Meta-analysis of the literature showed that RA was associated with lower AD incidence . On the contrary, MR analysis did not show any evidence of a causal association between RA and AD . Although there is epidemiological evidence for an association of RA with lower AD incidence, this association does not appear to be causal. Possible explanations for this discrepancy could include influence from confounding factors such as use of RA medication, selection bias and differential RA diagnosis.Rheumatoid arthritis (RA) patients have been observed to be at a lower risk of developing Alzheimer’s Disease (AD). Clinical trials have showed no relationship between nonsteroidal anti-inflammatory drug (NSAID) use and AD. The aim of this study was to establish if there is a causal link between RA and AD. A systematic literature review on RA incidence and its link to AD was carried out according to the PRISMA guidelines. Eight case-control and two population-based studies were included in a random effects meta-analysis. The causal relationship between RA and AD was assessed using Mendelian Randomization (MR), using summary data from the largest RA and AD Genome Wide Association (GWA) and meta-analysis studies to date using a score of 62 RA risk SNPs (p < 5 * 10 It impairs an individual’s ability to carry out basic tasks such as bathing and eating. Cognitive function declines, and patients in late stages may be unable to recognize loved ones and become dependent on constant care. Ultimately, AD is fatal1.Information transfer at the synaptic junctions of the brain is compromised in AD patients due to the accumulation of extracellular beta amyloid, which also contributes to neuronal cell death. Inside the neurons, increased levels of tau, a protein that stabilizes microtubules, forms neurofibrillary tangles that block transport of nutrition and necessary molecules throughout the cell. This process also contributes to neuronal cell death2, and memantadine, an NMDA receptor antagonist, in moderate to severe cases. Disease modifying treatments that affect the underlying AD pathogenesis are, as yet, unavailable. The optimal time to administer such treatments may be during the early stages of the pathophysiological process of the disease, before it is clinically apparent3.Pharmacological treatments of AD are limited, with current therapies improving symptoms only transiently. These include cholinesterase inhibitors such as donepezil and rivastigmine, in mild to moderate cases4. Astrocytes and microglia cluster at sites of amyloid beta deposits. Microglial expression of C/EBPβ, a protein that regulates pro-inflammatory molecules such as interleukin 6 (IL-6), interleukin 8 (IL-8), granulocyte colony-stimulating factor, tumour necrosis factor alpha (TNF-α), complement C3 and C-reactive protein (CRP), is significantly increased in the AD cortex compared to the non AD cortex4. Additionally, astrocytes are thought to secrete many of the same pro-inflammatory molecules, although less is known about their role in inflammation in AD4. A study in which lipopolysaccharide (LPS) was used to produce chronic neuroinflammation in rats reproduced some of the features of AD, such as working memory deficit, elevated levels of beta amyloid precursor protein, and temporal lobe pathology associated with cell loss5.Neuroinflammation has been linked to AD pathology, although the lack of pain fibers in the brain means the classic signs of inflammation, such as pain and swelling, are absent6 and a number of conditions such as diabetes7, obesity8, atherosclerosis9, depression10, psoriasis11 and cardiovascular disease12, which have been proposed as risk factors for the development of AD are associated with chronic inflammation13.Neuroinflammation responses can be induced by both CNS-intrinsic factors and systemic influences14. It also has systemic features, and frequently occurs with a variety of co-morbidities, some of which have significant effects on its outcome and have been linked to its inflammatory pathogenesis such as cardiovascular disease17, diabetes mellitus19 and depression21.Rheumatoid arthritis (RA) is an autoimmune disease characterized by synovial inflammation, destruction of bone and cartilage, and autoantibody production, causing progressive disability22. Although, overall the incidence of RA in AD patients has been found to be reduced30 compared to healthy controls, contradictory results have been reported, with some studies reporting an increased incidence of RA in AD patients32. However, the majority of these studies have used a small number of AD and RA patients and there is a lack of more recent, large-scale studies.Paradoxically, RA, itself an inflammatory condition, which is also associated with risk factors for AD, is often considered a negative risk factor for the development of AD33, a recent randomized controlled trial (RCT), the Alzheimer’s Disease Anti-Inflammatory Prevention Trial (ADAPT), has shown that treatment with naproxen and celecoxib did not reduce AD incidence at 7 year follow up34. Additionally, a trial of the TNF-α inhibitor etanercept, another drug used to treat RA, caused no significant changes in cognition, behaviour or global function when recently trialled in AD patients35. A systematic review and meta-analysis published by McGeer et al. in 199622 investigated arthritis itself, in addition to NSAID use, as a protective factor against AD. This study found that arthritis itself was associated with reduced AD incidence. The overall odds ratio, using arthritis as an AD risk factor, was 0.5622.While it has been assumed that the protective effect of RA is due to the Nonsteroidal anti-inflammatory drugs (NSAIDs) that are used to treat it36, Mendelian Randomization (MR) was then employed to formally investigate the causal association of RA with AD.Here, we attempted to dissect the nature of the association between RA and AD by first employing a systematic literature review and an up-to-date meta-analysis of published epidemiological studies. As a fundamental limitation of observational data is that causation cannot automatically be inferred from an association between an exposure and a disease, as the association could be due to unobserved confounding or reverse causation37. It exploits the fact that genotypes are randomly assorted at meiosis, and are thus independent of conventional confounding factors and the disease process. Therefore, genetic variants associated with intermediate traits can be used to provide an unconfounded estimate of the causal association between the intermediate trait and disease outcome, unaffected by reverse causality. This is akin to a “genetically randomized trial” and the genetic variants are known as Instrumental Variants (IVs). The following three assumptions are necessary for a genetic variant to be a valid IV: 1. the variant is predictive of the exposure; 2. the variant is independent of any confounding factors of the exposure—outcome association; 3. the variant is conditionally independent of the outcome given the exposure and the confounding factors. However, MR studies may be potentially confounded by pleiotropy (association of a genetic variant with more than one trait). Whereas vertical pleiotropy  does not necessarily breach the assumptions of MR, horizontal pleiotropy, where the variant affects more than one independent causal pathways, can lead to spurious conclusions about causality38. Nevertheless when multiple genetic variants are used as IVs there is a higher chance that pleiotropic effects might become balanced and causal inference is possible. Additionally, new methods that can give valid estimates in the presence of pleiotropy have been recently developed. We therefore also used, in addition to multi-SNP Inverse-Variance Weighted (IVW) MR , two recently developed methods; Egger-MR39 regression to test for unbalanced pleiotropy and provide a causal estimate of exposure on outcome in its presence, and weighted median MR40 which can give valid estimates even in the presence of horizontal pleiotropy if at least 50% of the weight comes from valid IVs. In the absence of horizontal pleiotropy, all three tests should be consistent.MR is an established tool for probing questions of causality in order to characterize the aetiology of diseaseThe suggestion that it is RA itself that is protective, if found to be true, could contradict the current theory that AD pathogenesis is worsened by inflammatory processes in the periphery.Ten studies were included in the review and meta-analysis of the literature and provided data on 6346 study subjects. Publication dates ranged from 1983–2002, and there were large variations in both study design and sample size. 8 of the included studies were case control, while the remaining 2 were population-based studies . This is supported by both the analysis of the case control studies  and the population-based studies .The meta-analysis results showed that, overall, RA did significantly reduce the risk of developing AD  was low in the population-based studies, where it was estimated to be responsible for 0% of the variability. In the case control studies, it was responsible for an estimated 44.7% of variability. The overall I2 value was 33.2%.Heterogeneity , study type (p = 0.651), quality of study (p = 0.661), age of participants (p = 0.830), percentage of RA in controls (p = 0.986) and whether RA specifically or arthritis was investigated (p = 0.840) indicated that that there was no significant change at the (log)OR of the outcome per unit increase of these covariates. For age, studies were assessed on whether or not the study included participants < 65.Potential publication bias was explored graphically, producing the funnel plot shown in Additional File 2, which indicated a slight presence of asymmetry. Both Begg’s and Egger’s tests were therefore carried out to check for publication bias, and both showed that there was no evidence of bias (p = 0.929 and p = 0.668 respectively). Omitting the included studies one at a time indicated that no individual studies had any significant effect on the overall results.The results of the meta-analysis therefore indicated a consistent protective association of RA and AD.