Previous studies have suggested that exposure to air pollution may increase stroke risk, but the results remain inconsistent. Evidence of more recent studies is highly warranted, especially gas air pollutants.2.5, particulate matter with aerodynamic diameter less than 2.5 μm; PM10, particulate matter with aerodynamic diameter less than 10 μm; NO2, nitrogen dioxide; SO2, sulfur dioxide; CO, carbon monoxide; O3, ozone) and stroke . Fixed- or random-effects model was used to calculate pooled odds ratios (OR)/hazard ratio (HR) and their 95% confidence intervals (CI) for a 10 μg/m3 increase in air pollutant concentration.We searched PubMed, Embase, and Web of Science to identify studies till February 2020 and conducted a meta-analysis on the association between air pollution ; NO2: OR = 1.023 , per 10 μg/m3 increases in air pollutant concentration). Exposure to PM2.5, SO2, and NO2 was associated with increased risks of stroke incidence ; SO2: HR = 1.002 ; NO2: HR = 1.002 , respectively). However, no significant differences were found in associations of PM10, CO, O3, and stroke incidence. Except for CO and O3, we found that higher level of air pollution  exposure was associated with higher stroke mortality , SO2: OR = 1.006 .A total of 68 studies conducted from more than 23 million participants were included in our meta-analysis. Meta-analyses showed significant associations of all six air pollutants and stroke hospital admission , incidence , and mortality . Our study would provide a more comprehensive evidence of air pollution and stroke, especially SO2 and NO2.Exposure to air pollution was positively associated with an increased risk of stroke hospital admission (PMThe online version contains supplementary material available at 10.1186/s12199-021-00937-1. Stroke, characterized by acute cerebral blood circulation disorder, is caused by artery stenosis, occlusion, or rupture caused by various inducing factors in patients with cerebrovascular diseases . Stroke 2.5 was associated with increased stroke incidence and the adjusted risk ratio (RR) was 1.130  for each increase of 10 μg/m3 in n PM2.5 concentration [3 in PM2.5 concentration, while Wing et al. suggested no association was found between PM2.5 exposure and stroke incidence  [2.5, particulate matter with aerodynamic diameter less than 2.5 μm; PM10, particulate matter with aerodynamic diameter less than 10 μm) and stroke outcomes [2, nitrogen dioxide; SO2, sulfur dioxide; CO, carbon monoxide; O3, ozone) were scarce. Moreover, to the best of our knowledge, more than 30 studies exploring the association between air pollution exposure and stroke, especially conducted from the multi-city level and with large sample sizes, were published after the most recent meta-analysis. The more recent and comprehensive studies should be included in the meta-analysis to conclude an updated pooled effect estimate.Air pollution is the most significant environmental risk factor for all-cause mortality . Increasntration . The adj, 1.280) . Previou, 1.280) –19. Howeoutcomes –19; resu2.5, PM10, NO2, SO2, CO, and O3) and 3 stroke outcomes . This systematic review and meta-analysis was performed according to the guidelines of the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) criteria , NO2, SO2, CO, and O3) and stroke .Literature was searched in three databases , with published date until 1 February 2020. The search strategy was pairwise of combinations of terms concerning air pollution , and conflicts between the two authors were resolved by discussing with an arbitrator (H X).Articles that met the following criteria were included: (1) provided quantitative measure of the associations between air pollution exposure with stroke admission, incidence, and/or mortality (relative risk (RR), odds ratio (OR), or hazard ratio (HR), and their 95% confidence interval (95%CI); (2) cohort, cross-sectional, time series, cross-sectional, case-control, case-crossover, or panel studies; (3) focused on outdoor (ambient) air pollution exposure but not indoor air pollution; (4) original peer-reviewed human subject research studies; (5) published in English. Studies were excluded if they were (1) toxicological studies, summaries, or reviews, and (2) articles without effect estimates after contacting the authors. In addition, for more than one article conducted from the same population, only the most recent studies were included.3); (5) effect estimates of the association between air pollution and stroke risk . The effect estimates of single-pollutant model, generally called “main model” or “fully adjusted model,” were extracted [Data were extracted from all eligible studies, including the following: (1) study characteristics ; (2) study population ; (3) outcome ; (4) air pollution assessment method and increment of air pollution used in effect estimates (per interquartile range (IQR), standard deviation (SD), or per 10 μg/mxtracted .Two authors (ZP N and FF L) worked independently, and inconsistencies in quality assessment were resolved through discussion. We employed the Newcastle-Ottawa Scale (NOS) to evaluate the quality of included studies. The NOS Tool has designed 8 items to assess the critical appraisal of the potential risk of bias. Total score of NOS ranged from 0–9. Study score higher than or equal to 7 was regarded as high-quality; otherwise, the study was regarded as “low quality” .3 increases in air pollution. The significance of the pooled OR, RR, or HR was determined by the Z test [p value less than 0.05 was considered statistically significant. Standard error (SE) for each effect estimate was calculated by using the formula: (upper limit − lower limit)/3.92.This meta-analysis focused on examining the association between air pollution and three stroke outcomes, including admission, incidence, and/or mortality. We extracted effect estimates  from individual studies and then converted them into a standardized form of per 10 μg/me Z test , and p vI2 statistics and Q test [I2 > 50% or p < 0.01, the heterogeneity was “high” and random effect model was used to pool estimates. Otherwise, heterogeneity was considered as “low or moderate,” and fixed-effect model was used to pool estimates.Heterogeneity among studies was evaluated using d Q test . If the Begg’s test and Egger’s test were conducted to assess publication bias. The influence of individual studies on the pooled estimates was examined by removing each study from the analysis one by one. Moreover, we also performed sensitivity analysis and subgroup analysis to evaluate if the exposure period would change the significance of the pooled results. Because long-term studies were limited, sensitivity analysis was conducted by omitting long-term exposure (cohort) studies. Subgroup analysis was only performed if the number of short-term exposure studies or long-term exposure studies was more than 3. Publication bias and sensitivity analysis were only performed if the number of included studies was more than 5. All statistical analysis was performed in Stata version 15.0 .After removing duplicates, 737 records were identified in the initial literature search. By reviewing title and abstracts, 93 studies were downloaded for full-text reading. According to the inclusion and exclusion criteria, a total of 68 studies were included in our meta-analysis Fig. .Fig. 1FTable 2.5, 11 studies on PM10 and NO2, 10 studies on SO2 and O3, and 6 studies on CO with stroke hospital admission and suggested an increased stroke hospital admission risk after air pollution exposure. The pooled odds ratio (OR) of stroke with a 10 μg/m3 increase in PM2.5, PM10, SO2, NO2, CO, and O3 was 1.008 , 1.004 , 1.013 , 1.023 , 1.000 , and 1.002 , respectively .A total of 29 studies were performed to assess the association for air pollution and stroke hospital admission, and the results were inconsistent. Most studies showed a positive correlation between exposure to air pollution and the risk of hospital admission for stroke. In