Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults.

While numerous genomic loci have been identified for neuropsychiatric conditions, the contribution of protein-coding variants has yet to be determined. Here we conducted a large-scale whole-exome-sequencing study to interrogate the impact of protein-coding variants on 46 neuropsychiatric diseases and 23 traits in 350,770 adults from the UK Biobank. Twenty new genes were associated with neuropsychiatric diseases through coding variants, among which 16 genes had impacts on the longitudinal risks of diseases. Thirty new genes were associated with neuropsychiatric traits, with SYNGAP1 showing pleiotropic effects across cognitive function domains. Pairwise estimation of genetic correlations at the coding-variant level highlighted shared genetic associations among pairs of neurodegenerative diseases and mental disorders. Lastly, a comprehensive multi-omics analysis suggested that alterations in brain structures, blood proteins and inflammation potentially contribute to the gene-phenotype linkages. Overall, our findings characterized a compendium of protein-coding variants for future research on the biology and therapeutics of neuropsychiatric phenotypes.

Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants.

BACKGROUND: Blood-based biomarkers for dementia are gaining attention due to their non-invasive nature and feasibility in regular healthcare settings. Here, we explored the associations between 249 metabolites with all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VaD) and assessed their predictive potential. METHODS: This study included 274,160 participants from the UK Biobank. Cox proportional hazard models were employed to investigate longitudinal associations between metabolites and dementia. The importance of these metabolites was quantified using machine learning algorithms, and a metabolic risk score (MetRS) was subsequently developed for each dementia type. We further investigated how MetRS stratified the risk of dementia onset and assessed its predictive performance, both alone and in combination with demographic and cognitive predictors. RESULTS: During a median follow-up of 14.01 years, 5274 participants developed dementia. Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD. Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance. Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile. When MetRS was combined with demographic and cognitive predictors, the model yielded the area under the receiver operating characteristic curve (AUC) values of 0.857 for ACD, 0.861 for AD, and 0.873 for VaD. CONCLUSIONS: We conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.

Identifying modifiable factors and their joint effect on dementia risk in the UK Biobank.

Previous hypothesis-driven research has identified many risk factors linked to dementia. However, the multiplicity and co-occurrence of risk factors have been underestimated. Here we analysed data of 344,324 participants from the UK Biobank with 15 yr of follow-up data for 210 modifiable risk factors. We first conducted an exposure-wide association study and then combined factors associated with dementia to generate composite scores for different domains. We then evaluated their joint associations with dementia in a multivariate Cox model. We estimated the potential impact of eliminating the unfavourable profiles of risk domains on dementia using population attributable fraction. The associations varied by domain, with lifestyle (16.6%), medical history (14.0%) and socioeconomic status (13.5%) contributing to the majority of dementia cases. Overall, we estimated that up to 47.0%-72.6% of dementia cases could be prevented.

Association of Kidney Function with Risk of Incident Dementia: A Prospective Cohort Study of 275,167 UK Biobank Participants.

BACKGROUND: Previous studies have reported inconsistent associations between chronic kidney disease (CKD) and dementia. OBJECTIVE: To evaluate whether CKD is a risk factor for dementia and compare the performance of different measures of calculating estimated glomerular filtration rate (eGFR). METHODS: 275,167 participants from UK Biobank were included and eGFR at baseline was calculated using serum creatinine (eGFRcr), cystatin C (eGFRcys), and creatinine-cystatin C equations (eGFRcr-cys). Restricted cubic splines and Cox regression models were performed to assess the relationship of eGFR with all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD). RESULTS: We observed a U-shaped relationship between each eGFR and risk of all-cause dementia and VaD, with eGFRcys and eGFRcr-cys showing a closer linkage (peGFRcys <0.0001, peGFRcrhboxcys<0.0001 and peGFRcr = 0.0001). Lower and supranormal eGFR were related to increased risk of all-cause dementia. Compared to the reference category of 90-104 ml/min/1.73 m2, adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause dementia for eGFRcr-cys 30-59, <30, and ≥105 ml/min/1.73 m2 were 1.26 (95% CI [1.05-1.50], p = 0.012), 2.62 (95% CI [1.54-4.47], p < 0.001), and 1.41 (95% CI [1.17-1.70], p < 0.001). No statistically significant association was observed between eGFR with risk of AD. CONCLUSION: This prospective study identified impaired kidney function as a critical risk factor for dementia and noted the application of cystatin C strengthened the relationship between CKD and dementia, underlining the significant value of preserving kidney function to reduce the risk of dementia and considering cystatin C measurement as part of clinical practice.

