IL-1β) rs1143627 polymorphism and periodontal disease susceptibility was inconsistent; hence we performed this meta-analysis to explore the precise correlation between them. The degree of association was appraised through calculating pooled odds ratio (OR) and its 95% confidence interval (CI). The databases known as PubMed, Embase, and Chinese National Knowledge Infrastructure were searched up to October 26, 2016. A total of 8 eligible case-control studies were finally included, which involved 229 aggressive periodontitis patients, 382 chronic periodontitis patients, and 555 healthy controls. All the five genetic models revealed a non-significant association between IL-1β rs1143627 polymorphism and periodontal disease susceptibility . Sensitivity analyses indicated that the results were robust and the subgroup analyses reached similar conclusions. IL-1β rs1143627 polymorphism is not related to periodontal disease susceptibility in the overall population based on the current evidence, but further studies are required in more large scale sample size with risk factor adjusted.Association between interleukin-1 beta ( IL) polymorphisms and periodontal disease. IL-1β (beta) is highly polymorphic, and three polymorphisms that lead to transitions between C and T at positions -31, -511, and +3954/3953 base pairs (bp) from the transcriptional site have been widely researched [IL-1β rs1143634 polymorphism is significantly connected with the increased risk of CP [IL-1β rs16944 polymorphism and CP susceptibility [IL-1β rs1143634 polymorphism is correlated with CP [Periodontal disease, a multifactorial disease, is mainly composed of chronic periodontitis (CP) and aggressive periodontitis (AgP) –3. Periosearched –11. Metask of CP –13, espe1T→C, rs13627, -51tibility . In addi with CP –14 but hIL-1β rs1143627 polymorphism and periodontal disease, but as far as we know, no meta-analyses have been carried out about this issue yet. Therefore, the questions of whether IL-1β rs1143627 polymorphism is related to periodontal disease or not, and whether there is a difference of such relationship between CP and AgP still remain uncertain. As a consequence, we conducted this meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [An increasing number of studies have examined the association between tatement  in orderThe initial search identified 350 publications and 6 eligible publications involving 8 case-control studies –22 were p > 0.05).The characteristics and relevant data of all included studies are shown in Table Table IL-1β rs1143627 polymorphism and periodontal disease susceptibility under all 5 genetic models [T vs. C: odds ratio (OR) = 0.92, 95% confidence interval (CI) = 0.81-1.12, I2= 0%  showed that IL-1β rs1143627 polymorphism was connected with the increased risk of AgP while the CT+TT vs. CC  revealed a decreased risk of AgP.Subgroup analysis based on smoking status also revealed non-significant association. However, after stratified analysis by ethnicity, TT vs. CC  and TT vs. CT + CC  stated that p = 0.46; TT vs. CC: p = 0.44; CT vs. CC: p = 0.76; (TT+CT) vs. CC: p = 0.70; TT vs. (CT + CC): p = 0.81).There was no obvious asymmetry in the funnel plot through visual inspection Figure . The EggIL-1β rs1143627 polymorphism with periodontal disease susceptibility in total analysis. The sensitivity analyses supported that the overall analyses were robust, and the majority of subgroup analyses concluded similar results in the overall populations. Smoking, which is a classical risk factor of periodontal disease [IL-1β rs1143627 polymorphism is a co-factor of smoking in periodontal disease. Further studies should divide the populations into smokers and non-smokers, or only contain smokers to provide evidences for the collective effect of smoking with this polymorphism.Our meta-analysis, based on 8 eligible case-control studies, demonstrated that there was no obvious association of  disease  influenc disease . Hence, The current study was the first meta-analysis designed to investigate the correlation of IL-1β rs1143627 polymorphism with the risk of periodontal disease, and revealed a negative result, showing the lack of significant association. The results could be explained by some clues from published meta-analyses. First, the different polymorphisms in the same IL gene could show different results. For example, in 2009, Shao et al  conducteThe major limitations of our meta-analysis were the small sample size and limited number of included studies. The results also changed as sample size increased. In 2008, Nikolopoulos et al  conducteIL-1β rs1143627 polymorphism is not associated with periodontal disease on the basis of current available evidence. However, we suggest that the results should be examined in further better-designed researches with larger sample size and multiple ethnic groups considering the above mentioned limitations, in order to measure the relationship of IL-1β rs1143627 polymorphism with periodontal disease development more comprehensively and precisely.In summary, our meta-analysis suggests that Studies would be included if they met all the following criteria: (1) patients were clearly diagnosed with periodontal disease  and the controls were periodontally healthy people without periodontitis; (2) studies explored the association between IL-1β rs1143627 polymorphism and periodontal disease susceptibility using a case-control or cohort study design; (3) full data on OR and 95% CI were reported in each group, or sufficient data were provided to calculate them; and (4) if two or more publications were from the same institute, we would compared their detailed basic information and then chose the more comprehensive one.IL-1” or “interleukin-1”, “periodontal diseases” or “periodontitis”, and “polymorphism” or “mutation” or “variant” or “haplotype”. Moreover, all listed references of eligible studies and recently reviews were also screened for purpose of identifying the additional relevant publications. Only the studies published in Chinese or English were selected.Two authors independently searched multiple online electronic databases known as PubMed, Embase, and Chinese National Knowledge Infrastructure (CNKI) up to October 26, 2016. The following key words were used in search strategy: “Two authors independently collected and recorded the main information from each included case-control studies. Any discrepancies were resolved through discussion to come to a consensus. The extracted data were listed as follows: surname of the first author, year of publication, study design, country and ethnicity of included population, demographics, smoking status, number of cases and controls, genotype distributions, source of controls, genotyping method, and Hardy-Weinberg equilibrium (HWE) for controls. If HWE was not reported, we calculated the data according to genotype distributions of controls.IL-1β rs1143627 polymorphism with periodontal disease risk was evaluated under the allele comparison (T vs. C), homozygote comparison (TT vs. CC), heterozygote comparison (CT vs. CC), dominant model (TT+CT vs. CC), and recessive model (TT vs. CT + CC) [Q statistic and I2 statistic [p > 0.1 in Q statistic and I2 < 50% in I2 statistic which suggested an acceptable heterogeneity; otherwise, the random-effects model was used. The sensitivity analysis was also performed by omitting each included study in turn for investigating the robustness of overall results [IL-1β rs1143627 variant according to ethnicity, HWE status, periodontal disease type, and smoking status if it was appropriate. Publication bias was assessed with the method of funnel plot and Egger's test [Pooled OR and 95% CI were employed to estimate the association of CT + CC) , 31–35. tatistic , 36. The results , 31. Besr's test . All ther's test , 31, 38.


Antiepileptic drugs (AEDs) are effective medications available for epilepsy. However, many patients do not respond to this treatment and become resistant. Genetic polymorphisms may be involved in the variation of AEDs response. Therefore, we conducted an updated systematic review and a meta-analysis to investigate the contribution of the genetic profile on epilepsy drug resistance.We proceeded to the selection of eligible studies related to the associations of polymorphisms with resistance to AEDs therapy in epilepsy, published from January 1980 until November 2016, using Pubmed and Cochrane Library databases. The association analysis was based on pooled odds ratios (ORs) and 95% confidence intervals (CIs).ABCB1) C3435T polymorphism and AEDs responsiveness in a total of 454 epileptic AEDs-resistant cases and 282 AEDs-responsive cases. We found a significant association with an OR of 1.877, 95% CI 1.213–2.905. Subanalysis by genotype model showed a more significant association between the recessive model of ABCB1 C3435T polymorphism (TT vs. CC) and the risk of AEDs resistance with an OR of 2.375, 95% CI 1.775–3.178 than in the dominant one (CC vs. TT) with an OR of 1.686, 95% CI 0.877–3.242.From 640 articles, we retained 13 articles to evaluate the relationship between ATP-binding cassette sub-family C member 1 (ABCB1 C3435T polymorphism, especially TT genotype, plays an important role in refractory epilepsy. As genetic screening of this genotype may be useful to predict AEDs response before starting the treatment, further investigations should validate the association.Our results indicate that  Epilepsy is a chronic neurological worldwide disorder . Most caThe exact mechanism of refractory epilepsy is not well understood. Two main hypotheses are potentially involved in the biological mechanism of AEDs resistance: transporter and target hypotheses. The transporter hypothesis supports the overexpression of drug efflux transporters at the blood–brain barrier (BBB) reducing AEDs access to the brain. The target hypothesis contends that the changes in drug intracellular target sites (receptors) result in decreased sensitivity of AEDs , 5. TherSince drug resistance often occurs in patients with multiple AEDs, the multidrug transporter hypothesis is considered better than the target hypothesis to explain the phenomenon of AEDs resistant epilepsy. However, the two hypotheses may complement each other. Given that drug transport mechanisms are the candidate mechanisms underlying AEDs resistance , many stABCB1) and the atp-binding cassette sub-family c member 2 (ABCC2) also known as multidrug resistance protein 1 (MDR1) and multidrug resistance protein 2 (MDR2), located at the membrane of BBB endothelial cells, are members of the ABC superfamily. They are the most studied candidate genes in pharmacoresistant epilepsy [ABCB1 gene encodes it and it affects a wide range of drugs distribution in target compartments [ABCB1 gene (single nucleotide polymorphism (SNP) in exon 26) and it has received the most attention. It has been associated with the variations in the expression levels of