Lymphatic vessels in bone support regeneration after injury.

Blood and lymphatic vessels form a versatile transport network and provide inductive signals to regulate tissue-specific functions. Blood vessels in bone regulate osteogenesis and hematopoiesis, but current dogma suggests that bone lacks lymphatic vessels. Here, by combining high-resolution light-sheet imaging and cell-specific mouse genetics, we demonstrate presence of lymphatic vessels in mouse and human bones. We find that lymphatic vessels in bone expand during genotoxic stress. VEGF-C/VEGFR-3 signaling and genotoxic stress-induced IL6 drive lymphangiogenesis in bones. During lymphangiogenesis, secretion of CXCL12 from proliferating lymphatic endothelial cells is critical for hematopoietic and bone regeneration. Moreover, lymphangiocrine CXCL12 triggers expansion of mature Myh11+ CXCR4+ pericytes, which differentiate into bone cells and contribute to bone and hematopoietic regeneration. In aged animals, such expansion of lymphatic vessels and Myh11-positive cells in response to genotoxic stress is impaired. These data suggest lymphangiogenesis as a therapeutic avenue to stimulate hematopoietic and bone regeneration.

A radiomics and genomics-derived model for predicting metastasis and prognosis in colorectal cancer.

Approximately 50% of colorectal cancer (CRC) patients would develop metastasis with poor prognosis, therefore, it is necessary to effectively predict metastasis in clinical treatment. In this study, we aimed to establish a machine-learning model for predicting metastasis in CRC patients by considering radiomics and transcriptomics simultaneously. Here, 1023 patients with CRC from three centers were collected and divided into five queues (Dazhou Central Hospital n = 517, Nanchong Central Hospital n = 120 and the Cancer Genome Atlas (TCGA) n = 386). A total of 854 radiomics features were extracted from tumor lesions on CT images, and 217 differentially expressed genes were obtained from non-metastasis and metastasis tumor tissues using RNA sequencing. Based on radiotranscriptomic (RT) analysis, a novel RT model was developed and verified through genetic algorithms (GA). Interleukin (IL)-26, a biomarker in RT model, was verified for its biological function in CRC metastasis. Furthermore, 15 radiomics variables were screened through stepwise regression, which was highly correlated with the IL26 expression level. Finally, a radiomics model (RA) was established by combining GA and stepwise regression analysis with radiomics features. The RA model exhibited favorable discriminatory ability and accuracy for metastasis prediction in two independent verification cohorts. We designed multicenter, multi-scale cohorts to construct and verify novel combined radiomics and genomics models for predicting metastasis in CRC. Overall, RT model and RA model might help clinicians in directing personalized diagnosis and therapeutic regimen selection for patients with CRC.

RIP3 regulates doxorubicin-induced intestinal mucositis via FUT2-mediated α-1,2-fucosylation.

OBJECTIVE: Intestinal mucositis is one of the common side effects of anti-cancer chemotherapy. However, the molecular mechanisms involved in mucositis development remain incompletely understood. In this study, we investigated the function of receptor-interacting protein kinase 3 (RIP3/RIPK3) in regulating doxorubicin-induced intestinal mucositis and its potential mechanisms. METHODS: Intestinal mucositis animal models were induced in mice for in vivo studies. Rat intestinal cell line IEC-6 was used for in vitro studies. RNA­seq was used to explore the transcriptomic changes in doxorubicin-induced intestinal mucositis. Intact glycopeptide characterization using mass spectrometry was applied to identify α-1,2-fucosylated proteins associated with mucositis. RESULTS: Doxorubicin treatment increased RIP3 expression in the intestine and caused severe intestinal mucositis in the mice, depletion of RIP3 abolished doxorubicin-induced intestinal mucositis. RIP3-mediated doxorubicin-induced mucositis did not depend on mixed lineage kinase domain-like (MLKL) but on α-1,2-fucosyltransferase 2 (FUT2)-catalyzed α-1,2-fucosylation on inflammation-related proteins. Deficiency of MLKL did not affect intestinal mucositis, whereas inhibition of α-1,2-fucosylation by 2-deoxy-D-galactose (2dGal) profoundly attenuated doxorubicin-induced inflammation and mucositis. CONCLUSIONS: RIP3-FUT2 pathway is a central node in doxorubicin-induced intestinal mucositis. Targeting intestinal RIP3 and/or FUT2-mediated α-1,2-fucosylation may provide potential targets for preventing chemotherapy-induced intestinal mucositis.

