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Breaking Down Parkinson’s Disease: Causes, Symptoms and Latest Treatment Options



Breaking Down Parkinson’s Disease: Causes, Symptoms and Latest Treatment Options

Authors:

Degiri Kalana Senevirathne
Pre-Medical Students, Class of 2027
Weill Cornell Medicine-Qatar

Anns Mahboob
Pre-Medical Students, Class of 2027
Weill Cornell Medicine-Qatar

Ali Chaari, PhD
Assistant Professor of Biology
Weill Cornell Medicine-Qatar

 

Parkinson’s Disease (PD) is the most common movement disorder and the second most common degenerative disease of the central nervous system, globally [1]. A recent study reported that incident cases of PD in 2008 was 27-43 per 100,000 individuals in the Middle Eastern area [2].

PD was first described in 1817 by James Parkinson in his “Essay on the Shaking Palsy”, and the major motor signs identified then still remain the hallmarks of PD: bradykinesia, rigidity, and tremor [3]. Additionally, other common motor symptoms like stiffness, speech difficulty and poor balance and coordination are prevalent whilst common non-motor symptoms include fatigue, low blood pressure, bladder and bowel problems, anxiety, and dementia [1,4].

The cause of PD in many cases is still unclear with recent evidence identifying genetic predisposition to the disease [1]. However, there are many risk factors, which have shown to increase the risk for PD [5]. The greatest risk of PD arises from age with the majority of cases happening between ages 50 to 60. Moreover, other risk factors include family history (a genetic link) and environmental causes like exposure to environmental hazards including farming chemicals, like pesticides and herbicides, and working with heavy metals, detergents, and solvents [5].

Pathologically, PD is defined with a loss or degeneration of the dopaminergic neurons in the substantia nigra and the development of Lewy bodies in the neurons [5]. Lewy bodies are intracellular aggregates containing various proteins including α-synuclein which can become misfolded and self-aggregated. Systems in place to break down abnormal proteins like ubiquitin-proteasome are also impaired, leading to depressed neural functioning [6]. Moreover, there are other impaired processes that could play a role in PD such as mitochondrial dysfunction and abnormal oxidative stress through reactive oxygen species causing neuronal degeneration [6]. Recent evidence suggests that environmental stress and aging itself may promote neuropathology through cellular senescence in brain neurons [7].

Diagnosis of PD is difficult and usually based on the clinical presentation of the patient. The use of functional magnetic resonance imaging (fMRI), single photon emission computed tomography (SPECT) and more recently dopamine transporter scans (DaTscan) have allowed doctors to distinguish PD and non-dopaminergic diseases with similar clinical presentations [8]. Furthermore, recent advances in artificial intelligence (AI) and machine learning (ML) systems have shown their potential role in identification of PD at earlier stages of onset [9,10]. Most importantly, these systems use clinical and non-clinical data which could be collected on widely available wearable devices, promising easy integration into daily life [10,11].

Currently, levodopa remains the gold standard for treatment of PD. This drug is classified under the larger group of dopamine agonists which directly increase the depleting levels of dopamine in the patients’ brain. Moreover, other treatments like catechol O-methyltransferase (COMT) inhibitors and monoamine oxidase-B (MOA) inhibitors stop enzymatic pathways driving the depletion of dopamine in the brain [12]. However, these treatment options have been known to have significant side effects including psychiatric problems and psychosis [12]. More recently, surgical techniques like deep brain stimulation (DBS) and transcranial cranial magnetic stimulation (TMS) have been shown to have positive effects in the treatment of PD, with DBS receiving FDA approval to be used in treatment [13].

In summary, as we come to understand more about this debilitating disease the future holds some hope for patients suffering from it. Education and awareness are also crucial aspects of tackling the problem at a community level, so people suffering from this condition will be able to receive the care they need.

 

References:

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[2]       H.T.S. Benamer, R. de Silva, K.A. Siddiqui, D.G. Grosset, Parkinson’s disease in Arabs: A systematic review, Movement Disorders. 23 (2008) 1205–1210. https://doi.org/10.1002/MDS.22041.

[3]       J. Parkinson, NEUROPSYCHIATRY CLASSICS An Essay on the Shaking Palsy Member of the Royal College of Surgeons PREFACE, 2002.

[4]       S.Y. Lim, A.E. Lang, The nonmotor symptoms of Parkinson’s disease-An overview, Movement Disorders. 25 (2010). https://doi.org/10.1002/mds.22786.

[5]       J. M. Beitz, Parkinson’s Disease : A Review, Frontiers in Bioscience. (2014) 65–74. https://doi.org/10.2741/S415

[6]       A.H.V. Schapira, Etiology and Pathogenesis of Parkinson Disease, Neurol Clin. 27 (2009) 583–603. https://doi.org/10.1016/j.ncl.2009.04.004.

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[9]       J. Mei, C. Desrosiers, J. Frasnelli, Machine Learning for the Diagnosis of Parkinson’s Disease: A Review of Literature, Front Aging Neurosci. 13 (2021) 184. https://doi.org/10.3389/FNAGI.2021.633752/BIBTEX.

[10]     M. Belić, V. Bobić, M. Badža, N. Šolaja, M. Đurić-Jovičić, V.S. Kostić, Artificial intelligence for assisting diagnostics and assessment of Parkinson’s disease—A review, Clin Neurol Neurosurg. 184 (2019) 105442. https://doi.org/10.1016/J.CLINEURO.2019.105442.

[11]     Y. Yang, Y. Yuan, G. Zhang, H. Wang, Y.C. Chen, Y. Liu, C.G. Tarolli, D. Crepeau, J. Bukartyk, M.R. Junna, A. Videnovic, T.D. Ellis, M.C. Lipford, R. Dorsey, D. Katabi, Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals, Nature Medicine 2022 28:10. 28 (2022) 2207–2215. https://doi.org/10.1038/s41591-022-01932-x.

[12]     S.S. RAO, L.A. HOFMANN, A. SHAKIL, Parkinson’s Disease: Diagnosis and Treatment, Am Fam Physician. 74 (2006) 2046–2054. https://www.aafp.org/pubs/afp/issues/2006/1215/p2046.html (accessed April 7, 2023).

[13]     R. Mehanna, E.C. Lai, Deep brain stimulation in Parkinson’s disease, Translational Neurodegeneration 2013 2:1. 2 (2013) 1–10. https://doi.org/10.1186/2047-9158-2-22.