P-gp [ABCB1 C3435T polymorphism and drug-resistant epilepsy showed discordant findings. Several studies have supported the hypothesis of this association  to AEDs resistance [ABCC2 gene (SNP in exon 10). The overexpression of the ABCC2 transporter protein reduces AEDs levels in brain tissues, which is a risk factor for pharmacoresistant epilepsy. A genotypic association between this polymorphism and responsiveness to AEDs has been suggested in Asian populations [ABCC2 G1249A polymorphism was significantly associated with the decreased risk of AED resistance [Bioavailability and response to medication in epilepsy are mainly influenced by atp-binding cassette (ABC) transporter superfamily. The atp-binding cassette sub-family b member 1 . It alters the proportion of human brain NaV1.1-5N (exon 5N) and NaV1.1-5A (exon 5A) proteins, but the functional impact of the splicing on NaV1.1 is unknown. The correlation between SCN1A IVS5-91G > A polymorphism and maximum doses of Oxcarbazepine (OXC) may have a potential effect on resistant to epilepsy. The same study found the same correlation for ABCC2 G1249A polymorphism [SCN1A IVS5-91G > A polymorphism with the response to Carbamazepine (CBZ)/OXC [Among their pharmacological effects, some AEDs may block voltage-dependent sodium channels , 60, whimorphism . An addiCBZ)/OXC , 62, andCBZ)/OXC . HoweverCBZ)/OXC –66 and oCBZ)/OXC  were unaOverall, even the most considered polymorphisms that may explain mechanisms of pharmacoresistant epilepsy, showed contradictory and inclusive results. Therefore, we assembled pharmacogenetics (PGt) and pharmacogenomics (PGx) studies reporting associations between AEDs resistant epilepsy and eventual polymorphisms. Then, we performed an updated meta-analysis to clarify their role in response to AEDs.We defined search strategy, study selection criteria, data elements and methods for study quality assessment.We conducted a literature search using Pubmed and Cochrane Library with English-language restriction from January 1980 to November 2016. The key words used in the search strategy were: “anti-epileptic drug(s)”, “antiepileptic drug(s)”, “anti epileptic drug(s)” and “epilepsy” and “efficacy”, “intractable”, “refractory”, “resistance”, “resistant”, “response to treatment”, “pharmacoresistance”, “pharmacoresistant” and “genetic factor(s)”, “genotype(s)”, “pharmacogenetic(s)”, “pharmacogenomic(s)”, “polymorphism(s)”, “variant(s)”, “variation(s)”, “SNP(s)”. We did not search of additional publications. The reported results followed the preferred reporting items for systematic reviews and meta-analyses guidelines (PRISMA).For eligibility, we retained full-text publications showing a relationship between genetic polymorphisms and responsiveness of AEDs in epilepsy (monotherapy or polytherapy).The included studies met the following criteria: 1) Original research articles reported a genotypic evaluation of polymorphisms and resistant epilepsy to antiepileptic treatment. 2) Studies compared AEDs-resistant cases with AEDs-responsive cases. 3) Studies showed sufficient individual genotype frequencies for specific genotype model. 4) At least three studies on the same polymorphism were available in order to avoid the non-pertinence of the results and the high risk of bias.Two independent authors performed the data eligibility, they extracted the following information from each included study: first author, publication year, ethnicity of the study population, the number of cases and controls, genotype model for each polymorphism, age, gender, aetiology, type of epilepsy, and AEDs administered.P-value determined the significance of the combined ORs. If the P-value (P) < 0.05, we considered the pooled ORs statistically significant [Z-value showed uniformisation of values and their position in the full distribution of values in the program. The I2 statistic test assessed statistical heterogeneity among included studies; if I2 < 50%, fixed-effects model pooled study data and if I2 ≥ 50%, random-effects model pooled it [P < 0.05 determined the existence of bias [We calculated the association between polymorphisms and AEDs resistant epilepsy using individual and overall odds ratios (OR) with corresponding 95% confidence intervals (CIs) by Forest Plot . The nificant . The Z-vooled it . Additio of bias .We identified a total of 640 potentially relevant articles. We excluded a total of 591 publications from the further analysis: abstract, articles showing absence of associations between polymorphisms and AEDs resistant epilepsy for insufficient data, case reports, duplicated articles, letter to the editors, meta-analysis, not epileptic studies, not human reports, researches about other treatments than AEDs, review articles and studies not related to associations between polymorphisms and AEDs resistant epilepsy , gamma-aminobutyric acid-a receptor alpha2-subunit (GABRA2), gamma-aminobutyric acid-a receptor alpha3-subunit (GABRA3), sodium channel nav1.1 (SCN1A), sodium channel nav1.2 (SCN2A), in other potential genes as apolipoprotein e (ApoE), cytochrome p450 1a1 (CYP1A1), cytochrome p450 family member 2c9 (CYP2C9), gamma-aminobutyric acid transporter 3 (GAT3), glutathione s-transferases mu 1 (GSTM1) and solute ligand carrier family 6 member a4 (SLC6A4). We summarized the characteristics of polymorphisms implicated in AEDs resistance in different ethnic groups  and 282 of 1732 AEDs-responsive patients (16.282%) were included in the statistical analysis [ABCB1 C3435T polymorphism and cases with Phenytoin (PHT) therapy, the administration of PHT as monotherapy or polytherapy was not mentioned [We carried out a meta-analysis to evaluate the relationship between analysis , 33–36. patients .465% andanalysis , 34–36, analysis , 26, 31,analysis  and one patients .465% andanalysis , 33, 35 patients .465% andanalysis , 33, 35.analysis , 35, 36.entioned . Howeverpatients .465% andI2 = 82.961%, P < 10-3) and we used a random-effects model [P = 0.005 showing that ABCB1 C3435T was significantly associated with AEDs resistance  in the dominant model [P = 0.117 under a random-effects model  among the four included studies [P < 10-3 under a fixed-effects model  and recessive (TT vs. CC) genotype models. The heterogeneity among the nine included studies was high   [ABCB1 3435TT genotype  than 3435CC genotype   . Zimpric= 0.006) . Moreove= 0.006) , 16–23. = 0.006) –36 and o= 0.006)  showed tABCB1 C3435T polymorphism and drug-resistant epilepsy. The majority suggest that the ABCB1 C3435T polymorphism may not be involved in the response to AEDs [ABCB1 C3435T polymorphism with risk of drug resistance in overall and in the subgroup analysis by ethnicity (Asian and Caucasian populations) (n = 3371 subjects) [n = 6755 subjects) [ABCB1 alleles, genotypes, and haplotypes with recurrent seizures (n = 7067 patients) [ABCB1 C3435T polymorphism in cases and controls (n = 3996 subjects) [ABCB1 C3435T polymorphism with childhood risk of drug resistance was found in overall and in the subgroup analysis by ethnicity (Asian and Caucasian populations) (n = 1249 subjects) in the study of Sun et al. [ABCB1 C3435T polymorphism is associated with the risk of resistance to AEDs in Asians and Caucasians [Due to these controversial results, meta-analyses were made in order to clarify the association between  to AEDs –62. The ubjects)  and the atients) . In the ubjects) . No allen et al. . Recentln et al. , 64. In n et al.  and simin et al. , 47. Hown et al. , 64. Then et al. . Howeverucasians , 47. TheABCB1 gene. ABCB1 protein or P-gp was transporte AED in the BBB [ABCB1 polymorphisms reducing plasmatic levels of AEDs and minimizing antiepileptic treatment efficiency in epileptic patients [AEDs transporters have contribute in pharmacoresistant epilepsy. In fact, the most studied AEDs transporter proteins like membrane proteins, are ABC transporter superfamily members. They are ATP-dependent drug efflux pumps for specific AED and are mainly encoded by  the BBB . P-gp acpatients , 99. If patients , 18. Hompatients , 100.ABCB1 3435TT genotype on response to AEDs. Our findings may contribute to exhibit the implication of genetic markers in refractory epilepsy before starting the treatment. In order to have a better AEDs therapeutic response, the identification of new potential genetic markers become necessary against pharmcoresistance in epilepsy. This will lead to a better understanding of drug resistance mechanisms in epilepsy. Furthermore, it will be extremely important for individual AEDs selection, early surgery feasibility and development of new efficacious treatments.Compared to literature search supporting conflicting results, our results show a higher contribution of ABCB1 C3435T polymorphism and drug resistance epilepsy could be affected. Correlation between PGt and PGx results with specific AED should be required. 4) Different inclusion criteria are used to classify AEDs-resistant patients in the included studies, subsequently, the interpretation of the meta-analysis results become very complex. In fact, AEDs-resistant patients were defined as patients who had at least one seizure per month or 10 seizures over the previous year, despite two or more AEDs at therapeutic dosages and/or serum drug concentrations in three studies [Our analysis is consistent to our strategy search, inclusion criteria and statistical parameters. However, it may be limited due to several factors: 1) Few number of included studies is insufficient to carry out a subgroup analysis by ethnicity. In addition, the ethnicities in the included studies are heterogeneous. PGt and PGx studies of AEDs resistance should be performed by ethnicity. 2) Publication bias and heterogeneity might have an impact on the meta-analysis results. 3) Most of the included studies match different types of epilepsy with different AEDs. The affinity of each AED for ABC transporters is variable. In fact, Valproic acid (VPA) is a widely used AED and it is not transported by P-gp . Thereby studies , 28, 34. studies , 31, 33. studies , 29, wit studies , or any  studies  and more studies .ABCB1 C3435T polymorphism and AEDs resistance in epilepsy. In the current meta-analysis, we demonstrate the existence of a statistical significant association between ABCB1 3435TT genotype and refractory epilepsy. Therefore, the screening of ABCB1 gene for this polymorphism in the future might be useful to decide the best treatment option for each patient and to predict the treatment outcome for new epileptic patients. However, considering the few number of included studies and the significant publication bias found in this meta-analysis, further investigations should be helpful to validate the use of this polymorphism in treatment decisions.Various studies have yielded contradictory findings regarding the relationship between


