International Journal of Alzheimer’s Disease

International Journal of Alzheimer’s Disease / 2011 / Article
Special Issue

Biomarkers for Dementia

View this Special Issue

Review Article | Open Access

Volume 2011 |Article ID 842475 |

Gilbert J. Ho, Willie Liang, Masaaki Waragai, Kazunari Sekiyama, Eliezer Masliah, Makoto Hashimoto, "Bridging Molecular Genetics and Biomarkers in Lewy Body and Related Disorders", International Journal of Alzheimer’s Disease, vol. 2011, Article ID 842475, 18 pages, 2011.

Bridging Molecular Genetics and Biomarkers in Lewy Body and Related Disorders

Academic Editor: G. B. Frisoni
Received30 Dec 2010
Accepted20 Apr 2011
Published03 Jul 2011


Recent advances have been made in defining the genetic and molecular basis of dementia with Lewy bodies (DLBs) and related neurodegenerative disorders such as Parkinson's disease (PD) and Parkinson's disease dementia (PDD) which comprise the spectrum of “Lewy body disorders” (LBDs). The genetic alterations and underlying disease mechanisms in the LBD overlap substantially, suggesting common disease mechanisms. As with the other neurodegenerative dementias, early diagnosis in LBD or even identification prior to symptom onset is key to developing effective therapeutic strategies, but this is dependent upon the development of robust, specific, and sensitive biomarkers as diagnostic tools and therapeutic endpoints. Recently identified mutations in the synucleins and other relevant genes in PD and DLB as well as related biomolecular pathways suggest candidate markers from biological fluids and imaging modalities that reflect the underlying disease mechanisms. In this context, several promising biomarkers for the LBD have already been identified and examined, while other intriguing possible candidates have recently emerged. Challenges remain in defining their correlation with pathological processes and their ability to detect DLB and related disorders, and perhaps a combined array of biomarkers may be needed to distinguish various LBDs.

1. Introduction

Over the past decade, dementia with Lewy bodies (DLBs) has arguably become the second most common form of neurodegenerative dementia behind Alzheimer’s disease (AD). In addition to progressive decline in cognition, DLB is characterized by fluctuations in cognition with variations in attention and alertness, recurrent formed visual hallucinations, visuospatial dysfunction, and spontaneous parkinsonism. Often, DLB patients also exhibit neuroleptic sensitivity, transient loss of consciousness, falls, and rapid eye movement (REM-) sleep behavior disorder [1]. The clinical separation of DLB from other similar disorders is often difficult resulting in poor diagnostic accuracy, but the relative temporal co-occurrence of parkinsonian features with the typical DLB cognitive and behavioral symptoms such as visuospatial disturbance strongly suggests the diagnosis. Clinical presentation of DLB is also influenced by the amount of AD tau pathology, further complicating the diagnosis [2]. Approximately 20–40% of Parkinson’s disease (PD) patients also eventually develop a progressive dementing illness designated as Parkinson’s disease dementia (PDD) characterized by a frontal-subcortical clinical presentation [3]. DLB/Diffuse Lewy body disease (DLBD), Lewy body variant of AD (LBV), and PDD comprise an emerging spectrum of clinical phenotypes from relatively pure motor PD to the more predominant cognitive and behavioral disturbance observed in PDD and DLB, yet the reason for the variability remains unknown. Despite the heterogeneity of their clinical phenotypes, a significant neuropathological overlap is observed among these diseases, hence the term “Lewy body disorders” (LBDs) to collectively describe conditions in which Lewy bodies (LBs) and Lewy neurites (LNs) predominate as the hallmark histological lesions. Variation in the distribution of Lewy body pathology is present among LBDs, with more neocortical and limbic system LB in both DLB and PDD compared to the brains of PD patients without cognitive symptoms and greater neuronal loss in substantia nigra in PDD than DLB [4]. Yet, DLB and overlap disorders such as LBV, more so than PDD, have β-amyloid pathology and basal forebrain cholinergic deficit similar to AD patients [5].

As with other forms of dementia, the pathobiological changes in LBD likely occur decades prior to the onset of clinical symptoms and correspond to widespread irreversible neurodegeneration [6, 7]. It is increasingly clear from the AD therapeutic experience that by the time widespread neuronal injury ensues, symptomatic cholinergic treatments are minimally effective at best, and disease-modifying therapeutic approaches in trials have thus far proven ineffective at altering disease course or in rescuing diseased brain [8, 9]. To demonstrate efficacy, any potential disease-modifying therapy in neurodegenerative dementia must be initiated prior to the expression of the clinical phenotype during the initial molecular pathogenetic events before irreversible neuronal damage has occurred. At present, accurately predicting those individuals at risk for developing neurodegenerative dementia is challenging, and this places greater urgency on developing earlier methods of disease detection. Critically important is not only distinguishing the LBD from AD and other forms of dementia, but also separating DLBs and other LBDs. Although there are many promising candidates for LBD, no biomarkers have yet been validated for clinical diagnostic use, and thus many opportunities exist to develop such tests. Here, we highlight from the perspective of how major genetic discoveries in the LBD and their corresponding biomolecular processes might translate into useful disease markers in biological fluids. Because of many common pathogenetic features among the LBDs, the emerging genetic influences found in PD have readily been translated to DLBs and other LBDs, providing clues to rational approaches for selecting future DLB and LBD biomarker targets for exploration. This paper will highlight several PD and DLB genes and their protein products as candidates for biological disease markers (Table 1).

