Particularly, compared with endotype A infants, endotype B infants—who are characterized by a high proportion of IgE sensitization and rhinovirus coinfection, S. pneumoniae/M. catarrhalis codominance, and high IFN-α and -γ response—had a significantly higher risk for developing asthma . Our findings provide an evidence base for the early identification of high-risk children during a critical period of airway development.Respiratory syncytial virus (RSV) bronchiolitis is not only the leading cause of hospitalization in U.S. infants, but also a major risk factor for asthma development. While emerging evidence suggests clinical heterogeneity within RSV bronchiolitis, little is known about its biologically-distinct endotypes. Here, we integrated clinical, virus, airway microbiome (species-level), transcriptome, and metabolome data of 221 infants hospitalized with RSV bronchiolitis in a multicentre prospective cohort study. We identified four biologically- and clinically-meaningful endotypes: A) clinical Respiratory syncytial virus (RSV) bronchiolitis during infancy is a major risk factor for asthma development. Here, Raita et al. integrate clinical data with airway microbiome, transcriptome, and metabolome data and identity four endotypes with differential risks for developing asthma. In addition to the substantial acute morbidity, ~30% of infants hospitalized for bronchiolitis (“severe bronchiolitis”) subsequently develop asthma in childhood2. Of the major causative pathogens, respiratory syncytial virus (RSV) infection during infancy has the largest population attributable fraction in asthma development 3.Bronchiolitis is the leading cause of hospitalization in U.S. infants, accounting for ~110,000 hospitalizations with the direct cost of $734 million annually2, emerging evidence suggests heterogeneity in clinical presentations4 and chronic morbidities 6. Growing evidence also suggests distinct upper airway microbiome8, transcriptome9, cytokine11, and metabolome12 profiles among infants with bronchiolitis. However, these findings have been solely derived from single-level  data. Understanding the complex interplay among the host, respiratory viruses, airway microbiome, and subsequent chronic morbidities of bronchiolitis involve several major challenges—e.g., identification of the responsible mechanisms , the effect of clinical factors reflecting multi-level environmental relations, and heterogeneity of bronchiolitis itself. To our knowledge, no study has integrated clinical, virus, and multi-omics data to investigate the endotypes of RSV bronchiolitis and their longitudinal relations with chronic morbidities in childhood. Our still limited understanding of the heterogeneity of RSV bronchiolitis during infancy—an important period of lung development—has hindered efforts to develop endotype-specific RSV bronchiolitis treatment and asthma prevention strategies in this large patient population with substantial morbidity burden.While bronchiolitis has been considered a single disease with similar mechanismsclassicmicrobiomeM. nonliquefaciensinflammationIFN-intermediate, (B) clinicalatopicmicrobiomeS. pneumoniae/M. catarrhalisinflammationIFN-high, (C) clinicalseveremicrobiomemixedinflammationIFN-low, and (D) clinicalnon-atopicmicrobiomeM.catarrhalisinflammationIL-6. Specifically, the endotype B characterized by a high proportion of parental asthma, immunoglobulin E (IgE) sensitization, and rhinovirus coinfection, S. pneumoniae/M. catarrhalis codominance, and high IFN-α and -γ response had the highest risk for developing asthma by age 5 years.To address this knowledge gap in the literature, analyzing data from a multicentre prospective cohort, we sought to 1) identify biologically distinct RSV bronchiolitis endotypes through applying integrative network and clustering approaches to clinical, virus, nasopharyngeal airway microbiome, transcriptome, and metabolome data and to (2) investigate the association of the derived endotypes with chronic morbidity outcomes (recurrent wheeze by age 3 years and asthma at age 5 years)  study. This prospective cohort study completed enrollment of 1016 infants (age < 1 year) hospitalized with bronchiolitis at 17 sites across 14 U.S. states. Of these 1016 infants , 921 (91%) completed the run-in procedure  and comprise the MARC-35 longitudinal cohort. Of the infants enrolled into this longitudinal cohort, this study included 221 infants with RSV bronchiolitis who were randomly selected for the nasopharyngeal microbiome, transcriptome, and metabolome testing , both the average silhouette score and the network modularity were highest with k = 4 , B) clinicalatopicmicrobiomeS. pneumoniae/M. catarrhalisinflammationIFN-high (28.5%), C) clinicalseveremicrobiomemixedinflammationIFN-low (28.5%), and D) clinicalnon-atopicmicrobiomeM. catarrhalisinflammationIL-6 (23.5%)  rmediate 9.5%, B) rmediate 9.5%, B) -RSV infection), higher abundance of M. nonliquefaciens, and intermediate IFN-α and -γ response  response profile  had a significantly higher risk of developing asthma by age 5 years  and each of the other endotypes. Compared with endotype A infants, endotype B infants  and highest-risk (endotype B) groups, we compared the nasopharyngeal microbiome, transcriptome, and metabolome in both individual and integrated manner. For example, compared with endotype A infants, endotype B infants had a higher abundance of P = 0.006; Supplementary Table P = 0.051; Supplementary Table P = 0.012; Supplementary Table S. pneumoniae, M. catarrhalis). In addition, the differential gene expression analysis demonstrated that, compared to endotype 1 (which is concordant with endotype A), endotype 2 (which is concordant with endotype B) infants also had upregulated IFN-γ and NFκB pathways , those with endotype B—characterized by a high proportion of parental asthma, IgE sensitization, and rhinovirus coinfection, 5. Similarly, studies have also reported the association of unique airway microbiome profiles with the risk of recurrent wheeze and childhood asthma. Indeed, research has shown the pathogenic role of Streptococcus genus and S. pneumoniae in the upper airway—both among infants with or without bronchiolitis14—in the development of these chronic morbidities. However, the current literature has conflicting findings about the role of Moraxella genus in the infant airway, with higher Moraxella abundance associated with increased and decreased risk of developing asthma. In contrast to these earlier reports based on a culture-dependent method13 or 16S rRNA gene sequencing15, our study with the species-level resolution of microbiome structure revealed that the endotypes with distinct Moraxella species  exhibit differential risks of chronic morbidities. Research that examined the role of airway immune response in RSV bronchiolitis and its sequalae has also shown somewhat conflicting results—e.g., the associations of higher type-2/-17 cytokines10 or CCL-5 chemokine11 with higher risks of recurrent wheeze. Moreover, research has also suggested the role of metabolome—which represents the downstream functional products of the microbiome, child’s genetic make-up, and immune response—in the pathogenesis of bronchiolitis and asthma2. For example, a recent study of airway metabolome has shown differences in pro- and anti-inflammatory mediators  in infants with bronchiolitis12. These studies—while limited to single-level data —have discovered potential mechanisms that underlie the bronchiolitis–asthma link. The current study corroborates these earlier reports and extends them by identifying biologically meaningful RSV bronchiolitis endotypes that have differential risks of chronic morbidities.Recent studies have examined the potential mechanisms that link infant bronchiolitis to its health sequelae. For example, we previously reported that interactions between infecting virus and IgE sensitization in infants with bronchiolitis are associated with the risk of developing asthmaatopicmicrobiomeS. pneumoniae/M. catarrhalisinflammationIFN-high)—with subsequent chronic morbidities. Emerging evidence suggests that RSV infection increases the virulence of S. pneumoniae17 and induces type I IFN production by macrophages in S. pneumoniae infection18. Likewise, airway infection of mice by M. catarrhalis induces an inflammatory response with CD4+ T-cell-derived IFN-γ19. In addition, a recent study has shown that the higher types 1 and 3 IFN response of RSV-infected bronchial epithelial cells from children with asthma is correlated with the magnitude of airway obstruction, suggesting that an accelerated airway IFN response to RSV infection promotes the obstructive processes of lungs20. Furthermore, in an animal model of allergic asthma, there were synergistic effects of pneumovirus infection and allergic sensitization on type 1 IFN response21. In this study, the integrated analysis also demonstrated that endotype B had upregulated PI3K-Akt-mTOR-signaling pathway. The literature has shown its role in the pathobiology of asthma, including activating both innate and adaptive immunity, and airway remodeling22. PI3K inhibition not only reduces allergen-induced inflammation and hyperresponsiveness but also prevents the expression of IFN-γ-induced protein 10—a mediator released by virus-induced asthma22. Besides, both the PI3K-Akt-mTOR-signaling pathway and anti-inflammatory polyamines regulate the function of dendritic cells linking innate to adaptive immunity23. In conjunction with earlier studies, our data collectively suggest the integrated role of RSV infection, pathogenic bacteria , and IFN-α/-γ airway response in the development of asthma among infants at risk for atopy.There are several potential mechanisms linking the endotypes of RSV bronchiolitis—in particular endotype B , also plays a role in the pathobiology of both severe respiratory infection and asthma. In agreement with our study, research has previously shown the interrelations between RSV infection, M. catarrhalis, higher nasopharyngeal IL-6 level, and wheezing26. Notwithstanding the complexity of these mechanisms, the observed endotypes of RSV bronchiolitis and their longitudinal relations with chronic morbidities are important findings that could advance research into the development of endotype-specific strategies for bronchiolitis treatment and asthma prevention.In addition to endotype B, the identification of other endotypes such as endotype C—characterized by a high proportion of previous antibiotic use, higher bronchiolitis severity, mixed microbiome profile, and low IFN-α/-γ response—is also intriguing. Consistently, studies have reported the relations of early-life exposures to systematic antibiotics, airway dysbiosis, and higher asthma risk7 but also has the largest population attributable fraction in asthma development3. Second, bronchiolitis involves