP-values for both Begg's and Egger's tests were >0.05 , indicating a low likelihood of potential publication bias.The funnel plot was not performed because of the small number of included studies at the end. The To our knowledge, this is the first study to systematically assess the association between RA and PD risk. The pooled result from four population-based studies showed a 26% reduction in the risk of PD among patients with RA compared to the general population. Despite the small number of included studies, the results from high-quality studies and more than 300,000 participants can be considered a stringent estimate. A Mendelian randomization study provided further strong evidence for the inverse association between RA and risk of PD. Overall, the inverse association between RA and PD risk is relatively stable in populations with different characteristics.I2 = 0%, P = 0.737), and the pooled results remained statistically significant . The cohort study by Li et al. used a database covering the Swedish Hospital Discharge Register from 1964 to 2007, and standardized incidence ratios were calculated by the ratio of observed to expected number of cases; they found no correlation between RA and risk of PD   . Interes . Intere89-1.26) .RA often requires treatment with anti-inflammatory drugs that may affect the correlation between RA and risk of PD. Drugs commonly used in RA patients are non-steroidal anti-inflammatory drugs (NSAIDs) and immunosuppressive drugs including traditional disease-modifying anti-rheumatic drugs (DMARDs)  and biologic DMARDs  , 28. SomAlthough our meta-analysis and Mendelian randomization study demonstrated that RA patients have a lower risk of PD, the exact mechanism of the reduced risk is unclear. In fact, the current results contradict the hypothesis on the pathological mechanisms of RA and PD. Inflammation is thought to play a critical role in RA and PD, and long-term chronic inflammation and excessive production of inflammatory mediators such as interleukin (IL)-1, IL-6, TNF-α, and chemokines may trigger inflammatory processes and activate microglia in the brain, leading to degeneration of dopaminergic neurons and an increased risk of PD , 44–46. First, the association between RA and PD may be influenced by lifestyle factors. A classic example is smoking; smoking is an important risk factor for RA but is associated with a reduced risk of PD , 47, 48.The strength of our study is that the pooled results from large sample size studies could provide a stringent estimate. Although there may be multiple theoretical mechanisms for the reduced risk of PD, the implications of anti-inflammatory drugs associated with RA are of interest. Due to limited data, subgroup analyses stratified by medications were not performed, but the study by Sung et al. provided evidence that biologic DMARDs use may reduce the risk of PD . PreviouThere are several limitations to this study that should be noted. The main limitation is the relatively small number of included studies, but the large sample and high-quality characteristics of these studies partially compensate for this and make the conclusions relatively stable. All included studies were derived from medical record databases and used readable codes to identify cases, whereas diagnostic criteria for PD and IBS may be inconsistent and subject to misdiagnosis and underdiagnosis. In addition, as discussed above, the results of observational studies may be biased by unmeasured and unconsidered variables.According to the meta-analysis of population-based studies and the Mendelian randomization study, patients with RA had a lower risk of developing PD than those without RA. The current results may be partially explained by anti-inflammatory drugs related to RA. Further studies are needed to explore the underlying molecular mechanisms of the interaction between the two diseases, which may help provide new insights into prevention and therapeutic targets for PD.The original contributions presented in the study are included in the article/DL contributed to the conception and design of the study. DL and XH performed the database search and study selection. DL and TC extracted data, conducted data analysis, and wrote the manuscript. XH checked and verified all data. All authors contributed to manuscript revision, read, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


A high dietary acid load (DAL) can produce metabolic acidosis, which is linked to cancer development through mechanisms of inflammation and cell transformation. There is limited epidemiological evidence linking DAL and cancer risk; however, none of the published studies focused on DAL and esophageal cancer (EC) risk in particular. Therefore, we sought to explore this association in the present study.A case‐control study was performed in 1295 male patients  through a multitopic inquiry, including a food frequency questionnaire. Food‐derived nutrients were calculated from available databases. The DAL was calculated based on two validated measures: Potential renal acid load (PRAL) score and net endogenous acid production (NEAP) score. Odds ratios (OR) and their 95% confidence intervals (95% CI) were estimated by unconditional logistic regression, adjusting for confounders.We found direct, significant associations between dietary acid load and EC risk:  and  for highest PRAL and NEAP tertiles, respectively. Our data raise the possibility that a high DAL may contribute to EC development. Both acid load scores were directly associated with animal‐based foods (mainly meat) and inversely associated with the intake of plant‐based foods.To the best of our knowledge, this is the first epidemiological case–control study analyzing associations of DAL and squamous cell EC risk. Further research is warranted to confirm our findings. Study summary. Modified from Servier Medical Art database by Servier (Creative Commons 3.0). Interestingly, analyzed by country, the extreme rates belong to Africa: the highest is in Malawi (18.7/105), whereas the lowest is in Guinea (0.42/105), making the ratio higher than 40:1.Esophageal cancer (EC) is the eighth most common cancer type worldwide and accounts for approximately 500 000 global cancer deaths annually.It has the potential to metastasize at early stages and is characterized by disproportionally high mortality rates and a poor prognosis.The two most common histological cancer types include esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC),In addition, tobacco smoking, alcohol drinking, and very hot “mate” drinking are already reported risk factors for ESCC.There are several established risk factors for EC that may also affect patient prognosis and survival. It is now widely accepted that EC is often preceded by chronic local inflammation in the esophagus which may alter normal cell signaling and growth.Of note, there is now increasing evidence highlighting the pivotal role of nutritional risk factor for esophageal cancer risk and prognosis.The composition of diet may also influence the body's acid–base balanceA high DAL has been associated with the following malignancies in large epidemiological studies on cancer: prostate,In light of the conceivable pathomechanisms that may link several cancers (particularly low‐grade chronic inflammation as a common risk factor for ESCC), we sought to address this gap in the literature. To investigate the potential association between an acidogenic diet and EC, we performed a case‐control study in Montevideo, Uruguay.This secondary data analysis uses data from a large Uruguayan multisite case‐control study investigating potential associations between environmental factors and the risk of cancer in the country's capital, Montevideo. The methods have been described previously in great detailn = 1295 individuals. We identified a total of n = 185 cases of esophageal cancer, which were matched to n = 1110 age‐ and residence‐matched controls that suffered from various nonmalignant disorders. This resembled a 1:6 matching ratio. All cancer cases and controls were identified during the same period and at the same institutions in order to minimize selection bias. All controls were admitted for medical conditions unrelated to stimulants . Controls that reported recent dietary modifications were excluded. Controls were admitted for the following medical conditions: abdominal hernia , eye disorders , urinary disorders , injuries and trauma , skin diseases , appendicitis , varicose veins , hydatid cyst , bone