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Biomarkers for Parkison's disease Tools to assess Parkinson's disease onset and progression.

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FUTURE ISSUES
Biomarkers for Parkison’s Disease: Tools to
Assess Parkinson’s Disease Onset and
Progression
Kenneth Marek, MD, Danna Jennings, MD, Gilles Tamagnan, PhD, and John Seibyl, MD
Reliable and well-validated biomarkers for PD to identify individuals “at risk” before motor symptoms, accurately diagnose
individuals at the threshold of clinical PD, and monitor PD progression throughout its course would dramatically accelerate
research into both PD cause and therapeutics. Biomarkers offer the potential to provide a window onto disease mechanism,
potentially generating therapeutic targets for disease. In particular, biomarkers enable investigation of the premotor period of PD
before typical symptoms are manifest, but while degeneration has already begun. Given the multiple genetic causes for PD
already identified, the marked variability in the loss of dopaminergic markers measured by imaging at motor symptom onset and
the clear heterogeneity of clinical symptoms in PD onset and clinical progression, it is likely many biomarkers with a focus
ranging from clinical symptoms to PD pathobiology to molecular genetic mechanisms will be necessary to fully map PD risk and
progression. Biomarkers are also critical in new drug development for PD, both in early validation studies to assess drug dosing
and to determine drug penetrance into the brain, and in later efficacy studies to complement PD clinical outcomes. During the
past two decades, much progress has been made in identifying and assessing PD biomarkers, but as yet, no fully validated
biomarker for PD is currently available. Nonetheless, there is increasing evidence that molecular genetics, focused -omic (proteomic, metabolomic, and transcriptomic) assessment of blood and cerebrospinal fluid, and advanced in vivo brain imaging will
provide critical clues to assist in the diagnosis and medical management of PD patients.
Ann Neurol 2008;64 (suppl):S111–S121
The defining motor features of Parkinson’s disease
(PD) are characterized by their insidious onset and inexorable but variable progression. Reliable and wellvalidated biomarkers for PD to identify individuals “at
risk” before motor symptoms, accurately diagnose individuals at the threshold of clinical PD, and monitor
PD progression throughout its course would dramatically improve patient care and accelerate research into
both PD cause and therapeutics. During the past two
decades, much progress has been made in identifying
and assessing PD biomarkers, but as yet, no fully validated biomarker for PD is available. Nonetheless,
there is increasing evidence that molecular genetics, focused -omic (proteomic, metabolomic, and transcriptomic) assessment of blood and cerebrospinal fluid
(CSF), and advanced in vivo brain imaging will pro-
vide critical clues to assist in the diagnosis and medical
management of PD patients.
Biomarkers are broadly defined as characteristics that
are objectively measured and evaluated as indicators of
normal biological processes, pathogenic processes, or
pharmacological responses to a therapeutic intervention. It is critical to make the distinction between biomarkers in general and surrogate markers. Surrogate
markers are a subset of all biomarkers that can be used
in a clinical study as a substitute for a clinically meaningful end point that is expected to predict the effect of
a therapeutic intervention.1,2 In addition, it would be
required for a surrogate to be successfully tested in several studies with different therapeutic interventions to
fully designate that marker as a surrogate.3–5
Although biomarkers that are not true surrogates
From the Institute for Neurodegenerative Disorders, New Haven,
CT.
and Teva. D.J. is an employee of Molecular NeuroImaging, LLC.
G.T. has no financial interests to disclose. J.P.S. has served as a
consultant for BI, Avid Radiopharmaceuticals, Bayer Schering
Healthcare, Pfizer, Takeda Pharmaceuticals, Lilly, GE Healthcare,
Alseres, Novartis, Eisai, and has equity interest in Molecular Neuroimaging, LLC.
Received Mar 19, 2008, and in revised form Oct 31. Accepted for
publication Nov 7, 2008.
Additional Supporting Information may be found in the online version of this article.
Potential conflicts of interest: This article is part of a supplement
sponsored by Boehringer Ingelheim (BI). K.M. has served as a consultant for BI, Pfizer, Novartis, GE Health, Alseres, Merck Serono,
Lilly, Bayer Schering Pharma, Elan, and has equity interest in Molecular NeuroImaging, LLC. D.J. is a consultant for BI, Genzyme
Published online in Wiley InterScience (www.interscience.wiley.com).
