Subgroup analysis restricted to the crop species with significant low GI found two crops, i.e., sorghum  and red kidney bean . Meta-analysis from in vivo studies revealed that the two significant factors responsible for the GI of starchy foods were flavonoid and phenolic content , while the lowest-GI crop type was fruit (banana). In conclusion, resistant starch and phenolic content may have a desirable impact on the GI of starchy food, while sorghum and red kidney bean are found to have low GI.The chemical properties that serve as major determinants for the glycemic index (GI) of starchy food and recommended low-GI, carbohydrate-based foods have remained enigmatic. This present work performed a systematic assessment of linkages between chemical properties of foods and GI, and selected low-GI starchy foods. The data were sourced from literature published in various scientific journals. In total, 57 relevant studies and 936 data points were integrated into a database. Both in vitro and in vivo studies on GI values were included. The database was subsequently subjected to a meta-analysis. Meta-analysis from in vitro studies revealed that the two significant factors responsible for the GI of starchy foods were resistant starch and phenolic content : −2.52, 95% confidence interval (95%CI): −3.29 to −1.75,  Type 1 diabetes mellitus (T1DM) has become a chronic metabolic disorder world-wide, and the regulation of blood glucose at a near-normal level could best fit the goals of preventing or delaying long-term diabetes complications in T1DM . GlycemiEvidence from randomized controlled trials (RCTs) was reported to be inconsistent ,6,7, whiThis research referred to the guidelines of a meta-analysis handbook . RelevanKeywords used in the search strategy included “chemical properties”, “glycemic index”, “carbohydrate category”, and/or “blood glucose response”. After examining the titles and abstracts, we excluded irrelevant studies. Subsequently, we examined the full texts of all remaining articles to determine eligibility. The discrepancies were verified by discussion and consensus. We also reviewed the identified trials and review articles in reference lists to find any other potential proper reports.This systematic review and meta-analysis were based on the PRISMA  checklist. Each section and each subsection should be clearly identified. The search strategy used in the electronic databases employed keywords, inclusion criteria, and exclusion criteria. The keywords that were used in this research were: available carbohydrate, glycemic index, blood glucose, diabetic, weight management, and hypoglycemic. Among those keywords, only glycemic index was detected in the MeSH  database. The inclusion criteria were the following: peer-reviewed, clinical trial, completely randomized design, in vitro, in vivo, within the last 20 years. Exclusion criteria were the following: letters to the editor, proceedings, abstracts, and book chapters.The eligibility of the trials was determined according to the following criteria: (1) design: completely randomized design that analyzed the relationships between food chemical properties and GI values; (2) population: all research that applied both in vitro and in vivo protocols for determining GI; (3) intervention: comparison between chemical properties, GI value, and selected low-GI carbohydrate-based foods; and (4) data: sufficient information (data) for calculating the standardized mean difference (SMD) and the corresponding 95% confidence interval (CI). Further, all published papers were written in English.Data from each included study were extracted and integrated into the database. The following data were collected: authors, year of publication, country of origin, number of patients or participants, intervention, control, sample/type, method/reference food, outcomes data , and follow-up.To assess the risk of bias, Cochrane risk of bias tool was employed . This waThe quality of evidence for primary and secondary outcomes was evaluated according to GRADE  procedure for risk of bias, inconsistency, indirectness, imprecision, and publication bias, which were categorized as high, moderate, low, or very low . The res2 index [2 > 50% indicated sufficient heterogeneity), and publication bias was determined using the Begg’s test and Egger’s test . We used Meta-Essentials tools for the meta-analysis process. The criterion of publication bias assessment approach using the GRADE System, consisted of selection, performance, attrition, detection, and reporting bias. The variables used for subgroup analysis were the method of study (in vivo or in vitro), type of reference food, and type of crops.We used weighted analysis using Hedges’ d (Standard Mean Difference/SMD) for statistical methods. The data extracted from selected journals were mean, standard deviation or standard error, and the number of replicate experiments. The SMD with corresponding 95%CI values were pooled using the random-effects model. Exploration of heterogeneity across studies was carried out using the I2 index   were selected for full-text review, resulting in fifty-seven articles  articles,59,60,61Fifty-seven studies, involving 936 participants, were published from 2002 to 2019. Twenty-six studies ,60,61,62p < 0.001; SMD: −0.72, 95%CI: −1.26 to −0.17, p = 0.005) with heterogeneity  (p < 0.001) with heterogeneity   . The low< 0.001) . The hetp < 0.001; SMD: −0.39, 95%CI: −2.37 to 1.59, p = 0.001), with heterogeneity . All results of subgroup analyses are presented in Crop species, i.e., sorghum and red kidney bean, had low GI , as was also found in tuber type  or fruit type .The contribution of six chemical properties to GI and five source types of carbohydrates to GI can be seen in p = 0.020; Egger’s, p = 0.004) . For the meta-analysis of legume type on GI food, any publication bias was observed by Begg’s test and Egger’s test .The quality of evidence was evaluated by the GRADE system. The level of evidence of RS content was at level A and highly recommended. Phenol content and legume type were at level B and moderately recommended. All evidence profiles for the primary and secondary outcomes are provided in = 0.004) a. For php < 0.001; SMD: −0.72, 95%CI: −1.26 to−0.17, p = 0.005), with heterogeneity  (p < 0.001), with heterogeneity  , with heterogeneity   . The low< 0.001) . The het= 0.001) .p < 0.001; SMD: − 0.63, 95%CI: −1.15 to−0.11, p = 0.009), with heterogeneity  , with heterogeneity  (p = 0.433)  . In in v 87.50%) . The low= 0.433) .This work systematically reviewed the current accessible literature and found that, in general, among the various chemical properties, the presence of resistant starch and phenolic compounds exerted significant impacts on the GI of starchy foods. It is noteworthy that evidence of this finding was consistent with the previous study. Moreover, some chemical properties show an essential impact on the GI beyond those mentioned, i.e., flavonoid, protein, dietary fibre, and amylose, which were negatively correlated with GI. Further, we found that the crop type with the lowest GI value was legumes. Subgroup analysis revealed that significant low-GI crop species were sorghum and red kidney bean, while the subgroup analysis was restricted to trials that compared some crop species. This may relate to a larger quantity of RS and phenolic compounds in the crop species.d-glucan, which is obtained mainly from the retrogradation of the amylose fraction and has a relatively low molecular weight (1.2 × 105 Da) [No meta-analysis has been conducted on the effect of resistant starch levels on starchy food’s GI. Previous researchers stated that the relationship between resistant starch levels and GI is a negative correlation . Resista 105 Da) . The res 105 Da) . The sam 105 Da) .Furthermore, meta-analysis has not been conducted on the effect of dietary fibre levels on starchy foods’ GI. Previous researchers stated that the relationship between dietary fibre levels and GI is negatively correlated ,35. The Meta-analysis of the effect of fat content on starchy foods’ GI has not been carried out. Previous researchers stated that the relationship of fat content to GI is negatively correlated . The samIn addition, meta-analysis of the effect of protein levels on starchy foods’ GI has not been done. Previous researchers stated that the relationship between protein levels and GI is negatively correlated . The mecNo meta-analysis has been conducted on the effect of phenol levels on starchy foods’ GI. Previous researchers stated that the relationship between phenol levels and GI is negatively correlated . The samNo meta-analysis has been conducted on the effect of flavonoid levels on starchy foods’ GI. Previous researchers stated that the relationship between flavonoid levels and GI is negatively correlated . The samThis study used both the in vivo and in vitro methods. This consideration was based on previous studies in which in vitro test results had the same trend as in vivo tests, though in vitro tests tended to have absolute values (overestimation) about 5–25 higher than those of in vivo tests ,81,82. TFor in vivo food model simulation, we suggest some recommendations. First, our study found that RS and phenolic content had positive effects on the reduction of the GI value of starchy foods. Such a correlation is stable and reliable. Thus, RS and phenolic content should be recommended for the chemical properties of starchy foods determined to affect the GI value. Second, to date, little attention has been paid to the study of the chemical properties determinant that affects the glycemic index of starchy foods and selected low-GI carbohydrates using meta-analysis. The determinant factor discussed in this study can be a meaningful direction for further research. Finally, comprehensive in vivo trials are warranted to validate  the posip < 0.05; n = 4). In the case of the relation between legume and GI, the previous study using meta-analysis included forty trials totaling 253 participants. We included ninety-eight trials, and added subgroup analysis based on chemical properties and the source of starchy foods according to the control group, enabling us to reach a more robust conclusion by eliminating interference factors. Our meta-analysis found that heterogeneity among trials was due mainly to the design of different control group, rather than population. In addition, we assessed the quality of the evidence and the strength of the recommendations. Thus, our work was the latest and most comprehensive one.In our study, the determinant effect of RS or phenolic content on GI and legume, as the selected low-GI carbohydrate food, was in accordance with the previous meta-analysis . NeverthLow-GI foods, such as legumes, had the lowest GI compared to other carbohydrate foods because legumes have relatively higher levels of resistant starch and bioactive compounds. Beans’ resistant starch levels were 24.7% . In the Our study also has limitations. Though this meta-analysis includes high-quality studies, the sample sizes are small. Additionally, there is enough heterogeneity among studies, which could alter the reliability of the results. Trials with higher-quality samples and larger sample sizes are required to confirm the current results.Although the concept of GI is widely used in explaining the causes of diabetes, some scientists consider that GI is not accurate enough to explain this. The concept of GI is considered inappropriate to classify a food as healthy or not or to describe its impact on human health. Several aspects of criticism of the GI concept include reproducibility, its impact on physiological effects, and levels and standards of the reference food used . TherefoThe results evidenced that resistant starch and phenolic content reduce the GI value of starchy foods. As regards in vitro studies, it is well known that resistant starch is negatively correlated to GI, but the results obtained for the phenolic content in this systematic review were not obvious, even though part of phenolics were bound to fibre compounds known to reduce the digestion in the flattening of postprandial glucose response. Moreover, phenols inhibit the α-amylase and α-glucosidase enzymes. Among cereals, sorghum—a gluten free cereal—is the only one that reveals high-resistant starch and low GI. This is a very interesting result due to the fact that gluten-free foods generally are low in fibre and high in GI. This finding could be useful to investigate the potential of sorghum as gluten-free products.The present work successfully elucidated that resistant starch, phenolic, flavonoid, protein, and dietary fibre content exerted crucial roles in reducing the glycemic index of starchy foods. Among the starchy foods, sorghum and red kidney bean were identified to have low-GI properties. Sorghum and kidney beans have a low GI because both contain relatively high resistant starch and phenolic compounds. The relationship between levels of resistant starch, phenolic, flavonoids, protein, and fibre to GI was a negatively correlation. Resistant starch causes steric hindrance in the molecular structure of the starch, while phenolic compounds (including flavonoids) are capable of inhibiting the α-amylase and α-glucosidase enzymes. The mode of action of resistant starch in reducing GI is making the enzyme unable to hydrolyze and disrupting the hydrolysis on non-resistant starch (which creates steric hindrance). Nevertheless, microbes ferment the resistant starch in the colon so that the body will not absorb it as glucose. Protein is supposed to stimulate the secretion of insulin so that blood glucose is not excessive and can be controlled. The fibre functions as an inhibitor of physical digestion in the intestine, thereby slowing down the interactions between enzymes with the substrates.


