Following cervical and uterine cancer, ovarian cancer (OC) has the third rank in gynecologic cancers. It often remains non-diagnosed until it spreads throughout the pelvis and abdomen. Identification of the most effective risk factors can help take prevention measures concerning OC. Therefore, the presented review aims to summarize the available studies on OC risk factors. A comprehensive systematic literature search was performed to identify all published systematic reviews and meta-analysis on associated factors with ovarian cancer. Web of Science, Cochrane Library databases, and Google Scholar were searched up to 17th January 2020. This study was performed according to Smith et al. methodology for conducting a systematic review of systematic reviews. Twenty-eight thousand sixty-two papers were initially retrieved from the electronic databases, among which 20,104 studies were screened. Two hundred seventy-seven articles met our inclusion criteria, 226 of which included in the meta-analysis. Most commonly reported genetic factors were MTHFR C677T ; P-value<0.001), BSML rs1544410 ; P-value=0.004), and Fokl rs2228570 ; P-value<0.001), which were significantly associated with increasing risk of ovarian cancer. Among the other factors, coffee intake ; P-value=0.030), hormone therapy ; P-value<0.001), hysterectomy ; P-value=0.049), and breast feeding  and P-value<0.001) were mostly reported in studies. Among nutritional factors, coffee, egg, and fat intake significantly increase the risk of ovarian cancer. Estrogen, estrogen-progesterone, and overall hormone therapies also are related to the higher incidence of ovarian cancer. Some diseases, such as diabetes, endometriosis, and polycystic ovarian syndrome, as well as several genetic polymorphisms, cause a significant increase in ovarian cancer occurrence. Moreover, other factors, for instance, obesity, overweight, smoking, and perineal talc use, significantly increase the risk of ovarian cancer.The online version contains supplementary material available at 10.1186/s13048-021-00911-z. Following cervical and uterine cancer, ovarian cancer (OC) has the third rank in gynecologic cancers. A woman’s risk of getting ovarian cancer during her lifetime is about 1 in 78. Mortality rate of ovarian cancer is about 1 in 108.  It often remains non-diagnosed until it spreads throughout the pelvis and abdomen, making its treatment even more difficult. At its early stages, when it is limited to the ovary, the treatment success has a higher rate. The silent tumor growth in OC increases its mortality rate and deteriorates its prognosis .Besides the undetectable progress of this type of cancer, improper screening methods further delay its diagnosis . Due to A significant increase is estimated in its mortality rate by 2040. Nonetheless, identification of the most effective risk factors can be helpful in prevention measures concerning OC . ConflicThe presented umbrella meta-analysis and systematic review is focused on any kind of risk factors on ovarian cancer among all women and aimed to summarize the available reviews and find the most important OC risk factors.This study is focused on any kind of risk factors on ovarian cancer among all women.A systematic review of systematic reviews was conducted to identify the associated factors with OC. This study was performed according to Smith et al. methodology for conducting a systematic review of systematic reviews .What are the most important factors associated with ovarian cancer found in systematic reviews?A comprehensive systematic literature search was performed to identify all published systematic reviews and meta-analysis on associated factors with OC. Medline through PubMed, Scopus, Embase, Web of Science, Cochrane Library databases, and Google Scholar all were searched up to 17th January 2020 without time limitation. The search strategy included the use of Mesh terms and keywords related to subject and study design . The detailed search strategy for the Medline can be found in the supplementary, Table This overview only included systematic reviews of factors associated with OC.The articles which met the following criteria were included in our study: 1) systematic reviews or meta-analysis; (2) have evaluated risk factors of Ovarian cancer; (3) have at least abstracts in English. The articles that were narrative reviews or had assessed prognostic factors of OC or did not provide at least abstract in English were excluded. Characteristic of included studies are illustrate in Table  systematFour authors  independently screened the titles and abstracts of citations to identify potentially relevant studies. Then, the full texts of potentially eligible articles were obtained and reviewed for further assessment according to the inclusion and exclusion criteria. Controversies were resolved by consulting a third person (LJ).Data were extracted from eligible studies using a prespecified form in Microsoft Excel by four authors  independently. The following information was collected: first author, year of publication, number of included primary studies, number of participants, age of participants, factors associated with OC, besides the measure of association , and its confidence intervals. Any discrepancy was resolved through discussion with a third author (LJ). EndNote X9 was used to extracting the records and removing duplicates .The SIGN checklist was used to assess the methodological quality of systematic reviews (2); it is composed of 12 items containing ‘yes,‘ ‘no,‘ ‘can’t,‘ or ‘not applicable’ options. Generally, the methodological quality of the studies in this checklist was categorized into low quality, acceptable, and high quality, . Any disagreements were resolved through discussion.All statistical analyses were performed using Stata version 16 .Most of the studies reported measures of the association between each factor and OC using the odds ratio (OR) or risk ratio (RR) with their corresponding CIs. Only one study used a standardized incidence rate ratio (SIR) and standardized mean difference (SMD) as an effect size. Thus, OR or RR and 95 % confidence intervals (CIs) were used to present the association between the factors and OC. For conducting the meta-analysis, all related information about measures of association  were extracted and converted to pooled effect size and its SE for every factor in each study.2 statistic. A random-effects model using restricted maximum-likelihood was used if heterogeneity was high (I2 > 50 %); otherwise, a fixed-effects model was applied.Since the reported combined effects from systematic reviews were used in the analysis, so primary studies may have been included in different systematic reviews and meta-analyses in the different years which we were not able to exclude them in the analysis. Heterogeneity was evaluated among the primary studies using the forest plots, Cochran’s Q statistic, and ISince the number of first reviews combined for the meta-analysis was less than 10, Egger’s regression asymmetry tests were used for assessing the publication bias instead of funnel plots , where p <0.10 was considered as evidence of bias. The characteristics of the included studies were descriptively summarized using a structured table.Twenty-eight thousand sixty-two papers were initially retrieved from the electronic databases, among which 20,104 studies were screened. Two hundred seventy-seven articles met our inclusion criteria, 226 of which included in the meta-analysis  Nutritional factors, (2) Drug use and Medical history, (3) Diseases, (4) Genetic factors, (5) Other factors.Among all of the studied factors, 109 had one quantitative synthesis report, and 53 did not have any quantitative synthesis of individual findings but reported valuable data in systematic review articles (Table 2 S and Table 3 S).. The results of publication bias assessed using the Egger’s test indicate significant publication bias only for MTHFR C677T factor .Meta-analyses were conducted on the 53 associated factors with OC with sufficient data (two or more reports with the same measures). Most commonly reported genetic factors were MTHFR C677T ; P-value<0.001), BSML rs1544410 ; and P-value=0.004) and Fokl rs2228570 ; P-value<0.001), which were significantly associated with increasing risk of OC Among the other factors, coffee intake ; P-value=0.030), hormone therapy ; P-value<0.001), hysterectomy ; P-value=0.049), and breast feeding ; P-value<0.001) were mostly reported in studies. Final results of all conducted meta-analysis are presented in Table 11; P-valThe risk of bias was assessed using the SIGN checklist. Among 277 included studies, 24.19 %, 39.35 %, and 36.46 % had “low quality”, “acceptable” and “high quality,“ respectively.This study focuses on OC risk factors and protective measures. The factors can be classified into nutritional, drug use and medical history, diseases, and genetic. As regards nutritional factors, intake of coffee, egg, and fat can significantly enhance the risk of OC. Estrogen and estrogen-progesterone therapies  are also associated with the elevated risk of OC. Several diseases , as well as some genetic polymorphisms , can significantly increase the incidence of OC. Other factors, like obesity, overweight, smoking, and the use of perineal talc, are also accompanied by an increased risk of OC.Coffee is rich in several anti-oxidant and anti-carcinogenic bioactive compounds  . This beEggs are rich in cholesterol and choline, thus providing quite high protein per energy content, all of which are linked to the risk of breast, ovarian, and prostate cancers. Nonetheless, the majority of these studies on the mentioned cancers have not explored egg consumption as a primary exposure of interest, restricting a robust assessment of the hypothesized correlations. Since eggs have been considered as a source of protein and fat, its intake association with the OC risk has been primarily explored to examine the impact of protein or fat . In thisAs one of the most controversial nutritional factors, dietary fat can enhance the development of hormone-related cancers . However, the reports on this field are discrepant. High-fat diets may stimulate over-secretion of ovarian estrogen, leading to tumor-promoting mechanisms through mitogenic impacts on ERα- positive or negative tumor cells .Epidemiologic reports indicate an association between estrogen exposure duration and OC induction and biology . Recent Diabetes mellitus (DM) is also positively and significantly associated with the risk of OC. Although the carcinogenic influence of DM on the ovary has not been completely understood, some mechanisms have been introduced to describe it partially. Hyperinsulinemia (often associated with insulin resistance) is commonly observed in type 2 DM patients. Chronic hyperinsulinemia has an association with tumor promotion due to the oncogenic potentials of insulin by stimulating cellular signaling cascade or incrementing growth factor-related cell proliferation . MoreoveARID1A [Based on the results, the risk of developing OC is 43 % in women with endometriosis. The endometriosis mechanisms in epithelial OC can be divided into 3 types. The first one is estrogen-dependent. Ness et al. introduce endometriosis as a precursor for