Proteomic characteristics of the treatment trajectory of patients with COVID-19.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 has prompted global concern due to its profound impact on public health and the economy. Effective treatment of COVID-19 patients in the acute phase or of those with long COVID is a major challenge. Using data-independent acquisition (DIA) technology, we performed proteomic profiling on plasma samples from 22 COVID-19 patients and six healthy controls at Dazhou Central Hospital. Random forest and least absolute shrinkage and selection operator algorithms were used for analysis at various COVID-19 treatment stages. We identified 79 proteins that were differentially expressed between COVID-19 patients and healthy controls, mainly involving pathways associated with cell processes and binding. Across different treatment stages of COVID-19, five proteins-PI16, GPLD1, IGFBP3, KRT19, and VCAM1-were identified as potential molecular markers for dynamic disease monitoring. Furthermore, the proteins BTD, APOM, IGKV2-28, VWF, C4BPA, and C7 were identified as candidate biomarkers for distinguishing between SARS-CoV-2 positivity and negativity. Analysis of protein change profiles between the follow-up and healthy control groups highlighted cardiovascular changes as a concern for patients recovering from COVID-19. Our study revealed the infection profiles of SARS-CoV-2 at the protein expression level comparing different phases of COVID-19. DIA mass spectrometry analysis of plasma samples from COVID-19 patients undergoing treatment identified key proteins involved in signaling pathways that might be used as markers of the recovery phase. These findings provide insight for the development of therapy options and suggest potential blood biomarkers for COVID-19.

A Sedentary Lifestyle Changes the Composition and Predicted Functions of the Gut Bacterial and Fungal Microbiota of Subjects from the Same Company.

A sedentary lifestyle affects the diversity and composition of the gut microbiota, but previous studies have mainly focused on bacteria instead of fungi. Here, we compared both the fecal bacterial and fungal microbiota compositions and functions in sedentary persons and controls. Subjects from the China Railway Corporation, including 99 inspectors and 88 officials, were enrolled in our study. Fecal microbiota communities were analyzed using 16S rRNA gene sequencing for bacteria and ITS sequencing for fungi. We found that the diversity of the gut microbiota of the sedentary group was significantly lower than that of the control group (P < 0.05). The sedentary group had a higher abundance of Firmicutes, a lower abundance of Actinobacteria and Proteobacteria and a higher abundance of Ascomycota, and a lower abundance of Basidiomycota. Furthermore, functional prediction analysis of the fungal microbiota revealed more L-tryptophan degradation to 2-amino-3-carboxymuconate semialdehyde, more phospholipid remodeling (phosphatidylethanolamine, yeast), and more L-tyrosine degradation I, as well as less pentose phosphate pathway (non-oxidative branch), less adenosine nucleotide biosynthesis and less L-valine biosynthesis in the sedentary group (P < 0.05). Thus, a sedentary lifestyle changes the composition and function of the gut microbiota. It may change the pentose phosphate pathway (non-oxidative branch), nucleic acid and amino acid biosynthesis and phospholipid metabolism in fungi.

Preoperative prediction model of microvascular invasion in patients with hepatocellular carcinoma.

