Studies have shown strong positive associations between serum urate (SU) levels and chronic kidney disease (CKD) risk; however, whether the relation is causal remains uncertain. We evaluate whether genetic data are consistent with a causal impact of SU level on the risk of CKD and estimated glomerular filtration rate (eGFR).N = 110,347 for SU, N = 69,374 for gout, N = 133,413 for eGFR, N = 117,165 for CKD), electronic-medical-record-linked UK Biobank data , and population-based cohorts , all in individuals of European ancestry, for SU levels and CKD. Our MR analysis showed that SU has a causal effect on neither eGFR level nor CKD risk across all MR analyses . These null associations contrasted with our epidemiological association findings from the 4 population-based cohorts . In contrast, the same MR approaches showed that SU has a causal effect on the risk of gout , which served as a positive control of our approach. Overall, our MR analysis had >99% power to detect a causal effect of SU level on the risk of CKD of the same magnitude as the observed epidemiological association between SU and CKD. Limitations of this study include the lifelong effect of a genetic perturbation not being the same as an acute perturbation, the inability to study non-European populations, and some sample overlap between the datasets used in the study.We used Mendelian randomization (MR) methods to evaluate the presence of a causal effect. We used aggregated genome-wide association data  levels and chronic kidney disease (CKD) risk.Elevated SU levels are often found in patients with CKD, but it is not clear whether high serum urate is a cause of kidney disease or just a common co-occurrence.Previous studies examining whether SU levels had a causal effect on CKD were limited due to not having large enough samples to detect a true causal relationship if it existed and/or had limitations related to the methodology.Several clinical trials have been started that aim to use urate-lowering medication to prevent CKD.To determine whether SU level has a causal effect on CKD, we used a methodology known as Mendelian randomization to test whether genetic variants known to increase SU level also increased the risk of CKD.We used multiple datasets to perform Mendelian randomization analyses, which included meta-analyses performed across multiple population-based cohorts, 4 individual population-based cohorts, and the large electronic-medical-record-linked UK Biobank.Across all datasets, we found no significant causal connection between SU level and risk of CKD.Our findings do not support a causal role of SU level in CKD.Lower SU levels would be unlikely to translate into reduced risk of CKD. Approximately 10% of the global population has chronic kidney disease (CKD) , which cObservational studies have consistently shown strong positive associations between serum urate (SU) levels and the risk of CKD ,5; howevAs effective medications to lower SU levels are available, the potential causal role of SU level in CKD has become one of the most investigated targets for a renoprotective agent. As such, clinical trials of xanthine oxidase inhibitors  for the endpoint of CKD progression/development are currently underway .Genetic epidemiology can be used to evaluate the causality of risk factors with respect to potential endpoints of interest. This approach, called Mendelian randomization (MR), posits that causality can be inferred because the alleles of a particular exposure-associated genotype are assigned randomly at conception. This can minimize the bias that can occur by confounding and reverse causation in conventional observational studies . GenotypOur objective was to evaluate whether genetic data are consistent with a causal effect of SU levels on estimated glomerular filtration rate (eGFR) and risk of CKD. We performed a series of MR analyses of SU level and eGFR and CKD using genetic variants influencing SU level as the exposure without the influence of confounders.Our study approach was composed of several complementary components . We firsWe examined 26 SNVs strongly associated with SU level identified in a GWA meta-analysis study of 110,347 participants of European ancestry conducted by the Global Urate Genetics Consortium  14]..14].2, available in up to 12,385 cases and 104,780 controls.For MR analyses for eGFR and CKD endpoints, we retrieved GWA study summary statistics for eGFR and CKD from a published meta-analysis conducted by the Chronic Kidney Disease Genetics Consortium (CKDGen) . We usedFor MR analyses for gout (as a positive control endpoint), we retrieved GWA study summary statistics (effect sizes and standard errors) for gout from a published meta-analysis in 2,115 cases and 67,259 controls of European ancestry from the Global Urate Genetics Consortium .N = 335,212), and 4 population-based cohorts . In the UK Biobank, based on recommendations from UK Biobank (http://www.ukbiobank.ac.uk/wp-content/uploads/2018/03/ukb_genetic_data_description_v3.txt), we excluded samples that belonged to any of the following categories: outliers in heterozygosity and missing rates, putative sex chromosome aneuploidy, self-reported non-white British ancestry, and related individuals. Excluded related individuals were defined as 1 individual in each pair with relatedness up to the third degree. In total, 335,212 individuals of white British ancestry remained for analyses. For samples from the UK Biobank, we treated the following ICD-10 codes as indicative of CKD: N03 (chronic nephritic syndrome), N05 (unspecified nephritic syndrome), N17.1 , N17.2 (acute kidney failure with medullary necrosis), N18 (chronic kidney disease), N19 (unspecified kidney failure), N26.9 , N25.0 , R80.2 , I12 (hypertensive chronic kidney disease), I13 (hypertensive heart and chronic kidney disease), Z99.2 , Z94.0 (kidney transplant status), and Z49 . In total, this produced 5,615 cases. We performed logistic regression for each of the 26 SU-associated SNVs to generate association summary statistics for CKD using this case definition.Our additional datasets consisted of electronic-medical-record-linked UK Biobank data , we conducted individual-level analyses using a genetic risk score (GRS) of the 26 SNVs associated with SU level. eGFR was recalculated in the 4 prospective cohorts using the Modification of Diet in Renal Disease (MDRD) 4-variable equation. CKD cases were defined as individuals who had an eGFR less than 60 ml/min/1.73 m². A description of the 4 cohorts is provided in the SLC2A9 gene and rs2231142 in the ABCG2 gene. These are the 2 SNVs with the most significant effects on SU, and are also the only 2 SNVs identified in the SU GWA analysis as having significant sex-specific effects after applying multiple test correction [First, we tested our 26 instrumental SNVs for heterogeneity/pleiotropy using a published test for heterogeneity, the MR-PRESSO  global tFor our individual-level analyses in the 4 population-based cohorts , we calculated the weighted GRS per individual based on the number of risk alleles for the SNVs and the effect size of these SNVs on SU level based on summary results from the Global Urate Genetics Consortium . IndividEpidemiological associations between SU level and eGFR were assessed using linear regression, and between SU level and CKD using logistic regression, adjusting for age and sex in the 4 population-based cohort studies.We performed analytic power calculations using mRnd  based onAll statistical analyses were performed using R  or Python 2.7 .P < 10−6 for MR-PRESSO global test), which may indicate the presence of pleiotropy. Accordingly, we selected 7 MR approaches considered to be appropriate for instrumental variables displaying potential pleiotropy: a standard WLS regression analysis with a random effects model, 5 alternative MR methods designed to be robust to heterogeneity, and a WLS regression analysis after removing 4 SNVs identified as outliers for the effect of SU on CKD and 11 SNVs identified as outliers for the effect of SU on eGFR (P = 0.06); heterogeneity/pleiotropy in the eGFR analysis was still present but reduced (P = 0.004). We also performed leave-one-out analysis with the WLS regression method (SLC2A9 rs12498742 and ABCG2 rs2231142), which are also known to have sex-specific effects . However, unlike for eGFR and CKD, all 7 approaches showed a highly significant causal effect of SU on gout . This result serves as a positive control of our approach as it is consistent with the known causal role of SU in gout [As a positive control, we repeated the same procedure using the same 26 SNVs associated with SU to test for a causal effect of SU on gout. Similarly to the analyses of eGFR and CKD, we observed significant heterogeneity among the 26 SNVs . However, the GRS was not associated with either eGFR  or CKD risk  (P = 0.49), and still produces a null result for a causal effect of SU on CKD (P = 0.34).To account for limitations of using aggregated GWA data, such as heterogeneity among study populations in the meta-analyses or unaccounted for population stratification within the sample, we performed an individual-level analysis on 4 population-based cohorts. Within these cohorts, we observed a highly significant association of a urate-specific GRS composed of the 26 urate-associated SNVs with SU  . We repe = 0.59) . We alsoSLC2A9 gene, which encodes the GLUT9 transporter (for glucose and urate) in the renal proximal tubule and is the largest contributor to genetic control of SU level, explaining 3% of variance [P < 10−700) but neither with eGFR  nor with CKD .We also specifically examined rs12498742 in the variance . This SNP = 8.08 × 10−6) and increased risk of CKD , after adjustment for age and sex , we observed that an equivalent (1 mg/dl) increase in SU level was associated with reduced eGFR level  .In this study, we investigated a potential causal role for SU level in the development of CKD using a series of complementary MR analyses. Despite previous observational study findings that SU levels were strongly associated with the risk of incident CKD ,5, our MN > 400,000) and therefore has higher power than the previous studies above. Our failure to detect by MR the expected epidemiological association of SU with CKD/eGFR is therefore not due to lack of power. We suggest instead that it is due to our MR analyses being robust to unknown confounders and reverse causation, which can create positive correlations in observational epidemiological studies.Unlike previous studies based on smaller sample sizes, our power calculations show that our study is sufficiently powered to assess a causal relationship between SU level and CKD. One study that examined only eGFR (not CKD) reported that increased SU levels due to SNVs in urate transporter genes were associated with increased eGFR only in men  . HoweverClinical trial data on lowering SU levels for preventing CKD progression to date have been conflicting ,33. MoreSLC2A9 gene), as well as an analysis excluding both this SNV and a second large-effect SNV (rs2231142 in the ABCG2 gene). Second, an assumption of MR is that the SNVs used as instrumental variables are not subject to “horizontal pleiotropy,” meaning that the SNVs should not have pleiotropic effects on the outcome outside of the target biomarker or risk factor. We have used MR approaches designed to be robust to horizontal pleiotropy to account for this. Third, our MR findings cannot predict with absolute certainty that therapeutics lowering SU levels will not result in a lowering of CKD risk, since the effects of genetic variation may not be exactly the same as the effects of a therapeutic intervention. Nevertheless, studies have suggested that genetic findings can predict the effect of drugs on disease outcomes [Potential limitations of this study and, in particular, MR deserve comment. First, MR analysis requires suitable SNVs to act as instrumental variables, and selection of inappropriate or unrepresentative instrumental variables may undermine the validity of the study. Here, we used the SNVs significantly associated with SU in a previously published GWA study. We also performed an additional analysis using a single SNV with a strong effect on SU and a well-understood mechanism Click here for additional data file.S2 FigSLC2A9 gene and rs2231142 in the ABCG2 gene. Lines show 95% confidence intervals; odds ratio estimates are per 1 mg/dl of SU. Four outliers were removed in the outlier-corrected (MR-PRESSO) analysis Click here for additional data file.S3 FigLines show 95% confidence intervals; odds ratio estimates are per 1 mg/dl of SU. One outlier was removed in the outlier-corrected (MR-PRESSO) analysis see .(TIFF)Click here for additional data file.S4 FigLines show 95% confidence intervals; odds ratio estimates are per 1 mg/dl of SU. Four outliers were removed in the outlier-corrected (MR-PRESSO) analysis see .(TIFF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.


