Parkinson’s Disease

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra and striatum.  These dopaminergic neurons are involved in reward pathways and the control of movement, specifically fine tuned movement.  The reduction of these neurons is most notably seen in the tremors that PD subjects experience.  As the disease progresses, control of movement diminishes, tremors increase, and many individuals begin to experience an associated Parkinsonian dementia similar to that seen in Alzheimer’s disease patients.  Until recently, PD also increased the mortality rate of patients three times that of normal age-matched subjects (Dauer & Przedborski, 2003).
    Despite precise descriptions of the disease dating back to the early 19th century, there is still very little known about what causes PD in the majority of the population.  Due to this lack of understanding, investigators have divided PD into two broad categories based on the development of the disease: genetic (familial) and sporadic.  Genetic PD occurs in about 5% of all patients, the other 95% having an apparently non-genetic form (Liu, Gao, & Hong, 2003).  The most obvious differences between the familial and sporadic forms of PD is that familial PD has a much earlier age of onset and a faster rate of progression than does sporadic PD. However, familial PD does offer a benefit to science.  Due to the genetic nature of familial PD, the identification of genes that are involved in the development of the disease can allow for in vitro models and transgenic animal models for experimentation and study of what leads to the symptoms of PD.
    There are two well-characterized genetic mutations that lead to familial PD and have been observed in sporadic PD: mutations of the a-synuclein gene and the parkin family of proteins.  a-synuclein is a prevalent presynaptic protein that has been implicated in vesicular trafficking and may also play a role in dopamine biosynthesis.  Mutations in the a-synuclein gene lead to dysregulation of this protein and the accumulation of a-synuclein.  One of the major physiological markers of PD is the formation of Lewy Bodies, and a-synuclein aggregation is believed to be responsible for the formation of these proteinaceous inclusions (Katsuse, Iseki, Marui & Kosaka, 2003).  It is unclear what role the Lewy Bodies play in PD, but they do not appear in healthy individuals and are present in other neurodegenerative conditions.  There are four known mutations of the a-synuclein gene that lead to genetic PD: 3 point mutations (Ala53->Thr, Ala30->Pro, and Glu46->Lys) and repeat mutations that cause overexpression of the protein.  The other proteins implicated in protein aggregation are the parkin genes.  Unlike a-synuclein, it is a deletion mutation in these genes that leads to familial PD.  The role of parkin genes is unclear, but they may help rescue function of the ubiquitin proteasomal system that is intended to regulate a-synuclein (Dawson & Dawson, 2003).  When a-synuclein aggregates, the ubiquitin proteasomal system is unable to break down the misfolded protein, leading to further aggregation. 
    Alpha-synuclein aggregation is not limited to familial PD.  Individuals who originally produced healthy a-synuclein have nevertheless developed PD and the comorbid a-synuclein protein aggregates (Raichur, Vali, and Gorin, 2006).  Since improper a-synuclein expression is not limited to individuals with a genetic predisposition, then there are other factors involved.  It is possible that there are genetic interactions about which we know nothing, but with the prevalence of PD in the population and the sequencing of the human genome, it is highly unlikely that these alternate genetic factors would not have been discovered.  This implies that there are environmental factors that can lead to PD.  The mean age of onset for PD is 55 years, and disease progression usually goes unnoticed for the first few years of disease-by the time symptoms appear, up to 60% of dopaminergic neurons in the substantia nigra have already been lost (Dauer & Przedborski, 2003).  Due to this delay, it will be difficult to positively identify any environmental factors that may have contributed to the development of the disease.  Furthermore, there is an increased risk for developing PD associated with age.  This essentially makes the hunt for environmental factors moot, as there are always a great deal of variables when trying to identify environmental causes of neurological diseases, particularly in diseases as prevalent and widespread as PD.