Cyp2C19*2 gene polymorphism and clopidogrel resistance reflected by platelet function assay has been studied extensively, but there is no clear conclusion yet. In order to evaluate the relationship between Cyp2C19*2 gene polymorphism and clopidogrel resistance more accurately, meta-analysis was conducted in this study. The I2 value taking 50% as the limit, the heterogeneity is judged as high or low, and then a random effect model or a fixed effect model is selected for statistical analysis. PubMed, EMBASE, Web of Science, CNKI, and China Wanfang database were searched, and the related literatures from the establishment of the database to May 2020 were collected and analyzed by STATA 15.0 software. A total of 3,073 patients were involved in 12 studies, including 1,174 patients with clopidogrel resistance and 1,899 patients with non-clopidogrel resistance. The results of this study showed that allele model (A vs. G): OR = 2.42 (95%CI: 1.97–2.98); dominant model (AA+GA vs. GG): OR = 2.74 (95%CI: 2.09–3.59); recessive model (AA vs. GA+GG): OR = 4.07 (95%CI: 3.06–5.41); homozygous model (AA vs. GG): OR = 5.70 (95%CI: 4.22–7.71); heterozygote model (GA vs. GG): OR = 2.32 (95%CI: 1.76–3.07), the differences were statistically significant. Also, the analysis of the Ethnicity subgroup indicated that the Asian allele model and the other four gene models were statistically significant. In conclusion, Cyp2C19*2 gene polymorphism is strongly associated with clopidogrel resistance. Allele A, genotype GA, AA, and GG + GA can increase clopidogrel resistance, especially in the Asian population.In recent years, the relationship between  P2Y12 receptor. Among the genes researched, the study of gene polymorphisms affecting the metabolic transformation of clopidogrel has attracted the most attention. The relationship between CYP2C19 gene polymorphism and clopidogrel response variability is consistent in different studies, which may suggest of the important role of CYP2C19 in the two-step metabolic transformation of clopidogrel. The metabolic transformation of clopidogrel in the liver mainly goes through two cytochrome P.450 (CYP)-dependent steps: the first step produces 2.OXO. Clopidogrel is catalyzed by cytochrome Cyp2C19, CYPlA2, and CYP286 in different proportions, and the second step produces active metabolites catalyzed by cytochrome CYP3A4/5, CYP286, Cyp2C19, and CYP2C9 , hereinafter referred to as Coronary Heart Disease (CHD), is a kind of heart disease caused by coronary atherosclerosis, which could induce vascular stenosis or obstruction, coronary circulation disturbance, myocardial ischemia, hypoxia and even necrosis. With the improvement of living standards, the incidence of coronary heart disease is increasing year by year. CHD has become one of the common diseases seriously affecting human health  AND  AND clopidogrel AND (“resistance” OR “platelet reactivity” OR “platelet response”). For studies with overlapping data or the same population, only the most recent group of subjects were included. There are no language restrictions. Literature retrieval was carried out independently, cross-checked by two researchers in each database. If there were differences, they could be resolved through discussion, or decided by the third researcher.We performed this meta-analysis based on Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA)  The study was a cohort study or a case-control study; (3) Patients were diagnosed with coronary heart disease; (4) All patients received clopidogrel antiplatelet therapy; (5) The study should provide the number of patients with clopidogrel resistance and non-resistance of each genotype; (6) Diagnostic criteria of clopidogrel resistance: percentage of adenosine diphosphate inhibition ≤ 10%, MPA induced by adenosine diphosphate ≥ 50%, angiotensin converting enzyme index ≥ 50%, PRI ≤ 50%, PRU > 208, IPA < 30%.(1) The relationship between (1) Studies belong to reviews, letters, or case reports; (2) Studies involve other definitions of clopidogrel resistance; (3) Repeatedly published data from the same study; (4) Non-coronary heart disease studies, such as ischemic stroke; (5) The control group does not meet the Hardy-Weinberg equilibrium (HWE); (6) NOS score is <6.The information was extracted as follows: first author, publication years, age, country, diagnostic criteria of clopidogrel resistance, clopidogrel load, genotype, and number of patients with clopidogrel resistance. The data were extracted independently by two researchers and discussed and solved by the third researcher when there was disagreement. When the included research information was insufficient, contacting author if possible.After reading the literature carefully, the quality of the literature was evaluated according to The NOS Stang, . The litQ-test was used to test the heterogeneity of the research results. If I2 ≥ 50%, or P ≤ 0.05 were considered heterogeneity, Random-effects model (REM) was used  should be used for data merging , the difference was statistically significant. According to the Ethnicity subgroup analysis, the results showed that there was a significant difference in Asian population with OR = 2.37 , and there was also statistical significance in Caucasian population shown in Cyp2C19*2 polymorphism and clopidogrel resistance. The funnel plot in P-value was >0.05, which indicated that there was no publication bias.The main results of meta-analysis were shown in 2 = 63.0%, P < 0.05, which indicated that the heterogeneity among the studies was statistically significant, and the random effect model was used. The results showed that there was a significant difference with OR = 2.74 . The ethnic subgroup analysis showed the same results, the comparison of Caucasian and Asian dominant genetic models was statistically significant in P-value was >0.05, which meant that the publication bias was well-controlled.The genotype AA + GA vs. the genotype GG, I2 = 0.0%, P > 0.05, which suggested that there was no statistical significance in the heterogeneity among the studies, and the fixed effect model was used. The results showed that there was a significant difference with OR = 4.07 . The ethnic subgroup analysis indicated the same results, the comparison of Caucasian and Asian recessive genetic models was statistically significant, and was shown in P < 0.05, which indicated that there was a certain bias.The genotype AA was compared with genotype GA + GG, I2 = 33.9%, P > 0.05, which showed that there was no statistical significance in the heterogeneity among the studies, and the fixed effect model was used. The final results showed that there was a significant difference with OR = 5.70 . The ethnic subgroup analysis indicated the same results, the comparison of Caucasian and Asian homozygous genetic models was statistically significant shown in P > 0.05, which suggested that the publication bias was well-controlled.The genotype AA vs. GG, I2 = 61.4%, P < 0.05, which showed that the heterogeneity among the studies was statistically significant, and the random effect model was used. The final results showed that there was a significant difference with OR = 2.32 . The ethnic subgroup analysis suggested the same results, the comparison of Caucasian and Asian heterozygous genetic models was statistically significant, and the forest plot was shown in P > 0.05, the difference was not statistically significant, which indicated that the publication bias was well-controlled.The genotype GA compared with GG, IThe results of subgroup analysis of the published year  showed tThe results of subgroup analysis defined by CR  showed tThe results of the sensitivity analysis were shown in Cyp2C19 gene determines the difference of its enzymes among individuals, which affects the concentration of the metabolically active products and anti-platelet aggregation of clopidogrel  was significantly increased in patients with Cyp2C19*2 genotype. Pettersen et al. : OR = 2.42 (95%CI: 1.97–2.98), the difference was statistically significant. Dominant gene model, recessive gene model, homozygote model, and heterozygote model were also statistically significant. The funnel chart and Egger's Test results of publication bias showed that there was no publication bias. The results of subgroup analysis showed that the results of the Asian population were consistent with those of the total population, while the Caucasian population was inconclusive because only two articles were included. The results of subgroup analysis of different definitions of clopidogrel resistance and the year of publication showed that the differences were statistically significant in each genetic model of each subgroup. Sensitivity analysis results indicated that after excluding a single study, the meta-analysis results of the allele model and the other four gene models did not have a statistically significant change, indicating that the results were robust. Therefore, it could be considered that there is a strong association between u et al.  includinIn this study, several limitations should be noted: (1) Since there is no standard definition of clopidogrel resistance at present, multiple definitions of clopidogrel resistance were used in this study, which may weaken the comparability of the data; (2) In the subgroup analysis, the sample size is relatively small, and there are only 2 studies in the Caucasian population, so the conclusion need to be carefully adapted to the Caucasian population; (3) The lack of raw data also limits further assessment of potential gene-gene or gene-environment interactions.Cyp2C19*2 gene polymorphism is associated with clopidogrel resistance reflected by platelet function assay, and the allele (A vs. G) increases clopidogrel resistance, which is reflected in the other four models, especially in the Asian population. This conclusion can be used to guide the individualized antiplatelet therapy of clopidogrel. Due to the limitations of this study, such as multiple definitions of clopidogrel resistance, gene-gene interaction, it is necessary to do more and more in-depth studies on Cyp2C19*2 gene polymorphism and antiplatelet therapy.In conclusion, YS, GY, and QL have given substantial contributions to the conception or the design of the manuscript, GY and YS to acquisition, analysis, and interpretation of the data. All authors have participated to drafting the manuscript, BC and GY revised it critically. All authors read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Chronic obstructive pulmonary disease (COPD) is a multifactorial disease with gene-environment interaction leading to airflow limitation through the respiratory tract. Reports on the association of matrix metalloproteinase 12 (MMP-12) polymorphisms with COPD have been controversial. A new systematic evaluation which could examine whether MMP-12 mutations are associated with the susceptibility to COPD is needed.We will search PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure and Google Scholar to obtain eligible case-control studies for meta-analysis. The time is limited from the construction of the library to July 2020. Two investigators systematically will extract relevant data within those included studies.The odds ratio and 95% confidence intervals will be used to assess the genetic association between the allelic, dominant and recessive models of MMP-12 gene polymorphisms and COPD risk. Stata 12.0 software and Revman 5.3 will be adopted for statistical analysis. This protocol reported under the Preferred Reporting ltems for Systematic Reviews and Meta-Analyses Protocols statement.This study will provide a better understanding of the association between MMP-12 polymorphisms and COPD risk.Publishing this protocol will minimise the possibility of bias due to post hoc changes to the analysis protocol. About 384 million people worldwide suffer from COPD, of which China accounts for 100 million. In 2015, 3.2 million deaths due to COPD were reported, that is, an 11.6% increase in mortality from 1990.,5 Hence, COPD exerts enormous economic burden on the society and is likely to remain as a major health care issue in the coming decades.,7Chronic obstructive pulmonary disease (COPD) is a common disease with persistent respiratory symptoms and airflow limitation. COPD is characterized by symptoms including progressive dyspnea, cough, and expectoration and can lead to adverse outcomes, such as osteoporosis, heart disease, anxiety, depression, and lung cancer.