BACKGROUND: Microvascular invasion (MVI) is an adverse factor for the prognosis of patients with hepatocellular carcinoma (HCC). We aimed to construct a preoperative prediction model for MVI, thereby providing a reference for clinicians in formulating treatment options for HCC. METHODS: A total of 360 patients with non-metastatic HCC were retrospectively enrolled. We used logistic regression analysis to screen out independent risk factors for MVI and further constructed a predictive model for MVI. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: Logistic regression analysis revealed that fibrinogen (>4 g/L) (OR: 6.529), alpha-fetoprotein (≥ 400 ng/mL) (OR: 2.676), cirrhosis (OR: 2.25), tumor size (OR: 1.239), and poor tumor border (OR: 3.126) were independent risk factors of MVI. The prediction model of MVI had C-index of 0.746 and 0.772 in the training and validation cohorts, respectively. The calibration curves showed good agreement between actual and predicted MVI risk. Finally, DCA reveals that this model has good clinical utility. CONCLUSION: The nomogram-based model we established can predict the preoperative MVI well and provides reference for surgeons to make clinical treatment decisions.

Glycerophospholipid metabolism is involved in rheumatoid arthritis pathogenesis by regulating the IL-6/JAK signaling pathway.

To explore the metabolic mechanism of differential plasma interleukin (IL)-6 expression in patients with rheumatoid arthritis (RA). A total of 240 RA patients were enrolled in the non-target metabolomics study cohort and 69 healthy volunteers were included as healthy controls (HCs). Plasma IL-6 levels were detected by electrochemiluminescence assay. Plasma metabolites were detected by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Patients with active RA (n = 20) and remissive RA (n = 20) and 20 HCs were enrolled in the targeted validation cohort. Metabolites identified by non-target metabolomics were quantitatively analyzed by ultra-performance liquid chromatography-triple quadrupole tandem mass spectrometry. Effects of 1-oleoyl-sn-glycero-3-phosphocholine (OGPC) associated with IL-6 on MH7A cells were assessed. After 24-h or 48-h induction by TNF-α, the supernatants were collected for IL-6 quantification by enzyme-linked immunosorbent assay. Furthermore, Western blot was performed to investigate the relative JAK2 and p-JAK2 expressions. With an increasing IL-6 level, OGPC shown to be related to the glycerophospholipid metabolism pathway by Kyoto Encyclopedia of Genes and Genomes analysis displayed a significant decrease. In the validating RA cohort, the OGPC concentrations in remissive RA group and active RA group decreased compared with HC group. OGPC down-regulated IL-6 secretion and p-JAK2 expression in TNF-α-induced MH7A cells in vitro. In conclusion, glycerophospholipid metabolism is the main metabolic pathway associated with the differential IL-6 expression in RA patients. The down-regulated OGPC is a promoting factor for the increased IL-6 plasma level in RA patients, which further affects the downstream JAK signaling pathway.

Identification of upper GI diseases during screening gastroscopy using a deep convolutional neural network algorithm.

BACKGROUND AND AIMS: The clinical application of GI endoscopy for the diagnosis of multiple diseases using artificial intelligence (AI) has been limited by its high false-positive rates. There is an unmet need to develop a GI endoscopy AI-assisted diagnosis system (GEADS) to improve diagnostic accuracy and clinical utility. METHODS: In this retrospective, multicenter study, a convolutional neural network was trained to assess upper GI diseases based on 26,228 endoscopic images from Dazhou Central Hospital that were randomly assigned (3:1:1) to a training dataset, validation dataset, and test dataset, respectively. To validate the model, 6 external independent datasets comprising 51,372 images of upper GI diseases were collected. In addition, 1 prospective dataset comprising 27,975 images was collected. The performance of GEADS was compared with endoscopists with 2 professional degrees of expertise: expert and novice. Eight endoscopists were in the expert group with >5 years of experience, whereas 3 endoscopists were in the novice group with 1 to 5 years of experience. RESULTS: The GEADS model achieved an accuracy of .918 (95% confidence interval [CI], .914-.922), with an F1 score of .884 (95% CI, .879-.889), recall of .873 (95% CI, .868-.878), and precision of .890 (95% CI, .885-.895) in the internal validation dataset. In the external validation datasets and 1 prospective validation dataset, the diagnostic accuracy of the GEADS ranged from .841 (95% CI, .834-.848) to .949 (95% CI, .935-.963). With the help of the GEADS, the diagnosing accuracies of novice and expert endoscopists were significantly improved (P < .001). CONCLUSIONS: The AI system can assist endoscopists in improving the accuracy of diagnosing upper GI diseases.

