GERD) are major risk factors associated with Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC). EAC has been increasing the past few decades, and early discovery and treatment are crucial for survival. Telomere shortening due to cell division and oxidative damage may reflect the impact of chronic inflammation and could possibly be used as predictor for disease development. We examined the prevalence of shorter leukocyte telomere length (LTL) among individuals with GERD, BE, or EAC using a pooled analysis of studies from the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON). Telomere length was measured in leukocyte DNA samples by Q‐PCR. Participants included 1173 patients  and 736 population‐based controls. The association of LTL (in tertiles) along the continuum of disease progression from GERD to BE to EAC was calculated using study‐specific odds ratios (ORs) and 95% confidence intervals (CIs) from logistic regression models adjusted for potential confounders. Shorter LTL were less prevalent among GERD patients , compared to population‐based controls. No statistically significant increased prevalence of short/long LTL among individuals with BE or EAC was observed. In contrast to some earlier reports, our findings add to the evidence that leukocyte telomere length is not a biomarker of risk related to the etiology of EAC. The findings do not suggest a relationship between LTL and BE or EAC.Chronic inflammation and oxidative damage caused by obesity, cigarette smoking, and chronic gastroesophageal reflux disease ( Oxidative stress can cause large intragenic deletions, as well as chromosomal loss and chromosomal instability Gastroesophageal reflux disease (GERD) and Barrett's esophagus (BE) are both major risk factors in the development of esophageal adenocarcinoma (EAC), which has been rapidly increasing in incidence in the Western world Several studies have, however, reported associations between telomere length and esophageal cancer, with somewhat conflicting results http://beacon.tlvnet.net/). We hypothesized that the prevalence of LTL shortening would be higher among those with more severe disease compared to population‐based controls.In this analysis, we evaluated leukocyte telomere length (LTL) in three sets of cases: GERD, BE, and EAC, using seven studies from the Barrett's and EAC Consortium , smoking, alcohol, DNA concentration, and extraction method was collected from each study. Two studies contributed samples from individuals with GERD: the Study of Reflux Disease (SRD) based in western Washington, USA Restricted to Whites only, we selected 400 individuals with GERD, 404 individuals with BE, 384 individuals with EAC, and 749 population‐based controls.Controls were selected from the same source population from which the cases arose and were frequency matched to cases by gender and age in each study. In total, 386 GERD individuals, 403 BE individuals, 384 EAC individuals, and 736 controls were included in our analysis (Table S1). In total 173 samples were excluded from our analysis. A total of 17 samples had insufficient amounts of DNA, 121 samples either had missing information on DNA extraction method or DNA was extracted with various methods within the study population. Furthermore, 35 cardia stomach cancer cases were previously misclassified as EAC cases, these cases were excluded from the analysis when this was discovered.IRB approval was obtained for each of the included studies.Four different methods were used to extract leukocyte DNA from whole blood among the selected studies: 5‐Prime  was used in the SRD study; Gentra Puregene DNA purification kit  was used in the FINBAR, EIBO, and SECC studies; the salting out method LTL was measured by quantitative PCR (q‐PCR) at the Cytometry and Telomere Center, Department of Pathology, University of Washington, using the method described by Cawthon 2) and alcohol consumption (ever or never drinking), and a subsequent analysis also including years of smoking . To evaluate possible effect modification, we conducted sensitivity analyses by mean age at recruitment (<60 years or >60 years), gender, BMI (<30 kg/m2 or >30 kg/m2), smoking status (ever or never smoking), and alcohol intake (ever or never drinking).The association of LTL with GERD, BE, and EAC was calculated using a two‐step analytic approach. First, the association between LTL and each outcome was investigated separately in each of the included studies. LTL was treated both as a continuous variable and categorized as tertiles  based on the distribution among population‐based controls. We used logistic regression modeling to calculate study‐specific odds ratios (ORs) and 95% confidence intervals (CIs). Site‐specific ORs were pooled together using individual results from each relevant BEACON study. The model was minimally adjusted for gender, age (continuous), and method of DNA extraction. Further in the fully adjusted model for smoking status (ever or never smoking), BMI . LTL was negatively correlated with male gender , increased age , and positively correlated with alcohol use . LTL was negatively correlated with BMI , although not statistically significant. We found no correlation between LTL and ever/never smoking . However, years of smoking was correlated with LTL . Subsequently, including years of smoking in our model did not change the results notably in the main analysis (data not shown). The longest median LTL was observed among those with GERD , followed by BE  and EAC  (Table S3).Seven study populations were included from the BEACON consortium Table . CharactCompared to population controls, a decreased risk of GERD was observed among those with short LTL T3 vs. T1), OR 0.57 (95% CI: 0.35–0.93) Table . Very li vs. T1, 2 (Table S4).Compared to patients with GERD, those with BE were more likely to have short telomere length T3 vs. T1) (OR 1.48 [95% CI: 0.91–2.40]); this was, however, not statistically significant  and performed in 100‐well using Rotor Gene Q (Qiagen). Each reaction included 1× Rotor Gene Sybrgreen PCR master mix (Qiagen), 2.5 ng of DNA, 500 nmol/L primer, and 1 uM control‐gene primer. In addition, 400 nmol/L of a passive HEX‐labeled oligo was included in all reactions as a passive reference dye. The Rotor Gene software (Qiagen) was used to normalize the Sybrgreen intensity to the HEX passive reference dye.Table S3. Study characteristics of GERD, BE, and EAC cases by study. The following studies used Gentra Puregene DNA purification kit : FINBAR, EIBO, and SECC. ACS and SDH used Protein Salting Out method. In SRD study 5‐Prime  was used and in LAM study Qiagen QIAamp DNA Blood kit (Qiagen) was used. Abbreviations: FINBAR, the Factors Influencing the Barrett's/Adenocarcinoma Relationship study; EIBO, the Epidemiology and Incidence of Barrett's Oesophagus study; SECC, the Swedish Esophageal and Cardia Cancer study; ACS, the Australian Cancer study; SDH, the Study of Digestive Health; LAM, the Los Angeles Multi‐ethnic Study; SRD, the Study of Reflux Disease.Table S4. Leukocyte telomere length and prevalence of GERD, BE, and EAC stratified by smoking, obesity, and alcohol consumption. Odds ratios and 95% confidence interval for leukocyte telomere length (LTL)  with risk of gastroesophageal reflux (GERD), Barrett's esophagus (BE), and esophageal adenocarcinoma (EAC), stratified by smoking (ever smokers and nonsmokers) BMI (<30 kg/m2 and >30 kg/m2), and alcohol consumption (consumers and nonconsumers). The analysis was minimally adjusted for age, gender, and DNA extraction method.Click here for additional data file.


The genetic architecture of bone and soft tissue sarcomas susceptibility is yet to be elucidated. We aimed to comprehensively collect and meta-analyze the current knowledge on genetic susceptibility in these rare tumors.We conducted a systematic review and meta-analysis of the evidence on the association between DNA variation and risk of developing sarcomas through searching PubMed, The Cochrane Library, Scopus and Web of Science databases. To evaluate result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate result noteworthiness. Integrative analysis of genetic and eQTL (expression quantitative trait locus) data was coupled with network and pathway analysis to explore the hypothesis that specific cell functions are involved in sarcoma predisposition.ZNF365/EGR2, rs231775 of CTLA4, and rs454006 of PRKCG) was 37.2%. We also identified 53 SNPs significantly associated with sarcoma risk based on single studies.We retrieved 90 eligible studies comprising 47,796 subjects  and investigating 1,126 polymorphisms involving 320 distinct genes. Meta-analysis identified 55 single nucleotide polymorphisms (SNPs) significantly associated with disease risk with a high (N=9), moderate (N=38) and low (N=8) level of evidence, findings being classified as noteworthy basically only when the level of evidence was high. The estimated joint population attributable risk for three independent SNPs (rs11599754 of Pathway analysis enabled us to propose that sarcoma predisposition might be linked especially to germline variation of genes whose products are involved in the function of the DNA repair machinery.We built the first knowledgebase on the evidence linking DNA variation to sarcomas susceptibility, which can be used to generate mechanistic hypotheses and inform future studies in this field of oncology. Sarcomas are a family of rare malignant tumors arising from bone and soft tissues with more than 50 different histologies accounting for about 1-2% of cancers in adults and 15-20% in children . The pathogenesis of sarcomas is multifactorial including environmental  and genetic components, although the disease rarity represents an objective hurdle to the research in this field of investigation. Significant advances have been made in the understanding of the acquired genetic events leading to sarcomagenesis. It has been recognized that three types of somatic DNA alterations, translocations, mutations, and copy number variations, play a key role in these tumors ,where Pr is the proportion of control subjects exposed to the allele of interest and the relative risk (RR) was estimated using the summary estimates (i.e. ORs) calculated by the meta-analysis. The joint PAR for combinations of polymorphisms was calculated as follows:1→n[1 − PARi]),1 −  analysis was used to identify genes whose expression is affected by DNA variants . The resFor the former, the STRING web server was employed to study protein-protein interaction (PPI) across the selected genes , the conAs regards pathway analysis, the Enrichr web server was utilized to identify in our list over-representation of genes involved in specific pathways described in dedicated databases . HypergeEthics approval and consent to participate: Not applicableConsent for publication: Not applicableAvailability of data and material: All data generated or analysed during this study are included in this published article [and its supplementary information files].


