BACKGROUND: The American Heart Association recently released a new cardiovascular health (CVH) metric, Life's Essential 8 (LE8), for health promotion. However, the association between LE8 scores and the risk of chronic kidney disease (CKD) remains uncertain. We aimed to explore the association of LE8 scores with new-onset CKD and examine whether socioeconomic deprivation and genetic risk modify this association. METHODS: A total of 286,908 participants from UK Biobank and without prior CKD were included between 2006 and 2010. CVH was categorized using LE8 scores: low (LE8 scores <50), moderate (LE8 scores ≥50 but <80), and high (LE8 scores ≥80). The study outcome was new-onset CKD, ascertained by data linkage with primary care, hospital inpatient, and death data. Cox proportional hazard regression models were used to investigate the association between CVH categories and new-onset CKD. RESULTS: During a median follow-up of 12.5 years, 8857 (3.1%) participants developed new-onset CKD. Compared to the low CVH group, the moderate (adjusted hazards ratio [HR], 0.50; 95% confidence interval [CI]: 0.47-0.53) and high CVH (adjusted HR, 0.31; 95% CI: 0.27-0.34) groups had a significantly lower risk of developing new-onset CKD. The population-attributable risk associated with high vs. intermediate or low CVH scores was 40.3%. Participants who were least deprived ( vs.  most deprived; adjusted HR, 0.75; 95% CI: 0.71-0.79) and with low genetic risk of CKD ( vs.  high genetic risk; adjusted HR, 0.89; 95% CI: 0.85-0.94) had a significantly lower risk of developing new-onset CKD. However, socioeconomic deprivation and genetic risks of CKD did not significantly modify the relationship between LE8 scores and new-onset CKD (both P -interaction >0.05). CONCLUSION Achieving a higher LE8 score was associated with a lower risk of developing new-onset CKD, regardless of socioeconomic deprivation and genetic risks of CKD.
Humans ; Renal Insufficiency, Chronic/epidemiology* ; Male ; Female ; Middle Aged ; Genetic Predisposition to Disease/genetics* ; Aged ; Risk Factors ; Adult ; Proportional Hazards Models ; Socioeconomic Factors

OBJECTIVES: Sepsis-associated encephalopathy (SAE) is a common complication of sepsis, which can lead to long-term cognitive impairment and anxiety in patients, and may even contribute to mortality in septic individuals. There is substantial individual variability in the incidence and severity and susceptibility of SAE, but the mechanisms regulating susceptibility remain unclear. Previous studies have shown that hippocampal damage is directly associated with cognitive and emotional disturbances in SAE. This study aims to explore the impact of hippocampal differentially expressed genes on SAE susceptibility in a mouse model. METHODS: Male specific pathogen-free (SPF)-grade C57BL/6 mice (6-8 weeks old) were randomly divided into a saline control group (Con group) and an SAE model group. SAE was induced by intraperitoneal injection of 10 mg/kg lipopolysaccharide (LPS), while control mice received an equivalent volume of saline. Cognitive and anxiety-like behaviors were assessed using the open field test (OFT), novel object recognition (NOR), and Y-maze test. Based on mean±standard deviation of behavioral results from the Con group, SAE mice were further classified into high-sensitivity (HS) and low-sensitivity (LS) subgroups. Immunohistochemistry was performed to detect the expression of immediate early gene c-Fos and neuronal marker neuronal nuclei (NeuN). Nissl staining was used to assess neuronal injury in the dentate gyrus (DG), cornu ammonis 1 (CA1), and cornu ammonis 3 (CA3) regions of the hippocampus. RNA sequencing (RNA-seq) was conducted on hippocampal tissues from HS and LS mice to identify differentially expressed genes, followed by pathway enrichment analysis. RESULTS: No significant behavioral susceptibility differences were observed between the overall SAE group and controls. However, HS mice showed severer cognitive deficits and anxiety-like behavior compared to LS mice. Immunohistochemistry revealed significantly higher expression of c-Fos in the hippocampus of LS mice (P<0.05), while Nissl and NeuN staining revealed milder neuronal damage in the hippocampus of LS mice than that of HS mice (both P<0.05). RNA-seq analysis identified 130 upregulated and 142 downregulated DEGs in LS and HS mice, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that upregulated genes in LS mice were primarily involved in pluripotency regulation, cyclic adenosine monophosphate (cAMP) signaling, and Wnt signaling pathways, in contrast, the downregulated genes were mainly related to cell adhesion, neuroactive ligand-receptor interaction, and calcium signaling pathways. CONCLUSIONS Differential gene expression in the hippocampus may contribute to individual susceptibility to cognitive and emotional dysfunction in SAE, suggesting potential genetic targets for individualized intervention.
Animals ; Sepsis-Associated Encephalopathy/genetics* ; Male ; Hippocampus/pathology* ; Mice, Inbred C57BL ; Mice ; Anxiety/genetics* ; Lipopolysaccharides ; Genetic Predisposition to Disease ; Disease Models, Animal ; Sepsis/genetics*