diseases , and other medical disorders .This secondary data analysis is based on a sample that comprised Following Dupont's suggestions, a value of 0.2 was assumed as the correlation for the exposure rates between cases and controls.The employed questionnaire covered sociodemographic and anthropometric variables. It has been described elsewhere in great detail.Two different markers were used to assess DAL in participants: Potential renal acid load (PRAL) and net endogenous acid production (NEAP).PRAL was calculated as follows:NEAP was estimated as follows:Negative PRAL scores reflect an alkaline‐forming potential, whereas positive scores indicate an acid‐forming potential. For NEAP scores, greater values indicate greater acid‐forming potentials.We used STATA software  to analyze our data. The majority of variables were treated as continuous, and categorization was done for analysis purposes only.Descriptive statistics included frequencies for categorical variables and means (standard error in parenthesis) for continuous, normally‐distributed variables. Inferential statistics included odds ratios (ORs) and their corresponding 95% confidence intervals (95% CI) which were calculated using unconditional logistic regression. Potential confounders that were included in the multivariate logistic regression models included age, residence, family history of cancer in first and second‐degree relatives, body mass index, total energy intake, smoking history, mate intake, ethanol intake, and iron intake.p‐value was less than 0.05.No participants were excluded as outliers for any dietary component. Heterogeneities in the stratified analyses were explored through likelihood‐ratio tests. Statistical results were regarded to be statistically significant when a two‐tailed All participants gave verbal and written consent to participate in this study.Table Table Table Table Our results demonstrate that higher acid load scores (both NEAP and PRAL) significantly increased the odds for ESCC. To the best of our knowledge, this is the first case‐control study to examine such an association in the English‐speaking scientific literature. Our findings are in line with two previous meta‐analyses that observed a significant association between higher DAL scores and the risk of cancer.Several plausible pathophysiological mechanisms may explain the observed associations. It is noteworthy that a high DAL has been linked with various EC risk factors, including obesity and visceral fat,Obesity significantly increases the risk of several chronic illnesses including cancer development.In this context, a 2019 meta‐analysis by Farhangi et al.p[trend] < 0.001), milk intake (p[trend] = 0.007) and phosphorus intake (p[trend] < 0.001). An inverse relationship was found for vegetables (p[trend] = 0.02) and beta‐carotene (p[trend] = 0.02). Findings by Crowe et al.The consumption of a high DAL diet abundant in protein was found to significantly increase IGF‐1 levels in patients with type 2 diabetes.Discussing DAL calculations, it is also essential to emphasize that PRAL‐lowering foods  are frequently associated with reduced odds for developing EC.Nevertheless, this study has an explorational character and is – to the best of our knowledge ‐ the first analysis to investigate potential associations between EC, particularly ESCC, and DAL. Additional trials are thus warranted to confirm our findings.Our study has multiple strengths and weaknesses that warrant a detailed discussion. As for the strengths, all the interviews with participants were done face‐to‐face (excluding proxy interviews) by the same interviewers at the same institutions to reduce potential selection bias. In addition, the selected population sample was comprehensive from the viewpoint of country areas and socioeconomic subsets. The low attrition rate of identified cases and controls (rates ~3%), favored by the interview performed during the hospital stay, limited possible selection bias. Another strength is the exclusion of individuals that reported previous (major) dietary modifications.As for the weaknesses, the study included a detailed but nonvalidated FFQ. However, as reported earlier, the FFQ was shown to be satisfactorily reproducible. Although our investigation dates back to the early 2000s, the general dietary habits have not changed a lot in Uruguay,In conclusion, we present evidence for a potential significant association between elevated DAL scores and increased odds for ESCC. In both cases, findings were supported by complex regression models adjusting for multiple confounders. This is the first study to suggest that an acidogenic diet high in animal protein may have contributed to an increased EC risk in the examined population. Our results are in line with several previous epidemiological studies on dietary patterns and EC risk. Nevertheless, additional investigations are warranted to confirm our findings, since there are two distinct subtypes of EC and the present study was focused on one of both.ALR participated in the original idea, design, data processing, statistical analyses, text redaction, and general supervision; MAS collaborated in the text redaction, draft supervision, graphic design, language checking, and general supervision; WML collaborated in the text supervision, biochemical and molecular supervision, and final draft supervision; JMC collaborated in tables design and the text supervision.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Abnormalities of the ERCC1 gene can affect DNA repair pathways, thereby having a vital effect on genomic stability. A growing amount of case-control studies have focused on making an investigation of the association between ERCC1 rs11615 polymorphism and cervical cancer susceptibility. However, the controversial results have raised concerns. To draw a more accurate conclusion, six studies were elaborately selected from the electronic databases for this meta-analysis, with 753 cervical cancer cases and 851 healthy controls. We applied pooled ORs combined with 95% CIs to test the potential associations. Significant associations were revealed in Chinese populations . Even when the studies deviating from HWE were excluded, an increased cervical cancer susceptibility was observed in Chinese. These results disclose that there is an obvious correlation between the risk of cervical cancer and ERCC1 rs11615 polymorphism, especially in Chinese populations, and the T variant is the risky one. Also, our findings need further studies to validate. Cervical cancer is the fourth most frequently diagnosed malignant tumor in clinical practice , and it DNA damage refers to changes in DNA composition and structure caused by various internal and external factors, including ionizing radiation, ultraviolet radiation, and free radicals , 8. TherAs a DNA repair protein, excision repair cross-complementation group 1 (ERCC1) participates in numerous DNA damage repair pathways, such as nucleotide excision repair (NER), basic excision repair (BER), inter-strand cross-linking (ICL) repair, and recombinant DNA repair –17. GeneIn the past, many literatures have studied the effect of ERCC1 polymorphism on cancers, especially ERCC1 rs3212986 and rs11615. For example, Bajpai et al.  have repBased on this hypothesis, we searched the literatures and found that the correlation between ERCC1 rs11615 polymorphism and susceptibility to cancers has been reported in multiple meta-analyses, such as breast cancer, lung cancer, pancreatic cancer, head-and-neck cancer, and colorectal cancer , 25–28. All relevant studies were independently searched and screened by two researchers. By entering the following keywords: ‘cervical cancer' or ‘cervical carcinoma' or ‘cervical neoplasm' and ‘SNP' or ‘polymorphism' or ‘genetic variant' and ‘ERCC1' or ‘excision repair cross-complementary group 1' or ‘rs11615', we retrieved correlative articles published in the CNKI, Embase, Pubmed, WanFang, and EBSCO databases up to September 2021. Additionally, we attempted to find potentially relevant studies from the abstracts, full texts, and reference lists of the identified articles.Articles selected for our meta-analysis should accord with the following criteria: (1) evaluating the correlation between ERCC1 rs11615 polymorphism and cervical cancer susceptibility; (2) human case-control study; and (3) containing complete genotyping data for calculation. Articles with repeated published data or which were case reports or conference reports or reviews and where genotype