MTHFR) C677T (rs1801133) gene polymorphisms are related to a growing risk of Alzheimer's disease; however, whether this association applies to mild cognitive impairment (MCI) remains unclear.  Methylenetetrahydrofolate reductase (MTHFR C677T (rs1801133) gene variants to the risk of MCI.  We conducted this meta-analysis to evaluate the contribution of MTHFR C677T (rs1801133) gene variants and MCI susceptibility. Forest plots of pooled odds ratios (ORs) and 95% confidence intervals (CIs) were generated.  PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched from their inception to March 21, 2021, with language restricted to English or Chinese. We used fixed or random effects to examine the association between MTHFR C677T (rs1801133) gene variants and MCI susceptibility under the allelic , dominant , recessive , heterozygous , or homozygous  models.  Eight articles with 2,175 participants were included in the present meta-analysis. There was no significant association between MTHFR C677T (rs1801133) gene polymorphisms are not associated with MCI susceptibility. However, large-scale studies covering various factors are required. The results suggest that  Mild cognitive impairment (MCI) is defined as a transitional stage between normal aging and dementia , that isMTHFR) C677T (rs1801133) gene polymorphisms were associated with Hcy concentration [Several studies have shown that a higher serum homocysteine (Hcy) concentration increases the risk of cognitive function impairment, such as AD, vascular dementia, and Parkinson's disease –15. Seruntration .MTHFR gene, where the cytosine is replaced by thymidine (C→T) at nucleotide position 677 [MTHFR C677T (rs1801133) polymorphic allele carriage [MTHFR, the key enzyme of folate and Hcy metabolism , catalyztion 677 , are asstion 677 . Severe tion 677 . Recentlcarriage . The TT carriage , 24. Parcarriage , 26.MTHFR C677T (rs1801133) gene mutations and AD susceptibility [MTHFR C677T (rs1801133) gene polymorphisms and the risk of MCI [MTHFR C677T (rs1801133) gene polymorphisms to MCI susceptibility with greater precision.Extensive studies have reported that there was an association between tibility , 27–29. k of MCI –32, the MTHFR C677T (rs1801133) polymorphisms and MCI susceptibility. PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched from their inception to March 21, 2021, by two reviewers independently. The following search term combinations were used: (MTHFR or C677T or homocysteine) and (polymorphism or variant or mutation or SNP) and (cognitive or cognition), which were adjusted based on the characteristics of the database  guidelines . We perf C677T rs801133 poMTHFR C677T (rs1801133) gene polymorphism as the exposure factor, (3) control group individuals with normal cognitive function, and (4) case-control study design or cohort study design. The exclusion criteria were as follows: (1) repeated publication, (2) full text unavailable, and (3) genotype distributions unavailable for both cases and controls to calculate odds ratio (ORs) or 95% confidence intervals (CIs).Studies included in the meta-analysis met the following criteria: (1) patients with MCI, (2) MTHFR polymorphisms, allele and genotype distribution, and sample size. “C” is used to indicate the wild-type allele while “T” indicates a mutant allele of single-nucleotide polymorphisms (SNP), respectively (C>T). We assessed the quality of eight retrospective studies, according to the Newcastle-Ottawa Scale (NOS), by examining three factors: patient selection, comparability of the study groups, and assessment of outcome [The data extracted from the candidate studies included the first author, publication year, country, study type, ethnicity, age, sex,  outcome . A score outcome , while sI2 tests were used to examine the heterogeneity among the studies. A fixed effects model was adopted if heterogeneity was acceptable ; otherwise, a random effects model was adopted. The pooled OR was assessed using the Z test and defined p value < 0.05 as statistical significance. The chi-square test was used to determine the Hardy–Weinberg equilibrium (HWE) for the genotype frequencies, and p < 0.05 was considered a significant imbalance. Sensitivity analysis for this meta-analysis was conducted by sequentially omitting one study at a time to evaluate the stability of the results. We performed subgroup analysis by stratification by ethnicity (Asian and Caucasian). To evaluate any potential publication bias, the funnel plot and Egger's linear regression tests were adopted, and publication bias was defined as a p value of <0.05.All analyses were performed using Stata version 15.0 . Five separate analyses, the allelic model (T vs. C), dominant model (CT+TT vs. CC), recessive model (TT vs. CC+CT), heterozygous model (CT vs. CC), and homozygous model (TT vs. CC), were conducted in this meta-analysis. Pooled ORs and 95%, 95% CIs were used to assess the association between C677T (rs1801133) gene mutations and MCI susceptibility. Chi-square and A total of 538 potentially relevant studies were retrieved from the four databases. After 185 duplicates and 318 studies according to titles and abstracts were eliminated, the full texts of 35 articles were examined in detail; only eight papers –43 met aMTHFR C677T (rs1801133) genotypes and allele frequencies in MCI cases and controls are shown in Eight studies were included in the present meta-analysis, involving 1,183 patients with MCI and 992 controls. I2 was less than 50% in the heterozygous model; therefore, a fixed effects model was adopted. Random effects models were adopted in other gene models because of significant heterogeneity (I2 > 50%). Forest plots of pooled ORs with the corresponding 95% CIs are shown in MTHFR C677T (rs1801133) polymorphism was not significantly associated with the risk of MCI in any of the genetic frameworks, i.e., the allelic model , dominant model , recessive model , heterozygous model , or homozygous model  (The = 0.160) .MTHFR C677T (rs1801133) gene polymorphisms and MCI susceptibility. Similar to the above results, no statistically significant association was observed in Caucasians or Asians under any genetic model between MCI risk and MTHFR C677T (rs1801133) genotype  and heterozygous (p = 0.005) models, but no evidence of publication bias was found in the other gene models  gene polymorphisms and MCI susceptibility based on a broad range of studies involving 2,175 participants. In the current study, we did not find any statistically significant evidence that MTHFR C677T (rs1801133) gene variants can contribute to MCI susceptibility. No association between MTHFR C677T (rs1801133) gene polymorphisms and the risk of MCI was observed in the stratified analysis. The heterogeneity of the study was significant.To our knowledge, this study represents the first meta-analysis of MTHFR C677T (rs1801133) gene variants result in lowered catalytic activity and are associated with elevated blood Hcy concentration [MTHFR gene polymorphisms and serum Hcy levels [MTHFR C677T (rs1801133) polymorphisms are not associated with individual changes in cognitive function [MTHFR, which depends on folate and vitamin B12, is a pivotal enzyme in one-carbon metabolism . It has  C677T rs01133 genntration , which lntration , 46–48. y levels . Howeverfunction , 50, 51.MTHFR C677T (rs1801133) gene variant could contribute to AD susceptibility [β40) concentrations, which might result in AD [MTHFR T allele group with MCI [MTHFR C677T (rs1801133) gene polymorphisms and MCI.Previous reports have indicated that the C677T rs101133 gentibility . It has tibility , 53. Firtibility , 54. Seclt in AD . Additiolt in AD . Finallywith MCI . MCI wasMTHFR C677T (rs1801133) gene polymorphisms of the three studies were not in HWE in control groups, which might have affected our findings. Therefore, the possible association is needed to verify by a representative sample.SNPs are DNA sequence polymorphisms resulted by single-nucleotide mutations that occur at genomic levels, which might affect the expression or activity of the encoded protein and affect its function . GeneticMTHFR C677T (rs1801133) polymorphisms and MCI risk. Third, the literature search was restricted to articles published in Chinese and English, which might introduce publication and language bias. A limited number of electronic databases were investigated, and relevant studies might have been overlooked.In interpreting the results of the current research, a few limitations should be recognized. First, the results were highly heterogeneous, which may have distorted the meta-analysis. We considered the following possible sources of this heterogeneity: (i) different study types were pooled in our research, and (ii) inconsistent results might be limited by the ethnicity of the included population. We conducted a subgroup analysis based on ethnicity, but this did not affect the final result. Second, the sample size of our research was relatively small to investigate the association between MTHFR C677T (rs1801133) gene polymorphisms were not associated with MCI susceptibility based on current studies. The TT genotype did not confer an increased risk of MCI compared to the CC and CT genotypes. However, considering the small sample size and limitations of the included research, further large-scale prospective studies and randomized controlled trials are needed to confirm our findings. In particular, future studies should take into account gene–gene and gene–environment interactions, as well as other confounding factors. We hope that our results will provide background data for future MCI research and will contribute to genetic marker screening.In conclusion,


