Introduction: The links between flavonoid intake and mortality were previously evaluated in epidemiological studies. The aim of the present study was to perform a systematic review and meta-analysis of cohort studies evaluating the link of flavonoid consumption with total and cause-specific mortality. Methods: Prospective cohort studies reporting flavonoid intake and mortality data published up to 30th April 2019 (without language restriction) were searched using PubMed, Scopus and EMBASE database. Generic inverse variance methods and random effects models were used to synthesize pooled and quantitative data. Sensitivity analysis was also performed by a leave-one-out method. Results: Overall, 16 articles met the inclusion criteria ; a total of 462,194 participants  with 23,473 mortality cases were included in the final analysis. The duration of follow-up ranged from 4.8 to 28 years. Most of the studies assessed flavonoid intake using food frequency questionnaires, whereas four studies used interviews and 1 study used 4-day food records. The meta-analysis showed that flavonoid consumption was inversely and significantly associated with total (relative risk (RR): 0.87, 95% confidence interval (CI) = 0.77–0.99) and cardiovascular disease mortality risk , but not cancer  mortality risk. These findings remained robust in sensitivity analyses. Conclusions: The present findings highlight the potential protective role of flavonoids against total and cause-specific mortality. These results support the recommendations for flavonoid-rich foods intake to prevent chronic diseases. Cardiovascular disease (CVD) remains the leading cause of death worldwide; however, in the high-income countries, cancer deaths have exceeded it . The totFlavonoids present in foods may contribute to CVD protection . Flavonon = 10 studies) showed a protective role of flavonoid intake in relation to total mortality , but no significant correlation with CVD mortality  [n = 15 cohort studies) found that flavonoid intake significantly decreased total and CVD mortality but did not investigate the association with cancer mortality [A previous meta-analysis 70–1.03) . Regardi0–1.03 . 70–1.03) , while a70–1.03) . AnotherIn the present meta-analysis, we systematically reviewed current data from prospective studies on flavonoid consumption in relation to the risk of total, cancer and CVD mortality.The Observational Studies in Epidemiology (MOOSE) guidelines were followed to design, conduct and report the present meta-analysis . The prip < 0.001), and any disagreements were resolved between the reviewers before the selected articles were retrieved  who were blinded to the qualifications, names or the institutional affiliations of the study authors to avoid bias. Between these two reviewers, agreement was excellent  the primary exposure of interest was flavonoid consumption; (2) the studies were population-based cohort studies, reporting total, CVD and cancer mortality; (3) hazard ratio (HR), RR or odds ratio (OR) estimates with 95%CI adjusted for multivariable parameters were provided or were able to be calculated; and (4) original articles with full texts in English.We excluded: (1) letters, reviews, comments, editorials, expert opinion papers, methodological articles, unpublished data or any publication lacking primary data and/or explicit method descriptions; (2) non-English papers; (3) studies other than population-based cohorts; and (4) studies in which HR, RR or OR estimates with 95%CI were not available or not able to be calculated.The full texts of the included studies were retrieved and screened for eligibility by two reviewers . The Newcastle–Ottawa Scale NOS,  was usedp value for heterogeneity were calculated with the random-effect model. RRs comparing the highest with the lowest flavonoid intake category were combined across studies to generate the summary associations. The I2 test [I2 > 50% together with p (two-sided) < 0.05 indicated significant heterogeneity across studies [When study results were from different multivariable-adjusted models, the model with the majority of the confounding parameters was used for the present meta-analysis. Pooled RR, 95%CI and  I2 test ,25,26 an studies ,25,26. AThe presence of publication bias was evaluated by the visual inspection of Begg’s funnel plot asymmetry and Egger’s weighted regression tests. Furthermore, the Duval and Tweedie trim method was applied to adjust the analysis for the effects of publication bias . The preOverall, of the 34 eligible full articles, 16 articles met the inclusion criteria . An overp = 0.039, n = 9 studies, p = 0.017, n = 15 studies, p = 0.302, n = 4 studies, There was a reverse and significant association between flavonoid consumption and all-cause mortality , CVD  and cancer  mortality.p = 0.170) indicated the absence of publication bias. After using the ‘trim and fill’ correction to adjust the effect size for potential publication bias, there were no potentially missing studies in the funnel plot. According to the ‘fail-safe N’ test, 20 studies would be needed for the RR to become non-significant (p > 0.05).Visual examination of the funnel plot symmetry showed no publication bias for the association between flavonoid intake and total mortality. Similarly, the Egger’s linear regression  mortality. Pooled data from observational prospective studies showed a significant and negative relationship between flavonoid intake and the risk of all-cause and CVD mortality.Previous studies on flavonoid consumption and mortality have reported conflicting findings. Our results are in agreement with previous meta-analyses of randomized controlled trials (RCTs) and observational studies on flavonoids, suggesting that their intake might be protective against CVD, cancer and total mortality ,29,30,31n = 93,145 young and middle-aged US women in the NHS-II) found an insignificant relationship between total-flavonoid intake and risk of all-cause mortality [In contrast with our findings, another study  might have affected the observed associations, although we controlled for potential confounding variables with the use of RRs. Furthermore, the reliability of the available data may have been affected by (1) a small number of cases in some studies, possibly affecting the statistical power of the analyses; (2) a single baseline assessment of dietary intake, with a lack of specific information over time related to mortality; and (3) a lack of data on the associations between different flavonoid types and causes of mortality. Finally, some of the included studies involved specific groups of individuals, limiting the generalizability of these results to the general population .Our findings highlighted the potential protective role of flavonoids against total, cancer and CVD mortality. These results further support the recommendations for flavonoid-rich foods intake to prevent cardiovascular diseases and cancers. Due to the potentially different effects of flavonoids, recommendations should also highlight the importance of dietary variety, including diverse flavonoid sources. Further research is required to establish the specific role of individual flavonoid classes as well as the quantities needed to be consumed to achieve health benefits.


This study aimed to verify noteworthy findings between genetic risk factors and autism spectrum disorder (ASD) by employing the false positive report probability (FPRP) and the Bayesian false-discovery probability (BFDP). PubMed and the Genome-Wide Association Studies (GWAS) catalog were searched from inception to 1 August, 2019. We included meta-analyses on genetic factors of ASD of any study design. Overall, twenty-seven meta-analyses articles from literature searches, and four manually added articles from the GWAS catalog were re-analyzed. This showed that five of 31 comparisons for meta-analyses of observational studies, 40 out of 203 comparisons for the GWAS meta-analyses, and 18 out of 20 comparisons for the GWAS catalog, respectively, had noteworthy estimations under both Bayesian approaches. In this study, we found noteworthy genetic comparisons highly related to an increased risk of ASD. Multiple genetic comparisons were shown to be associated with ASD risk; however, genuine associations should be carefully verified and understood. Autism spectrum disorder (ASD) is a brain-based neurodevelopmental disorder characterized by pervasive impairments in reciprocal social communication, social interaction, and restricted and repetitive behaviors or interests, resulting in a substantial burden of individuals, families, and society ,2. The rAlthough the full range of etiologies underlying ASD remain largely unexplained, progress has been made in the past decade in identifying some neurobiological and genetic risk factors, and it has been well established that combination of genetic and environmental factors is involved in the etiopathogenesis of autism ,6. ThereASD is polygenic and genetic variants contribute to ASD risk and phenotypic variability. The results of previous studies showed genome-wide genetic links between ASD ,12. TheyTo the best of our knowledge, this is the comprehensive study to summarize the loci that are associated with ASD among the several known loci reported to be related with ASD. We have synthesized all available susceptibility loci for ASD retrieved from meta-analyses regarding the association between the individual polymorphisms and ASD. For the study, we reviewed observational studies, Genome-Wide Association Studies (GWAS) meta-analyses, the combined analysis of GWAS discovery and replication cohorts, the GWAS catalog and GWAS data from GWAS meta-analyses . FurtherThis review was conducted following a registered protocol. The specified methods are available on the PROSPERO database with the registration number CRD42018091704. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of this review are shown in Studies were included if they satisfied the following conditions: (1) estimated the risk of ASD in humans using meta-analyses in terms of odds ratio (OR) and 95% confidence interval (CI); (2) published in English. Articles were excluded if (1) they did not cover the subject of genetic polymorphism or ASD; (2) did not have individual results for ASD; (3) did not use statistical methods of meta-analysis.A PubMed search was performed to extract data from meta-analyses regarding the gene polymorphisms of ASD published until 1 August, 2019. Two of the authors (MJ Son and CY Son) used the search terms  and obtained relevant articles, first, by scanning the titles and abstracts and, second, by reviewing the full-text . During p-value. We retrieved all the main data (preferably adjusted), and, for comprehensiveness we additionally extracted subgroup analysis data if the main data were not statistically significant. When data were incomplete, we contacted the corresponding authors for additional information. From each article, we extracted the first author, year of publication, the number of individual studies included, the number of cases and controls, and the number of families if a meta-analysis included family-based studies, the type of statistical model (fixed or random) and study design. We also recorded gene name, gene variants, genotypic comparison, OR with 95% CI, and the corresponding p-value < 0.05 for meta-analyses of observational studies, and <5 × 10−8 for GWAS or meta-analyses of GWAS. Meanwhile, genetic associations with a 5 × 10−8 < p-value < 0.05 were defined as being of borderline significance in GWAS or meta-analyses of GWAS. In addition, we recorded genetic comparisons with p-value < 5 × 10−8 for our gene network, even when they were not re-analyzable due to insufficient raw data.Reported association was considered statistically significant if p-value [−3 and 10−6 and used statistical power to detect two OR levels, 1.2 and 1.5, so that readers can make their own judgment about the evidence for each genetic variant. BFDP is similar to FPRP but uses more information than FPRP [-3 and 10−6. We set the thresholds of noteworthiness of FPRP and BFDP to be <0.2 and <0.8, respectively, as recommended by the original papers and highlighted corresponding results in bold type [Evaluations of the statistical significance of studies about genetic polymorphisms too often inferred false positives, when the evaluations were solely based on p-value . Therefop-value . We usedp-value  and Wakep-value  to calcuhan FPRP . Both prold type ,15. Genep-value < 5 × 10−8 to establish a network of genes using STRING 9.1  related to ASD [p-value < 5 × 10−8) or borderline significance  with a noteworthy association under both Bayesian approaches, were included. Any results with a p-value < 5 × 10−8 that were not re-analyzable were also added in the network analysis. PPI networks provide a critical assessment of protein function on ASD including direct  as well as indirect  associations. We collected genetic comparisons either with noteworthy results under both FPRP and BFDP or with d to ASD . GeneticThe initial PubMed literature search yielded 747 articles. Out these, 656 articles were excluded after screening the title and abstract, and 64 articles were omitted after reviewing the full-text. Twenty-seven studies were finally included for the re-analysis of observational studies, GWAS, and meta-analyses of GWAS . p-value < 5 × 10−8). Out of the remaining six articles, two were already in our dataset from the literature search from PubMed. Finally, four articles from the GWAS catalog were manually added to 27 articles previously screened from PubMed, leading to a total of 31 eligible articles [Additionally, 25 articles were searched on the GWAS catalog, but 14 articles did not meet the criteria were excluded. Among the remaining 11 articles, five articles were not re-analyzable due to insufficient raw data. Moreover, five articles were already included in our dataset from the PubMed search. However, we retained three of the non-re-analyzable articles ,18,19 siarticles ,45,46,47This paper is divided into two parts: (1) the observational studies part, and (2) the GWAS part. In the observational studies, all statistics were collected considering the overlapping, and results of gene variants with/without statistical significance . Even thp-value < 0.05 as listed in Among the 31 eligible studies, 19 were meta-analyses of observational studies, which corresponded to 125 genetic comparisons. Thirty one out of 125 genotype comparisons were reported as being statistically significant using the criteria of −3 and 10−6 with a statistical power to detect an OR of 1.2; seven (22.6%) and two (6.5%) were verified to be noteworthy (<0.2) using FPRP estimation, at a prior probability of 10−3 and 10−6 with a statistical power to detect an OR of 1.5. In terms of BFDP, five (16.1%) and two (6.5%) comparisons had noteworthy findings (<0.8) at a prior probability of 10−3 and 10−6. Two single nucleotide polymorphisms (SNPs) were found to be noteworthy under FPRP estimation only, and not under BFDP . In conp-value ≥ 0.05 , while the remaining 202 comparisons (99.5%) satisfied the criteria of borderline significance  previously defined.Seven GWAS meta-analyses and one study with a combined analysis of GWAS discovery and replication added up to 203 genetic comparisons ,46,47,48e ≥ 0.05 , none of−3 and 10−6 with statistical power to detect an OR of 1.2. Moreover, fifty-four (26.6%) and eight (3.9%) were identified as noteworthy at a prior probability of 10−3 and 10−6 with statistical power to detect an OR of 1.5. Overall, forty genetic comparisons (19.7%) were found noteworthy under both Bayesian approaches, which included a single genetic comparison satisfying the conventional significance threshold of p-value < 0.05  and four (2.0%) were assessed to be noteworthy at a prior probability of 10e < 0.05 .p-value < 5 × 10−8. The remaining 18 comparisons were of borderline statistical significance . Genetic comparisons additionally extracted from the GWAS catalog were also re-analyzed . Among t−3 and 10−6, respectively, with the statistical power to detect a 1.2 OR. In addition, eighteen (90.0%) and four (25.0%) showed noteworthiness at a prior probability of 10−3 and 10−6 with the statistical power to detect a 1.5 OR, respectively. In the BFDP estimation, nineteen (95.0%) and two (10.0%) were assessed as being noteworthy at a prior probability of 10−3 and 10−6, respectively. Finally, 18 genetic associations (95%) of both significant and borderline statistically significant results were verified as being noteworthy under both the FPRP and BFDP approaches. The total number of associations included two comparisons with genome-wide significance  and sixteen comparisons with borderline significance .While assessing noteworthiness, five (25.0%) and three (15.0%) were verified as being noteworthy using FPRP estimation, at a prior probability of 10In order to develop the analysis further, we extracted the GWAS data that was both statistically significant and noteworthy under both Bayesian approaches, from the GWAS meta-analysis and GWAS catalog. They were extracted from five articles ,32,33,34p-value < 5 × 10−8. We included the results of both re-analyzed and non-re-analyzable genetic comparisons from meta-analyses of observational studies and GWAS, GWAS included in meta-analyses of GWAS, and the GWAS catalog. The statistically significant results of non-re-analyzable studies are presented in the We established PPI networks related to the risk of ASD by filtering genes noteworthy under both FPRP and BFDP or genes with a The major genes that included a strong genetic connection were the myc-associated factor X (MAX) network transcriptional repressor (MNT), oxytocin receptor (OXTR), nucleolar and coiled-body phosphoprotein (NOLC1), peroxisome proliferator-activated receptor gamma related coactivator-related 1 (PPRC1), pyruvate carboxylase (PC), methylenetetrahydrofolate reductase (MTHFR), multiple epidermal growth factor like domains 10 (MEGF10), nuclear factor kappa B subunit 2 (NFKB2), histone deacetylase 4 (HDAC4), etc. .To our knowledge, this study is the first study of ASD genetic risk factors, which assessed the levels of evidence of the published meta-analyses showing the association between susceptible loci and ASD. Overall, genetic comparisons with noteworthy results were confirmed as risk factors for ASD. The genetic comparisons highly related to an increased risk of ASD might reflect the implication in neurodevelopment and specific synaptogenesis of ASD. According to the PPI network, composed of noteworthy results obtained when using both Bayesian approaches, multiple genes were included as a risk factor for ASD. Investigating the lists genes as a risk factor, promising candidates encoded the protein associated with neural development and specification, and also with neurotransmitters and its receptors. These genes were RELN and DRD3 from observational studies, and PC, OPCML, ERBB4, OR2M4, MEGF10, OR2T33, NMB, and NOLC1, from GWAS. In line with our findings, previous reports have supported that the migration and proliferation of neuronal cells is essential to understanding neurodevelopmental disorders such as ASD or schizophrenia ,50. In ap-value < 0.05 exhibited noteworthy associations with ASD under both Bayesian approaches  meta-analyses of observational studies and 163 out of 203 (80.3%) in meta-analyses of GWAS, respectively. However, only a small portion of genetic comparisons with a proaches .