Meningiomas are the most common brain tumours; however, little is known regarding their aetiology. The data are inconsistent concerning atopic disease and the risk of developing meningioma. Thus, we conducted a meta-analysis to investigate the association between allergic conditions and the risk of developing meningioma. A systematic literature search was conducted using PubMed and Web of SCI from Jan 1979 to Feb 2016. Two investigators independently selected the relevant articles according to the inclusion criteria. Eight case-control studies and 2 cohort studies were included in the final analysis, comprising 5,679 meningioma cases and 55,621 control subjects. Compared with no history of allergy, the pooled odds ratio (OR) for allergic conditions was 0.81 (0.70–0.94) for meningioma in a random-effects meta-analysis. Inverse correlations of meningioma occurrence were also identified for asthma and eczema, in which the pooled ORs were 0.78 (0.70–0.86) and 0.78 (0.69–0.87), respectively. A reduced risk of meningioma occurrence was identified in hay fever; however, the association was weak . The source of this heterogeneity could be the various confounding variables in individual studies. Overall, the current meta-analysis indicated that allergy reduced the risk of developing meningiomas. Large cohort studies are required to investigate this relationship. Meningiomas are the most frequently reported brain tumours and account for 36.4% of all central nervous system (CNS) tumours. The incidence of meningioma increases with age and is 2.5 times higher in females than in males14Numerous studies have investigated the relationship between the occurrence of brain tumours and allergic conditions, including asthma, eczema, and hay fever. Atopic diseases have been inversely correlated with the risk of developing gliomas67871011126815Eleven articles, including 9 case-control studies and 3 cohort studies, that investigated the relationship between brain meningiomas and allergic conditions were identified through literature searches81011121315161718The details of the included subjects are presented in 2 = 69.8%, P = 0.000). We identified an inverse association in the case-control study ; however, we failed to identify similar results in the cohort study  compared with the alternative (I2 = 82.6%). Proxy respondents were less likely to report an allergic condition, which may lead to bias10Study-specific log ORs and the corresponding confounders adjusted are shown in The relationship between the risk of developing meningioma and the occurrence of specific allergic conditions was also investigated in 8 asthma studies, 9 eczema studies and 6 hay fever studies . We idenIn the two previous meta-analyses, no relationship between allergy history and meningioma occurrence was identified6815+ and CD8+ T lymphocytes, an increase in FOXP3+ Treg and PD-L1 (programmed death-ligand 1) levels26272829Our results were also supported by the fact that serum IgE levels  were reduced in patients with meningiomas compared with control subjects2120232. The occurrence of meningiomas was likely to vary according to region, race, smoking history and socioeconomic status131322, which provided log ORs adjusted by at least 3 compounding variables . Moreover, the relationships between ionizing radiation exposure, BMI and physical activity and the risk of meningiomas were completely ignored in the included studies4There were several limitations in our study. First, there was substantial heterogeneity in the analysis of meningiomas with allergy, i.e., 69.8% by IIn summary, allergic conditions were significantly associated with a reduced risk of developing meningiomas in this meta-analysis. We also identified a lower risk of meningiomas in subjects with asthma and eczema, whereas hay fever was weakly correlated with meningioma occurrence. Large cohort studies that include adequate samples remain necessary to investigate this relationship.Two authors independently conducted literature searches using PubMed and ISI Wed of SCI from Jan 1979 to Feb 2016, using the search terms brain tumour, meningioma, allergy, atopy, asthma, eczema, and hay fever. The eligibility criteria for the studies included in this meta-analysis were as follows: (1) contained data from a case-control study or a cohort study, (2) a medical diagnosis of meningioma, (3) investigated the relationship between the risk of meningioma and allergy, and (4) provided an OR or relative risk (RR) with estimates of 95% CIs . In cases in which patients were included in more than one publication, the most recent study was selected for analysis.All potential articles were independently reviewed and the data were extracted by two investigators; the variables included the first author’s name, publication year, geographical origin, number of cases and controls, exposure definitions and risk estimates. Discrepancies were solved by discussion and consensus. We assessed the study quality using the NOS2. To investigate the potential origin of the heterogeneity, the included studies were further divided into subgroups according to the study characteristics (case-control vs. cohort study), proxy rates (high vs. low), and potential cofounders adjusted in individual studies . Publication bias was assessed by Funnel plots, the Begg test, and the Egger test.To compute the pooled ORs of allergy in meningiomas, we used the multivariate-adjusted risk estimates in each study rather than raw data. Study-specific log RRs or log ORs were weighted by the inverse of their variances. We present the pooled ORs in the random-effect models, which provide pooled results that are less precise but provide correct coverage. The heterogeneity among the studies was assessed by the method of DerSimonian and Laird QHow to cite this article: Wang, P.-f. et al. Allergy reduces the risk of meningioma: a meta-analysis. Sci. Rep.7, 40333; doi: 10.1038/srep40333 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Information regarding association between cytomegalovirus (CMV) infection and essential hypertension (EH) risk is not consistent across studies. Therefore, we conducted a meta-analysis to investigate the association in detail.We comprehensively searched the published literature from the PubMed and Embase databases for any study analyzing the association between CMV and EH risk. A random-effects model was used to calculate the pooled odds ratio (OR) with 95 % confidence interval (CI).P = 0.017). There was significant heterogeneity among the studies included (I2 = 70.5 %). The funnel plot and Egger’s test also indicated no publication bias.Three studies involving 9657 patients were included in the meta-analysis, and the results showed a significantly increased risk of EH in patients with CMV infection. Overall, 79.3 % of the hypertension patients were CMV-positive, which was significantly higher than the percentage for controls (OR = 1.39, 95 % CI = 0.95–2.05, The results showed a significant association between CMV and EH, which indicates that CMV infection is a possible cause of EH. Essential hypertension (EH) is the most common form of hypertension  and is aHerpesviridae family, cytomegalovirus (CMV) contains double-stranded DNA [As a member of the human nded DNA  and estanded DNA , overt hnded DNA –7. In heCMV infection is associated with various chronic inflammatory diseases, including cardiovascular diseases (CVDs)  such as We comprehensively searched the PubMed and Embase databases up to July 2015. The search key words used included “EH or hypertension”, “blood pressure”, and “CMV”. Relevant articles in the reference lists of the published literature were also searched manually for other potential studies.Studies were included in the meta-analysis if they met the following criteria (1) case-control study, (2) investigated the positive rate of CMV in hypertension patients and controls, (3) hypertension is defined as systolic blood pressure (SBP) or diastolic blood pressure (DBP) of 140 or 90 mmHg, respectively, (4) not an animal study. Studies were excluded if insufficient details were reported to be able to perform the meta-analysis.Two authors (JH and Y-YQ) extracted the data independently. In cases where any data were lacking from an article, the authors of selected studies were contacted directly for the missing data. The two reviewers came to an agreement before the final analysis. The following information was extracted from each study: first author’s name, year of publication, country, ethnicity, CMV detection method, patient characteristics, the sample sizes of cases and controls, and the relationship between CMV and EH.2 statistic (range 0–100 %) [P < 0.1 or I2 > 50 %, respectively. We select the random-effects model in the analysis if significant heterogeneity was observed across studies; otherwise, the fixed-effects model was used. Sensitivity analysis was performed with the random-effects model to evaluate the stability of the crude results by removing one study at a time. The Begg’s funnel plot and Egger’s linear regression test were performed to determine the level of potential publication bias [P-value lower than 0.05 was considered statistically significant.We performed statistical analyses using Stata statistical software ver.12.0. . Meta-analysis was conducted by combining odds ratios (ORs) with corresponding 95 % confidence intervals (CIs) for the association between the CMV-positive rate of hypertension patients and controls. Heterogeneity across all selected studies was evaluated using the Q-test and the I0–100 %)  and was ion bias , 21. A PA total of three articles , 13, 16 P = 0.017). We used a random-effects model, given the significant heterogeneity (I2 = 70.5 %) observed across studies. The overall result of the meta-analysis is shown as a forest plot in Fig. We pooled data from all studies included and analyzed the association between CMV and EH risk. A total of 79.3 % of the hypertension patients were CMV-positive compared with 64.2 % of the controls. The pooled OR was 1.39 .Begg’s funnel plot and Egger’s test were used to evaluate the potential publication bias. Although Begg’s funnel plot was not symmetrical, the Egger’s linear regression test indicated that there was no significant publication bias  and the Ministry of Major Science & Technology of Shihezi University  and the Xinjiang Graduate Student Research Innovation Project (No. XJGRI2015054). No conflict of interest exists in this study.


