Meta-analysis was used to compare the effects of two interventions, high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT), on inhibition in executive function in healthy people, providing some theoretical basis for exercise practice and health interventions. We searched the PubMed, Science Direct, Web Of science, Cochrane, and CNKI databases for relevant articles on the inhibition function effects of HIIT and MICT in healthy populations for the period of library construction to 15 September 2022. The basic information of the screened literature was organized and summarized using Excel. Statistical analysis of the correct rate and response time indicators of the inhibition function in the HIIT and MICT groups was performed using Review Manager 5.3 analysis software. A total of 285 subjects from 8 studies were included in this study, the number of HIIT subjects was 142, the number of MICT subjects was 143, including teenagers, young adults, and the elderly. Eight studies included response time, and four included correct rate and response time. The standardized mean difference (SMD) for correct rate inhibition function in the HIIT and MICT groups was 0.14, 95% CI , SMD at response time was 0.03, 95% CI . In addition, no significant differences were found between the two exercise modalities in either the intervention period or the population receiving the intervention. Both HIIT and MICT could improve inhibition function in healthy people, but there was no significant difference in the improvement effect between them. It is hoped that this study can provide some references for people’s choice of health intervention methods and clinical practice. Executive function refers to the process of self-control and coordination by using the higher cognitive functions in the human brain when people encounter difficulties or want to achieve certain goals, mainly including inhibition, refreshment, and transformation functions . Good exInhibition function plays an important role in the executive functions of the brain , one stuHIIT is an effective training method that involves repeatedly performing short periods of high-intensity exercise, with active recovery at each interval, this produces more intense stimulation of the cardiovascular and muscular systems . MICT exAlthough some research has been conducted comparing the effects of HIIT and MICT methods on the improvement of inhibition function in executive functions in healthy individuals ,24,25, aIn this study, two researchers searched PubMed, Science Direct, Web of Science, Cochrane, and CNKI databases by computer, using a hybrid search combining subject terms and free words in English and Chinese. The search terms were mainly  and (moderate-intensity continuous exercise) and . To make the search more comprehensive, we also conducted a manual search from published meta-analyses to literature reviews. The search was conducted from the date of creation to September 15, 2022.Study screening was conducted by two pretrained researchers, who screened the studies retrieved from each database separately according to inclusion and exclusion criteria, and then pooled the selected studies. If the conclusions of the two researchers did not agree, the disagreement was first resolved through discussion. If the problem remained unresolved, a third-party expert adjudicated and agreement was obtained before inclusion.The inclusion criteria were as follows: (1) All studies published in the public domain; (2) the interventions used in the experiment must include HIIT and MICT; (3) the control measures were randomized controls; (4) the experimental subjects were healthy people; (5) the tests used for inhibition control were go/no go, flank, and Stroop methods, and the outcome indicators were response time and correct rate.The exclusion criteria were as follows: (1) Exclusion of review articles, conference abstracts, animal experiments, and other articles for which full text and outcome indicators are not available; (2) experimental interventions other than HIIT and MICT, or only one of these interventions; (3) the experimental design did not meet the requirements of this study; (4) the measurement paradigm used or the outcome indicators did not meet the requirements of this study; (5) subjects with chronic diseases, mental illnesses, etc.2 (post) + SD2 (pre)) − (2 × corr × SD (post) × SD (pre))], corr set to 0.5. If only the standard error (SE) and 95% confidence interval are provided in the literature, the SD = SE × SQRT (N), where N is the sample size, or SD = SQRT (N) × [(UCI − LCI)/3.92], where U = upper CI and L = lower CI [According to the needs of the study, two researchers were arranged to independently extract and enter data after reading the full text, which mainly included the following: First author of the article; year of publication; age and number of participants; intervention method ; test methods and results of outcome indicators. Ending indicators were entered according to the Cochrane handbook of systematic evaluation, and the difference between the mean and standard deviation before and after the intervention was extracted and, if not reported in the literature, calculated by the following formula: Mean (change) = Mean (post) − Mean (pre), SD (change) = SQRT [ scale to evaluate the methodological quality of the included studies ,30.p < 0.05 indicated that the study was statistically significant. Heterogeneity among the included literature was tested using a Q test and I2 test, p > 0.1 and I2 < 50% indicate homogeneity of the included indicators in this study, and meta-analysis should be performed using a fixed effect model, otherwise meta-analysis should be performed using a random effect model [2, with I2 < 25%, 25–49%, 50–74%, ≥ 75% representing low, moderate, high, and very high heterogeneity, respectively. The amount of effect is classified as: 0.2–0.5, 0.5–0.8, >0.8, representing small, medium, and large effect, respectively. When heterogeneity is significant, subgroup analysis or sensitivity analysis is required. A funnel plot and Egger method were used to check whether publication bias existed.The basic information and data of the acquired study were organized and summarized by Excel 2013, and meta-analysis of the two types of outcome indicators included in this study was performed by applying Review Manager 5.3 software. Due to the differences between the measurement tasks selected for this study and the experimental subjects, standardized mean difference (SMD) was used to express effect sizes and to estimate 95% confidence intervals, and ct model . The sizThe results of the study search and screening from the database are shown in The quality of the eight RCTs included was assessed methodically using two methods, all of which provided detailed descriptions of subjects’ inclusion conditions and described the use of random assignment to group them, but only one study provided detailed description of assignment . SubjectBasic information on the inclusion of all studies is shown in df = 3, p = 0.24, I2 = 29% < 50%, suggesting a low heterogeneity in the literature for this inclusion, and a fixed effects model was chosen for the meta-analysis. Combined effect size: SMD = 0.14, 95% CI , Z = 0.86, p = 0.39. The forest plot , Z = 0.28, p = 0.78. The forest plot , p = 0.53, I2 = 0%, SMD = −0.05, 95% CI , p = 0.39, I2 = 55%, SMD = 0.03, 95% CI , p = 0.78, I2 = 0%, According to the results of the subgroup analysis of the intervention method, as only one study  includedSMD = 0.27, 95% CI , p = 0.29, I2 = 11%, SMD = 0.03, 95% CI , p = 0.13, I2 = 57%, SMD = −0.03, 95% CI , p = 0.49, I2 = 0%, SMD = 0.06, 95% CI , p = 0.33, I2 = 13%, The results of the subgroup analysis of the intervention population showed no significant difference between HIIT and MICT for the improvement of correct rate in adolescents  and t = 0.25, p = 0.814 > 0.05, 95% CI  at response, further indicating that there was no publication bias in the literature included in this study.In this study, the funnel plot and Egger method were used to test for the presence of publication bias. The funnel plots  showed tThe aim of this study was to directly compare the effects of HIIT and MICT on the improvement of inhibition function in a healthy population through quantitative analysis using the meta-analysis method. Our results showed no significant differences in the improvement of inhibition function between the two exercise modalities overall, and no significant differences in the target population and duration of the intervention.Compared to MICT, HIIT has a variety of types, and shortens the duration of exercise, but the exercise effect does not diminish, and even shows better physiological adaptations, which is ideal for people with busy work schedules and lack of exercise time , and is The many advantages of HIIT have caused it to receive more scrutiny, but there is no clear consensus on which has a more significant effect on inhibition function between HIIT and MICT. Yang showed the effects of single HIIT and MICT exercise interventions on executive function in 36 university students and showed that MICT had a significantly better effect on inhibition function than the HIIT group . Cai admThis study also conducted subgroup analyses of the duration of intervention for HIIT and MICT, but there were no significant differences between acute and long-term exercise. Acute exercise may affect brain regions such as the anterior cingulate gyrus and prefrontal cortex associated with inhibitory function and increase cerebral blood flow and brain-derived neurotrophic factor concentrations contributing to cognitive function . Long-teIn addition, this study noted the large age range of subjects in the included studies, so a subgroup analysis of the intervention population was performed. The results showed that there was no significant difference in the effect of HIIT and MICT intervention on adolescents and adults. Zhang  found thHIIT, as an emerging method of sports training, has been favored by people in recent years. Compared with the traditional continuous exercise, HIIT has distinct features such as interest and timeliness, which can improve people’s sense of pleasure in the process of exercise . StudiesThere are some shortcomings in this study. First, this study was not registered on PROSPERO beforehand, and we will pay more attention to this requirement in future studies and actively seek experts in related fields to control the details of the article. Second, there are multiple experimental paradigms to test the suppression function, and since we do not fully unify the paradigm requirements, whether using different paradigms will have an impact on the results needs to be further verified. Third, although we have tried our best to find the literature related to this study, there is still a possibility of omission and the quality of the included literature is mostly moderate, which may have some influence on the reliability of the meta-analysis. Fourth, most studies did not provide information about the subjects’ daily physical activity level, so we did not make a summary of this in our study. The subjects’ daily physical activity level may affect the final test result. Fifth, whether the effects of the two exercise interventions on inhibitory function are related to gender is also worthy of future detailed discussion. Finally, due to the limitation of data in the literature, the analysis and discussion of the content of the subgroup analysis are not comprehensive and in-depth, and more perspectives are needed in the future to explore the effect of exercise on the improvement of inhibition function.The results of a meta-analysis showed that there is no significant difference between HIIT and MICT in terms of improving inhibition function in healthy individuals. Each type of exercise has its own advantages, so different people can choose the one that suits their needs and preferences. Future studies could further analyze the effects of both exercise modalities on interventions for other components of executive function, as well as include studies with special populations.