To elucidate the veritable relationship between three hMLH1 polymorphisms  and cancer risk, we performed this meta-analysis based on overall published data up to May 2017, from PubMed, Web of knowledge, VIP, WanFang and CNKI database, and the references of the original studies or review articles. 57 publications including 31,484 cancer cases and 45,494 cancer-free controls were obtained. The quality assessment of six articles obtained a summarized score less than 6 in terms of the Newcastle-Ottawa Scale (NOS). All statistical analyses were calculated with the software STATA . We found all the three polymorphisms can enhance overall cancer risk, especially in Asians, under different genetic comparisons. In the subgroup analysis by cancer type, we found a moderate association between rs1800734 and the risk of gastric cancer  and lung cancer in recessive model . The G allele of rs1799977 polymorphism was proved to connect with susceptibility of colorectal cancer  and prostate cancer . Rs63750447 showed an increased risk of colorectal cancer, endometrial cancer and gastric cancer under all genetic models. These findings provide evidence that hMLH1 polymorphisms may associate with cancer risk, especially in Asians. As one of the pivotal pathways in maintaining genetic stability, MMR system is mainly in charge of repairing the replication-associated errors, including removing mistaken bases, correcting substitutions and rectifying insertion-deletion mismatches. Its defects may result in microsatellite instability (MSI), a type of genetic instability related to colorectal cancer, gastric cancer, and endometrial cancer, etc. –3 IntereMLH1 not only takes part in the activities of MMR system, but also has other interesting cellular functions, such as participating in cell cycle arrest, triggering DNA damage-induced apoptosis to response to some chemical or physical agents , and intet al [et al. [For example, Nizam et al.  concludeet al  found noet al  detected [et al.  hold a c [et al. , 12–14, et al [et al. [Finally, we obtained a total of 57 publications including 31,484 cancer cases and 45,494 cancer-free controls . The detail selection process was shown in the flow diagram  for every single study are exhibited in Table P = 0.001; homozygote comparison: OR = 1.23, 95%CI = 1.06-1.42, P = 0.006; allele comparison: OR = 1.08, 95%CI = 1.01-1.16, P = 0.023). After excluding nine studies that were not in accordance with HWE [P = 0.012; homozygote comparison: OR = 1.18, 95%CI = 1.00-1.39, P = 0.048, Figure Overall, there are 39 studies including 29,331 cases and 29,588 controls for rs1800734 polymorphism. Statistically significance was found between rs1800734 polymorphism and overall cancer risk under five genetic models . In the cancer-specific analysis, rs1800734 polymorphism showed a potential tendency to enhance gastric and lung cancer susceptibility in different genetic comparisons . Besides, the subgroup analysis depended on the source of controls suggested us that rs1800734 polymorphism had an influence on cancer risk under four genetic models among population-based controls  and recessive comparison among hospital-based controls . And, when the subgroup analysis was conducted based on a quality score, rs1800734 polymorphism displayed an increased cancer risk among high-quality studies, but no association was found among low-quality studies . After excluding four studies [P < 0.0001; homozygote comparison: OR = 1.13, 95%CI = 1.01-1.26, P = 0.027).We finally derived 11,665 cases and 15,538 controls from 24 eligible studies for rs1799977 polymorphism. All the studies obtained high-quality scores according to the Newcastle-Ottawa Scale (NOS). In general, we found the variant G allele of rs1799977 could improve overall cancer risks under three genetic models  and Caucasians in only dominant model . In the cancer-specific analysis  and prostate cancer under dominant model .When the subgroup carried out by ethnicity Figure , a signis Figure , rs17999Besides, the results of subgroup analyses by source of control and study design exhibited in the P < 0.0001; heterozygote comparison: OR = 2.21, 95%CI = 1.73-2.84, P < 0.0001; allele comparison: OR = 2.19, 95%CI = 1.72-2.78, P < 0.0001), as shown in Figure A total of 2153 cancer cases and 1365 cancer-free controls from 11 studies were involved in our meta-analysis for rs63750447 polymorphism. Since the homozygous mutant AA of rs63750447 polymorphism was in very rare frequencies, we chose allele model, heterozygous model and dominant model to evaluate the association strength. The pooled analysis observed a significant association between cancer risk and rs63750447 polymorphism , gastric cancer , and endometrium cancer . When we conducted the subgroup analysis by quality score, there was a significantly increased cancer risk for rs63750447 polymorphism in both high-quality studies and low-quality studies , thus further subgroup analyses base on ethnicity, cancer type, source of control, and quality scores were performed. No obvious heterogeneity was found for rs63750447 polymorphism (P > 0.10 or I2 < 50%). Subsequent sensitivity analysis proved the stability of our study, since no significant alteration was detected after removing each individual study and rechecking the pooled ORs and 95%CIs for the rs1800734 and rs1799977 polymorphisms  and cancer risk, we performed this meta-analysis based on overall published data up to May 2017. We found all of these polymorphisms can enhance overall cancer risks, especially Asians, under different genetic comparisons . FurtherP = 0.017; OR = 1.33, P = 0.019; OR = 1.27, P = 0.024) and lung cancer in recessive model , while no connection was display with colorectal cancer. As far as we know now, microsatellite instability (MSI) often occurs when mismatch errors failed to be corrected or hMLH1 gene was epigenetic silencing. Campbell et al. [Interestingly, we found a moderate association existing between rs1800734 and the risk of gastric cancer in three genetic models  resistance, which has a possible shorter progression-free survival . Thus, iCompare with previous meta-analyses study on the association between hMLH1 and cancer risk, our study included a larger sample size and performed more detailed stratification analysis. Besides, our study has stricter inclusion criteria and exclude criteria, thus avoided omissive and false drop . Thus, we think our results are more reliable and convinced. Moreover, we found rs1800734 was related to gastric cancer, while rs1799977 may have an influence on colorectal and prostate cancer. It may give us some hints for the further study.There are still some limitations existing in this meta-analysis. Firstly, insufficiency of original data limited us to proceed more accurate analyses on the potential interaction between these polymorphisms and other risk factors such as age, sex, hereditary background, lifestyle, and MSI status, etc. Secondly, the studies involved in the rs63750447 analysis was insufficient, whose statistical significance was needed to verify by further well-designed study with larger sample sizes. Thirdly, we couldn't exclude the publication bias absolutely according to the negative results of Egger's test and funnel plots. Fourthly, the sample size was still small for any given cancer type, although we have pooled all published literatures. Hence, all the three hMLH1 polymorphisms were associated with cancer risk, but further profoundly investigation was requisite to clarify the strength of these associations.PRISMA statement was used to guide the process of this meta-analysis .A comprehensive literature search was conducted using the following search terms:  and  and (“hMLH1”). The PubMed, Web of knowledge, VIP, WanFang and Chinese National Knowledge Infrastructure (CNKI) databases were searched up to May, 2017. Additional studies were identified by manual search of the references of the original studies or review articles. This study was approved by the ethics committee of Xi’an Jiaotong University.To be eligible for this meta-analysis, the included study was required to (1) be case-control or case-cohort studies; (2) focused on the relationship between hMLH1 polymorphisms and risk of any cancer; (3) have at least three articles for each studied hMLH1 polymorphism, and available information concerning the genotype frequency of each included SNP of hMLH1 ; (4) be published in English or Chinese. The exclusion criteria were as follows: (1) studies were not focused on cancer risk or targeted hMLH1 SNPs ; (2) studies failed to supply any data on genotype distribution, (3) studies were updated by a following study where a larger number of subjects were included, (4) studies were designed as a case-case or case-only study. If 2 or more studies contained overlapping data, we selected the paper included more samples. Studies containing two or more case-control groups were considered as two or more independent studies.For each included study, two investigators independently extracted the raw data and demographic information, including publication year, first author, ethnicity and country or origin, the number of cases and controls, source of controls, genotyping methods, genetic distribution, and P value of Hardy-Weinberg equilibrium (HWE) among the controls. Studies not follow HWE were excluded in subgroup analysis. We applied the Newcastle-Ottawa Scale (NOS) to evaluate the methodological quality of the eligible studies according to Zeng et al . Accumul2 statistic were applied to examine the statistical heterogeneity among studies. When no obvious heterogeneity existed across the studies (P>0.10 or I2 <50%), we pooled the ORs using fixed-effect model (Mantel– Haenszel); otherwise, the random effects model (DerSimonian and Laird) was chosen. The potential publication bias was evaluated by funnel plot and Egger's test. To access the stability of the results in this meta-analysis, we performed sensitivity analysis by sequentially excluding each study and rechecked whether the pooled ORs were altered significantly.To evaluate the strength of association between hMLH1 polymorphisms  and cancer risk, we calculated the odds ratios (ORs) and 95% confidence intervals (CIs) based on the genotype and allele frequencies in cases and controls of each eligible study. We used the Z test to access the significance of all pooled ORs and it was considered statistically significant if the P value < 0.05. The Chisquare-based Q statistic test and IThe following genetic models were evaluated: allele comparison (B vs. A), homozygote comparison (BB vs. AA), heterozygote comparison (AB vs. AA), recessive model (BB vs. AA+ AB), and dominant model (BB+ AB vs. AA). “A” represents the wild allele, while “B” represents the mutation allele. After excluded studies not according to HWE, we conducted the subgroup analysis based on ethnicity (divided into Asian and Caucasian), cancer type, and source of control. All statistical analyses were calculated with the software STATA .