Subgroup analysis by ethnicity found a significant lower risk of T2DM in Chinese in all genotype models. No significant relation was found between ALDH2 rs671 and DR. In conclusion, the current meta-analysis indicated that ALDH2 rs671 was significantly related with T2DM. The ALDH2 rs671 might be able to be used as a predictor for the risk of T2DM. However, due to the existence of heterogeneity and publication bias in the involved studies, our results should be interpreted with caution.Type 2 diabetic mellitus (T2DM) is a disease with high prevalence and a major cause for death worldwide. Diabetic retinopathy (DR) is one of the major manifestation of diabetes. Aldehyde dehydrogenease 2 (ALDH2) detoxifies aldehyde produced during ethanol metabolism and oxidative stress. It has been found that the polymorphism in ALDH2 rs671 is probably associated with the risk of T2DM and DR. However, a lot of inconsistency and controversy still exists. In order to get a more precise and comprehensive estimation for the association between ALDH2 polymorphism with the risk of T2DM and DR, we conducted the present meta-analysis. A comprehensive literature search was conducted using databases, such as Pubmed, Embase, Cochrane Central Register of Controlled Trials, Chinese National Knowledge Infrastructure, and Chinese Biomedical Literature Database, for all related studies. The included studies met the inclusion criteria, such as being case-control studies about the association of ALDH2 polymorphism and T2DM or DR susceptibility, with sufficient data for the present analysis. Eight studies with 2374 cases and 6694 controls were involved in the present meta-analysis. The results indicated a significant lower risk of T2DM for *1/*1 genotype in homozygous models (*1/*1 vs. *2/*2, OR = 0.31, 95% CI = 0.11–0.89,  Type 2 Diabetic mellitus (T2DM) is a major risk factor for many diseases such as coronary artery disease (CAD) and ocular disorders ,2. DurinALDH2 is a key enzyme for alcohol metabolism. It is encoded by the ALDH2 gene in chromosome 12. There is a significant single-nucleotide polymorphism (SNP) in ALDH2, named rs671 (G-to-A), which causes a replacement of glutamate to lysine at position 504. The Glu504 is named *1, and the 504Lys is named *2. The ALDH2 *2 allele causes a drastic decrease of enzyme activity ,9. It isUp to the present, several studies have demonstrated the relationship between ALDH2 rs671, T2DM, and diabetic retinopathy (DR). However, the results are controversial. Some of them reported a lower susceptibility of T2DM for the *1 allele, while the associations between them were not significant in other studies. To get a more precise and comprehensive estimation for the association between ALDH2 polymorphism with the risk of T2DM and DR, we conducted the present meta-analysis.All the literature in the electronic databases Pubmed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Chinese National Knowledge Infrastructure (CNKI), and Chinese Biomedical Literature Database were checked systematically and comprehensively. The search terms used were as follows: , , and . The literature in English or Chinese were included, and the search deadline for publications was 24 September 2016. All publications from the databases which met the search criteria were screened carefully, and the references and citations of included studies were checked for other potentially relevant studies. The PubMed option ‘Related Articles’ was also checked for additional studies.The inclusion criteria were as follows: (1) case-control study; (2) study was about the association of ALDH2 polymorphism and diabetic mellitus or diabetic retinopathy susceptibility; (3) the data in the studies were sufficient for the present analysis. The exclusion criteria were as follows: (1) repeat publications, abstracts, dissertations, or reviews; (2) studies violating any of the inclusion criteria.The information from each included study was extracted by two investigators manually. The extracted information includes: first author’s name, publishing year, country, ethnicity, genotype method, the source of control, and case or control numbers of each genotype. All discrepancies that happened during the data extraction process were resolved by a consensus achieved by a third author.The quality of each involved study was evaluated according to previous studies ,14,15. B2-test, and the results with p < 0.05 were considered to be HWE deviations. We used the crude odds ratio (OR) with 95% confidence interval (CI) to assess the association between ALDH2 rs671 and T2DM risk, as well as DR risk. For the meta-analysis, pooled ORs were calculated in homozygous (*1/*1 vs. *2/*2), heterozygous (*1/*1 vs. *1/*2), dominant (*1/*1 vs. *1/*2 + *2/*2) and allelic models (*1 vs. *2), and the statistical significance was determined by the Z-test. If the results were p < 0.05, it was considered to be statistically significant. Subgroup analysis by sample size was conducted. Groups with total samples less than 1000 were treated as small and all other groups were treated as large.The HWE of control group polymorphisms was evaluated by χI2 test, which was considered to be independent of the number of studies in the meta-analysis, was used to evaluate the statistical heterogeneity between studies  cp-values of both tests were shown in p < 0.05). We also found an obvious asymmetry in Begg’s funnel plots, indicating an obvious publication bias existing in the involved studies. No significant asymmetry was found for studies on ALDH2 rs671 and DR.In order to evaluate the publication bias, we conducted Egger’s test and Begg’s test. The I2 % values were greater than 50% in all subgroups, which indicated that none of them were the source of heterogeneity.We found a high heterogeneity between the involved studies during the meta-analysis. In order to figure out the source of the heterogeneity, subgroup analyses by source of control, ethnicity, and sample size were performed. However, as shown in In the present meta-analysis, we found a significantly lower risk of T2DM for ALDH2 *1/*1 genotype in the homozygous and dominant model (OR = 0.31 and OR = 0.61 respectively). Subgroup analysis by ethnicity discovered a drastic decrease in the risk for T2DM among Chinese. No significant relationship between ALDH2 rs671 and DR was found in the dominant model.For the rs671 polymorphism of the ALDH2 gene, *1 was considered to be an active form and *2 to be an inactive form. ALDH2 was first known as a key enzyme for alcohol metabolism, especially in East Asians. Previous studies indicated that the *1/*2 or *2/*2 genotype decreased the activity of the ALDH2 enzyme. The *2/*2 lost almost all of the enzyme activity, while *1/*2 showed only 6.3% of the activity compared with the *1/*1 genotype ,11. The In diabetes mellitus patients, hyperglycemia leads to both micro- and macrovascular complications, including diabetic retinopathy ,25. The Interestingly, the *2 allele resulted in a drastically higher level of acetaldehyde in the blood and subsequently inhibited the consumption of alcohol . AlcoholWe found an obvious heterogeneity in the present meta-analysis for ALDH2 rs671 and DM. We have conducted subgroup analyses by source of control, ethnicity, and sample size to explore the source of this heterogeneity. However, none of them were responsible for it. Interestingly, in the study of Xu (2010) , the assWe found an obvious publication bias in Egger’s test and Begg’s test for ALDH2 rs671 and DM in the present study. After a comprehensive literature search, all the published studies were involved. However, most of the studies included in the present study had a small sample size. The small-sample effect might be responsible for the bias. We found a significant influence of the study of Yakoyama 2013) [13 [20] oThe results of the present meta-analysis should be interpreted with caution as they have the following limitations: Firstly, the number of patients involved was relatively small. In the present meta-analysis, only 6 studies were included for ALDH2 polymorphism and T2DM (1247 cases and 2817 controls), and another 4 studies were included for ALDH2 polymorphism and DR susceptibility (1127 cases and 3877 controls). Secondly, a big heterogeneity and publication bias existed among the involved studies, which might affect our results. Thirdly, DM is a multi-factorial disease; the environmental factors may play important roles in its pathogenesis. In the present meta-analysis, most of the included studies lacked sufficient data on environmental exposure, such as alcohol consumption, smoking, hyperlipidemia, body mass, fasting plasma glucose, and the complications of DM. Finally, DM is a multi-gene disease which may be related with gene-gene or gene-environment interactions. However, no such information was available in the included studies.In conclusion, the present meta-analysis indicated a significantly lower risk of T2DM for the *1 allele and *1/*1 genotype of ALDH2 rs671, especially among Chinese. No significant relationship between ALDH2 rs671 and DR was found in the dominant model. Thus, ALDH2 rs671 might be suggested as a predictor for the risk of T2DM. However, because of heterogeneity among the studies involved, the results of the present meta-analysis should be interpreted with caution. Further studies with large samples, including environmental factors and clinicopathological characteristics are needed to evaluate the association between ALDH2 rs671 and T2DM.


