GSTA1; p = 4.3E−4), Tonsuko Like, DNA Repair Protein , and Aspartylglucosaminidase (AGA: p = 4.5E−4). We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk. Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein.Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene–environment (G × E) interactions and may provide information on the underlying biological pathway. We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based G × E approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case–control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4839 genes with available genetically predicted expression. We pooled results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. We used a false discovery rate of 0.2 to identify genes with suggestive evidence of an interaction. We found suggestive evidence of interaction with folate intake on CRC risk for genes including glutathione S-Transferase Alpha 1 ( Supplementary folic acid is routinely prescribed during pregnancy as an evidence-based intervention to prevent neural tube defects in utero3. Dietary deficiency is typically found in persons subsisting on inadequate diets, as well as chronic alcoholics with diminished absorption4. Fortification of grains with folic acid began in the early 1990s to prevent nutritional deficiencies6. To date, 71 countries have legislative mandates for including folate in the fortification of milled grains5. Results pre- and post-fortification and risk of CRC have been somewhat inconsistent13, suggesting that folate might play a more complex role in colorectal carcinogenesis through various interactions16. Given the complexity of the relationship between CRC and folate, there is a need to elucidate the underlying biological mechanisms and possible differential risk based on individual genetics15.Folate is a naturally occurring, water-soluble B vitamin that cannot be produced by the human body and plays a key role in DNA formation and is necessary for cellular division and tissue differentiation. It is found abundantly in green leafy vegetables, legumes, fruits, and its more potent form, folic acid, is found in supplements and fortified foods18. The absence of folic acid leads to impaired DNA synthesis and disturbances in red blood cell maturation19. Due to its role as a carrier of one-carbon groups and in folate-mediated one-carbon metabolism (FOCM), insufficient folate consumption has been implicated as a possible cause of cancer23. Consistent with this hypothesis previous studies have shown evidence that greater folate intake is associated with a reduced risk of colorectal adenomas and cancers (CRC)24. A pooled analysis of 13 prospective studies in 2010 observed a modest effect, estimating a 2% risk reduction for CRC per 100 μg/day increase in total folate consumption25.Increased folic acid consumption is known to lower circulating levels of homocysteine, a common amino acid that has been associated with numerous diseases27. This has raised interest in studying interactions between folate and genetic variants28. As such, it has been hypothesized that germline mutations to the enzyme 5,10-methylenetetrahydrofolate reductase (MTHFR) would be a driver of the effects on folate on CRC risk30. A common mutation, 677TT in MTHFR has been associated with a greater decreased risk of CRC in high consumers of folate and low alcohol consumption32 compared to lower folate consumers. However, such analyses have relied on the assumption that FOCM-related genes are the driving genetic force on the pathway from folate consumption to CRC development. A genome-wide approach has the potential to identify novel genes that may modify the folate–CRC association.Candidate gene approaches targeting FOCM-related genes have shown associations with CRC risk33.To this end, we conducted a novel set-based genome-wide analysis to test interactions between genes and total folate intake on CRC risk. By using a set-based approach we may increase the power to detect associations, which is a common issue in traditional gene–environment interaction studies. We incorporate functional annotation based weights from PrediXcan, a transcriptome prediction tool35, and the demographic characteristics of study participants are summarized in Table We used epidemiological and genetic data from studies included in three international CRC consortia: the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colorectal Transdisciplinary Study (CORECT) and the Colon Cancer Family Registry (CCFR). Full details have been published previously36. In brief, DNA was mostly obtained from blood samples, with some from buccal swabs. Several platforms  were used for genotyping38. Samples were excluded on the basis of sample call rate ≤ 97%, heterozygosity, unexpected duplicates or relative pairs, gender discrepancy and principal component analysis (PCA) outlier of HapMap2 CEU cluster. SNPs were excluded on the basis of inconsistency across platforms, call rate < 98%, and out of Hardy–Weinberg equilibrium (HWE) in controls (p < 0.0001)37. SNPs were imputed to the CEU population in Haplotype Reference Consortium (HRC version r1.0) if not directly genotyped39, and restricted by imputation accuracy (R2 > 0.3).Details on genotyping and imputation have been reported previouslyhttps://hakyimlab.org/resource/predixcan/). The weights for the predicted gene expression were obtained by an elastic net penalized regression approach using the genome-wide variant data and transcriptome data from 169 colon tissue samples from the GTEx project (GTEx v6)40 (The sets of genetic variants and weights for predicting gene expression were downloaded from the publicly available PredictDB Repository (Ex v6)40 . We rest49. For these data, we carried out a multi-step data harmonization procedure, reconciling each study’s unique protocols and data-collection instruments as discussed previously34. Folate and folic acid intake were assessed at the reference time using food frequency questionnaires (FFQs). For cohort studies, the reference time was time of enrollment or blood collection. Folate and folic acid intake in each study were determined based on micrograms per day (mcg/day) of folate from foods  and mcg/day of folic acid from supplements (single or multivitamins) when available. Only two of the 23 studies with dietary folate intake did not capture information regarding supplemental folate. To account for the higher bioavailability of synthetic folic acid vs. natural folate in foods, we calculated total folate intake as dietary folate equivalents 50. Because the time of enrollment for some studies overlapped or followed the period of folic acid fortification (1996–1998), these studies accounted for folic acid fortification when calculating dietary folate intake and entered dietary folate intake as mcg of natural food folate + 1.7 × mcg folic acid from fortified food  supplemental folate separately.Basic demographics and environmental risk factors were collected using in-person interviews and/or structured questionnaires53, a mixed effects score test for gene-based interaction test with folate consumption on CRC risk, to conduct a pooled analysis across all studies. MiSTi modeled the gene–environmental interaction effect by two components. The fixed effects component incorporates variant functional information from PrediXcan as weights with our genotype data to calculate the genetically predicted gene expression and then assess its interaction with folate consumption. The random effects component involves residual interaction effects that have not been accounted for by the fixed effects. We used sex- and study-specific quantiles of folate consumption. p-values were calculated separately for fixed and random effects interaction terms, after adjusting for age, sex, study, sex-study specific quartiles of total energy consumption in kcal, and principal components to account for population stratification. We used the MiSTi data-adaptive weighted combination approach to combine the fixed and random effects components.We used the Mixed effects Score Tests for interaction (MiSTi)2 < 0.9.Genes with p-values less than the Bonferroni correction (0.05/4839 = 1.03E−5) were considered genome-wide statistically significant for an interaction with folate. p-values that reached false discovery rate (FDR) at 20% were considered having suggestive evidence of interaction as it is less stringent than a Bonferroni threshold. We conducted follow-up analyses based on the fixed and random effects p-values. For associations driven by the fixed effects, we investigated the direction and magnitude of these interactions using the generalized linear model, which included all covariates in the original model, folate, standardized predicted gene expression, and an interaction term for folate and predicted gene expression. Genes for which the signal was driven by the random effects component were further investigated to identify individual variants of the gene set as drivers using the same approach with interactions for individual variants and folate while adjusting for all other variants in the gene set. Due to some of the variants having high collinearity, we pruned variants by R54.All analyses were performed using R version 4.0.158. We additionally include the results of the gene–environment interaction between rs1801133 (C677T mutation) per additional effect allele with sex-study specific quantiles of total folate consumption on colorectal cancer.We performed these additional follow-up analyses for MTHFR, as prior candidate gene studies have shown variants, specifically the C677T mutation, alter the association between folate and CRCThe final sample included 13,498 cases and 13,918 controls with both folate and energy consumption measures available from 23 studies. We present demographic characteristics of all samples and report on measures for factors associated with CRC risk for study participants by case–control status in Table MTHFR gene and sex-study specific folate on risk of CRC in our analysis. Supplementary Table We found no suggestion of interaction between predicted gene expression for the The median number of SNPs included in the gene sets was 25 . Figure GSTA1; p = 4.3E−4), Tonsuko Like, DNA Repair Protein , and Aspartylglucosaminidase . In follow-up analyses for these three genes we observed positive interactions for GST1A and AGA, showing greater risk for CRC associated with higher gene expression and increasing folate consumption (Table TONSL primarily came from the random effects, indicating one or a few variants were drivers of the association, we investigated the individual interactions of variants with sex-study specific folate. We see two variants as possible drivers of the signal in our main analysis, 8:144964455_T/C and 8:144965104, as shown in Table We present the findings with p-values that