DOI: 10.1002/ana.21602
Address correspondence to Dr Marek, Institute for Neurodegenerative Disorders, 60 Temple Street, New Haven, CT 06510. E-mail:
kmarek@indd.org
© 2008 American Neurological Association
Published by Wiley-Liss, Inc., through Wiley Subscription Services
S111
may be extraordinarily useful, experience from many
areas of medicine raise important cautions in using biomarkers in clinical studies. An example of a biomarker
“gone wrong” was the Cardiac Arrhythmia Suppression
Trial (CAST) in which the antiarrhythmic drugs tested
suppressed ventricular arrhythmias (the biomarker) but
resulted in increased mortality compared with placebo.6,7 In oncology, the commonly used surrogate of
tumor shrinkage has had mixed results as a predictor of
clinical improvement or remission.8 In contrast, the
development of highly sensitive molecular tools for the
detection and quantitation of circulating human immunodeficiency virus type 1 RNA was critical in the
acceleration of anti–human immunodeficiency virus
therapies for acquired immune deficiency virus.9 These
examples demonstrate both the potential high value
and the risk in using biomarkers to make clinical decisions and inform our requirements for validation of
and potential use of biomarkers for PD.
Although it is important to acknowledge that a true
surrogate marker for PD does not exist, it is even more
critical to note that existing and developing biomarkers
for PD are and may be extremely useful both for disease diagnosis and monitoring, and for drug development. In considering biomarkers for PD, three crucial
issues must be addressed. The first issue is face validity:
Is the marker meaningful or relevant to the disease process? Second, what are the performance characteristics
of the marker in the relevant subject population under
study; for example, diagnostic markers must predict
disease in individuals who are not diagnosed. Third,
how generalizable is the biomarker? The effect of stage
of disease, age, sex, medications, or environment on
the biomarker must be carefully assessed.
What Do Biomarkers Offer?
Biomarkers for PD are critical to our understanding of
disease cause and disease progression. Biomarkers are
tools that provide information about disease mechanism that is generally not obtainable from clinical studies and are particularly valuable in drug development
to investigate drug mechanisms and drug dosage. In
particular, biomarkers may provide a window to the
premotor period of PD before typical symptoms are
manifest, but while degeneration has already begun.
The spectrum of why biomarkers may be both necessary and useful is outlined in Table 1. Given the multiple genetic causes for PD already identified, the
marked variability in the loss of dopaminergic markers
measured by imaging at motor symptom onset, and the
clear heterogeneity of clinical symptoms in PD onset
and clinical progression, it is clear that many biomarkers with a focus ranging from clinical symptoms to
PD pathobiology to molecular genetic mechanisms will
be necessary to fully map PD risk and progression.10 –12
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December 2008
Table 1. Rationales for Use of Biomarkers for
Parkinson’s Disease
Biomarker
Rationale
Disease and drug
mechanism
What Do Biomarkers
Offer?