frequency or allele frequency could not be obtained were excluded. After identifying the original studies required, we performed a quality control assessment of the literature by using Newcastle-Ottawa Scale (NOS).Two researchers extracted the original data according to the selection criteria, and a third researcher assisted them if the collected data were found to be inconsistent. The information we collected was as follows: (1) first author; (2) published year; (3) country and ethnicity; (4) case number and control number; (5) genotyping method; (6) allele and genotype frequency; and (7) Hardy-Weinberg equilibrium (HWE) in controls .P < 0.05 indicates that HWE is not balanced [I2 test to detect heterogeneity, with I2 > 50% indicating significant heterogeneity, and Q-test with a P < 0.1 indicating that. When the result showed P > 0.1 and I2 < 50%, it means that no or low heterogeneity was found and a fixed-effects model could be utilized. If not, a random-effects model was selected [P < 0.05, it can be regarded as there is significant bias [In this study, almost all the analysis processes were accomplished by the STATA 12.0 software. A Chi-square test for the genotypes frequencies of controls was applied to judge whether it is in keeping with HWE; balanced . We usedselected , 32. Furant bias . Finallyhttps://github.com/ZYFNJMU/ERCC1-rs11615-and-cervical-cancer. The detailed procedure of literature selection and inclusion is shown in All the related scripts and supported data were uploaded on the Github page In the subgroup analysis based on country classification, four case-control studies on Chinese people were included. Since there are only two studies, respectively, for the people of Bangladesh and Korea, no subgroup analysis of Bangladeshi and Korean populations was performed. The results showed a growing risk of cervical cancer in the Chinese population in four models but not in the heterozygous model . We remoP > 0.1 and I2 < 50%; otherwise, we chose a random-effects model. When no studies were excluded, we found significant heterogeneity in six studies . In all analyses only about Chinese populations, we found there was nearly no heterogeneity.The results of heterogeneity testing are summarized in As mentioned earlier, sensitivity analysis was carried out by eliminating individual studies once to research the impact of individual studies on the whole. It can be seen that Das's study has a great influence on several models and Han's has a little influence . The resZ-curve sometimes crossed the traditional boundary, but never crossed the TSA boundary and required information size (RIS), suggesting the possibility of false positive errors. However, when only four literatures about Chinese were included, the Z-curve passed the traditional boundary and TSA boundary, suggesting that the results of the meta-analysis were stable, even if they did not reach RIS.As shown in Abnormal mechanisms of cell proliferation, differentiation, and death can lead to tumors. The specific mechanisms of their occurrence and development have always been the focus of research. However, as is known to all, abnormal gene structure, DNA damage, and abnormal expression or function of tumor genes and tumor suppressor genes are important preconditions for malignant transformation . TherefoSNPs are a common type of heritable variation in humans, and rs11615 (C > T) is a familiar polymorphism of the ERCC1 gene. As mentioned above, many meta-analyses have been reported about rs11615 and cancer. Most of the results show a significant correlation between multiple cancers and this mutation locus. For cervical cancer, Ma et al.  and XionThis meta-analysis is aimed at making an investigation into the correlation between ERCC1 rs11615 polymorphism and the risk of cervical cancer. In the process of literature searching, we were surprised to find a Genome-Wide Association Studies (GWAS) about cervical cancer from the Swedish population, which also reported the relationship between ERCC1 rs11615 and cervical cancer susceptibility, but unfortunately, it was difficult to obtain allele and genotype data from GWAS of cases and controls . TherefoIn addition, after sensitivity analysis, we found that Das's and Han's studies had a greater impact on the overall results, possibly because their case number was relatively larger compared to other studies, and they targeted, respectively, Bangladeshis and Korean people. They may also be the source of heterogeneity in our analysis. Our analysis after the exclusion of both Das's and Han's studies showed a stronger association and significantly reduced heterogeneity. This also reveals that our results are reliable for the Chinese. Unfortunately, other ethnic groups were not included in our analysis. As a result, the association of different ethnic groups is not fully understood at this time. Furthermore, we found no proof of publication bias in this study. Finally, our trial sequential analyses also suggested that the results of the meta-analysis were stable in Chinese populations.Therefore, based on the results of our meta-analysis and existing research reports, we believe that ERCC1 rs11615 polymorphism may reduce DNA repair ability by affecting its mRNA stability and protein expression level, leading to an increased risk of cervical cancer . ERCC1 hCertainly, limitations still exist in this meta-analysis. First, only six pieces of literature were included, with a relatively low case number; therefore, the risk assessment of ERCC1 rs11615 polymorphism was not clear enough. In addition, most of the data of cases and controls provided are from Chinese populations, and there is no information such as age, environmental factors, and sex, which cause it difficult for us to conduct more subgroup analyses.In brief, this meta-analysis put forward a conclusion that the ERCC1 rs11615 polymorphism increases cervical cancer susceptibility, especially in the Chinese populations, while TT genotype may have a higher risk. To promote in-depth research on genetic susceptibility to cervical cancer, more randomized controlled studies and systematic reviews with large samples, rigorous design, multicenter, and multilink will be of great importance and far-reaching significance.


Staphylococcus, Streptococcus, Neisseria, Prevotella, Fusobacterium, Porphyromonas, Herpes Simplex Virus I (HSV-1), Epstein-Barr Virus (EBV), Human Papilloma Virus (HPV), Candida plays an important role in OSCC. Increased microbial load affects tumor initiation and progression through direct effects on the tumor cells and indirectly through manipulation of the immune system. But the mechanisms describing the steps of oral microflora initiating the OSCC remain an enigma. This systematic review aims to understand the potential carcinogenic effect of oral microflora on OSCC. A systematic literature search was done in PubMed and Google Scholar databases, and six studies were obtained, comprising 1267 participants. The incidence was evaluated as an odds ratio (OR) with a 95% confidence interval (95% CI) using review manager 5.2 software. Oral microflora increased 2.10-fold risk of oral squamous cell carcinoma . In our subgroup analysis, there is a significant relation between Fusobacterium and oral squamous cell carcinoma . Individuals with Epstein-Barr Virus infection exhibit increased incidence of oral squamous cell carcinoma . The meta-analysis revealed that oral microflora increases the risk of oral squamous cell carcinoma.The oral cavity has the second largest and most diverse microflora. A wide variety of bacteria, viruses, and fungi are present in the oral cavity. A significant number of studies have shown the important role of oral microflora in the initiation and pathogenesis of oral squamous cell carcinoma (OSCC). Microorganisms like  Oral cancer is the eleventh most common cancer in the world . Its incHelicobacter pylori (H. pylori) in gastric cancer reported by various researchers led the World Health Organization International Agency for Research on Cancer (IARC) in 1994 to classify H. pylori as a definite cause of cancer in human beings [Staphylococcus, Streptococcus, Neisseria, Fusobacterium, and Porphyromonas but also viral and fungal species like Epstein-Barr Virus (EBV), Herpes Simplex virus-I (HSV-1), Human Papilloma Virus (HPV), Candida also play an important role in the initiation and carcinogenesis of OSCC. In this review, we conducted a systematic literature search in PubMed and Google Scholar on this topic, after