KLK3, IGFBP3, ESR1, SOD2, CAT, CYP1B1, VDR, RFX6, HNF1B, SRD5A2, FGFR4, LEP, HOXB13, FAS, FOXP4, SLC22A3, LMTK2, EHBP1 and MSMB) exhibited significant association with prostate cancer. The average summary OR was 1.33 (ranging from: 1.016–3.788) for risk alleles and 0.838 (ranging from: 0.757–0.896) for protective alleles. Of these positive variants, FOXP4 rs1983891, LMTK2 rs6465657 and RFX6 rs339331 had not been previously meta-analyzed. Further analyses with sufficient power design and investigations of the potential biological roles of these genetic variants in prostate cancer should be conducted.In the past twenty-five years, over 700 case-control association studies on the risk of prostate cancer have been published worldwide, but their results were largely inconsistent. To facilitate following and explaining these findings, we performed a systematic meta-analysis using allelic contrasts for gene-specific SNVs from at least three independent population-based case-control studies, which were published in the field of prostate cancer between August 1, 1990 and August 1, 2015. Across 66 meta-analyses, a total of 20 genetic variants involving 584,100 subjects in 19 different genes ( BRCA1, BRCA2, and HOXB13 definitely account for a small proportion of cases of hereditary prostate cancer [Prostate cancer (PCa) is the second most common type of solid cancer and the sixth leading cause of cancer death in men worldwide . In the e cancer –10. Basee cancer –13. Popue cancer , 15. To e cancer .To better assess and explain the association of genetic variants with PCa, we have collected and catalogued all population-based case-control genetic association studies, which were published in the field of PCa between August 1, 1990 and August 1, 2015. Subsequently, we systematically meta-analyzed gene-specific SNVs using genotyping data available from at least three independent case-control studies.After screening over 40,000 titles and abstracts, we obtained 728 publications reporting on 217 genetic SNVs in 136 different genes . Based oKLK3, IGFBP3, ESR1, SOD2, CAT, CYP1B1, VDR, RFX6, HNF1B, SRD5A2, FGFR4, LEP, HOXB13, FAS, FOXP4, SLC22A3, LMTK2, EHBP1 and MSMB) had significant summary ORs (referred to as “positive” association)  with an average protective summary OR of 0.838 (ranging from 0.757–0.896) decreased the risk for PCa by approximately 14%. Apart from 17 SNVs that have been previously meta-analyzed using published data .Among the 217 SNVs, 66 variants in 51 different genes with sufficient data were finally included for our meta-analysis . Combini) Tables  and S3. P values of eleven variants clearly decreased, and three positive variants  became insignificant (P >0.05) . Of twenty positive SNVs, eleven variants showed study homogeneity (P >0.1 in Q statistic) in the meta-analyses combining all ethnic groups, and their summary ORs and 95% c.i. values were calculated using the fixed-effect model (Table P < 0.1 in Q statistic), and the summary ORs of them were calculated using the random-effect model  of these twenty positive meta-analyses showed notable changes in statistical significance. The Forty-six SNVs in thirty-five different genes did not show significant summary ORs (referred to as negative SNVs) utilizing random-effect models, after all published population-based case-control studies were allelic-specifically meta-analyzed in all ethnic groups . The comSRD5A2, rs1001179 in CAT, rs1056836 in CYP1B1 and rs1544410 in VDR) became insignificant after the exclusion of HWE-deviation studies , except RFX6 rs339331. Although the overwhelming majority of significant results only showed slight changes after the process, one positive variant (rs9340799 in ESR1) lost significant effect size (Eight of the twenty positive variants in the control subjects showed deviation from Hardy-Weinberg equilibrium (HWE). While four variants (rs9282858 in ect size .HOXB13 rs138213197 and LEP rs2167270) for which all published case-control studies were of Caucasian-ancestry, we stratified other eighteen positive variants into racial subgroups and re-meta-analyzed summary ORs and 95% c.i. values. Two variants (in EHBP1 and HNF1B) consistently showed significant association  with PCa across Asian-ancestry, Caucasian-ancestry and African-ancestry; Five variants  showed positive results in both Asian-ancestry and Caucasian-ancestry; Six variants in KLK3, SRD5A2, SOD2, CAT, SLC22A3 and LMTK2 only maintained statistical significance in Caucasian-ancestry; Two variants in the VDR gene showed positive results only in Asian ancestry; While the variant rs9340799 in ESR1 was significantly associated with PCa only in African-ancestry patients. Of note, no positive results were seen in IGFBP3 rs2854744 and in FAS rs1800682 in all ethnic subgroups  in one or two ethnic groups, when re-analyzed them based on different ethnic ancestries. Of these fifteen positive variants, seven (∼47%) were seen only in Asian-ancestry population. Except for one protective variant (MTHFR rs1801133) for prostate cancer , six of the seven variant  showed risks for prostate cancer. The average risk OR was 1.417 (range: 1.148-1.911), and the mean sample size combining case-control individuals in all Asian-ancestry studies was 2091 (range: 407-3430). Six of the fifteen significant variants were observed in African and Caucasian ancestries, respectively . Among the fifteen variants, only one (rs10486567 in JAZF1) shared association with prostate cancer in 5,747 African  and in 19,461 Caucasian   became positive results ( MTHFR rs801133 fo) Figure .SOD2 rs4880, ESR1 rs9340799, VDR rs1544410, FOXP4 rs1983891 and EHBP1 rs721048) showed evidence of significant publication bias   . The resto 0.01) .VDR rs731236 and KLK3 rs2735839 with OR <0.8; SRD5A2 rs9282858, HOXB13 rs138213197 and MSMB rs10993994 with OR > 1.2) approached 80%  ranged from 0.28 to 1, and the average power was 0.77. The power of nine meta-analyses with OR<1.2 was below 80%. The genetic power of five variants  became negative when the studies with a large sample size were removed  reached significant cumulative ORs until their all samples were included.To estimate the sufficiency and stability of the positive meta-analyses, we performed one-study-removed tests and cumulative meta-analyses (see methods). The results from the one-study-removed test revealed that most of positive meta-analyses (85%) had a slight change in the summary ORs and 95% c.i. values in one direction, but the summary ORs of three variants  of SNVs in 371 independent studies involving 418,393 subjects showed no significant association with PCa when combining all samples across all ancestral groups. As we detected the sample size using the medium genotype relative risk of 1.16 that was observed in the present study, α defined as 0.05 and a disease prevalence of 0.1%, the sample size of case subjects ranged from ∼3,500 to 14,500 with minor allelic frequencies between 0.1 and 0.5, when a statistical power approached 80% . According to this estimation, 29 and 44 of 46 negative results could not meet these sample size requirements, respectively. Therefore, the small effect sizes across the current negative meta-analyses might account for the insufficient power.P<0.1 in Q statistic) across 560 published studies . Of them, nine were positive associations and thirty-four were negative associations.Meta-analysis is a powerful way not only to measure heterogeneity of associations across independent studies, but also to quantify the extent of between-study heterogeneity . In totaP value decreased, on average, by 9.6-fold (range: 1.429 to 44.214)  often exhibits an underlying statistical inflation . In our ) Tables . Four me) Tables . These rP-value >0.1). We further excluded the outlier studies from nine positive meta-analyses with significant between-study heterogeneity until reaching homogeneity. Eight of nine could be reduced to display no between-study heterogeneity. We also stratified all studies into the same racial groups and re-performed the meta-analyses. Thirty-three of sixty-six meta-analyses showed positive associations in one or more racial groups. Fifteen negative SNVs identified in the initial meta-analyses became positive  within a single-ancestry population, suggesting that an evidence of bias for positive results might partly be attributed to undetected population stratification in Asian-, African- and Caucasian-ancestry. Finally, ten initially “negative variants”  under the random-effects model became significant when analyzed using the fixed-effects model .After removing 37 HWE-deviated studies (including 9 positive associations and 26 negative associations), the heterogeneity values of only nine negative analyses were corrected . Although the trim and fill analyses also showed that thirteen positive variants need to impute average missing studies of 2, only small shift of adjusted ORs was observed (shift range: 0.1%-0.7%)  . These b1%-0.7%) . StatistFOXP4 and LMTK2 with risk effects and one in RFX6 with protective effects), to our current knowledge, were not reported in previous publications. The vast majority of differences between the results of previously published meta-analyses and the results reported here arose from the different inclusion- and exclusion criteria. For example, five previous meta-analyses included family-based publications. In addition, one difference likely arose from miscalculation in one previous meta-analysis  were significantly associated with PCa risk, but the last two variants with small summary ORs (an average of 1.12) had significant between-study heterogeneity . The rs351855 C>T resides in exon 9 of the FGFR4 gene leads to a glycine to arginine substitution at codon 388 (p.Gly388Arg). The risk allele (T) of the variant was significantly associated with a poor cancer prognosis [HOXB13, yielding a rare G84E missense variant, significantly increases the risk of prostate cancer, and the biological function of this 84E remains unclear.In this meta-analyses, five protein-coding variants  It must be an association study between a SNV and PCa. Note that in this study, as we exclusively focused on population-based case-control designs to investigate the genetic risk loci of disease, studies based on family designs or quantitative trait analyses were not included in any of the statistical analyses. Studies on microsatellite variants or on genetic markers with complex allelic architecture  were also not included. As SNVs occurring in known gene sequences can exert severe effects on biological functions, we thus exclusively meta-analyzed gene-specific SNVs here. (ii) The study must be a research published in a peer reviewed journal. (iii) Only studies published in English were included. Because non-English-publishing genetic association papers in PubMed and EMBASE represent 5.6% of all population-based case-control association studies of PCa, the exclusion of these papers is not expected to produce a drastic effect on any of the overall conclusions. (iv) The SNVs were reported on at least three independent case-control studies. For studies with underlying duplicate publications, we contacted the corresponding authors by e-mail to ask for clarification. Those publications that could not be clarified by authors after twice e-mails were considered as duplication publications. We only included the initial publication in our study.We first performed a search for all publications included in the PubMed database using the keywords “prostate cancer AND (polymorphism OR association OR variation OR variant OR risk OR susceptible OR susceptibility