−8 < p-value < 0.05) accounted for 53 out of 126 (42%) noteworthy comparisons from GWAS or meta-analyses of GWAS. These genetic comparisons might have been neglected if the p-value alone was considered to determine noteworthiness. Using the two Bayesian approaches as we did, or relaxing the current GWAS threshold as Panagiotou et al. suggests, might enable better interpretation of GWAS results [Moreover, we also detected that genetic comparisons with borderline statistical significance  were found noteworthy under both FPRP and BFDP: T vs. C, MTHFR C677T; T (minor), MTHFR C677T; G vs. A, DRD3/rs167771; C vs. G, RELN/rs362691; A (minor), OXTR/rs7632287. From the meta-analyses of GWAS, we could confirm that 34 distinct genes are noteworthy under both Bayesian approaches with about 30 genetic connections. However, the fact that all three comparisons with a s1879532 , rs47730s1879532 , rs41414s1879532 —displayep-value per genetic variant. Therefore, we could not consider potentially meaningful subgroup analyses for different ethnicity, location, gender, and type of genotype comparison  when selecting a certain outcome. We focused on whether the individual genotype variant was truly associated with ASD or not, regardless of the specific type of the genotype comparison or ethnicity.There are several limitations in our review. First, we did not include studies that have not been meta-analyzed, or meta-analyses that had insufficient data in our review. Secondly, we only included the single findings of a meta-analysis with the lowest Our study has several strengths and implications. For example, to our knowledge, this is the first study that simultaneously analyzed a sizeable amount of data about genetic factors including not only GWAS but also the GWAS catalog. Despite the known high heritability of ASD and abundant research in ASD that has focused on the underlying genetic causes, the literature on genetic risk factors for ASD has not fully reached a consensus. This comprehensive review of genetic associations linked to ASD may improve understanding of the strengths and limitations of each form of research, and advance better and novel approaches for examining ASD in the field of genetic research. The findings of this study could provide mechanisms that may be explored for the development of novel neurotherapeutic agents both for the prevention and treatment of ASD.p-value ranging between 0.05 and 5 × 10−8, but also from genetic variants within borderline significance rage which were almost half of the genetic variants. This finding speculates that the genetic variants with borderline significance needs to be further analyzed to determine what associations are genuine. In conclusion, we synthesized published meta-analyses on risk factors of ASD to acquire noteworthy findings and false positive results by adopting two Bayesian approaches for genetic factors. We attempted to synthesize all meta-analyses on genetic polymorphisms linked to ASD and found noteworthy genetic factors highly related to an increased risk of ASD. We also investigated their validity by discovering false positive results under Bayesian methods. To verify results obtained from genetic analyses, both approaches may have advantages, especially for interpretation of results obtained from observational studies. We found noteworthy results from GWAS, not only with


Participants with MHO had a significantly lower risk of all-cause mortality  than MHNO participants, but a borderline significantly higher risk of all-cause mortality than MHNW participants . The CVD risk and all-cause mortality of the MHO group changed depending on the control group. Thus, future studies should select control groups carefully.We investigated the association among metabolically healthy obesity (MHO), cardiovascular disease (CVD)risk, and all-cause mortality in the Asian population. We searched databases from inception to 16 November, 2019 and pooled data using a random-effects model. Subgroup analysis was conducted according to the following comparison groups: MHNW (without overweight or underweight participants) and MHNO . Nineteen studies were included. The mean Newcastle–Ottawa Scale score was 7.8. Participants with MHO had a significantly higher CVD risk (odds ratio (OR) = 1.36, 95% confidence interval (CI) = 1.13–1.63) and significantly lower risk of all-cause mortality  than the comparison group. Subgroup analyses revealed participants with MHO had a significantly higher CVD risk than MHNW participants (OR = 1.61; 95% CI = 1.24–2.08; I Cardiovascular disease (CVD) is an important global health issue. In 2016, an estimated 17.9 million people died from CVD, representing 31% of all global deaths . We. We11]. 2), definitions of metabolically healthy/unhealthy status, adjusted variables, definition of CVD, and main results from the tables and text of the full paper. Adjusted odds ratio (OR) for the risk of CVD and all-cause mortality were extracted from each study.A standardized data collection form was implemented to extract data. We extracted the following information from each study: First author’s name, year of publication, country where the cohort study was conducted, numbers of participants, proportion of women, percentage of smokers, prevalence of MHO, participant age at baseline, follow-up duration, definition of obesity, BMI categories  for cohort studies . The NOS2 statistic and Cochran’s Q-test to measure heterogeneity. A significant Q test  or I2 > 50% indicated the presence of heterogeneity [All statistical analyses and plotting were performed using the meta package and metafor package in the RStudio software . For the meta-analysis of cohort studies, OR was transformed to natural logarithms and the 95% confidence intervals (CIs) were used to calculate the standard errors. If multiple effect sizes were reported in one study, we calculated the average logarithms of the OR (LOR) and the average standard errors. We assumed that the true effect could vary between studies. Thus, we employed a random-effects model. We used the Iogeneity .A total of 12,826 studies were identified using keywords in the initial database search, and 103 studies were identified through the manual search of the references of the related articles. After the removal of duplicate articles and reviewing titles and abstracts, 220 full-text articles were retrieved and assessed for eligibility. During the processing process, the two reviewers had no disagreement on involving studies and a total of 19 studies met the inclusion criteria in the qualitative analysis. After failing to receive the data required to perform the analysis for one study, 18 studies were included in our final quantitative analysis . Nineteen cohort studies were included in our systematic review including 13 studies from east Asia and six studies from west Asia. No mixed population or race diversity was reported in our included studies. This included a total of 1,637,994 participants with a median age of 49.9 years (range = 31.2–71.8), a median MHO prevalence of 7.5% (0.6–24.8), a median percentage of women of 54.8% (0–77.9), and a median follow-up duration of 8.0 years (3.2–18.4). Most of the included studies used BMI as the index of obesity except for one study that used body fat  and anotMost of the included studies defined metabolic health according to the original or revised risk factors of metabolic syndrome except for one study that used the homeostasis model to assess insulin resistance  and one The risk of bias assessment is summarized in 2 = 75%; between-study variance (τ2) was 0.0859; forest plot shown in 2 = 73.%, τ2 = 0.12), but there was no statistically significant difference compared with MHNO participants . The forest plot of the subgroup analysis is presented in A total of 18 studies were included in our quantitative analysis. Since Doustmohamadian et al.  only repp = 0.58, p = 0.50, p = 0.60, respectively; bubble plots are shown in The meta-regression analysis revealed a nonsignificant and weak trend for declining CVD risk of MHO with an increasing proportion of women, age, and proportion of smokers (p = 0.48).Each bubble represents one study, and the bubble size represents the study’s sample size. The regression line shows a nonsignificant and weak trend for the declining risk of CVD with the increasing proportion of women .The funnel plot was symmetrical on inspection , and the2 = 46%, τ2 = 0.01; 2 = 9%, τ2 = 0) than the MHNO participants but a borderline significantly higher risk of all-cause mortality than the MHNW participants . Heterogeneity in both subgroups was zero, and the subgroup analysis is shown in There were six studies that assessed the all-cause mortality rate in our pooled analysis. This showed that participants with MHO had a significantly lower risk of all-cause mortality than the comparison groups . We performed a sensitivity analysis of MHO and all-cause mortality by omitting each study in turn . An addiSimilar to a previous study , we founIn view of unexpectedly lower risk of all-cause mortality of MHO than the comparison groups, we performed the subgroup analysis. The result showed that when the comparison group was MHNW, MHO had a marginally higher risk of all-cause mortality. However, when compared with MHNO, MHO had a lower risk of CVD and all-cause mortality. To analyze this comparison group, six studies selected MHNO as the comparison group. One study used waist circumference , and anoThe Asian diet is relatively high in carbohydrates. As the diet habit westernized, the Asians consumed more highly processed foods than the traditionally complex carbohydrates, which are linked to insulinemic responses and further risk of obesity and CVD . At simiSince obesity is increasing in Asia, the results of this study are relevant for future studies. After choosing the reasonable comparison group and defining obesity among a heterogeneous population , we showThe present study has several limitations. First, none of our included articles adopted the latest definition of MHO. A new robust definition has been published in the last two months , but, toAsian individuals with MHO had a higher risk of CVD and all-cause mortality than MHNW individuals. Future studies should be careful in selecting the index of obesity and the control group. Our results suggest that Asians, notably MHO individuals, should aim to have a normal weight to avoid CVD.


