PRM1 (rs737008 and rs2301365) and PRM2 (rs1646022 and rs2070923) polymorphisms and susceptibility to male infertility. The association between PRM1 and PRM2 polymorphisms and the risk of male infertility was evaluated using specific search terms in the Web of Science, Cochrane Library, PubMed, and Scopus databases without language restriction until January 28, 2020. The association was determined by odds ratio (OR) and 95% confidence interval (CI) on five genetic models using Review Manager 5.3 software. The funnel plot analysis and sensitivity analysis were done by the Comprehensive Meta-analysis 2.0 software. Out of 261 records retrieved from the databases, 17 studies were analyzed in the meta-analysis, including the four PRM polymorphisms. The pooled results as OR  showed 0.96 (0.44), 1.04 (0.70), 0.94 (0.51), 0.94 (0.48), and 1.03 (0.72) for PRM1 rs737008 polymorphism and 1.67 (0.0007), 1.73 (0.06), 1.50 (0.007), 1.56 (0.004), and 1.62 (0.33) for PRM1 rs2301365 polymorphism in allele, homozygous, heterozygous, recessive, and dominant models, respectively. Moreover, the pooled results as OR  showed 1.19 (0.004), 1.15 (0.26), 1.08 (0.70), 1.05 (0.76), and 0.98 (0.82) for PRM2 rs1646022 and 0.88 (0.04), 0.84 (0.10), 1.05 (0.81), 0.90 (0.24), and 0.80 (0.02) for PRM2 rs2070923 in allele, homozygous, heterozygous, recessive, and dominant models, respectively. The results showed PRM1 rs2301365 and PRM2 rs1646022 polymorphisms were associated with an elevated risk of male infertility and PRM2 rs2070923 polymorphism had a protective role in infertile men.Studies have reported the genetic gives rise to male infertility. The aim of the present meta-analysis was to evaluate the association between  Male factor infertility affects up to 50% of couples' infertility and accounts for only 20% of total infertility2. Recently, however, the male factor infertility incidence has increased4. Male infertility is currently assessed through routine analysis according to sperm concentration/number, motility, and sperm morphology. However, there is a significant integration of semen characteristics between fertile and infertile males. In fact, around 15% of patients with male factor infertility according to WHO guidelines5 have normal semen parameters6. Thus, there are several limitations to routine conventional semen analysis in assessing male infertility, indicating that conventional semen parameters are poor predictors of reproductive outcome and that definitive diagnosis of male infertility cannot be made by routine analysis alone7. These limitations have led to the development of advanced methods for the study of sperm function, oxidative stress, fragmentation and DNA packing8. Non-obstructive azoospermia and severe oligozoospermia are two of the dominant phenotypes associated with severe spermatogenesis9. However, many factors relate to male infertility, like to reproductive tract disorders, chemical exposure, and infection9. Genetic factors account for 50% or more of all male infertility etiology, and approximately 7% of men worldwide suffer from infertility10. In order to indicate the underlying causes, extensive research has been done on the genetic reasons of male infertility in recent years.Infertility is defined as couples' inability to have a baby after one year of regular unprotected intercoursePMN1 and PMN2, located on chromosome 16. In human sperm cells, 85% of histones are replaced by PRMN and from DNA in Protect against harmful agents. Altered ratio of histones to proteins has been shown to increase chromatin deficiency in sperm, increasing the risk of DNA damage and male infertility. In addition, an adequate ratio of PRMN1 and PRMN2  is needed for normal sperm function11. The expression of these two proteins in the sperm nucleus is approximately equal12. The complete translation of PRM1 and PRM2 mRNA happens throughout the elongated spermatids development, occurring in the production of positively charged PRMNs as a result of the high arginine content and this allows for strong binding to negatively charged DNA13. It was noticed a significantly diminished level of PRM1 mRNAs in spermatozoa isolated from crossbred Frieswal bulls with poor semen parameters, mostly featured by low progressive motility, in comparison to a group with good semen features14 and decreased PRM2 levels have been reported in various studies in infertile patients15. PRMs are believed to play a significant role in chromatin aggregation, transcriptional repression, haploid male genome conservation, sperm formation, and offspring production16. There were two previous meta-analyses reporting an association between PRM polymorphisms and the risk of male infertility including 8 studies17 and checking one PRM polymorphism and another9 included 13 studies with six PRM polymorphisms. Therefore, in the present meta-analysis including a meta-regression analysis of 17 studies, we investigated 13 PRM polymorphisms and then focused on the association between four functional PRM1 (rs737008 and rs2301365) and PRM2 (rs1646022 and PRM2 rs2070923) polymorphisms and male infertility susceptibility in case–control studies.There are two types of protamines (PRMNs), PRMN1 and PRMN2, which are encoded by two genes, 19.The meta-analysis was done based on PRISMA statement, and the study question was formulated based on the PICOS frameworkParticipants (P): Men with infertilityPRM1 and PRM2 polymorphismsInterventions (I): Prevalence of Comparisons (C): Male healthy controlsPRM1 and PRM2 polymorphismsOutcomes (O): Risk of Study design (S): Case–control studiesPRM1 and PRM2 polymorphisms with the risk of male infertility, one author used the search terms  and (“PRM1” or “PRM2" or “Protamine 1” or “Protamine 2”) and (“gene*” or “variant*” or “polymorphism*” or “single-nucleotide polymorphism”) in the Web of Science, Cochrane Library, PubMed, and Scopus databases without language restriction until January 28, 2020. Another author checked the titles and abstracts to exclude the duplicates and irrelevant records and checked the full-texts of eligible studies. The databases were searched manually by crosschecking the references of original papers, review papers, and previous meta-analyses related to our topic in this meta-analysis to find the possibly missed studies. In addition, among studies retrieved, two previous meta-analyses had reported an association between PRM polymorphisms and the risk of male infertility17. One of them17 included 8 studies checking PRM1 rs2301365 polymorphism and showed an association between this polymorphism and the risk of male infertility just in Caucasians. Another9 included 13 studies (11 studies on PRM1 and 7 studies on PRM2 polymorphisms) with six PRM polymorphisms and showed an association between PRM1 rs737008, PRM1 rs2301365, and PRM2 rs1646022 polymorphisms and the risk of male infertility.To search the association of PRM1 polymorphisms rs35576928, rs737008, rs35262993, rs2301365, rs140477029, and rs193922261 and also PRM2 polymorphisms of rs1646022, rs779337774, rs545828790, rs201933708, rs115686767, rs200072135, and rs2070923 with male infertility susceptibility; (2) case–control studies on human beings that the cases were infertile patients with idiopathic infertility and including all subtypes  and the controls were fertile; (3) including the details of genotype or allele frequency of cases and controls; (4) studies with complete full-text, and (5) studies with every language, (6) studies with or without deviation from the Hardy–Weinberg equilibrium (HWE) in controls. The exclusion criteria included (1) studies not concerning the association between PRM polymorphisms mentioned above and male infertility susceptibility; (2) animal articles, review studies, meta-analyses, and conference papers or editorial articles; (3) duplicate studies; and (4) studies with irrelevant data.The inclusion criteria included (1) study focus on The information retrieved from each study is mentioned in Tables PRM1 and PRM2 polymorphisms and male infertility risk was performed by odds ratio (OR) and 95% confidence interval (CI). Review Manager 5.3 software was applied to calculate the summary ORs based on five genetic models . In this state, the statistical significance of pooled results was illustrated with the Z-test. P-value < 0.05 was considered statistically significant. In addition, heterogeneity across the studies was estimated by the Chi-square-based Q test20. If the Ph or Pheterogeneity was > 0.10 and heterogeneity or I2 < 50%, showing lack of heterogeneity between studies, we should use the fixed-effects model, but conversely, we used the random-effects model21.The evaluation of the strength of association between PRM1 (rs737008 and rs2301365) and PRM2 (rs1646022 and rs2070923). The prevalence rates of CC (wild-type homozygote), CA (heterozygote), and AA genotype (rare homozygote) were calculated for PRM1 rs737008, PRM1 rs2301365, and PRM2 rs2070923 polymorphisms. Further, the GG (wild-type homozygote), GC (heterozygote), and CC (rare homozygote) were calculated for PRM2 rs1646022 polymorphism. Subgroup analyses were further performed based on ethnicity, method, and control source. A sensitivity analysis was conducted in which the studies with deviation from HWE in the controls were deleted. A meta-regression analysis was performed to detect the confounding factors affecting the pooled results by IBM SPSS 22.0 software. In addition, sensitivity analyses, including “one remove study” and “cumulative analysis”, were conducted each time on previous analyses to determine the stability of the pooled results. Funnel plots and Egger’s liner regression test were used to examine the publication bias. The funnel plot analysis and sensitivity analysis were done by Comprehensive Meta-analysis 2.0 software.The thirteen polymorphisms were assessed for the association with susceptibility to male infertility based on five genetic models. Among them, four polymorphisms were included in the meta-analysis: 22 was excluded because it did not include four eligible polymorphisms. Finally, 17 studies including four polymorphisms of PRM1 rs737008, PRM1 rs2301365, PRM2 rs1646022, and PRM2 rs2070923 were analyzed in the meta-analysis. One study23 checked the rs737008 and rs2301365 polymorphisms in two different populations .Out of 261 records retrieved in the databases, 25 articles including full-texts were evaluated for eligibility after excluding the duplicates and irrelevant records  in the meta-analysis mentioned in Table PRM1 rs35262993, rs140477029, rs35576928, and rs193922261 polymorphisms and PRM2 rs779337774, rs545828790, rs201933708, rs115686767, and rs200072135 polymorphisms) in Table P-values of HWE were less than 0.05 for the controls of PRM1 rs737008 polymorphism in two studies33, PRM2 rs1646022 in six studies39, and PRM2 rs2070923 in four studies38.Tables PRM1 rs737008 polymorphism based on five genetic models are illustrated in Fig. P-value) showed 0.96  with I2 = 44% (Pheterogeneity or Ph = 0.04), 1.04  with I2 = 19% (Ph = 0.25), 0.94  with I2 = 35% (Ph = 0.10), 0.94  with I2 = 39% (Ph = 0.07), and 1.03  with I2 = 7% (Ph = 0.37) in the allele, homozygous, heterozygous, recessive, and dominant models, respectively. Based on the results, this polymorphism was not associated with the male infertility susceptibility.The pooled results of PRM1 rs2301365 polymorphism based on five genetic models are indicated in Fig. P-value) showed the 1.67  with I2 = 82% (Ph < 0.00001), 1.73  with I2 = 50% (Ph = 0.03), 1.50  with I2 = 70% (Ph = 0.0004), 1.56  with I2 = 74% (Ph < 0.0001), and 1.62  with I2 = 83% (Ph < 0.00001) in the allele, homozygous, heterozygous, recessive, and dominant models, respectively. Based on the results, C allele and CA genotype of PRM1 rs2301365 polymorphism were associated with the elevated risk of male infertility.The pooled results of PRM2 rs1646022 polymorphism based on five genetic models are shown in Fig. P-value) showed the 1.19  with I2 = 44% (Ph = 0.08), 1.15  with I2 = 31% (Ph = 0.17), 1.08  with I2 = 68% (Ph = 0.002), 1.05  with I2 = 60% (Ph = 0.010), and 0.98  with I2 = 0% (Ph = 0.54) in the allele, homozygous, heterozygous, recessive, and dominant models, respectively. Based on the results, the G allele of PRM2 rs1646022 polymorphism was associated with the elevated risk of male infertility.The pooled results of PRM2 rs2070923 polymorphism based on five genetic models are demonstrated in Fig. P-value) showed the 0.88  with I2 = 1% (Ph = 0.43), 0.84  with I2 = 0% (Ph = 0.59), 1.05  with I2 = 63% (Ph = 0.009), 0.90  with I2 = 35% (Ph = 015), and 0.80  with I2 = 23% (Ph = 0.25) in the allele, homozygous, heterozygous, recessive, and dominant models, respectively. Based on the results, the C allele and CC genotype of PRM2 rs2070923 polymorphism were associated with the reduced risk of male infertility.The pooled results of PRM1 rs737008, PRM1 rs2301365, PRM2 rs2070923, and PRM2 rs1646022 polymorphisms are shown in Table P = 0.04) without heterogeneity. With regard to PRM1 rs2301365 polymorphism, the C allele and CA genotype in the Caucasian ethnicity were associated with the elevated risk of male infertility . Also, the C allele  and CC  and CA  genotypes in the studies with hospital-based controls were associated with the elevated risk of male infertility. For PRM1 rs2301365 polymorphism, the C allele and CA genotype in the studies with PCR-based method were associated with the elevated risk of male infertility . About PRM2 rs2070923 polymorphism, the G allele had an elevated risk in male infertility compared to male fertility , which was similar to the G allele  and GG genotype  in the studies with hospital-based controls. With regard to mass ARRAY, the G allele  and GG  and GC  genotypes had an elevated risk in male infertility compared to male fertility. As for PRM2 rs1646022 polymorphism, the CC genotype was associated with a reduced risk of male infertility  in the Caucasian ethnicity and C allele  in the mixed ethnicity. Further, the C allele  and CC genotype  in the PCR-based method had a reduced risk of male infertility.The results of subgroup analysis for PRM1 rs737008, PRM1 rs2301365, and PRM2 rs1646022 polymorphisms.The results of meta-regression analysis for four polymorphisms based on publication year are shown in Table 33 for polymorphism of PRM1 rs737008, six39 for PRM2 rs1646022, and four38 for PRM2 rs2070923. The results after excluding are presented in Table We excluded the studies with a deviation of HWE in the controls, including two studiesPRM1 and PRM2 polymorphisms based on five genetic models are shown in Figs. P = 0.04) in PRM1 rs737008 polymorphism and C vs. G model (P = 0.016) in PRM2 rs1646022 polymorphism. In addition, Begg’s test revealed the publication bias for AA + CA vs. CC (P = 0.001) model in PRM1 rs737008 polymorphism, CA vs. CC (P = 0.025) and AA + CA vs. CC models (P = 0.039) in PRM1 rs2301365 polymorphism.The funnel plots of 41 Any single nucleotide polymorphism in the coding and non-coding areas of PRM1 and PRM2 genes may cause significant abnormalities in their expression9. The changes in one set of genes and expression patterns impact the spermatogenesis process and its products, resulting in spermatogenesis dysfunction and leading to male infertility42. Nowadays, the findings on the association of PRM genes with male infertility are not fully convincing, and there are not sufficient studies on this topic32. A research confirmed that the expression of PRMs is uniquely related to the transcription/translation factors43. The present meta-analysis showed that PRM1 rs737008 polymorphism was not associated with the risk of male infertility. PRM1 rs2301365 and PRM2 rs1646022 polymorphisms were associated with an elevated risk of male infertility and PRM2 rs2070923 polymorphism had a protective role in infertile men. In addition, the subgroup analysis showed the effect of ethnicity, control source, and genotyping method on the association of PRM polymorphisms with the risk of male infertility. The results of meta-regression showed that publication year was a cofounding factor involved in the association between PRM1 rs737008, PRM1 rs2301365, and PRM2 rs1646022 polymorphisms and susceptibility to male infertility. Although single nucleotide polymorphism of G197T that lead to arginine to serine conversion was required in highly protected clusters of arginine for normal DNA binding has been found in 10% of unrelated infertile cases whose sperms were phenotypically same as those from mice with PRMN deficiency44.There is considerable empirical evidence to suggest that PRMs are necessary for male infertility and that PRM1 and PRM2 have a fundamental role in sperm chromatin density and spermatogenesisPRM1 and PRM2 variants are related to male infertility in both humans and animals26. In the animal model, reduction of PRM causes sperm morphology defects due to decreased motility and infertility as a result of haploid germ deficiency47. Using gene–gene interaction analysis, Jiang et al.36 examined twelve combined genotypes of PRM polymorphisms. Their results showed a significant association between the combined genotypes and male infertility. One study reported that sperm concentration, motility, and morphology significantly decreased in patients with an aberrant PRM ratio48. PRM protection is very important in mammals and minor alternations in the coding and non-coding regions of PRM genes may cause important abnormalities in the expression or maintenance of gene expression stability9. PRMs may act as a checkpoint for spermatogenesis, where abnormal PRM expression causes the induction of an apoptotic process that may explain the decrease in sperm production12. In addition, studies have shown that abnormal PRM expression is related to defective spermatogenesis12. There is some evidence that PRM mutations or polymorphisms may induce alternations at the protein level and their composition in sperm chromatin, resulting in sperm deficiency47. Semen quality decreases with age and characteristic molecular changes occur during aging . In addition, the logistic regression models have illustrated an association between age and semen parameters49.It has been shown that PRM polymorphisms are important and may contribute to the difference in susceptibility to male infertility. A meta-analysis17 reported an association between PRM1 rs2301365 polymorphism and the risk of male infertility in the Caucasians, not in the Asians. As in our meta-analysis, there was an elevated risk of male infertility for PRM1 rs2301365 polymorphism only in Caucasians and for PRM2 rs1646022 polymorphism only in Asians. In addition, there was significantly a decreased risk of PRM1 rs737008 in population-based controls, elevated risk of PRM1 rs2301365 and PRM2 rs1646022 in hospital-based controls. Also, with regards to method, an elevated risk of PRM1 rs2301365 and a decreased risk of PRM2 rs2070923 in PCR-based method and an elevated risk of PRM2 rs1646022 in Mass ARRAY method. It is noteworthy that the expression of genes, environmental factors, and spermatogenesis disorder can play an important role in male sterility9. Another possible reason for these inconsistent findings can be a particular selection of the clinical subtypes of male infertility and PRM1 and PRM2 variations in different populations examined9. Therefore, existence of heterogeneity among studies may be due to the differences genotyping method, clinical subtypes of male infertility, ethnicity, publication year, control source, and even number of recruited patients38.As the present meta-analysis demonstrated, ethnicity, control source, and genotyping method of This meta-analysis had two significant limitations. First, the clinical data such as age, abstinence time, serum hormone index, and semen quality and parameters were not analyzed due to lack of information. Second, the meta-analysis did not evaluate the gene–gene and gene-environment interactions due to lack of information in the published studies.PRM polymorphisms . The results showed PRM1 rs2301365 and PRM2 rs1646022 polymorphisms were associated with an elevated risk of male infertility and PRM2 rs2070923 polymorphism had a protective role in infertile men. In addition, ethnicity, control source, and genotyping method impacted the PRM polymorphisms and susceptibility to male infertility. Based on the results, the future studies need to evaluate these polymorphisms in a large number of participants in various areas, with an emphasis on environmental factors, interactions, age, method, and selection of controls (deviation of HWE and source).The present meta-analysis evaluated four


