When can site-specific glycoform compositions resolve biosynthetic rates?

Mass spectrometry measures site-specific glycoform compositions, but when these measurements can resolve upstream biosynthetic rates remains unclear. We assess whether small changes in effective rates, each representing the processing capacity of a group of biosynthetic reactions, can be distinguished near specified baseline rates with secretion held fixed. Because proportions sum to one, m jointly normalised glycoform classes provide at most m-1 independent quantities. Distinguishing changes in k rates therefore requires at least k+1 classes, although this count alone does not ensure identifiability. In a canonical N-glycan network with eight rates, exhaustive evaluation of nine-class panels identified panels that could locally distinguish all eight rates. Among these panels, class choice changed the allowable measurement error by approximately 18-fold for the same target uncertainty in inferred rates. A separate simulation within the fixed network showed that estimating rate-change combinations with weaker composition responses reduced bias but amplified measurement noise. We applied the framework to plasma data from 40 controls and 70 patients across 14 inherited glycosylation-disorder groups. A prespecified composition score for the expected pathway disturbance ranked among the top two in 13 of 14 groups. Network responses linked observed composition shifts to biosynthetic reaction classes. Expanding site models from five to eight reaction classes improved control-composition fit but reduced the number of sites at which all modelled rates were locally distinguishable and increased noise sensitivity. Rate inference thus requires sufficient panel size, separable rate responses, adequate measurement precision and a model that fits the composition. These requirements guide measurement design and help determine whether compositions support pathway-level interpretation or individual-rate inference.