I2 = 99.7%, n = 12,997,101; 11 studies, with high heterogeneity between studies. Subgroup analyses indicated stronger associations in studies with shorter follow-up periods, conducted in non-European countries, published after 2020, and where ≥60% of the sample were female. The risk was higher in people aged <60 years at baseline, in typical and late-onset psychotic disorders versus very late-onset psychosis, in broader psychotic disorders vs schizophrenia, and in prospective vs retrospective studies. Associations remained after excluding low quality studies , I2 = 99.0%). Our review finds a substantial association between psychotic disorders and subsequent dementia. Our findings indicate that psychotic disorders are a potentially modifiable risk factor for dementia and suggest that individuals with psychotic disorders need to be closely monitored for cognitive decline in later life. Further research is needed to investigate the mechanisms underlying the association between psychotic disorders and dementia.Non-affective psychotic disorders have been associated with an increased risk of developing dementia. However, research in this area remains limited, highlighting the need for an up-to-date systematic review and meta-analysis of the evidence. We aimed to systematically review and quantify the risk of dementia associated with psychotic disorders. We searched four electronic databases for longitudinal studies investigating non-affective psychotic disorders and subsequent dementia. We used random-effects meta-analyses to pool estimates across studies and assessed risk of bias for each study. Non-affective psychotic disorders were associated with increased risk of all-cause dementia; pooled risk ratio (RR) = 2.52, 95% confidence interval (CI) (1.67–3.80),  Dementia is a syndrome characterised by progressive cognitive and functional decline constituting one of the leading causes of disability worldwide  and very late-onset schizophrenia-like psychoses (VLOSLP), which have symptom onset after age 40 and 60 years respectively, relative to psychotic disorders with a more typical age-at-onset, occurring in late adolescence and early adulthood . Full-texts were searched for all identified studies, and two authors independently screened all full-text articles for relevant studies. Disagreements were discussed with a third reviewer. Reference lists of all relevant studies reaching the full-text phase were hand searched to ensure no relevant studies were missed.We included both prospective and retrospective longitudinal studies examining the association between psychotic disorders and dementia. The population of interest were adults aged ⩾18 years with a clinical diagnosis of a non-affective psychotic disorder , and the comparison group were adults without a non-affective psychotic disorder , risk ratios (RR), odds ratios (ORs), incidence rate ratios (IRRs), standardised mortality ratios (SMRs), and standardised incidence ratios (SIRs), along with standard errors and confidence intervals (CIs), were extracted for the meta-analysis. We combined various measures of relative risk in line with current guidelines, and the rare disease assumption, which states that various measures of relative risk will approximate each other when the outcome investigated is sufficiently rare  (see online Supplementary Table S3), covering three risks of bias domains: selection of study groups, comparability and study design, and outcome Stang, . Disagre2 Cochran's Q test and the I2-statistic. We examined sources of heterogeneity using subgroup analyses, sensitivity analyses, and meta-regression.STATA (Version 17.1) and the ‘metan’ and ‘metareg’ commands were used to conduct the meta-analyses and meta-regressions. The generic inverse variance method and a random-effects model was used to obtain pooled relative risk estimates across studies that reported IRRs, HRs, RRs, ORs, SMRs, and SIRs. Heterogeneity was measured using the χThe study selection process followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA)       , 11 years . For the11 years  study, w11 years  study we11 years  study we11 years  reportedt = 1.22, p = 0.252) , I2 = 98.9%, p < 0.001, n = 3). Studies with a follow-up of <10 years showed a larger effect compared to studies with a follow-up of ⩾10 years; pooled RR = 2.64, 95% CI (1.98–3.51), I2 = 10.9%, p = 0.338, v. pooled RR = 2.33, 95% CI (1.43–3.82), I2 = 99.8%, p < 0.001. Risk was higher in studies conducted in non-European countries compared to those recruiting in European countries; pooled RR = 2.96, 95% CI (1.56–5.62), I2 = 99.4%, p < 0.001, v. pooled RR = 2.04, 95% CI (1.12–3.71), I2 = 99.5%, p < 0.001. Studies in which ⩾60% of the sample were female showed a higher risk compared to studies with less than <60% of the sample being female; pooled RR = 3.24, 95% CI (2.09–5.02), I2 = 79.0%, p = 0.003, v. pooled RR = 2.10, 95% CI (1.42–3.12), I2 = 96.7%, p < 0.001. In addition, the association between psychotic disorders and dementia was stronger in studies published in 2020 or after, relative to those published before 2020; pooled RR = 3.13, 95% CI (1.55–6.33), I2 = 99.9%, p < 0.001, v. pooled RR = 1.93, 95% CI (1.34–2.77), I2 = 95.8%, p < 0.001.Our subgroup analyses indicated that the risk of dementia was higher in individuals with typical and late-onset psychotic disorders (onset <40 years and >40 years) compared to individuals with VLOSLP (onset >60 years); pooled RR = 3.10, 95% CI (2.33–4.14), I2 = 99.4%, p < 0.001, v. pooled RR = 2.13, 95% CI (1.66–2.73), I2 = 95.9%, p < 0.001. Risk was higher in prospective studies compared to retrospective studies; pooled RR = 2.65, 95% CI (2.10–3.35), I2 = 28.3%, p = 0.248, v. pooled RR = 2.34, 95% CI (1.45–3.78), I2 = 99.8%, p < 0.001. Our final set of analyses showed that studies in individuals with a minimum age <60 at baseline showed a higher risk of dementia compared to studies with a minimum age ⩾60; pooled RR = 3.16, 95% CI (1.59–6.28), I2 = 99.8%, p < 0.001, v. pooled RR = 2.61, 95% CI (1.39–4.92), I2 = 99.8%, p < 0.001. Correlations between potential moderators are reported in online Supplementary Table S5.Studies investigating broader non-affective psychotic disorders showed a higher risk compared to studies investigating schizophrenia; pooled RR = 2.78, 95% CI (1.57–4.91), p = 0.66), follow-up time-point (p = 0.59), geographical region (p = 0.41), or year of study publication (p = 0.22) (see online Supplementary Table S6).In line with current recommendations, we conducted meta-regressions for characteristics that were examined in at least 10 studies  remained the same after excluding any single study. Excluding low-quality studies (n = 3)  , I2 = 99.0%, p < 0.001, respectively  (interaction p < 0.001). Associations between schizophrenia and dementia were also stronger in the presence of diabetes, hypertension, Parkinson's disease, traumatic head injury, and alcohol-related disorders . Ribe et al. found that associations were stable in subgroups relating to medical comorbidities, with no evidence of differences in relation to diabetes, ischaemic heart disease, congestive heart failure, atrial fibrillation, or peripheral vascular disease. Schizophrenia showed stronger associations with dementia in those without cerebrovascular disease; IRR = 2.23, 95% CI (2.08–2.39) v. IRR = 1.71, 95% CI (1.47–2.00), p = 0.002. In contrast to the Lin et al. study, the association between schizophrenia and dementia was stronger in those without comorbid substance abuse; IRR = 1.96, 95% CI (1.82–2.11) v. IRR = 1.09, 95% CI (0.95–1.24), p < 0.001.Two studies examined associations between psychotic disorders and dementia in relation to comorbidities  as well as late-onset psychotic disorders (onset >40 years), and VLOSLP (onset >60 years). The association was stronger, however, in those with typical and late-onset psychotic disorders, in studies following individuals for <10 years, and in studies conducted in non-European countries. Associations were also stronger in studies with a higher proportion of females and a younger minimum age at baseline. Our narrative synthesis provided some evidence that people with psychotic disorders tended to be younger at dementia diagnosis and that the association between psychotic disorders and dementia was stronger when the interval between the two diagnoses was shorter. Our findings highlight a need for further research examining whether findings vary across different dementia subtypes, for example Alzheimer's disease relative to vascular dementia, and to formally test whether the age-at-onset of dementia differs between those with and without psychotic disorders.There are several potential causal mechanisms that may explain the association between psychotic disorders and increased dementia risk. Schizophrenia has been posited to be a disorder of accelerated ageing, whereby the physiological changes of ageing associated with the disorder may occur earlier than normal, predisposing individuals to cognitive decline (Kirkpatrick, Messias, Harvey, Fernandez-Egea, & Bowie, Furthermore, there is a substantial mortality gap between people with psychotic disorders and the general population (Saha, Chant, & McGrath, In addition, it has been posited that antipsychotic medications could contribute to an increased risk of dementia (Jonas, Abi-Dargham, & Kotov, Although our data indicate an increased risk of dementia in non-affective psychotic disorders, it remains possible that this association could be partly explained by reverse causation, whereby psychotic symptoms could represent markers of prodromal dementia rather than causal risk factors (Ismail et al., In line with this hypothesis, our subgroup analysis suggested that individuals with an earlier onset of psychotic disorders had a greater risk of dementia than individuals diagnosed with VLOSLP. People with typical and late-onset psychotic disorders are likely to have been diagnosed with a psychotic disorder many years before the symptoms of dementia begin, consistent with the possibility that psychotic disorders are a risk factor for dementia. A possible explanation for this finding is that individuals with an earlier onset have a longer exposure to the adverse effects of living with a psychotic disorder, resulting in accumulation of several negative health behaviours and medical comorbidities increasing dementia risk.Further longitudinal studies with long follow-up periods and studies that model trajectories of association over time are required to elucidate possible mechanisms underlying the relationship between psychotic disorders and increased dementia risk (Singh-Manoux et al., We used a comprehensive and highly sensitive search strategy, including a grey literature search of the worldwide evidence. Our meta-analysis included studies from several countries, most of which reported data on large sample sizes and long follow-up periods. Most of our studies were also assessed to be of high quality, which increases our confidence in the conclusions of our review. Our meta-analytic estimates are also similar to those reported in an earlier review examining the association between schizophrenia and risk of dementia (Cai & Huang, In addition, there were insufficient data available to conduct formal subgroup analyses for all factors of interest, including interval between psychotic disorder onset and dementia diagnosis, and age-at-onset of dementia, highlighting the need for further longitudinal evidence in this area. Most studies included in our meta-analysis were retrospective register-based studies, which often lack detailed information on socio-demographic confounders (Talari & Goyal, This systematic review and meta-analysis provides an up-to-date estimate and narrative synthesis of the association between non-affective psychotic disorders and future dementia risk. Our findings indicate that non-affective psychotic disorders constitute an important and potentially modifiable risk factor for all-cause dementia and highlight the need to revise current models of dementia prevention across the life span (Livingston et al.,


