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Cheng Z, Zhao S, Qiao D, Pi X, Zhang B. Resolving differences in digestion features of cooked rice and wheat noodles: A view from starch multiscale structure. Food Chem 2025; 465:141979. [PMID: 39541689 DOI: 10.1016/j.foodchem.2024.141979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Revised: 06/30/2024] [Accepted: 11/07/2024] [Indexed: 11/16/2024]
Abstract
The staple foods play an important role in providing energy in the human daily diet. Wheat is the main staple food in northern China, rice in southern China, and the different staple food patterns between the north and south result in health disparities. Therefore, analyzing the differences in the digestion of staple foods are particularly important for understanding the digestive energy supply of staple foods. The firmer gel network structure, thicker crystalline lamellae, more V-type crystallites, higher degree of helical structure, and short-range order in cooked rice impeded the diffusion of amylase on the starch surface and inhibited the amylase-starch binding, leading to a lower rate of enzymatic hydrolysis of starch molecular chains and significantly higher content of RS than wheat noodles (P < 0.05). The different processing methods of cooked rice and wheat noodles influenced the multiscale structure of starch and thus the rate of digestion.
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Affiliation(s)
- Zihang Cheng
- Group for Cereals and Oils Processing, College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, College of Food Science, Southwest University, Chongqing 400715, China
| | - Siming Zhao
- Group for Cereals and Oils Processing, College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Dongling Qiao
- Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, College of Food Science, Southwest University, Chongqing 400715, China
| | - Xiaowen Pi
- Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, College of Food Science, Southwest University, Chongqing 400715, China
| | - Binjia Zhang
- Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, College of Food Science, Southwest University, Chongqing 400715, China.
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Wang M, Xu K, Yang J, Bennett DA, Du H, Liu X. Normal-weight obesity subtypes and 10-year risks of major vascular diseases in 0.3 million adults. Clin Nutr 2024; 45:36-42. [PMID: 39740297 DOI: 10.1016/j.clnu.2024.12.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2024] [Revised: 12/18/2024] [Accepted: 12/24/2024] [Indexed: 01/02/2025]
Abstract
BACKGROUND & AIMS Obesity directly contributes to the progression of cardiovascular disease, but little is known about the association and risk attribution of normal-weight obesity subtypes with the incidence of major vascular events (MVEs) and their subtypes. METHODS This is a prospective cohort study based on the China Kadoorie Biobank (CKB). A total of 308,071 individuals with no prior vascular diseases or cancer were included at baseline. The incidence of MVEs and their subtypes were recorded during follow-up. Adjusted hazard ratios (HRs) for each disease were yielded by Cox regression. RESULTS During a median follow-up of 10.3 years, 62,040 MVEs occurred, with the adjusted HRs (95 % confidence intervals) were 1.11 (1.09-1.13) for normal-weight general obesity (NWGO), 1.27 (1.23-1.31) for normal-weight central obesity (NWCO), and 1.30 (1.27-1.33) for normal-weight central and general obesity (NWCGO). For subtypes of MVEs, increased waist circumference (WC) was associated with excess risk of ischaemic heart disease (IHD) independent of body fat percent (BF%) levels (HR range: 1.30-1.69 in men; 1.36-1.55 in women), while the risk plateaued with rising BF% within each WC quartile. However, even in men with lower WC (≤78 cm [median]), the risks of cerebrovascular disease (CeVD), particularly ischaemic stroke (IS), were increased with higher BF% (all P < 0.01). Conversely, in women, independent dose-response associations were primarily observed between increasing WC and CeVD, with the highest risk observed for IS (HR 1.38, 1.31-1.47). CONCLUSIONS This study provided novel, sex-specific evidence that normal-weight obesity subtypes were associated with distinct risks of subtypes of MVEs, with elevated risks predominantly attributable to WC in women and both WC and BF% in men.
