FCGR2A (Fc fragment of IgG receptor IIa) rs1801274 and MUC5B  rs35705950 variations on susceptibility to pneumonia diseases.Herein, we collected currently published data to comprehensively evaluate the impact of the We retrieved case-control studies from three online databases and applied the statistical approach of meta-analysis for a series of pooling analyses.FCGR2A rs1801274; while thirty-one case-control studies were included for MUC5B rs35705950. No significant difference between pneumonia cases and controls for FCGR2A rs1801274 was found. However, MUC5B rs35705950 was significantly associated with pneumonia susceptibility in the whole population under the genetic models of allelic T vs. G [OR (odds ratio) =3.78], carrier T vs. G (OR = 3.31), TT vs. GG (OR = 13.66), GT vs. GG (OR = 4.78), GT + TT vs. GG (OR = 5.05), and TT vs. GG + GT (OR = 6.47) . Furthermore, we observed a similar positive result for subgroup analyses of “Caucasian”, “Asian”, “population-based control”, and “idiopathic pulmonary fibrosis”.A total of fourteen case-control studies were included for MUC5B rs35705950, but not FCGR2A rs1801274, increases susceptibility to clinical pneumonia, especially to idiopathic pulmonary fibrosis, in both the Caucasian and Asian populations. FCGR2A rs1801274 and MUC5B rs35705950.Pneumonia is a group of viral or bacterial infection-induced lung disorders that can cause the symptoms of fever, cough, shortness of breath and fatigue –3. ThereFCGR2A gene in the 1q23 chromosome region encodes a member of the heterogeneous Fc fragment of the IgG receptor family of immune receptors and contains a functional rs1801274 variation in exon 4, which leads to the amino acid alteration from histidine (H) to arginine (R) at position 131 of the FCGR2A protein ; while the Mantel-Haenszel method for fixed-effect models was used for low or no heterogeneity (I2 < 50% and Pheterogeneity > 0.05). We also utilized the STATA software to conduct association tests and obtained the OR, 95% confidence interval (CI) and Passociation  under a total of six models to assess the association strength.To assess the statistical heterogeneity between studies, we performed IP value in the association tests using the p.adjust function of the R software, version 3.6.1. P values adjusted for the Bonferroni and false discovery rate (FDR) were also obtained. Furthermore, we performed a false-positive report probability (FPRP) analysis to assess the probability of a true genetic relationship using the genetic analysis “gap” R package  on the susceptibility to the different types of pneumonia in different populations when the data become available.When more case-control studies become available, it would be meaningful to take additional factors into consideration, such as gender, age, exposure, and drinking/smoking status. As mentioned above, MUC5B rs35705950 is strongly linked to an increased risk of pneumonia diseases in the Asian and Caucasian populations. Owing to data limitations, more available evidence is required to further clarify the genetic relationship between FCGR2A rs1801274 and pneumonia susceptibility.Our findings revealed that Additional file 1 Table S1. Detailed terms of database search (as of 25 February 2020). Table S2. Allelic and genotypic frequency data of the included case-control studies. Table S3. Quality assessment of included case-control studies. Table S4. FPRP values for the association between MUC5B rs35705950 and pneumonia risk in the Asian population. (DOCX 52.4 KB)Additional file 2 Figure S1. Subgroup analysis data of “control source” for MUC5B rs35705950 under the allelic model. Figure S2. Subgroup analysis data of “pneumonia type” for MUC5B rs35705950 under the carrier model. Figure S3. Subgroup analysis data of “pneumonia type” for MUC5B rs35705950 under the TT vs. GG model. Figure S4. Subgroup analysis data of “pneumonia type” for MUC5B rs35705950 under the GT vs. GG model. Figure S5. Subgroup analysis data of “pneumonia type” for MUC5B rs35705950 under the GT + TT vs. GG model. Figure S6. Subgroup analysis data of “pneumonia type” for MUC5B rs35705950 under the TT vs. GG + GT model. Figure S7. Sensitivity analysis (a) and Begg test data (b) for FCGR2A rs1801274 under the allelic T vs. G model. Figure S8. TSA data for FCGR2A rs1801274 under the AG + GG vs. AA model. Figure S9. TSA data for MUC5B rs35705950 under the GT + TT vs. GG model in the overall populations; Figure S10. TSA data for MUC5B rs35705950 under the GT + TT vs. GG model in the Caucasian population; Figure S11. TSA data for MUC5B rs35705950 under the GT + TT vs. GG model in the Asian population. (PDF 1.9 MB)


To assess the risk of three autoimmune diseases ‐ autoimmune thyroiditis (AIT), Guillain‐Barré syndrome (GBS), and inflammatory bowel disease (IBD) ‐ in females following AS04‐HPV‐16/18 vaccination.This meta‐analysis included data from 18 randomized controlled trials, one cluster‐randomized trial, two large observational retrospective cohort studies, and one case‐control study. Following vaccination, a risk window of 2 years was defined for AIT and IBD and 42 days for GBS. Odds ratios (ORs) were estimated using three methods: meta‐analysis inverse‐variance with continuity correction , pooled estimate, and beta‐binomial regression.In all studies apart from the case‐control study, 154 398 exposed and 1 504 322 non‐exposed subjects were included, among whom there were 141 and 1972 cases of (autoimmune) thyroiditis; 2 and 2 cases of GBS; and 43 and 401 cases of IBD, respectively. In the case‐control study, there were 97 cases of AIT and 13 of GBS; matched with 802 and 130 controls, respectively. The primary analysis OR estimates were 1.46 , 11.14 (2.00‐61.92), and 1.11 (0.75‐1.66) for (autoimmune) thyroiditis, GBS, and IBD, respectively.This meta‐analysis did not show an increased risk of IBD following vaccination with AS04‐HPV‐16/18. The 1.5‐fold increased risk of (autoimmune) thyroiditis does not allow us to conclude about a causal association. For GBS, the very low number of cases and wide 95% CIs negate any firm conclusion. There have been hypothesized concerns that vaccine adjuvants could lead to autoimmune conditions.This meta‐analysis examined cases of (autoimmune) thyroiditis, Guillain‐Barré syndrome, and inflammatory bowel disease following AS04‐HPV‐16/18 vaccination using all available data from clinical and post‐marketing observational studies.This analysis did not show a risk of inflammatory bowel disease.There was a 1.5‐fold increased risk of (autoimmune) thyroiditis, but no conclusion about a causal association could be drawn.The very low number of cases of Guillain‐Barré syndrome negated any firm conclusion.1Cervarix; GSK)Gardasil; Merck Sharp & Dohme Limited),Gardasil 9; Merck Sharp & Dohme Limited).O‐desacyl‐4′‐monophosphoryl lipid A (50 μg MPL) adsorbed on aluminium hydroxide (500 μg Al3+)Three human papillomavirus (HPV) vaccines are currently available: AS04‐adjuvanted HPV‐16/18 (AS04‐HPV‐16/18) vaccine  and post‐marketing observational studies that were identified in GSK internal repository of studies sponsored and supported by the Company, and information from Regulatory Authorities. In a complementary, systematic literature review searching for all studies published till end 2015. Details of the search strategy, the database consulted and number of references found and selected are described in Eighteen individually RCTs 9, 10A cluster‐randomized trial, in which communities of subjects received different vaccination schedules.Two large observational, retrospective cohort studies: a United Kingdom (UK) database cohort studyA French case‐control study,The following studies were included:2.2Subject‐level data were extracted from all studies except the French cohort studyThe following data were extracted for each study: numbers of subjects exposed and non‐exposed to AS04‐HPV‐16/18; mean ages; countries of enrollment; length of follow‐up; and numbers of cases of (autoimmune) thyroiditis, GBS, and IBD during the risk period (defined below).2.3Clinical definitions of AIT, GBS, and IBD events varied across studies, as detailed in In the French cohort study,2.4The post‐vaccination risk periods were determined based on the onset of the disease (acute or insidious) and possible or known pathologic mechanisms.As the clinical courses of AIT and IBD are generally insidious, 2 years between vaccination and disease onset was selected. For trials with longer follow‐up periods, only cases that occurred during the 2 years following first vaccination were included. For the French cohort study,For GBS, a shorter risk period (42 days following each vaccination) was considered for the main analysis, based on its anticipated acute onset. This period is also recommended by the Brighton Collaboration GBS Working Group,2.5To harmonize results across studies, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated from the numbers of cases and total numbers of subjects for the combined clinical studies ; the cluMeta‐analysis of rare events is challenging due to the inclusion of studies with no event in one or both arms .In the inverse‐variance method , a continuity correction ,3.2There were an estimated 140.6 cases of (autoimmune) thyroiditis among 152 225 exposed subjects (92/100 000) and 1971.5 cases among 1 453 729 non‐exposed subjects (136/100 000). The OR using the inverse‐variance method with continuity correction (primary method) was 1.46 (95% CI 1.22‐1.76), the beta‐binomial regression method without the case‐control studyResults using the original analysis of the French cohort study3.3The only GBS cases were from the French cohort study,The primary method OR was 11.14  and 401.4 cases among 1 504 322 non‐exposed subjects (27/100 000). The primary method OR was 1.11 (95% CI 0.75‐1.66); the other methods gave similar estimates  that had been identified as safety signals in observational studies of AS04‐HPV‐16/18 or HPV‐6/11/16/18 vaccines.The AIT primary analysis showed a slightly increased risk (OR = 1.46) of (autoimmune) thyroiditis following AS04‐HPV‐16/18 vaccination. This is likely a slight overestimation of risk given that this was heavily influenced by the large French cohort study,The other analysis methods showed ambiguous results for AIT due to differences in their weighting of data from different studies. The beta‐binomial model estimate was similar to that from the primary analysis, but the pooled analysis estimate provided an OR of 0.68. This simple pooled estimate is biased because there was a much higher incidence of (autoimmune) thyroiditis in the French cohort studyThe GBS results were driven by two cases among exposed individuals in the French cohort study,The IBD primary analysis did not show an increased risk following AS04‐HPV‐16/18 vaccination. This is in line with previous AS04‐HPV‐16/18 pooled analyses.Our results are also supported by a recent systematic review and meta‐analysis that examined the risk of various autoimmune disorders after vaccination with any HPV vaccine.4.1This study highlights the potential value, as well as the limitations of, meta‐analysis as a tool to investigate safety signals related to rare outcomes, which is challenging due to the inclusion of studies with no events in one or both arms.i2 index  ‐ appeared to be very low, although the CIs were very broad, so the apparent lack of heterogeneity should be interpreted with caution.There was also heterogeneity between studies, in terms of study design, coding of medical events , case asRegarding study design, the AS04‐HPV‐16/18 exposed and non‐exposed arms of the RCTs should have