surpassed the FDR threshold for gene interactions with total folate consumption and CRC risk in Table GSTA1, TONSL, and AGA.In this sizable analysis including a large number of studies we harmonized data on folate consumption and genome-wide genetic data to investigate interactions between folate intake and variants in genes on CRC risk. We observed an inverse association between folate intake and CRC risk across 23 studies. Using our novel statistical set-based G × E mixed effects score tests, MiSTi, we identified 3 genes with suggestive interactive effects with total folate consumption on CRC risk: GSTA1 and folate for CRC risk. GSTA1 located at 6p12.2 encodes for an enzyme that functions in cellular detoxification of electrophilic compounds through glutathione metabolism. Electrophilic compounds include carcinogens, therapeutic drugs, environmental toxins, and products of oxidative stress. Glutathione is a product of homocysteine metabolism, a key amino acid correlated with folate intake, and is bound to free radicals by GSTA159. Our results suggest that folate consumption may increase remethylation of homocysteine to methionine, thus reducing the production of glutathione need for DNA repair. Mutations in GSTA1 could feasibly alter the binding affinity of glutathione to carcinogenic compounds, leading to variation in cancer susceptibility. Of the 20 SNPs included in our analyses of GSTA1, three of the alternative alleles result in missense mutations to the gene60. Compromised function of glutathione as an antioxidant due to mutations in GSTA1 in conjunction with depleted levels of glutathione due to lower homocysteine levels may be a pathway to tumorigenesis22. Candidate gene studies have shown no association between GSTA1 and colorectal cancer or adenoma risk62. However, previous studies have shown interactions between diet, such as cruciferous vegetable consumption, and GSTA1 genotypes, supporting that associations between this gene and CRC are likely driven by dietary exposures65.We observed a positive interaction between the predicted gene expression of TONSL in the 8q24.3 region codes for a 1378 amino acid protein component of the MMS22L-TONSL complex, which functions in recovery of damaged replication forks66. Numerous mutations in TONSL are considered pathogenic60. Low levels of the MMS22L-TONSL complex result in increased frequency of DNA double-strand breaks and compromised DNA integrity66. In combination with increased DNA damage due to deficiencies in folic acid, impaired functionality of the MMS22L-TONSL due to functional mutations may be a pathway to increase tumorigenesis. Follow-up analyses further suggested that possible associations may be primarily driven by a small subset of variants included in our gene set in the main analysis.AGA with increasing folate consumption. The AGA gene is in the 4q34.3 region and codes for a 346 amino acid protein that functions in pathways related to the innate immune system and asparagine degradation67. Once the protein is processed into the mature enzyme it takes part in the catabolism of N-linked oligosaccharides, cleaving asparagine from N-acetylglucosamines in one of the final steps in the lysosomal breakdown of glycoproteins. Mutations in the AGA gene are known to cause the lysosomal storage disease aspartylglycosaminuria, eventually resulting in neurodegeneration. Previous research has not indicated a link to cancer for this gene.We observed increasing risk of CRC per standard deviation increase in predicted gene expression of 68.While we have many strengths in performing the largest investigation of gene–folate interactions to date using a powerful set-based approach that allows to account for functional prediction, some limitations should be considered when interpreting these findings. Approximately half of the studies in our consortium ascertained cases using a cohort study design which may have resulted in earlier and more frequent detection of tumors. Most cohort studies in our consortium used population-based registries for case ascertain. However, one study, The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, was a randomized trial to determine the effectiveness of screening. While we have adjusted for study in our approach there may be unknown residual effects of this design. Our study population was limited to those of European descent. As gene expression levels may differ across populations of different ancestry, our results may not be generalizable to populations of non-European ancestry. The studies included in our analysis occurred over a range of time and geographic locations. Fortification with folate occurred in different places at different times and we used adjusted dietary equivalents to account for these differences (see Supplementary Table 40. One limitation of this data is the diversity of cell types aside from epithelial cells of the mucosa of the colon, from which CRC derives given that the entire colonic wall was sampled. The impact of this would cause a dilution of gene expression for the tissue most relevant for CRC. However, we expect this to be an improvement over alternative tissue types including blood or sigmoid colon tissues in GTEx, which were collected from muscle tissues only and would not represent the gene expression profile of interest.We utilized colon-specific gene expression data, specifically transverse colon tissue captured by the GTex Project53. The previously suggested MTHFR gene was not identified in our analysis27. However, in using the penalized elastic net to create our predicted gene expression the C677T was not included in the variant weights due to the insignificant contribution to regulation of gene expression. While it was also not seen in the gene–environment interaction analysis either, we believe these results to be representative of an agnostic approach which has not been shown before, as opposed to candidate gene studies.Although MiSTi is a powerful statistical tool, which accounts for both fixed- and random-effects of the gene–folate interaction, none of our findings reached the Bonferroni corrected threshold, which can be overly conservative as many genes are co-expressed. We did not perform independent replication and thus follow-up investigations are warranted, as a FDR of 0.2 should be considered liberalMTHFR, were included among the 4839 genes examined. However, none of those previously hypothesized genes were found to interact with folate consumption in our analysis69. We conducted additional follow-up analysis for MTHFR using indicator terms for sex-study-specific folate quantiles and interaction terms for all quantiles with predicted gene expression were null (see Supplementary Table Our analysis was conducted in the largest pooled analysis of a well characterized and harmonized consortium of CRC with comprehensive genetic data which enabled a hypothesis-free genome-wide investigation of interactions with folate consumption on CRC risk. An extensive number of genes evaluated in prior candidate gene–folate interaction studies, including GSTA1, warrant follow-up in future studies with comprehensive genetic and data on folate intake in order to confirm the potential role of these genes in interacting with folate on CRC risk.The biological functions of our top genes serve to primarily prevent or repair DNA damage. The combined effects of increased DNA damage due to folate deficiencies and compromised functionality of these genes may be an important pathway in CRC tumorigenesis. These findings, particularly for Supplementary Information 1.Supplementary Information 2.


Constipation has been hypothesized to be associated with the increased risk of wheezing or asthma. However, the relation remains a subject of debate. We conducted this meta-analysis to assess whether constipation influences the risk of wheezing/asthma.PubMed, Embase, and Web of Science were systematically searched for studies published between 1955 and January 2022. Two reviewers independently extracted data and assessed the quality of each study. Results were pooled using fixed-effects models or random-effects models as appropriate.In total, 3 original articles with 178,661 participants, which met the criteria, were included in this meta-analysis. Constipation was associated with an increased risk of wheezing/asthma in later life .The meta-analysis suggests an association between constipation and the subsequent development of wheezing/asthma. Well-designed and highly standardized prospective studies that adequately address concerns for potential confounding factors are required to validate the risk identified in our current meta-analysis.The online version contains supplementary material available at 10.1186/s13223-022-00708-9. Asthma is one of the most common chronic airway inflammatory diseases arising from not fully understood heterogenic gene-environment interactions , which hConstipation is a common complaint that may be primary  or associated with several disorders or medications. The median prevalence of constipation is 16% in adults and 3% in children , it is gThe demonstration of a relation between constipation and the development of later wheezing/asthma, as well as a better understanding of the nature of this association, could have important implications for the prevention and treatment of asthma. To the best of our knowledge, no study has been published that has systematically reviewed the literature and synthesized the available evidence. Therefore, we performed a systematic review and meta-analysis of the existing evidence.The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.Two independent reviewers (LL and ZJ) systematically searched the PubMed, EMBASE, Web of Science to identify available studies published between 1955 and January 2022. The search terms used were constipation AND (wheezing OR asthma). A search strategy for each database was established with the help of a library expert of Xi’an Jiaotong University. The search details using PubMed, EMBASE and Web of science were shown in Additional file Studies were included in the meta-analysis that met the following criteria: (1) cohort study or case–control study; (2) diagnosis of constipation was made on the basis of one of the following: physician diagnosis of constipation, diagnostic code from the Health Insurance Research Database, or assessment questionnaire; (3) outcome of interest was wheezing/asthma , short-acting β-agonists, and systemic corticosteroids within 1 year, or assessment questionnaire); (4) measures of association  and their 95% CI or data allowing for computation of summary measures are provided. Studies were excluded if they did not meet these inclusion criteria. Unpublished data were not considered. Study selection was achieved by two investigators (YZ and YS) independently and all the disagreements were