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Affiliation(s)
- Menghan Wang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 710061, Xi'an, Shaanxi, China
| | - Kun Xu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 710061, Xi'an, Shaanxi, China
| | - Jiaomei Yang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 710061, Xi'an, Shaanxi, China
| | - Derrick A Bennett
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, OX37LF, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, OX37LF, Oxford, UK
| | - Xin Liu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 710061, Xi'an, Shaanxi, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, 710061, Xi'an, Shaanxi, China.
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Xu K, Zhang B, He Y, Wang Y, Liu Y, Shi G, Shen Y, Chen F, Mi B, Shi L, Zeng L, Liu X, Dang S, Yan H. Serum Lipidomic Signatures Mediate the Association Between Coarse Grain Preference and Central Obesity in Adults With Normal Weight and High Wheat Intake. Mol Nutr Food Res 2024:e202400515. [PMID: 39692176 DOI: 10.1002/mnfr.202400515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Revised: 10/11/2024] [Accepted: 11/29/2024] [Indexed: 12/19/2024]
Abstract
Little is known about the association between grain preference andabdominal fat accumulation, and mediating roles of circulating lipidomicsignatures. We quantified 1245 circulating lipids in 150 normal-weight centralobesity (NWCO) cases and 150 controls using targeted lipidomics. Grainpreference was determined by the highest intake frequency of grains (whiterice, wheat, or coarse grain). In our participants with high wheat intakefrequency, preferring coarse grain over rice was associated with a 60% lowerrisk of NWCO. Of the 585 lipids showing opposing associations with white riceand coarse grains, 46 were significantly linked to either (p < 0.05), predominantly alkylacyl phospholipids (PE-Os; n < 9) and alkenylacylphospholipids (PE-Ps; nx = 7). Network analysis identified a module primarilycomposed of PE-Os and PE-Ps, which was positively associated with coarse grain (p = 0.014). Another module, mainly consisting of triacylglycerols (TGs), was associatedwith white rice (p = 0.003) and mediated the association between white rice(mediation proportion: 20.30%; p = 0.027) or coarse grain preference (11.43%; p = 0.040) and NWCO. Specific lipids, such as TG(8:0_16:0_16:0) and TG(8:0_14:0_18:0), exhibited notable mediation effects. In normal-weight individuals with highwheat intake frequency, preferring coarse grain was inversely associated with NWCO, mediated by specific lipidomic signatures.
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Affiliation(s)
- Kun Xu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Binyan Zhang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Yifei He
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Yutong Wang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Yezhou Liu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Guoshuai Shi
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Yuan Shen
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Fangyao Chen
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Baibing Mi
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Lin Shi
- School of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi' an, Shaanxi, China
| | - Lingxia Zeng
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Xin Liu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Shaonong Dang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Hong Yan
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Nutrition and Food Safety Engineering Research Center of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Shaomei W, Dezhi J, Mengfen L, Huaan D, Xianbin D, Juan P, Xia L, Yanfeng Z. Association between major dietary patterns and obesity phenotypes in southwest China: baseline survey results from Hechuan. Front Nutr 2024; 11:1467025. [PMID: 39568722 PMCID: PMC11577167 DOI: 10.3389/fnut.2024.1467025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 10/15/2024] [Indexed: 11/22/2024] Open
Abstract
Background This study aimed to identify the main dietary patterns in Hechuan and clarify how they are associated with obesity phenotypes. Methods A cross-sectional study was conducted based on a baseline survey of a general population cohort study in southwest China. A semi-quantitative food frequency questionnaire (FFQ) was used to investigate the dietary habits of the participants in the past year. Principal component analysis was conducted to identify the main dietary patterns, and multinomial logistic regression analysis was conducted to describe the association between the major dietary patterns and obesity phenotypes. Results Three major dietary patterns were identified. The participants who followed the wheaten food dietary pattern had a higher likelihood of having metabolically normal obesity (MHO) (odds ratio (OR) 1.05, 95% confidence interval (CI) 1.02-1.08), metabolically abnormal normal weight (MUNW) (OR 1.08, 95%CI 1.00-1.16), and metabolically abnormal obesity (MUO) (OR 1.07, 95%CI 1.04-1.11). Specifically, those with the highest wheaten food dietary pattern were 1.60 times more likely to have MHO (OR 1.60, 95%CI 1.25-2.05), 2.62 times more likely to have MUNW (OR 2.62, 95%CI 1.28-5.37), and 2.01 times more likely to have MUO (OR 2.01, 95%CI 1.51-2.69) than those with the lowest wheaten food dietary pattern. Conclusion The wheaten food dietary pattern may increase the risk of obesity and metabolic abnormalities. Therefore, timely interventions should be carried out for this group of people.