meta-analysis, we enrolled 13 studies on PMly Table -S6. Hete2.5, 13 studies on PM10, 10 studies on O3, 7 studies on NO2, and 4 studies on SO2 and CO. Ten of these studies suggested increased risks for stroke incidence for at least one of the investigated pollutants. Meta-analysis showed that exposure to PM2.5, SO2, and NO2 was associated with increased risks of stroke incidence, and the pooled HR with a 10 μg/m3 increase was 1.048 , 1.002 , 1.002 , respectively. However, no significant differences were found in associations of PM10, CO, O3, and stroke incidence , PM10 , SO2 , and NO2  was associated with increased risks of mortality due to stroke. No significant difference was shown in association between CO, O3 exposure, and stroke mortality  and mortality (NO2) . We recle Table -50. Sensle Table . Subgrou2) Table .2.5, PM10, SO2, NO2, CO, and O3), incidence , and mortality . Although the high heterogeneity may reduce the credibility of the pooled evidence to some extent, the large number of studies included and the consistency of the results indicated that our conclusions were credible to some extent.We conducted a systematic review and meta-analysis of 68 epidemiological studies and performed a comprehensive evaluation on exposure ambient air pollution and stroke, which were conducted from more than 23 million participants. Most studies suggested that exposure to a higher level of air pollution was associated with increased stroke risk. Meta-analysis showed that exposures to air pollutants were associated with increased risk of stroke hospital admission  and O3 , but non-significant association for PM2.5, SO2, NO2, and CO [2.5 , SO2 , and NO2  [The positive associations between exposure to PM, and CO . The metcrement) .2.5 and PM10) and stroke incidence, whereas no meta-analysis of gas air pollutants was published before the current study. Li et al. performed a meta-analysis to explore the association between PM10 and stroke incidence in time-series studies and case-crossover studies. These studies indicated that PM10 was not associated with stroke incidence in the time-series design , but significantly associated in case-crossover studies . Meanwhile, PM2.5 exposure was related to an increased risk of stroke incidence in time-series design , but no significant association in case-crossover studies  [10 was associated with an increased risk of stroke incidence , but exposure to PM2.5 was not significantly associated with stroke incidence  [2 and NO2 was associated with higher risk of stroke incidence, which may fill the gap of meta-analysis of gas air pollutants and stroke incidence. We also found that compared to short-term exposure, long-term exposure to air pollution may be associated with a higher risk of stroke incidence , which may be explained by different pathophysiological pathways.Three meta-analyses were conducted to examine the association between exposure to particulate matter (PMcrement) . Yu et acrement) . The res3 increase in PM2.5, 0.65%  per 10 μg/m3 increase in PM10, 2.45%  per 10 parts per billion (ppb) increase in SO2, 7.78%  per 1 ppm increase in CO, and 1.50%  per 10 ppb increase in NO2, respectively [2.5, PM10, SO2, and NO2 was related to higher risk of stroke mortality. No association was observed in both our study and Yang et al.’s study. However, Yang et al. reported a positive association in CO, whereas our study did not, which may be explained by the limited number of included studies. Scheers et al. performed a meta-analysis of exposure to PM10 and stroke events  and suggested that exposure to PM10 was positively associated with overall stroke events  , but no significant association were observed in stroke mortality  [10 from studies using PM2.5, which may cause estimation bias to some extent.Studies investigating the association between exposure to air pollution and stroke mortality have been partly analyzed in two meta-analysis , 17. Yanectively . ConsistAlthough accurate mechanisms of air pollution exposure and stroke remain unclear, several pathways including systemic inflammation, oxidative stress, thrombosis, and vascular endothelial dysfunction have been proposed , 15, 82.2.5, PM10, NO2, SO2, CO, O3) and a rich set of stroke outcomes , which may be difficult to obtain from individual studies or isolated reviews or meta-analyses. However, some limitations should be acknowledged. Firstly, high heterogeneity existed in some meta-analysis, which may be due to different study designs, difference in exposure assessment method and population demographics, and the varied covariable adjustment strategies in different studies. Secondly, our study failed to perform the association between different subtypes of stroke  and air pollution exposure separately because most included studies (48 out of 68 articles) did not report subtypes of stroke or results of ischemic stroke and hemorrhagic stroke specifically. Finally, the correlation between different air pollutants was not examined in our study because different air pollutants were controlled in different studies, and the results of those studies could not be pooled directly.A major strength of our meta-analysis is that our systematic review and meta-analysis covered six main air pollutants , incidence , and mortality . Given the great global burden of stroke and air pollution, our findings could provide some scientific evidence to accurate prevention and treatment of stroke and air pollution exposure.Our study demonstrated that exposure to air pollution was positively associated with an increased risk of stroke hospital admission (PMAdditional file 1.


Thank you for the comments to our recent article “Sarcopenia and its association with falls and fractures in older adults: A systematic review and meta‐analysis”.P < 0.001, I2 = 36%; fractures prospective studies: pooled OR 1.73, 95% CI 1.14–2.64, P = 0.011, I2 = 6%)  could not be calculated because of insufficient data, or confidence intervals were not presented. Therefore, we were not able to include the studies of Cawthon,et al. suggested to take the types of fracture into consideration when conducting the meta‐analysis of the association between sarcopenia and fractures. We agree with the authors that fracture sites vary significantly in their risk profilesP = 0.001, I2 = 94%) and incident fractures , but the association was insignificant for non‐vertebral fractures (two studies)  and vertebral fractures (two studies)  among older adults (Figure Secondly, Zhang et al. raised an important point regarding the number of falls. As each fall is associated with a risk of injury, functional decline, and loss of autonomy, the risk profile of recurrent fallers is not equivalent to that of single fallers.Finally, Zhang


CTLA-4 rs231775  and VDR rs2228570  and additive gene model for TP53 rs9895829  were significantly associated with PC risk. TP53 rs9895829 was the most optimal SNP for diagnosing PC susceptibility with a false positive report probability < 0.2 at a stringent prior probability value of 0.00001. This systematic review and meta-analysis suggest that TP53 rs9895829, VDR rs2228570, and CTLA-4 rs231775 are significantly associated with PC risk. We also demonstrate that TP53 rs9895829 is a potential diagnostic biomarker for estimating PC risk.In this meta-analysis, we systematically investigated the correlation between single nucleotide polymorphisms (SNPs) and pancreatic cancer (PC) risk. We searched PubMed, Network Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Periodical Database (VIP), and Wanfang databases up to January 2020 for studies on PC risk-associated SNPs. We identified 45 case-control studies  relating to investigations of 27 genes and 54 SNPs for this meta-analysis. Direct meta-analysis followed by network meta-analysis and Thakkinstian algorithm analysis showed that homozygous genetic models for  TERT, UGT2B4, XRCC4, XPC, SLC22A3, NR5A2, ABO and XPD genes are associated with susceptibility to pancreatic cancer [Pancreatic cancer (PC) is the eighth leading cause of cancer-related deaths worldwide with a 1-year survival rate of less than 5% . Geneticc cancer . Single c cancer . SNPs inc cancer . Variantc cancer , 13–16. c cancer –20. TherThis study included 45 studies with 36,360 PC patients and 54,752 non-cancer controls. TP53 rs9895829 showed significant correlation with higher PC risk compared to the GA genotype . The CC and GG genotypes of COX2-765 showed significant correlation with reduced PC risk compared to the CG allele . According to the fixed effects model, AA and GG genotypes of HIF-1α rs11549467 correlated with increased PC risk compared to the AG genotype . According to the fixed effects model, the CC genotype of VDR rs2228570 was associated with increased PC risk compared to the TT genotype (CC vs. TT: pooled OR =0.326 95% CI: 0.218-0.488). The homozygous AA genotype of CTLA-4 rs231775 was associated with increased PC risk compared to the GG genotype . The fixed effects model showed that the TT and TC genotypes of MTHFR rs1801133 showed increased PC risk than the CC genotype . In addition to this, direct meta-analysis of other meaningful models showed the following in COX2-765, HIF-1α rs11549467, VDR rs2228570, TP53 rs9895829, CTLA-4 rs231775, MTHFR rs1801133, ABO rs495828, FTO rs9939609, CDKN2A/B rs2518719, XRCC4 rs2075685, XRCC1 rs25487, XPC rs2607775, MORC4 rs12837024, VEGF +405G/C rs2010963, MTHFR rs1801133) and their the most suitable gene model. Based on the rank probabilities, the optimal models for most genes were either additive or dominant ; pooled sensitivity: 0.55 ; pooled specificity: 0.50 ; +LR: 1.10 , and –LR: 0.90 .We performed diagnostic meta-analysis of the additive gene model of Several studies have investigated genetic susceptibility in PC, but the relationship between PC and SNPs is not conclusive. In this meta-analysis, we combined the results of several published studies to evaluate the association between PC and SNPs. We performed network meta-analysis, which is similar to pairwise meta-analysis, but is validated based on the quality of evidenceThe ranking probability was obtained by combining direct and indirect evidences with a Bayesian approach. A previous study successfully applied this approach to select the best genetic model for detecting the risk of hepatocellular carcinoma .TP53 rs9895829 showed stronger association with PC risk compared with COX2-765, HIF-1α rs11549467, VDR rs2228570, TP53 rs9895829, CTLA-4 rs231775, and MTHFR rs1801133. However, we were unable to conduct further subgroup analysis on TP53 rs9895829 to explore its specific association with PC because of smaller sample size.In our study, COX2-765, HIF-1α rs11549467, VDR rs2228570, TP53 rs9895829, CTLA-4 rs231775, MTHFR rs1801133, ABO rs49582, FTO rs9939609, CDKN2A/B rs2518719, XRCC4 rs2075685, XRCC1 rs25487, XPC rs2607775, MORC4 rs12837024, VEGF +405 rs2010963, and MTHFR rs1801133 were associated with greater risk of pancreatic cancer. The co-dominance model was the best genetic model to predict PC risk based on Thakkinstian's algorithm, but this model was not used in the pairwise meta-analysis  is a highly malignant cancer and is caused by a variety of factors of unknown etiology. The death rate of PC ranks eighth among all cancers worldwide and fourth among developed countries, with more than 260,000 deaths reported each year . Most pa2Vitamin D regulates cellular proliferation, differentiation, apoptosis, and angiogenesis [2VitD and its synthetic analogues inhibited the proliferation of PC cell lines [VDR rs2228570 polymorphism also significantly correlates with pathological differentiation and TNM stages, and is a potential prognostic biomarker for PC [Van et al. showed that vitamin D deficiency is very common in patients diagnosed with advanced pancreatic cancer . Severalogenesis . Colstonll lines . Vitaminll lines . VDR genll lines –75. Morell lines  and SLE ll lines . The VDRll lines , 79. Alill lines , 80. Li ll lines . VDR rs2r for PC .CTLA-4) gene is located on chromosome 2q33 and encodes a crucial immune checkpoint protein on the T-lymphocytes; it consists of four exons that encode the leader sequence, the extracellular domain, the transmembrane domain, and the cytoplasmic domain [CTLA-4 rs231775 changes of the amino acid from alanine17 to threonine17 and is associated with the high expression of CTLA-4, which inhibits T cell activation and proliferation [CTLA-4 + 49a allele is associated with increased risk of lung, breast and cervical cancers [CTLA-4 +49A allele is associated with increased risk of pancreatic cancer in Caucasians and Chinese populations compared to the +49G allele [The cytotoxic T-lymphocyte-associated protein 4  and registered in the INPLASY database (INPLASY202040023).We included case-control studies on SNPs related to PC risk for this meta-analysis. We excluded repetitive reports, conference reports, review reports, news articles, animal studies, studies without sufficient data to calculate genotype distribution, and studies regarding SNPs that deviate from Hardy-Weinberg equilibrium (HWE). In these included studies, the experimental group included serum samples from PC patients that had not received any chemotherapy, whereas, the control group included healthy individuals, patients with non-malignant diseases, and non-cancer patients of different ages, gender, country, and tumor stage.We used terms such as single nucleotide polymorphism, SNP, pancreatic cancer and pancreatic tumor to search PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Science and Technology Periodical Database (VIP), and Wanfang databases for studies published until January 2020 without any language restrictions. The search criteria for the Pubmed database are shown in Data selection was performed independently by two reviewers (ZY and LL). In the case of disagreements, a third independent reviewer (JZ) was involved to reach consensus. The strategy used for study selection is shown in https://www.stata.com/). The fixed effects or random effects pooled odds ratio (OR) were calculated using 95% confidence intervals (CIs) for pairwise meta-analysis based on the heterogeneity of the genetic models. We then conducted a network meta-analysis to determine the most suitable genetic model for each SNP.The statistical data was analyzed using the StataMP14.0 software  based on the Bayesian framework and Markov Chain Monte Carlo (MCMC) theory to generate mesh relationship diagram between genes related to PC risk. The four parallel Markov Chain Monte Carlo (MCMC) simulations underwent a burn-in phase of 20,000 stimulations and then an additional phase of 50,000 stimulations. The outcomes were evaluated by OR and 95% CI under random –effects model and consistency model was applied if 95% CI of log (OR) included 0. Otherwise, inconsistency model was used. The potential scale reduction factor (PSRF) was used to determine convergence. The model was considered convergent if the value of PSRF was closer to 1.0. This Bayesian method was used to rank each genetic model regarding the probability of PC risk and the corresponding rank probability map was automatically generated.We performed diagnostic meta-analysis using the Meta-DiSc software  and evalIn the mesh meta-analysis, we used the Thakkinstian's algorithm  to evaluSupplementary Table 1Supplementary Table 2Supplementary Table 3Supplementary Information 1Supplementary Materials 1