inflammation of the lower airways in addition to the upper airways. While our study is based on nasopharyngeal samples, studies have shown that upper airway sampling provides a reliable representation of the lung microbiome27 and transcriptome28 profiles. Furthermore, the use of upper airway specimens is preferable as bronchoscopy or other methods of lower airway sampling would be too invasive in young infants. Third, the nasopharyngeal samples were obtained at a single time point. While longitudinal molecular data are also important, the study objective was to identify endotypes of RSV bronchiolitis. Besides, even with single-time point data, we successfully identified biologically distinct endotypes that are longitudinally associated with chronic morbidities. Fourth, it is possible that asthma diagnosis (by age 5 years) is misclassified and that children are going to develop asthma at a later state. To address these points, the study sample is currently being followed longitudinally up to age 9 years. Fifth, this study did not have healthy “controls”. Yet, the study objective was not to evaluate the difference of endotypes from healthy infants but to define endotypes of RSV bronchiolitis. Sixth, the sample size of the present analysis is relatively smaller to the number of variables examined. This study should facilitate further validation research. Lastly, the study sample consisted of racially/ethnically- and geographically diverse infants hospitalized for bronchiolitis. While our sample had a large severity contrast, our inferences may not be generalizable to infants in ambulatory settings with mild-to-moderate bronchiolitis and warrant external and experimental validation. Nonetheless, our data remain relevant for the 110,000 infants hospitalized yearly in the U.S.1, a vulnerable population with a substantial morbidity burden.Our study has several potential limitations. First, we focused on infants with RSV bronchiolitis while other non-RSV viruses are also causative pathogens. However, RSV not only contributes to 75% of severe bronchiolitisS. pneumoniae/M. catarrhalis codominance, and high IFN-α and -γ response had the highest risk for developing asthma in later childhood. Considering the relatively small sample size of infants with severe RSV bronchiolitis in the present study, external validation is warranted. Regardless, our data lend significant support to the emerging concept that “bronchiolitis” represents several diseases with distinct biological mechanisms. For clinicians, our findings may provide an evidence base for the early identification of high-risk children during an important period of airway development—early infancy. For researchers, our data should facilitate further investigations into the development of endotype-specific strategies for bronchiolitis treatment and asthma prevention.In summary, by applying an integrated omics approach to data from a multicentre prospective cohort study of 221 infants with RSV bronchiolitis, we identified four biologically distinct and clinically meaningful endotypes. Specifically, the endotype characterized by a high proportion of parental asthma, IgE sensitization, and rhinovirus coinfection, With the exception of specimen collection , all study participants were evaluated and treated as usual and without regard to this observational study. Parent/legal guardians were approached about participating after the medical team had finished their assessments and stabilized the study participant. If necessary, the recruiting took place the morning after admission, but no later than 24 h after admission to the ward or intensive care unit. Samples and information of the participants were used to study the possible genetic causes of severe bronchiolitis, recurrent wheezing, asthma, and related concepts. The institutional review board at each of the participating hospitals approved the study. Written informed consent was obtained from the parent or guardian.7. MARC-35 is coordinated by the Emergency Medicine Network , an international research collaboration with 247 participating hospitals. Site investigators enrolled infants (age < 1 year) hospitalized with bronchiolitis at 17 sites across 14 U.S. states using a standardized protocol during three consecutive bronchiolitis seasons (from November 1 through April 30) during 2011–2014. The diagnosis of bronchiolitis was made according to the American Academy of Pediatrics bronchiolitis guidelines, defined as the acute respiratory illness with a combination of rhinitis, cough, tachypnoea, wheezing, crackles, or retraction29. We excluded infants with a preexisting heart and lung disease, immunodeficiency, immunosuppression, or gestational age of <32 weeks, history of previous bronchiolitis hospitalization, or those who were transferred to a participating hospital >24 h after initial hospitalization. Of 921 infants enrolled into the longitudinal cohort, the current analysis investigated 221 infants with RSV infection who were randomly selected for the nasopharyngeal microbiome, host transcriptome, and metabolome testing  studyts age <  year hos7. All data were reviewed at the EMNet Coordinating Centre , and site investigators were queried about missing data and discrepancies identified by manual data checks. In addition to the clinical data, nasopharyngeal airway samples were collected by trained site investigators using the standardized protocol that was utilized in a previous cohort study of children with bronchiolitis30. All sites used the same collection equipment  and collected the samples within 24 h of hospitalization. The nasopharyngeal airway specimens were immediately placed on ice and then stored at −80 °C. Frozen specimens were shipped in batches to Baylor College of Medicine  where they were tested for 17 respiratory viruses  using real-time polymerase chain reaction (RT-PCR) assays  for RNA sequencing (both transcriptome and metatranscriptome profiling) and to Metabolon  for metabolomic profiling32.Clinical data  were collected via structured interview and chart reviewsTotal RNA was isolated from the nasopharyngeal samples using Trizol LS reagent  in combination with the Direct-zol RNA Miniprep Kit . RNA quantity was measured with the Qubit 2.0 fluorometer ; its quality was assessed with the Agilent Bioanalyzer 2100  using the RNA 6000 Nano kit. Total RNA underwent DNase treatment using the TURBO DNA-free™ Kit  and rRNA reduction for both human and bacterial rRNA using NEBNext rRNA Depletion Kits . RNA was prepared for sequencing using the NEBNext Ultra II Directional RNA Library Prep Kit  and sequenced on an Illumina NovaSeq6000 using a S4 100PE Flowcell . All RNAseq samples had sufficient sequence depth  to obtain a high degree of sequence coverage.k-mers strategy in bbduck33 and default settings. We used PathoScope36 and the expanded Human Oral Microbiome Database (eHOMD) database37 to infer bacterial composition. Samples with <1000 reads, singletons, and strains not present in at least 10% of the samples were eliminated. The metatranscriptomic analysis obtained 1,968,352,599 merged sequences and identified 323 microbial lineages after singleton removal. The microbiome data are presented in Figs. Raw sequence reads were filtered and trimmed for adapters and contaminants using the 38 using the human transcriptome (hg38) and the mapping-based mode. We first generated a decoy-aware transcriptome and then quantified the reads using Salmon’s default settings and the following flags: –validateMappings, –recoverOrphans, –seqBias and –gcBias. Salmon is fast and accurate, corrects for potential changes in gene length across samples , and has great sensitivity. For the differential gene expression analysis, Salmon’s estimated transcript abundances were imported into DESeq2 using tximport39. The transcriptome data are presented in Fig. Transcript abundances from clean RNAseq reads were estimated in SalmonMetabolomic profiling used 125 μl of nasopharyngeal airway sample. All samples were blinded to Metabolon and processed in random order. The metabolic profiling used ACQUITY ultra-high performance liquid chromatography (UPLC)  and Q-Exactive high resolution/accurate MS interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution .41. In brief, recovery standards were added prior to the first step in the extraction process for quality control purposes. Proteins were precipitated with 500 μL of methanol added to 100 μL of the sample under vigorous shaking for 2 min  followed by centrifugation. The sample extract was dried then reconstituted in solvents compatible with each of the four methods. Each reconstitution solvent contained a series of standards at fixed concentrations to ensure injection and chromatographic consistency. One aliquot was analyzed using acidic positive ion conditions, chromatographically optimized for hydrophilic compounds. In this method, the extract was gradient eluted from a C18 column  using water and methanol, containing 0.05% perfluoropentanoic acid and 0.1% formic acid. Another aliquot was also analyzed using acidic positive ion conditions, but it was chromatographically optimized for hydrophobic compounds. In this method, the extract was gradient eluted from the same aforementioned C18 column using methanol, acetonitrile, water, 0.05% perfluoropentanoic acid, and 0.01% formic acid and was operated at an overall higher organic content. Another aliquot was analyzed using basic negative ion optimized conditions using a separate dedicated C18 column. The basic extracts were gradient eluted from the column using methanol and water, including 6.5 mM ammonium bicarbonate at pH 8. The fourth aliquot was analyzed via negative ionization following elution from a HILIC column  using a gradient consisting of water and acetonitrile with 10 mM ammonium formate, pH 10.8. The MS analysis alternated between MS and data-dependent MSn scans using dynamic exclusion. The scan range varied slightly between methods but covered 70–1000 m/z. Parameters for chromatography are summarized in Supplementary Table Sample preparation was carried out as described previouslym/z), preferred adducts, and in-source fragments as well as associated MS spectra, and curated by visual inspection for quality control using QUICS software42. Identification of known chemical entities was based on comparisons to metabolomic library entries of >3000 purified standards. Peaks were quantified using the area under the curve. The raw area counts for each metabolite in each sample were normalized to correct for variation due to instrument interday tuning differences by the median value for each run day, setting the median to 1.0 for each run. Missing values were imputed with the observed minimum for that particular compound.Metabolites were identified by automated comparison of the ion features in the experimental