epithelial OC, which is easily developed in the low-progesterone and high-estrogen conditions . The secARID1A . FurtherARID1A .The risk of OC shows a 60 % increase in women suffering from polycystic ovary syndrome (PCOS). PCOS has various risk factors, including obesity, diabetes, inflammation, metabolic syndrome, and aging. However, it is not clear whether the elevated risk of endometrial cancer is due to separate risk factors  or PCOS itself. PCOS has its own metabolic characteristics, including hyperinsulinism, hyperglycemia, insulin resistance, and hyperandrogenism, enhancing cancer risk. Moreover, such a relationship between PCOS and endometrial cancer could be due to common inherited genetic variants. Other factors, such as parity (nulliparous versus multi), age at first pregnancy, and use/length of hormone therapy , could confound the results.BRCA2 N372H rs144848, BSML rs1544410, Fokl rs2228570, GSTM1, MTHFR C677T, NFƙB1, P16INK4a, ERCC2 rs13181, MMP-12 rs2276109, and VDR rs11568820 have been found to increase the risk of OC significantly. Among the mentioned polymorphisms, P16INK4a has the strongest impact on the risk of OC (2.6-fold increase), followed by NFƙB1 and MMP-12. rs2276109.Some genetic factors may enhance the risk of developing OC. In the present study, Asn680Ser, p16INK4a inactivation as the result of aberrant hypermethylation in the lung, liver, stomach, breast, and uterus carcinogeneses [p16INK4a promoter hypermethylation and elevated risk of endometrial carcinoma [p16INK4a promoter with OC [Some studies have mentioned the crucial role of ogeneses , 27. In  with OC . This coNFκB1 can significantly inhibit cell apoptosis through regulation of the level of survival genes, such as BCL-2 homolog A1, PAI-2, and IAP family. Moreover, studies have indicated the role of the NFκB1 signaling pathway in cellular proliferation by IL-5 enhancement, MAPK phosphorylation, and cyclin D1 expression modulation .Numerous meta-analyses have addressed the relationship between NFκB1 promoter -94ins/del ATTG polymorphism and cancer risk, although their findings are not entirely consistent. For instance, Yang et al.  and DuanMMP-12 is involved in the pro-tumorigenesis process through inhibiting cancer cell apoptosis and promoting cancer cell invasion and migration . As SNP Obesity, overweight, smoking, and the use of perineal talc could be mentioned as other factors associated with OC risk. The biological mechanisms underlying the relation of overweight and obesity with OC are not clarified and consistent. Based on a study by Kuper et al. , progestKRAS gene is more common in mucinous rather than serous borderline ovarian tumors [Concerning biological mechanisms, the direct correlation of smoking with mucinous tumors can be assigned to the similarity of this neoplasm with cervical adenocarcinoma and colorectal cancers , both ofn tumors , and alsn tumors .The ovarian carcinogenesis mechanism of perineal talc use has remained unclear. Based on a hypothesis, however, as an external stimulus, talc can ascend from the vagina to the uterine tubes and trigger a chronic inflammatory response, further promoting the OC development. Cellular injuries, oxidative stresses, and local elevation of inflammatory mediators  could be mutagenic, thus encouraging carcinogenesis . SupportNumerous studies have addressed the effective factors of OC; however, these works have resulted in contradicting outcomes. The current study explores all previous meta-analyses and systematic reviews to provide a valuable summary of the OC protective and risk factors, among which nutritional and genetic factors play a more profound role. Although the genetic factors cannot be changed due to their inheritance, nutritional ones could be well regulated to prevent OC.Additional file 1.


IRF6, GRHL3, 8q24, VAX1, TGFA, FOXE1, ABCA4, NOG, GREM1, AXIN2, DVL2, WNT3A and WNT5A have high potential as biomarkers of nsOFC in populations of European descent. Although other meta-analyses that included European samples have been performed on a limited number of genetic variants, this study represents the first meta-analysis of all genetic markers that have been studied in connection with nsOFC in populations of European ancestry.To date, the involvement of various genetic markers in the aetiopathogenesis of non-syndromic orofacial cleft (nsOFC) has been extensively studied. In the present study, we focused on studies performed on populations of European ancestry to systematically review the available literature to define relevant genetic risk factors for nsOFC. Eligible studies were obtained by searching Ovid Medline and Ovid Embase. We gathered the genetic markers from population-based case–control studies on nsOFC, and conducted meta-analysis on the repeatedly reported markers. Whenever possible, we performed stratified analysis based on different nsOFC phenotypes, using allelic, dominant, recessive and overdominant genetic models. Effect sizes were expressed as pooled odds ratios (ORs) with 95% confidence intervals (CIs), and p ≤ 0.05 were considered statistically significant. A total of 84 studies were eligible for this systematic review, with > 700 markers included. Of these, 43 studies were included in the meta-analysis. We analysed 47 genetic variants in 30 genes/loci, which resulted in 226 forest plots. There were statistically significant associations between at least one of the nsOFC phenotypes and 19 genetic variants in 13 genes/loci. These data suggest that  The rate of occurrence varies substantially based on geographic origin, ethnicity and race. In general, with some exceptions, populations of Asian and Native American descent have the highest risk of developing OFC, while populations of European ancestry have intermediate risk, and African-derived populations have the lowest risk. In various European countries where White people predominate, OFC occurs at an incidence rate from 1/1000 to 1/500 live births1.Non-syndromic orofacial cleft (nsOFC) is a birth defect that is characterised by incomplete division of the oral and nasal cavities, without any other anomalies present. OFC is considered the most common form of congenital craniofacial malformation. The worldwide incidence ranges from around 1/2500 to 1/500 births, making OFC one of the most frequent congenital developmental defects4. NsOFC is generally divided into groups based on the structures affected, as: cleft lip only; cleft lip and alveolus; cleft lip, alveolus and palate; and cleft palate only (nsCPO). Due to the similar epidemiological features and embryological mechanisms involved, non-syndromic cleft lip only, non-syndromic cleft lip and alveolus, and non-syndromic cleft lip, alveolus and palate are most often investigated together as one group, which is indicated as cleft lip with or without cleft palate (nsCL/P), while nsCPO is believed to have a different, but overlapping, aetiology5.Non-syndromic OFC develops during embryogenesis as a result of incomplete growth and fusion of the soft and/or hard facial tissues, and the subsequent abnormal formation of some parts of the face and oral cavity 6. Furthermore, a higher level of concordance has been observed for monozygotic twins (40–60%) over dizygotic twins (3–5%), which suggests that the genetic component of nsOFC is strong8. Differences in the prevalence of nsOFC between ethnic groups and populations further confirm the involvement of genetics in this incidence.It is generally accepted that nsOFC is a complex multifactorial disorder that arises from interactions between multiple genetic and environmental factors. Various studies have reported high incidence of nsOFC within individual families and in the offspring of patients with nsOFC9. To date, many genetic association studies have been performed to investigate the involvement of such candidate genes in nsOFC16. While several of these studies have shown consistent and replicable genetic association between some genes and nsOFC12, many of them have failed to demonstrate that16. One reason might be that studies have been carried out on different populations or racial groups, and using insufficient sample sizes.Although the full pattern of inheritance is still unknown, nsOFC has been linked to numerous genes, including some that encode transcription factors and growth factors, and some that are involved in cellular signalling and metabolism of nutrients and xenobioticsIRF6, MSX1, MTHFR)19, which have used pooled data from different ethnic groups. One of these meta-analyses was aimed at identification of all of the genetic markers associated with nsOFC in a Brazilian population20, which exhibited high levels of racial and ethnic admixture. However, in the context of the genetics of nsOFC, the data of Brazilian study are not useful when studying populations of European ancestry. Thus, obtaining information about all the genes/genetic variants associated with nsOFC in populations of European ancestry is of importance.Several systematic reviews and meta-analyses have been performed for selected polymorphisms for some of the genes implicated  category highly heterogeneous22. The term ‘Caucasian’ is now obsolete. However, in the reviewed genetic studies, researchers classified the studied population as ‘Caucasian’ or ‘White’ when the population was European, Australian, Middle Eastern, or North/South African22. To reduce the genetic heterogeneity, this study was limited to populations of European ancestry only. The meta-analysis was carried out on repeatedly reported markers, to identify potential genetic risk factors for nsOFC. Although other meta-analyses that included samples of White people have been performed on a limited number of genetic variants26, to the best of our knowledge, this study represents the first systematic review and meta-analysis of all genetic markers that have been examined in connection with nsOFC in populations of European descent only.Traditionally, the term ‘Caucasian’ was used as a racial classification for White people that came from different ethnic groups. Zhang et al. addressed the inconsistency in the race and ethnic classification in pharmacogenetic studies27. The protocol was registered with PROSPERO  under the accession number CRD42020163436.The present systematic review and meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklistA literature search was conducted using two electronic bibliographic databases: Ovid Medline and Ovid Embase. The search was limited to human studies, and covered publications up to 20 June, 2019. There were no restrictions regarding language or publication period. Briefly, the search included the following terms:  and (nonsyndromic OR non-syndromic OR isolated) and . The full literature search strategy is available from the registered protocol in the PROSPERO database. References included in previous meta-analyses that examined associations between genetic markers and nsOFC were also screened to identify any publications that might have been missed.This review covered studies that investigated the association of genetic factors and nsOFC in populations of European ancestry. We used the ‘population, intervention, comparison, outcomes and study’ (PICOS) principle to define the research question and to set the inclusion