Pharmacovigilance reports have suggested that certain commonly used medications may trigger autoimmune diseases (ADs) and immune-mediated inflammatory diseases (IMIDs). We systematically reviewed the literature to evaluate whether psychiatric medication use is associated with ADs and IMIDs.th, 2021, for comparative studies, with any psychiatric medication as exposure and ADs and IMIDs as outcomes. Meta-analysis was performed using DerSimonian-Laird random-effects modeling. The PRISMA 2020 guidelines were followed in reporting. Study-level risk of bias was assessed using the Newcastle-Ottawa Scale, and the overall certainty of evidence using GRADE.The protocol was registered in PROSPERO (CRD42022296524) before the start of the study. We searched Medline Ovid and Scopus up to November 282 97.5%, 6 studies) was of low certainty. A subgroup analysis by the histological type of microscopic colitis showed a statistically significant association only with lymphocytic colitis . In two case-control studies, SSRI use had no significant association with psoriasis . The risk of acute pancreatitis was slightly increased with exposure to SSRIs , as was the risk of bullous pemphigoid after exposure to antipsychotics .There were 7,265 citations from which 31 studies were eligible, all from high-income countries, covering 15 distinct immune diseases. The evidence for the association between selective serotonin reuptake inhibitor (SSRI) use and higher risk of microscopic colitis (meta-OR 2.60, 95% CI 1.05–6.39, IWe reviewed the literature on whether psychiatric medications associate with the risk of ADs and IMIDs and concluded that, despite several signals, the credibility of evidence remains low at best. Prospective cohort studies would be needed as the next step to confirm the suggestions of increased risk. The causes of most autoimmune diseases (ADs) and immune-mediated inflammatory disorders (IMIDs) are unknown. The etiology and pathophysiology of most of them are probably unrelated, yet some share common genetic and environmental risk factors. The common denominator of these diseases is the dysregulation of immune pathways, leading to mistargeted or excessively activated responses, manifesting in subsequent organ-specific or multisystem damage . GloballThe most widely documented drug-induced autoimmune phenomenon is drug-induced lupus (DIL). A range of medications has been linked with it, including psychiatric drugs such as carbamazepine and levomepromazine . Drug-inAnimal models have associated mental stress with a proinflammatory state . In humaWe aimed to assess whether reports from case series could be supported by epidemiological evidence from comparative observational studies. Due to uncertainty in the etiology of the range of these diseases and finding no biological rationale to restrict the search to only a few of these diseases, we conducted a search of all major ADs and IMIDs covered in the literature.The systematic review protocol was registered on PROSPERO CRD42022296524) before commencing the study. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement was used to guide the reporting of the process [6524 befoWe considered original articles published in any language but excluded conference abstracts and reviews. We managed the citations using the RefWorks legacy edition. All authors participated in the data collection and risk-of-bias assessments, which were performed in duplicate by two authors using a Microsoft Excel sheet. The collected data were checked and synthesized by one author (ON). Data items included basic study details, which diseases were studied as outcomes, which medications were studied as exposures, drug exposure definitions, study country and continent, age and gender distributions, years of recruitment, study design (case-control or cohort), and whether the study was prospective or retrospective. Studies were excluded, if an effect measure was not reported and it was not possible to calculate it based on the reported data. Individual studies were assessed with the Newcastle–Ottawa Scale (NOS) in three domains: selection, comparability, and outcome ascertainment . The NOSmeta package with metagen and forest.meta functions were used to perform random-effects meta-analyses (DerSimonian and Laird) and create forest plots. Between-study heterogeneity in estimates is designated by the Tau2 and I2 statistics, and in the case of the latter, 0–40% indicates non-important heterogeneity, and 75–100% indicates very important heterogeneity [The summary measure for binary outcomes is the odds ratio (OR) in case-control studies, the risk ratio (RR) in cohort studies, and the hazard ratio (HR) in cohort studies with time-to-event data. RStudio (version 2022.02.2) and the ogeneity , 13. We ogeneity . ReanalyThe primary search yielded 7,265 citations, of which 203 were assessed in duplicate (authors IL and ON), eventually contributing 31 articles eligible for narrative review , Table 2Because of the limited number of studies by exposure-outcome pairs, a meta-analysis was possible only for 1) antipsychotics (any type) and bullous pemphigoid, 2) SSRIs and MC , 3) SSRIs and psoriasis, and 4) SSRIs and acute pancreatitis . Other s2 97.45%, 6 studies, at least 1,322 exposed cases). The studies by Fernández-Bañares and Pascua had the highest risk of bias  [2 92.01%, 4 studies) than in the analysis of all SSRI studies. All studies except Weimers et al. reported the numbers of individuals in the analysis [Seven case-control studies investigated the odds of MC (or CC and LC) by exposure to SSRIs (any) or sertraline . The ovectively) , 19. In analysis .2 00.00%, 3 studies) but not between SSRIs and CC . Based on GRADE, the certainty of the evidence was low, with considerably high heterogeneity.A meta-analysis by histologic subtype of MC showed a statistically significant association between SSRIs and LC . In individual studies, only lithium and phenothiazines were associated with a slightly increased psoriasis risk . However, these studies were small-scale, together contributing only 48 patients for the meta-analysis. The only reasonably powered study  was not included in the meta-analysis, as it reported individual medications instead of broader classes [Bullous pemphigoid as outcome was investigated in four case-control studies, all representing studies with a relatively higher risk of bias (NOS score range 5–6) –31. Meta2 00.00%, 649 SSRI-exposed patients) with adjustment for major confounding factors, including alcohol-related diseases. Current SNRI use was associated with a marginally increased pancreatitis risk after the adjustment of relevant confounders  [AP was the outcome in six case-control studies, all representing a low risk of bias according to NOS  –27. For 1.0–1.4) . The estGasse et al. were the only ones to investigate the potency of conventional antipsychotics in blocking dopamine receptors with pancreatitis as the outcome . The curThe current use of valproic acid increased the risk of pancreatitis in an analysis adjusted for, among other factors, alcohol-related diseases and gallstone disease . However, this estimate was based on only 16 valproic acid-exposed pancreatitis patients and thus constitutes very low-certainty evidence.Roberts et al. was the only cohort study on the risk of systemic lupus erythematosus (SLE), with a high risk of bias (NOS 5) . They foTwo cohort studies assessed the risks of alopecia areata after exposure to any antidepressants with contrasting results. Vallerand et al. found a protective effect , and Mirza et al. a modestly increased risk  with the use of antidepressants , 36. SimSingle studies assessed the risk of interstitial lung disease after SSRI or SNRI use , silent thyroiditis after lithium use , multiple sclerosis after valproic acid use , and vitiligo after antidepressant use  –45.We systematically searched an extensive list of ADs and IMIDs and evaluated whether the use of psychiatric medications can be considered a risk factor for their development. Published associations between any psychiatric medications and immune diseases were considered to represent low to very low certainty of evidence at best. This means that the available literature cannot reliably confirm or refute whether associations really exist, and the true effect sizes might be markedly different from the available estimates.In a meta-analysis, we found that SSRIs are associated with a 2–3-fold increase in the odds of developing MC. Furthermore, in a subgroup analysis by histological type, this risk appeared to be related to the development of LC rather than CC. However, considering the large imprecision and overall uncertainty, these analyses represent low-certainty evidence, and the estimate is, therefore, likely to change with further research. Serotonin is an important neurotransmitter in the gut, and animal models have shown SSRIs to increase the release of serotonin in the gut (Minami 2003), and that serotonin is involved in the inflammatory reaction of experimental colitis (Ghia 2009). Although common adverse effects of SSRIs include stomach complaints such as diarrhea, it remains uncertain whether SSRIs could trigger chronic inflammation manifesting in diarrhea. Hundreds of medications have been associated with chronic diarrhea, mainly in case reports and uncontrolled case series . In contThere was a non-statistically significant suggestion in two case-control studies that SSRI use would associate with a lower risk of psoriasis. All of the available outcome diseases are rare, and even in hypothetical causal cases, the absolute number of new diseases would be low. For example, using the incidence figures by Tzeng et al. 2021 to illustrate the scale of these risk magnitudes, and assuming the incidences were true, would yield a number needed to treat of 980 (95% CI 656–1936) to prevent the development of one psoriasis case with any antidepressant treatment . SSRIs hBP is the most common bullous autoimmune disease affecting the subepidermal layer of the skin and mainly affects elderly people. Our meta-analysis of three studies found a 1.8-fold increase in the odds of BP after exposure to antipsychotics, representing low certainty of evidence due to these studies’ relatively high risk of bias. Such a modest effect size could be explained by confounding and biases, and larger prospective studies would be needed before antipsychotics could be considered risk factors for BP. The case-control study by Varpuluoma et al. (2019) reported only statistically significant associations, therefore risking reporting bias . They reThe limitations of this study mostly reflect limitations in the available literature and especially how results have been reported. Although some individual studies reported the number of prescriptions, the literature was too heterogenous and scarce for a meta-analysis on dose dependence.Patients with immune diseases generally have higher than expected rates of psychiatric disorders, that are often treated with medications . In studAssessing drug exposure independently of outcome data using nationwide registers eliminates recall bias and diminishes the impact of selection bias. Other approaches would introduce more uncertainty. For example, Pascua et al. (2010) had only a modest inter-rater agreement (kappa statistic 0.50) when patient-reported medications were compared to those found in electronic databases .Currently, in the case of psychiatric medications, the entire literature of comparative studies represents, at best, low certainty of evidence linking them to any AD or IMID. We have reviewed important sources of bias in the field for future studies to be more reliable. Identified associations, particularly that of SSRIs and the risk of MC, should be investigated in prospective cohort studies.S1 File(RTF)Click here for additional data file.S2 File(RTF)Click here for additional data file.S3 File(RTF)Click here for additional data file.S4 File(RTF)Click here for additional data file.S5 File(RTF)Click here for additional data file.


