Here, we explored the vast potential of microbiome-based interventions in preventing and managing non-communicable diseases including obesity, diabetes, allergies, celiac disease, inflammatory bowel diseases, malnutrition, and cardiovascular diseases across different life stages. We discuss the intricate relationship between microbiome and non-communicable diseases, emphasizing on the "window of opportunity" for microbe-host interactions during the first years after birth. Specific biotics and also live biotherapeutics including fecal microbiota transplantation emerge as pivotal tools for precision medicine, acknowledging the "one size doesn't' fit all" aspect. Challenges in implementation underscore the need for advanced technologies, scientific transparency, and public engagement. Future perspectives advocate for understanding maternal-neonatal microbiome, exploring the maternal exposome and delving into human milk's role in the establishment and restoration of the infant microbiome and its influence over health and disease. An integrated scientific approach, employing multi-omics and accounting for inter-individual variance in microbiome composition and function appears central to unleash the full potential of early-life microbiome interventions in revolutionizing healthcare.

Diabetes and obesity are chronic diseases that are a burden to low- and middle-income countries. We conducted this systematic review to understand gene–diet interactions affecting the Southeast Asian population’s risk of obesity and diabetes. The literature search was performed on Google Scholar and MEDLINE (PubMed) search engines independently by four reviewers who evaluated the eligibility of articles based on inclusion criteria. Out of 19,031 articles, 20 articles examining gene–diet interactions on obesity and/or diabetes-related traits met the inclusion criteria. Three (Malaysia, Indonesia, and Singapore) out of eleven Association of Southeast Asian Nations (ASEAN) countries have conducted studies on gene–diet interactions on obesity and diabetes. From the 20 selected articles, the most common interactions were observed between macronutrients and genetic risk score (GRS) on metabolic disease-related traits in the Malay, Chinese, and Indian ethnicities. Overall, we identified 29 significant gene–diet interactions in the Southeast Asian population. The results of this systematic review demonstrate ethnic-specific gene–nutrient interactions on metabolic-disease-related traits in the Southeast Asian population. This is the first systematic review to explore gene–diet interactions on obesity and diabetes in the Southeast Asian population and further research using larger sample sizes is required for better understanding and framing nutrigenetic approaches for personalized nutrition.

Nutritional epidemiological studies show a triple burden of malnutrition with disparate prevalence across the coexisting ethnicities in Malaysia. To tackle malnutrition and related conditions in Malaysia, research in the new and evolving field of nutrigenetics and nutrigenomics is essential. As part of the Gene-Nutrient Interactions (GeNuIne) Collaboration, the Nutrigenetics and Nutrigenomics Research and Training Unit (N²RTU) aims to solve the malnutrition paradox. This review discusses and presents a conceptual framework that shows the pathway to implementing and strengthening precision nutrition strategies in Malaysia. The framework is divided into: (1) Research and (2) Training and Resource Development. The first arm collects data from genetics, genomics, transcriptomics, metabolomics, gut microbiome, and phenotypic and lifestyle factors to conduct nutrigenetic, nutrigenomic, and nutri-epigenetic studies. The second arm is focused on training and resource development to improve the capacity of the stakeholders (academia, healthcare professionals, policymakers, and the food industry) to utilise the findings generated by research in their respective fields. Finally, the N²RTU framework foresees its applications in artificial intelligence and the implementation of precision nutrition through the action of stakeholders.