–12 The gene encoding matrix metalloproteinase 12 (MMP-12) is 1 such candidate. Overexpression of MMP-12 can lead to pathological extracellular matrix protein degradation and excessive airway remodeling, and it may be an important factor in the development of COPD. Extensive evidence from genetic studies, animal models and human diseases suggests that MMP-12 derived from alveolar macrophages plays an indispensable role in lung destruction of COPD.–17 Two functional single nucleotide polymorphisms (SNPs) were described in the MMP-12 gene: the (–82) A/G (rs2276109) and Asn357Ser (A/G) (rs652438) polymorphisms are located in the promoter region and haemopexin domain of the enzyme, respectively, and may influence MMP-12 gene expression and activity.,19 A case-control genetic association study identified the 2 functional SNPs were associated with severe and very severe COPD (GOLD stages III and IV).,21 However, other studies have found that MMP-12 polymorphism are not associated with COPD risk.,22–24 Therefore, the association between MMP12 polymorphism and COPD remains unclear. Although a similar systematic review based on COPD was published in 2014, new studies have occurred since. In light of the small sample sizes and limited statistical capacity of individual studies, we will conduct a systematic review and meta-analysis of the existing literature to provide a more comprehensive and precise estimate of the association between MMP-12 polymorphism and COPD risk.COPD is a complex multifactorial disease and its development is thought to be largely under genetic control. A considerable number of genes and polymorphisms have been identified as possible candidates for COPD risk.22.1 Ethical approval is not required for the study.The protocol has been registered in the Open Science Framework (OSF) (registration number: DOI 10.17605/OSF.IO/KNGJC). This systematic review and meta-analysis will be reported in accordance with the preferred reporting items for systematic reviews and meta-analysis protocols 2015.2.22.2.1Case-control study related to the susceptibility of MMP-12 polymorphisms to the COPD will be incorporated in our review. And these studies provide the available genotype frequencies for the case and control groups to estimate the odds ratio (OR) and its 95% confidence interval. No restriction will be put on the language, publication date or status of the study.2.2.2Participants affected by COPD will be included in the meta-analysis. Control subjects should be defined as healthy subjects without history of COPD. No restrictions will be placed on age, gender, or country.2.2.3COPD risk comparsions.2.3Repeat report, conference abstracts, case reports, review paper, or animal study, or study has insufficient data for genotyping distribution calculation or which MMP-12 demonstrated a departure from Hardy-Weinberg equilibrium (HWE) in controls will be excluded. If duplicated studies reporting overlapping data are identified, the most comprehensive 1 will be included in the meta-analysis.2.4Publications will be searched through Pubmed, Web of Science, Embase, Google Scholar and China National Knowledge Infrastructure (CNKI) databases up to July, 2020. A combination of Medical Subject Headings (MeSH) alongside free terms will be used to hunt all the potentially eligible publications without any language restriction. The following terms will be utilized (“SNP” or “mutation” or “genetic polymorphism” or “variation” or “polymorphism” or “single nucleotide polymorphism” or “variant”) and (“chronic obstructive pulmonary disease” or “COPD” or “chronic obstructive airway disease” or “chronic obstructive lung disease” or “chronic airflow obstruction”’) and . We also will examine the cross-references in the retrieved studies for publications that were missed in the above search.2.52.5.1The article screening process will involve reading the title first, followed by the abstract and full text to determine whether the study should be included. Apart of the reviewers in our team will be trained regarding the purpose and process of the review. Two reviewers (Chuantao Zhang and Yang Hongjing) will conduct the selection process independently, with cases of disagreement resolved consulting a third reviewer (Qingsong Huang). A flow chart of study selection is shown in Figure 2.5.2 The NOS values arrange from 0 to 9. The studies will be included if the NOS values ≥ 6. Two reviewers (Chuantao Zhang and Yang Hongjing) will conduct the rating independently and a third reviewer (Qingsong Huang) will be consulted for consensus if disagreement occurred. The methodological quality of data will be evaluated strictly in accordance with the STrengthening the REporting of Genetic Association Studies statement.Data extracted from all qualified articles include: surname of the first author, year of publication, country where the study was performed, ethnicity of enrolled subjects, sample size, the value of HWE, sex composition, mean age, genotyping methods and frequencies of genotypes. All included studies will be evaluated using the Newcastle–Ottawa Scale (NOS).2.5.3We will try to contact the corresponding authors if the information of potential studies is missing, insufficient, or ambiguous. However, the studies will be excluded if the data cannot be obtained by the above method.2.5.4Z test, and pZ < .05 will be considered as statistically significant.Statistical analysis for the meta-analysis will be conducted by Stata version 12.0  and Revman 5.3 (Cochrane Collaboration). Departure from HWE will be evaluated by using Chi-square test to assess goodness of fit in control subjects of each included study. In order to avoid an inflated type I error rate, we will not perform any assumptions about the genetic model of inherence in advance. The ORs and 95% confidence intervals will be used to evaluate the association between the allelic, dominant and recessive models of MMP-12 and risk of COPD. Then the most plausible genetic model of inherence will be determined according to the relationships between the 3 pairwise comparisons. After that the underlying genetic model is confirmed, the counts of genotypes will be collapsed into 2 categories to obtain the merged results. The significance of the pooled OR will be assessed by the 2.5.5I2 statistic and P value; a I2 statistic < 50% and a P > .1 indicated low heterogeneity among studies, and a fixed model will be applied to estimate the pooled ORs. Otherwise the random model will be used. Subgroup analysis, meta regression analysis, sensitivity analysis will be undertaken to explore potential sources of heterogeneity across studies when statistical heterogeneity is detected.Heterogeneity will be quantified with the 2.5.6We will conduct subgroup analyses of the relationships between MMP-12 genetic polymorphisms and the risk of COPD, according to country, ethnicity, and genotyping method, etc.2.5.7Sensitivity analysis will be conducted by removing studies that do not conform to HWE to check the robustness and reliability of pooled outcome results.2.5.8The funnel plots will be utilized to analyze the potential publication bias if there are more than 10 studies. Egger regression test and Begg rank correlation test will be also used to evaluate the publication bias.2.5.9The quality of evidence for outcome will be assessed by the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group approach. High, medium, low, or very low quality represent the 4 levels of evaluation.3 In general, COPD is a multifactorial disease that can be attributed to an interplay of genetic and environmental factors. Although the specific pathogenesis of COPD is unclear, it is widely accepted that airway tissue remodeling results from disorder of the proteinase-antiproteinase balance and aberrant inflammation in the lung. Among various proteinases, MMP-12 have been shown to play a predominant role in the occurrence and progression of COPD.,32 Elevated MMP12 may lead to imbalance of protease-antiprotease and degradation of lung extracellular Matrix, thereby increasing individual's susceptibility to COPD. The genetic polymorphism of MMP-12 gene may induce the abnormal expression of MMP12, and may also be related to the occurrence of COPD. Although the results from a meta-analysis conducted in 2014 suggest that genetic polymorphisms in MMP12 gene may be strongly implicated in the development of COPD, some studies since then have not supported this view.–24 the association between MMP12 polymorphism and COPD remains unclear. It is necessary to update previous systematic review about the genetic polymorphism of MMP-12 gene and the risk of COPD MMP-12, which can provide a further reference for the diagnosis and potential therapeutic targets of COPD.COPD is the most common chronic respiratory disease characterized by high morbidity, high disability rate, high mortality and high disease burden. Patients with COPD may need more social and nursing care. The increased social and economic burdens associated with COPD worldwide make their targeting treatment a major public health goal.The advantages of this review will be:(1)this review will include more clinical studies than the previous 1, since only 5 research reports were included in the previous study.(2)In order to avoid bias, we will collect all relevant documents as comprehensively as possible.As to the exploration of heterogeneity, post hoc subgroup analysis should be avoided as much as possible. Publishing this protocol will reduce potential biases associated with data mining, thereby helping to generate reliable evidence.Conceptualization: Hongjing Yang, Chuantao Zhang.Investigation: Jianying Wu, Xiaohong Xie, Wei Xiao.Supervision: Zhu Zeng, Keling Chen.Writing – original draft: Wujun Wang, Xing An.Writing – review & editing: Qingsong Huang, Wenjun Tang.


