Although several case–control studies on the prevalence of Impulse-Control Disorders (ICDs) in Parkinson’s Disease (PD) have been conducted, no meta-analytic study on this topic has previously been published. Thus, knowledge about the overall prevalence rate of ICD in PD and factors that might moderate this relationship is lacking.N = 4,539, consisting of 2,371 PD patients and 2,168 healthy controls, representing 14 case–control studies were included. Estimation of the odds ratio (OR) of ICDs in PD compared to healthy controls was conducted using random-effects models. Mixed-effects models were applied in the moderator analysis of heterogeneity. Publication bias was estimated using a contour-enhanced funnel plot, the Rüker’s test, and fail-safe N test for estimating the number of potential missing studies.Prevalence studies of ICDs in PD were identified by computer searches in the MEDLINE, PsycINFO, and Web of Science databases, covering the period from January 2000 to February 2017. Data for ORs ranging between 2.07, 95% CI , for having any ICDs, and 4.26, 95% CI , for hypersexuality. However, the random-effects results for shopping were non-significant, though the fixed-effects model was significant . The testing of potential moderator variables of heterogeneity identified the following two variables that were both associated with increased risk: being medically treated for PD and disease duration. The results must be interpreted with some caution due to possible small-studies effect or publication bias.Overall, the results showed significantly higher ratios for several ICDs in PD compared to healthy controls with the estimated overall Individuals with PD seem to have a significantly greater risk of suffering from ICDs compared to healthy controls. Gambling, hypersexuality, eating, punding, and hobbying are all ICDs significantly associated with PDs being medically treated for PD. Impulse control disorders (ICDs) are a collective term for non-motor symptoms that include pathological gambling, compulsive shopping, hypersexuality, and binge eating . In addiImpulse control disorders have different levels of severity. Pathology is defined by its interference with financial, personal, family, and/or professional life. The addictive behavior is often time-consuming, and can cause significant distress and impinge on the quality of life , 8. ICDsAlthough ICDs are considered a common non-motor complication of PD, frequency estimates range from approximately 14–60% in PD , 13. EarImpulse control disorders in PD seem to be linked to certain risk factors: young age, male gender, being unmarried, higher education, novelty-seeking personality traits, personal or family history of addictions prior to PD diagnosis, and comorbid psychiatric disorders , 20–23. Dopaminergic medication, especially dopamine agonists (DAs) are associated with higher frequencies of ICDs –32. AlthAlthough several narrative reviews on ICDs related to PD have been published , 35, 36,We conducted a systematic search and literature review following the PRISMA guidelines  in MEDLIThe studies were included if they fulfilled the following criteria: (a) the full article was published in English, (b) the article was published between the year 2000 and January 19, 2017, (c) the article had to contain original data on prevalence rates for ICDs and/or impulse-control disorders and related behaviors, and (d) the article had to be a case–control study or a case–control poster.Together the search generated a total of 3,359 articles. References for 391 articles were further screened by their abstracts, as well as their N  measuring only outcomes for obsessive–compulsive disorders ; (2) usiN . In addiN . Thus, aN , 44–54. N = 4,538, consisting of 2,371 PD patients and 2,168 healthy controls. For further details regarding the specific studies’ characteristics of response rate, the severity of Parkinsonism or H–Y stage, mean age, sample size, duration of illness, number of patients on DAs, as well as the proportion of Parkinson patients versus healthy controls, see Table The total participant population was n participants on levodopa as well as n participants on DAs. In addition, we also included the mean UPDRSIII motor score, being medically treated versus “de novo” PDs (treated = 1) and mean onset of PD  as potentially moderators. The last section of the coding scheme included the prevalence of the total and individual ICDs. These were reported as numerals, as well as percentages. The last section was identical to that of the healthy control group.A coding scheme was developed and used by two of the authors (Yasaman Moussavi and Stine Therese Kopperud) who coded the studies and were trained to ensure a common understanding of the coding scheme. Potential disagreements were resolved by discussing the topic with a third author (Helge Molde) in order to reach an agreement. The coding scheme comprised a number of descriptive codes such as study ID (numeric), coder (1 or 2), journal of publication, publication year, country and continent, ethical approval, and conflicts of interest (yes/no). Furthermore, the coding scheme consisted of information regarding the specific data and findings; total sample size for PD patients, sample size for healthy controls, measurement instrument for the ICD , mean Parkinson stage (Hoehn–Yahr), mean age, sex, duration of PD and whether patients with dementia were included or not. Finally, the coding scheme covered information about medical treatment of PD: The ICDs that were listed in the coding scheme were: Gambling, shopping, binge eating, punding, hypersexuality, hobbying, gaming, internet addiction, kleptomania, skin picking, trichotillomania, intermittent explosive disorder, pyromania, walkabout, compulsive medication use, repetitive behavior, stereotypical movement disorder, and dopamine dysregulation syndrome.Two studies were multinational and included a number of European and US sites. Eight studies were from Europe, one was from South America, three from North America, one from the Middle East, and one from the southwest part of Asia (India). See Table Q-statistics implies significant between-study variance, or that there are significant differences between the studies in the overall estimate of the mean effect. The I2 statistics [100% × (Q − df./Q)] is a measure of percentage of variability in effect sizes that is a result of true differences between the studies. Hence, I2 is an index of percentage of unexplained between-study variance of the mean estimate. A rough guide to interpret I2 is that percentages of around 25, 50, and 75% imply low, medium, and high heterogeneity, respectively. Also, the I2 index and the Tau2 are directly related, as the higher the between-study variance (Tau2), the higher the I2 index . The OR was calculated in such a way that an OR above 1 indicates higher odds for the Parkinson group having an ICD, in comparison to the odds for the healthy control group.After assessing heterogeneity, potential moderators were regressed using mixed multivariate models. All moderators, except being medically treated for PD, were mean-centered in order to easily interpret the intercept . All resSome moderator variables had missing data. Data for these variables was imputed using “multivariate imputation by chained equations” through the mice package in R .contour-enhanced funnel plot. A funnel plot is a plot of each trial’s OR against the standard error. The plot should be shaped like a funnel if no publication bias is present  were estimated using a  present . The con present . Further present . Hence, N test was applied, estimating how many non-significant studies are needed in order to have a non-significant overall result , which is the default in the metafor package , indicating significant heterogeneity between the studies. The between-study variance, Tau2, was 0.27, and the percentage of unexplained between-study variance I2 = 70.7, 95% CI . This indicated high unexplained between-study variance with respect to the total number of ICDs. See Figure The results from the random-effects model on t = 0.69, p > 0.05), indicating no publication bias.We conducted a contour-enhanced funnel plot estimating publication bias. As seen from Figure N test was significant (p < 0.0001), indicating that 226 non-significant studies would be needed in order for the random-effects model to be non-significant.The Rosenthal’s fail-safe The univariate testing of possible moderators of heterogeneity resulted in two significant univariate models: treated PDs and disease duration. Hence, these parameters were included in a mixed multivariate model.OR point estimate of β0 = 0.03 . The intercept β0 refers in this model to de novo patients, or non-medically treated patients. The test for residual heterogeneity indicated non-significance, QE = 15.0, p = 0.13. The overall moderator model was significant, QM = 13.90 (p = 0.004). Being medically treated for PD was significant at the 0.01 level, OR = 2.46, 95% CI .The final model included only medically treated PDs as a moderator. The results from the meta-regression analysis showed a non-significant log-R2) of the heterogeneity, and the percentage of residual heterogeneity, I2, was 0%. Tau2, or residual heterogeneity, was 0.00 (SE = 0.04). The QQ-normal plot indicated a normal distribution of the residuals.The model accounted for 100% , indicating non-significant heterogeneity between the studies. The between-study variance, Tau2, was 0.02, and the percentage of unexplained between-study variance I2 = 1.70%, 95% CI = . This indicates almost no unexplained between-study variance with respect to gambling. See Figure The results from the random-effects model on CI 1.56, .67. The t = 1.01, p > 0.05).We conducted a contour-enhanced funnel plot estimating publication bias. As seen from Figure N test was significant (p < 0.0001), indicating that 81 non-significant studies would be needed for the random-effects model to be non-significant.Rosenthal’s fail-safe As there was no significant between-study variance or heterogeneity, no further analyses were conducted for gambling.hypersexuality showed a significant OR estimate of point 4.26, 95% CI . The Q-statistics were non-significant , indicating non-significant heterogeneity between the studies. The between-study variance, Tau2, was 0.51, and the percentage of unexplained between-study variance I2 = 42.4%, 95% CI . This indicated moderate unexplained between-study variance with respect to hypersexuality. See Figure The results from the random-effects model on t = 1.4, p > 0.05), indicating no publication bias.We conducted a contour-enhanced funnel plot estimating publication bias. As seen from Figure N test was significant (p < 0.0001), indicating that 165 non-significant studies would be needed for the random-effects model to be non-significant. The univariate testing of possible moderators of heterogeneity resulted in two significant bivariate models: disease duration and medically treated PDs.The Rosenthal’s fail-safe OR point estimate of β0 = 0.81 . The overall moderator model was significant, QM = 7.36 (p = 0.011). Both of the moderators included were significant. Disease duration was significant at the 0.05 level, OR = 1.20, 95% CI . Treated PDs was also significant at the 0.05 level, OR = 2.63, 95% CI . The test for residual heterogeneity was non-significant, QE = 7.60, p = 0.68.The results from the meta-regression analysis showed a significant log-2R) of the heterogeneity, and the percentage of residual heterogeneity, I2, was 2.39%. Tau2, or residual heterogeneity, was 0.02 (SE = 0.28). The QQ-normal plot indicated a normal distribution of the residuals.The model accounted for 96.5% , indicating no significant heterogeneity between the studies. The between-study variance, Tau2, was 0.40, and the percentage of unexplained between-study variance I2 = 50.8, 95% CI . This indicates a moderate level of between-study variance with respect to shopping. See Figure The results from the random-effects model on eating showed a significant OR estimate of 2.32, 95% CI . The Q-statistics were significant , indicating significant heterogeneity between the studies. The between-study variance, Tau2, was 0.58, and the percentage of unexplained between-study variance 2I = 66.8, 95% CI . This indicates high unexplained between-study variance with respect to eating. See Figure The results from the random-effects model on t = 0.14, p > 0.05), indicating no publication bias.We conducted a contour-enhanced funnel plot estimating publication bias. As seen from Figure N test was significant (p < 0.0001), indicating that 64 non-significant studies would be needed in order for the random-effects model to be non-significant.The Rosenthal’s fail-safe l-dopa and being medically treated for PD. The correlation between the two former moderators was 0.91, thus we only included being medically treated for PD in the mixed model.The univariate testing of possible moderators of heterogeneity resulted in three significant univariate models: number of patients using DAs, number of patients using OR point estimate of β0 = −0.20 . The intercept β0 refers in this model to de novo patients or non-medically treated patients. The results indicate that de novo PD patients do not differ in comparison with normal controls with respect to eating problems. The overall moderator model was significant, QM = 18.5 (p = 0.002), and as stated above, being medically treated for PD  was significant. The test for residual heterogeneity was non-significant, QE = 7.89, p = 0.44. The model accounted for 100% (2R) of the heterogeneity, and the percentage of residual heterogeneity, I2, was 0.0%. Tau2, or residual heterogeneity, was 0.00 (SE = 0.13). The QQ-normal plot indicated a normal distribution of the residuals.The results from the meta-regression analysis showed a non-significant log-punding showed a significant OR of point 3.02, 95% CI . The Q-statistics was non-significant , indicating no significant heterogeneity between the studies. The between-study variance, Tau2, was 0.0, and the percentage of unexplained between-study variance was: I2 = 0.0%, 95% CI . See Figure The results from the random-effects model on We conducted a contour-enhanced funnel plot estimating publication bias. As seen from Figure I2 estimate, no mixed-effects model was conducted. Hence, no further testing was applied for punding.Due to the hobbying showed a non-significant OR at point 1.73, 95% CI . The Q-statistics were significant , indicating significant heterogeneity between the studies. The between-study variance, Tau2, was 0.78, and the percentage of unexplained between-study variance I2 = 81.1, 95% CI . This indicates large unexplained between-study variance with respect to hobbying. See Figure The results from the random-effects model on hobbying studies included are using de novo PDs, we decided to use patients being medically treated for PD as a moderator.As two of the six OR point estimate of β0 = −0.53 . The intercept β0 refers in this model to de novo patients, or non-medically treated patients. The results indicate that de novo PD patients do not differ in comparison with normal controls with respect to hobbying.The results from the meta-regression analysis showed a non-significant log-p = 0.04), and being medically treated for PD  was significant. The test for residual heterogeneity was non-significant, QE = 7.59, p = 0.11. The model accounted for 92.6% (2R) of the heterogeneity, and the percentage of residual heterogeneity, I2, was 27.60%. Tau2, or residual heterogeneity, was 0.00 (SE = 0.28).The overall moderator model was significant, QM = 8.53 , meaning there is an effect for the studies included, but that the effect cannot be generalized to the wider population of studies. However, overall, it should also be noted that our mixed-effects models explained a significant amount of heterogeneity in the different models, to the point where there was no heterogeneity left to explain.The results suggest that impulsive behavior is not an invariant feature of PD, but varies by a number of important explanatory variables including; being medically treated for PD and disease duration. Still, it should be noted that the associations are not at the individual level, but at the study level, or as a moderation of between-study estimates. This distinction is important. That said, DA treatment has been suggested as a risk factor for ICDs , and ourStill, and as mentioned in Section “N from 64 (eating) to 165  to 226 (any ICD) non-significant studies would needed to be included to make the overall results non-significant. Overall, this suggest stability of results.As the presented results show, two of the models  had some possibility of publication bias according to the contour-enhanced plots. For the other models, the plots indicated very little publication bias. Notably also, the Rüker’s test was not significant for any model, supporting an interpretation of lack of publication bias within the models/results. Regarding the Rosenthal’s fail-safe The inclusion of observational studies in meta-analyses has led to questions about validity of results. Observational studies are in general criticized as susceptible to subjective interpretations, unidentified confounding variables, and risk modification. The analysis of the data from the meta-analysis itself is accordingly also vulnerable to subjective bias , 71.We made use of random-effects models, which are generally more vulnerable to publication bias than fixed-effects estimates. On the other side, using a fixed-effects model would assume only within-study errors, or no between-study variation, which is an assumption that is seldom met .We did not conduct a subgroup sensitivity analysis due to the low number of studies included. However, with a larger sample of studies, this would enable researchers to evaluate the impact of heterogeneity versus the impact of publication bias in the estimates .When evaluating the methods used, we depended on data reported in the included studies. We did not contact the authors if methods were poorly reported. Unclear reporting does not necessarily mean insufficient study administration, but can limit the understanding of the study .Although it can be challenging, one of the intents of a meta-analysis is to find and assess all studies meeting a set of inclusion criteria. Many studies may not have been published and can systematically differ from the published ones. Significant, positive findings are shown to be more likely to be published compared to small, negative studies, hence this may lead to publication bias , 72, 73.A potential bias can arise due to excluding studies reported in languages other than English. However, language bias is reported to only have modest or no effect .It should also be noted that direct comparisons of ICD prevalence in various studies are complicated by different assessment methods, with emphasis put on different time frames .The results of the present meta-analysis show that there is a significant chance of developing ICDs in PD patients compared to healthy controls. The investigation of possible moderators of heterogeneity resulted in two variables  which are significant in mixed models. This is supported by previous studies looking into risk factors for development of ICDs in PD , 26, 28.The present results show a significant relationship between ICDs and PD. Duration of PD and being medically treated for PD are moderators positively associated with ICDs in PD patients. Proper assessment during physician consultations is critical as ICDs can significantly harm the overall social functioning and personal relationships of this patient group. The use of DAs seems to pose an especially high-risk factor for ICD development, thus pharmacological treatment needs to be carefully monitored. Caretakers and relatives should be involved, as patients may lack insight, or find their behavior embarrassing.Finally, conducting a precise meta-analysis is dependent on the quality of the included research articles. As there always will be a risk of publication bias, results must be interpreted with caution.Ref. , 44–55 aHM, YM, and SK did the literature research and study coding. HM did the statistical analysis. All authors have significantly contributed ideas, commenting on the manuscript and reviewing the paper during the writing process.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.