criteria. Studies that met the following criteria were included in the systematic review:Patients with nsOFC that had European descent. In this review, the patients are considered as Europeans if they were residents of a European country, or of the United States, Canada, South America or Australia, and if their ancestors came from Europe and were White.Investigation of genetic factors (defined by ‘rs’ number or other identifiable name).The control group that comprised unrelated and unaffected individuals without any family history of OFC.Association of the selected genetic factors with the occurrence of nsOFC. The outcomes had to be reported as odds ratios (ORs) with 95% confidence intervals (CIs). Otherwise, there needed to be enough information for calculations of ORs with 95% CIs.Population-based case–control studies on humans ; studies focussing on candidate genes.One of the main exclusion criteria was the unsuitable origin of the population included. Studies that did not include people of European ancestry, but included other populations that were considered White , were excluded. For studies with a mixed population from non-European countries, only those with > 90% of patients and controls of European descent were included. A lack of this information also resulted in study exclusion. Studies such as case reports, family-based studies, case series, reviews and meta-analyses, were not included. The following were also excluded: genome-wide association studies (GWAS); studies not concerning genetic markers (SNVs or indels); studies not focused on humans ; studies without a control group; studies that only investigated maternal genetic markers; studies that examined the genetics of syndromic OFC (or other diseases); and studies without adequate information . Even though GWAS were not included, when they had a population-based replication phase on candidate genes/genetic variants, we did include the replication case–control sample in our study. Studies that looked only for DNA mutations in nsOFC patients that were not seen for a control group were also eliminated. Similarly for studies that examined rare polymorphisms without identifiable names, or for which the location on the chromosome was not determined. If two or more studies evaluated overlapping study populations, all of them were included in the systematic review, but only the study with the most information and the largest sample size was selected for inclusion in the meta-analysis.28 was searched. Markers without identifiable names that could not be found in any other study were excluded. The human gene database GeneCards29 (based on human reference genome version GRCh38/hg38) was used to extract the name, chromosome number and exact genomic location for each gene included. All of these steps were carried out by one of the authors (L.S.) and were then cross-checked and re-evaluated by a second author (N.K.K.). When it was necessary to resolve disagreements, a third author was available (I.L.).After the literature search, the eligible studies were selected in a two-phase process. Initially, all of the titles and abstracts were screened. Articles recognised as not relevant were excluded. Secondly, the full-text versions of all remaining articles were read, for selection of those that matched the inclusion criteria. The following information was extracted from all of the eligible articles: first author; year of publication; population studied; name of the gene/loci or genetic marker inspected; genotyping method; numbers of cases and controls included in the study; and results of the study. If an article included different types of studies, only the information (e.g. number of cases and controls) regarding population-based case–control studies that focussed on candidate genes was extracted. If the studies examined different populations, only the information about populations of European ancestry was extracted. For all of the genetic markers investigated, the genes in which they are located (or are in their proximity) were also defined. When the marker accession number  was not given, other published articles were examined for help using the PubMed database; and when the gene name was not given, dbSNP database30. Quality scores range from 0 stars  to 9 stars . For the studies included, the NOS quality scores were defined independently by two authors . A score ≥ 6 indicated good or high methodological quality, and therefore low risk of bias. Disagreements on the NOS quality scores were discussed and resolved with a third author (N.K.K.).The risk of bias for all of the studies included in the systematic review was assessed using the Newcastle–Ottawa Scale (NOS). This is a frequently used method for estimation of the methodological quality of non-randomised studies . The NOS uses a ‘star system’ to rate the quality of individual studies based on three separate aspects: selection of the groups studied; their comparability; and assessment of the outcomeAll of the eligible studies were included in the systematic review. The genetic variants that were examined in these studies in connection with nsOFC were manually extracted. Furthermore, where two or more studies investigated the relationships between one genetic marker and nsOFC, meta-analysis was also conducted. The allelic frequencies or ORs with 95% CIs were obtained from these studies.Genotyping counts were also collected, if available. The controls were checked for Hardy–Weinberg equilibrium (HWE). If information about the HWE was missing, this was calculated using Chi-squared tests, where p > 0.05 implied HWE compliance. Studies with NOS ≤ 5, studies with controls that deviated from HWE, and studies where not enough data were available for HWE calculation, were excluded from further analysis. Wherever possible, the data were extracted separately for different nsOFC phenotypes, with division into three groups: nsOFC, as all phenotypes together; nsCL/P, as cleft lip with or without cleft palate; and nsCPO, as cleft palate only. Where the phenotype was not clearly defined, the assumption was that all nsOFC subtypes were combined.The associations between most of the genetic markers and nsOFC were evaluated as ORs with 95% CIs, based on four distinct genetic models: allelic model ; dominant model (Aa + aa vs. AA); recessive model (aa vs. Aa + AA); and overdominant model (Aa vs. AA + aa). The studies that did not provide genotype counts of the polymorphisms studied were included in the allelic model analysis, but not in the analysis with the three other genetic models.2 statistic were used. If I2 < 50% or if the Q test p > 0.1, the assumption was for no significant heterogeneity and a fixed-effects model was used to pool the ORs. Otherwise, a random-effects model was applied. The significance of the results  was determined using Z-tests, with p ≤ 0.05 considered statistically significant. In addition, a Bonferroni correction was applied to adjust for multiple tests due to four different genetic models  and three different phenotypes , which resulted in 12 multiple tests in total and a Bonferroni-corrected threshold of 0.0042. For genetic markers not having all 12 multiple tests performed , an actual number of multiple tests performed was used, which equals to the product of number of phenotypes assessed and number of genetic models obtained. In such a case, a corrected threshold was recalculated accordingly. For example, four genetic models and two phenotypes resulted in eight multiple tests per genetic marker, and thus, a corrected threshold of 0.0063.To evaluate between-study heterogeneity, Cochrane Q tests and the I31. The upper threshold value (2.00 or 0.50) was arbitrarily set, which indicates doubled odds (or risks) associated with nsOFC if a specific genetic marker is present.The pooled ORs represented the effects size of a genetic marker for each nsOFC phenotype and genetic model used. The significant effects sizes were divided into three categories based on the magnitudes: large , moderate , and small (0.83 < OR < 1.20). The lower threshold value  was set from Ioannidis et al., which indicates that effect sizes of individual genetic markers for complex diseases < 1.2 are possible, but very difficult to differentiate for the potential impact of biasAll of the statistical analyses were carried out using Microsoft Excel (2016) or Review Manager (RevMan) version 5.4.1 .71 of which were also included in the meta-analysis.The detailed processes of the study identification and inclusion are summarised in the flowchart in Fig. The NOS scores of the studies included in the systematic review ranged from 4 to 9, with a mean of 7.1. This indicates that the majority of the studies were of good or high methodological quality. Only five studies  had NOS ≤ 5 . None of these five studies was included in the meta-analysis. The potential risk of bias in the selected studies mainly resulted from improper selection and definition of controls and non-comparability between cases and controls .71 included in the meta-analysis are presented in Supplementary Table The main characteristics of the 43 studiesThe 84 case–control studies included in the systematic review examined associations of > 700 genetic markers with nsOFC in these populations of European ancestry. These markers were distributed throughout the genome Fig. , and wit71 examined the effects of genetic variants on the development of the different nsOFC phenotypes. Although some of the studies investigated all of the nsOFC subtypes together , the majority  studied nsCL/P and/or nsCPO separately. While nsCL/P was the phenotype of choice in almost all of the studies with the separate phenotypes , the nsCPO cases were assessed in only 52.9% (n = 18). Furthermore, the size of the nsCPO sample was smaller than the nsCL/P sample in all of the studies that included both phenotypes , growth factors or receptors of growth factors , cell adhesion proteins (CDH1), transporters (ABCA4), enzymes (MMP9), and proteins involved in cellular signalling  and in metabolism of nutrients . The abbreviations of the gene names are provided in Supplementary Table Meta-analysis was performed for 47 genetic markers in or in close proximity to 29 genes, and in 1 non-coding region (8q24). These were genes that encode transcription factors , enough data were available such that the analysis was carried out not only for pooled nsOFC phenotypes, but also separately for the nsCL/P subtype. In contrast, the nsCPO phenotype was only evaluated for a total of five genetic markers. For some of the markers, only one type of phenotype was analysed: nsCL/P for 13 markers; nsCPO for 1 marker; or all phenotypes combined as nsOFC for 6 markers. More than half of the markers were studied in only two eligible studies. The complete results of the meta-analysis are given in the Tables 7; 57.4%,IRF6, GRHL3, VAX1, FOXE1), a growth factor (TGFA), a transporter (ABCA4) and proteins involved in cellular signalling . After applying Bonferroni correction, the association remained significant for 14 genetic variants in 1 non-coding region (8q24) and 10 genes (Tables WNT3A and AXIN2) did not remain significantly associated with nsOFC. Meta-analysis has shown associations between some of the genetic markers and nsOFC