which a meta-analysis was conducted to determine the potential carcinogenic effect of oral microflora on oral squamous cell carcinoma.Many reports have shown that microorganisms play an important role in carcinogenesis. Evidence describing the role of n beings ,9. Sincen beings . Based on beings . These mn beings . Intensen beings . Scientin beings . Not onlMethodsThe review was registered in Prospero. The registration id is CRD42022370586.Search strategyThe databases that were used for searching and collecting the articles were PubMed and Google Scholar, dated from its time of inception till December 2020. The search terms that were used to obtain the results were  OR (microbes)) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR (endodontic pathogens)) OR ) OR ) OR ) OR ) AND  OR (tumourigenesis)) OR (carcinogenesis)) ) OR (head and neck carcinoma)) OR (oncogenesis))) AND  OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) OR ) which resulted in 47 articles.Inclusion and exclusion criteriaInclusion CriteriaArticles that were published as original research. The diagnosis of oral squamous cell carcinoma was confirmed by pathological examination.Exclusion CriteriaReviews, meeting abstracts, animal studies, pilot studies, case reports, case series.Statistical analysisReview Manager 5.2 (Rev Man 5.2) was used for the statistical analysis. The heterogeneity between the included studies was calculated by using the I2 test. The random effect model was used to calculate the odds ratio (OR) and 95% confidence interval (CI). A two-tailed p-value of <0.05 was considered statistically significant.ResultsThe studies included in this article were selected by the process, which is summarized in Figure InterpretationAssociation Between Oral Microflora and Oral Squamous Cell CarcinomaStreptococcus , Prevotella , Neisseria , Porphyromonas , Herpes Simplex Virus-1 (HSV-1) . In our subgroup analysis, there is a significant relation between Fusobacterium and oral squamous cell carcinoma . Individuals with Epstein-Barr Virus (EBV) infection exhibit an increased incidence of oral squamous cell carcinoma . However, there was no significant relation between Heterogeneity and Sensitivity AnalysisStreptococcus  showed minimal evidence of heterogeneity, as discussed in Table There was evidence of heterogeneity in the overall effect of microflora and oral squamous cell carcinoma . In the subgroup, HSV-1 showed significant evidence of heterogeneity , and the subgroup of DiscussionOur meta-analysis included patient-level data on prognostic factors. The subgroup analysis was conducted and analyzed in 1,267 cases based on the characteristics, methodologies, and results of the study. We differentiated the effect of specific oral microorganisms and oral squamous cell carcinoma. From 17 studies, six studies were selected for the meta-analysis.Many studies have demonstrated that oral microflora participates in OSCC-promoting pathways. In our meta-analysis, we found that oral microflora increases 2.10 times the risk for oral squamous cell carcinoma, as shown in Figure Fusobacterium increased 4.86 times the risk for OSCC, as shown in Figure Fusobacterium may be because of the production of Matrix Metallo proteinase-13 (MMP) as a result of activation of mitogen-activated protein kinase p38, which leads to Heat shock protein (HSP-27) activation inducing MMP-9 which drives tumor invasion and metastasis [Fusobacterium synergistically induces the proinflammatory microenvironment along with other microflora through the recruitment of tumor-infiltrating cells, favoring tumorigenesis [In our analysis, we found that tastasis ,23. Fusoigenesis .Streptococcus species increase 0.58 times the risk for OSCC, as shown in Figure Streptococcus anginosus plays an important role in carcinogenesis through the integration of extrinsic Streptococcusanginosus DNA into the host genome, and another mechanism is a hit-and-run injury to the host genome. Streptococcus affects OSCC by producing lactic acid, acetic acid, butyric acid, isobutyric acid, and isovaleric acid, which reduces the environmental pH in OSCC, contributing to the growth and spread of OSCC [Various studies attempted in characterizing the relationship between oral microflora and OSCC. In our analysis, we found that  of OSCC .Neisseria increases 0.75 times the risk for OSCC, as shown in Figure Neisseria is that it is involved in the significant production of acetaldehyde from ethanol as it has a high alcohol dehydrogenase (ADH) activity [Neisseria species and thereby increasing the risk of OSCC [Since changes in the gut microbial composition may contribute to cancer initiation and progression . Oral miactivity . The add of OSCC .Prevotella increases 1.67 times the risk for OSCC, as shown in Figure Prevotellamelaninogenica is that alterations in tumor cell receptors could change the adhesion of certain specific bacteria [Prevotella on OSCC by stimulating the production of inflammatory mediators and having harmful effects on fibroblasts, epithelial and endothelial cells, and extracellular matrix components affecting the growth of local concentrations of cytokines like interleukin , tumor necrosis factor (TNF-α), MMP-8, MMP-9 [Bacteria at certain body sites have been believed to be involved in immune modulation and disease development . Our anabacteria . There a8, MMP-9 .Porphyromonas increases 2.98 times the risk for OSCC, as shown in Figure Porphyromonas gingivalis  inhibits macrophages from attacking the Cal-27 cells via membrane-component molecules [Porphyromonas. These compounds cause oxidative stress leading to DNA damage in oral calls. Low levels of hydrogen sulfide are sufficient to inhibit the enzyme superoxide dismutase, which is critical in preventing destructive reactive oxygen species (ROS) buildup in human cells, and methyl mercaptan has been implicated in collagen breakdown (type IV), leading to invasion of OSCC into basement membrane [Some periodontal pathogens might participate in various pathways to assist OSCC development. In our analysis, we found that olecules . Volatilmembrane .Virus plays an important role in carcinogenesis and increases the risk of OSCC. We observed that Epstein-Barr virus (EBV) increases 3.72 times the risk for oral squamous cell carcinoma, as shown in Figure Our study has shown that Herpes simplex virus-1 (HSV-1) increases 18.80 times the risk for OSCC, as shown in Figure Neisseria species present in our normal microflora have high ADH activity, and upon addition of ethanol by alcohol ingestion, Neisseria species will produce a significantly higher amount of acetaldehyde. The accumulation of acetaldehyde produced by Neisseria might be sufficient to affect the epithelial cells increasing the risk for OSCC. Habitual drinking provides Neisseria a growth advantage over ADH-negative bacteria. Not only alcohol drinking but also cigarette smoking also influenced the bacterial composition of the oral microflora [About six case-control studies subjected to meta-analysis revealed that the oral microflora increases 2.10 times the risk for oral squamous cell carcinoma. The risk notably decreased in patients with good oral hygiene. Alcoholics have an increased risk for OSCC. This is because generally the croflora . There aThough the meta-analysis has been done comprehensively, it has its limitations too. The included studies have been conducted in a diverse population, and each study included varied specimens and methods of analyzing the samples leading to varied heterogeneity. Future studies should consider focusing more on the effect of oral microflora on oral squamous cell carcinoma.To summarize, various pieces of research on the risk of microorganisms and oral squamous cell carcinoma have illuminated our knowledge of bacterial, viral, and fungal involvement in the carcinogenesis of oral squamous cell carcinoma. However, doubts about the role of microflora in initiation of oral squamous cell carcinoma still remain unclear. Further studies on investigating the role of microflora in the initiation of oral squamous cell carcinoma should be attempted to get a clear idea. It is also important to note that changes in oral microflora in oral squamous cell carcinoma may act as a diagnostic indicator. This meta-analysis suggested that oral microflora increases the risk of oral squamous cell carcinoma, which emphasizes that more focus on research is required in this area which could provide an important clue in the pathogenesis and treatment of OSCC.


