In recent years, pyroptosis, an inflammatory form of programmed cell death, has gained increasing attention in the field of metabolic disease research. Pyroptosis is closely associated with inflammatory responses. A growing body of evidence suggests that pyroptosis not only plays a critical role in regulating inflammation but can also influence metabolic status, cellular function, and tissue damage through multiple pathways, thereby either exacerbating or alleviating the progression of metabolic diseases. However, the precise molecular mechanisms of pyroptosis and its roles across different metabolic diseases remain unclear, and investigations into related therapeutic targets are still in early stages. Systematically elucidating the mechanisms by which pyroptosis contributes to metabolic diseases and exploring its potential roles in inflammation and pathophysiology may provide new insights and strategies for the prevention and treatment of metabolic disorders, and further promote advances in this research field.
Pyroptosis/physiology* ; Humans ; Metabolic Diseases/metabolism* ; Inflammation/physiopathology* ; Animals ; Inflammasomes

The gut microbiota is an indispensable symbiotic entity within the human holobiont, serving as a critical regulator of host lipid metabolism homeostasis. Therefore, it has emerged as a central subject of research in the pathophysiology of metabolic disorders. This microbial consortium orchestrates key aspects of host lipid dynamics-including absorption, metabolism, and storage-through multifaceted mechanisms such as the enzymatic processing of dietary polysaccharides, the facilitation of long-chain fatty acid uptake by intestinal epithelial cells (IECs), and the bidirectional modulation of adipose tissue functionality. Mounting evidence underscores that gut microbiota-derived metabolites not only directly mediate canonical lipid metabolic pathways but also interface with host immune pathways, epigenetic machinery, and circadian regulatory systems, thereby establishing an intricate crosstalk that coordinates systemic metabolic outputs. Perturbations in microbial composition (dysbiosis) drive pathological disruptions to lipid homeostasis, serving as a pathogenic driver for conditions such as obesity, hyperlipidemia, and non-alcoholic fatty liver disease (NAFLD). This review systematically examines the emerging mechanistic insights into the gut microbiota-mediated regulation of intestinal lipid metabolism, while it elucidates its translational implications for understanding metabolic disease pathogenesis and developing targeted therapies.
Humans ; Gastrointestinal Microbiome/physiology* ; Lipid Metabolism ; Animals ; Intestinal Mucosa/metabolism* ; Homeostasis ; Dysbiosis ; Obesity/metabolism* ; Intestines/microbiology* ; Non-alcoholic Fatty Liver Disease/metabolism* ; Metabolic Diseases/metabolism*

Macrophages are the crucial immune cells integral to host defense and the regulation of homeostasis, exhibiting remarkable plasticity across various tissues. Upon exposure to different stimuli, they can polarize into functional subsets. The reorganization process of cellular metabolism, known as metabolic reprogramming, involves the comprehensive adjustment of intracellular metabolites, enzymes, and metabolic pathways. Recent studies have revealed the critical role of metabolic reprogramming in shaping the phenotypes and functions of macrophages. Metabolism drives and regulates macrophages by generating bioenergy and biosynthetic precursors and by altering metabolites that affect gene expression and signal transduction. This review focuses on the immunomodulatory roles of key enzymes and specific products in major metabolic pathways, such as glucose metabolism, lipid metabolism and amino acid metabolism, in macrophages. Additionally, it will highlight recent advancements in targeting metabolic regulation of macrophages in the context of ocular diseases.
Humans ; Macrophages/immunology* ; Animals ; Eye Diseases/immunology* ; Lipid Metabolism ; Glucose/metabolism* ; Metabolic Networks and Pathways ; Signal Transduction ; Metabolic Reprogramming