previously26. However, to the best of our knowledge, this is the first study that provides meta-analysis of all of the genetic markers that have been repeatedly studied in association with nsOFC in populations of European ancestry.Statistically significant associations were observed between at least one of the nsOFC phenotypes and 19 genetic variants, under at least one of the genetic models. These variants were located in or in close proximity to 1 non-coding region 8q24) and 12 genes that encode transcription factors . For each genetic variant, the largest values were considered, regardless of the genetic model used or phenotype studied. When more than one variant of a gene was analysed, the gene was classified based on the result of the variant with the largest effect size. None of the genes with statistically significant findings fell into the category of genes with small effect sizes.IRF6), rs41268753 (GRHL3), rs987525 (8q24), rs7078160 (VAX1) and BamHI (TGFA)  Table . In the IRF6, there was significant association with nsOFC and nsCL/P. The effect sizes for the two phenotypes were similar, although a bit larger for nsCL/P under all of the models performed: allelic, dominant and overdominant. Minor allele A of rs2235371 was the protective allele against nsOFC and nsCL/P. Two other polymorphisms studied in or near IRF6, rs642961 and rs2013162, also showed significant associations with nsOFC and nsCL/P, but the effect sizes were only moderate or small. While minor allele A of rs642961 increased the risk of nsOFC and nsCL/P, minor allele A of rs2013162 decreased the risk. A fourth polymorphism near IRF6 (rs590223) was analysed in the nsCL/P group, but the association was not statistically significant. This might be because the sample was much smaller in comparison to the sample sizes of the other markers studied. These data are given in Table For rs2235371 in IRF6) encodes a transcription factor. Mutations in IRF6 were discovered to be the cause of two syndromic forms of orofacial clefts: Van der Woude syndrome , and popliteal pterygium syndrome 73. This resulted in the hypothesis that hypomorphic mutations in this gene are associated with nsOFC.Interferon regulatory factor 6  than Wang et al. did (three), both of them showed significant associations of rs642961 with nsOFC. Even though the present meta-analysis on this marker pooled the data of four studies, these were not the same studies as included in Wattanawong et al.75. One of the studies was excluded here that did not define the population as White, and one additional study that was included was performed on a Slovak population60. Moreover, we excluded one study that did not calculate whether the controls were in HWE. Here, there were moderate effects of minor allele A (rs642961) on nsOFC and nsCL/P. Due to low between-study heterogeneity and evidence from previous meta-analyses, we believe that rs642961 is involved in the aetiopathogenesis of nsCL/P. The involvement of IRF6 mutations in nsOFC has also been detected in cohorts that included European samples, in genome-wide linkage studies77 and GWAS80.The third variant located near GRHL3, only the nsCPO phenotype was studied. Significant association was seen here for the allelic, dominant and overdominant models, where the minor allele T increased the risk of nsCPO. These data are given in Table For rs41268753 in GRHL3) is one of the orthologues of Drosophila grainy head (grh) and encodes a transcription factor. The initial evidence of GRHL3 involvement in OFC was when mutations were reported for patients with Van der Woude syndrome , with an unusual CPO phenotype, rather than CL/P, which is typical of VWS182. Later Leslie et al. performed GWAS on only nsCPO, and showed significant association with rs41268753 in GRHL368. In the present meta-analysis, we combined their replication sample results from populations of European ancestry  with results obtained by Mangold et al. on central European, Latvian and English nsCPO patients68, and we showed that minor allele T of rs41268753 had significant and large effects on nsCPO. Importantly, this marker was only studied in a case–control study in a mixed Brazilian population, where a similar trend was recorded, although the association was not significant83. This implies that this nsCPO marker might be ethnically specific for populations of European origin. Of note, this variant was absent in a Chinese population84, which further supports this possibility.Grainyhead-like 3  encodes a transcription factor that contains a homeobox (DNA-binding) domain. VAX1 was initially associated with orofacial clefts when markers in or near this gene approached significance in two GWAS87. The meta-analysis performed on a Brazilian population did not find significant association between rs7078160 near VAX1 and nsOFC under the allelic model20. Li et al. performed a meta-analysis on rs7078160 and showed significant association between minor allele A and nsOFC. Although they also performed stratified analysis by ethnicity and showed significant association in White people, there was between-study heterogeneity24. In the present meta-analysis, one of their studies was excluded, as it only reported on case–control results from GWAS87, while one additional study was also included60. We also performed stratified meta-analysis by phenotype , where there was significant association under all of the genetic models performed. As we did not identify between-study heterogeneity and as the effect sizes were larger in the nsCL/P group, we believe that rs7078160 is associated with this phenotype.Ventral anterior homeobox 1 , but the association was significant only for nsCPO under the overdominant model. This association did not remain significant after applying Bonferroni correction. For the variant in the RsaI restriction site, it was only possible here to examine the association with nsCL/P, where we did not find any statistically significant associations. These data are given in Table A large effect size was also noted for a variant in a BamHI restriction site in TGFA) encodes a growth factor. Three meta-analyses assessed the variant in the TaqI restriction site of TGFA in different populations. While Lu et al., Yan et al. and Feng et al. included nine, ten and 14 studies on White people, respectively89, we only included five studies in the present meta-analysis. The reason was that some of their studies were excluded due to our strict criteria regarding the population characteristics and overlapping study populations, or because the studies did not provide adequate information. We also excluded two studies with NOS 5, and a study where insufficient data were available for HWE calculation. All the three previous meta-analyses showed significant associations with moderate effect sizes between the variant and nsOFC under the dominant model89. On the other hand, we included fewer studies and did not detect any significant association under the same model. Lu et al. and Yan et al. also investigated the association for nsCL/P and nsCPO in White people separately. Although both analyses showed association with nsCL/P under the dominant model, our analysis did not. Moreover, while Yan et al. did not report any association with nsCPO, Lu et al. reported significant association under the allelic and dominant models88. On the contrary, our results suggest significant association between the variant and nsCPO only under overdominant model, but the association did not remain significant after applying Bonferroni correction. Therefore, we believe that more studies with larger sample sizes should be performed to obtain more conclusive data.Transforming growth factor A ; rs227731 (NOG); rs35594616 and rs2074222 (DVL2); rs2240308 (AXIN2); rs1258763 (GREM1); rs481931 (ABCA4); rs708111 (WNT3a); and rs566926 (WNT5a) (Table WNT3a), rs2074222 (DVL2), and rs2240308 (AXIN2), did not remain significant. Along with significant variants with large effect sizes, significant data were seen for the listed variants mainly in the analysis where there was low between-study heterogeneity and fixed-effects models were used ; MTR (rs1805087); CTNNB1 (rs4533622); MTRR (rs1801394); FGF10 (rs1448037); BHMT (rs3733890); APC (rs351771); WNT8a (rs2040862); FGFR1 ; MTHFD1 (rs2236225); TGFB3 ; CDH1 (rs9929218); WNT3 ; WNT9B ; MAFB ; MMP9 (rs17576); and TCN2 (rs1801198) , we did not search other databases . The reason lies in the fact that we did not focus on a limited number of genetic variants, but were looking for all genetic variants that have been studied in connection with nsOFC in populations of European ancestry. Thus, by searching the two mentioned databases, we identified a large number of studies. Due to that and our strict inclusion criteria, we found database search extremely time-consuming. Furthermore, all of the studies included in the systematic review were found in Ovid Medline, which means that we did not improve the quality of our search strategy by adding Ovid Embase. We realized that by adding additional bibliographic databases, we would not significantly contribute to the study. However, we acknowledge this as a limitation to our study.Population-based case–control studies were included, but family-based association studies were omitted, which have often been used to examine connections between candidate genes and nsOFC.In addition, although we reduced the heterogeneity among the individuals by limiting the population here to Europeans, it is still present to some extent, as we included studies/samples from different countries.The data were also not adjusted for any other potential confounding factors. Moreover, we did not take into consideration gene–environment or gene–gene interactions, which can also be important in the aetiopathogenesis of this complex disorder. Some markers might well be associated with nsOFC through such interactions, but were not significantly associated in the present single marker meta-analysis.Furthermore, due to the small number of studies that have examined associations between most of the markers and nsOFC in populations of European ancestry, it was not possible to evaluate publication bias in the present meta-analysis.IRF6, GRHL3, 8q24, VAX1, TGFA, FOXE1, ABCA4, NOG, GREM1, AXIN2, DVL2, WNT3A and WNT5A are associated with nsOFC, nsCL/P or nsCPO under at least one of the genetic models included. To the best of our knowledge, this is the first meta-analysis to confirm the association between nsOFC and the following genetic variants in White people: IRF6 (rs2235371); GRHL3 (rs41268753); FOXE1 ; ABCA4 (rs481931); GREM1 (rs1258763); DVL2 ; AXIN2 (rs2240308); WNT3a (rs708111); and WNT5a (rs566926).In the present study, we systematically reviewed the available literature to identify 84 relevant population-based case–control studies where > 700 genetic markers were identified, to investigate their associations to nsOFC in a population of European ancestry. In this meta-analysis on repeatedly reported markers, statistically significant associations were seen between at least one of the nsOFC phenotypes and 19 genetic markers in or in close proximity to 12 genes and in 1 non-coding region. These data indicate that genetic variants in Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.