−4), the summary causal estimate from conventional IVW MR showed no evidence to support a causal inverse association between RA and AD   Table , Fig. 2.Finally, the “leave one out” results show that by omitting the included 62 SNPs one at a time, no individual genetic variants seem to have any significant effect on the overall results and after excluding 20% of the SNPs at a time (100000 times) 0.009% of the sensitivity coefficients layed outside the MR 95% CI highlighting that these results are not sensitive to SNP selection.The MR analysis results therefore do not support a causal inverse association between RA and AD.We conducted a comprehensive review and up to date meta-analysis of studies investigating the association of RA with AD, followed by a MR analysis. The findings of these two types of analyses are contradictory Fig. .Figure 3−4), a finding very similar to one proposed by McGeer et al. in 199622 in the earlier meta-analysis . This analysis therefore supports their work even with the inclusion of more recent population-based studies.The overall results of the meta-analysis indicated that RA is associated with lower AD risk with an overall OR estimate of 0.60 . We also found no evidence for unbalanced pleiotropy in the genetic instrument as indicated by the P-value of the MR-Egger intercept (p = 0.51), that provides additional confidence in the MR results.et al. in 199622, and the only one to produce both separate and an overall OR from case control and population-based studies. A more recent meta-analyses included studies that included dementia (and not only AD) as well as results from non peer-reviewed journals42. Attempts were made to ensure lack of publication bias and an influence analysis was carried out to ensure that no one study was predominantly affected the results. Study year, study type, study quality, participant age, RA incidence in controls, and type of arthritis investigated were shown to have no significant effect on the results. Publication bias was also shown to be insignificant.This was the first meta-analysis to investigate the effect on AD development of RA itself (irrespective of NSAID use) since McGeer 43.However, this meta-analysis also had limitations; owing to the limitations inherent to observational studies, heterogeneity was high due to differences in study design and population, despite taking factors that could have influenced it into consideration. Additionally, there were a small number of studies included in the meta-analyses and no eligible studies after 2002. The low number of studies that met the inclusion criteria meant that all were included, regardless of their quality rating using the NOS. Ideally, only those of medium or high quality would be included. However, including the quality of the study as a covariate did not influence the results of the meta-analysis. Additionally, the majority of the included studies were case control and utilized small study samples; however, the results of the only two longitudinal population-based studies included also showed a relationship between RA and AD. Ideally, more population-based studies, which confer advantages such as larger sample size, a more representative sample and the ability to estimate the prevalence rate of risk factors in the target population, would be carried out and included in a meta-analysis on this topic. In population-based studies, cofounders to exposures and outcomes can also be evaluated, reducing biaset al.27), the presence of RA was confirmed using structured interview or questionnaire. Ideally, it would be formally diagnosed by a clinician. Additionally, in studies that may have included osteoarthritis (“arthritis” was investigated), incidence in both cases and controls was higher than those that investigated RA alone, as expected. However, the variation of RA proportion in controls was not found to have a significant effect on the results. Additionally, incidence in cases correlated highly with that in controls .Another possible limitation of the meta-analysis was the large variation in RA incidence in controls given across the studies included in the meta-analysis analysis, ranging from 3.8–68%. While this could be due to a number of factors, including differing sources of controls, different sample sizes and different methods of diagnosing RA, it is worth considering as a factor that may have affected the results. In all but one of the studies  were generated for both of them, and their interaction was found to be non-significant (p = 0.10)29. Importantly, year of study may affect the treatment taken by included RA patients. Pharmacological therapies for RA have evolved over the past 25 years, with biologic response modifier treatments such as tumor necrosis factor alpha (TNF-α) inhibitors becoming available in the late 1990s44 – after most of the studies in this review were carried out. The antifolate drug methotrexate has become the initial treatment in many RA patients, and can be used as a monotherapy without the addition of NSAIDs or any other drugs44. The wide variety of RA treatments available today means that participants of earlier studies were probably more likely to be taking NSAIDs to treat their disease, while participants in later studies were possibly taking newer drugs . This is particular relevant as this meta-analysis also suffered from lack of recent data, with only three included studies having been carried out since the year 2000. Additionally, of the studies that did not investigate NSAID use and arthritis separately, there is no way to confirm that the RA patients involved were not taking NSAIDs, meaning that this meta-analysis did not investigate RA incidence completely independent of NSAID use.The links between RA and AD have previously been described as due to a protective effect of NSAIDs. Both RA/arthritis and NSAID use were investigated as risk factors for AD in several studies included in this analysis. Most notably, Lindsay 45 investigated the number of AD deaths in RA patients, compared to the entire Finnish population of age 55+. They found that 1.2% of RA patients (2/167) were diagnosed with AD at death, compared to 5.4% (227/4204) of the general population. A 1990 study by McGeer et al.33 was also excluded; this study found that out of 923 patients in RA clinic, only 4 (0.4%) had AD, while 2/409 (0.5%) patients at AD clinic had RA. They compared this to the incidence of AD in the general population, considered in this study to be 2.7%. Recently, a large population study by Bauer et al.46 compared comorbidity including arthritis in 9,139 elderly German individuals with dementia and 28,614 German age- and gender-matched control subjects aged 65 years and older. They reported that the presence of arthritis was less frequent in dementia patients  although this association was less strong when only community-living individuals were examined . However, this study was also excluded from our meta-analyses as it included patients with other types of dementia in addition to AD, such as vascular dementia. Similarly, a more recent study investigating the association between several chronic inflammatory disorders, including RA and anti-inflammatory drugs, and all-cause dementia was also excluded from our meta-analysis47. This study showed that RA, amongst other inflammatory disorders, was associated with higher dementia risk only in treated patients, suggesting a modifiable role of drug therapy in the association between inflammation and dementia risk and it also reported that combined glucocorticoid and NSAID anti-inflammatory therapy was associated with lower risk of dementia among individuals with rheumatoid arthritis.Finally, we also excluded a number of studies that did not match our criteria. A 1994 study by Myllykangas-Luosujarvi and Isomakiet al.48 was the only population study to show an increased risk for AD and dementia amongst RA patients. However, this study was not included in our meta-analysis as it differed slightly from the others in that patients with mild cognitive impairment (MCI) were included in addition to AD patients and ordinal regression analysis results were reported48 instead of an OR of AD risk in RA compared to controls. When we repeated our meta-analysis including the ordinal regression results by Wallin et al.48, we observed no association between RA and AD for the population-based cohorts . However there was no overall difference to the overall meta-analysis result . With the exception therefore of the study by Wallin et al.48 these population-based studies also support the finding of the meta-analysis, although an overall OR comparable to that of the other studies was not produced due to variations in outcomes investigated.Finally, a recent study by Wallin The MR study has a number of obvious strengths. MR studies minimize bias inherent to observational studies such as confounding, regression dilution bias and reverse causation. However, MR studies are susceptible to bias from pleiotropy (association of genetic variants with more than one variable). Although vertical pleiotropy does not necessarily breach the assumptions of MR, horizontal pleiotropy could invalidate the MR assumption of the genetic variant only affecting the outcome conditional on the exposure of interest, and potentially lead to biased causal estimates. Although the inclusion of multiple variants in MR analysis typically leads to increased statistical power it also results in the potential inclusion of pleiotropic genetic variants that are not valid IVs. To minimize horizontal pleiotropy we employed a weighted median estimator, which provides valid estimates even if 50% of the SNPs are not valid instruments and we employed MR-Egger regression to provide a test for unbalanced pleiotropy and a causal estimate of exposure on outcome in its presence. Our results using all three approaches were consistent, and the MR-Egger approach showed no evidence for unbalanced pleiotropy as indicated by intercept P-value. Even if MR-Egger results in loss of precision and power, our weighted median estimator results were also very similar to the IVW estimator providing additional confidence for these associations.37. For example, variants may be associated with RA by various mechanisms, such as chronic inflammation or immune dysregulation. A MR estimate constructed using variants associated with RA through chronic inflammation more closely represents the causal effect of intervening on AD via inflammatory processes. Differences in the causal estimates using genetic variants associated with different mechanisms may be informative in understanding the aetiology of the disease, and may highlight specific mechanisms to prioritize for pharmacological intervention37.Another possible limitation to this MR study is the strength of our IV. Although we used 62 established RA SNPs, a score including more RA associated SNPs would have more power to detect a causal effect. To this end, we also repeated our analyses including SNPs associated with RA below genome-wide significance  but results were almost identical. Also, larger RA studies and meta-analyses are necessary in order to obtain stronger estimates with narrower confidence intervals. Finally, a number of additional analyses can be performed. For example, genetic variants can be categorized as relating to different disease mechanisms and separate MR estimates can be obtained using each category of variantsOur study shows that although