Chinese medicine Linggui Zhugan formula protects against diabetic kidney disease in close association with inhibition of proteinase 3-mediated podocyte apoptosis in mice.

ETHNOPHARMACOLOGICAL RELEVANCE: Linggui-Zhugan (LGZG) comprises four herbs and is a classic formula in traditional Chinese medicine. There is strong clinical evidence of its pleiotropic effects in the prevention of diabetes and its related complications. Although several classes of drugs are currently available for clinical management of diabetic kidney disease (DKD), tight glycemic and/or hypertension control may not prevent disease progression. This study evaluated the therapeutic effect of the ethnopharmacological agent LGZG on DKD. AIM OF THE STUDY: This study aimed to investigate the effects of LGZG formula with standard quality control on experimental DKD and its related metabolic disorders in animal model. Meanwhile, the present study aimed to investigate regulatory effects of LGZG on renal proteinase 3 (PR3) to reveal mechanisms underlying renoprotective benefits of LGZG. MATERIALS AND METHODS: LGZG decoction was fingerprinted by high-performance liquid chromatography for quality control. An experimental model of DKD was induced in C57 BL/6J mice by a combination of high-fat diet feeding, uninephrectomy, and intraperitoneal injection of streptozocin. The LGZG decoction was administrated by daily oral gavage. RESULTS: Treatment with LGZG formula significantly attenuated DKD-like traits (including severe albuminuria, mesangial matrix expansion, and podocyte loss) and metabolic dysfunction (disordered body composition and dyslipidemia) in mice. RNA sequencing data revealed a close association of LGZG treatment with marked modulation of signaling pathways related to podocyte injury and cell apoptosis. Mechanistically, LGZG suppressed the DKD-triggered increase in renal PR3 and podocyte apoptosis. In-vitro incubation of mouse immortalized podocytes with LGZG-medicated serum attenuated PR3-mediated apoptosis. CONCLUSION: Our data demonstrated that the LGZG formula protected against DKD in mice and was closely associated with its inhibitory effects on PR3-mediated podocyte apoptosis.

Network-based approach for drug repurposing against mpox.

The current outbreak of mpox presents a significant threat to the global community. However, the lack of mpox-specific drugs necessitates the identification of additional candidates for clinical trials. In this study, a network medicine framework was used to investigate poxviruses-human interactions to identify potential drugs effective against the mpox virus (MPXV). The results indicated that poxviruses preferentially target hubs on the human interactome, and that these virally-targeted proteins (VTPs) tend to aggregate together within specific modules. Comorbidity analysis revealed that mpox is closely related to immune system diseases. Based on predicted drug-target interactions, 268 drugs were identified using the network proximity approach, among which 23 drugs displaying the least side-effects and significant proximity to MPXV were selected as the final candidates. Lastly, specific drugs were explored based on VTPs, differentially expressed proteins, and intermediate nodes, corresponding to different categories. These findings provide novel insights that can contribute to a deeper understanding of the pathogenesis of MPXV and development of ready-to-use treatment strategies based on drug repurposing.

Causal association of blood lipids with all-cause and cause-specific mortality risk: a Mendelian randomization study.

Dyslipidemia has long been implicated in elevating mortality risk; yet, the precise associations between lipid traits and mortality remained undisclosed. Our study aimed to explore the causal effects of lipid traits on both all-cause and cause-specific mortality. One-sample Mendelian randomization (MR) with linear and nonlinear assumptions was conducted in a cohort of 407,951 European participants from the UK Biobank. Six lipid traits, consisting of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and lipoprotein(a), were included to investigate the causal associations with mortality. Two-sample MR was performed to replicate the association between each lipid trait and all-cause mortality. Univariable MR results showed that genetically predicted higher ApoA1 was significantly associated with a decreased all-cause mortality risk (HR[95% CI]:0.93 [0.89-0.97], P value = 0.001), which was validated by the two-sample MR analysis. Higher lipoprotein(a) was associated with an increased risk of all-cause mortality (1.03 [1.01-1.04], P value = 0.002). Multivariable MR confirmed the direct causal effects of ApoA1 and lipoprotein(a) on all-cause mortality. Meanwhile, nonlinear MR found no evidence for nonlinearity between lipids and all-cause mortality. Our examination into cause-specific mortality revealed a suggestive inverse association between ApoA1 and cancer mortality, a significant positive association between lipoprotein(a) and cardiovascular disease mortality, and a suggestive positive association between lipoprotein(a) and digestive disease mortality. High LDL-C was associated with an increased risk of cardiovascular disease mortality but a decreased risk of neurodegenerative disease mortality. The findings suggest that implementing interventions to raise ApoA1 and decrease lipoprotein(a) levels may improve overall health outcomes and mitigate cancer and digestive disease mortality.

SARS-CoV-2 Omicron infection augments the magnitude and durability of systemic and mucosal immunity in triple-dose CoronaVac recipients.

