Precision Medicine in Type 2 Diabetes Subtyping

Type 2 diabetes is increasingly recognised as a spectrum of disorders rather than a single entity, with variation in insulin secretion, insulin sensitivity, adiposity and genetic predisposition driving heterogeneous clinical trajectories. Precision medicine in this context seeks to move beyond conventional glycaemic thresholds to identify mechanistically distinct subgroups that predict prognosis, complications and therapeutic response. Data-driven approaches, notably cluster analysis of clinical and biochemical variables, have delineated subtypes such as severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes and mild age-related diabetes, alongside an autoimmune form. Parallel efforts employ polygenic risk scores, proteomic and metabolomic signatures, and gut microbiome profiles to refine these subgroups. By integrating multi-omic data with routinely collected clinical measures—age at onset, body mass index, HbA₁c, C-peptide and lipid parameters—researchers have developed predictive models for personalised selection of glucose-lowering therapies. These stratification frameworks promise improved management by aligning treatment intensity with individual risk of microvascular and macrovascular complications, thus enhancing both efficacy and safety across diverse populations.

Research from Nature Portfolio

A randomised, placebo-controlled trial evaluated the effect of broccoli sprout extract, a source of sulforaphane, in individuals with prediabetes. Although the overall reduction in fasting glucose was modest, exploratory subgroup analyses revealed that participants with lower insulin resistance, preserved insulin secretion and specific gut microbiota compositions experienced a pronounced glycaemic benefit. Metagenomic profiling identified a bacterial operon enabling conversion of precursor compounds into active sulforaphane, correlating with serum levels of the bioactive compound. This study exemplifies a precision medicine paradigm in which host metabolic phenotype and microbial gene content jointly define responders to a dietary intervention, underscoring the potential of combined host–microbe subtyping for tailored prevention strategies.

Precision Medicine in Type 2 Diabetes Subtyping publication trend

The graph below shows the total number of articles in precision medicine in type 2 diabetes subtyping across all publications each year (not limited to Nature Index journals).

Technical terms

Cluster analysis: A statistical method that groups individuals by similarity across multiple variables, used to identify subtypes of diabetes.

C-peptide: A biomarker of endogenous insulin secretion, measured to distinguish insulin deficiency from resistance.

HbA₁c: Glycated haemoglobin, reflecting average blood glucose over the preceding two to three months.

Homeostasis model assessment (HOMA): An index estimating insulin resistance (HOMA-IR) and beta-cell function (HOMA-B) from fasting glucose and insulin concentrations.

Polygenic risk score: A composite measure of genetic susceptibility derived from multiple risk alleles to predict disease traits or subtypes.

Metagenomics: The study of collective microbial genomes in a sample, used here to profile gut bacteria associated with treatment response.

References

1. Effect of broccoli sprout extract and baseline gut microbiota on fasting blood glucose in prediabetes: a randomized, placebo-controlled trial. Nature Microbiology (2025).
2. Disease progression and treatment response in data-driven subgroups of type 2 diabetes compared with models based on simple clinical features: an analysis using clinical trial data. The Lancet Diabetes & Endocrinology (2019).
3. Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study. Diabetologia (2021).
4. Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study. BMJ Open Diabetes Research & Care (2020).