Proof of drug mechanism
Focus on disease
mechanism
Establish dosage
Clinical study design
Rapid outcome: POC
Reduce sample size
Repeat measurement
More accurate baseline
diagnosis
Enrich cohort
Premotor
Identify “at-risk” subjects
Establish and follow
premotor progression
Progression
Monitor disease
progression
Assess disease-modifying
medications
Subtypes
Dementia
Behavioral
Motor fluctuations
Response to drug
Individual efficacy
Individual adverse effects
Disease and Drug Mechanism
Biomarkers for disease mechanism may be directed at a
specific potential underlying pathophysiology of PD
such as inflammation, ␣-synuclein deposition, mitochondrial dysfunction, or protein misfolding.13–16 Recent pathological, imaging, and epidemiological data
have suggested that inflammatory changes may be a
risk biomarker for PD, and that imaging markers of
microglial activation or inflammatory changes in
plasma may be useful tools.17–21 An avalanche of data
from molecular genetics have implicated increased
␣-synuclein as a risk biomarker and possibly as a progression biomarker for PD.22–24 Developing ␣-synuclein
assays demonstrate changes in plasma and CSF of PD
patients.25,26 The confluence of genetic abnormalities
such as PINK1 and DJ-1 and of existing data implicating reduced mitochondrial function has also provided
potential for novel biomarkers of mitochondrial function.27–29 These biomarkers of disease cause can be further used to assess potential therapies that have been or
will be tested in clinical trials of antiinflammatory drugs,
mitochondrial enhancing drugs, and ␣-synuclein disag-
gregation drugs or small interfering RNA strategies to
block ␣-synuclein.30 –33
Biomarkers are critical in new drug development for
PD. Early in development, it is helpful to identify a
reliable biomarker signal to determine drug penetrance
into the brain, and drug selectivity and dosing at the
target site. In vivo imaging assessment has been a valuable tool in early drug development for PD. The displacement of dopamine transporter (DAT) imaging ligands to assess drugs that block the DAT is one
example of an imaging biomarker informing dosing
decisions.34 Similarly, the recent development of
KY6002, an adenosine 2A antagonist, was guided by
imaging of the radiolabeled drug.35 Biomarker signals
may even provide go/no-go decisions for drug development in the proof of concept to phase 2 stage of development. In later phase drug development, in vivo
dopaminergic imaging has been utilized in PD studies
to examine the mechanism of potential diseasemodifying medications.12,36,37 Although the interpretation of these study results using imaging biomarkers
has proved controversial, the use of imaging to assess
drugs in phase 1 through phase 4 studies of PD continues to expand.
Biomarkers may also be used to assess drug effect.
For example, it may be helpful to demonstrate a drug
effect unrelated to clinical outcomes of the study to
prove drug compliance or to indirectly assess drug levels to show brain penetrance. In future studies, drug
effect may allow for individualized dosing based on biomarker assessment as a guide. This may ultimately allow patients to minimize adverse effects of medication.
For example, assessment of dopamine D2 receptor may
uncover those subjects at risk for behavioral side effects
with these drugs who are either avoiding or limiting
treatment.
Like biomarker development, more predictive animal
models for PD would enhance research and drug development.38 As animal models are developed for PD,
biomarkers may be particularly useful in translating the
effects of drugs in animal models from animals to humans. The goal is to probe animal models with the
same biomarkers that could be used in clinical trials.
Developing tools to assess ␣-synuclein or LRRK2 kinase in transgenic mice models that could ultimately be
used in clinical drug trials or imaging non-human primates treated with MPTP (1-methyl-4-phenyl-1,2,3,6tetrahydropyridine) and human research subjects with
the same radiolabeled tracer provides a powerful link
between animal models and human studies.
Improve Clinical Design
Biomarkers offer the potential to complement the clinical assessments used as a primary study in clinical
studies of PD. First, biomarkers are generally objective
measures of disease and, therefore, are more easily stan-
dardized and identically measured repeatedly during
the trial. Although standardization of biomarker collection and analysis requires clear and detailed procedures,
it enables objective data to be pooled at multiple study
sites. Most often, biomarkers are assessed at a core laboratory with expertise in analytical methodology. Specific procedures for transfer of biological samples (ie,
genetic, proteomic, metabolomic analysis) and/or imaging data must be in place. The AMADEUS imaging
network, a single-photon emission computed tomography imaging consortium for PD, and the Alzheimer’s
Disease Neuroimaging Initiative (ADNI) for Alzheimer’s disease have demonstrated that both biological
and imaging samples can be collected and analyzed in
studies of disease progression.39
In clinical studies, multiple biomarkers may be assessed in the same subjects. This strategy may enable
comparison and correlation of biomarkers such as imaging markers, and proteomic and metabolomic markers, and/or markers that target multiple neuronal systems. When multiple biomarkers are evaluated
concurrently, the power of the study may be substantially increased. For example, in studies of PD relatives
tested for olfactory function and then undergoing
DAT imaging, combining the loss of olfaction and
DAT imaging density identifies a subgroup with increased risk for development of PD.40 Imaging studies
comparing dopaminergic ligands and metabolic tracers
have provided complementary data enhancing the utility of both tracers.41 The potential of combining in
vivo imaging and/or nigral ultrasound with proteomic,
metabolomic, and transcriptomic analyses is currently
under evaluation in several ongoing studies such as the
PARS study and other risk marker assessment studies.42,43
Perhaps the most important practical rationale for
using biomarkers in clinical studies is the potential for
longitudinal biomarker outcomes to provide critical
data with a shorter duration of follow-up and a reduced sample size compared with that required of typical clinical outcomes. The sample size requirements
for a progression study depend on the effect size and
the variance of the outcome measure. For example, in
vivo dopamine neuroimaging requires a similar sample
size and observation interval to that of common clinical outcomes (change in Unified Parkinson’s Disease
Rating Scale or need for dopaminergic therapy).12,36,44
Identifying biomarkers that could provide a more rapid
assessment of drug effect would substantially accelerate
development of putative disease-modifying drugs.
