Neurotransmitter-informed connectivity maps and their application for outcome inference after stroke

Abstract Neuroscience has evolved by framing numerous neuropsychiatric conditions as network diseases. Alterations within neurotransmitter (NT) systems are central to the development of these diseases. Recently, normative data on whole-brain NT fingerprints derived from PET tracer data have become accessible; limited data related this information to sequelae after stroke. This work aimed to explore: (i) the integration of NT data into whole-brain structural connectivity analyses; and (ii) its potential contribution to understanding outcome variability following stroke. Normative maps of NT receptor and transporter densities were integrated with a normative structural connectome to generate NT-specific connectivity maps for serotonin, dopamine, GABA, glutamate and acetylcholine receptors and transporters. Stroke lesion data from two independent, matched cohorts comprising a total of 126 severely impaired acute stroke patients were used to assess NT-related network damage on a patient-specific basis across the distribution of each receptor and transporter. Multivariable logistic regression models were applied to evaluate the relationship between NT-informed network disconnections and functional outcomes 3 to 6 months post-stroke, operationalized by the modified Rankin scale. Analyses were adjusted for lesion-induced global network damage, age, sex, lesion volume and baseline neurological symptom burden. We present an innovative method for incorporating PET tracer data on various NT systems into normative structural connectome datasets. The resulting NT-informed connectivity maps revealed distinct spatial distributions consistent with the established literature. In both cohorts of severely impaired stroke patients, incorporating lesion-induced disruptions within specific NT systems provided more insights into variability in stroke outcomes than the structural disconnection data alone. Notably, greater damage to networks with high dopamine transporter density was associated with poorer functional recovery. Based on NT-informed structural connectivity maps with distinct topographical features for individual receptors and transporters, we show that lesion-induced disruptions in large-scale dopaminergic brain networks, beyond global structural network damage, may play a key role in stroke recovery. These insights hold significant translational potential for advancing personalized medicine in stroke care, such as targeted pharmacologic interventions.