VDR) polymorphisms  and the risk of dental caries in children. Methods: PubMed/MEDLINE, Cochrane Library, Web of Science, and Scopus databases were comprehensively searched until 19 January 2021. Meta-analysis with odds ratios as the effect estimate along with 95% confidence intervals and subgroup analysis were conducted using Review Manager 5.3 software. Publication bias and sensitivity analyses were conducted by Comprehensive Meta-Analysis, version 2.0 software. Results: Seventy-eight studies were retrieved from the databases, with nine studies included in the final analysis. Based on five genetic models, there was no association between ApaI (rs7975232), TaqI (rs731236), BsmI (rs1544410), FokI (rs2228570), and BglI (rs739837) polymorphisms and susceptibility to dental caries, except for the FokI (rs10735810) polymorphism. Conclusion: Among the VDR polymorphisms considered, an association was found between the FokI (rs10735810) polymorphism and the risk of dental caries, with a protective role of the f allele and ff genotype.Vitamin D participates in the calcification of enamel and dentin and the appropriate immune responses to oral microbial infections. We aimed to assess the association between the most common vitamin D receptor ( VDR) protein , 1.15  polymorphism and susceptibility to dental caries.The pooled ORs for allele, homozygote, heterozygote, recessive, and dominant were 1.06  polymorphism, subgroup analyses in relation to ethnicity and genotyping were conducted (TaqI (rs731236) polymorphism and susceptibility to dental caries across the five genetic models.As there was an adequate number of studies on the onducted . The oveTaqI (rs731236) polymorphism, we removed two studies [We conducted “cumulative analysis” and “one study removed” analyses to evaluate the stability of the findings related to six polymorphisms. The results show that the results were consistent/stable for the six polymorphisms. Additionally, for the  studies ,36 reporp > 0.05 for both Egger’s and Begg’s tests demonstrate a lack of publication bias with regard to all six polymorphisms considered in this review.The funnel plots  and p > VDR polymorphisms (ApaI (rs7975232), FokI (rs10735810), TaqI (rs731236), BsmI (rs1544410), FokI (rs2228570), and BglI (rs739837)) and the risk of dental caries in children. None of the polymorphisms were associated with the risk of dental caries, except for the FokI (rs10735810) polymorphism, with the f allele and ff genotype of this polymorphism having a protective role in dental caries occurrence.The present meta-analysis evaluated the association between VDR and other transcriptionally active proteins, demonstrating the potential of VDR to exert a wide range of biological reactions [VDR gene polymorphisms have been shown to be strongly related to mineral density [VDR gene polymorphisms could modulate the effect of vitamin D supplementation. For instance, one study found some VDR polymorphisms to modify the association of vitamin D supplementation with the risk of a specific type of cancer [VDR polymorphisms in modifying the effect of vitamin D supplementation on dental caries needs further exploration.The role of genetic factors in the risk of dental caries is still largely unknown despite numerous studies. Dental caries is a multifactorial disease caused by interactions between environmental factors, behavioral factors, several genetic factors, and gene–environment interactions . Advanceeactions . Vitamineactions . VDR gen density ,40,41 an density  confirme density . Althougf cancer . The rolVDR plays an important role in regulating the expression of genes associated with the immune response, calcium homeostasis, and cell differentiation and proliferation [VDR polymorphisms could show different patterns based on ethnicities and age [feration . The dis and age ,45,46,47 and age ,18. HoweOur meta-analysis showed a protective role of the FokI (rs10735810) polymorphism on dental caries. This might be due to its interactions with co-transcription factors  and its VDR polymorphisms on the risk of dental caries.The meta-analysis has several limitations and strengths. Limitations include the presence of fewer published reports on this topic hindering the performance of any meta-regression analysis, studies with small sample sizes, and clinical and statistical heterogeneity between the studies. Some studies included in the meta-analysis did not match cases with controls, used genotyping methods different from other studies, and had controls with a deviation of the HWE. It also needs mentioning that we could not conduct any analysis to adjust the effect of multiple testing or multiplicity within the included studies. Despite the limitations, this review demonstrates several strengths in the form of the lack of publication bias, the suitable quality of all the included studies, and the use a population-based source for recruiting controls in all the studies. More studies on larger sample sizes and different ethnicities will help to explore the influence of different VDR polymorphisms explored in this meta-analysis, an association was only observed between the FokI (rs10735810) polymorphism and the risk of dental caries, with the f allele and ff genotype demonstrating a protective role in the occurrence of dental caries.Out of the six


Objective: Accumulated evidence has implicated that brain-derived neurotrophic factor (BDNF) gene polymorphisms play a role in the etiology of obsessive-compulsive disorder (OCD). A single nucleotide polymorphism in the coding exon of the BDNF gene at position 66, Val66Met (rs6265), is found to be associated with OCD in different populations, but results linking Val66Met with OCD have been inconsistent and inconclusive. In our study we performed a meta-analysis to further examine whether rs6265 genetic variants are involved in the etiology of OCD.Methods: By searching databases, relevant case-control studies were retrieved; using established inclusion criteria, we selected eligible studies for analysis.Results: Thirteen studies were identified that examined the association between the rs6265 polymorphism and OCD. After statistical analyses, no significant association was found between the rs6265 polymorphism and OCD . However, in gender-specific analysis, female Val carriers might be a risk factor for OCD .Conclusion: Our updated meta-analysis suggests that female carriers of the Val66Met BDNF polymorphism might be more suspectable to develop OCD. It has been demonstrated by twin studies that genetic factors play a key role in the etiology of obsessive-compulsive disorder (OCD) . While tThe brain-derived neurotrophic factor (BDNF) gene is considered to be one of the candidate genes of psychiatric disorders, as it is widely expressed in the brain and plays a major role in neurogenesis, neuronal growth, maturation, survival, synaptic plasticity, and microarchitectural integrity , 3. BDNFResearchers have extensively focused on the BDNF polymorphism, Val66Met, also known as G196A or rs6265 . This po(1) All studies investigated the association between OCD and Val66Met, G196A, or rs6265 polymorphisms. (2) OCD was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM) or the International Classification of Diseases (ICD) and included DSM-III, DSM-III-R, DSM-IV, DSM-IV-R, and ICD-10. (3) The study had a patient group with OCD and a control group. (4) The study included samples from varied ethnic backgrounds. (5) The frequencies of each allele and genotype met the criteria for Hardy-Weinberg disequilibrium in both case and control groups.This meta-analysis was conducted according to PRISMA guidelines. The English databases used for retrieval were PubMed, Cochrane, Web of Science, Embase, PsycINFO, PsycARTICLE, and the Chinese database was CNKI, CBM and WANFANG. The deadline is September 2020. In order to search OCD and BDNF rs6265 articles in the database more widely, no further restrictions were added. All published papers examined the association between OCD and the BDNF Val66Met polymorphism. The keywords “Brain-derived neurotrophic factor (BDNF),” “Brain Derived Neurotrophic Factor,” “Factor, Brain-Derived Neurotrophic,” “Neurotrophic Factor, Brain-Derived,” “BDNF,” “obsessive-compulsive disorder (OCD),” “Obsessive-Compulsive Neuroses,” “Val66Met,” “rs6265,” “G196A,” and “196G/A” were used to search the articles. We also examined all the references cited in the identified articles, as well as those cited in relevant review articles. The quality of the included studies was evaluated, and publication bias was evaluated.From each enrolled article, data were extracted; including the name of the first author, year of publication, ethnicity of samples, diagnostic criteria of OCD, exclusion criteria, sample size (number of cases and controls), sample age, sex ratio, experimental design, severity of symptoms, and the available genotype information of the BDNF Val66Met polymorphism. To prevent potential errors, all data were extracted independently by the three authors, and a discussion within the research group resolved any disagreement.The data analysis and statistical methods were based on previous research methods .Through our search strategy, we identified 105 linked research papers with potential. After reading the abstracts and full compilations of the studies, 65 of them did not meet the inclusion criteria and were not able to be included . At the n = 4), Caucasian (n = 7), Japanese (n = 1), Indian (n = 1)  . Polymer (n = 1)  did not The studies included in I2 = 72.6%, P = 0.00; P = 0.15), denoting that there was no link between the Met allele and OCD.We also hypothesized that the Met allele is required to see a susceptibility to OCD. The between-study heterogeneity results hinted that the effect each individual study size had was statistically significant , hinting there was no link between the Met allele and OCD in the Eastern population. Similarly, no association was identified in the Western populations . The pooled OR from these studies was 1.07 , and the Egger's test showed no significant results . Thus, we deduced there was no publication bias.The Begg-Mazumdar test for the BDNF Val66Met polymorphism demonstrated a low possibility of publication bias .We first compared the gene gender-specific interaction effects in the etiology of OCD using a meta-analysis method. The main finding of this study is that in gender-specific analysis, the female Val carriers might be a risk factor for OCD  has comorbid lifetime diagnoses of major depressive disorder . Overlap exists in some common genetic variants  found across the affective/anxiety disorder spectrums . HoweverFinally, in order to avoid the shortcomings of previous case-control and family-based studies in elucidating genes that contribute to psychiatric disorders, an endophenotype-based analysis has been recently adopted. This approach allows for a biological underpinning for diagnosis and classification, a net outcome to be established, and may help to identify the susceptibility of genes in the etiology of OCD. Future studies should adopt the endophenotype approach to improve ability to detect susceptibility loci in OCD in order to elucidate its etiology fully.One major limitation for this study is that except for different genetic background, negative life events, personality, gender and environmental factors may also involve in the etiology of OCD. As it has been demonstrated that exposure to stressful life events before the onset of the illness seems to confer an increased risk for OCD. OCD probands have a significantly greater prevalence of ‘anxious' personality disorders in general and avoidant and obsessive-compulsive personality disorders as compared to controls –41, whilTo conclude, our updated study suggests that the female BDNF Val66Met Val carriers may have an increased susceptibility to OCD.The original contributions presented in the study are included in the article/XZ and HL conceived and designed the experiments. YS, NW, and EZ performed the experiments. QL and NW analyzed the data. YS wrote the article. All authors contributed to the article and approved the submitted version.A National Natural Science Foundation of China (No. 81371494) supported this study.