Schizophrenia is a complex brain disorder, the pathogenesis of which remains unclear. Regulator of G-protein signaling 4 is regarded as a candidate gene for schizophrenia risk. The association between the regulator of G-protein signaling 4 gene and the risk of schizophrenia is complicated and controversial, thus, an updated meta-analysis is needed.P value of Hardy–Weinberg equilibrium, odds ratios, 95% confidence intervals, P values of association, heterogeneity (Ph), and publication bias, were analyzed by the Stata software using a random effects model. Subgroup analyses were performed to detect heterogeneity.A search strategy using Medical Subject Headings was developed in English  and Chinese  databases. Inclusion and exclusion criteria were used to screen for eligible studies. Parameters, such as P > .05). As shown by the East Asian and hospital-based subgroup analyses, the genotype TT of rs951436 might be related to the risk of schizophrenia. The genotypes CC + CT of rs2661319 and CC + CA of rs10759 were statistically different between the 2 groups, and the East Asian population contributed to these differences.There were 15 articles regarding rs10917670 (8046 cases and 8837 controls), 16 regarding rs951436 , 15 regarding rs951439 (7995 cases and 8646 controls), 15 regarding rs2661319 (8320 cases and 9440 controls), and 4 regarding rs10759 (2752 cases and 2866 controls). The frequencies of rs10917670 and rs951439 were not significantly different between the case and control groups (The genotypes CC + CT of rs2661319 and CC + CA of rs10759 might be associated with the risk of schizophrenia. The major mechanism by which regulator of G-protein signaling proteins negatively regulate G proteins is via their GTPase accelerating activity. Regulator of G-protein signaling 4 (RGS4) is known to play a fundamental role in neurotransmission and neuronal differentiation, in addition to axonogenesis during embryogenesis. RGS4 regulation of G-protein activity, may inhibit the interaction between neurotransmitters and their receptors, leading to dysfunction of glutamatergic neurotransmission, which is classically related to the etiology of psychotic disorders. Schwarz et al suggested that the RGS4 gene, localized to chromosome 1q23, might be an important part of a larger biological system contributing to schizophrenia risk. Mirnics et al showed that RGS4 expression was down regulated in schizophrenia.,11 However, the association between RGS4 and the risk of schizophrenia remains controversial.–15Schizophrenia is a complex brain disorder, the pathogenesis of which remains unclear. In the Chinese Han population, 1 meta-analysis showed no association between the RGS4 gene and the risk of schizophrenia; however, in another meta-analysis, the SNP, rs951436, was found to be associated with the risk of schizophrenia. Therefore, the association between RGS4 and the risk of schizophrenia remains complicated and controversial.–19 Additional articles have since been published; thus, an updated meta-analysis is needed. Here, we conducted an updated meta-analysis to detect the association between RGS4 gene polymorphisms and the risk of schizophrenia.Meta-analysis is a useful tool for the detection of disease–gene relationships.22.1 A search was performed in English  and Chinese  databases with the following keywords: “the regulator of G-protein signaling 4” or “RGS4”, and “schizophrenia”. References to related articles were also reviewed for further data.The systematic review and meta-analysis were conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.2.2 Information regarding the author, year, country, ethnicity, controls source, mean age of the control group, number of samples, diagnostic criteria, gender index the of cases and controls, and genotypes of the cases and controls were collected.The inclusion criteria were: studies with a case–control design; involvement of patients with schizophrenia; available allele or genotype frequencies; and published before May 12, 2020. The authors were emailed if there was no genotype frequency mentioned in the article. The exclusion criteria were: family-based studies; no control group data; no detailed genotype frequency data after emailing the authors; and duplicate samples.2.3P value of Hardy–Weinberg equilibrium was calculated. Parameters, such as the odds ratios (ORs), 95% confidence intervals (CIs), and P values of association (Pz), were calculated to detect the association in 5 genetic models, using the random effects model.,23 The heterogeneity of the studies (Ph) was determined by Cochran chi-square-based Q-statistic test. To assess the heterogeneity, subgroup analyses by ethnicity and control source were performed. The studies were classified by control source into community-based  and hospital-based  groups. The Egger test was conducted to detect the publication bias, which could be visualized using a funnel plot. To assess the impact of each study on the pooled results, sensitivity analysis was performed by removing single studies in turn. The power was calculated using the PS program. The threshold for statistical significance was P < .05 in all tests.The meta-analysis was conducted using Stata version 10.0 . In the control group, the 33.1,14,27 were unavailable. Date in 8 articles,18,28–33 were analyzed in previous meta-analyses,–19 however, data in the other 12 articles were not included in previous meta-analyses. Table –32,34–41 16 regarding rs951436,,38,39,42 15 regarding rs951439,,38–41,43 15 regarding rs2661319,18,28–40 and 4 regarding rs10759.,38,39,41 There were less than 4 articles regarding other SNPs of the RGS4 gene; therefore, these were not included in the present meta-analysis. The SNPs rs10917670, rs951436, and rs951439, are located in the promoter region, rs2661319 is located in the first intron, and rs10759 is located in the 3’ untranslated region.A total of 259 English and 46 Chinese articles were found, with 20 articles being eligible for analysis following exclusion Fig. . The dat3.23.2.1Pz = .946, OR = 0.997, 95% CI = 0.926-1.074). No association was detected in the subgroup analyses by ethnicity or control source. Moreover, no significant heterogeneity was observed in the pooled or subgroup analyses.Genotype frequency of 8046 cases and 8837 controls was used to perform pooled and subgroup analyses using the random effects model . Results of the pooled and subgroup analyses were summarized in Tables 3.2.2Pz = .51, OR = 0.965, 95% CI = 0.870-1.072) using the recessive model  and hospital-based  subgroup analyses. Significant heterogeneity was observed in the pooled analysis .Pooled and subgroup analyses of 8990 cases and 10,568 controls were performed . No association was found between rs951436 and the risk of schizophrenia  using the dominant model . Detailed genotype frequencies were not available in3.2.4Pz = .023), homozygous codominant , dominant , and recessive . According to the dominant model . An association was detected in the East Asian subgroup analysis , with a power of 0.694. No significant heterogeneity was observed in the pooled or subgroup analyses.Pooled and subgroup analyses of 8320 cases and 9440 controls were performed . Of the 5 genetic models, significant differences were detected when using allele contrast  and dominant . Using the random effects model, the dominant model was selected , with a power of 0.694. An association was found in the East Asian population . No significant heterogeneity was observed in the pooled or subgroup analyses.A total of 2752 cases and 2866 controls were analyzed in pooled and subgroup analyses . Significant differences were observed in 2 of the genetic models, allele contrast .4–19 In the East Asian and hospital-based subgroup analyses, an association between the genotype TT of rs951436 and the risk of schizophrenia was found; however, this relationship was not detected in the pooled analysis. Therefore, the geographical environment, culture, lifestyle, and genetic background might affect polymorphisms.,31,33 It was studied that rs951436 was associated with magnetic resonance imaging measurements of functional activation and connectivity related to working memory, an intermediate phenotype of schizophrenia. Moreover, Prasad et al reported that rs951436 was related the volume of dorsolateral prefrontal cortex (DLPFC). But the mechanism remained unclear.No association between rs10917670 and rs951439 and the risk of schizophrenia was detected in the present study, which was consistent with previous meta-analyses.RGS4-1 mRNA level, which was decreased in the postmortem DLPFC of schizophrenic patients. Moreover, rs2661319 was demonstrated to be associated with a more severe baseline total PANSS score and the treatment effect of perphenazine. The rs10759 polymorphism was suggested to increase the risk of schizophrenia by altering the binding of miRNA-124 to its target. MiRNA-124 might bind to the 3′UTR of mRNAs containing target sites, resulting in miRNA-mediated gene silencing, translational inhibition, and induction of mRNA de-adenylation or decay. The level of RGS4 might be decreased, leading to dysfunction of neurotransmission.Rs2661319 and rs10759 were found to be associated with the risk of schizophrenia in the present study, which was inconsistent with previous meta-analyses. It was detected by subgroup analyses that the East Asian population contributed to this association. It was previously reported that rs2661319 was related to RGS4 gene and the risk of schizophrenia; however, the sample size was relatively small, and the power was low. Further articles are needed to form a representative and comprehensive conclusion. Second, family-based and functional studies were not included in the present meta-analysis. In addition, it was reported that there was an association between DLPFC volume and RGS4 genotype interacting with COMT rs4818; thus, this association warrants further gene–gene interaction,50 and functional studies.More relevant data were included in our meta-analysis than those in previous meta-analyses, for instance, an increased number of more SNPs (5), and databases . However, the results described herein should be interpreted with caution. First, in the present study, the East Asian population contributed to the association between the 5No association between rs10917670 and the risk of schizophrenia was found. In the East Asian and hospital-based subgroup analyses, an association between rs951436 and the risk of schizophrenia was demonstrated. No association between rs951439 and the risk of schizophrenia was detected. The genotypes CC + CT of rs2661319 and CC + CA of rs10759 might be risk factors for schizophrenia, and the East Asian population contributed to this association. Further updated gene–gene interaction and functional studies are needed.Feng-Ling Xu, Jun Yao, and Bao-Jie Wang were worthy of acknowledgments.BW designed the study and wrote the protocol. FX managed the literature search. FX performed analyses. The manuscript was written by FX, and corrected by JY.Conceptualization: Feng-Ling Xu, Bao-Jie Wang.Data curation: Feng-Ling Xu.Formal analysis: Feng-Ling Xu.Investigation: Feng-Ling Xu.Methodology: Bao-Jie Wang.Project administration: Feng-Ling Xu.Software: Feng-Ling Xu.Supervision: Jun Yao, Bao-Jie Wang.Validation: Bao-Jie Wang.Visualization: Bao-Jie Wang.Writing – original draft: Feng-Ling Xu.Writing – review & editing: Jun Yao.