Biomarkers may also be used in clinical studies to
better define or enhance the study cohort. Although
predefining the cohort may reduce generalizability of
the study outcome, using biomarkers to define eligibility may ensure a more accurate diagnosis of the study
subjects and, therefore, reduce variance in the out-
Marek et al: Biomarkers for PD
S113
come. In several studies of newly diagnosed PD in
vivo, dopaminergic imaging has identified about 10%
to 15% with scans in the reference range termed scans
without evidence of dopaminergic degeneration
(SWEDD).12,37,44 Subsequent follow-up has indicated
that those study participants with SWEDD are unlikely to have PD.45 In the ELLDOPA study and
REAL Positron Emission Tomography study, data
analysis using the imaging biomarker to define the
study cohort changed trends to statistical significance
of study outcomes.37,44 In other studies, biomarkers
are used as an a priori definition of the study cohort as
in studies of subjects with a LRRK2 mutation. These
studies utilize biomarkers to explore a specific causative
factor or subtype of PD.
Premotor Assessment
Biomarkers may be especially useful to identify individuals at risk during the premotor period of PD and to
investigate the progression of PD during the premotor
period. Pathology and imaging studies have shown that
PD patients have already lost about 50% to 60% of
dopamine neuronal markers at the threshold of motor
symptoms46 – 48 (Fig). These data are consistent with
the notion that there is a prolonged period during
which an individual can be identified as “at risk” by
genetic testing, imaging evidence of neuronal degeneration, and/or early clinical signs associated with PD
such as olfactory loss, rapid eye movement behavior
disorder, cognitive dysfunction, or autonomic dysfunction.49 Although the duration of the premotor period
is unclear, imaging and pathology data suggest that the
duration is at least 5 years and may be as long as 20
years. Data from evaluation of postmortem tissue have
provided further evidence suggesting a characteristic
temporal pattern of brain pathology in PD ascending
from the brainstem to the basal ganglia and cortical
regions.50 Most recently, data have further suggested
Fig 1. Natural history of Parkinson’s disease (PD). Note that
although risk markers are most useful in the premotor period
and progression markers are focused on disease after diagnosis,
biomarkers also may inform both risk and progression of PD.
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that PD pathology may even originate in extra–central
nervous system regions such as the mesenteric plexus in
the gut or cardiac neuronal tissue.51,52 The pathology
data have led to a reexamination of a range of
Parkinson’s-related symptoms such as olfactory loss,
sleep disturbance such as rapid eye movement behavior
disorder, and autonomic dysfunction including constipation and loss of cardiac reflexes as possible early clinical markers or early clinical manifestations of PD.42,53
Reliable and validated biomarkers that identify individuals at risk before motor symptoms and monitor the
course of PD progression during the premotor period
would provide critical information to enhance our understanding of and provide therapeutic strategies for
the premotor period. Studies including the PARS study
plan to combine premotor biomarkers with early PDassociated nonmotor symptoms to identify an at-risk
population that could be followed to examine the premotor period and to identify a cohort of subjects who
will experience development of PD.