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Affiliation(s)
- Wang Shaomei
- Hechuan District Center Disease Control and Prevention, Chongqing, China
- Department of Nutrition and Health Management, Chengdu Medical College, Chengdu, China
| | - Jing Dezhi
- Hechuan District Center Disease Control and Prevention, Chongqing, China
| | - Li Mengfen
- Hechuan District Center Disease Control and Prevention, Chongqing, China
| | - Duan Huaan
- Hechuan District Center Disease Control and Prevention, Chongqing, China
| | - Ding Xianbin
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Peng Juan
- Hechuan District Center Disease Control and Prevention, Chongqing, China
| | - Li Xia
- Hechuan District Center Disease Control and Prevention, Chongqing, China
| | - Zhu Yanfeng
- Department of Nutrition and Health Management, Chengdu Medical College, Chengdu, China
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Xie J, Li J, Ma G, Wang M, Li Y, He Y, Xu K, Tian T, Yang N, Wang Q, Chang J, Liu X. Knowledge, Behavior, and Influencing Factors of Coarse Grain Consumption among Chinese Adults: A Focus Group Study in Xi'an. Curr Dev Nutr 2024; 8:104474. [PMID: 39582946 PMCID: PMC11582436 DOI: 10.1016/j.cdnut.2024.104474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 09/24/2024] [Accepted: 09/29/2024] [Indexed: 11/26/2024] Open
Abstract
Background Coarse grains are rich in fiber, minerals, and other beneficial nutrients but are consumed at low levels in modern populations. The factors that influence coarse grain consumption in current living and dietary environments are not fully understood. Objectives This study aimed to explore the knowledge and behavior related to coarse grain consumption and identify the influencing factors among Chinese citizens. Methods Six focus group discussions were conducted with 39 participants aged 18-65 years from diverse social backgrounds in Xi'an, China. All discussions were transcribed verbatim and analyzed using inductive thematic analysis. Results The majority of participants demonstrated insufficient knowledge about coarse grains, including their definitions, health benefits, and recommended intake. A small number of the participants reported regular consumption. The barriers to coarse grain consumption were poor sensory properties, insufficient cooking skills and time, limited availability of ready-to-eat foods, established dietary habits, and high prices. Additionally, new barriers included psychological burden, concerns about food safety, the impact of processing methods on health benefits, and special health conditions. Health benefits and family influence emerged as the 2 primary factors motivating coarse grain consumption. Most participants expressed a positive attitude toward partially replacing staple foods with coarse grains. Enhancing health education, innovating food processing methods, improving labeling systems, and strengthening safety supervision have been recommended for increasing coarse grain consumption. Conclusions A gap exists between health awareness and healthy behaviors regarding coarse grain consumption; thus, collaborative efforts among government agencies, educational institutions, nutrition societies, the food industry, policymakers, and health professionals are essential to overcome these challenges.