This paper aimed to explore the antidepressant effect of the essential oil from Schizonepeta tenuifolia Briq.(EOST) on the treatment of depression and its mechanism by using a combination of network pharmacology and the mouse model of lipopolysaccharide(LPS)-induced depression. The chemical components in EOST were identified using gas chromatography-mass spectrometer(GC-MS), and 12 active components were selected as the study objects. The targets related to EOST were obtained by Traditional Chinese Medicines Systems Pharmacology(TCMSP) and SwissTargetPrediction database. The targets related to depression were screened out through GeneCards, Therapeutic Target Database(TTD), and Online Mendelian Inheritance in Man(OMIM) database. The Venny 2.1 was applied to screen out the common targets of EOST and depression. The targets were imported into Cytoscape 3.7.2 to generate "drug-active component-diease-target" network diagram. The protein-protein interaction(PPI) network was constructed using STRING 11.5 database and Cytoscape 3.7.2, and the core targets were screened out. DAVID 6.8 database was used for Gene Ontology(GO) func-tional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and subsequently the enrichment results were visualized through the bioinformatics platform. The mouse model of depression was induced by intraperitoneally injecting with LPS in mice. Before modeling, mice were administrated orally with EOST. The antidepressant effect of EOST was evalua-ted by tail suspension test(TST), forced swimming test(FST), and novelty suppressed feeding test(NSFT) after modeling. The content of interleukin(IL)-1β was determined by enzyme-linked immunosorbent assay(ELISA), and the protein expression levels of IL-1β and pro IL-1β in the hippocampus were determined by Western blot. There were 12 main components and 179 targets in EOAT, of which, 116 targets were related to depression, mainly involved in neuroactive ligand-receptor interaction, calcium signaling pathway, and cyclic adenosine monophosphate(cAMP) signaling pathway. Biological processes such as synaptic signal transduction, G-protein coupled receptor signaling pathway, and chemical synaptic transmission were involved. Molecular functions such as neurotransmitter receptor activity, RNA polymerase Ⅱ transcription factor activity, and heme binding were involved. In mice experiments, the results showed that EOST at 100 mg·kg~(-1) and 50 mg·kg~(-1) significantly shortened the immobility time in TST and FST as well as the feeding latency in NSFT compared with the model group, decreased the levels of serum IL-1β and NO, and reduced the protein expression levels of IL-1β and pro IL-1β in the hippocampus. In conclusion, EOST shows a good antidepressant effect in a multi-component, multi-target, and multi-pathway manner. The mechanism may be attributed to the fact that EOST can down-regulate the protein expression levels of IL-1β and pro IL-1β, decrease the release of inflammatory factors, and reduce neuroinflammation response.
Animals ; Mice ; Oils, Volatile ; Depression ; Lipopolysaccharides ; Network Pharmacology ; Databases, Genetic ; Calcium Signaling ; Disease Models, Animal

