Progress and Prospects in Parkinson's Research/Monitoring Parkinson's Disease/Measurement of Parkinson's Disease Progression

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"There is an urgent need for biomarkers for disease progression that would faithfully reflect advancing neurodegeneration and resulted clinical disability in PD and that could be used in shorter term clinical trials testing putative disease modifying agents."[1] Werner Poewe (2009)

Why is this topic important?

The main reason is, as the above quote says, because you can only tell whether a therapy works if you can reliably detect whether it is slowing down or stopping the progress of the disease. At the moment the techniques for assessing disease stage and progress are pretty blunt instruments because Parkinson's progresses very slowly and its symptoms vary from day to day.

The following argues for why we need to define more closely what we mean by disease progression and rate of progression and what may be good targets for measurement.

There are also issues about what measurement targets are appropriate at different stages of the largely predictable evolution of this disease.

There is also the question of how well disease progression can be measured directly and whether secondary quantifiable effects of disease progression such as changes in protein expression and metabolyte levels might be good surrogate indicators.

What is the disease we call Parkinson's?

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Parkinson's affects movement - it is typically characterised by rigidity, tremor and slowness of movement. Degeneration of the substantia nigra in the mid-brain causes this.

But other centres in the brain and in the peripheral nervous system are also affected and give rise to a range of non-motor symptoms.

The mechanism of the neural degeneration is multifaceted but the dominant pathology is associated with the aggregation of the protein alpha-synuclein.


Nature of pathology and disease mechanism at cellular and biochemical levels

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While alpha-synuclein pathology is intimately associated with the Parkinson's disease mechanism, studies have shown that other phenomena also accompany the biopathology [2]. These include dysfunction of the mitochondria[3], the UPS[4], of autophagy[5](the lysosomal system) and of iron homeostasis; and oxidative stress[6], inflammation[7] involving the microglia[8] and the adaptive immune system (T cells)[9] and apoptosis[10] induced by cytokines[11].

A complex interplay of these would seem to constitute the underlying driver of the slow but relentless progression of the disease. Much work needs to be done to disentangle this complexity and to resolve these phenomena into causes, effects, synergisms, positive feedbacks and epiphenomena.

Quantification - How far, how fast and how intense

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From the patient's point of view, the crucial indicator of how far the disease has progressed is the sum total of the symptoms experienced.

From the pathological point of view, the proportion of nerve cells that have died in various centres, the damage to dopamine receptors in the striatum and the level of alpha-synuclein aggregation throughout the body may be more fundamental measures.

On the other hand, the intensity of oxidative stress and of neuroinflammation and measures of the dysfunction of the mitochondria, the UPS and the autophagy system ought to give a better indication of the rate of progression of the disease.

Further, since the disease has a profound effect on the differential expression of a great many proteins, cytokines and other biochemical entities, measurement of levels of these could give useful information on the disease stage, intensity and rate of progression once the relevant quantitative correlations have been established. Proteomics and metabolomics are relevant here.

The key of course is how these essentially biochemical markers can be assayed in humans (Parkinson's patients and healthy controls) in vivo. Indirectly, assays of markers in ethically accessible tissues and body fluids may correlate with biochemical status in tissues specifically involved in PD. However, there is a clear need for new technologies enabling biochemical status in target neurological tissues to be assayed directly and non-invasively.

Assessing disease stage and rate of progression

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Shortcomings of the rating scales

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The common rating scales for assessing the stage of the disease and its progression are comparatively blunt instruments. The Unified Parkisons's Disease Rating Scale, the UPDRS, the Hoehn and Yahr, Schwab and England and other scales are often used especially in the clinical context. Using these scales, the evaluation is largely done by interview and clinical observation. The result is a point score for each section which gives a general estimate of disease severity and the patient's disability.

Because the disease progresses slowly and the nature and severity of symptoms vary from day to day and even from hour to hour, these scales cannot give a precise measure of disease progress over the short term. They are therefore inadequate for the swift and reliable determination of the effect of new treatments or therapies. In the absence of better evaluation tools they are routinely used in trials. Such trials have to involve large numbers of patients over considerable time periods - several years - if they are to capture results that are statistically significant. Such trials are inevitably expensive and are consequently limited in number.

The rating scales are often supplemented with scanning techniques (PET, SPECT, DaTSCAN) which give a measure of the degeneration of the dopaminergic neurons. Because of their high cost, these methods for disease progress estimation are generally used for only a small proportion of the patients in a trial.

Biomarkers for detection and quantification

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Wikipedia describes a biomarker, or biological marker, as "in general a substance used as an indicator of a biological state. It is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention."