The beneficial role of gut microbiota and bacterial metabolites, including short-chain fatty acids (SCFAs), is well recognized, although the available literature around their role in colorectal cancer (CRC) has been inconsistent.We performed a systematic review and meta-analysis to examine the associations of fecal SCFA concentrations to the incidence and risk of CRC. Data extraction through Medline, Embase, and Web of Science was carried out from database conception to June 29, 2022. Predefined inclusion/exclusion criteria led to the selection of 17 case-control and six cross-sectional studies for quality assessment and analyses. Studies were categorized for CRC risk or incidence, and RevMan 5.4 was used to perform the meta-analyses. Standardized mean differences (SMD) with 95% confidence intervals (CI) were calculated using a random-effects model. Studies lacking quantitation were included in qualitative analyses.P = 0.02). Additionally, CRC incidence was higher in individuals with lower levels of SCFAs , compared to healthy individuals. Qualitative analyses identified 70.4% of studies reporting significantly lower concentrations of fecal acetic, propionic, butyric acid, or total SCFAs in those at higher risk of CRC, while 66.7% reported significantly lower concentrations of fecal acetic and butyric acid in CRC patients compared to healthy controls.Combined analysis of acetic, propionic, and butyric acid revealed significantly lower concentrations of these SCFAs in individuals with a high-risk of CRC (SMD = 2.02, 95% CI 0.31 to 3.74, Overall, lower fecal concentrations of the three major SCFAs are associated with higher risk of CRC and incidence of CRC.The online version contains supplementary material available at 10.1186/s12916-022-02529-4. According to the Global Cancer Incidence, Mortality and Prevalence (GLOBOCAN) 2020 report, colorectal cancer (CRC) is the third most commonly diagnosed cancer  and the second 9.4%) leading cause of cancer-related death , 4. It i% leadingThe effect of diet on colonic health is partly mediated through alteration of gut microbiota composition, diversity, and metabolism , 12. GutShort-chain fatty acids are small molecules generated via the fermentation of dietary fibers by gut microbiota. Acetic, propionic, and butyric acid constitutes the majority of colonic SCFA content , 15 and Several studies have assessed fecal SCFA concentration in patients with colorectal carcinoma or adenoma –34. HoweTherefore, systematic analyses designed to better understand the link between SCFA concentration in CRC risk and incidence is highly desired. We divided our analyses on the available evidence into two broad categories: (1) CRC-risk and (2) incidence. We aimed to systematically analyze the results of all primary observational human studies, which measured fecal SCFA levels in “at-risk” individuals or in CRC patients. In the CRC risk category, the focus was on at-risk individuals, which was further sub-divided into two groups based on (1a) studies that analyzed clinical data  or (1b) those that assigned CRC risk based on non-clinical evaluation of study participants (ethnic background or location). The CRC incidence category included studies that compared fecal SCFA levels in individuals with clinically diagnosed CRC and healthy individuals. Our results underline the potential association of the three major SCFA molecules  with CRC risk and incidence.We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guideline , 42 to sThe Medline, Embase, and Web of Science database search was performed for articles involving human subjects that are in English from database conception until June 29, 2022. The details of the search keywords and strategies utilized in Ovid and Web of Science are available in the Additional file n = 57) records were then screened to include only the observational studies which have measured fecal SCFA concentration. A final set of 23 observational studies qualified for further data extraction, quality assessment, and statistical analyses.All the records, including abstracts, were imported to EndNote X9 . Duplicate records were first removed. The records were then filtered using EndNote’s built-in search tool for the following criteria: (i) searching for concentration*, level*, quanti*, measure*, assess*, evaluat*, estimat*, calculat*, mmol, and μmol as the inclusion criteria to capture studies which reported the SCFA measurement based on these terms, and (ii) searching for mouse, mice, murine, rats, conference, ethyl acetate (EtOAc), and phorbol as the exclusion criteria to exclude rodent studies, conference proceedings, and studies that have stated the use of any unrelated chemicals (such as EtOAc and 12-O-Tetradecanoylphorbol-13-acetate) - the asterisk symbol (*) applied was to include all the variations of the search terms. The abstracts of the remaining records were then screened to exclude reviews, methodology, human studies not related to SCFAs in CRC or CRA, and non-human studies , to identify the human studies on SCFA measurement in CRC or CRA. The full text of the remaining  from the finalized primary studies were extracted and added to an Excel worksheet. The Newcastle-Ottawa Scale (NOS)  was usedχ2 and I2 tests and a P-value of 0.05 was considered significant  or inulin supplementation on the risk of colorectal neoplasia, did not find significant increase in fecal total SCFA or butyric acid concentration and excretion before and after the intervention . Many stAnother systematic review on the food-microorganism-SCFA axis, without any meta-analysis, concluded that most evidence demonstrated higher SCFA levels in individuals at risk of CRC compared to healthy individuals , which cBoth the quantitative and qualitative analyses of CRC risk identified comparable findings of significantly lower concentration of acetic and butyric acid in the high- versus low-risk CRC group. For the CRC incidence category, the quantitative meta-analysis of butyric acid was consistent with observations identified in most of the articles from the qualitative analysis, supporting the evidence of lower concentration of three SCFAs in CRC cases compared to healthy controls. The meta-analysis of propionic acid was not significantly different between cases and controls. Similarly, most of the studies (5 of 7) reported no significant difference in fecal propionic acid concentration between CRC and healthy control in the qualitative analysis. The meta-analysis on IBS revealed a significantly higher concentration of fecal propionic acid in these patients in comparison to healthy controls . TherefoTo our knowledge, this systematic review is the first to provide a comprehensive search and data collection on observational studies linking SCFA molecules with the CRC risk and incidence. A limitation of our analysis is the heterogeneity of the studies evaluated in this systematic review, which is very difficult to control for. One such factor was the age group assessed for CRC incidence and risk. The mean age of the group in the studies was greater than 50 years and fecal SCFA concentration was not measured in younger populations to provide a comparison with low-risk, young age individuals. Although CRC is most often diagnosed in individuals > 50 years, the incidence for early-onset CRC (EOCRC) in adults aged 20–49 years has increased over the past decade in the USA, Australia, and Europe –65. It wOne common limitation is related to the nature of observational studies. Case-control studies are inherently prone to recall bias and appropriate matching of case and control groups . SimilarAnother limitation is the diversity in sample handling/storage workflows and the methodologies used to measure fecal SCFA across the studies Table . We did In addition to the SCFAs assessed in this systematic review, other metabolites such as bile acids were also measured in six of the selected studies , 36, 39.This study supports further exploration into fecal concentration of SCFAs: acetic, propionic, and butyric acids, as biomarkers for CRC risk. Among the current CRC screening methods, colonoscopy is the gold standard ; howeverGut microbiota dysbiosis and changes in their metabolites have been the focus of epidemiological studies aimed at uncovering associations with colonic inflammation and carcinogenesis. In line with the protective role of fecal SCFAs against the development of gut diseases , 16, andThe study is registered in PROSPERO database (registration code: CRD42021256123).Additional file 1.


Evidence from observational studies suggests that Sjögren’s syndrome (SS) may contribute to an elevated risk of Parkinson’s disease (PD) and dementia. However, few studies have been undertaken to summarize and assess the consistency of the data quantitatively. Therefore, we evaluated the risk of dementia and PD in SS patients through a systematic review and meta-analysis approach.Two reviewers independently conducted a systematic search of PubMed, Embase, and Web of Science databases  to identify published literature on the association between SS and dementia or PD. The risk estimates of dementia or PD in patients with SS were pooled using fixed or random-effects models.P < 0.001), and such risk in females with SS was similar to that in males. The risk of PD was 1.36 times higher in SS . The association between SS and PD risk appeared to occur primarily in female patients . No significant effect of age was observed on the risk of developing PD and dementia in SS patients.Of the 631 studies initially searched, 10 were eventually included. Pooled results suggested that the risk of developing dementia significantly increased in patients with SS (HR = 1.24, 95% CI: 1.15–1.33, Our study supports that people with SS are at higher risk of PD and dementia than the general population. Further studies are needed to elucidate the underlying mechanisms and to assess whether interventions for SS have the potential to affect dementia and PD development. Sjögren’s syndrome (SS) is an autoimmune disorder that plagues 35 million people worldwide. Its main clinical manifestations include dry eyes and dry mouth as well as lymphocytic infiltration of glandular tissues . SS is cSince the beginning of the twenty first century, population aging has become a prominent issue, challenging all countries in the world . China nAn association between neuropsychiatric symptoms and autoimmune diseases has been increasingly noted. Several observational studies have explored the association between SS and dementia/PD. Therefore, the present study aimed to quantify the association between SS and dementia/PD. To achieve this end, data were collected to (1) investigate the comprehensive results of the association between SS and dementia, and that between SS and PD; (2) validate the main results by analyzing the results in different subgroups and determining the sources of heterogeneity; (3) test the robustness of the results through sensitivity analysis and assess the potential for publication bias.The study was reported according to the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (PRISMA-p) statement . We systStudies were eligible for inclusion if they were longitudinal case-control studies or cohort studies, entailed a clear definition of SS, dementia, and PD, or applied standard clinical diagnostic criteria to identify relevant cases. Included studies also should meet the following criteria: assessing the association between SS and dementia as well as SS and PD, or reporting effect estimates and corresponding 95% confidence intervals (CIs). The studies should also include relevant data to calculate hazard ratios (HRs) for the associations between SS and dementia/PD. We