According to recent evidence, up to 40–50% of variance in autism spectrum disorder (ASD) liability might be determined by environmental factors. In the present paper, we conducted a review of systematic reviews and meta-analyses of environmental risk factors for ASD. We assessed each review for quality of evidence and provided a brief overview of putative mechanisms of environmental risk factors for ASD.Current evidence suggests that several environmental factors including vaccination, maternal smoking, thimerosal exposure, and most likely assisted reproductive technologies are unrelated to risk of ASD. On the contrary, advanced parental age is associated with higher risk of ASD. Birth complications that are associated with trauma or ischemia and hypoxia have also shown strong links to ASD, whereas other pregnancy-related factors such as maternal obesity, maternal diabetes, and caesarian section have shown a less strong (but significant) association with risk of ASD. The reviews on nutritional elements have been inconclusive about the detrimental effects of deficiency in folic acid and omega 3, but vitamin D seems to be deficient in patients with ASD. The studies on toxic elements have been largely limited by their design, but there is enough evidence for the association between some heavy metals (most important inorganic mercury and lead) and ASD that warrants further investigation. Mechanisms of the association between environmental factors and ASD are debated but might include non-causative association (including confounding), gene-related effect, oxidative stress, inflammation, hypoxia/ischemia, endocrine disruption, neurotransmitter alterations, and interference with signaling pathways.Compared to genetic studies of ASD, studies of environmental risk factors are in their infancy and have significant methodological limitations. Future studies of ASD risk factors would benefit from a developmental psychopathology approach, prospective design, precise exposure measurement, reliable timing of exposure in relation to critical developmental periods and should take into account the dynamic interplay between gene and environment by using genetically informed designs.The online version of this article (doi:10.1186/s13229-017-0121-4) contains supplementary material, which is available to authorized users. Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by persistent impairment in social communication and interaction and restricted and repetitive patterns of behavior, interests, or activities . There iWhile in the majority of cases of the exact etiology of ASD remains unknown, novel technologies and large population-based studies have provided new insight into the risk architecture of ASD and the possible role of environmental factors in etiology . Twin stIn the present paper, we provide an evidence-based review of the current knowledge about environmental risk factors in ASD using findings from published systematic reviews and meta-analyses. Although reviewing systematic reviews and meta-analyses inherently focuses on the most well-studied findings, it automatically excludes the studies that are published after the included reviews or that, for any reason, are not systematically reviewed. It is therefore important to keep in mind that the purpose of this review is not to review all possible environmental risk factors, but rather to provide a wide view of the evidence landscape in epidemiology of risk factors for ASD.I2 > 50% or P value of heterogeneity test < 0.10), magnitude of association , publication bias, and indirectness (that is measuring exposure based on population-level assessment) . As. As31]. Jiang et al.  systematA meta-analysis of ten studies by Chen et al.  found thConti et al.  conducteGentile  systematThe association between maternal antidepressant use during pregnancy and ASD is more controversial. Kobayashi et al.  quantitaA meta-analysis of 15 studies by Rosen et al.  found prSeveral studies have tried to establish an association between nutritional elements such as folic acid or vitamin D and risk for ASD. However, many of those studies are fundamentally limited by the fact that they have assessed the deficiency and/or the efficacy of supplementing these nutrients after developing ASD. Therefore, one should be very cautious about causal interpretation of the findings in those studies.A meta-analysis by Sharp et al.  showed sSystematic reviews of the association between omega-3 fatty acids and ASD have mainly focused on interventional studies. In a Cochrane review, only two small randomized trials met the eligibility criteria . The autCastro et al.  systematThere are reports of other dietary interventions such as camel milk and casein and gluten-free diet in ASD, but studies of such interventions have generally been short term and of low quality.Studies of toxic exposure have been largely limited by indirect and cross-sectional methods of exposure measurement. Quantitative systematic reviews have been performed on air pollution, thimerosal (ethylmercury), inorganic mercury, and hair levels of heavy metals. In a meta-analysis, Lam and colleagues  found a In a meta-analysis of nine studies, Yoshimasu et al.  found prDe Palma and colleagues  performeRossignol et al.  carried Rossignol and colleagues  also madStudies of the association between endocrine-disrupting chemicals and ASD are scarce. Rossignol et al.  reviewedTaylor et al.  performeIn a meta-analysis of five studies, Gardener et al.  found imA fundamental question about the association between environmental risk factors and ASD is whether the association represents an underlying causality or not. Although evidence in this area is still speculative, here, we briefly review the possible mechanisms of involvement of environmental factors in ASD. It should be emphasized that the mechanisms reviewed here are by no means exhaustive. Furthermore, each environmental factor—if causal—might involve multiple mechanisms and at different levels of etiological pathways to ASD.A plausible explanation for many of the observed environmental effects of ASD might be that of confounding. For example, the association between several obstetric complications and ASD might be partially confounded by parity, because parity is associated both with the exposure  and the outcome  . MoreoveIn addition to gene-environment correlation, environmental factors could interact with genetic components on various levels. It has been suggested that some environmental factors such as certain toxins and vitamin D deficiency increase the risk of gene mutation that in turn can lead to an increased risk of ASD . Recent Epigenetic mechanisms are biochemical modifications of DNA or histones that affect gene expression without changing the DNA sequence. Epigenetic mechanisms are thought to be critical in the normal development of the nervous system . Some enGenetic mechanisms also serve to make the individuals susceptible to the effect of certain environmental risk factors. For example, mutation of Mecp2 gene (the cause of Rett syndrome) and a regulator of the epigenome in neurons causes social deficit in mice with prenatal exposure to the organic pollutant polybrominated diphenyl ethers (PBDE) . ParaoxoASD is associated with altered immune status, increased oxidative stress, and an active neuroinflammatory process characterized by microglial activation in various parts of the brain –71. A meAnother meta-analysis has demonstrated an association between ASD and altered metabolism of glutathione, an antioxidant . Some enDeth et al.  has madeEvidence shows that perinatal hypoxia and hypercarbia are associated with various neurodevelopmental outcomes including seizure, cerebral palsy, and intellectual disability , 84. As ASD affects gender differentially. Not only the prevalence of ASD seems to be higher in boys but also the psychopathological, biochemical, and genetic aspects of ASD also appear to be different between males and females , 90. ThiAnother link between endocrine disruptors and ASD is alteration in thyroid function. Several studies have shown evidence of prenatal maternal thyroid dysfunction and ASD in the offspring , 97. IntAbnormalities in glutamate, serotonin, and gamma-aminobutyric acid (GABA) have been linked to ASD . AlthougSome environmental risk factors interact with intracellular signaling pathways and might pave the way to impaired neurodevelopment. Exposure to PCB and PBDE seems to alter calcium-related signaling pathway, leading to alterations in dendritic growth and subsequent abnormalities in neuronal connectivity, a key feature of ASD , 107. PrCompared to genetic studies of ASD, studies of environmental risk factors are in their infancy. Many previous studies of environmental risk factors have been limited by small sample size, retrospective or cross-sectional design, indirect measurement of exposure, and inability to ascertain exact timing of exposure with relation to a critical neurodevelopmental period. Moreover, for various reasons, most previous studies have not investigated important factors that might explain the heterogeneity of ASD such as differences in risk between males and females, differences between subtypes, and relation of symptom severity to risk factors. Importantly, the definition of ASD is very broad and encompasses multiple subtypes of the disorder, mirroring the etiological heterogeneity of the condition.As results from large prospective cohorts or birth registries are starting to emerge, more valuable data on environmental risk factors become available. Still, heterogeneity of ASD, indirect measures, lack of a dimensional approach, and diagnostic difficulties make it challenging to draw substantial inferences from these studies. As Mandy and Lai in their state in their recent review, to understand the ASD, we must engage with its complexity and take into the account the substantial heterogeneity of the factors that affect its onset as well as its course . StudiesFurthermore, it is difficult to establish causality from observational studies due to possibility of genetic and/or environmental confounding. What is interpreted as an environmental effect might indeed be an epiphenomenon due to gene-environment correlation. Therefore, focus should be on designing studies that strengthen causal inferences of environmental risk by ruling out alternative explanation for the association. Studies that use genetically informed approach  offer a new way to address the challenge of gene-environment correlation . MoreoveIn the present paper, we reviewed systematic reviews and meta-analyses of environmental risk factors for ASD. Current evidence suggests that several environmental factors including vaccination, maternal smoking, thimerosal exposure, and most likely ART are unrelated to risk of ASD. Birth complications that are associated with trauma or ischemia and hypoxia have shown strong links to ASD, whereas other pregnancy-related factors such as maternal obesity, maternal diabetes, and C/S have shown a weak association with risk of ASD. Furthermore, factors such as maternal use of SSRI or C/S might be indicative of confounding by indication. The reviews on nutritional elements have yielded limited useful and/or inconclusive information about the beneficial effects of folic acid and omega-3, while vitamin D deficiency seems to be common in children with ASD. The studies on toxic elements have been largely limited by their design, but there is enough evidence for the association between some heavy metals (most important inorganic mercury and lead) and ASD that warrants further investigation. Reviews on the psychosocial risk factors for ASD are scarce, with maternal immigration being the only factor that has shown some association with ASD in systematic reviews. Biological underpinning of environmental risk factors of ASD are debated but might include non-causative association, gene-related effect, oxidative stress, inflammation, hypoxia/ischemia, endocrine disruption, neurotransmitter alterations, and interference with signaling pathways. Future studies of ASD risk factors would benefit from a developmental psychopathology approach, prospective design, precise exposure measurement, reliable timing of exposure in relation to critical developmental periods and should take into account the dynamic interplay between gene and environment by using genetically informed designs.


Several association analyses and linkage researches indicated that inherited genetic variations effectively influence differentiated thyroid carcinogenesis.2 based Q-statistic and I2 test were performed to assess heterogeneity using STATA software.The results from 15 published studies on differentiated thyroid carcinoma (DTC) were combined. The genetic model included rs965513, rs944289 and rs1867277. Meta-analyses were performed and cochran’s χSignificant results were noticed for rs965513(Odds Ratio(OR) = 1.162), rs944289) and rs1867277). In the subgroup analysis by ethnicity, rs965513 polymorphism conferred that risk of Caucasians ) was more than that of East Asians of 1.35 ).This meta-analysis revealed that common variations of FOXE1  were risk factors associated with increased DTC susceptibility. Thyroid cancer is classified as differentiated thyroid cancer and undifferentiated thyroid cancer according to histology. For further classification, differentiated thyroid cancer including papillary thyroid carcinoma and follictalar thyroid carcinoma, in which papillary thyroid carcinoma accounts for 75% in thyroid cancer –3. In thFOXE1 gene is a specific thyroid transcription factor. It plays an important role in the growth and development of thyroid gland, the proliferation and differentiation of thyroid follicular cells. It is the key regulator of cellular function, including cell growth and differentiation, and plays an important role in the process of tumor development, invasion and metastasis. Therefore, this meta-analysis was conducted to make this discrepancy clear and to create a comprehensive picture of the association between common variants on FOXE1 and differentiated thyroid cancer.Recently, significant progress has been made in the study of the association between DTC and susceptible genes through the genome-wide association strategy (GWAS). Single nucleotide polymorphisms (SNPs) related with DTC risk on chromosomes 5q24, 8q24, 9q22, and 14q13 had been identified by several recent studies –10. The google.com/) to query the articles citing these studies and all of the references therein as identified using PubMed.A comprehensive electronic literature search of the PubMed Database, EmBase Database, Cochrane Library and China National Knowledge Infrastructure (CNKI) from January 1981 to April 2016 was conducted. Two researchers carried out literature search independently. The search terms were as follows:  “associaP value or the study provided sufficient data to calculate the OR and 95% CI [The inclusion criteria were as follows:  the studd 95% CI  no lappiTwo authors assessed