It has been reported that the single nucleotide polymorphisms (SNPs) miRNA-196 (miR-196) rs11614913 and miRNA-146a (miR-146a) rs2910164 are related to susceptibility to ulcerative colitis (UC). Because the previously reported results have been mixed and uncertain, the aim of this study was to perform a meta-analysis and review to assess the relationship between these 2 SNPs and UC risk.In this analysis, 5 studies involving 1023 cases and 1769 controls for miR-196 rs11614913 and 4 studies involving 827 cases and 1451 controls for miR-146 rs2910164 were included. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to pool the effect size.P = .02), recessive comparison , and dominant comparison  of miR-146 rs2910164 in Asian but not Caucasian population. No evidence of an association was shown between the rs11614913 polymorphism and UC risk in allelic, heterozygote, homozygote, recessive, and dominant models in both Caucasian and Asian populations (P > .05).A decreased risk of UC was identified in homozygote comparison (GG vs CC: OR = 0.69, 95% CI: 0.52–0.93, MiR-146 rs2910164, but not miR-196 rs11614913, was associated with a decreased risk of UC in Asian population. However, the results should be treated with caution because of the limited sample size and heterogeneity. Well-designed studies with large sample sizes and more ethnic groups are needed to validate the risks identified in the current meta-analysis and review. It has been suggested that environmental factors, genetic predisposition, and immune dysregulation have important roles in the pathogenesis of UC.Ulcerative colitis (UC) is a common disease that affects the colon and rectum, and it especially involves the mucosa. The inflammation affects continuous segments of the mucosa but not areas of the intervening normal mucosa.,4 Some studies have shown a genetic predisposition through the inheritance of some contributory genetic polymorphisms leading to the pathogenesis of UC.–9UC is a multifactorial, polygenic disease thought to have genetic heterogeneity. According to this hypothesis, different genetic backgrounds may present with different clinical types of the disease.–12 It has been said that miRNAs are involved in various biological processes including cell proliferation, cell death, stress resistance, and metabolism. Moreover, a recent report has shown that miRNA plays an important role in regulating the pathogenesis of UC. MiRNA has been reported to regulate the nuclear transcription factor kappa b (NF-κB) pathway, thus causing UC. In addition, Wu et al have found that miRs-28-5p, -151-5p, -103-2, -199a-5p, -340, -362-3p, and -532-3p are increased and miR-505 is decreased in the peripheral blood of patients with UC. Moreover, Feng et al have found that miR-126 is increased in UC tissues. MiR-126 may activate the NF-κB signaling pathway through IκBα and promote the development of UC.MicroRNAs (miRNAs) are small noncoding RNA gene products that adjust gene expression by base pairing with target miRNAs at the 3′-untranslated region, leading to miRNA cleavage or translational repression. Recently, Wan et al screened for common SNPs in miRNA sequences and verified that 2 SNPs (rs2910164 and rs11614913) located at the pre-miRNA areas of miR-146a and miR-196 are associated with UC. They discovered that miR-146a rs2910164 does not have any correlation with colorectal cancer (CRC) risk. However, it was found that miR-196a2 rs11614913 is associated with the presence of CRC in all genetic models.Single-nucleotide polymorphisms (SNPs), mutations in the miRNA sequence, may affect miRNA expression and/or maturation. Recently, miR-146a rs2910164 has been found to be associated with UC patients, and other miR-196 rs11614913 polymorphisms have been reported to be involved in UC risk as well.–24There is an increased risk of CRC in patients with UC.–24 the results have been mixed and uncertain. To date, there has been no meta-analysis and review exploring the association between them. Therefore, the aim of this study was to perform a meta-analysis and review to assess the relationship between these 2 SNPs and UC risk.Although some studies have been performed to explore the association between these 2 SNPs and the risk of UC in various populations,22.1An ethical approval is not necessary for a meta-analysis. Two independent investigators did a systematic search in the PubMed and Embase databases. There was no limit in terms of language, and the last search was conducted on March 1, 2018. The following terms were searched: “microRNA” OR “miRNA” OR “microRNAs,” AND “ulcerative colitis” AND “polymorphism.” The reference lists of retrieved articles and recent reviews were searched by hand for further relevant studies.2.2To be included in this meta-analysis, studies had to satisfy the following inclusion criteria: assess the association between miR-146a/196 polymorphisms and UC; be a case–control study; focus on humans; and have detailed genotype data in order to calculate the odds ratios (ORs) and 95% confidence intervals (CIs). Exclusion criteria were as follows: repeat of previous publications; comment or editorial; family-based genealogical studies; and no detailed genotype data. When there were multiple studies from the same population, only the largest study was included. Two investigators independently selected the studies based on the inclusion and exclusion criteria by checking the title, abstract, and full-text. Discussion was used to resolve any disputes.2.3The following information was collected: first author's name, year of publication, country of origin, genotyping methods, ethnicity, UC criteria, Hardy–Weinberg equilibrium (HWE), numbers of cases and controls, and genotype frequencies in cases and controls for miR-146a and miR-196 genotypes, respectively. The Caucasian or Asian ethnicity was assigned according to the country where the research site was located, namely Caucasians for Europe and Asians for Asia. Two investigators independently extracted the data of the eligible studies. If a dissent existed, they reexamined the original data of the included studies, and discussed and reached a consensus. If a dissent still existed, a third investigator made the final decision.2.4The quality of the studies were evaluated according to the Newcastle-Ottawa scale Table .2.5 Each study was evaluated by HWE; and after a Chi-squared test with the control group, P < .05 was considered to be significantly incompatible with HWE. ORs and 95%CIs were used to assess the association strength between miR-146a/196 SNPs and the presence of UC. Pooled ORs were performed for allelic comparison , the heterozygote model , homozygote model (miR-146a: GG vs CC miR-196: TT vs CC), dominant model , and recessive model (miR-146a: GG vs CG + CC miR-196: TT vs CC + CT). A statistically significant level was decided by the Z-test, with a P-value < .05 considered to be significant. Heterogeneity was assessed using the Q statistic (P < .1) and the I2 statistic (greater than 50% as evidence of significant inconsistencies). Depending on heterogeneity, a fixed effects or random effects model was used to pool the effect size. Sensitivity analyses were performed to assess the impact of each study on each of the findings by omitting each study in turn. Subgroup analyses were performed based on ethnicity. Begg's funnel plots and Egger's regression tests were used to determine potential publication bias. Asymmetric graphs and Egger's tests with a P-value < .05 were considered to be a significant publication bias. All statistical analyses were conducted with Stata 12.0 software . A 2-tailed P < .05 was identified as significantly different from specified conditions, where a certain P-value was declared.A meta-analysis was conducted based on the PRISMA checklist, according to the guidelines.33.1 One was not a detailed genotype data study, and 2 others concerned interleukin gene variants of UC.,33 Finally, in the present study, 5 eligible case–control studies–24 satisfying the inclusion criteria were included. The characteristics of each study are shown in Table ,21 were Caucasian, while those in the other 2 studies were Asian.,24 With regard to miR-196 rs11614913, 2 studies were carried out on Caucasians,21 and 3 studies involved Asians.–24 The genotyping methods used included polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) and PCR sequencing. The genotype distribution was consistent with HWE in all studies except for 1 study on miR-196 rs11614913.A total of 37 studies were acquired from PubMed and Embase . The literature selection process is shown in flow diagram. Twenty-eight articles were excluded, of which 7 were duplicates, and 21 had no relation to this topic. The remaining nine studies were full-text reviews, and 4 studies were excluded, among which, one was a review.3.2Q test and the I2 statistic. Therefore, a fixed-effects model was used. No significant association was identified in the allelic and heterozygote model  , recessive comparison , and dominant comparison . A trend of reduced risk could be seen . A trend of a reduced risk was observed. In Asians,,24 homogeneity existed in all 5 genetic models. No significant association was discovered in the heterozygote model . In addition, a significant decreased risk of UC was discovered   and dominant model  in Caucasians. In contrast to the results from Caucasian, no significant association was observed in Asians (P > .05)    Table .In the study by Gazouli et al, the male/female ratio was 101/109. The proportion of male patients out of the total number was less than 50%. In the 3 other studies, the ratio was greater than 50%. In order to study whether the sex ratio caused heterogeneity, we analyzed the Gazouli et al study alone as a group, and the other 3 studies as another group. This resulted in a reduction of heterogeneity to an acceptable level  had a strong relation with many diseases.,40 In present combined analysis, we found that a statistical association in 4 genetic models. A decreased risk of UC was shown in allele comparison, homozygote comparison, recessive comparison, and dominant comparison. In the Asian population subgroup analysis, we found a similar result. However, the study on Caucasian populations showed no significant association in any of the genetic models. This finding might have been due to ethnicity, etc. The rs11614913 SNP is located in the pre-mir region, and it was previously associated with several types of cancers.,42 A previous study had demonstrated that the expression of mature mir-196a2 may be influenced by the rs11614913 genotype: the presence of the CC genotype decreased the expression of mature mir. The observation that this SNP was also reported to be associated with subclinical phenotypes of UC in the Greek population. However, no statistical association in any genetic model was found in both Caucasian and Asian populations, which indicated