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Genetic polymorphisms can influence the chemotherapeutic response; however, previous studies have produced conflicting results, and have failed to identify the most relevant polymorphisms for predicting the response to treatment in patients with cancer. The present meta-analysis was conducted to determine the correlation between two polymorphisms  and 95% confidence intervals (95% CIs). Several databases, including PubMed and Embase, were used to retrieve articles evaluating the association between the rs1128503 polymorphism on progression-free survival remained significant in the heterozygote  and homozygote  models. The TT genotype rs1128503 was associated with better overall survival . Fifteen studies involving 3320 patients were included in the meta-analysis. The effect of the ABCB1 showed a survival benefit after taxane-containing chemotherapy. Carriers of the rs1128503 T allele of  Taxanes, a class of diterpenes, are widely used to treat different types of solid tumors, such as breast cancer, ovarian cancer, some head and neck cancers, and lung cancer. Taxanes exert their anti-tumor effects by disrupting the dynamic balance between microtubules and tubulin dimers, promoting tumor cell apoptosis. Clinical studies have shown that the toxicity and efficacy of taxanes vary widely and exhibit inter-individual differences, leading to substantial variations in individual prognosis. An increasing number of studies have indicated that genetic factors such as single nucleotide polymorphisms (SNPs) play important roles in explaining the individual differences in the prognosis of patients administered taxane-containing chemotherapy .ABCB1), also known as multidrug resistance gene 1, which is located on the long arm of human chromosome 7. ABCB1 encodes P-glycoprotein (P-gp), which can transport a variety of drugs, and also functions as a transmembrane osmotic pump . Upon an increase in P-gp activity, antitumor drugs that enter the cell can be actively pumped out of the cell , leading to increased outflow and/or decreased inflow, so that the antitumor drugs do not accumulate at sufficiently high levels in tumor cells, thereby reducing their efficacy; this is the key mechanism by which P-gp exerts chemotherapy resistance . P-gp is involved in the transport of multiple antitumor drugs, including paclitaxel and docetaxel . Therefore, SNPs in ABCB1 may affect the function of P-gp to ultimately influence drug sensitivity and drug resistance, through mechanisms  such as alteration of the expression levels, stability, degradation, substrate specificity, activity, and/or role of transporters , with consequent impacts on prognosis . Several genetic polymorphisms have been shown to affect the activity of taxanes. The most common gene reportedly associated with these effects is ATP-binding cassette transporter B subfamily member 1 . Given the potential importance of ABCB1 polymorphisms in the response to chemotherapy, we conducted a meta-analysis of studies conducted to date, along with data obtained by doctors, pharmacists, and statisticians, to systematically integrate the current pharmacogenetic literature and obtain more credible evidence. In particular, we focused on the association between the ABCB1 SNPs rs1045642 (C3435T) and rs1128503 (C1236T) and the prognosis of patients administered taxane-based chemotherapy, to provide a basis for personalized clinical medicine.The association between Data sources, search strategy, and selection criteriaThis study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) the Meta-analysis of Observational Studies in Epidemiology guidelines  (PROSPERO Registration Number: CRD42019128195). The electronic databases PubMed, Embase, Web of Science, Cochrane library, Chinese National Knowledge Infrastructure, Wanfang, and Weipu were searched systematically from the time of library construction to August 2019 by two authors. The basic search was restricted to English-language articles with the following core search terms:  and  and (“multidrug resistance gene” or ABCB1 or MDR1). To identify additional published studies and unpublished literature, we manually searched the reference lists of the retrieved studies or relevant reviews, and the authors were contacted. Only the most recent study was included when overlap occurred between studies.ABCB1 C3435T and C1236T; all reported the overall survival (OS) and progression-free survival (PFS) of patients with different genotypes, and had sufficient genotype data to estimate the hazard ratio (HR) and 95% confidence interval (CI) in at least one genetic comparison model. The study selection process was performed by two authors independently; a third author determined the final criteria for any inconsistencies.Studies were considered to be eligible if they fulfilled all of the following criteria: all included patients were diagnosed with a solid tumor; all included patients were administered taxane-based chemotherapy; the studies included comparisons of different categories of the polymorphic genotypes Data collection and quality assessmentTwo authors were responsible for extracting the data from eligible studies using a standardized data extraction table. Disagreements were resolved by group discussion, or by a third author if a consensus could not be reached. Information on the first author’s name, publication year, country, patient mean age, sample size, tumor type, regimen, detection, Hardy-Weinberg equilibrium, PFS, and OS for each category of genotypes were collected. Bias caused by individual studies was examined by two authors independently using the Newcastle–Ottawa Scale score, which is useful for comprehensively evaluating the quality of observational studies in a meta-analysis. The bias of selection (four items), comparability (one item), and outcome (three items) were assessed during this process.Data synthesis and analysis2 statistic. A P value of < 0.10 or I2 > 50% was considered to indicate significant heterogeneity . When statistical heterogeneity existed, the random-effects model was used; otherwise, the fixed-effects model was applied. Sensitivity analyses were performed to evaluate the influence of single studies on the overall analysis. Subgroup analyses, including country , diagnosis , and regimen [paclitaxel plus cisplatin (TP) and others] were conducted. Publication biases were estimated using Egger tests . A two-sided P value of less than 0.05 was taken to indicate statistical significance. All statistical analyses were performed using R version 3.6.1 software.Three genetic models were analyzed for each SNP in this meta-analysis: a homozygote model (TT vs. CC), a heterozygote model (CT vs. CC), and a dominant model (CT + TT vs. CC). For time-to-event survival analysis, we assessed the effect of ABCB1 status on patient prognosis by calculating the HR. For each study, the HR and its 95% CI were retrieved. If these parameters were not available in the articles, we used the software Engauge Digitizer 4.1 to extract specific survival rates according to Kaplan–Meier curves and calculate the HR, as described by Tierney et al., (2007). Heterogeneity in the pooled analyses was determined via statistical analyses, using the Q statistic for homogeneity and the ISearch resultsStudy characteristicsThe characteristics of all studies included are listed in ABCB1 C3435T polymorphismPFS 2 = 53%, P = 0.04) and dominant model . Sensitivity analyses showed that heterogeneity was decreased in the heterozygous model  after excluding the study by Li et al., (2017).Eleven studies involving 2670 patients were included in the meta-analysis for PFS . The C34OSC3435T polymorphism was not associated with an improvement in OS among patients treated with taxane-containing chemotherapy. Results of the subgroup analysis showed that European patients who were CC carriers had a poor OS  compared to that of TT carriers. Patients with ovarian cancer who were CC carriers showed a poor OS  compared to that of TT carriers. Significant heterogeneities were found in the overall meta-analysis of the homozygote model  and dominant model . Sensitivity analyses showed that heterogeneity was decreased in the heterozygous model  after excluding the study by Li et al. (2017) and was decreased in the dominant model  after excluding the study by Bjorn et al., (2018) (Arm A). Nine studies involving 2255 patients were included in the meta-analysis for OS . The C34ABCB1 C1236T polymorphismPFS 2 = 60%, P = 0.03). Sensitivity analyses showed that heterogeneity was decreased in the dominant model  after excluding the study by Johnatty et al., (2013).Seven studies involving 1943 patients were included in the meta-analysis for PFS . The sumOSSix studies involving 1,217 patients were included in the meta-analysis for OS . The CC Publication biasNo significant publication bias was observed. rs1045642 and rs1128503 polymorphisms are the most extensively studied SNPs in ABCB1. Our results indicated that C3435T polymorphisms did not affect PFS and OS, whereas subgroup analysis according to the geographical area, tumor type, and treatment regimen identified significant associations of the polymorphisms with PFS and OS. This finding is consistent with the results of two previous multicenter studies conducted in the United States and Japan. A meta-analysis reported by Jiang et al., (2018) revealed that the rs1045642 and rs1128503 polymorphisms were not related to the response to chemotherapy. Although heterogeneities were found in the overall analyses of PFS and OS in the C3435T homozygote and dominant models, subgroup analysis identified geographical area, tumor type, and chemotherapy regimen as the three main sources of heterogeneity between studies.This is the first meta-analysis to investigate the role of ABCB1 