possibly related articles independently complying inclusion criteria and exclusion criteria. If there is disagreement between two researchers, a third author will help to solve it.The following information was extracted from every study:  the firsThe rs965513 polymorphism includes the two alleles G and A, of which A is the minor allele. A is assumed to be the high-risk allele and G the low-risk allele. The rs944289 involves the two alleles T and C, and T is the major allele which is reported to be the high-risk allele. In rs1867277, there existed two alleles G and A, in which A is the minor allele and assumed to be the high-risk allele. Additive, dominant, recessive genetic model were adopted for further meta-analysis. The additive model can be described as the A allele versus the G allele or the T allele versus the C allele.2 statistics [2 [2 value is 25%, it corresponded to no or little heterogeneity. The value 25 - 50% corresponds to the moderate heterogeneity, and the value 50% corresponds to the strong heterogeneity between studies. The random effect and the fixed effect are taken as the weighted average of the inverse variance of the logarithmic dominance ratio. The results of the random effect summary are reported in the text, because it takes into account the differences between the studies. Sources of heterogeneity were investigated by stratified meta-analyses based on ethnicity, sample size. Ethnic group was defined as East Asians, and Caucasians. Publication bias was assessed with the Begg’s and Egger’s t. Sensitivity analysis [P values were two-side analysis, and 0.05 were considered statistically significant.The risk of differentiated thyroid cancer with the relative intensity of the associated intensity of FOXE1 polymorphism was evaluated by crude ORs value with the corresponding 95% CIs. Cochran's χstics [2  were useanalysis  is conduA total of 528 articles were initially searched out after the primary selection, and finally 15 researches –27 were To analyze the association between rs965513 polymorphism and differentiated thyroid cancer, we performed the random effect model to calculate the total OR of the Caucasus population, and used the fixed effect model to analyze the heterogeneity in the East Asian population. The risk of thyroid cancer associated with the A allele was 1.16-fold that of the G allele .The genetic heterogeneity of the rs965513 polymorphism was evaluated based on the additive, dominant and recessive models and the data from the selected studies Table . The hetP< 0.0001; dominant: OR = 0.867, P<0.0001; recessive: OR = 1.284, P<0.0001). However, no significant associations were observed for East Asians , P=0.822; dominant: OR = 1.424 , P=0.721; recessive: OR = 0.678, P=0.085). To take the population scape into consideration, the samples were divided into <500 and ≥500. No.cases<500 was small samples group and no.cases≥500 was large sample group. When the number of cases was considered, both no.cases<500 and no.cases≥500 were significantly associated. For less than 500 group, the results showed that risk allele: OR = 1.32, P=0.029; dominant: OR = 0.578, P=0.043; recessive: OR = 1.92, P<0.0001). For more than 500 group, the results showed that risk allele: OR = 1.153, P<0.0001; dominant: OR = 0.881, P<0.0001; recessive: OR = 1.231, P<0.0001).In view of the significant heterogeneity and the search for its potential sources, we conducted a group of subgroups of race and sample size. When the race is stratified, the caucasians have a significant risk in all the comparisons. , Similarly, in the heterogeneity test of the rs944289 polymorphism, three models were significant and OR were 1.082, 1.127 and 0.974 in allele risk, dominant model and recessive model respectively. Except recessive model in East Asian was insignificant, two other models in East Asian and three models in Caucasian were significant. In Caucasian, the OR values in allele risk, dominant and recessive models were 1.067, 1.151 and 0.948 respectively. In East Asian, the OR values in allele risk and dominant were 1.764 and 0.548 respectively. In the heterogeneity test of the rs1801516 polymorphism, three models were significant and OR were 1.415, 0.631 and 1.583 in allele risk, dominant model and recessive model respectively. Dominant models in Caucasian and East Asian were insignificant and risk allele in East Asian was insignificant. In risk allele model of Caucasian, OR value was 1.463. In Caucasian and East Asian populations, the OR values in recessive model were 1.644 and 0.952 respectively.Sensitivity analysis was carried out to assess the robustness of the meta - analysis results Fig. . The pooP=0.005). However, Kang et al. evaluated the association of 12 SNPs in FOXE1 and PTC, and reported that rs965513 showed no association with PTC [It is reported that female, Asian, highly educated, history of goiter and family history of thyroid disease are risk factors for thyroid cancer. Zhu stated that differentiated thyroid cancer was a kind of disease which was influenced by several factors –30. Compwith PTC . It is iP<0.0001). When the number of cases was considered, both no.cases<500 and no.cases≥500 were significantly associated. For less than 500 group, the A allele had a 1.32 fold risk. For more than 500 group, the results showed that the A allele had 1.153 fold risk. The sensitivity analysis suggested that the results of this meta-analysis were stable. For short, the Caucasian populations had higher risk than East Asian populations. These were consistent with several previous researches [In this meta-analysis, the heterogeneity of rs965513 among the included studies was assessed, and there existed significant heterogeneity among the additive, dominant and recessive models. To further analyze the heterogeneity, stratified test was conducted and it showed that significant heterogeneity was observed among Caucasian populations but was not found in Asian populations. Meanwhile, both in no.case<500 and no.case≥500 groups, the heterogeneity was significant. These results may be resulted from that more studies corresponded to Caucasian populations, and the number of different case amount was similar. When studies were stratified for ethnicity, significant risks were found among Caucasians in all models, the A allele had a 1.1.62 fold risk. Compared with the dominant model, the recessive model showed the highest odds ratio in Caucasians populations , searches , 32.In addition, rs944289 among the selected studies had significant heterogeneity. The heterogeneity in the additive, dominant and recessive models were significant. The stratified results showed that three models in Caucasian and East Asian were significant. The risk of the T allele was 1.067 fold  in Caucasian populations and that was 1.764 fold  in East Asian populations. In No.cases <500 group, the T allele had 0.97 fold risk  and in No. cases≥500 group, the T allele had 1.093 fold risk . In conclusion, in rs944289, East Asian had more risk than Caucasian populations.At last, the research about heterogeneity in rs1867277 was carried out. Through subgroup analysis, we divide race into a potential source of heterogeneity. In the race stratified analysis, it is observed that association between rs1867277 polymorphism and risk for DTC in Caucasians  was stronger than that in East Asian populations . In the tratified analysis by number of cases, that association between rs1867277 polymorphism and risk for DTC in No.cases<500  was stronger than that in No.cases≥500 . Therefore, the Caucasian populations had higher risk than East Asian populations concerning rs1867277. These conclusions were similar with some previous studies –35.In inferring the results, some limitations of this meta-analysis should be added. At first, in this study, the majority of subjects are of European descent, so statistical power for analyses in other ethnicities is limited. This is due to the small sample size in East Asia studies. Therefore, The main conclusion of the manuscript is based on the analysis between the Caucasus. In the further studies, more East Asians or Africans are needed to clarify the consistency found by different ethnic groups. Second, meta-analysis is a kind of retrospective study, which might lead to the recall and selection bias.Despite these limitations, this meta-analysis suggested that the three common variations on FOXE1  had significant relationship with the increase in the risk of DTC, particularly in Caucasian population. Since the study of other ethnic groups is still limited, further studies will include a wider range of subjects to investigate the role of these variants in other populations. Besides, the possible gene-gene and gene-environmental interactions in this association would be explored in the further researches.This meta-analysis suggested that common variations of FOXE1  were risk factors associated with increased DTC susceptibility.


G6PC2) allele variants with elevated fasting glucose (FG) and type 2 diabetes (T2D).To collectively evaluate the association of glucose-6-phosphatase catalytic unit 2 , p = 5.856e-48, respectively). With regard to the relationship of rs16856187 and FG, an increase of 0.152  and 0.317  was found in the standardized mean difference (SMD) of FG for the AC and CC genotypes, respectively, when compared with the AA reference genotype. However, the G-allele of rs560887 in Caucasians under the additive model and the C-allele of rs16856187 under the allele and dominant models were associated with a decreased risk of T2D (OR (95% CI) = 0.964 , p = 0.570e-4; OR (95% CI) = 0.892 , p = 0.001; and OR (95% CI) = 0.923, p = 5.301e-6, respectively).Of the 423 studies identified, 21 were eligible and included. Data on three loci  were available. The G allele at rs560887 in three ethnicities, the C allele at rs16856187 and the A allele at rs573225 all had a positive association with elevated FG. Per increment of G allele at rs560887 and A allele at rs573225 resulted in a FG 0.070 mmol/l and 0.075 mmol/l higher (ß (95% CI) = 0.070 , G6PC2  are associated with elevated FG, with two variants  being associated with T2D as well. Further studies utilizing larger sample sizes and different ethnic populations are needed to extend and confirm these findings.Our meta-analyses demonstrate that all three allele variants of  Fasting plasma glucose (FPG) levels are associated with a risk of type 2 diabetes (T2D) and cardiovascular disease . There iG6PC2) gene in mice led to a significant decrease in blood glucose ,  and  in Caucasians, Asians and African-Americans, respectively , , ] in Caucasians, Asians and African-Americans, respectively.Meta-analysis estimates of SNP associations with FG are presented in ectively . Heterog2 = 58%, 95% CI: 0, 88%; H2 = 1.36) for AC vs AA while no heterogeneity was observed  for CC vs AA  and 0.317  increased in SMD of FG for AC and CC genotypes was found when compared to the AA reference genotype, respectively. Heterogeneity was observed , with no heterogeneity observed   .p = 0.076), with low heterogeneity . In Asians, rs560887 also had no association with risk of T2D  (p = 0.570e-4), with no heterogeneity observed . When both the pooled RAF and the pooled per-allele OR were taken into account, the presence of each risk allele would be associated with a 5.4%, 5.3% and 18.3% increase in incidence of T2D according to the PAR estimate in total sample, Caucasian and Asians subgroup, respectively.In the overall estimate, no association was detected between the rs560887 and risk of T2D  . Conversp = 0.001) with low heterogeneity among studies  (p = 5.301e-6) with no heterogeneity among studies  (p = 0.596) with high heterogeneity among studies   . Under t = 0.00) . Under t = 3.28) . Resultsp > 0.1). In the sensitivity test  in the G6PC2 gene for an effect on FG and two SNPs (rs560887 and rs16856187) for an association with T2D. We found that all three SNPs were associated with elevated FG level in participants with normal glucose regulation, and rs560887 in the Caucasians subgroup and rs16856187 under allele and dominant model were all associated with T2D.To the best of our knowledge, this is the most comprehensive meta-analyses on the evaluation of the associations between However, no associations with T2D risk were found for G at rs560887 in overall and Asians populations, which is consistent with a meta-analysis published in 2013.G6PC2 with T2D in the Chinese population in the near future.There may be some reasonable explanations for these differences between ethnic groups. First, the gene-gene interactions and different environmental factors may affect susceptibility to the genetic variant and diabetes , 74. SecG6PC2 belongs to the G6PC family of proteins, which catalyze the dephosphorylation of glucose-6-phosphate to glucose [G6PC2 activity might be connected to the relative expression of the full-length active protein [G6PC2 variants and insulin secretion [G6PC2 rs560887 displayed a higher risk of type 2 diabetes and a higher FPG level in Asians. It is unclear whether ethnic differences in beta cell function [ glucose . Thus, g glucose . However glucose , 6. The  protein , 77. Stu protein . Recent ecretion . The allecretion . Howeverfunction , 80 contG6PC2 among Asians were correlated with a higher risk of T2D [G6PC2 with FG and T2D.In addition, we also found that the presence of T at rs13387347, A at rs2232316, G at rs492594, A at rs483234, T at rs3755157 and C at rs478333 in k of T2D , 65, 69.k of T2D , 65, 69.G6PC2 SNPs (rs560887 and rs573225) when pooled, which was not seen in the previous studies. This is currently the most comprehensive meta-analyses on G6PC2.This study shows that ß value (linear regression coefficient) rather than SMD for the association of FG with Some limitations in our meta-analyses should be mentioned. First, our results on FG and T2D were based on slightly different adjusted estimates. Second, the studies included in the analyses may be insufficient to allow firm conclusions. Thus, potential publication bias is likely to exist, in spite of the lack of evidence for this obtained from our statistical tests. The power to detect bias is limited, particularly for moderate amounts of bias or meta-analyses based on a small number of small studies . Third, S1 Supplement(DOC)Click here for additional data file.S2 Supplement(DOC)Click here for additional data file.S3 Supplement(DOC)Click here for additional data file.S4 Supplement(DOC)Click here for additional data file.S1 FigFunnel plot of publication bias for the association of rs560887 (A), rs16856187 (CCvsAA) (B) and (ACvsAA) (C), rs573225 (D) with FG, rs560887 (E), rs16856187 under allele (F), dominant (G) and recessive (H) with T2D, respectively.(TIF)Click here for additional data file.S2 FigSensitivity tests for the association of rs560887 (A), rs16856187 (CCvsAA) (B) and (ACvsAA) (C), rs573225 (D) with FG, rs560887 (E), rs16856187 under allele (F), dominant (G) and recessive (H) with T2D, respectively.(TIF)Click here for additional data file.