there seems to be an inverse association between incidence of RA and AD based on observational studies, MR analysis points to lack of a causal association. Examining the results from different methods that make different assumptions  provides a sensitivity analysis that either adds to or questions the robustness of a finding from a MR investigation. Here, the same result is reported across all methods, making the findings more plausible than if the methods gave contradictory findings. The protective associations therefore observed in the observational studies could be due to bias inherent to observational studies such differential RA diagnosis, type of medication, small number of small size studies and selection bias. Further, well designed epidemiological studies and MR studies utilizing larger number of instruments and individuals could help draw more confident conclusions about the association of the two diseases.49.This review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) GuidelinesAlzheimer*, dementiaRheumatoid arthritis, risk factorIncidence, prevalence, epidemiolog*A search in October 2016 in a) MEDLINE and b) the Cochrane Library was carried out using the following search terms:Combination of these terms (1 ∩ 2 ∩ 3), resulted in 7587 publications. Initial screening, which searched for publications relevant to the aims of this study, resulted in 16 publications being retained for evaluation. Their references were then searched for further relevant publications. Further screening according to the inclusion and exclusion criteria of this review (described below) resulted in 10 studies being included.Publication in EnglishPublication in a peer-reviewed journalFull text availabilityDescription of empirical research methods relevant to the aims of this reviewComparison of the variable studied against a control groupInvestigation using RA as risk factor for ADThe use of clinically diagnosed AD patients. Studies investigating other forms of dementia such as mild cognitive impairment (MCI) and vascular dementia were not includedIn order to be included in this review, studies were selected on the basis of their:The search process is summarised in Supplementary Figure Methodological quality assessment was carried out on each of the 12 included studies.50.Studies were assessed using the Newcastle-Ottawa Quality Assessment Scale (NOS). Using this scale, studies are assessed and awarded stars based on three domains: selection of study groups (maximum 4 stars), comparability of study groups (maximum 2 stars), and ascertainment of exposure (maximum 3 stars). Slightly different versions of the scale are used for case control and population-based studiesA study with a score of 5 or less was considered of low quality, a score of 6–7 was considered medium quality, and a score or 8 or 9, high quality. The quality results are shown in Additional File 1. The use of the NOS resulted in 2 studies being deemed high quality, 6, of medium quality and 2 of low quality.Random-effects meta-analysis was performed using the “metan” command in STATA 12 . Subgroup analysis was undertaken first, based on the type of study (case-control or population-based study), and then the results of these were combined to produce an overall odds ratio (OR).2, a measure of the proportion of the total variability that can be explained by study heterogeneity. This was assessed first for each group of studies (case control and population-based), and then overall.Heterogeneity of studies was assessed using Cochran’s Q statistic to calculate Higgins and Thompson’s ITo estimate potential bias, the influence of individual studies on the summary effect estimate was first investigated using the “metainf” command. This performs an influence analysis, in which the meta-analysis estimates are computed omitting one study at a time.A funnel plot was used to visualize the variation of each study (using the “metafunel” command) followed by the Begg’s and Egger’s tests to investigate for funnel-plot asymmetry in meta-analysis (using the “metabias” command). If individual studies were found to have a large influence or introduce potential bias, analysis was repeated omitting them and results were compared.Finally, the “metareg” command was used to perform meta-regression analysis to investigate the associations between the outcome of the study (AD or control) and study characteristics that may result in study heterogeneity such as study year, study type (case control or population-based study), study quality, age of study participants, incidence of RA in controls and whether arthritis or RA specifically was investigated.8 case control and 2 population-based studies were included in the meta-analysis.51 and summary data from the International Genomics of Alzheimer’s Project (IGAP)52, the largest GWA study and meta-analysis of AD reported to date. Of the 102 SNPs (101 loci) reported to be associated with RA by Okada et al.51, we excluded 2 SNPs located on the X chromosome as there were no available IGAP data2, 2 SNPs that were not directly genotyped or imputed, 7 SNPs that were not directly genotyped or imputed and which were additionally not associated with RA in individuals of European ancestry at genome-wide significance (p < 5 * 10−8) in combined meta-analyses and 1 SNP that was not directly genotyped or imputed and for which there was no available summary data in Okada et al. for individuals of European ancestry in combined meta-analyses. Of the 90 SNPs (89 loci) that were directly genotyped or imputed, 28 SNPs were further excluded as they were not associated with RA at genome-wide significance (p < 5 * 10−8). We therefore used 62 SNPs (61 loci) that were directly genotyped or imputed and which were associated with RA in individuals of European ancestry at genome-wide significance (p < 5 * 10−8) in combined meta-analyses  study and meta-analysis to dateet al.51 in an IVW meta-analysis  applying the Johnson formula described by Burgess et al.53. The delta method was used to approximate the standard error. We used only the first-order term from the delta expansion here; further terms were not considered because they did not affect estimates or standard errors.The instrumental variable (IV) estimate from summary data was then obtained by summing the log Odds Ratio (log OR) of the individual logistic regression analyses of all 61 SNPs against AD and weighing this with the summary of the estimates of each SNP obtained from Okada Although the inclusion of multiple variants in a MR analysis typically leads to increased statistical power, it also presents challenges such as the potential inclusion of pleiotropic genetic variants that are not valid IVs. Whereas vertical pleiotropy does not necessarily breach the assumptions of MR, horizontal pleiotropy can lead to spurious conclusions about causality rendering the IVW estimator inefficient, especially when the precision of the individual estimates varies considerably.39 that tests for presence of, and accounts for, unbalanced pleiotropy by introducing a parameter for this bias. MR-Egger tests the hypothesis that the strength of the IV estimates of individual SNPs is symmetrically distributed around the point estimate. Symmetrical distribution suggests that pleiotropic effects, if present, are balanced and should not systematically bias the estimate of causal effect. Briefly, MR-Egger performs a weighted linear regression of the gene-outcome coefficients on the gene-exposure coefficients. The slope of this regression represents the causal effect estimate and the intercept can be interpreted as an estimate of the average  pleiotropic effect across the genetic variants. MR-Egger regression replaces the second and third IV assumptions with the InSIDE assumption that states that the individual SNP effects on the exposure are independent of their pleiotropic effects on the outcome39.To account for unmeasured horizontal pleiotropy, we performed MR-Egger analysis, an alternative summary data analysis method40. We assume that no single IV contributes more than 50% of the weight, otherwise the 50% validity assumption is equivalent to assuming that this IV is valid. Analogously to the IVW method, we adopted the inverse of the variance of the ratio estimates as weights, as previously suggested40. The weighted median estimator has the advantage of retaining greater precision in the estimates compared to MR-Egger40.We additionally used the weighted median estimator, a method using summary data that offers protection against invalid instruments and provides a consistent estimate of causal effect if at least 50% of the weight comes from valid IVsA number of sensitivity analyses were finally performed to examine the stability of the summary causal estimate. Firstly, we performed a “leave one out” analysis to further investigate the possibility that the causal association was driven by a single SNP. We further we examined the stability of the summary causal estimate by repeatedly  excluding ~20% SNPs (12 SNPs), with replacement, from the instrument chosen at random in each cycle and collecting the resulting IV estimates. When more than 5% of the sensitivity coefficients lay outside the CI from the normal distribution of the estimate with complete data, there was evidence that the result was sensitive to SNP selection.All MR analyses were performed in R 3.3.1.We have used publicly available data for this work.Supplementary Material