Inconsistent findings have been found among studies evaluating the risk of cardiovascular disease for women who have had pregnancies complicated by gestational hypertension (the new onset of high blood pressure without proteinuria during pregnancy). We provide a comprehensive review of studies to quantify the association between gestational hypertension and cardiovascular events in women.We conducted a systematic search of PubMed, Embase, and Web of Science in March 2019 for studies examining the association between gestational hypertension and any cardiovascular event. Two reviewers independently assessed the abstracts and full‐text articles. Study characteristics and the relative risk (RR) of cardiovascular events associated with gestational hypertension were extracted from the eligible studies. Where appropriate, the estimates were pooled with inverse variance weighted random‐effects meta‐analysis. A total of 21 studies involving 3 60 1192 women  were identified. Gestational hypertension in the first pregnancy was associated with a greater risk of overall cardiovascular disease  and coronary heart disease , but not stroke  or thromboembolic events . Women with 1 or more pregnancies affected by gestational hypertension were at greater risk of cardiovascular disease , coronary heart disease , and heart failure , but not stroke .Gestational hypertension is associated with a greater risk of overall cardiovascular disease, coronary heart disease, and heart failure. More research is needed to assess the presence of a dose–response relationship between gestational hypertension and subsequent cardiovascular disease.https://www.crd.york.ac.uk/prospero/; Unique identifier: CRD42018119031.URL:  ARIabsolute risk increasesCHDcoronary heart diseaseCVDcardiovascular diseaseGHgestational hypertensionHRhazard ratioICDInternational Classification of DiseasesIRRincident rate ratioMImyocardial infarctionORodds ratioRRrelative riskIn a systematic review of >3 million women, we found that gestational hypertension is associated with a greater risk of cardiovascular disease, coronary heart disease, and heart failure.Nonsignificant trends toward a greater risk of stroke after gestational hypertension were found.Women with a pregnancy complicated by gestational hypertension are at greater risk of developing several different kinds of cardiovascular disease.Women who experience gestational hypertension may benefit from counseling during and/or after pregnancy about their long‐term cardiovascular risk.Gestational hypertension (GH), also known as pregnancy‐induced hypertension, is defined as the onset of high blood pressure (at least 140 mm Hg systolic or 90 mm Hg diastolic) without proteinuria on 2 occasions at least 4 hours apart in an ordinarily normotensive pregnant woman after 20 weeks of gestation.Pregnancy‐induced hypertension is increasingly recognized as a risk factor for subsequent cardiovascular disease (CVD) in women.Studies that have assessed the CVD risk associated with GH have found mixed results. Results have ranged from no raised riskhttps://www.crd.york.ac.uk/prospero/; review reference number CRD42018119031).The design, implementation, analysis, and reporting for this systematic review and meta‐analysis are in accordance with the Meta‐Analysis of Observational Studies in EpidemiologyWe searched the databases PubMed, Embase, and Web of Science in March 2019. No restrictions were applied to the language or publication period of the articles. Both medical search headings and open‐text fields were used to identify articles.The exposure was GH and any cardiovascular outcome was of interest, including (1) overall CVD; (2) coronary heart disease (CHD); (3) any stroke, including ischemic and hemorrhagic stroke; (4) heart failure; and (5) thromboembolic events. The details of the search terms are provided in Table To be included in the review, the articles had to compare the risk of at least 1 cardiovascular outcome for women with previous GH with that of women who had 1 or more normotensive pregnancies. GH was defined as a new onset of systolic and/or diastolic hypertension after 20 weeks gestation without proteinuria. Events had to occur more than 1‐year postpartum to minimize the risk of comorbidity. Articles only evaluating pre‐eclampsia, or combining both pre‐eclampsia and GH as an exposure, were excluded to minimize heterogeneity in the exposure. Study designs were limited to cohort studies and case‐control studies. Exclusion criteria were the following: (1) studies that included animals, men, children, or nulliparous women; (2) studies that did not have a cardiovascular outcome; (3) studies that combined women with GH and women with pre‐eclampsia; and (4) studies that did not evaluate GH as an independent exposure.Using the software Abstrackr,For the fully adjusted measures of association, studies were categorized as poorly, adequately, or well adjusted. To be considered well adjusted, studies had to control for maternal age; socioeconomic factors; obstetric history, including pregnancy complications other than GH; and chronic diseases. We selected these categories as they broadly cover most potential confounders and are representative of the range of adjustments made in the studies included in the review. Adequately adjusted studies controlled for variables from 3 of these 4 categories, and poorly adjusted studies controlled for variables in 2 or fewer categories.Two authors independently evaluated the bias within each individual study using the validated Newcastle–Ottawa Scale, a semiquantitative scale designed to evaluate the quality of nonrandomized studies.The included studies used 2 different approaches to classify GH exposure. The first approach classified women based on the presence or absence of a diagnosis of GH in the first pregnancy. The second approach classified women as having either a history of 1 or more pregnancies affected by GH or only having normotensive pregnancies. Because of the distinction between these 2 classifications, our meta‐analyses were conducted assessing risk associated with 2 exposures: (1) a diagnosis of GH in the first pregnancy and (2) a history of 1 or more pregnancies affected by GH.For a meta‐analysis to be conducted, it was necessary to identify a minimum of 3 studies evaluating the risk of a particular cardiovascular outcome  associated with 1 of these exposures. If fewer than 3 studies were found for an exposure–outcome combination, then the results were included in the systematic literature review, but not in the meta‐analysis.For studies that reported separate relative risk (RR) estimates for subgroups (eg ethnic groups) or that reported CHD and overall stroke risk estimates separately for the same population, but did not report an overall CVD risk estimate, we used inverse variance weighted fixed effects meta‐analysis to generate overall study‐level RRs before combining these results with those from other studies.2 statistic and the I2 statistic. Individual RR estimates and summary estimates were displayed graphically with forest plots.When pooling the results from separate studies, the inverse variance weighted method was used to combine odds ratio (OR), RR, and hazard ratios (HR) to produce a pooled RR under the rare outcome assumption. Random effects analyses using the DerSimonian–Laird model were used to allow for between‐study heterogeneity as there were clear differences between the identified studies, such as ethnicity. Heterogeneity was assessed using the Cochrane χTo assess the number of cases that could be avoided if effective intervention for CVD are targeted to women with GH, the absolute risk increases (ARI) for overall CVD and CHD were calculated separately for both exposures. The equation ARI=(RR−1)×(assumed control risk) was used, where RR is from the meta‐analysis.Female‐specific European Heart Network statistics for 2015 were used to estimate the assumed control risk  of overall CVD and CHD because the largest number of studies came from Europe.A number of sensitivity analyses were conducted. The first analysis excluded studies with the largest effect estimates to assess the impact of these studies on the magnitude of the pooled result and the observed heterogeneity. The second analysis included all studies and reran all meta‐analyses with fixed effects models. This was performed because the DerSimonian–Laird method for random effects meta‐analysis may have statistical limitations in the case of few studies.A total of 5 stratified analyses were conducted to evaluate (1) the effect of different levels of adjustment, (2) the potential impact of bias in individual studies, and (3) the effect of study‐level characteristics on the association between GH and overall CVD. Only overall CVD was assessed as an outcome because too few studies were included in the meta‐analyses of other events. Analyses were stratified by (1) level of adjustment, (2) risk of bias, (3) duration of follow‐up, (4) year of publication, and (5) the population studied. In these analyses, we tested for trend across strata using random effects meta‐regression.Small study effects were evaluated through funnel plots and Egger tests for meta‐analyses including 6 or more studies.P values of <0.05 were considered statistically significant. STATA software package  was used for all statistical analyses.All tests were 2‐tailed and Our search strategy identified 6974 studies, of which 6882 were excluded during the initial abstract screen. The remaining 92 articles were reviewed in full, resulting in 71 being excluded and 21 included in our final review Figure * and NoAll of the studies ascertained GH and cardiovascular events through medical records, registry data, or health insurance claims . The durA total of 11 studies,11,34,37,39; RR, 1.46; 95% CI, 1.23–1.72), but not overall stroke , CHD , and overall stroke , but not thromboembolic events . Meta‐analyses of the unadjusted results were consistent with these findings , CHD , heart failure , and overall stroke . A greater CVD risk was also observed in the meta‐analysis of unadjusted findings  GH in the first pregnancy only, (2) GH in the second pregnancy only, (3) GH in both pregnancies, or (4) GH in neither pregnancy. A greater risk of overall CVD relative to normotensive women was found for women with GH in their first pregnancy , their second pregnancy , and in both pregnancies .2 results staying relatively constant (Table P<0.001)  Figure .The overall CVD analyses were separately