Potential Mechanism of Dingji Fumai Decoction Against Atrial Fibrillation Based on Network Pharmacology, Molecular Docking, and Experimental Verification Integration Strategy.

Background: Dingji Fumai Decoction (DFD), a traditional herbal mixture, has been widely used to treat arrhythmia in clinical practice in China. However, the exploration of the active components and underlying mechanism of DFD in treating atrial fibrillation (AF) is still scarce. Methods: Compounds of DFD were collected from TCMSP, ETCM, and literature. The targets of active compounds were explored using SwissTargetPrediction. Meanwhile, targets of AF were collected from DrugBank, TTD, MalaCards, TCMSP, DisGeNET, and OMIM. Then, the H-C-T-D and PPI networks were constructed using STRING and analyzed using CytoNCA. Meanwhile, VarElect was utilized to detect the correlation between targets and diseases. Next, Metascape was employed for systematic analysis of the mechanism of potential targets and protein complexes in treating AF. AutoDock Vina, Pymol, and Discovery Studio were applied for molecular docking. Finally, the main findings were validated through molecular biology experiments. Results: A total of 168 active compounds and 1,093 targets of DFD were collected, and there were 89 shared targets between DFD and AF. H-C-T-D network showed the relationships among DFD, active compounds, targets, and AF. Three functional protein complexes of DFD were extracted from the PPI network. Further systematic analysis revealed that the regulation of cardiac oxidative stress, cardiac inflammation, and cardiac ion channels were the potential mechanism of DFD in treating AF. Addtionally, molecular docking verified the interactions between active compounds and targets. Finally, we found that DFD significantly increased the level of SIRT1 and reduced the levels of ACE, VCAM-1, and IL-6. Conclusions: DFD could be utilized in treating AF through a complicated mechanism, including interactions between related active compounds and targets, promoting the explanation and understanding of the molecular biological mechanism of DFD in the treatment of AF.

Network Pharmacology-Based Systematic Analysis of Molecular Mechanisms of Dingji Fumai Decoction for Ventricular Arrhythmia.

BACKGROUND: Dingji Fumai Decoction (DFD), a traditional herbal mixture, has been widely used to ventricular arrhythmia (VA) in clinical practice in China. However, research on the bioactive components and underlying mechanisms of DFD in VA is still scarce. METHODS: Components of DFD were collected from TCMSP, ETCM, and literature. The chemical structures of each component were obtained from PubChem. Next, SwissADME and SwissTargetPrediction were applied for compounds screening and targets prediction of DFD; meanwhile, targets of VA were collected from DrugBank and Online Mendelian Inheritance in Man (OMIM). Then, the H-C-T-D network and the protein-protein interaction (PPI) network were constructed based on the data obtained above. CytoNCA was utilized to filter hub genes and VarElect was used to analyze the relationship between genes and diseases. At last, Metascape was employed for systematic analysis on the potential targets of herbals against VA, and AutoDock was applied for molecular docking to verify the results. RESULTS: A total of 434 components were collected, 168 of which were qualified, and there were 28 shared targets between DFD and VA. Three function modules of DFD were found from the PPI network. Further systematic analysis of shared genes and function modules explained the potential mechanism of DFD in the treatment of VA; molecular docking has verified the interactions. CONCLUSIONS: DFD could be employed for VA through mechanisms, including complex interactions between related components and targets, as predicted by network pharmacology and molecular docking. This work confirmed that DFD could apply to the treatment of VA and promoted the explanation of DFD for VA in the molecular mechanisms.