AD).Epidemiological studies indicate that gene–environment interactions play a role in atopic dermatitis  loss‐of‐function mutations.To review the evidence for gene–environment interactions in MEDLINE and BIOSIS was performed. Search terms included all synonyms for AD and filaggrin/FLG; any genetic or epidemiological study design using any statistical methods were included. Quality assessment using criteria modified from guidance (ROBINS‐I and Human Genome Epidemiology Network) for nonrandomized and genetic studies was completed, including consideration of power. Heterogeneity of study design and analyses precluded the use of meta‐analysis.A systematic search from inception to September 2018 in Embase, FLG–environment interactions in six of the studies , including early‐life cat ownership, older siblings, water hardness, phthalate exposure, higher urinary phthalate metabolite levels  and prolonged breastfeeding (which decreased AD risk in the context of FLG null genotype). Major limitations of published studies were the low numbers of individuals (ranging from five to 94) with AD and FLG loss‐of‐function mutations and exposure to specific environmental factors, and variation in exposure definitions.Of 1817 papers identified, 12 studies fulfilled the inclusion criteria required and performed formal interaction testing. There was some evidence for FLG–environment interactions in AD aetiology is limited. However, many of the studies lacked large enough sample sizes to assess these interactions fully. Further research is needed with larger sample sizes and clearly defined exposure assessment.Evidence on Linked Comment: Br J Dermatol 2020; 183:411Park and Seo. . What's already known about this topic?Gene–environment interactions are considered important in the aetiology of atopic dermatitis.FLG) are the most consistently reported genetic variants for atopic dermatitis.Loss‐of-function mutations in the gene coding filaggrin (FLG and a range of different environmental exposures.Studies have reported evidence for gene–environment interaction involving What does this study add?FLG–environment interactions in the aetiology of atopic dermatitis; however, the evidence is limited.There is some evidence for Studies lack large enough sample sizes to achieve adequate power in order to assess these interactions fully.Linked Comment: Br J Dermatol 2020; 183:411Park and Seo. .Plain language summary available online Atopic dermatitis (AD), also known as eczema or atopic eczema, is a complex, multifactorial, often debilitating disease.FLG) are the strongest and most significantly associated genetic variants for AD.Considerable phenotypic heterogeneity, evidence for multiple genetic risk mechanismsFLG is essential for normal epidermal barrier function and formation,FLG in white European populations are R510X and 2282del4, present in approximately 9% of healthy people in Northern European populations. These mutations are strongly associated with AD risk, particularly early‐onset and severe disease.FLG have been identified.in utero or in later life may play a role in AD aetiology.Profilaggrin is an insoluble protein found in the outer epidermis; monomeric filaggrin has multiple functions including aggregation of keratin filaments.FLG null genotype, because this is the strongest and most widely replicated AD genetic risk factor, and because the role of filaggrin in skin barrier function provides a priori support for a hypothetical GEI effect.Gene–environment interaction (GEI) may be defined as occurring when individuals with different genotypes respond to an environmental exposure in different ways; this interaction contributes to many common phenotypes and complex genetic traits. There is evidence that GEI plays a role in atopic diseases, such as asthma, in which genotype interacts with environmental factors, including maternal smoking and house dust mite.FLG mutations, ‘filaggrin’, ‘FLG’, possible misspellings and previously reported FLG mutation names were included in the strategy (P < 0·05) FLG–environment interaction in the aetiology of AD and the secondary outcome was the strength of the association of the interaction (evidence of a dose–response relationship) and AD severity. Details of abstract screening, inclusion and exclusion criteria and data extraction are provided in This systematic review was prospectively registered (PROSPERO ID CRD42017057818). A detailed electronic search of MEDLINE and Embase via Ovid, and BIOSIS via Web of Science was undertaken from inception of each database to September 2018, identifying manuscripts in any language. To define AD, the search terms ‘atopic dermatitis’, ‘atopic eczema’ and ‘eczema’ were used, and to define Quality and bias assessment was performed using criteria modified from guidance for nonrandomized studies to determine quality of studies; ROBINS‐I to assess risk of bias in nonrandomized studies of interventions, and HuGENet for genetic studies, including assessing whether confounders were considered.6 in a case–control/cohort study for a binary single‐nucleotide polymorphism (SNP) and binary exposure under a series of assumptions for model parameters (R 3·5·0 (R package powerGWASinteraction).Post hoc sample‐size calculations were undertaken to estimate the sample size required to detect a GEI effect varying between 1·2 and 2The search identified 1817 papers of possible relevance  to 459 (10·2%). The AD definition and method of ascertainment varied between studies  . Heterogeneity in study design and exposures precluded formal meta‐analysis.Of the 12 publications, including 15 studies  (n = 379) and reported an increased risk related to cat exposure at birth among children aged 0–5 years who had FLG null mutation ; findings were replicated in the Manchester Asthma and Allergy Study (MAAS) (n = 503), with an increased risk owing to interaction of cat exposure at birth and FLG null genotype . Schuttelaar et al. (n = 934) reported no overall interaction (P = 0·85) between FLG null genotype (one/two FLG loss‐of‐function mutations) and cat exposure at home . However, Schuttelaar et al. reported an interaction when examining the 2282del4 mutation only (P = 0·003), with a stronger effect in children aged 0–8 years with a cat at home  compared with those without .FLG loss‐of‐function mutations have biological equivalence on filaggrin protein expression, there is no clear biological plausibility for an interaction with one mutation and not another. Evidence for GEI comes from small numbers of individuals with FLG mutation, cat exposure and development of AD. In Bisgaard et al. five such individuals were reported. Schuttelaar et al. did not provide the number of individuals, but it can be inferred that n < 84 for the overall interaction and n < 50 for the 2282del4 interaction.Two studies assessed the et al. tested for an interaction between FLG loss‐of‐function mutations and dog ownership in the first year of life. There was no evidence for an interaction in COPSAC (n = 379) (result statistics not reported) or MAAS (n = 503) .Bisgaard FLG genotype and presence of older siblings among both children attending and those not attending daycare at 2 years of age in two separate studies – LISAplus cohort  and GINIplus cohort .One study reported an interaction between et al. found no evidence of an interaction between FLG genotype with parity , maternal asthma or AD  or the child's sex (P = 0·959)Henderson et al. conducted a parent‐of‐origin analysis investigating the effect of a child's FLG genotype and maternal and paternal FLG genotypes on the child's AD risk (n = 1209 families).FLG genotype in those whose mothers were or were not IgE sensitized. The child's FLG genotype had a stronger risk effect when mothers had normal IgE levels  compared with those who had sensitized mothers . However, CIs were wide and overlapping. Esparza‐Gordillo et al. reported the opposite for effect of maternal genotype, so it is unclear whether this evidence points to a true interaction with exposure to mothers with elevated IgE or whether the observation results from maternal genetic effects in utero or imprinting effects of FLG genotype.Esparza‐Gordillo FLG mutations and maternal smoking during pregnancy (n = 5140) or childhood environmental tobacco smoke exposure (n = 4874). Their results showed no evidence for either interaction .One study tested for possible interactions with et al. found evidence for a protective association between breastfeeding duration and AD in children aged 1 or 2 years (n = 885) carrying at least one FLG loss‐of‐function mutation (P = 0·02), with no evidence in those without an FLG null mutation (P = 0·64).et al. found no evidence for this interaction (P = 0·952) in their earlier, larger study (n = 5158).Ziyab et al. investigated FLG and year of birth in adults aged 18–69 years (n = 3202) but did not report any evidence of interaction (P = 0·19) on AD risk.Thyssen FLG genotype and water hardness has been investigated in two papers within the same cohort. Perkin et al. investigated the association between calcium and chlorine levels in water and AD during the first 3 months of life in the Enquiring About Tolerance study, a U.K. population‐based cohort of 1303 infants. Interaction tests did not show a statistically significant interaction between FLG genotype and high calcium‐low chlorine concentration in water, low calcium‐high chlorine or high calcium‐high chlorine concentrations.FLG loss‐of‐function mutations and water hardness increasing AD risk, when studying high calcium concentrations in water (> 256 mg L−1 CaCO3) from 3 months of age in this cohort .Interaction of FLG genotype was investigated by Berents et al. They measured serum vitamin D levels in 558 participants at age 1–13 months and 2 years alongside interviews assessing vitamin D intake. They did not find any evidence for an interaction (P > 0·13).A possible interaction between serum vitamin D levels and FLG genotype in children aged 3 years in the aetiology of AD (n = 453). They studied four phthalates, monoethyl phthalate, monobutyl phthalate (MBP), monobenzyl pthathlate (MBzP) and mono(2‐ethyl‐5‐hydroxyhexyl) phthalate, which they classified as lower or higher levels in relation to the median. They reported evidence for an interaction between the P478S genotype TT and phthalates MBP (P = 0·015) and MBzP (P = 0·018)et al. who assessed seven phthalates found in household dust, and 11 phosphorus flame retardants. They found evidence for an interaction between FLG loss‐of‐functions and diisononyl phthalate (P = 0·039).FLG loss‐of‐function mutation(s) in a categorical model . This analysis was undertaken on a sample size of five children with AD and FLG null genotypes and the researchers did not correct for multiple testing.Phthalates are added to plastic to increase flexibility. They have been reported to be associated with childhood AD.FLG genotype was assessed using accepted methodology  it is difficult to interpret the results, and findings must be interpreted with caution. Table Our results highlight important challenges when studying GEIs in the aetiology of AD. We identified only 12 articles that reported Our review has several strengths. A detailed search strategy was used to identify all relevant papers. Screening and data extraction were carried out in duplicate, with secondary resolution of conflicts, reducing the possibility of introducing bias by systematically selecting certain papers. The majority  of studies used data from cohort studies, thus they were able to consider temporality, and researchers mostly measured the outcome ‘AD’ using validated criteria.et al.,FLG–environment interactions, which by definition excluded the study of effects within populations where FLG null mutations are not prevalent or have not been identified.FLG null mutations are prevalent. Ongoing work to increase diversity in genetic researchOur findings should be considered in light of some limitations. Many studies were excluded from the review as they did not specifically test for GEI in their analyses. Studies were also excluded if they measured indirect outcomes of AD by examining IgE levels, transepidermal water loss, or skin‐prick tests, which are not measures of the outcome (AD), but responses to exposures. Many of the included studies performed GEI analysis as a secondary analysis, e.g. Berents et al. (FLG genotype and breastfeeding) and Henderson et al.Heterogeneity in methodology between published studies and the limited number of studies assessing the same exposure precluded