OR sequencing OR case-control OR gene)” between August 1, 1990 and August 1, 2015. A total of 41,955 articles were obtained. The titles and/or abstracts of these papers were scanned for the inclusion criteria above. This step yielded 560 studies containing 66 SNVs in 51 different genes that were eligible for the inclusion criteria in this study. Next, to test the completeness of our search strategies, we searched the EMBASE and Cochrane database using 7 random chosen SNVs or 7 matched genes combined with the keyword “prostate cancer”, respectively.First, full-text versions of all papers used for meta-analyses were obtained. Next, the first author, year of publication, ethnic group, genotype or allele data and PubMed ID were extracted from each paper. In this study, ethnic groups encompassed four general populations . All 66 SNVs for subsequent meta-analyses were represented using dbSNP identifiers (“rs” numbers). For the papers in which genotype or allele distributions were not provided, we requested genotype information by directly e-mailing the first or corresponding authors. For SNVs for which we could not obtain the genotype data after two e-mail, genotype distributions were deduced from their allelic data. All information extracted from the publications was summarized in P value< 0.1 showed the presence of significant heterogeneity. For meta-analyses that still showed evidence of between-study heterogeneity  after excluding deviations from HWE, we performed a heterogeneity correction by the stepwise removal of outlier studies until homogeneity was achieved. We performed one-study-removed analyses to show the effect of each study on the summary OR. In the one-study-removed analysis, a single study was removed from the meta-analysis and the summary ORs and 95% c.i. values of the remaining studies were re-calculated. We estimated publication bias for all statistically significant SNVs. Egger's regression procedure was used to test the extent of publication bias, with a funnel plot to show bias. Duval and Tweedie's trim and fill procedure to impute a shift of ORs and to impute the number of missing studies when a apparent bias was to be removed [P value < 0.05. The statistical power was detected using the Genetic Power Calculator online tool (http://pngu.mgh.harvard.edu/purcell/gpc/cc2.html). The prevalence of PCa was 0.1%. The minor allele frequencies of each SNV in combined cases were used as high-risk allele frequencies, and the genotype relative risks were calculated utilizing the genotype distribution from the combined case-control genotype data and sample size. The type I error rate was 0.05.SNVs with genotype and/or allele data in three or more independent studies were included for meta-analyses. We performed meta-analyses with i) all studies including general populations ; ii) studies excluding the initial publication ; iii) studies after the exclusion of samples deviating from HWE; iv) studies sorted by subgroups which have same ancestries. We calculated the crude ORs and 95% c.i. values using allele contrasts. Summary ORs and 95% c.i. values were calculated using the Mantel-Haenszel fixed-effects model  and the  removed . We also removed . In this


Recent studies suggested inconsistent results on the association between NOx exposure and cardiovascular-related malformations. We aimed to assess aforementioned association in pregnant women in the first trimester and cardiovascular-related malformations of infants. A systematic literature review identified studies for observational studies about NOx exposure and cardiovascular-related malformation in PubMed. Random-effect models were used to estimate summary odds ratio (SOR) and 95% confidence intervals (CIs) for aforementioned association. Finally, nine studies met the inclusion criteria. Overall, the SOR of cardiovascular-related malformation per 10 ppb increment in NOx and NO2 concentration was 1.01  and 0.99 , respectively. Stratifying by study design, geographic locations, and confounded adjustments, the majority of strata showed negative results, which were consistent with the main findings. However, we found that exposure to NOx and NO2 in the first trimester increased the risk of coarctation of the aorta (COA) malformation by 13% and 19%, respectively. Our study provided limited evidence regarding the association between NOx exposure in the first trimester and cardiovascular-related malformations in infants.Nitrogen oxide (NO These two substances are important trace species in earth's atmosphere.Air pollution has become a major problem in many countries. Increasing evidence showed that air pollution could not only lead to global warming, but also have adverse effects on the fetus and newborn from maternal exposure , 2, such2 exposure was related to increases in risk of coarctation of the aorta (COA) and tetralogy of Fallot (TOF) [2 exposure was only associated with COA [x of pregnant women was not consistent; for example, the meta-analysis carried out by Vrijheid et al. [x ; (2) the results of subgroup analyses stratified by adjustment for potential confounders were limited; (3) although atrial septal defect (ASD) and ventricular septal defect (VSD) are the most common cardiovascular-related malformations [x and ASD or VSD was relatively finite.Congenital malformations are an important cause of infant mortality and a leading cause of disability worldwide . Notablyot (TOF) , while twith COA . Howeverd et al.  includedrmations , the preIn order to better understand the relationship between nitrogen oxide exposure in pregnant women in the first trimester and cardiovascular-related malformations of infants, we performed a systematic review and meta-analysis using data from epidemiologic studies.x OR NO2 OR NO) AND . Additionally, the references cited in the retrieved articles were scrutinized by manual research.This meta-analysis was planned, performed, and reported in adherence to the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guideline . We condThe published studies were considered to be included if they met the following criteria: if they (i) used an epidemiologic study design ; (ii) defined the exposure period of nitrogen oxide as the first trimester or in the range of first trimester during pregnancy; (iii) reported cardiovascular-related malformation as the outcomes of interest; (iv) reported the usable risk estimates  or necessary data for calculation) of the association between nitrogen oxide exposure and cardiovascular-related malformation.x with the unit of “microgram per cubic meter (ug/m3)”); (iii) reported the exposure period during the period of preconception or other trimesters; (iv) were not human studies or published in English.The published studies were excluded by the following exclusion criteria: if they (i) were nonepidemiologic studies , review articles, systematic review and meta-analyses, commentaries, editorials, or meeting abstracts; (ii) reported the risk estimates that could not be summarized (such as reporting the risk estimates without 95% CIs) or used for further unit conversion .Data was independently extracted according to a standardized format by two researchers (Tie-Ning Zhang and Jing Xia) for each eligible study. Disagreements were discussed and solved by a third researcher (Qi-Jun Wu). The following important study characteristics were abstracted from each included study: the first author, year of publication, geographic location, study period, study design, number of cases, gestational period, kind of exposure, outcome with their risk estimates, and 95% CIs. We also extracted the factors matched between cases and controls and potential confounders of each study. If there were multiple estimates of the association, we extracted the estimate that was adjusted for the largest number of potential confounders. If both single- and multiple-pollutant models were presented in a study, we selected single-pollutant model in our meta-analysis.Two independent researchers (Tie-Ning Zhang and Jing Xia) conducted the quality assessment of included studies according to Newcastle-Ottawa Scale (NOS) for cohort and case-control studies. All 8 items in the scale were applicable to our study question. The items can be divided into 3 domains . We used these NOS parameters to evaluate the studies instead of scoring them and categorizing them into high or low quality on the basis of the scores –23.x or NO2 and cardiovascular-related malformation. Firstly, we converted the unit of ug/m3 into part per billion (ppb) in order to allow comparison of effects among different studies. Subsequently, we summarized and converted the study-specific ORs for each 10 ppb increment in NOx or NO2 concentration. For conducting dose-response meta-analysis, the study-specific trend from the correlated log ORs across the categories of NOx or NO2 concentrations was computed by using the generalized least-squares trend estimation method developed by Greenland and Longnecker [As the absolute risk of cardiovascular-related malformation is low, we reported all results in terms of OR for simplicity. Considering there was limited evidence regarding NO and cardiovascular-related malformation, we just examined the relationship between NOngnecker  and Orsingnecker . If the x and NO2) and the outcomes of our interest, the summary odds ratio (SOR) with 95% CIs was estimated by summarizing the risk estimates of each study using the random-effect models [To examine the associations between the exposure , geographic location (US versus others), and potential confounders considered or adjusted for in the analyses . Heterogeneity between subgroups was evaluated by meta-regression analysis. We also performed sensitivity analyses by excluding one study at a time to explore whether results were strongly influenced by a specific study.Heterogeneity among studies was assessed with P value is less than 0.05 for Egger's or Begg's test. All statistical analyses were performed with Stata 12.1 (StataCorp).Finally, publication bias was evaluated through Egger et al.'s test  and BeggOur literature search process is illustrated in The characteristics of the eight studies are summarized in Tables Tables x concentrations and cardiovascular-related malformation (x concentration was 1.01 (95% CI: 0.98–1.04), with low heterogeneity . There was no indication of a publication bias according to Begg's test (P-bias = 1.00) and Egger's test (P-bias = 0.65).Nine studies , 27–34 wormation , Table 1Furthermore, analyses of studies reported the cardiac malformation of interest that were ASD , 30–34, x exposure and VSD in cohort studies. Stratifying by adjustment for educational level, we observed significant results for cardiovascular-related malformation with low heterogeneity after summarizing three studies adjusted for this potential confounder. In addition, there was no evidence of significant heterogeneity between subgroups detected by meta-regression analyses.The results of stratified analyses by study characteristics are summarized in I2 = 0.0%, P = 0.56) after omission of the study by Stingone et al. [I2 = 16.2%, P = 0.30) after omission of the study by Padula et al. [In a sensitivity analysis, we evaluated the effect of removing a single study from the total in order to determine its effect on the summarized estimate for heterogeneity and to assess whether one study had a significant influence on the meta-analytic OR. The study-specific OR of cardiovascular-related malformation ranged from a low value of 1.00 , with low heterogeneity . There was no indication of publication bias with Egger's test (P-bias = 