Background: Emerging evidence shows that m.5178C>A variant is associated with a lower risk of coronary artery disease (CAD). However, the specific mechanisms remain elusive. Since dyslipidemia is one of the most critical risk factors for CAD and accounts for at least 50% of the population-attributable risk, it is tempting to speculate that the reduced CAD risk caused by the m.5178C>A variant may stem from an improved lipid profile. In order to verify this hypothesis, we conducted the present study to clarify the association of m.5178C>A variant with lipid levels.Methods: By searching ten databases for studies published before 30 June 2021. Thirteen East Asian populations  were included for the analysis.Results: The present study showed that m.5178C>A variant was associated with higher high-density lipoprotein cholesterol (HDL-C)  and total cholesterol (TC)  levels. In subgroup analysis, the association of m.5178C>A variant with higher HDL-C levels were observed in Japanese  and Chinese populations . However, the association of m.5178C>A variant with lower low-density lipoprotein cholesterol (LDL-C) levels were only observed in Japanese populations .Conclusions: The m.5178C>A variant was associated with higher HDL-C and lower LDL-C levels in Japanese populations, which may contribute to decreased CAD risk and longevity of Japanese. The human mitochondrial genome is closely associated with the human lifespan, and each human cell contains hundreds to thousands of copies of the mitochondrial genome, which encode 13 polypeptides .ND2) gene of mitochondrial DNA (mtDNA) and formed by a transversion from cytosine (C) to adenine (A). The mtDNA-ND2 m.5178C>A variant leads to replacing leucine with methionine (p.Leu237Met).The m.5178C>A variant is rare worldwide  and is t−/−) caused severe dyslipidemia [A series of mouse model experiments  showed tipidemia . Togetheipidemia . Moreoveipidemia  reportedipidemia . When coMoreover, it was well documented that ,7,16 varOver the last decade, intensive efforts  have beeThe studies regarding the relationship between m.5178C>A variant and acute myocardial infarction (AMI) were limited but consistent. For instance, Mukae et al.  reportedA comprehensive literature search was performed from 31 March 2021 to 30 June 2021 by using ten databases including PubMed, Medline, Embase, Cochrane Library, Web of Science, Google Scholar, Foreign Medical Journal Service, Excerpta Medica, CNKI, Wanfang. The following keywords were used in the search: ,  and . Additionally, the reference lists of all eligible studies were manually retrieved to obtain more literature.The specific inclusion criteria were listed: (1) The test subjects must be limited to the East Asian population. (2) The studies investigated the association of m.5178C>A variant with serum lipid levels. (3) The studies at least provided one of four parameters in lipid profile (triglyceride (TG), TC, low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C)). (4) The studies provided the frequency of m.5178C>A variant. (5) The studies offered the mean lipid levels with standard deviation (SD) or standard errors (SE) by m.5178C>A variant. (6) The interventional articles provided pre-intervention data. (7) The language of eligible studies was restricted to English or Chinese. The specific exclusion criteria were as follows: (1) The studies did not relate to m.5178C>A variant. (2) The studies did not relate to lipid levels. (3) The studies did not present the frequency of m.5178C>A variant. (4) The studies provided invalid data. (5) The studies provided incomplete data. (6) Pedigree studies. (7) Overlapping studies. (8) Abstract, review, case report, meta-analysis and animal studies.Two authors (Fuqiang Liu and Shengping Wang) extracted the data independently using a standardized data extraction table. The discrepancy in data extracted was resolved by consensus or a discussion with the third author (Zhi Luo). If critical data were absent, e-mail or telephone was used to contact the corresponding author to acquire this information. The following data were extracted from each eligible study: the last name of the first author, year, country , gender , ethnicity , the frequency of m.5178C>A variant, genotyping methods, type of study, type of disease, total sample size, mean lipid levels with SD or SE by m.5178C>A variant.P<0.05 was recognized as statistically significant. The standardized mean difference (SMD) and 95% confidence interval (CI) were used to evaluate the differences in lipid levels.The units of TG, TC, LDL-C and HDL-C were converted into mmol/l. All extracted data were expressed as mean ± SD. All the analyses were performed by STATA software . measurement results among a series of studies were defined as ‘heterogeneity’ [2I statistic and Cochran’s χ2-based Q statistic. Galbraith plots were used to detect the potential sources of heterogeneity. If heterogeneity was significant , the random-effects model (DerSimonian–Laird method) was used to calculate the results [Inevitably, there were differences between the studies included in the meta-analysis. The differences or diversity between participants, interventions, and the geneity’ . Heterog results . OtherwiThe publication bias among the included studies was evaluated by Begg’s funnel plot and Egger’s linear regression test .Subgroup analysis was carried out by ethnicity, gender and health status. The ethnicity was divided into Chinese and Japanese. The health status was divided into type 2 diabetes mellitus (T2DM) patients and healthy subjects. In some studies, the subjects were divided into more than one subpopulation . Each subpopulation was regarded as an independent comparison in the present study.Sensitivity analysis was conducted in the present meta-analysis, in which the comparison was excluded one by one and performed the analysis again after omitting each comparison. If the synthetic results in any study changed substantially to alter the results from significant to non-significant or the other way around. The absence of such a phenomenon usually indicates the robustness and stability of synthetic results.By searching the above ten databases, 70 studies were identified. After the screening, 28 studies were excluded by their title and abstract. Next, 42 studies were estimated by their contents. In which, 23 studies did not provide lipid data, 5 studies  had lipiThe references of the included studies were listed in Supplementary Material. The characteristics of the included studies were presented in Supplementary Table S1. The serum lipid levels by m.5178C>A variant were presented in Supplementary Table S2.P=0.001)  .Then the subgroup analysis was carried out . SubgrouThe analysis that excluded the studies with heterogeneity was also carried out . HoweverP=0.01) changed significantly after excluding these comparisons.In analyzing the association of m.5178C>A variant with lipid levels, significant heterogeneity was detected in TG, TC and HDL-C . Four K. HoweverP=0.66) did not change significantly after excluding this comparison.Sensitivity analysis showed that no comparison might affect the association of m.5178C>A variant with TG A, TC FiB and HDLP=0.78 for TG, P=0.37 for TC, P=0.22 for LDL-C and P= 0.31 for HDL-C).Begg’s funnel plot was used to evaluate the publication bias among the included studies. However, no publication bias was observed in synthetic results A–D, whicThe present study showed that the m.5178C>A variant was significantly associated with higher HDL-C and TC levels. Subgroup analysis showed the significant association of m.5178C>A variant with higher HDL-C levels was primarily in Japanese and Chinese populations. While the significant association of m.5178C>A variant with lower LDL-C levels was only observed in Japanese populations.237Met in mtDNA-ND2 may affect NADH dehydrogenase’s function and thus inhibit ROS release [The mechanisms underlying the association of m.5178C>A variant with lipid levels remain elusive. However, one hypothesis could be proposed to explain our findings, that is, by protecting against oxidative stress. The p.Leu release . Moreove release  showed t release . Therefo release , in whic release ,41–44.In the present study, the significant association of m.5178C>A variant with higher HDL-C and TC levels was observed in Chinese , indicatThe mechanisms underlying the effects of m.5178C>A variant on longevity have not been fully clarified. However, it is now increasingly evidenced that the higher levels of HDL-C ,45–47 anSeveral limitations of the present meta-analysis should be noted. First of all, a large number of genes as well as some environmental factors are involved in dyslipidemia. However, this meta-analysis has not investigated the interactions of m.5178C>A variant with other variant loci or environmental factors on serum lipid levels due to the lack of original data from the included studies. Secondly, a relatively small number of individuals have been included in the lipid association analysis for m.5178C>A variant due to the limited number of studies that met the inclusion criteria, which may reduce the statistic power and even cause type I error . Thirdly, this meta-analysis only included the studies published in English and Chinese as it is very difficult to get the full papers published in various languages.The m.5178C>A variant was associated with higher HDL-C and lower LDL-C levels in Japanese populations, which may contribute to decreased coronary artery disease (CAD) risk and longevity of Japanese.Click here for additional data file.Click here for additional data file.


