Xiu-Feng Huang

Acute myocardial infarction (AMI) remains a leading cardiovascular event, yet the metabolic signatures that precede its onset and their value for long-term risk prediction remain incompletely characterized. Using NMR metabolomics data from 271 430 UK Biobank participants without baseline AMI, this study evaluated 168 absolute metabolite measures in relation to incident AMI. Cox proportional hazards models identified 60 AMI-associated metabolites after adjustment for conventional risk factors, and CatBoost modeling with SHAP interpretation and forward selection further defined eight metabolite profiles, including glycine, albumin, glycoprotein acetyls, creatinine, triglycerides in large LDL, free cholesterol in chylomicrons and extremely large VLDL (XXL-VLDL-FC), cholesteryl esters in IDL, and cholesteryl esters in HDL. Integrating these metabolite profiles with conventional risk factors modestly improved 10-year AMI discrimination in both machine learning and survival models, with a CatBoost AUC of 0.741 and a Cox C index of 0.761 in validation analyses. SHAP analyses suggested sex- and age-related heterogeneity in metabolite contributions, particularly for HDL-related and inflammatory traits. A nested case-control trajectory analysis showed persistently lower levels of glycine and albumin, and higher levels of glycoprotein acetyls, large LDL triglycerides, and creatinine during the decade before diagnosis. This study identifies NMR-derived metabolic patterns associated with AMI risk and provides a basis for further investigation of their potential contributions to metabolomics-informed cardiovascular risk assessment.

Objective: To investigate the potential associations between therapeutically relevant single nucleotide polymorphisms (SNPs) with clinical characteristics and medication response of asthma in Chinese children. Methods: This prospective observational study was conducted at the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University from August 2021 to July 2022. Patients diagnosed with asthma and age-matched healthy individuals were recruited. Genotyping of 55 SNPs was performed using the Sequenom Mass Array platform. Both the association of 55 SNPs with clinical characteristics of asthma and the efficacy of budesonide/formoterol were analyzed. Results: A total of 412 asthma patients and 262 age-matched healthy were recruited. The Minor Allele Frequency of SNPs differs markedly from that observed in European, American, and African populations but closely in the Asian populations. Comparing genotype and allele frequencies revealed that ORMDL3-rs2872507 (AA) and ZNF432-rs3752120 (TT) were significantly more frequent in the asthma group than in the control group. ZNF432-rs3752120 and ORMDL3-rs2872507 were further analyzed, stratified by clinical features and laboratory indicators. Atopy was significantly more common in ZNF432-rs3752120 TT genotype carriers compared to CC and CT genotypes. Additionally, the demand for inhalation device use was higher in CT carriers compared to those with CC and TT genotypes. However, no significant differences in asthma clinical characteristics were observed among ORMDL3-rs2872507 genotypes. Besides, eight SNPs were confirmed to be associated with the response of inhaling Budesonide/Formoterol dry powder 80/4.5. Conclusion: This study revealed that the ORMDL3-rs2872507 AA genotype and the ZNF432-rs3752120 TT genotype might be susceptible genotypes in Chinese children with asthma. rs1042713, rs2305089, rs2540487, rs2712807, rs28364072, rs320995, rs4980524, and rs730012 were identified as potentially associated with the efficacy of Budesonide/Formoterol (80/4.5) inhalation therapy in a cohort of children with asthma from southern Zhejiang, China.

Background: Coronary artery disease (CAD) is a leading global cause of mortality, yet the predictive accuracy of conventional risk models is limited. Here, we integrate conventional risk factors, polygenic risk scores, and large‐scale proteomics to develop a unified model for enhanced CAD risk prediction. Methods: Using data from UK Biobank, participants with plasma proteomics and genetic risk data were included after excluding prevalent CAD. Participants from England were split into training (n=32 330) and internal validation (n=13 857) sets, and Scotland/Wales participants formed an external validation set (n=5775). Incident CAD was ascertained from linked health records. A 202‐protein proteomic risk score was derived by least absolute shrinkage and selection operator Cox regression, and CatBoost models were trained using conventional risk factors alone and with incremental addition of polygenic risk scores and protein proteomic risk scores; Shapley Additive Explanations‐guided forward selection identified a compact protein panel. Results: Across cohorts, the median age was 58 years and ∼45% were men. Protein proteomic risk score was dose‐dependently associated with CAD risk. Compared with conventional risk factors alone, integrating polygenic risk scores and protein proteomic risk scores improved discrimination, with the area under the curve increasing from 0.750 (95% CI, 0.732–0.767) to 0.789 (95% CI, 0.772–0.805) in internal validation and from 0.717 (95% CI, 0.683–0.750) to 0.762 (95% CI, 0.732–0.791) in external validation. A 9‐protein panel (GDF15 [growth differentiation factor 15], MMP12 [matrix metalloproteinase 12], NPPB [natriuretic peptide B], PGF [placental growth factor], REN [renin], ADGRG2 [adhesion G‐protein coupled receptor], ACE2 [angiotensin‐converting enzyme 2], CDCP1 [CUB domain‐containing protein 1], CXCL17 [C‐X‐C motif chemokine ligand 17)]) captured most proteomic predictive information. Conclusions: Our findings demonstrate that integrating conventional risk factors, polygenic risk scores, and proteomic data improves CAD risk prediction. This study highlights the utility of proteomics in precision cardiovascular medicine and simplified risk stratification tools.