HOTAIR has been demonstrated to be involved in carcinogenesis and progression of various human cancers. Previous studies have investigated the potential association between HOTAIR polymorphisms and cancer risk in Chinese population. However, the results remain conflicting. Therefore, for the first time, we conducted a meta-analysis to derive a more precise estimation of these associations for Chinese. PubMed, Embase, CNKI and Wanfang databases were systematically searched. Odds ratios with 95% confidence intervals were applied to assess the association between rs920778, rs4759314, rs7958904, rs874945 and rs1899663 polymorphisms of HOTAIR and cancer susceptibility. Heterogeneity, sensitivity analysis and publication bias were conducted to measure the robustness of our findings. A total of 21 eligible studies comprising 12,278 cases and 14,532 controls were analyzed. The pooled data showed that rs920778 polymorphism was significantly associated with an increased cancer risk in all five genetic models in Chinese population. As for rs4759314 and rs874945 polymorphisms, similarly increased risks were found in specific genetic models and stratified groups. However, significant decreases in cancer risk were observed for rs7958904 in the total population, as well as in subgroup analyses. In addition, lack of association was detected between rs1899663 polymorphism and cancer susceptibility. In summary, our meta-analysis implicates possible relationship between HOTAIR polymorphisms and cancer risk in Chinese population.As a well-known long non-coding RNA,  HOTAIR, an lncRNA located on chromosome 12q13.13, is coded from the homebox C gene (HOXC) locus [HOTAIR could specifically interact with polycomb repressive complex 2 (PRC2) and LSD1/CoREST/REST complex, in turn induce its relating methylation of histone H3K27 and demethylation of histone H3K4 respectively, and consequently result in the alteration of genes expression profile [HOTAIR has been reported in a variety of human cancers such as breast cancer, gastric cancer, colorectal cancer and liver cancer [HOTAIR was also shown to be involved in the progression of multiple types of cancers, indicating that HOTAIR might serve as a useful biomarker for tumorigenesis and progression [Long non-coding RNAs (lncRNAs), as a type of transcribed RNAs which are longer than 200 nucleotides with no protein-coding capacity, were initially claimed to be a fake transcriptional noise , 2. NowaC) locus . It has  profile , 9. The r cancer –13. In agression , 14–16.HOTAIR locus have been identified [HOTAIR polymorphisms and cancer risk in Chinese population [HOTAIR with the risk of cancers including gastrointestinal cancers [HOTAIR polymorphisms and cancer risk in Chinese population. To our knowledge, this is the first meta-analysis which investigates the association for Chinese.Several single nucleotide polymorphisms (SNPs) located in entified , 18. Amopulation . From th cancers , estroge cancers –27, thyr cancers  and oste cancers . HoweverThe screening process of the studies was shown in Figure HOTAIR rs920778 polymorphism and cancer risk are presented in Table P = 0.001; TT vs. TC+CC: P = 0.018; TC+TT vs. CC: P = 0.013; TT vs. CC: P = 0.215; TC vs. CC: P = 0.041).Thirteen eligible studies including 6,854 cases and 8,477 controls were recruited in the meta-analysis. The results for the association between HOTAIR rs4759314 polymorphism and cancer risk was observed in dominant and heterozygous models for Chinese  available genotype distribution data for calculating the odds ratios (ORs) with 95% confidence intervals (CIs). Reviews, letters, conference abstracts, duplicate studies and studies without sufficient genotype information were excluded. In addition, we finally selected the study with larger sample size from duplicate publications.Studies were all selected according to the following criteria: (1) case-control design study; (2) evaluating the association between P value for Hardy-Weinberg equilibrium (HWE) in the control group. Disputes were resolved through group discussion.The following data were extracted by two independent investigators: first author, publication year, source of controls, sample size, genotype frequency, genotyping methods, age and sex matched status, type of cancers, HOTAIR polymorphisms and cancer susceptibility in Chinese population. For the rs4759314 polymorphism, the pooled ORs were estimated by allelic (G vs. A), recessive (GG vs. GA+AA), dominant (GA+GG vs. AA), homozygous (GG vs. AA) and heterozygous (GA vs. AA) models. As for rs920778, rs7958904, rs874945, and rs1899663 polymorphisms, similar five genetic models were assessed. Subgroup analyses based on source of controls, type of cancers, genotyping methods, HWE status of controls and case-control matched status were subsequently performed. HWE was examined by chi-square test in the controls. The I2 statistic was used to evaluate the heterogeneity between studies. If I2 > 50%, significant heterogeneity was found and the random-effects model should be applied. Otherwise, the fixed-effects model should be used. Sensitivity analysis was conducted by sequentially omitting each single study to evaluate the stability of our results. Publication bias was assessed by both visual inspection of funnel plot and Egger's test. The STATA software 12.0  was used for all the statistical analyses. P < 0.05 was considered to be statistically significant.The crude ORs with 95% CIs were calculated to determine the relationship between the


In order to explore the effect of MTHFR SNPs on non-small cell lung cancer (NSCLC), we selected MTHFR tagging single nucleotide polymorphisms (SNPs) and carried out a case-control study to determine the potential relationship of MTHFR SNPs with NSCLC risk. Our study consisted of 521 NSCLC patients and 1,030 non-cancer controls. MTHFR SNPs were genotyped by SNPscanTM genotyping assay. Using four genetic models , the genotype frequencies were compared using the chi-squared (χ2) test. Crude/adjusted odds ratios (ORs) with their 95% confidence intervals (CIs) were used to assess the difference for the genotype distribution. We found that MTHFR rs1801133 G>A polymorphism decreased the risk of overall NSCLC. In a subgroup analysis, MTHFR rs1801133 G>A polymorphism also decreased NSCLC risk in female, < 60 years and never smoking subgroups. However, we identified that MTHFR rs4845882 G>A polymorphism was associated with the development of NSCLC in female subgroup. In addition, MTHFR rs9651118 T>C polymorphism increased the risk of NSCLC in < 60 years, never smoking and BMI < 24 kg/m2 subgroups. In conclusion, the current study highlights MTHFR rs1801133 G>A variants decreases the risk of NSCLC. Nevertheless, MTHFR rs4845882 G>A and rs9651118 T > C polymorphisms may be associated with NSCLC susceptibility. Well-designed large-scale studies are needed to confirm these findings and explore the interactions of gene-gene and gene-environment involved in MTHFR SNPs and NSCLC.Previous reports implicated 5,10- Lung cancer (LC) caused by multiple risk factors is one of the common malignancies worldwide. With very complex biological characteristics and high degree of invasiveness, it is difficult to diagnose at an early stage and lack of very effective treatment at an advanced stage. Thus, LC is a common public health problem with a poor prognosis. LC involves two major subtypes, such as small cell LC and non-small cell LC (NSCLC). In addition, NSCLC cases account for most of the total LC cases. The increasing incidence of NSCLC is closely related to tobacco consumption, air pollution, cooking fumes, asbestos and other environmental factors . HoweverFolic acid, or 5-methyltetrahydrofolate, is a cofactor in the metabolism of homocysteine to methionine . 5,10-ethttp://www.ncbi.nlm.nih.gov/SNP), such as rs1801131, rs1801133, rs1537514, rs9651118, rs1537516, rs3753584, rs4845882, rs4846048, rs2066462 and rs3737967 polymorphisms, etc. A number of case-control studies focused on the association between MTHFR polymorphisms and the risk of LC . Wang et al. reported there was no significant correlation between MTHFR rs4845882 G>A polymorphism and gastric cardia carcinoma (GCA) risk    was usedparisons .


Purpose. This work aimed to synthesize the results of recent meta-analysis focusing on polymorphism in inflammatory mediators and its relation with the risk of periodontitis development. Materials and Methods. A systematic search was conducted using databases for publications prior to October 2016. Three examiners extracted data from articles with a clear association between polymorphisms in the inflammatory mediator gene and the development of periodontitis through meta-analysis using the fixed or randomized statistical models to calculate the Odds Ratio with values of P < 0.05 considered significant. Results. A total of 13 meta-analysis articles with 25 polymorphisms in seven interleukins , three cellular receptors , and five inflammatory mediators , with a total of 71,531 participants, approaching different classifications of the disease. Conclusion. The study demonstrated that polymorphisms in the IL-1A, IL-1B, IL-6, IL-10, MMP-3 (chronic form), and MMP-9 (chronic form) polymorphisms were significantly associated with the risk of developing periodontitis, whereas other polymorphisms in the IL-4, IL-8, IL-18, Fcγ, COX-2, MMP-2, MMP-3 (aggressive), MMP-8, and MMP-9 (aggressive) polymorphisms had no significant association with risk of developing periodontitis. Periodontitis is a multifactorial inflammatory disease and both environmental and genetic factors play a major role in the progression of the disease with consequent tissue destruction around the dental roots, and alveolar bone is associated with systemic alterations such as diabetes , changesThe high risk in the progression of periodontitis is directly associated with the biofilm found in the gingival sulcus, in which both amount and presence of specific species of bacteria represent risk factors . HoweverThe evidence that periodontitis is a complex disease of multifactorial etiology has resulted in the development of focused researches in the identification of molecular markers capable of determining the risk of disease development .γ family (FCGRs), and cyclooxygenase- (COX-) 2 and matrix metalloproteinase (MMP) are considered key factors in the progression of periodontitis recruitment, differentiation and activation of B lymphocytes, inflammatory infiltrate, and stimulation of osteoclasts. Polymorphisms in these molecules have been suggested as factors that influence the risk of developing the disease [Recently, investigations on factors of susceptibility to periodontitis have been gaining focus on genes of immunoregulatory molecules, such as cytokines, chemokines, membrane surface receptors, and antigen recognition proteins . Cytokin disease –11, alth disease  or genom disease  have sou disease .In this perspective, meta-analysis studies have been increasingly used in genetic analysis for their ability to associate data by canceling the so-called short effects that studies with reduced sample numbers lead to . Meta-anGiven such reliability in meta-analysis studies, this study aimed to describe the association between polymorphisms in inflammatory mediators and the susceptibility to periodontitis based on available meta-analysis in the literature.This meta-analysis followed the recommended PRISMA  statement .Search Strategy. A systematic search in the Cochrane Library, Google Scholar, and Pubmed databases was performed for collection of studies previously published on October 2, 2016. A combination of the specific descriptors was used: “interleukin, or cytokine, or inflammatory Mediator”, “periodontitis, or periodontal disease, or chronic periodontitis, or aggressive periodontitis”, “polymorphism, or genetic variation”, and “meta-analysis”, as seen in Three independent investigators reviewed all abstracts of the papers and their references to identify possible relevant studies. There was no restriction of language in the collection of articles. When the search resulted in studies of different authors which were published in distinct years but which addressed the same polymorphism the most recent study was selected for inclusion analysis and subsequent data extraction.Inclusion Criteria. In order to be included in the research, the studies should show a clear association between polymorphisms in the inflammatory mediator gene and the risk in the development of periodontitis through meta-analyses. Following this, standard methods with allocation of patients in a case and control group data presented were dichotomous, using the fixed-effect or random-effect statistical models to calculate the Odds Ratio (OR) with values of P < 0.05 considered significant. Studies outside these criteria were excluded.Data Extraction. Two calibrated investigators performed the data collection and discussion following a standardized form by first author, year of publication, polymorphism analyzed, number of cases and controls, OR value, and type of periodontitis analyzed.