At the same time, a meta-analysis of the included studies revealed statistically insignificant reduction in fasting glucose, insulin, HbA1c, and HOMA-IR (changes in glucose metabolism) after consumption of soy isoflavones. The observed ability of both extracted isoflavone and soy protein with isoflavones to modulate the lipid profile suggests benefits in preventing cardiovascular events in diabetic subjects. Further multicenter studies based on larger and longer duration studies are necessary to determine their beneficial effect on glucose and lipid metabolism.The aim of the report was to investigate the impact of soy protein and isoflavones on glucose homeostasis and lipid profile in type 2 diabetes. The studies used in this report were identified by searching through the MEDLINE and EMBASE databases (up to 2020). Meta-regression and subgroup analyses were performed to explore the influence of covariates on net glycemic control and lipid changes. Weighted mean differences and 95% confidence intervals (CI) were calculated by using random-effect models. Changes in the lipid profile showed statistically significant decreases in total cholesterol and LDL-C concentrations: ‒0.21 mmol/L; 95% CI, ‒0.33 to ‒0.09;  Diabetes mellitus has been widely recognized to be a fundamental and leading cause of major health issues, such as cardiovascular disease. The world prevalence of diabetes among adults (aged 20–79 years) amounted to 285 million adults in 2010, and will increase to 439 million adults by 2030 [T2DM is characterized by elevated fasting plasma glucose (FPG), insulin resistance and relative lack of insulin ,4. A varImprovements in glycemic control have been demonstrated in adults with T2DM through a combination of pharmaceuticals and lifestyle changes, and with lifestyle changes alone ,10. LifeThis systematic review and meta-analysis was undertaken to investigate the influence of soy isoflavones on glucose metabolism, including fasting blood glucose (FBG), fasting insulin (FI), glycosylated hemoglobin A1 level (HbA1c) and peripheral insulin resistance (homeostasis model assessment of insulin resistance: HOMA-IR), as compared with healthy subjects, in patients with T2DM. A secondary aim of the study was to evaluate the influence of soy isoflavones on lipid metabolism. The study was conducted based on the PRISMA guidelines, and utilized the MEDLINE (PubMed) and EMBASE electronic database websites (up to March 2020) . The folThe following data was extracted from each of the included studies: first author’s name, year of publication, country of origin, study design; follow-up period, number of participants in the intervention and control groups; characteristics of the studied populations (age (range), menopausal status (years since menopause), body mass index), daily dose of soy isoflavones, type of control group, and initial and final mean values with corresponding standard deviations (SD) of the above-mentioned components of the lipid metabolism and glycemic profile, for each comparison group. When different units were given in the research , the following conversion factors were used to unify them: to convert cholesterol to mmol/L, multiply by 0.02586; to convert triglycerides to mmol/L, multiply by 0.01113; to convert insulin to pmol/L, multiply by 6; to convert glucose to mmol/L, multiply by 0.05551; and to convert HbA1c to %, multiply by 0.0915 + 2.15. To avoid duplication of data in trials with multiple time points, only the results from the shortest follow-up were taken into account. In the case of trials with more than one active group compared to one control group, all results were taken into account.The quality of trials was evaluated using the Cochrane Collaboration’s tool . This co2 + 2 −  × 2R), where R is the correlation coefficient; we took an R value = 0.50 according to the suggestion of Follmann et al. [p < 0.05 was considered statistically significant), according to DerSimonian and Laird [2 statistic were employed. The I2 test allowed assessing whether the variance across studies was correct and not due to sampling errors. Percentage of total variation indicates the degree of heterogeneity; I2 values of ≤25% were considered low, >25% as moderate, and ≥75% as high heterogeneity [Treatment effect of each comparison group was defined as the mean difference (MD)  from corresponding SD of change in individual components of lipid metabolism or glycemic profile for subjects ingesting soy isoflavones or control. When the standard error of the mean (SEM) was employed, the conversion to SD was made according to the formula: SD = SEM × √N. If a 95% confidence interval (95% CI) was applied, SD conversion was: SD = sqrt (N) × (upper bound–lower bound)/(2u) . The missing SD of MD were imputed using the formula: SD = sqrt n et al. ,29. Summnd Laird . For hetogeneity . Multiva2), duration of diabetes (<5 y vs. ≥5 y) and isoflavones dose per day (<80 mg vs. ≥80 mg) [Additional subgroup analyzes were performed in order to detect sources of heterogeneity according to the following covariate variables: design of studies , participants age (≤60 y vs. >60 y), follow-up period (≤8 w vs. >8 w), BMI (<30 kg/m2 vs. ≥30 kg/m ≥80 mg) . Further ≥80 mg) . Our search yielded 139 citations for double screening of abstracts, of which 38 were identified for full-text analysis. Of these, 12 randomized controlled trials were finally included. A detailed review of selection procedures is shown in The characteristics of selected studies are listed in Details of the risk of bias assessment are shown in p = 0.2779, this was accompanied by high heterogeneity: I2 = 85.33% for FBG  studied the effect of soy isoflavones on FBG. In five comparisons, as compared with control, a non-significant decrease in FBG was shown, but the reduction was statistically significant in one , while t for FBG A; ‒3.40 % for FI B; ‒0.80%or HbA1c C; and ‒0 HOMA-IR D.p = 0.0388. In turn, Egger’s test revealed no evidence of publication bias: intercept = ‒0.1931, t = ‒0.1032, p = 0.9207. Simultaneously, the results of Begg and Mazumdar’s test for rank correlation did not indicate publication bias in the meta-analysis of other components of glucose metabolism: Kendall’s tau = 0.3333, z = 1.0513, p = 0.2931 for insulin and Kendall’s tau = 0.4667, z = 1.3151, p = 0.1885 for HOMA-IR. The analysis did not generate results for Begg and Mazumdar’s test. Moreover, the results of Egger’s test for regression showed no evidence of publication bias for insulin, HbA1c and HOMA-IR: intercept: 1.2126, t = 1.8271, p = 0.1175; intercept: ‒5.0560, t = ‒0.9855, p = 0.3802; and 0.6407, t = 0.6994, p = 0.5632; respectively. Publication bias was examined by analyzing a series of regression tests for all pooled effects. Begg and Mazumdar’s test for rank correlation indicated evidence of publication bias: Kendall’s tau = ‒0.7333, z = ‒2.0665, To explore the possible influence of covariates on net glycemic change, a subgroup analysis was additionally conducted on the basis of eight pre-specified factors  as presented in p < 0.0001). Moreover, diabetes duration more than 5 years statistically significantly reduced FBG and FI levels , and additionally the levels of FBG and FI were decreased when diabetes with complications occurred .The results of subgroups analysis showed no statistically significant differences between groups for HOMA-IR. However, soy isoflavones supplementation in subjects’ age ≤60 statistically significantly reduced HbA1c levels (p = 0.001). Subject age  and diabetes duration  had significant influence on HbA1c , p < 0.0001, HDL-C: ‒0.02 , p = 0.1777, TAG: ‒0.15 , p = 0.3362.The pooled estimate revealed that the intake of soy isoflavones was associated with statistically significance decreases in plasma concentrations of TC: ‒0.21 mmol/L ,  < 0.01% A and LDL < 0.01% B. Howeve < 0.01% C and TAG= 77.96% D, comparp = 0.53), LDL-C , HDL-C  and TAG . Moreover, the results of Egger’s test for regression revealed no evidence of publication bias for TC, LDL-C, HDL-C and TAG: ‒0.2049, t = ‒0.4284, p = 0.68; intercept: ‒0.25, t = ‒0.4284, p = 0.69; intercept: 0.3289, t = 1.1212, p = 0.29; and 1.4968, t = 0.9616, p = 0.36; respectively. Begg’s and Mazumdar rank correlation test indicated no evidence of publication bias for TC . However, diet and/or drug administration statistically were observed to significantly reduce TC (p = 0.0028) and LDL-C levels (p = 0.0014). In addition, levels of TC were decreased among patients in parallel group studies (p = 0.0041), in obese patients (p = 0.0031), and in patients that used higher doses of isoflavones (p = 0.0022).To investigate the possible effect of covariates on lipid profile alteration, a subgroup analysis was additionally performed taking into account participant characteristics that included age, BMI and diabetes duration, study design, follow-up period, isoflavones dosing, diabetes therapy and diabetes complications . The resp = 0.035). However, follow-time , BMI , diabetes duration , and isoflavone intake  were found to have significant influence on LDL-C  and LDL-C  in the plasma, while the levels of HDL-C  and TAG  did not change significantly after ingesting soy isoflavone supplements. Zhang et al. [p < 0.01) and in LDL-C  and non-significant decrease in HDL-C  and TAG , while Yang et al. [p < 0.05), TAG , significant reduction in LDL-C  and significant increase in HDL-C . Furthermore, Soltanipour et al. [p < 0.01). In addition, soy products consumption was seen to be beneficial in decreasing LDL-C and TAG, but had no significant effects on HDL-C (results not shown). Beyond the aforementioned, Giordano et al. revealed in their study that soy isoflavones increased plasma TC concentrations and decreased triglyceride ones—adding further evidence to the notion that soy isoflavones have assorted effects on cardiometabolic risk factors [Our meta-analysis demonstrated a significant reduction in the concentration of TC . These results are similar to those of Yang et al. [p = 0.015; ‒0.29, p = 0.01; and ‒0.346, p < 0.01; respectively). Moreover, a recently published meta-analysis by Soltanipour et al. [p < 0.01), in the absence of significant effects on FBG . Simultaneously our meta-analysis for the effects on glycemic control revealed that soy protein and/or isoflavones are not significantly effective in reducing circulating glucose levels. In addition, the outcome of our meta-analysis of randomized controlled trials has indicated that soy protein and/or isoflavones supplementation has no statistical significance effect on glycemic control in T2DM , lead to gene activation and beneficial effects on glucose and lipid metabolism ,56. There is some evidence to intimate that estrogen receptor (ER) binding is only part of the isoflavone effect . GenisteMoreover, isoflavones can also regulate lipid metabolism without the mediation of estrogen receptors; increase expression of PPARα and activate AMPK—which results in increased activity of genes involved in lipoprotein metabolism; reduce TG-rich particle production and increase their lipolysis; promote HDL metabolism and promote the uptake, utilization and catabolism of fatty acid ,66,67. FLimitations of the presented meta-analysis must be acknowledged. First, the pooled population analyzed in our meta-analysis included a limited number of subjects because the sample size in some of the clinical trials was small. Secondly, the duration of treatment in some studies was short (<2 months), which could reduce the effect of soy isoflavones supplementation. Thirdly, the selected studies used different doses and different forms of soy isoflavones —which could have affected the results. Fourthly, the clinical effectiveness of soy isoflavones may be limited by the ability to transform soy isoflavones to the more potent estrogenic metabolite (equol). High variability in equol production is attributable to interindividual differences in the composition of the intestinal microflora; only approximately one-third to one-half of the population is able to metabolize daidzein to equol ,56,72.Our analysis found that consumption of soy isoflavones brought about a statistically significant reduction in total and LDL cholesterol, while simultaneously demonstrating no significant effects on HDL and TAG. Influence of soy isoflavones on glucose levels has been shown to be statistically insignificant. Moreover, the ability of both extracted isoflavone and soy protein with isoflavones to modulate the lipid profile suggests benefits in preventing cardiovascular events in people with type 2 diabetes. However, further multicenter studies based on a larger pool of research material and a well accurately defined dose of isoflavones are necessary to determine their beneficial effects on glucose and lipid metabolism.