samples to a reference library of chemical standard entries that include retention time, molecular weight  samples generated from a pool from a small portion of each experimental specimen that served as technical replicate; 2) extracted water samples that served as process blanks; 3) samples of solvent used in extraction; and 4) a cocktail of standards spiked into every analyzed specimen that allowed instrument performance monitoring. The median relative standard deviation (RSD) for the standards that are added to each sample—a measure of instrument variability—was <5%. The metabolome data are presented in Figs.  extracte samples  a cockta5. The definition of asthma was based on a commonly used epidemiologic definition of asthma43—physician-diagnosis of asthma by age 5 years, plus either asthma medication use  or asthma-related symptoms in the preceding year. The definition of recurrent wheeze was, based on the 2007 U.S. asthma guidelines44, defined as having at least two corticosteroid-requiring exacerbations in 6 months or at least four wheezing episodes in 1 year that last at least 1 day and affect sleep.The primary outcome was asthma at age 5 years. The secondary outcome was the development of recurrent wheeze by age 3 years, stratified by asthma status to account for the heterogeneity of recurrent wheeze according to prior research45. The analytic workflow is summarized in Fig. 3—age, sex, birth weight, history of breathing problems, lifetime antibiotic use, parental asthma, immunoglobulin E (IgE) sensitization, positive pressure ventilation use, and virus data , virus genomic load [count])5. The breathing problem variable had missingness in 2 infants (0.9%) which were imputed by a random forest method using R missForest package46. For the microbiome data, we used the relative abundance of 40 most abundant species which accounted for 95% of total abundance. For the host transcriptome data, we selected 3000 transcripts with high variances after normalization and variance stabilizing transformation using DESeq2 package47. For the metabolome data, we selected 100 metabolites with high variances with adjusting for batch effects using sva package49 after log2 transformation. Then, we computed Gower distance for the clinical data using StatMatch package50, Bray–Curtis distance for the microbiome data using vegan package51, Pearson distance for the transcriptome data using amap package52, and Euclidian distance for the metabolome data using amap package52.In the current study, our aims are to identify biologically distinct RSV bronchiolitis endotypes (description [clustering]) and to relate them to outcome risks (association)53 using SNFtool package54. We set all parameters of similarity network fusion . Finally, to identify mutually exclusive endotypes, we conducted spectral clustering using fused affinity matrix. To choose the optimal number of endotypes, we chose the optimal number of endotypes by using a combination of the average silhouette scores , and clinical and biological plausibility. The network modularity measures how well separated subnetworks are given a particular partitioning  of the network55. To complement these approaches, we have also used a priori knowledge. Indeed, these derived endotypes are characterized by major clinical characteristics , major airway bacteria , and immune response profiles : (A) clinicalclassicmicrobiomeM. nonliquefaciensinflammationIFN-intermediate, (B) clinicalatopicmicrobiomeS. pneumoniae/M. catarrhalisinflammationIFN-high, (C) clinicalseveremicrobiomemixedinflammationIFN-low, and (D) clinicalnon-atopicmicrobiomeM.catarrhalisinflammationIL-6. These endotypes are consistent with earlier studies that individually investigated each of clinical57 and omics  data in infants with bronchiolitis. We conducted differential expression gene and functional pathway analyses by comparing the reference endotype with each of the other endotypes. We also computed the ranking of normalized mutual information (NMI) score of each variable. Each variable is ranked based on the similarity in the clustering of fused matrix, meaning that high-ranked variables contribute more to form the similarity network53. After deriving these endotypes, we visualized a patient similarity network with Fruchterman-Reingold layout using qgraph package59.To conduct integrated omics endotyping, we computed an affinity matrix of each dataset separately, and computed a fused affinity matrix by similarity network fusionbors n = 5, hyperpbors n = 5, hyperp60 for the chord diagram, VennDiagram package61 for the Venn diagram, and ComplexUpset package62 for the upset plot. Lastly, to visualize the between-endotypes differences in the clinical characteristics, viruses, selected microbiota species, and selected metabolites, we developed a heatmap assigning the mean value for clinical variables and viruses, microbiome, and metabolome data. The clinical variables and viruses are treated as numeric variables and processed by autoscaling. The microbiome data (20 most abundant species) are processed by log2 transformation and autoscaling. The metabolome data (30 highest NMI scores) are processed by autoscaling.We also conducted several analyses to examine the between-endotype differences in clinical and virus, microbiome, and metabolome data. First, we examined the between-endotype differences in the patient characteristics and clinical presentation by using Kruskal–Wallis, chi-squared, and Fisher exact tests, as appropriate. Second, to examined the relationship between major clinical variables and endotypes, we developed a chord diagram, Venn diagram of three major clinical variables  and their intersections, and an upset plot corresponding to the presented Venn diagram. We used circlize packageP values. To investigate whether genes for specific biological pathways are enriched among the large positive or negative fold changes, we conducted a functional class scoring analysis using fgsea package63. To detect biologically meaningful pathways by integrating host transcriptome and metabolome data, we also performed a Wilcoxon pathway enrichment analysis using the Integrated Molecular Pathway Level Analysis (IMPaLA) method64.For transcriptome data, we conducted differential gene expression analysis and functional pathway analysis by comparing the reference endotype (endotype A) with each of the other three endotypes. To visualize the differentially expressed genes for each of the comparisons, we used a volcano plot and created a heatmap using 300 genes with the smallest P values were two-tailed, with P < 0.05 considered statistically significant. We corrected for multiple testing using the Benjamini–Hochberg FDR method65.To determine the association of endotypes with the risk of childhood asthma (binary outcome), we fitted a logistic regression model. To examine the longitudinal relations of endotypes with the rate of recurrent wheeze outcome, we modeled the time to outcome development  by fitting a Cox proportional hazards model. Patients who did not have an outcome were censored at their last follow-up interview during the 36-month follow-up period. The proportionality of hazards assumption was verified through evaluating the Schoenfeld residuals. To examine the robustness of endotype-outcome associations, we also conducted a series of sensitivity analyses—(1) excluding infants with coinfection with rhinovirus, (2) using all variables from the full datasets, and (3) a different number of endotypes—and examined the between-endotype difference in the clinical, microbiome, transcriptome, and metabolome data for the major between-group comparison. We analyzed the data using R version 3.6.1 . All Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


To evaluate the efficacy of repetitive transcranial magnetic stimulation (rTMS) in improving lower limb spasticity after stroke.  The PubMed, Web of Science, Cochrane Library, EMBASE, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM) disc, China Science and Technology Journal Database (VIP), and Wanfang databases were searched online from their inception to May 2021 for randomized controlled trials (RCTs) involving repetitive transcranial magnetic stimulation for lower extremity spasticity after stroke. Valid data were extracted from the included literature, and the quality evaluation was conducted with the Cochrane Handbook for Systematic Reviews of Interventions along with the Physiotherapy Evidence Database scale . The data that met the quality requirements were systematically analysed using Review Manager 5.4 software. P = 0.02; MD = 6.14, 95% CI , P ＜ 0.00001), compared with control conditions. Low-frequency rTMS (LF-rTMS) significantly improved FMA-LE scores . However, there was no significant difference in FMA-LE scores when using high-frequency rTMS (HF-rTMS) (P > 0.1) and in TUG times (P > 0.1) between the treatment and control groups.  A total of 554 patients from seven articles (nine studies) were quantitatively analysed. Outcomes included the Modified Ashworth Scale (MAS), Fugl–Meyer Assessment of Lower Extremity (FMA-LE), Modified Barthel Index (MBI), and Timed Up and Go (TUG), measured as the effect of rTMS compared with controls conditions after treatment. The systematic review showed that rTMS reduced MAS and increased MBI scores, respectively (SMD = −0.24, 95% CI ,  rTMS was effective in improving spasticity and activities of daily living. LF-rTMS has positive clinical effects on enhancing motor function in patients who experience lower extremity spasticity after stroke. To better validate the above conclusions, more multicentre, high-quality, and double-blind randomized controlled trials are needed. Stroke is a common disease worldwide and causes serious disabilities for patients. More than two-thirds of stroke survivors develop poststroke sequelae that involve impairment of motor function, balance, gait, and activities of daily living , 2. PostWe performed a search in the PubMed, Web of Science, Cochrane Library, EMBASE, CNKI, CBM, VIP, and Wanfang databases published up to May 2021. The search terms were “stroke” OR “hemiplegia” OR “cerebrovascular accident” OR “ischemic stroke” OR “hemorrhagic stroke” OR “CVA” OR “apoplexy” AND “repetitive transcranial magnetic stimulation” OR “rTMS” OR “transcranial magnetic stimulation” OR “TMS” AND “spasticity” AND “lower limb” OR “lower extremity”.The relevant articles were selected based on the following eligibility criteria: (1) the involved patients were clinically diagnosed with lower limb spasticity after stroke by relevant examinations; (2) the experimental group used rTMS and traditional physical therapy, while the control group underwent traditional physical therapy plus sham rTMS ; (3) the outcome measures included the MAS, FMA-LE, MBI, and TUG; and (4) the included articles were