The results of published studies about the relationships between folate intake and risk of head and neck squamous cell carcinoma (HNSCC) remained inconsistent. Hence, a comprehensive and dose–response meta-analysis was performed to clarify the association between folate intake and HNSCC risk.The electric searches of Pubmed, Medline, and EMBASE databases were performed to identify the studies examining the relationship between folate intake and HNSCC risk on April 5, 2017. According to the inclusion criteria, finally 9 studies were included in this meta-analysis. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to evaluate the strength of associations. Dose–response analysis was conducted to quantitate the relationship between dietary folate intake and HNSCC risk.The pooled OR for assessing the risk of HNSCC and folate intake in the highest level versus lowest level was 0.505 (95% CI 0.387–0.623). The linearity model of dose–response analysis indicated that with increased 100 μg/d folate intake, the risk of HNSCC decreased 4.3% degree .These results indicate that folate is a protective nutrient against HNSCC carcinogenesis. Therefore, efforts toward modifiable risk factors and primary prevention have become paramount importance.Head and neck squamous cell carcinoma (HNSCC), which is the sixth incidence of malignance worldwide, causes about 600,000 new cases and leads about 200,000 deaths annually.,5 Folate, also called vitamin B9, plays an important role in the process of DNA synthesis, repair, and methylation. Low level of folate attenuates DNA methylation and promotes carcinogenesis. By decreasing thymidylate biosynthesis de novo, folate deficiency causes mis-incorporation of uracil during DNA repair and synthesis, and induces DNA strand breaks, and ultimately results in malignant transformation.The fact that low levels of vegetable and fruit intake are associated with increased risks of HNSCC suggests that folate, which is abundant in vegetables and fruits, is a protective nutrient for HNSCC. and breast cancers, but decreased the risks of colorectal, oropharyngeal, esophageal,–15 pancreatic,,14,16 and cervical cancers. Almadori et al firstly reported a positive relationship between serum folate level and HNSCC risk. Then other epidemiologic studies have estimated the associations between folate intake and HNSCC risk.–21 However, the role of folate intake level in HNSCC has remained controversial. Hence, a comprehensive meta-analysis was conducted to determine the link between folate intake and HNSCC risk, and to evaluate the dose–response relationship between folate intake level and HNSCC risk.Many studies have summarized previous published data and indicated that increased folate intake was associated with the increased risks of prostate2This meta-analysis was performed according to the latest Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).2.1A systematically search was performed up to April 5, 2017 by 2 reviewers (CF and SZ) within Pubmed, Medline, and EMBASE, using the following search strategy: ((((folate OR folic acid OR vitamin B9))) AND )) AND ((cancer∗ OR tumor∗ OR carcinoma∗ OR neoplasm∗)). In addition, the reference lists from original reports were reviewed and manually selected for other available publications. No language restrictions were imposed in the searching process.2.2The inclusion criteria of the included studies were as followed: the experimental design was a case-control or cohort study; studies reported the associations of histological diagnosed HNSCC risk with dietary folate intake from diet and serum levels of folate; relative risk (RR), hazard ratio, or odds ratio (OR) with 95% confidence interval (CI) was given to estimate the association of the highest folate intake versus lowest folate intake; for dose–response analysis, the number of cases and participants, and eligible dose concentration must be provided. The selected studies were only limited in using dietary folate intake as only measurement standard.The most recent study was included for duplicate publications.2.3Data were extracted independently by 2 authors (SY and CF). The following information was selected according to the criteria listed previously: the first author's name, publication year, country, study design, total sample size (cases and controls), difference between highest and lowest folate levels, measurement, range of exposure, adjusted variables, risk estimates, and 95% CI for evaluating the highest folate levels versus lowest folate levels. The adjusted ratios that had been maximally adjusted for potential confounders were chosen when studies reported several multivariable adjusted effect estimates. All controversial questions were resolved by asking a third author.,23 NOS evaluating details including the following 3 subscales awarded a maximum of 9 items: selection of participants and measurement of exposure (4 items), comparability (2 items), and evaluation of methodological quality outcome (3 items). Studies with 7 score or higher score were considered as high-quality studies.,24We assessed study quality using the Newcastle–Ottawa quality assessment scale (NOS) system, which has been validated as a comprehensive tool for assessing the quality of observational studies in meta-analysis.2.4I2 statistic. Cut-off points of I2 value were for 25%, 50%, and 75% for low, moderate, and high degrees of heterogeneity, respectively. When heterogeneity was negligible, a fixed-effect model was chosen; otherwise, the random-effect model was chosen. Sensitivity analysis was performed to evaluate robust of pooled results by omitting 1 study each time when heterogeneity was significant. The publication bias was determined with the Begg rank model and Egger linear model. A stratified analysis was performed by study location, anatomical site, source of control, folate assessment, and study quality. At last, a dose–response meta-analysis was conducted by using the correlated natural logs of the RRs or ORs with their standard error (SE) across all folate intake categories. To drive the dose–response curve, we used the restricted cubic splines with 4 knots at the 5%, 35%, 65%, and 95% percentiles of the distribution to evaluate the potential curvilinear relations. All statistical analyses were performed using Stata 12.0 .Pooled risk estimates (RR or OR) with 95% CI were used for detecting the associations of folate intake with risk of HNSCC. The heterogeneity test was evaluated with 33.1After duplicates removing within EndNote, total 1607 articles were identified from our initial search. Then, 1354 studies were excluded after screening titles and abstracts; the remaining 253 studies were evaluated eligibly with full text reading. Lastly, according to our inclusive criteria mentioned in “Materials and methods” section, 9 studies were included in our meta-analysis. The search results and eligible literature selection process are shown in Fig. ,21,28–30 and others were conducted in Asia (n = 2),,31 North America (n = 1), and South America (n = 1). Among the 9 included studies, 3 studies involved patients with comprehensive HNSCC,–21 3 studies involved patients with laryngeal cancer,,29,32 2 studies involved patients with nasopharyngeal carcinoma,,31 and 1 study involved patients with oral cavity and pharyngeal squamous cell carcinoma (OPSCC). Seven studies investigated the associations between dietary folate intake and HNSCC risk.,20,28–32 Two studies evaluated the links between serum folate concentration and HNSCC risk.,21 In terms of source of control, 7 studies were hospital-based,28–32 and 2 studies were population-based.,21 Five studies matched high score with NOS scale,–21,31 and 4 studies matched low score.–30,32 Four studies were included in dose–response analysis.,29,31,32 The main profiles of the included 9 studies are summarized in Table The included main studies were conducted in Europe (n = 5),3.2P = .038, I2 = 50.9%) suggested that a random-effect model was available. The pooled ORs of HNSCC for highest levels versus lowest levels was 0.505 .To determine the relationship between dietary folate intake and HNSCC risk, a dose–response analysis including 4 case-control studies was performed. As shown in Fig. 3.4High heterogeneity suggested a sensitivity analysis to be necessary. As shown in Fig. 4,34 Folate intake was assumed to be protectable against varieties of cancers including colorectal, oropharyngeal, esophageal,–15 pancreatic,,14,16 and cervical cancers. Eighty-two countries have passed legislations that mandate folate fortification in at least 1 industrially milled cereal grain on December 2014. However, conflicting studies have summarized published results that indicated a positive relationship between folate intake, and prostate and breast cancers, which suggests different role of folate in cancer prevention. To our knowledge, no study has investigated the relationship between folate intake and HNSCC risk. Hence, we conducted a comprehensive meta-analysis to evaluate the association of folate intake and HNSCC risk, and to characterize the dose–response relationship between HNSCC and folate intake.Folate plays an important role in the process of DNA synthesis, repair, and methylation.The present meta-analysis of 9 studies including 4090 patients and 10,802 controls provided a quantitative estimate of associations between HNSCC risks and folate intake. Our results showed that increased folate intake was associated with risk of HNSCC. The inverse relationships could be detected in subgroup analysis stratified based on countries, anatomical sites, source of controls, folate intake measurement, and NOS quality. Moreover, a dose–analysis meta-analysis indicated that with a 4.3% decrease in HNSCC risk was recorded for increased 100 μg/d folate intake with a linearity model.,36 There are 2 main mechanisms that folate deficiency induces carcinogenesis: (1) by inducing complete transformation of dUMP to dTMP, which makes mis-incorporation of uracil into DNA and leads to chromosomal breaks and mutations; and/or (2) by causing abnormal methylation level of DNA, leading to alternations in expression of critical proto-oncogenes and tumor suppressor genes.,34 Experiments in vivo referring mice and dogs suggested that increased folate intake alternated