The generation of a tau-V337M point mutation mouse model using gene editing technology can provide an animal model with fast disease progression and more severe symptoms, which facilitate the study of pathogenesis and treatment of Alzheimer's disease (AD). In this study, single guide RNAs (sgRNA) and single-stranded oligonucleotides (ssODN) were designed and synthesized in vitro. The mixture of sgRNA, Cas9 protein and ssODN was microinjected into the zygotes of C57BL/6J mice. After DNA cutting and recombination, the site homologous to human 337 valine (GTG) in exon 11 was mutated into methionine (ATG). In order to improve the efficiency of recombination, a Rad51 protein was added. The female mice mated with the nonvasectomy male mice were used as the surrogates. Subsequently, the 2-cell stage gene edited embryos were transferred into the unilateral oviduct, and the F0 tau-V337M mutation mice were obtained. Higher mutation efficiency could be obtained by adding Rad51 protein. The F0 tau-V337M point mutation mice can pass the mutation on to the F1 generation mice. In conclusion, this study successfully established the first tau-V337M mutation mouse by using Cas9, ssODN and Rad51. These results provide a new method for developing AD mice model which can be used in further research on the pathogenesis and treatment of AD.
Animals ; Male ; Female ; Mice ; Humans ; CRISPR-Cas Systems/genetics* ; RNA, Guide, CRISPR-Cas Systems ; Rad51 Recombinase/genetics* ; Mice, Inbred C57BL ; Disease Models, Animal ; Recombination, Genetic

OBJECTIVES: To derive general formulas for calculating commonly used kinship index (KI). METHODS: By introducing the Kronecker symbol, the formulas used to calculate the same KI under different genotype combinations were summarized into a unified expression. RESULTS: The general formulas were successfully derived for KI in various case situations, including the paternity index, full sibling index, half sibling index, avuncular index, grandpaternity index, first-cousin index, and second-cousin index between two individuals without or with the mother being involved; grandpaternity index between grandparents and a grandchild without or with the mother being involved; half sibling index between two children with two mothers being involved; full sibling index among three children; and half sibling index among three children with no, one, or two mothers being involved. CONCLUSIONS The general formulas given in this study simplify the calculation of KIs and facilitate fast and accurate calculation through programming.
Female ; Child ; Humans ; Paternity ; Siblings ; Genotype ; Mothers ; Models, Genetic

OBJECTIVE: To compare the accuracy of five warfarin-dosing algorithms and warfarin stable dose model (2.5 mg/day) for Shandong population. METHODS: One hundred and twenty five patients who achieved stable warfarin dose were enrolled. Clinical and genetic data were used to evaluate the value of each algorithm by calculating the percentage of patients whose predicted warfarin dose was within 20% of the actual stable therapeutic dose and mean absolute error (MAE). RESULTS: The frequency of patients with CYP2C9*1/*1, CYP2C9*1/*3 and CYP2C9*1/*2 genotype was 92.00%, 7.20%, 0.80%, respectively. That of VKORC1-1639 AA, AG and GG genotype was 82.40%, 15.20%, 2.40%, respectively. CYP4F2*1/*1, *1/*3, *3/*3 genotype was 50.40%, 39.20%, 10.40%, respectively. With the same genotypes for other loci, patients who carried at least one VKORC1-16398G mutant allele had increased warfarin stable daily dose compared with VKORC1-1639AA. Compared with CYP4F2*1/*1, those carrying at least one CYP4F2*3 mutant allele had warfarin stable daily dose increased by 5.9%-13.00%. The percentage of ideal prediction calculated from IWPC model (59.20%), Huang model (57.60%) and Ohno model (52.80%) were higher than others. The MAE were 0.35 (95%CI: 0.11-0.49), 0.15 (95%CI: 0.10-0.32), 0.39 (95%CI: 0.12-0.51), respectively. CONCLUSION The polymorphisms of CYP2C9, VKORC1 and CYP4F2 genes can influence the stable dose of warfarin in Shandong population. IWPC algorithm is suitable for guiding the use of warfarin in this population.
Anticoagulants ; administration & dosage ; Aryl Hydrocarbon Hydroxylases ; Cytochrome P-450 CYP2C9 ; genetics ; Cytochrome P450 Family 4 ; genetics ; Dose-Response Relationship, Drug ; Genotype ; Humans ; Models, Theoretical ; Polymorphism, Genetic ; Vitamin K Epoxide Reductases ; genetics ; Warfarin ; administration & dosage