RCTs.Articles meeting with the following criteria were excluded: (1) total sample size of fewer than 10 participants in each study; (2) study with incomplete data; (3) meta-analysis, case report, literature review, guidelines, dissertation, and others; and (4) non-RCTs.Two researchers independently searched and screened the literature based on the above search strategy and removed the studies that did not meet the predefined criteria by reading the abstracts and full texts. Any inconsistencies between the two authors were resolved by discussion or in consultation with the third author. The following data were extracted: study characteristics  and intervention details .The quality of the included articles was evaluated by two authors using the Cochrane Handbook for Systematic Reviews of Interventions  and PE-DX and Y axes and the corresponding parameters. A six-point scale  was denoted as the MAS scale [+ as 1.5. If the results were not presented as the means and standard deviations, we calculated the original data using SPSS 25.0 [Hmax/Mmax), the mean difference (MD) or the standardized mean difference (SMD) with 95% CI were calculated for the outcome. The heterogeneity among the included studies was assessed by the χ2 test and Higgins I2 values. If there was clear heterogeneity (I2 > 50% or P < 0.1), a random effects model was used. Otherwise, a fixed effects model was applied.The outcomes in both the treatment and control groups after the intervention period were extracted. The results were shown by the histogram in one study , and we AS scale . To quanPSS 25.0  or the mPSS 25.0 . The datPSS 25.0 , 19, 20.PSS 25.0 , 21. QuaA total of 113 entries were retrieved from Chinese and English databases, including 33 in Chinese and 80 in English ; 50 duplI2 = 44%, P = 0.10). We used the fixed effects model because heterogeneity was not observed after two studies were [I2 = 0%, P = 0.78). The meta-analysis showed that rTMS had a significant beneficial effect on MAS scores in patients with lower limb spasticity after stroke  (Five articles (seven studies) , 21, 23 ies were , 21 excl = 0.02) .P = 0.001) with no statistical heterogeneity . There was no statistical significance between the two groups in the studies using high-frequency rTMS (P = 0.72)  with 554 patients , 19–23 p = 0.72) .I2 = 40% and P = 0.17 (P ＜ 0.00001).Two articles (four studies) , 21 withP = 0.17 . Jing waP = 0.17 . We founTwo studies , 20 showHmax/Mmax was described in two studies [The electrophysiological index  studies , 20 and The included articles reported adverse effects except for Hong . Three sVelocity-dependent increases in muscle tone, hyperexcitable stretch reflexes, and hyperreflexia tendon jerks are often described as features of spasticity that appear in patients with stroke . The reaHmax/Mmax showed no statistical improvement after five consecutive LF-rTMS sessions. Terreaux et al. [At present, the conventional treatment for lower limb spasticity after stroke includes drugs, motor therapy, and neuromuscular electrical stimulation . Howeverx et al.  showed tx et al.  or had ax et al. , our resHmax/Mmax. McIntyre et al. [The results indicated that rTMS was effective in improving lower limb spasticity and activities of daily living; LF-rTMS had a positive influence on enhancing motor function in patients who experienced lower extremity spasticity after stroke, whereas HF-rTMS did not have a significant effect on motor function. Furthermore, rTMS did not have an additional significant effect on TUG times or e et al.  performee et al.  was publHmax/Mmax) were [Hmax/Mmax, which has been related to an increase in muscle tone in spasticity to a certain extent, is the ratio of the maximum amplitude of H reflexion and M wave recorded by surface electromyography. Hmax/Mmax does not completely reflect the excitability of neurons with measurement of error, and HSLP/MSLP was proposed as a better outcome [HSLP/MSLP (the ratio of the slope of H and M-waves) was more sensitive to represent the excitability of motor neuron of the anterior horn of the spinal cord [Hmax/Mmax and MAS is not exact, which may not change with the change of MAS [Sensitivity analyses of the included studies found that the cause of high bias of risk in Jing and Yan  may haveax) were  not accoax) were , which wax) were . Hmax/Mm outcome . HSLP/MSnal cord . In addie of MAS . There we of MAS , 20–22 fe of MAS  reportede of MAS , while ne of MAS , as prevThe mechanism by which rTMS improves spasticity is not clear. There are two commonly used models of rTMS: (1) a high-frequency (>1 Hz) facilitatory mode, which is applied to the affected brain region to increase cortical excitability and thus reduce spasticity and improve upper limb motor function, and (2) a low-frequency (≤1 Hz) inhibitory mode, which decreases excitability in the unaffected hemisphere and therefore reduces inhibition from the contralateral hemisphere to the ipsilateral hemisphere , 38, 39.The stimulated site included in this study was the leg motor cortex, which is associated with a deep position that is located on the inner side of the anterior central gyrus under a thick skull . To ensuThe limitations of this study are as follows: first, the risk of bias was slightly high. The three crossover trials included in this paper only contributed data from the first stage to this analysis; thus, the testing power was reduced. In addition, the affected region of the brain is a factor that influences spasticity after stroke, and subgroup analyses of the main muscle groups in the context of lower extremity spasticity were not conducted. The MAS, FMA, and MBI are semiquantitative indicators, and the evaluators may have introduced subjectivity when assessing them. More large-scale and high-quality randomized controlled trials with targeted and precise quantitative indicators as outcomes are expected in the future.In summary, rTMS was effective in improving spasticity and activities of daily living in patients with lower limb spasticity after stroke. LF-rTMS had a positive effect on enhancing motor function.


Introduction Severe novel corona virus disease 2019 (COVID-19) causes dysregulation of the coagulation system with arterial and venous thromboembolism (VTE). We hypothesize that validated VTE risk scores would have prognostic ability in this population.Methods Retrospective observational cohort with severe COVID-19 performed in NorthShore University Health System. Patients were >18 years of age and met criteria for inpatient or intensive care unit (ICU) care. The International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) and Caprini scores were calculated and patients were stratified.Results This study includes 184 patients, mostly men (63.6%), Caucasian (54.3%), 63 years old (interquartile range [IQR]: 24–101), and 57.1% of them required ICU care. Twenty-seven (14.7%) thrombotic events occurred: 12 (6.5%) cases of disseminated intravascular coagulation (DIC), 9 (4.9%) of pulmonary embolism, 5 (2.7%) of deep vein thrombosis, and 1 (0.5%) stroke. Among them, 86 patients (46.7%) died, 95 (51.6%) were discharged, and 3 (1.6%) were still hospitalized. “Moderate risk for VTE” and “High risk for VTE” by IMPROVE score had significant mortality association:  and , respectively, with 87% sensitivity and 63% specificity . “High Risk for VTE” by Caprini score had significant mortality association  with 96% sensitivity and 55% specificity . Both scores were associated with thrombotic events when classified as “High risk for VTE” by IMPROVE  and Caprini scores .Conclusion The IMPROVE and Caprini risk scores were independent predictors of mortality and thrombotic events in severe COVID-19. With larger validation, this can be useful prognostic information. Initially described in China, the novel coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)Most affected individuals with COVID-19 will present a milder and self-limited form of the disease with flu-like symptoms.It is known that hospitalized patients with acute medical illness are at increased risk for the development of venous thromboembolism (VTE).As the number of cases of COVID-19 steadily increases, tools with the ability to risk stratify and triage these affected individuals can help allocate resources and optimize medical care. Several risk factors for disease severity and poorer outcomes have been identifiedThis was a retrospective observational study of consecutive hospitalized patients with severe COVID-19 disease, performed in NorthShore University Health System from March 12, 2020, through July 30, 2020. Patients were at least 18 years of age with SARS-CoV-2 infection confirmed by polymerase chain reaction. Severe COVID-19 disease was defined by the presence of with dyspnea, hypoxia , need for oxygen supplementation, or significant lung involvement on imaging. All patients met criteria for inpatient-level care (IC) or intensive care unit (ICU)-level care when they required invasive ventilatory support.2, need for high-flow nasal cannula, mechanical ventilation, sepsis-induced coagulopathy score of ≥4, and D-dimer > 6 times upper limit of normal) was the preferred treatment modality, unless patients had severe renal insufficiency. Furthermore, thromboprophylaxis was extended for 2 weeks with LMWH for patients over 40 years of age with reevaluation of VTE risk at follow-up. Alternatively, extended thromboprophylaxis up to 45 days with rivaroxaban 10 mg daily was recommended when criteria were met .On April 15, an institutional thromboprophylaxis protocol for patients with COVID-19 was implemented in line with multisociety recommendations.The present study was approved by the local Institutional Review Board  and written consent was waived given its retrospective design. The database with deidentified patient information was set up and maintained by the Cardiovascular Division.Faculties of the Department of Internal Medicine and the Division of Cardiology settled and extracted data by review of the institutional electronic medical record. We abstracted demographic data including age, gender, BMI, and laboratory parameters at hospitalization. Comorbidities, defined as simultaneous presence of >1 chronic condition, were recorded on hospital admission.Laboratory data were collected within the first 5 days from hospitalization and, taking into consideration, the available peak values.The IMPROVE and Caprini scores were calculated at the time of data collection and by a second author at the time of data analysis for corroboration. Patients were classified according to the IMPROVE risk score in “Low risk for VTE” (score 0–1), “Moderate risk for VTE” (score 2–3), and “High risk for VTE” (score ≥ 4).For the Caprini score, patients were classified according to their risk scores and dichotomized into “Low to Moderate risk for VTE” (score 0–4) and “High