DNA methylation and eventually reduced the risks of cancers.,38 In addition, the polymorphisms of the 5,10-methylenetetrahydrofolate reductase, which is a critical junction in folate-metabolizing pathway by guiding folate metabolites to DNA methylation pathway and away from the DNA synthesis pathway, may modulate the susceptibility of several cancers.,39Folate is a water-soluble B vitamin and is found in many foods including fruits, vegetables legumes, cereals, and liver. Humans cannot produce folate de novo and need to uptake folate from dietary intake.Our results in this meta-analysis firstly indicated that folate intake is associated with decreased risk of HNSCC, which is consistent with the role of folate plays in majority of cancers. In addition, a comprehensive dose–response meta-analysis was conducted to quantitate the relationship between dietary folate intake and the risk of HNSCC. Interestingly, compared with low levels of folate intake, high levels of folate intake also make a positive effect on overall survival of HNSCC, which indicated that folate intake is associated with prognosis of HNSCC. found that high level of folate intake was associated with decreased risk of oral and pharyngeal cancer (OPC). OPSCC is the major pathological type of OPC, which may support our results. In addition, compared with detecting folate level by Food Frequency Questionnaire, the OR of folate serum level was relative high in our meta-analysis. The plausible reason was that the subgroup analysis of folate serum level only included 2 studies, and the result of 1 study showed no link existed between folate intake and HNSCC risk.In subgroup analysis based on countries, anatomical sites, source of controls, folate intake measurement, and study quality, we observed an overall inverse association between folate intake and HNSCC risk. However, in OPSCC subgroup analysis, only 1 study matched the histological diagnosed squamous cell carcinoma and was included. In the previous study, Galeone et alSome limitations were significant in our meta-analysis: (1) since the included studies in our meta-analysis were all case-control studies, lack of prospective study, which could affect recall bias and selection bias, restricted the precision of our results; (2) in some subgroup analysis, the numbers of included studies were too small and may make influence on the last conclusions; (3) the analyses in our meta-analysis were pooled data , which prevented the further detailed analysis and precise results from being obtained. Hence, our results should be interpreted with caution.5In conclusion, the results of our meta-analysis indicate that a significant association exists between increased folate intake and decreased HNSCC risk. Dose–response analysis of dietary folate intake indicates that every 100 μg/d folate intake accounts for a 4.3% decrease of HNSCC risk. Furthermore, the present meta-analysis suggests that well-designed and observed prospective studies are necessary for detecting the precise relationship between folate intake and HNSCC risk in the future.


P = 0.002, I2 = 69.2%). There was a significant association between mild SAHS and the risk of AF , moderate SAHS , and severe SAHS . The results suggest that sleep apnea hypopnea syndrome could increase the risk of AF, and the higher the severity of SAHS, the higher risk of atrial fibrillation.Numerous reports have been done to seek the relationship between sleep apnea hypopnea syndrome (SAHS) and the risk of atrial fibrillation (AF). However, definite conclusion has not yet been fully established. We examined whether SAHS increases AF incidence in common population and summarized all existing studies in a meta-analysis. We summarized the current studies by searching related database for potential papers of the association between SAHS and the risk of AF. Studies that reported original data or relative risks (RRs) with 95% confidence intervals (CIs) for the associations were included. Sensitivity analyses were performed by omitting each study iteratively and publication bias was detected by Begg's tests. Eight eligible studies met the inclusion criteria. Fixed effects meta-analysis showed that SAHS increased AF risk in the common population (RR = 1.70, 95% CI: 1.53–1.89,  Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia encountered in clinical practice, affecting approximately 1% to 4% of the general population . It is r⩾30), respectively.Therefore, this study aims to conduct a meta-analysis by combining the results from all available cohort studies to examine whether SAHS increases AF incidence in common population and evaluate the risk of AF for mild SAHS , moderate SAHS , and severe SAHS  guidelines . Two invThe following inclusive selection criteria were applied: (1) the study design was based on retrospective or perspective cohort studies; (2) the study evaluated the association between sleep apnea hypopnea syndrome and the risk of atrial fibrillation; (3) a study reporting AF number in SAHS group and AF number in the control group or the relative risks (RRs) with 95% confidence intervals (95% CIs) was included; (4) one of the end points of interest were incident HF; (5) study must contain reference group. Only studies that provided a percentage of the incidence of AF or did not provide available data to allow calculation of the effect estimates were excluded.The following information was recorded by two authors independently for each study using a standardized form: first author, country in which the study was performed, year of publication, study design, follow-up duration, number in case and control groups, and SAHS diagnostic methods. Two investigators independently performed a quality assessment using the 9-star Newcastle-Ottawa Scale (NOS) , and theP > 0.05 and I2 < 50%); otherwise, a random effect model was used. Heterogeneity was considered as either a P value < 0.05 or I2 > 25% [P value of <0.1 was considered as significant statistical publication bias. Stata  was used for all statistical analyses.We performed a meta-analysis to examine the relationship between SAHS and AF risk. Relative risk (RR) with 95% confidence interval (CIs) was used to estimate the effect sizes. A fixed effects model was used to estimate the pooled RR with 95% CIs if there was no significant heterogeneity . We extracted variables that variables that affect research results. Then we further performed meta-analysis to pool the results in studies that adjusted for confounders. After adjustment for the confounders, there was still a positive association between SAHS and the risk of AF with an RR of 1.40 .Meta-analysis was conducted to ascertain the potential relationship between sleep apnea hypopnea syndrome and the risk of atrial fibrillation among eight studies. As shown in ⩾30 was regarded as mild, moderate, and severe OAHI, respectively, based on clinically accepted cut points [P = 0.01, I2 = 78.4%), moderate SAHS , and severe SAHS . The results also suggested that the higher the severity of SAHS, the higher the risk of atrial fibrillation.Three studies reported the severity of SAHS. The obstructive apnea hypopnea (OAHI) was the main index of SAHS severity, defined as the number of obstructive apneas plus hypopneas per hour of sleep. Those with an OAHI of <5% were considered without SAHS . An OAHI of 5%–14.9%, 15%–29.9%, and t points , 15. TheI2 = 0, P = 0.522). According to the NOS score of each study, the studies were divided into three subgroups. Three studies had been scored NOS of 8, four studies scored NOS of 7, and one study scored NOS of 6. Meta-analysis of studies with NOS score of 8 showed that AF risk increased due to SAHS . Studies with NOS score of 7 yielded an RR of 1.35 . Since noticeable heterogeneity was found to be present, metaregression analysis was performed to explore potential sources of heterogeneity. Out of all of the parameters, patients' age, follow-up duration, and countries where studies were performed were significant sources of heterogeneity . None of the publication year, gender, sample size, NOS score, and SAHS diagnosis was source of heterogeneity (P > 0.05). The meta-regression analysis results are shown in Sensitivity analysis was performed by subgroup analyses, which were conducted to handle the clinical heterogeneity across studies according to NOS score and countries. According to the countries where studies were performed, the studies were divided into three subgroups: USA (6 studies), China (one study), and Australia (one study). Meta-analysis of studies performed in USA showed that SAHS was associated with an increased risk of AF  without heterogeneity (P = 0.833), indicating a low probability of publication bias  [SAHS has been shown to contribute to the increased AF burden , 22. Pre = 0.67) . HoweverThere is emerging evidence from animal and human studies that the physiologic changes of sleep apnea, including hypoxia, hypercapnia, and intrathoracic pressure swing, precipitate electrical and structural changes. The exact mechanisms for the association between sleep apnea hypopnea syndrome and atrial fibrillation remain unclear, as the two conditions share many of the same risk factors; however, emerging evidence from animal and human studies indicated that the physiologic changes of sleep apnea including hypoxia, hypercapnia, and activation of sympathetic nervous function may be involved in this process . On the In this meta-analysis, we confirmed that sleep apnea hypopnea syndrome could increase the risk of atrial fibrillation. However, our meta-analysis also has limitations. Although we perform a metaregression analysis to evaluate the influence of variables such as history of cardiovascular disease and BMI on the risk of atrial fibrillation, there was significant heterogeneity among dose-response and subgroup studies; we failed to conduct metaregression analysis in these studies because these variables were always unavailable.In conclusion, our results indicated that sleep apnea hypopnea syndrome could increase the risk of atrial fibrillation. There is a dose-response relationship between sleep apnea hypopnea syndrome severity and rates of incident atrial fibrillation, and the higher the severity of sleep apnea hypopnea syndrome, the higher the risk of atrial fibrillation.