resolved by discussion.The quality of each study included in this study were independently assessed by two reviewers (ZJ and LL) according to the Newcastle–Ottawa Scale (NOS) . We consData were extracted by two independent reviewers (LL and XZ) using a standardized data collection form and then compared. In the case of discrepancies, the final decision was made by a third reviewer (YZ). From each included study, we recorded: first author, publication year, original country where the study was conducted, number of participants, study design, age at enrollment in the study, outcome, and the effect estimate (95% CI).1/P0, P1 indicates the incidence of the outcome of interest in the exposed group and P0 in the non-exposed group) [0) (P0 × OR)] [We extracted the association (OR or RR or HR) and their 95% CI or derived them by using data from the original studies (unadjusted RR = Pd group) . The RRs0 × OR)] . We also0 × OR)] .2 index is proposed to quantify the degree of heterogeneity and considered as a complement to the Q statistic, although it has the same problems of power with a small number of studies [2 statistics (> 50% was significantly inconsistent) to comprehensively evaluate between study heterogeneity [Meta-analysis was performed using Stata V.12.0 software . We used the “metan” command in Stata to pool the lnRR. Forest plots were used to visually assess the RR estimates and corresponding 95% CIs across studies. In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q statistics. However, the Q statistic only informs meta-analysis about the presence versus the absence of heterogeneity, but does not report on the extent of such heterogeneity. Moreover, it has poor power to detect true heterogeneity among studies when the meta-analysis includes a small number of studies. Small studies have higher mean heterogeneity estimates than medium/large studies of the same meta-analysis . I2 inde studies . Therefoogeneity . PotentiA total of 1762 studies were identified. Of them, 217 were excluded for duplicates and 1369 were excluded after screening the titles and abstracts, leaving 176 studies for full-text review. Two articles were published by the same authors in the same year and reported the results from the same database, but for different age groups , and thus a random-effects model was used. The combined results demonstrated that constipation was associated with increased risk of wheezing/asthma  the number of studies and subjects included in the present meta-analysis was relatively small. The limited number of included articles (n = 3) and great difference in sample size among studies might affect the representativeness of results from this meta-analysis. The study by Huang et al. only included participants from Taiwan, represented 97–98% of the total numbers. We could not investigate the influence of this single study on the overall risk estimate by excluding it as only 2 studies remained should not result in any model tests of significance. We will re-analysis and validate the risk identified in the current meta-analysis when more relevant studies are available. (ii) The diagnosis of wheezing/asthma was not always provided by a physician, this might affect the accuracy of the diagnosis and create a bias; Even if the diagnosis was made by a physician, it is not clear whether the physician was blind to the presence or absence of constipation. (iii) The large Taiwan study used constipation that was included in the health insurance database while the other 2 studies used questionnaire data. It is probable that constipation in the health database could be more severe/significant that that reported on questionnaires. Moreover, we could not confirm the accuracy of information obtained from questionnaire. (iv) It is commonly thought that asthma is a multi-factorial disease resulting from complex interactions between genetic predisposition and environmental factors, so the association of constipation with asthma would be affected by ethnic origin. However, we were not able to evaluate interaction effect of genetic backgrounds by constipation because there were only 1 study in Asians and 2 studies in European. In addition, although the results of some studies included in our meta-analysis were adjusted for some factors which might alter the association between constipation and wheezing/asthma risk, there were still other potential confounding factors. For example, smoking may be a confounding factor, which has been defined as a pivotal risk factor for constipation  and the In conclusion, the current meta-analysis indicates that constipation may be associated with subsequent development of wheezing/asthma. In view of these limitations, more large-size prospective studies that adequately address concerns for potential confounding factors are required to validate the risk identified in the current meta-analysis.Additional file 1. The search strategies for PubMed, Embase and Web of Science.Additional file 2: Table S2. The quality of each cohort study according to the Newcastle-Ottawa Scale (NOS) manual (n=3).


No consensus has yet been reached on the associations of lipid variability (LV) with cardiovascular diseases (CVDs) and all-cause mortality. We aimed to quantify the associations of different types and metrics of LV with CVDs and all-cause mortality. PubMed, Medline, and Embase databases were searched for eligible cohort studies published until 14 December 2021. Lipids included total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). Metrics of variability included standard deviation (SD), coefficient of variation (CV), and variation independent of the mean (VIM). The primary outcomes were CVDs and all-cause mortality. Random-effects meta-analysis was used to generate a summary of the relative risks (SRRs). Sources of heterogeneity were explored by subgroup analysis and meta-regression. A total of 11 articles based on seven cohorts were included. Participants in the top quartile of TC variability had an increased risk of CVDs  and all-cause mortality . Participants in the top quartile of HDL-C variability had an increased risk of CVDs  and all-cause mortality . LDL-C variability was also associated with an increased risk of CVDs  and all-cause mortality . The relationships of TG variability with the risk of CVDs and all-cause mortality were inconclusive across different metrics. The effects of SRR became stronger when analyses were restricted to studies that adjusted for lipid-lowering medication and unadjusted for mean lipid levels. These findings indicate that the measurement and surveillance of lipid variability might have important clinical implications for risk assessment of CVDs and all-cause mortality. Cardiovascular diseases (CVDs) are the leading cause of death worldwide . In 2019A growing body of epidemiologic evidence suggested that individuals’ lipid patterns over time could be governed by two dimensions: the mean level and intraindividual variability . Lipid vBy far, the associations of LV with CVDs and all-cause mortality have not been synthesized via meta-analysis. To fill this gap in knowledge, we conducted a systematic review and meta-analysis of cohort studies to assess and quantify the associations of different LV metrics with CVDs and all-cause mortality. A series of subgroup analyses and meta-regression were further conducted to evaluate sources of heterogeneity and robustness of the results across subgroups.This study followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines ,18. The From database inception to 14 December 2021, we conducted a comprehensive English literature search in PubMed, Medline, and Embase to identify cohort studies that assessed the associations of LV with CVDs and mortality. Further details regarding the search strategy are provided in The title and abstract of retrieved records were screened, followed by a full-text review by two independent reviewers (SL and LH). Eligible articles were included based on predetermined inclusion criteria: (i) cohort study; (ii) the exposure of interest was different types and metrics of LV ; (iii) tTwo reviewers (SL and LH) independently extracted data from the included articles and assessed the quality of these articles, followed by a cross-check for consistency. Discrepancies were resolved through discussion or consultations with the senior investigator (PS).For each included article, basic characteristics were extracted as follows: authors, publication year, the country and setting where the study was based, cohort, study period, mean/median follow-up time, participant characteristics , types of lipid , variability metrics , average successive variability (ASV), root mean square error (RMSE), SD of the residuals (SDR)), CVDs or mortality ascertainment, comparison level, and covariates included in the adjusted models. The adjusted RR/HR with the corresponding 95% CI were also extracted from each study. If estimates were available from multiple multivariable-adjusted models, we only extracted the most fully adjusted one. If a study simultaneously reported several estimates based on different types of lipid or metrics of variability, we extracted all estimates.Due to the limited numbers of studies on ASV, ARV, RMES, and SDR for each type of lipid, we classified these variability metrics into the group of “Others.” For example, TC-ARV, TC-ASV, TC-RMSE, and TC-SDR were considered TC-Other. Given that different cohorts reported effect sizes in HR or RR, we treated HR as RR to ensure consistency . FurtherQuality assessment was performed based on the Newcastle–Ottawa quality assessment scale (NOS) for cohort studies . Up to aFor studies that reported effect sizes for males and females separately, an overall RR for each study was generated using a fixed-effects meta-analysis. Any effect sizes stratified by different outcomes were treated as separate data points. The summary RRs (SRRs) (for top vs. bottom quartile) were generated using inverse-variance weighted random-effects meta-analysis and illustrated with forest plots. Furthermore, subgroup analyses and meta-regression were performed for studies exploring the associations between different types and metrics of LV with CVDs and all-cause mortality (number of data points ≥3) to evaluate sources of heterogeneity. The variables used for the subgroup meta-analysis included: subtypes of CVDs , gender , whether adjusted for mean lipid level or not, whether adjusted for lipid-lowering medication or not, whether adjusted for hypertension or not, whether adjusted for diabetes or not, whether adjusted for body mass index (BMI) or not, and whether adjusted for smoking or not. We also performed a sensitivity analysis that excluded the studies conducted on participants with hypertension and diabetes to assess the stability of the results.2 statistic. In Cochran’s Q