meta‐analysis or formal assessment of publication bias. None of the included studies reported correcting for multiple testing; hence, interaction effects could be a result of chance. It is unclear how many studies had predefined hypotheses, which risks introducing reporting bias. Replication of findings was limited and in some cases where two studies investigated the same interaction, discordant findings were seen, such as Ziyab FLG null genotype) was small; hence, included studies were likely to be underpowered. The number of individuals with both a FLG loss‐of‐function mutation and exposure to the specific environmental factor was not always specified, but in those studies that did specify this number, it ranged from N = 5 to N = 167.One reason for the limited evidence for GEI and lack of replication is lack of statistical power. Detailed review showed that the number of individuals on which the interaction analysis was based (i.e. cases with both exposure and In complex diseases such as AD, where the main genetic effect sizes are small, a large sample size is necessary to detect small interaction effects.et al. study, which tested for an interaction between phthalate exposure and FLG genotype. To measure exposure, phthalate metabolite levels were measured using urine samples.Studies of GEI face inherent challenges in attempting to gain a full understanding of interactions because of the difficulty in uniformly measuring the environmental parameter, which in turn limits the understanding of the underlying disease mechanism.FLG haploinsufficiency might have different responses; for example, pet exposure and older siblings could act via microbial exposure, as proposed by the hygiene hypothesis.Variation in the timing of environmental exposure is important in terms of influencing subsequent disease risk, as timing of exposure may not be accurately measured with methods such as infrequent questionnaires.FLG loss‐of‐function mutations. The Early Genetics and Lifecourse Epidemiology consortium is investigating possible GEIs with selected SNPs associated with AD. Our recommendations for future studies of GEIs can be shown in Table GEIs are widely viewed as important in the aetiology of AD. However, the limited evidence and lack of power of published studies to detect GEI effects, as indicated by the sample‐size calculations we carried out, highlights the importance of further research. Such research is needed to test for replication of interactions reported to date Table  using laMethods S1 Search strategies.Methods S2 Method of screening and data extraction of relevant studies.Table S1 Inclusion and exclusion criteria.Table S2 Sample size required to detect gene–environment interaction.Table S3 Characteristics of studies of loss‐of‐function mutations in FLG and gene‐environment interaction in atopic dermatitis.Table S4 Studies examining the interactions between FLG mutations and environmental exposure and risk of atopic dermatitis.Click here for additional data file.Powerpoint S1 Journal Club Slide Set.Click here for additional data file.


Background: Rs13216675 T>C polymorphism, an SNP (single-nucleotide polymorphism) close to the gap junction protein alpha 1 (GJA1) gene, has been reported to be associated with risk of atrial fibrillation (AF); however, the results remained inconclusive. We aimed to perform a systematic review to clarify the relationship between rs13216675 and risk of AF.Materials and methods: We systematically searched the databases of PubMed, EMBASE, Web of Science, and the Chinese National Knowledge Infrastructure up to July 15, 2020. Data were synthesized using the random-effects model. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the relationship between rs13216675 and risk of AF.Results: Seven studies involving 39,827 cases and 458,466 controls were analyzed in the meta-analysis. The overall pooled OR of rs13216675 polymorphism for AF was significant  under the additive genetic model. Subgroup analyses revealed that rs13216675 polymorphism was significantly associated with AF in both Asians  and Europeans . When data were stratified by control sources, rs13216675 polymorphism was significantly related to AF in studies with both population-based controls  and hospital-based controls . No evidence of publication bias was detected.Conclusion: Our meta-analysis suggested that rs13216675 was significantly related to risk of AF and, therefore, might serve as a potential biological marker of AF. Atrial fibrillation (AF) is the most common type of cardiac arrhythmia, affecting over 33 million individuals worldwide, with a prevalence of 5.96 per 1,000 in men and 3.73 per 1,000 in women . AF is aGJA1 gene. One study reported that rs13216675 was associated with the susceptibility to AF  statement . A systeThe eligibility criteria included: (1) prospective or retrospective study on relationship between rs13216675 and early onset of AF; (2) prospective or retrospective study reporting incident of recurrent AF in patients after catheter ablation; (3) data available for extraction.Studies were excluded if one of the following criteria was fulfilled: (1) not relevant to rs13216675 polymorphism and AF; (2) case reports or case series; and (3) no information for data extraction. For duplicate reports, only the study with the largest sample size was included.P-value of HWE (Hardy–Weinberg equilibrium), and genotyping methods. Two reviewers (XC and GL) independently performed the data extraction and solved any disagreement by discussion.A standardized data collection form was used to obtain the information from each study: the surname of the first author, publication year, the country of origin, population, study design, sample sizes of cases and controls, number of genotypes, the adjusted relative risk (RR) or odds ratio (OR) of AF with its 95% confidence interval (CI), I2 statistic. Subgroup analyses were carried out by populations (Asian vs. European) and sources of control . The funnel plot and Egger's test were applied to evaluate potential publication bias.All statistical analyses were conducted with STATA version 12.0. We performed a meta-analysis of the included studies using a random-effects model. We pooled the point estimates from each study using the generic inverse-variance method of Der Simonian and Laird. The heterogeneity of effect size estimates across these studies was quantified using the The Newcastle–Ottawa scale (NOS) was employed to assess the quality of eligible studies from three aspects: (1) selection of cases and controls; (2) comparability between cases and controls; and (3) exposure in cases and controls. The NOS has a score ranging from zero to nine, and a higher score indicates higher study quality. Studies with a score of more than seven points were considered as of high quality .post hoc sensitivity analysis by omitting one study at a time and calculating pooled ORs for the remaining studies.Five predetermined sensitivity analyses were performed by: (1) excluding studies reporting RRs (rather than ORs), (2) excluding studies investigating AF recurrence after catheter ablation (rather than onset of AF), (3) excluding studies not with a case-control design, (4) applying a fixed-effects model, and (5) excluding studies not with a low-risk-of-bias. Moreover, we conducted a The literature search identified 9,100 studies from the databases. After excluding irrelevant and duplicate records by screening titles and abstracts, 28 potential eligible studies remained. We excluded 21 articles that had no data available for extraction. A total of seven studies containing 39,827 cases and 458,466 controls were included for analyses . CharactP < 0.001) (P < 0.001) and Europeans . Moreover, a significant association between rs13216675 and risk of AF was observed in both studies with population-based controls  and hospital-based controls   . Similar< 0.001) .a priori sensitivity analyses were conducted, with all reporting a statistically significant relationship between rs13216675 and risk of AF  based on a total of seven studies. Findings from subgroup and sensitivity analyses supported the robustness of our main result.Our systematic review and meta-analysis aimed to ascertain whether rs13216675 T>C polymorphism was significantly associated with risk of AF. A significant relationship was found between rs13216675 and risk of AF  for the potential mechanism related to AF susceptibility remains sparse and limited, leaving an important gap for further understanding of AF. In our systematic search, there was no study providing how rs13216675 may play a role in the development and progress of AF in detail. Only one recent report found that rs13216675 may play an important role in DNA methylation close to the PKIB gene CpG site to regulate gene expression and downstream biological processes by decreasing the methylation level, based on the data from Framingham Heart Study (Accumulating evidence indicates the AF locus . Connexi tissues . It was  tissues , 21. Thert Study .GJA1 rs13216675 and AF (P = 0.31 for subgroup difference. This may indicate a potentially consistent effect of rs13216675 on AF susceptibility across various ethnicities. However, as mentioned above, the pathophysiological mechanisms responsible for AF were still far from completely understood (Sinner et al. first reported the association between 5 and AF . Subsequ5 and AF . As showderstood , 25. Givpost hoc sensitivity analysis showed that these two individual studies did not substantially influence our main result (To the best of our knowledge, this is the first systematic review and meta-analysis assessing the association between rs13216675 T>C polymorphism and risk of AF. We performed a comprehensive and exhaustive search to retrieve all relevant studies. Data were extracted and managed in duplicate with a good level of consensus between the independent reviewers. Robustness was supported by rigorous statistical analyses including subgroup and sensitivity analyses. It should also be noted that some limitations existed for our study. First, the association between rs13216675 and risk of AF may be influenced by gene–gene and gene–environmental interactions ; howevern result , it wouln result . Taken tIn summary, our study found that rs13216675 polymorphism was significantly related to risk of AF and, therefore, might serve as a potential biological marker of AF. Further well-designed and adequately powered studies are needed to explore gene–environmental interactions and the potential targets related to rs13216675 for the prevention, treatment, and management of AF.The original contributions generated for the study are included in the article/XC and GL were responsible for the study conception, design of the study, data acquisition, and analysis and interpretation of results. ZY and YZ were responsible for data acquisition. XC wrote the manuscript that was reviewed and revised by GL, JZ, and XH. All authors contributed to the article and approved the submitted version.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.