P = 0.015). No clear associations between the rs1617640 and rs507392 polymorphisms and diabetic retinopathy were observed. By contrast, rs551238 polymorphisms were associated with increased diabetic retinopathy risk . These results indicate that EPO polymorphisms are a risk factor for diabetic microvascular complications.We conducted a meta-analysis to evaluate the relationship between erythropoietin (EPO) polymorphisms and diabetic microvascular complications. We searched the PubMed, Embase, Cochrane library, Web of Science, Wanfang, and Chinese National Knowledge Infrastructure databases for appropriate studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the associations. Ultimately, eight studies consisting of 2,861 cases and 2,136 controls were identified and included in our meta-analysis. Results with our genotype model indicated an association between rs1617640 polymorphisms and diabetic microvascular complications (TT vs. GG: OR = 1.544, 95% CI = 1.089–2.189,  Diabetes prevalence has increased globally from 4.7% in 1980 to 8.5% in 2014 among adults over 18 years of age , and is Erythropoietin (EPO) is a kidney-derived peptide hormone that plays a major role in the stimulation of bone marrow stem cells and erythropoiesis –7. EPO cet al. suggested that erythropoietin polymorphisms increased diabetic retinopathy risk [et al. found no significant association [Several studies have examined associations between EPO polymorphisms and diabetic complications; however, the results have been inconsistent. Fan, thy risk . Conversociation . Thus, oFigure Hardy-Weinberg equilibrium (HWE) was assessed via Chi-square test in the control subjects of each study. Genotype distributions among controls were consistent with HWE in only eight studies –20. ThesP = 0.015)  . For diabetic retinopathy and end-stage renal disease, rs1617640 polymorphisms were associated with diabetic microvascular complications in all genetic models . Only one study assessed T1DM in Australian populations, and no association was found in any genetic model .Eight studies investigated the association between EPO rs1617640 gene polymorphisms and diabetic complications risk –20. Diff) Figure . For diaP = 0.886; genotype model: TC vs. CC: OR = 0.896, 95% CI = 0.371–2.165, P = 0.808, TT vs. CC: OR = 1.019, 95% CI = 0.412–2.517, P = 0.968; dominant model: OR = 0.951, 95% CI = 0.417–2.168, P = 0.904; recessive model: OR = 1.102, 95% CI = 0.580–2.094, P = 0.766.Only one study investigated the relationship between EPO rs507392 polymorphisms and diabetic retinopathy . No assoP = 0.002; genotype model: AC vs. CC: OR = 0.598, 95% CI = 0.402–0.890, P = 0.011; dominant model: OR = 0.561, 95% CI = 0.385–0.817, P = 0.003; recessive model: OR = 0.791, 95% CI = 0.643–0.973, P = 0.026) , which exhibited a slight publication bias Figure , Table 3EPO is located on chromosome 7q21 and encodes a potent angiogenic factor expressed in the retina and kidney –25. Seveet al. suggested an association between the T allele of SNP rs1617640 and proliferative diabetic retinopathy as well as end-stage renal disease [et al. concluded that all three EPO SNPs  were associated with diabetic retinopathy risk independent of duration of DM, degree of glycemic control, and nephropathy [P = 0.015).We searched several databases for relevant studies assessing the association between the EPO polymorphisms and diabetic complications. Our analysis included eight studies with a combined total of 2,861 cases and 2,136 controls. These studies were conducted between 2008 and 2015 to investigate the association between EPO polymorphisms and diabetic retinopathy and nephropathy. Tong,  disease . Gong asOur subgroup study stratified by complication type showed that rs1617640 polymorphisms were associated with diabetic retinopathy and end-stage renal disease. However, the association with diabetic retinopathy was not significant in any model. Only one study evaluated T1DM in Australian populations, so we were not able to evaluate statistical significance in this case.Only one study investigated rs507392 polymorphisms, and found no association between these polymorphisms and diabetic retinopathy. Three studies investigated the association between EPO rs551238 polymorphisms and diabetic retinopathy risk, with inconsistent results. We pooled the results and found a relationship between rs551238 polymorphisms and diabetic retinopathy.Our meta-analysis had some limitations. First, the number of included studies was relatively small. rs1617640 polymorphisms were examined in eight studies, and rs507392 and rs551238 polymorphisms were investigated in one and three studies, respectively. Previous studies demonstrated that EPO variations played roles in DR and DN development , 26, andIn summary, we found that EPO polymorphisms are a risk factor for diabetic microvascular complications. rs1617640 polymorphisms are associated with increased risk of diabetic retinopathy and nephropathy, and rs551238 polymorphisms are associated with increased risk of diabetic retinopathy.Relevant studies were retrieved from the PubMed, Embase, Cochrane library, Web of Science, Wanfang, and Chinese National Knowledge Infrastructure databases. The last search was performed on August 22, 2017, with keywords including  AND ” OR “Genetic Polymorphisms” OR “Polymorphism” OR “genetic” OR “allele” OR “variation” OR “variant” OR “mutation”) AND (“Diabetes” OR “Diabetes-Related ” OR “Diabetic ”) AND . We also manually searched the reference lists of relevant reports to identify additional studies.All selected studies in this analysis met the following criteria: (1) case-control studies; (2) explored the correlation between EPO polymorphisms and diabetic microvascular complications; and (3) contained sufficient data for calculating odds ratios (ORs) and 95% confidence intervals (95% CIs). Exclusion criteria were as follows: (1) studies without Hardy-Weinberg equilibrium (HWE) in the control groups; (2) studies not relevant to diabetic complications or lacking a control population; and (3) studies lacking sufficient data for quantitative analyses.Two investigators (Li H and Xu HP) independently reviewed all articles and extracted available data from individual studies. Any discrepancies were resolved by discussion between these two investigators. The following information was extracted from each eligible study: (1) first author, (2) year of publication, (3) country of origin and ethnicity of study participants, (5) type of diabetes mellitus and complications, (6) genotyping method, (7) number of cases and controls, (8) polymorphism and genotype distribution, and HWE for controls. We assessed the quality of each eligible study according to the Newcastle-Ottawa quality assessment scale (NOS) . QualityP < 0.05 was considered statistically significant. The strength of the association was determined using the following models: allele model , genotype model , dominant model , and recessive model . Subgroup analyses were conducted according to ethnicity, type of diabetes mellitus, and complication. We used the Q-statistic and I2 statistic to evaluate statistical heterogeneity among studies [P ≥ 0.1 and I2 < 50% suggested a lack of heterogeneity among studies. A random-effect model was used through the DerSimonian and Laird method in the presence of heterogeneity (P < 0.1 or I2 > 50%); otherwise, a fixed-effect model based on the Mantel-Haenszel method was employed (P ≥ 0.1 or I2 < 50%). We conducted a sensitivity analysis to assess the stability of the results. Egger's test and Begg's funnel plot were used to evaluate publication bias. Analyses were performed using STATA version 11.0 software .HWE was assessed via Chi-square test in the control populations of each study. Pooled ORs and corresponding 95% CIs were calculated to estimate associations between EPO polymorphisms and diabetic microvascular complications. Z test was used to assess the overall effect and  studies . P ≥ 0.1