Oleanolic acid and ursolic acid inhibit proliferation in transformed rat hepatic oval cells.

AIM: To investigate H2O2-induced promotion proliferation and malignant transformation in WB-F344 cells and anti-tumor effects of ursolic acid (UA) and oleanolic acid (OA). METHODS: WB-F344 cells were continuously exposed to 7 x 10(-7) mol/L H2O2 for 21 d. Observations of cell morphology, colony formation rates, flow cytometric analysis of cell cycle changes and aneuploidy formation indicated that H2O2 was able to induce malignant transformation of WB-F344 cells. We treated malignantly transformed WB-F344 cells with 4 µmol/L OA or 8 µmol/L UA for 72 h and analyzed the cell cycle distribution by flow cytometry. RESULTS: MTT assay showed that 7 x 10(-7) mol/L H2O2 decreased G1 phase subpopulation from 73.8% to 49.6% compared with the control group, and increased S phase subpopulation from 14.5% to 31.8% (P < 0.05 vs control group). Cell morphology showed that nucleus to cytoplasm ratio increased, many mitotic cells, prokaryotes and even tumor giant cells were shown in H2O2-induced WB-F344 cells. Fluorescence activated cell sorting analysis showed that WB-F344 cell aneuploidy increased to 12% following H2O2 treatment. Flow cytometric analysis of the transformed WB-F344 cells following treatment with OA (4 µmol/L) and UA (8 µmol/L) showed that OA increased G1 subpopulation to 68.6%, compared to 49.7% in unexposed cells. UA increased G1 subpopulation to 67.4% compared to 49.7% in unexposed cells (P < 0.05 vs H2O2 model group). CONCLUSION: H2O2 causes the malignant transformation of WB-F344 cells. OA and UA exert anti-tumor effects by inhibiting the proliferation in malignantly transformed WB-F344 cells.

Urotensin II inhibits skeletal muscle glucose transport signaling pathways via the NADPH oxidase pathway.

Our previous studies have demonstrated that the urotensin (UII) and its receptor are up-regulated in the skeletal muscle of mice with type II diabetes mellitus (T2DM), but the significance of UII in skeletal muscle insulin resistance remains unknown. The purpose of this study was to investigate the effect of UII on NADPH oxidase and glucose transport signaling pathways in the skeletal muscle of mice with T2DM and in C2C12 mouse myotube cells. KK/upj-AY/J mice (KK) mice were divided into the following groups: KK group, with saline treatment for 2 weeks; KK+ urantide group, with daily 30 µg/kg body weight injections over the same time period of urantide, a potent urotensin II antagonist peptide; Non-diabetic C57BL/6J mice were used as normal controls. After urantide treatment, mice were subjected to an intraperitoneal glucose tolerance test, in addition to measurements of the levels of ROS, NADPH oxidase and the phosphorylated AKT, PKC and ERK. C2C12 cells were incubated with serum-free DMEM for 24 hours before conducting the experiments, and then administrated with 100 nM UII for 2 hours or 24 hours. Urantide treatment improved glucose tolerance, decreased the translocation of the NADPH subunits p40-phox and p47-phox, and increased levels of the phosphorylated PKC, AKT and ERK. In contrast, UII treatment increased ROS production and p47-phox and p67-phox translocation, and decreased the phosphorylated AKT, ERK1/2 and p38MAPK; Apocynin abrogated this effect. In conclusion, UII increased ROS production by NADPH oxidase, leading to the inhibition of signaling pathways involving glucose transport, such as AKT/PKC/ERK. Our data imply a role for UII at the molecular level in glucose homeostasis, and possibly in skeletal muscle insulin resistance in T2DM.