Background and objective: Some variants in defensin beta 1 (DEFB1) and mannose-binding lectin 2 (MBL2) genes can be associated with oral diseases. Herein, we designed a systematic review and meta-analysis to evaluate the association of DEFB1  and MBL2 (rs7096206 and rs1800450) polymorphisms with the susceptibility to dental caries (DC) in children. Materials and methods: A systematic literature search was conducted in the PubMed/Medline, Web of Science, Scopus, and Cochrane Library databases until 3 December 2022, without any restrictions. The odds ratio (OR), along with a 95% confidence interval (CI) of the effect sizes, are reported. Analyses including a subgroup analysis, a sensitivity analysis, and funnel plot analyses were conducted. Results: A total of 416 records were identified among the databases, and nine articles were entered into the meta-analysis. A significant relationship was found between the T allele of DEFB1 rs11362 polymorphism and DC susceptibility, and the T allele was related to an elevated risk of DC in children . No other polymorphisms were associated with DC. All articles were of moderate quality. Egger’s test in homozygous and dominant models demonstrated a significant publication bias for the association of DEFB1 rs1799946 polymorphism with DC risk. Conclusions: The results demonstrated that the T allele of DEFB1 rs11362 polymorphism had an elevated risk for DC in children. However, there were only few studies that evaluated this association. Oral health is important for a child’s overall health and development . Dental Oral bacteria ,9, dietaDEFB1 gene and is the main molecule for protection from DC [The human beta-defensin 1 (DEFB1) is a 36-amino-acid antimicrobial peptide depending on the defensin family . This pe from DC , and it  from DC , salivar from DC , and gin from DC . The DEF from DC ,24.MBL2 gene [Mannose-binding lectin (MBL) is a protein molecule inherent to the immune system, in which the activation of lectin (ubiquitous carbohydrate-binding protein) domains are found in relation to collagenous structures ,26. MBL BL2 gene .DEFB1  and MBL2  polymorphisms with DC risk [DEFB1 rs11362 polymorphism [Two meta-analyses ,28 repormorphism . Both memorphism ,28 analymorphism ,30,31,32DEFB1 and MBL2 genes to have an influence on the progression of DC, the results are still unconfirmed and inconsistent. We designed a systematic review and meta-analysis to evaluate the association of DEFB1  and MBL2 (rs7096206 and rs1800450) polymorphisms with the risk of DC in children with more studies for the first time in the English literature based on our knowledge.Although some researchers have reported selected polymorphisms of the DEFB1 and MBL2 polymorphisms and susceptibility to DC? (P: Children with DC (CDC), E: DEFB1 and MBL2 polymorphisms, C: Children free of DC (CFC); O: DC).To design the study, the PRISMA guidelines provided in the The Scopus, PubMed/Medline, Cochrane Library, and Web of Science databases were searched by one author (M.S.) to retrieve records published until December 3, 2022, without any restrictions . The keywords or search terms were (“beta defensin*” or “β-defensin*” or “beta-defensin 1” or “β-defensin-1” or “beta-defensin-1” or “defensin beta 1” or “DEFB1” or “human beta-defensin-1” or “HBD-1” or “mannose-binding lectin” or “MBL” or “mannose binding lectin 2” or “MBL2” or “mannose binding lectin-2” or “MBL-2” or “mannan-binding lectin” or “mannan-binding protein” or “MBP”) and . Moreover, the citations of the retrieved original articles/reviews/meta-analyses linked to the subject were searched to ensure that no study was missed. A second reviewer (G.H.) evaluated the titles/abstracts of the articles linked to the subject; afterwards, the full texts of the articles that met the inclusion criteria were downloaded and screened. Any study that was excluded was tagged with the reason for exclusion. In the event of a lack of agreement among the authors, a third reviewer (M.M.I) was involved.The quality of studies was evaluated based on the modified Newcastle–Ottawa scale (NOS)  by two rDEFB1 or MBL2 genes including minimum two studies for the analysis with any amount of the Hardy–Weinberg equilibrium (HWE); and (IV) CDC and CFCs had no chronic illnesses, genetic diseases, or other disorders. Irrelevant studies, meta-analyses, studies without a control group, studies with insufficient data for analysis, case reports, and conference papers were excluded.The inclusion criteria were as follows: (I) any type of articles including two independent groups (CDC and CFCs); (II) studies with any defined DMFT/dmft score for CDC and CFCs; (III) studies including polymorphisms of . The extracted data were the name of first author, publication year of the study, country of origin of the study, number of CDC and CFCs, ethnicity, age range of individuals, investigated dentition, DMFT/dmft score of the CDC and CFCs, type of reported polymorphism(s), the quality score of each study, and effect sizes (odds ratio (OR) and 95% confidence interval (CI)) for DC occurrence of each polymorphism according to five genetic models.Two authors (S.B. and R.S.) independently extracted the data of the studies. Disagreement between the authors was resolved by a third author (P.C.)p-value (two-sided) less than 0.05 was considered significant. The I2 statistic was used to estimate heterogeneity, with I2 > 50% (Pheterogeneity < 0.1) recommending a significant heterogeneity, and we used the fixed-effects model [p-value (two-sided) was less than 0.10 (two-sided) for one and both tests, a significant publication bias was considered to be present. With regard to the stability of the results, two sensitivity analyses, including ‘one-study-removed’ and ‘cumulative analyses’ were carried out. A subgroup analysis based on ethnicity, type of dentition, and sample size was carried out for DEFB1 rs11362 polymorphism while such analysis wasn’t possible for MBL2 polymorphisms due to an insufficient number of studies.To compute the effect sizes (ORs and 95% CIs) and the rest of the analyses, two authors (G.H. and M.S.) independently used comprehensive meta-analysis version 2.0 (CMA 2.0) software. Disagreement between the authors was resolved by a third author (M.M.I.). A ts model . The pubts model ,38; if pBy searching the databases and electronic resources, 416 records were identified. After removing duplicates and irrelevant records, 16 full-text articles were obtained and, after that, assessed. Among the evaluated full-text articles, seven were excluded for different reasons . FinallyMBL2 [DEFB1 [The articles were published from 2005 to 2020 . Four arMBL2 ,43,44,452 [DEFB1 ,39,41,42DEFB1 rs11362 polymorphism and DC risk based on six studies for homozygous and heterozygous models and five for other models. The pooled ORs were 1.225 , 1.233 , 1.177 , 1.289 , and 1.207  in the allelic model (AM), the homozygous model (HoM), the heterozygous model (HeM), the dominant model (DM), and the recessive model (RM), respectively. There was only a significant relationship between the T allele of DEFB1 rs11362 polymorphism and DC risk.DEFB1 rs1799946 polymorphism and DC risk based on four studies. The pooled ORs were 0.935 , 0.824 , 1.040 , 0.987 , and 0.838  in AM, HoM, HeM, DM, and RM, respectively. There was no significant relationship between DEFB1 rs1799946 polymorphism and the DC susceptibility in any of the five genetic models.DEFB1 rs1800972 polymorphism and DC susceptibility based on three studies in two models. The pooled ORs were 0.952  and 1.285  in HoM and HeM, respectively. There was no significant association between DEFB1 rs1800972 polymorphism and susceptibility to DC.MBL2 rs7096206 polymorphism and DC susceptibility based on three studies in allelic models and two studies for other models. The pooled ORs were 0.970 , 0.894 , 0.771 , 0.791 , and 0.933  in AM, HoM, HeM, DM, and RM, respectively. There was no significant association between MBL2 rs7096206 polymorphism and susceptibility to DC.Forest plot in MBL2 rs1800450 polymorphism and DC susceptibility based on two studies. The pooled ORs were 1.488 , 2.730 , 1.413 , 1.493 , and 2.462  in AM, HoM, HeM, DM, and RM, respectively. There was no significant association between MBL2 rs1800450 polymorphism and susceptibility to DC.Forest plot in DEFB1 rs11362 polymorphism and susceptibility to DC. Among ethnicity, type of dentition, and sample size in the five genetic models, the TT + CT genotype in mixed ethnicity and T allele in deciduous dentition had elevated risks of DC. Therefore, ethnicity and type of dentition were significant factors for the association between DEFB1 rs11362 polymorphism and DC risk.The sensitivity analyses demonstrated stability of the results for all explorations where there were a minimum of three studies (results are not presented).DEFB1 rs1799946 polymorphism and DC risk showed a significant publication bias.The results of Egger’s and Begg’s tests were checked to evaluate the publication bias across the studies. The funnel plots are illustrated in the DEFB1  and MBL2  polymorphisms, just MBL2 rs11003125 had an association