γ receptors: FCGR2A, FCGR3A, and FCGR3B), and five inflammatory mediators  comprised 71.531 participants (32.011 patients and 39.520 controls), as shown in At the end of the systematic search  13 meta-In the pathophysiology of periodontitis, several inflammatory mediators contribute to damage of periodontal sites, destruction of supporting connective tissue, and loss of alveolar bone. An example of such mediators is interleukin 1, a soluble molecule involved in the host's immune response against microbial agents by signalling to neutrophilic infiltrate and tissue destruction due to increased secretion of matrix metalloproteinases .P = 0.87).Five meta-analysis studies were found for polymorphisms in two IL-1 variants (IL-1A and IL-1B) , 18–21. P = 0.98). Aggressive and chronic periodontitis have distinct pathophysiological mechanisms; chronic and aggressive periodontitis can not be differentiated as to their histopathological changes [Such contradictory results can be explained by the greater heterogeneity in the genetic pattern of the Brazilian population . Wang et changes  or type  changes . However changes  and an i changes ; so appr changes .The polymorphisms −511 C/T and +3954 C/T in the IL-1B gene were not significantly associated with the risk of developing either chronic  or aggreIn IL-4, a proinflammatory cytokine is capable of inducing apoptosis of osteoblasts thus contributing to the progression of alveolar bone loss  and induInterleukin-6 (IL-6) is a potent mediator of bone resorption capable of stimulating macrophages and osteoclasts with increased tissue damage in both types of periodontitis evaluated . The metP < 0.001, P = 0.40, resp.), because between-study heterogeneity was not evident. This meta-analysis evidenced that the IL-8 −251A/T polymorphism is related with a decreased risk of periodontitis in a Brazilian mixed population and an increased risk of periodontitis in an Asian population. The IL-8 gene has q13-q12 localization on chromosome 4, where the −251 A/T variant is related to an increase in the transcriptional activity of this cytokine [ Porphyromonas gingivalis and Tannerella forsythia [In another meta-analysis study addressing two polymorphisms in the IL-8 gene , it was cytokine . The eviorsythia , bacteriorsythia .IL-10 is a suppressor cytokine that regulates negatively the immunological response of monocytes and macrophages. The meta-analysis  that evaData from the meta-analysis on polymorphisms in this interleukin corroborates with previously published data where there was also no association of these genetic variations with periodontitis, in both forms . It has Although there was no significant association in the evaluation calculations of the polymorphisms in the IL-18 gene and periodontitis, the meta-analysis developed by Li et al.  found a The findings suggest that the FCGR2A H131R allele and the FCGR3A F158V polymorphisms may be associated in the development of periodontitis. However, the associations between FCGR2A, FCGR3A, and FCGR3B polymorphisms and chronic periodontitis are susceptible due to a causal association or imbalance with the true polymorphism causing the disease not yet determined . AlreadyEvaluating polymorphisms in COX-2 and MMP-2, MMP-3, MMP-8, and MMP-9 genes, two meta-analysis are available in literature . There aAs showed in γ receptors: FCGR2A, FCGR3A, and FCGR3B), and five inflammatory mediators  which comprised 71.531 participants (32.011 patients and 39.520 controls), approaching different classifications of the disease and demonstrating that polymorphisms in the IL-1A, IL-1B, IL-6, IL-10, MMP-3 (chronic form), and MMP-9 (chronic form) genes were significantly associated with risk of development of the disease, while other polymorphisms in the IL-4, 18, Fcγ, COX-2, MMP-2, MMP-3 (aggressive form), MMP-8, and MMP-9 (aggressive form) receptors were not significantly associated with periodontitis development.In conclusion, this systematic review consisted of 13 meta-analysis articles with 25 polymorphisms in seven interleukins , three cellular polymorphisms (Fc


CXCL5 is a member of the CXC-type chemokine family, which has been found to play important roles in tumorigenesis and cancer progression. Recent studies have demonstrated that CXCL5 could serve as a potential prognostic biomarker for cancer patients. However, the prognostic value of CXCL5 is still controversial.We systematically searched PubMed, Embase and Web of Science to obtain all relevant articles investigating the prognostic significance of CXCL5 expression in cancer patients. Hazards ratios (HR) with corresponding 95% confidence intervals (CI) were pooled to estimate the association between CXCL5 expression levels with survival of cancer patients.A total of 15 eligible studies including 19 cohorts and 5070 patients were enrolled in the current meta-analysis. Our results demonstrated that elevated expression level of CXCL5 was significantly associated with poor overall survival (OS) , progression-free survival  and recurrence-free survival  in cancer patients. However, high or low expression of CXCL5 made no difference in predicting the disease-free survival  of cancer patients. Furthermore, we found that high CXCL5 expression was associated with reduced OS in intrahepatic cholangiocarcinoma  and hepatocellular carcinoma . However, there was no significant association between expression level of CXCL5 with the OS in lung cancer  and colorectal cancer  in current meta-analysis.In conclusion, our meta-analysis suggested that elevated CXCL5 expression might be an adverse prognostic marker for cancer patients, which could help the clinical decision making process. Despite great improvements in early detection, surgical techniques, chemotherapy, radiotherapy, biological treatment and multidisciplinary treatment in recent years, cancer is still a major public health problem globally, which is associated with high morbidity, mortality and economic burden . It is eChemokines are chemotactic cytokines that could regulate the migration of immune cells into damaged or diseased organs in response to pro-inflammatory stimuli . AccordiCXCL5, also known as epithelial-derived neutrophil-activating peptide 78 (ENA78), is originally discovered as a potent chemoattractant and activator of neutrophil function. Through binding to its receptor CXCR2, CXCL5 could induce the chemotaxis of neutrophils, promote angiogenesis, and remodel connective tissue . AccumulThe present review was performed in accordance with the standard guidelines for meta-analysis and systematic reviews of tumor marker prognostic studies , 29. TheStudies included in this analysis had to meet the following inclusion criteria: (1) patients were pathologically diagnosed with any type of human cancer. (2) CXCL5 expression levels were determined in human tissues or plasma samples. (3) Patients were divided into two groups according to the expression levels of CXCL5, the relationship between CXCL5 expression levels with survival outcome was investigated. (4) Sufficient published data or the survival curve were provided to calculate hazard ratios (HR) for survival rates and their 95% confidence intervals (CI). Exclusion criteria were as follow: studies using non-human samples, studies without usable or sufficient data, laboratory articles, reviews, letters, case reports, non-English or unpublished articles and conference abstracts. All eligible studies were carefully screened by two researchers (Binwu Hu and Huiqian Fan), and discrepancies were resolved by discussing with a third researcher (Xiao Lv).Two investigators (Binwu Hu and Huiqian Fan) extracted relevant data independently and reached a consensus on all items. For all eligible studies, the following information of each article was collected: author, year of publication, tumor type, samples detected, expression associated with poor prognosis, Newcastle–Ottawa Scale (NOS) score, method of obtaining HRs, characteristics of the study population , follow up (month)), endpoints, assay method, cut-off value and survival analysis. For endpoints, overall survival (OS), disease-free survival (DFS), progression-free survival (PFS) and recurrence-free survival (RFS) were all regarded as endpoints. We employed HR which was extracted following a methodology suggested previously to evaluate the influence of CXCL5 expression on prognosis of patients . If possQuality of all included studies was assessed independently by two researchers (Binwu Hu and Huiqian Fan) using the validated Newcastle–Ottawa Scale, and disagreements were resolved through discussion with another researcher (Songfeng Chen). This scale uses a star system to evaluate a study in three domains: selection of participants, comparability of study groups, and the ascertainment of outcomes of interest. We considered studies with scores more than 6 as high-quality studies, and those with scores no more than 6 as low-quality studies.2 statistics. A p value less than 0.10 or an I2 value larger than 50% were considered statistically significant. The fixed-effect model was used for analysis without significant heterogeneity between studies . Otherwise, the random-effect model was chosen. To explore the source of heterogeneity, subgroup analysis and meta-regression were preformed through classifying the included studies into subgroups according to similar features. We also conducted sensitivity analysis to test the effect of each study on the overall pooled results. The publication bias was evaluated by using both Begg’s test and Egger’s test. A p value less than 0.05 was considered statistically significant.Statistical analysis was performed using Stata Software 14.0 . Pooled HRs (high/low) and their associated 95% CIs were used to analyze the prognostic role of CXCL5 expression in various cancers. The heterogeneity among studies was evaluated using Cochran’s Q and IAccording to our search strategy, the initial search algorithm retrieved a total of 554 studies. The