stratified by average duration of follow‐up, risk of bias, level of adjustment, year of publication, and population Table . There wP=0.935) , with publications of small studies with null or negative effect estimates missing   Figure . The fung Figure . Use of ) Figure .This systematic review found that women previously diagnosed with GH had a greater risk of overall CVD, CHD, and heart failure and some indication of a greater risk of stroke as well.This study adds to the literature on the relationship between women's obstetric history and risk of cardiovascular events. A single previous review evaluated cardiovascular events after GHThis study adds to the growing literature on the relationship between women's obstetric history and their subsequent risk of cardiovascular events. These include a greater risk of overall CVD with recurrent miscarriages,Strengths of this study include the large number of women included and the variety of cardiovascular events assessed, which allowed us to obtain the most holistic picture to date of the effect of GH on long‐term cardiovascular health. Because of the larger number of studies included in the overall CVD analysis, it was possible to assess the impact of study characteristics on the meta‐analysis and to conduct sensitivity analyses. Furthermore, there was sufficient follow‐up duration in many of the studies (10 studies had more than 15 years of follow‐up) for long‐term CVD risk to be adequately assessed. Lastly, diagnoses of GH and cardiovascular events were mainly ascertained through medical records, which reduced possible information bias arising from self‐report.Nevertheless, our study has limitations. First, it is possible that despite searching multiple databases without language or time restrictions, relevant studies were missed. Second, there were only 21 studies identified, and at most 8 studies were included in any single meta‐analysis, suggesting that analyses could be influenced by a single study. However, exclusion of the studies with the largest effect estimates did not materially alter the conclusions of the meta‐analyses. Few studies were found for some events, such as stroke and thromboembolic events, and thus limited sensitivity analyses.2>70%) was found for most meta‐analyses. This may be attributed to differences in study design, methodology, or population. Stratified analyses in the current review were limited to CVD only and may have been underpowered to detect some of these differences. Other potential sources of heterogeneity include differences in the frequency of postpartum chronic hypertension and variation in outcome and exposure identification. Chronic hypertension is likely to be an important mediator of the relationship between GH and CVD,International Classification of Diseases (ICD) codes to define the same outcome  and an early career fellowship from Homerton College, University of Cambridge. A.F. is supported by a UK Medical Research Council Fellowship (MR/M009351/1). The funding source had no role in the design or conduct of the study, collection or analysis of the data, or the decision to submit the manuscript for publication.None.Tables S1–S10 Figures S1–S6 References 11–18, and 29–41Click here for additional data file.


Hepatocellular carcinoma (HCC) is an intractable public health threat worldwide, representing the second leading cause of cancer-related mortality, with limited early detection and therapeutic options. Recent findings have revealed that the susceptibility of HCC is closely related to microRNA (miRNA). We performed this systematic review with a network meta-analysis to investigated four single nucleotide polymorphisms (SNPs) that most regularly reported in miRNAs, exploring their involvement in HCC susceptibility and interaction with hepatitis B virus (HBV).Databases were reviewed for related studies published up to May 2019 to identify all studies that compared genotypes of miR-146a rs2910164, miR-149 rs2292832, miR-196a2 rs11614913, and miR-499 rs3746444 with no language and date restrictions. A pairwise meta-analysis was performed to estimate pooled odds ratios and 95% confidence intervals incorporating heterogeneity to assess the relationship between four miRNA polymorphisms and HCC. To further clarify the effect of polymorphisms on HCC, a Bayesian network meta-analysis was conducted to combine the effective sizes of direct and indirect comparisons. Calculations were performed by R version 3.6.1 and STATA 14.0. All steps were performed according to PRISMA guidelines.A total of 20 studies were enrolled in this network meta-analysis, providing 5,337 hepatocellular carcinoma cases and 6,585 controls. All included studies had an acceptable quality. Pairwise meta-analysis demonstrated that miR-196a2 rs11614913 was significantly associated with the susceptibility of HCC, while the other three SNPs were not found to have a significant association. In the analysis of HCC patients under different HBV infection status, only miR-196a2 revealed correlation of threefold risk. The network results showed no significant difference in the distribution of genotype frequencies except for miR-196a2, which appeared to have the highest superiority index when comparing and ranking four SNPs.MiR-196a2 rs11614913 was significantly associated with the susceptibility of HCC, especially for HBV- related HCC, and that individuals with TC/CC were more susceptible. No significant association was found in the other three miRNA genes. MiR-196a2 could serve as the best predictor of susceptibility in HCC. Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, has been an intractable public health threat worldwide . ApproxiGenetic association studies are of great significance for epidemiological analyses, as they can identify candidate genome regions associated to specific diseases . Many fiMiR-146a rs2910164), miR149 rs2292832), miR-196a2 (rs11614913), and miR-499 (rs3746444) are well-established functional miRNAs –24. Rese32, miR-110164, miIn this systematic review and meta-analysis, we searched the database of PubMed, EMbase and the Cochrane Central Register to identify all eligible case-controlled trials that compared genotypes of the four selected miRNA genes in HCC patients with non-cancer control groups. All searches were performed in May 2019 and no language and date restrictions were set. The searching items were: “hepatocellular carcinoma”, “hepatoma”, “liver cancer”, “HCC”, and “microRNAs”, “miRNA”, and “polymorphism”, “allele”, “variation”, “SNP”.Eligible studies met the following criteria: (1) Case-controlled trials of subjects with HCC and healthy participants without HCC; (2) Evaluate the relationship between four common SNPs of miRNA  and HCC risk; (3) Investigate at least two selected SNPs at the same time; (4) Either DNA sequencing or PCR is used as a genotypic method for detection.Articles were excluded based on the criteria: (1) Duplicated articles or data; (2) Irrelevant cancers or SNPs; (3) Functional studies; (4) Lack of available genotype frequency.Two investigators independently abstracted the data on the studies. Discrepancies were resolved by consensus, referring back to the original study, or consulting a third reviewer. Besides genotype and frequency, the following data were also extracted from original studies: first author, year of publication, country, ethnicity, genotyping method, study design, case-control matching, sample size (cases/controls), and HBV infection status. To reduce the risk of bias due to individual studies, the Newcastle-Ottawa scale (NOS) score was applied to evaluate the methodological quality. The scale assesses three domains , based on “yes” or “no” answers to the following questions: (1) Is the case definition adequate; (2) Is there representativeness of the cases; (3) Is there selection of controls; (4) Is there a definition of controls; (5) Is there comparability of cases and controls; (6) Is there ascertainment of exposure; (7) Is the same method of ascertainment used for cases and controls; (8) Is there a non-response rate. The total score of NOS ranges from 0 to 9. A systematic analysis of the included studies was performed, and those with scores less than 5 were excluded. Two investigators independently performed the risk of bias assessments, with disagreement resolved by a third researcher when needed.2I are over 50%  and 95% confidence intervals (CIs) incorporating heterogeneity within and between studies. Statistical heterogeneity between each study was assessed with using the Chi-square tests and the inconsistency index I-square, with the values of 25%, 50%, and 75% denoting low, moderate and high heterogeneity, respectively. A random effects model was applied when over 50% . We wentTo further clarify the effect between four polymorphisms of miRNA on HCC, we conducted a Bayesian network meta-analysis. First a network plot depicting the connection within four SNPs was drawn. Every SNP was represented by a node, and the node size represented the number of studies of a corresponding SNP, the line thickness between two nodes represented the number of paired studies. Then, the analysis of variance (ANOVA) model was applied to combine the effective sizes of direct and indirect comparisons. The ability to rank interventions is an attractive feature of NMA compared to traditional analysis. The superiority index was calculated to rank competing polymorphisms. The superiority index ranges from 0 to ∞, which tends toward ∞ as the genetic model has a higher likelihood of predicting the risk of HCC and tends toward 1 indicating equal effect. Calculations were performed by R version 3.6.1 and STATA 14.0 was used to assist graphical functions.Overall, 985 citations were identified using the search strategy. Among them, 269 citations were duplicates and 623 were excluded due to inappropriate tumor, functional studies, meta-analysis, reviews after assessing titles and abstracts. In the remaining 93 articles, there are two unhealthy controls, seven lack of sufficient data, 62 articles of irrelevant polymorphisms were removed. In Akkiz’s study, three articles investigating the same population and separately reporting three miRNA genes were considered as one. Therefore, 20 studies were enrolled providing a total of 5,337 HCC cases and 6,585 controls Figure 1The forest plots of four miRNAs and their involvement in HCC susceptibility and relationship with HBV were explored and compared in The current study contained four SNPs: miR-146a