The 2019 novel coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has occurred in China and around the world. SARS-CoV-2-infected patients with severe pneumonia rapidly develop acute respiratory distress syndrome (ARDS) and die of multiple organ failure. Despite advances in supportive care approaches, ARDS is still associated with high mortality and morbidity. Mesenchymal stem cell (MSC)-based therapy may be an potential alternative strategy for treating ARDS by targeting the various pathophysiological events of ARDS. By releasing a variety of paracrine factors and extracellular vesicles, MSC can exert anti-inflammatory, anti-apoptotic, anti-microbial, and pro-angiogenic effects, promote bacterial and alveolar fluid clearance, disrupt the pulmonary endothelial and epithelial cell damage, eventually avoiding the lung and distal organ injuries to rescue patients with ARDS. An increasing number of experimental animal studies and early clinical studies verify the safety and efficacy of MSC therapy in ARDS. Since low cell engraftment and survival in lung limit MSC therapeutic potentials, several strategies have been developed to enhance their engraftment in the lung and their intrinsic, therapeutic properties. Here, we provide a comprehensive review of the mechanisms and optimization of MSC therapy in ARDS and highlighted the potentials and possible barriers of MSC therapy for COVID-19 patients with ARDS.
Adoptive Transfer ; Alveolar Epithelial Cells ; pathology ; Animals ; Apoptosis ; Betacoronavirus ; Body Fluids ; metabolism ; CD4-Positive T-Lymphocytes ; immunology ; Clinical Trials as Topic ; Coinfection ; prevention & control ; therapy ; Coronavirus Infections ; complications ; immunology ; Disease Models, Animal ; Endothelial Cells ; pathology ; Extracorporeal Membrane Oxygenation ; Genetic Therapy ; methods ; Genetic Vectors ; administration & dosage ; therapeutic use ; Humans ; Immunity, Innate ; Inflammation Mediators ; metabolism ; Lung ; pathology ; physiopathology ; Mesenchymal Stem Cell Transplantation ; methods ; Mesenchymal Stem Cells ; physiology ; Multiple Organ Failure ; etiology ; prevention & control ; Pandemics ; Pneumonia, Viral ; complications ; immunology ; Respiratory Distress Syndrome, Adult ; immunology ; pathology ; therapy ; Translational Medical Research

PURPOSE: Interleukin-1 beta (IL-1β), a pro-inflammatory cytokine, has been shown to influence breast cancer susceptibility. The relationship between its risk of breast cancer and IL-1β-C31T polymorphism has been demonstrated, but the results remain controversial. Therefore, our study aimed to investigate the correlation between the IL-1β-C31T gene polymorphism and susceptibility to breast cancer. METHODS: The genotype frequencies of IL-1β-C31T polymorphism were compared between 204 breast cancer cases and 210 controls using polymerase chain reaction and restriction fragment length polymorphism techinques. Further multivariate binary logistic regression analyses were used to assess the association between IL-1β-C31T polymorphism and breast cancer risk. RESULTS: The frequency of the T allele of IL-1β-C31T polymorphism in breast cancer cases was significantly higher than that in the controls (56.1% vs. 47.9%). The frequencies of genotypes CC, CT, and TT in the cases were 22.1%, 43.6%, and 34.3%, respectively, while in the control group they were 24.3%, 55.7%, and 20.0%, respectively. There was a significant difference between the prevalence of TT genotype in the 2 groups (adjusted odds ratio [OR], 2.06; 95% confidence interval [CI], 1.16–3.66; p  =  0.014). Breast cancer risk increased in women with TT genotype, body mass index (BMI) ≥ 25 kg/m2 (OR, 2.19; 95% CI, 1.09–4.36), late age at first birth (OR, 2.43; 95% CI, 1.29–4.56), postmenopausal status (OR, 3.15; 95% CI, 1.39–7.16), and negative smoking history (OR, 2.52; 95% CI, 1.32–4.82). Furthermore, increase in breast cancer risk among women diagnosed with invasive ductal carcinoma was associated with CT/TT genotypes (OR, 2.82; 95% CI, 1.38–5.76). CONCLUSION: The IL-1β-C31T polymorphism affects breast cancer susceptibility, especially in women with late age at first birth, high BMI, postmenopausal status, negative smoking history, and invasive ductal carcinoma. Our study adds to the evidence about the importance of IL-1β-C31T polymorphism in breast cancer susceptibility.
Alleles ; Birth Order ; Body Mass Index ; Breast Neoplasms ; Breast ; Carcinoma, Ductal ; Female ; Genetic Predisposition to Disease ; Genotype ; Humans ; Interleukin-1beta ; Logistic Models ; Odds Ratio ; Polymerase Chain Reaction ; Polymorphism, Genetic ; Polymorphism, Restriction Fragment Length ; Prevalence ; Smoke ; Smoking