test, significant heterogeneity was defined as a p-value of less than 0.10. The degree of heterogeneity across studies was considered high, moderate, and low by I2 cut-off values of 25% and 75% [p < 0.05, and all p-values were two-tailed.Between-study heterogeneity was assessed with Cochran’s Q test and the I and 75% . PublicaA literature search identified a total of 4673 records, of which 2842 were considered for screening of title and abstracts after removing the duplicates. After detailed screening against selection criteria, a total of 11 articles based on seven cohorts were finally included in analyses  6,14,15,30,31.The detailed characteristics of the 11 included articles in this meta-analysis are presented in All six cohort studies from 10 articles were included in the meta-analysis of LV and CVDs.2TC-CV = 92.4%, I2TC-SD = 90.7%, I2TC-VIM = 91.1%, and I2TC-Other = 86.4%, all p < 0.001). HDL-C variability was also associated with an increased risk of CVDs . The associations of LDL-C-CV and LDL-C-Other with CVDs were not significant . TG-CV, TG-VIM and other metrics of TG variability were not significant with CVDs . Compared with people in the bottom quartile of TG-SD, those in the top quartile had a 11% increased risk of all-cause mortality . More details about other metrics of LDL-C variability and TG variability with all-cause mortality are in Compared with people in the bottom quartile of TC variability, those in the top quartile had an increased risk of all-cause mortality . Compared with studies without adjustment for lipid-lowering medication, studies that adjusted found a stronger association between TC variability and CVDs .In subgroup analyses of TC variability with all-cause mortality, there were positive associations in all subgroups . In addiThe funnel plots suggested a slight publication bias in the different LV metrics with CVDs and all-cause mortality .Lipid variability is increasingly proposed as a predictor for CVDs and all-cause mortality risk ,13,14,15A review from Simpson et al. illustrated that visit-to-visit variability in lipoprotein  and TG was found to be associated with CVD outcomes and all-cause mortality, independent of their mean absolute levels, each other, and their traditional risk factors . AnotherIn our meta-analysis, TC, HDL-C, and LDL-C variabilities were significantly associated with the risk of CVDs and all-cause mortality. Despite a growing body of evidence from epidemiological studies ,33,34, tOur study found that adjustment for lipid-lowering medication or not and adjustment for mean lipid level or not might be sources of heterogeneity between studies of LV with CVDs. There were some heterogeneities between studies that adjusted for lipid-lowering medication and studies without such adjustment for TC variability, HDL-C variability, and LDL-C variability with CVDs. It is likely because the beneficial effects of using lipid-lowering agents mitigated the impact of the high variability of TC, HDL-C, and LDL-C on CVDs . MoreoveThere are several strengths to our study. First, we utilized a comprehensive literature search strategy across multiple bibliographic databases and a rigorous extraction process. Second, we included a substantial sample size of over five million participants from eligible cohort studies, which could ensure the accuracy of the results. Third, we used comprehensive lipid variability metrics to explore their relationships with CVDs and all-cause mortality, which enriches the previous studies and may help guide the subsequent development of standardized LV metrics. We also performed a sensitivity analysis that excluded the studies conducted on participants with hypertension and diabetes to assess the robustness of the results. The sensitivity analysis showed good robustness of the results. Moreover, we conducted between-study subgroup and meta-regression analyses to evaluate whether effect sizes of LV differ across characteristics of the studies and populations and to explore the potential sources of heterogeneity.However, several limitations should be considered. First, due to the limited numbers of available studies, the LV effects on the ARV, ASV, RMSE, and SDR metrics could not be taken into account separately. Similarly, firm conclusions could not be drawn regarding the limited information on different types and metrics of LV with subtypes of CVDs  and subtypes of mortality . Second, given that different cohorts reported effect sizes in HR or RR, we treated HR as RR to ensure consistency. Third, there was high heterogeneity between studies in several analyses, but we conducted subgroup meta-analyses and meta-regression by common study characteristics and population characteristics to explore the sources of heterogeneity. There were some heterogeneities between studies that adjusted for mean lipid level and lipid-lowering medication and studies without such adjustment for LV with CVDs. There were also some heterogeneities between studies conducted on HICs and studies conducted on UMICs of LV with CVDs and all-cause mortality. An updated analysis should be undertaken when more data become available in the future. In addition, we did not conduct dose–response analysis to quantify the linear or nonlinear relationships between LV and CVDs and all-cause mortality due to the limited data.The present findings support that LV may be used as an important clinical indicator for the risk of CVDs and all-cause mortality. More sophisticated measures of LV are needed, as well as consensus about how such LV should be defined, including types of lipids, metrics of variability, measurement intervals, times of measurements, and the temporality of the variance . MeanwhiIn conclusion, lipid variability, particularly the variability in TC and HDL-C, is positively associated with the risk of CVDs and all-cause mortality. Measurement and surveillance of lipid variability beyond mean lipid levels have important clinical implications for the risk assessment of CVDs and all-cause mortality.


The function of uric acid (UA) in the genesis and evolution of chronic kidney disease (CKD) has motivated numerous studies, but the results remain inconclusive. We sought to conduct a systematic review and meta-analysis of cohort studies aiming to analyze the association of UA levels with the incidence and progression of CKD. Pubmed/Medline, Lilacs/Bireme and Web of Science were searched to identify eligible studies, following the PRISMA protocol. Data were presented for CKD incidence and progression separately. For the meta-analysis, studies with data stratified by subgroups according to serum UA levels were selected. The inverse variance-weighted random effects model was used to generate a combined effect estimate. Meta-regressions were performed to identify the causes of heterogeneity. The Newcastle–Ottawa Scale was used to assess the risk of bias. The publication bias was tested by funnel plot and Egger’s test. Eighteen CKD incidence studies  and six CKD progression studies  were included. An inverse relationship was observed between UA levels and protection from CKD incidence and progression. Lower UA levels were protective for the risk of CKD incidence (RR 0.65 [95% CI 0.56–0.75]) and progression (RR 0.55 [95% CI 0.44–0.68]). UA seems to be implicated both in the genesis of CKD and its evolution. The prevalence of CKD has been increasing worldwide, with an annual increase of 8 to 16%, which is higher than the general population growth3.Chronic kidney disease (CKD) is a global public health problem affecting more than 697 million people6. The coexistence of risk factors, such as hypertension and chronic inflammation9 and pathophysiological peculiarities of CKD make it complex to define the role of UA.In recent decades, the function of uric acid (UA) in the genesis and evolution of CKD has motivated numerous studies, but the results remain inconclusive due to the complex and bidirectional interaction between the change in UA levels and renal function, which hinders the isolation of the causal effect of UA in the progression of CKD10. The remnant of circulating UA accounts for more than half of the antioxidant potential of human blood11. However, when it is inside the cells, it exhibits a pro-oxidant behavior, stimulating the production of free radicals and pro-inflammatory cytokines, reducing the bioavailability of vasodilator substances and increasing vasoconstrictor substances such as angiotensin, which lead to oxidative stress, chronic inflammation and endothelial dysfunction, the tripod of the pathogenesis and progression of CKD13.UA is the final product of purine catabolism from exogenous sources, through diet, and endogenous, by cell degradation14, and some prospective observational studies17 and retrospective studies20 showed an association between UA and incident or prevalent CKD, while other studies found no association22, evidencing the controversial role of UA in the incidence and progression of CKD. Furthermore, to the best of our knowledge, no review has been performed to assess the association between different UA levels (subgroups of UA levels) and the incidence and progression, contemplating all stages of CKD. Therefore, we performed a systematic review and meta-analysis of cohort studies to analyze the association of serum UA levels with the incidence and progression of CKD.The growing interest in UA considerably increased the number of publications23.Systematic review study conducted according to protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO), under identification number CRD42020142073, respecting the recommendations of the Cochrane Collaboration, reference for the preparation and publication of systematic reviews and meta-analyses. The results were presented according to recommendations proposed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)The identification and selection of the studies occurred from December 2019 to January 2020, completely independently by two researchers. The health databases consulted were: US National Library of Medicine National Institutes of Health (PubMed)/Medical Literature Analysis and Retrieval System Online (Medline), Latin American and Caribbean Center on Health Sciences Information (Lilacs) and Web of Science, main health science databases. The descriptors used in the search are indexed in the Medical Subject Headings (MeSH), which are: “Hyperuricaemia”, “Uric Acid”, “Renal Insufficiency, Chronic”, “Kidney Diseases”, “Kidney Failure, Chronic”, “Chronic Kidney Disease”. The following combinations were used: “Hyperuricaemia” or “Uric Acid” and “Renal Insufficiency, Chronic”; “Hyperuricaemia” or “Uric Acid” and “Kidney Diseases”; “Hyperuricaemia” or “Uric Acid” and “Kidney Failure, Chronic”; “Hyperuricaemia” or “Uric Acid” and “Chronic Kidney Disease”. In order to contemplate the entire scientific