polymorphisms in patients administered taxane-containing chemotherapy. This comprehensive quantitative study included 15 studies involving 3,320 patients with a broad range of characteristics. The C3435T homozygote model. This observation may arise because Li et al., (2017) enrolled patients with breast cancer, which differs from the patient groups in the other studies. Therefore, it is important to analyze the relationship between ABCB1 and prognosis for different tumor types separately. Our study showed that in patients with ovarian cancer, being a C3435T TT carrier had a significant predictive value for the response to chemotherapy, as these patients had better OS and PFS. Wang et al., (2005) showed that the rs1045642 wild-type allele produces significantly higher ABCB1 mRNA levels, leading to higher P-gp expression levels; whereas patients with homozygous variants of C3435T exhibited reduced P-gp expression levels . Penson et al., (2004) 1 reported that patients with ovarian cancer with high expression levels of P-gp had a shorter survival time and poorer prognosis than those with higher P-gp levels. ABCB1 polymorphisms have different effects on the activities of different chemotherapeutic drugs, and the response to chemotherapy and prognosis following administration of different regimens vary widely. ABCB1 polymorphisms are related to the response to platinum-based chemotherapy . Considering TP as a first-line chemotherapy regimen and platinum as a substrate of ABCB1, inconsistent effects may be observed when the chemotherapy regimen involves TP. Our study showed that TT carriers exhibited conflicting outcomes in patients treated with different regimens. Additionally, the level of medical care and medical resources in different regions are inconsistent, factors that will affect the prognosis of patients . There are differences in the genetic and biological characteristics, clinical progression pattern, therapeutic responses, and prognoses among different tumor types; moreover, the distribution of paclitaxel varies among different tumors . Sensitivity analysis revealed that the study by Li et al., (2017) was a source of statistical heterogeneity. When this outlier study was removed, there was no evidence of heterogeneity in the four remaining studies in the ABCB1 C1236T for PFS and OS in patients who were administered taxane-containing chemotherapy. Our results were consistent with those reported by Bjorn et al., (2018) and Zhou et al., (2015). The effect of genetic variation on prognosis may be related to mutations that cause changes in the encoded amino acids, affecting the normal function of certain drug transporters, and leading to phenomena such as decreased expression of P-gp. These changes can lead to changes in the pharmacokinetics of a drug, and decreased levels of the drug pumped out of the cell, resulting in the accumulation of the drug in the cell, which may adversely affect therapeutic efficacy (2003). Bosch et al., (2006) reported that the C1236T homozygous mutant had decreased clearance of docetaxel, leading to an increase in the area under the curve. The C1236T polymorphism may also indirectly affect the stability of the mRNA . Shen et al., (1999) suggested that allele-specific differences in RNA folding influence downstream mRNA splicing, processing, or translational control and regulation, and reduced translational activity may also occur. Our study demonstrated the predictive value of G2677T/A were not evaluated because of the unavailability of data. Despite these limitations, our meta-analysis showed that the precision of the estimation was improved by integrating multiple datasets and enlarging the sample size. Additionally, we found no publication bias, supporting the validity of the results of our meta-analysis. There were some limitations to this study. The adjusted factors of the extracted data on survival time differed among the studies included, which may have affected the results for disease progression and death. Additionally, subgroup analyses based on other baseline characteristics of patients were not conducted, because these data were not available in the studies. The composite effects with other clinical factors and gene variants such as ABCB1 polymorphisms in the survival of patients undergoing taxane chemotherapy. Specifically, T gene carriers have a greater survival benefit. These results provide preliminary evidence of a correlation between the prognosis of patients with cancer and different geographical regions, tumor types, and chemotherapy regimens. Additional large-scale prospective studies are needed to evaluate the relationship between other factors such as specific populations, tumors, G2677T/A polymorphisms, and clinical cancer prognosis, to produce more accurate and robust conclusions.In conclusion, our study suggests a predictive role for


Several studies have explored the relationship among traditional semen parameters, sperm DNA fragmentation (SDF), and unexplained recurrent miscarriage (RM); however, the findings remain controversial. Hence, we conducted a meta-analysis to explore the relationship among traditional semen parameters, SDF, and unexplained RM. Multiple databases, including PubMed, Google Scholar, MEDLINE, Embase, Cochrane Library, Web of Science, and China National Knowledge Infrastructure (CNKI), were searched to identify relevant publications. From the eligible publications, data were extracted independently by two researchers. A total of 280 publications were identified using the search strategy. According to the inclusion/exclusion criteria, 19 publications were eligible. A total of 1182 couples with unexplained RM and 1231 couples without RM were included in this meta-analysis to assess the relationship among traditional semen parameters, SDF, and unexplained RM. Our results showed that couples with unexplained RM had significantly increased levels of SDF and significantly decreased levels of total motility and progressive motility compared with couples without RM, although significant differences were not observed in the semen volume, sperm concentration, and total sperm count between couples with and without RM. The SDF assay may be considered for inclusion in evaluations of couples with unexplained RM. A uniform definition of recurrent miscarriage (RM) has not been established. The American Society for Reproductive Medicine (ASRM) defines RM as two or more consecutive miscarriages , while tMale fertility is usually assessed by the semen volume, sperm concentration, total sperm count, progressive motility, and total motility according to WHO guidelines. However, traditional semen parameters have relatively poor predictive value for spermatozoa fertilizing capacity and reproductive outcomes . The intMany SDF assays have been developed, and the main methods are as follows: sperm chromatin dispersion (SCD) –23, termThis systematic review and meta-analysis aimed to assess the relationship among traditional semen parameters, SDF, and unexplained RM.“recurrent pregnancy loss”, “repeated pregnancy loss”, “recurrent abortions”, “recurrent spontaneous abortion”, “recurrent miscarriage”, “sperm DNA fragmentation”, “sperm DNA integrity”, “sperm DNA damage”, “SDF”, “DFI”, “traditional semen parameters”, and “conventional semen parameters”.　The study was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines . MultiplStudies that met the following criteria were included in this study: (1) original research; (2) the topic is unexplained RM; (3) natural conception; and (4) the data for traditional semen parameters and SDF are expressed as the means with standard deviations (SDs). The exclusion criteria were as follows: (1) reviews, letters, editorials, and abstracts; (2) inaccessible full articles; (3) case-only studies; and (4) duplicate publications.Based on the predefined inclusion/exclusion criteria, all publications were independently selected for eligibility by two authors (Y.D. and J.L.). After removing duplicates, articles were selected by reviewing the titles and abstracts. The remaining publications were retrieved for full-text assessment if their appropriateness could not be determined. Any discrepancy was resolved through discussion with the third reviewer (E.Y.).From the eligible publications, data were extracted independently by two authors (Y.D. and J.L.). Any discrepancy between the two authors (Y.D. and J.L.) was resolved by discussion with the third reviewer (E.Y.). The following information was collected for each eligible publication: name of the first author, publication year, country of origin, ethnicity group, type of study design, sample size, and methods used to evaluate SDF. The main characteristics of the included studies are listed in Quality assessments were performed using the Newcastle–Ottawa Scale (NOS) . A NOS s2 statistic and Cochran’s Q test. Heterogeneity was considered significant at P<0.10 and/or 2I<50%. Based on the heterogeneity assessment, random- or fixed-effects models were selected to calculate the weighted mean differences (WMDs) and their corresponding 95% confidence intervals (CIs). To explore the potential sources of heterogeneity, subgroup analyses were performed. To estimate the stability of the pooled results, a sensitivity analysis was conducted by excluding each publication. To estimate the possible publication bias, Egger’s regression test and Begg’s funnel plot were used. Statistical significance was set at P<0.05.All analyses were performed using Stata/SE 12.0 . The heterogeneity between publications was calculated using the IP>0.05), sperm concentration , and total sperm count  (P<0.05) and total motility  , subgroup analyses were performed by the study design type, RM definition, and ethnicity to explore the source of heterogeneity  Figure 2P=0.018) , subgroup analyses were performed by the assay type, RM definition, and ethnicity to explore the source of heterogeneity (P<0.001)  (P=0.001)  Figure 4The sensitivity analysis showed that the pooled results were stable and reliable Figure 5As shown in RM affects approximately 1% of couples trying to conceive . In almoSome studies have reported that male partners of couples with unexplained RM had significantly decreased levels of semen volume  and progMarked between-study heterogeneity was observed for progressive motility and total motility, and it could not be ignored. Therefore, subgroup analyses by the study design type, RM definition, and ethnicity were performed to explore the source of heterogeneity. However, heterogeneity was still observed despite performing the subgroup analyses. Such heterogeneity may be explained by differences in age and number of participants, duration of sexual abstinence, ethnicity, lifestyle habits, laboratory techniques, etc.However, approximately 15% of male factor infertility patients show normal parameters in their ejaculates , suggestRoutine semen analysis does not assess all aspects of sperm quality. SDF is used to assess the integrity of sperm chromatin and may be a better