rs2910164, miR-149 rs2292832, miR-196a2 rs11614913, miR-499 rs3746444. It was observed from the network evidence that the number of direct comparisons of miR-146a vs. miR-499 was the largest, followed by miR-146a vs. miR-196a2, miR-196a2 vs. miR-499 Figure 6MiRNAs play an important role in gene regulation of diseases , and havOf the 20 studies included in our research, the vast majority came from Asia, only two from Africa. Despite the rising incidence in North America and Europe, no enrolled studies came from either continent. The incidence of HCC varies widely within geographic locations. It is more common in low- and middle-income countries than in developed countries . It’s woThe pairwise results indicated that among the polymorphisms of miR-146a rs2910164, miR-149 rs2292832, miR-196a2 rs11614913, miR-499 rs3746444, only miR-196a2 was significantly associated with the susceptibility of HCC. When compared with TT genotype, CT or TT genotype in miR-196a2 carried a 1.232-fold increased risk of HCC. The network results were consistent with the direct results, with slight difference which was acceptable, indicating that our network evidence were robust. When comparing and ranking four SNPs, miR-196a2 rs11614913 appeared to have the highest superiority index. All of the above might come to the conclusion that miR-196a2 could serve as the best predictor of susceptibility in HCC.HBV infection has been well established as one of the leading causes for the carcinogenesis of HCC . When coMiR-196a2 rs11614913 is reported to be an important SNP associated with the etiology, progression and prognosis of several kinds of cancer. MiR-196a2 is located in the 3’passenger strand mature sequence of miR-196a2 , whose CAlthough our results indicated that only miR-196a2 was associated with the susceptibility of HCC, and there was not enough evidence to support the association in miR-146, miR-149 or miR-499, the negative results still could not be ignored and should be interpreted cautiously. This is due to the occurrence of HCC is the result of multiple factors, in addition to complex genetic factors, there are hepatitis, aflatoxin exposure, Hepatitis C virus infection and other factors –76. InstThere are some limitations in our study. Only published studies were included, and those studies with negative results that could not be published were likely to be omitted, leading to incomplete studies. Secondly, selection bias could exist and impact on the results since the control group in most studies are hospital-based rather than population-based. Finally, although we found that miR-196a2 could be a potential indicator, how this might predispose to HCC are unclear and further functional studies are needed to clarify the mechanisms.In conclusion, we found that the genetic polymorphism of miR-196a2 rs11614913 is significantly associated with the occurrence of HCC, especially for HBV- related HCC, and that individuals with TC/CC allele were more susceptible. No significant association was found in miR-146a rs2910164, miR-149 rs2292832, or miR-499 rs3746444. Our work could provide important information on the relationship between these four miRNAs and the susceptibility of HCC, suggesting potential novel diagnostic options. This would contribute to the reduction of mortality through early screening and diagnosis and improve the efficacy in HCC management.The original contributions presented in the study are included in the article/supplementary materials. Further inquiries can be directed to the corresponding author.QZ conducted the design of study, extracted the data, performed statistical analysis, and wrote the initial manuscript after consultation with the other authors. XX and HL improved the design, revised the manuscript, and approved the final version. TQ and SW checked the preliminary data. MW participated in the quality assessment adjudication. All authors contributed to the article and approved the submitted version.This study was partly supported by the Social Sciences Foundation of Liaoning Province (No. L18ATJ001).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background. The presence or absence of glutathione S-transferase M1 gene (GSTM1) and glutathione S-transferase T1 gene (GSTT1) polymorphisms, and their combined effects have been suggested as a risk factor for colorectal cancer (CRC). However, the results are inconsistent.Objectives. An updated meta-analysis was performed to solve the controversy.Methods. Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines were used.Results. Overall, the GSTM1 null genotype was associated with an increased CRC risk in Caucasians (odds ratio (OR) = 1.14, 95% confidence interval (CI): 1.05–1.23), Asians , high-quality studies . Moreover, the GSTM1 null genotype was also associated with an increased colon cancer risk . The GSTT1 null genotype was also associated with an increased CRC risk in Asians  and Caucasians . Moreover, The GSTT1 null genotype was associated with an increased rectal cancer risk  in subgroup analysis by tumor location. Last, the GSTM1 null/GSTT1 null genotype was associated with an increased CRC risk in Asians.Conclusion. This meta-analysis indicates that the GSTM1 and GSTT1 null genotypes are associated with increased CRC risk in Asians and Caucasians, and the GSTM1 null/GSTT1 null genotype was associated with increased CRC risk in Asians. Colorectal cancer (CRC) is a common form of cancer, with more than 1.5 million new patients diagnosed every year worldwide ,3. CRC iGSTs) are a large family of enzymes that catalyze the conjugation of electrophiles to glutathione and the conversion of toxic compounds to hydrophilic metabolites [GSTM1 maps to chromosome 1p13.3 contains 10 exons, while GSTT1 maps to chromosome 22q11.23 and contains six exons. GSTM1 present/null and GSTT1 present/null polymorphisms have been reported in human [GSTM1 and GSTT1, and have been proven to be associated with the loss of enzyme activity [Glutathione S-transferases  AND (polymorphism OR variant OR mutation) AND . The search strategy was designed to be sensitive and broad. We first carefully reviewed the title and abstract of the search results, and then downloaded full articles to identify possible articles. These were evaluated in detail to identify relevant articles. The reference lists of identified articles and reviews was also examined as appropriate. The corresponding author may be contacted by e-mail if only the abstract was available online or the data was incomplete.Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines were used . PubMed,GSTM1 present/null, GSTT1 present/null, and their combined effects with CRC risk; (2) sufficient genotype data to calculate ORs and 95% CIs; and (3) case–control studies. Exclusion criteria were as follows: (1) no raw data; (2) no control; (3) review articles, case reports, editorials, or animal research; (4) duplicate and insufficient data.Inclusion criteria were as follows: (1) articles on the GSTM1, GSTT1, and their combined effects in cases and controls. Different ethnicities included “Caucasians”, “Asians”, “Indians”, and “Africans”. If ethnicity was not stated or if the sample size could not be separated, the term “Mixed populations” was used. Two investigators independently assessed the quality of each individual study. The quality assessment criteria  first author’s name, (2) publication year, (3) country, (4) source of controls , (5) sample size, (6) genotyping method, and (6) genotype distribution of the criteria  were obtGSTM1 and GSTT1 polymorphisms was null vs. present. Their combined effects used the following five genetic models: − − vs. + +, − − vs. + −, − − vs.− +, − − vs. (+ −) + (− +), and − − vs. (+ −) + (− +) + (+ +). − − referred to the GSTM1 null/GSTT1 null genotype, + − referred to the GSTM1 present/GSTT1 null genotype, − + referred to the GSTM1 null/GSTT1 present genotype, and + + referred to the GSTM1 present/GSTT1 present genotype. Heterogeneity among studies was tested using the I2 value [I2 ≤ 50% [I2 > 50%. However, these studies cannot be pooled into together when I2 value > 75%. Subgroup analyses were performed by ethnicity, source of controls, tumor location, smoking history, gender, quality score, and tumor site. Then, a sensitivity analysis was carried out to assess the stability, a single study was excluded one at a time. Publication bias was tested by using Begg’s funnel and Egger’s test (significant publication bias was considered if P < 0.05). A nonparametric “trim and fill” method was applied to accredit missing studies if publication bias was detected. Finally, a meta-regression analysis was applied to assess the heterogeneity source. All results were calculated using Stata version 9.0 .We used crude odds ratios (ORs) and 95% confidence intervals (CIs) to estimate the association on the above issues. The genetic model of the individual I2 value . A fixedI2 ≤ 50% ; otherwiI2 ≤ 50%  if I2 > A flowchart of study selection is shown in GSTM1 present/null polymorphism  with CRC risk. Sixty-three articles of sixy-four case–control studies [GSTT1 present/null polymorphism  with CRC risk. Thirty-two publications of thirty-three case–control studies [GSTM1 present/null polymorphism; 48 high-quality studies were examined and the remaining 16 were low-quality concerning the GSTT1 present/null polymorphism; a total of 25 high-quality and eight low-quality studies were included on their combined effects with CRC risk.The main study characteristics are listed in  studies ,111–114  studies ,109,112 GSTM1 null genotype with CRC risk. The GSTM1 null genotype was associated with an increased CRC risk  in the overall population. In subgroup analyses by ethnicity, source of controls, and quality score, a significantly increased CRC risk was observed in Caucasians , high-quality studies  and low quality studies . Moreover, the GSTM1 null genotype was also associated with an increased colon cancer risk .GSTT1 null genotype with CRC risk. The included studies could not be merged together because I2 > 75% was found between the GSTT1 present/null polymorphism and CRC risk in the overall analysis and Caucasians. In subgroup analysis by ethnicity and quality score, a significantly increased CRC risk was observed in Asians . The GSTT1 null genotype was also associated with an increased rectal cancer risk  in subgroup analysis by tumor location.GSTM1 null/GSTT1 null genotype was associated with an increased CRC risk in the overall analysis  + (− +): OR = 1.26, 