this polymorphism might not the susceptible factor for UC risk.The results of our subgroup and sensitivity analyses were stable. A recent research has reported that polymorphisms within the miR-146a sequence caused the additional generation of mature microRNAs from the passenger strands of the miRNA precursor, which can be functionally important because of different target selections.As for sensitivity analysis of miR-146a rs2910164, although the research varied in many aspects, the association could not be driven by a single study. However, for miR-196 rs11614913, sensitivity analysis showed that the study with deviation from HWE conducted by Ranjha et al could alter the association between miR-196 rs11614913 and UC.The current meta-analysis has several advantages. First, this is the first meta-analysis focusing on the association between miRNA SNPs and risk for UC. Additionally, another miRNA polymorphism of miR-196, rs11614913, was also explored. In addition, according to methodological quality assessments, all of the studies included were of high quality. Moreover, no obvious publication bias was found by either the Begg's funnel plot or Egger's regression test. Finally, there was no limit to the literature search, so selection bias was well controlled. which deviated from HWE. It is suggested that subphenotype distribution, to some extent, contributed to the source of heterogeneity. This result should be treated with caution. Finally, we did not study different lifestyles to explore the relationship between lifestyle and risk of UC. Therefore, further studies on comparisons between different human populations are valuable and necessary.Although there were considerable efforts to explore the possible association between the 2 SNPs and UC risk, some limitations should be considered. First, the number of studies involving miR-146a rs2910164 and miR-196 rs11614913 was limited, and further analysis was limited by insufficient primary research. Second, 1 study did not conform to HWE. Third, heterogeneity was detected in some genetic models of rs11614913 by excluding 1 study,In conclusion, our results showed that the miR-146a rs2910164 polymorphism has a decreased risk for UC, except in the homozygote model, especially in Asians, but the conclusion did not extend to Caucasians. While miR-196 rs11614913 polymorphisms may have a decreased association with the risk for UC in the dominant model, the same result was identified in Caucasians, but not in Asians. There was not enough data to adequately confirm the association between UC and miR-196 rs11614913, and the results should be interpreted with caution. Well-designed studies with large sample sizes and different ethnic groups are needed to validate the risks identified in the current meta-analysis.Data curation: Yi Zhu, Zhongyi Li, Yao Wang.


Brain-derived neurotrophic factor (BDNF) is widely expressed in the central nervous system and prolongs the survival of dopaminergic neurons in the substantia nigra. Several studies have recently investigated the association between BDNF G196A , a single nucleotide polymorphism influencing cognitive processes, and cognitive impairment in Parkinson's disease (PD), but with contradictory findings. Thus, this meta-analysis was performed to clarify the possible association. Relevant studies were identified by a systematic search of PubMed, Embase, and China National Knowledge Infrastructure (CNKI) databases. The strength of the association was evaluated using crude odds ratios and 95% confidence interval. Finally, six studies involving 532 cases and 802 controls were included. Our analyses suggested the G196A  polymorphism was significantly associated with cognitive impairment in PD, especially in Caucasian populations. In conclusion, BDNF G196A  is confirmed to be a risk factor for cognitive impairment in PD. Parkinson's disease (PD) is a neurodegenerative disease characterized by the degeneration and loss of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies. The main clinical manifestations of PD are tremor, myotonia, bradykinesia, and abnormal posture and gait. Non-motor symptoms  are other important clinical manifestations running throughout all stages of PD and occur earlier than motor symptoms, seriously reducing the quality-of-life . As one The pathogenesis of PD is still unclear, but is believed to be caused jointly by genetic and environmental factors and to be related to many mechanisms, such as altered protein handling, reactive microgliosis, oxidative stress, and mitochondrial dysfunction . The basThe exact pathogenesis of cognitive impairment of PD is unclear. Neuropathological findings showed that cognitive impairment of PD was correlated with the number of cortical Lewy bodies, Alzheimer’s disease (AD)-related pathological changes , and cerebrovascular lesions. At present, the specific susceptibility genes for cognitive impairment of PD are unknown. The brain-derived neurotrophic factor (BDNF), which can significantly enhance the tolerance of dopamine neurons against the acidic environment, is significantly downregulated in the ventral substantia nigra of PD patients . G196A  polymorphism and cognitive impairment in PD, but reported conflicting and inconclusive findings . There min vitro experiments.Inclusion criteria were: 1) case-control studies investigating the association between gene BDNF G196A  polymorphism and cognitive impairment in PD; 2) sufficient data for calculating the pooled odds ratio (ORs) with 95% confidence interval (CI); 3) studies on humans. Exclusion criteria were 1) duplication; 2) case report or review; 3) article with other genetics polymorphisms and Two investigators independently and systematically searched PubMed, EMBASE, and China National Knowledge Infrastructure (CNKI) databases online up to October 1, 2018 to identify relevant studies using the following keywords:  AND ("genetic polymorphism" or "single nucleotide polymorphisms" or "SNP") AND ("cognitive impairment" or "dementia") AND ("Parkinson's disease" or "PD"). References in the cited studies and reviews were also checked for other relevant publications. When two studies overlapped, we chose the latest study or the one with a larger sample size. There was no restriction on language, ethnicity, or region of study population. Cognitive impairment was diagnosed according to classification criteria.Two investigators reviewed and extracted data independently in accordance with the inclusion criteria. The following information from each study was collected: surname of first author, year of publication, country, ethnicity, sample size, and genotype distributions among cases and controls. When a study involved more than one ethnicity, the genotype data were extracted separately. The quality of the selected studies was assessed using the Newcastle-Ottawa Scale (NOS). Analyses were based on three broad dimensions of selection, comparability, and exposure in the case-control studies. The NOS scores vary from 0 up to 9: high quality (>7); medium quality –6; poor 2>50% was considered to be significant heterogeneity and a random-effects model was applied; otherwise a fixed-effect model was used. Sensitivity analysis was conducted by excluding studies one-by-one to evaluate the effect of individual studies on the pooled ORs and evaluate the stability of the results. A χ2 test was used to determine whether the observed genotype frequencies conformed to the Hardy-Weinberg equilibrium (HWE). Publication bias was evaluated by visual inspection of symmetry of Begg's funnel plot and by Egger's test . All statistical analyses were performed on STATA 11.0.Pooled ORs with 95%CI were calculated to evaluate the strength of relationship between BDNF gene rs6265 polymorphism and cognitive impairment in PD. Subgroup analyses were performed according to ethnicity. Heterogeneity between studies was detected by the chi squared-based Q-test. P<0.10 or IThe initial search returned a total of 20 articles. vs GA+GG and AA vs GA; vs GA+GG, AA vs GG, and AA vs GA; Allele and genotype distributions of the BDNF G196A polymorphism from each included study are shown in Sensitivity analysis showed that the omission of any individual study did not substantially influence the risk estimates, which supported the credibility and reliability of this meta-analysis.Begg's funnel plot or quantitative Egger's test did not find any obvious publication bias for the association between BDNF G196A  and cognitive impairment in PD.PDMCI is often considered an early manifestation of cognitive decline in PD and a transitional state for the subsequent progression to PDD . PDMCI iBecause of the family clustering of PDD, it is speculated that there may be some genetic susceptibility to cognitive impairment of PD . AlthougBDNF isolated from pig brain plays an important role in promoting the proliferation, regeneration, synaptic remodeling, and regulated release of neurotransmitters . The humA meta-analysis in 2015 found no association between Val66Met polymorphism and the risk of developing PD in the overall analysis, or between the BDNF G196A genotype and cognitive impairment in the clinical data summarization, but no subgroup analysis of races was performed . Lee et We performed this meta-analysis to resolve the contradictory results of all relevant studies published up to 2018. Our analyses suggested that the G196A  polymorphism was significantly associated with cognitive impairment in PD, especially in Caucasian populations. The only study involving the Asian population  showed nSeveral potential limitations of this meta-analysis should be considered. First, no subgroup analysis of gender, age of onset, educational level, duration of illness, or genotype methods was conducted owing to the limited number of articles and the small sample size. Second, this meta-analysis only included Asian and Caucasian populations, which calls for future studies on other ethnic groups because of ethnic differences in gene polymorphisms. Third, there was no uniform diagnosis of Parkinson's cognitive impairment in these studies. In 2007, the Movement Disorder Society Task Force (MDS-TF) issued a unified and standardized PDD diagnostic guide and revised it, but the four core cognitive domains were placed in the same weight, and any two cognitive domains with significant impairment could be diagnosed as PDD . HoweverIn conclusion, the BDNF gene rs6265 polymorphism plays important roles in cognitive impairment in Parkinson's disease, especially among Caucasian populations. Although cognition cannot be considered a pre-motor biomarker of PD, it acts as a staging and prognostic biomarker and plays a key role in sub-typing and disease stratification. Nevertheless, more large-sample studies following the unified diagnostic criteria for cognitive impairment in PD are needed to further confirm the relationship between BDNF rs6265 and the pathogenesis of PD.