EGFR and glioma risk, we performed a case-control study with 394 glioma patients and 298 cancer-free controls in which captured a total of 8 tag single nucleotide polymorphisms of EGFR gene from Xi’an, China. SPSS 19.0 statistical packages, χ2 test, genetic model analysis and SHEsis software platform were analyzed s the variants in EGFR gene associations with glioma risk. For five different inheritance models analyzed, the following genotypes were associated with increased glioma risk. In the codominant model, genotype CC ; In the dominant model, genotype CA and CC , genotype GA and AA ; In the recessive model, genotype CC ; In the additive model, genotype CC , genotype GG  and genotype AA . Our study indicated that 8 mutants located in EGFR gene were risk-conferring factors, larger and different populations with EGFR polymorphisms are required to verify these associations.The Epidermal Growth Factor Receptor gene has been reported to be involved in the progression of gliomas which is one of the deadliest primary brain tumors in humans. To determine potential association between  Glioma is the most common primary central nervous system (CNS) tumors that originate from glia, accounting for approximately 80% of all primary malignant brain tumors, with nearly 20,000 people affected annually in the United States . The surEGFR) is a transmembrane tyrosine kinase in 7p11.2, It is one of the critical oncogenes for several cancers and variably expressed from embryogenesis to adulthood in the normal brain development. For low-grade glioma [EGFR amplification is a hallmark of glioblastoma (GBM). As the most frequent and the most malignant glioma in the adult population [EGFR (EGFRvIII).The Epidermal Growth Factor Receptor  .We assumed that the minor allele of each tSNP was a risk factor compared to the wild-type allele. MAF in cases and controls were showed in Table 2 test, three tSNPs were found to be associated with glioma and risk at a 5% level . Given the number of glioma subjects, we only performed the stratified analysis with more common histologies (astrocytoma and glioblastoma), and also detected that three tSNPs were associated with an increased risk of astrocytoma . However, there was no association of all tSNPs with risk of glioblastoma  were successfully genotyped in all participants, and all of the tested tSNPs were in accordance with Hardy–Weinberg equilibrium (HWE) in control subjects . Table p = 0.024; rs1468727, OR = 2.02, 95%CI: 1.26-3.24, p = 0.007); In the dominant model, genotype CA and CC , genotype GA and AA ; In the recessive model, genotype CC ; In the additive model, genotype CC , genotype GG  and genotype AA . In addition, we observed the association between the EGFR and increased astrocytoma risk ; In the recessive model, genotype CC  and genotype GG . In the additive model, genotype CC , genotype GG .We further analyzed the association between EGFR tSNPs , CGT haplotype and CAT haplotype with an increased risk of astrocytoma   that were associated with glioma risk. In addition, CGT and CAT in block 3 trends to increase glioma risk, which suggested that this gene may contribute to glioma in a case-control study from the Han Chinese population. EGFR (erbB-1), the prototypical member of the erbB receptor family and is frequently expressed in human tissues. The EGFR signaling pathway regulates a wide range of cellular activities associated with cell growth, migration and survival [EGFR gene that is implicated in human tumors, such as breast cancer [EGFR gene may be related to glioma susceptibility, which indicated EGFR polymorphisms play an important role in the carcinogensis of glioma [EGFR gene, which was associated with an increased risk of glioma compared to controls. Previously, in Chinese populations, Liu et al suggested that the T allele of rs1468727 and C allele of rs730437 were associated with decreased glioma risk [p=0.008 ) [p=0.556). A study in Han Chinese population indicated that genotype CC of rs1468727 and rs730437 conferred an elevated risk for glioma [We successfully genotyped 8 tSNPs in survival . Severalt cancer , lung caf glioma . Our res=0.008 ) , but in r glioma , which wEGFR was identified to be associated with an increased risk of glioma, according to allele G association analysis, which is inconsistent with a previous study in a European population, the A allele of rs11506105 had been found to be associated with increased risk of glioma  [The SNP 11506105 in = 0.012) . Our datEGFR tSNPs and risk of glioma was attenuated.Besides the allelic model analysis, we further performed genotypic model analysis to investigate the role of EGFR variants on glioma risk. Our study found that rs730437 and rs1468727 were associated with increased glioma risk in co-dominant, recessive and log-additive models  and HapMap (http://www.hapmap.org/) and identify linkage disequilibrium (LD) blocks within EGFR to get a dense tagging of SNPs, we used Haploview software (http://www.broad.mit.edu/mpg/haploview/) setting the minimum r2 to 0.9 and the minimum minor allele frequency to 5 % in HapMap Chinese Han Beijing residents. Finally we selected candidate 8 tSNPs in the EGFR gene for genotyping, which previously reported being associated with gliomas [Using the public dbSNP  using an exact test among controls. We compared genotype frequencies and allele frequencies between cases and controls using the χ2 test. To estimate the association between the EGFR genetic polymorphisms and risk of glioma, as measured by odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression with adjustment for age and gender [EGFR gene and glioma risk, with SNPstats software (http://bioinfo.iconcologia.net/snpstats/start.htm) [Statistical calculations were made using Microsoft Excel  and SPSS 19.0 statistical package . All statistical tests were two-sided, and art.htm) . For eacFinally, we used Haploview software package (version 4.2) to evaluate the pairwise linkage disequilibrium (LD), haplotype construction, and genetic association at polymorphism loci , 22.


While previous studies have researched in association analyses between TNFα promoter polymorphisms and responses to TNF blockers in spondyloarthritis patients, their results were conflicting. Therefore, we aimed to determine whether TNFα promoter polymorphisms could predict response to TNF blockers and find the source of heterogeneity. Data were extracted and analyzed from published articles and combined with our unpublished data. We found that the greatest potential sources of heterogeneity in the results were gender ratio, disease type, continents, and TNF blockers. Then Stratification analysis showed that the TNFα −308 G allele and the −238 G allele predicted a good response to TNF blockers . However, G alleles of TNFα −308 and −238 could predict the response to etanercept  much more powerfully than the response to infiliximab/adalimumab . TNFα −857 could not predict the response in either subgroup. Cumulative meta-analysis performed in ankylosing spondylitis patients presented the odds ratio decreased with stricter response criteria. In conclusion, TNFα −308 A/G and −238 A/G are more powerful to predict the response to Etanercept and it is dependent on the criteria of response. Spondyloarthritis (SpA) is a group of inflammatory diseases comprising five subgroups: ankylosing spondylitis (AS), psoriatic spondyloarthritis (PsA/Ps), reactive spondyloarthritis, spondyloarthritis associated with inflammatory bowel disease (IBD/CD), and undifferentiated spondyloarthritis. They share common clinical and genetic featuresTumor necrosis factor-a (TNFα) is an inflammatory cytokine that has been implicated in the pathogenesis of spondyloarthritis. TNFα inhibits collagen synthesis in osteoblasts and stimulates the synthesis of proteolytic enzymes such as plasminogen activators and matrix metalloproteinases. In addition, activation of osteoclast production by TNFα promotes bone resorption and joint damage, which results in disease progression of ASIn recent years, TNF-blocking agents have been used widely in the treatment of SpA, especially in AS6910The response of SpA patients to TNFα blockade is associated with several SNPs in the TNFα promoter region. Among these, the polymorphisms TNFα −308 A/G, −238 A/G, and −857 C/T have been studied extensively to determine their association with the response to TNFα blockers in different SpA subgroups 121314151617181920After filtering the studies for several criteria, we selected 10 articles121314151617181920We assessed the association between the TNFα −308 A/G, TNFα −238 A/G polymorphisms and the response to TNF blockers according to the criteria of clinical responses. Because of the limited number of patients were included, all of the prediction did not get significant level and it was required to add to the meta analysis to get more persuasive conclusion. The detailed result was elucidated in et al. and Giuseppe Murdaca et al. did not present this information. All other factors were analyzed in all 10 of the articles. Regression meta-analysis