In the context of Parkinson's disease, biomarkers have, in recent years, been researched and discussed mainly as means of detecting the condition in advance of diagnosis. In the vast majority of cases diagnosis is carried out as the result of the appearance of motor symptoms. Even though the disease will have started many years before this, earlier symptoms are likely to have been comparatively mild and, taken individually, non-specific for Parkinson's. The interest in biomarkers arises to some extent because of the realisation that the emergence of a pattern of symptoms in the prodromal stage could give an early indication of the likelihood of Parkinson's and could enable measures to be taken, as soon as such measures have been developed, to slow down or stop disease progression. Even now, there is strong evidence that environmental and lifestyle choices reduce the risk of the development of Parkinson's and individuals in the prodromal stage may well wish to take some action to forestall the development of the full-blown disease.

The challenge that one project has taken up, however, is to investigate whether a range of biomarkers can be used to measure, with a higher degree of precision and reliability than at present, the actual rate of progression of the disease. If this were possible it would provide an invaluable toolset for the assessment of the effect of new therapies over short timescales and with smaller cohorts of patients and thus at much less expense. This project (and if you know of others with similar aims please add references) is the MJFox Foundation Parkinson’s Progression Markers Initiative[Biomarker Refs 1] (PPMI), which announces itself as "a landmark observational clinical study to comprehensively evaluate a cohort of recently diagnosed PD patients and healthy subjects using advanced imaging, biologic sampling and clinical and behavioral assessments to identify biomarkers of Parkinson’s disease progression."

Biomarkers and their potential as measures of disease progression

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For a list of candidate biomarkers see the Biomarkers page.

Michael G Schlossmacher and Brit Mollenhauer have written and excellent introduction in the journal Biomarkers in Medicine.[Biomarker Refs 2]

A candidate biomarker can be discussed in terms of whether it can be used

  1. to quantify a symptom or groups of symptoms,
  2. to measure the extent of a pathological or degenerative change either in a specific location or across a range of locations in sequence and
  3. to quantify the level or intensity of a biopathological process (such as the level of microglia activation of a given type or of the intensity of oxidative stress).

For 1 and 2 the difference in measurements at two moments in time should, on the face of it, give the rate of disease progression. But it is likely that the rate of change of almost all target phenomena will not be linear with some changing rapidly early on in the disease and others much later on.

For 3 - level or intensity of a biopathological process - the relationship between the intensity of a biopathological process and pathological damage will need to be established. This will be different at different stages of the disease and for different neural locations. It will also need to be established whether the chosen process is a causative factor or a result of another process. The quantitative relationships between processes and pathology will need to be established.

The following sections need expanding and referencing with up to date material.

M J Fox Foundation Parkinson's Progression Measurement project

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See the PPMI summary [Biomarker Refs 1]

The Parkinson's UK Tracking Parkinson's project

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[Biomarker Refs 3]

Rating scales

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Towards a baseline for the progression of disability [Biomarker Refs 4]

References are also needed here for inconsistencies between UPDRS scores and imaging results

Citations needed for works reviewing the utility and shortcomings of the various rating scales

Saccadic eye movement

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This subsection needs material on progress in correlating impairment of saccadic eye movements with pathological damage.

[Biomarker Refs 5]


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This section needs material on progress in correlating imaging data with disease progression and the level or intensity of pathogenesis.

PET, SPECT, DaTSCAN, fMRI, echogenicity/sonography, myocardial scintigraphy, fluorescent imaging of amyloid formation

Diffusion Tensor Imaging (DTI) which enables the measurement of the restricted diffusion of water in tissue in order to produce neural tract images. Imaging of olfactory tract. [12]

Fluorescent imaging: see ref [13]

Proteomics and Metabolomics

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This section needs material on what these techniques are and which proteins and metabolites are most promising for the quantification of disease stage and rate of pathogenesis?

Alpha-synuclein in saliva and CSF: [Biomarker Refs 6], [Biomarker Refs 7]

Pathological assay

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This section needs up to date information on biopsies and peripheral tissue assay especially for alphasynuclein deposition.

Colonic Biopses[Biomarker Refs 8][Biomarker Refs 9][Biomarker Refs 10]

Cutaneous nerves[Biomarker Refs 11]



This article is in the process of being developed. Droflet (talk) 09:47, 25 March 2012 (UTC)

Possible further headings:

Problem of deciding what characteristics to measure to assess disease progression

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< Back to Monitoring Parkinson's disease

Sub pages:

None yet

See also

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The neuropathology of Parkinson's

A H V Schapira, “Challenges to the development of disease-modifying therapies in Parkinson's disease,” European Journal of Neurology: The Official Journal of the European Federation of Neurological Societies 18 Suppl 1 (March (2011): 16-21.