    Since identifying environmental causes of PD is beyond the grasp of current science (there are proposed risk factors, but these do not apply to the entire population), it makes sense to look at other possible factors involved in the development of the disease.  It is well established that cellular regulation of oxidative stress diminishes with age.  There are two factors that make the dopaminergic system particularly susceptible to oxidative stress: dopamine can undergo spontaneous auto-oxidation into toxic and reactive species (dopamine-quinones, superoxide free radicals and H2O2 (Adamczyk, Kazmierczak, & Strosznajder, 2006)), and the synapses of dopaminergic are densely populated with mitochondria.  In PD patients and animal models, it has been observed that mitochondrial complex I efficacy is diminished (Dauer & Przedborski, 2003).  Mitochondrial complex I is critical for regulation of oxidative species.  It has also been shown that synaptic mitochondria are more sensitive to stressors than somatic mitochondria, putting synapses at greater risk for oxidative stress.  There are a number of other potential physiological sources of oxidative stress, but none of these have been expressly implicated in PD.
    One of the emerging models of PD traces cellular malfunction to the mitochondrial complex I, the source for oxidative stress that leads to other deficits, such as a-synuclein aggregation (Raichur, Vali, and Gorin, 2006).  As more information is gathered regarding the development of PD and various mechanisms involved, it is becoming increasingly clear that Lewy bodies and a-synuclein aggregates may not be the cause of dopaminergic cell loss as previously believed. Induced a-synuclein aggregation was shown to have no toxic effects in the ventral tegmental area, another region of dopaminergic innervation, suggesting that there is something else in the substantia nigra and striatum that is inducing cell death (Maingay, Romero-Ramos, Carta, & Kirik, 2006).  In contrast to this result, a very recent study did find that a-synuclein levels in healthy individuals did increase with age, and these levels were directly correlated with decreased levels in staining intensity for tyrosine hydroxylase (a dopamine precursor) (Chu & Kordower, 2007).  In neural networks, if a cell is not being utilized, then it serves no purpose and an apoptotic cascade is initiated.  However, apoptosis was not investigated in this study and the authors proceed to implicate a-synuclein in PD pathology.  Although the hypothesis of the authors is nothing new, the fact that a-synuclein levels increase with age seems to explain the relatively late onset of the disease.  Understanding why a-synuclein levels are increased with age could be important to understanding the development of PD.  It is possible that the toxic nature of dopamine necessitates the increased levels of a-synuclein to regulate formation of dopamine.  However, if there are already reactive oxygen species affecting a-synuclein folding, this natural upregulation of a-synuclein expression would merely increase the formation of aggregates.  As noted by Chu and Kordower (2007), all of the subjects observed were healthy, showing that although TH levels may be decreased, the individuals were functioning normally and therefore a-synuclein should not be viewed as a target for treatment.  Reducing levels of endogenous a-synuclein could even inadvertently lead to increased pathology.
    Following this logic, oxidative stress should remain a target for treatment.  To date, the most successful treatment for PD has been injections of L-DOPA, a dopamine precursor.  Based on this logic, the treatment proposed by Chu and Kordower (2007) makes sense (it would increase dopamine production).  However, years of use have demonstrated that dopamine replacement is not a satisfactory treatment.  Patients receiving L-DOPA still experience neurodegeneration in the form of dyskenesias and develop resistance/tolerance to treatment (Kuno, 2006).  These results indicate that L-DOPA is merely treating the symptoms, not the underlying pathology.  In recent years, a number of new treatment strategies have emerged.  One of these is deep brain stimulation, which requires implanting electrodes and a battery similar to a pacemaker battery.  A different approach under investigation is identifying a method for increasing levels of a chemical naturally produced in the brain, glial cell line-derived neurotrophic factor (GDNF).