was performed to search for the source of heterogeneity in each article. Age, gender ratio, and disease duration were analyzed in only 8 of the 10 articles, because Lopez-Hernandez The meta-analysis of the selected studies showed an association between the TNFα −308 A/G polymorphism and the response to TNF blockers  . TNFα −22 = 70.9%, p = 0.0081), although no heterogeneity existed in the infliximab/adalimumab  subgroup . Based on these data, we performed further analyses according to the baseline condition of the patients in the etanercept subgroup. We defined longer mean disease duration and higher mean PASI (PASI > 20) as characteristics of a more serious disease condition. In patients with a more serious condition, those with the −857 TT polymorphism had a better response to etanercept (OR = 0.38: 95% CI = [0.15–0.99]), while in patients with a less serious condition, those with the −857 CC polymorphism had a better response to etanercept (OR = 3.23: 95% CI = [1.51–6.89]) . However, marked heterogeneity existed in the etanercept subgroup (I1–6.89]) .Cumulative meta-analysis was performed for 3 articles and our unpublished data to further investigate whether different criteria would influence the association between disease response and the polymorphisms. The selected data were all relevant to the different response criteria in the AS subgroup. Interestingly, OR decreased with stricter response criteria for both ASAS criteria (OR changed from 6.48 to 1.87) and BASDAI criteria (OR changed from 18.33 to 6.78) . The ovePublication bias was first examined qualitatively by funnel plots and estimated by Begg’s and Egger’s tests. The p-values were 0.29 (−308 GG), 0.25 (−238 GG), 0.75 (−857 CC) in Egger’s test and 0.41 (−308 GG), 0.32 (−238 GG), 0.79 (−857 CC) in Begg’s test. Based on these results, we concluded that there was no publication bias in our selected articles.In order to prove that our unpublished data could be integrated to the meta analysis, sensitivity analysis was performed. As described in Some of the studies included in this meta-analysis had identified associations between SpA patient response to TNF blockers and the presence of TNFα −308 A/G, −238 A/G, and −857 T/C polymorphisms, while others had not121314151617181920We found that TNFα polymorphisms could predict the response to etanercept  but not infliximab/adalimumab . Etanercept is a TNFR:Fc recombinant drug made up of two p75 receptors adjacent to the Fc portion of IgG1. Infliximab is an IgG1κ monoclonal antibody from mouse that neutralizes the biological activity of human TNFα25In our cumulative meta-analysis of AS patients, we found that the association between the TNFα −308 A/G polymorphism and the response to TNF blockers was dependent on response criteria. Stricter BASDAI or ASAS criteria decreased OR. Interestingly, although OR decreased with stricter criteria, the 95% confidence interval (CI) became smaller, suggesting that the stricter response criteria was excluding unknown confounders . This in2 < 0.01, data not shown). These findings demonstrate the existence of heterogeneity among different types of Spondyloarthritis.To find the heterogeneity in the selected articles, we performed meta-regression analysis. We concluded that TNF blockers, continents, disease duration, and gender ratio of selected populations were the source of heterogeneity. We also performed further analyses of different disease types. We found that the TNFα −308 A/G polymorphism could predict the response to TNF blockers in Ps patients and CD patients, but not in AS patients . That di2829113132There are several important differences between the present study and two related meta-analyses that had been published previously35Some limitations of the meta-analysis should be taken into consideration. First, more subjects should be included to obtain a more powerful result. Second, in our own data, we concluded that response criteria was one of the sources of heterogeneity. We could not do subgroup analysis in other diseases because data was unavailable. In addition, although in the meta-regression analysis we knew that ethnicity was a source of heterogeneity, we were not able to perform further analysis because most of the selected data were from Caucasian patients and only three were from Chinese patients (including our unpublished data). Considering the confounding effect of response criteria, one article performed the response evaluation at a long termWe performed a search for studies that examined the associations between the responses of SpA patients to TNF blockers and the presence of TNFα −308 A/G, −238 A/G, or −857 C/T polymorphisms. The literature search was performed within the databases PubMed (Language: English) and CNKI (Language: Chinese) and included studies published in Nov 2015 or earlier. We searched for studies containing the following keywords in the databases: ‘tumor necrosis factor’ or ‘TNFα’; ‘polymorphism 308’, ‘polymorphism 238’, or ‘polymorphism 857’; ‘TNF blocker’, ‘TNF therapy’, ‘etanercept’, ‘infliximab’, or ‘adalimumab’; and ‘spondyloarthritis’, ‘SpA’, ‘ankylosing spondylitis’, ‘AS’, ‘psoriatic arthritis’, ‘PsA’, ‘Crohn’s disease’, or ‘CD’. All articles found using the above strategy were read thoroughly. Recessive modeling was performed in order to include most of the articles and obtain a large enough sample size.It was an original article;The study included at least one of the three SNPs of interest ;The article had to have determined genotype frequency.Several additional criteria were used to select articles for this study:Two investigators independently screened titles, abstracts, and full articles.The AS patients in our study were being treated at Guanghua Hospital and Changhai Hospital. This study was approved by the Ethical Committees of the School of Life Sciences of Fudan University and all participants provided written informed consent. AS was diagnosed according to 1984 modified New York criteria. All of the 72 patients were given subcutaneous injections of Etanercept 25 mg twice a week according to standard operating procedure and clinical information was collected at intervals of 0, 2, 4, 8, 12 weeks. In addition the biochemical indexes (including CRP (C-reactive protein)’ ESR (erythrocyte sedimentation rate), etc.), disease duration, HLA-B27 status, and so on. The disease activity of AS patients was evaluated using the Bath AS disease activity index (BASDAI) and criteria of the Assessment of SpondyloArthritis International Society (ASAS). Clinical response was evaluated according to ASASPeripheral blood was collected from blood samples of the patients. Genomic DNA was then extracted form whole blood using a QIAamp DNA Blood Mini kit  and stored at −20 °C immediately. The concentration and quality of isolated DNA was evaluated by a Nanodrop Lite spectrophotometer  according to the optical density (OD) 260/280 and 260/230 measurements. The experiment approaches were carried out in accordance with the approved guidelines.Genotyping of TNF −238, −308 was performed by Sanger Sequencing and the primer was designed by ourselves. Patient genotypes were determined by screening all peak figures using CodonCode Aligner software. The statistical analysis of our unpublished data was calculated by Fisher’s exact test, and values below 0.05 was considered statistically significant.2 > 5% were considered as sources of heterogeneity.A meta-regression model was first used to explore sources of heterogeneity across studiesIn order to further explore the sources of heterogeneity among studies, we stratified the extracted data according to the TNF blocker used. For studies with extreme heterogeneity (p < 0.01), extracted data was further stratified. Since different studies used distinct AS response criteria, such as ASAS20, ASAS40, BASDAI20%, BASDAI50%, cumulative meta-analysis was performed to identify whether results in AS patients were dependent on response criteria.We assessed the Q statistic to determine the heterogeneity among studiesFinally, through creating funnel plots qualitatively and as estimated by Begg’smeta’ package in R (Version 3.2.2: www.r-project.org/). P-values < 0.05 in two-tailed tests were regarded as statistically significant.Statistical analysis was performed by the ‘How to cite this article: Liu, J. et al. TNF-α Promoter Polymorphisms Predict the Response to Etanercept More Powerfully than that to Infliximab/Adalimumab in Spondyloarthritis. Sci. Rep.6, 32202; doi: 10.1038/srep32202 (2016).