Biomarkers of Disease Progression
Biomarkers of disease progression after diagnosis have
been a focus for studies of disease-modifying medications. The lack of success of recent disease-modifying
therapeutic trials coupled with the huge expense of
these studies has highlighted the need for biomarkers
of PD progression for future clinical studies of diseasemodifying drugs. Given that current clinical end points
for disease modification trials for PD are limited by
potentially confounding symptomatic treatments, difficulty in drug washout, and subjectivity of clinical examination and clinical scales, the promise that biomarkers may provide a rapid, objective measure of disease
progression to complement clinical outcomes remains
appealing. Biomarkers such as targeted radioligands or
molecules identified by proteomic or metabolomic
screening may easily be assessed repeatedly in studies of
PD progression. A further critical advantage for biomarkers is that they may track disease progression
without being themselves affected by typical symptomatic dopaminergic medications that would be used in
clinical practice to treat PD patients during a progression study. However, the effect of PD therapies on biomarker changes must be carefully examined. For example, although there are numerous studies that
demonstrate that in vivo imaging studies are useful in
monitoring disease progression, the potential for imaging biomarker outcomes to be confounded by symptomatic dopaminergic treatment had limited the interpretation of imaging biomarker data.54 –56 Recent
studies have demonstrated that there is no short-term
regulation of DAT imaging by dopaminergic treatment
in early PD.57 Yet, the essential lesson is that biomarkers of disease progression must be fully tested to ensure that change in the biomarker outcome is not con-
founded by age, sex, PD medications, other coexisting
disease, or any factors other than progression of PD.
Although biomarkers for disease risk and progression
are ideally designed to be generalizable to all PD patients, it may also be useful to develop biomarkers specifically directed at subsets of PD patients. The discovery of several PD genes has identified subtypes of PD
defined by molecular genetics.11,58 Although identified
mutations generally account for a small number of PD
patients, in some populations, such as the Ashkenazi
Jewish population or in regions of Spain or North African, LRKK2 mutations may identify approximately
20% to 35% of the PD population.59 – 61 PD subtypes
may be defined by demographic features such as age of
onset, sex, clinical symptoms such as dementia, depression, behavioral disorders, sleep disorders, or clinical
milestones such as motor fluctuations. Biomarkers of
PD subtypes may predict those subjects at risk for development of PD symptoms such as PD dementia or
motor fluctuations. For example, older age of onset is
associated with increased risk for PD dementia and
younger age of onset with increased likelihood of motor fluctuations.62,63 More recently, in several imaging
studies, markers such as ␤-amyloid burden, fluorodeoxyglucose pattern, or nicotinic receptor binding have
been suggested as tools to identify subjects at risk for
PD dementia.64 – 66 Similarly, changes in dopamine
D2, opioid, and/or nicotinic receptors may be associated with increased risk for motor fluctuations.67,68
Studies evaluating potential progression markers for
PD dementia, motor fluctuation, and other PD subtypes are currently under way.
Parkinson’s Disease Biomarkers: Risk Markers
versus Progression Markers
Current Landscape
Biomarkers for PD may be directed at disease risk, disease progression, or both. Biomarkers may be disease
stage or disease medication specific. For example, progression biomarkers may be useful during the premotor
period, at the onset of clinical symptoms disease,
and/or to mark disease progression and neurocompensatory mechanism after typical symptoms occur.69 Similarly, risk markers may predict onset of disease during
the premotor period or risk for development of a motor or nonmotor complication after disease onset. Biomarkers may monitor progression or identify risk for
specific subsets of PD patients such as those with or at
risk for cognitive, autonomic, and behavioral changes.
Finally, biomarkers for response to therapy may be unrelated to PD but predispose individuals to either improvement or adverse effects of medication.
Risk Biomarkers
Biomarkers of PD risk broadly include any marker or
risk factor that modifies the risk for development of
clinical PD. Risk markers may be genetic or nongenetic, or may require a gene-environment interaction.