following studies were excluded: duplicates n = 196), review (n = 14), patent (n = 9), meeting abstract (n = 64), studies describing non-cancer topics (n = 27), studies describing non-CXCL5 topics (n = 126), studies belonging to basic research (n = 75), studies lacking relevant data (n = 26) and non-English articles (n = 2). Eventually, 15 studies meeting the inclusion criteria were included in this meta-analysis. The screening process and results are shown in Fig. 96, revieThe main characteristics of the included studies are shown in Table 2 = 65.1%; p < 0.001), we further conducted subgroup analysis by factors of sample size (fewer than 100 or more than 100), type of cancer (digestive system or non-digestive system carcinoma), follow-up time (fewer than 100 or more than 100 months), samples detected (blood or tissue), paper quality (NOS scores ≥ 7 or < 7) and source of HR (directly or indirectly) to explore the source of heterogeneity , which suggested that elevated expression level of CXCL5 was significantly associated with poor OS in cancer patients  Fig. a and hepThere were three studies respectively evaluating the relationship between CXCL5 expression levels with DFS, PFS and RFS. Through systematic analysis, our results revealed that higher expression level of CXCL5 was significantly associated with shorter PFS   and Speetjens et al. affected results greatly, which indicated that these two studies were possible to be the main source of heterogeneity. However, the list of pooled HRs and 95% CIs after excluding single study one by one indicated robustness of our results, in which all pooled HRs and 95% CIs were above the null hypothesis of 1 Fig. a. For DFBegg’s test and Egger’s linear regression test were conducted to evaluate publication bias. For OS, Begg’s test (p = 0.773) Fig. e and EggCXCL5 is originally discovered as a potent chemoattractant and activator of neutrophil function . ThroughHere we performed the current comprehensive meta-analysis to systematically explore the prognostic value of abnormally expressed CXCL5 in cancer patients. We examined 15 independent studies including 19 cohorts and 5070 patients. Through systematic analysis, our results demonstrated that high expression level of CXCL5 was significantly associated with poor OS in cancer patients. Due to the significant heterogeneity across these studies, we performed subgroup analysis and meta-regression analysis to explore the sources of heterogeneity. The results of subgroup analysis suggested that sample size (fewer than 100 or more than 100) altered the significance of prognostic role of CXCL5 in OS . This indicated that difference in sample size might be the source of heterogeneity. However, meta-regression analysis failed to identify the source of the significant heterogeneity in above covariates. In addition, by combining HRs from Cox multivariate analysis, we found that CXCL5 was an independent prognostic factor of OS in cancer patients.Furthermore, we evaluated the prognostic value of CXCL5 in certain types of cancer. We found that high CXCL5 expression was associated with reduced OS in intrahepatic cholangiocarcinoma and hepatocellular carcinoma, which was consistent with previous studies. However, there was no significant association between expression level of CXCL5 with the OS of lung cancer and colorectal cancer. For lung cancer, results from Oksana et al. were contrary to others greatly . The reaDFS, PFS and RFS are all important parameters reflecting the progression of tumor. Our results demonstrated that higher expression level of CXCL5 was significantly associated with shorter PFS and RFS in cancer patients. However, high or low expression of CXCL5 made no difference in predicting the DFS of cancer patients. In addition, because only three studies respectively were included to evaluate the association between CXCL5 expression levels with DFS, PFS and RFS, more studies are necessary to explore the relationship between CXCL5 with tumor progression.Mechanisms underlying the regulatory role of CXCL5 in tumorigenesis and tumor progression have been extensively investigated. CXCL5 could activate multiple signaling pathways to promote the progression of cancer. Dai et al. found that overexpression of CXCL5 markedly upregulated the activity of the JNK, ERK and p38 MAPK signaling pathways, which may contribute to the promoting effects of CXCL5 on the proliferation and migration of glioma cells . In bladHowever, the current meta-analysis had some limitations. First, the cut-off value of high and low CXCL5 expression was different among studies, which might lead to the bias of the results. Second, some HRs could not be directly obtained from the publications. Thus, calculating them through survival curves might not be precise enough. Third, differences of paper quality and sample size across the studies might cause bias in the meta-analysis, although meta-regression did not show the paper quality or sample size as the resource of heterogeneity. Therefore, larger-scale, multicenter, and high-quality studies are desperately necessary to confirm our findings.In conclusion, our study revealed that elevated expression level of CXCL5 might be an adverse prognostic marker for OS, PFS and RFS in cancer patients. However, no significant association was found between CXCL5 expression level with DFS in the current meta-analysis. In a word, this is the first meta-analysis to evaluate the relationship between expression levels of CXCL5 with prognosis of cancer patients. In the future, more relevant studies are warranted to investigate the role of CXCL5 in human cancer.


Published data on the relationship between matrix metalloproteinases (MMPs) polymorphisms and ovarian cancer risk have implicated inconclusive results. To evaluate the role of MMPs polymorphisms in ovarian cancer risk, a meta-analysis and systematic review were performed.MMPs polymorphisms which could be quantitatively synthesized were involved in meta-analysis. Five comparison models  were carried out, a subgroup analysis was performed to clarify heterogeneity source. The remaining polymorphisms which could not be quantitatively synthesized were involved in systematic review.OR = 0.60; heterozygote model: OR = 1.09, 95%CI = 0.78–1.54, POR = 0.61; dominant model: OR = 1.02, 95%CI = 0.83–1.25, POR = 0.84; recessive model: OR = 0.95, 95%CI = 0.75–1.21, POR = 0.67; additive model: OR = 1.00, 95%CI = 0.85–1.17, POR = 0.99), MMP3 rs34093618  and ovarian cancer. Furthermore, similar results were detected in subgroup analysis. The systematic review on 12 polymorphisms suggested that MMP2 C-735T, MMP7 A-181G, MMP8 rs11225395, MMP9 rs6094237, MMP12 rs2276109, MMP20 rs2292730, MMP20 rs12278250, MMP20 rs9787933 might have a potential effect on ovarian cancer risk.10 articles with 20 studies were included in this paper. Among those studies, 8 studies involving MMP1 rs1799750 and MMP3 rs34093618 could be meta-analyzed and 12 studies involving 12 polymorphisms could not. Meta-analysis showed that no associations were found between MMP1 rs1799750 (homozygote model: OR = 0.93, 95%CI = 0.70–1.23, PIn summary, polymorphisms of MMPs might not be associated with ovarian cancer risk. However, it is necessary to conduct more larger-scale, multicenter, and high-quality studies in the future. Ovarian cancer is main cause of death with gynecological tumors worldwide, and is often at an advanced stage by the time of diagnosis and has metastasized throughout the peritoneal cavity –2. In 20Genome-wide association studies (GWAS) concerning genetic aetiology of cancer have established more than 150 regions associated with various specific cancers, which expand the current understanding of carcinogenesis mechanisms .Matrix metalloproteinases (MMPs), a family of more than 20 zinc-dependent enzymes known to degrade extracellular matrix and basement membrane components , are notThe databases Pubmed, Embase, Web of knowledge, were searched for all articles with the following search terms:  AND (polymorphism OR polymorphisms) AND (ovarian cancer OR ovarian carcinoma) up to search date: March 25, 2017. No limitation of publication language was defined for this search. Additional published data were identified by reviewing the bibliographical references listed in each retrieved article.All studies included in this meta-analysis were accorded with the following inclusion criteria: (a) study focused on the association between MMPs polymorphisms and ovarian cancer; (b) case-control design; (c) provided available frequency for each genotype in both cases and controls to calculate odds ratio (OR) and corresponding 95% confidence interval (95%CI). In addition, exclusion criteria were as follows: (a) reviews, editorials, comments or animal studies; (b) overlapped articles or studies with overlapping data.Two investigators independently extracted the following data: first author’s name, year of publication, study country, ethnicity, source of controls, MMPs gene, polymorphisms, number of cases and controls, value of Hardy-Weinberg equilibrium (HWE). A consensus on the extracted items was reached by discussion between the two investigators.The quality of study was assessed according to the quality assessment criteria  S1 Tabl, in whic2 value. If I2 value < 50% or P > 0.10, the fixed effect model was used [In order to evaluate the association between MMPs polymorphisms and ovarian cancer risk, OR and 95% CI were summarized under five comparison models, including homozygote model, heterozygote model, dominant model, recessive model, additive model. The definition of comparison model was listed in was used . Otherwiwas used , then a A total of 17 articles –27 were OR = 0.60; heterozygote model: OR = 1.09, 95%CI = 0.78–1.54, POR = 0.61; dominant model: OR = 1.02, 95%CI = 0.83–1.25, POR = 0.84; recessive model: OR = 0.95, 95%CI = 0.75–1.21, POR = 0.67; additive model: OR = 1.00, 95%CI = 0.85–1.17, POR = 0.99). For MMP3 rs34093618 polymorphism and ovarian cancer risk, overall, no significant association was found .The results of meta-analysis for MMP1 rs1799750 and MMP3 rs34093618 polymorphisms were listed in The results of systematic review were presented in 2 = 53%, Phet = 0.08; MMP3 rs34093618: I2 = 69%, Phet = 0.04). Then, a subgroup analysis by ethnicity was conducted to assess the source of heterogeneity. The forest plots of subgroup analysis for MMP1 rs1799750 and MMP3 rs34093618 were respectively presented in Figs 2 = 31%, Phet = 0.15), while MMP3 rs34093618 did not decreased . No significant association was found between MMPs polymorphism and ovarian cancer in both two subgroup analysis.For both MMP1 rs1799750 and MMP3 rs34093618 polymorphism, there was obvious heterogeneity in heterozygote model Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S2 File(DOC)Click here for additional data file.