Individuals with established psychosis and those at high-risk for the disorder have been found to show abnormalities within the hypothalamic-pituitary-adrenal (HPA) axis, including elevations in basal and diurnal cortisol, but a blunted cortisol awakening response. However, the extent to which these features are associated with psychosocial stressors encountered in the natural environment  is currently unclear. We therefore conducted a systematic review and meta-analysis to investigate the concordance between naturally-occurring psychosocial stressors and cortisol levels in these populations.PubMed, PsycINFO, and EMBASE were searched up to November 2019 to identify studies examining the concordance between psychosocial stressors and cortisol in healthy controls and individuals on the psychosis spectrum . An overall meta-analysis  was performed to determine the degree of concordance irrespective of group status, with meta-regression employed to test whether the degree of concordance differed in established psychosis and high-risk groups compared to controls. Planned stratified analyses were then performed to examine group differences (where established psychosis and high-risk groups were combined) within individual stressor-cortisol pairings.r=0.05 (95% CI: -0.00 to 0.10), p=0.059] and that neither established psychosis status  nor high-risk status  had a significant effect of the strength of correlation. In stratified analyses, significant differences between healthy controls and psychosis spectrum groups were observed for only one of the six stressor-cortisol pairings examined, where life event exposure and diurnal cortisol were positively correlated in controls [r=0.25 (95% CI: 0.01 to 0.46)], but negatively correlated in the psychosis spectrum group [r=-0.28 (95% CI: -0.49 to -0.04)].Eighteen studies (16 datasets) were eligible for inclusion. The overall model, comprising 134 effect sizes, showed that stressors and cortisol measures were only weakly correlated [Overall, we observed poor concordance between naturally-occurring psychosocial stressors and cortisol irrespective of stressor type, cortisol measure, or group status. We consider a range of methodological factors that may have obscured the ability to detect “true” associations and provide recommendations for future studies in this field. Research conducted over the past four decades has provided evidence to suggest that psychosocial stress contributes to the onset and exacerbation of psychosis. Meta-analyses indicate that major life events and childhood trauma  are associated with increased risk of developing psychotic disorders , 2. FurtOne leading hypothesis, the neural diathesis-stress model –20, propSeveral systematic reviews/meta-analyses have been published concerning the “stress response” in psychosis [for an overview see ]; howeveTo this end, we conducted a systematic review and meta-analysis of studies examining the concordance between naturally-occurring psychosocial stressors and HPA axis function among individuals on the psychosis spectrum. Given that cortisol is the most widely used measure of HPA axis function , 35, we As this was the first review to address these specific questions, we tested four possible (and competing) hypotheses regarding the pattern of findings across controls and psychosis spectrum groups , the search strategy and reporting was conducted in compliance with the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines .PubMed and Ovid  databases were searched for articles published up to November 2019 using the following terms: (genetic high risk) OR family history) OR prodrom*) OR at risk mental state) OR clinical high risk) OR ultra high risk) OR sibling*) OR offspring*) OR relative*) AND (psychotic) OR psychosis) OR schizophren*) OR schizotyp*) OR psychotic experiences) OR subclinical psycho*) OR psychotic) OR psychosis) OR schizophren*) OR schizotyp*) OR psychotic experiences) OR subclinical psycho*) AND (trauma) OR advers*) OR neglect) OR stress*) OR hassles) OR life events) OR maltreatment) OR abuse) AND (HPA axis) OR stress response) OR cortisol) OR glucocorticoid). The searches were performed independently by two researchers . No restrictions were applied for year of publication. Reference lists of eligible studies and relevant reviews were manually searched to identify additional studies.We included observational studies  that examined the relationship between naturally-occurring psychosocial stressors and cortisol in individuals on the psychosis spectrum (patients with established psychosis or those at elevated risk for psychosis) and healthy controls. Patients with diagnoses of first-episode psychosis, multi-episode psychosis, schizophrenia, and schizoaffective disorder were eligible for the established psychosis group. Consistent with a previous review by our group , we defiAll articles identified in the search were independently rated for eligibility by two authors . Disagreements were resolved following a discussion with a third author (AC). Article titles and abstracts were first screened to remove those that were clearly not relevant to the review; a full text review was then performed for all potentially eligible articles (both phases performed in duplicate). Original studies meeting the following criteria were eligible: i) inclusion of a psychosis spectrum group  and healthy control group, ii) assessment of naturally-occurring psychosocial stressors , iii) measurement of cortisol , iv) concordance between psychosocial stressor and cortisol reported, and v) published in English in a peer-reviewed journal. Articles that did not include a control group or report the association between psychosocial stressors and cortisol were excluded. Conference abstracts were not included (as none included sufficient data), but where relevant abstracts were identified, additional searches (by author name) were conducted to determine whether a full text article had been subsequently published and/or corresponding authors were contacted for further details. Where studies with potentially overlapping samples were identified we contacted study authors to clarify.Two researchers  extracted study characteristic data from eligible articles, this included: author(s), year of publication, psychosis spectrum group(s), psychosis spectrum group recruitment/identification method, sample size, mean age and sex of psychosis spectrum and control groups, proportion treated with antipsychotic medication, stressor measurement method, cortisol measure (tissue and type), and lapse-of-time between stress measurement and cortisol collection. Researchers were not blind to the names of authors, journals, or institutions. A third author (AC) then checked all study details for accuracy and extracted data necessary for effect size computation. The latter varied across studies and included any statistical value representing a within-group measure of the association between psychosocial stressors and cortisol . Where these data were not provided for each group separately, we contacted study authors for additional details –56 whichA modified version of the Newcastle-Ottawa scale [NOS ], a qualAll computations and statistical analyses were conducted using Stata version 16 . In ordeAs nearly all studies included in the review provided multiple effect sizes derived from the same study sample, thereby violating the independence assumption, it was necessary to account for dependence of effects. For the overall meta-analysis  we therefore used robust variance estimation (RVE) which accounts for correlated effects . We firsvia the Cochran Q and the I² statistics, where classification of the latter as likely unimportant (0%–40%), moderate (30%–60%), substantial (50%–90%), or considerable (75%–100%) is dependent on the magnitude and/or direction of effects and statistical significance (Cochran Q) of heterogeneity , followed by life event exposure (n=6). There was consistency across studies in the measures of perceived stress employed, with most studies using the Perceived Stress Scale . For chiAcross the 18 studies, cortisol was most frequently measured in saliva (n=12), two of these studies also examined cortisol in blood samples  that was not observed in healthy controls [r=-0.06 (95% CI: -0.25 to 1.33)], yet evening cortisol was significantly associated with childhood trauma in controls [r=0.22 (95% CI: 0.03 to 0.40)] but not patients [r=0.14 (95% CI: -0.13 to 0.39)]. In contrast, Labad and colleagues (r=-0.30 (95% CI: -0.54 to -0.01)] that was not present in either UHR individuals [r=-0.01 (95% CI: -0.34 to 0.33)] or FEP patients [r=0.14 (95% CI: -0.20 to 0.45)]. Plasma morning cortisol was not, however, associated with childhood trauma in either controls or individuals with schizophrenia in a further study , only three of which were statistically significant. The pattern of findings varied across studies and stressor types. In one large study of patients with psychotic disorder , morninglleagues , who asser study , 70; morer study .r=0.52 (95% CI: 0.13 to 0.77)] and previous distress [r=0.51 (95% CI: 0.11 to 0.77)] in relation to negative life events in children with a FHx of schizophrenia, but found no significant associations in children presenting antecedents of illness (including PEs) or controls (r=-0.43 (95% CI: -0.56 to -0.28)] whilst in the other study (r=0.39 (95% CI: 0.11 to 0.62)]. Interestingly, Ciufolini and colleagues also calculated the CARg and found a significant positive association in the control group [r=0.21 (95% CI: 0.04 to 0.37)] that was not present in the FEP group. In contrast, there were no significant associations in controls, UHR individuals, or FEP patients in any of three studies examining the relationship between perceived stress and the CARi  calculated the increase in cortisol following awakening (CARi) with only two pertaining to the total output of cortisol in the hour following awakening (CARg). Five effect sizes achieved statistical significance: A study of children at elevated risk of schizophrenia observed that the CARi was strongly associated with both current  but positively associated in healthy controls [r=0.42 (95% CI: 0.11 to 0.66)]. In contrast, two further studies that assessed diurnal cortisol using the same sampling procedure as this study found no significant relationships with life event exposure or life event distress in any group  were AUCg values , with the remaining (n=8) representing the diurnal slope . Significant associations were found in a single study , in whic were AUCny group . Moreoveny group , 65, 70.r=0.42 (95% CI: 0.08 to 0.67)] and lifetime trauma [r=0.48 (95% CI: 0.15 to 0.71)] among individuals with a FHx of illness, and similarly a positive association with lifetime trauma in individuals reporting PEs [r=0.31 (95% CI 0.01 to 0.56)]; none of these associations were significant in controls. However, this study observed no significant associations between hair cortisol and any other stressor  in any group. The only other study to report a significant effect (r=-0.66 (95% CI: -0.89 to 0.17)] that was not observed among patients with early schizophrenia, individuals