Mapping Inter-Metabolite Relationships in the Human Brain: A Multi-Site, Multi-Modal MRS Study

Technological advances in magnetic resonance spectroscopy (MRS), particularly at ultra-high field strengths (e.g., 7T), now allow for the reliable quantification of an increasing number of brain metabolites across multiple brain regions. How-ever, most studies remain constrained to analyses of isolated metabolite levels, overlooking the complex interdependencies that govern neurometabolic regula-tion. Here, we present a multivariate framework that applies network analysis and systematic evaluation of pairwise metabolite ratios to a reference dataset of 53 individuals, revealing coordinated patterns of metabolite covariation as well as a hierarchical inter-metabolite architecture. We validate the generaliz-ability and robustness of these findings across four independent MRS datasets, encompassing both longitudinal and cross-sectional samples from 78 humans and 7 rats across five brain regions and three field strengths. Our results show that inter-metabolite relationships are broadly conserved across methodological contexts, while selective axes exhibit graded, network-informed modulation in response to physiological challenges such as caloric restriction or transcranial magnetic stimulation. By moving beyond univariate measures, our multivariate framework accommodates the innate complexity in human brain metabolism and carries translational relevance for biomarker discovery and the development of metabolically targeted therapeutic strategies.