Promising biomarkers and therapeutic targets for the management of Parkinson's disease: recent advancements and contemporary research

Revolutionizing our understanding of Parkinson's disease: Dr. Heinz Reichmann's pioneering research and future research direction

Millions of individuals around the world are afflicted with Parkinson's disease (PD), a prevalent and incapacitating neurodegenerative disorder. Dr. Reichmann, a distinguished professor and neurologist, has made substantial advancements in the domain of PD research, encompassing both fundamental scientific investigations and practical applications. His research has illuminated the etiology and treatment of PD, as well as the function of energy metabolism and premotor symptoms. As a precursor to a number of neurotransmitters and neuromodulators that are implicated in the pathophysiology of PD, he has also investigated the application of tryptophan (Trp) derivatives in the disease. His principal findings and insights are summarized and synthesized in this narrative review article, which also emphasizes the challenges and implications for future PD research. This narrative review aims to identify and analyze the key contributions of Reichmann to the field of PD research, with the ultimate goal of informing future research directions in the domain. By examining Reichmann's work, the study seeks to provide a comprehensive understanding of his major contributions and how they can be applied to advance the diagnosis and treatment of PD. This paper also explores the potential intersection of Reichmann's findings with emerging avenues, such as the investigation of Trp and its metabolites, particularly kynurenines, which could lead to new insights and potential therapeutic strategies for managing neurodegenerative disorders like PD.

Unveiling Parkinson's disease through biomarker research: current insights and future prospects

Parkinson's disease (PD) is a neurodegenerative condition marked by the gradual depletion of dopaminergic neurons in the substantia nigra. Despite substantial strides in comprehending potential causative mechanisms, the validation of biomarkers with unequivocal evidence for routine clinical application remains elusive. Consequently, the diagnosis heavily relies on patients' clinical assessments and medical backgrounds. The imperative need for diagnostic and prognostic biomarkers arises due to the prevailing limitations of treatments, which predominantly address symptoms without modifying the disease course. This comprehensive review aims to elucidate the existing landscape of diagnostic and prognostic biomarkers for PD, drawing insights from contemporary literature.

11C-CFT PET brain imaging in Parkinson's disease using a total-body PET/CT scanner

PURPOSE

This study aimed to evaluate the feasibility of 11C-CFT PET brain imaging in Parkinson's Disease using a total-body PET/CT scanner and explore the optimal scan duration to guide the clinical practice.

METHODS

Thirty-two patients with Parkinson's disease (PD) performing 11C-CFT PET/CT brain imaging using a total-body PET/CT scanner were retrospectively enrolled. The PET data acquired over a period of 900 s were reconstructed into groups of different durations: 900-s, 720-s, 600-s, 480-s, 300-s, 180-s, 120-s, 60-s, and 30-s (G900 to G30). The subjective image quality analysis was performed using 5-point scales. Semi-quantitative measurements were analyzed by SUVmean and dopamine transporter (DAT) binding of key brain regions implicated in PD, including the caudate nucleus and putamen. The full-time images (G900) were served as reference.

RESULTS

The overall G900, G720, and G600 image quality scores were 5.0 ± 0.0, 5.0 ± 0.0, and 4.9 ± 0.3 points, respectively, and there was no significant difference among these groups (P > 0.05). A significant decrease in these scores at durations shorter than 600 s was observed when compared to G900 images (P < 0.05). However, all G300 image quality was clinically acceptable (≥ 3 points). As the scan duration reduced, the SUVmean and DAT binding of caudate nucleus and putamen decreased progressively, while there were no statistically significant variations in the SUVmean of the background among the different groups. Moreover, the changes in the lesion DAT binding (ΔDAT-binding) between the full-time reference G900 image and other reconstructed group G720 to G30 images generally increased along with the reduced scan time.

CONCLUSION

Sufficient image quality and lesion conspicuity could be achieved at 600-s scan duration for 11C-CFT PET brain imaging in PD assessment using a total-body PET/CT scanner, while the image quality of G300 was acceptable to meet clinical diagnosis, contributing to improve patient compliance and throughput of PET brain imaging.

Blood-brain barrier biomarkers

The blood-brain barrier (BBB) is a dynamic interface that regulates the exchange of molecules and cells between the brain parenchyma and the peripheral blood. The BBB is mainly composed of endothelial cells, astrocytes and pericytes. The integrity of this structure is essential for maintaining brain and spinal cord homeostasis and protection from injury or disease. However, in various neurological disorders, such as traumatic brain injury, Alzheimer's disease, and multiple sclerosis, the BBB can become compromised thus allowing passage of molecules and cells in and out of the central nervous system parenchyma. These agents, however, can serve as biomarkers of BBB permeability and neuronal damage, and provide valuable information for diagnosis, prognosis and treatment. Herein, we provide an overview of the BBB and changes due to aging, and summarize current knowledge on biomarkers of BBB disruption and neurodegeneration, including permeability, cellular, molecular and imaging biomarkers. We also discuss the challenges and opportunities for developing a biomarker toolkit that can reliably assess the BBB in physiologic and pathophysiologic states.

Retina Oculomics in Neurodegenerative Disease

Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocular imaging biomarkers to provide insights into systemic diseases. Advances in diagnostic and imaging technologies including electroretinography, optical coherence tomography (OCT), confocal scanning laser ophthalmoscopy, fluorescence lifetime imaging ophthalmoscopy, and OCT angiography have revolutionized the ability to understand systemic diseases and even detect them earlier than clinical manifestations for earlier intervention. With the advent of increasingly large ophthalmic imaging datasets, machine learning models can be integrated into these ocular imaging biomarkers to provide further insights and prognostic predictions of neurodegenerative disease. In this manuscript, we review the use of ophthalmic imaging to provide insights into neurodegenerative diseases including Alzheimer Disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, and Huntington Disease. We discuss recent advances in ophthalmic technology including eye-tracking technology and integration of artificial intelligence techniques to further provide insights into these neurodegenerative diseases. Ultimately, oculomics opens the opportunity to detect and monitor systemic diseases at a higher acuity. Thus, earlier detection of systemic diseases may allow for timely intervention for improving the quality of life in patients with neurodegenerative disease.