been balanced by randomization, but there could have been multiple unknown confounders between arms in the observational studies, which it is impossible to adjust for. Also, subjects in both arms could have received additional vaccines, with or without adjuvants, further complicating interpretation of the results. Another difference between the RCTs and observational cohort studies is the level of medical surveillance. In the RCTs, vaccinated and control subjects were followed up according to protocol‐defined scheduled visits. However, in the two observational cohort studies,The case‐control studyCase definitions and ascertainment methods varied between studies. In the RCTs, all cases were fully medically validated, whereas in the French cohort study,Unfortunately, individual subject data (including time‐to‐event data) for the case‐control studyIdeally, disease onset would be from the date of first symptoms, but this is not necessarily known, especially in retrospective database studies. Using diagnosis dates, some autoimmune cases that were diagnosed after vaccination may have had their first symptoms prior to vaccination. Conversely, some cases with first symptoms within 2 years or 42 days following vaccination might have been diagnosed after these windows and therefore not have been included.Overall, our analysis illustrates that a meta‐analysis can be powerful tool, but its strength is related to the quality of the input data.5This meta‐analysis ‐ including approximately 150 000 AS04‐HPV‐16/18‐exposed and 1 500 000 non‐exposed subjects ‐ did not indicate an increased risk of IBD. The results of the analysis showed a 1.5‐fold increased risk of (autoimmune) thyroiditis, but based on existing epidemiological and mechanistic evidence, there is insufficient evidence to conclude a causal association with vaccination. No conclusion regarding the risk of GBS can be drawn as they were driven by two cases among exposed individuals, the times‐to‐onset of which were unknown. Although the GBS OR estimates were high, the number of cases was low and the 95% CIs were wide.Considering the current results and ongoing surveillance of AS04‐HPV‐16/18 vaccination including other available post‐marketing data and pooled analyses of clinical trial data,Given the overall safety data and the demonstrated high and sustained efficacy of AS04‐HPV‐16/18 against HPV‐16/18 infection and cervical lesions,The authors state that no ethical approval was needed.A.G., C.W., D.R., F.T.D.S., S.C., S.W. are employees of the GSK group of companies. A.G., D.R., F.S., F.T.D.S., S.W. hold shares in the GSK group of companies as part of their employee remuneration. F.S. was an employee of the GSK group of companies at the time the study was performed and is currently an employee of Janssen, Pharmaceutical Companies of Johnson & Johnson. F.S. owns shares in the GSK group of companies.D.R., C.W. and F.T.D.S. were involved in the design of the study, collection of the data, and interpretation of the results. D.R. and S.C. were involved in the statistical analysis. A.G. and S.C. were involved in the interpretation of the results. F.S. was involved in the design of the study and interpretation of the results.Data S1. Supporting Information.Click here for additional data file.Data S2. Supporting Information.Click here for additional data file.Data S3. Supporting Information.Click here for additional data file.Data S4. Supporting Information.Click here for additional data file.Data S5. Supporting Information.Click here for additional data file.Data S6. Supporting Information.Click here for additional data file.Data S7. Supporting Information.Click here for additional data file.Data S8. Supporting Information.Click here for additional data file.


Preeclampsia (PE) and gestational diabetes mellitus (GDM) are the most common complications of pregnancy, which result in adverse outcomes for the mother and the fetus. GDM is regarded as a separate independent risk factor for PE development, as evidenced by a higher preeclampsia rate in gestational diabetes mellitus than in the general population. The role the endothelial cell dysfunction plays is considered to be the most reasonable one in the origin of these diseases. The activity of plasma and tissue angiotensin converting enzyme (ACE) is believed to be genetically controlled. The available data suggests that increased ACE activity due to deletion (D)/insertion (I) in the 16th intron of ACE gene, which is called ACE gene I/D polymorphism, is associated with preeclampsia and varies depending on the studied population and the geography. We did not find any literature data that estimates the influence of ACE gene I/D polymorphism on PE rate in pregnant women with GDM. Therefore, the present study aimed to investigate a relationship between ACE gene I/D polymorphism and preeclampsia development in the case of GDM in the Russian population. The study used the genomic DNA derived by phenol-chloroform extraction method from venous blood samples in 137 pregnant women, including samples of 74 women with GDM accompanied with PE and the blood samples of 63 women with GDM w/o preeclampsia. Genotyping of insertion/deletion in the I/D region (16 intron of АСЕ gene) was conducted by real-time PCR using the TaqMan competing probe technology. The particular features in the frequency array of alleles and genotypes of the ACE gen I/D polymorphism under review, as associated with preeclampsia development risk in pregnant women with GDM, were identified. The acquired data testify to the need to further study of ACE gene I/D region polymorphism association in a large patient sample taking into account the PE and GDM risk factors estimated in the clinical practice. Preeclampsia (PE) is a multi-system disorder that arises after gestation week 20 and is described by arterial hypertension, combined with proteinuria (≥0.3 g/l in daily urine), oedema and multi-organ dysfunction –3. PE deEven though the preeclampsia clinical manifestations and diagnostic criteria do not overlap with those of GDM, certain studies suggested that the same predisposing factors are typical of PE and GDM ; however, GDM is a separate and independent risk factor of PE development –22.Just as with GDM and with preeclampsia, the main pathophysiological criterion is the vascular endothelial dysfunction –26. The The ACE gene is located on locus 17q23.3, in the DNA plus chain, which consists of 26 exons and 25 introns, and encodes an angiotensin-converting enzyme , 35. TheI/D polymorphism of АСЕ gene is associated with ACE blood level and determines the onset of such diseases as coronary heart disease, left ventricular hypertrophy, arterial hypertension, stroke, diabetic nephropathy, type 2 diabetes mellitus, diabetic nephropathy, diabetic neuropathy, diabetic retinopathy and hypertensive retinopathy, according to different research , 38–46. The results of association studies of I/D polymorphism in the case of PE and GDM are inconsistent –58. SomeWe did not find in the literature any data that estimates the influence of ACE gene I/D polymorphism on PE rate in pregnant women with GDM. Therefore, this study was aimed at investigating the relationship between I/D polymorphism of ACE gene and preeclampsia in the case of GDM.The study involved DNA samples extracted from the venous blood of 137 GDM pregnant women, including those of 74 pregnant women with combined GDM and PE and those of 63 pregnant women with GDM not combined with preeclampsia, who were followed up and gave birth in 2018/2019 in the Maternity Department of the State Clinical Hospital No. 29  of the Healthcare Department of Moscow. All respondents were Russian speakers of indefinite ethnicity  and enrolled in the study voluntarily. The study was approved by the Ethical Committee of the Research and Development Institute of General Pathology and Pathophysiology.GDM and PE diagnosis were the study inclusion criteria. The absence of acute and chronic diseases at the exacerbation stage was the exclusion criterion. Pregnant women with autoimmune, nervous and mental diseases and with cancer of any localization were also excluded from the study.GDM diagnosis was established based on the criteria of the Russian National Consensus and clinical guidelines “Gestational Diabetes Mellitus: Diagnosis, Treatment, Postpartum Follow-Up” .Preeclampsia was diagnosed based on the clinical guidelines “Hypertensive Disorders in Pregnancy, Labor and Post-Partum. Pre-eclampsia. Eclampsia” .DNA was extracted from venous blood with the standard phenol-chloroform extraction method of Maniatis et al. . The bloThe extracted DNA quality and quantity was estimated by the 260/280 wavelength ratio when measuring DNA concentration in the NanoDrop 1000 spectrophotometer, in the two-chain DNA analysis mode, dsDNA-50. Defective samples were not included into further analysis, just as those with low DNA concentration.The deletion/insertion in the I/D area (ACE gen 16th intron) was studied by real-time PCR  using the primers we designed. The set of primers includes 2 forward primers: ACE-I/D-F1: 5'-GGAGACCACTCCCATCCTTTC-3' and ACE-I/D-F2: 5'-GCCTCAGCCTCCCAAG-3', and 1 reverse primer ACE-I/D-R1: 5'-ATGTGGCCATCACATTCGTCAGAT-3'. The primers were designed so that the ACE-I/D-F1 forward primer and the ACE-I/D-R1 reverse primer amplify the I/D area (ACE gen 16th intron) with insertion, while ACE-I/D-F2 and ACE-I/D-R1 primers, the I/D area (ACE gen 16th intron) with deletion. The ACE-I/D-R1 forward primer is annealed in the insertion area and creates a specific PCR product while the ACE-I/D-F2 primer, in a specific site that is formed in case of the Alu-repeat deletion only. To detect the amplification in real-time with subsequent analysis by the allele discrimination method, the specific Taq-man probes are used: ACE-I: 5'HEX-CCCGCCACTACGCCCGGCTAA-3'BHQ1 to detect an insertion and ACE-D: 5'FAM-GCTGCCTATACAGTCACTTTTATGTGGT-3'BHQ1 to detect a deletion. All primers and Taq-man probes were synthetically produced by Syntol LLC, Russia.