Biochemical markerGene defectRelevance to LB disordersSource of biomarker

AD lesionsAβAPP: K670M/N671L and so forth. PS1: H163R and so forth PS2: N141I and so forthDeposited in plaquesCSF, plasma
TauTauopathy: P301L, N279K, K317M, and so forthFound in NFT in AD brain, released after neuronal damageCSF

PD/DLB lesionsα-synuclein
A53T, A30P (PD), G209A (DLB), E46K, triplication (PD & DLB)Mutation → ↑ α-syn aggregation.
LB component, toxic oligomers and protofibrils
CSF, skin cells, platelets
β-synucleinP123H, V70M (DLB)Inhibit α-syn aggregation: mutant causes degenerationCSF
γ-synucleinSNP in DLBDAmyloidogenic: affects neuronal and axonal cytoskeletonVentricular CSF

oxidative stress
Parkin (PARK 2)K161N, W453Stop, 202-203delAG, M192L, K211N, and so forthUbiquitin E3 ligase, LOF mutation in PD alters mitophagyND
UCHL-1 (PARK 5)I93M, S18Y (SNP)Neuronal deubiquitinating hydrolase; impaired synaptic and cognitive function in AD & PDND
PINK 1 (PARK 6)A168P, A217D, E417G, E240K, and so forth (PD)Mitochondrial serine/threonine kinase; LOF mutation in PD alters mitophagyND
DJ-1 (PARK7)M26I, D149A, G78G, R98Q (PD), L166P (PD & DLB)Redox-dependent chaperone; LOF mutation in PDCSF, plasma
LRRK2 (PARK 8)G2019S, duplication, triplication (PD)Gain of function mutant in PD?DLB: interacts with α-syn and tau, and with parkin in apoptotic cell deathND

CytoskeletalNFNEFM (PD)Disrupted NF → abnormal axonal transport; released in cell damageCSF

Lysosomal dysfunctionGBA84 dupl G, IVS 2 + 1, N370S, L444P (PD)Gaucher’s disease, abnormal lysosomal function/autophagy in PDCSF, plasma

InflammationIL-1α, IL-1β, IL-6, TNFαSNP: IL-1β −511,TNF-α −308α-syn-induced microglial activation → ↑ secretion of neuroinflammatory mediatorsCSF

CSF: cerebrospinal fluid; GBA: glucocerebrosidase; Aβ: β-amyloid; NF: neurofilament; ND: not yet determined; PD: Parkinson’s disease; DLB: Dementia with Lewy body; UCHL1: ubiquitin carboxy terminal hydrolase L1; PINK 1: PTEN-induced putative kinase 1; LRRK2: leucine-rich repeat kinase 2; LOF: loss of function; SNP: single nucleotide polymorphism.

2. Amyloid and Tau in Lewy Body Disorders

2.1. Amyloid Genetics and Biomarkers in LBD

Aβ, a key component of neuritic plaques in AD brain, is overproduced leading to various degrees of amyloid aggregation and synaptic and neuronal toxicity [10]. As indicated previously, amyloid pathology in the form of neuritic and diffuse plaques can be also found in varying degrees in the brain tissue of patients with DLB, which may interact with LB or synuclein pathology or influence the clinical features of LBDs [4, 11]. The genetic mechanisms of Aβ overproduction in AD are well established; the βAPP gene (chromosome 21), the first identified AD susceptibility gene, encodes a transmembranous protein ranging from 695 to 770 residues, which undergoes a process of regulated intramembranous proteolysis ultimately releasing Aβ peptides, primarily Aβ42 and Aβ40, as well as other fragments. Aβ is generated by the concerted action of β-secretase and γ-secretase complex, while the α-secretase pathway precludes Aβ formation by cleaving βAPP at a site within the Aβ sequence. Genetic analysis of early-onset familial AD cases revealed numerous mutations in the βAPP gene as well as presenilin 1 (PS1; chromosome 14) and presenilin 2 (PS2; chromosome 1) genes, all of which accelerate the processing of βAPP, leading to increased Aβ generation [12]. Specifically, the βAPP KM670/671NL (Swedish) mutation affects the β-secretase site, A692G (Flemish) mutation alters the α-secretase site, and both V717F (Indiana) and V717I (London) mutations affect the γ-secretase processing, leading to elevated Aβ levels. Also important in the Notch developmental signaling pathway which is analogous to βAPP processing, the presenilins are thought to be a component of the γ-secretase enzyme complex, which suggests that missense mutations in the presenilins mechanistically lead to accelerated βAPP processing to Aβ [13].

Therefore, the abnormal proteolytic cleavage of βAPP leads to elevated brain Aβ deposition, and as a result, diminished peripheral levels of Aβ. Reflecting a shift from soluble Aβ to insoluble brain deposits, significant decreases in CSF Aβ42 levels have been demonstrated in AD and more recently in DLB cases [14]. Parnetti et al. found that DLB, compared with PD, PDD, and AD patients, showed the lowest CSF levels of Aβ42 and, when combined with CSF tau, differentiated DLB from PD and PDD, but not from AD [15]. Also, Spies and colleagues showed a greater decrease in Aβ40 in clinical DLB and vascular dementia patients compared with control levels and even with AD. Differentiation of non-AD dementias such as vascular dementia and DLB was improved by comparing the ratio of Aβ42 and Aβ40 [16]. More recently, the detection of amyloid in dementia patients has been greatly enhanced by the use of amyloid-binding agents such as Pittsburgh compound B [17], which also demonstrated amyloid burden in DLB. An Australian study reported more variable cortical PiB binding in DLB patients than in AD [18], whereas a subsequent examination of PiB binding in LBDs including DLB, PDD, and PD, compared with AD and normal patients, showed higher amyloid burden in DLB and AD than in PDD, PD, or NC patients [19]. Amyloid load was highest in LBD patients in the parietal and posterior cingulate regions, corresponding to visuospatial impairments on neuropsychological testing, suggesting that amyloid deposition could partly contribute to the clinical presentation of LBDs.