During the past decade, the landscape of the molecular
genetics of PD has been rewritten. Studies of families
of PD patients have uncovered a growing list of several
PD genes. The best studied to date include both the
dominantly inherited Park 1/␣-synuclein and Park
8/LRRK2 (dardarin), and the recessively inherited Park
2/Parkin, Park 6/PINK1, and Park 7/DJ-1.11,58 Other
studies have examined patterns of gene expression in
PD to identify groups of genes that may modify risk or
attempted a targeted gene pathways approach to examine the joint actions of gene variants within pathways.70,71 Numerous studies have begun to investigate
the gene products of these mutations or arrays of
genes. Markers such as ␣-synuclein and SP13 are under study as potential protein biomarkers that might
both identify risk and monitor disease.25,26,70
Insights from epidemiological studies have also suggested several risk markers for PD. These findings provide clues for disease causative factors, but these studies
cannot establish causality. The most well-established
risk factor for PD is age. In numerous studies, the incidence of PD increases with age.72,73 These epidemiological data are supported by the pathological and imaging data demonstrating an age-related reduction in
dopamine neurons and the DAT density, and by recent data showing reduced ␣-synuclein in CSF with
aging.26,46,74 The changes in brain compensatory function with age remain a target of further investigation.
Male sex is also a risk factor for PD. Although the
explanation for increased risk for PD in male individuals is unclear, recent evidence showed that sex may
modify gene expression in dopamine neurons, and that
female individuals have an increased DAT density
compared with male individuals, examples of the biology that may underpin this phenomenon.75,76
Several studies have demonstrated that cigarette
smoking reduces the risk for development of PD. Data
further suggest that the reduced risk may be dose dependent and may occur with noncigarette tobacco.77
Interestingly, among PD patients, there is some suggestion that cigarette smokers have an increased risk for
development of dementia compared with nonsmokers.78 Use of coffee or caffeine also reduces risk for PD
in several studies,79,80 raising the possibility that adenosine receptors may be a disease and a therapeutic target for PD.81 In other studies, use of nonsteroidal antiinflammatory medication tends to reduce PD risk,
whereas dietary lipid and milk consumption may increase risk.17,82,83 Environmental exposures including
pesticide use may increase risk for PD, but the specific
toxicants have not been established.84,85 Increased
plasma urate levels are also associated with reduced risk
for PD, consistent with the hypothesis that the antioxidant activity of urate may modify PD risk.86
Marek et al: Biomarkers for PD
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Several clinical signs and symptoms associated with
PD such as loss of olfactory function, sleep disturbances such as rapid eye movement behavior disorder,
autonomic dysfunction including constipation, and behavioral and cognitive changes may occur before the
typical motor symptoms of PD.53 These clinical features may be more accurately considered early features
of PD rather than biomarkers. These PD-associated
clinical features are most often not caused by dopamine
loss but may involve pathology in norepinephrine, serotonin, cholinergic, or other neuronal systems. Biomarkers for these nondopaminergic early PDassociated clinical manifestations have begun to
emerge. For example, cardiac imaging with metaiodobenzylguanidine may identify early norepinephrine
dysfunction in autonomic neurons,87,88 whereas serotonin dysfunction may identify PD patients with depression.89 Several studies have begun to combine early
nonmotor clinical PD with imaging and/or blood and
CSF biomarkers to enrich populations at risk for
PD.40,90
PD diagnostic biomarkers are a subset of risk markers that may be used to assist in the clinical diagnosis
of PD in individuals with clinical manifestation of disease but without clinical features that meet a clinical
definition of disease.91 PD diagnostic markers have focused on brain imaging using radiolabeled tracers for
positron emission tomography and single-photon emission computed tomography and on nigral ultrasound.