μl sample contained 20 ng DNA, 10 mM Tris–HCl (pH 8.3), 50 mM КСl, 3 mM MgCl2, 0.125 mM dNTP, 0,1 μM ACE-I/D-F1, 0,2 μM ACE-I/D-F2, 0,2 μM ACE-I/D-R1, 0,2 μM ACE-I, 0,2 μM ACE-D, 0.4 μM each of Taq-man probes, 0.25 units of act. TaqDNA-polymerase.The reaction mixture for RT-PCR for one 15 Amplification was carried out in the CFX 96 programmable amplifier  with the subsequent thermocycling parameters: initial denaturation for 5 minutes at 95°С; then 40 cycles including denaturation at 95°С for 20 seconds, at 60°С for 30 seconds and at 25°С for 10 minutes; primer annealing and subsequent elongation at 72°С for 10 minutes, with subsequent fluorescence pickup. The obtained data was examined using the CFX Manager TM software (Bio-Rad).http://ihg.gsf.de/cgi-bin/hw/hwa1.pl.). The trend analysis was carried out using the general, dominant and recessive inheritance models. Differences were regarded as significant at p ≤ 0.05. The association force for the tested attributes was determined by the odds ratio (OR) with the confidence interval (CI) at 95% significance level. The anticipated risk factor was regarded as significant for pathology if OR adjusted by CI was greater than 1.The results were statistically processed using the Hardy-Weinberg equilibrium tests and the chi2 association test in DeFinetti application (freely available on the website of the Institute of Human Genetics (Germany), The insertion/deletion test in the I/D area (ACE gen 16th intron) enabled to assess the allele frequency of the polymorphic loci genotypes in the studied gen. The distribution of genotype and allele frequencies in the I/D polymorphic locus of the ACE gen matched the one expected in the Hardy-Weinberg equilibrium, both for the pre-eclampsia group and for the control (no preeclampsia) group .The investigation into the distribution of genotype and allele frequencies in the study groups revealed that the D allele frequency came to 48.6% in the group of GDM PE+ pregnant women vs 37.3% in the group of GDM PE-. The frequency of DD homozygous genotype in the GDM PE+ group is higher than that in the GDM PE- group (24.3% vs 11.1%).The association analysis revealed the association between ACE gene I/D polymorphism and preeclampsia . So, DD Preeclampsia and GDM are the most common pregnancy complications that result in an adverse outcome for the mother and the fetus. Despite numerous data on the reasons for these complications in the literature, the key drivers are still unknown; however, the role the endothelial cell dysfunction plays is considered to be the most probable cause of GDM and preeclampsia onset.The research and clinical studies suggest that an array of genetic factors are involved in PE and GDM pathogenesis. So far, 100 polymorphic gene allelic variants, in particular, those regulating the endothelium, vascular system etc. functions, have been found to be associated with pre-eclampsia. Special focus was on ACE gen, one of the renin-angiotensin system encoding elements, because the Alu-repeat deletion of I/D polymorphism in ACE gen 16th intron leads to increased expression of the gen, which explains the inter-individual differences in angiotensin-converting-enzyme (ACE) blood levels. The available data suggests that persons with D/D genotype have the maximum ACE blood level and those with I/I genotype, twice as low level , 62.The available reference data on the study of the ACE gen I/D polymorphism association with preeclampsia is inconsistent. Our study findings conform to some previous studies that pointed to the high frequency of DD genotype and/or D allele in preeclampsia. For instance, in the Asian region, ACE gene I/D polymorphism is associated with PE development risk in the Korean and Chinese populations , 63, 64.On the other hand, some studies did not find any differences in the allocation of allele genotypes and frequencies and the association between DD genotype and preeclampsia , 69–74. The differences in the data derived from different studies on the association between ACE gene I/D polymorphism and preeclampsia are likely to be due to the size, population features and the ethnicity of the study groups and also depend on the analytical inheritance model selection. The meta-analysis conducted by Medica et al. (2006) on 10 studies with participation of 1,121 patients and 1,361 control group participants demonstrated the statistical significance in consideration of the I/D polymorphism of ACE gene 16th intron in the recessive model: the odds ratio came to 1.51 (95% CI: 1.17-1.94) . BereketThe principal goal of this study was to investigate into the relationship between I/D polymorphism of АСЕ gene and the preeclampsia risk in pregnant women with gestational diabetes mellitus in the Russian population. Our study suggested that the frequency of the DD homozygous genotype of АСЕ gen varied between the groups, and D allele was more frequent in pre-eclampsia women than it was in PE- group. The relationship between this polymorphism and preeclampsia was found in the general inheritance model. We discovered a higher frequency of DD genotype in the preeclampsia group as compared with the control group. It is noteworthy that no studies of the association between ACE gene I/D polymorphism and preeclampsia development in GDM pregnant women have been conducted in the Russian population so far.Our study revealed a statistically significant association between the DD homozygous type of ACE gene I/D polymorphism and preeclampsia in GDM women in the general inheritance model. A small size of the study groups is the main limitation of this study. Nonetheless, the data we received point to the need for further study of the association between ACE gene I/D polymorphism in a large patient sampling, with the parallel trial of polymorphism in other genes and taking into account PE and GDM risk factors estimated in the clinical practice , which can also affect the development of these disorders. In the future, it will enable to use this genetic marker as the criterion in assessing the individual forecast of preeclampsia development in GDM pregnant women, which will enable to take efficient preventive efforts for timely correction and improvement of the pregnancy outcome.


To provide an understanding of the role of common genetic variations in colorectal cancer (CRC) risk, we report an updated field synopsis and comprehensive assessment of evidence to catalogue all genetic markers for CRC (CRCgene2).We included 869 publications after parallel literature review and extracted data for 1063 polymorphisms in 303 different genes. Meta-analyses were performed for 308 single nucleotide polymorphisms (SNPs) in 158 different genes with at least three independent studies available for analysis. Scottish, Canadian and Spanish data from genome-wide association studies (GWASs) were incorporated for the meta-analyses of 132 SNPs. To assess and classify the credibility of the associations, we applied the Venice criteria and Bayesian False-Discovery Probability (BFDP). Genetic associations classified as ‘positive’ and ‘less-credible positive’ were further validated in three large GWAS consortia conducted in populations of European origin.We initially identified 18 independent variants at 16 loci that were classified as ‘positive’ polymorphisms for their highly credible associations with CRC risk and 59 variants at 49 loci that were classified as ‘less-credible positive’ SNPs; 72.2% of the ‘positive’ SNPs were successfully replicated in three large GWASs and the ones that were not replicated were downgraded to ‘less-credible’ positive (reducing the ‘positive’ variants to 14 at 11 loci). For the remaining 231 variants, which were previously reported, our meta-analyses found no evidence to support their associations with CRC risk.The CRCgene2 database provides an updated list of genetic variants related to CRC risk by using harmonised methods to assess their credibility. Colorectal cancer (CRC) is a global public health challenge. A large number of genetic association studies have been conducted to assess the potential correlation between common genetic variations and CRC risk.MUTYH, SMAD7, TERT, CDH1, RHPN2, BMP2, TGFB1 and common variants tagging loci at 8q24, 8q23.3, 10p14, 11q23.1, 20p12.3) as highly credibly associated with CRC risk. A total of 63 variants at 52 loci were classified as ‘less-credible positive’ SNPs; variants of nine of these genes could be mostly highly prioritised for further investigation. For 231 variants previously reported to be associated with CRC, our meta-analyses found no evidence to support such associations.Using an established framework for grading credibility of genetic associations, we classified 14 independent variants at 12 loci  is one of the most commonly diagnosed malignancies and the leading cause of cancer deaths in the world, with 1.65 million new cases and about 835 000 deaths in 2015.APC, SMAD4, LKB1/STK11, MUTYH) have been identified to influence CRC susceptibility with large effects, overall they account for only 2%–5% of incident CRC cases in the general population because these mutations are very rare.It is estimated that 15%–25% of CRC risk variance is attributed to inherited genetic factors, and the first-degree relatives of CRC patients have two to four times higher risk of developing CRC.MUTYH, MTHFR, SMAD7, 8q24, 8q23.3, 11q23.1, 14q22.2, 1q41, 20p12.3, 20q13.33, 3q26.2, 16q22.1, 19q13.1),APC, CHEK2, DNMT3B, MLH1, MUTYH) that were strongly associated with CRC.In 2012 and 2014, we reported two independently conducted series of meta-analyses to systematically evaluate associations between CRC and common variants using data from candidate gene studies and genome-wide association studies (GWASs) and identified a number of promising genetic risk variants for CRC risk.In this study, we aimed to perform an updated field synopsis for CRC risk by including the most recently published genetic association studies, by following established guidelinesTo identify genetic association studies of CRC risk, we searched the Medline database via the Ovid gateway and the search terms comprising medical subject headings (MeSH) and keywords relating to colorectal neoplasms, the MeSH heading ‘genetic predisposition to disease’, and the keywords ‘gene$’ and ‘associate$’ were applied to terms in the entire article. The latest literature search was performed on 21 November 2018. We screened the eligibility of retrieved publications in a three-step parallel review of title, abstract and full text by following the predefined inclusion and exclusion criteria. Thus, each eligible study evaluated the association between a polymorphic genetic variant  and a sporadic CRC. Studies investigating only premalignant conditions such as adenomas, polyps or dysplastic tissue were excluded. Studies investigating hereditary CRC syndromes, such as familial adenomatous polyposis, hereditary non-polyposis CRC, juvenile polyposis syndrome and Gardner’s syndrome; solely focusing on the progression or histological phenotype of CRC; or studies in animals; were excluded. Case-control, cohort and GWASs were included, while family-based studies were excluded. All included studies were published in English in a peer-reviewed journal; studies only reported as conference abstracts were excluded. Data from the eligible studies were abstracted into two standardised tables, including the key variables with regard to the study identifiers and context, study design and limitations, genotype information and outcome effects.A list of genetic variants that were investigated in meta-analyses was summarised and data from three GWAS consortia  were incorporated for meta-analyses, when the genotype data are available for the listed variants. In brief, the Study of CRC in Scotland (SOCCS) is a population-based case-control GWAS that includes 3417 cases and 3500 controls. The Assessment of Risk for Colorectal Tumors In Canada (ARCTIC) is a case-control GWAS database that includes 1231 cases and 1240 controls. The population-based cohort study in Spain comprised two phases (EPICOLON I and EPICOLON II) adding up to 2000 cases and 2000 controls. Restricted candidate gene genotyping data were available from both phases and GWAS data were only accessible from 881 cases and 667 controls from phase 2.10.1136/gutjnl-2019-319313.supp1Supplementary data2 metric were calculated to quantify between-study heterogeneity. Funnel plot analysis with an Egger test was conducted to test for small study effects. We also estimated the statistical power of each meta-analysis based on the significance level of α=0.05, the effect sizes and the allele frequencies of genetic variants  analysis).Meta-analysis was performed for genetic variants with data available from at least three independent studies. Summary crude ORs and 95% CI for allelic, recessive and dominant genetic models were calculated by applying either the fixed-effect model (Mantel-Haenszel method) or the random-effects model (DerSimonian-Laird method) in case of the existence of substantial heterogeneity. The Q statistic  and Ihttps://research.fhcrc.org/peters/en/corect-study.html) and Colon Colorectal Cancer Family Registry (CFR).We first applied the BFDP−3), close to what would be expected for a candidate gene, and a very low prior level (10−4 to 10−6), close to what would be expected for a random SNP. A noteworthy threshold was defined as 0.2 based on the assumption that the cost of false discovery would be four times higher than that of false non-discovery.The BFDP assesses the noteworthiness of an observed association. The BFDP was selected rather than the false-positive report probability (FPRP) because it uses more information, defines the noteworthiness threshold explicitly in terms of the costs of false discovery and non-discovery, and does not suffer from the inferential limitations identified for the FPRP.2 criterion), and a grade of A, B and C was assigned, respectively, when I2 was less than 25%, 25%–49% or greater than 50%.According to the Venice criteria, the credibility of associations is assessed for three aspects: the amount of evidence, the extent of replication and the protection from bias.2 less than 50%. A class of ‘less-credible positive’, with a less-stringent threshold, was assigned to the associations (1) that were statistically significant at a p value threshold of 0.05 in at least one of the genetic models, but (2) their BFDP was greater than 0.20 or their statistical power was between 50% and 79% or had an I2 greater than 50%. Associations with p value large than 0.05 were further classified as ‘null’ or ‘negative’ by assessing if there are more than 5000 cases. After credibility assessment, genetic variants classified as ‘positive’ and ‘less-credible positive’ were sent to the CORECT coordinating centre to validate their associations with CRC risk using additive, dominant and recessive models. At this stage, ‘positive’ associations that failed to be validated (at p<0.05) were downgraded to ‘less-credible positive’. A schematic diagram is shown in Genetic associations were then classified into four categories based on the following criteria. Associations were classified as ‘positive’ if they: (1) were statistically significant at a p value level of 0.05 in at least two of the genetic models, (2) had a BFDP less than 0.20 at least at the p value level of 0.05, (3) had a statistical power greater than 80%, (4) had an IA total of 20 900 citations were identified from literature search. Of these, 6770 (32.4%) papers were published after the search period of the most recent field synopsis (31 December 2012).Meta-analyses were conducted for 308 polymorphisms in 158 different loci with data available in three or more candidate or GWA studies . On aver10.1136/gutjnl-2019-319313.supp2Supplementary dataMUTYH, rs2066847 in NOD2, rs12953717 and rs4464148 in SMAD7, rs1569686 in DNMT3B, rs2736100 in TERT, rs9858822 in PPAR-gamma, rs1862748 in CDH1, rs7259371 in RHPN2, rs355527 in BMP2, rs1800469 in TGFB1, rs10505477 in 8q24, rs16892766 in 8q23.3, rs3802842 in 11q23.1, rs961253 in 20p12.3, rs10795668 in 10p14, rs4951291 in 1q32.1) had the most credible associations with CRC risk and are therefore referred to as ‘positive’ SNPs  tagging 16 loci (rs36053993 and rs34612342 in ve’ SNPs . These f(2 >0.20 . The oth(2 >0.20 . The sumMUTYH [Y179C] gene) was dropped due to its low imputation quality in these GWASs; 5 ‘less-credible positive’ polymorphisms  had no rs numbers; and 3 polymorphisms (in TP53 and KRAS) were not available in these GWASs; therefore, they were not able to be validated. Of the 17 ‘positive’ SNPs sent for validation, 7 polymorphisms (41.2%) in 6 different loci  reached a genome-wide statistical significance (p≤5×10−8) in at least one meta-analysis model and 6 polymorphisms (35.3%) in 6 different loci  reached a nominally statistical significance (p<0.05) in at least one meta-analysis model. However, the remaining 4 polymorphisms (23.5%) in 4 different loci  failed in the GWAS validation of all genetic models (APC) reached a genome-wide statistical significance (p≤5×10−8) in at least one meta-analysis model and 11 polymorphisms (21.6%) in 11 different loci  reached a nominally statistical significance (p<0.05) in at least one meta-analysis model, whereas the remaining 38 polymorphisms (74.5%) failed in the GWAS validation of all genetic models  and for 10 (15.9%) of 63 ‘less-credible’ polymorphisms . Therefore, their reported association with CRC risk should be interpreted with caution.Funnel plots were produced for all ‘credible’  and ‘les10.1136/gutjnl-2019-319313.supp3Supplementary dataThe remaining 231 polymorphisms (75.0%) assessed in meta-analyses were reported to have no statistically significant association (p>0.05) with CRC risk in all three genetic models , based oMUTYH, SMAD7, 8q24, 8q23.3, 11q23.1, 20p12.3) were also classified as credibly associated with CRC risk in the previous field synopses and the other 6 loci  are novel findings as they have not been assessed or reported as credible risk loci in the previous field synopses.This systematic, comprehensive field synopsis of genetic association studies on CRC updates the two previous field synopsesWe note that a synopsis was undertaken of literature on genetic associations with CRC published in the period 2012–2017.MYC proto-oncogene has been controversial,MYC promoter, via transcription factor Tcf-4 binding and allele-specific regulation of MYC expression, has been demonstrated.CARLo-5, in normal colon tissue have been found to be statistically significantly correlated with rs6983267, and chromosome conformation capture analysis of genomic DNA from CRC-derived cell lines provided evidence of physical interaction between the active regulatory region of the CARLo-5 promoter and the MYC enhancer region.Similar to our previous field synopses,SMAD7 were identified to be associated with CRC with highly credible evidence. Associations with rs12953717 and rs4464148 were successfully validated in the three GWAS consortia. In fine-mapping and bioinformatics analysis performed within the GECCO-CCFR consortia, rs4464148 was appraised as having less strong functional evidence than the highly correlated rs9932005 variant, which is located within 5 kb away.CDH1), rs355527 (BMP2), rs961253 (BMP2) and rs7259371 (RHPN2) variants, which are TGF-ß related, and replicated in the data from the GWAS consortia. In the recent East Asian analysis, the association with the rs961253 (BMP2) variant was replicated, as well as additional variants of SMAD7 , CDH1 (rs9929218), BMP2 (rs4813802) and RHPN2 (rs10411210).BMP2 as well as each other, novel associations with the BMP2 variants rs28488 and rs994308 were detected.Two genetic polymorphisms (rs12953717 and rs4464148) tagging in MUTYH gene were highly credibly associated with increased CRC risk, of which rs36053993 was validated in the three GWAS consortia data, while rs34612342 was not tested due to its poor imputation quality. The MUTYH gene is known to be involved in the dysfunction of base-excision repair, which is the major pathway for repairing oxidative damage. This biological pathway in which the MUTYH gene is involved contributes to the development of multiple colorectal adenomas and carcinomas (MUTYH-associated polyposis (MAP) syndrome).Additionally, two variants (rs34612342 and rs36053993) tagging the COLCA1 and COLCA2 arranged on opposite strands and sharing a regulatory region containing rs3802842.COLCA1 and COLCA2, which is further correlated with lymphocyte infiltration of colonic lamina propia. Further, in an expression quantitative trait locus analysis in colorectal tissue, there were signals for COLCA1 and COLCA2.GATA3 gene was reported with a highly credible association with CRC, and this association was further replicated in the GWAS consortia and in the recent East Asian analysis.PPARγ was identified; however, this association was not replicated in the GWAS consortia. Bioinformatics analysis showed that PPARγ and its ligands have been found to block proinflammatory genes in colon cancer cell lines, activated macrophages and monocytes.PPARγ is also involved in lipid metabolism, adipocyte differentiation, and glucose homeostasis and insulin sensitivity.NOD2 gene; however, this association was not replicated. Evidence from experimental studies in mice investigating the role of Nod2 in colorectal tumour risk has also been inconsistent.Highly credible associations were also reported for four variants tagging four different genes that are involved in inflammation or immune response. First, a positive association with the rs3802842 variant in the 11q23.1 was identified for CRC risk and this association was replicated in the data from the GWAS consortia and in the recent East Asian analysis.TERT and rs16892766 at 8q23.3 tagging EIF3H. These variants were all validated in the GWAS consortia datasets. Fine-mapping and bioinformatics analysis performed within the GECCO-CCFR consortia supported these variants with strong functional evidence, for which polymorphism rs2736100 in TERT gene has been reported to be associated with telomere length and the risk of different types of cancer and chronic diseases other than cancer.EIF3H, another variant rs16888589 was previously reported with the lowest p value for the association with CRC in this locus.EIF3H expression,UTP23 rather than EIF3H is the target of genetic variation associated with CRC in this region.The remaining two variants with highly credible associations with CRC risk included rs2736100 tagging AXIN2, MMP1); alcohol metabolism (ADH1B); angiogenesis (VEGF); blood clotting (SERPINE1); DNA repair ; hormone metabolism ; inflammation and immune response ; inhibition of cell growth ; iron metabolism (HFE); lipid metabolism ; one-carbon metabolism ; substrate metabolism ; tumour suppression ; vitamin D metabolism (VDR)—common low penetrance variants at 1q32.1  and 9p24 (rs719725); and the common rs1801155 (I1307K) variant of APC, for which large numbers of rare variants have been identified,MLH1, for which rare variants confer a high risk of Lynch syndrome.PARP1, MYC, VDR, ADIPOR1, APC, PTGS2/COX2, SCD, HPGD and ESR2), which were replicated in the GWAS data and for which their linked pathways are worthy of further investigation in future studies.The less credible associations with 63 variants of 52 genes involved the following pathways—adhesion . All the remaining 13 variants had p values for association less than 5.0×10−5 with no more than moderate heterogeneity. Such an empirical comparison was not appropriate with the data of Huyghe et alWe checked whether the 14 variants we classified as ‘highly credible’ were replicated in the paper of Law In summary, we have conducted a comprehensive study to capture and meta-analyse all SNP data for common genetic variants. The analysis clearly identifies 14 variants at 12 loci for which there is robust evidence of their impact on CRC risk, 63 variants at 52 loci for which further evidence through international collaboration should be generated and 231 variants for which the overall evidence does not support any association with CRC risk. With increasing availability of data from multiple SNPs, it is clear that studies to test associations must achieve very high levels of statistical stringency. Nonetheless, the analysis here provides a resource for mining available data and puts into context the sample sizes required for the identification of true associations for common genetic variants. Future resequencing studies are expected to identify rarer variants  with intermediate or perhaps even large effects, and GWAS of structural variation will likely identify deletions, amplifications and other copy number variations that may also influence CRC risk.