with the risk of DC, while another meta-analysis [DEFB1 rs11362 polymorphism to be associated with the risk of DC in permanent dentition, not deciduous or mixed dentitions. This systematic review evaluated the association of DEFB1  and MBL2 (rs7096206 and rs1800450) polymorphisms with DC risk; the findings suggest that DEFB1 rs11362 polymorphism in T allele is related to an increased likelihood of DC occurrence. In addition, ethnicity and type of dentition were significant factors in the subgroup analysis checking the relationship of DEFB1 rs11362 polymorphism with DC risk.A meta-analysis  reportedanalysis  found DEDC is a chronic disease that is usually affected by environmental and host agents and even genetic factors ,47,48,49There are many genetic agents that probably contribute to DC susceptibility and resistance, such as salivary agents, taste preference, tooth morphology, immune system, enamel structure and composition, organic and inorganic substances, and behavior ,52,53,54DEFB1 rs11362 polymorphism with susceptibility to DC in children. Other reports showed that Africans had 32% and Mixed ethnicities had 69% more DC experience than Whites [DEFB1 (rs1799946 and rs1800972) and MBL2 (rs7096206 and rs1800450) polymorphisms, we could not perform a subgroup analysis due to the limited number of reported studies. Therefore, a large number of studies are needed to prove the role of ethnicity in the prevalence of tooth decay. This can be due to the difference in ethnical factors  that have affected dental genetics over time. To find these relationships, further studies and further emphasis on ethnicity and the risk of DC in the future can be discussed in further possible mechanisms. With regard to the type of dentition, the etiology of dental anomalies is partly environmental and partly genetic [Two studies ,40 reporn Whites  and thatn Whites . For DEF genetic  and the DEFB1 rs1799946 polymorphism was related to the elevated risk of DC in children, and therefore, this can cause a reduction in DEFB1 and then oral infections. DC is caused by bacteria that destroy the enamel and dentin [DEFB1 polymorphisms could be considered in future studies for reaching better and more accurate results.DEFB1 as an oral antimicrobial peptide gives the first line of defense against an extensive range of pathogens ,64. The d dentin ,68,69. TMBL2 plays an important role in the innate immune system and few polymorphisms in this gene can be responsible for increased susceptibility to some infectious diseases [MBL2 (rs7096206 and rs1800450) polymorphisms, perhaps due to a limited number of included studies. Therefore, more studies are needed to support or reject the present meta-analysis results.The diseases ,71,72; tdiseases . The preThe role of oral peptides as therapeutic agents and for clinical assessment of an individual’s susceptibility to DC can be promising in the future ,75,76. OThis meta-analysis has three limitations: (1) There were a limited number of published studies, therefore, an inability to conduct subgroup analyses for most polymorphisms; therefore, more studies with more cases are needed to confirm the association of these polymorphisms with DC risk. (2) There was possibly a publication bias for some analyses, which could also be due to fewer studies being included in the analyses. (3) None of the studies were of high quality. In contrast, the stability of the results and low/lack of heterogeneity across the studies were the strengths of the meta-analysis.DEFB1 rs11362 polymorphism is associated with an increased likelihood of DC. Therefore, this polymorphism could have a significant role in the pathogenesis of DC. The limited number of studies and the moderate quality of the included studies demonstrate that well-designed studies with more cases are needed to confirm or reject the results.The findings suggest that the T allele of


Coronary artery disease (CAD) is a metabolically perturbed pathological condition. However, the knowledge of metabolic signatures on outcomes of CAD and their potential causal effects and impacts on left ventricular remodeling remains limited. We aim to assess the contribution of plasma metabolites to the risk of death and major adverse cardiovascular events (MACE) as well as left ventricular remodeling.l-thyronine, and kynurenine) for death  and metabolic signatures  for MACE  yielded better predictive value than trimethylamine N-oxide plus clinical model, which were successfully applied to predict patients with high risks of death (P = 0.0014) and MACE (P = 0.0008) in the multicenter validation cohort. Mendelian randomisation analysis showed that 11 genetically inferred metabolic signatures were significantly associated with risks of death or MACE, such as 4-acetamidobutyric acid, phenylacetyl-l-glutamine, tryptophan metabolites , and modified nucleosides  guanosine). Mediation analyses show that the association of these metabolites with the outcomes could be partly explained by their roles in promoting left ventricular dysfunction.In a prospective study with 1606 Chinese patients with CAD, we have identified and validated several independent metabolic signatures through widely-targeted metabolomics. The predictive model respectively integrating four metabolic signatures (dulcitol, β-pseudouridine, 3,3ʹ,5-Triiodo-This study provided new insights into the relationship between plasma metabolites and clinical outcomes and its intermediate pathological process left ventricular dysfunction in CAD. The predictive model integrating metabolites can help to improve the risk stratification for death and MACE in CAD. The metabolic signatures appear to increase death or MACE risks partly by promoting adverse left ventricular dysfunction, supporting potential therapeutic targets of CAD for further investigation.The online version contains supplementary material available at 10.1186/s13578-022-00863-x. Coronary artery disease (CAD) imposes a major burden on modern society with annual morbidity and mortality comparable to cancer –3. DespiCAD is a metabolically perturbed pathological condition , 11. PlaGiven the fact that metabolism has been closely implicated in CAD pathogenesis and development, there is a need to identify novel metabolic signatures and integrate the genetic regulation of circulating metabolites to improve understanding in causality, and thus provide potential pathological insights and therapeutic targets to improve CAD survival and prognosis. Therefore, we performed a study on 1606 Chinese patients with CAD through metabolomic profiling in plasma to evaluate the contribution of metabolites to the risks of death or MACE as well as LV remodeling and then built a good prognostic model based on metabolic signatures. Moreover, we further conducted Mendelian randomisation (MR) analysis by integrating genomic data to infer the potential causal effects of metabolites, and mediation analysis to explore possible mediation effects through promoting LV remodeling.The baseline characteristics are listed in Table It is noteworthy that adverse LV remodeling manifested as low LVEF and high LVMI was strongly related to increased death or MACE risks in CAD , see Fig. FDR = 3.27E−08), β-pseudouridine , dulcitol , (2-(dimethylamino) guanosine , S-(5-adenosy)-l-homocysteine  and kynurenine . In the multicenter validation cohort, 15 metabolites positively associated with the death risk were reproduced, including 4-acetamidobutyric acid, β-pseudouridine, 2-(dimethylamino) guanosine, S-(5-Adenosy)-l-homocysteine, kynurenine, cyclic AMP, adipic acid, 3-methylcrotonyl glycine, 5ʹ-deoxy-5ʹ-(methylthio) adenosine, Dl-P-hydroxyphenyllactic acid, D-sorbitol, Dulcitol, kynurenic acid, N6-succinyl adenosine, and N6-acetyl-l-Lysine.In the discovery phase, among the 202 metabolites, we identified 35 plasma metabolites that were significantly associated with the risks of death, and 24 metabolites remained significant after adjustment for confounding factors (FDR < 0.05) in the discovery phase, see Fig. FDR = 8.87E−06) was also the most significant metabolites. During multicenter validation, 2-(dimethylamino) guanosine , dulcitol , d-sorbitol  and kynurenine  were well-replicated to be positively associated with MACE risks. 