{"title":"针对肠道微生物特征个性化肥胖治疗:将基于微生物组的分层整合到精准医学中","authors":"Okechukwu Paul-Chima Ugwu , Melvin Nnaemeka Ugwu , Mariam Basajja , Chinyere Nkemjika Anyanwu","doi":"10.1016/j.obmed.2025.100639","DOIUrl":null,"url":null,"abstract":"<div><div>Obesity is a chronic heterogenous metabolic disease that is on the rise in low- and middle-income countries like sub-Saharan Africa, where they are experiencing an urbanisation and westernisation of the diet, transforming the nutrition environment. Although microbiome-based stratification of obesity treatment has been suggested as a global solution, there are no African-specific structures. The current communication introduces the first Africa-adapted, conceptual and evidence-informed, enterotype-based model, combining recent African microbiome data. Unique microbial signatures of the gut e.g., a greater occurrence of <em>Succinivibria, Treponema</em>, and <em>Methanobrevibacter</em> are likely to affect nutritional response patterns and responses to interventions among Africans. The four-step conceptual model includes (1) gut profiling, (2) enterotype-matched diets, (3) metabolite tracking and (4) digital feedback loops, which are enabled by culturally adapted, low-cost diagnostics (e.g., portable quantitative polymerase chain reaction (qPCR) kits, lateral-flow short-chain fatty acid (SCFA)/lipopolysaccharide (LPS) assays), and mobile health platforms. We clarified that this is a hypothesis-driven framework, conceptually informed by existing evidence but not empirically validated. A randomised controlled trial (RCT) design proposal to use permutational multivariate analysis of variance (PERMANOVA) to test microbiome composition and multivariate regression to test the diet-microbiome body mass index (BMI) association. This methodology provides solutions to some of the main translational gaps in precision obesity care by incorporating African-specific microbial data, culturally specific diets, and scalable technology.</div></div>","PeriodicalId":37876,"journal":{"name":"Obesity Medicine","volume":"57 ","pages":"Article 100639"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Targeting gut microbial signatures to personalize obesity treatment: Integrating microbiome-based stratification into precision medicine\",\"authors\":\"Okechukwu Paul-Chima Ugwu , Melvin Nnaemeka Ugwu , Mariam Basajja , Chinyere Nkemjika Anyanwu\",\"doi\":\"10.1016/j.obmed.2025.100639\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Obesity is a chronic heterogenous metabolic disease that is on the rise in low- and middle-income countries like sub-Saharan Africa, where they are experiencing an urbanisation and westernisation of the diet, transforming the nutrition environment. Although microbiome-based stratification of obesity treatment has been suggested as a global solution, there are no African-specific structures. The current communication introduces the first Africa-adapted, conceptual and evidence-informed, enterotype-based model, combining recent African microbiome data. Unique microbial signatures of the gut e.g., a greater occurrence of <em>Succinivibria, Treponema</em>, and <em>Methanobrevibacter</em> are likely to affect nutritional response patterns and responses to interventions among Africans. The four-step conceptual model includes (1) gut profiling, (2) enterotype-matched diets, (3) metabolite tracking and (4) digital feedback loops, which are enabled by culturally adapted, low-cost diagnostics (e.g., portable quantitative polymerase chain reaction (qPCR) kits, lateral-flow short-chain fatty acid (SCFA)/lipopolysaccharide (LPS) assays), and mobile health platforms. We clarified that this is a hypothesis-driven framework, conceptually informed by existing evidence but not empirically validated. A randomised controlled trial (RCT) design proposal to use permutational multivariate analysis of variance (PERMANOVA) to test microbiome composition and multivariate regression to test the diet-microbiome body mass index (BMI) association. This methodology provides solutions to some of the main translational gaps in precision obesity care by incorporating African-specific microbial data, culturally specific diets, and scalable technology.</div></div>\",\"PeriodicalId\":37876,\"journal\":{\"name\":\"Obesity Medicine\",\"volume\":\"57 \",\"pages\":\"Article 100639\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Obesity Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2451847625000594\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Obesity Medicine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451847625000594","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
Targeting gut microbial signatures to personalize obesity treatment: Integrating microbiome-based stratification into precision medicine
Obesity is a chronic heterogenous metabolic disease that is on the rise in low- and middle-income countries like sub-Saharan Africa, where they are experiencing an urbanisation and westernisation of the diet, transforming the nutrition environment. Although microbiome-based stratification of obesity treatment has been suggested as a global solution, there are no African-specific structures. The current communication introduces the first Africa-adapted, conceptual and evidence-informed, enterotype-based model, combining recent African microbiome data. Unique microbial signatures of the gut e.g., a greater occurrence of Succinivibria, Treponema, and Methanobrevibacter are likely to affect nutritional response patterns and responses to interventions among Africans. The four-step conceptual model includes (1) gut profiling, (2) enterotype-matched diets, (3) metabolite tracking and (4) digital feedback loops, which are enabled by culturally adapted, low-cost diagnostics (e.g., portable quantitative polymerase chain reaction (qPCR) kits, lateral-flow short-chain fatty acid (SCFA)/lipopolysaccharide (LPS) assays), and mobile health platforms. We clarified that this is a hypothesis-driven framework, conceptually informed by existing evidence but not empirically validated. A randomised controlled trial (RCT) design proposal to use permutational multivariate analysis of variance (PERMANOVA) to test microbiome composition and multivariate regression to test the diet-microbiome body mass index (BMI) association. This methodology provides solutions to some of the main translational gaps in precision obesity care by incorporating African-specific microbial data, culturally specific diets, and scalable technology.
Obesity MedicineMedicine-Public Health, Environmental and Occupational Health
CiteScore
5.50
自引率
0.00%
发文量
74
审稿时长
40 days
期刊介绍:
The official journal of the Shanghai Diabetes Institute Obesity is a disease of increasing global prevalence with serious effects on both the individual and society. Obesity Medicine focusses on health and disease, relating to the very broad spectrum of research in and impacting on humans. It is an interdisciplinary journal that addresses mechanisms of disease, epidemiology and co-morbidities. Obesity Medicine encompasses medical, societal, socioeconomic as well as preventive aspects of obesity and is aimed at researchers, practitioners and educators alike.