The use of meta-analysis to aggregate the results of multiple studies has increased dramatically over the last 40 years. For homogeneous meta-analysis, the Mantel–Haenszel technique has typically been utilized. In such meta-analyses, the effect size across the contributing studies of the meta-analysis differs only by statistical error. If homogeneity cannot be assumed or established, the most popular technique developed to date is the inverse-variance DerSimonian and Laird (DL) technique :177–88, 1986). However, both of these techniques are based on large sample, asymptotic assumptions. At best, they are approximations especially when the number of cases observed in any cell of the corresponding contingency tables is small.k 2 × 2 tables for any level of heterogeneity as an alternative to the asymptotic techniques. Monte Carlo simulations show that even for large values of heterogeneity, the Enhanced Bernoulli Technique (EBT) is far superior at maintaining the pre-specified level of Type I Error than the DL technique. A fully tested implementation in the R statistical language is freely available from the author. In addition, a second related exact test for estimating the Effect Size was developed and is also freely available.This research develops an exact, non-parametric test for evaluating statistical significance and a related method for estimating effect size in the meta-analysis of This research has developed two exact tests for the meta-analysis of dichotomous, categorical data. The EBT technique was strongly superior to the DL technique in maintaining a pre-specified level of Type I Error even at extremely high levels of heterogeneity. As shown, the DL technique demonstrated many large violations of this level. Given the various biases towards finding statistical significance prevalent in epidemiology today, a strong focus on maintaining a pre-specified level of Type I Error would seem critical. In addition, a related exact method for estimating the Effect Size was developed. Not only does it take a cannon to shoot a sparrow, but it misses the sparrow. The elaborate mechanism built on the theory of infinitely large samples is not accurate enough for simple laboratory data.” The use of meta-analysis in epidemiological research has been increasing at a very rapid rate. A review of the National Library of Medicine’s online database (“Pub Med”) shows that in 1977 there was only a single research article with the term “meta-analysis” in its title. This number had increased to 138 in 1991, 966 in 2005 and to 17,205 in 2019 . Many researchers feel that it is highly misleading to attempt to combine a series of disparate studies  while otk contributing studies each described by a 2 × 2 contingency table. Every cell of each 2 × 2 table contains the number of occurrences of an event  for the particular combination of row and column variables. For the sake of illustration, we can associate the two columns of each table with Disease Manifestation vs. No Disease Manifestation and the two rows with Exposure vs. No Exposure. Table k studies.The “2 × 2 × k” categorical meta-analysis paradigm is probably the most frequently encountered situation in meta-analysis. It consists of a series of k contributing studies; and (2) A method to pool the observed differences between groups across the k studies in order to estimate the true difference (the Effect Size).In most meta-analyses, there are typically two distinct components: (1) A statistical test of the overall difference between the Exposure and No Exposure groups across the . , or they could readily have applied a more exact procedure for the data at hand” (p. 134).The problem in applying large sample asymptotic techniques to meta-analyses involving small numbers of cases will be illustrated in the older and much more developed domain of homogeneous meta-analyses. Mantel developed what is probably the most widely used technique for homogeneous meta-analyses . In applanalysis . This isStatistical Methods for Research Workers ).2 in Eq. 2 = 0.8, a nominal exposure group event probability In addition, the heterogeneity between the contributing studies, τmentclass2pt{minimp values in a less conservative manner leading to more realistic power levels.The statistical significance and effect size were evaluated using both the EBT and DerSimonian techniques for each replication. All simulation runs were conducted with 10,000 replications. A value of 0.05 was used as the pre-specified level of Type I Error. The “Mid-P” technique advocated by Agresti  and otheFigure shows the results of both the EBT and the DL methods. To simplify presentation, only scenarios in which the expected number of cases was greater than or equal to two were utilized. Table 2 = 0, both the EBT and the DL methods respect the prespecified Type I error level. However, for τ2 = 0.4 and for τ2 = 0.8, the DL method exhibits large violations of this level. As expected, as the number of contributing studies increases, the power for Relative Risk greater than one increases for both the EBT and DL methods. A separate analysis showed that the standard deviation of the power estimates in Fig. When the Relative Risk equals one, the power is the Type I error or, equivalently, the false alarm rate. The basic finding was that the EBT method maintained the prespecified level of Type I error for both the homogeneous and heterogeneous scenarios while the DL method had many violations of this level for heterogeneous scenarios. For the homogeneous scenario where τIn actuality, comparing the power between the EBT and DL techniques for Relative Risk ratios greater than 1.0 is not truly permissible due to the large number of violations of the pre-specified Type 1 Error for the DL technique.2).Figure As can be clearly seen, the current EBT technique is relatively resistant to the effects of increasing heterogeneity over a very large heterogeneity range. The DL technique, however exhibits a monotonically increasing sensitivity to heterogeneity. A related aspect of any meta-analysis technique’s ability to perform well in the face of heterogeneity is its resistance to “contamination” from one or a small number of “rogue studies”. Since the EBT method does not directly allow such rogue studies to directly affect the test statistic, it should be much more resistant to these distortions.The large costs of discreteness have been studied by Agresti  and otheA first cost of discreteness results when the number of contributing studies is small. The general issue of overcoverage is highlighted in Fig. k contributing studies, and generally decreases as the number of contributing studies increases. As Fig. . have shown in their extensive analysis of all meta-analyses in the Cochrane Library [The overcoverage is greatest for the smallest number of  Library .Additional Monte Carlo testing was done for unbalanced designs  and meta-analyses with unequal sample sizes across contributing studies. Table 2 = 0 and τ2 = 0.8, Event (“disease”) Probability of 0.05, Number of Studies = 10, and Sample Size (avg.) = 100 at the same five levels of Relative Risk used above. The simulation run consisted of 10,000 replications as in Fig. Table As the results in Table Table 2 = 0 and τ2 = 0.8, Event (“disease”) Probability of 0.05, and Sample Size  = 100, at the same five levels of Relative Risk as used above. The simulation run consisted of 10,000 replications as in Fig. Table Most importantly, at a heterogeneity level of 0.8, the EBT Technique was superior at protecting the pre-specified level of Type I Error relative to the DL technique.A clear finding of the Monte Carlo simulations common to both meta-analysis techniques studies is the apparent fruitlessness of searching for small effect sizes. Both the EBT and DL techniques are very poor at reliably finding statistically significant results until the relative risk approaches 2.0. While this finding does not directly bear on the issues studied in this report, it does serve as a cautionary tale to those who continue to try to tease out very small effects especially from sparse data.Figures 2 = 0 and overestimated it for τ2 = 0.4 and τ2 = 0.8. Finally, as shown in Fig.  Again, only simulation scenarios in which the expected number of observed cases was greater than or equal to two were utilized. Since the effect of the number of studies contributing to the meta-analysis was small for this effect size estimation, results were averaged across this variable. As shown in Fig. This research has developed an exact test for the meta-analysis of dichotomous, categorical data and a related method to estimate the size of the effect.The EBT technique was greatly superior to the DerSimonian technique in maintaining a pre-specified level of Type I Error. As shown, the DerSimonian technique demonstrated many large violations of this level when heterogeneity was present. Given the various biases towards finding statistical significance prevalent in epidemiology today, a strong focus on maintaining a pre-specified level of Type I Error would seem critical . The EBA related but separate method was developed to estimate the effect size. This new technique was comparable to the often-used DL method although both methods demonstrated some accuracy issues. The DL method exhibited a somewhat smaller Semi-IQR variability. The fact that the EBT method was clearly superior in assessing statistical significance while the DL method demonstrated a smaller variability in estimating effect Size supports the possible utility of separating these two procedures as outlined at the beginning of this article. One possibility is to use the EBT method for statistical significance assessment and the DL method for effect size estimation.While statistical programs providing exact solutions already exist such as Cytel’s StatXact, they are beyond the means of most practicing statisticians and epidemiologists. For example, Cytel Inc. currently lists a price of over $900 USD for their current version of StatXact 11 .The techniques developed here are written in the almost universal statistical language of R and are freely available from the author. As such, it is hoped that other researchers would be able to extend and improve these initial versions.As outlined in this report, the use of meta-analysis in epidemiology is increasing very rapidly and appears to be meeting an important need. Fortunately, inexpensive and readily available computer power has also vastly increased in the past forty years. For example, task speed as measured in Million Instructions per Second (“MIPS”) has increased from 0.64 for the IBM370 mainframe computer in 1972 to 238,000 for an Intel Pentium processor personal computer in 2014 . By usin


