Haoneng Hu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Haoneng Hu has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Chuancheng Wu
Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350122, China
2 shared publications - Dan Wang
Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350108, China
2 shared publications - Jianjun Xiang
Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350122, China
2 shared publications - Ruoyu Li
Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350108, China
2 shared publications - Shilin Chen
Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350108, China
2 shared publications - Yongxin Wang
Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350108, China
2 shared publications
Latest Publications
- Open Access
- 5 August 2026
- Published by MDPI AG in Metabolites
- Vol. 16 (8) , 553
Untargeted Metabolomics Reveals Metabolic Perturbations in Community-Dwelling Elderly Exposed to PM2.5-Bound Ester Compounds
Background/Objectives: Ambient fine particulate matter (PM2.5) poses significant health risks to older adult populations, yet the specific contributions of its chemical constituents, particularly non-phthalate and non-organophosphate ester compounds, remain poorly understood. This study aimed to elucidate the mechanistic links between PM2.5-bound ester exposures and metabolic pathway alterations in elderly individuals. Methods: A total of 258 elderly residents aged 60 years or older from Fuzhou, China, were recruited. Personal PM2.5 exposure was monitored over 72 h using UPAS V2 samplers, with chemical components analyzed via gas chromatography–mass spectrometry (GC–MS). Plasma metabolomic profiling was conducted using liquid chromatography–mass spectrometry (LC–MS), and metabolic pathway enrichment was performed using MetaboAnalyst 5.0. Linear regression models adjusted for covariates (age, sex, BMI, lifestyle factors) assessed associations between ester exposures and metabolite abundance. Results: The mean PM2.5 concentration was 38.06 μg/m3, with ester compounds dominating the chemical composition. Twenty high-concentration non-target esters were prioritized for analysis. PM2.5 ester exposure was associated with alterations in key metabolic pathways, including steroid biosynthesis, glycolysis/gluconeogenesis, glycerophospholipid metabolism, and purine/pyrimidine metabolism. When interpreted alongside prior epidemiological evidence, these alterations represent putative links to increased risks of insulin resistance, cardiovascular dysfunction, and metabolic syndrome—relationships that require confirmation in prospective cohort studies and controlled toxicological experiments. Conclusions: Putatively annotated PM2.5-bound ester compounds, particularly non-regulated subclasses, are associated with systemic metabolic alterations in older adults, coincident with perturbations in steroid and lipid metabolism. While these findings are exploratory and hypothesis-generating, they highlight the need to incorporate specific ester profiles into PM2.5 risk assessments and develop targeted interventions for vulnerable aging populations.
- 5 August 2026
- Published by MDPI AG in Metabolites
- Vol. 16 (8) , 553
Open AccessUntargeted Metabolomics Reveals Metabolic Perturbations in Community-Dwelling Elderly Exposed to PM2.5-Bound Ester Compounds
Background/Objectives: Ambient fine particulate matter (PM2.5) poses significant health risks to older adult populations, yet the specific contributions of its chemical constituents, particularly non-phthalate and non-organophosphate ester compounds, remain poorly understood. This study aimed to elucidate the mechanistic links between PM2.5-bound ester exposures and metabolic pathway alterations in elderly individuals. Methods: A total of 258 elderly residents aged 60 years or older from Fuzhou, China, were recruited. Personal PM2.5 exposure was monitored over 72 h using UPAS V2 samplers, with chemical components analyzed via gas chromatography–mass spectrometry (GC–MS). Plasma metabolomic profiling was conducted using liquid chromatography–mass spectrometry (LC–MS), and metabolic pathway enrichment was performed using MetaboAnalyst 5.0. Linear regression models adjusted for covariates (age, sex, BMI, lifestyle factors) assessed associations between ester exposures and metabolite abundance. Results: The mean PM2.5 concentration was 38.06 μg/m3, with ester compounds dominating the chemical composition. Twenty high-concentration non-target esters were prioritized for analysis. PM2.5 ester exposure was associated with alterations in key metabolic pathways, including steroid biosynthesis, glycolysis/gluconeogenesis, glycerophospholipid metabolism, and purine/pyrimidine metabolism. When interpreted alongside prior epidemiological evidence, these alterations represent putative links to increased risks of insulin resistance, cardiovascular dysfunction, and metabolic syndrome—relationships that require confirmation in prospective cohort studies and controlled toxicological experiments. Conclusions: Putatively annotated PM2.5-bound ester compounds, particularly non-regulated subclasses, are associated with systemic metabolic alterations in older adults, coincident with perturbations in steroid and lipid metabolism. While these findings are exploratory and hypothesis-generating, they highlight the need to incorporate specific ester profiles into PM2.5 risk assessments and develop targeted interventions for vulnerable aging populations.
- Open Access
From Environmental Concentrations to Individual Inhalation: Analysis of Exposure Differences to PM2.5 and Chemical Components in Elderly Populations and Their Influencing Factors
(1) Background: This study investigated the characteristics and influencing factors of exposure to fine particulate matter (PM2.5) and its chemical composition among elderly residents, with the aim of revealing potential differences in exposure. (2) Methods: A total of 258 elderly individuals were monitored for 72 h through individual, indoor, and outdoor PM2.5 measurements. Concentrations were determined, and non-targeted components were analyzed by gas chromatography-mass spectrometry (GC-MS). Through Spearman correlation analysis, generalized linear model, and linear regression to explore the influencing factors. (3) Results: The individual PM2.5 concentration was higher than both the indoor and outdoor concentrations. A total of 20,962 compounds were detected in personal PM2.5 samples, 6794 in indoor PM2.5 samples, among which 4285 compounds were shared between the two sample types. The components were mainly esters, aromatic compounds, and amines. PM2.5 concentration was correlated with age, housing area, humidifier use, and second-hand smoke exposure. Chemical composition is related to outdoor pollution, furniture material, and daily behavior. (4) Conclusions: The individual PM2.5 concentration is higher than the environmental concentration, and its chemical composition overlaps with the indoor and outdoor environment, which is jointly affected by demography, living conditions, and daily behavior.
Open AccessFrom Environmental Concentrations to Individual Inhalation: Analysis of Exposure Differences to PM2.5 and Chemical Components in Elderly Populations and Their Influencing Factors
(1) Background: This study investigated the characteristics and influencing factors of exposure to fine particulate matter (PM2.5) and its chemical composition among elderly residents, with the aim of revealing potential differences in exposure. (2) Methods: A total of 258 elderly individuals were monitored for 72 h through individual, indoor, and outdoor PM2.5 measurements. Concentrations were determined, and non-targeted components were analyzed by gas chromatography-mass spectrometry (GC-MS). Through Spearman correlation analysis, generalized linear model, and linear regression to explore the influencing factors. (3) Results: The individual PM2.5 concentration was higher than both the indoor and outdoor concentrations. A total of 20,962 compounds were detected in personal PM2.5 samples, 6794 in indoor PM2.5 samples, among which 4285 compounds were shared between the two sample types. The components were mainly esters, aromatic compounds, and amines. PM2.5 concentration was correlated with age, housing area, humidifier use, and second-hand smoke exposure. Chemical composition is related to outdoor pollution, furniture material, and daily behavior. (4) Conclusions: The individual PM2.5 concentration is higher than the environmental concentration, and its chemical composition overlaps with the indoor and outdoor environment, which is jointly affected by demography, living conditions, and daily behavior.