Biomedical subjects

Weiqing Wang

Publications and source records attributed to Weiqing Wang.

8 recordsLinked to original sources

PubMed2026

Effects of intensive blood pressure control on cardio-kidney outcomes by KDIGO risk categories: a Post Hoc analysis of ACCORD-BP and SPRINT trials.

The effects of intensive systolic blood pressure (SBP) control on cardiovascular (CV) and kidney outcomes across different Kidney Disease Improving Global Outcomes (KDIGO) risk categories remain unclear. We performed a secondary analysis of the Systolic Blood Pressure Intervention Trial (SPRINT) and the SPRINT-eligible Action to Control Cardiovascular Risk in Diabetes Blood Pressure (ACCORD-BP) trial. Participants were categorized into low, moderate, and high/very-high KDIGO risk groups. The primary outcomes were composite adverse CV events (defined as nonfatal myocardial infarction (MI), nonfatal stroke, fatal or hospitalized heart failure (HF), and CV mortality) and composite adverse kidney events (defined as a sustained decline in eGFR of ≥ 40% and end-stage kidney disease (ESKD)). We found that intensive BP control reduced the risk of composite CV events (HR 0.68; 95% CI 0.59-0.78), with attenuated benefits in higher KDIGO risk categories (P for interaction = 0.055). This interaction was mainly driven by nonfatal MI and fatal or hospitalized HF (both P for interaction < 0.05). Intensive BP control increased the risk of composite kidney events (HR 1.88; 95% CI 1.52-2.33), mainly in low- and moderate-risk groups rather than in high/very-high risk groups (P for interaction = 0.04). Similar patterns were observed for sustained eGFR decline (P for interaction = 0.03), but not for ESKD (HR 1.05; 95% CI 0.74-1.48; P for interaction = 0.71). The KDIGO risk classification modified the effects of intensive BP control. Balancing CV benefits against potential kidney impacts in patients with different KDIGO risks during intensive BP treatment is recommended. Trial Registration: ClinicalTrials.gov Identifiers: NCT01206062 (SPRINT) and NCT00000620 (ACCORD).

Cardiovascular outcome↗

PubMed2026

Molecular subtyping of adrenocortical carcinoma reveals distinct subtypes with prognostic and therapeutic implications.

Adrenocortical carcinoma (ACC) is a rare but aggressive malignancy with poor survival and limited treatment options. To comprehensively characterize its molecular landscape and identify clinically relevant subtypes, we performed an integrated genomic analysis - including whole-exome sequencing, RNA sequencing, and copy number variation profiling - on 61 Chinese patients with ACC. We identified recurrent mutations in TP53 (25%), CTNNB1 (15%), ZNRF3 (10%), and MEN1 (8%). Unsupervised clustering of transcriptomic data revealed four distinct molecular subtypes: cortisol-driven (CD, 14%), immune-suppressed (IS, 40%), cell cycle-altered (CCA, 22%), and immunomodulatory (IM, 24%). The CD subtype exhibited steroidogenic pathway activation; the IS subtype showed T cell receptor downregulation and the worst disease-free survival; the CCA subtype was marked by chromosomal instability and cell cycle gene overexpression; and the IM subtype displayed enriched immune signaling and favorable outcomes. Copy number analysis further uncovered focal amplifications (e.g. TERT, CDK4) and HLA-II deletions. This study establishes a novel molecular classification of ACC, providing a framework for subtype-specific therapeutic strategies, such as CDK4/6 inhibition for CCA and immunotherapy for IM tumors, while highlighting the clinical challenges of immune-cold IS tumors.

Humans↗

PubMed2026

Age-stratified associations of glycemia, blood pressure, and cholesterol with mortality in diabetes: A prospective cohort study.