production, the publication period was not delimited.After searching the databases, duplicate studies were excluded. Next, a refining was carried out to select the studies related to the theme addressed through the reading of titles and abstracts.Studies were included if they met the following criteria: longitudinal cohort studies that evaluated the role of UA in the progression and/or incidence of CKD and had a follow-up of at least one year.To reduce any confounding variables that may affect the association between CKD and UA, we excluded: studies with animals, children, adolescents, pregnant women and kidney transplant recipients, cross-sectional or case–control studies , studies addressing acute kidney disease and/or specific types of kidney disease , studies on drug effectiveness, studies whose outcome was mortality and studies that assessed risk factors in general for progression of CKD , whose focus was not to evaluate the role of uric acid.2) but experienced a decline in GFR to less than 60 mL/min/1.73 m2 during follow-up. Progression was defined as decline in GFR and/or end-stage renal failure, requiring renal replacement therapy.As they were different measures, the outcomes progression and incidence of CKD were presented separately. Incidence of CKD was defined as individuals who were free of CKD at baseline (glomerular filtration rate (GFR) ≥ 60 mL/min/1.73 mThe following data were extracted from the selected studies: author’s name, date of publication (year), study design (follow up time), characteristics of the studied population, GFR estimation equation, exposure variable, main outcome, adjustment for possible confounding factors in multivariate analyses and evidence quality analysis.24. Each domain had a rating of “yes,” “no”, or “unclear.” If there was adequate data against a domain in the included study and met the criteria, it was classified as low risk of bias (yes). Conversely, a domain was classified as high risk of bias if adequate information was not available (no) or not enough data was available to make an assessment (unclear). “Yes” was scored as “1”, and “no” or “unclear” was scored as “0.” Scores were tallied up to calculate the final cumulative score. A study was considered high quality if the cumulative score was ≥ 4, and low quality if < 425.The Newcastle–Ottawa Scale (NOS) was used to assess the risk of bias for cohort studies. We used three items to assess study quality: (1) selection of participants (including four domains); (2) comparability of study results (including one domain); and (3) outcome (including two domains)For the quantitative analysis, studies with data stratified by groups according to serum UA levels (quartiles or quintiles) were selected. To evaluate the gradient, the groups with the lowest levels of UA were compared to the other groups .For incidence studies, the absolute number of incident and non-incident cases in each group was used to calculate the relative risk (RR), with a 95% confidence interval and p values. For progression studies, the absolute number of cases that progressed and did not progress in each group was used to calculate the RR, with a 95% confidence interval and p values.2 statistic, which describes the proportion of total variation in the study estimates due to heterogeneity26. The degree of heterogeneity was assessed from the I2 statistic using the following thresholds for interpretation: (1) 0% to 30%: marginal heterogeneity; (2) 30% to 50%: moderate heterogeneity; (3) 50% to 75%: substantial heterogeneity; and (4) 75% to 100%: represents considerable heterogeneity26. The estimation of each study and the standard error (SE) generated a combined estimate, graphically represented by the forest plot.The effect estimates rate ratios were combined in the meta-analysis to calculate the overall risk estimate. A random-effects model was used for analysis to account for the variation of real effects across studies. Heterogeneity was quantified using the IMeta-regressions (univariate and multivariate) were performed to identify the causes of heterogeneity. The following variables were investigated: sex (difference in percentage of men between comparison groups), serum UA level (mean difference between comparison groups), age (mean difference between comparison groups) and sample size (mean difference between comparison groups). Initially, a univariate analysis was performed and all variables that values of p ≤ 0.200 were included in the final multivariate model. Variables with p values < 0.05 in the multivariate analysis were considered significant.The publication bias was tested by funnel plot and Egger test. All analyses were performed using the ‘meta’ package in STATA version 14.39 related to the incidence of CKD in the general population and six42 on CKD progression. For the quantitative analysis, nine incidence studies39 and three progression studies21 were included. Figure We identified 6889 publications at the electronic databases. After exclusion by duplicity, 4134 studies remained. In the paired selection through the screening by the titles and abstracts, 4084 more articles that did not fit our scope were eliminated. Among the 50 studies selected for full reading, we excluded 26 that did not meet the eligibility criteria. Finally, 24 studies were included and stratified into two groups: 18Tables An inverse relationship was observed between UA levels and protection for the CKD incidence Fig. . Lower U2 statistic (I2 = 97.7%). Regarding meta-regression .The meta-analysis showed considerable heterogeneity by the Ion Table , in the p = 0.249).Funnel plot analysis qualitatively showed an asymmetric shape Fig. , indicatAn inverse relationship was observed between UA levels and protection from CKD progression Fig. . Lower U2 statistic (I2 = 96.4%). Regarding meta-regression  increased the risk between UA and incidence of CKD.43. This relationship highlights a potential benefit of UA screening in different phases of CKD44.UA levels are an independent predictor of the development of CKD and its progression. Some studies have shown that the prevalence of hyperuricaemia gradually increases with the decrease in renal function, being 10 times higher in stages 3–5 than in stage 145. Similarly, a Japanese retrospective cohort with 5,507 adults followed-up for an average period of 4.6 years found a positive association of hyperuricaemia (≥ 7 mg/dl) with the incidence of CKD (adjusted HR = 1.58 [95% CI = 1.21–2.07]), but with no effect on its progression (HR = 1.08 [95% CI = 0.73–1.59])46.A retrospective cohort involving 13,133 healthy adults  showed that increasing UA levels doubled the risk of incident CKD47 made a critical review of observational and experimental studies on the potential effect of UA reduction therapy on the prevention of the incidence and progression of CKD and concluded that UA participates in inflammation and evolution of CKD. The authors acknowledge, however, that such conclusions are controversial because they are based on small studies and without placebo group.Jalal49 concluded the use of allopurinol was not beneficial to prevent the progression of pre-existing kidney disease, with no statistical difference between using or not using the UA-lowering agents. On the other hand, a recent systematic review and meta-analysis of 11 randomized clinical trials, including 4,277 participants with CKD, suggested that UA-lowering therapy preserves GFR so that xanthine oxidoreductase inhibitors could improve renal outcomes50. This finding may indicate a different role for UA in the pathophysiology of CKD in addition to a nitrogen slag.Thus, two recently published double-blind, placebo-controlled, multicenter randomized trial52.The definition of the role of UA is still complex, especially due to the coexistence of risk factors such as hypertension, chronic inflammation and pathophysiological peculiarities of CKD. Recent studies have shown that soluble UA exhibits a behavioral duality acting as pro-oxidant within the cell and antioxidant in the extracellular environment55. Furthermore, UA induces the activation of dependent or independent pathways of NLRP3 inflamassome with release of pro-inflammatory cytokines (IL1β and IL18), necro-inflammation and interstitial fibrosis56. Such pathophysiological mechanisms may justify the role of UA in the incidence and progression of CKD.In relation to the pro-oxidant effect, the UA stimulates the generation of reactive oxygen species culminating in oxidative stress and mitochondrial damage, endothelial dysfunction with activation of the renal-angiotensin-aldosterone system, reduction of nitric oxide bioavailability and afferent arteriolopathyThere were several strengths to this systematic review: 1. it is one of the first studies to gather evidence from observational studies in the search for an association of UA levels, not only with the incidence of CKD, but also with its progression to terminal stages, thus contemplating all stages of CKD; 2. the literature search included several large databases with the search criteria designed to identify as many relevant articles as possible; 3. a proportion of the study selection, data extraction and quality assessment were conducted in duplicate by separate reviewers to reduce reporting bias; 4. all studies were classified as high quality and encourages future researches related to the use of UA reduction therapies for preventing CKD in at-risk populations.There are some limitations to our study that need to be taken into consideration. First, the studies presented heterogeneous sample sizes, which was minimized with the use of appropriate statistical tests in the meta-analysis. Secondly, different definitions were observed for the final outcome  and for the independent variable (UA levels). Subgroup analysis based on the UA levels (quartiles or quintiles) was conducted to assess whether the presentation of exposure contributed to differences in study results. This analysis showed similar results regardless of the method of presenting the exposure. Thirdly, different forms of GFR estimation  were adopted. Finally, there was some heterogeneity among risk estimates from the included studies, possibly due to some bias at the study level. However, the variables included in the meta-regression were not sufficient to explain the heterogeneity between studies. Other important variables that interfere in the UA metabolism could not be included, as they were not present in all studies, such as gout, basal GFR, diet components, use of UA-lowering agents.In conclusion, the present study provides evidence that lower UA levels were protective for the risk of CKD incidence and progression. Increasing the age difference between the groups increased the risk between UA and the incidence of CKD.Supplementary Information 1.Supplementary Information 2.