2.2. Tau Genetics and Biomarkers in LBD

Mutations in the tau gene on chromosome 17 may also present with phenotypic features of PDD or DLB, but they differ pathologically from these disorders in that LBs are generally absent [20]. Tau-bearing neurofibrillary tangles remain one of the pathological hallmarks of AD but are also central to a diverse group of disorders termed “tauopathies” which include progressive supranuclear palsy, corticobasal ganglionic degeneration, frontotemporal dementia (FTD) with parkinsonism linked to chromosome 17, and other disorders [21]. Tau is a microtubule binding protein, which acts to stabilize tubulin polymerization in microtubules critical for axonal cytoskeletal integrity and function. In disease, tau protein truncation at Glu 391 or hyperphosphorylation causes microtubule destabilization and aggregation of unbound tau into paired helical filaments (PHFs) leading to characteristic tangle formations [22]. Unlike the tauopathies, no direct pathogenetic tau mutations have been identified in LBDs, but tau pathology appears to be a consistent feature among neurodegenerative dementias including AD and LBDs, and given the pathological overlap, they might share similar pathogenetic pathways (reviewed in Stoothoff and Johnson) [23]. The Ser/Thr kinase and glycogen synthase kinase-3β (GSK3β), in concert with other molecules such as fyn kinase, normally regulate tau function but with aberrant activation accelerate the hyperphosphorylation of tau in neurodegenerative disease. Similarly, the cell cycle family kinase and cyclin-dependent kinase 5 (Cdk5/p35), active during normal brain development and involved in regulatory tau phosphorylation during mitosis, may also contribute to PHF formation.

Consequently, both total tau and hyperphosphorylated forms have been widely investigated and detected in CSF, but not serum, by enzyme-linked immunosorbent assay methods. In the differentiation of dementia types, Arai et al. initially reported elevated total CSF tau levels in AD but not in PD, but subsequently, they showed that total tau was also increased in DLB at similar levels to AD [24]. Yet, others have found differences for both total and phospho-tau (p-tau) in differentiating DLB from AD [25], and levels of total tau and p-tau 181 were significantly increased in autopsy-confirmed DLB patients [26]. In clinically diagnosed dementia cases, CSF p-tau 231 discriminated AD from non-AD dementias as a group, where levels were significantly higher in AD patients compared with DLB, FTD, vascular dementia, other disorders, and control subjects [27]. Separation of DLB from AD, however, was less robust, provided that CSF p-tau 231 levels were also increased in DLB. Clinically diagnosed DLB cases also showed elevated levels of CSF p-tau 181 compared with controls [28], and Hampel et al. reported that p-tau 181 provided the best discrimination of DLB from AD yielding a sensitivity of 94% and specificity of 64% [29]. In autopsy-confirmed DLB and AD patients, however, sensitivity decreased to 75% and specificity to 61%, with a diagnostic accuracy reported as 73% [30].

3. Synucleins: Genetics to Biomarkers in the Lewy Body Disorders

3.1. Pathogenetics of Synucleins in LBD
3.1.1. Functions of α-Synuclein

LBs are filamentous inclusions consisting primarily of the presynaptic protein α-synuclein (α-syn), which might have several roles in vivo. Studies demonstrate that it is localized to multiple neural tissues, including high expression in neocortex and hippocampus, and that expression increases during acquisition-related synaptic plasticity [31]. Interaction with tubulin suggests α-syn could be a microtubule-associated protein similar to tau [32, 33], and it is highly active in various membrane lipid bilayers such as in presynaptic vesicles acting as a chaperone for soluble NSF attachment protein receptor (SNARE) complex formation [34], in neuronal Golgi apparatus influencing protein trafficking [35] and in the inner membrane of neuronal mitochondrial [36]. The synucleins might act to preserve membrane stability, provide antioxidant function, and assist with membrane turnover, although the actual role of synucleins remains elusive [37, 38]. Because of its association with LB and the tendency to self-aggregate into pathological oligomers and ultimately fibrillar structures [39], α-syn plays a central role in the pathogenesis of LBD, hence the alternate designation “synucleinopathies.” The degree of α-syn immunoreactivity in cortical LBs correlates with cognitive severity and disease progression in PDD and DLB [4, 40]. Also, the protein can be recovered from filaments in purified Lewy bodies from PDD and DLB brain [41], and recombinant α-syn tends to form Lewy body-like fibrillar structures in vitro [42].

3.1.2. α-Synuclein Mutations in PD and DLB

In the past decade, tremendous advances have been made in understanding the genetic factors influencing the pathogenesis of Lewy body disorders. Compelling evidence for a genetic basis for PD and DLB followed the discovery of mutations in the α-syn gene (PARK1/4) in patients with autosomal dominant familial Parkinson’s disease, and subsequently, mutations were identified in patients with both sporadic and familial DLBs. From a susceptibility marker on chromosome 4q21-23 that segregated with the PD phenotype in Italian and Greek kindreds, A53T [43] and A30P [44] were the first two missense mutations in α-syn associated with familial Parkinson’s disease. Clinical analysis of the Italian A53T mutation revealed phenotypic variability over the disease course with several individuals demonstrating moderate to severe dementia [45]. Subsequently, a case of clinically and pathologically well-characterized DLBD in the United States and a Greek proband of DLB with a family history of PD were both determined to have the A53T α-syn mutation [46, 47]. Another mutation, E46K, was discovered in a Spanish family presenting with autosomal dominant DLB [48], and in genetic studies of a large family with the spectrum of Lewy body phenotype ranging from PD to DLB, α-syn gene triplication was described, causing α-syn overproduction similar to the trisomy effect observed in Down syndrome patients [49].

Autosomal dominant point mutations are shown to affect the aggregative properties of α-syn, which has mechanistic implications for the pathogenesis of LBD. Compared to wild-type α-syn, biophysical analyses reveal that α-syn aggregation is folding state dependent, where A53T and A30P mutated proteins cause increased aggregation only from the partially folded intermediate state and not the monomeric state [50]. A53T α-syn transgenic mice have increased oligomerization of the protein in brain regions devoid of inclusions as well as those areas with more abundant lesions and neurodegeneration, and consistent with prior biophysical findings, α-syn toxicity in these mice was dependent on the conformation of intermediate species [51]. In fact, the E46K mutation, as well as the others not only increase the tendency toward aggregation, but also promote formation of annular protofibrillar structures, causes pore formation in various membranes and neuronal damage [52].

