Dopamine Buffering Capacity Imaging: A Pharmacodynamic fMRI Method for Staging Parkinson Disease

Levodopa: From Biological Significance to Continuous Monitoring

A continuous levodopa sensor can improve the quality of life for patients suffering with Parkinson's disease by enhancing levodopa titration and treatment effectiveness; however, its development is currently hindered by the absence of a specific levodopa molecular recognition element and limited insights into how real-time monitoring might affect clinical outcomes. This gap in research contributes to clinician uncertainty regarding the practical value of continuous levodopa monitoring data. This paper examines the current state of levodopa sensing and the inherent limitations in today's methods. Further, these challenges are described, including aspects such as interference from the metabolic pathway and adjunct medications, temporal resolution, and clinical questions, with a specific focus on a comprehensive selection of molecules, such as adjunct medications and structural isomers, as an interferent panel designed to assess and validate future levodopa sensors. We review insights and lessons from previously reported levodopa sensors and present a comparative analysis of potential molecular recognition elements, discussing their advantages and drawbacks.

Refining the clinical diagnosis of Parkinson's disease

Our ability to define, understand, and classify Parkinson's disease (PD) has undergone significant changes since the disorder was first described in 1817. Clinical features and neuropathologic signatures can now be supplemented by in-vivo interrogation of genetic and biological substrates of disease, offering great opportunity for further refining the diagnosis of PD. In this mini-review, we discuss the historical perspectives which shaped our thinking surrounding the definition and diagnosis of PD. We highlight the clinical, genetic, pathologic and biologic diversity which underpins the condition, and proceed to discuss how recent developments in our ability to define biologic and pathologic substrates of disease might impact PD definition, diagnosis, individualised prognostication, and personalised clinical care. We argue that Parkinson's 'disease', as currently diagnosed in the clinic, is actually a syndrome. It is the outward manifestation of any array of potential dysfunctional biologic processes, neuropathological changes, and disease aetiologies, which culminate in common outward clinical features which we term PD; each person has their own unique disease, which we can now define with increasing precision. This is an exciting time in PD research and clinical care. Our ability to refine the clinical diagnosis of PD, incorporating in-vivo assessments of disease biology, neuropathology, and neurogenetics may well herald the era of biologically-based, precision medicine approaches PD management. With this however comes a number of challenges, including how to integrate these technologies into clinical practice in a way which is acceptable to patients, promotes meaningful changes to care, and minimises health economic impact.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Mechanisms of Antiparkinsonian Anticholinergic Therapy Revisited

Before the advent of L-DOPA, the gold standard symptomatic therapy for Parkinson's disease (PD), anticholinergic drugs (muscarinic receptor antagonists) were the preferred antiparkinsonian therapy, but their unwanted side effects associated with impaired extrastriatal cholinergic function limited their clinical utility. Since most patients treated with L-DOPA also develop unwanted side effects such as L-DOPA-induced dyskinesia (LID), better therapies are needed. Recent studies in animal models demonstrate that optogenetic and chemogenetic manipulation of striatal cholinergic interneurons (SCIN), the main source of striatal acetylcholine, modulate parkinsonism and LID, suggesting that restoring SCIN function might serve as a therapeutic option that avoids extrastriatal anticholinergics' side effects. However, it is still unclear how the altered SCIN activity in PD and LID affects the striatal circuit, whereas the mechanisms of action of anticholinergic drugs are still not fully understood. Recent animal model studies showing that SCINs undergo profound changes in their tonic discharge pattern after chronic L-DOPA administration call for a reexamination of classical views of how SCINs contribute to PD symptoms and LID. Here, we review the recent advances on the circuit implications of aberrant striatal cholinergic signaling in PD and LID in an effort to provide a comprehensive framework to understand the effects of anticholinergic drugs and with the aim of shedding light into future perspectives of cholinergic circuit-based therapies.

Imaging of the dopamine system with focus on pharmacological MRI and neuromelanin imaging

The dopamine system in the brain is involved in a variety of neurologic and psychiatric disorders, such as Parkinson's disease, attention-deficit/hyperactivity disorder and psychosis. Different aspects of the dopamine system can be visualized and measured with positron emission tomography (PET) and single photon emission computed tomography (SPECT), including dopamine receptors, dopamine transporters, and dopamine release. New developments in MR imaging also provide proxy measures of the dopamine system in the brain, offering alternatives with the advantages MR imaging, i.e. no radiation, lower costs, usually less invasive and time consuming. This review will give an overview of these developments with a focus on the most developed techniques: pharmacological MRI (phMRI) and neuromelanin sensitive MRI (NM-MRI). PhMRI is a collective term for functional MRI techniques that administer a pharmacological challenge to assess its effects on brain hemodynamics. By doing so, it indirectly assesses brain neurotransmitter function such as dopamine function. NM-MRI is an upcoming MRI technique that enables in vivo visualization and semi-quantification of neuromelanin in the substantia nigra. Neuromelanin is located in the cell bodies of dopaminergic neurons of the nigrostriatal pathway and can be used as a proxy measure for long term dopamine function or degeneration of dopaminergic neurons. Both techniques are still primarily used in clinical research, but there is promise for clinical application, in particular for NM-MRI in dopaminergic neurodegenerative diseases like Parkinson's disease.

An integrative model of Parkinson's disease treatment including levodopa pharmacokinetics, dopamine kinetics, basal ganglia neurotransmission and motor action throughout disease progression

Levodopa is considered the gold standard treatment of Parkinson's disease. Although very effective in alleviating symptoms at their onset, its chronic use with the progressive neuronal denervation in the basal ganglia leads to a decrease in levodopa's effect duration and to the appearance of motor complications. This evolution challenges the establishment of optimal regimens to manage the symptoms as the disease progresses. Based on up-to-date pathophysiological and pharmacological knowledge, we developed an integrative model for Parkinson's disease to evaluate motor function in response to levodopa treatment as the disease progresses. We combined a pharmacokinetic model of levodopa to a model of dopamine's kinetics and a neurocomputational model of basal ganglia. The parameter values were either measured directly or estimated from human and animal data. The concentrations and behaviors predicted by our model were compared to available information and data. Using this model, we were able to predict levodopa plasma concentration, its related dopamine concentration in the brain and the response performance of a motor task for different stages of disease.

Nonlinear pharmacodynamics of levodopa through Parkinson's disease progression

The effect of levodopa in alleviating the symptoms of Parkinson's disease is altered in a highly nonlinear manner as the disease progresses. This can be attributed to different compensation mechanisms taking place in the basal ganglia where the dopaminergic neurons are progressively lost. This alteration in the effect of levodopa complicates the optimization of a drug regimen. The present work aims at investigating the nonlinear dynamics of Parkinson's disease and its therapy through mechanistic mathematical modeling. Using a holistic approach, a pharmacokinetic model of levodopa was combined to a dopamine dynamics and a neurocomputational model of basal ganglia. The influence of neuronal death on these different mechanisms was also integrated. Using this model, we were able to investigate the nonlinear relationships between the levodopa plasma concentration, the dopamine brain concentration, and a response to a motor task. Variations in dopamine concentrations in the brain for different levodopa doses were also studied. Finally, we investigated the narrowing of a levodopa therapeutic index with the progression of the disease as a result of these nonlinearities. In conclusion, various consequences of nonlinear dynamics in Parkinson's disease treatment were studied by developing an integrative model. This model paves the way toward individualization of a dosing regimen. Using sensor based information, the parameters of the model could be fitted to individual data to propose optimal individual regimens.