There is conflicting evidence about the association between dairy products and cardiometabolic risk (CMR). We aimed to assess the association of total dairy intake with CMR factors and to investigate the association of unfermented and fermented dairy intake with CMR in Asian Indians who are known to have greater susceptibility to type 2 diabetes and cardiovascular diseases compared to white Europeans. The study comprised 1033 Asian Indian adults with normal glucose tolerance chosen from the Chennai Urban Rural Epidemiological Study (CURES). Dietary intake was assessed using a validated open-ended semi-quantitative food frequency questionnaire. Metabolic syndrome (MS) was diagnosed based on the new harmonising criteria using central obesity, dyslipidaemia [low high-density lipoprotein cholesterol (HDL) and increased serum triglycerides (TG)], hypertension and glucose intolerance. Increased consumption of dairy (≥5 cups per day of total, ≥4 cups per day of unfermented or ≥2 cups per day of fermented dairy) was associated with a lower risk of high fasting plasma glucose (FPG) [hazards ratio (HR), 95% confidence interval (CI): 0.68, 0.48–0.96 for total dairy; 0.57, 0.34–0.94 for unfermented dairy; and 0.64, 0.46–0.90 for fermented dairy; p < 0.05 for all] compared to a low dairy intake (≤1.4 cups per day of total dairy; ≤1 cup per day of unfermented dairy; and ≤0.1 cup per day of fermented dairy). A total dairy intake of ≥5 cups per day was also protective against high blood pressure (BP) (HR: 0.65, 95% CI: 0.43–0.99, p < 0.05), low HDL (HR: 0.63, 95% CI: 0.43–0.92, p < 0.05) and MS (HR: 0.71, 95% CI: 0.51–0.98, p < 0.05) compared to an intake of ≤1.4 cups per day. A high unfermented dairy intake (≥4 cups per day) was also associated with a lower risk of high body mass index (BMI) (HR: 0.52, 95% CI: 0.31–0.88, p < 0.05) compared to a low intake (≤1 cup per day), while a reduced risk of MS was observed with a fermented dairy intake of ≥2 cups per day (HR: 0.71, 95% CI: 0.51–0.98, p < 0.05) compared to an intake of ≤0.1 cup per day. In summary, increased consumption of dairy was associated with a lower risk of MS and components of CMR.

Pregnancy complications like gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy, and obesity are rising. Emerging evidence suggests dietary strategies targeting maternal microbiota, such as increased fiber or polyphenols, may help manage these conditions. This study aimed to 1) synthesize existing evidence on the relationship between maternal diet and the gut microbiota, with a focus on its potential link to gestational outcomes, and 2) provide insights based on the available literature to inform future pregnancy guidelines. This systematic review included observational and interventional studies on pregnant females assessing maternal diet and gut microbiota. Searches were conducted in PubMed and Web of Science up to July 2025. Risk of bias was assessed using appraisal tool for cross-sectional studies, Risk Of Bias In Nonrandomized Studies - of Interventions, and Risk Of Bias 2 tools. Narrative synthesis and a correlational meta-analysis stratified findings by trimester and obstetric condition. Across 29 studies involving 3077 pregnant females, high-fiber and vegetarian diets were consistently associated with increased abundance of taxa such as Roseburia spp. and Bifidobacterium spp., alongside more favorable metabolic markers. In contrast, high-fat and Westernized diets were frequently linked to reduced microbial diversity and increased proinflammatory taxa including Collinsella and members of the Lachnospiraceae family. In GDM pregnancies, interventions like medical nutrition therapy were associated with favorable microbial profiles, whereas proinflammatory diets were associated with reduced diversity. Meta-analyses indicated that maternal health status significantly moderated associations between fat intake and Gram-negative bacteria [Likelihood Ratio Test (LRT) = 53.929, P = 0.020], and between protein intake and Gram-positive bacteria (LRT = 68.735, P = 0.009), suggesting differential microbial responses by metabolic risk profile. This systematic review found that specific dietary components, particularly fiber, omega-3 fatty acids, and micronutrients, were associated with differences in maternal gut microbiota, with potential relevance to metabolic outcomes such as GDM, obesity, and hypertensive disorders of pregnancy. Meta-analysis results indicate that maternal health status significantly moderated the associations between dietary fat and protein intake and microbial taxa, suggesting that precision nutrition interventions warrant evaluation in metabolically at-risk populations. This study was registered at PROSPERO as CRD420251085137.

The increased prevalence of metabolic diseases in the Arab countries is mainly associated with genetic susceptibility, lifestyle behaviours, such as physical inactivity, and an unhealthy diet. The objective of this review was to investigate and summarise the findings of the gene–lifestyle interaction studies on metabolic diseases such as obesity and type 2 diabetes in Arab populations. Relevant articles were retrieved from a literature search on PubMed, Web of Science, and Google Scholar starting at the earliest indexing date through to January 2024. Articles that reported an interaction between gene variants and diet or physical activity were included and excluded if no interaction was investigated or if they were conducted among a non-Arab population. In total, five articles were included in this review. To date, among three out of twenty-two Arab populations, fourteen interactions have been found between the FTO rs9939609, TCF7L2 rs7903146, MC4R rs17782313, and MTHFR rs1801133 polymorphisms and diet or physical activity on obesity and type 2 diabetes outcomes. The majority of the reported gene–diet/ gene–physical activity interactions (twelve) appeared only once in the review. Consequently, replication, comparisons, and generalisation of the findings are limited due to the sample size, study designs, dietary assessment tools, statistical analysis, and genetic heterogeneity of the studied sample.