Glial Cell Line-Derived Neurotrophic Factor

GDNF is a molecule that was first identified as a potential treatment for PD in 1993 (Lin, et al., 1993).  It was in this paper that some of the first properties and physiological effects of GDNF were described.  The authors found that GDNF is a trophic factor that specifically exerts its effects on dopaminergic neurons, increasing dopamine uptake in TH+ immunolabeled cells by 2.5-3 times the uptake of untreated cells.  GDNF was also shown to increase neurite outgrowth and cell body size.  In individuals suffering from PD these results are encouraging, since they are signs of neural viability.  Increased cell-growth can also have negative effects, such as too many synaptic connections, which can be a risk factor for seizures.  The potential benefits of a treatment derived from GDNF brought to light by this study apparently outweighed the potential side effects, as there has been a surge of interest in furthering understanding of the mechanisms by which this protein operates.  A search of the ISI Web of Science® database using the topic keyword GDNF returns 2471 results, all following the release of the Lin, et al. (1993) study (which has apparently been cited in 1396 papers).
    The next major breakthrough regarding GDNF to reach print came four years later with the crystallization and x-ray determination of GDNF structure (Eigenbrot and Gerber, 1997).  The Lin, et al. (1993), study was able to provide some characteristics of the GDNF molecule, but the crystallography structure provided a much clearer picture of the folded state of the protein and the inter- and intramolecular forces at work.  To begin with, GDNF became the first member in a new family of neurotrophins.  This family is the transforming growth factor beta (TGF-b) superfamily.  One of the characteristics of this family is that there are seven cysteine residues in similar spacing to other members of the superfamily (Saarma, 2000).  These cysteine residues are very important as they lead to the creation of inter- and intra-protein disulfide bridges in a very constricted area leading to the formation of a cysteine knot (Figures 1 and 2) and covalently bonding two units of the protein to create the biologically active homodimeric unit (Eigenbrot and Gerber, 1997).  GDNF has a ‘fingers’ region (2 fingers) consisting of b-sheets and an abrupt crossover in the finger 2 b-sheet.  The finger 1 region consists of continuous b-strands with a single turn about a 310 helix followed by a turn and an extended stretch that leads to the next b-strand (Figure 3).  When compared to TGF-b2 and OP-1 (other members of the TGF-b superfamily), there is a one-residue insertion in the finger 2 crossover (Figure 4), which coupled with the presence of the His126 residue creates a greater separation between the fingers than that seen in TGF-b2.  This separation exposes the His126 residue to solvent, leading to the formation of a hydrogen bond to a water molecule (Figure 5).
    GDNF has a very structured segregation of charged regions (Eketjäll, Fainzilber, Murray-Rust, & Ibáñez, 1999).  There is a ‘continuous belt’ of net positive charge across the middle of the dimer (Figure 6).  In contrast, there is a patch of negative electrostatic potential localized in the finger regions of each protein unit (Figure 7).  There is also a section of highly exposed hydrophobic residues located in the tip of the second finger of each unit (not shown).  The segregation of these charged residues is believed to be critical to the function of GDNF.

GDNF, GFRa1 and Ret Complex

There is no known independent function of GDNF.  What is known is that GDNF signals through the formation of a complex with GFRa1 and Ret to initiate downstream effects.  More recent studies have shown that GDNF must first bind to GFRa1 and then to the Ret protein (Amoresano, et al., 2005).  This study investigated the binding characteristics of the GDNF-GFRa1-Ret complex.  The results showed that the GFRa1 region 191-197 is directly joined to the 125-134 region in the C-terminal area of GDNF, although another means of analysis showed that there were a number of other potential binding sites.  An earlier targeted mutation study showed that the binding of GDNF to GFRa1 may also occur at the location of the hydrophobic residues on the finger of GDNF, although the corresponding binding site on GFRa1 is not discussed (Eketjäll, et al., 1999).  Another mutational study showed that there are two clusters of residues located on the GFRa1 protein necessary for binding to GDNF and activation of Ret phosphorylation (Wang, et al., 2004).  These residues are 152AsnAsn153 and 316SerAsnSer318.  However, this article does not attempt to propose the corresponding residues necessary for binding on GDNF.  Amoresano and colleagues (2005) attempt to incorporate the earlier findings of Eketjäll and colleagues (1999) into their results (also Leppänen, et al., 2004, Figure 8).  They note that the region 125-134 in the C-terminal domain of GDNF identified in their study is a region neighboring the negatively charged finger region implicated in GDNF-GFRa1 binding observed six years earlier.  Although the mechanism for the binding of GDNF to GFRa1 has not been clearly identified, there is an observed increase in binding affinities when Ret is present, possibly the result of conformational changes that lead to contact between the 91-97 region of the GFRa1 molecule and the N-terminal region (1-37) of GDNF (Amoresano, et al., 2005).  This N-terminal region is unstructured in the crystallized state, but upon binding, it may gain stability and a structured form providing the added stabilization observed when the complex is completed.