Interleukin 27 (IL-27) has potent antitumor activity. Several epidemiological studies have designated that genetic variants of the IL-27 gene may contribute to various cancer susceptibility, but the data were inconclusive.  IL-27 rs153109, rs17855750, and rs181206 polymorphisms and the risk of cancer. The current meta-analysis aimed to address the association betweenOur team has selected eligible studies up to May 1, 2020, from several electronic databases, including Web of Science, PubMed, Scopus, and Google Scholar databases. rs153109 A>G polymorphism in the IL-27 gene have higher risks of diseases in the heterozygous , homozygous , dominant , and allele  genetic models. Stratified analysis by cancer type indicated that this variant was significantly associated with gastrointestinal cancer, colorectal cancer and breast cancer. The findings did not support an association between rs17855750 T>G, rs181206 T>C polymorphisms of IL-27 and cancer risk.  Our meta-analysis revealed that the carriers the current study findings suggest that IL-27 rs153109 polymorphism significantly increased the risk of cancer susceptibility. Well-designed replication in a larger independent genetic association study with larger sample sizes in diverse ethnicities is required to verify the findings.  Cancer, a major public health concern, remains a leading cause of morbidity and mortality worldwide . While the etiologies of cancer is complicated and not fully understood, growing evidences indicating that a complex interaction between genetic and environmental factors involved in cancer development . Il-27 gene (IL-27P28) is located on chromosome 16 (16p11) . It is well-known that IL-27 possesses antitumor activities against a variety of tumor types . IL-27 is a polymorphic gene and several studies examined the association between IL-27 gene polymorphisms and risk of various cancers including, non-small-cell lung cancer (NSCLC) , acute lymphoblastic leukemia (ALL) , nasopharyngeal carcinoma (NPC) , colorectal cancer (CRC) , prostate cancer (PCa) , papillary thyroid carcinoma (PTC) , hepatocellular carcinoma (HCC) , renal cell carcinoma (RCC) , osteosarcoma , esophageal cancer , cervical cancer , endometrial cancer , ovarian cancer , breast cancer , glioma , and bladder cancer . However, the findings of these studies have been controversial. So we conducted the present meta-analysis of eligible published studies to further assess the association between the IL-27 polymorphisms and cancer risk.Interleukin-27 (IL-27), belonging to the IL-12 family, is a heterodimeric cytokine comprising of two subunits, 1L-27p28 and the Epstein-Barr virus-induced gene 3 protein (EBI3), and is generally secreted by activated antigen-presenting cells . The human Identification of Eligible StudiesIL-27 or IL27 or interleukin 27” and “polymorphism or SNP or variation” and “cancer or tumor or carcinoma or malignancy or neoplasm”. The last search was updated on March 04, 2019. Two authors independently carried out a systematic literature search in PubMed, Web of Knowledge, and Scopus for all related reports using the key words “Inclusion and Exclusion CriteriaStudies were implemented in the current meta-analysis if they met all of the criteria: (1) Assessment of the relationship between IL-27 gene polymorphisms and cancer susceptibility; (2) Case–control studies; (3) Adequate data to estimate pooled ORs with a 95% CIs. The exclusion criteria were: (1) not a case–control study, reviews, case reports, meta-analysis, and comments; (2) duplicate publication; (3) studies with insufficient data.Data extractionThe data extraction from the eligible studies was achieved independently by two researchers according to the inclusion and exclusion criteria mentioned above. In each study, the following items were collected from each study: first author’s name, publication year, country, ethnicity, cancer type, source of controls, total number of cases and controls, genotype distributions of cases and controls, and Hardy-Weinberg equilibrium (HWE), respectively.Statistical analysisAll statistical analyses were achieved using Stata, version 14.1 . The HWE was evaluated for each study by the chi-square test in the control group. Pooled ORs and corresponding 95%CIs were calculated to estimate the strength of association between IL-27 gene polymorphism and cancer risk. The significance of the pooled OR was determined by Z test, in which p-value less than 0.05 was considered statistically significant.The Q statistic test was used to check the heterogeneity among studies included in the meta-analysis. A p>0.10 indicated a lack of heterogeneity among studies, consequently the fixed effect model was used to calculate pooled OR. Otherwise, a random effects model was utilized.Publication bias was evaluated by Begg’s funnel plot qualitatively, and Begg’s and Egger’s tests quantitatively. P-value less than 0.05 considered significant publication bias. Sensitivity analysis was done by removing each study in turn to measure the results stability.Study Characteristics rs153109, 21 studies containing 6,331 cases and 7,287 controls for were included in the quantitative analysis. Regarding rs17855750 variant, 4,023 cases and 4,671 controls from 14 studies and for rs181206 polymorphism, 2,078 cases and 2,242 controls from were 7 studies were included in the meta-analysis. The characteristics of the included studies are summarized in In the current study, according to the inclusion and exclusion criteria, ultimately 20 case-control studies included in the meta-analysis. For Association between IL-27 polymorphisms and cancer riskIL-27 polymorphisms in cases and controls are indicated in rs153109 A>G variant, 21 independent studies were pooled and a random effect was applied due to the presence of significant heterogeneity. The finding revealed that rs153109 variant significantly increased the risk of cancer in heterozygous , homozygous , dominant , and allele  genetic models  significantly increased the risk of overall cancer. Stratified analysis by cancer type designated that rs153109 polymorphism was positively associated with GI cancer, CRC and BC susceptibility. The findings did not support an association between rs17855750 (2905 T>G) and rs181206 (4730 T>C) polymorphisms and cancer susceptibility. Several studies examined the association between IL-27 polymorphisms and the risk of various cancer . The findings were controversial, though it is difficult to clarify the inconsistent findings. In this study, we conducted a comprehensive meta-analysis of all eligible studies to derive a more precise estimation of the relationship between rs153109 polymorphism effects on IL-27 expression. There is increasing evidence that the expression level of IL-27p28 gene is decreased in various cancers including epithelial ovarian cancer , bladder cancer , esophageal cancer , osteosarcoma , as well as papillary thyroid cancer . It has been shown that IL-27 differentially regulates the expression of several microRNAs (miR) such as hsa-miR-7702, hsa-miR-7704, hsa-miR-7704 hsa-miR-6852, and hsa-miR-6852 .The molecular mechanisms by which variant increased the risk of cancer have not been clarified. It seems reasonable to speculate that IL-27 is produced early after activation by antigen-presenting cells, including monocyte-derived dendritic cells and lipopolysaccharide-stimulated monocytes . IL-27 mediates its biological functions via a heterodimeric receptor consisting of WSX-1 and glycoprotein 130 (gp130) . Binding of IL-27 to its receptor activates Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and mitogen-activated protein kinase (MAPK) signaling . IL-27 has potent antitumor activity . It exerts antitumor activity by promoting the generation of myeloid progenitor cells that can differentiate into M1 macrophages . In addition, IL-27 synergizes with IL-12 to potentiate IFN-γ production by activated naive T-cell and natural killer-cell populations . Beside, IL-27 is a major stimulus of IL-10 production by T cell . Cytokines, secreted by cells of innate and adaptive immune systems, are small proteins that play key roles in immune responses. IL-27 and cancer susceptibility. Gene-gene as well as gene-environment interactions could influence cancer risk. Third, all studies were from Asian populations; consequently, conclusions drawn may not apply to the all population. Finally, the sample sizes of the studies are relatively small particularly in subgroup analysis. So, the results should be interpreted with caution.Some limitations should be addressed in our meta-analysis. First, heterogeneity among studies was observed which may be result of difference of ethnicity, source of control, and cancer type. Second, this study focused on the impact of limited variants of IL-27 rs153109 polymorphism and cancer risk. Well-designed studies with larger sample sizes in various cancer and different ethnicities are still needed in the future.In conclusion, the findings of this meta-analysis provide evidence for an association between