OBJECTIVES: To develop a quality control indicator system for neonatal screening of inherited metabolic diseases in obstetric settings, so as to provide a standardized tool for quality control in clinical neonatal screening of inherited metabolic diseases. METHODS: From March to May 2024, a literature review combined with expert clinical experience was conducted to develop a preliminary questionnaire on quality control indicators for neonatal screening of inherited metabolic diseases. The final indicator system was established after two rounds of the Delphi method, and the Analytic Hierarchy Process was used to determine indicator weights. RESULTS: Sixteen questionnaires were distributed in each of the two consultation rounds, with a valid response rate of 100% for both. The expert authority coefficients were 0.863 and 0.876, respectively. Kendall's coefficient of concordance for the importance and feasibility of the indicators ranged from 0.091 to 0.125. The final indicator system comprised 3 primary indicators, 8 secondary indicators, and 28 tertiary indicators for neonatal screening of inherited metabolic diseases in obstetric settings. CONCLUSIONS The quality control indicator system developed using the Delphi method demonstrates a strong systematic structure, high clinical adaptability, and strong operability, and can be effectively applied to quality control in neonatal screening of inherited metabolic diseases in obstetric settings.
Humans ; Infant, Newborn ; Neonatal Screening/standards* ; Quality Control ; Metabolism, Inborn Errors/diagnosis* ; Metabolic Diseases/diagnosis* ; Delphi Technique ; Female ; Quality Indicators, Health Care ; Pregnancy

Skin fibrosis is primarily characterized by excessive fibroblasts proliferation and aberrant extracellular matrix accumulation, leading to pathological conditions such as hypertrophic scars, keloids, and systemic sclerosis. This dynamic and complex process involves intricate interactions among various resident skin cells and inflammatory cells, ultimately resulting in extracellular matrix deposition and even invasive growth. The maintenance of cellular phenotypes and functions relies on dynamic metabolic responses, and cellular signal transduction is closely coupled with metabolic processes. Given that the coupling of cell metabolism and signaling in the skin fibrosis microenvironment plays a critical role in inflammatory responses and fibrotic activation, modulation of these metabolic pathways may offer novel therapeutic strategies for inhibiting or even reversing the progression of skin fibrosis. This review systematically summarizes the metabolic characteristics of various cell types involved in skin fibrosis, with a focus on core metabolic reprogramming mechanisms such as hyperactive glycolysis, dysregulated fatty acid metabolism, cellular metabolic dysfunction and dysregulated mTOR/AMPK signaling. Furthermore, potential intervention strategies targeting these metabolic pathways are explored, thereby providing new research perspectives for the treatment of skin fibrosis.
Humans ; Fibrosis/metabolism* ; Skin/metabolism* ; Signal Transduction ; Fibroblasts/pathology* ; TOR Serine-Threonine Kinases/metabolism* ; Skin Diseases/pathology* ; Cellular Reprogramming ; Metabolic Reprogramming

The intestine is a complex symbiotic system, and the gut microbiota is closely related to host health. Studies have indicated that the gut microbiota influences physiological functions of the host by producing a variety of metabolites, which act as signaling molecules and substrates for metabolic reactions in the host. Dysbiosis of the gut microbiota affects the abundance of gut microbiota-derived metabolites, thereby influencing host health by disrupting signal transduction in multiple organs. Additionally, dietary compounds can shape the gut microbiota, affecting gut microbiota-derived metabolite levels and regulating host metabolism. This article introduces the methods for mining gut microbiota-derived metabolites, reviews the roles of these metabolites in metabolic diseases and related dietary interventions. Which provides a perspective on the prevention and treatment of metabolic diseases by targeting these metabolites, enriching the knowledge on the role of gut microbiota in the regulation of host metabolism.
Gastrointestinal Microbiome/physiology* ; Humans ; Dysbiosis/microbiology* ; Metabolic Diseases/metabolism* ; Diet

Kidney stones are a urinary system disease with a high incidence,among which calcium oxalate stones are the most common.Metabolic disorders such as hypertension,diabetes,obesity,hyperlipidemia,and hyperuricemia can cause changes in oxalate,uric acid,and pH and calcium ion concentrations in the urine through multiple pathways including inducing oxidative stress and inflammatory responses by generating reactive oxygen species,ultimately affecting the formation of calcium oxalate stones.This article reviews the possible pathways and mechanisms by which metabolic diseases influence the formation of calcium oxalate stones,providing new ideas for the clinical prevention and treatment of calcium oxalate stones.
Humans ; Calcium Oxalate/metabolism* ; Kidney Calculi/etiology* ; Metabolic Diseases/complications*