3.1.3. β-Synuclein Mutations in DLB

α-Syn is a member of a larger family of synuclein proteins which also includes β-synuclein (β-syn) and γ-synuclein (γ-syn). β-syn has recently been implicated in PD and DLB pathogenesis, but its precise role in disease is still emerging. Despite having strong homology with α-syn, it is not clearly amyloidogenic, but is highly localized to presynaptic sites in neocortex, hippocampus, and thalamus like α-syn [53, 54]. Normal β-syn may act as a biological negative regulator of α-syn. In bigenic α-syn/β-syn-overexpressing mice and in doubly transfected cultured cells, β-syn ameliorated amyloidogenicity, neurodegenerative changes, and motor deficits induced by α-syn overexpression alone [55]. On the other hand, mutated β-syn leads to neuronal damage and disease and augments neurodegeneration, perhaps through a loss of its natural regulator function. Two novel β-syn point mutations, P123H and V70M, were found in highly conserved regions of the β-syn gene in respective familial (P123H) and sporadic (V70M) DLB index cases [56], where abundant LB pathology and α-syn aggregation was present without β-syn aggregation. P123H β-syn overexpression in transgenic mice resulted in axonal damage, gliosis, profound memory, and behavioral deficits [57]. These phenomena may involve α-syn, since bigenic mice overexpressing α-syn with P123H β-syn show greater deficits compared with monogenic mice and compared with P123H β-syn expressed with α-syn knockout, implying that the P123H mutation has a synergistic effect with other synucleinopathies to cause neurodegeneration. P123H as well as V70M β-syn mutations might also injure neurons by disrupting normal lysosomal pathways and corresponding cellular autophagic processes [58].

3.1.4. Association of γ-Synuclein with LBD

Unlike the other synuclein family members, γ-syn or persyn is largely expressed in the cell bodies and axons of primary sensory neurons, sympathetic neurons, and motor neurons as well as in brain [59]. In cancer biology, γ-syn is associated with abnormally altering cellular mitotic checkpoints in various types of malignancies, making them more aggressively metastatic [60], but as far as neurodegeneration, it is the most recent synuclein member to be linked to LBD neuropathology and the least well understood. Single-nucleotide polymorphisms in all three synucleins have been associated with sporadic DLBD, most prominently γ-syn [61], and in sporadic PD, DLB, and LBV patients, γ-syn antibodies, as well as β-syn and α-syn reveal unique hippocampal axonal pathology [62]. In vivo, γ-syn overexpression in transgenic mice shows age- and dose-dependent neuronal loss throughout the neuraxis, especially in spinal motor neurons, where γ-syn-bearing inclusions, gliosis, and alterations in heat shock protein and neurofilament structure are found [63], perhaps suggesting relevance to motor neuron disease associated with dementia. In vitro evidence further supports a cytoskeletal role for γ-syn in maintaining neurofilament structure; γ-syn overexpression in cultured neurons causes disruption of the neurofilament network by destabilizing the structural integrity of neurofilament-H allowing degradation by calcium-dependent proteases, which has implications for neurodegeneration [64].

3.2. Synucleins as Biomarkers of LBD
3.2.1. Synucleins in the Extracellular Compartment

Synucleins are known as intracellular molecules, but they also appear in extracellular and peripheral fluids from active and passive processes. Evidence suggests that turnover and secretion of these proteins might occur during normal cellular processing, releasing synucleins into extracellular space and hence into peripheral sites. In transfected and untransfected cultured neuroblastoma cells, 15 kDa α-syn is released into surrounding media [65], and furthermore, not only monomeric α-syn but also aggregated forms are secreted in an unconventional exocytic manner into extracellular fluid in response to proteasomal and mitochondrial dysfunction [66]. Remarkably, Desplats et al. recently showed that neuronally secreted α-syn can also be taken in endocytically by other neurons or glia as a means of transmitting pathology [67]. Secreted α-syn interacts with various molecules such enzymes; in cultures, matrix metalloproteinase-3 cleaves native α-syn to smaller proteolytic fragments that enhance its aggregative properties [68]. Whether β-syn and γ-syn also undergo unconventional exocytosis and secretion remains unknown, but given structural and functional similarity to α-syn, the possibility exists. Certainly, synaptic and axonal damage reflecting neurodegeneration may also allow release of synucleins into the extracellular millieu and access to peripheral fluids such as CSF and blood.

3.2.2. α-Synuclein as a PD and DLB Biomarker

Multiple forms of α-syn are released into cerebrospinal fluid (CSF) and other biological fluids. Full-length α-syn has been recovered from lumbar CSF from living normal control, PD and DLB patients [69, 70], and also from postmortem CSF from DLB and other neurodegenerative diseases [71]. Comparative findings regarding differences in CSF α-syn levels among various neurodegenerative diseases, however, are difficult to interpret because of inconsistent observations. In PD, a smaller early study showed that no differences in full-length CSF 19 kDa α-syn have been found in relation to control individuals [69], but a recent effort using a new Luminex assay in a larger sample controlling for extraneous influences showed significantly decreased levels in PD compared to controls with 92% disease sensitivity and 58% specificity [72]. Elevated α-syn levels, however, were found in DLB, AD, and vascular dementia with no differences among them [71]. Perhaps more intriguing, higher-molecular weight aggregated α-syn species in CSF might be associated with PD and DLB. Reduced levels of a 24 kD α-syn-immunoreactive band were found in DLB CSF and correlated directly with declining cognition [73]. Moreover, using a specific enzyme-linked immunosorbent assay (ELISA), soluble aggregated α-syn oligomers in CSF were significantly increased in PD patients compared against control subjects, AD and progressive supranuclear palsy, and specificity ranged from approximately 85 to 87%, while sensitivity was about 53–75% range [74].