P = 0.026); however, this effect was not significant after 6 months . Meta-regression analysis suggested that the effect of this device is associated with users’ age and body mass index 3 months after insertion. No publication bias was found by Egger’s test or funnel plots. Overall, the results of this meta-analysis support the view that vaginal ring use is associated with a positive effect on the sexual function of women 3 months after insertion, while the effect of this device on the sexual function of women was insignificant after 6 months. However, given the dearth of available data, it is not possible to reach a definite conclusion on the effect of vaginal rings on females’ sexual function.There are controversial debates regarding the effects of contraceptive vaginal ring devices on females’ sexual function. Therefore, the meta-analysis of before-after was conducted on the intervention studies published in the past years to clarify these contradictions. The existing literature on the subject was reviewed by searching through such databases as PubMed, Scopus, ISI Web of Sciences, Embase, Cochrane Library and Google Scholar up to July 2021. Before-after intervention studies that had examined the effect of vaginal rings on females’ sexual function were collected as well. In total, five studies with 369 participants were included in quantitative syntheses. Pooled results from the random-effect model showed that NuvaRing had a positive effect on females’ sexual function three months after insertion (WMD: 2.48; 95% CI: 0.30, 4.67;  Today, several highly effective and safe hormonal contraceptive products are available to control and regulate human fertility behaviour . HoweverThere are many studies on the effect of hormonal contraceptives on females’ sexuality. However, since most of these studies have been restricted to oral contraceptives, there is limited evidence in the literature regarding the effect of new combined contraceptive delivery systems on sexuality , 4, 6.Although vaginal rings releasing etonogestrel and ethinyloestradiol are acceptable modern hormonal contraceptives, recent observational studies have shown conflicting results regarding their effect on females’ sexual function . Some stFurthermore, negative sexual changes, such as irregular uterine bleeding and physical discomfort during sexual intercourse due to the presence of a foreign body in the vagina attributable to the application of this type of contraceptive can interfere with the females’ sexual function , 13. ConTherefore, given the disagreements in the existing literature, the review of recent evidence on this subject seemed to be necessary. In general, due to the lack of comprehensive data in this area, the current study was conducted to measure the effects of the combined contraceptive vaginal ring on females’ sexual function.Databases including PubMed, ISI web of science, Scopus, Embase, Cochrane Library and Google Scholar were searched, up to July 2021, using such search terms as ‘Vaginal Ring’, ‘Nuvaring’, ‘Sexual’, ‘Sexuality’, ‘Sexual Behaviour’, ‘Sexual Dysfunctions’ and ‘Sexual Function’. Moreover, PICO elements were used, including Population, Intervention, Comparison and Outcome. The study population included reproductive-aged women and the intervention consisted of the insertion of a vaginal ring as a hormonal contraceptive method. The vaginal ring is a safe and convenient birth control method and releases 15 μg of ethinylestradiol (EE) and 120 μg of etonogestrel (ENG), daily. The comparison group was the group receiving other contraceptive or no contraceptive method at all. Outcomes consisted of sexual function. This variable was measured using valid tools and reported as mean and standard deviation (SD). Full search terms are available in Additional relevant studies were also collected by searching through reference lists of all the identified studies.Inclusion criteria in the meta-analysis included: i) prospective cohort of intervention studies  that examined the effect of vaginal ring on sexual function; ii) full articles available in English and iii) sexual function measured in baseline and follow-up and presented as mean ± standard deviation (SD) values or mean difference and SD difference. On the other hand, exclusion criteria included: i) letter or editorial papers, narrative reviews or case reports, and ii) conference abstracts without a full text. No time restriction was applied when searching the relevant studies.Moreover, study selection was performed independently by two investigators (EA and AA). Any disagreement between the research team members was resolved through discussion. Details of the study selection process are presented in the PRISMA flow diagram in All data were reviewed and extracted from the collected studies by two independent authors (EA and AA) using a standardised information sheet. The extracted data included information about the first author, year of publication, study setting, study design , the follow-up time interval, sample size, sexual function assessment scales, sexual function mean ± SD and age at baseline.n = 14) and before-after (pre-post) studies with no control group (n = 12) through consensus by two authors. The assessed criteria in controlled intervention studies included a description of randomisation, adequate randomisation method, blinding, the similarity of groups at baseline, overall and differential dropout rate, adherence to the study protocols, avoiding other interventions, reliable and valid outcome measurement method, selection of sufficient sample size and intention-to-treat analysis.Furthermore, the quality of the included studies in the meta-analysis was evaluated using the National Institutes of Health (NIH) framework for the quality assessment of controlled intervention studies  were considered statistically significant.Effect sizes for the meta-analysis were selected based on the weighted mean difference (WMD) of sexual function score. Subgroup analysis, as well as meta-regression analysis, were performed to determine the source of heterogeneity. Statistical heterogeneity was also measured by the Cochran Q test and the I2 statistic. A funnel plot and Egger’s tests were further used to evaluate publication bias. Sensitivity analyses were also performed to evaluate the effects of each study on the overall results. A random-effect model was used to derive the overall effect. The data synthesis was carried out using Comprehensive Meta-Analysis software . The PRISMA flow chart of included studies is presented in The risk of bias for three studies was rated as moderate, whereas two studies had a low risk of bias. No study met the criteria for a high risk of bias .P = 0.026) (P = 0.357)  . However= 0.357) .P = 0.001, I2 = 97.95% and Q-statistic P = 0.022, I2 = 73.87%, respectively).The Q-test results showed significant heterogeneity among the studies in two time periods (Q-statistic P = 0.001). Furthermore, the results suggested that the effect of ring on sexual function of women varied significantly based on their BMI, 3 months after insertion , though not after 6 months .Meta-regression analysis was also conducted to evaluate the association between sexual function score and potential moderator variables, such as participant’s age and body mass index (BMI). The results suggested that the pooled estimate was associated with the participant’s age 3 months after ring insertion   .P = 0.945) showed no publication bias . Moreover, most of the included studies in the meta-analysis had been carried out in Italy, which makes it impossible to overgeneralise the results obtained in the present study. Moreover, given that the overall risk of bias for all included studies was moderate, more high-quality RCTs are needed to clarify the precise effects of vaginal rings on the sexual function of women.Based on the obtained results in this meta-analysis, it can be concluded that the application of vaginal rings is associated with a positive effect on the sexual function of women 3 months after insertion. However, this device had no impact on the sexual function of women after 6 months. Given the limited available data on the effect of vaginal rings on the sexual function of women, future randomised, controlled and double-blinded studies with low risk of bias levels are recommended to increase the validity of the results obtained in this study.


Since the release of previous meta-analyses, some studies on the associations between fruit and vegetable intake with gastric cancer risk have been published. Therefore, we aimed to update the previous meta-analyses on these associations by including recently published studies as well as considering the main limitations of those meta-analyses.A comprehensive search was conducted in online databases including PubMed, Scopus, ISI Web of Science, and Google Scholar to detect relevant prospective cohort studies published up to October 2021. Summary relative risks (RRs) were estimated using a random-effects model.I2 = 0%] and total fruit and vegetable  were associated with a lower risk of gastric cancer. For total vegetable intake, a significant inverse association was found among the studies that controlled their analysis for energy intake. Based on the linear dose-response analysis, each 100 g/day increase in total fruit intake  and 200 g/day increase in total fruit and vegetable intake  were associated with a 5 and 6% lower risk of gastric cancer, respectively.Overall, 17 articles containing 18 prospective studies with a total sample size of 1,527,995 participants, aged between 18 and 90 years, were included in the current meta-analysis. During the follow-up periods ranging between 4.5 and 21 years, 8,477 cases of gastric cancer were diagnosed. A higher intake of total fruit [RR: 0.87, 95% confidence interval (CI): 0.80 to 0.94, Fruit and vegetable consumption has a protective association with gastric cancer risk. Although the incidence of gastric cancer is declining, it ranks as the third cause of cancer mortality . PreviouIn a meta-analysis in 2014, Wang et al.  reportedGiven the points mentioned above, we conducted the current comprehensive and updated systematic review and dose-response meta-analysis of prospective cohort studies to review available findings on the association of total fruit, total vegetable, total fruit and vegetable, and total citrus intake with gastric cancer risk in adults.We used the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines to report the findings of this systematic review and meta-analysis .A comprehensive search was conducted in the online databases including PubMed, Scopus, ISI Web of Science, and Google Scholar to detect relevant papers that assessed total fruit, total vegetable, total fruit and vegetable, and total citrus intake in relation to gastric cancer risk published to October 2021. We developed and performed the literature search (SN), and two reviewers (ES and MN) screened the titles and abstracts. The MeSH  and non-MeSH terms used in the search strategy are presented in Two of the authors (ES and MN) screened the title and abstract of all publications found in the systematic search to identify studies that met our inclusion criteria. We included studies with prospective cohort design that were performed on adults (≥ 18 years) and assessed dietary intake of total fruit, total vegetable, total fruit and vegetable, or