Risk for VTE” (score ≥ 5) to make groups comparable, and were subsequently stratified by Caprini score at accepted cut-offs as follows: very low risk (Caprini score: 0–2), moderate risk (Caprini score: 3–4), high risk (Caprini score 5–6), very high risk (Caprini score: 7–8), and the highest risk (Caprini score >8).VTE was defined as deep vein thrombosis (DVT) or pulmonary embolism (PE) when clinically observed and treated during hospitalization. Patients were considered to have DVT if treated for DVT and/or had positive compression ultrasonography test. Routine screening for DVT was not instituted by the time of adjudication, this was in line with the recommendations from the World Health Organization until the time of censoring. Patients were considered to have PE if they were treated for PE and had a positive lung scan, pulmonary angiogram, or spiral computed tomography (CT) scan. The International Society for Thrombosis and Hemostasis (ISTH) criteria for the diagnosis of disseminated intravascular coagulation (DIC) was used.Clinical and mortality outcomes were extracted and censored at the time of death and at time of last follow-up until July 30, 2020. The data and scores were verified by a second independent author for their accuracy and, in case of discrepancy, adjusted by consensus.t-test to compare normally distributed continuous variables and Mann–WhitneyU-test to compare nonparametric continuous variables; Pearson's Chi-square test or Fisher's exact test were used to compare categorical variables.Descriptive data were summarized to characterize the distribution of baseline parameters. Kolmogorov–Smirnov and Shapiro–Wilk tests were used to evaluate if continuous variables were normally distributed; we used Student'sp < 0.05) were included in multivariate analysis to identify independent risk factors for mortality and thrombotic outcomes. Development of a thrombotic outcomes was treated as a time-dependent variable to eliminate the effect of misclassification from immortal time bias.We performed univariate and multivariate analyses using Cox's proportional hazards regression with forward modeling to explore the association of each variable and mortality, as well as thrombotic outcomes. Variables with statistical significance in univariate analysis (We used the receiver-operating characteristics (ROCs) curve to analyze the discriminatory capacity of each RAM, and used the Kaplan–Meier method to estimate the cumulative event-free survival curves for the different groups.p-value of <0.05 was considered statistically significant.We present categorical variables as absolute numbers and percentages, and continuous variables by their mean and standard deviation, or by the median and interquartile range (IQR) as appropriate. All statistical analyses were performed with SPSS version 27.0 . AA total of 184 consecutive patients with severe COVID-19 were included for analysis. The patients in this study were predominantly men (63.6%), Caucasian (54.3%), 63 years of age (IQR: 24–101 years), and the majority (57.1%) required ICU-level care. Patients were hospitalized on average 1 day (IQR: 0–25 days) after diagnosis of COVID-19, spent on average 7 days (IQR: 0–68 days) in the hospital, and were followed-up for a median of 52 days (IQR: 0–108 days) from their initial encounter.At the time of censoring, a total of 27 (14.7%) thrombotic events had occurred. There were 12 (6.5%) cases of DIC, 9 (4.9%) cases of pulmonary embolism, 5 (2.7%) DVT, and 1 (0.5%) stroke. A total of 86 patients (46.7%) died, 95 patients (51.6%) were discharged, and 3 patients (1.6%) were still hospitalized and undergoing medical care at the time of censoring.Comparison between the groups showed that mortality was significantly higher in patients who were older, had hypertension, diabetes mellitus, coronary artery disease, cerebrovascular disease, cancer, and patients who required ICU-level care. Mortality was significantly higher in those classified as “Moderate risk for VTE” and “High risk for VTE” by the IMPROVE score, and “High risk for VTE” by the Caprini score .Direct comparison of laboratory values collected revealed that nonsurvivors had significantly lower hemoglobin and albumin levels. Also, nonsurvivors had significantly higher prothrombin time, international normalized ratio (INR), D-dimer levels, creatinine levels, C-reactive protein levels, aspartate transaminase, and significantly higher absolute lymphocyte count .p = 0.003, and HR = 2.49; 95% CI: 1.62–3.83;p < 0.001, respectively. When adjusted for other variables in multivariate Cox's regression analysis, the association remained significant for “High risk for VTE” , followed by “Moderate risk for VTE” , the presence of diabetes , and hypertension . An ROC curve was plotted with an area under the curve (AUC) of 0.752 (p < 0.001) and a corresponding sensitivity of 87% and specificity of 63% for the patients classified as “Moderate risk for VTE” or above  = 2.02; 95% confidence interval (CI): 1.27–3.21;r above . When sr above .p < 0.001). Furthermore, this association remained significant when adjusted in multivariate Cox's regression analysis , followed by the presence of diabetes . An ROC curve was plotted with an AUC of 0.843 (p < 0.001) and a corresponding sensitivity of 96% and specificity of 55% for the designated dichotomized cut-off  had no mortality events. Those stratified at moderate risk (Caprini score: 3–4) had 6.8% mortality, high risk (Caprini score: 5–6) had a 44.4% mortality, very high risk (Caprini score: 7–8) had a 60.8% mortality, and the highest risk (Caprini score > 8) had a mortality rate of 80% .p < 0.001) and “High risk for VTE” by Caprini score . Patients, classified as “Moderate risk for VTE” by IMPROVE score, did not statistically associate with thrombotic event occurrence In univariate and multivariate analyses, both scores were statistically associated with thrombotic event occurrence when classified as “High risk for VTE” by IMPROVE score  with corresponding 85% sensitivity and 44% specificity for those classified as “High risk for VTE” (The ROC curve for thrombotic event prediction with the IMPROVE score had an AUC of 0.718 (or VTE” . The cuor VTE” .p < 0.001) with corresponding 92% sensitivity and 35% specificity for the designated dichotomized cut-off  with LMWH, or direct oral anticoagulants (DOACs) can reduce the risk of VTE at the cost of increased bleeding, with net clinical benefit seen by the DOAC rivaroxaban in key low bleed risk subgroups of medically ill patients.Our analysis showed the strong predictive ability of both VTE risk assessment models for the hard outcome of mortality in this cohort of patients with severe COVID-19. It also validates the predicting capacity for thrombotic events in this population at increased risk. Because routine screening for VTE or autopsies was not performed routinely amid the pandemic, we could not verify if deaths were VTE related. Also, given the initial scarcity of personal protective equipment that was seen nationwide, is likely that the true number of thrombotic events was underestimated.Despite the strengths of our findings, there are limitations intrinsic to the observational design of our study and the relatively small sample size from a single-center experience conferring a degree of ascertainment bias. Furthermore, the severity of disease from COVID-19 in our cohort introduces selection bias, thus the results may not be generalizable to all comers with COVID-19 disease.Like many other retrospective studies, we did not perform a formal power calculation. Therefore, our study might be underpowered to draw firm conclusions about the association of the VTE risk tools, mortality, and VTE. Hence, external validation with large prospective cohorts should be pursued to confirm our findings.Nonetheless, the implementation of either VTE RAM may be a valuable source with prognostic value for the outcome of death or thrombosis. With further validation, this strategy can assist in triaging individuals with severe COVID-19 disease and optimize resource allocation.The IMPROVE and Caprini VTE risk assessment models were independent predictors of mortality and thrombotic events in our cohort of patients with severe COVID-19. With largescale validation, this prognostic information can assist triaging individuals and optimize resource allocation.


Gestational trophoblastic disease (GTD) usually affects young women of childbearing age. After treatment for GTD, 86% of women wish to achieve pregnancy. On account of the impacts of GTD and treatments as well as patient anxiety, large numbers of couples turn to assisted reproductive technology (ART), especially in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI). But few studies have investigated whether a history of GTD affects the outcomes of IVF/ICSI in secondary infertile patients and how it occurs. We investigate whether a history of GTD affects the IVF/ICSI outcomes and the live birth rates in women with secondary infertility.This retrospective cohort study enrolled 176 women with secondary infertility who underwent IVF/ICSI treatment at the reproductive medical center of Nanjing Drum Tower Hospital from January 1, 2016, to December 31, 2020. Participants were divided into the GTD group (44 women with GTD history) and control group (132 women without GTD history matched from 8318 secondary infertile women). The control group and the study group were matched at a ratio of 3:1 according to patient age, infertility duration, number of cycles and body mass index (BMI). We assessed retrieved oocytes and high-grade embryos, biochemical pregnancy, miscarriage, ectopic pregnancy, gestational age at delivery, delivery mode and live birth rates.p < 0.001) but no differences in the mode of delivery (p = 0.267). Furthermore, the number of abandoned embryos in the GTD group was greater than that in the control group (p = 0.018), and the number of good-quality embryos was less than that in the control group (p = 0.019). The endometrial thickness was thinner (p < 0.001) in the GTD group. Immunohistochemistry (IHC) showed abnormal endometrial receptivity in the GTD group.We found a significantly reduced live-birth rate (34.1% vs 66.7%) associated with IVF/ICSI cycles in patients with a GTD history compared to those without a GTD history. The biochemical pregnancy and miscarriage rates of the GTD group were slightly higher than those of the control group. In addition, there was a difference in gestational age at delivery between the GTD and control groups (The GTD history of patients undergoing IVF/ICSI cycles had an impact on the live-birth rate and gestational age at delivery, which might result from the thinner endometrium and abnormal endometrial receptivity before embryo transfer.The online version contains supplementary material available at 