Nigral ultrasound studies have demonstrated hyperechogenicity in early PD compared with healthy subjects, with the caveat that about 10% of subjects cannot be adequately studied.92 Several dopaminergic
tracers including F-dopa, many DAT ligands, and the
vesicular transporter (VMAT2) can distinguish PD
subjects from healthy subjects or subjects with essential
tremor or other nondopaminergic disorders.93–95 Most
recently, two studies have directly assessed the accuracy
of imaging in PD diagnosis. In these studies, the
QUERY and CUPS studies, the accuracy of DAT imaging was examined in subjects with possible but not
definite PD.96,97 Imaging was compared with a longitudinal “gold standard” clinical diagnosis. These studies demonstrated that those individuals with a reduction in DAT density were at high risk for a clinical
diagnosis of PD. DAT imaging marketed as Datscan is
available as a diagnostic marker in several countries
in Europe. Importantly, these imaging markers cannot distinguish between idiopathic PD and other
parkinsonisms such as progressive supranuclear palsy,
multiple system atrophy, cortical basal ganglionic degeneration, and diffuse Lewy body disease. Fluorodeoxyglucose imaging to assess metabolic anatomy may
be more useful in distinguishing PD from related Parkinson’s syndromes.98
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Progression Markers
Progression markers for PD are both a critical need
and as yet an unmet need. Although risk markers may
provide valuable insight into disease cause, tools for
disease diagnosis, and clues to new therapies, validated
biomarkers of disease progression are necessary to monitor the natural history of PD and to assess therapies
that may modify disease progression.
Although no fully validated progression biomarker
has been developed, several risk biomarkers have been
tested in PD progression studies. For example, imaging
studies have indicated that nigral ultrasound hyperechogenicity and microglial activation as measures of
neuroinflammation do not appear to change with disease progression.19,99 However, other studies have
identified biomarkers such as ␣-synuclein, increased
plasma urate, and imaging measures such as DAT density that may track disease. There are little direct data
that ␣-synuclein is a progression marker, but the agerelated changes in ␣-synuclein and with PD severity
suggest that it may be possible to measure change as
PD progresses.26 Recent assessment of two large PD
clinical trials has demonstrated that increased urate
may be associated with slowed disease progression in
addition to reduced risk for development of PD.100
Imaging tracers targeting presynaptic nigrostriatal
function have been the most widely used biomarker to
assess PD progression. Most of these studies have used
either F-dopa or DAT tracers to monitor dopaminergic
degeneration.101–108 Dopamine ligands are useful to
assess PD in so far as they reflect the ongoing dopaminergic degeneration in PD. In the study most directly
correlating changes in dopamine pathology and imaging outcomes, there is good correlation between dopamine neuron loss and F-dopa uptake, although conclusions are limited by a small sample size of only five
subjects.109 Numerous other studies have shown that
the DAT density is reduced in striatum in postmortem
brain from PD patients.110 –112 In turn, numerous
clinical imaging studies have shown reductions in
F-dopa, VMAT2, and DAT ligand uptake in PD patients and aging healthy subjects consistent with the
expected pathology of PD and of normal aging. Specifically, these imaging studies demonstrate asymmetric, putamen⬎caudate loss of dopaminergic uptake,
and the imaging loss correlates with worsening clinical symptoms in cross-sectional evaluation.105,113–117
In addition, DAT ligands demonstrate reductions in
activity with normal aging.74,118,119
In longitudinal studies of PD progression, F-dopa,
VMAT2, DAT (␤-CIT and CFT), and fluorodeoxyglucose using both positron emission tomography and
single-photon emission computed tomography have
demonstrated an annualized striatal rate of reduction of
about 4% to 13% in PD patients compared with 0%
to 2.5% change in healthy control subjects.36,44,120 –126
Evidence from studies of hemi-PD patients provides
further insight into the rate of progression of disease.
In early hemi-PD, there is a reduction in F-dopa,
VMAT2, and DAT of about 50% in the affected putamen and of 25% to 35% in the unaffected putamen.
Because most patients will progress clinically from unilateral to bilateral in 3 to 6 years, it is, therefore, likely
that the loss of these in vivo imaging markers of dopaminergic degeneration in the previously unaffected putamen will progress at about 5% to 10% per annum.106,116,127,128
DAT and F-dopa imaging have been used to assess
the effects of possible disease-modifying drugs in several clinical trials. However, several caveats limit the
interpretation of these imaging data.55,56 There has
been concern that the drug under testing or concomitant symptomatic medications might directly regulate
the imaging outcome so that it would not be a true
measure of disease progression. Although recent studies
demonstrating that the most common symptomatic
medications (L-dopa and dopamine agonists) do not
have a short-term regulatory effect on DAT imaging
increase confidence in DAT imaging as a measure of
progression,57 nonetheless, future imaging studies must
include an assessment of the short-term effect of the
test drug on the imaging outcome. A second caveat for
imaging studies of disease progression has been the inconsistent correlation of changes in imaging outcomes
and clinical outcomes in these clinical trials. The lack
of clinical–imaging correlation may be explained because these outcomes reflect different aspects of the disease (imaging: a physiological measure of dopamine
presynaptic function; clinical: a functional measure of
disability). Therefore, imaging and clinical outcomes
may best be considered complementary rather than
correlative. Many clinical outcomes may be also confounded by symptomatic medications, further complicating the correlation of clinical and imaging outcomes
once symptomatic treatment has begun. In summary,
the studies of dopaminergic imaging as a tool for disease progression have provided useful and important
data but have also highlighted the difficulties in validating a progression marker and the as yet unmet need
for additional tools to more fully and reliably assess
disease progression.