total citrus as an exposure variable and the risk of gastric cancer at any histological sites as an outcome variable. In addition, we only included the studies that reported risk estimates, including hazard ratios (HRs) and risk ratios (RRs) with 95% confidence intervals (CI) for the association between exposure and outcome. If results from one dataset were published in more than one paper, we selected the most recent one; otherwise, the one with the more complete data or with higher quality was included.We did not include letters, comments, reviews, and ecological studies. Also, we excluded qualitative studies, studies that were conducted on children and adolescences, those that investigated other gastric disorders such as gastritis rather than gastric cancer, and articles that reported unadjusted risk estimates or with insufficient data (studies that did not report RR or 95% CI for the link between exposure and outcome). Moreover, we did not include those studies that assessed dietary intakes of pickled or canned vegetables, raw vegetables, green-yellow vegetables, other vegetables, apple fruits or other individual fruits rather than total fruits or vegetables, in relation to gastric cancer. One exception is a study  in whichTwo investigators independently extracted required data from each paper (MN and ES). Since the main risk estimates in the current meta-analysis were RRs, or HRs along with 95% CIs, we extracted them from included articles. We extracted the risk estimates in the fully adjusted model if an article contained crude and multivariable-adjusted models. In addition to risk estimates, the following information was extracted from each article: the first author name, publication year, sample size, number of cancer cases, demographic characteristics of participants , study location, duration of follow-up, methods used to assess dietary intake and gastric cancer, and confounding variables taking into account in the statistical analysis.The quality of included studies was determined using the Newcastle Ottawa Scale, designed for non-randomized studies . Based oI2 values as indicators of heterogeneity. We considered the I2 values of < 25%, 25–50%, 50–75%, and > 75% as low, moderate, high, and very high between-study heterogeneity, respectively (We included the risk estimates (including HRs and RRs) and 95% CIs of gastric cancer for the comparison between the highest and lowest intakes of fruit/vegetable intake into the meta-analysis. We first calculated the natural log form (and its standard error) of these RRs and then we combined them using a random-effects model to calculate the overall RR of gastric cancer for the comparison between the highest and lowest intakes of fruits/vegetables. Compared to a fixed-effects model, a random-effects model can take between-study heterogeneity into account . For stuectively . We perfectively . In the ectively . To asseP < 0.05 was considered as statistically significant for all tests, including Cochran’s Q test.We used the generalized least squares trend estimation method described by Greenland and Longnecker  and OrsiIn our initial search in the online databases, we found 8,095 articles that 2136 of them were duplicates and therefore were excluded. Of the remaining articles, 5,906 were also excluded because they were unrelated to our subject based on assessing their title and abstract. In total, 53 papers remained for full-text assessment, of them, 19 were excluded because of case-control design. Also, Jeurnink et al.  study wan = 17), BMI (n = 5), smoking (n = 14), alcohol consumption (n = 8), physical activity (n = 3), and energy intake (n = 8) were adjusted in the analysis of fruit and vegetable intake with gastric cancer risk. Based on the NOS, all included studies except two , indicating no significant association between total vegetable intake and gastric cancer .In total, 10 papers (containing 15 studies) with a total sample size of 1,445,175 participants and 7,075 cases of gastric cancer assessed the link between vegetable intake and gastric cancer , 25–27. c cancer . HoweverI2 = 37.4%, Pheterogeneity = 0.10) (P non-linearity = 0.26)  . Also, w = 0.26) .I2 = 0%, Pheterogeneity = 0.82), illustrating a significant inverse association between total fruit intake and gastric cancer (We included 12 articles 16 studies) with a total sample size of 1,465,515 participants and 7,330 cases of gastric cancer in this section  studies , 25–27. c cancer .I2 = 49%, Pheterogeneity = 0.03) (P non-linearity = 0.004), with a significant reduction in risk from no intake up to 200 g/day and there was no further reduction in risk above the 200 g/day  . Also, w00 g/day .I2 = 55.2%, Pheterogeneity = 0.04), indicating a significant inverse association in this regard (Six publications (nine studies) entered total intake of fruits and vegetables, rather than total fruits or total vegetables, in their analysis , 23, 27.s regard .I2 = 37.6%, Pheterogeneity = 0.17) (P non-linearity = 0.82)  . In the  = 0.82) .I2 = 37.2%, Pheterogeneity = 0.15) that indicated a non-significant association  (P non-linearity = 0.17) (Five articles (six studies) containing 1,147,546 participants and 2,837 gastric cancer cases were included in the analysis of citrus intake and gastric cancer , 23–25. ociation . In the  = 0.58) . In addi = 0.17) .Findings from the subgroup analyses are shown in I2 = 0, Pheterogeneity = 0.87). Also, excluding the study of Freedman et al.  resulted in a significant association between citrus intake and gastric cancer. Sensitivity analyses for the Wang et al. article  and total fruit intake  did not change the overall results obtained for these exposures. Of note, this article did not present data on citrus intake and total vegetable and fruit intake. In terms of publication bias, Egger’s linear regression test showed no substantial publication bias in all associations except for total fruit and vegetable intake and gastric cancer, in which there was evidence of publication bias. Nevertheless, the application of the trim-and-fill method did not change the average effect size, further suggesting that results were not affected by publication bias.Based on sensitivity analysis, our findings on the link between total vegetable intake and gastric cancer depended on Tran et al. study  so that  article  showed tIn the current meta-analysis, we found that a higher intake of total fruit and total fruit and vegetable was associated with a 13 and 25% lower risk of gastric cancer, respectively. Although the overall association was not significant for total vegetable intake, we found a significant inverse association among the studies that controlled their analysis for energy intake. Moreover, in the linear dose-response analysis, each 100 g/day increase in total fruit intake and 200 g/day increase in total fruit and vegetable intake were associated with a 5 and 6% lower risk of gastric cancer, respectively. Such linear association was not seen for total vegetable intake and also citrus intake.Gastric cancer is a major public health concern worldwide due to its frequency, limited therapies, and poor prognosis . PreviouN-nitroso compounds in humans (In the current meta-analysis, we found that total fruit intake had a protective association with gastric cancer. This finding was similar to the previous meta-analysis conducted by Wang et al.  in whichn humans . In the n humans . These fIn the case of total vegetable intake, we found no significant association with gastric cancer risk in the overall analysis. However, the results depended on Tran et al. study  so that When we confined the analysis to studies that controlled for energy intake in their analysis, a significant inverse association was seen between total vegetable intake and gastric cancer. In the meta-analysis of Wang et al.  no signiIt should be kept in mind that different types of vegetables may have different associations with the risk of gastric cancer. For instance, in a meta-analysis, Wu et al.  reportedVegetables are a rich source of fiber and antioxidants that induce cancer-preventive effects. The meta-analysis of Zhang et al.  indicateSince small studies with non-significant results or unattractive findings tend not to be published, the possibility of publication bias is unavoidable in meta-analyses. This bias is particularly common among observational studies . In the The major strength of this meta-analysis was the prospective design of included studies. Prospective studies have the highest quality among observational studies. Also, the linear and non-linear dose-response analysis provided the most compelling evidence for quantitative evaluation of associations and enabled us to determine the strength and shape of the dose-response relationships. In addition, between-study heterogeneity was low in most associations evaluated in the current meta-analysis. Our findings should be interpreted by considering several limitations. First, since the studies included in the present meta-analysis were observational in nature, causality cannot be established. Second, the role of residual confounders from unmeasured behavioral and biological factors or errors in the measurement of covariates cannot be entirely excluded because of the observational design of included studies. Third, measurement errors are inevitable in estimation of fruit and vegetable intakes. Misclassification due to measurement errors could result in underestimating the associations of fruit and vegetable intake with the risk of gastric cancer. Fourth, as usually the case in cohort studies, most included studies had estimated dietary intakes based on a single measurement at study baseline, and changes in the diet throughout the follow-up were not considered. In addition, regional differences in fruit and vegetable intake may have been an issue in this meta-analysis that might affect the highest and lowest categories of exposures and the results obtained from the comparison of these categories. However, we performed a subgroup analysis accordingly to control these differences. We also conducted the dose-response analysis as another strategy to control these differences and the overlap between the ranges of fruit and vegetable intake among different studies.In conclusion, a greater intake of total fruits and total fruits and vegetables were associated with a 13 and 25% lower risk of gastric cancer, respectively. Also, when we combined the studies that excluded the confounding effect of energy intake from their analysis, such inverse association was seen for total vegetable intake. Also, each 100 g/day increase in total fruit intake and each 200 g/day increase in total fruit and vegetable intake were associated with a 5 and 6% lower risk of gastric cancer. Further studies should examine the associations of individual fruits and vegetables with gastric cancer risk.The original contributions presented in this study are included in the article/MN and ES contributed to the literature search and data extraction. SN and OS contributed to the data analysis. OS drafted the manuscript which was critically revised for important intellectual content by ES, HT, MA, MN, OS, SM, and SN. HT and ES contributed to the manuscript drafting and data analysis. SM and MA obtained funding and contributed to the manuscript editing. OS supervised the study. All authors have read and approved the final manuscript.