P < 0.001) with no significant heterogeneity (I2 = 0%). Sensitivity by excluding one study at a time showed consistent results . Subgroup analyses showed that the association between skipping breakfast and hypertension in adults was consistent in the general population and in patients with type 2 diabetes, in studies from different countries, in cohort and cross-sectional studies, in breakfast skippers defined as taking breakfast ≤3 days/week and as self-reported habitual breakfast skipping, and in studies with and without adjustment of body mass index . In conclusion, skipping breakfast is associated with hypertension in the adult population.Previous studies evaluating the association between skipping breakfast and hypertension in adult population showed inconsistent results. We performed a meta-analysis to systematically evaluate the association. Observational studies which evaluated the relationship between skipping breakfast and hypertension in adult population with multivariate analyses were identified by systematic search of PubMed, Embase, and Web of Science databases. A random-effect model which incorporated the potential intrastudy heterogeneity was used for the meta-analysis. A total of six observational studies with 14189 adults were included, and 3577 of them were breakfast skippers. Pooled results showed that skipping breakfast was independently associated with hypertension in these populations (adjusted odds ratio (OR): 1.20, 95% confidence interval: 1.08 to 1.33,  Hypertension is a prevalent risk factor of cardiovascular diseases, particularly in elderly population and in the developing countries –3. ReducThe meta-analysis was performed in accordance with the MOOSE   and CochStudies were identified via systematic search of electronic databases of PubMed and Embase via the following terms: (1) “breakfast” OR “morning meal” OR “eating patterns” OR “meal frequency” OR “skipping meals” and (2) “hypertension” OR “blood pressure” OR “hypertensive.” The search strategies were developed based on previous meta-analyses of “skipping breakfast”  and “hypThe inclusion criteria for the studies were as follows: (1) observational studies published as full-length articles; (2) included adult population; (3) evaluated the association between skipping breakfast and hypertension; and (4) reported the relative risk for this association after adjustment of potential confounding factors. The definition of skipping breakfast was consistent with the criteria of the included studies. Diagnosis of hypertension was in accordance with the criteria applied in the included studies, which was generally defined as systolic BP ≥ 140 mmHg and diastolic BP ≥ 90 mmHg or on treatment of antihypertensive medications. Reviews, editorials, studies in children and adolescents, studies without information about breakfast skipping, studies irrelevant to the aim of the current meta-analysis, and studies with univariate analysis were excluded.Literature search, data extraction, and quality assessment of the included studies were performed according to the predefined inclusion criteria. Discrepancies were resolved by consensus. The extracted data included the following: (1) name of first author, publication year, and country where the study was performed; (2) study design characteristics; (3) participant characteristics, including health status, sample size, age, sex, and body mass index (BMI); (4) exposure characteristics, including definition of breakfast skipping and number of breakfast skippers included; (5) follow-up durations for cohort studies; (6) methods for hypertension evaluation and the number of patients with hypertension; and (7) confounding factors adjusted in the multivariate analyses. The quality of each study was evaluated using the Newcastle-Ottawa Scale  which raP values and were logarithmically transformed to stabilize variance and normalize the distribution [Q test and estimation of I2 statistic were used to evaluate the heterogeneity among the included observational studies [I2 > 50%. We used a random-effect model to synthesize the OR data because this model is considered as a more generalized method which incorporates the potential heterogeneity among the included studies [We used odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) as the general measure for the association between breakfast skipping and hypertension in the adult population. Data of ORs and their corresponding stand errors (SEs) were calculated from 95% CIs or ribution . Cochran studies . Signifi studies . Sensiti studies . Predefi studies . We usedThe process of database search is summarized in The characteristics of the included studies are summarized in P < 0.001; P for Cochrane's Q test = 0.56, I2 = 0%). Sensitivity by excluding one study at a time showed consistent results .The funnel plots regarding the association between skipping breakfast and hypertension in the adult population are shown in In this meta-analysis, we pooled the results of six available observational studies, and the results showed that skipping breakfast is associated with a moderately increased risk of hypertension in the adult population. Further results of sensitivity analyses showed the robustness of the findings which were not primarily driven by either of the included studies. Moreover, results of subgroup analyses showed that the findings of the meta-analyses were not significantly affected by study characteristics, such as the source of the participants, country of the study, study design, definition of breakfast skippers, adjustment of BMI, and quality scores of the included studies. Taken together, these results indicated that skipping breakfast was associated with hypertension in the adult population, and the association seemed to be independent of previously proposed confounding factors such as obesity.To the best of our knowledge, this study may be the first meta-analysis summarizing the current evidence for the association between breakfast skipping and hypertension in the adult population. Our meta-analysis has several methodological strengths which should be noted before the interpretation of the results. Only studies with multivariate analysis were included in this meta-analysis, which therefore could provide an independent association between skipping breakfast and hypertension. Moreover, comprehensive sensitivity and subgroup analyses were performed, and the consistent results suggested the stability and robustness of the findings of the meta-analysis. Results of a meta-analysis showed that skipping breakfast was associated with hypertension, which may suggest that skipping breakfast is a modifiable risk factor for hypertension in the adult population. Several mechanisms underlying the association between skipping breakfast and hypertension have been proposed. Firstly, skipping breakfast may cause hunger sensations and overeating later in the day, leading to insulin resistance, overweight, and obesity . Indeed,Our study also has limitations. Firstly, the number of available studies for the meta-analysis is limited. We were unable to determine a dose-response association between skipping breakfast and hypertension according to the frequency and duration of the breakfast skipping habits. Besides, the possible influences of participant characteristics on the association of interest could not be determined based on this meta-analysis, such as age and sex. Moreover, we were unable to determine the ethnic differences in breakfasts on the results of the meta-analyses because none of the included studies reported the outcome according to the ethnicity of the included population. However, a subgroup analysis based on country of the study showed a consistent association between skipping breakfast and hypertension in studies from the USA, Korea, and Ghana. In addition, although the results of the meta-analysis were based on multivariate analyses, we could not exclude the possible influence of residual factors which may confound the association, such as dietary components. Finally, a causative relationship between skipping breakfast and hypertension could not be derived from this meta-analysis because it is based on observational studies.In conclusion, the results of this meta-analysis suggested that skipping breakfast is associated with a moderately increased risk of hypertension in the adult population. Future studies are needed to determine whether long-term regular breakfast eating in former breakfast skippers is associated with improved cardiometabolic risk profiles, including hypertension.


Background: Retinopathy of prematurity (ROP) is a major cause of childhood blindness. Antenatal corticosteroids (ACS) exposure is known to ameliorate the risk of and mortality of neonatal morbidities. However, the effect of ACS on ROP development is currently unknown. We conducted a meta-analysis with up-to-date evidence to assess the association between ACS exposure and the development of ROP in at-risk preterm infants.Methods: PubMed, EMBASE, Scopus, Web of Science, and the Cochrane Library were systematically searched from inception to May 2021, supplemented with manual search from reference lists. Studies with a control group reporting ROP rate in ACS-exposed infants were included. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated utilizing a random-effects model. The Newcastle-Ottawa Scale was used for assessment of risk of bias in the included studies. Meta-regressions were performed to explore the predictive role of confounders for between-study variance.Results: A total of 63 studies, involving 196,264 infants, were included. Meta-analysis showed ACS exposure was not associated with ROP occurrence . Results from extremely immature subgroups revealed significant reduced risks of ROP occurrence in ACS-exposed infants. ACS exposure was associated with significantly lower odds of ROP progression in adjusted analysis  instead of unadjusted analysis . Meta-regression showed birth weight and patent ductus arteriosus of the cohort were associated with ROP occurrence, sample size and study design strongly associated with ROP progression in ACS-exposed infants.Conclusion: ACS treatment may decrease, but not prevent, the severity of ROP. Findings from severe ROP should be interpreted with caution owing to limited studies and the possibility of false-positive results. Considering the particular benefits in extremely immature infants, we recommend routine usage of ACS in mothers with threatened delivery to this particular birth cohort to prevent ROP occurrence. Future studies adjusting for major confounders are warranted to mitigate risk of bias in such observational evidence. Systematic Review Registration: (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=270250), identifier (CRD42021270250)Retinopathy of prematurity (ROP) is a major cause of childhood blindness associated with aberrant development of retinal vasculature in preterm infants . An estiAntenatal corticosteroids (ACS), first introduced in 1972 , are nowAfter meta-analysis by Yim et al. have been published, a substantial number of relevant studies have been published. Some of them are large-scale cohort studies of high methodological quality. We therefore conducted an updated meta-analysis to examine the association between ACS exposure and ROP development, as well as the role of potential confounders.http://www.crd.york.ac.uk/PROSPERO/, ID = CRD42021270250).This meta-analysis was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines . A PRISMA comprehensive search of related studies was conducted in PubMed, EMBASE, Scopus, Web of Science, and the Cochrane Library from inception to May 2021. The following keywords were used as search terms:  AND (“Steroid*” OR “Cortico*” OR “Betamethasone” OR “Dexamethasone”). Search strategy for other databases was adapted from the initial PubMed strategy. The detailed search strategies were listed in Studies were included if they met all of the following criteria: 1) original observational studies (cohort or case-control studies) or randomized controlled trials (RCTs). 