CACNA1C) gene as a significant risk gene for schizophrenia. However, there are inconsistent conclusions in case–control studies.Schizophrenia is a serious mental illness with a genetic predisposition. Genome‐wide association studies (GWAS) have identified the α‐1C subunit of the L‐type voltage‐gated calcium channel (CACNA1C rs1006737 is an authentic risk single nucleotide polymorphism (SNP) for schizophrenia.We performed a comprehensive meta‐analysis of all available samples from existing studies under four different genetic models  to further confirm whether p < 0.05) was observed by pooling nine Asian and European studies, including a total of 12,744 cases and 16,460 controls. For European‐decent samples, a significant difference was identified between patients and controls for the four models . We observed a significant difference between patients and controls for the recessive model and allele model  using a fixed effect model, but the dominant model (GG + GA vs. AA: OR: p = 0.15) and additive model (GG vs. AA: p = 0.11) showed no significant difference between patients and controls in the Asian samples.A statistically significant difference under the four models (all CACNA1C as a susceptibility gene for schizophrenia across world populations, but its roles in the pathogenesis of schizophrenia need to be further investigated.Our findings provide important evidence for the establishment of  The following data were extracted from the eligible study: first author's name, year of publication, country of origin, ethnicity, sample techniques, number of cases and controls, Hardy–Weinberg equilibrium (HWE) score, and allele and genotype frequencies, among other information. If the authors did not provide additional information, the studies were excluded.2.4p > 0.05 was considered to be consistent with HWE. Meta‐analysis was performed using RevMan 5.3 software . Pooled ORs (odds ratio) and their 95% CIs  were calculated to assess the association between CACNA1C rs1006737 and susceptibility to schizophrenia for the recessive model (GG vs. AG + AA), dominant model (GG + AG vs. AA), additive model (GG vs. AA), and allele model (G vs. A). Pooled ORs with Z‐test p < 0.05 were considered statistically significant. Statistical heterogeneity among studies was assessed by Cochran's Q‐test and the I2 metric. Cochran's Q‐test approximately follows a distribution with k‐1 degrees of freedom . The I2 metric was used and ranges from 0% to 100%. Low, moderate, large, and extreme heterogeneity corresponded to 0%–25%, 25%–50%, 50%–75% and 75%–100%, respectively. p < 0.05 and I2 > 50% were deemed to indicate significant heterogeneity. A fixed effect model  was used in the absence of heterogeneity; otherwise, a random effect model (using the DerSimonian and Laird's method) was applied. Sensitivity analysis was performed to evaluate the influence of each study on the overall pooled result by sequentially excluding each individual study. A funnel plot was generated to evaluate the potential publication bias using Stata 15.1 software . Furthermore, power analysis was performed by Power and Sample Size Calculation software .HWE was assessed for each study using the chi‐squared test. 33.1A flow chart of the literature search and selection process is shown in Figure The characteristics of each study are shown in Table We conducted a power analysis for detecting significant allelic associations; our total sample size and Asian sample size revealed a 100% power using OR values for the risk allele of 1.20，but the power for the European sample size was 83.1%.3.2We conducted a meta‐analysis of Asian populations, European populations, and total populations. ORs with corresponding 95% CIs for the association between the rs1006737 polymorphism in the CACNA1C gene and the risk for schizophrenia in the different populations that were studied are detailed in Figures p > 0.05 and I2 < 50%), the fixed effect model was applied to all the models. As shown in Figure p < 0.00001; GG + GA vs. AA: OR: 0.79, 95% CI: 0.67–0.93 p = 0.004; GG vs. AA: OR: 0.76, 95% CI: 0.64–0.90, p = 0.001; and G vs. A: OR: 0.85, 95% CI: 0. 81–0.90, p < 0.00001) were observed by pooling the night included studies.Nine studies including two European‐decent samples and seven Asian cohorts contributed 12,744 cases and 16,460 controls for the analysis of CACNA1C rs1006737 and schizophrenia. As no heterogeneity was detected under any genetic model .For European‐decent samples, only two studies including 1,455 cases and 4,425 controls were included. Using a fixed effect model, a significant difference was identified between patients and controls for the four models  using a fixed effect model but the dominant model  and additive model  showed no significant difference between patients and controls.For Asian samples, seven studies were included in the meta‐analysis. We observed a significant difference between patients and controls for the recessive model and allele model  were all <0.05. The results were replicated in the European population. As for the Asian population, only two models (GG vs. GA + AA and G vs. A) showed a significant difference with schizophrenia. Therefore, the overall meta‐analysis proves that there is a significant association between rs1006737 and schizophrenia, and allele A of rs1006737 is associated with the risk for schizophrenia at a comparable power within both populations. Our results are consistent with most previous studies  in each study, ranging from 0.041 in Han Chinese populations to 0.333 in European populations, we conducted heterogeneity analysis. To our surprise, no heterogeneity was found in our meta‐analysis between European and East Asian ancestries. Similarly, heterogeneity analysis was performed on Asian and European populations separately, and the same results were obtained. In addition, our meta‐analysis showed no publication bias.CACNA1C rs1006737 and schizophrenia in the world's populations.There are, however, limitations to the interpretation of our results. First, there are few studies included. Due to insufficient information provided in the original literature, several articles were not included in the meta‐analysis. Future research should include as much information as possible for more realistic results. Second, because the current research is only in Europe and Asia, the relationship between rs1006737 and schizophrenia in other ethnic groups cannot be determined. Therefore, there is an urgent need to conduct research on American, Oceanian, and African populations to understand the relationship between CACNA1C as a susceptibility gene for schizophrenia across world populations, but further investigations on its role in the pathogenesis of schizophrenia are warranted.Our findings contributed important evidence for the establishment of The authors declare no conflict of interest.Dongjian Zhu, Jingwen Yin, and Chunmei Liang were responsible for the study design, statistical analysis, and manuscript preparation. Xudong Luo, Dong Lv, Zhun Dai, and Susu Xiong managed the literature searches and analyses. Jiawu Fu, You Li, and Juda Lin were involved in evolving the ideas. The study was supervised by Zhixiong Lin, Yajun Wang, and Guoda Ma.https://www.sciencedirect.com/, Wiley Online Library at https://onlinelibrary.wiley.com/, PubMed at https://www.ncbi.nlm.nih.gov/pubmed, Cochrane Library at https://www.cochranelibrary.com/, and Wanfang data resource database at http://www.wanfangdata.com.cn/index.html. Additional datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.The data that support the findings of this study were derived from the following resources available in the public domain: Science Direct at  Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Endothelin (ET)‐1 is a potent vasoconstrictor peptide produced by endothelial cells and associated with vascular dysfunction and cardiovascular disease. Lys198Asn is a single‐nucleotide polymorphism (SNP) of gene encoding ET‐1 (EDN1). It is hypothesized that it might have a role in altering ET‐1 and ultimately leading to vascular dysfunction and ischemic stroke. We therefore conducted a meta‐analysis to investigate the association between Lys198Asn polymorphism of EDN1 gene and susceptibility of ischemic stroke.This meta‐analysis was conducted according to the guidance of the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) statement. We searched PubMed, Google Scholar, Embase, Web of Science, J‐STAGE, and China National Knowledge Infrastructure (CNKI) for relevant studies. The association between Lys198Asn polymorphism and ischemic stroke susceptibility was evaluated by calculating the pooled ORs and 95% CIs.p = .03; I2 = 41%) or dominant model . There was no evidence of publication bias in either of the recessive model  or dominant model . A subgroup analysis based on subtypes of ischemic stroke showed that Lys198Asn SNP was only associated with large vessel infarction but not with lacunar infarction caused by small vessel disease. A subgroup analysis based on ethnicity revealed that the Lys198Asn polymorphism of the EDN1 gene was associated with ischemic stroke only in Caucasians.Our analysis included 1,291 cases and 2,513 controls. Meta‐analysis established a significant association between Lys198Asn SNP of EDN1 gene and ischemic stroke when assuming either recessive model ‐1 is a potent vasoconstrictor peptide produced by endothelial cells and associated with vascular dysfunction and cardiovascular disease. Lys198Asn is a single‐nucleotide polymorphism of gene encoding ET‐1 (EDN1). It is hypothesized that it might have a role in altering ET‐1 and ultimately leading to vascular dysfunction and ischemic stroke. We therefore conducted a meta‐analysis to investigate the association between Lys198Asn polymorphism of EDN1 and susceptibility of ischemic stroke. The present meta‐analysis suggests that Lys198Asn polymorphism of EDN1 gene is associated with an increased risk for ischemic stroke. Approximately 70% of new strokes are ischemic in origin, 51% stroke death, and 58% of stroke disability‐adjusted life years are because of ischemic stroke  contains 5 exons and spans ∼6.8 kb of genomic Deoxyribonucleic Acid (DNA) and is located on chromosome 6p23‐p24. Transcription of the human EDN1 gene yields a 2.8‐kb messenger Ribonucleic Acid (mRNA) that encodes a 212‐amino acid precursor protein, pre‐pro‐ET‐1  statement  for studies published from January 2000 to September 2018. Searches were conducted using the keywords “EDN1 polymorphism” or “Endothelin‐1 gene polymorphism” or “rs5370 polymorphism” or “Lys198Asn polymorphism” in combination with “stroke” or “ischemic stroke” or “cerebrovascular disease” or “cerebral infarction.” Titles and abstracts were screened and the full text of any that were considered to possibly meet the inclusion criteria were then obtained. The cited references of retrieved articles were manually checked to identify any additional eligible trials. Two authors (GN and RO) screened and retrieved reports and excluded irrelevant studies. When uncertainty about eligibility criteria arose, it was solved by discussion with all the authors.2.2We included studies that were conducted on human subjects, and the studies were searched without any limitations on language. In this meta‐analysis, all included studies met the following criteria: (a) case–control studies focused on the association between rs5370/Lys198Asn polymorphism and ischemic stroke susceptibility, (b) patients with ischemic stroke were diagnosed with neuroimaging confirmed by neurologist, and (c) there were sufficient data of the genotypes in the case–control groups to evaluate the ORs and 95% CIs. The exclusion criteria were as follows: (a) publications with overlapping cases and controls from the similar study, (b) no genotypic data available, and (c) publications with patients with cardioembolic stroke or hemorrhagic stroke.2.3The relevant data from each study were independently extracted by two reviewers (GN and RO) using a standardized, structured form. Extracted data included the first author, type of design, site of study, patient ethnicity, year of publication, sample size of cases and controls, control design, Hardy–Weinberg equilibrium, source of DNA, genotyping method, data of the genotypes in the case–control groups, type of ischemic stroke, mean age of participants, mean BMI of participants, and male to female ratio.The methodological quality of each study was assessed independently by two reviewers (GN and RO) using the parameters previously used by Kumar et al.  