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Arya R, Haque AKMA, Shakya H, Billah MM, Parvin A, Rahman MM, Sakib KM, Faruquee HM, Kumar V, Kim JJ. Parkinson's Disease: Biomarkers for Diagnosis and Disease Progression. Int J Mol Sci 2024; 25:12379. [PMID: 39596444 PMCID: PMC11594627 DOI: 10.3390/ijms252212379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Revised: 11/11/2024] [Accepted: 11/14/2024] [Indexed: 11/28/2024] Open
Abstract
Parkinson's disease (PD) is a progressive neurological disease that causes both motor and nonmotor symptoms. While our understanding of putative mechanisms has advanced significantly, it remains challenging to verify biomarkers with sufficient evidence for regular clinical use. Clinical symptoms are the primary basis for diagnosing the disease, which can be mild in the early stages and overlap with other neurological disorders. As a result, clinical testing and medical records are mostly relied upon for diagnosis, posing substantial challenges during both the initial diagnosis and the continuous disease monitoring. Recent biochemical, neuroimaging, and genetic biomarkers have helped us understand the pathophysiology of Parkinson's disease. This comprehensive study focuses on these biomarkers, which were chosen based on their relevance, methodological excellence, and contribution to the field. Biochemical biomarkers, including α-synuclein and glial fibrillary acidic protein (GFAP), can predict disease severity and progression. The dopaminergic system is widely used as a neuroimaging biomarker to diagnose PD. Numerous genes and genome wide association study (GWAS) sites have been related to the development of PD. Recent research on the SNCA gene and leucine-rich repeat protein kinase 2 (LRRK2) has shown promising results. By evaluating current studies, this review intends to uncover gaps in biomarker validation and use, while also highlighting promising improvements. It emphasizes the need for dependable and reproducible indicators in improving PD diagnosis and prognosis. These biomarkers may open up new avenues for early diagnosis, disease progression tracking, and the development of personalized treatment programs.
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Affiliation(s)
- Rakesh Arya
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea;
| | - A. K. M. Ariful Haque
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia 7003, Bangladesh; (A.K.M.A.H.); (M.M.B.); (A.P.); (M.-M.R.); (H.M.F.)
| | - Hemlata Shakya
- Department of Biomedical Engineering, Shri G. S. Institute of Technology and Science, Indore 452003, India;
| | - Md. Masum Billah
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia 7003, Bangladesh; (A.K.M.A.H.); (M.M.B.); (A.P.); (M.-M.R.); (H.M.F.)
| | - Anzana Parvin
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia 7003, Bangladesh; (A.K.M.A.H.); (M.M.B.); (A.P.); (M.-M.R.); (H.M.F.)
| | - Md-Mafizur Rahman
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia 7003, Bangladesh; (A.K.M.A.H.); (M.M.B.); (A.P.); (M.-M.R.); (H.M.F.)
| | - Khan Mohammad Sakib
- Department of Biology, Adamjee Cantonment College, Dhaka Cantonment, Dhaka 1206, Bangladesh;
| | - Hossain Md. Faruquee
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia 7003, Bangladesh; (A.K.M.A.H.); (M.M.B.); (A.P.); (M.-M.R.); (H.M.F.)
| | - Vijay Kumar
- Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Jong-Joo Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea;
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Železníková Ž, Nováková L, Vojtíšek L, Brabenec L, Mitterová K, Morávková I, Rektorová I. Early Changes in the Locus Coeruleus in Mild Cognitive Impairment with Lewy Bodies. Mov Disord 2024. [PMID: 39535454 DOI: 10.1002/mds.30058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 09/12/2024] [Accepted: 10/28/2024] [Indexed: 11/16/2024] Open
Abstract
BACKGROUND Although neuromelanin-sensitive magnetic resonance imaging (NM-MRI) has been used to evaluate early neurodegeneration in Parkinson's disease, studies concentrating on the locus coeruleus (LC) in pre-dementia stages of dementia with Lewy bodies (DLB) are lacking. OBJECTIVES The aims were to evaluate NM-MRI signal changes in the LC in patients with mild cognitive impairment with Lewy bodies (MCI-LB) compared to healthy controls (HC) and to identify the cognitive correlates of the changes. We also aimed to test the hypothesis of a caudal-rostral α-synuclein pathology spread using NM-MRI of the different LC subparts. METHODS A total of 38 MCI-LB patients and 59 HCs underwent clinical and cognitive testing and NM-MRI of the LC. We calculated the contrast ratio of NM-MRI signal (LC-CR) in the whole LC as well as in its caudal, middle, and rostral MRI slices, and we compared the LC-CR values between the MCI-LB and HC groups. Linear regression analyses were performed to assess the relationship between the LC-CR and cognitive outcomes. RESULTS The MCI-LB group exhibited a significant reduction in the right LC-CR compared to HCs (P = 0.021). The right LC-CR decrease was associated with impaired visuospatial memory in the MCI-LB group. Only the caudal part of the LC exhibited significant LC-CR decreases in MCI-LB patients compared to HCs on both sides (P < 0.0001). CONCLUSIONS This is the first study that focuses on LC-CRs in MCI-LB patients and analyzes the LC subparts, offering new insights into the LC integrity alterations in the initial stages of DLB and their clinical correlates. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Žaneta Železníková
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC, Masaryk University, Brno, Czech Republic
| | - L'ubomíra Nováková
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC, Masaryk University, Brno, Czech Republic
- International Clinical Research Center, ICRC, Faculty of Medicine and St. Anne's University Hospital, Masaryk University, Brno, Czech Republic
| | - Lubomír Vojtíšek