Plasma α-syn detected by immunoblotting was decreased in PD compared with age-matched control subjects, and those PD patients with age-at-onset prior to 55 years (early-onset) had significantly lower levels than those with onset after 55 years of age (late-onset) [75]. In addition, soluble oligomeric α-syn detected by specific ELISA was significantly elevated in plasma from PD. This test demonstrated a specificity of approximately 85%, a sensitivity of 53%, and a positive predictive value of 0.818 [76]. Although measurement of plasma α-syn appears interesting as a biomarker, it was reported that skin cells and platelets are also sources for α-syn, and their levels did not correlate with disease presence or severity [77]. Moreover, red blood cells are also a major source of α-syn [78], and thus, plasma could be contaminated by α-syn not originating from brain, which might render interpretation of results difficult. One promising consideration for the future exploration of α-syn as an LBD biomarker will be the development of novel imaging compounds and techniques, similar to amyloid imaging, to specifically target and visualize α-syn distribution in the PD and LBD brain. The availability of such methods will be a significant advance in biomarkers for synucleinopathies.

3.2.3. β-Syn and γ-Syn as Potential Biomarkers in Lewy Body Disorders

Due to their increasing importance in LBD pathogenesis, β-syn and γ-syn, as much as α-syn, might be excellent targets as peripheral markers of disease. As such, levels of these synucleins might be altered in the CSF of patients with PD/PDD and DLB, reflecting the underlying degenerative processes in brain. No studies to date have examined β-syn levels in peripheral fluids in relation to neurodegenerative disease, but a small study reported elevated postmortem ventricular CSF γ-syn levels in DLB, AD, and vascular dementia patients, with the highest levels seen in DLB patients [71]. More detailed examination of both β-syn and γ-syn as a peripheral disease markers in well-characterized populations of PD, DLB, and other disorders is warranted to determine their specificity and sensitivity in the synucleinopathies.

4. DJ-1 in the Lewy Body Disorders

4.1. Functional Role of DJ-1 in Lewy Body Diseases

Recently, DJ-1 (PARK 7) has emerged as a significant molecular target of interest in LBD principally because of its genetic association with PD and its increasing importance in cellular oxidative neuroprotection. Although its exact role is unknown, multiple functions have been assigned to the DJ-1 protein. Described by Nagakubo et al. as a mitogen-dependent oncogene involved in Ras-related signaling pathways [79], it shares structural homology with the carboxy-terminal domain of Escherichia coli HPII catalase and is reported to possess catalase activity which reduces oxidative stress in cultured cells [80]. It also binds to and regulates the PIAS SUMO-1 ligase and is itself posttranslationally modified by sumoylation [81, 82]. Of relevance to Lewy body formation and neurotoxicity, DJ-1 displays redox-dependent chaperone activity conferring proper protein folding and thermal stability, which in fact, also inhibits α-syn aggregation [80]. The overexpression of DJ-1 in rats protects nigral dopaminergic neurons against degeneration involving 6-hydroxydopamine, while mutant DJ-1 in mice causes abnormal dopamine reuptake and susceptibility to 1-methyl- 4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) toxicity [83]. Deletion of DJ-1 homologs in Drosophila renders them sensitive to H2O2, paraquat, and rotenone toxicity [84].

4.2. DJ-1 Mutations and Possible Relevance to LBD

No less than 13 gene mutations have been identified in DJ-1 in atypical younger-onset PD patients, but their significance to idiopathic late-onset PD remains uncertain. In autosomal recessive early-onset PD from consanguineous families, a complete DJ-1 deletion in a Dutch family and a point mutation L166P in an Italian case were identified [85]. When expressed in cultured cells, L166P appears to be a loss-of-function mutation which leads to DJ-1 functional instability, degradation by the proteasome system [86, 87], abnormal translocation of DJ-1 to mitochondria, and loss of chaperone activity [80]. The importance of DJ-1 gene alterations in dementia and DLB, however, is uncertain. One report found no impact on dementia risk of the DJ-1 14kb deletion [88], and analysis of an insertion/deletion variant (g.168_185del) in DJ-1 in a larger sample of patients also showed no association with either PD or DLB compared to control patients [89]. Given these early negative findings, the relevance of DJ-1 genetic mutations to DLB and other LBD is not known. At present, no patient harboring a DJ-1 mutation has come to autopsy, so the precise pathology is not known. Although DJ-1 mutant cases may ultimately not be LBDs, it is possible that alterations in DJ-1 may somehow influence the aggregation of α-syn and LB formation [80] or contribute to pathogenesis by other molecular pathways.

DJ-1 is found in brain across a wide range of neurodegenerative diseases including PD, FTD, AD, DLB, and LBVAD, and demonstrates striking association with neuropil threads and neurofibrillary pathology in neocortex and subcortical brain regions in these disorders [90]. Interestingly, this association with tau pathology was seen in DLB and LBV brains, suggesting that as a chaperone molecule, DJ-1 may be involved in tangle formation, and the binding of DJ-1 with these lesions could abolish the normally protective effect of DJ-1, enhancing oxidative neurotoxicity. Wang et al. observed that DJ-1 knockout mice have markedly abnormal hippocampal long-term depression accompanied by a less severe abnormality in long-term potentiation, which was reversed by the D2/3 agonist quinpirole, indicating that DJ-1 has a role in dopamine-dependent signaling in hippocampal plasticity [91]. This implies that DJ-1 may be important in the maintenance of memory and cognition.