0.39) and Begg's test (P-bias = 0.20).Eight studies –32, 34 wormation , Table 22 in the first trimester.In addition, analyses of studies reported the cardiac malformations of interest that were ASD –32, 34, I2 = 0.0%, P = 0.51) after excluding the study by Stingone et al. [I2 = 34.6%, P = 0.16) after excluding the study by Dadvand et al. [Stratifying by study design, geographic locations, and confounded adjustments, the majority of strata showed negative results in the outcome of cardiovascular-related malformation, ASD, and VSD, which were consistent with the main findings. There was no evidence of significant heterogeneity between subgroups detected by meta-regression analyses. In a sensitivity analysis omitting one study at a time and after we analyzed the SOR of the rest, the SORs of cardiovascular-related malformation ranged from 0.98  and 19% (95% CI: 1.08–1.30), respectively.Overall, the findings from this meta-analysis indicated there was no obvious increased risk between NO2 could oxidize tissue composition, increase lipid peroxidation in fetal and maternal vivo, and inhibit the protective action of the antioxidant defense system, which can affect fetal growth and development. Additionally, there was evidence that air pollution could also contribute to epigenetic change, including alteration of DNA methylation [x or NO2 exposure, which might result from exposure assessment of individual study. For example, exposure indices were usually calculated from pollutant measurements at the nearest monitoring station or as a distance-weighted average of measurements of all stations in the area. These methods apply a similar exposure to a relatively large geographic area and thereby measure predominantly community-wide variations in air pollution [The cause and mechanism of cardiovascular-related malformation still remain unclear. A study conducted by Wilhelm and Ritz  suggestehylation . Besideshylation . These follution .x and NO2, this approach is not completely suitable for nitrogen oxide assessment, which may have a much finer spatial distribution. Power may be improved by using more personal measures of NOx exposure and the ideal solution is to set monitors in a cohort of pregnant women, but this method would be very expensive [Considering traffic exhaust fumes are the main source of NOxpensive . A cheapxpensive . This rax exposure might be associated with cardiovascular-related malformations, but this association is too small to detect because there were several known and unknown factors that might influence the results of individual study. Considering each included study was based on the data from registry or hospital program, the condition of personal exposure might be unpredictable and could be related to specific factors such as behavior pattern, living activity, working history, and indoor air pollution. Nondifferential errors were assumed between cases and controls, and therefore this exposure misclassification could influence effect estimate. For example, if mothers of included cases had more difficult pregnancies, this could limit their outdoor movement [x exposure effects rather than positive results in the association.It is possible that NOmovement . Besidesmovement . These rn = 19,079). This large sample size not only allowed us to investigate the association between NOx exposure and cardiovascular-related malformations, but also facilitated for us carrying out numerous stratified and sensitivity analyses to explore the heterogeneity. Additionally, we only included the studies whose exposure period of pregnancy was first trimester or in the range of first trimester. This could help reduce the selection and detection bias of the final results.Compared to the limited sample size of each study, our meta-analysis included a large number of cardiovascular-related malformations cases (Despite the clear strengths of this study, some limitations of our study should be acknowledged. First of all, we could not get detailed information on diagnostic tests for all cardiovascular-related malformations of included studies. Although echocardiography has been the most useful diagnostic test to confirm the presence of congenital heart defects , it greaSecondly, confounding factors included in the individual studies are an additional concern. In fact, there are some known or suspected risk factors for congenital anomalies including maternal age, smoking, and season of conception –44. Howex or NO2. For example, atrioventricular septal defect, Ebstein's anomaly, and tricuspid valve dysplasia can all cause intrauterine congestive heart failure, increasing the risk of intrauterine fetal death [x or NO2 could increase the risk of these malformations, in turn increasing the risk of abortion before week 20, we could not be able to detect these bad effects on cardiovascular-related malformations. Besides, there is experimental research showing that triggering oxidative stress in diabetic mice can result in apoptosis among migrating neural crest cells, which later results in outflow tract defects [Thirdly, the results of some studies , 29, 32  defects . This sux/NO2 concentration. Except for the outcome of COA and NO2 exposure, there were no significant risks of other outcomes in infants born to mothers who are exposed to NOx/NO2 in the first trimester. Herein, the exposure dose was not the explanation for our negative results.Finally, in order to determine whether the exposure dose of per 10 ppb increment is too small, we recalculated the SORs of cardiovascular-related malformation per 50 ppb increment in NOx or NO2 exposure in pregnant women in the first trimester and cardiovascular-related malformations, although there was a small increase risk between exposure to NOx/NO2 and COA malformation. Additional epidemiologic studies are warranted to provide more detailed results, including research into different kinds of cardiovascular-related malformation after better adjustment for more potential confounders.Our meta-analysis provided the limited evidence about the relationship between NO


The role of oxidative stress in schizophrenia has been demonstrated, particularly in subjects with treatment-resistant schizophrenia (TRS). In such patients, the decreased levels of antioxidants in conjunction with the increased generation of reactive oxygen species in the brain exposes the neurons to a higher risk of damage.GSTT1 and GSTM1, with susceptibility to TRS. A total of 54 TRS patients (mean age 38.7 years) and 78 healthy control subjects (mean age 39.0 years) were enrolled in this study. The subjects were matched by sex, age, and smoking and alcohol consumption habits. In the case group, the frequencies of GSTT1-null and GSTM1-null genotypes were 24.1 and 51.9%, respectively, whereas for the control group, the frequencies were 12.8 and 46.2%, respectively. Analysis performed with respect to the risk of developing TRS associated with the GSTT1 and GSTM1 deletion polymorphisms, resulted in odds ratio (OR) values of 2.1 and 1.2, respectively. However, the association was not found to be significant . The analysis performed with respect to the combined genotypes of GSTT1 and GSTM1 revealed that the double-null genotype confers a 4.6-fold increased risk of developing TRS (p = 0.0412).We evaluated the association of deletion polymorphisms of two genes of the antioxidant Glutathione S-Transferase family, GSTT1 and GSTM1 can have implications in the prediction of the clinical course of the disease.The results of the present study indicate that a combination of GST deficiencies may play a role in enhanced susceptibility to TRS, and the present genotype of one of these genes may buffer the deficiency caused by the lack (null genotype) of the other. The results suggest that combined deletion polymorphisms of  Schizophrenia is a severe disabling mental disorder that affects 0.4 to 0.7% of the general population  and is cAs the consumption of oxygen by brain cells is very high , this can lead to generation of increased levels of reactive oxygen species in the brain, expositing the neurons to oxidative stress ,5. This Increased lipid peroxidation and neuronal damage has been demonstrated in TRS patients, compared to non-refractory cases . It appeThe genetic factors have an important role in schizophrenia, as it has been observed that the disease is familial, with a high heritability of about 80% . It is wGSTT1 and GSTM1, exhibit a well-established deletion polymorphism that leads to a non-functional null allele. In homozygote form, the null allele results in an absence of active isoforms, and the genotypes are called GSTT1-null and GSTM1-null [Glutathione S-transferases (GSTs) are a multigenic superfamily of detoxifying enzymes, involved in the phase II biotransformation of a wide range of compounds, including products generated by oxidative damage and the conjugation of reduced glutathione (GSH) to electrophilic species. Two members of the GST family, TM1-null ,15.GSTT1 and GSTM1 has been associated with an increased susceptibility to several types of multifactorial conditions in which oxidative stress may be involved, such as diabetes mellitus [The null genotype of mellitus  and manymellitus . Recent mellitus –20. Howemellitus  evaluateGSTM1 and GSTT1, in TRS patients from Brazil diagnosed according to American Psychiatric Association criteria [We evaluated two antioxidant enzymes that are members of the GST family, which are known to have a deletion polymorphism, criteria , to achiIn this study, we enrolled 54 patients  from the Brain Institute, Goiânia, Goiás, Brazil diagnosed with schizophrenia according to the criteria mentioned in the Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) published by American Psychiatric Association  and consThis study was approved by the Ethics in Research Committee at the Federal University of Goiás under protocol number 39/2013. All participants answered a health questionnaire and signed an informed consent document after being informed about the research. The questionnaire used for the control group was pretested in a sample of patients and relatives or companions at the reception of the psychiatric clinic before the test in study participants, and was based on the self-report of a previous diagnosis of mental illness. For the case group, the data were extracted from the record file of the patients indicated by the psychiatrist and only personal data and data about consumption of alcohol and tobacco were asked directly to them. The translated and untranslated versions of the questionnaires used can be seen in ®, USA). The deletion polymorphism of GSTM1 and GSTT1 was determined using a multiplex Real-Time PCR (SYBR Green) followed by melting curve analysis, and confirmed with conventional multiplex PCR and gel electrophoresis, as previously described [Peripheral blood samples were collected in tubes containing EDTA and stored at -20°C. DNA was extracted using the Illustra Blood Genomic Prep Mini Spin Kit , with their corresponding 95% confidence intervals (CI), and p-values were calculated in order to estimate the risk of developing TRS by multiple logistic regression controlled for the confounding factors sex, smoking, and alcohol consumption. All tests were performed using p < 0.05 as the level of significance.A total of 54 TRS patients treated with clozapine  and 78 healthy control subjects  were enrolled in this study. The mean age was 38.7 years for patients and 39.0 years for the control group. Demographic and clinical characteristics of case and control groups are outlined in The distribution by sex and age did not