Development and validation of a machine learning-derived radiomics model for diagnosis of osteoporosis and osteopenia using quantitative computed tomography.

BACKGROUND: To develop and validate a quantitative computed tomography (QCT) based radiomics model for discriminating osteoporosis and osteopenia. METHODS: A total of 635 patients underwent QCT were retrospectively included from November 2016 to November 2019. The patients with osteopenia or osteoporosis (N = 590) were divided into a training cohort (N = 414) and a test cohort (N = 176). Radiomics features were extracted from the QCT images of the third lumbar vertebra. Minimum redundancy and maximum relevance and least absolute shrinkage and selection operator were used for data dimensional reduction, features selection and radiomics model building. Multivariable logistic regression was applied to construct the combined clinical-radiomic model that incorporated radiomics signatures and clinical characteristics. The performance of the combined clinical-radiomic model was evaluated by the area under the curve of receiver operator characteristic curve (ROC-AUC), accuracy, specificity, sensitivity, positive predictive value, and negative predictive value. RESULTS: The patients with osteopenia or osteoporosis were randomly divided into training and test cohort with a ratio of 7:3. Six more predictive radiomics signatures, age, alkaline phosphatase and homocysteine were selected to construct the combined clinical-radiomic model for diagnosis of osteoporosis and osteopenia. The AUC of the combined clinical-radiomic model was 0.96 (95% confidence interval (CI), 0.95 to 0.98) in the training cohort and 0.96 (95% CI 0.92 to 1.00) in the test cohort, which were superior to the clinical model alone (training-AUC = 0.81, test-AUC = 0.79). The calibration curve demonstrated that the radiomics nomogram had good agreement between prediction and observation and decision curve analysis confirmed clinically useful. CONCLUSIONS: The combined clinical-radiomic model that incorporates the radiomics score and clinical risk factors, can serve as a reliable and powerful tool for discriminating osteoporosis and osteopenia.

Design, Synthesis and Bioactivity Evaluation of Coumarin-BMT Hybrids as New Acetylcholinesterase Inhibitors.

Coumarin possesses the aromatic group and showed plentiful activities, such as antioxidant, preventing asthma and antisepsis. In addition, coumarin derivatives usually possess good solubility, low cytotoxicity and excellent cell permeability. In our study, we synthesized the compound bridge methylene tacrine (BMT), which has the classical pharmacophore structure of Tacrine (THA). Based on the principle of active substructure splicing, BMT was used as a lead compound and synthesized coumarin-BMT hybrids by introducing coumarin to BMT. In this work, 21 novel hybrids of BMT and coumarin were synthesized and evaluated for their inhibitory activity on AChE. All obtained compounds present preferable inhibition. Compound 8b was the most active compound, with the value of Ki as 49.2 nM, which was higher than Galantamine (GAL) and lower than THA. The result of molecular docking showed that the highest binding free energy was -40.43 kcal/mol for compound 8b, which was an identical trend with the calculated Ki.

Newly Designed Quinazolinone Derivatives as Novel Tyrosinase Inhibitor: Synthesis, Inhibitory Activity, and Mechanism.

We synthesized a series of quinazolinone derivates as tyrosinase inhibitors and evaluated their inhibition constants. We synthesized 2-(2,6-dimethylhepta-1,5-dien-1-yl)quinazolin-4(3H)-one (Q1) from the natural citral. The concentration, which led to 50% activity loss of Q1, was 103 ± 2 µM (IC50 = 103 ± 2 µM). Furthermore, we considered Q1 to be a mixed-type and reversible tyrosinase inhibitor, and determined the KI and KIS inhibition constants to be 117.07 µM and 423.63 µM, respectively. Our fluorescence experiment revealed that Q1 could interact with the substrates of tyrosine and L-DOPA in addition to tyrosinase. Molecular docking studies showed that the binding of Q1 to tyrosinase was driven by hydrogen bonding and hydrophobicity. Briefly, the current study confirmed a new tyrosinase inhibitor, which is expected to be developed into a novel pigmentation drug.