Q-test and I2 statistic were used to estimate the degree of heterogeneity. Publication bias among enrolled studies was examined by using Egger's test and Begg's test. Overall, there was no evidence of positive association between SLE risk and D299G and T399I polymorphisms in TLR4. The meta-analysis reported a null association between TLR4 polymorphisms and SLE risk in included study populations, but the role of TLR4 polymorphisms in developing SLE among other populations remains undetermined. Moreover, some laboratory studies still discovered the involvement of TLR4 in SLE process. Therefore, the association between TLR4 polymorphisms and SLE risk requires further investigation both in laboratory and in epidemiological efforts. Family aggregation was observed among systemic lupus erythematosus (SLE) cases, suggesting the genetic factor may contribute to the susceptibility. Toll-like receptors (TLR) play key role in human immune system; in order to gain better insight on the association between TLR4 polymorphisms and SLE risk, a meta-analysis was conducted. In total 4 case-control studies have been included, involving 503 SLE cases and 636 healthy controls. The association between TLR4 polymorphisms and SLE risk was evaluated by calculating pooled odd ratio (OR) and its 95% confidential interval (CI). The  Systemic lupus erythematosus is an autoimmune disease that causes a chronic inflammatory condition for life-long time, and the inflammation triggered by SLE can affect multiple organs in human body, including joints, skin, lung, kidneys, and blood vessels. Particularly the impairment of kidneys may lead to lupus nephritis and possibly develop to acute or end-stage renal failure. Although some of SLE complications could be fatal, the development and application of immunosuppressive drugs aiming to control the autoimmune process helped to improve the prognosis of SLE cases; approximately 80–90% of SLE cases can expect to have a normal life expectancy . HoweverAlthough many studies have been done to investigate the risk factors of SLE, the cause of SLE has not yet been fully understood so far. Based on the family aggregation observed, it can be assumed that genetic factor plays a critical role in developing SLE. No single causal gene has been identified so far, but several genes have been proved to influence individual's chance of developing SLE. A study conducted in Caucasian population demonstrated that the human leukocyte antigen classes I, II, and III are associated with SLE risk . SimilarWe performed the meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines .Literature search was independently conducted by two investigators for genetic studies on TLR4 in PUBMED. All relevant studies reported up to January 2015 and following key words were searched: “systemic lupus erythematosus,” or “SLE”, “polymorphism” or “SNP”, “toll-like receptor 4,” or “TLR4”. The search was performed in February 2016 and no date and language limits were applied. In order to further expand the dataset, we also reviewed the reference lists of all retrieved studies to identify eligible studies.The eligibility of study was defined as follows: (1) case-control study design; (2) investigating the association between TLR4 polymorphisms and the risk of developing SLE; (3) genotype distribution of TLR4 polymorphisms in both cases and controls available; reviews, cases reports, editorial comment, communications, and reports without sufficient data were excluded in our meta-analysis.The following information was extracted from each eligible study: name of first author, year of publication, ethnicity of study participants, number of cases and controls, the frequency of TLR4 genotypes in SLE cases and controls, and Hardy-Weinberg equilibrium (HWE) test results in controls. In order to assess the quality of enrolled studies, we rated the methodological quality of each included study by using the Newcastle-Ottawa quality assessment scale. This scale contains 9 items in total (1 point for each) in three parts: selection (4 items), comparability (2 items), and exposure (3 items).P value of HWE was not provided in the original study. A P value less than 0.05 was considered as the deviation of HWE. The association between TLR4 polymorphisms and SLE risk was evaluated by calculating pooled odd ratio and its 95% confidential interval and forest plot was created to demonstrate the overall effect. With respect to heterogeneity, the Q-test and I2 statistic were used to estimate the degree of heterogeneity among the enrolled studies. In the absence of heterogeneity, fixed-effects model was applied to estimate the pooled OR and 95% CI. Otherwise, random-effect model was used to yield more conservative overall effects. Moreover, publication bias among enrolled studies was examined by using Egger's test and Begg's test, where a P value of less than 0.10 was considered statistically significant.Statistical analysis was performed by using STATA version 12 . Chi-squared test was employed to determine the HWE of controls if the As shown in The main outcomes of this meta-analysis were presented in I2 statistics we calculated by using STATA software, there was no interstudy heterogeneity among all enrolled studies of TLR4 polymorphisms for all 3 genetic models . Due to the absence of heterogeneity, the pooled ORs were estimated by using fixed-effect model.According to the P values for all genetic models were all greater than 0.05, suggesting no evidence of publication bias.Due to the limited number of enrolled studies, it was inappropriate to evaluate the publication bias by using funnel plot. Therefore, the publication bias in our meta-analysis was estimated by using Begg and Egger's test. As shown in  Drosophila in 1985 and they have been proved to play fundamental role in innate immune system. After that, Nomura et al. identified the first toll-like receptor in cDNA clones of human in 1994 [ Drosophila to human and share structural and functional similarities. The main function of TLR4 is recognizing lipopolysaccharide (LPS) and activating immune response; previous findings also revealed that TLR4 is capable of binding a variety of endogenous proteins such as low-density lipoprotein and heat shock protein [Toll-like receptors were firstly discovered in in 1994 . By comp protein . With th protein . Eventua protein . Given t protein . in vitro and in vivo [I2 statistics among all genetic models, it can be assumed that the heterogeneity was insignificant in our meta-analysis; therefore, fix-effect model was employed to estimate the pooled OR. Both D299G and T399I were not significantly associated with SLE risk in dominant and recessive model. We further analyzed the overall impact of TLR4 polymorphisms allele on SLE risk, and the results were similar with the genotype analysis. Therefore, we can conclude that, based on the current evidence we obtained, the TLR4 polymorphisms are not associated with SLE risk.The mutation occurring in TLR4 sequence may also alter individual's susceptibility to some diseases. In detail, two nonsynonymous polymorphisms in TLR4 gene have been well investigated; an A/G transition causes an Asp/Gly polymorphism at amino acid 299 and a C/T transition causes a Thr/Ile polymorphism at amino acid 399. Notably, the amino acid change caused by two above-mentioned polymorphisms would lead to changing the ligand-binding site of the receptor  and cons in vivo . A much  in vivo . Althoug in vivo . In a ca in vivo . However in vivo . So far  in vivo , 9, whil in vivo . TherefoThe major limitation of our meta-analysis is that the number of enrolled studies was small; despite expanded search applied by reviewing the reference of enroll studies, still only 4 studies were available in our final analysis. The reason behind this problem is the unique distribution pattern of TLR4 polymorphisms between different races. According to the data of a study involving study subjects from all over the world, the D299G and T399I double mutation haplotype were of high frequency in Caucasians in Europe, and D299G and 399 wildtype can be found in African population; however, no mutations in both D299G and T399I were observed in East Asian countries, including China, Japan, and Korea . TherefoAlthough the meta-analysis we conducted reported a null association between TLR4 polymorphisms and SLE risk, some laboratory studies still discovered the involvement of TLR4 in SLE process. Flow cytometry was applied to detect the expression of TLR4 in blood monocytes from SLE cases and healthy control; the statistical comparison revealed that the TLR4 expression was significantly suppressed in SLE cases . Moreove