2) reported ROP outcome of children whose mothers were administrated any type of ACS treatment regimen, including betamethasone, and dexamethasone, complete, and partial courses. 3) evaluated the outcome with odds ratios (ORs) and their confidence intervals (CIs), or with raw data provided for calculation. 4) studies reported in English or Chinese. The exclusion criteria were: 1) animal studies, reviews, comments, case reports, and conference abstracts. 2) Studies with no control arm or insufficient data. 3) overlapping cohorts from the same database or reporting repeated outcomes (study with more comprehensive data was included).The author (YZ) searched the aforementioned database and assimilated an original list of literature. Two reviewers (YZ and GG) screened all retrieved records and subsequently extracted data using a standardized form independently. Discrepancies were resolved by checking the primary article and consulting a third reviewer (CL). Data were collected as follows: First author, year of publication, country of study, study design, inclusion criteria, type and course of steroid administration, sample size, association results , adjusted factors. Data based on different doses  and types of steroids (betamethasone or dexamethasone) was extracted separately for subgroup analysis. A complete or optimal course of antenatal steroid use was defined if 24 mg betamethasone  or dexamethasone  were prenatally administrated to mothers with threatened preterm labor. Severe ROP was variably defined as stage 3 and above, threshold ROP, type 1 ROP, or ROP requiring treatment .Two reviewers (YZ and GG) independently evaluated the methodological quality of each study using the Newcastle-Ottawa Scale . This scStata 16.0 software  was used to combine and analyze the outcomes. To correspond to the majority of studies, individual studies with multiple adjusted ORs stratified by different types of steroids or number of embryos were pooled using the method by Hamling et al. to obtain combined risk for the whole population . For sub2 statistic, with 25, 50, and 75% defining threshold for low, moderate and high heterogeneity, respectively. To explore the sources of heterogeneity and the potentially significant associations, subgroup analyses stratified by mean GA and BW, sample size, study design, administration regiment, country economic levels, and adjusted factors were conducted. Further, we performed a random-effects meta-regression in which the predefined covariates were available in more than 10 studies, including sample size, study design, sex, multiple pregnancy, need for mechanical ventilation, and surfactant, RDS, bronchopulmonary dysplasia (BPD), NEC, patent ductus arteriosus (PDA), IVH III/IV, sepsis, and mortality. A p value of < 0.05 (0.10 for Q test) was considered statistically significant.Due to the anticipated inter-study heterogeneity, a random-effects model was utilized to yield the summary statistics. Statistical heterogeneity was calculated using Cochran’s Q test and quantified by Ip value of < 0.05 indicated significant publication bias  to assess the risk of bias. The analysis indicated that all included 63 studies attained a total NOS score of 5–9 (median = 7) .2 = 71.4%, p = 0.29; 2 ranging from 66% to 72%, p value ranging from 0.11 to 0.57).40 studies provided numerical counts on ACS exposure between any stage of ROP and non-ROP groups. For the study by 2 = 70.1%, p = 0.22; 2 ranging from 52% to 72%, p value ranging from 0.12 to 0.49).By pooling adjusted data from 16 studies, the result also yielded no significant difference between ACS exposure and non-ACS infants .33 studies reported numerical counts on the comparison between ACS exposure and severe ROP. Studies by 2 = 81.9%, p = 0.02; 2 = 84.3%, p = 0.05) and Console et al.  individually.Adjusted data provided from 7 studies was subsequently pooled. Interestingly, we found the adjusted odds of severe ROP  and extremely low birth weight infants  . Moreover, a significant association between the two variables was observed in studies with sample sizes less than 500 . No statistical difference was detected when stratified by other factors. Subgroup analysis for studies adjusted for RDS or oxygen therapy was also performed for any stage ROP. Pooled results of eight included studies remained insignificant .Subgroup analysis based on unadjusted data was conducted to unveil the potential influence of other study characteristics. Results from prespecified subgroups were shown in p < 0.0001), and the heterogeneity reduced to 0%. We also noted a significant association in case-control studies  with reduced heterogeneity to 26.9%. However, no significant between-subgroup deference was detected (p = 0.06). There were no special positive findings of other aforementioned factors .As for the association between ACS and severe ROP, significantly lower risks were found in studies with sample sizes smaller than 500 . Each increment of 100 g in the BW of the cohort resulted in an increase in any stage ROP log OR of 0.11 (p = 0.02), indicating each 10% decrease in PDA rate across studies associated with an increase in any stage ROP log OR of 0.2 (k = 25) revealed non-significant result .To address the potential sources of heterogeneity, random-effects meta-regression was conducted for analyses involving more than 10 studies. Results of all univariate analysis are shown in  of 0.11 . SimilarR of 0.2 . Howeverp = 0.003) of variance. One study, with a relatively large sample size , played a dominate role in this effect . Study design of the cohort also explained a significant proportion of variance . Multivariate meta-regression including those two covariates (k = 35) failed, probably due to the same large study as an outlier. Additional multivariate analysis without this study showed non-significant result , indicating their associations with the effect size were interdependent.For severe ROP, sample size of the cohort significantly explained 58%  except for pooled unadjusted data for severe ROP  (p = 0.57).Neither visual inspection of funnel plots nor Egger’s test suggested publication bias ( = 0.01) . Therefo = 0.01) . Filled n > 5,000) were also identified since 2014. Owing to the lack of available RCTs, our meta-analysis of observational studies provides the current best evidence on the association of ACS exposure and ROP. After integrating all available studies, we demonstrated no significant association between ACS exposure and any stage ROP. Results were more variable concerning severe ROP. Unadjusted analysis showed similar nonsignificant effects, while adjusted data revealed that ACS-exposure infants were at significantly reduced risks of severe ROP development.Our present study is a substantial update of the previous meta-analysis by One important finding in our subgroup analysis was that ACS at extreme preterm gestations could prevent the occurrence of ROP, rather than ROP progression. Various efforts have been made to prevent ROP in this particularly high-risk birth cohort . Unlike Unlike mild ROP, infants with severe ROP are prone to develop irreversible vision loss . GrowingWe performed further hypothesis-generating analyses considering possible benefits from varying exposure of ACS regimens. Although the therapy is extremely variable in low-income countries, no significant differences in ROP outcomes were detected based on economic levels . We focuConsiderable differences in ACS effect on ROP incidence were present across studies. Thus, meta-regression analyses were performed to evaluate how these confounders, such as prematurity, contributed to the overall heterogeneity. Univariate meta-regression showed mean BW and PDA rate of the cohort significantly modified the effect of ACS on any ROP development. That is, those studies including infants with lower BW and higher PDA rates might result in a stronger protective effect of ACS on the occurrence of ROP. Although the two covariates changed to nonsignificant in multivariate meta-regression, the results are less reliable with only 25 studies available. We can speculate, at least in part, that the potential protective effect of ACS on ROP can be masked by the diverse subject characteristics. Proper control of these two covariates is thereby essential for the future studies. Besides, the association between ACS and severe ROP was stronger in case-control studies with smaller sample size, corresponding to the subgroup analysis. In that case, the overweight of those study designs in the meta-analysis may produce false-positive results . Those cThe protective effect of ACS on ROP is controversial yet biologically plausible. ACS have long been suggested to modulate fetal maturity, thus may accelerate maturation of retinal vasculature as well . HoweverThe present meta-analysis has several strengths. First, this is the largest meta-analysis to date examining the risk of ROP in ACS-exposed infants. We include 63 cohort studies involving infants at gestational week from 25 to 32.7 weeks. Results are therefore applicable to the general populations of preterm infants born to mothers with standard care of ACS . Second,Certain limitations of the present study should be considered. First, the results are based on observational studies because RCTs are not available on this issue. One should be notified the results from such study design do not provide true assessment of causality between the two variables, as it is subjected to potential bias and confounding. For example, we acknowledge that there might be risk of selection bias if mothers who are potential candidates for ACS are not treated with steroids, because of maternal or fetal emergencies. Those non-treated infants might suffer circulatory or/and respiratory instability, thereby at greater risk of developing ROP . HoweverThe current meta-analysis based on robust evidence confirmed that ACS could not prevent the occurrence of ROP in the general population, but are protective in extremely immature infants. We thereby suggest routine usage of ACS in expected extremely premature infants to prevent ROP occurrence. We further observed that ACS might decrease the severity of ROP, which still warrants further investigations to reach a more reliable conclusion.