1. The Bacillus Calmette-Guérin (BCG) vaccine is the most widely used and historically the oldest tuberculosis vaccine, with proven protective efficacy against severe childhood tuberculosis, such a...

Dietary patterns play a pivotal role in managing hypertension and preventing mortality. However, comparative studies on the effects of different dietary patterns on mortality risk in hypertensive patients remain limited. The aim of this study is to evaluate and compare the associations between six established dietary indices and mortality risk in this population. Utilizing data from the 2005-2018 NHANES, 13,230 hypertensive adults were included in the analysis. Six standardized dietary indices were employed, and the associations between these dietary patterns and mortality were analyzed using a weighted Cox proportional hazards model. Additionally, time trend analysis was conducted to examine changes in dietary patterns, while weighted quantile regression (WQS) was used to identify key dietary components contributing to mortality risk. Over a median follow-up of 8.3 years, a total of 2,420 deaths were recorded, including 637 due to cardiovascular diseases. Higher scores for AHEI, DASH, HEI-2020, MED, and MEDI were significantly associated with reduced risk of all-cause mortality, whereas a proinflammatory diet, reflected by elevated DII scores, was associated with increased risk. Only higher DASH index scores were independently associated with reduced cardiovascular mortality. Time trend analysis revealed a decline in adherence to DASH over the years, whereas MEDI scores slightly increased. WQS regression identified dairy products, whole grains, and fatty acids as key dietary components influencing mortality risk. Healthy dietary patterns markedly reduce all-cause mortality risk in hypertensive patients, with the DASH diet offering notable cardiovascular protection. These findings support personalized dietary interventions for hypertension management.

This study aims to elucidate the genetic and phenotypic characteristics of pediatric patients with potential Dent disease (DD). High-throughput sequencing was conducted on 11 pediatric patients with potential cases of DD. We also analyzed clinical phenotype and treatment regimens. Variants in CLCN5 and OCRL were identified in nine patients, including three novel variants. The predominant clinical manifestations among these patients with a definitive diagnosis of DD included low molecular weight proteinuria (LMWP) (100%), hypercalciuria (66.7%), abnormal renal function (55.6%), nephrocalcinosis (44.4%), and hypophosphatemia (44.4%). Patients with CLCN5 or OCRL variants exhibited significantly elevated levels of both β2-microglobulin and α1-microglobulin, exceeding the normal threshold by more than tenfold. In contrast, the potential cases of DD without identified genetic mutations showed a moderate increase in β2-microglobulin (5-10 times the normal level), while α1-microglobulin levels remained below this range. Seven DD patients were treated with nonsteroidal angiotensin-converting enzyme inhibitors. By the end of this study, five DD patients were diagnosed with stage 2 chronic kidney disease (CKD2), while four were classified as having CKD1. This study provides insight into the clinical and genetic profiles of DD patients. Notably, integrating genetic analysis with the detection of markedly elevated levels of LMWP, particularly α1-microglobulin,can substantially reduce the misdiagnosis of this disease.

Congenital cataracts (CC) are one of the leading causes of impaired vision or blindness in children, with approximately 8.3–25% being inherited. The aim of this study is to investigate the mutation spectrum and frequency of 9 cataract-associated genes in 19 Chinese families with congenital cataracts. To identify the gene variants associated with congenital cataracts. This study included a total of 58 patients from 19 pedigrees with congenital cataracts. All probands were initially screened by whole-exome sequencing(WES), and then validated by co-segregation analysis using Sanger sequencing. Likely pathogenic variants were detected in 8 families, with a positivity rate of 42.1%. Variants in various genes were identified, including GJA3, CRYGD, CRYBA4, BFSP2, IARS2, CRYAA, CRYBA1, ARL2 and CRYBB3. Importantly, this study identified compound heterozygous variants of IARS2 in one family. Our research findings have revealed multiple gene variants associated with cataracts, providing clinical guidance for improved molecular diagnosis of congenital cataracts in the era of precision medicine.

Nance–Horan syndrome (NHS) is a rare X-linked dominant disorder caused by pathogenic variants in the NHS gene on chromosome Xp22.2-Xp22.13. Clinical manifestations consist of congenital cataracts, along with dysmorphic facial features and dental anomalies and, in certain instances, intellectual disability. This study aimed to identify the genetic cause responsible for NHS in a Chinese family with four individuals primarily presenting with congenital cataracts. Genomic DNA was collected from six family members, including four affected individuals (three females and one male) from a two-generation family. The family history and clinical data were documented. Whole-exome sequencing was performed on the proband, and candidate pathogenic variants were filtered through a series of screening steps and validated by Sanger sequencing. Co-segregation analysis was conducted to confirm the pathogenicity of the identified variant. Genetic analysis revealed a novel frameshift pathogenic variant in NHS gene (c.1735delA: p.R579Gfs*91) present in all four affected members. All affected members exhibited congenital cataracts, congenital ptosis, strabismus, high myopia as well as dental and facial anomalies, and more severe characteristic features observed in the male patient. These clinical manifestations were consistent with the phenotype of NHS. This study identified a novel NHS pathogenic variant in a Chinese family, expanding the mutational spectrum of NHS. Contrary to previous reports of female carriers exhibiting mild symptoms, we demonstrated severe ocular phenotypes in three affected females. These findings will assist in providing genetic counseling for NHS patients.