In this 2.4Q test and I2 test. The presence of p values above 0.1 or I2 more than 50% was considered as an indicator of significant heterogeneity. When there was no heterogeneity, we selected the fixed effects model and, in the presence of significant heterogeneity, we selected the random effects model to calculate the effect size. Genotypes at each locus were coded as follows: TT = mutant homozygotes, TG = heterozygotes, and GG = wild homozygotes. Two genetic models were examined, including dominant model (TT + TG vs. GG), and recessive model (TT vs. GG + TG). Sensitivity analysis was performed to examine the stability of analysis. Subgroup analysis was performed based on ethnicity and stroke subtype. Meta‐regression was performed to determine whether methodological quality of study have role in effect size associated with Lys198Asn polymorphism. Egger's linear regression test and Begg's test were used for the identification of publication biases. Statistical analysis was performed using comprehensive meta‐analysis software .In the majority of selected studies, the authors presented odds ratio (OR) and 95% confidence intervals (CIs) for association between Lys198Asn polymorphism and ischemic stroke susceptibility. In study where OR and 95% CI was not available, we calculated the OR and 95% CI comparing the number of genotypes in cases and controls. The association between Lys198Asn polymorphism and ischemic stroke susceptibility was evaluated by calculating the pooled ORs and 95% CIs. Heterogeneity between the included studies was determined using Cochran's 33.1The results of the systematic literature search and selection are summarized in Figure 3.2Our research included studies from two continents and five different countries. Two studies were from China  or dominant model of inheritance . Forest plot of the result for recessive model demonstrated in Figure p = .23; Begg test: p = .85) or dominant model . Funnel plot for detection of publication bias in recessive model and dominant model is demonstrated in Figures In dominant model, there was significant heterogeneity, so we applied random‐effects model to estimate pooled ORs and 95% CIs. In recessive model, there was no heterogeneity, so we applied fixed‐effects model. Meta‐analysis established a significant association between Lys198Asn polymorphism of EDN1 gene and ischemic stroke when assuming either recessive model of inheritance . However, in the dominant model, quality scores were significant predictors of the effect size (p = .02). Meta‐regression plot for recessive model and dominant model is shown in Figures Meta‐regression analysis was used to explore whether the methodological quality scores of the included studies play an important role in the association between the Lys198Asn polymorphism of the EDN1 gene and the risk of ischemic stroke. In recessive model, we found that quality scores were not significant predictors of the effect size for the association between Lys198Asn polymorphism and ischemic stroke risk . This may be due to a number of issues, including sample size, heterogeneous pathophysiology, and silent SVD. Silent SVD is defined as hyperintensities of the white matter that correlate with an asymptomatic cerebral infarction. Many cases of lacunar infarctions due to SVD are silent. As these cases often do not present to the hospital, they are excluded from the analysis. Complex interactions between genetic and nongenetic factors have been reported to play an important role in the progression of ischemic stroke  demonstrating the association between Lys198Asn polymorphism and ischemic stroke. We conducted a comprehensive search, which was not only limited to English literature but also included one paper published in Chinese language. Our analysis included patients of both Asian and Caucasian ethnicity. There was no deviation from Hardy–Weinberg Equilibrium (HWE) in control subjects in all included studies. We performed analysis in both recessive and dominant model. In recessive model, there was no evidence of heterogeneity. However, in dominant model, minimal heterogeneity was seen. Based on the subgroup analysis and the meta‐regression analysis, it was evident that the heterogeneity was due to the difference in the study population and the methodological quality of the included studies. Finally, publication bias was not obvious in our analysis.There were some limitations in our study. Some studies included in the meta‐analysis had a small sample size and may have provided inconsistent results due to low statistical power. Among the included studies, different methodologies were used for genotyping and the selection of controls. The haplotype analysis, which plays a pivotal role in genetic association studies, was not performed. The gene‐environment interaction and the gene‐gene interaction were not studied in this meta‐analysis. Owing to the above limitations, the results of this meta‐analysis should be interpreted with caution.5Our meta‐analysis suggests a significant association of Lys198Asn polymorphism of EDN1 gene with ischemic stroke. Lys198Asn polymorphism might influence on disease susceptibility and can also be an important marker of risk for ischemic stroke. Large cohort studies with gene–gene and gene–environment interactions in diverse ethnicity should be conducted to reach more reliable conclusion.The authors declare no conflicts of interest.GN and BKY designed the study. GN and RO carried out literature search, review, and selection. GN and HD carried out the statistical analysis and drafted the manuscript. All authors were involved in revising the manuscript critically for important intellectual content. All authors read and approve the final manuscript.This research does not include human participants.For this type of study formal consent is not required.


P = .071; I2 = 41.7%). This association was not modified by the glaucoma type of the included patients. A significant association was observed in case–control design studies, but not in cohort design studies. Little evidence of publication bias was found. The findings of this meta-analysis suggest that migraine can significantly increase the risk of the development of POAG. However, the cohort study design failed to identify this association. Whether migraines can significantly increase the risk of developing POAG is still controversial.Migraine is increasingly being reported as a risk factor for primary open angle glaucoma (POAG). However, studies aimed to investigate this association yielded conflicting results. To assess the consistency of the data on the topic, we performed a systematic review and meta-analysis. A systematic literature search from Embase, Web of Science, and PubMed was performed to identify relevant studies on the relationship between migraine and POAG. Random effects models were used to estimate the pooled relative risks (RRs) with 95% confidence intervals (95% CIs) in this meta-analysis. A total of 11 studies meeting the inclusion criteria were included in this meta-analysis. Our findings showed an RR of developing POAG of 1.24 (95% CI = 1.12–1.37) in migraine patients. No evidence of significant heterogeneity was detected across studies ( The main risk factor for POAG is old age, with an increasing risk for POAG of 1.73 for each decade increase in age over 40 years. In addition, ethnic background , family history of glaucoma, elevated intraocular pressure (IOP), and high myopia are all known risk factors for POAG.–8Glaucoma is a multifactorial condition characterized by a progressive optic neuropathy and distinctive visual field loss and has become the most common cause of irreversible blindness worldwide. found that subjects with migraine were 1.2 times more likely to have POAG compared with those without migraine, even after adjustment for the risk factors such as gender, age, monthly income, and level of urbanization of the community. However, another study on Chinese cohorts reported that migraines did not increase the risk of POAG.Recent epidemiologic studies have suggested that migraine may be associated with POAG, although these findings have been inconclusive and conflicting. For example, Lin et alTo date, the pathogenesis of POAG is not totally understood. A clearer understanding of the association between migraine and POAG may therefore provide insights into the pathophysiology of this disease. For this reason, we conducted this meta-analysis of the available published literature to examine the potential relationship between migraine and POAG. The major drawback of cross-sectional studies is that they cannot establish a clear, temporal relationship between exposure and outcome. Thus, only case–control and cohort studies were included in this meta-analysis.22.1 A systematic literature search from Embase, Web of Science, and PubMed was performed to identify relevant studies on the relationship between migraine and POAG published up to October 2017. The following search terms were used: glaucoma, IOP, ocular hypertension, intraocular hypertension, migraine, cephalagra, and hemicrania. Additional information was obtained by searching Google Scholar. We also screened the reference lists of all retrieved trials to identify studies not yet included in the computerized databases. The search did not restrict the language, methodological filter, or publication year.The study was performed according to the recommendation of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.2.2The following inclusion criteria were met in the present meta-analysis: the study design was a cohort or case–control design; the study evaluated the association between migraine and POAG; ORs or relative risks (RRs) estimates with their 95% confidence intervals (CIs) were provided . The following exclusion criteria were also considered: studies focused on angle-closure glaucoma or secondary glaucoma rather than POAG; crude data did not provide RRs or ORs or sufficient data for their calculation; the reports were letters, reviews, case reports, or abstracts, or reports with incomplete data. If multiple publications from the same study population were available, then duplicate analyses were checked and only the most recent publication was included.2.3 The variables of the methods used for selecting study subjects, the methods used for measuring outcomes and exposure, the methods used to control