Estimating the risk of pre-existing comorbidities on coronavirus disease 2019 (COVID-19) mortality may promote the importance of targeting populations at risk to improve survival. This systematic review and meta-analysis aimed to estimate the association of pre-existing comorbidities with COVID-19 mortality.st, 2019, to July 9th, 2020. The outcome of interest was the risk of COVID-19 mortality in patients with and without pre-existing comorbidities. We analyzed 11 comorbidities: cardiovascular diseases, hypertension, diabetes, congestive heart failure, cerebrovascular disease, chronic kidney disease, chronic liver disease, cancer, chronic obstructive pulmonary disease, asthma, and HIV/AIDS. Two reviewers independently extracted data and assessed the risk of bias. All analyses were performed using random-effects models and heterogeneity was quantified.We searched MEDLINE, SCOPUS, OVID, and Cochrane Library databases, and medrxiv.org from December 1Eleven pre-existing comorbidities from 25 studies were included in the meta-analysis . Overall, the between-study heterogeneity was medium, and studies had low publication bias and high quality. Cardiovascular disease (risk ratio (RR) 2.25, 95% CI = 1.60–3.17, number of studies (n) = 14), hypertension , diabetes , congestive heart failure , chronic kidney disease (3.25 [1.13 to 9.28)], n = 9) and cancer (1.47 [1.01 to 2.14), n = 10) were associated with a significantly greater risk of mortality from COVID-19.Patients with COVID-19 with cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease and cancer have a greater risk of mortality compared to patients with COVID-19 without these comorbidities. Tailored infection prevention and treatment strategies targeting this high-risk population might improve survival. CerebroThe risk of publication bias was found to be significant for hypertension, cerebrovascular disease, and cancer . Trim anSignificant between- study heterogeneity was observed for cardiovascular disease, hypertension, diabetes, cerebrovascular disease, chronic kidney diseases, COPD, and HIV/AIDS. If a specific comorbidity had more than 10 studies and exhibited significant medium or high between-study heterogeneity, we further conducted meta-regression to explore the sources of heterogeneity.  Mean or We further performed influence sensitivity analyses for outcomes with high between-study heterogeneity by excluding and replacing one study at a time (Leave-One-Out method) from the meta-analysis and calculated the RR for the remaining studies . No subsThe results of this systematic review and meta-analysis suggest that hospitalized patients with COVID-19 with pre-existing cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease and cancer have a greater risk of death from COVID-19.This review provides up-to-date results of comorbidities’ influence on the higher risk of mortality in patients with COVID-19 by synthesizing a large number of recently published studies. The study yielded a large number of individuals from countries representing Europe, North America, Africa, and Asia. Nevertheless, this meta-analysis had several limitations. While some studies reported the race and ethnicity of study participants, others provided little or no information. Thus, we could not investigate race and ethnicity’s influence, which could have been a cause of variation between studies. Due to a lack of individual patient-level data, we used study level data in meta-regression analyses to assess heterogeneity between studies. We were unable to identify the main sources of heterogeneity in the effect estimates. Perhaps future analysis could use individual patient-level data to explore sources of heterogeneity.Most of the studies included were at low risk of bias. Nevertheless, the NOS used to assess the included studies’ quality has low or unknown validity.  The alteMany of the included studies reported effect size estimates from all covariates within each model, which can induce multiplicity and lead to “the th, 2020, and included 4448 patients from 16 studies. [Our study findings are similar to results from previously published systematic reviews, suggesting a higher mortality rate of COVID-19 individuals with cardiovascular, chronic kidney disease and cancer. The overall 95% confidence interval obtained by Singh and colleagues overlapped with the one we identified. Pranata and colleagues assessed studies published until April 10studies.  They fouA probable hypothesis for the pathophysiological mechanism related to the higher risk of mortality among patients with COVID-19 with pre-existing chronic conditions may stem from the increased allostatic load. Chronic conditions cause dysregulation of major physiological system, including the hypothalamic-pituitary-adrenal axis, the sympathetic nervous system, and the immune system.  The chroAs the race towards developing a vaccine against SARS-CoV-2 intensifies, our results support the notion that individuals who appear to be at increased risk should receive immunization priority. Individuals with pre-existing cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease and cancer are at heightened risk of death from the virus, thus should be given a priority during the allocation of a vaccine, especially if it is in limited supply. Historically, targeted public health vaccination intervention strategy for influenza vaccination is recommended by the Advisory Committee on Immunization Practices against seasonal influenza.  In the pAce2 mRNA compared with a placebo. [Ace2 mRNA increased by 4.7-fold or 2.8-fold with either lisinopril (an ACE inhibitor) or losartan (an ARB), respectively. Nonetheless, recent clinical studies have found no association between the RAAS blockers and increased mortality from COVID-19. [The majority of patients with pre-existing cardiovascular disease, hypertension, diabetes, chronic kidney disease and congested heart failure use renin-angiotensin-aldosterone system (RAAS) blockers, which are postulated to increase the risk of developing a severe and fatal SARS-CoV-2 infection.  In experplacebo.  Notably,OVID-19. , 63 SuchOur findings suggest that of the major comorbidities analyzed, cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease, and cancer carry the highest risk of death from COVID-19. This research highlights the importance of paying attention to the populations with these specific comorbidities and tailor treatment to meet their need.S1 Table(DOCX)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S1 Checklist(DOC)Click here for additional data file.


Systemic sclerosis (SSc) is an autoimmune disorder leading to extensive fibrosis and microvascular injury. Macrovascular disease is well documented in other autoimmune rheumatic diseases such as systemic lupus erythematosus and rheumatoid arthritis. However, the link is unclear between SSc and macrovascular disease, particularly atherosclerotic cardiovascular disease (CVD). This meta-analysis aimed to investigate the association between SSc and CVD.A thorough literature search was conducted in the Cochrane, Embase, Medline, and PubMed to identify all cohort studies comparing the risk of CVD with and without SSc. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) of cardiovascular end points were calculated. The risk of bias of included studies was assessed by the Newcastle-Ottawa scale.Seven cohort studies with a total of 14,813 study participants were included. In a comparison of SSc patients versus non-SSc controls, the pooled HR for cardiovascular disease was 2.36 (95% CI 1.97–2.81); for peripheral vascular disease was 5.27 (95%CI 4.27–6.51); for myocardial infarction was 2.36 (95% CI 1.71–3.25); and for stroke was 1.52 (95% CI 1.18–1.96).This meta-analysis revealed that SSc was associated with an increased risk of CVD. Clinicians who manage patients with SSc should be aware of the increased cardiovascular burden and undertake preventive measures. The clinical presentation of SSc is characterized by Raynaud's phenomenon, skin thickening, and fibrosis of internal organs. Although the underlying pathology is unknown, autoimmune inflammation, fibrosis, and vasculopathy may be involved in the pathogenesis of SSc.,4Systemic sclerosis (SSc), also termed scleroderma, is a multisystem autoimmune disease affecting approximately 20 per million people.,5 Macrovascular impairment was not originally identified as a feature of SSc with manifestations such as myocardial infarction, stroke, and peripheral vascular disease. However, SSc patients have been shown to have decreased peripheral vascular reactivity and endothelial dysfunction compared with healthy controls. Several studies have revealed an increased prevalence of subclinical atherosclerosis in SSc via measurements of carotid intima-media thickness (CIMT) and flow-mediated dilatation (FMD) on Doppler ultrasound, and coronary artery calcification on multidetector CT.–9 Previous meta-analysis reported a higher incidence of coronary artery disease among patients with SSc. In addition, other autoimmune rheumatic diseases such as rheumatoid arthritis and systemic lupus erythematosus have been linked with an increased risk of developing cardiovascular disease (CVD), predominantly due to accelerated atherosclerosis.