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Affiliation(s)
- Jiawen Xie
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Junqi Li
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Guoqing Ma
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Menghan Wang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yunfeng Li
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
- The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yafang He
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
- SpecAlly Life Technology Co., Ltd., Wuhan, China
| | - Kun Xu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Tian Tian
- Department of Nutrition, Xi’an Daxing Hospital, Xi'an, China
| | - Nan Yang
- Health Management Department, the Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Qian Wang
- Health Management Department, the Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Jie Chang
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Health Science Center, Xi'an, China
| | - Xin Liu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, School of Public Health, Global Health Institute, Health Science Center, Xi'an Jiaotong University, Xi'an, China
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Xu K, Shen Y, Shi L, Chen F, Zhang B, He Y, Wang Y, Liu Y, Shi G, Mi B, Zeng L, Dang S, Liu X, Yan H. Lipidomic perturbations of normal-weight adiposity phenotypes and their mediations on diet-adiposity associations. Clin Nutr 2024; 43:20-30. [PMID: 39307096 DOI: 10.1016/j.clnu.2024.09.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 09/03/2024] [Accepted: 09/05/2024] [Indexed: 10/26/2024]
Abstract
BACKGROUND & AIMS Normal-weight obesity (NWO) and normal-weight central obesity (NWCO) have been linked to higher cardiometabolic risks, but their etiological bases and attributable dietary factors remain unclear. In this study we therefore aimed to identify lipidomic signatures and dietary factors related to NWO and NWCO and to explore the mediation associations of lipids in diet-adiposity associations. METHODS Using a high-coverage targeted lipidomic approach, we quantified 1245 serum lipids in participants with NWO (n = 150), NWCO (n = 150), or propensity-score-matched normal-weight controls (n = 150) based on the Regional Ethnic Cohort Study in Northwest China. Consumption frequency of 28 major food items was recorded using a food frequency questionnaire. RESULTS Profound lipidomic perturbations of NWCO relative to NWO were observed, and 249 (dominantly glycerolipids) as well as 48 (dominantly glycerophospholipids) lipids were exclusively associated with NWCO or NWO. Based on strong lipidomic signatures identified by a LASSO model, phospholipid biosynthesis was the top enriched pathway of NWCO, and sphingolipid metabolism was the top pathway of NWO. Remarkably, sphingolipids were positively associated with NWO and NWCO, but lyso-phosphatidylcholines were negatively associated with them. Rice, fruit juice, and carbonated drink intakes were positively associated with the risk of NWCO. Both global and individual lipidomic signatures, including SE(28:1_22:6) and HexCer(d18:1/20:1), mediated these diet-NWCO associations (mediation proportion: 15.92%-26.10%). CONCLUSIONS Differential lipidomic signatures were identified for overall and abdominal adiposity accumulation in normal-weight individuals, underlining their core mediation roles in dietary contributions to adiposity deposition.
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Affiliation(s)
- Kun Xu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Yuan Shen
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Lin Shi
- School of Food Engineering and Nutritional Science, Shaanxi Normal University, 710062, Xi' an, Shaanxi, China
| | - Fangyao Chen
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Binyan Zhang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China; School of Public Health, Xi'an Medical College, Xi'an, 710021, China
| | - Yafang He
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Yutong Wang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Yezhou Liu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Guoshuai Shi
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Baibing Mi
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Lingxia Zeng
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China
| | - Shaonong Dang
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China.
| | - Xin Liu
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China.
| | - Hong Yan
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China; Nutrition and Food Safety Engineering Research Center of Shaanxi Province, Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, 76 West Yanta Road, 710061, Xi'an, Shaanxi, China.