Evidences have identified the correlation of 8-oxoguanine DNA glycosylase-1 (OGG1) and eph-receptor tyrosine kinase-type A2 (EPHA2) polymorphisms in age-related cataract (ARC) risk. However, the results were not consistent. The objective of this study was to examine the role of these two gene polymorphisms in ARC susceptibility.Eligible case–control studies published between January 2000 and 2015 were searched and retrieved in the electronic databases. The odds ratio with 95 % confidence interval (CI) was employed to calculate the strength of the relationship.P = 0.01) and dominant model , especially in patients with cortical cataract of subgroup analysis by phenotypes (P < 0.05). For EPHA2 rs7543472 and rs11260867, we did not find a positive association between these two mutations and ARC susceptibility in total cases. Subgroup analysis by phenotypes of cataract showed that only in cortical cataract, genotypes of rs7543472 under the allele model, homogenous model and recessive model; genotypes of rs11260867 under the heterogenous model and dominant model were associated with ARC risk.We totally screened out six articles, including 5971 cataract patients and 4189 matched controls. Three variants were contained . For OGG1 rs1052133, we detected a significant correlation between OGG1 polymorphism and ARC risk under the heterogenous model  might be risk factor for ARC, particularly in cortical cataract risk. EPHA2 rs7543472  and rs11260867 (CG and GG+CG genotypes) might be associated with cortical cataract. Cataract is a leading cause of blindness and visual impairment throughout the world, increasing the public health and economic burden of this disease . AccordiEtiological research have found that the set of genes were associated with cataract, especially for ARC . In receEPHA2, located in human chromosome 1p36, is a member of the Eph receptor tyrosine kinases family . It is aAlthough epidemiologic studies have identified the correlation of these genes polymorphisms in ARC risk, however, the results remain inconclusive. Therefore, we conducted this meta-analysis to establish the true association between OGG1 and EPHA2 SNPs and the risk for ARC.We performed a comprehensive literature search in the following electronic databases of Medline, PubMed, Springer and Elsevier to retrieve relevant articles published between January 2000 and 2015. The key terms were “cataract” or “age-related cataract”, “8-oxoguanine glycosylase-1 or OGG1 or DNA repair gene”, “Eph-receptor tyrosinekinase-type A2 or EPHA2”, and “variant or polymorphism” as well as their combinations. References of related studies were manually searched to obtain more sources. Only studies written in English were included in this meta-analysis.The inclusion criteria were as follows: 1) case–control studies concerning the role of OGG1 or EPHA2 polymorphisms in ARC risk; 2) patients with ARC was defined as lens opacity along with disturbance of vision and were over 50 years old ; controThe exclusion criteria were: 1) review reports or conference papers; 2) without control group; 3) studies with duplicate data; and 4) genotype information couldn’t be extracted.Two investigators independently assessed the quality of related articles. Any disagreement was subsequently resolved by discussion with another expert to reach a consensus on all of the items. The following information was extracted from each article: first author, year of publication, country, ethnicity, mean age, sample size, genotyping method, and genotype distribution in cases and controls.P value less than 0.05 was considered statistically significant. For all the genetic polymorphisms, the comparison models  were examined. The I2 test and the Q-statistic test were used to estimate between-study heterogeneity. The random-effect model was employed when the P-value less than 0.10 for the Q-test and I2 more than 50 %; otherwise, the fixed-effects model was used. The evidence of publication bias was assessed by visual funnel plot inspection. Statistical analyses were conducted in Review Manager . All the tests were two-sided.The strength of association between polymorphisms of OGG1, EPHA2 and ARC risk was measured by the pooled ORs with its 95 % CI. The Z test was employed to determine the significance of the pooled ORs, and a P > 0.05). Tables We finally screened out 6 relevant articles, including 5971 cataract patients and 4189 controls. Figure Table P = 0.05). This insignificance was also found under the homogenous model and recessive model (P > 0.05). But we detected a significant correlation between OGG1 polymorphism and ARC risk in the heterogenous model  and dominant model  in the fixed-effect model as shown in Fig. P = 0.03) and dominant model . Figure Three articles concerned the OGG1 variant, including 1069 patients and 680 controls. Although the frequency of G allele (minor) was shown to be higher in ARC cases than that in controls (45.4 versus 35.5 %), our result found that the G allele was not associated with ARC susceptibility in the random-effect model . Subgroup analysis by phenotypes of cataract showed a significant relationship between rs7543472 and cortical cataract under the allele model , homogenous model  and recessive model  in the fixed-effect model as shown in Fig. Three articles contained 4902 cases and 3509 controls evaluating the association of EPHA2 genetic polymorphisms and ARC occurrence. For rs7543472, our result found that this variant was not associated with ARC risk under any genetic models  and dominant model  as shown in Fig. For rs11260867, we did not observe a significant positive correlation between this variant and ARC risk under any genetic models as well Table . SubgrouTo confirm whether each included study influences the overall results or not, we successively omitted each single study, respectively. Our result found that the pooled ORs were not significantly changed. The funnel plots were used to evaluate the publication bias. All the plots were found to be roughly symmetrical, indicating no publication bias presented as shown in Fig. In this meta-analysis, we totally identified six articles concerning three genetic polymorphisms. Our results showed that CG genotype and GG+CG genotype of OGG1 rs1052133 were associated with increased the risk of ARC, in particular with cortical cataract. This significant relationship was not found in EPHA2 polymorphisms (rs7543472 and rs11260867), however, subgroup analysis by phenotypes of cataract showed that only in cortical cataract, the genotypes of rs7543472 under the allele model, homogenous model and recessive model; genotypes of rs11260867 under the heterogenous model and dominant model were associated with ARC risk. This was the first meta-analysis concerning these three SNPs in ARC risk.Cataract is the single largest contributor to blindness in the world. Age is the major risk factor for cataract. Even though several measures have been identified as a solution for cataract treatment , 36, theOGG1 is involved in multiple vital processes. Recent studies showed that OGG1 was highly expressed in the embryonic brain, and lack of OGG1 might cause severe brain defects in brain integrity, balance and mobility . The aceEPHA2 is an epithelial cell tyrosine kinase, and was shown to be enriched in adult tissues . It is hSeveral limitations were presented in this meta-analysis. First of all, the number of included studies for each SNP was small, future large-scale researches with more ethnicities are needed to further evaluate the relationship. Secondly, between-study heterogeneity was presented in several comparisons. Thirdly, we did not conduct the subgroup analysis by ethnicities due to the less data, which should be concerned in the future. Lastly, gene-gene and gene-environment interactions were not addressed in our meta-analysis.Our results indicated that CG genotype and GG+CG genotype of OGG1 rs1052133 might be risk factor for ARC, especially in cortical cataract risk. The T allele and TT genotype of EPHA2 rs7543472; CG genotype and GG+CG genotype of EPHA2 rs11260867 were associated with cortical cataract risk. Future studies are still required to re-evaluate the results of OGG1 and EPHA2 polymorphisms in ARC risk.