BACKGROUND: Optimization of HbA1c, blood pressure and cholesterol, referred to as the "ABCs", is central to the management of diabetes. However, the age-specific associations of these factors with mortality in patients with diabetes remains unclear. METHODS: In this prospective cohort study, 43,732 Chinese adults aged ≥ 40 years with diabetes were included from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. Participants were stratified by age (< 55, 55-<65, 65-<75, ≥ 75 years). Cox proportional hazards regression and Fine-Gray competing risk models were employed to estimate the associations of HbA1c, systolic blood pressure (SBP), and low-density lipoprotein cholesterol (LDL-C) with all-cause, cardiovascular, and non-cardiovascular mortality across age groups. Relative importance and population attributable fractions (PAFs) were computed for each metabolic factor. RESULTS: During a median follow-up of 10.1 years, 3,975 deaths were documented. Age significantly modified the associations of HbA1c, SBP, and LDL-C with all mortality outcomes (all P for interaction < 0.05). Among participants aged < 75 years, HbA1c showed graded positive associations with all-cause, cardiovascular, and non-cardiovascular mortality. The SBP thresholds associated with increased mortality risk were 140 mmHg in those aged < 65 years and 160 mmHg in those aged 65-<75 years. Among those aged ≥ 75 years, however, the patterns of these associations differed markedly. Elevated mortality risk was observed only at HbA1c ≥ 9%, with a hazard ratio (HR) of 1.51 (95% confidence interval [CI]: 1.19-1.91) for all-cause mortality and a subdistribution hazard ratio (SHR) of 1.70 (95% CI: 1.23-2.36) for cardiovascular mortality, while SBP showed no significant association with any mortality outcome in this age group. Moreover, LDL-C emerged as a significant risk factor for cardiovascular mortality. Compared with participants with LDL-C < 1.8 mmol/L, those with LDL-C of 1.8-<2.6 mmol/L exhibited a significantly higher risk (SHR: 1.86; 95% CI: 1.11-3.11). Additionally, LDL-C had the largest PAF for cardiovascular mortality (9.6%) within this age group. CONCLUSIONS: The impacts of ABC factors on mortality risk vary substantially by age among adults with diabetes. In patients aged ≥ 75 years, less stringent glycemic and blood pressure targets may be appropriate, whereas lipid management remains critically important for reducing cardiovascular mortality.

Humans↗

PubMed2026

The association between GLP-1R expression and cardiovascular-kidney-metabolic-related diseases in non-diabetic and non-obese population: evidence triangulation using Mendelian randomization, observational and polygenic score association analysis.

BACKGROUND: Glucagon-like peptide-1 receptor (GLP-1R) agonists are emerging as promising therapies for cardiovascular-kidney-metabolic (CKM) related diseases in individuals with type 2 diabetes mellitus (T2DM) or obesity. But their effects in non-obese and non-diabetic individuals are unclear. This study triangulates evidence using Mendelian randomization (MR), polygenic scores (PGS) and observational analyses to estimate the associations of GLP-1R expression with chronic kidney disease (CKD), heart failure (HF) and metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: For the MR analysis, instruments mimicking GLP-1R expression were identified using pancreas-specific cis-expression quantitative trait loci from GTEx (N ≤ 305). MR-Robust method was used as the primary MR approach. PGS and observational analyses were performed both in non-diabetic and non-obese individuals separately. A genome-wide association study (GWAS) for MASLD (14,231 cases and 348,091 controls) was performed in the general population using data from UK Biobank. RESULTS: GLP-1R expression showed robust effects on CKD (odds ratio [OR] 0.96, 95%CI 0.95 to 0.97, q = 1.7 × 10- 10 ), HF (OR = 0.96, 95%CI 0.94 to 0.97, q = 2.5 × 10- 8) and MASLD (OR = 0.96, 95%CI 0.93 to 0.98, q = 1.3 × 10- 3) in the general population. Consistent results were observed in validation analyses. Furthermore, PGS and observational analyses among non-T2DM and non-obese individuals found little evidence to support its association with CKD, HF or MASLD. GWAS analysis identified eight conditionally independent variants associated with MASLD, in which rs563199662 was a new signal located at TFPI region. CONCLUSIONS: This study provides multilayered evidence for GLP-1R expression in mitigating CKD, HF and MASLD risks in the general population, while de-prioritized its effect on CKM-related diseases in non-obese and non-diabetic individuals. Further clinical trials are needed to validate the effects of GLP-1R agonists in relative health population.

Humans↗

PubMed2026

Life-course influence of birthweight and subsequent pathways on healthy aging: a Mendelian randomization study.