Accumulating evidence suggested that long noncoding RNAs (lncRNAs) possess a potential role in prostate cancer (PCa) diagnosis and prognosis. Rapid biochemical recurrence (BCR) is considered as a sign for clinical recurrence metastasis and PCa-specific mortality. Hence, the aim of the present study was to identify a lncRNA signature that can predict BCR of PCa accurately. Bioinformatics analysis, Kaplan-Meier analyses, Cox regression analyses, and Gene Set Enrichment Analysis (GSEA) were performed in a publicly available database with 499 PCa tissues and 52 matched normal tissues. A signature was identified. All these lncRNAs were differentially expressed between tumor and normal tissues and differentially expressed between high Gleason score and low Gleason score tissues. Furthermore, we developed a seven lncRNAs signature that can predict PCa BCR. Patients classified into low-risk group showed better BCR survival significantly than the patients in the high-risk group (hazard ratio = 0.32, 95% CI: 0.20-0.52, concordance index = 0.63). The area under the curve was 0.68 for BCR. The signature also had good discrimination for BCR in men with Gleason 7 PCa. In conclusion, our results suggest that the seven lncRNAs signature is a new biomarker of BCR and high risk in PCa. In addition, the individual lncRNA warrants further study to uncover the associated mechanisms of PCa progression and the signature could be used to design direct clinical trials for adjuvant therapy.
Biomarkers, Tumor/genetics* ; Genetic Predisposition to Disease/genetics* ; Humans ; Kaplan-Meier Estimate ; Male ; Middle Aged ; Neoplasm Grading ; Neoplasm Recurrence, Local/genetics* ; Prognosis ; Proportional Hazards Models ; Prostatic Neoplasms/genetics* ; RNA, Long Noncoding/genetics* ; Risk Assessment

OBJECTIVE: Deep learning models, including recurrent neural network (RNN) and gated recurrent unit (GRU), were used to construct the clinical prognostic prediction models for peritoneal dialysis (PD) patients based on routine clinical data. The performance of the RNN and GRU were compared with logistic regression (LR), which is commonly used in medical researches. The possible underlining clinical implications based on the result from the GRU model were also investigated. METHODS: We used the clinical data from the PD center of Peking University Third Hospital as the data source. Both the baseline data at the beginning of dialysis, and the follow-up and prognostic data of the patients were used by the RNN and GRU prediction models. The hyper-parameters were tuned based on the 10-fold cross-validation. The risk prediction performance of each model was evaluated via area under the receiver operation characteristic curve (AUROC), recall rate and F1-score on the testset. RESULTS: A total of 656 patients with the 261 occurrences of death were included in the experiment. The total number of all diagnostic records were 13 091. The results on the testset showed that the AUROC of the LR model, RNN model, and GRU model was 0.701 4, 0.786 0, and 0.814 7, respectively. The predictive performances of the GRU and RNN models were significantly better than that of the LR model. The performances of the GRU and RNN models assessed by recall rate and F1-score were also significantly better than that of the LR model, in which the GRU model reached the best performance. In addition, the recall rates were different among different causes of death or by different prediction time windows. CONCLUSION The recurrent neural network model, especially the GRU model, is more effective in predicting PD patients' prognosis as compared with the LR model. This new model may be helpful for clinicians to provide timely intervention, thus improving the quality of care of PD.
Databases, Genetic ; Humans ; Logistic Models ; Neural Networks, Computer ; Peritoneal Dialysis ; Prognosis