10.1186/s12958-022-00898-2. Gestational trophoblastic disease (GTD) covers a range of premalignant and malignant pregnancy-related disorders associated with highly abnormal placental trophoblastic tissue . GTD incAlthough GTD was previously considered a lethal disease, progressive improvements in the diagnostic process, clinical management and follow-up protocols as well as the development of effective treatments and centralization of care have resulted in excellent cure rates (exceeding 98%) . Future Treatments for GTD usually include uterine curettage and chemotherapy, both of which have a negative influence on women’s fertility and psychological states. Even though GTD evolves from a previous pregnancy, not all women are interested in a new pregnancy, and some may avoid this due to treatment-related anxiety. After treatment for GTD, 86% of women wish to achieve pregnancy [The outcomes of IVF/ICSI in secondary infertile patients with a history of GTD remain unknown. There are few reports of IVF/ICSI in infertile patients with a history of GTD, and only individual cases have been reported. Pal et al.  reported2) with Social Sciences Statistical Package (SPSS). This study was approved by the Ethics Committee of Drum Tower Hospital, which is affiliated with the Nanjing University Medical School (no. 2021–104-01).All secondary infertile patients undergoing IVF/ICSI treatments from January 1, 2016, to December 31, 2020, at the reproductive medical center of Nanjing Drum Tower Hospital were reviewed  with a flexible protocol for the medication dose selected. When the diameters of at least two follicles reached 16–18 mm, ovulation was triggered. Subcutaneous injection of 0.2 mg gonadotropin-releasing hormone agonist  and/or intramuscular injection of 5000–10,000 IU human chorionic gonadotropin (hCG) was given –11.Four to six hours after oocyte retrieval, treated sperm were added for IVF or ICSI. Fertilization was defined as the presence of two pronuclei the morning after oocyte retrieval. After 2–3 days of in vitro culture, the quality of the embryos was evaluated, and high-quality embryos were selected for transfer or freezing , 13, TheFrozen embryo transfer (FET) cycle: The hormone replacement cycle started on the second day of menstruation by 14–20 days of estradiol pills. When the endometrial thickness reached at least 8 mm, progesterone was injected for 5–6 days, and then the embryos were transferred. Follicular development and LH values were monitored during the natural cycle, and embryo transfer was performed on the 4th/5th day after the LH peak or the 3rd/4th day after ovulation.One or two good-quality embryos were selected and transferred to the uterus through abdominal ultrasound guidance. After embryo transfer, oral dydrogesterone or estradiol combined with dydrogesterone was employed with vaginal progesterone for luteal support. Serum β-hCG was detected 14 days after embryo transfer. If serum β-hCG was positive (> 200 mIU/mL), biochemical pregnancy was confirmed. Transvaginal ultrasound examination was performed 28–30 days after embryo transfer, and clinical pregnancy was determined by the presence of the gestational sac. Outcome data were collected until the live birth.2). The process of ovulation induction was mainly reflected as the days of ovulation hyperstimulation, the amount of Gn, the level of E2 on the trigger day and the number of oocytes retrieved. The main results of ovulation induction were the number of oocytes retrieved, fertilization rate, normal fertilization rate, number of good-quality embryos, and abandoned embryos. Clinical outcomes were the implantation rate , miscarry rate , live-birth rate, gestational age at delivery and cesarean delivery rate.The general fertility of each patient was determined based on age, infertility duration, BMI, antral follicle count (AFC), and levels of follicular stimulating hormone (FSH), luteinizing hormone (LH), and estrogen (EWe checked differences between groups using parametric and nonparametric descriptive statistics. Multivariate logistic regression was conducted to identify variables independently associated with the live-birth outcome. The primary exposure factor was defined as a history of GTD. The covariates were as follows: age (< 35 vs ≥35 years old), infertility duration (< 3 vs ≥3 years), gravidity (< 3 vs ≥3), number of uterine curettages (< 1 vs ≥1), type of ART (IVF vs ICSI vs PGT), endometrial thickness on trigger day (≤9 mm vs 9–12 mm vs ≥12 mm), number of good-quality embryos (< 3 vs ≥3), and number of abandoned embryos (< 6 vs ≥6). Data analysis was performed using EmpowerStats 2.0 and R statistical software.2O2 and 100% methanol for 30 min at room temperature to quench endogenous peroxidase, embedded in partial segments with 10% normal goat serum, and incubated with anti-FHL1 , anti-FOXO1 , anti-HOXA10 , or anti-Ki67  overnight at 4 °C. On the following day, the sections were incubated with secondary antibody conjugated to horseradish peroxidase (Vector Laboratories) for 1 h at room temperature. Immunoreactivity was measured using diaminobenzidine , photographed using microscopy software, and then analyzed using Image-Pro.After ethical approval and written informed consent, we used residual endometrial biopsy samples collected during the hysteroscopic surgery of patients with suspected endometrial polyp、adhesion or endometritis but proved without later in both Control and GTD group. The dewaxed hydrated paraffin-embedded tissue sections were immersed in 3% HIn total, 176 IVF/ICSI cycles from January 1, 2016, to December 31, 2020 met the inclusion criteria, 44 patients had a history of GTD, and 132 patients did not have a GTD history. The patients in our cohort study were 31.6 ± 3.9 years old. The infertility duration was 3.1 ± 2.5 years, and tubal factor (63.6%) was the most common infertility diagnosis.2), we matched 132 cycles associated with patients with no history of GTD; these patients served as the control group. On account of the matching, there were no differences in patient age , infertility duration , number of IVF/ICSI cycles (1.0 (0.0–7.0) vs 1.0 (1.0–5.0), p = 0.106) or BMI  (Table p < 0.001) and curettage times (0.0 (0.0–3.0) vs 2.0 (0.0–6.0), p < 0.001). In addition, we found no statistically significant differences in ovarian reserve reflected by AFC  and FSH  . There were 23 (52.3%) patients who underwent ICSI cycles and 6 (13.6%) patients who underwent PGT cycles in the GTD group, which were significantly more than those in the control group. Furthermore, we found that the number of good-quality embryos in the GTD group was less than that in the control group , but the number of abandoned embryos was much greater than that in the control group . The endometrial thickness on the trigger day was significantly thinner in the GTD group . All these results were shown in Table The mean days of ovarian stimulation of the GTD group were 10.0 (5.0–18.0) with a total gonadotropin dose of 1977.7 ± 897.5 IU and a total GnRHa dose of 1.2 mg 0.0–3.8), which were similar to those of the control group. In addition, E.8, whichp > 0.05), although slight discrepancies existed between the two groups . Fifteen patients (34.1%) in the GTD group and 88 patients (66.7%) in the control group had already delivered, 19 (43.2%) and 27 (20.5%) patients were not pregnant, 3 (6.8%) and 4 (3.0%) patients had miscarriage, and 4 (9.1%) and 8 (6.1%) patients were still in pregnancy, respectively. There was a statistically significant difference in the gestational age at delivery (p < 0.01): the mean gestational age of patients in the control group was 38.1 ± 1.6 weeks, and that of patients in the GTD group was 36.3 ± 3.3 weeks. Regarding the mode of delivery, there was no difference in the cesarean delivery rate between the two groups (p > 0.05). All the outcomes are presented in Table In evaluating the implantation rate and ovarian hyperstimulation syndrome (OHSS) rate, there were no statistically significant differences (p < 0.01). We also found that some factors were also related to the live-birth rate , such as the age of the patients and endometrial thickness on the trigger day. In the multivariate analysis, the presence of a GTD history did not significantly impact the live-birth rate associated with IVF/ICSI cycles . In the GTD group, there were no significant differences in the live-birth rate associated with IVF/ICSI/PGT cycles  in the endometrial epithelial and stromal cells of infertile women with a GTD history than in those of the controls. FOXO1 expression was evidently lower (p < 0.05), mainly in stromal cells. Ki67 expression was much higher (p < 0.05) in both endometrial epithelial and stromal cells of patients with a GTD history.To determine the influence of endometrial factors on the live-birth outcome, endometrial receptivity was measured in some of these patients. As shown by IHC Fig. , HOXA10 Gestational trophoblastic disease, especially hydatidiform mole, is thought to be associated with empty oocyte fertilization or polyspermy , 18. In In addition to embryological factors, the endometrium must also be considered. A thin endometrium on ultrasound in the course of ovarian hyperstimulation has been thought to be associated with pregnancy rates in IVF/ICSI . In our Blastocysts were successfully implanted only when transferred into the receptive uterus . In humaAt present, many studies of subsequent natural pregnancy in GTD patients have found that, except for the increased risk of stillbirth and premature birth, most pregnancy conditions are not significantly different from those in patients without a GTD history , 31. HowSimilarly, we also need to consider whether ovulation induction drugs will increase the probability of subsequent progression to recurrent GTD in these patients. Patignat et al.  retrospeThe disadvantage of this retrospective study is that the sample size was small, which may be related to the decreasing incidence of GTD in recent years  and the In conclusion, secondary infertile patients with a history of GTD can obtain similar numbers of normal fertilization in the process of IVF/ICSI cycles as patients without a history of GTD. However, the pregnancy rate is lower than that of patients without a GTD history due to two factors: (1) the fewer available embryos and more abandoned embryos and (2) the thinner endometrial thickness because of the greater number of uterine curettages. Furthermore, the miscarriage rate was higher and the gestational age at delivery was smaller, which might result from the harmful effect of uterine curettage. This study can provide some clinical data for IVF/ICSI cycles in infertile patients with a history of GTD to better guide clinical treatment.Additional file 1: Supplemental Table 1. The reasons of patients receiving hysteroscopic in Control group and GTD group.