excluded reviews, conference abstracts, commentaries, reprinted literature, and studies with duplicated or incomplete data. To avoid omitting any studies, we manually searched the literature cited in the reference lists of included studies.The final screening results were compared by two authors (WZZ and SZ) based on the same inclusion and exclusion criteria, and any disagreements were resolved by third-party authors. An MS Excel form was created to record essential data from the included studies, including first author, year of publication, study type, country, sample size, the mean age of samples, exposure definition, factors adjusted for the outcome, eligible subgroups, and follow-up periods. All authors approved the final version of the template. Two independent reviewers (WZZ and SZ) extracted data using the pre-determined form, and any discrepancies were addressed through discussion. The corresponding authors of the included literature were also contacted for further information when necessary.Two independent reviewers (WZZ and SZ) scored the quality of the included case-control and cohort studies, following the Newcastle-Ottawa Quality Assessment Scale. Studies were rated as high-quality if scored between 7 and 9, medium-quality (5∼6), and low-quality (≤4) .I2 < 50% and p > 0.05, and a fixed-effects model was used for analysis. A random-effects model was applied when I2 ≥ 50% or p ≤ 0.05. HR, an effective indicator for meta-analysis, was used to calculate pooled effect values, and forest plots were drawn. Further subgroup analyses were conducted based on the available data from the included studies. Sensitivity analysis was performed to evaluate the stability of the results. Publication bias was assessed using Begg’s and Egger’s tests and graphing funnel plots. All statistical analyses were done using Stata 16.0 software.The HRs were pooled to examine the relationship between SS and PD/dementia risk . HeterogThe screening process is summarized in the flow chart . We idenAll included studies were published between 2017 and 2021. Of the 10 included studies, three were case-control studies  and seveThe Newcastle-Ottawa Quality Assessment Scale scores for the included studies are shown in I2 = 2.0%, p (heterogeneity) = 0.395]. Therefore, a fixed-effects model was used to pool the effect size of each study to determine the association between SS and the risk of dementia (p < 0.001).We performed meta-analyses and calculated pooled effect estimates for five studies that included 190 704 subjects . Heterogdementia . The oveOur subgroup analyses were conducted by age (<65 and >65) and sex . Corresponding subgroup analyses of follow-up time and comorbidities on risk were not performed due to the lack of data on the effect .p = 0.004), and this risk was similar in patients with SS under 65 years of age . Two studies were included in the subgroup analysis by sex .In terms of stratified analysis for age, people with SS had a 26% higher relative risk of dementia than those without SS among those over 65  . FurtherI2 = 74.5%, p (heterogeneity) = 0.003), so a random-effects model was adopted. Pooled results showed that SS was significantly associated with a subsequent increased risk of PD   .We conducted a meta-analysis of subgroups according to age, sex, and duration of follow-up . In the p = 0.000) in female SS patients and 1.00  in male SS patients. These results revealed that the correlation between SS and PD risk seemed to be applicable primarily to female patients.In the subgroup analysis by sex, two cohort studies  examinedOnly Begg’s and Egger’s tests as well as funnel plots were used to assess potential publication bias. No potential publication bias was present (Begg = 0.806 and Egger = 0.242) . The robTo our knowledge, this meta-analysis is the first to comprehensively investigate and quantify the association between SS and the risk of dementia/PD. We found a 1.24-fold greater risk of dementia in people with SS compared to the general population; age and gender appear to have no significant effect on this risk. The risk of PD in SS patients was 1.36 times higher in SS individuals. This elevated risk, interestingly, appeared to be prevalent solely in female individuals. Age had no significant effect on the risk of developing PD in SS patients. Based on the fact that over 10,000 patients with both SS and dementia or both SS and PD were involved, the study provided convincing information for the association between SS and PD.In recent years, the prevalence of dementia has been rising at an alarming rate in our aging population . DementiThe influence of neuroinflammation on dementia remains a controversial topic. The interaction between SS and dementia is becoming more obvious, yet the factors that contribute to progression are unclear. Vasculitis, autoantibodies, immune complex deposition, and cellular inflammation are potential pathways through which SS may elevate the risk of dementia, resulting in nerve damage, cognitive impairment, and initial dementia . PreviouNoteworthily, PD is the second most common neurodegenerative disease after Alzheimer’s disease, and it is expected to place an increasing medical and economic burden on society as the population ages . TypicalIt is crucial to determine the causal relationship between SS and PD. In several of the included studies, all patients with PD were diagnosed after an episode of SS . In the SS is known to be mediated by the interaction of genetic, epigenetic, and environmental factors causing immune dysregulation, which leads to an aggressive autoimmune disease affecting the central nervous system (CNS) and peripheral nervous system , often eThere are still some limitations to our meta-analysis. First, we could not distinguish whether SS was primary or secondary to another autoimmune disease in our meta-analysis. Failure to fully elucidate the clinical severity of SS and the subtypes of dementia and PD may lead to inaccurate estimates of their genuine association. Secondly, most of the eligible studies were conducted in Taiwan region (China), which may lead to geographical bias and relatively high overlap of included samples. Therefore, it is unclear whether this association holds for other races and regions in the world. In addition, none of the 10 included studies assessed the effect of monitoring bias on outcomes. Since subjects with SS typically experienced more medical visits than those without SS, they were more likely to be diagnosed with dementia or PD. In this way, the risk of dementia or PD for subjects with SS may be skewed higher in the overall analysis results. Finally, all original studies were designed retrospectively and their data collection did not consider the need for specific scientific research, thus limiting the completeness and homogeneity of the data.The results of this study reveal that patients with SS are at significantly elevated risk of developing PD and dementia and that regular neurological screening of SS patients may be warranted. More prospective studies from different regions are necessary to elucidate the underlying mechanisms and to further characterize the impact of SS on development of PD and dementia.The original contributions presented in this study are included in the article/Z-ZW, M-SL, and ZS developed the protocol, participated in the literature search, extracted data, and drafted the manuscript. X-LZ and M-LZ was responsible for the analysis and interpretation of the data. KX contributed to statistical expertise. FZ supervised the study. All authors contributed to the article and approved the submitted version.


Background: Recently, increasing evidence has implicated methylenetetrahydrofolate reductase (MTHFR) gene mutation as a risk factor for ischemic stroke (IS) in the general population. However, studies have been inconclusive and lack evidence on specific populations. We aim to determine whether the rs1801133 (NC_000001.11 (MTHFR):g. 677C>T  variant, we termed as MTHFR rs1801133 (677 C>T), is linked to an increased risk of IS in different age groups and ancestry groups.Methods: The literature relevant to our study was found by searching the PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI databases. A random effect model analysis was used to calculate the pooled odds ratio (OR) and 95% confidence interval (CI) to evaluate any possible association. We conducted a subgroup analysis based on the age and ancestry groups of the included populations.Results: As of March 2022, 1,925 citations had been identified in electronic databases, of which 96 studies involving 34,814 subjects met our eligibility criteria. A strong link was found between IS and the MTHFR gene rs1801133 (677C>T) polymorphism in all genetic models . Further subgroup analyses indicated that the MTHFR rs1801133 (677C>T) variant may increase the risk of IS in Asian, Hispanic, or Latin population, middle-aged, and elderly populations (p < 0.001).Conclusion: Our results implied that mutation of the T allele of MTHFR rs1801133 (677C>T) could be a risk factor for IS. A significant association was found among Asian, Hispanic, or Latin population, middle-aged, and elderly people. Ischemic stroke (IS) is an acute neurological deficit caused by vascular occlusion. It is one of the leading causes of death and disability worldwide  and is cThe previous study had demonstrated that approximately 40% of the intragenic coding CpG islands were hyper-methylated, which had a higher C>T mutation rate. Also, the amino acid sequence of a protein and individual phenotypes could be changed by C>T substitutions at the CpG contexts in the protein-coding regions . The rs1Many researchers have examined the relationship between MTHFR rs1801133 (677C>T) polymorphism and IS risk. However, there have been no definitive conclusions because different populations were examined and inconsistent results were obtained . Two metThe study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines .A systematic search of the PubMed, EMBASE, Cochrane Library, Web of Science, and CNKI databases for relevant observational studies published until 15 March, 2022, was undertaken independently by two reviewers (Zhao and Li). We used the following search terms to identify eligible studies: (“methylenetetrahydrofolate reductase” OR “MTHFR” OR “C677T” OR “rs1801133”), , AND (“single nucleotide polymorphism” OR “SNP” OR “genetic polymorphism” OR “mutation” OR “variation”). We reviewed the full text of each study when abstracts and titles were insufficient to make a final determination regarding study inclusion. The reference lists of included studies and existing reviews were screened to identify additional eligible studies. Any disagreements in the study selection process were resolved by a third person (Dang).p-value of the Hardy–Weinberg equilibrium (HWE) test was <0.05.We included the studies according to the following inclusion criteria: 1) the full text could be searched in electronic databases; 2) the studies were case-control or cohort studies examining MTHFR rs1801133 (677C>T) and stroke susceptibility; 3) the study population was limited to patients diagnosed with stroke for the first time; 4) the MTHFR rs1801133 (677C>T) genotype frequency was provided; and 5) articles were published in English or Chinese. The main exclusion criteria included the following: 1) the studies were duplicate articles or non-original research ; 2) the studies were case reports or involved animal experiments; 3) the genotype frequency of MTHFR rs1801133 (677C>T) was not provided; and 4) the p-value was also calculated using the genotypic frequencies of MTHFR polymorphisms, and the threshold of HWE deviation was set at 0.05. The quality of