95% CI: 1.05–1.51, I2 = 70.4%; − − vs. (+ −) + (− +) + (+ +): OR = 1.26, 95% CI: 1.09–1.46, I2 = 69.0%).GSTM1 null/GSTT1 null genotype was associated with an increased CRC risk in Asians  + (− +): OR = 1.50, 95% CI: 1.20–1.86, I2 = 70.0%; − − vs. (+ −) + (− +) + (+ +): OR = 1.38, 95% CI: 1.19–1.60, I2 = 49.3%), hospital-based studies  + (− +) + (+ +): OR = 1.38, 95% CI: 1.19–1.60, I2 = 49.3%) and high-quality studies  + (− +): OR = 1.33, 95% CI: 1.09–1.62, I2 = 73.6%; − − vs. (+ −) + (− +) + (+ +): OR = 1.29, 95% CI: 1.10–1.51, I2 = 73.0%).In subgroup analyses by ethnicity, source of controls, and quality score, the P=0.002) was the source of heterogeneity for the GSTM1 present/null polymorphism. Concerning the GSTT1 present/null polymorphism and the combined effects of GSTM1 and GSTT1, meta-regression analysis did not reveal a source of heterogeneity under any genetic model. Additionally, 2I > 75% as shown in Significant heterogeneity was detected in the meta-analysis, as shown in GSTT1 null genotype was associated with an increased CRC risk in the following subgroups: Caucasians  and hospital-based studies . When the study of Martínez et al. [I2 value dropped and no significant association was found between the combined effects of GSTM1 and GSTT1 polymorphisms and CRC risk in Caucasians  + (− +): OR = 0.81, 95% CI: 0.53–1.26, I2 = 68.1%; − − vs. (+ −) + (− +) + (+ +): OR = 0.99, 95% CI: 0.69–1.41, I2 = 57.0%) and population-based studies  + (− +): OR = 1.16, 95% CI: 0.93–1.45, I2 = 73.9%; − − vs. (+ −) + (− +) + (+ +): OR = 1.08, 95% CI: 0.93–1.26, I2 = 63.5%). When the study of Gorukmez [I2 value dropped and no significant association was observed between the combined effects of GSTM1 and GSTT1 polymorphisms and CRC risk in low-quality studies . When the study of Cong et al. [I2 value dropped and no significant association was observed between the combined effects of GSTM1 present/null and GSTT1 present/null polymorphisms and CRC risk in population-based studies . A single study was excluded each time to assess the stability of the results. When the study of Laso et al.  was exclz et al.  was exclGorukmez  was deleg et al.  was exclP<0.001) revealed obvious publication bias between the GSTM1 present/null polymorphism and CRC risk in the overall analysis. GSTT1 present/null polymorphism (P=0.195). Concerning their combined effects, no publication bias was detected under any genetic model  + (− +); P=0.280 for − − vs. (+ −) + (− +) + (+ +)).Begg's funnel plot and Egger's test were used to assess publication bias in the meta-analysis. The Begg's funnel plot shape and Egger’s test , and the results of meta-regression analysis indicated that sample size was the source of heterogeneity between the GSTM1 null genotype and CRC risk. Small sample size studies may be important confounding bias in molecular epidemiological studies, because random error and bias were common in the studies with small sample sizes, and the results were unreliable [2I > 75% dropped when a single study was excluded, the results indicate that source of heterogeneity also may be from one or multiple small sample or low quality studies. Subgroup analysis by source of control found a significant association in hospital-based studies, but not in population-based studies in the present meta-analysis. However, hospital-based controls are not likely to replace the general population because they may have more bias than population-based studies . Thereforeliable . FurtherGSTM1 present/null and/or GSTT1 present/null polymorphisms with CRC risk. Cai et al. [GSTM1 null genotype and CRC risk in Asians, reporting that the GSTM1 null genotype was associated with an increased CRC risk. Liao et al. [GSTT1 null genotype was associated with an increased CRC risk in Caucasians and Asians. Wan et al. [GSTT1 null genotype was associated with an increased CRC risk in Caucasians. Teng et al. [GSTM1 null genotype with CRC risk and they found that the GSTM1 null genotype was associated with an increased CRC risk in Chinese. Gao et al. [GSTM1 null genotype with CRC risk in all races  and indicated that the GSTM1 null genotype was associated with an increased risk of CRC, especially in Caucasians. Qin et al. [GSTT1 null genotype may contribute to an increased CRC risk in Asians and Caucasians. Wang et al. [GSTM1 and GSTT1 and the dual null genotype of GSTM1/GSTT1 were not associated with CRC risk in Chinese population. The examination of 44 studies of GSTM1  and 34 studies of GSTT1  by Economopoulos and Sergentanis [GSTM1 and GSTT1 null genotypes were associated with an increased CRC risk in Caucasians. Li et al. [GSTM1 null genotype conferred susceptibility to CRC, especially in Chinese population. Xu et al. [GSTT1 null genotype was associated with an increased CRC risk in Asians. Zhong et al. [GSTT1 null genotype contributed to an increased CRC risk in Asians. Du et al. [GSTM1 and 8 studies of GSTT1, and found no association on the GSTM1 or GSTT1 null genotype with CRC risk. Huang et al. [GSTM1 null genotype was a risk factor for CRC.A total of 13 meta-analyses ,126,127 i et al.  examinedo et al.  examinedn et al.  identifig et al.  examinedo et al.  assessedn et al.  selectedg et al.  (19 studgentanis  indicatei et al.  analyzedu et al.  examinedg et al.  conducteGSTM1 present/null polymorphism, 64 case–control studies including 19,725 CRC cases and 28,725 controls for the GSTT1 present/null polymorphism, and 33 case-control studies including 8306 CRC cases and 14,369 controls for their combined effects in all races. Second, this is the first meta-analysis to explore their combined effects in overall population. Third, we used a meta-regression analysis method to explore the source of heterogeneity. Finally, the current meta-analysis included the most recent relevant publications to produce more accurate results.The current meta-analysis has several advantages over previous meta-analyses ,126,127.Similar to previous meta-analyses, our study also has several limitations. First, only published articles were selected. Hence, publication bias may be found as shown in GSTM1 null genotype is associated with increased CRC risk in Asians and Caucasians, the GSTT1 null genotype is associated with increased CRC risk in Asians, and the GSTM1 null/GSTT1 null genotype was associated with increased CRC risk in Asians. Further investigations involving large population-based studies should be conducted to explore the associations on the GSTM1 null genotype, GSTT1 null genotype and their combined effects with CRC risk.In summary, the present study indicates that the


Background: CYP4A11 gene T8590C (rs1126742) is proved to be an important locus that is relevant to hypertension. Various research on the relationship between rs1126742 polymorphism and hypertension have been published, but due to small sample sizes and limitations of the research objects, the combined results remain controversial.Methods: We searched PubMed, Embase, OVID, Web of Science, Wan Fang, and CNKI databases for related articles. Three authors individually extracted data and the quality of studies was evaluated by using the 9-point Newcastle–Ottawa Scale (NOS) independently. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in different genetic models by using a random-effect model or fixed-effect model according to inter-study heterogeneity. Besides, subgroup analysis and sensitivity analysis were performed and the publication bias was assessed.Results: There were totally 12 independent case–control studies of 8673 cases and 6611 controls included. Significant associations were found between CYP4A11 gene T8590C polymorphism and hypertension under all genetic models . We also found that there was no obvious relationship between the rs1126742 polymorphism and hypertension in Asian. But positive association has been found in Caucasian in allele, homozygote, and recessive model.Conclusions: CYP4A11 gene T8590C (rs1126742) polymorphism increases the occurrence of hypertension, particularly in Caucasian. Hypertension (HTN) is a key risk factor for many common diseases, including stroke, renal failure, heart failure, and coronary heart disease . And it Cytochrome P450 is a superfamily of cysteine isozymes and a major mediator for oxidative transformation of many endogenous and exogenous molecules. CYP4A11 is a major member of cytochrome P450 superfamily and is classified as cytochrome P450 family 4. CYP4A11 is mainly used as an enzyme to convert arachidonic acid (AA) into 20-hydroxytetradecanoic acid (20-HETE) and 20-HETE plays a pivotal role in the regulation of hypertension . Given tBecause allele frequencies are often different, meta-analysis can help to compare genetic associations in different studies. Accordingly, we conducted this meta-analysis to further validate the relationship between T8590C (rs1126749) polymorphism and the risk of hypertension.We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to perform this meta-analysis . RelevanWe reviewed all retrieved publications and citations, then evaluated the quality of each study by using the 9-point Newcastle–Ottawa Scale (NOS) independently . We haveThree authors individually extracted useful data of each study in this meta-analysis. Any potential conflicts were resolved by discussion. Extraction of study data includes: first author’s name, ethnicities, publication year, age, gender, systolic and diastolic blood pressure of patients and control individuals, source of controls, genotyping method, and genotypes distribution. We made attempts to contact the original authors for detailed information, if the data were missed in the publication.I2 is between 0 and 100, representing the degree of heterogeneity between studies. When I2 > 50 indicating heterogeneity between studies, a set analysis should be performed by using the random-effect model (Der Simonian and Laird methods). Otherwise the fixed-effect model (Mantel–Haenszel method) should be adopted. Subgroup analyses were also performed according to ethnicity, study sample size, source of control, and genotyping methods. The overall and subgroup analyses were both performed in five genetic models: allele (C vs. T), homozygote model (CC vs. TT), heterozygote model (TC vs. TT), recessive model (CC vs. TC+TT), and dominant model (CC+TC vs. TT). We have also investigated publication bias by calculating Egger’s test and drawing Begg’s funnel plot. We thought it was statistically significant between rs1126742 polymorphism with hypertension