PPARGC1A or PGC-1alpha) gene rs8192678 locus and the susceptibility to type-2 diabetes mellitus (T2DM).To systematically investigate the correlation between the G>A polymorphism of the peroxisome proliferator-activated receptor γ coactivator 1α (PPARGC1A gene rs8192678 locus and susceptibility to T2DM were included for the meta-analysis.The inclusion and exclusion criteria and retrieval strategies of original literatures were formulated. Then, subjects and free words “PPARGC1A”,”gene polymorphism”, and “T2DM” were retrieved from the PubMed, EMBASE, and Cochrane Library databases. Case-control studies on the G>A polymorphism of the PPARGC1A gene rs8192678 locus G>A polymorphism is associated with susceptibility to T2DM. There are differences in each group of genetic models, of which three groups of genetic models are highly significant. In the allele model, OR=1.249, 95% CI: 1.099-1.419, and P=0.001. In the dominant inheritance model, OR=1.364, 95% CI: 1.152-1.614, and P=0.000. In the additive inheritance model, OR=0.828, 95% CI: 0.726-0.945, and P=0.005. And one group is significant, in the recessive inheritance model, OR=1.187, 95% CI: 1.021-1.381, and P=0.026.The number of cases in the T2DM group and control group was 5,607 and 7,596, respectively. The meta-analysis revealed that the PPARGC1A gene rs8192678 locus may be one of the risk factors for T2DM.In Western Asian, South Asian, European and African populations, the A allele of the  PPARGC1A or PGC-1alpha) gene can regulate lipid secretion, fatty acid metabolism and insulin sensitivity [PPARGC1A gene is a candidate gene for studying the metabolic syndrome and T2DM. The genetic variation at the 1444th locus (rs8192678) in exon 8 of the PPARGC1A gene leads to G>A base substitution, causing the substitution of glycine by serine (Gly482Ser) in the amino acid sequence and structural change [PPARGC1A gene in 53 Danish T2DM patients. The study showed that the Gly482Ser polymorphism was associated with T2DM. Subsequently, Lacquemant et al [PPARGC1A gene rs8192678 polymorphism and T2DM in recent years showed a significant association for this locus and T2DM in the Indian population . However, no significant associations were found among Caucasians or East Asians [P<0.001) [PPARGC1A gene rs8192678 polymorphism and T2DM in different ethnicities, which will provide a basis of future biological functional research and clinical research of the PPARGC1A gene.Type-2 diabetes mellitus (T2DM) is a disorder of the metabolism of sugar, fat and protein caused by insulin resistance (IR) or the relative insufficiency of insulin secretion in islet beta cells, in which its occurrence and development are impacted by the dual factors of environment and heredity . T2DM isl change . Initialus rs819278 in exo11.1PPARGC1A gene polymorphism and T2DM was retrieved from the PubMed, EMBASE and Cochrane Library databases. Literature containing the subjects and free words “PPARGC1A”, “gene polymorphism”, and “T2DM” was retrieved from these databases. In addition, the cited references in relevant treatises and reviews were manually retrieved to collected case-control studies on the correlation between the G>A polymorphism of the PPARGC1A gene rs8192678 locus and susceptibility to T2DM. The retrieval time range was from the establishment of the databases to June 2018. By reading the titles and abstracts, and reading the full text when necessary, two investigators conducted an independent evaluation of the literature on the basis of the inclusion and exclusion criteria. When these two investigators disagreed with each other, all researchers in our team participated in the assessment of whether the literature should be included.Literature about the correlation between 1.1.1PPARGC1A gene polymorphism and T2DM, and the case group should comprise of diabetic patients, who have combined diseases with no special restrictions. The control group should comprise of subjects with normal blood glucose levels and no family history of diabetes mellitus. (2) The literature must provide the genotype distribution frequency in the case group and control group, or the genotype distribution frequency could be calculated from the data provided by the literature. (3) If an article contains studies in two or more ethnic or regional populations, each study in one population was considered as one independent study. (4) The language in which the article was published was confined to English, and the sample size was unrestricted. For studies with incomplete data, the investigators did not intend to contact the authors.(1) The study must be a case-control study, cohort study, or cross-sectional study on the association between 1.1.2Literature with incomplete data, literature in which the observed disease was not T2DM, literature in which the polymorphic loci did not meet the requirements, and literature with animal study subjects, reviews and meta-analysis studies were excluded.1.2After reading the full text of the literature, two investigators filled in a standard form with the following data in advance: author information, year of publication, ethnicity and country of the study subjects, the sample sizes of the case group and control group, the number of genotypes, and whether the genotype distribution in the control group was in accordance with the Hardy-Weinberg equilibrium (HWE). When these two investigators disagreed with each other, a third researcher would participate in determining the accuracy of the extracted data.1.3The Newcastle Ottawa scale (NOS) was used to assess the quality of THE selected case-control studies, in which literature with a NOS score ≥5 was considered as high quality literature . The Age1.4PPARGC1A gene polymorphism and risk of T2DM in four different genetic inheritance models: allele model (A vs. G), dominant inheritance model (AA+GA vs. GG), recessive inheritance model (AA vs. GG+GA), and additive inheritance model (AA+GG vs. GA). (3) In order to determine whether there was significant heterogeneity among studies, the q statistic based on Chi-square test was used for qualitative analysis, while I2 statistic was used for quantitative analysis. If I2<50% and P>0.1, it was considered that there was no statistical heterogeneity among studies. Then, a fixed-effects model (M-H) was used for data consolidation, If I2≥50% and P<0.1, it was considered that there was statistical heterogeneity among studies. Then, a random-effects model (D-L) was used for data consolidation. (4) In order to explore for potential heterogeneity sources and robustness of the test results, a subgroup analysis was carried out based on ethnicity, sample size (number of case groups ≥300 or <300) and age (≥60 and <60), respectively. In order to explore the impact of a single study on the overall result, the step-by-step elimination method was used for the sensitivity analysis. That is, merely one study was eliminated at a time, and the effect size of the remaining studies was reconsolidated to observe the stability of results. If the OR value of the remaining studies was outside the range of the total effect size of 95% CI after one study was excluded, it was considered that the study results impacted the overall results. Finally, funnel plot and Begg’s method were used to detect for publication bias in the included literature. If the funnel plot was asymmetrical or P<0.05, publication bias was inferred.(1) Chi-square goodness of fit test was used to determine whether the distribution of genotypes in the control group in each study was in accordance with HWE. The odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the correlation between 22.1According to the retrieval strategy, a total of 70 pieces of literature were primarily obtained. After reading the titles and abstracts, 29 irrelevant pieces of literature were excluded. Among the remaining 41 pieces of literature, after reading the full text, 25 literature pieces were excluded, which included two reviews, four meta analyses, 11 literature items with incomplete data, four literature items that did not study the gene polymorphic locus, one literature piece with suspected data duplication, and three literature items that studied diseases that were not T2DM. Finally, a total of 16 pieces of literature were included in the present meta-analysis , 24, 25.2.2P=0.001, and Pheterogeneity=0.000. In the dominant inheritance model, OR=1.364, 95% CI: 1.152-1.614, P=0.000, and Pheterogeneity=0.000. In the recessive inheritance model, OR=1.187, 95% CI: 1.021-1.381, P=0.026, and Pheterogeneity=0.077. In the additive inheritance model, OR=0.828, 95% CI: 0.726-0.945, P=0.005, and Pheterogeneity=0.006. In addition, the aggregated data exhibited relatively robust heterogeneity, and a subgroup analysis was further applied to explore the sources of heterogeneity. Taking into account the differences in genetic backgrounds and environmental factors among different ethnicities, the same gene locus may have different effects on the same disease. Therefore, the investigators further explored the correlation in different ethnicities. The results revealed that in the allele model, gene polymorphism rs8192678 was associated with T2DM in the Western Asian population , South Asian population , European population , and African population , and the associations were all statistically significant. However, no significant correlation was detected in the East Asian population . In the dominant inheritance model, the correlation between gene polymorphism rs8192678 and risk of T2DM in Western Asian, South Asian, European and African populations was further confirmed. However, in the recessive inheritance model, no significant correlation between gene polymorphism rs8192678 and risk of T2DM was found in East Asian, West Asian, South Asian and African populations. In the additive inheritance model, no significant correlation between gene polymorphism rs8192678 and risk of T2DM was found in East Asian, European and African populations. The results of the meta-analysis on the correlation between rs8192678 and T2DM are presented in A total of 12 case-control studies and one cross-sectional study, which involved 4,416 patients and 5,781 controls, were included in the meta-analysis. The results of meta-analysis revealed that the gene polymorphism rs8192678 locus was significantly correlated to T2DM in the general population. In the allele model, OR=1.249, 95% CI: 1.099-1.419, 2.3P>0.05). Except for the recessive inheritance model, when the sample size was ≥300, the heterogeneity among studies was significantly lower than before grouping. When the sample size was <300, the heterogeneity among studies was significantly higher than before grouping  and age (≥60 and <60). The results of the subgroup analysis revealed that after grouping, G>A polymorphism rs8192678 remained uncorrelated to susceptibility to T2DM (grouping . In the grouping .2.4P=0.059).As shown in 3PPARGC1A is a highly conservative transcriptional co-activator, which is abundant in metabolic active tissues, such as the liver, fat, pancreas and muscles. It plays a role in regulating energy metabolism in the wholePPARGC1A gene rs8192678 is correlated to susceptibility to T2DM, the relative risk of obesity and insulin resistance, and lower β-cell function index [PPARGC1A gene G>A polymorphism rs8192678 and susceptibility to T2DM has gradually become a focus of attention. However, there were inconsistencies in these studies. The