4.3. DJ-1 as a Potential Biomarker for Lewy Body Diseases

Given its pathogenetic significance, DJ-1 could be a candidate biological marker for DLB and LB and might serve as a means of monitoring in vivo oxidative damage and protein misfolding. Although intracellular and mitochondrial in localization, DJ-1 is presumed to be secreted perhaps specifically under disease conditions which induce oxidative damage. Using semiquantitative immunoblotting, we previously identified DJ-1 in CSF of sporadic PD patients, where levels were significantly elevated compared with controls. Levels were higher in the earlier stage PD cohort (Hoehn-Yahr stages I-II) than in the more severe patients (Hoehn-Yahr stages III-IV) [92]. Similarly, plasma DJ-1 levels in PD patients were markedly increased compared to controls, but unlike CSF, levels were relatively higher in late stage (III-IV) rather than early stage PD (I-II) [93]. The reason for this difference between plasma and CSF DJ-1 is unknown, but we surmised previously that since CSF DJ-1 originates from a central source produced mainly by reactive glia, early increases in CSF DJ-1 levels probably represent an early protective response to damage, whereas plasma DJ-1, like other plasma disease markers, likely represents peripheral oxidative stress damage. In fact, DJ-1 is secreted into blood in breast cancer, melanoma, familial amyloid neuropathy, and stroke [9496]. In the largest study to date, Hong et al. developed a more sensitive and quantitative Luminex assay for CSF DJ-1 to complement immunoblotting mass spectrometric and chromatographic analysis methods and found decreasing rather than increasing levels of DJ-1 in PD CSF compared with control patients [72]. The 90% disease sensitivity and 70% disease specificity for PD using this method approaches minimal desired parameters for a clinically useful biomarker for PD. Importantly, the study highlighted the fact that DJ-1 levels are greatly influenced by such variables as the extent of blood contamination and patient age, which could account for some of the variability across studies. Of note, DJ-1 is also subject to oxidative modifications in PD and AD brain tissue, and this might be measured in peripheral fluids as well, as another monitor of oxidative damage [97]. CSF DJ-1 remains a promising and perhaps clinically useful biomarker for PD, but as far as DLB and other LBD, it is unknown whether CSF levels of DJ-1 are altered. Since plasma DJ-1 is increased in DLB, it is hypothesized that CSF DJ-1 may also be elevated. Further investigation will be necessary to clarify the utility of DJ-1 as a biomarker in DLB and LBD.

5. Glucocerebrosidase as a Novel Biomarker for Lewy Body Disorders

5.1. Glucocerebrosidase Mutations Influence PD and DLB

Many clinicopathologic parallels can be drawn between the lysosomal storage disorders, such as Niemann-Pick, Sandhoff’s, Tay-Sachs disease and others, and the age-related neurodegenerative disorders, when considering the aberrant accumulation of pathological substances (e.g., lysosomal sphingomyelin in Niemann-Pick disease versus synucleins in PD and DLB) and the phenotypes of neuronal loss and cognitive deterioration found in both. Common to these diseases are abnormalities in lysosomal and autophagic mechanisms as part of a larger disruption of cellular proteostasis leading to abnormal storage/accumulation of toxic materials and neuronal damage. In the past few years, an altogether unexpected pathogenetic relationship emerged between Gaucher’s disease (GD), a prototypic storage disease, and the synucleinopathies. Despite its overall rarity, GD is the most common inherited lysosomal storage disease, especially in the Ashkenazi Jewish population. It is caused by autosomal recessive gene mutations in the glucocerebrosidase (GBA) gene (chromosome 1q21), leading to either partial or complete deficiency of GBA, and hence, toxic lysosomal accumulation of its substrate, glucosylceramide, in multiple cell types including neurons [98]. Recent reports documented an increased incidence of PD in heterozygous relatives of patients with GD [99, 100], but interest in this phenomenon was propelled by the finding that GBA mutations were in fact more common in PD patients of Ashkenazi background compared with AD patients and PD patients in the general population [101103]. Moreover, more severe GBA mutations such as 84 dupl G and IVS 2 + 1 were associated with a greater degree of PD risk, compared with less severe GBA mutations such as N370S [104]. The relationship between PD and GBA has now been replicated in much larger international studies with the most common mutations being L444P and N370S, and about 28 GBA mutations are presently recognized [105].

Interestingly, in a study of British patients with PD and GBA mutations, all 17 carrier patients demonstrated abundant α-syn neuropathology with Braak stage 5-6 severity and common neocortical LB pathology. Clinically, these patients had earlier age at onset, and hallucinations were present in 45% of patients, while 48% had cognitive impairment or dementia consistent with PDD [106]. Greater severity of GBA mutation also predicted the presence of cognitive impairment in PD patients; 56% of severe GBA mutation carriers had cognitive impairment compared to 25% of mild mutation carriers [107]. These observations suggest a much broader link between GBA mutations and the dementia phenotype of LBD. In fact, examination of GBA gene alterations in DLB patients, with and without concomitant LBV-type AD pathology, showed that the majority of GBA mutations were found in DLB patients rather than in PD, with a mutation rate in DLB ranging from 18 to 23% overall [108, 109]. The proportion of DLB patients with GBA mutations was higher in those with pure neocortical LB pathology compared to those with mixed LB and AD pathology and to those with predominantly brainstem LB. A significant association was also found between GBA mutation status and the presence of LB, indicating that altered GBA might play a role in their formation and in synucleinopathy [108].

5.2. Glucocerebrosidase and Chaperone-Mediated Autophagy in LBD

Important in neurodegeneration, disrupted cellular proteostasis represents a state in which an imbalance exists between effective functioning of the innate cytoprotective machinery and excessive accumulation and aggregation of abnormally misfolded proteins, leading to neurotoxicity. It is increasingly apparent that chaperone-mediated autophagy (CMA) and lysosomal degradation pathways are important in maintaining cellular proteostasis as part of a larger network of cellular actions, with particular relevance for neurodegenerative diseases. Recently, as evidence for CMA dysfunction in synucleinopathies, a significant decrease in autophagy markers was reported in substantia nigra from PD brain [110]. Soluble forms of α-syn, including monomers, oligomers, and even protofibrils, are normally cleared through the CMA/lysosomal degradation by interacting with the chaperone, heat shock cognate-70, and becoming internalized into lysosomes via the Lamp-2a membrane receptor [111, 112]. Studies have indicated that α-syn shares a common pentapeptide structure with other lysosomal substrates, designating it as a target for removal by this pathway [111], and the lysosomal structure is critical to maintaining the internal acidic environment, allowing lysosomal hydrolases to degrade α-syn into peptides released into the cytosol [112]. Mutant GBA could therefore disrupt lysosomal activity leading to abnormal accumulation of nondegraded α-syn, which then aggregates to toxic soluble oligomers and protofibrils. Also, abnormalities in the ubiquitin-proteasome system (UPS) are present in AD and PD, and GBA alterations might secondarily overwhelm the ability of UPS to remove accumulated α-syn, promoting aggregation and neurotoxicity [113]. Pathologically, in GD with parkinsonism, α-syn-positive inclusions were observed in neurons in hippocampal CA2-4 regions, while cortical synuclein pathology was identified in other GD cases [114]. Further, parkin, an E3 ubiquitin ligase also implicated in PD, has been shown to affect the stability of mutant GBA and increase its degradation causing further lysosomal dysfunction [115].