Background: The hypocretin receptor 2 (HCRTR2) gene may play a pathological role in cluster headache (CH). However, the conclusions of published reports on the relationship between the G1246A polymorphism (rs2653349) in the HCRTR2 gene and risk of CH remain controversial. This purpose of this article is to comprehensively study the current evidence and assess the association between G1246A polymorphism (rs2653349) in the HCRTR2 gene and risk of CH.Materials and Methods: Four electronic databases—ISI Web of Science, CNKI, PubMed, and EMBASE—were comprehensively searched on August 2020 to find and pinpoint all observational articles related to this study. The association between G1246A polymorphism in the HCRTR2 gene and risk of CH under five different genetic models was evaluated based on the summary odds ratio and corresponding 95 confidence interval (95% CI). Methodological quality was assessed based on the Newcastle–Ottawa Scale (NOS). To assist the analysis, RevMan 5.3 software was used to perform subgroup and sensitivity analyses. Egger's and Begg's tests were then conducted to evaluate and assess publication bias. Finally, a meta-regression was carried out by residual (restricted) maximum likelihood (REML).Results: Eight observation studies containing 3,161 healthy controls and 1,964 patients with CH were identified and to be used for the meta-analysis. With methodological quality NOS assessment, the incorporated studies showed an average score of 6.4 stars. The pooled data didn't support the association between G1246A polymorphism in the HCRTR2 gene and CH vulnerability in the overall population . Subgroup analysis by ethnicity showed no significant association between G1246A and CH in either Caucasians  or Asians . The robustness of the conclusion was tested and confirmed with the leave-one-out sensitivity analysis. Meta-regression analysis showed that chronological order of publication appeared to be significantly associated with the heterogeneity .Conclusion: Our present study showed that the G1246A polymorphism in the HCRTR2 gene did not appear to be an accomplice and associated with CH predisposition among either the Asian or Caucasian population. Cluster headache (CH) is a severe neurovascular disease characterized by recurring short-lasting attacks of excruciating unilateral pain     network and its closest functional protein partners. From the figure, a few proteins that interact and collaborate with HCRTR2 are also associated with the pathogenesis of CH, including GNB3  guidelines . Last, the keyword strings (HCRTR2) and (Duo Tai Xing) and (Tou Tong) were used for the CNKI electronic database. The reference list of related studies was also manually searched for additional eligible studies.Four electronic databases—ISI Web of Science, CNKI, PubMed, and EMBASE—were comprehensively searched from their initiation up to December 2019 without any language restriction. Before submission of this paper, these databases were searched again so that no newly published articles were missed (the last literature search was performed in August 2020). A combination of Medical Subject Headings (MeSH) alongside free terms was utilized to increase the sensitivity of the literature search. For English databases, we adopted the following search strings: [“Cluster Headache” (Mesh) or cluster headache or ciliary neuralgia or neuralgic migraine or histamine cephalgias or Horton Syndrome or trigeminal autonomic cephalalgia] and  and  the primary outcome was the relationship between HCRTR2 polymorphism and risk of CH, which must be shown by odds ratio (OR) and the associated 95% confidence interval (95% CI), which comes from the original study or built on the allele frequencies of the variant calculations. Editorials, case reports, case series, in vitro experiments, and animal studies were eliminated and removed. If there were numerous studies that gave overlying outcomes and data, the most comprehensive one would be used and included in the meta-analysis. If there was only an abstract without a full paper, we would make three attempts to reach the authors by e-mail for their raw data. In the event that the authors did not respond to our e-mail, these abstracts would be regretfully dropped and discarded.Studies that met the following inclusion criteria were included: (1) subjects in CH groups should be patients diagnosed with CH according to well-established guidelines, such as the ICHD-II criteria; (2) control subjects should be defined as healthy subjects without a history of CH; (3) observational studies (case control study or cohort study) on humans; (4) the polymorphism of interest was rs2653349 in the The methodological quality of eligible studies was evaluated according to the Newcastle–Ottawa Scale (NOS) for observational studies  independently performed data extraction of all included studies according to the predetermined eligibility criteria. The data extraction would be done with the standard data collection form: first author's name, publication year, origin country, subjects' ethnicity, source of the subjects, size of the sample, diagnostic criteria of CH, genotype distribution in CH and control groups, Hardy–Weinberg equilibrium (HWE), calculated OR, and 95% CI of individual study.Q-test and the Higgins I2 test were used to estimate the intrastudy heterogeneity. p > 0.1 and I2 <50% indicated acceptable variability among the included studies , recessive model (AA vs. AG + GG), allelic model (A vs. G), homozygote model (AA vs. GG), and heterozygote model (AG vs. GG). The significance threshold for the meta-analyses was estimated by the Bonferroni correction (0.05/5 = 0.01) , methodological quality  and diagnostic criteria (ICHD-II or ICHD-III) was performed to identify the potential source of heterogeneity. Additionally, meta-regression was performed to test whether the discrepancy between results of the first several studies (published before 2010) and subsequent studies (published after 2010) appeared genuine . Egger's regression test and Begg's rank correlation test were used to estimate the publication bias using Stata version 12.0 . The outcome of The initial search of four online databases yielded 66 records, comprising 15 from PubMed, 8 from EMBASE, 36 from ISI Web of Science, and 7 from CNKI. No additional record was identified through other sources. After the first stage of scanning, 31 duplicated records were excluded. Of the remaining 35 records, a further 24 citations were eliminated after title and abstract screening. Among the remaining 11 articles, 1 was considered unrelated based on predefined inclusion and exclusion criteria and was removed, and 2 were excluded because of duplicated data. Ultimately, eight articles , statistical analysis was done with the random-effect model. The combined OR and corresponding 95% CI gave an outcome that rs2653349 and risk of CH in the overall population  have no significant association statistically  and Asian populations  have no significant associations statistically. The leave-one-out sensitivity analysis was done, and the overall estimate remained unchanged after each included study was removed one by one (detailed data not shown). This confirmed that our conclusion was a robust and reliable one. The overall estimate remained unchanged after the removal of any included study (detailed data not shown). Interestingly, the heterogeneity across studies descended sharply after the removal of the study by Rainero et al. [I2 = 18%)  and Begg's test  also suggested no significant publication bias.Subgroup analysis by ethnicity (Asian and Caucasian) was performed to assess the correlation between rs2653349 and risk of CH in subjects of different ethnicities . The outo et al.  (I2 = 182 = 18%) . Therefo2 = 18%) , and then < 500 or n ≥ 500), chronological order of publication (before or after 2010), methodological quality (moderate or high), and diagnostic criteria for CH (ICHD-II or ICHD-III). Intriguingly, sample size, methodological quality, and chronological order of publication all explained 100.00% of the variation observed across studies, but only chronological order of publication appeared to be significantly associated with the heterogeneity . Based upon the meta-regression analysis, ethnicity (p = 0.080) and diagnostic criteria for CH (p = 0.053) did not contribute significantly to the intrastudy variation  maximum likelihood (REML) with Knapp–Hartung modification to identify the possible source of variation among studies. Five different factors that may contribute to the heterogeneity between studies were tested: ethnicity (Asian or Caucasian), sample size . These findings altogether demonstrated that HCRTR2 genes participate and play an important role in CH pathogenesis.For the majority of patients, CH shows a distinct circadian and circannual regularity of the attacks, strongly suggesting involvement of the biological clock, which is regulated in the hypothalamic region of the brain . This result was similar to previous studies. Baumber et al. [HCRTR2 gene by comparison to wild-type sequence, which is consistent with Zarrilli et al. [HCRTR2 gene and CH. This result is in agreement with studies performed in Sweden  in an in vitro study  , suggesting that chronological order of publication could be a possible source of intrastudy variability. It could be possible that the conclusions of first-published studies have important implications for the pursuit of research on the given association. Statistically significant first-published articles are more attractive and are more likely to be followed by more studies over time, whereas initially non-significant results do not attract further investigation. It should be noted that although the relatively small sample size of included studies (n < 500) was not statistically associated with the intrastudy variability, it explained part of the heterogeneity among studies , which again highlighted the need for studies with larger sample sizes to detect the modest genetic effect of HCRTR2 polymorphisms.Our result was inconsistent with the previous meta-analysis led by Rainero et al.  and Well2 = 18%) . (5) TheHCRTR2 gene and risk of CH. Second, seven out of the eight studies were hospital-based. This might exaggerate OR values caused by a high selection of subjects. Third, two causes were considered to account for the null association of our present study. First, according to our results of meta-regression, the sample size (n < 500) appeared to be the source of heterogeneity among included studies. The limited sample size of our included studies was not vigorous enough to obtain a significant association. Second, the frequency distribution of rs2653349 showed a statistically significant difference between Southeastern European Caucasian and other European and East Asian populations (Katsarou et al., HCRTR2 gene and risk of CH based upon the results of our meta-analysis. Further association studies with larger sample size are strongly encouraged.There were several limitations in this review that should not be neglected. First, the sample size of all included studies was hundreds of cases and controls. Studies with thousands of cases and controls could provide better evidence to identify the marginal effect of correlation between the HCRTR2 gene and CH vulnerability across both Caucasian and Asian ethnics. Concerning limitations of the current study, our findings need further confirmation by well-designed and population-based investigations with larger sample sizes among more ethnicities.Collectively, the combined results didn't support the association between G1246A polymorphism in the The original contributions presented in the study are included in the article/S-yY and Z-tL designed and supervised the research. JiaY, JK, and JieY participated in the acquisition of data and performed the meta-analyses. JiaY and Z-tL helped draft the manuscript. F-rL and Z-tL revised the manuscript. All authors reviewed and approved 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.


This study aimed to comprehensively collect and synthesize the existing evidence to appraise whether rs28362491 was correlated to CAD susceptibility.The association of rs28362491 polymorphism and CAD were presented as odds ratios (ORs) and 95% confidence intervals (CIs).Databases of Web of Science, EMBASE, PubMed, Wanfang, and CNKI were retrieved from inception to August 1, 2019 without any restriction on language. The strengths of association between rs28362491 polymorphism was significantly correlated to CAD risk in five genetic models: D vs. I, OR = 1.16, 95%CI 1.11–1.21, P<0.01; DD vs. II, OR = 1.37, 95%CI 1.25–1.49, P<0.01; DI vs. II, OR = 1.11, 95%CI 1.05–1.18, P<0.01; DD + DI vs. II, OR = 1.17, 95%CI 1.11–1.24, P<0.01; DD vs. DI + II, OR = 1.29, 95%CI 1.15–1.43, P<0.01. After stratification by ethnicity and gender, significant association still existed between rs28362491 and CAD, especially in the dominant model.Thirteen case-control studies with 17 individual cohorts containing 9378 cases and 10,738 controls were incorporated into this meta-analysis. The findings indicated that rs28362491 locus may increase the risk of CAD, and carriers of D allele appear to be more susceptible to CAD.The findings suggest that the mutant D allele in  Coronary artery disease (CAD), which consists of clinical manifestations including stable or unstable angina, myocardial infarction, and sudden coronary death, is a leading cause of disability and death worldwide , 2. The A range of environmental factors like smoking , unhealtNF-κB1 gene, which is mapped to chromosome 4q24. Rs28362491 polymorphism is a 4 bp ATTG insertion/deletion variation in -94 bp of NF-κB1 promoter. This polymorphic site was reported to have great impact on the expression of NF-κB1 gene, with the deletion of ATTG causing reduced promoter activity.Nuclear factor-κB (NF-κB) is a cluster of ubiquitous transcription factors. In the NF-κB family, there are five members including NF-κB1, RelA, c-Rel, RelB, and NF-κB2. As a fundamental transcription regulator, NF-κB participates in most biological processes. The NF-κB signaling pathway also plays a crucial role in heart diseases . NF-κB1 rs28362491 polymorphism and risk of CAD in a Chinese cohort, investigators attempted to conduct replicate studies in different populations with inconsistent results. The conflicting findings might ascribe to small sample size and weak statistical power of an individual study. Therefore, we carried out this meta-analysis to obtain more convincing evidence on the association of rs28362491 polymorphism and CAD susceptibility.Xie et al.  initiallWe searched databases of Web of Science, EMBASE, PubMed, Wanfang, and CNKI before August 1, 2019. For PubMed database, the search string was  AND (“NF-kappa B p50 Subunit”[Mesh] OR NFKB1 OR NF-kappa B p50 Subunit OR NF-κB1 OR NF-kappa B p50 OR NF kappa B p50) AND (Acute coronary syndrome OR Coronary Artery Disease OR Coronary Arteriosclerosis OR Coronary Atherosclerosis OR “Coronary Artery Disease”[Mesh]). No language restriction was set during the literature search process. The reference lists of relevant studies were manually examined to obtain more publications.rs28362491 and CAD; (ii) confirmed diagnosis of CAD for cases; (iii) studies with available data to calculate odds ratios (ORs) and 95% confidence intervals (95%CIs); (iv) studies that conformed to Hardy-Weinberg equilibrium (HWE) [Identified studies met the