Studies of angiotensin-converting enzyme insertion/deletion (ACE I/D) polymorphisms and the risks of knee osteoarthritis (OA) have yielded conflicting results.To determine the association between ACE I/D and knee OA, we conducted a combined case-control study and meta-analysis.For the case-control study, 447 knee OA cases and 423 healthy controls were recruited between March 2010 and July 2011. Knee OA cases were defined using the Kellgren-Lawrence grading system, and the ACE I/D genotype was determined using a standard polymerase chain reaction. The association between ACE I/D and knee OA was detected using allele, genotype, dominant, and recessive models. For the meta-analysis, PubMed and Embase databases were systematically searched for prospective observational studies published up until August 2015. Studies of ACE I/D and knee OA with sufficient data were selected. Pooled results were expressed as odds ratios (ORs) with corresponding 95% confidence intervals (CI) for the D versus I allele with regard to knee OA risk.2: 87.2%).We found no significant association between the D allele and knee OA [OR: 1.09 (95% CI: 0.76–1.89)] in the present case-control study, and the results of other genetic models were also nonsignificant. Five current studies were included, and there were a total of six study populations after including our case-control study (1165 cases and 1029 controls). In the meta-analysis, the allele model also yielded nonsignificant results [OR: 1.37 (95% CI: 0.95–1.99)] and a high heterogeneity (IThe association between ACE I/D and knee OA tended to yield negative results. High heterogeneity suggests a complex, multifactorial mechanism, and an epistasis analysis of ACE I/D and knee OA should therefore be conducted. Knee osteoarthritis (OA) is characterized by a highly catabolic state, chondrocyte apoptosis, articular cartilage degeneration, morphologic changes to the subchondral bone, and damage to the surrounding synovium –5. MultiBradykinin is an inflammatory nonapeptide vasodilator and has a role in pain and inflammation mainly mediated via its receptor . Previouin vivo experimental studies, which demonstrated that ACE inhibitor treatment decreased the blood angiotensin II concentration but increased the blood bradykinin concentration in normal human subjects and dogs  participated in this study up to July 2011.We recruited potential participants at the Health Management Centre of TSGH from those participating in a check-up program. The Taipei city senior medical check-up program is a governmental welfare program provided for people aged 65 years or older and who have been registered residents in Taipei city for more than 1 year. Accordingly, we began to release related recruitment information in March 2010. Participants who met the following criteria were excluded from this study: (1) patients who had undergone knee surgery  and (2) those unable to provide a sufficient blood sample. Demographic data included age, gender, and body mass index  grading system . In the Genomic DNA was extracted from peripheral blood samples using standard procedures for proteinase K  digestion and phenol/chloroform extraction. ACE I/D polymorphisms were screened using the polymerase chain reaction (PCR) according to a previously described protocol . The pri2 test performed to identify possible genotyping errors among the controls of each study. Genotypes and allelic frequencies were compared between patients with knee OA and healthy controls using the χ2 test or Fisher’s exact test where appropriate. Logistic regression was used to estimate ORs and 95% confidence intervals (CIs) as a measure of the association with the risk of knee OA. Allele type, genotype, and dominant/recessive models were used to calculate the association between genetic polymorphism and knee OA risk. To avoid the multiple comparison problem, we tested the global p value via two robust tests, MAX3 [Continuous demographic variables were evaluated using a Student’s t test and reported as means ± SDs. The Hardy–Weinberg equilibrium (HWE) was assessed using a goodness-of-fit χts, MAX3 ,50 and tts, MAX3 . This stts, MAX3 .The PRISMA checklist and Meta-analysis on Genetic Association Studies Checklist is described in All related studies that assessed the association between ACE I/D polymorphisms and the risk of knee OA were considered for inclusion. The criteria for study inclusion were as follows: (1) cross-sectional surveys or case–control studies, (2) OA defined as a KL grade of ≥2, and (3) a detailed distribution of ACE genotypes. If the published data was incomplete, we made attempts to contact the authors for further information.Two reviewers (Chin Lin and Wen-Hui Fang) independently extracted data and assessed the risk of bias. For each article, we recorded the first author’s name, year of publication, ethnicity of the study population, definition of the case group, and population characteristics . All extracted papers were assessed using the Newcastle–Ottawa Scale (NOS) , and all2 statistic, which was estimated using the DerSimonian–Laird method, was used to assess heterogeneity, and a random-effects model was used to calculate the weighed effect size. Three common genetic models, including allele type, dominant, and recessive models, were used to calculate the association between genetic polymorphism and the risk of knee OA. Moreover, we performed a genotype model with three comparisons  for comprehensively examining the association between ACE I/D and knee OA. Because the genotype model tested three times in an association, the Bonferroni method was used to correct these for significant values (divided by 3).The population characteristics of each included study are presented as means or proportions where appropriate. Our meta-analysis examined the association between ACE I/D polymorphisms and the risk of knee OA in each study using ORs with 95% CIs. The τ2 was calculated with the Cochrane Q test and used to quantify heterogeneity; an I2 value >50% indicated a moderate to high heterogeneity [Egger’s regression and a funnel plot were used to test the symmetry of pooled results . I2 was ogeneity . Moreoveogeneity ,58; we tMeta-regression using an average summary value is used to explore the source of heterogeneity. According to our previous studies, the average summary value of the case group can be used to build a model and can help to estimate the interaction effect ,60. An iThis study considered a p value of <0.05 to be significant for all analyses. Statistical analyses were conducted using the “metafor”  and “metThere were 870 samples in this study, and 83 (9.5%) ambiguous calls were identified and re-genotyped. After the first round of genotyping, we randomly selected 96 (11.0%) repeated samples for re-genotyping. The reproducibility rate of analyzing ACE I/D in this study was 100%.The characteristics of subjects according to the severity of knee OA are shown in We further used the global test and four types of genetic models to test the association between ACE I/D and knee OA; the results are shown in 2 values of classical genetic models exceeded 57%. This indicated a high heterogeneity on the association between ACE I/D on knee OA.Our case-control study results showed no significant associations between ACE I/D and knee OA. A meta-analysis of the associations in six studies yielded the same results. In our hypothesis, the ACE I/D DD genotype was associated with higher gene expression  and seruThe main function of ACE is to convert angiotensin I to the potent vasoconstrictor angiotensin II ,25, and 2 (heterogeneity) = 90%. Following these settings, the number of needed samples is equal to 2575 and we collected 2194 samples in this meta-analysis. Although this was still insufficient, We performed a Trial Sequential Analysis (TSA) for calculating the required sample size in this issue . The setDespite the high heterogeneity in the current study, our case–control study results were most similar to those reported by Hong et al. . We consCompared with the other included populations, our study population had the highest mean age, highest proportion of men, and lowest mean BMI. However, we considered that these differences in population characteristics might not affect the association between ACE I/D and knee OA because the results of a meta-regression showed that age, gender, and BMI could not explain the heterogeneity. Therefore, a high heterogeneity, regardless of the inclusion of Asian studies or Arab studies, might be due to another unknown factor. Because the role of ACE in knee OA may involve many possible pathways that even include opposing effects, we considered that the source of heterogeneity might include molecular factors such as gene–gene interactions. In fact, complex gene–gene interactions in the RAS were reported in the context of other diseases , which iIn sensitivity analysis, we found none of the Arab population studies passed the HWE test. Previous studies reported that genotyping error was the most common reason for this HWE failure –77. AlthAlthough we investigated the most common polymorphism in ACE, a previous study suggested that this might not be a functional locus. The functional polymorphism is most likely located between intron 18 and the 3′ UTR , and othSeveral potential limitations should be acknowledged. First, we relied on the tabular data for the meta-analysis, rather than on the individual patient data. However, we included a case–control study to improve the sample size and evidence level. Second, in addition to our case–control study, only five studies had investigated the link between OA and the ACE I/D polymorphism. The relationship between ACE I/D and knee OA involves a complex mechanism, thus indicating the need for additional studies. Our case–control study involves the largest sample to date and thus provides more evidence for a clear understanding of this association.In conclusion, our meta-analysis provides evidence important to an exploration of the association between ACE I/D and knee OA. The ACE I/D D allele might not be protective against knee OA, and negative results revealed ACE I/D was not directly associated with OA. The high level of heterogeneity suggests a complex mechanism, and several possible environmental factors, including gender, age, and BMI, cannot explain this heterogeneity. This unexplainable heterogeneity might be related to gene–gene interactions although additional well-designed studies to address the relationship between ACE I/D and knee OA are needed to explore the underlying mechanism. An epistasis analysis of ACE I/D and knee OA should be conducted. A potential gene–environmental interaction should not be excluded, and additional environmental factors should also be investigated.S1 Fig(PDF)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOC)Click here for additional data file.