The inactivated whole-virion vaccine, CoronaVac, is one of the most widely used coronavirus disease 2019 (COVID-19) vaccines worldwide. There is a paucity of data indicating the durability of the immune response and the impact of immune imprinting induced by CoronaVac upon Omicron infection. In this prospective cohort study, 41 recipients of triple-dose CoronaVac and 14 unvaccinated individuals were recruited. We comprehensively profiled adaptive immune parameters in both groups, including spike-specific immunoglobulin (Ig) G and IgA titers, neutralizing activity, B cells, circulating follicular helper T (cTfh) cells, CD4+ and CD8+ T cells, and their memory subpopulations at 12 months after the third booster dose and at 4 and 20 weeks after Omicron BA.5 infection. Twelve months after the third CoronaVac vaccination, spike-specific antibodies and cellular responses were detectable in most vaccinated individuals. BA.5 infection significantly augmented the magnitude, cross-reactivity, and durability of serum neutralization activities, Fc-mediated phagocytosis, nasal spike-specific IgA responses, memory B cells, activated cTfh cells, memory CD4+ T cells, and memory CD8+ T cells for both the ancestral strain and Omicron subvariants, compared to unvaccinated individuals. Notably, the increase in BA.5-specific immunity after breakthrough infection was consistently comparable to or higher than that of the ancestral strain, suggesting no evidence of immune imprinting. Immune landscape analyses showed that vaccinated individuals have better synchronization of multiple immune components than unvaccinated individuals upon heterologous infection. Our data provide detailed insight into the protective role of the inactivated COVID-19 vaccine in shaping humoral and cellular immunity to Omicron infection. IMPORTANCE: There is a paucity of data indicating the durability of the immune response and the impact of immune imprinting induced by CoronaVac upon Omicron breakthrough infection. In this prospective cohort study, the anti-severe acute respiratory syndrome coronavirus 2 adaptive responses were analyzed before and after the Omicron BA.5 infection. Our data provide detailed insight into the protective role of the inactivated COVID-19 vaccine in shaping humoral and cellular immune responses to heterologous Omicron infection. CLINICAL TRIAL: This study is registered with ClinicalTrials.gov as NCT05680896.

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank.

AIMS/HYPOTHESIS: The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. METHODS: From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. RESULTS: At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. CONCLUSIONS/INTERPRETATION: Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

Genome-wide association and Mendelian randomisation analysis among 30,699 Chinese pregnant women identifies novel genetic and molecular risk factors for gestational diabetes and glycaemic traits.

AIMS/HYPOTHESIS: Gestational diabetes mellitus (GDM) is the most common disorder in pregnancy; however, its underlying causes remain obscure. This study aimed to investigate the genetic and molecular risk factors contributing to GDM and glycaemic traits. METHODS: We collected non-invasive prenatal test (NIPT) sequencing data along with four glycaemic and 55 biochemical measurements from 30,699 pregnant women during a 2 year period at Shenzhen Baoan Women's and Children's Hospital in China. Genome-wide association studies (GWAS) were conducted between genotypes derived from NIPTs and GDM diagnosis, baseline glycaemic levels and glycaemic levels after glucose challenges. In total, 3317 women were diagnosed with GDM, while 19,565 served as control participants. The results were replicated using two independent cohorts. Additionally, we performed one-sample Mendelian randomisation to explore potential causal associations between the 55 biochemical measurements and risk of GDM and glycaemic levels. RESULTS: We identified four genetic loci significantly associated with GDM susceptibility. Among these, MTNR1B exhibited the highest significance (rs10830963-G, OR [95% CI] 1.57 [1.45, 1.70], p=4.42×10-29), although its effect on type 2 diabetes was modest. Furthermore, we found 31 genetic loci, including 14 novel loci, that were significantly associated with the four glycaemic traits. The replication rates of these associations with GDM, fasting plasma glucose levels and 0 h, 1 h and 2 h OGTT glucose levels were 4 out of 4, 6 out of 9, 10 out of 11, 5 out of 7 and 4 out of 4, respectively. Mendelian randomisation analysis suggested that a genetically regulated higher lymphocytes percentage and lower white blood cell count, neutrophil percentage and absolute neutrophil count were associated with elevated glucose levels and an increased risk of GDM. CONCLUSIONS/INTERPRETATION: Our findings provide new insights into the genetic basis of GDM and glycaemic traits during pregnancy in an East Asian population and highlight the potential role of inflammatory pathways in the aetiology of GDM and variations in glycaemic levels. DATA AVAILABILITY: Summary statistics for GDM; fasting plasma glucose; 0 h, 1 h and 2h OGTT; and the 55 biomarkers are available in the GWAS Atlas (study accession no.: GVP000001, https://ngdc.cncb.ac.cn/gwas/browse/GVP000001) .