N-of-1 multi-omics precision nutrition modeling after an energy-restricted anti-inflammatory intervention in a subject with obesity

Abstract

Background/objective

N-of-1 methodologies have emerged as a promising precision nutrition framework, merging clinical and multi-omics data to characterize individual metabolic responses and to follow dynamic biological pathways. This approach offers an opportunity to understand obesity physiopathology and to advance in personalized disease management. The objective was to investigate the physiological response to an energy-restricted anti-inflammatory diet in obesity through the integration of clinical and multi-omics data within an N-of-1 precision nutrition model.

N-of-1 methodologies have emerged as a promising precision nutrition framework, merging clinical and multi-omics data to characterize individual metabolic responses and to follow dynamic biological pathways. This approach offers an opportunity to understand obesity physiopathology and to advance in personalized disease management. The objective was to investigate the physiological response to an energy-restricted anti-inflammatory diet in obesity through the integration of clinical and multi-omics data within an N-of-1 precision nutrition model.

Methods

A 76-year-old man with obesity (BMI 31.9 kg/m²) underwent a 32-week anti-inflammatory intervention involving 30% energy restriction (ethic committee no.PI 164–21). The resulting data were compared with those from a healthy normal-weight subject following a N-1 approach. Conventional anthropometric and biochemical assessments were performed before and after the intervention using validated methods. Multi-omics characterization included gut microbiota by 16S rRNA gene sequencing, targeted serum metabolomics, genotyping, miRNA transcriptomic, and DNA methylation. MEDAS-14 validated questionnaire was used to determine diet adherence.

A 76-year-old man with obesity (BMI 31.9 kg/m²) underwent a 32-week anti-inflammatory intervention involving 30% energy restriction (ethic committee no.PI 164–21). The resulting data were compared with those from a healthy normal-weight subject following a N-1 approach. Conventional anthropometric and biochemical assessments were performed before and after the intervention using validated methods. Multi-omics characterization included gut microbiota by 16S rRNA gene sequencing, targeted serum metabolomics, genotyping, miRNA transcriptomic, and DNA methylation. MEDAS-14 validated questionnaire was used to determine diet adherence.

Results

The intervention resulted in body weight decreased by 4.4%, waist circumference by 4.2%, systolic blood pressure by 15.0%, lipid metabolism variables decreased between 10.1–15.7%, and glucose metabolism markers decreased between 2.8–40%. Adherence to the Mediterranean diet increased by 22.2%, while C-reactive protein decreased by 50%. Genetic profiling revealed high susceptibility to appetite dysregulation (90th percentile), impaired liver function (90th percentile), reduced thermogenesis (79th percentile), and altered fasting insulin regulation (82nd percentile). Gut microbiota analyses revealed an increase in relative abundance of Prevotella_9, Bacteroides and Collinsella. Metabolomic profiling identified greater differences with control in branched chain aminoacids such as isoleucine (+31%) and glutamate (+57%), whereas epigenetic analysis revealed greater differences in DNA methylation involving MC4R (+5.7%) and MACROD2 (−9.5%). Small RNA sequencing revealed differences after intervention in miRNAs annotated as obesity and inflammation-related from −63.5% to +187.2%.

The intervention resulted in body weight decreased by 4.4%, waist circumference by 4.2%, systolic blood pressure by 15.0%, lipid metabolism variables decreased between 10.1–15.7%, and glucose metabolism markers decreased between 2.8–40%. Adherence to the Mediterranean diet increased by 22.2%, while C-reactive protein decreased by 50%. Genetic profiling revealed high susceptibility to appetite dysregulation (90th percentile), impaired liver function (90th percentile), reduced thermogenesis (79th percentile), and altered fasting insulin regulation (82nd percentile). Gut microbiota analyses revealed an increase in relative abundance of Prevotella_9, Bacteroides and Collinsella. Metabolomic profiling identified greater differences with control in branched chain aminoacids such as isoleucine (+31%) and glutamate (+57%), whereas epigenetic analysis revealed greater differences in DNA methylation involving MC4R (+5.7%) and MACROD2 (−9.5%). Small RNA sequencing revealed differences after intervention in miRNAs annotated as obesity and inflammation-related from −63.5% to +187.2%.

Conclusion

The intervention featured favorable clinical, metabolic and inflammatory changes, accompanied by microbiome, metabolomic and epigenetic adaptations. These findings support the use of N-of-1 multi-omics approaches as a valuable framework for understanding individual treatment responses and advancing precision nutrition strategies for obesity. Relevant confirmatory findings were found concerning obesity features and weight loss outcomes, evidencing differential responses concerning anthropometric, biochemical, inflammatory and omics markers.

The intervention featured favorable clinical, metabolic and inflammatory changes, accompanied by microbiome, metabolomic and epigenetic adaptations. These findings support the use of N-of-1 multi-omics approaches as a valuable framework for understanding individual treatment responses and advancing precision nutrition strategies for obesity. Relevant confirmatory findings were found concerning obesity features and weight loss outcomes, evidencing differential responses concerning anthropometric, biochemical, inflammatory and omics markers.