for confounding, design-specific sources of bias, potential conflicts of interest, and statistical methods were examined.The following information was extracted by 2 independent reviewers: publication year, first author, study design, the ascertainment method of migraines, definition of glaucoma, age of subjects, sample size, the provided adjusted ORs or RRs with their 95% CIs or the data for calculating the ORs, the adjusted variables, and the methods for selecting study participants. The study quality was assessed by 2 reviewers using the tool described by Sanderson et al.2.4,14 We evaluated the presence of among-studies heterogeneity using the χ2 and I2 tests. For the χ2 test, P < .05 was considered to represent significant heterogeneity. For I2, a value >50% indicated significant heterogeneity. We conducted a stratified analysis based on the study's design , the methods used to determine migraines , the geographical area , the type of glaucoma ), and the adjusted variables for age and sex, diabetes, and hypertension. The reliability of the outcomes of the meta-analysis was determined by a sensitivity analysis performed by omitting each individual study one at a time. Finally, publication biases were detected using the Begg and Egger tests and assessed using Begg funnel plots.,17P < .05 was considered statistically significant in the test results of overall effect.We conducted this meta-analysis using the Stata software package . We assessed the correlation between migraine and POAG by estimating the pooled RR with 95% CI using the random-effects model. Using the rare disease assumption, RR in cohort studies and the OR in case–control studies were integrated to estimate the pooled RR.33.1; no focus on the relationship between the migraine and POAG (n = 3)–21; comparison of the incidence of migraine between familial and sporadic glaucoma (n = 1); no provision of RRs or ORs or data for their calculation (n = 3)–25; letter (n = 1); not case–control or cohort design (n = 5).–31 Ultimately, 11 studies,,10,32–40 including 3 cohort or nested case–control,,32,35 and 8 case–control studies,,34,36–40 were included in the present meta-analysis. The detailed process of data selection is described in Fig. A total of 1942 papers were identified through literature searches of 3 databases. Of these, 445 were duplicate publications and were removed. A further 1472 papers were also excluded following title and abstract review. Of the remaining 25 publications retained for further assessment and a full-text review, nine papers were excluded for the following reasons: review (n = 1)3.2–40 and 7 by medical records.,10,32–36 The methods used to determine glaucoma varied across the studies. Most studies defined POAG based on glaucomatous visual field loss and glaucomatous optic neuropathy. Several studies included other additional factors, such as open angle, elevated IOP, and the exclusion of angle closure or secondary glaucoma. A detailed quality assessment of all the included studies is displayed in Table Table 3.3P = .071; I2 = 41.7%). The results of a series of prespecified stratified analyses conducted according to study design, the methods used to determine migraine, geographical area, type of glaucoma, and the adjusted variables are presented in Table The pooled effect estimates and the heterogeneity tests of the association between migraine and POAG are presented in Fig. 3.4PBegg test and PEgger test were .533 and .272, respectively, indicating a low probability of publication bias. The funnel plot for the studies is presented in Fig. The robustness of the increased risk of POAG incidence due to migraine was evaluated by performing a sensitivity analysis by omitting one study at a time and then calculating the pooled RR for the remaining studies. The results of this “leave-one-out” sensitivity analysis showed that the corresponding global estimation did not change by the deletion of any single study, indicating the robustness of this meta-analysis. We used the Begg funnel plot and Egger test to detect potential publication bias. The value of 4,4,6 but the investigation continues. Several publications have reported a correlation between migraine and POAG,32; however, no definitive link has yet been established. With this in mind, we conducted this meta-analysis to evaluate this potential relationship. Our examination of the 8 case–control and 3 nested case–control/cohort studies revealed a statistically significant relationship between migraine and POAG. Subjects who suffered from migraine had a 24% higher risk of developing POAG when compared to those who had never suffered from migraine.Many risk factors for the development of POAG have been identified, used ocular hypertension subjects as controls, which differed from the other studies that used normal subjects. However, the sensitivity analysis that excluded the Landers et al study also showed no significant change in the pooled RR. Similarly, the publication bias analysis showed a low probability of publication bias, which also implied the robustness of this meta-analysis.The evidence linking migraine and POAG was further strengthened by performing sensitivity and publication bias analyses. Omission of individual studies one at a time and then recalculating the pooled RR for the remaining studies revealed insignificant changes in the corresponding estimates when any single study was deleted, indicating the high stability and reliability of this study. Of note, of the included studies, the study by Landers et alThe stratified analyses revealed a more prominent relationship between migraine and POAG in the case–control studies than in the longitudinal studies. Several reasons might explain this difference. First, the small number of included longitudinal studies could have led to an insufficient statistical power to detect a positive association between migraine and POAG in those studies. Second, for longitudinal studies, survival bias may occur, which could mask a real association. Separate analyses of the migraine ascertainment method by medical records and self-report indicated that patients with migraines ascertained by medical records had a 27% increased risk of POAG, whereas the risk of POAG was nonsignificant in those whose migraines were ascertained by self-reports. Self-reporting has its own limitation of recall bias, which might also mask the real association. Among the included studies, some only included POAG patients (IOP > 21 mm Hg), whereas others included both POAG patients (IOP > 21 mm Hg) and NTG patients (IOP ≤ 21 mm Hg). The results suggested that migraine increased the risk of POAG but it also increased the risk of NTG. Notably, the results from the subgroup analyses that were adjusted for age and sex, diabetes, and hypertension, showed a significant association between migraines and POAG. These studies proved to be more reliable than those used in the overall analysis because the true association between migraines and POAG might be diluted by studies that have used poor methodologies. The dysregulation of retinal vascular and poor blood flow at the optic nerve head is associated with the incidence of glaucoma. Patients with NTG have reduced blood flow velocities and higher resistive indices in most retrobulbar vessels. Similarly, migraine is also viewed as a vascular disorder to some extent. Charles defined migraine as a disorder with both vascular and neural involvement as part of its pathophysiology. The pain of a migraine is attributed to the activation of the trigeminovascular system. Activation of nociceptors leads to the release of certain vasoactive peptides and inflammatory mediators that act directly to decrease the diameter of cerebral blood vessels. These changes in blood vessel caliber are viewed as indicative of vascular dysregulation or vasospasm. Therefore, potential pathophysiological mechanisms shared in common might form the link between glaucoma and migraine. Some researchers have posited that the relationship between the migraine and POAG is due to a common vasospastic mechanism.Our findings suggest an association between migraine and the risk of POAG. However, to date, no mechanisms have been elucidated that could support the notion that migraine could increase the risk of the progression of POAG. One possible explanation might be vascular regulation, as the multifactorial nature of glaucoma is well known and vascular factors play a key role in its pathophysiology, and especially of NTG.Our meta-analysis has several advantages. First, it is the first and the largest analysis, to date, that explores the relationship between migraine and POAG and it represents a comprehensive literature search that included as many relevant studies as possible to provide a more precise conclusion. Second, the sensitivity analysis and the publication bias analysis all confirmed the reliability and robustness of the pooled results. Third, the studies included in this meta-analysis revealed no obvious heterogeneity, indicating a very good homogeneity among the currently available studies. Fourth, study-level data allowed meaningful stratified analyses. This analysis therefore provides the most up-to-date information in the area of the migraine and POAG relationship. The quality of most of the included studies is relatively high. However, there are still some design-specific sources of bias in most of the studies, and the methods for measuring exposure and outcome is not uniform among the different studies.Several limitations of this meta-analysis should also be acknowledged. First, the potential biases in the included studies were not considered. For example, the case–control designs could be subject to selection bias, and the longitudinal studies could be subject to survival bias. Second, in some of the studies, migraine was ascertained by self-reporting, which could have introduced a recall bias. More likely, some migraine patients could be misclassified as nonmigraine subjects. Third, not all the studies controlled for potential confounding variables. However, the results from subgroup analysis restricted to studies adjusted for relative covariates showed a significant association between migraine and POAG, and this is more reliable than the association reported for the overall analysis because the real association might be diluted by studies with poor methodologies. Fourth, some of the subgroup analyses were performed using studies with small numbers and should be interpreted with caution. Fifth, the number of cohort studies included was relatively small and the durations of follow-up of these studies might not be sufficiently long to detect any associations. Finally, in this meta-analysis, the study quality was assessed using the tool described by Sanderson et al.In conclusion, the current limited evidence suggests that migraines can significantly increase the risk of developing POAG. However, the cohort study design failed to identify this association. Whether migraines can significantly increase the risk of developing POAG is still controversial. Better designed longitudinal studies with longer follow-ups are required in the future to confirm the association between migraines and POAG.Conceptualization: Chang Xu.Data curation: Jingjing Li.Formal analysis: Jingjing Li.Methodology: Zhi Li.Project administration: Chang Xu.Resources: Zhi Li.Supervision: Xiaochun Mao.Writing – original draft: Chang Xu.Writing – review & editing: Xiaochun Mao.


