Access to the CNS: Biomarker Strategies for Dopaminergic Treatments

Abstract

Despite substantial research carried out over the last decades, it remains difficult to understand the wide range of pharmacological effects of dopaminergic agents. The dopaminergic system is involved in several neurological disorders, such as Parkinson's disease and schizophrenia. This complex system features multiple pathways implicated in emotion and cognition, psychomotor functions and endocrine control through activation of G protein-coupled dopamine receptors. This review focuses on the system-wide effects of dopaminergic agents on the multiple biochemical and endocrine pathways, in particular the biomarkers (i.e., indicators of a pharmacological process) that reflect these effects. Dopaminergic treatments developed over the last decades were found to be associated with numerous biochemical pathways in the brain, including the norepinephrine and the kynurenine pathway. Additionally, they have shown to affect peripheral systems, for example the hypothalamus-pituitary-adrenal (HPA) axis. Dopaminergic agents thus have a complex and broad pharmacological profile, rendering drug development challenging. Considering the complex system-wide pharmacological profile of dopaminergic agents, this review underlines the needs for systems pharmacology studies that include: i) proteomics and metabolomics analysis; ii) longitudinal data evaluation and mathematical modeling; iii) pharmacokinetics-based interpretation of drug effects; iv) simultaneous biomarker evaluation in the brain, the cerebrospinal fluid (CSF) and plasma; and v) specific attention to condition-dependent (e.g., disease) pharmacology. Such approach is considered essential to increase our understanding of central nervous system (CNS) drug effects and substantially improve CNS drug development.

Keywords: CNS drug development; biomarkers; dopaminergic agents; systems pharmacology.

Fig. 1. Overview of the dopaminergic system.

A Representation of the dopamine pathway architecture in the brain. B Illustration of the dopamine production and degradation, as well as the synaptic signaling.

Fig. 2. Effects of dopamine drugs on 12 biochemical or endocrine pathways. Potential biomarkers are mentioned for each pathway. The reader is referred to the text for detailed discussion of the interaction between dopamine drugs and each pathway.

5-HIAA: 5-hydroxyindoleacetic acid; ACTH: adenocorticotropic hormone; Alpha-MSH: alpha melanocyte stimulating hormone; B-end: beta-endorphin; COMT: catechol-O-methyl transferase; CSF: cerebrospinal fluid; D1R: dopamine 1-like receptor; D2R: dopamine 2-like receptor; DA: dopamine; DHPG: dihydroxyphenylglycol; DOPAC: 3,4-dihydroxyphenylacetic acid; DRN: dorse raphe nucleus; FSH: follicle stimulating hormone; GABA: gamma-aminobutyric acid; HVA: homovanillic acid; L-DOPA: levodopa; LH: luteinizing hormone; MAO: monoamine oxidase; MHPG: 3-methoxy-4-hydroxyphenylglycol; N. Accumbens: nucleus accumbens; NE: norepinephrine; NO: nitric oxide; NOS: nitric oxide synthase; prolactin: prolactin; VMA: vanillylmandelic acid; VTA: ventral tegmental area.

Fig. 3. Conceptual considerations for the use of accessible biomarkers in CSF, plasma or urine to reflect dopamine drug effects in the brain.

The grey solid lines represent the distribution of biochemical pathway components to CSF, plasma and urine. Since only part of the pathway components may distribute to these biofluids, some of the nodes are filled blank. The grey dashed line represents the peripheral nervous system (PNS) that may influence the peripheral release of biochemical markers through electrical signaling. The grey dotted lines represent the neuroendocrine system (NES), which is electrically controlled at the level of the hypothalamus and the pituitary, causing the release of hormones into plasma. Feedback mechanisms of these hormones on their own release may complicate the interpretation of their responses in plasma. The black dashed lines represent the levels at which dopamine drugs may interact with these systems.

Fig. 4. Mathematical model containing expressions for the interactions between the different neurotransmitter systems in multiple brain regions.

Rather than looking at single biomarkers, this model enables the prediction of disbalances among the neurotransmitter systems under conditions of drug administration. Adapted from reference (132) with permission.