eligible publications was assessed using the Newcastle–Ottawa scale , study design, mean or median age of the population, HWE, and the Newcastle–Ottawa scale score. Disagreements regarding data extraction were resolved by discussions among the two investigators (Zhao and Li), and a third reviewer (Dang) was consulted if necessary. The HWE wa scale , and stuvs. C), dominant model (TT + TC vs. CC), recessive model (TT vs. CC + TC), heterozygous model (TC vs. CC), and homozygous model (TT vs. CC), to estimate the relationship between MTHFR rs1801133 (677C>T) polymorphism and stroke susceptibility by calculating the odds ratio (OR) and 95% confidence interval (CI). The I2 statistic was used to evaluate heterogeneity among genetic comparison models, and the pooled OR was estimated via the Mantel-Haenszel random effect model. Heterogeneity between studies is indicated by an I2 > 50%. Moreover, the Bonferroni method was utilized to adjust for multiple comparisons to control the false positive error rate. As we performed multiple comparisons in this meta-analysis for 45 times, the p-value which was less than 0.05/50 (0.001) indicated statistical significance after Bonferroni correction. To determine the possible causes of heterogeneity, the ancestry groups , and other and not reported ancestries (ONR)) and the study population  were analyzed in subgroups. In addition, we examined the impact of a single study on the pooled OR by performing sensitivity analyses on different genetic comparison models. Egger’s test, Begg’s test, and funnel plots were used to evaluate the potential publication bias in our study  in the 96 studies included in the meta-analysis.2 = 69.9%; p < 0.001) (p < 0.001). In the ancestry subgroup analysis, the rs1801133 (677C>T) polymorphism of MTHFR was evidently linked to an increased risk of IS in Asian  and Hispanic or Latin population . MTHFR rs1801133 (677C>T) gene polymorphism was associated with IS susceptibility in all age groups except young populations .The TT + CT genotype showed significant heterogeneity compared with the CC genotype in the dominant genetic model (I< 0.001) . The MTH2 = 55.7%; p < 0.001) (p < 0.001). The ancestry subgroup analysis showed a significant difference in the Asian populations, with combined ORs of 1.58 . The middle-aged and elderly people had an increased risk of stroke according to the subgroup analysis The TT genotype showed significant heterogeneity compared with the CC + CT genotype in the recessive genetic model (I< 0.001) . MTHFR r2 = 60.4%; p < 0.001) (p < 0.001). In the subgroup analysis, MTHFR rs1801133 (677C>T) gene polymorphism was associated with stroke susceptibility in Asian , Hispanic or Latin populations , middle-aged , and elderly groups .The TC genotype showed significant heterogeneity compared with the CC genotype in the heterozygous genetic model (I< 0.001) . There w2 = 64.2%; p < 0.001) (p < 0.001). However, the stratification analysis results were similar to those of the recessive model. Significant correlation was detected between MTHFR rs1801133 (677C>T) polymorphisms and the increased risk of stroke in the Asian population . Furthermore, the middle-aged and elderly people had an increased risk of stroke in the subgroup analysis .The TT genotype showed significant heterogeneity compared with the CC genotype in the homozygous genetic model (I< 0.001) . There w2 = 75.7%; p < 0.001) (p < 0.001). In the subgroup analysis, MTHFR rs1801133 (677C>T) gene polymorphism was associated with stroke susceptibility in Asian populations . The middle-aged and elderly people with T allele mutation had a higher risk of stroke .The T allele showed significant heterogeneity compared with the C allele in the allelic genetic model (I< 0.001) . There wA sensitivity analysis was conducted to compare the pooled ORs after individually excluding each included study. There was no significant change in the results .p = 0.04) and heterozygous models (p = 0.03) (The funnel plot is shown in  = 0.03) . Nonethe = 0.03) , type I This meta-analysis demonstrates associations between MTHFR rs1801133 (677C>T) genetic polymorphism and susceptibility to IS under all genetic models. Our results were consistent with a previous meta-analysis performed in 2016, wherein this polymorphism was found to be potentially involved in the development of IS . This suSeveral factors might explain the association of the MTHFR rs1801133 (677C>T) mutation and increased IS risk. Most importantly, the MTHFR rs1801133 (677C>T) mutation leads to decreased MTHFR activity and elevated homocysteine levels . HyperhoWe also conducted a subgroup analysis on the basis of age and ancestry of the study population to further understand the significance of the MTHFR rs1801133 (677C>T) mutation in various populations. The result of subgroup analysis showed increased IS risk in populations with the MTHFR rs1801133 (677C>T) mutation in middle-aged and elderly groups. It was consistent with the fact that older people were more susceptible to atherosclerosis, which was an important cause of IS. Previous studies had demonstrated that the MTHFR rs1801133 (677C>T) mutation increased the risk of IS in patients with large-artery atherosclerosis  and adulAnother important finding of this meta-analysis was the stable association between IS risk and MTHFR rs1801133 (677C>T) polymorphism in Asian populations in all genetic models and Hispanic or Latin American population in dominant and heterozygous models. Similar trends were also found among other populations, although no statistically significant difference was found in some genetic models. This may be related to the following reasons: 1) the frequency of the MTHFR 677T gene variant differs among ethnic groups due to different genetic backgrounds. Previous studies indicated that the frequency of the MTHFR rs1801133 T allele was 24–40% in Europeans, 40% in Koreans, and 26–37% in Japanese ; 2) MTHFThis study has several strengths. First, we included the most recent and relevant studies in this meta-analysis. In addition, we further analyzed the association between MTHFR rs1801133 (677C>T) polymorphism and IS risk in different populations. Finally, this meta-analysis included high-quality observational studies using real-world data with a large number of patients.However, this meta-analysis also has some limitations. First, the study was based on the secondary study-level data. Age groups were defined according to the mean or median age of study subjects, and some studies did not provide clear information on age. Thus, the age stratification of subgroups might not be accurate. Second, the findings of this meta-analysis were mainly based on case-control studies and lacked prospective research; therefore, they should be interpreted with caution.Our findings showed that the MTHFR rs1801133 (677C>T) variant may contribute to an increased risk of IS. This association was statistically significant in the Asian and Hispanic or Latin American cohorts and showed a similar trend in the populations of other ancestries. For middle-aged and elderly people, MTHFR rs1801133 (677C>T) might be a promising biomarker for early detection and prediction of the prognosis of IS. However, high-quality, prospective studies are needed in the future.


I2. Sources of heterogeneity were examined by meta‐regression and risk of bias was assessed with the Clark Baudouin scale. This systematic review comprised of 43 studies including a total of 3938 athletes and 10 752 controls in the pooled analysis. Of the 42 identified genetic variants, 13 were investigated in independent studies. Significant associations were found for five polymorphisms. Pooled odds ratio [95%CI] favoring athletes compared with controls was 1.42 [1.12–1.81] for ACE II (I/D), 1.66 [1.26–2.19] for ACTN3 TT (rs1815739), 1.75 [1.34–2.29] for PPARGC1A GG (rs8192678), 2.23 [1.42–3.51] for AMPD1 CC (rs17602729), and 2.85 [1.27–6.39] for HFE GG + CG (rs1799945). Risk of bias was low in 25 (58%) and unclear in 18 (42%) articles. Heterogeneity of the results was low (0%–20%) except for HFE (71%), GNB3 (80%), and NOS3 (76%). (Inter)national competing runners and cyclists have a higher probability to carry specific genetic variants compared with controls. This study confirms that (inter)national competing endurance athletes constitute a unique genetic make‐up, which likely contributes to their performance level.The aim of this systematic review and meta‐analysis was to identify the genetic variants of (inter)national competing long‐distance runners and road cyclists compared with controls. The Medline and Embase databases were searched until 15 November 2021. Eligible articles included genetic epidemiological studies published in English. A homogenous group of endurance athletes competing at (inter)national level and sedentary controls were included. Pooled odds ratios based on the genotype frequency with corresponding 95% confidence intervals (95%CI) were calculated using random effects models. Heterogeneity was addressed by Q‐statistics, and  By combining the results of multiple scientific studies in the form of a meta‐analysis, the problem of small sample sizes can be partially overcome and at the same time provides a more valid pooled estimate.22.1This meta‐analysis was conducted according to the 2020 PRISMA guidelines2.2Medline and Embase databases were searched on July 1, 2020, and updated on November 15, 2021. All relevant studies and reviews related to the topic were checked for cross references. The search strategy for both databases consisted of three online searches. The search terms and the full search strategies are summarized in ESM 2, 3, and 4. No filters were applied during the search. Identified studies from databases were extracted to Endnote  and automatically screened for duplicates. Title and abstract of the retrieved reports were initially read by one reviewer (MK). Two independent reviewers (MK and JB) then screened the full texts for eligibility. Disagreement between MK and JB was solved by discussion. Data collection was performed independently by the two reviewers using Excel. The following items were extracted: first author's name, publication year, journal, country of origin, ethnicity and sex of participants, number and performance level of athletes (runners and cyclists), number of controls, rs‐number, and genotype frequencies. The authors were contacted in case the full text was not available or relevant information for data extraction was missing or unclear.2.3The risk of bias within each study was assessed independently by the two reviewers using the Clark Baudouin scale, a 10‐point scoring system for the quality of genetic association studies.2.4Odds ratios between (inter)national competing runners and cyclists and controls were calculated for genotype status and genetic variant assuming a recessive inheritance model. A dominant inheritance model was assumed when zero counts were reported for the effect allele. Eligible for the synthesis of results were at least two independent studies analyzing identical variants. All statistical analyses were performed with R (version 4.0.3). Pooling of effect sizes (odds ratio) was performed based on raw genotype data using the meta package/metabin function. The random effects model for pooling of effect size was applied because between‐study heterogeneity was expected.2.52 (DerSimonian and Laird).I2 represented inconsistency and was categorized as low (<25%), moderate (25%–75%), or high (>75%). Heterogeneity, outliers, and influential cases were inspected with Baujat and Gosh plotsp < 0.05.Heterogeneity was analyzed by Q‐statistics based on the Mantel–Haenszel estimator and tau2.6Certainty of the evidence was