5.3. Glucocerebrosidase as a LBD Biomarker

Because of the importance of mutant GBA function to PD and DLB pathogenesis, the issue arises as to whether the measurement of GBA activity, or a perhaps other related molecules, might be utilized as a biological marker. The activity of peripherally secreted GBA was measured in plasma and CSF in a 10-month-old female with GD with the aim of monitoring the effect of experimental Cerezyme replacement therapy [116]. Baseline GBA activity was detected in both plasma (2.7 × 10−6 U/μL) and CSF (0.096 × 10−6 U/μL), although CSF activity was several magnitudes lower than plasma. Intravenous Cerezyme, a macrophage-targeted GBA, rapidly raised the plasma activity within 1 hour and CSF activity by 2.3-fold at 3 hours, both returning to baseline after 24 hours. This study suggests the intriguing possibility that GBA activity, especially in CSF and plasma, might be useful in monitoring the efficacy of novel therapies involving CMA and lysosomal function. To extend this observation, Balducci et al. determined that multiple lysosomal hydrolases, including GBA, are significantly decreased in the lumbar CSF of PD patients [117], perhaps supporting a more widespread lysosomal dysfunction in PD not limited to GBA alone. In this regard, other lysosomal enzymes such as mannosidase and β-hexosaminidase might be important additional biomarker targets for neurodegeneration. Moreover, in DLB, AD, and FTD patients, lysosomal enzyme activities in CSF demonstrated a very specific pattern of decrease, in which only DLB showed significant decreases in CSF activity of α-mannosidase, β-mannosidase, GBA, galactosidase, and β-hexosaminidase, whereas in AD and FTD, only CSF α-mannosidase activity was significantly diminished [118]. In DLB, CSF GBA activity showed the greatest magnitude of decrease, reinforcing its importance in the LBD, but also noteworthy is the fact that AD and FTD showed decreased α-mannosidase activity, suggesting that this might be another important factor in lysosomal dysfunction in neurodegeneration. Indeed, these promising candidates need to be investigated further to establish diagnostic accuracy in terms of disease specificity and sensitivity in cohorts of PD, DLB, and other dementing disorders.

6. Miscellanous Candidate Biomarkers

6.1. Inflammatory Cytokines

Polymorphisms in proinflammatory cytokine genes including IL-1α, IL-1β, and TNF-α are associated with increased risk in AD [119]. In PD, several case control genetic analyses have demonstrated that homozygous carriers of the IL-1β −511 and TNF-α −308 promoter region variants have increased disease risk [120, 121], and that earlier age at onset in PD was associated with IL-1β −511 homozygosity at allele 1 [122]. But as yet, no such genetic alterations in cytokines genes have been reported in DLB. Similar to Aβ-induced upregulation of inflammatory cytokines in AD, soluble secreted α-syn in the extracellular space in LBD might also induce the production of a variety of neuroinflammatory mediators into the extracellular fluid. For instance, microglial activation in response to stimulation by secreted α-syn from cultured cells and from overexpression in transgenic mouse models occurs in a dose-dependent manner, causing release TNF-α, IL-1β, and IL-6 [123]. Because secreted CNS cytokines are readily detected in CSF, they have been extensively examined as potential disease biomarkers. IL-1β, IL-2, IL-6, and TNF-α are all upregulated in PD brain, as well as in CSF from PD patients [124126], and Chen et al. showed that plasma IL-6, but not IL-1β, TNF-α, or other acute phase reactants, predicted risk for future PD in males [127]. In terms of DLB, CSF IL-1β levels, which were relatively low, did not differ compared to AD or normal controls and could not distinguish them apart. Comparable increases in CSF IL-6 levels were found in AD and DLB, but again not significantly different from each other to be of diagnostic value [128]. Indeed, the neuroinflammatory cytokines may be important as a pathogenetic response to CNS injury caused by accumulation of amyloidogenic proteins, but their role as biomarkers for the LBD, especially for DLB, is still unclear.

6.2. Neurofilament Proteins

Disorganization and breakdown in the cytoskeletal network occurs in various LBDs and other neurodegenerative diseases, and as discussed, gamma-synuclein and proteolytic degradation of the cytoskeleton may be involved. As a result, a failure of normal axonal transport results from the accumulation of disrupted neurofilament molecules within the neuropil, causing neuronal demise [129]. Recently, a mutation in the NEFM gene encoding the rod domain 2B of neurofilament M (NF-M) which causes aberrant NF assembly was identified in a single early-onset PD patient [130]. It is recognized that in addition to α-syn, three types of NF protein also comprise the structure of Lewy bodies [131]. Upon cell death or axonal damage, accumulated neurofilament leaks into the extracellular space, subsequently appearing in CSF and perhaps other peripheral fluids. Elevated CSF NF protein was reported in MSA and PSP, but not in PD, and this was suggested to clinically aid in differentiating parkinsonian syndromes [132]. CSF NF protein was also measured in dementia, and although increased levels were observed in DLB, late-onset AD, and FTD, there were no differences among them [28]. Therefore, because cytoskeletal abnormalities are present in many neurodegenerative dementias as well as in PD, NF protein may be more a reflection of nonspecific alterations in neuronal and axonal function, which does not appear to able to clinically separate DLB from other disorders.

