Constructing the Human Brain Metabolic Connectome Using MR Spectroscopic Imaging: Insights into Biochemical Organization, Cytoarchitectonic Similarity and Gene Co-expression Networks

Abstract

Network science has revolutionized our understanding of brain organization by revealing self-organizing patterns underlying its structural and functional connectivity. However, capturing metabolic contrast remains a challenge, leaving a critical gap in connectomics. Using advanced 3D whole-brain proton MR spectroscopic imaging with high spatial resolution and shortened acquisition times, we constructed the first human brain metabolic connectome in 51 healthy subjects, validated on an independent cohort (N=12) scanned at a different site. Our pipeline generates consistent and reliable metabolic similarity matrices. Upon further analysis, metabolic similarity networks display distinct topological features, notably a smoothly varying gradient delineating functionally and spatially distinct yet integrated brain regions via connector hubs. Although metabolic hubs correlate with structural hubs, overall alignment with structural connectivity is poor. However, metabolic organization aligns more closely with cytoarchitectonic and genetic co-expression patterns, suggesting a neurodevelopmental origin. This work puts forward the metabolic similarity gradient as a hallmark of the brains overarching biochemical organization, and provides a foundation for incorporating metabolite imaging into the broader domain of connectomics and its potential applications in health and disease.