BACKGROUND: Birthweight readily measurable marker of fetal growth that may influence health across the lifespan. We aimed to investigate the potential causal association between birthweight and healthy aging and to identify the mediating roles of subsequent socioeconomic, behavioral, functional, and disease-related factors to inform life-course strategies to promote healthy aging and reduce health inequities. METHODS: We performed two-sample Mendelian randomization analyses in European-ancestry participants to estimate the effect of birthweight (n = 298,142-423,683) on two robust, composite healthy aging phenotypes (genetically independent phenotype of aging (aging-GIP) and multivariate aging-related genetic factor (mvAge)) and six individual aging phenotypes, including healthspan, resilience, parental lifespan, self-rated health, phenotypic age deceleration, and 90th percentile self-longevity (n = 34,710-1,958,774), and screened for 100 candidate mediators (n = 14,267-1,812,017) using a two-step mediation analysis. RESULTS: Genetically determined each 1-SD higher birthweight was associated with higher aging-GIP (β [95% CI] in different models ranging from 0.131 [0.066-0.196] to 0.162 [0.089-0.235] SDs) and mvAge (0.036 [0.010-0.063] to 0.045 [0.024-0.067]), independent of later-life obesity indicators; also with more interpretable benefits, including 12%-16% higher odds of longer healthspan, a 0.079-0.089 SD improvement in resilience, and a 1.22-1.74 year increase in parental lifespan. Of 100 candidates, 26 and 25 mediated the effect of birthweight on aging-GIP and mvAge, respectively, including socioeconomic indicators (education, household income, occupational attainment; individual mediation proportion: 12.72%-27.79%); behaviors (e.g., cheese intake, age at first sex; 10.38%-29.56%); physical functions (e.g., blood pressure, grip strength; 7.57%-42.65%); and cardiometabolic diseases (e.g., type 2 diabetes, cardiovascular diseases; 25.02%-70.11%). CONCLUSIONS: Higher birthweight within the normal range directly promotes healthy aging, mediated by multifaceted modifiable factors. Our findings advocate adopting a life-course approach to foster healthy aging, starting with optimal birthweight and extending to interventions that enhance socioeconomic status, promote healthy behaviors, strengthen physical functions, and prevent cardiometabolic diseases.

Mendelian Randomization Analysis↗

PubMed2026

Embryophyte-wide detection of natural Agrobacterium-mediated horizontal gene transfer reveals an ancient role for mini T-DNAs.

Agrobacterium transfers DNA into plant cells, leading to tumors, hairy roots (HR), and natural genetically modified organisms (nGMOs). Transferred DNAs (T-DNAs) from agrobacteria and T-DNA-derived cellular T-DNAs (cT-DNAs) from nGMOs vary considerably and may carry up to 15 different genes. Among these, opine synthase (ops) genes encode the synthesis of opines used as nutrients by the agrobacteria. Earlier studies predicted large numbers of naturally transformed plant species, but only few have been identified and studied so far. We therefore developed a general method to detect cT-DNAs in all publicly available whole genome sequences (WGS) and Sequence Read Archive (SRA) data from land plants. To avoid false positives, we only retained DNA sequences coding for T-DNA proteins. A total of 2614 nGMO species were identified, most are eudicots. However, cT-DNAs were also found in 82 mosses and 75 ferns, showing that Agrobacterium can also generate natural transformants among the early land plants. Analysis of 149 cT-DNA maps revealed different types of T-DNAs. Most notably, these included small T-DNAs (mini T-DNAs) with a single opine synthase gene. Mini T-DNAs are not expected to induce tumors or HRs. The predominance of mini cT-DNAs in mosses and ferns, and the presence of more complex cT-DNAs in spermatophytes, indicate that mini T-DNAs represent the earliest types of T-DNA. Our study also detected unusual T-DNA integration patterns, with multiple copies spread out over several hundreds of kilobases.

DNA, Bacterial↗

PubMed2025

Development and Validation an Integrated Deep Learning Model to Assist Eosinophilic Chronic Rhinosinusitis Diagnosis: A Multicenter Study.

BACKGROUND: The assessment of eosinophilic chronic rhinosinusitis (eCRS) lacks accurate non-invasive preoperative prediction methods, relying primarily on invasive histopathological sections. This study aims to use computed tomography (CT) images and clinical parameters to develop an integrated deep learning model for the preoperative identification of eCRS and further explore the biological basis of its predictions. METHODS: A total of 1098 patients with sinus CT images were included from two hospitals and were divided into training, internal, and external test sets. The region of interest of sinus lesions was manually outlined by an experienced radiologist. We utilized three deep learning models (3D-ResNet, 3D-Xception, and HR-Net) to extract features from CT images and calculate deep learning scores. The clinical signature and deep learning score were inputted into a support vector machine for classification. The receiver operating characteristic curve, sensitivity, specificity, and accuracy were used to evaluate the integrated deep learning model. Additionally, proteomic analysis was performed on 34 patients to explore the biological basis of the model's predictions. RESULTS: The area under the curve of the integrated deep learning model to predict eCRS was 0.851 (95% confidence interval [CI]: 0.77-0.93) and 0.821 (95% CI: 0.78-0.86) in the internal and external test sets. Proteomic analysis revealed that in patients predicted to be eCRS, 594 genes were dysregulated, and some of them were associated with pathways and biological processes such as chemokine signaling pathway. CONCLUSIONS: The proposed integrated deep learning model could effectively predict eCRS patients. This study provided a non-invasive way of identifying eCRS to facilitate personalized therapy, which will pave the way toward precision medicine for CRS.

Humans↗

PubMed2024

Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption.

Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in vitro and in vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M. rupellensis or E. coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M. rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.

Inositol↗