at UHR, or healthy controls. In contrast, a further study of patients with established schizophrenia found no association between hair cortisol and childhood trauma ], a relationship that was not present among healthy controls [B=0.00 (95% CI: -0.01 to 0.02)]. A later study by the same group (B=0.28 (95% CI: 0.01 to 0.05)] that was not present among FHx individuals [B=-0.00 (95% CI: -0.02 to 0.02)] or controls [B=0.02 (95% CI: -0.04 to 0.01)]. Similarly, in the quadratic model a significant negative relationship (inverted U-shape) was detected in patients with psychotic disorder [B=-0.02 (95% CI: -0.03 to -0.00)] whereas positive (U-shaped), non-significant associations were found in the FHx [B=0.00 (95% CI: -0.01 to -0.02)] and control [B=0.12 (95% CI: -0.03 to 0.03)] groups.Two studies, yielding five effect sizes, assessed stressor-cortisol concordance using the ESM method. The first of these , reporteme group  tested br=0.05 (95% CI: -0.00 to 0.10), p=0.059]. A second model testing for group differences also showed no significant effect of either established psychosis status  or high-risk status  on effect sizes, indicating that the degree of concordance in these groups did not differ from healthy controls (see r = -0.01 (95% CI: -0.05 to 0.03), p=0.525]; moreover, as the funnel plot was not asymmetric (2 = 0.016) indicated that 95% of the “true effects” were estimated to lie between r values of -0.20 and 0.30.The overall RVE model, which included data from all stressor-cortisol pairings, was performed on 134 effect sizes (beta coefficients were excluded as they could not be converted to a common metric). This model indicated a weak, positive association between stressors and cortisol that did not achieve statistical significance , whereas a significant negative correlation was observed in the psychosis spectrum group [r=-0.28 (95% CI: -0.49 to -0.04)]. No other group differences or individual effects achieved statistical significance. Overall, heterogeneity estimates ranged from low (particularly in the control group) to moderate, except for the association between childhood trauma and basal (morning) cortisol in the psychosis spectrum group, where substantial and significant heterogeneity was observed .Sufficient data were available to examine six individual stressor-cortisol pairings : i) childhood trauma and basal morning cortisol; ii) perceived stress and basal morning cortisol; iii) life event exposure and the CARi; iv) perceived stress and the CARi; v) life event exposure and diurnal cortisol (AUCg); and vi) perceived stress and diurnal cortisol (AUCg). Results of these stratified analyses are presented in In the first meta-analysis to compare associations between naturally-occurring psychosocial stressors and cortisol in individuals on the psychosis spectrum and healthy controls, we observed poor concordance irrespective of stressor type, cortisol measure, or group status. The overall model, comprising 134 effect sizes, showed that stressors and cortisol measures were only weakly (and not significantly) correlated. Moreover, meta-regression analyses indicated that effect sizes among individuals with established psychosis and those at high-risk for psychosis did not differ from controls. In stratified analyses, performed to test for group differences within individual stressor-cortisol pairings, significant differences between healthy controls and psychosis spectrum groups were observed for only one of the six stressor-cortisol pairings examined. Thus, we found little evidence to suggest that cortisol responses to naturally-occurring stressors are any different in individuals on the psychosis spectrum compared to healthy controls.a priori alternative hypotheses presented  as opposed to cortisol fluctuations.Of the four resented  which reresented , 51, whiresented –39 and tresented , 75 demoThere are several reasons why we should be cautious about drawing these conclusions; these fall into the broad domains of statistical power, analytical approaches, heterogeneity (relating to study measures and populations), and timing of cortisol collection in relation to stressor onset/measurement, which will now be discussed in turn. First, low statistical power at both the study level and meta-analysis level may explain the poor concordance we observed between stressors and cortisol. Our systematic review indicated that only a small number of studies (2/18) included sufficient participants in each group to be able to detect a moderate correlation. Given that the majority of studies (87%) reported negligible-to-small correlations, this might explain why so few statistically significant correlations were observed at the study level. At the meta-analysis level, we were only able to include data from 16 separate datasets, far less than the minimum number (N=40) recommended . As suchThe analytic approaches adopted across studies may have also contributed to poor concordance. With regards to the analysis of cortisol data, a study of healthy females reported that while perceived stress scores showed no relationship with absolute cortisol levels (mean of multiple samples obtained throughout a single day), they were significantly associated with change in cortisol levels , implyinHeterogeneity across studies with regards to study measures may have impacted on our ability to detect a significant overall association between psychosocial stressors and cortisol. In this review, we examined a broad range of psychosocial stressors, including: exposure to specific, pre-defined events ; distress related to these specific events; subjectively-rated stressfulness of current activities (ESM activity stress); and appraisals of the degree to which life is stressful, unpredictable, and uncontrollable (perceived stress). While all of these measures are relevant to the concept of “stress”  there is likely substantial variability in the extent to which they are associated with a biological stress response. Moreover, perceived stress has been found to correlate with both personality traits and depressive symptoms , suggestmeasurement and cortisol collection might be a contributing factor. A recent study using data from a large sample of individuals at UHR for psychosis and healthy controls indicated that the degree of concordance between psychosocial stressors and basal cortisol was moderated by the lapse-of-time between collection of these measures  our meta-analyses were likely underpowered. This would have affected our ability to detect statistically significant correlations between stressors and cortisol , and to test for group differences in the degree of concordance. However, it is important to note that previous meta-analyses have observed group differences in cortisol responses to psychosocial stressor tasks with far fewer studies , 39. Thea priori power calculations to determine the minimum number of participants required for each group and ensure that recruitment is matched to the target number; ii) investigate within-subject deviation from normative cortisol levels, whether this be daily fluctuations  or variations across days , as these variations may be more strongly associated with psychosocial stressors; iii) move beyond simple cross-sectional analyses and instead attempt to obtain longitudinal measures of both stressors and cortisol in order to disentangle the temporal relationship between these measures; iv) report the lapse-of-time between stressor assessment and cortisol collection and test whether this variable moderates the strength of association ; and (v) investigate potential confounders and adjust analyses as appropriate. It is important to note that we found no association between study quality/bias scores (which considered some of these factors) and effect sizes. As such, it is possible that these recommendations will not necessarily increase the likelihood that a study is able to detect concordance between naturally-occurring psychosocial stressors and cortisol; however, this is an important first step to elucidating these relationships.As noted above, there are several methodological issues that might explain the poor concordance that we observed between psychosocial stressors and cortisol. As such, we recommend that future studies in this field i) conduct Our findings should be considered with reference to existing theories of psychosis aetiology. The neural diathesis-stress model of schizophrenia hypothesized that HPA axis dysregulation among those on the psychosis spectrum could be stress-induced, a manifestation of hippocampal dysfunction or glucocorticoid receptor abnormalities, or genetically determined –20. WhilThis comprehensive systematic review and meta-analysis found no evidence to suggest that individuals on the psychosis spectrum are characterized by either hyper- or hypo-responsivity of the HPA axis to naturally-occurring psychosocial stressors. These findings are in contrast to the blunted cortisol response observed during psychosocial stressor tasks among patients with established illness and individuals at high-risk for psychosis. While our findings suggest that psychosocial stressors cannot explain the cortisol abnormalities that have been previously reported in psychosis spectrum groups, this might also reflect methodological issues that are common to studies of naturally-occurring psychosocial stressors  but are tightly controlled in experimental studies employing psychosocial stressor tasks. Moreover, without adequate assessment of potential confounders and moderating factors, no conclusions can be drawn regarding the true relationship between psychosocial stressors encountered in the natural environment and cortisol levels. Thus, we strongly advocate that future studies attempting to investigate stressor-cortisol concordance consider these factors during the study planning phase and when conducting analyses. Nevertheless, the current evidence suggests that cortisol responses to naturally-occurring stressors are not a robust marker of either risk for psychosis or established illness.The dataset generated and analyzed in this study is available from AC on request.AC conceived the study, oversaw all systematic searches, conducted all statistical analyses, and wrote the first draft of the manuscript. SR and MV contributed equally to the study and were responsible for conducting the systematic search, reviewing studies for eligibility, extracting study characteristic data, and rating study quality/bias. VM and PM contributed intellectually to the critical interpretation of results. All authors reviewed and contributed to the final manuscript.AC is supported by a Sir Henry Welcome Postdoctoral Fellowship from the Wellcome Trust (107395/Z/15/Z), and a NARSAD Young Investigator Grant awarded by the Brain & Behavior Research Foundation (28336) and funded by the Evelyn Toll Family Foundation. This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London (IS-BRC-1215-20018 awarded to AC). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.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.The handling editor declared a past co-authorship with one of the authors, PM.