Support for GDNF as a Treatment for Parkinson’s Disease

It has been a decade since the first study connecting GDNF to activation of the Ret receptor was published (Worby, et al., 1996), and this is still the only known mechanism by which GDNF can exert its effects.  GDNF initiation of the Ret receptor causes autophosphorylation of tyrosine residues, inducing activation of a large number of pathways (see Figure 9) (Ichihara, Murakumo & Takahashi, 2004; Li, et al., 2006).  RET has been shown to activate CREB, NFkB, and JNK pathways as well as upregulate intracellular cAMP levels.  With the exception of the JNK pathway, which can result in cell survival or programmed cell death, the changes caused by Ret activation (at least those mentioned) all promote cell survival.  Furthermore, Ret, in combination with GDNF, has been shown to increase expression of dopamine transporters (DAT), but this complex has no effect on levels of TH positive cells (Li, et al., 2006).  This suggests that the GDNF-GFRa1-Ret complex does not contribute to cell proliferation, but by increasing DAT levels it may lead to improved cell-cell communication and enhanced rates of clearing unused dopamine from synaptic clefts.  This could then account for some of the apparent antioxidant effects observed in relation to GDNF activity.
    One study expressly looked at whether or not GDNF had a neuroprotective function in regards to oxidative stress.  Saavedra and colleagues (2006) investigated GDNF activity in vitro following selective injury to nigral dopaminergic neurons caused by H2O2 and L-DOPA.  L-DOPA was chosen because there is evidence suggesting that this treatment for Parkinson’s disease may lead to an overabundance of dopamine, which causes oxidative stress when broken down by monoamine oxidase.  Cultured cells were exposed to media, 100 mM H2O2, or 200 mM L-DOPA to induce dopaminergic cell-specific damage. In response to this damage, real-time PCR showed that GDNF mRNA is significantly upregulated for 1 hour in H2O2 treated cells and for up to 3 hours in L-DOPA treated cells, while protein levels are increased in both conditions for up to 24 hours.  When GDNF activity was inhibited by antibody neutralization, TH staining revealed a 23% loss of dopaminergic neurons in response to H2O2 treatment compared to samples in which GDNF activity was not neutralized, demonstrating that GDNF acts to prevent the negative effects of reactive oxygen species (ROS) outside of those caused by excess dopamine levels.
    In another study Onyango, Tuttle, and Bennett Jr. (2005) investigated the method by which this protection against oxidative species is achieved using cytoplasmic hybrid cells (cybrids).  These cells were generated using SH-SY5Y cells populated with mitochondria containing platelet mtDNA from Parkinson’s disease patients (PD cybrids) and healthy individuals (CNT cybrids).  These cells show a number of characteristics similar to Parkinson’s disease, including (but not limited to) enhanced cleavage of the native form of poly-ADP ribose polymerase (PARP), increased susceptibility to oxidative damage, and glutathione deficiency.  PARP is a DNA repair enzyme that leads to caspase 3 induced apoptosis when degraded.  Treatment of the PD cybrids with GDNF blocked PARP degradation, preventing caspase 3 induced apoptosis.  This study also showed that GDNF application can help maintain levels of glutathione, a potent endogenous antioxidant that is significantly diminished in PD.
    Finally, GDNF not only protects cells in vitro from oxidative damage, but can also restore previously damaged motoneurons in vivo.  Parsadanian and collegues (2006) used a transgenic mouse model overexpressing GDNF to investigate neurorestoration.  To this effect, the right facial nerve was avulsed under traction and the stump resected. Whereas WT subjects showed avulsed motoneuron survival rates of 44.7% at 2 months and 29.5% at 4 months compared to the control, the mice overexpressing GDNF had avulsed motoneuron survival rates of 98.7% at 2 months and 99.3% at 4 months compared to the control.  The authors then went on to investigate the causes of this observed result and found that c-Jun, previously thought to be involved in an apoptotic pathway, actually aided in the observed neurorestoration.
    After years of successes in animal models, GDNF treatments have recently moved to clinical trials.  A phase I trial published in 2003 that employed chronic infusion of GDNF directly into the putamen showed promising results (Gill, et al., 2003).  However, it is hard to generalize the results due to the small sample size (5 individuals), and although apparently mild, there were a number of side effects to the treatment.  Despite the drawbacks of the study, at the one-year check in, there was a 61% improvement in the activities of daily living, 64% reduction in medication induced dyskenesias, and PET scans revealed a 28% increase in dopamine uptake.  While these results are promising, a number of more recent studies have yielded disappointing results.  One of these disappointing results comes from Amgen, who discontinued its phase 2 trials of a GDNF based PD therapy due to concerns about patient health.  Controlled alteration of neural functions is still an imprecise science and understanding the problems experienced with GDNF treatment may be discouraging, but there is potential to be harnessed from GDNF.  The majority of scientific findings have shown that GDNF treatment can have very positive results–it is only a matter of determining how to apply this knowledge to humans that is holding us back.