4-Acetamidobutyric acid, β-pseudouridine, kynurenic acid, and l-tryptophan were significant only before adjustment. In particular, kynurenine was validated to be robustly associated with both death and MACE risks.Twenty-one metabolites were significantly associated with the risks of MACE after adjustment for confounders  guanosine, kynurenine, 3,3ʹ,5-triiodo-l-thyronine, d-sorbitol, DL-P-hydroxyphenyllactic acid, phenyllactate, cyclic AMP, and S-(5-Adenosy)-l-homocysteine. Besides, among the 21 metabolites associated with MACE risk, 11 endogenous metabolites were identified as independent metabolic signatures, including 4-acetamidobutyric acid, l-cystine, l-tryptophan, dulcitol, 5-methyluridine, kynurenine, phenyllactate, lysoPC 20:2, d-sorbitol, lysoPC 20:1, N6-succinyl adenosine.To identify a minimal set of metabolites and develop a prognostic model, we firstly selected independent metabolic signatures based on the 24 metabolites associated with the risks of death from the discovery cohort, using lasso Cox regression adjusting for potential confounders , see Additional file l-thyronine, β-pseudouridine, dulcitol, and kynurenine) and five clinical variables. The metabolomic model yielded higher predictive efficiency than the clinical model . Moreover, the model combining metabolomics and the clinical model for death yielded an improved predictive efficiency than the TMAO and the clinical model (Table l-tryptophan) to the clinical model was also with better predictive value than that of the TMAO and the clinical model  model consisted of TMAO and five clinical variables. The metabolomic model was built only based on the metabolites screened after lasso Cox regression and finally included five metabolites , and 20 metabolites were validated during multicenter validation , β-pseudouridine , kynurenine , N6-succinyl adenosine , 4-acetamidobutyric acid , dulcitol , kynurenic acid , phenylacetyl-l-glutamine , adipic acid , DL-P-hydroxyphenyllactic acid , and cyclic AMP  were validated to be associated with reduced LVEF. Besides, 2-(dimethylamino) guanosine , cyclic AMP , kynurenine  and phenylacetyl-l-glutamine  was confirmed to be related to increased LVMI.Network analysis of metabolites associated with risks of death Fig. : Fig. S2N6-Succinyl adenosine , phenyllactate , and kynurenine  were associated with increased death and MACE risks (P < 0.05). DL-P-hydroxyphenyllactic acid with HR of 3.11, adipic acid (HR = 4.67), S-(5-Adenosy)-l-homocysteine (HR = 2.88), trimethylamine N-oxide (HR = 1.76), 3,3ʹ,5-Triiodo-l-thyronine (HR = 0.11), and 4-acetamidobutyric acid (HR = 2.34), were linked to the risks of death. d-Sorbitol with HR of 1.76 and phenylacetyl-l-glutamine with HR of 1.74 were linked to increased risk of MACE. Moreover, we still observed 14 metabolites, including 4-acetamidobutyric acid , phenylacetyl-l-glutamine , phenyllactate , kynurenine , adipic acid , kynurenic acid , 2-(dimethylamino) guanosine , β-pseudouridine  were associated with decreased LVEF, and Dl-2-aminooctanoic acid  were associated with decreased LVMI.As secondary analyses, we performed MR analyses using genetic variants as the instrumental variables, to rule out the influences from confounders, thus providing inference of causality between the important metabolic signatures and clinical outcomes as well as LV remodeling  and 13% (MACE), kynurenine was at 18% on death and 14% on MACE, 4-acetamidobutyric acid and kynurenic acid were at 13–15%.Moreover, mediation analysis of LVEF was performed to further explain the associations between the metabolites and the clinical endpoints. Here, only those metabolites that were observed to have causal effects on LVEF in MR analysis were focused on. Mediation analysis proposed that the seven metabolites increase death and MACE risks could partly through impair LVEF , adipic acid, S-(5-Adenosy)-l-homocysteine, TMAO, 4-acetamidobutyric acid, d-sorbitol, and phenylacetyl-l-glutamine. In addition, we proposed for the first time that 7 metabolic signatures inferred as causal on the reduced LVEF by MR analysis increased the risks of death and MACE possibly partly through impairing LV function, including kynurenine, phenylacetyl-l-glutamine, 4-acetamidobutyric acid, phenyllactate, kynurenic acid, and two modified nucleosides. To our knowledge, our study provided the most comprehensive metabolomic and causal inference for the major clinical outcomes of CAD to date, suggesting potential pathological mechanisms, and offering biomarkers and potential therapeutic targets for the secondary prevention of CAD.In this prospective cohort of Chinese CAD patients, we described a comprehensive metabolomic study to identify endogenous metabolites that were associated with the major clinical outcomes of CAD, i.e. death and MACE. Based on these findings, we built prognostic models and found that combining metabolic signatures and clinical factors outperformed other models that used solely clinical risk factors, or clinical factors with established biomarker TMAO. Subsequently, we performed MR analysis to assess the potential causal effects of the metabolites on clinical outcomes. We observed that 11 metabolites were causally associated with the risk of death or MACE, including kynurenine, l-homocysteine), TMAO, and phenylacetyl-l-glutamine. Interestingly, the impacts of these metabolites on the death or MACE risk were further confirmed by our MR analysis. Their potential biological mechanisms in CAD were discussed as follows. Increased catabolism of tryptophan to kynurenine was related to cardiovascular events and mortality [l-homocysteine) was reported as a strong predictor of mortality in cirrhosis [Deciphering the details of the circulating metabolome could help to predict the risk of CAD and subsequent cardiovascular events . To dateortality , 29, andortality . Consistortality . Therefoortality . S- guanosine and β-pseudouridine, were found in our study as robust metabolic signatures for high risks of death and MACE, despite no causal relationship being observed in the MR analysis. Importantly, they displayed the strongest correlation with LV remodeling and were causally associated with reduced LVEF in MR. Furthermore, mediation analysis also inferred that their associations with clinical outcomes could be explained about 18–20% through impaired LVEF. It was consistent with recent studies that increased levels of 2-(dimethylamino) guanosine and β-pseudouridine levels were related to incident heart failure and LV remodeling , 46. Fur4-Acetamidobutyric acid appeared in our study as the metabolite most strongly associated with both risks of death and MACE, and about 14–15% of these effects could be mediated by promoting LV malfunction. Recent studies also found that 4-acetamidobutyric acid was associated with incident heart failure and LVMI , rheumatN6-succinyl adenosine, a purine metabolite, was reported to accumulate in the fluid of patients with adenylosuccinase deficiency, causing severe neurological impairment [N6-succinyladenosine was reported to promote inflammasome activity and IL-1β production in subjects with high expression of the inflammasome module, which was related to all-cause mortality [N6-succinyl adenosine was dramatically increased following myocardial infarction [In addition, it is interesting to note that two elevated aromatic lactic acids, phenyllactate, and DL-P-hydroxyphenyllactic acid, were inferred being causally associated with the adverse outcomes in CAD. They have been reported to be produced by the human gut microbiome  and werepairment . N6-succortality . Moreovefarction  in rats farction , providifarction . A studyfarction .Understanding the effects of these metabolic markers on the clinical events to be causal or merely associated could shed light on potential novel intervention targets for CAD. Therefore, unique in this study, we have explored whether there are potential causal effects of metabolic markers on the prognosis and LV remodeling of CAD using MR analysis. MR analysis is a popular causality inference tool that uses the inherent genotype as the instrumental variable which follows Mendelian laws of inheritance . GenotypIn addition, a recent study revealed that heterogeneous metabolic deviation profiles were evident even in a homogenous subgroup of acute coronary syndrome patients, which emphasizes that personalized risk stratification and preventative measures are essential in CAD . Our stuFirst, the study was based on Chinese patients, and the sample size of the validation cohort was relatively small, therefore we only validated the results with strong signals and could miss the weak signals that were weak. Studies expanding to other ethnicities and large-scale cohorts were also needed. Secondly, due to the metabolomic platform and method updating, the conditions for metabolite detection between the two cohorts were different, leading to 600 metabolites being detected in the multicenter validation cohort, while only 160 metabolites were identical to the discovery cohort. If more metabolites were added, then more novel metabolic signatures could be found. Another limitation is that the effect of CAD severity on the clinical outcomes was controlled by adjusting the SYNTAX scores in the discovery cohort, but the multicenter cohorts did not eliminate this bias since the data was unavailable. Finally, even though this study is prospective research based on observational data and explored the potential causal relationship between the key metabolites with LV remodeling traits and the outcomes, further mechanistic experiments are needed to verify the biological linkage and whether the biomarkers we identified precede LV remodeling incidence or concomitant result. Future studies using improved metabolomic detection methods can leverage the analysis framework we described in this study for discovering more novel metabolic signatures and better prognostic models.This study provided new insights into the relationship between plasma metabolites