show significant differences, indicating homogeneity between the groups. Furthermore, there were no significant differences between the case and control groups in terms of proportion of smokers and drinkers, and there was no association observed with respect to these variables in all the analyses performed. Only those individuals who smoked for at least one year of their life before being diagnosed with schizophrenia in the test group were considered smokers. All subjects reported drinking only occasionally or socially.GSTM1 and GSTT1 genotype frequencies in TRS patients and controls are shown in GSTT1-null and GSTM1-null genotypes were 24.1 and 51.9%, respectively, whereas for the control group, the frequencies of GSTT1-null and GSTM1-null genotype were 12.8 and 46.2%, respectively. There was no difference in the genotypic distribution between case and control groups for both polymorphisms, as confirmed by the chi-square test.The data regarding the GSTT1 and GSTM1 deletion polymorphisms of developing TRS, OR values of 2.1 and 1.2 were obtained, respectively. However, the association of these polymorphisms with susceptibility to disease was not significant  in the population studied  and an increase in the risk for developing TRS  of the other gene.It was observed that, despite tibility   in Italian patients but obtained positive associations only for the GSTT1-present/GSTM1-null combination.This result is unprecedented and is in accordance with the theory of the complex genetics of schizophrenia, emphasizing the influence of the interaction of several genes , and indGSTT1-null genotype showed a significantly increased risk for developing schizophrenia in a Tunisian population, a study by Saadat et al. (2007) revealed a significant association between the GSTT1-present genotype and an increased risk for developing schizophrenia in an Iranian population. Both studies obtained only small OR values for GSTT1 . A meta-analysis conducted by Kim et al. (2015) [GSTM1 can be a candidate gene conferring susceptibility to schizophrenia in the East-Asian population. The inconsistent results can be explained by the lack of studies specifically evaluating the association of these polymorphisms with the treatment-resistant profile of schizophrenia. This highlights the necessity of conducting more studies with other populations, as the differences in the ethnical composition and environmental conditions can play an important role in the genetic susceptibility to diseases, particularly multifactorial disorders such as schizophrenia.Other studies, such as the ones by Saadat et al. (2007) and Raffa et al. (2013) also found different results. While a study by Raffa et al. (2013) revealed that individuals with the . (2015)  concludeGSTT1, which is involved in the metabolism of a wide range of compounds [As a large amount of auto-oxidizable neurotransmitters such as dopamine, epinephrine, and norepinephrine are present in the brain, the capacity of the cell to detoxify the oxidized metabolites can be of great importance toward prevention of cell damage . O-quinoompounds , we can It has been observed that antipsychotic drugs can increase oxidative stress by altering the levels of antioxidant enzymes and consequently leading to oxidative injury, particularly lipid peroxidation in the brain . TherefoThe frequencies of GSTM1-null and GSTT1-null genotypes in the control group  are close to the frequencies obtained in other case-controlled studies carried out in Brazilian population ,32 Click here for additional data file.S2 FileTranslated questionnaires applied to case and control groups.(DOCX)Click here for additional data file.S3 FileQuestionnaires in Portuguese applied to case and control groups.(DOCX)Click here for additional data file.S1 TableData are reported as mean ± standard deviation. Statistical analysis by t test or chi-square. Level of significance (p <0.05).(DOCX)Click here for additional data file.S2 TableAnalysis by chi-square and multiple logistic regression to obtain adjusted odds ratio values (OR) and confidence intervals (95% CI). Level of significance (p <0.05).(DOCX)Click here for additional data file.S3 TableAnalysis by chi-square or Fisher's exact test and multiple logistic regression to obtain adjusted odds ratio values (OR) and confidence intervals (95% CI). *Significant difference between groups (p <0.05).(DOCX)Click here for additional data file.


Possible dementia is usually identified in primary care by general practitioners (GPs) who refer to specialists for diagnosis. Only two-thirds of dementia cases are currently recorded in primary care, so increasing the proportion of cases diagnosed is a strategic priority for the UK and internationally. Variables in the primary care record may indicate risk of developing dementia, and could be combined in a predictive model to help find patients who are missing a diagnosis. We conducted a meta-analysis to identify clinical entities with potential for use in such a predictive model for dementia in primary care.We conducted a systematic search in PubMed, Web of Science and primary care database bibliographies. We included cohort or case-control studies which used routinely collected primary care data, to measure the association between any clinical entity and dementia. Meta-analyses were performed to pool odds ratios. A sensitivity analysis assessed the impact of non-independence of cases between studies.From a sift of 3836 papers, 20 studies, all European, were eligible for inclusion, comprising >1 million patients. 75 clinical entities were assessed as risk factors for all cause dementia, Alzheimer’s (AD) and Vascular dementia (VaD). Data included were unexpectedly heterogeneous, and assumptions were made about definitions of clinical entities and timing as these were not all well described. Meta-analysis showed that neuropsychiatric symptoms including depression, anxiety, and seizures, cognitive symptoms, and history of stroke, were positively associated with dementia. Cardiovascular risk factors such as hypertension, heart disease, dyslipidaemia and diabetes were positively associated with VaD and negatively with AD. Sensitivity analyses showed similar results.These findings are of potential value in guiding feature selection for a risk prediction tool for dementia in primary care. Limitations include findings being UK-focussed. Further predictive entities ascertainable from primary care data, such as changes in consulting patterns, were absent from the literature and should also be explored in future studies. With an aging population, dementia is becoming an increasingly important health issue in the United Kingdom (UK) and across the world. In 2015 it was estimated that 46.8 million people worldwide were living with dementia, and this number is expected to increase to 74.7 million in 2030 and 131.5 million in 2050.) OR Alzheimer*[Title/Abstract])) AND (((("primary care"[Title/Abstract]) OR "Primary Health Care"[Title/Abstract]) OR family pract*[Title/Abstract]) OR general pract*[Title/Abstract])) AND (((diagnos*[Title/Abstract]) OR onset[Title/Abstract]) OR predict*[Title/Abstract]).Three searches were carried out. In the first search, PubMed and Web of Science, were searched between 7Second, Online bibliographies of publications from CPRD and THIN during June 2016 by EF using keywords “Dementia” and “Alzheimer*”. No date ranges for publications were specified.th September 2017. PubMed and Web of Science, were searched using the search string defined above.Third, an updated search was conducted by EF on 26After duplicates were discarded, the following inclusion criteria were then applied:Studies using routinely collected primary care data extracted from existing databases.Studies that looked at all cause dementia, Alzheimer’s or vascular dementia as their outcome.Studies that had a cohort or case-control design in which exposures to risk factors in dementia cases could be compared to exposures to risk factors in a control group reflective of the general practice population.Risk factors were measured before dementia diagnosis.Studies published in English.Studies were excluded if they focused on: management, screening tools (except those developed using routine primary care data), imaging or novel biomarkers for dementia; the ability of GPs to diagnose dementia; barriers to diagnosis of dementia; concordance with guidelines; patient/caregiver experience of diagnosis; prediction of prognosis, survival or institutionalization; cognitive decline; presenting clinical guidance or consensus; were review articles; or were published in languages other than English.Using these criteria, the articles extracted from the literature search were screened based on their title, then abstract, then finally full text analysis, by two authors (NG and EF).Bias was assessed by author EF using the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS). Each stuStudy quality was assessed by author EF using the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies. Each stuTo examine the risk of publication bias within analyses, we performed funnel plots for comparisons which had 10 or more studies. The Cochrane handbook states that “as a rule of thumb, tests for funnel plot asymmetry should be used only when there are at least 10 studies included in the meta-analysis, because when there are fewer studies the power of the tests is too low to distinguish chance from real asymmetry”.The following meta-data from studies were extracted into a table in Excel: author names, date of publication, country of origin, name of primary care database, data extraction period, type of dementia, case definition of dementia, number of cases and controls, control matching criteria, conditions assessed, medications assessed, follow up time, mean age of patients, and percentage of female patients.The following study data were extracted by risk factor: total number of dementia cases, number of cases exposed to risk factor, total number of controls, and number of controls exposed to risk factor. Firstly, all results in each study were combined for a category of “all dementia”. Data on Alzheimer’s disease (AD) and Vascular Dementia (VaD) were extracted separately where available. For medication data, the value for “ever prescribed” was extracted from all studies, as dosage format varied. For eight studies where study data were not published in an extractable format, we emailed authors, resulting in data on three studies.2 > 50%) a random effects analysis was used and is presented. The I2 statistic describes the percentage of variation across studies that is due to heterogeneity rather than chance.