Association of polymorphisms in endothelial dysfunction-related genes with susceptibility to essential hypertension in elderly Han population in Liaoning province, China.

Hypertension is a complex disease which is mainly influenced by genetic factors. Recently, genome-wide association study (GWAS) found three novel endothelial dysfunction-related sites: Vascular endothelial growth factor A (VEGFA) rs9472135, Faciogenital dysplasia 5 (FGD5) rs11128722, Zinc Finger C3HC-type Containing 1 (ZC3HC1) rs11556924. Endothelial dysfunction is one of the early events in pathophysiology of essential hypertension. To investigate the association of endothelial dysfunction-related genes with essential hypertension, we conducted a case-control study of 431 patients with hypertension and 345 controls. The polymorphisms were detected using Taqman Probe. The alleles and genotypes of ZC3HC1 rs11556924 and VEGFA rs9472135 were not statistically different between the two groups, while the allele of FGD5 rs11128722 was different [P = 0.045, OR = 1.265, 95% CI = (1.009-1.586)], especially in the male [P = 0.035, OR = 1.496, 95% CI = (1.037-2.158)]. Analyzing the different of genotype distribution of 3 SNPs in the two groups under different genetic models, the genotypes of FGD5 rs11128722 showed difference in male under dominant model [P = 0.049, OR = 1.610, 95% CI = (1.018-2.544)]. The polymorphism of FGD5 rs11128722 had a significant difference in Body Mass Index (BMI) among different genotypes; In the additive genetic model, BMI of GA genotype was higher than that of GG (P = 0.038); GA + AA was higher than GG in the dominant genetic model (P = 0.011). In our study, we found that the polymorphisms of VEGFA rs9472135 and ZC3HC1 rs11556924 may not significantly associated with the risk of essential hypertension, and FGD5 rs11128722 may increase the risk of it, especially in elderly men.

Meta-analysis of genotype and phenotype studies to confirm the predictive role of the RNF213 p.R4810K variant for moyamoya disease.

BACKGROUND AND PURPOSE: The aim of this meta-analysis study was to assess the predictive effects of RNF213 p.R4810K on phenotype in moyamoya disease (MMD). METHODS: Electronic databases (e.g., Pubmed and EMBASE) were searched, and relevant articles published up to August 2020 were retrieved. Review Manager 5.3 and Stata 12.0 were used for all statistical analyses. Pooled odds ratios, with 95% confidence intervals, and three comparison models were evaluated to analyze the association between RNF213 pR4810K variant and clinical characteristics of MMD patients using a fixed-effects model. RESULTS: A total of 2798 patients with MMD were selected and the effects of the heterozygous or homozygous RNF213 p.R4810K variant on 18 clinical features were identified. There were more patients aged <15 years in the GA and AA groups (AA vs GA: p = 0.009; AA vs GG: p = 0.003; GA vs GG: p = 0.001). Among homozygous patients, the majority experienced MMD onset before the age of 4 years (AA vs. GA: p < 0.00001; AA vs GG: p < 0.00001). The frequency of infarctions and transient ischemic attack was significantly higher in homozygotes and heterozygotes，respectively. However, the frequency of intracerebral/intraventricular hemorrhage was lower in patients with the GA than the GG genotype. More MMD patients with AA and GA genotypes had a family history of the disease (p = 0.003, p < 0.00001, respectively). Posterior cerebral artery involvement was more common in patients with the GA genotype (p < 0.00001). CONCLUSION: The homozygous or heterozygous RNF213 variant may be an efficient biomarker with which to classify different clinical phenotypes of MMD.

Clinical characteristics of inpatients with coronavirus disease 2019 (COVID-19) in Sichuan province.