This review summarizes a selection of epidemiologic research assessing the associations between carbohydrate intake and cancer incidence and survival. Evidence for plausible biological mechanisms is also considered.The mechanistic paradigm explaining the relationship between carbohydrates and cancer risk has been contested by numerous observational studies.Carbohydrates have conventionally been ascribed a deleterious role in the field of cancer research due to previous preclinical findings. A breadth of studies suggests that complex carbohydrate intake is inversely associated with risk of a number of cancer types. Data from studies assessing simple carbohydrates and cancer risk are mixed. Furthermore, recommendations for subsequent studies are framed. An estimated 606,880 deaths in the USA will be attributable to cancer in 2019 ••. Diet Carbohydrate intake is one aspect of diet that has been hypothesized to modulate cancer risk depending on the amount and type consumed. Carbohydrates are a broad category of biomolecules, which, in their monosaccharide forms, function as preferred cellular energy substrates . Aside fEarly findings from experimental in vitro and in vivo models enhanced understanding of the acute physiological effects of carbohydrates. On the basis of these discoveries, a series of etiological frameworks tying their consumption to cancer risk were hypothesized. Owing to the work of Otto Warburg, a deleterious role, albeit a simplistic one, was ascribed to dietary carbohydrates; a hypothesis that, as we shall examine, has seemingly been only moderately supported by observational data. A more coherent framework, primarily implicating insulin-signaling networks, was born out of subsequent research. These hypotheses, detailed below, have provided a foundation that has motivated a vast collection of the observational studies we address in this review.Exploitation of glycolytic pathways and their corresponding machinery are appreciable metabolic adaptations that cancer cells use to enhance and perpetuate their survival and proliferative capabilities. Specifically, tumor cells transition from aerobic cellular respiration to aerobic glycolysis as the primary energy-harvesting mechanism . This hiThe insulin/IGF-1 signaling axis plays a critical role in glucose metabolism and subsequently modifies cellular proliferation and growth . InsulinMany anabolic functions of the IGF-1 axis, such as the activation of PI3K/Akt, parallel those of the insulin-IR signaling cascade , 20. DysConsumption of simple sugars, glycemic index (GI) and glycemic load (GL), has been hypothesized to increase cancer risk, although findings have been mixed. Makarem et al. analysis of the Framingham cohort reported no significant associations between GI or total carbohydrates and risk of several adiposity-related cancers . NonetheAn ecological analysis undertaken by Grasburger and his colleagues on observational data collected across 39 European countries reported weak and moderate positive associations between refined sugar consumption and CRC incidence in men and women, respectively . GiovannUsing GL as a predictor, Zelenskiy et al. case-control study reported significantly increased odds of CRC in the second through fourth upper quartiles of GL consumption . The effArguably, the most comprehensive set of meta-analyses conducted to date, by Reynolds et al., included 185 studies that examined several carbohydrate predictors  and their associations with a range of clinical outcomes, including incidence of many adiposity-related cancers  and total cancer mortality. Both randomized controlled trials (RCTs) and prospective cohort studies were considered. Results from the meta-analysis on GI and CRC incidence, which included 10 studies, reported a non-significant but 5% increased risk associated with greater consumption of higher GI foods . The onlStudies examining the relationship between high consumption of simple carbohydrate and the risk of PCa have been inconsistent. While some studies suggested a positive association between simple carbohydrate consumption and risk of PCa, others reported null associations. The two longitudinal studies cited by Makarem et al. in their systematic review come from Giovannucci et al. and Drake et al. who reported on the Health Professionals Follow-Up and Malmö Diet and Cancer cohorts, respectively. Notably, Giovannucci et al. found a significantly reduced risk of advanced PCa associated with higher fructose consumption . In contThe data on the risk of female reproductive cancers in relation to simple carbohydrate intake, primarily GL and GI, have been inconsistent. The ecological associations reported by Grasburger et al. indicated moderate positive linear relationships between the consumption of refined sugar and breast cancer . An earlMullie et al. were the first to conduct a meta-analysis that adjusted for ER status. However, they found that ER status did not change relative risk estimates and reported modest increases in risk between the highest versus lowest levels of GI and GL regardless of ER status . In contMakarem et al. 2018 systematic review identified 11 prospective cohort studies that examined the following carbohydrate variables in relation to risk of breast, endometrial, and ovarian cancers: total sugar, added sugar, fructose, sucrose, sugary foods, and sugar-sweetened beverages ••. The sCiting evidence of disparate CRC incidence among rural African and Western populations, Denis Burkitt postulated fiber intake as responsible for these observations given the ubiquitous and significantly higher consumptions exhibited by the former group . Since tInitial epidemiologic research examining fiber and primary prevention of CRC risk was mixed. A meta-analysis of 13 prospective cohort studies by Park et al. was unable to ascertain a significant inverse relationship between fiber intake and CRC risk . An analEvidence of a protective association with high fiber intake emerged from an analysis by Murphy et al. of EPIC data. Specifically, every 10-g increase in total fiber consumption was associated with a 13% reduction of risk . In a mePCa progression and risk have been previously correlated to the IGF-1 system. Its associations with increased concentrations of IGFBP and IGF-1 were demonstrated through several case-control studies –66. A stMore recent meta-analyses on epidemiologic data suggested a null association between fiber intake and PCa risk. Sheng et al. meta-analysis of 17 observational studies reported a significant protective association between fiber and PCa risk when considering only case-control studies . When exA pooled analysis of seven individual case-control studies participating in the International Head and Neck Cancer Epidemiology Consortium (INHANCE) characterized dietary patterns and assessed their associations with oropharyngeal and laryngeal cancers. Results of their analysis revealed that an “antioxidants and fiber” pattern was associated with a significant inverse association with these cancer types . In a siThe most comprehensive longitudinal cohort study of complex carbohydrates and head and neck cancer risk to date comes from Lam et al., whose analysis on the NIH-AARP Diet and Health Study cohort revealed a significant inverse association between fiber and whole grains with head and neck cancer risk over the 11-year follow-up period . Resultsn = 20) and included both pre- and post-menopausal cohorts.The systematic review and meta-analysis by Chen et al. included 24 individual observational studies and reported a significant inverse association between fiber intake and breast cancer risk •. NotablThe scope of evidence linking carbohydrate intake to cancer recurrence and survival is limited. However, a selection of studies addressing survival outcomes is summarized below.An analysis of the EPIC cohort that assessed pre-diagnosis associations between dietary fiber and survival of non-metastatic CRC cases reported null results . HoweverSong et al. demonstrated dose-response patterns and significant reductions in mortality risk with high fiber intake in CRC survivors pooled from the Nurses’ Health Study and the Health Professionals Follow-up Study cohorts. Fully adjusted post-diagnosis models suggested a 22% and 14% reduced risk of CRC-specific and all-cause mortality, respectively, for each 5-g increase in dietary fiber ••. With A prospective cohort study of head and neck cancer patients by Arthur et al. examined associations between pre- and post-treatment carbohydrate intake and recurrence, disease-specific, and all-cause mortality. Results indicated that high pre-treatment intake of total carbohydrate, total sugar, glycemic load, and simple carbohydrate foods  were significantly associated with increased risk of all-cause mortality ••. TotalA nested case-control study conducted by Emond et al. investigated the association between carbohydrate intake and breast cancer recurrence . Cases wA longitudinal study in ovarian cancer survivors suggested an inverse association between complex carbohydrate consumption and mortality . PlaydonThe majority of the research on carbohydrates and cancer risk reviewed herein was derived largely from case-control and cohort designs, which makes it impossible to draw definitive conclusions of causality. Moreover, the breadth and strength of the evidence were most convincing for associations between fiber and complex carbohydrate consumption with CRC risk, although a similar association is suggested in other cancer types. Consistent with the findings of this review, the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) now recognizes dietary fiber as a probable protective agent against colorectal carcinogenesis ••. The dThere is an urgent need for additional prospective cohort studies and RCTs, particularly for cancer types other than CRC and of tertiary cancer prevention. There was significant heterogeneity across the studies reviewed and thus adopting consistent methodologies for studying the associations between carbohydrate intake and cancer risk are needed. Doing so will lead to more consistent results that can be used to design rigorous RCTs that will ultimately inform public health and clinical recommendations. Specifically, consistent examination of various subtypes of carbohydrates should be considered in future research. Many studies considered carbohydrates as either an all-encompassing predictor or in stratified classifications , albeit at times confounded by inappropriate groupings . Moreover, it must be noted that obesity is an accepted etiologic factor implicated in several of the cancer types considered in this review ••. As suClinical recommendations based off this review need be tempered. The data do not support any conclusion regarding the feasibility or efficacy of extreme carbohydrate-restricting dietary protocols, such as the ketogenic diet, despite the fact that several experimental mouse models have highlighted its benefits when implemented concomitantly with pharmacological treatments. Several recent reviews on the topic of the ketogenic diet and cancer have been published, and thus, it was not considered in the current review , 83, 84.In sum, the body of evidence related to carbohydrates and cancer risk is strongest for the association between fiber and CRC, where increased consumption is associated with reduced risk of disease development and mortality after diagnosis. Results of studies examining complex carbohydrates and risk of cancer types other than CRC generally suggest a protective association, whereas results of studies examining simple carbohydrates and cancer risk are mixed. Future prospective studies and RCTs that include homogenous study populations and consistency in study design and methods of modeling carbohydrate intake are urgently needed. Lastly, given the rapidly growing population of adults living with a history of cancer worldwide, more research should be conducted to determine how varying amount and type of carbohydrates may impact outcomes after cancer diagnosis, including recurrence, survival, second primary cancers, and health-related quality of life .