if P<0.05 or less. All statistical tests were performed by using Stata version 15.0 (Stata Corporation).We conducted Hardy–Weinberg equilibrium (HWE) tests of each study in our analysis for evaluation of included populations. We study the association strength between rs1126742 polymorphism and hypertension susceptibility by combining ORs and 95% CIs in a fixed or random-effect model based on the quantification of the heterogeneity calculated. The range of n = 4), insufficient data (n = 3), and not relevant to hypertension (n = 2). We search 6 databases and 162 records were found in total. After deleting duplicated studies, there were 58 studies remained for screening and 104 records were excluded. About 21 studies were read in full, and 9 of full-text articles were excluded because of unmatched study design , homozygote , heterozygote , recessive , and dominant genetic model . In summary, our meta-analysis proved that rs1126742 polymorphism of the CYP4A11 gene significantly increases the risk of hypertension. The results of forest plot are shown in P = 0.026; homozygote: OR = 1.79, 95%CI = 1.27–2.52, P = 0.001; recessive: OR = 1.76, 95%CI = 1.26–2.48, P = 0.001) excluding heterozygote , and dominant genetic model . But there was no obvious relationship between the rs1126742 polymorphism and hypertension in Asian . In subgroup analysis of source of control, we found population-based controls showed significant increased risk of hypertension in some models .We chose random effect model to conduct the data analysis when We performed sensitivity analysis to evaluate the stability of the results in the association between rs1126742 and hypertension susceptibility by removing one study at each round of the analysis. As it is shown in P>0.05).Publication bias is a common problem in meta-analysis. In our meta-analysis, we calculated Egger’s test and drew the Begg’s funnel plot to evaluate the publication bias. Visually from the Begg’s funnel plot , we coulCYP4A11 is one of the main enzymes that synthesizes 30% of 20-HETE in human body. The transfer to cytosine in nucleotide 8590 of exon 11 results in a nonsynonymous phenylalanine (F) to serine (S) substitution at residue 434 of CYP4A11. The change of protein 434 F to S affects the oxidation of arachidonic acid to 20-HETE . 20-HETEMany studies have tried to discover a possible association between the rs1126742 polymorphism and hypertension. Mayer et al.  revealedUnderstanding the genetic background of CYP4A11 is of great significance for better clinical application in the near future. People with high genetic risk scores may increase occurrence of hypertension. So we can use this genetic locus to predict hypertension. Second, some people believe that rs1126742 might be a promising locus for genetic therapy of hypertension .There are some limitations we can’t ignore. First, the data were not further stratified in subgroup by alcohol consumption, age, gender, smoking and other lifestyle factors, because the included studies in this research lacked consistent baseline data. Second, hypertension is a complex disease involved in several genes as well as many interferential factors such as environmental factors, which could influence the final results. Third, all the studies included were conducted in Asian and Caucasian, so people in other ethnicity did not attend this meta-analysis which may make our study localized. Taken these limitations into consideration, the results we concluded should also be interpreted with caution.The current meta-analysis concluded that the rs1126742 polymorphism of CYP4A11 significantly increases the risk of hypertension, particularly in Caucasian. It could be a promising locus for clinical genetic diagnosis and therapy of hypertension in the future. But more case–control studies with high quality are needed to strengthen the findings of this meta-analysis.


ABCG2 genepolymorphisms of 34 GG/(GA + AA) loci, 421 CC/(AC + AA) loci, and non-small celllung cancer (NSCLC) therapeutic effects via meta-analysis. With key words, thedatabases PubMed and EMBASE were searched for clinical studies on ABCG2polymorphism and NSCLC. RR and 95% CIs wereused to compute combined effects, followed by heterogeneity testing. Publicationbias was examined using the funnel plot method. Review Manager 5.3 software wasused for the meta-analysis. Ten studies were included. No evidence ofheterogeneity exists in these studies. The results indicate that two polymorphicloci of ABCG2 gene  had norelationship with the curative effect of chemotherapy for NSCLC, except ABCG234G>A, which had a significant relationship with the skin toxicitycomplication. There was no significant relationship between these polymorphismsand complications . Begg’s test and Egger’s test indicated that therewas no obvious publication bias. The meta-analysis indicated that there was nosignificant correlation between ABCG2 gene polymorphism andNSCLC outcomes.We aimed to analyze the correlation between  SpecifiABCG2 gene polymorphism and treatment effects ofchemotherapy on NSCLC patients, however no consensus has been reached  . As mentABCG2gene polymorphism on the chemotherapy effect of NSCLC through a systematic review ofstudies and meta-analysis.Therefore, this study aims to explore the prognosis value of ABCG2 gene polymorphism and NSCLCoutcomes published before December 3, 2018. The keywords included: [‘non-smallcell lung cancer’ OR ‘NSCLC’ OR ‘squamous cell lung cancer’ OR ‘lungadenocarcinoma’ OR ‘large cell lung cancer’] AND [‘ATP-binding cassettesub-family G member 2’ OR ‘ABCG2’ OR ‘breast cancer resistance protein’ OR‘BCRP’ OR ‘CDw338’ OR ‘mitoxantrone resistance protein’ OR ‘MRP’ OR ‘ABCP’] AND[‘polymorphism’ OR ‘polymorphisms’ OR ‘genetic’ OR ‘variation’ OR ‘genotyping’OR ‘SNP’].The search strategy was pre-designed. The databases PubMed and EMBASE weresearched for studies on ABCG2 genepolymorphisms and NSCLC treatment effects; 3) studies that reported thefrequencies of gene types and alleles or from which these data can becalculated; 4) studies that reported curative effect indicators such asprogression free survival (PFS), overall survival (OS), mortality risk, andresponse; and adverse effect indicators such as drug-induced diarrhea, skintoxicity, liver dysfunction, and interstitial pneumonia; 5) reviews, reports,comments or letters were excluded. Newcastle-Ottawa Scale (NOS) (The inclusion criteria were 1) clinical studies with NSCLC patients as cases; 2)studies that investigated the correlation between le (NOS)  was usedThe following data from the included studies was extracted independently by tworesearchers, including first author, publication year, distribution of ethnicgroups, distribution and frequencies of genotypes and alleles, and the genderand age of patients in each study. If there was inconsistency during dataextraction, discussion with a third researcher was initiated until an agreementwas reached.CI.RR and 95% CIs (m (mutation)/m + w(wild)/m vs. w/w) were used to calculate the combined effect sizes of the otherindicators. Heterogeneity test was conducted according to the chi-square-basedQ test , the random-effect model (byDersimonian-Laird method) was used to pool the effect sizes; otherwise, the FEmodel (by Mantel-Haenszel method) was used. Subgroup meta-analysis based onchemotherapeutics, race, and grade of toxicity was performed. Begg’s test andEgger’s test were used to examine publication bias for studies with the largestnumber of publications included. All tests were two-sided, with a significancethreshold of P < 0.05.Meta-analysis was conducted using the Review Manager Version 5.3 (2008).Mortality risk was combined using HR and 95% The characteristics of correlational studies are listed in ABCG2 gene and the prognosis of chemotherapy for NSCLC wereinvestigated. The results are displayed in FiguresS1-S8. For the indicators of OS, PFS,mortality , and interstitial pneumonia, the included literature only report thedata related to ABCG2 421C>A. There were no heterogeneities among studies forall curative effect indicators and adverse effect indicators , thus theFE model was adopted to combine all effect sizes. The meta-analysis results showthat the polymorphism ABCG2 421C>A had no relationship with outcomes ofchemotherapy for NSCLC (P > 0.05), and ABCG2 34G>A wassignificantly correlated with skin toxicity (P < 0.05).The correlations between the polymorphisms of two loci of thevs. others), races (Asianvs. Caucasian) and grade of toxicity  were performed. The results show that ABCG2421C>A had no influence on skin toxicity or diarrhea  based onthe chemotherapeutics .The publication bias test was conducted on “drug-induced diarrhea” of ABCG2421C>A that had the most included papers. Both Begg’s test and Egger’s testindicated that no publication bias exists (Begg’s test: ABCG2 gene polymorphismsand the efficacy and safety of NSCLC treatment. Polymorphisms at two loci of theABCG2 gene (34 G>A and 421 C>A) were evaluated. Inaddition, the qualities of the included studies are relatively high. There is nosignificant heterogeneity among studies for the entire analysis. Moreover, nopublication bias is noted. Furthermore, compared with a recent meta-analysis ofABCG2 gene polymorphisms are associatedwith the risk of gefitinib-induced toxicity in NSCLC patients, our study addedmeta-analysis of survival outcomes.This meta-analysis systematically reviewed ABCG2 gene polymorphisms and the curative effects and adverseeffects of chemotherapy of NSCLC, except that ABCG2 34G>A showed a negativerelationship with skin toxicity in patients after chemotherapy. However there wasonly one study (Overall, this meta-analysis did not find a significant relationship between evaluatedABCG2 may have an effect on the multi-drug resistance of chemotherapeutic agents suchas mitoxantrone and camptothecin analogues (This meta-analysis did not limit the types of chemotherapy drugs and included as manystudies as possible. Additionally, we added the analysis of survival outcomes.Nevertheless, there were shortcomings in this study, due to the small sample sizefor some indices, and conclusions from the results should therefore be drawn withcaution.In all, it can be concluded that the ABCG2 polymorphism could not be used as aprognosis indicator of chemotherapy for NSCLC. However, due to the limitations inthis study, the results should be interpreted cautiously. More studies with largesample sizes, randomized designs, and unified styles of outcomes are necessary.