We searched PubMed, Embase, and Web of Science databases for eligible whole-brain rs-fMRI studies that measured ALFF differences between patients with PD and healthy controls published from January 1st, 2000 until June 24, 2016. Eleven studies reporting 14 comparisons, comparing 421 patients and 381 healthy controls, were included. The most consistent and replicable findings in patients with PD compared with healthy controls were identified, including the decreased ALFFs in the bilateral supplementary motor areas, left putamen, left premotor cortex, and left inferior parietal gyrus, and increased ALFFs in the right inferior parietal gyrus. The altered ALFFs in these brain regions are related to motor deficits and compensation in PD, which contribute to understanding its neurobiological underpinnings and could serve as specific regions of interest for further studies.There is convincing evidence that abnormalities of regional brain function exist in Parkinson’s disease (PD). However, many resting-state functional magnetic resonance imaging (rs-fMRI) studies using amplitude of low-frequency fluctuations (ALFF) have reported inconsistent results about regional spontaneous neuronal activity in PD. Therefore, we conducted a comprehensive meta-analysis using the Seed-based  Parkinson’s disease (PD) is a common neurodegenerative disorder associated with progressive disability and chronic suffering that lead to a great social burden1345in vivo and numerous studies have sought to unravel the key abnormalities of brain function involved in the pathophysiology of PD91011121316171619201315171819222324252623During the last decade, resting-state functional magnetic resonance imaging (rs-fMRI) has become an established approach for exploring functional neuroanatomy d Mapping (SDM), a well validated meta-analytic tool for coordinate-based neuroimaging data28293031323437293028We aimed at conducting a quantitative and voxel-based meta-analysis of ALFF changes in patients with PD. In addition, we set out to perform meta-regression analyses to examine the confounding effects of demographics and clinical variables on ALFF changes in PD. Furthermore, several complementary analyses of jackknife sensitivity, heterogeneity, and publication bias were performed to explore the most consistent and reliable findings. Here, we used Seed-based 22231913151718192123242526As shown in The jackknife sensitivity analysis  revealedMeta-regression analysis revealed that the PD group with older mean age  exhibited greater ALFFs in the right inferior temporal gyrus extending to the middle temporal, fusiform, and parahippocampal gyri, right inferior parietal gyrus and lesser ALFFs in the bilateral cuneus cortices. Higher average H&Y stage in the PD group (available in 10 datasets) was associated with greater ALFFs in the bilateral precuneus/PCC and right inferior parietal gyrus. Higher average UPDRS-III score in the PD group  correlated with greater ALFFs in the right inferior parietal gyrus and bilateral precuneus/PCC, and lesser ALFFs in the bilateral SMAs. Regression analysis indicated that longer mean illness duration of PD patients (available in 13 datasets) was associated with greater ALFFs in the right fusiform/inferior temporal gyri. The results of these meta-regression analyses are listed in In the present study, we conducted a meta-analysis to identify the most consistent and reliable ALFF changes in PD. Besides the main voxel-based meta-analysis, several complementary analyses, such as jackknife sensitivity, heterogeneity, and publication bias analyses were performed to explore the robustness of the findings. These comprehensive analyses showed that decreased ALFFs in the bilateral SMAs, left putamen, left lateral premotor cortex, and left inferior parietal gyrus and increased ALFFs in the right inferior parietal gyrus were the most consistent and reliable findings in patients with PD compared to healthy controls. Further meta-regression analyses indicated an effect of motor severity on ALFF changes in the bilateral SMAs and right inferior parietal gyrus, and illness severity on ALFF changes in the right inferior parietal gyrus.Cardinal motor impairments characterize PD and dysfunction of the cortico-striatal-thalamic-cortical motor circuits is a fundamental model implicated in its pathophysiology454547484950515253555658Hypoactivity in the SMA in our meta-analysis is well in line with previous task-related and resting-state fMRI, and positron emission tomography (PET) studies515260615261626364656370et al. found a decreased resting-state functional connectivity of the right medial temporal lobe and bilateral inferior parietal cortex within the DMN even in cognitively unimpaired patients with PDInterestingly, the present study observed an asymmetrical activation in the inferior parietal cortex. Analysis of anatomical connectivity using probabilistic tractography shows that the rostral inferior parietal areas were predominantly connected to inferior frontal, motor, premotor, and somatosensory areas involved in higher motor functions, whereas the caudal areas are more strongly connected with posterior parietal, higher visual and temporal areas related to spatial attention and language processing727365666977Other regions are highly heterogenous or not robust detected in the meta-analysis. Besides the unexplained between-study variability of ALFF changes in the right inferior temporal gyrus extending to the middle temporal, fusiform, and parahippocampal gyri (BA 20), brainstem (pons and midbrain), and left cuneus cortex (BA 23), several moderator variables contributed to understanding the source of the heterogeneity. Of these, mean age in the PD group had a significant effect on the ALFF changes in the right inferior temporal gyrus extending to the middle temporal, fusiform, and parahippocampal gyri (BA 20), and bilateral cuneus cortices (BAs 18 and 17). In addition, we noted that the PD group with longer mean illness duration tended to have greater ALFF changes in the right fusiform extending to the inferior temporal gyri (BA 20). We also observed that decreased ALFFs in the left cuneus cortex (BA 23) were replicable only in 10 out of the 14 datasets as revealed by the jackknife sensitivity analysis. Unlike other coordinate-based meta-analytic methods for neuroimaging data, such as the activationlikelihoodestimation6781283030Despite the strengths, several limitations of the present meta-analysis should be acknowledged. First, SDM is a coordinate-based rather than an image-based meta-analytic method, which might lead to less accurate results that is also inherent to other coordinate-based meta-analytic approaches288082172324Using the comprehensive meta-analytic approach, we identified the most consistent and reliable ALFF changes, including decreased ALFFs in the bilateral SMAs, left putamen, left premotor cortex, and left inferior parietal gyrus, and increased ALFFs in the right inferior parietal gyrus in patients with PD compared to healthy controls. The altered ALFFs in these brain regions may be related to motor deficits and compensation in PD, which could serve as specific regions of interest for further studies. Other highly heterogenous or not robust regions, such as right inferior temporal gyrus extending to the middle temporal, fusiform and parahippocampal gyri, brainstem (pons and midbrain), right orbitofrontal cortex, and bilateral cuneus cortices merit further investigations.We comprehensively searched PubMed, Embase, and Web of Science databases for studies published between January 1st, 2000 and June 24, 2016 using the following keywords “Parkinson” OR “Parkinson’s disease”, AND “amplitude of low frequency fluctuations” OR “ALFF”. Other resources, such as the reference lists of included studies and relevant review articles were additionally identified. Studies were included if they satisfied the following conditions: (i) they were published in English as an original article in a peer-reviewed journal; (ii) they reported ALFF results at the whole-brain level for direct comparison between patients with idiopathic PD and healthy controls; (iii) they reported negative results or three-dimensional coordinates in a standardized stereotaxic space for regions with significant differences; (iv) they reported significant results using thresholds for significance corrected for multiple comparisons or uncorrected with spatial extent thresholds. In order to reduce the heterogeneity, studies were excluded if they explicitly indicated patients with PD diagnosed with comorbid neurological or psychiatric disorders  or if they only reported the on-state results. The baseline result was included if the study was longitudinal. In cases where multiple articles were identified to use the overlapped patient datasets, the one with the largest sample size and the most comprehensive information was selected. The quality of each study included in this meta-analysis was assessed according to a 20-point checklist developed for rs-fMRI studieshttp://www.sdmproject.com. The details of the approach have been described elsewhere283132t-values) of ALFF differences between patients with PD and healthy controls from each dataset. Second, an effect-size signed map of the ALFF differences was then separately recreated for each dataset. SDM calculates both positive and negative differences between datasets in the same map3131This voxel-wise meta-analysis was carried out using the SDM software package available at To assess the replicability of the results, a jackknife sensitivity analysis was performed by iteratively repeating the same analysis, excluding one dataset each time28In addition, a heterogeneity analysis was conducted using a random effects model with Q statistics to explore unexplained between-study variability in the results. These analyses were thresholded with the default SDM settings 31In order to evaluate possible publication bias, the Stata/SE 12.0 software for Windows  was used to perform the Egger’s test by extracting the values from the peak coordinates of the voxel-wise meta-analysis between patients with PD and healthy controlsThe Stata/SE 12.0 software was additionally used to meta-analyze mean age and gender distribution in the PD groups and control groups across studies with a random-effects model to test whether there is heterogeneity.Meta-regression analyses were carried out to explore the effects of age, illness severity (Hoehn and Yahr [H&Y] stage), motor severity  Part III [UPDRS-III] score), and illness duration, which could potentially influence the analytic results. P-value less than 0.0005 and cluster extent more than 10 voxels were considered statistically significant31How to cite this article: Pan, P. L. et al. Abnormalities of regional brain function in Parkinson's disease: a meta-analysis of resting state functional magnetic resonance imaging studies. Sci. Rep.7, 40469; doi: 10.1038/srep40469 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.