following criteria were included: (i) case-control or cohort studies investigating um (HWE) . AccordiQuality assessment was carried out by two investigators independently (YW and BW) based upon Newcastle-Ottawa Scale (NOS) . The quaThe following data were collected by two investigators independently (YW and BW): (i) first author; (ii) date of publication; (iii) nationality of participants; (iv) ethnicity; (v) gender; (vi) sample size; (vii) genotype distribution; (viii) results of HWE test. Any disagreement was resolved until reaching a consensus.rs28362491 polymorphism and CAD risk was presented as ORs and 95%CIs in allelic model (D vs. I), homozygous model (DD vs. II), heterozygous model (DI vs. II), dominant model (DD + DI vs. II), and recessive model (DD vs. DI + II). Q-statistical test and I2 test were used to examine the between-study heterogeneity. P < 0.1 and I2 > 50% indicated the heterogeneity was considerable, and a random-effects model should be applied, otherwise a fixed-effects model could be employed. Subgroup-analyses by ethnicity and gender were performed to test if there were ethnicity-specific and gender-specific effects. The data analyses were accomplished using RevMan 5.3 software.The association of Stability of the pooled results was detected through sensitivity analysis by removing each dataset in turn and recalculating the effect sizes. Publication bias was examined by funnel plots.Ninety-six items were obtained after the search of five databanks and reference lists of relevant studies. Thirty-nine items were deleted because of duplication. Of the remaining 57 items, 40 obviously irrelevant citations were removed after the screen of titles and abstracts. After that, another four ineligible articles were deleted after comprehensive assessment. Finally, 13 studies with 17 individual cohorts were included in the final meta-analysis. The procedures of literature search and selection were displayed in Fig. Main characteristics of the eligible studies were summarized in Table rs28362491 was significantly associated with increased risk of CAD under all five genetic models: D vs. I, OR = 1.16, 95%CI 1.11–1.21, P<0.01  and dominant model , and no association was observed under other contrasts.Subgroup analysis by ethnicity revealed that rs28362491 was significantly associated with an increased risk of CAD in females under allelic model , homozygous model , dominant model , and recessive model . When it came to males, significant associations were found under allelic model , homozygous model , heterozygous model , and dominant model .Further subgroup analysis by gender demonstrated that After removal of each study, the re-calculated effect sizes did not reverse, which confirmed the stability and reliability of our findings. Visual inspection of funnel plots did not identify obvious asymmetry, indicating the outcomes were unlikely to have severe publication bias Fig. .Fig. 3FRs28362491 polymorphism in NF-κB1 gene is one of the most widely studied locus.CAD causes nearly one-third of all deaths in individuals aged over 35 . Howeverrs28362491 polymorphism and CAD predisposition have been carried out in different regions. However, it is quite regrettable that those studies reported inconsistent findings and more convincing evidence remains to be determined. By merging the data from previous studies, this meta-analysis indicated that rs28362491 was significantly associated with CAD. The findings of subgroup-analyses witnessed that rs28362491 was significantly associated with CAD in dominant comparison, regardless of ethnicity and gender. Of note, in the Caucasian population, the association was of borderline significance, which might be attributable to limited sample size of participants. In addition, the trends of associations in different genders were not always consistent, which might be caused by gender differences of genotype distributions.Studies on the association of NF-κB1 gene encodes a non-DNA-binding cytoplasmic protein (p105) and a DNA-binding protein (p50) that bind to N-terminus of p105 [NF-κB is a pleiotropic transcription regulator implicating in diverse biological process including cell proliferation, differentiation, adhesion, and apoptosis, thus exerting crucial effects on multiple pathological states like inflammatory response, which plays a vital role in the development of CAD . Despite of p105 . Campbel of p105  reportedRs28362491 polymorphism is located between two putative key promoter regulatory elements of NF-κB1 gene. This polymorphic site consists of three genotypes, namely mutant homozygous DD (deletion/deletion), heterozygous DI (deletion/insertion), and wild homozygous II (insertion/insertion) [rs28362491 was associated with higher level of C-reactive protein, which was an established risk indicator for cardiovascular disease. The in vitro study revealed that the D allele in rs28362491 polymorphism might result in reduced NF-κB1 message, thus decreasing the expression of NF-κB1 [sertion) . Additiosertion) . Fontainsertion)  observedf NF-κB1 . The NF-f NF-κB1 , which af NF-κB1 , 42.The findings of this study could contribute to a broader recognition of the genetic architecture of CAD. In the near future, with the enhanced understanding of genetics, evidence from the genetic studies may have the capacity to improve healthcare of an individual with CAD by taking preventive measures, offering accurate diagnosis, as well as providing personalized treatment. Additionally, appropriate screening programs can be carried out for an individual with a first-degree relative has a history of CAD. Genetic studies may serve to recognize genes as potential therapeutic targets.It was noted that Chen et al.  had publInevitably, this study had several drawbacks. First, the effect sizes were based on unadjusted evaluation for lack of sufficient data, and failure to perform further adjusted analyses might influence the reliability of those findings. Second, like most disease, CAD is a multi-factorial disorder that is associated with genetic and environmental factors. Nevertheless, owing to lack of detailed data in primary studies, we were unable to evaluate the effects of multi-factor interactions. Third, the included populations were from Asian and Caucasian populations, ethnicity bias might exist in our analysis. Thus, the findings might not be applicable to other populations. Last, only three English databases and two Chinese databases were retrieved for potentially relevant studies, although no obvious dissymmetry in any funnel plot was observed, publication biases might exist which could influence the results.rs28362491 locus may increase the risk of CAD, and carriers of D allele appear to be more susceptible to CAD. Due to limitations of this study, the association between rs28362491 polymorphism and CAD could not be entirely concluded. Further well-designed studies among different ethnicities are still warranted to confirm our findings.The current study indicates that the mutant D allele in