assessed using the GRADE framework categorizing the evidence as high, moderate, low, or very low.33.1n = 24), other definitions of the sport disciplines (n = 152) or control group (n = 26), unclear genotype frequency (n = 10), case studies (n = 4),n = 1), duplicate study populations (n = 3),n = 1),n = 1),n = 1).The literature search identified 4627 records. Of the initial dataset, 1014 duplicates were removed as well as 120 non‐English studies. Consequently, 3493 articles were screened based on title and abstract thereby excluding another 3224 records. Next, 269 articles were read for detailed evaluation of which three articles were not retrievable even after contacting the author(s).3.2ESM 7 displays the key characteristics of all included studies. ESM 8 presents the observed genotype and allele frequencies as well as the estimated population frequencies. Of the 43 articles, 25 (58%) were rated as low and 18 (42%) were rated as unclear risk of bias. Detailed information about the risk of bias assessment is summarized in ESM 9. Overall, we identified 42 genetic variants. Of those, 29 variants were investigated by single studies included in this meta‐analysis (ESM 10). Therefore, these 29 polymorphisms could not statistically be pooled and 12 of the 29 variants showed a significant association with runners and cyclists competing at (inter)national level compared with controls.3.3ACE I/D (II vs. ID+DD), 1.66 [1.26–2.19] for alpha‐actinin 3 (ACTN3) rs1815739 (TT vs. CT + CC), 1.75 [1.34–2.29] for peroxisome proliferator‐activated receptor gamma coactivator 1‐alpha (PPARGC1A) polymorphism rs8192678 (GG vs. AG + AA), 2.23 [1.42–3.51] for adenosine monophosphate deaminase 1 (AMPD1) rs17602729 (CC vs. CT + TT), and 2.85 [1.27–6.39] for homeostatic iron regulator (HFE) rs1799945 (GG + CG vs. CC). The remaining eight variants did not show a significant result in the main analysis: myostatin , bradykinin receptor B2 , interleukin‐6 , adrenoceptor beta 2 , creatine kinase M‐type , G protein subunit beta 3 , and nitric oxide synthase 3 . Heterogeneity of the pooled results was low (0%–20%) except for HFE (71%), GNB3 (80%) and NOS3 (76%).Thirteen genetic variants were examined in at least two independent studies, yielding 3938 (inter)national runners and cyclists and 10 752 controls in total national competing runners and cyclists and 4637 controls.ACE‐specific study characteristics and the risk of bias assessment. The reports mainly involved Caucasian participants (n = 12). One study comprised AfricanThe following figures illustrate the forest plots of the significant genetic variants associated with (inter)national runners and cyclists compared with controls. Figure T2 = 0.04 and an I2 [95%CI] value of 20.0% [0.0%–57.2%]. Meta‐regression results for sex (p = 0.23), discipline (p = 0.79), ethnicity (p = 0.74), and performance level (p = 0.26) were not significant. Finally, reporting biases were not detected, funnel plot (ESM 13) asymmetry was not significant (p = 0.24), and certainty of evidence was rated as high national competing runners and cyclists showed a significantly higher prevalence of the II genotype (II vs. ID + DD) compared with controls (pooled odds ratio [95%CI]: 1.42 [1.12–1.81]). The II genotype frequency was 24.7% in athletes and 21.8% in controls. The between‐study heterogeneity variance was estimated with 3.3.2ACTN3 in which 557 (inter)national competing runners and cyclists as well as 1085 controls were analyzed . In total, nine studies were included in the meta‐analysis of ACTN3.Figure T2 = 0.03 and I2 at 19.1% [0.0%–60.8%]. Meta‐regression results regarding sex (p = 0.86), discipline (p = 0.77), ethnicity (p = 0.16), and performance level (p = 0.17) were not significant. Noteworthy, two publicationsN = 123) but different athletes. Excluding one or both studies did not change the present finding (p < 0.01). The control group of four reportsp < 0.01). ESM 16 displays the funnel plot for ACTN3, which did not indicate the presence of publication bias. Finally, certainty of evidence was rated as high (see Table (Inter)national competing runners and cyclists showed 1.66 times the odds of possessing the TT genotype (TT vs. CT + CC) compared with controls (pooled odds ratio [95%CI]: 1.66 [1.26–2.19]). The frequency of the TT genotype was 28.4% in the athlete and 19.5% in the control group. The between‐study heterogeneity variance was estimated with 3.3.3PPARGC1A. Five studies with in total 359 (inter)national competing Caucasian runners and cyclists and 1292 controls were investigated in the meta‐analysis for PPARGC1A . Lastly, publication bias was not detected (ESM 19) and certainty of evidence for PPARGC1A was rated high (Table The results showed that (inter)national competing runners and cyclists had 1.75 times the odds of carrying the GG genotype (GG vs. AG + AA) compared with controls (pooled odds ratio [95%CI]: 1.75 [1.34–2.29]). GG genotype frequency was 55.2% in the athlete and 40.1% in the control group. The between‐study heterogeneity variance was estimated at 3.3.4AMPD1HFEAMPD1 and HFE, respectively. All publications were rated with unclear risk of bias (ESM 21 and 23) and examined male Caucasian runners and cyclists together.Figure AMPD1, 271 (inter)national competing runners and cyclists and 368 controls were analyzed. Two studiesT2 = 0.00 and an I2 value of 0% [0.0%–89.6%]. Two articles involved the same control group but different athletes.p < 0.01). Furthermore, one control group deviated from Hardy–Weinberg equilibrium,p < 0.01).For T2 = 0.24 and an I2 value of 70.8% . Certainty of evidence for AMPD1 as well as for HFE was moderate  was significantly associated with (inter)national competing runners and cyclists when compared with controls. In sensitivity analysis 3, the Hartung–Knapp adjustment for random effects model was applied and HFE was no longer significant (p = 0.24). However, in addition to ACE, ACTN3, PPARGC1A, and AMPD1, two other genetic variants showed a significant association. For MSTN (rs1805086), (inter)national competing runners and cyclists showed a greater prevalence of carrying the G allele (GG + AG) than controls (pooled odds ratio [95%CI]: 1.40 [1.11–1.78]). For CKMM (rs8111989) runners and cyclists had 1.50 [1.03–2.20] times the odds of carrying the TT genotype (TT vs. TC + CC) compared with controls. Further, in sensitivity analysis 4, we excluded studies in which control groups deviated from Hardy–Weinberg equilibrium, however, sensitivity analysis 4 did not influence the results. Finally, sensitivity analysis 5 was not applied because no report in the pooled analysis encompassed high risk of bias.Most of the sensitivity analyses did not change our main findings (ESM 24). In sensitivity analysis 1, we applied a fixed effect model which did not change the results. In sensitivity analysis 2, in which a dominant inheritance model was assumed, only 4ACE II, ACTN3 TT (rs1815739), PPARGC1A GG (rs8192678), AMPD1 CC (rs17602729), and HFE GG + CG (rs1799945).The aim of this systematic review with meta‐analysis was to identify genetic variants contributing to (inter)national competing long‐distance runners and road cyclists. Based on our pooled analysis, the following five genetic variants were significantly associated with runners and cyclists competing at (inter)national level when compared with sedentary controls: 4.1ACE insertion/deletion variant, which plays a key role in the renin‐angiotensin system, has been a major focus of sport genetics.ACE enzyme than DD individuals.ACE I/D genotype distribution (II vs. ID+DD) between 2979 “endurance” athletes  and 10 048 controls (pooled odds ratio [95%CI]: 1.48 [0.30–2.67]).The 4.2ACTN3 (rs1815739) TT genotype results in α‐actinin‐3 deficiency which affects the muscle's ability to generate rapid contractions.ACTN3 among power athletes and concluded that the C allele was associated with elite power sports.ACE I/D nor the ACTN3 (rs1815739) genotypes and personal‐best running times.The 4.3PPARGC1A polymorphism (rs8192678) has been associated with multiple functions such as mitochondrial biogenesis, energy metabolism, oxidative phosphorylation, angiogenesis, and antioxidant defense.PPARGC1A mRNA levels (GG vs. AG + AA),PPARGC1A mRNA levels. In the present analysis, we found a clear association of the GG genotype (GG vs. AG + AA) with (inter)national competing runners and cyclists compared with controls (pooled odds ratio [95%CI]: 1.75 [1.34–2.29]). This is in accordance with the results of two recent meta‐analyses involving various “endurance” disciplines .The 4.4ACE only one polymorphism (AMPD1 (rs17602729)) to be associated with (inter)national performance level of runners and cyclists. By pooling three cohorts, we found that (inter)national competing runners and cyclists had a higher prevalence of the CC genotype (CC vs. CT + TT) compared with controls (pooled odds ratio [95%CI]: 2.23 [1.42–3.51]). The AMPD1 polymorphism plays an important role in energy metabolism and is a key enzyme necessary to produce adenosine triphosphate (ATP). ATP is the main molecule responsible to store and transfer energy in cells.A recent review highlighted 16 polymorphisms potentially associated with marathon running performance, however, most of the results have not been replicated.4.5HFE gene regulates iron absorption and individuals carrying one or two mutations (GG or CG) of the rs1799945 polymorphism show higher circulating iron concentrations than individuals without mutation.HFE) polymorphism and “endurance” athletes revealing a higher prevalence of the G allele (GG + CG vs. CC) in athletes compared with controls (pooled odds ratio [95%CI]: 1.96 [1.58–2.45]).The 4.6We would like to highlight several strengths of this systematic review and meta‐analysis. (i) This is the first comprehensive systematic review with meta‐analysis identifying genetic variants associated with (inter)national competing long‐distance runners and road cyclists. (ii) We only included leg‐dominated disciplines and excluded whole‐body sports such as triathlon, rowing, or cross‐country skiing. This distinction is important since differences in muscle mass, oxygen extraction,PPP3CA, PPP3CB, PPP3CC, PPP3R1, and PPP3R2) between 123 elite runners and 125 healthy controls has been excluded due to efficiency reasons.PPP3CA gene and rs3763679 in the PPP3CB gene) significantly associated with elite endurance athlete status in Han Chinese, but not in Caucasians. (ii) Most of the study subjects included in this review were male, and due to this sample sex imbalance, we were not able to analyze male and female athletes apart. In future, both sexes with adequate sample sizes for both should be investigated.AGT (rs699).ACE and BDKRB2 gene. Future studies should adopt reporting genes consistently using rs‐numbers and correct allele forms.We also would like to acknowledge some limitations. (i) Most publications in the field of sport genetics make use of a candidate gene approach in which replication of results is often lacking.4.7It seems that (inter)national competing runners and cyclists constitute a unique genetic make‐up, which likely contribute to the high level of performance. We advise future studies to analyze homogenous group of athletes as well as different types of control groups  and to keep the necessity of sex balance in mind. It is important to emphasize that the observed associations between the genetic variants and the endurance performance level do not necessarily equate causation.Magdalena Johanna Konopka, Jorn Carlos Maria Leonardus van den Bunder, Gerard Rietjens, Billy Sperlich, and Maurice Petrus Zeegers declare that they have no conflict of interest.Appendix S1Click here for additional data file.