OBJECTIVE: To explore the incidence, clinical features, genetic variant characteristics and prognosis of Glutaric acidemia type I (GA1) among neonates from Henan Province. METHODS: A total of 814 625 neonates undergoing screening for inherited metabolic diseases by tandem mass spectrometry (MS/MS) at the Third Affiliated Hospital of Zhengzhou University from January 2016 to December 2022 were selected as the study subjects. A retrospective method was adopted to collect the clinical data of the patients. Whole exome sequencing was carried out to detect GCDH gene variants in individuals with positive results by GA1 newborn screening, and Sanger sequencing was used to verify the candidate variants. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the pathogenicity of candidate variants was rated. This study was approved by the Medical Ethics Committee of the Hospital (Ethics Number: 2019 Medical Ethics Review No. 67). RESULTS: Eight cases of GA1 were diagnosed among the 814 625 neonates. Blood glutaryl carnitine (C5DC) and urine glutaric acid (GA) levels of the 8 children were higher than the normal reference values. In total 12 variants were detected, all of which were missense variants. c.1064G>A (p.Arg355His) was the most common one, accounting for 21.4% (3/14). Three GCDH gene variants, including 1297G>C (p.Ala433Pro), c.467G>A (p.Gly156Asp) and c.1125T>G (p.Cys375Trp), were previously unreported. REVEL software analysis predicted that all of the three variants were harmful. 3D protein structure modeling indicated that the three variants may cause amino acid residue alterations, and c.1297G>C (p.Ala433Pro) and c.1125T>G (p.Cys375Trp) may result in increase in hydrogen bonds and affect the function of GCDH protein. By December 2023, one of the eight children had deceased, and another child had severe clinical symptoms with poor prognosis. Six children had a good prognosis, of which two had mild motor development delay and four had normal development without clinical symptoms. CONCLUSION The incidence of GA1 in newborns screened by MS/MS in Henan Province is 1/101 828, and the carrier rate of pathogenic GCDH variants is 1/160. The c.1064G>A (p.Arg355His) may be the hotspot variant of the GCDH gene among children with GA1 in Henan. Discovery of the three novel variants has enriched the mutational spectrum of the GCDH gene and provide a basis for the early diagnosis, treatment, prognosis and genetic counseling of this disease.
Humans ; Amino Acid Metabolism, Inborn Errors/epidemiology* ; Glutaryl-CoA Dehydrogenase/chemistry* ; Infant, Newborn ; Female ; Neonatal Screening/methods* ; Male ; Brain Diseases, Metabolic/epidemiology* ; China/epidemiology* ; Retrospective Studies ; Mutation ; Genetic Variation ; Glutarates

BACKGROUND: The American Heart Association (AHA) introduced the concept of cardiovascular-kidney-metabolic (CKM) health and stage, reflecting the interaction among metabolism, chronic kidney disease (CKD), and the cardiovascular system. However, the association between CKM stage and the long-term risk of cardiovascular disease (CVD) has not been validated. This study aimed to evaluate the long-term CVD risk associated with CKM health metrics and CKM stage using data from a population-based cohort study. METHODS: In total, 5293 CVD-free participants were followed up to around 13 years in the Chinese Multi-provincial Cohort Study (CMCS). Considering the pathophysiologic progression of CKM health metrics abnormalities (comprising obesity, central adiposity, prediabetes, diabetes, hypertriglyceridemia, CKD, and metabolic syndrome), participants were divided into CKM stages 0, 1, and 2. The time-dependent Cox regression models were used to estimate the cardiovascular risk associated with CKM health metrics and stage. Additionally, broader CVD outcomes were examined, with a specific assessment of the impact of stage 3 in 2581 participants from the CMCS-Beijing subcohort. RESULTS: Among participants, 91.2% (4825/5293) had at least one abnormal CKM health metric, 8.8% (468/5293), 13.3% (704/5293), and 77.9% (4121/5293) were in CKM stages 0, 1, and 2, respectively; and 710 incident CVD cases occurred during a median follow-up time of 13.3 years (interquartile range: 12.1 to 13.6 years). Participants with each poor CKM health metric exhibited significantly higher CVD risk. Compared with stage 0, the hazard ratio (HR) (95% confidence interval [CI]) for CVD incidence was 1.31 (0.84-2.04) in stage 1 and 2.27 (1.57-3.28) in stage 2. Significant interactive impacts existed between CKM stage and age or sex, with higher CVD risk related to increased CKM stages in participants aged <60 years or females. CONCLUSION These findings highlight the contribution of CKM health metrics and CKM stage to the long-term risk of CVD, suggesting the importance of multi-component recognition and management of poor CKM health in CVD prevention.
Humans ; Female ; Male ; Cardiovascular Diseases/etiology* ; Middle Aged ; Adult ; Cohort Studies ; Renal Insufficiency, Chronic/metabolism* ; Aged ; Risk Factors ; Metabolic Syndrome/metabolism* ; China ; East Asian People