- Multimodal and Functional Neuroimaging Research Group, Central European Institute of Technology, CEITEC, Masaryk University, Brno, Czech Republic
| | - Luboš Brabenec
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC, Masaryk University, Brno, Czech Republic
- International Clinical Research Center, ICRC, Faculty of Medicine and St. Anne's University Hospital, Masaryk University, Brno, Czech Republic
| | - Kristína Mitterová
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC, Masaryk University, Brno, Czech Republic
- International Clinical Research Center, ICRC, Faculty of Medicine and St. Anne's University Hospital, Masaryk University, Brno, Czech Republic
| | - Ivona Morávková
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC, Masaryk University, Brno, Czech Republic
- First Department of Neurology, Faculty of Medicine and St. Anne's University Hospital, Masaryk University, Brno, Czech Republic
| | - Irena Rektorová
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC, Masaryk University, Brno, Czech Republic
- International Clinical Research Center, ICRC, Faculty of Medicine and St. Anne's University Hospital, Masaryk University, Brno, Czech Republic
- First Department of Neurology, Faculty of Medicine and St. Anne's University Hospital, Masaryk University, Brno, Czech Republic
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Wengler K, Trujillo P, Cassidy CM, Horga G. Neuromelanin-sensitive MRI for mechanistic research and biomarker development in psychiatry. Neuropsychopharmacology 2024; 50:137-152. [PMID: 39160355 PMCID: PMC11526017 DOI: 10.1038/s41386-024-01934-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/21/2024] [Accepted: 07/15/2024] [Indexed: 08/21/2024]
Abstract
Neuromelanin-sensitive MRI is a burgeoning non-invasive neuroimaging method with an increasing number of applications in psychiatric research. This MRI modality is sensitive to the concentration of neuromelanin, which is synthesized from intracellular catecholamines and accumulates in catecholaminergic nuclei including the dopaminergic substantia nigra and the noradrenergic locus coeruleus. Emerging data suggest the utility of neuromelanin-sensitive MRI as a proxy measure for variability in catecholamine metabolism and function, even in the absence of catecholaminergic cell loss. Given the importance of catecholamine function to several psychiatric disorders and their treatments, neuromelanin-sensitive MRI is ideally positioned as an informative and easy-to-acquire catecholaminergic index. In this review paper, we examine basic aspects of neuromelanin and neuromelanin-sensitive MRI and focus on its psychiatric applications in the contexts of mechanistic research and biomarker development. We discuss ongoing debates and state-of-the-art research into the mechanisms of the neuromelanin-sensitive MRI contrast, standardized protocols and optimized analytic approaches, and application of cutting-edge methods such as machine learning and artificial intelligence to enhance the feasibility and predictive power of neuromelanin-sensitive-MRI-based tools. We finally lay out important future directions to allow neuromelanin-sensitive-MRI to fulfill its potential as a key component of the research, and ultimately clinical, toolbox in psychiatry.
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Affiliation(s)
- Kenneth Wengler
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paula Trujillo
- Department of Neurology, Vanderbilt University Medical Center, Vanderbilt, TN, USA
| | - Clifford M Cassidy
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Guillermo Horga
- New York State Psychiatric Institute, New York, NY, USA.
- Department of Psychiatry, Columbia University, New York, NY, USA.
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Ellis EG, Meyer GM, Kaasinen V, Corp DT, Pavese N, Reich MM, Joutsa J. Multimodal neuroimaging to characterize symptom-specific networks in movement disorders. NPJ Parkinsons Dis 2024; 10:154. [PMID: 39143114 PMCID: PMC11324766 DOI: 10.1038/s41531-024-00774-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 08/05/2024] [Indexed: 08/16/2024] Open
Abstract
Movement disorders, such as Parkinson's disease, essential tremor, and dystonia, are characterized by their predominant motor symptoms, yet diseases causing abnormal movement also encompass several other symptoms, including non-motor symptoms. Here we review recent advances from studies of brain lesions, neuroimaging, and neuromodulation that provide converging evidence on symptom-specific brain networks in movement disorders. Although movement disorders have traditionally been conceptualized as disorders of the basal ganglia, cumulative data from brain lesions causing parkinsonism, tremor and dystonia have now demonstrated that this view is incomplete. Several recent studies have shown that lesions causing a given movement disorder occur in heterogeneous brain locations, but disrupt common brain networks, which appear to be specific to each motor phenotype. In addition, findings from structural and functional neuroimaging in movement disorders have demonstrated that brain abnormalities extend far beyond the brain networks associated with the motor symptoms. In fact, neuroimaging findings in each movement disorder are strongly influenced by the constellation of patients' symptoms that also seem to map to specific networks rather than individual anatomical structures or single neurotransmitters. Finally, observations from deep brain stimulation have demonstrated that clinical changes, including both symptom improvement and side effects, are dependent on the modulation of large-scale networks instead of purely local effects of the neuromodulation. Combined, this multimodal evidence suggests that symptoms in movement disorders arise from distinct brain networks, encouraging multimodal imaging studies to better characterize the underlying symptom-specific mechanisms and individually tailor treatment approaches.