A Plan for Developing Progression Biomarkers
Given the recent advances in molecular genetics, neurobiology, imaging technology, and radiochemistry that
have provided new tools that may be useful PD biomarkers and the recognition that the lack of PD progression biomarkers has created a roadblock for further
studies of disease-modifying therapies, there is increasing consensus that a major initiative to develop PD
progression biomarker is both necessary and feasible.
The goal of this biomarker initiative would be to create
a consortium of academic centers, government agencies, PD foundations, and pharmaceutical and biotechnology companies to collectively design, implement,
and fund a comprehensive program to develop markers
of PD progression. This strategy has been successfully
employed by a consortium of Alzheimer’s disease reTable 2. Clinical Markers and Biomarkers
Associated with Parkinson’s Disease
Clinical Markers
Cognition
Affective
Depression
Apathy
Anxiety
Autonomic
Constipation
Bladder
Sexual
Cardiac
Olfaction
Sleep: RBD
Skin
Motor analysis
Speech
Biomarkers for PD
Imaging Phenotomics
SPECT/PET: dopamine, DAT, F-dopa, VMAT
SPECT/PET: nondopamine, FDG, MIBG, targets
for NE, 5-HT, A2a, nicotine
MRI: spectroscopy
Functional MRI
Nigral ultrasound
Genetics
Synuclein, LRRK2
Parkin DJ-1, Pink1
CSF, blood
Proteomics
Transcriptomics
Metabolomics
PD ⫽ Parkinson’s disease; SPECT ⫽ single-photon emission
computed tomography; PET ⫽ positron emission tomography;
DAT ⫽ dopamine transporter; VMAT ⫽ vesicular transporter;
FDG ⫽ fluorodeoxyglucose; MIBG ⫽
metaiodobenzylguanidine; NE ⫽ norepinephrine; 5-HT ⫽
5-hydroxytryptamine; MRI ⫽ magnetic resonance imaging;
CSF ⫽ cerebrospinal fluid; RBD ⫽ rapid eye movement
behavioral disorder.
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searchers to create the Alzheimer’s Disease Neuroimaging Initiative, a group that has now organized infrastructure and developed a research cohort to examine
progression biomarkers.
To minimize costs and time, a PD progression biomarker consortium could utilize both existing and developing clinical PD cohorts at different stages of PD
to create a mosaic of PD patients from premotor to
newly diagnosed to treated PD. The plan will be to
develop a comprehensive, focused, and collaborative
strategy to test and validate biomarkers of PD progression utilizing these cohorts. Progression markers at various stages of validation can be examined, and a mechanism to test novel biomarkers in well-characterized
clinical cohorts would be initiated.
Technologies including neuroimaging modalities,
biochemical markers in the CSF and plasma, and genetic markers, as well as clinical evaluation, will be investigated (Table 2). A major initial focus of the
biomarker consortium would be to standardize biomarker acquisition and assessment, and establish welldefined quantitative biomarker outcomes that are consistent among many research sites and laboratories. It is
likely that core laboratories for each biomarker would
be identified.
Although this approach to biomarker development is
costly and requires cooperation among many individuals in academics, industry, and government, the lack of
success of recent disease-modifying therapeutic trials
coupled with the huge expense of these studies has
highlighted the need for such an ambitious approach
to identify and validate biomarkers of PD progression
for future clinical studies of disease-modifying drugs.
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