Background: Studies have shown that ambient air pollution is linked to preeclampsia (PE), possibly via generation of oxidative stress in the placenta. Telomere length and mitochondrial DNA copy number (mtDNAcn) are sensitive to oxidative stress damage.Objective: To study the association between prenatal exposure to ambient nitrogen oxides , and PE, as well as potential mediation effects by placental telomere length and mtDNAcn.Methods: This is a cross-sectional study of 42 preeclamptic and 95 arbitrarily selected normotensive pregnant women with gestational ambient NOx exposure assessment in southern Scania, Sweden. Hourly concentrations of NOx were estimated at the residential addresses by a Gaussian-plume dispersion model with 100 × 100 m spatial resolutions and aggregated into trimester-specific mean concentrations. Placental relative mtDNAcn and telomere length were measured using qPCR. Linear and logistic regression models were used to investigate associations, adjusted for perinatal and seasonal characteristics.Results: Exposure was categorized into low and high exposures by median cut-offs during first , second , third trimesters  and entire pregnancy . Increased risk of PE was found for high prenatal NOx exposure during the first trimester , and entire pregnancy . High exposed group during the first trimester had lower placental relative mtDNAcn compared with low exposed group . Changes in relative mtDNAcn did not mediate the association between prenatal NOx exposure and PE. No statistically significant association was found between placental relative telomere length, prenatal NOx exposure and PE.Conclusion: In this region with relatively low levels of air pollution, ambient NOx exposure during the first trimester was associated with reduced placental relative mtDNAcn and an increased risk of PE. However, we did not find any evidence that mtDNAcn or TL mediated the association between air pollution and PE. Future research should further investigate the role of mtDNAcn for pregnancy complications in relation to exposure to ambient air pollution during pregnancy. Ambient air pollution is a major global contributor to morbidity and mortality globally, accounting for 7.6% of all deaths worldwide in 2015 , carbon monoxide and sulfur dioxide. Another reason is that pregnancy complications, especially preeclampsia (PE), tend to be caused by a dysfunctional placenta. According to the recommendation of International Society for the Study of Hypertension in Pregnancy (ISSHP), PE is defined as de-novo hypertension combined with maternal organ dysfunction and/or utero-placental dysfunction including FGR presenting after 20 weeks of gestation  of different sizes and compositions, ozone, nitrogen oxides , as well as lipid peroxidation, resulting in DNA mutations and cell death  by the World Health Organization (WHO)  with measured façade NO2 levels. According to our previous studies, a total NOx concentrations were used in the data analysis by adding a background concentration of 2.5 μg/m3 on the modeled hourly NOx concentrations to account for transboundary air pollution , PM10 and black carbon as reported in our population-based study   according to manufacturer's instruction, and thereafter stored at −80°C until further use. The DNA samples were thawed only once in preparation for the present study. The purity ratios [A260/280 1.87  and A260/230 2.05 ] and DNA yield (ng/μl) were determined by using a NanoDrop Spectrophotometer ND-1,000 .HBB)]. MT-TL1 encoding the Mitochondrially Encoded TRNA-Leu (UUA/G) 1 was the target gene that was used to determine mtDNAcn  , 10 μM HBB forward primer (5′-TGT GCT GGC CCA TCA CTT TG-3′), and 10 μM reverse primer (5′-ACC AGC CAC CAC TTT CTG ATA GG-3′) , 20 μM TEL2 primer (5'-GGC TTG CCT TAC CCT TAC CCT TAC CCT TAC CCT TAC CCT-3'), 10x SYBR Green I  (50x), ROX (1x) , and 0.5 U Taq Platina DNA polymerase   and 7.5 μl master mix, resulting in total volume of 10 μl.To quantify relative mtDNAcn and telomere length, real-time polymerase chain reactions (qPCR) were performed using an Applied Biosystems 7900HT Fast Real-Time PCR System . The PCR products of mtDNAcn and telomere length were related to PCR product of a single copy gene [hemoglobin beta  or two (n = 13) trimester-specific NOx exposure data although they were term pregnancies. To account for a cumulative effect of exposure during the entire period of pregnancy, complete case analysis (n = 117) on complete exposure data at all trimesters was performed and reported.All statistical analyses were performed using the IBM SPSS Statistics software version 25 . Continuous data was checked for normality and presented as means ± SD or as median with interquartile range (IQR) when data were not normally distributed. Categorical data are presented as numbers and percentage. A x exposure and risk of PE, adjusted odds ratios (OR) with their 95% confidence intervals (95% CI) were estimated using logistic regression, after controlling for maternal age, pregestational body mass index (BMI), parity, gestational age and fetal sex. These covariates were defined based on a priori knowledge  association between prenatal NOx exposure and PE was investigated; (2) association between prenatal NOx exposure and placental relative mtDNAcn or telomere length was investigated; and (3) if the association between prenatal NOx exposure and placental relative mtDNAcn or telomere length was statistically significant, mtDNAcn or telomere length were entered in to the regression model of the first step . In all models, the same set of confounding factors were included into the models. To be considered a mediating variable in the third step: (1) placental relative mtDNAcn or telomere length should be statistically significant; and (2) the coefficient for prenatal NOx exposure should be substantially diminished as compared to in the first step.The standard Baron and Kenny  method oA total of 42 PE cases consisted of three early-onset PE and 39 late-onset PE. x concentrations varied between 14.0 and 16.2 μg/m3 over the three trimesters and entire period of pregnancy  to high  correlations that were statistically significant. The range in ambient NOx was wide, modeled NOx concentrations were split to low and high exposure groups by median cut-offs during first , second , third trimesters , and entire period of pregnancy   . The chax exposure and PE when looking at exposure during first trimester  and entire pregnancy   . Effect x had lower placental mtDNAcn  as compared with women exposed to low NOx concentrations during the first trimester  nor in adjusted analyses .Women exposed to high concentrations of NOrimester . The assx exposure during first trimester and PE, as well as an association between prenatal NOx exposure during first trimester and placental relative mtDNAcn. To investigate if placental mtDNAcn was mediating this association, we performed a mediation analysis.There was an association between prenatal NOY is the dependent variable, i.e., PE; X the independent variable, prenatal NOx exposure; and Me the proposed mediator variable, mtDNAcn. In order for a variable to be considered a mediator, β32 should be statistically significant, however this was not the case (p = 0.954). Furthermore, β31 should be either substantially smaller than β11, which it was slightly smaller (β11 = 1.382 > β31 = 1.375), or statistically not significant, which it was not (p = 0.010). Therefore, mtDNAcn was not a mediator for the association between prenatal NOx exposure and PE (In e and PE .p = 0.43) nor in the adjusted analyses . Since the assumption of mediation analysis did not meet, we did not further investigate any mediation effect of placental relative telomere length on the association between prenatal NOx exposure and PE.There was no statistically significant difference in placental relative telomere length between exposure groups . There wx during the first trimester was associated with reduced placental relative mtDNAcn and increased risk of PE, which indicate that early pregnancy is the most vulnerable period for damage of the placenta by ambient air pollution. In contrary to our hypothesis, we found no evidence that placental relative mtDNAcn mediate the association between ambient NOx and PE. Placental relative telomere length was not associated with prenatal NOx exposure or with PE.We found that prenatal exposure to ambient NOx coincides with epigenetic reprogramming of germ cells and preimplantation embryos by DNA methylation occurring in the first trimester  during pregnancy and birth weight, was mediated by a decrease in placental mtDNAcn  in that study and the mean NO2 concentrations ranged between 21.1 and 25.5 μg/m3 which is higher than the mean NOx concentrations (14–16.2 μg/m3) in our study, which could possibly explain the effect of mediation. Future research in a larger cohort is therefore needed to assess the value of this biomarker for assessing mitochondrial dysfunction in placental pathology.However, mediation analysis of placental mtDNAcn undertaken here, did not appear to influence the relationship between prenatal NOx on placenta have not previously been studied, the detrimental effect of fine and ultrafine particles on placenta have been reported. Ambient black carbon particles have been found to be translocated to the fetal side of the placenta collected from full term pregnancies  and mean NOx and total PM2.5 concentrations  during the entire pregnancy  and a larger variation (4.3–32.5 μg/m3) in weekly PM2.5 exposure. Furthermore, shorter telomeres were found in placental trophoblasts from pregnancies complicated by PE, FGR and PE with FGR as compared to uncomplicated pregnancies  during the first trimester was associated with reduced placental relative mtDNAcn and an increased risk of PE. However, we did not find any evidence that mtDNAcn or TL mediated the association between air pollution and PE. Future research should further investigate the role of mtDNAcn for pregnancy complications in relation to exposure to ambient air pollution during pregnancy.Our data show that exposure to ambient air pollution . The patients/participants provided their written informed consent to participate in this study.EM, YM, SH, KB, AO, CI, and LE: conceptualization, methodology, and writing—review and editing. YM, KB, and AO: formal analysis and investigation. KB, SH, and LE: resources. EM, SH, and LE: data curation. YM: writing—original draft preparation. EM, AO, KB, and SH: supervision. EM: project administration. EM, CI, and SH: funding acquisition. All authors have read and approved the submitted version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