ADAM12 gene is one of the recognized candidate genes although the results are conflicting. To derive a more precise estimation of the association between rs3740199 polymorphism in ADAM12 gene and risk of knee OA, we performed a meta-analysis based on six related studies, including a total of 2185 cases and 3716 controls.Knee osteoarthritis (OA) is a complex arthritic condition in which genetic factors play an important role. A comprehensive search was performed to identify related studies up to April 14, 2017. We used odds ratios (ORs) with 95% confidence intervals (CIs) to assess the strength of the association. Different genetic models were used to assess the pooled and stratified data.Overall, no significant association was found in all genetic models . When stratified by ethnicity, no significant association was found.This meta-analysis suggested that the rs3740199 polymorphism does not contribute to the development of knee OA. Additional well-designed large studies are required to confirm these findings in different populations. ASPN [FRZB [GDF5 [Osteoarthritis (OA) is a complex arthritic condition characterized by progressive cartilage loss, synovitis, osteophyte formation, and subchondral sclerosis. It is a cause of important handicap among the elderly , 2. It hASPN , FRZB [9ZB [GDF5 . These tZB [GDF5 . Many otZB [GDF5 .ADAM12 may play an important role in chondrocyte proliferation, maturation, bone formation, and osteoclast differentiation [ADAM12 with OA [. [ADAM12 was associated with knee OA risk although the results were conflicting rather than conclusion [A disintegrin and metalloprotease (ADAM), a member of the Zn-dependent metzincin superfamily, is associated with many complex diseases such as heart disease, rheumatoid arthritis, Alzheimer’s disease, and cancer , 14. ADAntiation –18. ADAMntiation , 20. Rec with OA –25. Poonth OA [.  and Kernnclusion , 26, 27.ADAM12 rs3740199 polymorphism and knee OA susceptibility and whether the association varies by ethnicity.In the present study, a meta-analysis was performed to determine the overall association between ADAM12,” “polymorphism” or “polymorphisms” or “SNP,” “osteoarthritis” or “OA”. Additional eligible studies were identified by a manual search of the references of retrieved studies and review articles.To identify all relevant reports on rs3740199 polymorphism and knee OA risk, we performed a systematic search for all English language papers from PubMed , using the key words “rs3740199” or “ADAM12 rs3740199 polymorphism and knee OA risk; and (3) contained available genotype or allele frequency of rs3740199.According to the following criteria, six studies were included in this meta-analysis: (1) was a cohort or case-control study; (2) was a study of the Two of the investigators extracted all data independently according to the criteria described above. We developed a data extraction sheet including year of publication, the first author’s name, OA type, country of origin, ethnicity, assessment of OA, genotyping method, source of control groups, genotype, and allele frequency. For studies contain the results from different knee OA types, each type was treated independently. Any controversies of the data were discussed within our research team and the authors reached a consensus on all items.ADAM12 rs3740199 polymorphism from the six eligible studies were calculated by the allele counting method respectively. Hardy–Weinberg equilibrium (HWE) was used to evaluate the deviation of data associated with the ADAM12 rs3740199 SNP in the control groups using χ2 test. The strength of association between the ADAM12 rs3740199 polymorphism and knee OA susceptibility was evaluated by pooled odds ratios (ORs) and their 95% confidence intervals (CIs). The significance of the ORs and 95% CIs was determined by Z test. The pooled ORs and 95% CIs were performed for additive model (C vs. G), co-dominant model , dominant model (CC/CG vs. GG), and recessive model (CC vs. CG/GG). Stratified analysis was also performed by ethnicity.Allele frequencies of the Q test. If the P value was less than 0.10, the heterogeneity was considered significant. We also used the I2 statistic (I2 = 100% × (Q − df)/Q) to quantify heterogeneity. I2 greater than 50% indicated the presence of heterogeneity among studies. The fixed-effects model based on the Mantel–Haenszel method and the random-effects model based on the Dersimonian and Laird method were used to pool the data [We assessed the between-study heterogeneity using chi-square-based the data . The ranIn meta-analysis, publication bias is also a concern. To test for publication bias, both Egger’s and Begg’s test are commonly used . In thisAll analyses were carried out using Stata software version 8.2 . All tests were two-sided.Eleven relevant studies identified and screened. Four studies were added through manual search of the reference lists of retrieved studies. Nine of the 15 studies were excluded: three not polymorphism, one not for OA research, and five no useable data reported. A total of six reports were identified , 23–27. ADAM12 rs3740199 polymorphism with knee OA risk are shown in Table The details of meta-analysis for ADAM12 rs3740199 polymorphism and knee OA risk. No significant association was found in all genetic models  . No significant association was found in European population either.ADAM12 rs3740199 polymorphism was not found in all subjects, and thus, the meta-analysis of the ADAM12 rs3740199 polymorphism was performed using a fixed-effects model for all subjects except for the recessive model in European population, which was analyzed using a random-effects model (I2 = 73.4%) .In this study, publication bias was evaluated by funnel plot and the linear regression asymmetry test. As shown in Fig. ADAM12 gene is one of the possible candidate genes for OA [ADAM12 in chondrocyte proliferation, maturation, bone formation, and osteoclast differentiation [ADAM12 in knee OA risk that has been reported to date [OA is well recognized as a multifactorial disease. In addition to age, sex, trauma, and body weight, genetic factors are also strong determinants of this disease . More ths for OA –27. Somentiation –18. Asso to date , 26, 34.ADAM12 rs3740199 polymorphism with knee OA risk in different ethnic populations. To our knowledge, the present study is the first meta-analysis which estimated the association between ADAM12 rs3740199 and knee OA susceptibility. No significant association of ADAM12 rs3740199 polymorphisms with knee OA risk was demonstrated in our study. We also failed to find the association between knee OA and the ADAM12 polymorphism in Asian and European population. No heterogeneity was found in overall population and Asian population, while high heterogeneity was seen in the recessive model in European population.Meta-analysis is a suitable method to combine the results of individual studies, overcome the disadvantages of a single study, and increase the statistical power. The present study was to investigate and update the results associating the ADAM12 rs3740199 polymorphism and knee OA risk, which is not consistent with the association or functional studies of the ADAM12 polymorphism. However, epidemiologic results are always different from the functional studies because OA is a multifactorial disease influenced by different genetic backgrounds, multiple genes, and environmental factors. Our negative results of the ADAM12 polymorphism may also be due to type II error. In recent years, some genome-wide association studies (GWAS) have already reported GDF5, BTNL2, DUS4L, COG5, SENP6, and FILIP1 as OA candidate genes [ADAM12 polymorphism has not been confirmed in these GWAS [Association studies with complex outcomes for detecting genetic variants must be considered with caution because the results may be influenced by many factors. Our present study showed a lack of association between the te genes , 36. Howese GWAS , 36.ADAM12 rs3740199 and PFOA in male patients [ADAM12 rs3740199 genotypes and alleles from subjects with different ethnicities.Our results are consistent with some studies that also failed to detect association between rs3740199 and OA susceptibility in either male or female patients , 26, 27.patients . The reaADAM12 gene. Third, because it was difficult to get all full papers published in different languages, we only included six studies published in English language. Fourth, the included subjects were not adequate to confirm a robust conclusion and the association should be resolved by larger studies.Some limitations of this meta-analysis should also be noted. First, the potential confounding factors  were not adjusted in the present study. Second, the gene-environment interactions and the effect of gene-gene should also be considered because they might influence the biological effects of the polymorphisms of the ADAM12 rs3740199 polymorphism and knee OA risk. Additional larger studies are needed to confirm our findings in the future.In conclusion, this meta-analysis did not reveal any association between the


P = 0.002, I2 = 37.80%). The OR of T vs. C for good TR was 0.554 . Few significant outcome was observed in subgroup analyses stratified based on study characteristics with adjustments for potential confounders. Our results suggest that ERCC1 rs11615 CC is associated with a better clinical outcome. This suggests rs11615 may be a useful genetic marker for predicting osteosarcoma prognosis.To investigate correlations between excision repair cross-complementation group 1 (ERCC1) and 2 (ERCC2) polymorphisms and osteosarcoma prognosis, we conducted a meta-analysis of studies published through October 2016. Studies were identified in the PubMed, ScienceDirect, Springer, and Web of Science databases using preferred reporting items for systematic reviews and meta-analyses (PRISMA). Odds ratios (ORs) or hazard ratios (HRs) and their 95% confidence intervals (CIs) for overall survival (OS), tumor response (TR), and event-free survival (EFS) were estimated. Our meta-analysis included eleven studies in which four SNPs  reportedly associated with osteosarcoma prognosis were investigated. Each of these studies scored > 6 on the Newcastle-Ottawa Scale (NOS). We found that only one SNP, ERCC1 rs11615, correlated with improved OS and TR. The HR of T vs. C for OS was 1.455 (T/C, 95% CI = 1.151–1.839,  VEGF, GRM4, GSTP1, ABCB1, and key enzymes of the DNA repair system, have been identified as osteosarcoma biomarkers that may predict patient susceptibility and prognosis [Osteosarcoma is one of the most common and aggressive malignant bone tumors, primarily occurring during adolescent growth and in the elderly . Osteosarognosis .DNA repair is critical for maintaining DNA stability and integrity, and cell function. The nucleotide excision repair (NER) pathway is responsible for recognizing and excising DNA lesions . ExcisioThe combined search yielded 556 potentially relevant references. References were screened by title, abstract, and full-text Figure . We founet al. and Hao, et al., rs13181 referred to G/A, but was an A/C SNP of ERCC2 according to PubMed dbSNP, websites of dbSNP of the studied SNPs were provided in et al. study, rs1799793 referred to G/T, but was a G/A SNP of ERCC2 according to PubMed dbSNP. We therefore excluded these rs13181 and rs1799793 studies. Additionally, two rs11615 genotype formats were referred to as T/C and C/T, which was also the case in previous rs11615-related studies, and this issue remains unsettled.Data extracted from the 11 studies are shown in et al. and Liu, et al. Primary and adjusted PTR were only available in the study by Carolina, et al. Therefore, we used crude ORs from other studies so that this study could be included. OS was usually obtained from diagnosis until death by any cause or last follow-up. EFS was usually defined as the period before first relapse and after tumor diagnosis.In these 11 studies, we were able to examine tumor response (TR), overall survival (OS), and event-free survival (EFS). TR was categorized as either good (GTR) or poor (PTR). GTR was defined as the extent of tumor necrosis > 90% in histology or response (complete response (CR) and partial response (PR)) as per Response Evaluation Criteria in Solid Tumors (RECIST) criteria. Tumor necrosis < 90% or non-response (stable disease (SD) and progressive disease (PD)) as per RECIST criteria was defined as PTR. If the histological findings and RECIST criteria showed good homogeneity, subgroup analysis would be performed if necessary. RECIST criteria was employed to assess TR only in the studies by Yang, Newcastle-Ottawa Scale (NOS) assessments are shown in Table et al. into the pooled analysis, and these data were therefore excluded. Hattinger, et al. found that ERCC1 rs11615 and rs3212986 were not associated with osteosarcoma EFS. Meta-analysis results are shown in Statistical analysis was performed after study assessment and primary data extraction. This study included 1834 osteosarcoma cases. We were unable to merge OS/TR/EFS data extracted from the study by Hattinger, P = 0.002, I2 = 37.80%). For the ERCC2 rs1799793 G allele and the rs13181 A allele, we observed slightly positive OS trends, but these were not significant. In rs3212986, no significant outcome was observed. OS forest plot for rs11615 subgroup analysis is shown in Figure For ERCC1 rs11615, no correlation was observed in the pooled outcomes, but high heterogeneity was detected, which may have resulted from the unclear genotype designations discussed above. We observed a strong positive correlation between the C allele and OS in the T/C subgroup. The hazard ratio (HR) of the T vs. C OS model was 1.455 . The C/T subgroup showed