–14 The association between SSc and CVD, however, remains unclear.Involvement of the microvasculature is a prominent feature of SSc. Etiological factors include endothelial injuries, immune activation, proliferative obliterative vascular lesions, and progressive loss of capillaries. Increased risk of microvascular diseases in SSc, including Raynaud's phenomenon, pulmonary arterial hypertension, and renal crisis, has been well established.Therefore, in this study, we aimed to quantitatively synthesize current evidence on the association of SSc with CVD using a meta-analysis of cohort studies.2In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA), we performed this meta-analysis of cohort studies on the association between SSc and risk of CVD.2.1The Cochrane Library for literature, Embase, Medline, and PubMed were systematically searched from inception to October 14, 2019, without language or geographic restrictions. We used different combinations of terms “systemic sclerosis” OR “systemic scleroderma” and “cardiovascular disease” OR “peripheral vascular disease” OR “myocardial infarction” OR “stroke” and “cohort study.” We also screened the reference lists of all articles identified . The study protocol was approved by the Ethics Committee of the Zhujiang Hospital of Southern Medical University.2.2Two independent authors (XC and LY) screened the titles and abstracts of the search results. The remaining full text of articles was assessed for eligibility. Any disagreements were resolved by consensus. Studies were eligible for inclusion if they were cohort studies; reported a quantitative association between SSc and risk of CVD versus non-SSc; enrolled participants without a history of CVD; and had at least 1-year follow-up. Studies were excluded if they were case-control studies or cross-sectional studies; were case series, reviews, abstracts or conference articles; did not report on CVD outcomes of interest.2.2.1Data were extracted independently by 2 authors (LY and SW), using a pilot-tested form. For each study, the following information was extracted: first author name, year of publication, country, study design, study period, participant characteristics, outcomes, outcome assessment, number of cardiovascular disease cases, and mean follow-up years. The risk of bias in cohort studies was assessed by the Newcastle-Ottawa scale.2.3We chose to perform a meta-analysis on adjusted results from included studies. We used hazard ratio estimates that were fully adjusted for confounding factors .2 value greater than 50%. Publication bias was evaluated by visual inspection of funnel plots and by identifying asymmetry of funnel plots using the Egger test.This statistical analysis was conducted using Review Manager software, version 5.3 (The Cochrane Collaboration) and Stata software, version 12.1 (StataCorp). We calculated pooled hazard ratios (HRs) with 95% confidence intervals (95% CIs) of cardiovascular end points in patients with SSc when compared with non-SSc controls. Specifically, these included cardiovascular disease, peripheral vascular disease, myocardial infarction, and stroke. A generic inverse-variance (IV) method was used to pool the data with a random-effects meta-analysis model. Statistical heterogeneity was quantified with the I-squared statistics for each end point category. Substantial heterogeneity was defined as an I3The PRISMA study flow diagram is shown in Figure 3.1 USA,,20 the UK, Denmark,,22 and Taiwan.,24 The 7 studies included a total of 14,813 SSc patients and 5,506,836 controls. The SSc cohorts had mean follow-up period that ranged from 4.3 to 5.2 years. The assessment of outcomes varied among these studies.The basic characteristics of the included cohort studies are presented in Table 3.23.2.12 = 44%, P = .18) , and mild heterogeneity was detected  . No statistically significant heterogeneity was found across these studies  . Substantial statistical heterogeneity was observed across these studies  . There was substantial statistical heterogeneity between studies .4In this meta-analysis of 14,813 study participants from 7 cohorts, SSc was significantly associated with higher risks of cardiovascular disease, peripheral vascular disease, myocardial infarction, and stroke. In this work, Ungprasert et al analyzed 4 cohort studies and found a significant association between SSc and increased risk of stroke . However, some limitation to select data in their study should be noted. They included the study by Zoller et al using hospital-based data, which may lead to potential selection bias. Considering several limitations of Ungprasert's study, our meta-analysis provides more precise estimates using nation- or state-wide data.Our study indicated that patients with SSc were prone to have comorbid CVD. A previously published meta-analysis investigated the risk of stroke in patients with SSc.,21 Consequently, to confirm the association between SSc and CVD more exactly, these points in study design should be taken into account in future prospective cohort studies.Most of the included cohort studies were deemed to have a low risk of bias according to the Newcastle-Ottawa Scale. We evaluated the two included studies as having a high risk of bias because of study participants from a specific group and no control for confounder factors. SSc has been characterized by T-cell activation and autoantibody formation. Various pro-inflammatory cytokines that have been associated with both atherosclerotic plaques and CIMT, including interleukin (IL)-2, IL-6, and C-reactive protein, have been shown to be increased in patients with SSc.,28 Furthermore, emerging studies have found that autoantibodies may have a role in atherogenesis, including those against oxidized low-density lipoproteins (ox-LDL), β2-glycoprotein-I (β2GPI), centromere and cardiolipin.,30 Anti-centromere antibody (ACA) is one of the specific hallmark antinuclear antibodies (ANAs) of SSc. Ischemic macrovascular events and plaques are more common in the ACA positive SSc patients when compared with both ACA negative SSc patients and controls.The mechanisms for the increased risk of atherosclerotic cardiovascular disease in patients with SSc are far from being fully elucidated. One possible mechanism is inflammation. In addition, several evidences have suggested that high levels of reactive oxygen species (ROS) and oxidative stress caused by endothelial dysfunction and vascular inflammation, was observed in SSc, leading to oxidation of LDL. Accumulation of oxidized low-density lipoproteins triggers endothelial cell activation and further amplifies inflammatory processes.,33,34 The derangement of vasoactive mediators has also been suggested to be an essential component of endothelial dysfunction in SSc, with upregulation of vasoconstrictive endothelin and downregulation of the vasodilator nitric oxide. Inflammatory vascular injury, intimal proliferation and fibrosis may result in the formation and development of atherosclerotic plaques.,36 Thus, inflammation and endothelial dysfunction may contribute to the pathogenesis of vascular abnormalities in atherosclerosis and SSc.Another possible mechanism is endothelial dysfunction, which is the key event in the pathophysiology of SSc and atherosclerosis. Although the original stimulus is unknown, endothelial cell injury is regarded as a main driver of vascular alterations, increased matrix deposition and excess fibrous tissues characterizing SSc. Activated endothelial cells express adhesion molecules that promote the recruitment and transmigration of inflammatory cells into vessel walls and infiltration of the extracellular matrix.–39 Compared with earlier cohorts, later cohorts were more likely to contain a larger number of patients with early mild SSc, which may tend to bias the results in the assessment of CVD risk. Thirdly, there was some evidence that the rate of cardiac involvement in diffuse cutaneous SSc was higher than that in limited cutaneous SSc. However, we could not evaluate the risks for the two major disease subtypes because no studies examined the association between different subtypes of SSc and CVD. Fourthly, most studies were conducted in Caucasian populations. Several evidences have revealed that SSc in blacks had more severe clinical manifestations and greater mortality than in whites.,42 Considering racial differences, more studies in other ethnicities such as Afro-Americans and Asians are needed. Finally, we could not rule out the possibility of residual confounding because no data was available on traditional cardiovascular risk factors, such as body mass index, smoking and family history of CVD.This study has several limitations. Firstly, there was substantial statistical heterogeneity with regard to the outcomes of stroke and myocardial infarction, given the differences in baseline characteristics such as gender, age and SSc history. Although we used random-effects models and pooled only studies with similar outcomes, it did not eliminate heterogeneity. Secondly, none of the primary studies provided information on disease severity of SSc. However, because of the evolving classification criteria and the growing use of serum markers and capillaroscopy, patients fulfilling SSc criteria have increased.Despite these limitations, this study has some strengths. First, to our knowledge, this is the largest study of adults with SSc and long-term follow-up of cardiovascular outcomes. Second, only large-scale cohort studies providing more definitive evidence were included. We excluded cross-sectional and case-control studies, which highly reduced the likelihood of recall bias and selection bias. Third, considering the degree of risk, a meta-analysis provides greater statistical power to detect potential associations in comparison with individual studies alone.In conclusion, this meta-analysis confirms a significant association of SSc with CVD. Future studies should focus on identifying risk factors for CVD in SSc, such as clinical subtypes or disease severity. Furthermore, clinicians who manage patients with SSc should be aware of the increased risk of CVD from the time of SSc diagnosis and undertake preventive measures.LS conceived and designed the study. XC and LY did the literature review. LY and SW extracted the data and performed the analysis. XC and LY wrote and edited the manuscript. All authors revised the manuscript and provided approval of the final version.Conceptualization: Ledong Sun.Data curation: Shanshan Wei, Lu Yan.Formal analysis: Shanshan Wei, Lu Yan.Investigation: Xintao Cen, Lu Yan.Software: Shanshan Wei, Lu Yan.Supervision: Ledong Sun.Writing – original draft: Xintao Cen, Sining Feng.Writing – review & editing: Xintao Cen, Sining Feng.