results of the present meta-analysis revealed that in non-grouped populations, Pheterogeneity=0.000. In the allele model, OR=1.249, 95% CI: 1.099-1.419, P= 0.001, and Pheterogeneity=0.000. In the dominant inheritance model, OR=1.364, 95% CI: 1.152-1.614, P=0.000, and Pheterogeneity=0.000. In the recessive inheritance model, OR=1.187, 95% CI: 1.021-1.381, P=0.026, and Pheterogeneity=0.077.body. The single nucleotide variation of the P=0.005, and Pheterogeneity=0.006. These results reveal that the A allele of the PPARGC1A gene rs8192678 locus is susceptible to T2DM. Since the heterogeneity among studies was high, subgroup analysis was carried out based on the ethnicity of the population. The results suggest that the A allele was associated with the incidence of T2DM in Western Asian, South Asian, European and African populations (P<0.05), but was not associated with T2DM in East Asian population (P>0.05). The meta-analysis of Yang et al showed a significant association for this locus and T2DM in the Indian population  [P<0.001) [PPARGC1A and PPARGC1B, and suggested that they have different regulatory functions on glucose and fat oxidation in muscle cells. The authors suggested that this could provide an explanation by which an environmental trigger (age) modifies genetic susceptibility to T2DM. Heterogeneity at ages greater than 60 years may be related to environmental factors.In the additive inheritance model, OR=0.828, 95% CI: 0.726-0.945, www.internationalgenome.org/1000-genomes-browsers/) Another possibility is about the linkage disequilibrium (LD). In LD-based indirect correlation analysis, if a disease-causing locus and genetic markers  have strong LD, then it can be compared to normal individuals by comparing genetic markers. Differences ultimately lead to the relative risk of disease-causing loci in the disease. If LD between the SNP and the causal loci is weaker in East Asian than in South Asian or Europeans, it may lead to a weaker association which may not be detected [An interesting aspect is the A allele frequency in the East Asian populations is 44%, more than 15% in relation to South Asian, 8% of the European population and more than 39% of the African population. This may be due to the fact that this variant does not influence T2DM due to adaptive issues  the T2DM diagnosis was drawn in most of the included studies, according to the Diagnostic Criteria of Diabetes published by the World Health Organization (WHO), but this was drawn according to the Diagnostic Criteria of Diabetes published by the American Dental Association (ADA) in some studies, which may result in some differences among patients who were included in these studies; (2) merely the PPARGC1A gene G>A polymorphism rs8192678 may increase the risk of T2DM in Western Asian, South Asian, European, and African populations, while this was not correlated to susceptibility to T2DM in the East Asian population. Taking into account that the occurrence of T2DM is the result of the combined action of genetic and environmental factors, and some limitations in the present study, the exact conclusions need to be further verified through large sample case-controlled or prospective clinical studies.In summary,


Pregnancy-associated breast cancer (PABC) is defined as breast cancer that is diagnosed during pregnancy and/or the postpartum period. Definitions of the duration of the postpartum period have been controversial, and this variability may lead to diverse results regarding prognosis. Moreover, evidence on the dose-response association between the time from the last pregnancy to breast cancer diagnosis and overall mortality has not been synthesized.We systematically searched PubMed, Embase, and the Cochrane Library for observational studies on the prognosis of PABC published up to June 1, 2019. We estimated summary-adjusted hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). Subgroup analyses based on diagnosis time, PABC definition, geographic region, year of publication and estimation procedure for HR were performed. Additionally, dose-response analysis was conducted by using the variance weighted least-squares regression (VWLS) trend estimation.P < 0.001). Compared to nulliparous women, the mortality was almost 60% higher in women with PABC diagnosed at 12 months after the last delivery , and the mortality was not significantly different at 70 months after the last delivery . This finding suggests that the definition of PABC should be extended to include patients diagnosed up to approximately 6 years postpartum (70 months after the last delivery) to capture the increased risk.A total of 54 articles (76 studies) were included in our study. PABC was associated with poor prognosis for overall survival (OS), disease-free survival (DFS) and cause-specific survival (CSS), and the pooled HRs with 95% CIs were 1.45 (1.30–1.63), 1.39 (1.25–1.54) and 1.40 (1.17–1.68), respectively. The corresponding reference category was non-PABC patients. According to subgroup analyses, the varied definition of PABC led to diverse results. The dose-response analysis indicated a nonlinear association between the time from the last delivery to breast cancer diagnosis and the HR of overall mortality (This meta-analysis suggests that PABC is associated with poor prognosis, and the definition of PABC should be extended to include patients diagnosed up to approximately 6 years postpartum. Breast cancer is the second most common cancer worldwide and the most commonly occurring malignancy in women . Due to Pregnancy itself may temporarily increase the risk of developing breast cancer, although it has a long-term protective effect on the development of breast cancer , 12. HowThis meta-analysis was performed in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. We did our best to include studies published to date regarding the prognosis of PABC. Eligible studies were found by searching PubMed, Embase, and the Cochrane Library for relevant reports published before June 1, 2019. The keywords used for the search were (“pregnan*” OR “gestation*” OR “childbirth” OR “postpartum” OR “parity”) AND “breast” AND (“cancer” OR “neoplasia” OR “carcinoma”). The references lists of all retrieved articles and previous systematic reviews were manually searched.All eligible studies met the following criteria: (1) observational prognostic studies with a follow-up period longer than 6 months; (2) participants were diagnosed with breast cancer by clinical diagnosis and/or histologically; (3) the case group was diagnosed with PABC, and the control group was non-PABC or nulliparity; (4) the outcomes were in terms of overall survival (OS), disease-free survival (DFS) or cause-specific survival (CSS); and (5) the risk point estimate was reported as an HR with 95% CI, or the data were presented such that an HR with 95% CI could be calculated. The exclusion criteria were as follows: (1) duplicated or irrelevant articles; (2) reviews, letters, and case reports; (3) non-human studies; and (4) studies with inappropriate data for meta-analysis, such as incomplete or inconsistent data.Two reviewers extracted the data independently using a predefined data extraction form. Any disagreements were resolved by discussion. The extracted data included the first author, publication year, country, PABC definition, control definition, sample size, cancer type, stage or grade, age, matching criteria, adjusted variables, and adjusted HRs with 95% CIs.The methodological quality of the studies was assessed by the Newcastle-Ottawa scale (NOS) . A score2) test was performed to assess the impact of study heterogeneity on the results of the meta-analysis. If severe heterogeneity was present at I2 > 50%, a random effects model was chosen; otherwise, a fixed effects model was used. Visual inspection of the funnel plot and Egger’s and Begg’s tests were performed to assess publication bias. Subgroup analyses were performed according to the diagnosis time, PABC definition, geographic region, year of publication and estimation procedure for HR.We used adjusted HRs and 95% CIs, which are most appropriate for time-to-data events. If HRs were not reported, we estimated HRs from the raw data or Kaplan-Meier curves . The I-sP < 0.05 was considered significant.Variance-weighted least squares regression (VWLS) model was used to evaluate the dose-response association between the time from the last pregnancy to breast cancer diagnosis and HR of overall mortality . RestricWe initially identified 12,414 articles and screened their titles and abstracts . The subgroup analysis according to different follow-up durations  had similar results to the overall analysis . There was significant heterogeneity . The subgroup analysis according to different follow-up durations  had similar results as the overall analysis . There was no significant heterogeneity . The subgroup analysis (5-year CSS) had similar results as the overall analysis . There was no significant heterogeneity . The nonlinear spline showed a decreasing trend. Compared to nulliparous women, the mortality was almost 60% higher in women with PABC diagnosed at 12 months after the last delivery , and the mortality was not significantly different at 70 months after the last delivery  .As shown in Fig. We reviewed and meta-analyzed the existing scientific literature on the prognosis of PABC to draw a powerful conclusion that PABC is associated with a poor prognosis. Our results are consistent with those of the previous meta-analysis conducted in 2016 . HoweverThere are two explanations that may account for the results. On the one hand, mammary gland involution following pregnancy has been suggested to explain the poor prognosis . Breast To the best of our knowledge, this is the first dose-response meta-analysis providing comprehensive insights into the association between the time from the last pregnancy to breast cancer diagnosis and the overall mortality of PABC. The scientific value of dose-response meta-analyses is higher than meta-analyses with exposure classified as two categories , 76. ThrThe present meta-analysis has the following limitations that must be taken into account. First, if HRs and 95% CIs were not directly reported in the included studies, we estimated HRs from the crude data or Kaplan-Meier curves. This may cause bias without adjustment. However, we performed subgroup analysis based on the estimation procedure for HR. This analysis consistently showed a worse prognosis for women with PABC than for those with non-PABC. Second, the meta-analysis was based on data from observational studies; although most of the included studies adjusted for several relevant confounders , residual confounding by other potential factors cannot be ruled out. Third, high between-study heterogeneity is another limitation of the current meta-analysis. This was likely due to significant differences in the sample sizes, definitions of PABC and/or treatment interventions. Last, the language of the studies was limited to English, which may result in potential language bias.In summary, this meta-analysis suggests that PABC is associated with a poor prognosis for OS, DFS and CSS compared to non-PABC cases. The definition of PABC should be extended to include patients diagnosed up to approximately 6 years postpartum to capture the increased risk of death. Further long-term prospective cohort studies with larger sample sizes should be conducted to validate this article’s findings.


