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Wolever TM, Zurbau A, Koecher K, Au-Young F. The effect of adding protein to a carbohydrate meal on postprandial glucose and insulin responses: a systematic review and meta-analysis of acute controlled feeding trials. J Nutr 2024:S0022-3166(24)00392-4. [PMID: 39019167 DOI: 10.1016/j.tjnut.2024.07.011] [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: 02/02/2024] [Revised: 05/21/2024] [Accepted: 07/10/2024] [Indexed: 07/19/2024] Open
Abstract
BACKGROUND protein influences acute postprandial-glucose and -insulin responses but the effects of dose, protein-type and health-status are unknown. OBJECTIVE to determine the acute effect of adding protein to carbohydrate on postprandial responses and identify effect modifiers. METHODS we searched MEDLINE, EMBASE and Cochrane databases through 30 July 2023 for acute, crossover trials comparing acute postprandial-responses elicited by carbohydrate-containing test-meals with vs without added protein in adults without-diabetes or with type-2 (T2DM) or type-1 (T1DM) diabetes. Group data were pooled separately using generic inverse-variance with random-effects models and expressed as ratio-of-means with [95% CIs]. Risk-of-bias and certainty-of-evidence (GRADE) were assessed. RESULTS in 154 trial-comparisons of animal-, dairy- and plant-proteins (without-diabetes, n=22,67,32; T2DM, n=14,16,3), each gram-protein/gram-carbohydrate (g/g) reduced glucose-area-under-the-curve (AUC) less in T2DM than in those without-diabetes (-10% vs -50%, P<0.05) but increased insulin-AUC similarly (+76 vs +56%, respectively). In subjects without-diabetes, each g/g of dairy- and plant-proteins reduced glucose-AUC by 52 and 55% and increased insulin-AUC by 64 and 45% (all P<0.05). Animal-proteins significantly reduced glucose-AUC by 31% and increased insulin-AUC by 37% (pooled effects), but without a significant dose-response. In T2DM animal-protein reduced glucose-AUC by 13% and increased insulin-AUC by 105%, with no significant dose-response. Dairy-protein reduced glucose-AUC by 18% (no dose-response), but each g/g increased insulin-AUC by 34% (P<0.05). In T1DM protein increased glucose-AUC by 40% (P<0.05, n=5). Data-source (reported vs calculated) and study-methodology-quality significantly modified some outcomes and contributed to high between-study heterogeneity. CONCLUSIONS in people without-diabetes, adding dairy- or plant-protein to a carbohydrate-containing meal elicits physiologically significant reductions in glucose-AUC and increases insulin-AUC. Animal-protein may slightly reduce glucose-AUC and may increase insulin-AUC. In T2DM, protein may not have such large and consistent effects. Further research is needed to determine if the effects of protein differ by health status and protein-source. REGISTRATION PROSPERO CRD42022322090. FUNDING General Mills.
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Affiliation(s)
- Thomas Ms Wolever
- INQUIS Clinical Research, Inc., Toronto, Ontario, Canada; Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Ontario, Canada.
| | - Andreea Zurbau
- INQUIS Clinical Research, Inc., Toronto, Ontario, Canada; Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Katie Koecher
- General Mills, Bell Institute of Health & Nutrition, Minneapolis, MN, USA
| | - Fei Au-Young
- INQUIS Clinical Research, Inc., Toronto, Ontario, Canada; Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, Ontario, Canada
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Lai H, Sun M, Liu Y, Zhu H, Li M, Pan B, Wang Q, Yang Q, Cao X, Tian C, Lu Y, Song X, Ding G, Tian J, Yang K, Ge L. White rice consumption and risk of cardiometabolic and cancer outcomes: A systematic review and dose-response meta-analysis of prospective cohort studies. Crit Rev Food Sci Nutr 2023; 63:12476-12487. [PMID: 35852223 DOI: 10.1080/10408398.2022.2101984] [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] [Indexed: 11/03/2022]
Abstract
White rice is the food more than half of the world's population depends on. White rice intake can significantly increase the glycemic load of consumers and bring some adverse health effects. However, the quality of evidence implicating white rice in adverse health outcomes remains unclear. To evaluate the association between white rice consumption and the risk of cardiometabolic and cancer outcomes, a systematic review and dose-response meta-analysis of the relevant publications were performed. Twenty-three articles including 28 unique prospective cohorts with 1,527,198 participants proved eligible after a comprehensive search in four databases. For the risk of type 2 diabetes mellitus (T2DM), the pooled RR was 1.18 (16 more per 1000 persons) for comparing the highest with the lowest category of white rice intake, with moderate certainty evidence. Females presented a higher risk (23 more per 1000 persons) in subgroup analysis. And every additional 150 grams of white rice intake per day was associated with a 6% greater risk of T2DM (5 more per 1000 persons) with a linear positive trend. We found no significant associations between white rice intake and risk of cardiovascular diseases (CVD), CVD mortality, cancer, and metabolic syndrome. In conclusion, moderate certainty evidence demonstrated that white rice intake was associated with T2DM risk, with a linear positive trend. However, low to very low certainty of evidence suggested that no substantial associations were found between white rice intake and other cardiometabolic and cancer outcomes. More cohorts are needed to strength the evidence body.