BACKGROUND: The outbreak of COVID-19 has resulted in serious concerns in China and abroad. To investigate clinical features of confirmed and suspected patients with COVID-19 in west China, and to examine differences between severe versus non-severe patients. METHODS: Patients admitted for COVID-19 between January 21 and February 11 from fifteen hospitals in Sichuan Province, China were included. Experienced clinicians trained with methods abstracted data from medical records using pre-defined, pilot-tested forms. Clinical characteristics between severe and non-severe patients were compared. RESULTS: Of the 169 patients included, 147 were laboratory-confirmed, 22 were suspected. For confirmed cases, the most common symptoms from onset to admission were cough (70·7%), fever (70·5%) and sputum (33·3%), and the most common chest CT patterns were patchy or stripes shadowing (78·0%); throughout the course of disease, 19·0% had no fever, and 12·4% had no radiologic abnormality; twelve (8·2%) received mechanical ventilation, four (2·7%) were transferred to ICU, and no death occurred. Compared to non-severe cases, severe ones were more likely to have underlying comorbidities (62·5% vs 26·2%, P = 0·001), to present with cough (92·0% vs 66·4%, P = 0·02), sputum (60·0% vs 27·9%, P = 0·004) and shortness of breath (40·0% vs 8·2%, P <  0·0001), and to have more frequent lymphopenia (79·2% vs 43·7%, P = 0·003) and eosinopenia (84·2% vs 57·0%, P = 0·046). CONCLUSIONS: The symptoms of patients in west China were relatively mild, and an appreciable proportion of infected cases had no fever, warranting special attention.

A novel prognostic model based on epithelial-mesenchymal transition-related genes predicts patient survival in gastric cancer.

BACKGROUND: Gastric cancer (GC) represents a major malignancy and is the third deathliest cancer globally. Several lines of evidence indicate that the epithelial-mesenchymal transition (EMT) has a critical function in the development of gastric cancer. Although plentiful molecular biomarkers have been identified, a precise risk model is still necessary to help doctors determine patient prognosis in GC. METHODS: Gene expression data and clinical information for GC were acquired from The Cancer Genome Atlas (TCGA) database and 200 EMT-related genes (ERGs) from the Molecular Signatures Database (MSigDB). Then, ERGs correlated with patient prognosis in GC were assessed by univariable and multivariable Cox regression analyses. Next, a risk score formula was established for evaluating patient outcome in GC and validated by survival and ROC curves. In addition, Kaplan-Meier curves were generated to assess the associations of the clinicopathological data with prognosis. And a cohort from the Gene Expression Omnibus (GEO) database was used for validation. RESULTS: Six EMT-related genes, including CDH6, COL5A2, ITGAV, MATN3, PLOD2, and POSTN, were identified. Based on the risk model, GC patients were assigned to the high- and low-risk groups. The results revealed that the model had good performance in predicting patient prognosis in GC. CONCLUSIONS: We constructed a prognosis risk model for GC. Then, we verified the performance of the model, which may help doctors predict patient prognosis.

Clinical and Genetic Risk Factors of Long-Term Outcomes after Encephaloduroarteriosynangiosis in Moyamoya Disease in China.

OBJECTIVES: This retrospective study was conducted to analyze the associations between ring finger protein 213 p.R4810K variant, clinical features and long-term outcomes in patients with moyamoya disease (MMD) after encephaloduroarteriosynangiosis treatment. MATERIALS AND METHODS: A total of 2,545 patients with MMD in China were included in this study (median of follow-up duration: 32.00 months). Multiple Cox regression models were used to assess the associations between p.R4810K variant, clinical features and long-term outcomes. RESULTS: For all patients, in multivariate Cox analysis, no association was observed between p.R4810K and long-term outcomes. Pediatric onset (HR, 0.38; 95%CI, 0.25-0.59) and headache (HR, 0.26; 95%CI, 0.08-0.83) were inversely and hypertension (HR, 1.43 95%CI, 1.06-1.94), diabetes (HR, 1.55; 95%CI, 1.00-2.40), bilateral lesions (HR, 2.73; 95%CI, 1.12-6.65) and posterior cerebral artery involvement (HR, 1.44; 95%CI, 1.08-1.90) were positively associated with follow-up stroke (all P < 0.05). Pediatric onset (HR, 0.46; 95%CI, 0.26-0.82) was inversely and hyperlipidemia (HR, 1.83; 95%CI, 1.23-2.73), smoking (HR, 1.86; 95%CI, 1.13-3.07), high Suzuki angiographic stage (HR, 1.71, 95%CI, 1.09-2.70), poor admission neurologic status (HR, 8.93; 95%CI, 6.49-12.29) and follow-up stroke (HR, 8.31; 95%CI, 6.01-11.49) were positively associated with poor neurologic outcome at the last follow-up visit (all P < 0.05). The factors were not consistent in the different groups of age at onset. CONCLUSIONS: In our study, p.R4810K may play no role in long-term outcomes in Chinese MMD. Clinical features including age at onset, initial symptoms, risk factors of stroke, imaging, poor admission neurologic status were associated with poor outcomes in MMD after EDAS.