P < 0.001), fasting plasma insulin , homeostasis model assessment of insulin resistance (HOMA-IR) , and glycosylated hemoglobin (HbA1c) . In terms of lipid profiles, higher dietary fiber intake was associated with significant reductions in the serum level of total cholesterol  and low-density lipoprotein cholesterol , but not triglycerides  and high-density lipoprotein cholesterol . Higher dietary fiber intake was also significantly associated with improved tumor necrosis factor-alpha serum levels , while no significant effect was observed for C-reactive protein . Finally, blood pressure was also significantly improved following higher dietary fiber intake . Subgroup analysis revealed that the study population and type of dietary fiber could be partial sources of heterogeneity. In conclusion, the present umbrella meta-analysis provides evidence for the role of dietary fiber supplementation in the improvement of established cardiovascular risk factors.Although several meta-analyses have revealed the beneficial effects of dietary fiber intake on human health, some have reported inconsistent findings. The purpose of this work was to perform an umbrella meta-analysis to evaluate the relevant evidence and elucidate the effect of dietary fiber intake on glycemic control, lipid profiles, systematic inflammation, and blood pressure. Eligible studies were searched in several electronic databases, including Web of Science, PubMed, Scopus, and the Cochrane Library, up to March 2022. A total of 52 meta-analyses involving 47,197 subjects were identified to assess the pooled effect size. Overall, higher dietary fiber intake was significantly associated with reductions in parameters involving glycemic control, including fasting plasma glucose (ES = −0.55, 95% CI: −0.73, −0.38,  Cardiovascular diseases (CVDs), which represent a group of disorders of the heart and blood vessels, including coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other conditions, are the leading cause of death globally . It was Despite the existence of non-variable risk factors for CVDs, such as age, gender, and family history, shifts in some variable risk factors, including sedentary lifestyle, unhealthy diet, and physical inactivity, are much more important; among these, a healthy diet may be the most effective method with the lowest cost and could be regarded as a primary target for CVDs prevention . DietaryUmbrella meta-analysis is a synthesis method developed to evaluate the pooled effects of existing published meta-analyses and the quality and strength of the presented evidence. For example, Veronese et al. reported an umbrella meta-analysis of observational studies on the summarized associations of dietary fiber intake and various health outcomes . HoweverUmbrella reviews can provide a broad understanding of a given topic for decision makers . The curTwo authors (LF and SQ) independently searched the four databases  from inception to March 2022 for meta-analyses that explored the effects of dietary fiber intake on cardiovascular risk markers  using the following search strategy:  AND  AND . We also performed a manual review of the references from eligible meta-analyses so that any relevant studies were not missed  meta-analysis of RCTs that explored the effects of dietary fiber intake on cardiovascular risk factors  and reported the effect sizes (ESs) and corresponding confidence intervals (CIs) and (2) RCTs comparing any proper control groups .in vitro or ex vivo studies; (2) were only a systematic review without a meta-analysis; and (3) were a meta-analysis of observation studies on self-reported dietary fiber intake.We excluded studies that (1) involved animal research; (2) were Two independent authors (QZ and GZ) screened the potential studies on the basis of the inclusion and exclusion criteria. Any disagreement was resolved either by consultation together or a third author (MT). For each eligible study, information regarding first author's name; published year (country); sample size (the number of involved subjects); the type, dosage, and duration of interventions; and outcomes assessed were extracted. In addition, the pooled ESs and corresponding CIs for the influence of dietary fiber intake on cardiovascular risk factors were also extracted.The AMSTAR 2 questionnaire was employed to evaluate the quality of each eligible meta-analysis and served as a reliable and valid tool for assessing the quality of systematic reviews and meta-analyses; it consisted of 16 items scored as High, Moderate, Low, or Critical low of overall confidence . When a I2 statistic and Cochrane's Q-test. We considered an I2 value > 50% or a P-value from the Q-test of <0.1 as indicators of substantial heterogeneity, in which case the random-effect model was applied; otherwise, a fixed effect model was used ; (2) systematic reviews without meta-analysis (n = 4); (3) results confounded by non-dietary fiber (n = 9); and (4) outcomes were not interested (n = 3)  abstracts or letters to editors ( (n = 3) . The stuThe characteristics of the included meta-analyses are depicted in Most of the meta-analyses employed the Cochrane Risk of Bias tool to assess the quality of individual meta-analyses ; in addiThe results of the AMSTAR 2 scale indicated that the present umbrella meta-analysis included 30 meta-analyses with moderate overall confidence, nine meta-analyses with high overall confidence, and eight and five with low and critically low overall confidence, respectively . In summP < 0.001; I2 = 97.08, P < 0.001). A subgroup analysis by the type of intervention presented a moderate decrease in heterogeneity. On the other hand, the asymmetric distribution of the funnel plot showed the presence of publication bias (Egger's regression test P = 0.01). However, the “trim and fill” analysis with three imputed studies suggested that the effects of dietary fiber on FPG were still significant , the “trim and fill” analysis with five imputed studies suggested that FPI remained unchanged with dietary fiber intake . The heterogeneity decreased when focusing on subgroup analyses by the type of intervention, sample size, and dosage. Similarly, the visual inspection of the funnel plot showed an asymmetric distribution (Egger's regression test P = 0.036), while the further “trim and fill” analysis with five imputed studies showed that the conclusion observed for HOMA-IR was reliable . A subgroup analysis by the type of intervention showed a mild decrease in between-study heterogeneity. The exploration of publication bias using funnel plots and egger's regression test showed evidence of the small-study effect in the present umbrella meta-analysis (P < 0.001). However, the results from the “trim and fill” analysis with five imputed studies showed that the overall effects were not significantly confounded by the bias , and the type of intervention was recognized as a potential source of this heterogeneity. Significant small-study effects were observed when conducting Egger's regression test (P < 0.001). Consequently, the “trim and fill” analysis was performed with five imputed studies, and the results showed that the corrected ES was still significant . Factors such as the type of effect size, type of intervention, and dosage may have been possible sources of heterogeneity. The results of Egger's regression test showed the presence of publication bias (P = 0.003). Therefore, a “trim and fill” analysis was conducted with six imputed studies, and the results remained non-significant even after the amendment of the small-study effect  or small-study effect , which was reduced with a subgroup analysis by the type of intervention. Notably, a significant small-study effect was observed when performing Egger's regression test (P < 0.001). The results of the “trim and fill” analysis with five imputed studies showed a robust effect after considering the publication bias , and there was a moderate small-study effect (Egger's regression test P = 0.056). However, further “trim and fill” analysis with one imputed study indicated that the corrected ES for the effect of dietary fiber on TNF-α remained the same  or publication bias . Overall, the present umbrella meta-analysis showed that compared to the control group, dietary fiber intake did not lead to a significant decrease in serum CRP concentration . However, the visual inspection of the funnel plot indicated an asymmetric distribution (Egger's regression test P = 0.040). Therefore, we conducted a “trim and fill” analysis with two imputed studies, and the corrected result showed that the beneficial effect of dietary fiber on SBP was stable . The results revealed a significant reduction in SBP after dietary fiber intake . In addition, no evidence of publication bias was found .We also conducted subgroup analyses on studies that used dietary fiber for the four glycemic parameters stratified based on seven specific factors, including country, study population, type of effect size, type of intervention, sample size, dosage, and duration. It seemed that the beneficial effects of dietary fiber on glycemic control were more pronounced in patients with diabetes than in the rest of the population . In addiSimilar to the subgroup analysis above, we also performed a subgroup analysis of the effect of dietary fiber on lipid profiles. Firstly, we noted that the effect of dietary fiber intake on serum TC became non-significant in patients with diabetes, which was contradictory to patients with dyslipidemia . Next, aSince the number of meta-analyses reporting the effect of dietary fiber intake on systematic inflammation and blood pressure is scarce, we did not think it was necessary to perform further subgroup analyses.Despite the critical role of dietary fiber intake in the management of CVDs, a consistent conclusion between studies has yet to be reached. Our purpose in this work was to provide a systematic overview of the current evidence and evaluate the methodological quality of this evidence, which could be expected to be used as dietary advice in patients at risk for CVDs. The present umbrella meta-analysis, which consisted of 52 meta-analyses involving 47,197 participants, demonstrated that compared to the control group, dietary fiber intake conferred a favorable effect on glucose metabolism, improving lipid profiles (TC and LDL-C), ameliorating inflammation factors (TNF-α), and controlling blood pressure, indicating a strong protection effect against cardiovascular-related diseases.Historical evidence has indicated a negative relationship between dietary fiber intake and the risk of diabetes mellitus . In the via different kinds of mechanisms. Firstly, the dietary fiber-induced high-viscosity microenvironment within the small intestine could prevent the absorption of dietary cholesterol as well as promote the excretion of bile acids (synthesized by endogenous cholesterol) from stool  can act as inhibitors of HMG-Co AR, leading to impairment in endogenous cholesterol biosynthesis  and inhibiting the expressions of proteins involved with the Toll-like receptor-4/nuclear factor-kappa B (TLR-4/NF-κB) signaling pathway (in vitro study, Hung et al. found that guar gum, a type of dietary fiber, could increase suppressor of cytokine signaling-1 expression through the TLR-2 and dectin-1 pathways, resulting in anti-inflammatory regulation in small intestinal cells (It is believed that the acceleration of arterial plaque formation and transformation into vulnerable plaques induced by chronic low-grade inflammation is one pathophysiology of atherosclerotic disease . Indeed, pathway . In addial cells . Currental cells , 108, thHypertension, an asymptomatic clinical condition, is an important public health issue. Both observational studies and meta-analyses have demonstrated graded associations between higher SBP/DBP and increased CVDs risk , 110. ThThere are some limitations to our study that should be noted. Firstly, dosage plays an important role in nutritional assessment, and we failed to provide evidence for a dose–response relationship between dietary fiber intake and improvements in cardiovascular risk factors. In addition, it seems that most of our funnel plots presented some asymmetries, indicating potential publication bias in the present umbrella meta-analysis; however, further “trim and fill” analysis delivered evidence for the robustness of the results. Finally, we did not register the protocol of this umbrella meta-analysis in the Cochrane Library or PROSPERO. On the other hand, our study is the first umbrella meta-analysis to systemically evaluate the relevant evidence and elucidate the efficacy of dietary fiber intake on cardiovascular risk factors. Additionally, we performed a subgroup analysis and assessment of the study population, type of intervention, dosage, and sample size, which could provide some strategies for precision nutrition.The results of the current umbrella meta-analysis strongly support the beneficial effects of dietary fiber intake for the improvement cardiovascular risk factors. However, it should be noted that the health-promoting effects of dietary fiber intake may differ between populations with different metabolic diseases.The original contributions presented in the study are included in the article/LF designed the study and wrote the paper. LF and SQ employed the searched strategies and reviewed the relevant trials. QZ and GZ are responsible for the data extraction. MT played a role as a consultant. GZ was responsible for the quality assessments for the studies and the corresponding author. All authors have read and agreed to the published version of the manuscript.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.