and clinical outcomes and LV remodeling in CAD. The prediction model based on the metabolic signatures and clinical risk factors can significantly improve the risk stratification for death and MACE, serving as a potential prognostic tool. Several metabolic markers such as kynurenines, phenylacetyl-L-glutamine, 4-acetamidobutyric acid, and modified nucleosides may causally increase the risk of death and MACE, and these impacts appear to be partly mediated by impaired cardiac function, which still merits further study. These findings suggest important risk markers and potential therapeutic targets for the secondary prevention of CAD.The study flow is depicted in Fig. Patients who were diagnosed with CAD (50% stenosis on coronary angiography) or received the percutaneous coronary intervention (PCI) were included. The exclusion criteria for patients in the discovery cohort included the following: (1) age < 18 years or > 80 years, (2) renal insufficiency , (3) hepatic insufficiency , (4) being pregnant or lactating, (5) advanced cancer or haemodialysis, (6) history of thyroid problems and taking antithyroid drugs or thyroid hormone medication, (7) incomplete information about cardiovascular events during follow-up. The exclusion criteria for patients in the multicenter validation cohort was the seventh criterion above. Baseline informations, including demographics, medical history, biochemical measurements, and medication, were obtained from the hospital information database.The primary outcome was death and the second was MACE . Coronary angiography was performed, and the Synergy between PCI with TAXUS and Cardiac Surgery (SYNTAX) score was calculated to assess the severity of CAD. The echocardiography was conducted to determine left ventricular ejection fraction (LVEF) and left ventricular mass index (LVMI). For detailed information see Additional file Widely targeted metabolomic profiling was conducted in the discovery cohort  and the multicenter validation cohort  by Wuhan Metware Biotechnology, detailed information sees Additional file The analytical method of this study was similar to our previous published lipidomic research . FirstlyP of 0.05 was considered for statistical significance, and Benjamini–Hochberg method was used to control the false discovery rate (FDR) for correcting the number of metabolites in multiple hypothesis testing.Univariate and adjusted Cox regression analysis was performed to identify the clinical characteristics and metabolites that were associated with clinical endpoints and to estimate the hazard ratio (HR) and 95% confidence intervals (CI). Univariate and adjusted Linear regression was used to reveal the clinical characteristics and metabolites that were related to LVEF and LVMI with results presented as estimates ± standard errors (SE). In the adjusted analysis, covariates included 17 potential confounders, including age, sex, aspartate aminotransferase, estimated glomerular filtration rate, diabetes, hypertension, systolic blood pressure, glucose, cholesterol, high-density lipoprotein cholesterol, proton pump inhibitors, angiotensin-converting enzyme inhibitors, β-blockers, calcium channel blockers, current smoking, family history of cardiovascular disease (CVD) and SYNTAX. A two-tailed P-values were analyzed using the log-rank test. The Spearman correlations in the metabolites associated with death and MACE risks in the adjusted analysis, together with traditional clinical factors , correlations above the significant level of P < 0.01 and |rho|> 0.1 for clinical factors and |rho|> 0.2 for metabolites, were visualized using Cytoscape (version 3.7) to construct a correlation network. The metabolites with FDR < 0.05 in the adjusted Cox regression analysis were used for least absolute shrinkage and selection operator (lasso) Cox regression analysis (“glmnet” package) to reduce the dimensions of variables and select the powerful metabolic features to build a multivariable prognostic model. This procedure was performed within a tenfold cross-validation framework (200 repeats), and the variables with repeats zero were removed and the metabolites left were selected to establish the prognostic model using multivariate Cox regression, based on the Akaike Information Criterion (AIC) with a forward and backward stepwise process.Time-to-event free survival was shown using Kaplan–Meier curves, and the 1X1 + β2X2 + …… + βiXi), where β is the regression coefficient, and Xi is the selected marker. Time-dependent receiver-operating characteristic (ROC) analysis (by ‘timeROC’ package in R) was used to assess the prognostic abilities of the hazard models. The model performance was assessed by calculating the area under the curve (AUC), continuous net reclassification indices (continuous NRI by ‘survIDINRI’ package in R), and integrated discrimination improvement (IDI by ‘survIDINRI’ package in R). The sensitivity and specificity of each model were calculated, and the corresponding optimal cut off values (Youden’s index) were determined according to the formula: sensitivity + specificity − 1 [To evaluate the prediction efficiency of the multivariate model, hazard estimates of individuals were calculated using the following formula: h (X) = exp (βcity − 1 . The mulhttp://www.R-project.org/).Statistical analyses were performed using GraphPad Prism 7 and R . A schematic diagram sees Additional file P < 1 × 10–5 as a threshold [P-value and the independent SNPs with them  as the independent instruments. A two-stage least squares (2SLS) method was used in this MR analysis process and we calculated the 2SLS regression in R (version 3.6.3).Association results between genotypes and the metabolites were obtained from our previous metabolome-based genome-wide association study , and thehreshold , 76 to shreshold  for the P-value < 0.05 was used to define causality.Briefly, in the first stage, we regressed by exposure (X) to the instrumental variable (IV) to derive fitted values for exposure to IV (G-X). In the second stage, we regressed the outcome (Y) based on the fitted values from the first stage regression (X–Y). The causal estimated effect size is the regression coefficient for this second stage that reflects the change in outcome due to a unit change in exposure. In the case of multiple IVs, the 2SLS estimator can be viewed as a weighted average of the ratio estimates calculated from a single instrumental variable, with weights determined by the relative strength of the instrumental variable in the first stage regression. The outcome was regressed over the predicted values of exposure by using Cox regression to estimate HR and 95% CI for risks of death and MACE, using Linear regression to calculate estimates and SE for LVEF and LVMI, 1X), where β1 is indirect effect 1; (3) regressing outcomes on mediators (model 3 Y = β2M), where β2 is indirect effect 2; (4) regressing outcomes  on predictors controlling for mediators (LVEF). The regression equation is Model Y = β2M + cʹX, where β2 is indirect effect 2, and c′ is direct effect; and calculating mediation effect as (β1 × β2)/c. Mediation analyses were conducted using Lavaan package of R 4.0.5.Mediation analysis decomposes the total exposure-outcome effect into a direct effect and an indirect effect through a mediator variable , 78. TheAdditional file 1: Table S1. Baseline characteristics on death and MACE risks. Table S2. Baseline characteristics on LVEF and LVMI. Table S3. Relationship between metabolites and death risk. Table S4. Relationship between metabolites and MACE risk. Table S5. Multivariate Cox proportional hazards model for clinical outcomes. Table S6. Spearman correlation analysis between clinical factors and those metabolites associated with death risk. Table S7. Spearman correlation analysis between clinical factors and those metabolites associated with death risk. Table S8. Relationship between metabolites and LVEF. Table S9. Relationship between metabolites and LVMI. Table S10. Estimation of the potential causal relationships between the metabolites and outcomes and LV remodeling traits by MR analyses. Table S11. Mediation effect of metabolites-LVEF-outcomes association. Table S12. The ionisation modes and ion pairs of the metabolites. Table S13. The coefficient of deviation of the metabolites between QC samples. Table S14. Associations between SNP and metabolites in the metabolome-based genome-wide association study.Additional file 2. Additional Methods. Fig. S1. The Kaplan–Meier curves of LVEF (A-B) and LVMI (C-D) for risks of death and MACE in the discovery cohort. Fig. S2. Correlation network of metabolic signatures for MACE risk and clinical factors. Fig. S3. Representative total ion flow diagrams between different QC samples under positive ion mode (A) and negative ion mode (B). Fig. S4. The visualization image analysis of the quality improvement procedures for typical features (Kynurenine) in metabolomics data. Fig. S5. Comparison of the cumulative frequency of RSD% of all features in QC samples before and after batch correction by QC-RLSC. Fig. S6. Diagram of Mendelian randomization analysis and mediation analysis.