Validation and Extension Study Exploring the Role of RNF213 p.R4810K in 2,877 Chinese Moyamoya Disease Patients.

OBJECTIVE: To validate, update, and extend the role of RNF213 p.R4810K (G>A) for predicting the phenotype of moyamoya disease (MMD) patients and explore the different effects on pediatric and adult groups. METHODS: A total of 2,877 patients conducted from 2004 to 2018 were included. Review Manage 5.3 and SPSS 20.0 were applied to complete all statistical analyses. Information on age at onset, sex, initial symptom, family history and complications were obtained via retrospective chart review. Angiographic records were evaluated. RESULTS: In China, geographic proximity to Korea or Japan may affect the carrying rate of RNF213 p.R4810K. The proportion of patients with the following characteristics was significantly higher (P <0.017) in the GA than in the GG group: female, age at onset < 18 years, infarct after transient ischemic attack, family history of MMD, and posterior cerebral artery involvement. For pediatric patients, GA showed more cerebral hemorrhage (CH) (odds ratios (ORs) [95% confidence intervals (CIs)] = 3.99 (1.61-9.88), P = 0.003), more patients were in the Suzuki early and intermediate stage (P = 0.001; P = 0.001, respectively), while for the adult group, GA indicated more female (OR [95% CIs] = 1.43 [1.15-1.79], P = 0.001), fewer patients with diabetes (0.58 [0.38-0.86], P = 0.007) and intermediate Suzuki stage (P = 3.70 × 10-4). CONCLUSIONS: The incidence and carrying rates of RNF213 p.R4810K in various regions for Chinese MMD patients were obviously different. RNF213 p.R4810K has different predictive effects on phenotypes of pediatric and adult patients.

Association of Genetic Variants With Moyamoya Disease in 13 000 Individuals: A Meta-Analysis.

Background and Purpose- A growing body of evidence indicates genetic components play critical roles in moyamoya disease (MMD). Firm conclusions from studies of this disease have been stymied by small sample sizes and a lack of replicative results. This meta-analysis was conducted to determine whether these genetic polymorphisms are associated with MMD. Methods- PubMed, Google Scholar, Embase, Wanfang, Web of Science, and China National Knowledge Infrastructure databases were used to identify potentially relevant studies published until January 2020. The Review Manager 5.2 and Stata 15.0 software programs were used to perform the statistical analysis. Heterogeneity was assessed using the Cochran Q test and quantified using the I2 test. Results- Four thousand seven hundred eleven MMD cases and 8704 controls in 24 studies were included, evaluating 7 polymorphisms in 6 genes. The fixed-effect odds ratios (95% CI) in allelic model of MMP-2 rs243865 were 0.60 (0.41-0.88) (P=0.008). In the country-based subgroup analysis, the fixed-effect odds ratios (95% CI) of RNF213 rs112735431 in allelic model were China, 39.74 (26.63-59.31), Japan, 74.65 (42.79-130.24) and Korea, 50.04 (28.83-86.88; all P<0.00001). In the sensitivity analysis, the fixed-effect odds ratios (95% CI) of allelic and dominant models were the RNF213 rs148731719 variant, 2.17 (1.36-3.48; P=0.001), 2.20 (1.35-3.61; P=0.002), the TIMP-2 rs8179090 variant, 0.33 (0.25-0.43; P<0.00001), 0.88 (0.65-1.21; P=0.440) and the MMP-3 rs3025058 variant, 0.61 (0.47-0.79; P=0.0002), 0.55 (0.41-0.75; P=0.0001), respectively. Conclusions- RNF213 rs112735431 and rs148731719 were positively, and TIMP-2 rs8179090, MMP-2 rs243865, and MMP-3 rs3025058 were inversely associated with MMD using multiple pathophysiologic pathways. Studies in larger population should be conducted to clarify whether and how these variants are associated with MMD.