predictor of male fertility and reproductive outcomes than conventional semen parameters. Sperm DNA integrity plays an important role in the initiation and maintenance of pregnancy . The stuMarked between-study heterogeneity was observed, and it could not be ignored. Several factors may account for the measured heterogeneity. First, there are several methods used to assess SDF. Second, there are two definitions of unexplained RM. Third, the subjects included in the studies were of diverse ethnic backgrounds. All of these factors may have significantly affected the between-study heterogeneity. Subgroup analyses by the assay type, RM definition, and ethnicity were performed to explore the source of heterogeneity. However, heterogeneity was still observed despite performing these subgroup analyses. The results of the subgroups by the definition of RM showed that the couples with a history of RM≥2 times and ≥3 times had significantly increased levels of SDF. Given the limited sample size of the included studies and the significant heterogeneity between studies, further large prospective cohort studies are needed to validate these findings.There were four strengths of this meta-analysis. First, more reliable results can be obtained as a result of the large sample size. Second, we also assessed the relation between traditional semen parameters and unexplained RM. Third, the subgroup analyses by the assay type, RM definition, and ethnicity were also conducted in this study. Fourth, no publication bias was found in this meta-analysis.This meta-analysis has two limitations. First, between-study heterogeneity was found despite using strict inclusion/exclusion criteria. Second, the number of included publications was small in some subgroups.Couples with unexplained RM had significantly increased levels of SDF compared with couples without RM, and they also had significantly decreased progressive motility and total motility. The SDF assay may be considered for inclusion in evaluations of couples with unexplained RM. Future large prospective studies are needed to evaluate the impact of elevated SDF on the risk of RM.The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.All authors contributed to the study’s conception and design. YD and JL participated in drafting the manuscript and the study design. EY and YL searched and selected the relevant articles. YS and LZ contributed to the statistical analysis. All authors contributed to the article and approved the submitted version.By Joint Construction Project of Henan Medical Science and Technology Research Plan (LHGJ20190396).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Benign prostate hyperplasia (BPH) is the most common urological problem in elderly males. Recent studies have reported polymorphism in various metabolic genes in BPH. However, their association with the susceptibility of BPH is still inconsistent. Here, we systematically reviewed and performed a meta-analysis of CYP17, VDR, and ACE genes to determine their precise association with the risk of BPH.A comprehensive literature search for published studies on candidate gene associations involving vitamin D receptor (VDR), angiotensin-converting enzyme (ACE), and CYP17 genes with the risk of BPH was done up to April 2020 in PubMed, Scopus, Cochrane Central Register of Controlled Trials (CENTRAL), and Google Scholar databases. Fixed/random effects models were used to estimate the odd’s ratio (OR) and 95% confidence intervals (CIs). Begg’s funnel plot was used to assess the potential for publication bias.OR = 1.67, 95% CI = 1.03–2.73). Similar trends were observed for ACE gene polymorphism in Caucasian  and Asian  populations under study. No significant association was observed in VDR and CYP17 gene polymorphisms in any dominant or recessive models.We found a total of 23 studies containing 3461 cases and 3833 controls for these gene polymorphisms. A significant association of ACE gene polymorphism was observed under the recessive (II vs. ID + DD) model for BPH susceptibility compared to control subjects (overall Significant OR demonstrated the implication of ACE gene polymorphism in the proliferation of prostate tissue, which in turn is associated with BPH susceptibility. However, prospective studies at large scale and sample size are needed to confirm the current findings.The online version contains supplementary material available at 10.1186/s13643-022-01914-7. Benign prostatic hyperplasia (BPH) is one of the most common diseases in lower urinary tract symptoms (LUTS), in middle-aged and elderly men. It is a non-malignant enlargement of the prostate which can cause urinary dysfunction and may affect the quality of life of patients . Being aCYP17 gene codes for the cytochrome P450c17α enzyme, which plays a crucial role in the synthesis of testosterone from its precursor cholesterol. The CYP17 gene, in its 5′-untranslated region, harbours a nucleotide substitution (rs743572) of ‘T’  to ‘C’  resulting in higher levels of androgens. This change in nucleotide results in a new Sp-1 site (CCACC box) at 34 bp upstream of the translation site and downstream of the transcription site, which in turn acts as an additional promoter elevating CYP17 transcription [Androgens are required for normal growth and development of the prostate gland and even reported in the maintenance of BPH . The CYPAnother metabolic factor, angiotensin-converting enzyme (ACE), plays a significant role in “classical” renin–angiotensin–aldosterone system (RAAS) through which the proliferation of cellular elements in the prostate is regulated . One of Vitamin D and its analogues possess antiproliferative and differentiation effects on prostate cells in both in vivo and in vitro , 12. TheTherefore, we performed the present meta-analysis based on the multivariate method to evaluate the possible role of CYP17, VDR, and ACE gene polymorphisms towards the risk of BPH.This systematic literature review was performed using the guidelines of the PRISMA statement   and CochCase–control candidate gene association studies reporting genetic polymorphisms of VDR, ACE, and CYP17 polymorphisms with the risk of BPH were included. Two authors independently and in duplicate screened titles, abstracts, and full texts determined eligibility, abstracted data, and assessed the credibility of pooled associations. Meta-analyses were performed for genetic variants assessed in more than two studies.Two investigators independently extracted the data. The following data were extracted from each study: first author’s name, published year, ethnicity, country, number of cases and controls, mean age, genotyping method, source of control population, either hospital- or population-based, and frequency distribution of selected polymorphisms. Hardy–Weinberg equilibrium (HWE) was calculated for the allelic frequency distribution. Ethnicities were categorized as Asian and Caucasian populations.The Newcastle–Ottawa Scale (NOS)  was usedThe risk of bias was assessed with Newland Ottawa Scale, and publication bias was assessed using Begg’s and Egger’s funnel plot analysis.Q statistic and I2 metric [I2 metric was used to describe the degree of heterogeneity between the included studies, where 0–25% indicated no observed heterogeneity and larger values showed increasing heterogeneity, with 25–50% regarded as low, 50–75% as moderate, and 75–100% as high. Heterogeneity between studies was adjusted by subgroup analysis, HWE status, and meta-regression by quality score of the included studies.Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to investigate the relationship between ACE, Cyp17, and ACE gene polymorphisms and the risk of BPH using fixed (Mantel–Haenszel method)  or rando2 metric , 24. TheP value <0.05 was considered statistically significant.One-way sensitivity analyses were performed to assess the stability of the results, namely, a single study in which the meta-analysis was deleted each time to reflect the influence of the individual dataset on the pooled OR. Funnel plots and Egger’s linear regression test were used to obtain the potential publication bias , 26. TheThe initial search yielded 310 records from PubMed, Embase, Scopus, Web of Science Cochrane Central Register of Controlled Trials (CENTRAL), and Google Scholar databases. Of them, 281 were excluded after the review of the title/abstract, leaving 29 potential studies for full-text information review. Finally, 23 studies met the inclusion criteria and were included in this study  and recessive model , respectively  and recessive model ; also, on the Caucasian population, no significant association was observed under dominant  as well as recessive model , respectively .A non-significant relationship between CYP17 rs743572) gene polymorphism and risk of BPH was observed under dominant model , but not in the dominant (II + ID vs. DD) model   as well as the Caucasian population , respectively. However, no significant association was observed under the dominant model  in Asian as well as in Caucasian  .A significant association between angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism and risk of BPH was observed under the recessive (II vs. ID + DD) model  of the VDR gene with risk of BPH from seven case–control studies were identified. Seven case–control studies focused on Taq-I, six case–control studies focused on Fok-I, and five case–control studies focused on Bsm-I and Apa-I gene polymorphisms of VDR. The pooled analyses indicated that these four polymorphisms might not be associated with the risk of BPH.OR 1.16, 95% CI (0.95–1.42) for TT + Tt vs. tt; Bsm-I: OR 1.05, 95% CI (0.80–1.39) for BB + Bb vs. bb; Apa-I: OR 1.07, 95% CI (0.77–1.51) for AA +Aa vs. aa; Fok-I: OR 0.90, 95% CI (0.78–1.04) for FF + Ff vs. ff and recessive model  for tt vs. TT; Bsm-I: OR 1.34, 95% CI (0.90–1.99) for bb vs. BB; Apa-I: OR 1.23, 95% CI (0.57–2.64) for aa vs. AA; Fok-I: OR 0.76, 95% CI (0.54–1.07) for ff vs. FF) , 10 studies for VDR , and 4 studies for ACE  across two different ethnicities (Asians and Caucasian)  are more susceptible to BPH onset. Although relatively few studies on ACE polymorphism than VDR/CYP17 genes were analysed in the present study, large studies with prospective data and large sample size should be conducted.Additional file 1. Figure S1. Meta-analysis of included studies reporting on CYP17 polymorphism in BPH susceptibility compared with controls. Figure S2. Meta-analysis of included studies reporting on ACE gene polymorphism in BPH susceptibility compared with controls. Figure S3. Meta-analysis of included studies reporting on VDR Taq1 polymorphism in BPH susceptibility compared with controls. Figure S4. Meta-analysis of included studies reporting on VDR bsm1 polymorphism in BPH susceptibility compared with controls. Figure S5. Meta-analysis of included studies reporting on VDR APa1 polymorphism in BPH susceptibility compared with controls. Figure S6. Meta-analysis of included studies reporting on VDR Fok1 polymorphism in BPH susceptibility compared with controls.