Inflammation is one of the factors associated with prostate cancer. The cytokine tumor necrosis factor-alpha (TNF-α) plays an important role in inflammation. Several studies have focused on the association between TNF-α polymorphisms and prostate cancer development. Our meta-analysis aimed to estimate the association between TNF-α rs1800629 (− 308 G/A), rs361525 (− 238 G/A) and rs1799724 polymorphisms and prostate cancer risk.Eligible studies were identified from electronic databases  using keywords: TNF-α, polymorphism, prostate cancer, until Nov 15, 2019. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to determine the association from a quantitative point-of-view. Publication bias and sensitivity analysis were also applied to evaluate the power of current study. All statistical analyses were done with Stata 11.0 software.P = 0.580 in the allele for rs1800629; OR = 0.95, 95% CI = 0.84–1.07, P = 0.381 in the allele for rs1799724). The rs361525 polymorphism also had no association with prostate cancer in the cases  and ethnicity subgroup. The stratified subgroup of genotype method, however, revealed that the rs361525 variant significantly decreased the risk of prostate cancer in the Others  and PCR-RFLP  methods.Twenty-two different articles were included . Overall, no significant association was found between rs1800629 and rs1799724 polymorphisms and the risk of prostate cancer in the whole (such as: OR = 1.03, 95% CI = 0.92–1.16, In summary, the findings of the current meta-analysis indicate that the TNF-α rs1800629, rs361525 and rs1799724 polymorphisms are not correlated with prostate cancer development, although there were some pooled positive results. Further well-designed studies are necessary to form more precise conclusions. Prostate cancer (PCA) is the second most frequent tumor in men worldwide, with 1.27 million new cases and 0.35 million deaths in 2018 [P < 0.05) in the control group (5.12 pg/ml) than in the localized PCA group (2.20 pg/ml). Moreover, TNF-α was the strongest single predictor between localized and metastatic PCA  and was higher than the PSA value (AUC = 0.963). Taken together, these results suggest that TNF-α may be considered a novel serum biomarker for the diagnosis of PCA [There is growing evidence that chronic inflammation is involved in the regulation of cellular events in prostate carcinogenesis, including disruption of the immune response and regulation of the tumor microenvironment . One of s of PCA .The TNF-α gene, also termed DIF/TNFSF2/TNLG1F, is located in the class III region of the major histocompatibility complex (MHC III) and mapped to chromosome 6p21.33 with 4 exons , 9. SevePreviously, two meta-analyses focused on TNF-α polymorphisms and PCA risk have been published: Cai et al. identified 12 case-control studies and concluded that the rs1800629 polymorphism had an increased association with PCA risk in the GA vs. GG genetic model  . Ma et aWe performed a literature search for all eligible articles regarding the association between four TNF-α polymorphisms and PCA risk on multiple electronic databases, including PubMed, Embase, Wanfang and CNKI, using the following keywords: ‘tumor necrosis factor alpha OR TNF-α’ AND ‘polymorphism OR variation OR mutation’ AND ‘prostate cancer OR carcinoma OR neoplasm OR tumor’ until Nov 15, 2019.Relevant studies were selected based on the following inclusion criteria: (1) case-control studies addressing the correlation between a TNF-α polymorphism and PCA risk; (2) studies containing sufficient genotype data on both the cases and controls; and (3) the largest sample sizes were selected among articles with overlapping study groups. The exclusion criteria were (1) conference abstracts, case reports, reviews and duplicated information; and (2) inadequate genotype data.The following data were gathered from each eligible study: the first author’s name, publication year, country, sample size for the case and control groups, source of control, Hardy-Weinberg equilibrium (HWE) of the controls, genotyping techniques and the genotype of the cases and controls.Z-test, and P < 0.05 was considered to be statistically significant. The between-study heterogeneity was evaluated by the Q-test. In cases where significant heterogeneity was detected, if P < 0.1, indicating the presence of heterogeneity, a random-effects model was selected; otherwise, a fixed-effects model was applied [P < 0.05 was considered statistically significant [P < 0.05 was considered significant [The strength of the association between the four TNF-α polymorphisms and PCA susceptibility was measured by the odds ratio (OR) with 95% confidence interval (CI) in 3  genetic models. The significance of the pooled OR was assessed by the  applied , 38. Pubnificant . The HWEnificant . SensitiA total of 168 published articles were retrieved from the PubMed, Embase, Wanfang and CNKI databases in accordance with the selection criteria. Finally, 20 different articles (22 case-control studies) were included in our meta-analysis  and dominant  genetic models. To evaluate the power and stability, some studies not consistent with HWE were excluded, and similar results were obtained. Stratified analyses by ethnicity, source of control and genotyping methods were conducted, and no significant association was detected  and dominant genetic models .For the TNF-α rs1799724 polymorphisms, no significant associations were identified in the cases and subgroups. Further, the rs1799724 polymorphism was not significantly associated with PCA in the allele , heterozygous , for HWE, ethnicity and source of control, pooled significant relationships were observed in genotyping subgroups, such as Others  are not associated with PCA risk, which should be verified in the future, but they may be poised to become serum biomarkers in several subgroups for the detection of PCA susceptibility.


We performed a systematic review and meta-analysis of the Matrix metalloproteinases (MMP)-9 (C1562T), MMP-9 (R279Q), MMP-9 (P574R) and MMP-9 (R668Q) polymorphisms and risk of Coronary Artery Disease (CAD).After a systematic literature search, pooled odds ratio (OR) and their corresponding 95% confidence interval (CI) were used to evaluate the strength of the association.P < 0.001), recessive model , allelic model , TT vs. CC model , and CT vs. CC model . Moreover, the subgroup analysis based on the continent of the study populations in this SNP indicated strong significant association in Asians but not in Europeans. Subgroup analysis was not performed in Africa, America and Oceania, due to lack of sufficient data.We identified 40 studies with 11,792 cases and 8280 controls for C1562T, 7 case-control studies with 5525 cases and 2497 controls for R279Q, 2 studies with 1272 cases and 785 controls for P574R, and 2 studies with 1272 cases and 785 controls for R668Q. MMP-9 (C1562T) polymorphism was associated with increased risk of CAD under dominant model  SNP conferred a susceptibility risk for CAD in the overall analysis and Asian population. The overall analysis and subgroup analysis of the other three SNPs reject the association between MMP-9 polymorphisms and the risk of CAD. Although the results should interpret with caution because of small sample size of included studies in these three SNPs. Coronary artery disease (CAD) is a worldwide medical problem that is the leading cause of death in both developed and developing countries, especially in older people , 2. Seve. This enzyme is involved in the degradation of extracellular matrix (ECM) components, such as type IV collagen, which is involved in the neovascularization, angiogenesis, inflammatory processes, and development of atherosclerosis.MMPs are zinc containing enzymes that belong to a neutral protease family. Among the MMP family, MMP-9 is the most important enzyme of this class that is produced by the cells in the vascular wall. Moreover, inflammatory immune cells, such as neutrophils, monocytes as well as endothelial cells and vascular smooth muscle cells (VSMCs) generate MMP-9 . This enThe MMP family is grouped into gelatinizes , collagenases , stromelysins , and the membrane-type MMPs (MT-MMPs) that are coded by separate genes and have different tissue distribution and bioactive function .P > 0.05) [Several studies have shown that MMP-9 family polymorphisms might be associated with the risk of CAD –18. Howe > 0.05) . However > 0.05) . The cauWe followed a protocol based on observational studies in epidemiology (MOOSE) guidelines , and resAn exhaustive systematic search was conducted through electronic databases  retrieving all potential publications considered the association between MMP-9 family gene polymorphism and susceptibility to CAD. All publications from inception to February 2020 were included (the search was updated before manuscript submission). The combination of key words and Mesh  terms were as follow:  AND  AND (“single nucleotide polymorphism” OR “SNP” OR “polymorphisms” OR “mutation” OR “variation”). The references of review articles were cross-checked to find potential publications. Only human studies and English language publications were considered.We screened retrieval publications according to following inclusion criteria: 1) observational studies (cohort or case-control design); 2) publications considered the association between MMP-9 family gene polymorphism  and susceptibility to CAD; 3) publications reporting sufficient data to extract or calculate risk estimates with 95% CI; 4) publications reporting numbers or genotype frequencies in cases and healthy controls. Duplicates, book chapters, letters to editor, animal study, case reports, review articles, and studies with repetitive subjects all were excluded. The application of these criteria recognized 40, 7, 2, and 2 eligible studies for C1562T SNP, R279Q SNP, P574R SNP and R668Q SNP, respectively.Two authors screened the literature and extracted data independently according to the inclusion and exclusion criteria. The following data was extracted: the first author’s name, journal and year of publication, country of origin, ethnicity, number of subjects in the case and control groups, mean or range of age, genotyping method, genotype counts in the case and control group.The quality of eligible studies was assessed by using the Newcastle-Ottawa Scale (NOS) . StudiesP value less than 0.1 and I2 exceed 50%, the random effects model (REM) was used; otherwise, the fixed effect model (FEM) was applied [P < 0.05 was regarded as statistically significant publication bias) [In the current meta-analysis, the strengths of association between MMP-9 family gene polymorphism and the risk of CAD was estimated via the OR and 95% CI in five genetic models: dominant model, recessive model, allelic model, homozygote contrast, and heterozygotes contrast. The potential heterogeneity was evaluated by the Q test and the I2 test . Accordi applied , 25. Addon bias) , 27. BesThe search and screening process workflow is shown in Fig. P < 0.001), recessive model , allelic model , TT vs. CC model , and CT vs. CC model . FEM was used for recessive and homozygote compressions and REM was applied for dominant, heterozygote, and allelic models. Furthermore, the results of subgroup analysis by ethnicity remarkably showed that MMP-9 (C1562T) polymorphism increase the susceptibility of CAD in the Asian under all genotyping models; dominant model , recessive model , allelic model , TT vs. CC model , and CT vs. CC model   polymorphism and CAD susceptibility , 63, 64.MMP9 (C1562T) polymorphism and stable angina susceptibility across all genotype model. However, the positive association between MMP-9 (C1562T) polymorphism and ACS susceptibility was observed in dominant model , allelic model , CT vs. CC model , but not recessive model  and TT vs. CC model  and stable angina. The findings demonstrated a statistically significant association between There were 7 case-control studies with 5525 cases and 2497 controls concerning MMP-9 (R279Q) polymorphism and risk of CAD , 50, 62.For MMP-9 (P574R) SNP, two studies with 1272 case and 785 controls were included for quantitative analysis , 50. StuTwo studies with 1272 case and 785 controls were included for quantitative analysis for MMP-9 (R668Q) SNP , 50. Stu2 and Q test was significant in some models  to measure publication bias Fig. . Overallls Table .Fig. 