Normative modelling of cortical networks identifies subtypes of type 2 diabetes associated with distinct clinical and transcriptomic profiles

Abstract

Type 2 diabetes (T2D) is characterized by substantial clinical heterogeneity, yet its neurobiological substrates remain unclear. Here, we leverage normative modelling of cortical morphometric networks to quantify individual-level brain deviations using structural MRI data from 3,723 participants (1,941 T2D patients and 1,782 healthy controls) across three independent cohorts. Data-driven clustering reveals two robust T2D biotypes characterized by widespread positive (biotype 1) and negative (biotype 2) brain deviations. Despite comparable overall metabolic burdens, these biotypes feature distinct brain–metabolic coupling patterns: biotype 1 is primarily associated with lipid metabolism, whereas biotype 2 reflects a multifactorial metabolic burden spanning glycaemic control, adiposity, lipid, vascular risks, and disease duration. These divergent brain vulnerability profiles have distinct cognitive consequences; notably, biotype 2 shows poorer performance in complex cognitive tasks, aligning with negatively deviated connectivity gradients along the sensorimotor-to-association axis. Spatial transcriptomic analyses further link biotype 2 deviations to gene expression patterns enriched in insulin signalling, mitochondrial functions, tight junctions, and neurodegenerative disease pathways, alongside specific involvement of inhibitory neurons and oligodendrocyte lineage cells. Our findings provide a neurobiological understanding of T2D heterogeneity and establish a data-driven framework for characterizing personalized brain vulnerability, with implications for advancing precision diabetes medicine.