[ReviewManager 5.3 was used to perform meta-analyses and estimate odds ratios (ORs) for all risk factors. Initially a fixed effects analysis was conducted for each meta-analysis, but where results were heterogeneous . Resampling may artificially increase the precision of estimates, reduce heterogeneity and narrow confidence intervals. For every risk factor which had 3 or more CPRD studies in the “all dementia” category, we removed all but one CPRD paper per analysis. The CPRD paper spanning the longest time period was retained; where two studies had equal time spans, the study with the larger sample size was retained.The initial database search identified 3,836 unique papers. Following title sifting, 421 abstracts from the database search, and 20 from searches of the CPRD bibliography and THIN publications list were examined, and of these, 94 papers were examined in full text. 19 papers met inclusion criteria and were included in the analysis. A second database search was performed which elicited 555 unique papers from 2016 onwards. Of these 64 abstracts were examined, and 8 papers in full text. One further paper was found to meet inclusion criteria. Thus 20 papers are included in the final analysis .Scoring is presented in We produced funnel plots for two comparisons: diabetes (12 studies) and hypertension (10 studies). Neither funnel plot showed asymmetry, suggesting the risk of publication bias was low .The characteristics of studies are shown in All associations between dementia and other conditions are shown in Studies reported on current smoking, alcohol use, body mass index (BMI), deprivation index and level of education. High BMI (>30) had a negative association with all dementia  and AD  but no association with VaD . Current smoking status showed no association with all dementia or AD but was significantly associated with VaD . Current alcohol usage was positively associated with all types of dementia in one study  but history of an alcohol problem was negatively associated with all cause dementia . Deprivation index and level of education were not associated with dementia.Depression , and anxiety , showed strong positive associations with all dementia, as did a record of a referral to psychiatrist, geriatrician or neurologist . For depression, this association was maintained across AD and VaD. For epilepsy or seizures  the positive effect found was non-significant for dementia NOS but significant for singles studies looking at AD  and VaD  dementia separately. A positive relationship was found between dementia and Parkinson’s disease  but not for schizophrenia (1 study).Cardiovascular (CV) risk factors showed contrasting directions of association with AD and VaD. The only CV factors associated with all dementia were history of stroke  and orthostatic hypotension . Most CV risk factors showed a negative relationship with AD, ranging from an OR of 0.55 (95%CI 0.52–0.58) for stroke (1 study) to 0.95 (95%CI 0.92–0.99) for dyslipidaemia (4 studies); the exception to this was orthostatic hypotension which showed a positive association . Most CV factors showed a positive association with VaD, ranging from OR 1.16 (95%CI 1.08–1.24) for hypertension (3 studies) to 3.26 (95%CI 3.14–3.37) for stroke (1 study).Diabetes showed a positive association with all dementia  and VaD  and a negative association with AD . Other associations with all dementia were found with renal disease , hepatic disorders , chronic obstructive pulmonary disorder (COPD) , and infective episodes . Intracranial injury was also significantly associated with all dementia .One small study (N = 199) examined composite variables of dementia signs and symptoms such as cognitive, affective and behavioural symptoms, gait disturbances and changes in weight or appetite. These all showed strong associations ranging from OR 3.05 (95%CI 1.51–6.18) for affective symptoms up to OR 56.41 (95%CI 16.41–193.95) for cognitive symptoms, in the year preceding a recorded dementia diagnosis.Fewer studies reported on associations with medication, so many results in this section are from single studies. Results are reported in full in One study reported this risk factor finding a positive association between number of prescriptions and all dementia .Antipsychotics  and antidepressants  showed the strongest associations with all dementia, with lithium, hypnotics, and anticonvulsants also showing positive associations.Positive associations were found between CV medications and VaD , and negative associations with AD . A similar pattern was found with diabetes medications .Non-steroidal anti-inflammatory drugs (NSAIDs) (with the exception of aspirin) and corticosteroids had a negative association with all dementia .Antibiotics had a negative association with all dementia .Twelve UK papers drew their samples from the same study population (CPRD). The meta-analysis was repeated with all but one CPRD study removed for every risk factor which had 3 or more CPRD studies in the all dementia category: BMI, smoking, depression, coronary heart disease, hypertension, dyslipidemia, atrial fibrillation, heart failure, diabetes, COPD, inflammatory conditions, and statins.Results are presented in This meta-analysis shows that a limited number of variables are associated with dementia diagnoses in primary care records, particularly neuropsychiatric and cardiovascular conditions, symptoms and medication. Cardiovascular risk factors were found to have strong negative associations with Alzheimer’s disease and strong positive associations with vascular dementia. Potential risk factors explored in this study will inform feature selection for development of a clinical risk tool for identifying or risk stratifying patients for dementia in primary care records.Psychiatric or neurological risk factors were the category most positively associated across all dementia sub-types, with significant associations found for depression, anxiety, and seizures, as well as history of stroke. These have previously been reported to be associated with dementia.–45 ThereMany cardiovascular risk factors appeared not to be associated with all-cause dementia, but when specific diagnoses were examined, they had contrasting associations between AD and VaD, which resulted in a non-association when these two outcomes were combined. Of note, several CV risk factors had a negative association with Alzheimer’s disease, as well as diabetes, cancer, COPD and asthma. This apparently “protective” effect is of interest. Previous studies have noted a positive relationship between CV risk factors and dementia, even usiThis review and meta-analysis is designed to guide feature selection for creating a clinical risk tool for dementia in primary care. The types of risk factors consistently associated with dementia suggest that a patient record quality improvement model, or case detection algorithm, could feasibly be developed using primary care data, as the most predictive features include signs and symptoms of dementia that will have already been picked up by GPs. However, a risk stratification model, aiming to identify patients at increased risk of dementia when no clinical signs have yet been identified, may be more problematic, given the few clinical conditions consistently found to be associated with dementia.Notably absent from the literature, despite a thorough examination of primary care database studies, were other elements in a primary care record which could be utilised in a predictive model for dementia. Patterns of attendance, missed appointments, missed prescriptions, and consultations by family members could all be used as indicators of behaviour change, and might increase the predictive validity of a model. The demonstration of their absence from the literature is a useful outcome of this review, and future research should undertake investigation as to whether these would be valuable predictors.This is the first meta-analysis using routinely collected primary care data to establish a range of risk factors for dementia. We only included articles published in English, and only represented countries which have an established primary care database system. A single author extracted data from the included studies, which may have introduced error. We also only searched two medical literature databases, although we supplemented this with a targeted search of UK primary care database literature. This gives our work greater relevance to the UK but potentially limits the generalisability of our results beyond the UK primary care system.We conducted a review of bias in individual studies, and we generated funnel plots to examine systematic heterogeneity for the best populated comparisons. We found little evidence of bias within studies, due to the data all being gathered in real time in routinely collected health records, and then extracted retrospectively, thus diminishing the risk of selection bias, detection bias, performance bias and attrition bias. However, there may have been a publication bias both in studies that were published (by only including significant associations in the results) and negative studies going unpublished. If this were the case, were we to recover these additional unpublished findings we would expect to find even fewer of the risk factors to show associations with the outcome.Other characteristics of the data also urge cautious interpretation. First, heterogeneity was high for almost all analyses, which was unexpected due to the consistent nature of data generation between studies. This heterogeneity may have been caused by variation in the way participants, exposures and outcomes were defined in studies, such as the variation in average age of participant. The varying practices and coding systems in different countries may also have played a part as well as variation in coding practices of clinicians. For example, clinical entities were defined differently between studies, as some case definitions required a single Read code to define dementia and others a more complicated combination of codes. In many cases, code lists for the risk factors were not available. This may have limited the value of pooling results from studies. We attempted to mitigate the effects of heterogeneity by conducting random effects modelling for many analyses, but further thought may be needed to understand the source of this heterogeneity. Such heterogeneity may be a wider issue to be considered in all meta-analyses performed on routinely collected health record studies.Another source of heterogeneity could have come from the timing of the measurement of exposures, as this varied between studies. In most studies, very little temporal information was given about when risk factors occurred or were measured, and the best description of our understanding is that they were present at some point in the record. More work is needed to unpick exactly when different risk factors have the greatest association with subsequent dementia, as longitudinal information and time-at-risk could usefully be incorporated into a clinical prediction model.Additionally, the problem of resampling from the CPRD population meant that cases could not be assumed to be independent. However, our sensitivity analysis approach showed that for analyses with three or more CPRD studies, there were minimal differences between including one versus all CPRD studies, with the exception of BMI >30.A further potential criticism of the overall endeavour of creating a risk prediction tool from primary care records is that GPs tend to diagnose dementia late in the course of the disease. Thus the data is not optimal for training an early risk identifier, as all studies assessing associations between risk factors and dementia will be identifying risk factors for late-diagnosed dementia on the whole. Additionally, those individuals who do get a diagnosis of dementia may differ systematically from the undiagnosed, and the low level of diagnosis in primary care records (possibly around 50% ) means tThis study provides a summary of the current literature on risk factors for dementia as ascertained from routinely collected primary care records. Few factors were consistently associated with dementia, and many gaps in the literature for examining potential risk factors were found. These findings are of potential value for feature selection for building a clinical risk prediction tool to aid the identification of cases of dementia in primary care.S1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(DOC)Click here for additional data file.