Background: Clinical and ultrasonic risk factors for lateral lymph node metastasis (LLNM) in papillary thyroid microcarcinoma (PTMC) are not well-defined. Herein, a systematic review and meta-analysis was conducted to investigate clinicopathologic and ultrasonic risk features for LLNM in PTMC.Methods: A systematic search of electronic databases  for studies published until April 2019 was performed. Case–control studies and randomized controlled trials that studied clinical and ultrasonic risk factors of LLNM in PTMC were included.Results: Fourteen studies  involving 43,750 patients met final inclusion criteria. From the pooled analyses, younger age<45 , male patients , extrathyroidal extension , tumor multifocality , tumor > 0.5 cm , central lymph node metastasis , >25% tumor contact with thyroid capsule , tumor calcification , upper tumor  were significantly associated with increased risk of LLNM in PTMC, while Hashimoto's thyroiditis and other ultrasonic features  were not significantly associated with LLNM in PTMC.Conclusions: Our analysis identified several clinicopathologic and ultrasonic factors associated with LLNM in PTMC. This finding highlights the need for a cautious and frequent postoperative surveillance of the lateral neck in high-risk PTMC patients. Moreover, high-risk ultrasonic features also need to be considered during selection of PTMC for active surveillance. The global incidence of papillary thyroid carcinoma (PTC) has increased substantially during past decade, with 4.4% annual percent increase in the United States from 1974 to 2013 . The revIt is well-accepted that lateral neck dissection (LND) is only recommended for PTMC patients when LLNM is diagnosed by preoperative evaluation such as physical examination, radiological imaging, and/or fine needle aspiration (FNA) . ProphylMoreover, active surveillance could be recommended as the first-line treatment for low-risk PTC patients . But aroAccordingly, several studies have published on the preoperative clinicopathologic risk factors of LLNM for PTMC , 12. HowAccording to the guidelines proposed by the preferred reporting items for systematic reviews and meta-analyses  original articles; (2) PTMC patients who received thyroidectomy as primary surgical procedure; (3) evaluation of clinicopathologic and/or ultrasonic risk factors for LLNM; and (4) study of the association between LLNM and relevant risk factors. Initially, titles, and abstracts were checked to include studies which fulfilled the inclusion criteria. After excluding studies which did not fulfill inclusion criteria, letters to the editor, abstracts, and meeting posters were also excluded. The same reviewers independently assessed eligibility after obtaining full text of candidate studies. In case of disagreement, a third investigator (ZH) was consulted. Discrepancies were resolved by discussion and consensus.Two investigators (SX and PSW) independently summarized the studies meeting the inclusion criteria and performed data extraction. Disagreement was resolved by discussion and a third investigator (ZH) was consulted. We extracted the following data for each study: first author's last name, publication year, country, study design, sample size, patient characteristics (age and gender), surgical intervention (surgery type and therapeutic LND scope), and percentage of patients with LLNM. Following review by an expert panel (ZH and GC), we selected 14 factors that had been analyzed in at least three studies. These factors included clinicopathological factors like age, sex, extrathyroidal extension, multifocality, tumor size, Hashimoto's thyroiditis (HT), central lymph node metastases (CLNM), and ultrasonic characteristics of tumor like >25% contact with thyroid capsule, calcification, composition, echo, margin, shape, location.The Risk of Bias Assessment Tool for Non-randomized Studies (RoBANS) was used in our study to evaluate the quality of non-randomized experimental studies. The six domains included in the RoBANS tool are the selection of participants, confounding variables, measurement of intervention, blinding for outcome assessment, incomplete outcome data, and selective outcome reporting were considered for assessment. Two reviewers (ZH and QYL) independently reviewed each term for every study, and disagreement was resolved by re-evaluation and a third investigator (GC) was consulted. The measurement of each item is categorized as low risk, high risk, or unclear risk. Review Manager 5.3  was used to report the result of this evaluation.P < 0.10. The I2 statistic was used to quantify heterogeneity as followings: (1) exclude heterogeneity if I2 was from 0 to 40%; (2) moderate heterogeneity if I2 was from 30 to 60%. (3) Substantial heterogeneity if I2 was from 50 to 90%; (4) considerable heterogeneity if I2 was from 75 to 100%. If heterogeneity was present among the included studies, sensitivity analysis were performed to explore the origins of the heterogeneity.Revman software  and Stata software  were used for this meta and statistical analysis. We also calculated the odds ratios (ORs) and 95% confidence intervals (CIs) for estimating the association between binary factors and LLNM. Meta-analysis was performed using the random-effects model or the fixed-effect model according to the absence or presence of significant heterogeneity. The heterogeneity among studies was evaluated by Cochran's chi-squared statistics and with significance set at P < 0.1 has been used as evidence of asymmetry for funnel plot because of limited number of studies in this study.The risk of publication bias was analyzed using Egger's test and was presented as a funnel plot. The statistical power of Egger's test was mainly dependent on the number of studies included in a meta-analysis. The We identified a total of 561 studies during initial literature search. After evaluation of the titles and abstracts, 112 duplicate studies and another 433 studies were excluded. After scrutiny of the full text of the remaining 16 articles, a further 2 studies were excluded for various reasons as shown in P = 0.05; I2 = 52%). On pooled analysis, the risk of LLNM was significantly higher in patients with younger age<45 .The effect of age on the risk of LLNM was investigated in 7 studies . A randoP = 0.009; I2 = 56%). On pooled analysis, the risk of LLNM was significantly higher in male patients .The effect of sex on the risk of LLNM was investigated in 12 studies . A randoP < 0.00; I2 = 90%). On pooled analysis, the risk of LLNM was significantly higher in patients with ETE .The effect of ETE on the risk of LLNM was investigated in 9 studies . A randoP = 0.009; I2 = 63%). On pooled analysis, the risk of LLNM was significantly higher in patients with multifocal tumor .The effect of multifocality on the risk of LLNM was investigated in 9 studies . A randoP = 0.37; I2 = 23%). On pooled analysis, the risk of LLNM was significantly higher in patients with tumor larger than 0.5 cm. .Assessment of tumor size as a risk factor for LLNM was conducted in 9 studies . A fixedP = 0.87; I2 = 0%). On pooled analysis, the risk of LLNM was significantly higher in patients with CLNM .Assessment of CLNM as a risk factor for LLNM was conducted in 7 studies . A fixedP = 0.07; I2 = 50%). On pooled analysis, the risk of LLNM was not significantly lower in HT patients .The effect of HT on the risk of LLNM was investigated in 6 studies . A randoP = 0.02; I2 = 75%). On pooled analysis, the risk of LLNM was significantly higher in patients with tumor contact >25% thyroid membrane .The prediction of >25% contact of tumor with thyroid membrane on the risk of LLNM was investigated in 3 studies . A randoP = 0.01; I2 = 65%). On pooled analysis, the risk of LLNM was significantly higher in patients with tumor calcification .The prediction of calcification on the risk of LLNM was investigated in 6 studies . A randoP = 0.63; I2 = 0%). On pooled analysis, the risk of LLNM was not significantly higher in patients with solid tumor .Assessment of tumor composition as a risk factor for LLNM was conducted in 3 studies . A fixedP = 0.85; I2 = 0%). On pooled analysis, the risk of LLNM was not significantly higher in patients with hypoechoic tumor .Assessment of tumor echo as a risk factor for LLNM was conducted in 4 studies . A fixedP = 0.10; I2 = 52%). On pooled analysis, the risk of LLNM was not significantly higher in patients with smooth margin .The prediction of tumor margin on the risk of LLNM was investigated in a total of 4 studies . A randoP = 0.48; I2 = 0%). On pooled analysis, the risk of LLNM was not significantly higher in patients with taller than wide tumor .Assessment of tumor shape as a risk factor for LLNM was conducted in a total of 4 studies . A fixedP = 0.09; I2 = 44%). On pooled analysis, the risk of LLNM was significantly higher in patients with upper tumor .The prediction of tumor location on the risk of LLNM was investigated in a total of 8 studies . A randoAs shown in Overall, leave-one-out meta-analysis revealed that age, sex, multifocal, HT, contact>75%, calcification and margin did not retain significance when single studies were excluded. For ETE and tumor location, no single studies were identified for the huge heterogeneity. The detailed results, including the forest plots, of the sensitivity analyses have been reported in Publication bias was evaluated by Egger test and no bias existed in this meta-analysis, as shown in To the best of our knowledge, this is the first meta-analysis to assess clinical and ultrasonic risk factors for LLNM in PTMC. It was found that younger age, male gender, ETE, multifocal tumors, larger tumor size, and positive CLNM were clinical risk factors for LLNM in PTMC. Additionally, >25% tumor contact with thyroid capsule, calcification, and upper location were ultrasonic risk features for LLNM. In contrast, HT and other US features  were not considered as risk factors of LLNM in these patients.I2 >50% was found in the analysis of age, sex, ETE, multifocality, HT, >25% contact with thyroid capsule, calcification as well as margin, and moderate heterogeneity with an I2 >30% was found when analyzing tumor location. Interestingly, after the removal of one study from the analysis, similar results were confirmed, but the heterogeneity was decreased remarkably in the analysis of age, sex, multifocal, HT, contact>25%, calcification, and margin. Possible reasons for high heterogeneity were presented as I2 values for the analysis of ETE and tumor location were not changed significantly in the sensitivity analysis.High heterogeneity with an Younger age was identified to be associated with aggressiveness of PTC, such as vascular invasion and lymph node metastases . HoweverSimilarly, cervical lymph node metastases and ETE were more frequent in PTC patients with multifocality , 33. A mFurthermore, another novelty of this study is the first meta-analysis for ultrasonic features of LLNM in PTMC. A >25% tumor contact with thyroid capsule is related with the degree of ETE, which is also associated with LLNM of PTMC. Moreover, microcalcification(s) at US can also predict a diagnosis of malignancy, clinically cervical lymph node metastases, and prognosis, as reported previously , 42. In By meta-analyzing populations from different studies, the present study was able to evaluate the risk factors of LLNM for PTMC in a larger study sample and to adjust the results for the presence of some confounding factors. Except for ETE and tumor location, high heterogeneity of other risk factors was compensated by sensitivity analysis. The results of ETE and tumor location should be interpreted with caution because of moderate heterogeneity, and further study is needed to confirm the corresponding results.This meta-analysis has some potential limitations. First, patients in the 14 studies were predominantly Asian. Whether ethnicity plays a role in LLNM remains unknown. Accordingly, risk factors of LLNM in PTMC from other races need further evaluation. Second, the limited number of studies hindered the implementation of subgroup and meta regression analysis. Third, the retrospective and non-randomized nature of all studies included in the analysis might be considered a source of bias. This provided associative, not causal, evidence, and mandates caution when interpreting these results. In future trials, randomized controlled trials of a higher methodological quality are needed to improve the quality of evidence.Taken together, several risk factors for LLNM in PTMC patients which are readily available in clinical settings were identified in our systematic review and meta-analysis. The identification of high-risk patients is of utmost importance to plan a more cautious and frequent evaluation of lateral neck in the post-operative course. Moreover, high-risk ultrasonic features also need to be considered during selection of PTMC for active surveillance.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.