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Gou W, Wang H, Su C, Fu Y, Wang X, Gao C, Shuai M, Miao Z, Zhang J, Jia X, Du W, Zhang K, Zhang B, Zheng JS. The temporal dynamics of the gut mycobiome and its association with cardiometabolic health in a nationwide cohort of 12,641 Chinese adults. Cell Rep Med 2024; 5:101775. [PMID: 39368480 PMCID: PMC11513856 DOI: 10.1016/j.xcrm.2024.101775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 07/30/2024] [Accepted: 09/13/2024] [Indexed: 10/07/2024]
Abstract
The dynamics of the gut mycobiome and its association with cardiometabolic health remain largely unexplored. Here, we employ internal transcribed spacer (ITS) sequencing to capture the gut mycobiome composition and dynamics within a nationwide human cohort of 12,641 Chinese participants, including 1,946 participants with repeated measurements across three years. We find that the gut mycobiome is associated with cardiometabolic diseases and related biomarkers in both cross-sectional and dynamic analyses. Fungal alpha diversity indices and 19 mycobiome genera are the major contributors to the mycobiome-cardiometabolic disease link. Particularly, Saccharomyces emerges as an effect modifier of traditional risk factors in promoting type 2 diabetes risk. Further integration of multi-omics data reveals key metabolites such as γ-linolenic acid and L-valine linking the gut mycobiome to type 2 diabetes. This study advances our understanding of the potential roles of the gut mycobiome in cardiometabolic health.
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Affiliation(s)
- Wanglong Gou
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China
| | - Huijun Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China; NHC Key Laboratory of Public Nutrition and Health, Beijing, China
| | - Chang Su
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China; NHC Key Laboratory of Public Nutrition and Health, Beijing, China
| | - Yuanqing Fu
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Xinyu Wang
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China
| | - Chang Gao
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China
| | - Menglei Shuai
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China
| | - Zelei Miao
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Jiguo Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China; NHC Key Laboratory of Public Nutrition and Health, Beijing, China
| | - Xiaofang Jia
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China; NHC Key Laboratory of Public Nutrition and Health, Beijing, China
| | - Wenwen Du
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China; NHC Key Laboratory of Public Nutrition and Health, Beijing, China
| | - Ke Zhang
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China
| | - Bing Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China; NHC Key Laboratory of Public Nutrition and Health, Beijing, China.
| | - Ju-Sheng Zheng
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China; Research Center for Industries of the Future, School of Life Sciences, Westlake University, Hangzhou, China.
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Yang Z, Wang Y, Tang C, Han M, Wang Y, Zhao K, Liu J, Tian J, Wang H, Chen Y, Jiang Q. Urinary neonicotinoids and metabolites are associated with obesity risk in Chinese school children. ENVIRONMENT INTERNATIONAL 2024; 183:108366. [PMID: 38061247 DOI: 10.1016/j.envint.2023.108366] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/06/2023] [Accepted: 12/01/2023] [Indexed: 01/25/2024]
Abstract
BACKGROUND Neonicotinoids are the most widely used insecticides. Laboratory studies have suggested that neonicotinoids are one potential obesogen, but relevant data are limited in human. OBJECTIVE To examine the association between exposure to neonicotinoids and childhood obesity. METHODS We investigated 442 children in Shanghai, East China and measured eight neonicotinoids (thiamethoxam, clothianidin, acetamiprid, imidacloprid, thiacloprid, nitenpyram, dinotefuran, and imidaclothiz) and four metabolites (N-desmethyl-thiamethoxam, N-desmethyl-clothianidin, N-desmethyl-acetamiprid, and 5-OH-imidacloprid) in urine. Body mass index (BMI) and waist circumference (WC) were used to identify general overweight/obesity and central obesity, respectively. Linear and logistic regression models based on generalized estimating equations were used to investigate the associations of urinary neonicotinoids and metabolites with BMI z-score, WC z-score, general overweight/obesity, and central obesity. RESULTS Children with a positive detection of clothianidin and its metabolite had a marginally higher BMI z-score (regression coefficient (β): 0.08, 95% confidence interval (95% CI): 0.01, 0.14) after adjusted for relevant covariates. After creatinine-adjusted concentration was trichotomized, compared to children with a negative detection, children in the high urinary concentration of acetamiprid and its metabolite had a low BMI z-score (β: -0.19, 95%CI: -0.30, -0.08), children in the medium urinary concentration of neonicotinoids and metabolites other than thiamethoxam, clothianidin, acetamiprid, and their metabolites had a marginally higher BMI z-score (β: 0.25, 95%CI: 0.03, 0.46), a higher WC z-score (β: 0.24, 95%CI: 0.14, 0.33), and a higher odds of central obesity (odds ratio (OR): 2.16, 95% CI: 1.28, 3.63), and children in the medium urinary concentration of all neonicotinoids and metabolites had a higher odds of central obesity (OR: 1.55, 95%CI: 1.04, 2.33). Some associations showed sex- and age- related differences. CONCLUSION Urinary neonicotinoids and metabolites were found to be differently associated with obesity-related indexes, which suggested that exposure to neonicotinoids might have a mixed effect on childhood obesity.