TMEM18 gene, which plays a significant role in feeding behaviour; however, subsequent studies among different ethnic populations and age groups have shown inconsistent results. Therefore, this present meta-analysis examines the relationship between TMEM18 polymorphisms with the risk of obesity with regard to age group and ethnic population.Many studies have proposed that the pathogenesis of obesity has a genetic basis, with an important risk factor being the presence of polymorphisms in the region of the TMEM18. Pooled odds ratio (OR) and 95% confidence intervals (95% CI) were calculated by either a fixed-effects model or random effect model based on a heterogeneity test. The meta-analysis of rs6548238 and its surrogates examined the relationships between 53 395 obesity cases and 123 972 healthy controls from 27 studies and published data from the POPULOUS collection (Poland).A literature database search was conducted for available relevant studies investigating the association between obesity risk and the presence of rs6548238, rs4854344, rs11127485, rs2867125 and rs7561317 polymorphisms in A significant association is observed between rs6548238 (and surrogate) and obesity risk, with OR = 1.25 (95% CI: 1.08–1.45). Regarding population type, a significant association was revealed among groups of Europeans with OR = 1.32 (1.10–1.59) and Mexicans with OR = 1.39 (1.13–1.73). However, a lack of statistical significance was noticed in groups in Asia with OR = 1.11 (95% CI: 0.86–1.42). Regarding age, a significant association was observed among children with OR = 1.28 (95% CI: 1.18–1.39) but not in adults OR = 1.21 (95% CI: 0.92–1.58).TMEM18 appear to play a role in the development of obesity. Our findings indicate that differences exist between ethnic populations and age groups, supporting those of a previous study showing the various effects of genetic factors on age and ethnic groups.The polymorphisms near The online version contains supplementary material available at 10.1186/s12920-021-01025-7. Obesity is a nutritional disorder associated with weight gain  caused b2). In adults, the threshold for obesity is considered to be a BMI of 30 [Obesity is classified by Body Mass Index (BMI), an index of weight-for-height defined as weight in kilograms divided by the square of height in meters , which is located in the nuclear membrane. This protein is reported to be involved in weight regulation through transcriptional repression [TMEM18 and changes in BMI has been confirmed by a third wave of GWAS (Genome-wide association study) [Obesity is considered by many researchers to be a heritable disease , and manpression . TMEM18 n study) , and subn study) , 14. Apan study) .TMEM18 region and obesity, there is a clear need to determine more precisely the effect size of polymorphisms rs6548238, rs4854344, rs11127485, rs2867125, and rs7561317 localised near the gene itself with regard to age and population type. Therefore, the present meta-analysis reviews a range of data meeting the required criteria, with the age categorization.With the discovery of an apparent relationship between the Identification of relevant studies concerning the association of rs6548238 rs4854344, rs11127485, rs2867125, and rs7561317 polymorphisms with obesity was conducted by systematic literature search from PubMed, Science Direct, Web of Science databases and GWAS catalogue. The following search terms were used: obesity AND (TMEM18 OR GWAS). Obtained results were divided into two categories: age and population. No restriction was placed on the time period, sample size or language. If more than one article was published using the same case series, only the original study was included.The present meta-analysis included genetic association studies based on cohort or case–control models, in which the case subjects were obese and the control subjects were individuals within the normal BMI range. The following inclusion criteria were applied: (a) case–control or cohort studies presenting original data on the associations between the risk of obesity and TMEM18 polymorphisms , (b) sufficient data for the calculation of odds ratio (OR) with the 95% confidence interval (95% CI) or calculated OR with 95% CI. The following exclusion criteria were applied: (a) review articles and meta-analysis, (b) studies on the association between other gene polymorphisms and obesity risks, (c) no information about number of alleles and number of cases and controls (d) studies based on non-human models (e) quantitative traits such as Body Mass Index or Body Fat Percentage since the data were not uniform .Two researchers collected data independently. Disagreements were resolved by discussion with a third researcher. The following information was extracted from each study: (a) name of the first author, (b) year of publication, (c) country of origin, (d) ethnicity, (e) sample size, (f) association of the SNPs with obesity (OR and 95% CI), (g) analysed polymorphism, (h) number of case and controls, (i) mean age of case and controls.POPULOUS collection [POPUlation—LOdz UniverSity Biobank) at the Biobank Lab of the Department of Molecular Biophysics, University of Lodz. The POPULOUS population collection is currently registered in Directory (v. 4.0) of BBMRI-ERIC consortium under the registration number bbmri-eric:ID:PL_BLUL:collection:POPULOUS_BLUL. POPULOUS contains saliva samples from over 10,000 volunteers from all over the Poland [Additional data from adults of Polish origin were collected between 2010–2012 within the TESTOPLEK research project and registered as the llection , 17 , and each participant from the POPULOUS study gave their written consent to take part. All procedures were performed in accordance with the Declaration of Helsinki  .2, based on self-assessment of height and weight controlled by trained pollsters. People were considered as obese when BMI values were ≥ 30, and were normal when BMI was in the range of 18.5–24.9 [The BMI of each participant was calculated from the standard formula: BMI = weight/height8.5–24.9 . Allele The results indicate that 6047 unrelated Polish adult subjects were enrolled in the study group. Of these, 3 495 subjects remained after exclusion of underweight (BMI < 18.5) and overweight (BMI in the range of 25.0–29.9) individuals. Following this, 3 334 individuals, including 827 obese cases (BMI > 30) and 2667 control cases with normal weight (BMI in the range of 18.5–25.0), were successfully genotyped for SNPs rs6548238, rs2867125 and rs7561317. For rs4854344 there were 804 cases and 2 592 controls. 24 × 1 Infinium HTS Human Core Exome  microarrays were used for genotyping according to the protocol provided by the manufacturer.The Newcastle–Ottawa Scale  was usedp ≤ 0.05 was considered as statistically significant. The statistical analysis of the extracted data was conducted using Review Manager 5.3 [The association between obesity risk and the presence of rs6548238, rs4854344, rs11127485, rs2867125 or rs7561317 polymorphisms was estimated by calculation of pooled ORs and 95% CI in the allele model . The combined outcomes were displayed as forest plots. Statistical differences of the pooled ORs were assessed using Z-test, ager 5.3 . This prp-value threshold of 0.1 was considered as statistically significant. The heterogeneity between the studies was also tested by I2 statistics; I2 values of at least 50% were taken as indicators of heterogeneity. When heterogeneity existed, a random effect model was used to evaluate the pooled ORs and 95% CIs, otherwise a fixed effect model was used.Cochran’s Chi-squared test (based on Q test) was used to evaluate heterogeneity between studies, a Potential publication bias was assessed via visual inspection of the funnel plot, with an asymmetric funnel plot indicating publication bias. To identify the source of heterogeneity, a sensitivity analysis was applied by removing individual studies from the data for children or adults. Subgroup analysis was performed based on population type  and age: adults (> 18 years) vs. children (≤ 18 years). A total of five polymorphisms were evaluated independently , as was rs6548238 and its surrogates.The following studies were included in the meta-analysis: Albuquerque et al. , Almen eThe PRISMA  flow chart explaining study selection and literature search is presented in Fig. The sample size showed great variation, from n = 77 to n = 40 872. Throughout the meta-analysis, if the study contained results for more than one polymorphism, only rs6548238 was selected. Detailed information about the studies selected for the meta-analysis is gathered in Additional file 2 statistics. The results of the I2 test found low heterogeneity concerning rs6548238 and its surrogate in the group of children . Therefore the fixed effect model was used for further analysis. As the group of adults demonstrated high heterogeneity , the random effect model was used. Regarding population type, low heterogeneity was only observed in the Mexican group ; higher heterogeneity was observed among the European and Asian groups .The heterogeneity among studies was assessed by the Chi-squared test based on Q-test and the IThe overall results showed that rs6548238 and its surrogate was significantly associated with obesity risk  Fig. .Fig. 2FoBased on 1000 Genomes Project data, polymorphism rs6548238 is used in the main analysis since it is in a high linkage disequilibrium with rs4854344  with Northern and Western European ancestry); D’ = 1; r = 1 in CHB ; D’ = 1; r = 1 in MXL (Mexican Ancestry from Los Angeles USA), rs11127485 , rs2867125  and rs7561317 .In the analysis of each polymorphism without division into subgroups, independently pooled ORs indicate that allele C of rs6548238  . Despite all of these strengths, some limitations should be addressed. OR with 95% CI from genetic data was used to evaluate the sole genetic influence; however, when it was not given, calculated OR with 95% CI was used after covariate adjustment from the individual study. The potential interactions between the genetic factors and environmental factors were not addressed due to insufficient data, which might also affect the accuracy of the results.The second limitation concerns the variation in BMI cut-offs for obesity between studies. Most studies used the basic classification of obesity (BMI ≥ 30) and normal weight (BMI 18.5–24.9); however, in some studies, mostly among Asian populations, other BMI thresholds were used for obesity (e.g. BMI ≥ 27.5) and normal weight (e.g. BMI 18.5–23.0) (Additional file TMEM18 polymorphisms and obesity across different population types based on ethnicity and age. Our findings indicate that rs6548238 was significantly associated with an increased risk of obesity and similar trends were found among subgroups of European and Mexican origin but not Asian. While the presence of this polymorphism appears to have a significant influence on obesity among children, no significant association was found with obesity risk among adults.The present meta-analysis is the first to systematically explore the association between TMEM18 and the risk of obesity. Differences appear to exist between ethnic populations and age groups. Our findings support those of a previous study showing the various effect of genetics in age and ethnic groups.The results of this meta-analysis suggest an association between rs6548238 polymorphisms and its surrogate near Additional file 1: Fig. S1. Meta-analysis of the association between rs6548238 and obesity risk using random effect model. Forest plot created within RevMan 5.3 software.Additional file 2: Fig. S2. Meta-analysis of the association between rs4854344 and obesity risk using random effect model. Forest plot created within RevMan 5.3 software.Additional file 3: Fig. S3. Meta-analysis of the association between rs11127485 and obesity risk using fixed effect model. The size of the red box corresponding to each study is proportional to the sample size. Forest plot created within RevMan 5.3 software.Additional file 4: Fig. S4. Meta-analysis of the association between rs2867125 and obesity risk using random effect model. Forest plot created within RevMan 5.3 software.Additional file 5: Fig. S5. Meta-analysis of the association between rs7561317 and obesity risk using random effect model. Forest plot created within RevMan 5.3 software.Additional file 6: Table S1. Characteristics of studies included in the meta-analysis.Additional file 7: Table S2. Sensitivity analysis of general results of rs6548238 and its surrogates.Additional file 8: Table S3. The quality of studies included in the analysis.