Biomarker References

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  1. 1.0 1.1, and Cite error: Invalid <ref> tag; name "PPMI" defined multiple times with different content
  2. Michael G Schlossmacher and Brit Mollenhauer, “Biomarker research in Parkinson’s disease: objective measures needed for patient stratification in future cause-directed trials,” Biomarkers in Medicine 4, no. 5 (October 2010): 647-650.
  4. Leland E Dibble et al., “Charting the progression of disability in parkinson disease: study protocol for a prospective longitudinal cohort study,” BMC Neurology 10 (2010): 110.
  5. Ashley J Hood et al., “Levodopa slows prosaccades and improves antisaccades: an eye movement study in Parkinson’s disease,” Journal of Neurology, Neurosurgery & Psychiatry 78, no. 6 (June 1, 2007): 565 -570
  6. Ivana Devic et al., “Salivary {alpha}-synuclein and DJ-1: potential biomarkers for Parkinson’s disease,” Brain: A Journal of Neurology 134, no. 7 (July 2011): e178.
  7. Brit Mollenhauer et al., “α-Synuclein and tau concentrations in cerebrospinal fluid of patients presenting with parkinsonism: a cohort study,” Lancet Neurology 10, no. 3 (March 2011): 230-240.
  8. Thibaud Lebouvier et al., “Colonic Biopsies to Assess the Neuropathology of Parkinson's Disease and Its Relationship with Symptoms” PLoS One. 2010; 5(9): e12728.
  9. Shannon, Kathleen M, Ali Keshavarzian, Hemraj B Dodiya, Shriram Jakate, and Jeffrey H Kordower. “Is Alpha-synuclein in the Colon a Biomarker for Premotor Parkinson’s Disease? Evidence from 3 Cases.” Movement Disorders: Official Journal of the Movement Disorder Society (May 1, 2012).
  10. Shannon, Kathleen M, Ali Keshavarzian, Ece Mutlu, Hemraj B Dodiya, Delia Daian, Jean A Jaglin, and Jeffrey H Kordower. “Alpha-synuclein in Colonic Submucosa in Early Untreated Parkinson’s Disease.” Movement Disorders: Official Journal of the Movement Disorder Society (July 15, 2011).
  11. Masako Ikemura et al., “Lewy body pathology involves cutaneous nerves,” Journal of Neuropathology and Experimental Neurology 67, no. 10 (October 2008): 945-953.


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  1. Werner Poewe, “Clinical measures of progression in Parkinson's disease,” Movement Disorders: Official Journal of the Movement Disorder Society 24 Suppl 2 (2009): S671-676. PMID: 19877235
  2. Diogo Martins Branco et al., “Cross-talk between mitochondria and proteasome in Parkinson's disease pathogenesis,” Frontiers in Aging Neuroscience 2 (2010): 17.
  3. Lee J. Martin, “Mitochondrial and Cell Death Mechanisms in Neurodegenerative Diseases,” Pharmaceuticals (Basel, Switzerland) 3, no. 4 (2010)</: 839-915.
  4. 1. Casey Cook and Leonard Petrucelli, “A Critical Evaluation of the Ubiquitin-Proteasome System in Parkinson's Disease,” Biochimica et biophysica acta 1792, no. 7 (July (2009)</: 664-675.
  5. Rebecca Banerjee, M Flint Beal, and Bobby Thomas, “Autophagy in neurodegenerative disorders: pathogenic roles and therapeutic implications,” Trends in Neurosciences 33, no. 12 (December ): 541-549.(2010)</
  6. 1. Noriyuki Shibata and Makio Kobayashi, “The role for oxidative stress in neurodegenerative diseases,” Brain and Nerve = Shinkei Kenkyū No Shinpo 60, no. 2 (February 2008): 157-170.
  7. Malú G Tansey, Melissa K McCoy, and Tamy C Frank-Cannon, “Neuroinflammatory mechanisms in Parkinson's disease: potential environmental triggers, pathways, and targets for early therapeutic intervention,” Experimental Neurology 208, no. 1 (November 2007): 1-25.
  8. Patrick L McGeer and Edith G McGeer, “Glial reactions in Parkinson's disease,” Movement Disorders: Official Journal of the Movement Disorder Society 23, no. 4 (March 15, 2008): 474-483.
  9. Li Qian, Patrick M Flood, and Jau-Shyong Hong, “Neuroinflammation is a key player in Parkinson's disease and a prime target for therapy,” Journal of Neural Transmission (Vienna, Austria: 1996) 117, no. 8 (August 2010): 971-979.
  10. Simone Fulda et al., “Cellular Stress Responses: Cell Survival and Cell Death” 2010 (2010).
  11. Ian A Clark, Lisa M Alleva, and Bryce Vissel, “The roles of TNF in brain dysfunction and disease,” Pharmacology & Therapeutics 128, no. 3 (December 2010): 519-548.
  12. Naroa Ibarretxe-Bilbao et al., “Olfactory impairment in Parkinson's disease and white matter abnormalities in central olfactory areas: A voxel-based diffusion tensor imaging study,” Movement Disorders: Official Journal of the Movement Disorder Society 25, no. 12 (September 15, 2010): 1888-1894.
  13. 1. Tjakko J van Ham et al., “Towards multiparametric fluorescent imaging of amyloid formation: studies of a YFP model of alpha-synuclein aggregation,” Journal of Molecular Biology 395, no. 3 (January 22, 2010): 627-642.