no significance. For the ERCC2 SNPs, rs1799793 and rs13181, no significance was observed before sensitivity analysis. The rs1799793 A allele might have a better TR than the G allele, and the rs13181 C allele had a better TR than the A allele. No significance was found in rs3212986. GTR forest plot for rs11615 is shown in Figure For ERCC1 rs11615, the C allele was more significant in the T/C subgroup than overall outcomes. The odds ratio (OR) for CC vs. TT was 2.659  is a protein kinase C (PKC) inhibitor that inhibits the ERCC1/xeroderma pigmentosum group A (XPA) interaction, and may reduce ERCC1-induced cisplatin resistance. However, UCN-01 was not developed with the specific aim of reversing cisplatin resistance, and remains in Phase I clinical trials –36. Li, c cancer . Zhang, er cells . Similarer cells .et al. reported ERCC2 overexpression in cervical squamous cell carcinoma compared to normal cervical tissue [et al. found no ERCC2 expression changes in lung cancer-derived lymphocytes [ERCC1 overexpression indicated worse survival in osteosarcoma , 40 and l tissue , but Vogphocytes .ERCC1 SNP rs11615 in codon 118 reduces ERCC1 transcription  and is cet al. In addition, in ERCC1 rs11615, discrepancies between T/C and C/T remain unsettled [Our study had limitations. First, numerous factors were involved in tumor prognosis. Single SNPs are unlikely to be major factors affecting tumor prognosis. Gene-environment and gene-gene interactions, and the combined effects of multiple SNPs in several genes are more effective outcome predictors than single SNPs alone –78. Howensettled . While rnsettled , but it In conclusion, our meta-analysis indicated that ERCC1 rs11615 is associated with improved osteosarcoma prognosis. Additional studies with larger sample sizes are needed to more precisely estimate the correlation between ERCC polymorphisms and osteosarcoma prognosis.We conducted this meta-analysis based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement . PRISMA We comprehensively searched for potential references from the PubMed, ScienceDirect, Springer, and Web of Science databases using key words such as “ERCC,” “osteosarcoma,” “outcome,” etc. through October, 2016. Our detailed literature search strategy is provided in the Studies included in our analysis met the following criteria: (1) studies were limited to the published research concerning osteosarcoma prognosis and ERCC polymorphisms; (2) patients in the original studies must have been diagnosed with osteosarcoma via imaging, pathology, or the latest clinical diagnostic criteria, and genotyping was performed using valid molecular techniques; and (3) detailed patient data and the number of participants with distinct genotypes were published in the studies so that the adjusted or crude OR/HR value could be calculated. If the same or overlapping data appeared in multiple studies, the study with the largest sample size or most recent publication date was included in the meta-analysis.Data were extracted by two investigators independently and double-checked by a third investigator. Inconsistent data were addressed by open discussion and consensus was achieved via input from a senior investigator.Two investigators conducted literature quality assessments of the included studies according to the NOS developed for case-control studies , and theP < 0.05 was considered a significant imbalance. Adjusted HRs/ORs from confounders  in every model were used in our meta-analysis; otherwise, crude HRs/ORs calculated by Revman 5.3 software or given were used. Pooled data had low heterogeneity if P > 0.1 and I2 < 50%. In these cases, a fixed effects model was used; otherwise, a random effects model was used. Statistical analysis of pooled data was performed using models as follows: 12 versus 11, 22 versus 11, 12 versus 22, 12+22 versus 11, 1 versus 2 .Stata 11.0 software was used to perform this meta-analysis. A Hardy-Weinberg equilibrium (HWE) test was performed using extracted data, and P < 0.05 was considered significant. Z-score was evaluated by the P value of two-sided u-test for overall effect estimation.Tumor-related indexes, including TR, OS, and EFS, were assessed if the number of studies containing usable data was greater than 3. Statistical analyses were two-sided and et al. study [Subgroup analyses were conducted based on study characteristics, to investigate sources of heterogeneity and potential correlations. As per the Savage, l. study , the fol2 value decreased (or even reached 0%), the removed study was considered a source of heterogeneity. Meta-analysis outcomes before and after the study was removed were then compared. If heterogeneity could not be eliminated, maximum or minimum extremes were excluded to achieve a more conservative estimation. Sensitivity analysis was not performed when the number of studies was < 3.Sensitivity analysis was performed to investigate sources of heterogeneity and estimate the impacts of excluded studies on pooled outcomes. We also performed sensitivity analyses by excluding one study at a time to explore whether results were strongly influenced by a specific study. If the IP < 0.05 designated a significant publication bias. Funnel plots were used to visually evaluate publication bias.Egger’s linear regression and Begg’s rank correlation tests were performed to evaluate potential publication bias . P < 0.0


Association between dietary protein intake and colorectal cancer risk has not been fully quantified, while the results were controversial. This study aimed to evaluate the role of protein intake in the development of colorectal cancer.PUBMED and EMBASE were searched up to December 2016. Two independent reviewers independently extracted data from eligible studies. Relative risk (RR) with 95% confidence intervals (CI) was pooled using random-effects model to estimate the result. Besides, publication bias and sensitivity analysis were conducted.Thirteen articles involving 21 studies comprising 8187 cases were included in this report. The pooled RR of colorectal cancer was 1.006 (95% CI = 0.857–1.179) indicating that there is no significant association between dietary protein intake and colorectal cancer risk. Furthermore, the pooled RRs for colon cancer and rectum cancer were 1.135(95% CI = 0.871–1.480) and 0.773(95% CI = 0.538–1.111), respectively, with the highest category of dietary protein intake. The association was not significant either in subgroup analysis of study design, protein type , sex, and or geographic locations.The present study indicated that the highest category compared to the lowest category of protein intake had no significant association on colorectal cancer risk. Dose-response analysis was not conducted due to limited information provided. Therefore, more studies with large cases and participants as well as detailed amounts of dietary protein intake are wanted to confirm this result.The online version of this article (10.1186/s12957-017-1241-1) contains supplementary material, which is available to authorized users. Colorectal cancer is one of the high incidence of malignant tumors worldwide, with the morbidity and mortality ranking third among malignant tumors in the Western world . Owing tIn animal and in vitro studies which investigated the effect of protein intake on colorectal cancer risk, high-protein diet could lead to DNA damage of colonocytes, decrease colonic mucosal thickness, and reduce the height of the colonocyte brushborder membrane –6. SeverThis meta-analysis followed the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines . We systStudies were included if they met all of the following criteria: (1) the study subjects were adults (≥ 18 years old) without specific diseases at study baseline; (2) the study was conducted with observational studies; (3) the exposure of interest was dietary intake of protein with two or more quantitative categories; (4) the outcome of interest was colorectal cancer, colon cancer, or rectum cancer; and (5) relative risk (RR) and 95% confidence intervals (CI) for dietary protein intake .The following data from each study were extracted independently by two authors: the first author’s name, publication year, study location, age and sex of the study population, outcomes of disease type, type of protein intake, number of cases and controls, variables adjusted in each original study, and RR with their 95% CI. If the paper reported total protein, animal protein, and vegetable protein at the same time, we used the data of the total protein for the whole analysis and animal protein or vegetable protein for the subgroup analysis if possible. Otherwise, animal protein and vegetable protein was as an independent study for the whole analysis. Furthermore, sex  and disease type  was analyzed as the same as protein type. Newcastle-Ottawa Scale (NOS) was used to assess the quality of included studies , which cI2 test, and < 25%, 25–50%, and > 75% represents low, moderate, and severe heterogeneity, respectively [P ≤ 0.05 was accepted as statistically significant for computed effects.The pooled RR with 95% CI was calculated using random-effects models with the method of DerSimonian and Laird, which considers both within-study and between-study variation . The betectively , 14. Subectively . The indectively . We usedn = 986), obvious irrelevance (n = 2022), and animal or cell studies (n = 26). Twenty-two of the remaining 35 articles are excluded due to the following reasons: review articles (n = 6), duplicate publications (n = 1), letter to the editors (n = 2), and paper provided insufficient data (n = 13). Finally, 13 articles [We have searched databases of PubMed and Embase and finally got 3069 articles. We then reviewed the titles and abstracts to exclude 3034 articles because of duplicates .To assess if the intake of protein could influence the colorectal cancer risk, we used random-effect model to pool the study-specific RR. Compared with the lowest category of protein intake, the pooled RR of colorectal cancer for the highest category was 1.006 (95% CI = 0.857–1.179) indicating that highest category of dietary protein intake had no significant association on colorectal cancer risk Fig. . HeterogIn the pooled results of the overall studies, significant heterogeneity was demonstrated for the associations between dietary protein intake and colorectal cancer risk. Thus, we used univariate meta-regression to explore the reason of causing with the covariates of publication year, disease type, study design, protein type , sex, and geographic locations. No significant findings were found contributing significantly to the between-study heterogeneity.Subgroup analyses were also conducted to explore the potential relationship and heterogeneity. For the subgroup of disease type, the pooled RRs for colon cancer and rectum cancer were 1.135 (95% CI = 0.871–1.480)  and Begg’s funnel plot . However, heterogeneity is common in the meta-analysis [I2 = 0.0%, Pheterogeneity = 0.624) or vegetable protein studies . Therefore, the protein type may increase the heterogeneity to the whole results.Significant between-study heterogeneity was found in the process of merging results  between dietary intake of protein and colorectal cancer. The methods of dietary assessment in all the included studies are food frequency questionnaire (FFQ). Subgroup analysis by geographic locations was conducted to find the opposite correlation between dietary intake of protein and colorectal cancer, but there is no significant association among American populations, Asian populations, or European populations. The detailed amounts of dietary protein intake are not provided in most studies. Then, we did not consider the influences of dietary intake considerations to the colorectal cancer risk. Furthermore, the results are unstable due to the small sample size in each independent study. Therefore, this meta-analysis was performed to obtain a comprehensive result of this issue.Several restrictions in this report should be attended. Firstly, our study included 21 individual studies; therefore, many diversification such as adjustments and quality that may influence the whole result. Secondly, although most of the included studies have adjusted for potential confounding factors, such as age, sex, and BMI, we cannot rule out the possibility that some other un-measured factors, such as intake of other energy, might have been partly responsible for the observed association. Thirdly, due to the limited information in the reported studies, dose-response analysis was not performed for dietary protein intake and colorectal cancer risk. Therefore, detailed information for each category of protein intake is wanted to assess the relationship between protein intake and colorectal cancer. Fourthly, dietary protein intake was collected via food-frequency questionnaires (FFQs), recall bias, and measurement bias could not be eliminated. Finally, significant heterogeneity was observed across studies included in the present meta-analysis. And the between-study heterogeneity was not resolved by meta-regression, the results of subgroup analyses were also with high heterogeneity in some groups except in the subgroup of protein type. Therefore, dietary protein type  may be the potential contributor to the between-study heterogeneity, and it would be further affecting the heterogeneity.In summary, this study suggested that the highest category of dietary protein intake had no significant association for the risk of colorectal cancer. Therefore, further studies with large cases and participants as well as detailed amounts of dietary protein intake are wanted to confirm this result, during some limitation that existed in our study.