Background: Fractures are common in physically active populations and genetic differences may mediate injury risk.Objective: To meta-analyse the pooled results of candidate gene association studies with non-osteoporotic fracture risk in physically active humans.Methods: Systematic searching of databases returned 11 eligible studies published in English. Pooled odds ratios (ORs) with 95% confidence intervals (CI) were produced using allele contrast, recessive and homozygote contrast meta-analysis models to evaluate associations of risk alleles in the COL1A1 (rs1800012), COL2A1 (rs412777), CTR (rs1801197), ESR1 (rs2234693 and rs9340799) LRP5 (rs3736228), VDR  genes with fracture incidence.Results: Eligible study quality was generally low (7/11) and no significant overall effect was found for any genetic variant with any comparison model (p > 0.05). A trivial reduction in fracture risk was found for female participants with the COL1A1 Sp1 (rs1800012) T allele .Conclusions: No overall effect was found from the pooled results of included genetic variants on fracture risk in physically active participants. The COL1A1 Sp1 rs1800012 T allele may reduce fracture risk in physically active females but further high-quality research with sex-specific analysis is required.Trial Registration: . Fractures are major musculoskeletal injuries, accounting for 22% of all sport and recreation related injuries in the United States , vitamin D receptor (VDR), and LDL receptor related protein 5 (LRP5) genes have been associated with a three- to eight-fold increase of fracture risk among physically active participants in some studies  and was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines  or lifestyle, as defined by the ACSM's Guidelines for Exercise Testing and Prescription  with discrepancies concluded by consensus agreement. The following data were extracted from eligible articles: (1) study details ; (2) population characteristics ; (3) genetic variant(s). Quality assessment and risk of bias assessments were carried out using the Q-Genie  and reviewed by another (MW). Data were extracted, where possible, in the form of genotype frequency distributions between fractures (cases) and non-fractures (controls) for males, females, and combined if not reported separately. If only percentage distributions were reported, participant number for each group was calculated using overall participant number. If neither of the above was possible, authors were contacted directly for data.A meta-analysis was performed to calculate overall fracture risk, with sub-analysis of males, and females separately, as odds ratios (OR) for each SNP, with extracted data available from two or more studies using the following genetic association meta-analysis models of comparison: allele contrast, recessive, and homozygote contrast, as recommended by Lee . The freI2 <20%) or random (I2 ≥ 20%) effects models, depending on heterogeneity between studies, quantified with the I2 statistic with sub-analysis of sex. To provide a qualitative indication of the magnitude of effect observed, the OR produced by meta-analysis were converted to the standard mean difference and described in line with those suggested for Cohen's d .Only one paper achieved the highest classification of study quality , COL2A1 (rs412777), CTR (rs1801197), ESR1 (rs2234693 and rs9340799), LRP5 (rs3736228), and VDR  were replicated at least once in seven of the 10 eligible studies, which constituted the quantitative meta-analysis. The summary statistics for each genetic comparison model meta-analysis are presented in p > 0.06). COL1A1 rs1800012 SNP using the allele contrast model , however this was not statistically significant in the recessive model .Ten genetic variants from six different genes; COL1A2 rs412777, ESR1 rs9340799, and VDR rs10735810 meta-analyses, with significant sub-group heterogeneity found in the COL1A1 rs1800012, COL1A2 rs412777, and ESR1 rs2234693 SNPs. Exclusion of poor-quality studies reduced the analysis to two genetic variants in two different genes (COL1A1 rs1800012 and VDR rs1544410) from three studies, but this did not change the overall effect in these analyses.Significant overall heterogeneity was observed between studies in the COL1A1 rs1800012 SNP using the allele contrast model . However, no statistically significant overall effect was observed from the pooled results of any SNP (p > 0.05).The aim of this meta-analysis was to evaluate the findings of candidate gene association studies on non-osteoporotic fracture risk in physically active humans. Only ten SNPs from six different genes were independently replicated, despite the 10 studies eligible for meta-analysis including 39 SNPs from 14 different genes. A sub-analysis indicated a sex-linked significant trivial reduction of fracture risk for physically active females with the T allele of the COL1A2 PvuII (rs412777) analysis presented conflicting results, with one reporting that the “PP” genotype halved fracture risk  SNP with fracture risk. The results of the studies may differ if two different proximal PvuII sites in the COL1A2 gene have been assessed, only Blades et al.  SNP analysis  analysis, as heterogeneity was significantly high  and the participants' ethnicity unknown. Nevertheless, all three studies reported accordance with Hardy-Weinberg equilibrium and a significant trivial increase of fracture risk is associated with the C allele using a fixed effects model  and ethnic variation across studies may have masked a valid genetic association.Five studies investigated the genetic association of stress fracture risk in Caucasian, or predominantly Caucasian, male adult military or athletic individuals. However, five additional studies did not report participant ethnicity; three of which provided the data for the LRP5 and ESR1 genes, and the LRP5 rs3736228 SNP, have been associated with fracture risk  and VDR FokI (rs10735810) SNPs, may still warrant further investigation. Indeed, genetic variants in LRP5 and ESR1 have been associated with osteoporotic fracture risk and bone mineral density in GWAS  and VDR BsmI (rs1544410) SNPs replicated in females in more than one study. Stress fracture risk has been suggested to be three times greater in physically active female military personnel and 50% higher in female athletes than their male colleagues, due to biomechanical and physiological differences , COL1A2 PvuII (rs412777), and ESR1 PvuII (rs2234693) SNPs, highlighting the potential for sex-specific associations. Epidemiological data suggest that fracture incidence is greater in males between the age 18 and 49 than females in the general population  SNP, located in the 1st intron of the COL1A1 gene, is one of the most extensively investigated genetic variants in the injury risk literature. Sub-group analysis within the current meta-analysis indicated a trivial reduction in fracture risk for the T allele of the COL1A1 rs1800012 SNP in physically active females, but not males. However, the T allele was not associated with fracture risk when males and females were combined , 10 of which were TT homozygotes. This is lower than expected (~5%) considering the overall size of the sample as the minor T allele is present in ~16–19% of Europeans and 9–13% of individuals globally. It may be that no association was observed in the recessive and homozygote contrast models or the individual studies  T allele in females despite previous associations with increased risk of osteoporotic fracture in the elderly. This suggests that the genetic penetrance of the T allele is influenced by sex/age and is not ubiquitously detrimental to bone strength as has been previously suggested. The null effects observed in the overall analyses of SNPs included in this meta-analysis should not be considered finite due to potential limitations of the included studies. Pediatric participants, only present in the COL1A1 (rs1800012) and COL1A2 PvuII (rs412777) combined sex analyses, are more likely to include individuals with undiagnosed asymptomatic diseases which could influence the genetic association results. Nevertheless, the overall findings COL1A1 (rs1800012) combined sex analyses do not change if pediatric participants are removed. However, the COL1A2 PvuII (rs412777) analyses is comprised exclusively of pediatric participants and should, therefore, be considered specific to this population and with the limitations discussed. Readers should also consider the potential influence that nutritional differences which could interact with the exposure of physical activity and genetic predisposition to mediate susceptibility to fracture occurrence in the included studies. Overall review of study designs indicated several recommendations for consideration in future research such as the inclusion of a-priori power calculations, sex-specific analysis, and greater clarity in the reporting of participant ethnicity. Consequently, further high-quality investigation of the COL1A1 (rs1800012), COL1A2 PvuII (rs412777), and VDR FokI (rs10735810) SNPs with fracture risk in a homogenous sample of physically active participants is warranted.The aim of the current meta-analysis was to synthesize the findings and quality of genetic case-control association studies on fracture risk in physically active participants. Sex-specific analysis indicated a protective effect of the The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.ER-M performed the initial literature search and eligibility screening which was replicated by MW. ER-M and YM independently completed the quality and risk of bias assessments for eligible studies. Data extraction and analysis were performed by ER-M, YM, and MW. The first draft of the manuscript was written by ER-M. Discrepancies were resolved by consensus agreement amongst all authors. All authors commented on previous versions of the manuscript, approved the final manuscript, and contributed to the study conception and design.Sponsorship to complete the research was provided by St Mary's University, Twickenham and Fulham Football Club, London as part of ER-M's. The authors acknowledge the potential conflict of interest resulting from YM's role as Head of Nutrigenetics for Nell, a well-being company that incorporates genetics analyses in its approach. Nevertheless, the research was conducted in a fair, honest, impartial, and transparent manner. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Research focusing on the relationship between five types of tumor necrosis factor-alpha (TNF-α) SNPs and the risk of hepatocellular carcinoma (HCC) were still controversial. Hereby, we performed a meta-analysis to determine the association between TNF-α promoter SNPs: -1031 T/C, − 863 C/A, − 857 C/T, − 308 G/A, and − 238 G/A with HCC risk.We interrogated articles from journal database: PubMed, Pro-Quest, EBSCO, Science Direct, and Springer to determine the relationship between five types of SNPs in TNF-α gene with HCC risk. RevMan 5.3 software was used for analysis in fixed/random effect models.This meta-analysis included 23 potential articles from 2004 to 2018 with 3237 HCC cases and 4843 controls. We found that SNP − 863 C/A were associated with a significantly increased HCC risk . Similar results were obtained in − 857 C/T , − 308 G/A , and − 238 G/A . While no associations were observed between SNP TNF-α − 1031 T/C and HCC risk.The present meta-analysis showed that TNFα SNPs -863C/A, − 857 C/T, − 308 G/A, and − 238 G/A were associated with the risk of HCC.The online version contains supplementary material available at 10.1186/s12885-020-07606-6. Hepatocellular carcinoma (HCC) or liver cancer accounts for the cancer with the fourth highest mortality rate in the world. In 2018, there are estimated to be 841,080 of HCC new cases worldwide . It is kTumor Necrosis Factor-α (TNF-α) is an important inflammatory cytokine in the development of liver disease. This cytokine can cause hepatic injury, cirrhosis and eventually promote hepatocellular carcinoma , 6. SeveHigh production of TNF-is related to the increase of pro-inflammatory cytokine secretion, the activation of proto oncogenes and several genes associated with cell growth, invasion, and cancer cells metastasis , 13. ExcThe results of various previous studies regarding the relationship between TNF-α polymorphism and HCC across various ethnicities and populations show mixed results, related –18 or thOur meta-analysis was reported based on the items outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to ensure adequate reporting of this meta-analysis of observational studies in epidemiology . We condAll included studies should meet the following criteria: (1) investigate the association between any of the five SNPs  in TNF-α gene and risk of HCC; (2) have cohort or case-control study design; (3) risk of HCC was reported as RR (relative risk) and/or OR (odds ratio) with 95% Confidence Interval (CI) or provide sufficient data to extract RR and/or OR with 95% CI data; (4) include human subjects; (6) in English language. We excluded studies with the following criteria: (1) studies with design other than case-control or cohort; (2) duplicated studies; (3) studies with unmeasurable population and not qualified data; (4) using non-English language; (5) Studies in which the full text or main data could not be obtained.Two investigators independently performed the electronic search and retrieved the articles that matched with our searched terms. Any disagreement was settled by discussion and consensus with all the authors. Final decision was merely based on the agreements of all authors.A standardized reporting form was used to extract the data from each article which included the first author’s name, year of publication, population country, TNF-α SNP type, study design, etiology of HCC, SNP genotyping method, controls, and frequencies of SNP. Hardy–Weinberg equilibrium test was performed and its significance of the control groups was calculated when the original information was not provided.Newcastle - Ottawa quality assessment scale (NOQS) was used for measuring the quality of the included studies. This scale was designed through collaboration between the Universities of Newcastle, Australia and Ottawa, Canada. The purpose of this scale was to assess the quality of observational studies for producing good meta-analysis. The studies were qualified as high quality (9 stars), medium quality (7–8 stars), and low quality (less than 7 stars) .2 statistic. The pool estimated ORs was calculated with either fixed or random effects model assumptions. If Q test showed significant result (p < 0.05), we used a random effects model. Otherwise, if Q test showed insignificant result (p > 0.05), we used a fixed effect model. We also calculated the 95% confidence interval (CI) of pool estimated OR. Inverted funnel plots were conducted to find any presence of publication bias.Analysis were conducted using Review Manager 5.3 software . Hardy-Weinberg Equilibrium was examined by Chi Square test when the original information was not provided. We evaluate 5 genetic models  for each SNP type separately. Major alleles for each SNP were: -1031TT, −863CC, −857CC, −308GG, and -238GG, while minor alleles for each SNP were: -1031CC, −863AA, −857TT, −308AA, and -238AA. Heterogeneity assumption was assessed with Cochrane Q statistic and IAccording to the PRISMA flow diagram Fig. , we initEventually, as much as 23 potential articles were included which recruited 9792 participants and consisted of 3237 HCC cases and 4843 controls Table . The pap2) was less than 60% and p-value for the heterogeneity was more than 0.05, fixed-effects models were applied. However, we did not obtain any significant association between SNP TNF-α − 1031 and HCC risk in all model analyses. For the estimation of publication bias, we found no visual asymmetry in Funnel Plot analysis.Only five studies regarding the association between SNP TNF-α − 1031 and HCC risk with 825 cases and 1518 controls were available. The number of cases for CC and TC genotypes was reported together in the studies by Niro et al.  and Jin 2) more than 60% and p-value for the heterogeneity was less than 0.05, we applied random-effects models. We found significant association between the allele model of A versus C of TNF-α C/A SNP with the risk of HCC . The dominant-model analysis (CA/AA vs CC) also showed significant association between SNP TNF-α 863 C/A and HCC risk  was less than 60% and p-value for the heterogeneity was more than 0.05, fixed-effects models were applied. A significant association between SNP TNF-α − 857 C/T and HCC risk was found in dominant-model analyses  more than 60% and p-value for the heterogeneity was less than 0.05, random-effects models were applied. All five genetic models showed significant association with risk of HCC with OR for allele model = 1.98, 95% CI = 1.62–2.42, p < 0.001; OR for dominant model = 1.95, 95% CI = 1.53–2.49, p < 0.001; OR for recessive model = 2.52, 95% CI = 1.69–3.76, p < 0.001; OR for codominant major vs minor homozygote model = 3.14, 95% CI = 2.06–4.79, p < 0.001; and OR for codominant heterozygote vs major homozygote model = 2.07, 95% CI = 1.60–2.68, p < 0.001; Fig. Interestingly, we found most included studies analyzing the association between SNP TNF-α − 308 G/A and HCC risk. The number of cases for AA and GA genotypes was reported together in the studies by Niro et al.  and Jin 2) more than 60% and p-value for the heterogeneity was less than 0.05, we applied random-effects models. The allele model of A versus G of SNP TNF-α − 238 G/A was significantly associated with risk of HCC . The codominant-model analysis (AA vs GG) also showed significant association between SNP TNF-α 238 G/A and HCC risk . The recessive model analysis (AA vs GA + GG) proved significant association between SNP TNF-α 238 G/A and HCC risk as well , metabolism, and genetics , 45. TheAs research on SNP TNF-α − 1031 T/C and HCC risk is still limited, we only found five studies investigating this SNP, even though many studies have shown significant association between this SNP with other diseases such as polycystic ovary syndrome and endometriosis , 50. In This study shows a significant relationship between SNP TNF-α − 863 C/A with HCC risk in allele models and dominant model analysis. A meta-analysis conducted by Wei et al. also showed a significant relationship betweehis SNP and HCC in dominant and codominant (CA vs CC) model analysis . PolymorIn the present study, we also found a significant relationship between SNP TNF-α − 857 C/T with dominant model analysis. Limited studies were present regarding the relationship between this polymorphism with HCC risk, thus there were only 7 studies that came within our inclusion criteria. This is different from the meta-analysis conducted by Wei et al. which showed no significant relationship between this SNP and HCC risk, however in that meta-analysis there were only 3 included studies .There have been many previous studies investigating SNP TNF-α − 308 G/A with HCC risk, thus we got 19 included studies. All five genetic analysis models showed a significant relationship between the SNP and HCC risk. This is in line with several previous meta-analysis studies, including those conducted by Hu et al. and Tavakolpour and Sali on allele models and dominant model analyses , 57. WeiStudies on SNP TNF-α − 238 G/A have also been extensively performed. Nevertheless, meta-analyses of these SNPs are still limited and yield conflicting results. The present study showed a significant relationship between this SNP and HCC risk. This is in line with a meta-analysis conducted by Xiao et al. showing that this SNP is associated with HCC risk, although in that study only HBV-related HCC was studied . AnotherThose SNPs on TNF-α promoter can influence TNF-α level. They resulted in higher and constitutive TNF-α expression and were associated with an increased risk of HCC , 17. TNFThis meta-analysis still had several limitations. To date, there has rarely been any meta-analysis discussing the relationship between all each SNPs of TNF-α − 1031 T/C, − 863 C/A, − 857 C/T, and − 238 G/A with HCC. The second limitation of this study was that we only included studies in English language so that it does not rule out the exclusion of any good research in non-English languages. Third, the role of other factors, such as variations in genes adjacent to the TNF-α gene or epigenetic factors are said to also be able to regulate TNF-α expression , 62. FouIn conclusion, this meta-analysis determined the association between SNP TNF-α − 1031 T/C, − 863 C/A, − 857 C/T, − 308 G/A, and − 238 G/A and HCC risk. Our novel data demonstrated that all these SNPs but − 1031 T/C might increase HCC risk. Therefore, genetic predisposition, especially polymorphism of TNF-α gene may play important role in the pathogenesis of HCC. Further studies in larger population and analysing gene-environment interaction are required to provide better understanding between TNF-α polymorphisms and the risk of HCC.Additional file 1.