BACKGROUND: Studies on the impact of blood glucose indicators on metabolism remain relatively scarce. The aim of this study was to investigate the associations between blood glucose indicators and metabolic disorders in China. METHODS: Data were from the Thyroid disorders, Iodine status and Diabetes Epidemiological survey (TIDE survey), which randomly selected 31 cities from 31 provinces in the Chinese mainland. A total of 68,383 participants without preexisting diabetes and have complete data on blood glucose, lipids, and blood pressure were included in the analysis. The diabetic population was divided into seven groups based on different types of elevated blood glucose levels, including fasting plasma glucose (FPG), postprandial glucose (PPG), and hemoglobin A1c (HbA1c): FPG ≥7 mmol/L; PPG ≥11.1 mmol/L; HbA1c ≥6.5%; FPG ≥7 mmol/L and PPG ≥11.1 mmol/L; FPG ≥7 mmol/L and HbA1c ≥6.5%; PPG ≥11.1 mmol/L and HbA1c ≥6.5%; FPG ≥7 mmol/L, PPG ≥11.1 mmol/L, and HbA1c ≥6.5%. The effects of each blood glucose indicator on metabolism were investigated separately. Weighted calculation was applied during the analysis, with the weighting coefficient based on the number of people corresponding to the population characteristics of each sample in the 2010 Chinese Census. A logistic regression model with restricted cubic splines (RCS) was employed to characterize the nonlinear associations of age and body mass index (BMI) with the risk of diabetes subtypes defined by distinct blood glucose indicators elevations, as well as the relationships between different blood glucose indicators (FPG, PPG, HbA1c) and the risk of metabolic disorders such as hypertension, hypertriglyceridemia, hypercholesterolemia, high low-density lipoprotein cholesterol (high LDL-C) and low high-density lipoprotein cholesterol (low HDL-C). RESULTS: Among individuals with diabetes, elevated PPG alone was the most common abnormality, affecting 26.96% (1382/5127) of the population. Among the seven groups with only one elevated blood glucose indicator, individuals with elevated PPG alone exhibited the highest mean levels of triglycerides (TG) at 2.11 mmol/L (95% confidence interval [CI]: 1.97-2.25 mmol/L, P = 0.004), total cholesterol (TC) at 5.26 mmol/L (95% CI: 5.18-5.33 mmol/L, P <0.001), and low-density lipoprotein cholesterol (LDL-C) at 3.12 mmol/L, (95% CI: 3.06-3.19 mmol/L, P = 0.001). Individuals with elevated PPG alone showed a high prevalence of hypertension (806/1382, 58.32%), hypertriglyceridemia (676/1382, 48.91%), hypercholesterolemia (694/1382, 50.22%), High LDL-C (525/1382, 37.94%), and Low HDL-C (364/1382, 26.34%). The association of age and BMI with the risk of diabetes revealed that the older the patient, the steeper the RCS curve for the odds ratio (OR) of diabetes with elevated PPG alone (age = 60, OR = 2.79, 95% CI [2.49-3.12], P <0.01). Similarly, as BMI increased, the RCS curve for the OR of diabetes with elevated HbA1c alone also steepened (BMI = 35, OR = 3.75, 95% CI [3.23-4.35], P <0.001). Additionally, the RCS yielded a positive association between blood glucose indicators and metabolic diseases risk. In individuals with diabetes, RCS for both the ORs of metabolic diseases (hypertension, hypertriglyceridemia, hypercholesterolemia, high LDL-C, low HDL-C) and the levels of metabolic indicators (TG, TC, LDL-C, HDL-C) revealed some inflection points within the ranges of FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%. CONCLUSIONS PPG is more closely related to metabolic disorders than FPG and HbA1c in people with diabetes. For patients with diabetes and metabolic disorders, it may be necessary to monitor blood glucose fluctuations within specific ranges (FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%).
Humans ; Female ; Cross-Sectional Studies ; Male ; Blood Glucose/metabolism* ; Middle Aged ; Glycated Hemoglobin/metabolism* ; Adult ; Metabolic Diseases/epidemiology* ; Aged ; China ; Diabetes Mellitus/blood* ; East Asian People