Effects of TNF-α-308G/A Polymorphism on the Risk of Diabetic Nephropathy and Diabetic Retinopathy: An Updated Meta-Analysis.

Diabetic nephropathy (DN) and diabetic retinopathy (DR) are the major factors of morbidity and mortality in the patients with diabetes mellitus (DM). Growing studies have investigated the relationship between the TNF-α-308G/A polymorphism and the susceptibility to DN and DR, without achieving consensus. Thus, we conducted this meta-analysis to reach more comprehensive conclusions for these issues. Eligible studies were retrieved through electronic databases such as PubMed, Embase, Web of Science and China National Knowledge Infrastructure. Summary of odds ratios (OR) and 95% confidence intervals (CIs) were generated to evaluate the intensity of the associations. Statistical analyses were performed by STATA 11.0 and RevMan 5.2. There are fourteen eligible publications involving nineteen studies in this meta-analysis. TNF-α-308G/A polymorphism was significantly related to increasing risk of DN under recessive model (OR=1.37, 95% CI=1.03-1.83) and homozygous model (OR=1.54, 95% CI=1.15-2.06). Moreover, the similar results were also obtained in Asian groups for DN (recessive: OR=1.69, 95% CI=1.18-2.42; homozygous: OR=1.99, 95% CI=1.38-2.86; respectively), and significant association was also detected between TNF-α-308G/A and DN susceptibility in type 2 DM in recessive model (OR=1.39, 95% CI=1.02-1.89). No significant association was observed between TNF-α-308G/A and DR susceptibility in total analyses and subgroup analyses by ethnicity and type of DM. TNF-α-308G/A polymorphism may enhance the susceptibility to diabetic nephropathy, especially in Asian population and in T2DM patients, but not diabetic retinopathy.

Association of MTHFR gene polymorphisms with pancreatic cancer: meta-analysis of 17 case-control studies.

BACKGROUND: Pancreatic cancer (PC) is a seriously malignant tumor with a low 5-year survival rate. The relationship between methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms and PC has been reported by several studies. However, the results were controversial. Thus, we conducted a meta-analysis to summarize available data on MTHFR gene and PC. METHODS: We searched PubMed, Embase, Web of Science, Wanfang, CNKI databases prior to July 2019. Data were analyzed by RevMan 5.3 and STATA 12.0 software. Odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the strength of the association. Subgroup analysis, sensitivity analysis and assessment of publication bias were performed in this study. RESULTS: Ten articles with 17 reports (10 for C677T, 7 for A1298C) were eligible for inclusion in the meta-analysis (1864 cases and 3165 controls for C677T, and 1488 cases and 1946 controls for A1298C). Our meta-analysis detected that C677T was associated with PC for three genetic models (allele model: OR = 1.24, 95% CI: 1.00-1.53, P = 0.047; recessive model: OR = 1.39, 95% CI: 1.04-1.86, P = 0.027; homozygous model: OR = 1.60, 95% CI: 1.04-2.45, P = 0.034). In the stratified analyses according to ethnicity, source of controls and genotyping method, significant association was observed in genotyping method subgroup. For the A1298C polymorphism, no significant association was observed either in overall analysis or in subgroup analysis under all genetic models. CONCLUSIONS: MTHFR gene C677T rather than A1298C polymorphism may be associated with PC. Larger sample size studies should be performed to find the association between MTHFR gene and PC.