The exact shape of the dose-response relationship between maternal body mass index (BMI) and the risk of congenital heart defects (CHDs) in infants has not been clearly defined yet. This study aims to further clarify the relationship between maternal obesity and the risk of CHDs in infants by an overall and dose-response meta-analysis. PubMed, Embase, and Web of Science databases were searched to identify all related studies. The studies were limited to human cohort or case-control studies in English language. Random-effect models and dose-response meta-analysis were used to synthesize the results. Heterogeneity, subgroup analysis, sensitivity analysis, and publication bias were also assessed.2 increase in maternal BMI. A nonlinear relationship between maternal BMI and risk of infants with CHDs was also found (p=0.012). Nineteen studies with 2,416,546 participants were included in our meta-analysis. Compared with the mothers with normal weight, the pooled relative risks (RRs) of infants with CHDs were 1.08 (95% CI=1.03-1.13) in overweight and 1.23 (95% CI=1.17-1.29) in obese mothers. According to the findings from the linear meta-analysis, we observed an increased risk of infants with CHDs  for each 5 kg/m The results from our meta-analysis indicate that increased maternal BMI is related to increased risk of CHDs in infants. Congenital heart defects (CHDs), which account for nearly one-third of all major congenital anomalies, are the most common birth defects in newborns . As the Obesity has become a major public health problem that challenges both developed and developing countries –23. DataAs the dose-response meta-analysis is a reliable quantitative measure of causality, in our study, we conducted a dose-response meta-analysis on maternal BMI and the risk of CHDs in infants by synthesizing the results of published original studies. Our aim was to clearly delineate the shape of the dose-response relationship between maternal BMI and CHDs in infants and to examine the possibility of the nonlinear relationships.We systematically searched PubMed, Embase, and Web of Science databases to April 31, 2018, for studies on the relationship between maternal BMI and infants with CHDs. The following search strategy was used:  AND (overweight OR obesity OR body mass index OR BMI). Additional possible relevant publications were identified by reviewing the references lists of retrieved articles and published meta-analysis. The searched studies were strictly limited to human cohort studies or case-control studies in English language.Studies satisfying the following criteria were included in our meta-analysis: (1) cohort or case-control study design; (2) having clear BMI categories of prepregnancy or early pregnancy; (3) CHDs or one of the CHD subtypes as outcome; (4) relative risk (RR) or odds ratio (OR) with 95% confidence intervals (CIs) available or having sufficient published data to calculate them. In addition, the study for dose-response analysis had to report the estimates of at least three BMI classifications. The Newcastle-Ottawa Scale in which the star system ranges from 0 to 9 was used to assess the methodological quality of studies, and a study awarded seven or more stars was considered high-quality and was included in the meta-analysis , 30. WheData were extracted by 2 independent investigators (X.L. and W.Y.), and any disagreement was resolved through consensus from another author (L.J.). The following variables were collected from each publication: first author's name, publication year, study location, study period, study sample size, number of cases, study design, BMI category and the corresponding risk estimate, confounding factors adjusted in multivariable analysis, and study conclusion. Considering that the rate ratio, risk ratio, and hazard ratio can be used as a valid estimate of the relative risk and the meaning of the odds ratio is similar to the relative risk, then we used the RRs to report the results for convenience. In order to reduce the impact of covariates, the adjusted RRs in multivariate analysis were preferentially extracted.The average BMI corresponding to each classified RR was calculated by the midpoint of the upper and lower boundary of each category. In the case where the highest category or the lowest category was the open interval, we assumed that they had the same amplitudes as the adjacent category . When a 2; normal weight, 18.5-24.9 kg/m2; overweight, 25.0-29.9 kg/m2; obesity, ≥30.0 kg/m2) [ I2 statistic and the Q-test were used to assess the heterogeneity across studies, and I2 values of 0, 25%, 50%, and 75% were considered indicative of no, low, moderate, and high heterogeneity, respectively [We conducted separate meta-analysis to calculate the pooled RRs and 95% CIs for overweight and obese mothers versus normal-weight mothers. For the category of BMI, we used the classification standard of WHO  , 34. The0 kg/m2) . The I2 ectively . Conside p value for nonlinearity [A two-stage random-effect dose-response meta-analysis, which required the variables of cases, person-years, mean level of BMI, and the corresponding RR in each category, was used to depict the trend from the relevant log-RRs estimated across BMI categories, considering the heterogeneity between studies. In the inearity . p value less than 0.05 was considered statistically significant, except for the Q-test (p<0.10) because of the low power of the test.In addition, we conducted sensitivity analysis, in which one study involved in the meta-analysis was eliminated at a time and the rest pooled to evaluate the stability of our results . EvidencOur meta-analysis included 6 cohort studies , 41–43 a I2=54.5%  and 62.7%, while the pooled RR and the I2 statistic for studies conducted outside the United States were 1.04 (95% CI=0.99-1.10) and 30.4%, which demonstrated that American studies resulted in the heterogeneity  for maternal overweight and some evidence of heterogeneity across studies was found withI2=54.5% . Subgrouogeneity .I2 = 48.3%) . No evidence of high heterogeneity was found for the category of obesity (= 48.3%) . When st= 48.3%) .2 increase in maternal BMI was shown in this meta-analysis. When stratified by study design, it was found that the risk of infants with CHDs increased by 7% for every 5 kg/m2 increase of maternal BMI, in both cohort studies  and case-control studies   .p=0.012). Compared with BMI=22.05 kg/m2, the pooled RRs (95% CIs) of infants with CHDs were 1.03 (95% CI=1.02-1.04), 1.08 (95% CI=1.06-1.10), 1.18 (95% CI=1.16-1.21), 1.36 (95% CI=1.30-1.42), and 1.42 (95% CI=1.34-1.50) for BMI=25, 30, 35, 40, and 45 kg/m2, respectively. The evidence of significant nonlinear relationship was also observed in cohort studies (p=0.015) when adjusting the factor of study design. At the points of BMI=25, 30, 35, 40, and 45 kg/m2, the corresponding RRs (95% CIs) for cohort studies were 1.02 (95% CI=1.01-1.04), 1.13 (95% CI=1.10-1.16), 1.21 (95% CI=1.16-1.25), 1.42 (95% CI=1.31-1.54), and 1.50 (95% CI=1.36-1.65), respectively (As shown in ectively .p=0.346), maternal obesity group (p=0.744), and dose-response group (p=0.605)  .In a sensitivity analysis in which one study at a time was eliminated and the remaining analyzed, the pooled RRs of infants with CHDs ranged from 1.07 to 1.09 for maternal overweight group, from 1.21 to 1.24 for maternal obesity group, and from 1.15 to 1.17 for dose-response analysis group separately, which demonstrated that the pooled estimates were steady and not affected by a single study.2 increase of maternal BMI is accompanied by a 7% increment of risk of infants with CHDs, and a significantly nonlinear relationship between maternal BMI and infants with CHDs risk was observed (p=0.012). When stratified by study design, the pooled RR of infants with CHDs increased by 7% per 5 kg/m2 increase of maternal BMI, for both cohort and case-control studies. The evidence of significant nonlinear relationship between maternal BMI and risk of infants with CHDs was also found in cohort studies (p=0.015).In the present meta-analysis, we discovered an increase of 8% risk of infants with CHDs in maternal overweight group and an increase of 23% risk in maternal obesity group compared with the mothers with normal weight. Subgroup analysis by study design showed that the significant association between maternal overweight and increased risk of infants with CHDs existed only in case-control studies, while the significant association between maternal obese and increased risk of infants with CHDs existed in both cohort studies and case-control studies. Dose-response meta-analysis showed that each 5 kg/mOur findings are similar to meta-analysis by Cai et al., who examined the association between maternal BMI and CHDs in offspring and reported a similar summary for overweight and obese individuals . HoweverGCLC) gene (rs6458939) significantly increased the risk of conotruncal defects (CTDs) in infants, compared with those obesity mothers who carried the CC genotype [β/p38 signaling pathway at late gestation, and such changes may negatively impact offspring heart function [2+ treatment, overloading fetal Ca2+, and abnormal myofibrillar proteins [κB, decreases cytoplasmic NF-κB levels, and increases neutrophil and monocyte infiltration, eventually leading to inflammation in the fetal heart and altering fetal cardiac morphometry [Maternal obesity might be associated with increased risk of infants with CHDs through several mechanisms. Data from epidemiology research suggest that folate, glutathione, and homocysteine metabolism related genetic variants in maternal and fetal may have great impact on the heart development . It had gene rs64939 signigenotype . Decreasgenotype –64. Addigenotype . Anothergenotype . Huang efunction . Secondlproteins . Thirdlyphometry . Furtherphometry .The present meta-analysis had some advantages. Firstly, more relevant original studies and a large number of participants and cases were included, which significantly improved the statistical power of the analysis. Meanwhile, we conducted a quality assessment of eligible studies using the Newcastle-Ottawa Scale, and the included studies can be considered as high-quality because they all awarded seven or more stars. Secondly, the dose-response meta-analysis was performed, and the possibility of nonlinear relationship was evaluated in our study, which made the association between maternal BMI and the risk of CHDs in infants better described. In spite of these strengths, the interpretation of the results in our meta-analysis may be affected by several potential limitations. First, most studies included in our meta-analysis were case-control studies and it is reported that the information bias might be more prone to occur in case-control studies than cohort studies. Then, some confounding factors  only were adjusted in very few included studies, which may lead to an overestimation of the true association between maternal obesity and risk of CHDs in offspring. Finally, it is impossible to completely exclude the potential publication bias because some studies with invalid results tend not to be published.In conclusion, our overall and dose-response meta-analysis indicate that increased maternal BMI is related to increased risk of CHDs in infants. The measures of maternal weight control before they plan to conceive are necessary to decrease the risk of CHDs in infants. The findings from our meta-analysis need to be confirmed in well-designed intervention studies in the future.