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Affiliation(s)
- Zichen Yang
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yuanping Wang
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Chuanxi Tang
- Changning District Center for Disease Control and Prevention, Changning District, Shanghai 200051, China
| | - Minghui Han
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yi Wang
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Ke Zhao
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Jiaqi Liu
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Jiacheng Tian
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Hexing Wang
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China.
| | - Yue Chen
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario K1G5Z3, Canada.
| | - Qingwu Jiang
- School of Public Health/Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
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Kobayashi K, Wang X, Wang W. Genetically Modified Rice Is Associated with Hunger, Health, and Climate Resilience. Foods 2023; 12:2776. [PMID: 37509868 PMCID: PMC10379675 DOI: 10.3390/foods12142776] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 07/14/2023] [Accepted: 07/19/2023] [Indexed: 07/30/2023] Open
Abstract
While nearly one in nine people in the world deals with hunger, one in eight has obesity, and all face the threat of climate change. The production of rice, an important cereal crop and staple food for most of the world's population, faces challenges due to climate change, the increasing global population, and the simultaneous prevalence of hunger and obesity worldwide. These issues could be addressed at least in part by genetically modified rice. Genetic engineering has greatly developed over the century. Genetically modified rice has been approved by the ISAAA's GM approval database as safe for human consumption. The aim behind the development of this rice is to improve the crop yield, nutritional value, and food safety of rice grains. This review article provides a summary of the research data on genetically modified rice and its potential role in improving the double burden of malnutrition, primarily through increasing nutritional quality as well as grain size and yield. It also reviews the potential health benefits of certain bioactive components generated in genetically modified rice. Furthermore, this article discusses potential solutions to these challenges, including the use of genetically modified crops and the identification of quantitative trait loci involved in grain weight and nutritional quality. Specifically, a quantitative trait locus called grain weight on chromosome 6 has been identified, which was amplified by the Kasa allele, resulting in a substantial increase in grain weight and brown grain. An overexpressing a specific gene in rice, Oryza sativa plasma membrane H+-ATPase1, was observed to improve the absorption and assimilation of ammonium in the roots, as well as enhance stomatal opening and photosynthesis rate in the leaves under light exposure. Cloning research has also enabled the identification of several underlying quantitative trait loci involved in grain weight and nutritional quality. Finally, this article discusses the increasing threats of climate change such as methane-nitrous oxide emissions and global warming, and how they may be significantly improved by genetically modified rice through modifying a water-management technique. Taken together, this comprehensive review will be of particular importance to the field of bioactive components of cereal grains and food industries trying to produce high-quality functional cereal foods through genetic engineering.
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Affiliation(s)
- Kaori Kobayashi
- Department of Food Nutrition Dietetics and Health, Kansas State University, Manhattan, KS 66506, USA
| | - Xiaohui Wang
- College of Agronomy, Sichuan Agricultural University, Chengdu 611130, China
| | - Weiqun Wang
- Department of Food Nutrition Dietetics and Health, Kansas State University, Manhattan, KS 66506, USA
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