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Affiliation(s)
- Elizabeth G Ellis
- Turku Brain and Mind Center, University of Turku, Turku, Finland.
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia.
| | - Garance M Meyer
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Valtteri Kaasinen
- Clinical Neurosciences, University of Turku, Turku, Finland
- Neurocenter, Turku University Hospital, Turku, Finland
| | - Daniel T Corp
- Turku Brain and Mind Center, University of Turku, Turku, Finland
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Nicola Pavese
- Institute of Clinical Medicine, Department of Nuclear Medicine & PET, Aarhus University, Aarhus, Denmark
- Translational and Clinical Research Institute, Newcastle University, Upon Tyn, UK
| | - Martin M Reich
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080, Würzburg, Germany
| | - Juho Joutsa
- Turku Brain and Mind Center, University of Turku, Turku, Finland.
- Clinical Neurosciences, University of Turku, Turku, Finland.
- Neurocenter, Turku University Hospital, Turku, Finland.
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Kemp AF, Kinnerup M, Johnsen B, Jakobsen S, Nahimi A, Gjedde A. EEG Frequency Correlates with α 2-Receptor Density in Parkinson's Disease. Biomolecules 2024; 14:209. [PMID: 38397446 PMCID: PMC10886955 DOI: 10.3390/biom14020209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
INTRODUCTION Increased theta and delta power and decreased alpha and beta power, measured with quantitative electroencephalography (EEG), have been demonstrated to have utility for predicting the development of dementia in patients with Parkinson's disease (PD). Noradrenaline modulates cortical activity and optimizes cognitive processes. We claim that the loss of noradrenaline may explain cognitive impairment and the pathological slowing of EEG waves. Here, we test the relationship between the number of noradrenergic α2 adrenoceptors and changes in the spectral EEG ratio in patients with PD. METHODS We included nineteen patients with PD and thirteen healthy control (HC) subjects in the study. We used positron emission tomography (PET) with [11C]yohimbine to quantify α2 adrenoceptor density. We used EEG power in the delta (δ, 1.5-3.9 Hz), theta (θ, 4-7.9 Hz), alpha (α, 8-12.9 Hz) and beta (β, 13-30 Hz) bands in regression analyses to test the relationships between α2 adrenoceptor density and EEG band power. RESULTS PD patients had higher power in the theta and delta bands compared to the HC volunteers. Patients' theta band power was inversely correlated with α2 adrenoceptor density in the frontal cortex. In the HC subjects, age was correlated with, and occipital background rhythm frequency (BRF) was inversely correlated with, α2 adrenoceptor density in the frontal cortex, while occipital BRF was inversely correlated with α2 adrenoceptor density in the thalamus. CONCLUSIONS The findings support the claim that the loss or dysfunction of noradrenergic neurotransmission may relate to the parallel processes of cognitive decline and EEG slowing.
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Affiliation(s)
- Adam F. Kemp
- Department of Nuclear Medicine, Odense University Hospital, 5000 Odense, Denmark;
| | - Martin Kinnerup
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
| | - Birger Johnsen
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
- Department of Clinical Neurophysiology, Aarhus University Hospital, 8200 Aarhus, Denmark
| | - Steen Jakobsen
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
| | - Adjmal Nahimi
- Clinical Memory Research Unit, Department of Clinical Sciences, 211 46 Malmö, Sweden;
- Department of Neurology, Skåne University Hospital, 221 85 Lund, Sweden
| | - Albert Gjedde
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
- Department of Neuroscience, University of Copenhagen, 1172 Copenhagen, Denmark
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 0G4, Canada
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
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Theis H, Pavese N, Rektorová I, van Eimeren T. Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2024; 14:S353-S365. [PMID: 38339941 PMCID: PMC11492013 DOI: 10.3233/jpd-230385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/07/2024] [Indexed: 02/12/2024]
Abstract
Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.
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Affiliation(s)
- Hendrik Theis
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
| | - Nicola Pavese
- Aarhus University, Institute of Clinical Medicine, Department of Nuclear Medicine & PET, Aarhus N, Denmark
- Newcastle University, Translational and Clinical Research Institute, Newcastle upon Tyne, United Kingdom
| | - Irena Rektorová
- Masaryk University, Faculty of Medicine and St. Anne’s University Hospital, International Clinical Research Center, ICRC, Brno, Czech Republic
- Masaryk University, Faculty of Medicine and St. Anne’s University Hospital, First Department of Neurology, Brno, Czech Republic
- Masaryk University, Applied Neuroscience Research Group, Central European Institute of Technology – CEITEC, Brno, Czech Republic
| | - Thilo van Eimeren
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
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