Meta-analyses were planned when possible. The methodological quality and potential for bias of included studies were also evaluated. Of the 3362 titles retrieved, 77 were included (62 for EBV infection and 22 for PTLD). The overall quality of the studies was strong. Several risk factors were explored in these studies, but few statistically significant associations were identified. The use of anti-thymocyte globulin (ATG) was identified as the most important risk factor positively associated with post-transplant active EBV infection and with PTLD. The pooled relative risks obtained using the random-effect model were 5.26 (95% CI: 2.92–9.45) and 4.17 (95% CI: 2.61–6.68) for the association between ATG and post-transplant EBV infection and PTLD, respectively. Other risk factors for EBV and PTLD were found in the included studies, such as graft-versus-host disease, type of conditioning regimen or type of donor, but results are conflicting. In conclusion, the results of this systematic review indicate that ATG increases the risk of EBV infection and PTLD, but the link with all other factors is either nonexistent or much less convincing.This systematic review was undertaken to identify risk factors associated with post-transplant Epstein–Barr virus (EBV) active infection and post-transplant lymphoproliferative disease (PTLD) in pediatric and adult recipients of hematopoietic stem cell transplants (HSCT). A literature search was conducted in PubMed and EMBASE to identify studies published until 30 June 2020. Descriptive information was extracted for each individual study, and data were compiled for individual risk factors, including, when possible, relative risks with 95% confidence intervals and/or  Hematopoietic stem cell transplant (HSCT) recipients are at risk of developing post-transplant lymphoproliferative disease (PTLD) following primary or reactivated infection by the Epstein–Barr virus (EBV) ,4,5,6,7.The occurrence of PTLD in patients receiving an allogeneic HSCT can reach 24%, depending on the presence of risk factors ,18,19. TThe rapid increase of EBV viral load (EBV-VL) in the blood is a well-documented predictive biomarker of EBV-associated diseases. Following transplantation, regular monitoring of EBV-VL is usually performed for better management of patients who show large spikes in VL ,23. A reWe conducted, using Medline and EMBASE, a systematic search of all articles on risk factors for active EBV infection (including EBV primary infection as well as EBV reactivation) and PTLD in pediatric and adult recipients of HSCT published in peer-reviewed journals between 1946 and 30 June 2020. A non-exhaustive list of concepts and keywords was obtained by referring to articles related to active EBV infection and PTLD; the list was broadened using medical subject heading (MeSH) descriptors in Medline and Emtree in EMBASE. The ovidSP interface was used to search in both databases. The search equations are presented in For the systematic review, three inclusion conditions were applied: (1) the study population had to be composed of pediatric and/or adult HSCT recipients; (2) risk factors for EBV infection or for PTLD had to be analyzed using univariate and/or multivariate statistical methods; and (3) the paper had to be in English or French. Abstracts, conference papers, congress papers, editorials, guidelines, reviews and case reports were excluded from the systematic review.p-values were extracted when reported. In some cases, the corresponding author was contacted to clarify ambiguities.Two independent authors (PE and MZ) extracted the following information from the selected articles: authors, publication year, location, study type, post-transplant follow-up duration, transplant type, sample size, population , the definition of PTLD or definition of EBV infection, frequency of EBV-VL testing, blood compartment used to measure EBV-VL, and statistical methods used. In addition, for all potential risk factors explored in the studies, point estimates, such as odds ratio (OR), risk ratio (RR), the hazard ratio (HR) and subhazard ratio (SHR), confidence intervals (CI) and The quality of each individual study was independently evaluated by two authors (PE & MZ) using a modified version of the Effective Public Health Practice Project (EPHPP) quality assessment tool for quantitative studies ,26. The Finally, risk factors explored in these studies were described by providing the total number of studies showing a statistically significant association contrasted to the total number of studies investigating the risk factor.p-value was reported (not the measure of association). Since post-transplant EBV infection is not a rare event in this population, to obtain pooled estimates, results from studies that reported adjusted HR or SHR were combined separately from those that reported adjusted OR. This distinction was not made for PTLD, which is a relatively less frequent event. Adjusted estimates were combined using the inverse variance method with the fixed-effect model or random-effect model. The choice between these two models was guided by the value of statistic I, which revealed the proportion of the total variance observed due to a real difference in the measures of effects between studies. The fixed-effect model was used when I2 < 25% and the random-effect model when I2 ≥ 25% [The data reported made it possible to perform a meta-analysis solely to measure the association between the use of anti-thymocyte globulin (ATG) and two outcomes: post-transplant EBV infection and PTLD. Studies using multivariate analysis were considered for the meta-analysis except for the study by Liu et al.  because I2 ≥ 25% ,29. We aI2 ≥ 25% . The anaIn total, 3362 titles were identified in the research bases, 1883 in EMBASE and 1479 in Medline. Once duplicates and papers with exclusion criteria were removed, 77 articles ,101,102 Characteristics of the selected studies are described in The definition of post-transplant EBV infection and the diagnostic criteria for PTLD differed among studies. Active post-transplant EBV infection was diagnosed when the EBV-VL in blood, determined using a PCR test, was above a given threshold. In some cases, thresholds were not readily comparable because there was no direct conversion between the units of measurement used. In two studies ,91, actip-value ˂ 0.1 in univariate analysis were retained for multivariate analysis in eight studies, a p-value ˂ 0.2 in three, a p-value ˂ 0.3 in one, a p-value ˂ 0.05 in one; a p-value < 0.05 was used for the multivariate analysis in three studies. In four studies, the investigators used a p-value < 0.1 in the univariate analysis combined with a p-value < 0.05 in multivariate analysis. Altogether, 52 studies were considered as properly adjusted for confounding bias.Various statistical methods were used. Logistic regression was used in 13 studies, Cox model in 22, survival analysis using the log-rank test in one, multiple linear regression in two, Fine and Gray competitive risk model in 10 and Poisson regression for grouped survival data in one. Among the 28 studies employing univariate analysis, the statistical method was not explicitly reported in one study; one study used univariate logistic regression, another used the univariate Cox model, another used time-dependent landmark, while other studies used at least one of the following tests: Log-rank test, Gray’s test, Chi 2 test, Wilcoxon nonparametric test, Kruskal–Wallis test, Fisher’s exact test, Mann–Whitney test or Wald test. Among the 49 studies in which a multivariate analysis was performed, the criteria for selecting variables for the multivariate model were explicitly indicated in 20. Variables with a p-value. p = 0.009). However, these results were not corroborated in four other studies [The association between acute (a)GvHD and post-transplant EBV infection was examined in 21 studies ,91,101.  studies ,65,68,76 studies ,86,88, t studies ,69 did np = 0.04).In regards to PTLD, its occurrence was associated with aGvHD grade ≥2 in Landgren et al. (RR = 1.7 [1.2–2.5)) , Uhlin ep = 0.004). All studies compared patients who received ATG versus those who did not, but one: Van Esser et al. [p = 0.04) as well as for CD4+ depleted grafts by Torre-Cisneros et al. [ATG use appears to be an important risk factor for the development of active post-transplant EBV infection or PTLD. Among 15 multivariate studies ,85,86,96r et al.  , Xuan et al. [An association between ATG and PTLD was reported by Landgren et al.  , but Xuan et al. [The use of reduced-intensity conditioning regimen was determined as a risk factor for post-transplant EBV infection by Sanz et al.  . Similar results were found by Gao et al. (HR = 5.9 (2.5–13.9)) [p = 0.005) [p = 0.04) [p = 0.030) [+ count in the graft ≥ median (OR = 0.11 (0.02–0.78)) [+CD8+ count in the graft ≥ median (OR = 0.05 (0.01–0.43)) [+ count in the graft >1.35 × 106/kg (HR = 2.6 (1.5–4.6)) [+ lymphocyte/µl at one month after HSCT ≥ 50 (OR = 0.1 (0.02–0.481)) [+ T cell count 30 days post-transplant (HR = 0.347 (0.161–0.747)) [p < 0.001).With regard to viral infections, a study by Zallio et al.  suggests5–13.9))  and by Z5–13.9)) . Xu et a5–13.9))  and Gao 5–13.9))  found th5–13.9)) , the ris5–13.9))  found a = 0.005)  and the = 0.005) , (2) the= 0.005) , (3) unr = 0.04) , (4) unr= 0.030) , (OR = 5= 0.030) , (HR = 2= 0.030) ), (5) HL= 0.030) , (HR = 1= 0.030) ), (6) CD1–0.43)) , (8) CD3.5–4.6)) , (9) CD4–0.747)) , (11) Ig–0.747)) , (12) pr–0.747)) , and (13–0.747)) . Also, a–0.747))  in patie–0.747))  (HR = 18+ count (≥median vs. <median) 30 days after HSCT (HR = 0.34 (0.13–0.92)), (2) prior HSCT ((HR = 2.6 (1.1–6.4)) [Other factors associated with PTLD include: (1) CD8.1–6.4)) , (RR = 3.1–6.4)) ), (3) sp.1–6.4)) , (4) inf.1–6.4)) , (5) a s.1–6.4)) , (6) HLA.1–6.4)) , and (7).1–6.4)) . Fujimot.1–6.4))  found thThis systematic review includes 77 papers. It aims to characterize risk factors associated with active post-transplant EBV infection and PTLD in HSCT recipients. Active EBV infection can result in rapidly increasing EBV-VL, which is a high-risk marker for PTLD development. Proper identification of the risk factors associated with active EBV infection and PTLD is needed for effective patient management.In this systematic review, we focused on risk factors explored in published studies; very few statistically significant associations were found. The use of ATG was identified as one of the most important risk factors for the development of active post-transplant EBV infection and PTLD. The pooled relative risks estimated from the meta-analysis that was carried out confirmed a positive and statistically significant association between ATG and EBV infection (RR = 3.98 (95% CI: 2.20–7.18) and PTLD (RR = 3.69 (95% CI: 2.24–6.08)). ATG is a potent immunosuppressive agent that obliterates the T-cell pool ,105,106,Some studies included in this review also found an association with the presence of GvHD, which is an immune-mediated complication of HSCT whereby donor T cells present in the graft initiate an alloreactive process that ultimately causes destruction of host tissues . aGvHD uMany other variables were analyzed in the 77 included studies, but results were either inconsistent, failed to find an association, or limited in terms of the number of studies that investigated the risk factor. Some studies showed that primary diagnosis was associated with post-transplant active EBV infection ,39,88, m+, CD3+, CD8+, CD3+/CD8+), genotype , splenectomy, mesenchymal stromal cells, donor gender and transfusion   . In our  plasma) . The senp-values. However, as indicated above, a meta-analysis was carried out to measure the association between ATG use and post-transplant EBV infection and PTLD, respectively. The results, however, must be considered with caution, as the definition of outcome was quite variable from one study to another. Based on all the above arguments, further studies using large cohorts of children and adults are needed to better elucidate the determinants of active EBV infection and PTLD among HSCT recipients.This review was not able to discern whether differences exist between children and adults. While statistical power was higher in studies combining both groups, differences in terms of risk factors may exist. Immune restoration through T-cell reconstitution after transplantation is different in children and adults , and risIn conclusion, we found ATG as the most important risk factor for the development of active post-transplant EBV infection and PTLD in HSCT patients. ATG considerably increases the risk of EBV and PTLD. Other risk factors have been linked with EBV and PTLD in studies, such as GvHD or type of donor, but the association for these other factors is less clear due to conflicting results, the potential for bias, particularly confounding, or because of the low number of studies that considered these risk factors. Further studies using large cohorts of children and adults with appropriate control for confounding are needed to better characterize other determinants of active EBV infection and PTLD among HSCT recipients.