Metabotypes

Metabotype is a term used to describe a classification of individuals according to their metabolic phenotype, as revealed by metabolite patterns in biofluids such as blood or urine. Metabotypes aim to capture stable, biologically meaningful differences in metabolism that arise from interactions among genetics, the gut microbiome, diet, and environment. Unlike genetic genotypes, metabotypes reflect dynamic physiological states and can change with time or context.

Detection typically uses metabolomics approaches—untargeted or targeted analyses of plasma, serum, urine, or other samples—followed by multivariate data analysis to identify clusters of individuals with similar metabolite profiles. Techniques include mass spectrometry and nuclear magnetic resonance spectroscopy, with downstream statistical methods such as clustering, principal component analysis, or machine learning.

Applications include precision nutrition and medicine. Metabotypes can influence drug metabolism and response, informing dose selection and risk of adverse effects. In nutrition, metabotype-guided diets aim to improve glycemic control, weight management, or lipid outcomes. In disease research, certain metabotypes associate with obesity, insulin resistance, type 2 diabetes, or cardiovascular risk.

Challenges include variability over time and across platforms, context dependence of metabolic states, and the need for replication across populations. Interpretations must consider that metabotypes represent probabilistic rather than absolute categorizations, and that environments such as fasting state or recent meals can shift metabolite levels. Standardization of methods and longitudinal studies are ongoing.

Overall, metabotyping is a developing field that supports stratified approaches to health, but it is not yet a universally adopted clinical tool.