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Affiliation(s)
- Honghao Lai
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Mingyao Sun
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
| | - Yafei Liu
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Hongfei Zhu
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Mengting Li
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Bei Pan
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Qi Wang
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Qiuyu Yang
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
| | - Xiao Cao
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
| | - Chen Tian
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Yao Lu
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Xuping Song
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Guowu Ding
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
| | - Jinhui Tian
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
| | - Kehu Yang
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
| | - Long Ge
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
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Chen P, Li S, Zhou Z, Wang X, Shi D, Li Z, Li X, Xiao Y. Liver fat metabolism of broilers regulated by Bacillus amyloliquefaciens TL via stimulating IGF-1 secretion and regulating the IGF signaling pathway. Front Microbiol 2022; 13:958112. [PMID: 35966703 PMCID: PMC9363834 DOI: 10.3389/fmicb.2022.958112] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 06/30/2022] [Indexed: 11/29/2022] Open
Abstract
Bacillus amyloliquefaciens TL (B.A-TL) is well-known for its capability of promoting protein synthesis and lipid metabolism, in particular, the abdominal fat deposition in broilers. However, the underlying molecular mechanism remains unclear. In our study, the regulations of lipid metabolism of broilers by B.A-TL were explored both in vivo and in vitro. The metabolites of B.A-TL were used to simulate in vitro the effect of B.A-TL on liver metabolism based on the chicken hepatocellular carcinoma cell line (i.e., LMH cells). The effects of B.A-TL on lipid metabolism by regulating insulin/IGF signaling pathways were investigated by applying the signal pathway inhibitors in vitro. The results showed that the B.A-TL metabolites enhanced hepatic lipid synthesis and stimulated the secretion of IGF-1. The liver transcriptome analysis revealed the significantly upregulated expressions of four genes (SI, AMY2A, PCK1, and FASN) in the B.A-TL treatment group, mainly involved in carbohydrate digestion and absorption as well as biomacromolecule metabolism, with a particularly prominent effect on fatty acid synthase (FASN). Results of cellular assays showed that B.A-TL metabolites were involved in the insulin/IGF signaling pathway, regulating the expressions of lipid metabolism genes (e.g., FASN, ACCα, LPIN, and ACOX) and the FASN protein, ultimately regulating the lipid metabolism via the IGF/PI3K/FASN pathway in broilers.
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Decreasing the RAG:SAG ratio of granola cereal predictably reduces postprandial glucose and insulin responses: a report of four randomised trials in healthy adults. J Nutr Sci 2022; 11:e21. [PMID: 35399553 PMCID: PMC8943571 DOI: 10.1017/jns.2022.22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 02/22/2022] [Indexed: 11/29/2022] Open
Abstract
Dietary starch contains rapidly (RAG) and slowly available glucose (SAG). To establish the relationships between the RAG:SAG ratio and postprandial glucose, insulin and hunger, we measured postprandial responses elicited by test meals varying in the RAG:SAG ratio in n 160 healthy adults, each of whom participated in one of four randomised cross-over studies (n 40 each): a pilot trial comparing six chews (RAG:SAG ratio 2·4–42·7) and three studies comparing a test granola (TG1-3, RAG:SAG ratio 4·5–5·2) with a control granola (CG1–3, RAG:SAG ratio 54·8–69·3). Within studies, test meals were matched for fat, protein and available carbohydrate. Blood glucose, serum insulin and subjective hunger were measured for 3 h. Data were subjected to repeated-measures analysis of variance (ANOVA). The relationships between the RAG:SAG ratio and postprandial end points were determined by regression analysis. In the pilot trial, 0–2 h glucose incremental areas under the curve (iAUC0–2; primary end point) varied across the six chews (P = 0·014) with each 50 % reduction in the RAG:SAG ratio reducing relative glucose response by 4·0 %. TGs1-3 elicited significantly lower glucose iAUC0–2 than CGs1–3 by 17, 18 and 17 %, respectively (similar to the 15 % reduction predicted by the pilot trial). The combined means ± sem (n 120) for TC and CG were glucose iAUC0–2, 98 ± 4 v. 118 ± 4 mmol × min/l (P < 0·001), and insulin iAUC0–2, 153 ± 9 v. 184 ± 11 nmol × h/l (P < 0·001), respectively. Neither postprandial hunger nor glucose or hunger increments 2 h after eating differed significantly between TG and CG. We concluded that TGs with RAG:SAG ratios <5·5 predictably reduced glycaemic and insulinaemic responses compared with CGs with RAG:SAG ratios >54. However, compared with CG, TG did not reduce postprandial hunger or delay the return of glucose or hunger to baseline.
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