HHEX) and gestational diabetes mellitus (GDM) via meta-analysis.To evaluate the association between the rs5015480 single-nucleotide polymorphism of hematopoietically expressed homeobox , Wanfang, and VIP databases for studies worldwide on the relationship between A total of 4 eligible case–control studies were included, involving a total of 1651 patients and 3513 controls. The meta-analysis showed the following odds ratios: C allele vs T allele, 1.24 ; CC genotype vs TT genotype, 1.65 (95% CI: 1.26–2.17); CC genotype vs CT genotype, 1.22 (95% CI: 1.00–1.50); and CC genotype vs CT + TT genotype, 1.32 (95% CI: 1.09–1.61).HHEX rs5015480 represents a risk factor for the development of GDM, and pregnant women carrying the CC genotype have an increased risk of GDM. The 2017 International Diabetes Federation (IDF) Diabetes Atlas showed that the global incidence of GDM was as high as 14.0%. The incidence of GDM in China has reached 18.9%. There is evidence that women with a history of GDM have an approximately 48% chance of developing diabetes in the next pregnancy; 25% to 70% of women with GDM may develop true diabetes within 20 years and tend to experience serious consequences, including miscarriage and fetal growth restriction, and the newborns have significantly increased risk of developing obesity and diabetes in adulthood.Gestational diabetes mellitus (GDM) is one of the most common perinatal complications. The etiology of GDM is multifactorial, with many factors such as maternal health status and social psychology involved in its development and outcome.HHEX) gene and the risk of GDM have been reported. Such studies have focused on the HHEX SNP rs5015480 but less on rs1111875; accordingly, rs5015480 was selected as the target in the present study.In recent years, with the completion of the Human Genome Project, new breakthroughs have been made in molecular genetics research on GDM. Studies on the association between single-nucleotide polymorphisms (SNPs) of the hematopoietically expressed homeobox  AND (“Homeobox gene expression in hematopoietic stem cells" OR “HHEX") AND (“rs5015480" OR “single nucleotide polymorphism"). An electronic search was also performed for articles written in Chinese in the China National Knowledge Infrastructure (CNKI), Wanfang, and VIP databases using the relevant terms  AND (“Homeobox gene expression in hematopoietic stem cells" OR “HHEX") AND (“rs5015480" OR “single nucleotide polymorphism"). Epidemiological studies on the association between the 2.22.2.1HHEX rs5015480 and GDM; well-designed cohort studies, case–control studies, case–cohort studies, and cross-sectional studies; sufficient genotype or allele frequency data were provided; all patients included were confirmed with GDM according to the criteria in International Association of Diabetes in Pregnancy Study Groups (IADPSG) and Obstetrics and Gynecology (8th edition); and the allele frequencies were in Hardy–Weinberg (H–W) equilibrium.The inclusion criteria were as follows: epidemiological studies on the association between 2.2.2The exclusion criteria were as follows: abstracts, reviews, lectures, commentaries, and dissertations with duplicate publication; and studies with genotype or allele frequency data that were incomplete or that could not be extracted.2.3Two reviewers independently screened the studies according to the inclusion criteria. Disagreement was settled by discussion or by a third investigator. The following information was extracted from eligible studies: first author, publication date, definition and characteristics of subjects in case and control groups, total number of cases included, distribution and frequency of alleles and genotypes in cases and controls, and sources of genotyping samples.2.4Q test and I2 statistic), forest plot generation, and publication bias analysis. Differences were considered statistically significant at P < .05.The methodological quality of the studies was evaluated using the Newcastle–Ottawa scale (NOS); all studies scoring >5 were included in the meta-analysis. RevMan 5.3 was used for heterogeneity testing  of 1.24 , suggesting that HHEX rs5015480 is a risk factor for GDM development . Assessment of the heterogeneity of the included studies showed Chi-square = 1.87, 3.2.2P = .55, and I2 = 0%, suggesting no heterogeneity in the genotype distribution of the included studies; therefore, a fixed-effects model was used for data pooling. The results showed an OR of 1.65 (95% CI: 1.26–2.17)  Fig. .3.2.3P = .11, and I2 = 50%. The P value was >.1 and I2 = 50%, indicating no heterogeneity in the genotype distribution of the included studies; therefore, a fixed-effects model was used for data pooling. The results showed an OR of 1.22 (95% CI: 1.00–1.50)  Fig. .3.2.4P = .11, and I2 = 51%. The P value was >.1 and I2 was approximately 50%, indicating no heterogeneity in the genotype distribution of the included studies; therefore, a fixed-effects model was used for data pooling. The results showed an OR of 1.32 (95% CI: 1.09–1.61), suggesting increased risk of GDM development in pregnant women with the CC genotype , with a total length of 5.7 kb and 4 introns. In recent years, several studies have confirmed that HHEX is a GDM susceptibility gene.–14 Changes in HHEX expression, associated with its polymorphism, may contribute to altered paracrine regulation of insulin secretion. This causes reduced insulin secretion by β-cells, which in turn leads to diabetes. In addition, the C allele of HHEX rs5015480 has been linked to decreased pancreatic β-cell function, β-cell glucose sensitivity, and insulin secretion, as evaluated using a β-cell (homeostasis model assessment-B]) homeostasis model.The HHEX SNPs are associated with the risk for type 2 diabetes mellitus, which has been confirmed in a replication study in a different population. Researchers worldwide have started to study their association with GDM. However, the results have been inconsistent due to the differences in research methods or inclusion criteria, too small sample size, or great variation in sample size across the studies. Therefore, we performed a meta-analysis to increase the sample size and resolve the inconsistency between the results of individual studies and thereby obtain comprehensive assessment results closer to reality.Human genome-wide association studies have demonstrated that HHEX rs5015480 is a risk factor for GDM, and pregnant women carrying the CC genotype have elevated risk of developing GDM. However, given the small number of relevant studies and populations involved, the generalization of this conclusion awaits additional studies.Here, a total of 4 eligible case–control studies were included, consisting of 1 Chinese article and 3 English articles and involving a total of 1651 patients and 3513 controls. All the subjects in the studies did not deviate from H–W equilibrium, suggesting good representativeness of subjects. In addition, the NOS scores indicated that the included studies had high methodological quality. The meta-analysis showed that the OR were as follows: C allele vs T allele, 1.24 (95% CI: 1.12–1.38); CC genotype vs TT genotype, 1.65 (95% CI: 1.26–2.17); CC genotype vs CT genotype, 1.22 (95% CI: 1.00–1.50); and CC genotype vs CT + TT genotype, 1.32 (95% CI: 1.09–1.61). The data show that HHEX rs5015480 and rs1111875, and all studies on rs5015480 suggest that it is a risk factor for the development of GDM. For example, in a Korean population, the C allele of HHEX rs5015480 was associated with increased risk of GDM and decreased insulin secretion upon glucose challenge. In a Danish population,HHEX rs1111875 was also associated with GDM. A study in Poland indicated that the C allele of HHEX rs5015480 might be a risk allele for GDM and was associated with increased body mass index (BMI) during pregnancy. However, there have been inconsistent conclusions on rs1111875 in China and other countries. In Korean population and Jining population of Shandong Province studied by Cho et al and He et al, respectively, the authors drew the same conclusion: the 3 genotypes  of HHEX rs1111875 were associated with GDM development. In contrast, Hu et al studied the population in Jiangsu Province and Liu et al studied the population in central China, and concluded that there was no association between rs1111875 and GDM susceptibility. The inconsistency regarding rs1111875 may be attributed to regional differences and small sample size. In the future, the sample size and multicenter cooperation in different regions should be increased to investigate the relationship between this locus and GDM susceptibility.The related studies have mainly focused on We thank all the participants for their contribution to this work.Conceptualization: Xingjie Wang, Yuanlin Ding.Investigation: Jiawei Rao, Xinshan Zhang.Supervision: Haiyan Pan, Haibin Yu.Writing – original draft: Xingjie Wang, Yuanlin Ding.Writing – review & editing: Haiyan Pan, Haibin Yu.