Evidence for the association between chocolate intake and risk of chronic diseases is inconclusive. Therefore, we aimed to synthesize and evaluate the credibility of evidence on the dose-response association between chocolate consumption with risk of all-cause mortality, coronary heart disease (CHD), stroke, heart failure (HF), type 2 diabetes (T2D), colorectal cancer (CRC), and hypertension.Prospective studies were searched until July 2018 in PubMed, Embase, and Web of Science. Random-effects meta-analyses comparing highest versus lowest intake categories, linear, and non-linear dose-response analyses were conducted. The credibility of evidence was evaluated with the NutriGrade scoring-system.n = 2 for all-cause mortality, n = 9 for CHD, n = 8 for stroke, n = 6 for HF, n = 6 for T2D, n = 2 for hypertension and CRC, respectively). No associations with HF  and T2D  per each 10 g/day increase in chocolate intake were observed in the linear dose-response meta-analyses. However, a small inverse association for each 10 g/daily increase could be shown for the risk of CHD , and stroke . The credibility of evidence was rated either very low  or low .Overall, 27 investigations were identified  contains supplementary material, which is available to authorized users. Cocoa, mostly consumed as chocolate in Western countries, is rich in various bioactive compounds such as flavanols including catechins, epicatechin, and proanthocyanidins as well theobromine . The flaDiet is recognized as a modifiable risk factor for NCD and a change in dietary behaviour is a cornerstone for disease prevention . HoweverPrevious meta-analyses of prospective studies have shown that chocolate intake is associated with decreased risk of coronary heart disease (CHD), T2D, heart failure (HF), and stroke –9. MoreoThe review was registered in PROSPERO International Prospective Register of Systematic Reviews (ID: CRD42016037069). The methodological procedure for conducting this review was based on a previously published protocol , that waLiterature search was performed until July 2018 to identify relevant articles in the electronic databases PubMed, Embase (Ovid), and Web of Science. Full search strategies for all three sources are listed in ESM Material 1. Citation lists from retrieved articles, systematic reviews, and meta-analyses were searched for additional studies. Moreover, we searched Google Scholar for articles citing or associated with included articles, which could meet the inclusion criteria. Two authors  conducted the literature search, while any uncertainty was resolved by consensus of third reviewer (HB).Studies were included in the systematic review and meta-analysis if they (1) were cohorts, case–cohorts, case–control nested in cohort studies, as well as follow-ups of randomized controlled trials; (2) investigated the association between chocolate consumption with risk of all-cause mortality, CHD, stroke, heart failure, CRC, T2D, or hypertension in adults (aged ≥ 18 years). Corresponding chronic diseases were defined using information from previously published meta-analyses –19.Two authors  screened and extracted the following data independently: first author’s name, year of publication, country, study name, study design, baseline age of participants, sex, sample size, number of cases, dietary assessment method, outcome, outcome assessment method, quantity of chocolate intake, multivariable effect estimate with corresponding 95% confidence intervals (CIs), and covariates. If only separate estimates for male and female participants were reported in a study, the risk ratios (RRs) were pooled using a fixed-effect model.For high versus low and dose-response comparisons, we applied a random-effects model to derive pooled RRs and 95% CIs , summariIf studies reported only the total number of cases or person-years and the exposure was defined in categories, we obtained the number of person-years or cases in each category by dividing the total number of person-years/cases per number of reported categories, as it was previously described . The medThe dose-response was expressed as 10 gram/d of chocolate. If a study did not provide information on the amount of chocolate per serving, 28.5 g/d (1 oz.) were used as serving size .If more than three categories of exposure were provided by a study, restricted cubic splines were calculated to explore possible non-linear associations. Three fixed knots were used through the total range of the reported intake at 10%, 50%, and 90% and combined using multivariate meta-analysis .Q test and the I2 statistic were used. A value for the I2 statistic greater than 50% was considered as potentially important statistical heterogeneity [To explore heterogeneity between studies, the Cochran ogeneity . SubgrouAccording to the Cochrane Handbook, we explored potential small-study effects such as publication bias using Egger´s test and funnel plots, if 10 or more studies were available . StatistTo evaluate the credibility of evidence for the association between chocolate consumption and risk of all-cause mortality, CHD, stroke, heart failure, T2D, CRC, and hypertension, a recently developed NutriGrade scoring system was implemented (max 10 points). This tool is based on the following criteria for prospective studies: (1) risk of bias, study quality, study limitations (up to 2 points), (2) precision (up to 1 point), (3) heterogeneity (up to 1 point), (4) directness (up to 1 point), (5) publication bias (up to 1 point), (6) funding bias (up to 1 point), (7) effect size (up to 2 points), and (8) dose-response (up to 1 point) . The folOut of the 287 records identified by the literature search, 47 full-text articles were assessed in detail , and 27 were included in the meta-analysis as they reported on chocolate consumption and at least one of 7 diseases .Two prospective observational studies were included for all-cause mortality , 29, 9 rI2 = 0%, pheterogeneity = 0.44) when comparing extreme categories . Due to the limited availability of data, it was not possible to conduct any further meta-analyses.Two studies with 11,596 death cases were included in the highest versus lowest intake category meta-analysis . No association between all-cause mortality and chocolate intake was observed   and HF  , whereas an inverse association was observed for risk of stroke  .Nine prospective observational studies with 21,294 CHD cases, eight studies with 11,949 stroke cases, and 6 studies with 4606 HF cases, were included in the highest versus lowest intake category meta-analysis (range of intake 0–46.1 g/d). Comparing categories of highest versus lowest intake of chocolate intake, we observed no association with risk of CHD  , but was inversely related with risk of CHD   and stroke  .Similarly, an increase in chocolate intake by 10 g per day was not associated with risk of HF . However, in the subgroup analysis considering geographic location, CHD and stroke showed an inverse association in European studies, but not in US studies.pnon-linearityp = 0.07, n = 8 studies) and stroke  and significance for HF  . The risk of CHD and stroke decreased by approximately 7–8% with increasing intake of chocolate up to ~ 20 g/d, with no further risk decreasing association above this intake level. The risk of HF decreased by approximately 14% with increasing intake of chocolate up to ~ 12 g/d, and a trend for a risk increasing association was observed with intakes > 35 g/d .The non-linear dose-response analyses showed a borderline significance for CHD  comparing extreme categories . A linear increase in chocolate intake by 10 g per day was not associated with risk of T2D  .Six studies with 21,758 incident T2D cases were included in the meta-analysis comparing extreme intake categories (range of intake 0–35.4 g/d). We observed an inverse association between risk of T2D and chocolate consumption .pnon-linearity = 0.002, n = 6 studies). The risk of T2D decreased by approximately 8% with increasing intake of chocolate up to ~ 10 g/d, and a trend for a risk increasing association was observed with intakes > 30 g/d .There was a non-linear dose-response trend  when comparing extreme categories . Due to the limited availability of data it was not possible to conduct linear and non-linear dose-response meta-analyses.Only 2 studies with 1368 incident colorectal cancer cases were identified (range of intake 0–10.7 g/d). No association between colorectal cancer and chocolate intake was observed  when comparing extreme categories . Due to the limited availability of data, it was not possible to conduct linear and non-linear dose-response meta-analyses.Only 2 studies with 9530 incident hypertension cases were identified (range of intake 0–18 g/d). No association between hypertension and chocolate intake was observed . Overall, there is very low or low confidence in the effect estimate, and the evidence is (very) limited and uncertain.The present systematic review and meta-analysis examined the association between chocolate intake and risk of all-cause mortality, CHD, CRC, HF, hypertension, stroke, and T2D using data from 27 prospective studies, including more than 1 million participants. For stroke, we found a high versus low risk gradient coupled with a linear dose-response relation, and with some indication of non-linearity of the relation. For CHD, we found no significant high versus low gradient, but a linear dose-response and also an indication of non-linearity of the relation. For HF and T2D, we found also a high versus low risk gradient but coupled with a non-linear dose-response relation. Interestingly, the non-linear analyses indicated an increased risk with consumption above 20–30 g/d for HF. For all-cause mortality, CRC, and hypertension we found no associations. However, the credibility of evidence assessed with the NutriGrade tool did not exceeded the grade low for CHD and stroke, and very low for the other endpoints.Previous meta-analyses focused predominantly on CVD , 54–57 aRegarding T2D, we found a 13% lower risk when comparing high and low chocolate consumption and a clear non-linear association suggesting lowest risk when consuming 10 g/d of chocolate and no association when the amount consumed exceeds 30 g/d. Similarly to the findings of HF, the credibility of evidence for T2D is very low.Our meta-analysis is the first summarizing the evidence between chocolate consumption and risk of hypertension as well as CRC. In both cases no associations were observed. Results on risk of all-cause mortality were in line with previous data, showing no association with chocolate intake .There are several mechanisms which are proposed to explain the link between chocolate and health effects. Polyphenols including flavanols such as catechin, epicatechin and polymeric proanthocyanidins are main bioactive substances found in cocoa extracts . Cocoa cChocolate is an energy-dense food and contains a relatively high amount of saturated fat and added sugar . An incrDue to the high energy density of chocolate, adjustment for energy intake is a reasonable approach to exclude potential cofounding . HoweverThere is evidence that the link between health outcomes and chocolate consumption might differ depending on the type of chocolate consumed . Dark chSeveral limitations should be considered when interpreting the results of the present meta-analysis. Most of the included studies assumed a constant intake of chocolate using intake assessed at baseline. None of the identified studies distinguished between intakes of dark and milk chocolate. Moreover, some studies estimated chocolate intake including chocolate sweets, snacks, milk or general confectionery , 47, 49;Strengths of this meta-analysis are the inclusion of prospective studies only, usage of multiple meta-analytical comparisons to investigate high versus low, linear and non-linear dose-response relationships. Furthermore, we included conference abstracts and letters to the editor which published results from big and recognized cohort studies, not included in previous reviews. Additionally, we assessed credibility of evidence using the NutriGrade tool, which was rarely implemented in previous reviews and only for high versus low comparisons.Chocolate consumption is not related to risk of several chronic diseases, but could reduce risk of CHD and stroke. However, this finding is limited by low trust into such a conclusion, highlighting the uncertainty of health consequences of chocolate intake. Any discussion about the inclusion of small amounts of dark chocolate in food-based dietary guidelines need to consider this uncertainty. The presence of several methodological issues such as insufficient information on energy misreporting and type of chocolate should be taken into account in further prospective studies.Below is the link to the electronic supplementary material.Supplementary material 1 (PDF 521 KB)