4B. The significance of ORs was not altered through omitting any single study, indicating that our results were statistically robust Up until now, numerous investigations have been performed to address the association between SNPs of the MMP gene family, including MMP-9 (C1562T), MMP-9 (R279Q), MMP-9 (P574R), and MMP-9 (R668Q) polymorphisms and risk of CAD. The findings of these investigations have sometimes been in accordance with each other, but sometimes conflicting. By meeting the limitations of the individual studies, such as little statistical strength and small sample size, meta-analysis studies provide a beneficial tool to settle these limitations and confer a conclusive outcome. In order to solve this issue in respective of MMP-9 gene family polymorphisms and risk of CAD, here we carried out this meta-analysis by including the most comprehensive and up-to-date original studies worldwide to come up with valid approximation of this association. In the current meta-analysis, we included 40 studies with 11,792 cases and 8280 controls for MMP-9 (C1562T) SNP, 7 case-control studies with 5525 cases and 2497 controls for MMP-9 (R279Q) SNP, 2 studies with 1272 case and 785 controls for MMP-9 (P574R) SNP, and 2 studies with 1272 case and 785 controls for MMP-9 (R668Q) SNP. The analysis indicated that MMP-9 (C1562T) SNP was significantly associated with increased risk of CAD susceptibility in the overall analysis and Asian population particularly.MMP9 gene, migration potency of the VSMCs as well as atherosclerosis lesions were reduced in comparison to the wild-type animals [Different human and animal experiments have suggested that there is an elevated level of MMP-9 in the atherosclerotic arteries in comparison to health controls. It was also shown that MMP-9 is predominantly active in the lipid core margin of the atherosclerotic plaques, the shoulder regions of plaque, and in regions with active formation of microvessels. As a consequence, it appears that MMP-9 plays a critical role in the stability/instability of the coronary artery plaques and development of myocardial infarction during CAD . In addi animals . Accordi animals . Based o animals .MM9 gene, including MMP-9 (R279Q), MMP-9 (P574R), and MMP-9 (R668Q) polymorphisms, were not associated with CAD risk.Zhang et al. in the 214 meta-analysis, by including 26 studies containing 12,776 cases and 6371 controls, indicated that MMP-9 (C1562T) polymorphism was not associated with the risk of CAD in the overall results . HoweverP < 0.001), recessive model , allelic model , TT vs. CC model , and CT vs. CC model , which was associated with an increased risk of CAD significantly. Upregulation of MMP-9 may be involved in the CAD development by multiple approaches, including increased proliferation and migration of VSMCs, remodeling of the injured vascular cells, and enhancing the plaque instability and rupture (that leads to the development of thrombosis), eventuating in myocardial infarction and CAD [Regulatory mechanisms at the transcriptional level is involved in the modulation of MMP-9 expression. The MMP-9 (C1562T) SNP is harbored within the 9 bp sequence GCGCAC/TGCC (− 1567 → − 1559), which is considered as a regulatory element of the gene and confers a site for binding of molecules involved in the inhibition of transcription . It was  and CAD .MMP9 gene SNPs and the risk of CAD, a number of limitations and caveats of this meta-analysis study should be taken into consideration. First, the number of studies and sample size for MMP-9 (R279Q), MMP-9 (P574R), and MMP-9 (R668Q) polymorphisms in this meta-analysis was relatively small to conclude a valid report of the association of these SNPs and CAD risk. Second, we searched for the articles published in only the English language and a number of potential studies might be omitted. Third, this meta-analysis was based on a crude analysis of the genetic polymorphisms, and the adjusting the analysis by gender, age, and other environmental factors were not implemented. Fourth, we detected some degrees of heterogeneity for the analyzed SNPs, that might stem from difference in genetic stratification and ethnicity, diversity in the environmental factors in different populations, and the detection methods.In spite of an attempt to perform the most comprehensive meta-analysis of the MMP9 gene SNPs in association with CAD. We reported that MMP-9 (C1562T) SNP conferred a susceptibility risk for CAD in the overall analysis and Asian population. That notwithstanding, other three polymorphisms were not associated with disease risk, probably due to little sample size. Hence, we warrant further studies with respect to evaluation of other MMP9 gene SNPs in association with CAD. Furthermore, the role of other factors, such as age, gender, environmental contributing factors as well as other MMP9 gene variations in the analyses ahead will hopefully shed further light on the bona fide association of MMP9 gene polymorphisms and risk of CAD susceptibility.Taken all the evidence into conclusion, this was the most comprehensive evaluation of the four


Published data on the relationship between pregnancy outcomes of preimplantation genetic diagnosis (PGD) in translocation carriers have implicated inconclusive results. To identify potentially eligible reports, an electronic search was conducted in several databases, including PubMed, Scopus, Web of Knowledge, and Cochrane. Pooled odd ratios (ORs) and 95% confidence intervals (Cis) were estimated based on a random-effect model to evaluate the strength of association between PGD and successful pregnancy outcome in translocation carriers. A total of six cohort studies were included in the current study. The meta-analysis of these studies revealed that the PGD method was associated with an increased successful pregnancy outcome of translocation carriers . In subgroup analysis, there was no significant association according to the chromosomal translocation carrier origin and the type of translocated chromosomes, as well as country. In developed countries, the pregnancy outcome of PGD was significantly improved in translocation carriers . The current meta-analysis demonstrated that the PGD method is associated with successful pregnancy outcome in both types of reciprocal and Robertsonian translocation carriers, especially in developed countries. Chromosome structural rearrangement, including reciprocal and Robertsonian translocation, is the most common type of chromosome abnormality.Although there is a high probability for a successfully natural outcome in many translocations, patients carrying translocations with a significant risk of viable abnormality are increasingly pursuing to improve their chances of a normal pregnancy with the help of preimplantation genetic diagnosis (PGD).In recent years, various studies indicated that PGD may play pivotal roles in increasing successful pregnancy outcome in translocation carriers.The major reason for using PGD in translocation carriers is the reduction of miscarriages and more live births by eliminating the transfer of abnormal embryos. However, there is insufficient evidence regarding the pregnancy outcome for translocation carriers who underwent PGD and those of non-PGD patients. The statement that PDG increases successful pregnancy outcomes should be confirmed before the technique is applied for daily clinical practice. To improve informed decision making, we conducted a meta-analysis regarding clinical effectiveness and pregnancy outcomes after PGD, in couples carrying translocation chromosomal abnormality in comparison to none-PGD group. Until now, no meta-analysis has been performed to investigate this purpose. The aim of the present study was to assess the outcome of PGD in couples who at least one partner is a carrier of a reciprocal or Robertsonian translocations.The databases PubMed, Scopus, Web of Knowledge, and Cochrane were systematically searched for all available articles published till 2018, without considering limitation for any age range, time, or language. Publications with the following search words in the titles, abstract, or keywords of the original studies were included: “clinical effectiveness” OR “outcome” OR “pregnancy outcome” AND “preimplantation genetic diagnosis” OR “PGD” OR “PGP” OR “preimplantation genetic profiling” AND “translocation” OR “Chromosomal translocation.” We also improved this search by reviewing the reference lists of all of the retrieved publications and identifying supplementary relevant articles.For our meta-analyses, articles with the following criteria were includedThe articles were selected and extracted of the original data by two of the authors (M.M. and S.S.D.) independently using a standardized and consistent method. The following information was collected from each study: first author, year of publication, ethnicity of the patients, numbers of cases and controls, PGD method and variables adjusted for in the analysis, as well as multivariate adjusted ORs and 95% CIs.Z-test. All statistical analyses were conducted using STATA software  andp < 0.05 was considered statistically significant. To detect heterogeneity among studies, the Chi-square test–based Q statistic was performed and was quantified using theI2statistic.p < 0.05 andI2 > 50%), random-effect model (the DerSimonian–Laird method) was employed.p < 0.05 for these tests indicate significant publication bias.The pregnancy outcome of PGD in translocation carrier populations was estimated by calculating pooled ORs and associated 95% CI. The significant of the pooled OR was determined byA detailed ﬂow chart of the study selection process is shown inI2 = 96.8%). For the subgroup analysis, according to country (I2 = 96.4%) but no significant association was found in Asian countries . Moreover, for the translocation carrier origin , significantly increased successful pregnancy outcome of PGD in translocation carriers was not found in female  and one of the partner carriers  and autosomal chromosomes 1 to 22  group  group .In the present meta-analysis, significant heterogeneity was observed. We next performed a sensitivity analysis by removing the individual studies sequentially to assess the effect of individual studies. The results showed that there was no different from the initial analysis (figure not shown), suggesting that the results of the meta-analysis were strong.p = 0.16) suggested no evidence of publication bias in the meta-analysis.Funnel plot and Egger's test were executed to access publication bias. Both funnel plots  and EggIt is well known that chromosomal abnormalities, such as translocation, are of important reasons for recurrent miscarriage losses. PGD might seem an attractive alternative for couples carrying chromosomal translocation.PGD analysis of translocations' embryos has been studied since the 1990s.Our meta-analysis illustrates strong evidence for significant association between the pregnancy outcome of PGD in reciprocal and Robertsonian translocation carriers. The findings from subgroup analysis indicated the significantly positive effect of PGD on pregnancy outcome in translocation carriers from developed countries not at Asian countries. However, Kyu Lim et al reported that spontaneous abortion rate could be significantly reduced by PGD in translocation carries from Korean population.In Asian studies, all of the participants had only translocation with two or more consecutive clinical miscarriages,The clear evidence of heterogeneity in this meta-analysis should be discussed. Though a sensitivity analysis was performed, the origin of the heterogeneity among the studies was not found. The heterogeneity might have been due to other factors, such as diversity in the population characteristics , PGD methods, and study design. Our meta-analysis was based on estimates without adjusting the data for these factors, which is the potential limitation of this study. Some another limitations of our meta-analysis was the insufficient number of studies, especially for subgroup analysis and languages of the publications.In conclusion, this meta-analysis provide reliable evidence that the PGD method is associated with the development of pregnancy outcome in translocation carriers, especially in developed countries. However, it is required to conduct further larger scale, multicenter, and high-quality studies in the future.