Psychiatric disorders have seriously affected human life, one of the risk genes related to psychosis is the methylenetetrahydrofolatereductase (MTHFR) gene. This gene has a potential role in psychiatric disorders. Therefore, a meta-analysis is conducted to investigate the correlations between two prevalent MTHFR single nucleotide polymorphisms (SNPs), MTHFR C677T, A1298C, severe psychological disorders .A total of 81 published studies were screened and selected by a search of electronic databases up to April 2022. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the association between MTHFR polymorphism and psychiatric disorders susceptibility by using random effect models.We found that MTHFR C677T polymorphism is significantly related to schizophrenia and major depression in the overall population. MTHFR C677T has been linked to an increased risk of bipolar disorder in the recessive model (TT vs. CT + CC). Ethnic subgroup analysis shows that schizophrenia and major depression significantly correlate with MTHFR C677T and A1298C in Asian populations but not Caucasians. Besides, schizophrenia is correlated substantially with MTHFR C677T in the African population. However, the MTHFR A1298C polymorphism is only marginally linked to major depression.Findings of the current study revealed that MTHFR may contribute to the common pathogenesis of psychiatric diseases and that its variants may be essential in controlling the expression of psychosis-related genes. This study could help the researchers and health specialists in the early diagnosis and treatment of psychiatric disorders. Mental disorders have seriously affected human life, causing considerable familial and social burden . They arThe MTHFR is a crucial enzyme in the one-carbon metabolism (OCM) process, which involves folate and homocysteine (Hcy) metabolisms. It transforms 5,10-methylenetetrahydrofolate  to 5-methyltetrahydrofolate (5-methyl THF), and it is involved in folate and homocysteine conversion, which is linked to DNA methylation –10. A nuThe human Methylenetetrahydrofolatereductase (MTHFR) gene is located in chromosomal region 1p36.3 . The MTHThe association between MTHFR polymorphism and mental illnesses has already been explored, but the influence of MTHFR on psychiatric disorders is still disputed, and limited studies have been found –23. ThesWe initially searched PubMed, Embase, Proquest, Web of Science, CNKI , VIP (Chinese) database, and Wanfang (Chinese) database for the following terms: MTHFR (methylenetetrahydrofolatereductase), gene (gene or genetic or polymorphism or variants or variation), and psychiatric disorders . We discovered that most research concentrated on MTHFR C677T and MTHFR A1298C. The researchers investigated the relationships between MTHFR gene variants and susceptibility to mental diseases such as schizophrenia, bipolar disorder, and depression. To guarantee that we missed no studies, we searched these databases again using these gene terms (MTHFR C677T and A1298C) and major mental disorders such as “schizophrenia,” “bipolar disorder,” “depression,” and so on. All of the research was completed and published by April 2022. After that, we selected relevant papers and examined their bibliographies to find additional references.Selection of articles for analysis purposes was made based on the following criteria: (1) case-control studies; (2) giving comprehensive data of formally diagnosed patients with unrelated healthy control subjects for generating an odds ratio (OR) with a 95% confidence interval (CI); (3) Case status was classified as having a DSM-IV-diagnosed mental condition, with control patients having no history of psychiatric disorders or other neurological abnormalities; (4) the studies used samples that did not overlap with other studies; (5) the use of internationally recognized loci gene polymorphism detection techniques ; and (6) the demographic characteristics of the control group, such as gender and age, were comparable to those of the case group. In addition, articles were excluded if they (1) not reported the target genotype frequencies, (2) were reviews, letters, or commentaries, or (3) were duplicate reports.Two reviewers independently extracted the following information from all eligible studies: author, year of publication, country, ethnicity , and the number of distinct genotypes in cases and controls for C677T or A1298C genotype. In the case of a disagreement, a discussion was held, and if no agreement could be achieved, a third person was consulted for consensus.Q) X2 test and I2 statistic were used to assess the heterogeneity between individual studies  and associated 95% confidence intervals (CIs) were used to examine the strength of the connection between MTHFR polymorphism and mental disorders: the allele model , the dominant model , the homozygote model  and the recessive model . The Chi-square test was used to analyze the genotype distribution in the control groups for Hardy Weinberg equilibrium (HWE). The Cochran’s ( studies . Conside studies . Subgrou studies . Stata 1HWE) of included articles are summarized in Out of screened articles, 843 unduplicated association studies were found. P < 0.001; for TT + CT vs. CC: OR = 1.18, 95% CI = 1.10–1.27, P < 0.001; for TT vs. CT + CC: OR = 1.25, 95% CI = 1.13–1.37, P < 0.001; for TT vs. CC: OR = 1.35, 95% CI = 1.19–1.52, P < 0.001) (Findings of the association and the heterogeneity test is shown in < 0.001) .P < 0.001; for TT + CT vs. CC: OR = 1.22, 95% CI = 1.10–1.35, P < 0.001; for TT vs. CT + CC: OR = 1.31, 95% CI = 1.16–1.48, P < 0.001; for TT vs. CC: OR = 1.46, 95% CI = 1.24–1.72, P < 0.001); in Caucasian populations, a significant association was found with the allele model  and the dominant model ; in African populations, there was a significant association with the allele model , the recessive model  and the homozygote model . All these findings are summarized in An ethnic subgroup analysis revealed a substantial association between MTHFR C677T polymorphism and SZ among Asian populations . Sensitivity analysis for the MTHFR A1298C polymorphism revealed that excluding Lee et al.  (< 0.001) .P < 0.001; for TT + CT vs. CC: OR = 1.52, 95% CI = 1.11–2.08, P = 0.009; for TT vs. CT + CC: OR = 1.75, 95% CI = 1.34–2.28, P < 0.001; for TT vs. CC: OR = 1.89, 95% CI = 1.40–2.57, P < 0.001), but not in Caucasian and African populations  and the homozygote model    . Moreove= 0.004) . Nonethe= 0.004) . SubgrouFour articles were not found in Hardy–Weinberg equilibrium , 85, 95 P = 0.028) and the homozygote model  (= 0.049) . Moreove= 0.049) . Additio= 0.049) .Only one study was not in Hardy Weinberg equilibrium  Table 2Table 2, Significant publication biases were found when all diseases were considered . TherefoMost studies were not in Hardy–Weinberg equilibrium when all diseases were considered. Moreover, analysis between MTHFR A1298C and psychiatric disorders was also unsuitable. Significant correlations were detected between the MTHFR A1298C polymorphism and psychiatric disorders . HoweverPEgger = 0.01). The Egger’s test results for MD were substantial in two genetic models of overall populations . And there was no publication bias for BPD. Publication bias may correlate to the editor’s decision for publication. However, it is common that only the positive results are published, and negative findings are unavailable. So, we could not exclude this kind of possibility.In order to evaluate publication bias, we used formal statistical methods (Egger’s regression test). A mental disorder is a neurological disease with complicated etiology, which may be closely related to genetic factors. A great number of research on the susceptibility to mental illnesses  have been undertaken using MTHFR gene polymorphism. Some studies supported the susceptibility variation of MTHFR in mental diseases , 105, 69For Sz, our meta-analysis found a substantial association between MTHFR C677T polymorphism and higher incidence of SZ, which is consistent with research by Hu et al.  and PeerFor MD, our meta-analysis’s results showed a significant correlation between MTHFR C677T polymorphism and increased risk of MD. The meta-analysis of Wu et al.  supportsFor BPD, meta-analysis reveals that MTHFR C677T polymorphism is weakly related to the occurrence of diseases (in recessive models and homozygous models). The meta-analysis of Hu et al.  found a Many researchers have discovered that MTHFR is closely related to cognitive function, such as verbal fluency, visual-motor coordination, attention selectivity, and distribution –113. MTHSome limitations of this meta-analysis should be considered when interpreting the findings. Firstly, we can only search for English and Chinese articles with some language limitations. Second, publication bias cannot be ignored in the current study since Egger test findings are substantial in several SZ and MD genetic models. It may correlate to the editor’s decision for publication and so on. However, it is common that only the positive results are published, and negative findings are unavailable. And we could not exclude this kind of possibility. Furthermore, the number of articles on A1298C polymorphism with MD are insufficient to provide conclusive evidence. More original research is required to validate our results. Despite some limitations, our current research also has some value. First of all, our meta-analysis includes a large sample size, which can reduce errors. Secondly, we fully considered and analyzed the impact of race on the disease.Our meta-analysis findings demonstrate that MTHFR C677T polymorphism increases the risk of schizophrenia and severe depression in the general population, and a marginal correlation of MTHFR C677T with a higher risk of bipolar disorder has also been reported for the recessive model. More original research and a bigger sample size are required to validate our results. Nevertheless, the findings of our meta-analysis imply that MTHFR may play a significant role in the common pathogenesis of mental illness and that its variation may be involved in controlling the expression of genes associated with it. It would help in the early diagnosis and treatment of related mental disorders. Moreover, studies on risk factor analysis could be performed on psychiatric disorders to better prevent these mental health problems.The original contributions presented in this study are included in the article/Y-XZ: conceptualization, software, data curation, and writing – original draft preparation. DH: conceptualization, methodology, and funding acquisition. L-PY: data curation and validation. CG: visualization and investigation. C-CC: software and validation. Z-YG: writing – reviewing and editing. H-MS: project administration and supervision. All authors contributed to the article and approved the submitted version.