KIR genes diversity in recurrent spontaneous abortion (RSA). The present paper is a meta-analysis of previous genetic association studies and our previous original study. The results showed that KIR3DL1 was a significantly protecting factor for RSA . KIR2DS2  and KIR2DS3  were significantly risk factors for RSA. For KIR2DS1 there was a high heterogeneity and publication bias. Briefly, the inhibitory gene KIR3DL1 was a protecting factor, and the activating genes KIR2DS2 and KIR2DS3 were risk factors for RSA. However, the effect sizes were not suitable. We suggest further studies on different causes of pregnancy loss, to find the role of KIR2DS1.Natural killer cells (NKs) are the most important cells in the fetomaternal immune tolerance induced through interaction of maternal killer-cell immunoglobulin-like receptors (KIR) and fetal human leucocyte antigens (HLA). Hence, we intend to perform a meta-analysis on the role of maternal  Recurrent spontaneous abortion (RSA) and pregnancy loss have different pathogeneses, consisting of genetic and chromosomal abnormalities , environKIR and HLA genes in human genome have loci (not locus), inherited as haplotypes. In addition, each gene in their loci is polymorphic. Thus, interaction of different KIR molecules with different HLA molecules results in different outcomes consisting of inhibitory and activating responses. KIR gene cluster is located on chromosome 19. This cluster has two types of genes, including 8 inhibitory and 6 activating genes, and 2 pseudogenes. Some of these genes exist in all individuals, like the KIR2DL4. From the viewpoint of medical anthropology, different people from different ethnicities have different KIR-HLA interactions . Usually CD56tory NKs . 2DL1, 2DL2, 2DL3, 2DL4, 2DL5, 3DL1, 3DL2 and 3DL3) and 6 activating genes . Since the involving NKs in implantation of embryo are maternal, we intend to perform a meta-analysis on the role of maternal KIR genes diversity in RSA. Previously, KIR. Nevertheless, their studies were few and therefore our study can serve as an update for that meta-analysis.As we mentioned above, KIR and HLA have different genes and interactions. KIR has 8 inhibitory , the odds ratios (OR) (effect sizes) achieved from these p values were underestimated. This statistical protocol has been previously published . The analyses were carried out through a 2I scale and 2I<50 was considered as homogeneity. In the cases of heterogeneity, we used the random-effect model. In order to find publication bias, we used funnel plots. If a study were to be find outside the funnel, it meant that its effect size was outside the expected 95% confidence interval (CI). In other words, its difference with other studies is statistically significant at p=0.05. Hence, a publication bias does not have necessarily a negative connotation. In the present study, a funnel plot p value < 0.05 means that the mentioned individual study is outside the funnel of 95% CI. We used the In order to cluster the studies for meta-analysis, we designed a dendrogram using the STATA14 software . This cluster analysis involved the complete linkage of binary variables . p values were analyzed through Yate's correction (or fisher's exact test when necessary). Positive effect directions show each gene as a risk factor and negative effect directions show each gene as a protecting factor. Our cluster analysis showed that the study by Dambaeva et al. (2016) had a different design in comparison to other studies . p value <0.05) (The role of e <0.05)  and 3. KIR2DL2 in RSA was not statistically significant . p value <0.05) . No publication bias was found based on the funnel plot . p value <0.05) (The role of e <0.05)  and 5. Tnel plot  and 7. Te <0.05)  and 9. KIR3DL1 in RSA was statistically significant . p<0.05; based on funnel plot) . Inconclusive publication bias was found for this analysis based on the funnel plot . Faridi et al. (2009) study showed significantly more risk effect of this gene in comparison to other studies  . p value <0.05) (The role of el plot)  and 11. nel plot  and 13. e <0.05)  and 15. e <0.05)  and 17. KIR2DS4 in RSA was not statistically significant . p value <0.05) . p value <0.05) . et al. (2009) showed significantly more protective and risk effect of this gene in comparison to other studies, respectively  (The role of e <0.05)  and 19. e <0.05)  and 21. e <0.05)  and 23. +CD56dim and CD16-CD56bright that are called as cytotoxic and immune-regulatory NKs, respectively. In the implantation site, the NKs are mainly CD56bright. Hence, the immune system has a positive and protecting role in implantation and early pregnancy. Embryo implantation and pregnancy are a type of transplantation called semi-allograft. Thus, we need immune tolerance to have a successful pregnancy. The NKs play their roles with their KIRs interacting with the HLAs expressed on trophoblasts , because its activating role  results in higher cytokine releasing of UNKs (AA genotype was a risk factor for the success of assisted reproduction. AA is the most inhibitory genotype and therefore it supports this hypothesis that NK activation is necessary in early pregnancy. Pregnancy loss has numerous causes, in particular embryo genetic and chromosomal abnormalities. Therefore, the immune system's theoretical role is to reject such malformed embryos. Therefore, this risky role of activating KIRs is in fact a protecting role! Of course, it is remarkable that the lack of genetic evaluation of the lost embryos was a limitation for the studies imported to this meta-analysis. It is suggested that this variable should be adjusted in future studies. The results of Although we found significant associations involving 3 genes in the meta-analysis , but theKIR gene diversity in RSA is still in unclear, although our meta-analysis showed 3 genes as associated factors. KIR3DL1 was a protecting factor, and KIR2DS2 and KIR2DS3, which proved to be risk factors for RSA. For KIR2DS1 there was a high heterogeneity. It seems that its role is different among different causes of pregnancy loss. Our previous case-control original investigation showed a significant relation with maternal KIR2DS1 in combination with paternal HLA-C2 as a risk factor. In order to clarify this role we have some suggestions for future studies, such as investigations of this combination concerning the success rate of assisted reproduction, for early first trimester abortions occurring after implantation and early placentation, for stillbirth groups, for abortions secondary to APS, and for successful and unsuccessful pregnancies of malformed embryos and fetuses. We would also like to suggest adjusting models and cohort studies. The role of maternal


Differences in epidemiological and clinical patterns of lung adenocarcinoma have been described between male and female patients. Our study aimed to assess the molecular mechanisms underlying those differences through functional profiling and meta-analysis of lung adenocarcinoma expression datasets. We discovered an overrepresentation of terms related to acute inflammatory responses in female patients, suggesting an increase in certain cell populations, such as T CD8+ cells, and in interleukin production. We also identified purinergic signaling and lipid metabolism as relevant upregulated functional groups in female lung adenocarcinoma samples. Overall, we identified molecular processes and pathways that will aid the understanding of the differential clinical patterns described in lung adenocarcinoma in male and female patients and provide new pathways for the discovery of novel biomarkers and therapeutic targets.While studies have established the existence of differences in the epidemiological and clinical patterns of lung adenocarcinoma between male and female patients, we know relatively little regarding the molecular mechanisms underlying such sex-based differences. In this study, we explore said differences through a meta-analysis of transcriptomic data. We performed a meta-analysis of the functional profiling of nine public datasets that included 1366 samples from Gene Expression Omnibus and The Cancer Genome Atlas databases. Meta-analysis results from data merged, normalized, and corrected for batch effect show an enrichment for Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to the immune response, nucleic acid metabolism, and purinergic signaling. We discovered the overrepresentation of terms associated with the immune response, particularly with the acute inflammatory response, and purinergic signaling in female lung adenocarcinoma patients, which could influence reported clinical differences. Further evaluations of the identified differential biological processes and pathways could lead to the discovery of new biomarkers and therapeutic targets. Our findings also emphasize the relevance of sex-specific analyses in biomedicine, which represents a crucial aspect influencing biological variability in disease. Lung cancer is the most frequently diagnosed cancer and the leading cause of cancer-related death worldwide, representing 18.4% of all cancer deaths ,3; howevLung cancer exhibits sex-based disparities in clinical characteristics and outcomes, with better survival observed in women ,6,7. WhiAdenocarcinoma represents the most frequent non-small cell lung cancer (NSCLC) subtype in both sexes , with a We performed a meta-analysis based on functional profiles of transcriptomic studies to explore the molecular mechanisms underlying sex-based differences in early-stage lung adenocarcinoma. We carried out exhaustive review and selection steps to guarantee the homogeneity of the selected studies and the subsequent comparison and integration of the data in the meta-analysis with an appreciation of this strategy’s specific limitations. After the systematic review, we retrieved and analyzed nine studies from Gene Expression Omnibus (GEO)  and The We organized our findings into three sections: the first describes the studies evaluated and selected in the systematic review; the second section reports on the results of the bioinformatic analysis of each of these selected studies as follows: (i) exploratory analysis, (ii) differential expression, and (iii) functional characterization; while the third section presents the results of the differential functional profiling by sex.The systematic review identified 207 non-duplicated studies, of which 48.8% included both male and female patients . We applAs the normalized data derives from different platforms, we performed exploratory and processing steps for the data set to ensure the comparability and integration of subsequent analyses. The exploratory analysis found a lack of abnormal behavior except for three samples in the principal component analysis (PCA) and unsupervised clustering; therefore, we excluded the GSM47570 and GSM47578 samples in study GSE19188, and the GMS773784 sample in study GSE31210 from further analysis.The differential expression results for each study demonstrated a large number of differentially expressed genes when comparing female lung adenocarcinoma samples to female control samples and male adenocarcinoma samples to male control samples . HoweverWe performed an individual functional enrichment analysis of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) to identify the possible implications of these sex-specific differentially-expressed genes in pathways relevant to lung adenocarcinoma. The identified pathways revealed a diversity of significant results among datasets, which we have summarized in We performed a functional meta-analysis for each of the 8672 GO functions and KEGG pathways, including every term found in at least two studies. Results with a false discovery rate (FDR) of <0.05 included 106 GO biological processes (BP), 3 GO molecular functions (MF), and 20 KEGG pathways, which were associated with 21 wider functional groups. We rejected potential bias on the significant results after the inspection of funnel plots; furthermore, sensitivity analyses failed to indicate alterations in the results due to the inclusion of any study. The results for the 129 significant GO terms and KEGG pathways are further detailed in We discovered that 43.88% of detected functions related to the immune response , which aWe also uncovered evident sex-based differences in cell metabolism. Studies have shown the significant upregulation of lipid metabolism (ceramide and sphingolipid biosynthetic processes) in females and the higher utilization of carbohydrates by males ,36. FurtIt should be noted that 23.26% of the significant functions exhibited lower activity in female compared to male lung adenocarcinoma patients. Downregulated functional groups include those related to cell cycle progression, cell junctions, DNA repair and telomere protection, mitochondrial processes, neural development, post-translational changes, post-transcriptional changes, protein degradation, and transcription regulation . Taken thttps://bioinfo.cipf.es/metafun-nsclc) contains information related to the nine studies and 1329 samples involved in this study. For each study, this resource includes fold-changes of genes and LOR of functions and pathways that users can explore to identify profiles of interest. The Metafun-NSCLC web tool  and graphical representations by function as forest and funnel plots. This open resource hopes to contribute to data sharing between researchers, the elaboration of innovative studies, and the discovery of new findings.We carried out a total of 8672 meta-analyses. For each of the 129 significant functions and pathways, Metafun-NSCLC depicts the global activation level for all studies and each study’s specific contribution using statistical indicators  and experimental design . The final inclusion criteria were:Finally, normalized gene expression data of six array NSCLC datasets  and counts matrix of three RNA-seq NSCLC datasets  were retrieved.Individual transcriptomics analysis consisted of three steps: pre-processing, differential expression analysis, and functional enrichment analysis a.edgeR [2 transformed the matrices when necessary. Annotation from probe set to Entrez identifiers from the National Center for Biotechnology Information [biomaRt [Data pre-processing included the standardization of the nomenclature of the clinical variables included in each study, normalization of RNA-seq counts matrix, and exploratory analysis. RNA-seq counts were pre-processed with the edgeR  R packagedgeR . We asseormation  database[biomaRt  R packaglimma [limma linear model to reduce its impact on data. p-values were calculated and corrected for FDR [Differential expression analyses were performed using the limma  R packag for FDR . This comdgsa [p-values were, again, corrected for FDR. For functional annotation, two functional databases were used: the KEGG Pathway database [Functional enrichment analyses were performed using the Gene Set Enrichment Analysis (GSEA) implemented in the mdgsa  R packagdatabase  and GO [database . GO termdatabase  , which is freely accessible to any user and allows the confirmation of the results described in this manuscript and the exploration of other results of interest.All data and results generated in the different steps of the meta-analysis are available in the Metafun-NSCLC web tool  Summary of analysis results in each phase. Then, for each of the studies, the detailed results of the (2) exploratory analysis, (3) differential expression, and (4) functional profiling. The user can interact with the web tool through graphics and tables and search for specific information for a gene or function. Finally, Section (5) provides several indicators for the significant functions identified in the meta-analysis that inform whether they are more active in men or women. Sex-based molecular differences may influence the incidence and outcome of lung adenocarcinoma and, therefore, may have important clinical implications. We identified immune responses, purinergic signaling, and lipid-related processes as the main biological processes altered between male and female lung adenocarcinoma patients by a meta-analysis of transcriptomic datasets. Said processes exhibit increased activity in female lung adenocarcinoma patients, whereas other processes (such as DNA repair) are more active in male lung adenocarcinoma. Although further studies are required to verify and fully explore these findings, our results provide new clues to understand the molecular mechanisms of sex-based differences in lung adenocarcinoma patients and new perspectives regarding the identification of biomarkers and therapeutic targets.