6.3. Brain Neurotransmitter Alterations in CSF and by Imaging Modalities

Severe cortical cholinergic deficits originating from deficiencies in the nucleus basalis of Meynert are characteristic of AD brain, but studies have shown that cholinergic deficits are perhaps more severe in DLB brain [5]. This suggests that measurement of cholinergic activity and/or acetylcholine (ACh) might be developed into a potential biomarker for the LBDs. Indeed, early attempts to quantify ACh or its major metabolite, choline, have shown baseline levels to be low and perhaps difficult to measure accurately. In AD, CSF ACh was reported to be significantly lower than control levels [133], while in PD and Huntington’s disease patients, despite some cholinergic deficit, lumbar CSF ACh and choline levels did not differ from normal [134]. No studies have directly examined CSF cholinergic levels in DLB or LBDs, but recently, Shimada and colleagues employed positron emission tomography (PET) mapping of brain ACh activity in DLB and PDD patients and normal controls and demonstrated a marked reduction in cholinergic activity in medial occipital cortex of DLB and PDD, greater than that observed in PD patients without dementia [135]. Some correlation of mapped cholinergic activity with cognitive decline measured by the Mini-Mental State Exam was also found. Although preliminary, this has potential to be a more practical and sensitive cholinergic biomarker for LBD.

Because of similar nigrostriatal loss to PD, a relative dopaminergic deficiency also exists in DLB and LBDs. CSF dopamine (DA) and its metabolites have been investigated previously in PD, and recently, Lunardi et al. showed differences in CSF DA and its metabolites, homovanillic acid (HVA) and dihydroxyphenylacetic acid (DOPAC), in PD patients, demonstrating early-stage dopaminergic loss and a correlation with the development of dyskinesia [136]. In DLB, HVA levels were significantly reduced compared with AD, separating the disorders [137]. Similar to cholinergic activity, imaging modalities may also contribute to the assessment of dopaminergic function in the LBDs. In a small study, striatal DA uptake as measured by 18F-fluorodopa PET was decreased in both caudate and putamen in DLB as compared with AD patients and controls [138]. Also, DA transporter loss was determined across multiple studies using 123I-2β-carbometoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane ligand with single-photon emission computed tomography (123I-FP CIT SPECT) and demonstrated significant loss of caudate and putaminal DA transport compared with AD and control levels [139141]. A larger phase III, multicenter study of 123I-FP CIT SPECT in possible and probable DLB patients and non-DLB comparators (mostly AD) demonstrated a mean sensitivity of 77.7% for detecting clinically probable DLB, with a specificity of 90.4% and 85.7% overall diagnostic accuracy [141]. 123I-FP CIT SPECT DA transporter imaging greatly enhanced diagnostic accuracy for DLB over clinical diagnosis alone when coupled with autopsy confirmation, raising sensitivity for DLB from 75% to 88% and specificity from 42% to 100% [139]. Furthermore, DA transporter loss in the caudate may also be inversely associated with depression, apathy, and delusions in DLB patients [142].

6.4. Miscellaneous Imaging Biomarkers in LBD
6.4.1. MIBG Scintigraphy as a DLB Biomarker

Autonomic failure is a common clinical finding in LBD, including PD and DLB, but not in non-LBD dementias, and therefore it has been investigated as an alternative biomarker for the diagnostic separation of DLB from other dementias. Abnormal autonomic function can be determined using cardiac 123I-meta-iodobenzyl guanidine (123I-MIBG) imaging, a technique which assesses cardiac sympathetic nerve function in both cardiac and neurological disorders by measuring the uptake of 123I-MIBG, a norepinephrine analogue [143]. In the last decade, a series of Japanese studies consistently demonstrated delayed heart to mediastinum ratio (H/M) of 123I-MIBG uptake in DLB compared with AD and controls [143146]. 123I-MIBG scintigraphy was found superior to brain perfusion SPECT imaging [147]. Estorch et al. further showed that in dementia patients followed for four years before “final diagnosis,” 123I-MIBG imaging distinguished DLB from other dementias with a sensitivity of 94%, specificity of 96%, and a diagnostic accuracy of 95% [148]. Finally, consistent with autonomic dysfunction in DLB, both early and delayed H/M 123I-MIBG uptake were significantly associated with the presence of orthostatic hypotension in DLB patients and discriminated DLB from AD even in the absence of parkinsonism [149].

6.4.2. Other Structural and Functional Imaging Biomarkers

Various magnetic resonance (MR) imaging modalities have been explored in DLB and PDD, including volumetric imaging, diffusion tensor imaging, and proton magnetic resonance spectroscopy (reviewed in Watson et al.) [150], and although not directly useful as biomarkers at present, they have revealed insights in the pathobiology of LBDs. Using conventional MRI techniques such as voxel-based morphometry and region of interest analysis, some degree of diffusion or focal frontal and parietal atrophy has been observed [151]. Atrophy has been rated at 1.4% per year in DLB brain [152], 1.31% per year in PDD, and 0.31% per year in PD [153]. Not surprising is the fact that unlike AD brain, medial temporal structures are relatively preserved in DLB and PDD, with global hippocampal loss at about 10–20% compared with controls and about 21–25% in AD [154]. Diffusion tensor imaging, an MR technique mapping brain microdiffusion of water in the direction of white matter tracts, has shown decreased fractional anisotropy of water movement in DLB in the precuneus and posterior cingulate areas, perhaps highlighting their role in DLB pathogenesis [155].

Brain perfusion SPECT (99mTc-HMPAO SPECT) has been evaluated in its ability to diagnostically separate DLB from AD, and in AD, reduced relative cerebral blood flow (rCBF) in the frontal, and medial temporal regions is characteristic, whereas in DLB, occipital hypoperfusion is often observed [156]. Colloby et al. applied statistical parametric mapping to SPECT imaging of DLB patients, more precisely showing large perfusion deficits in the left medial occipital gyrus and the bilateral central, inferior parietal, precuneate, superior frontal and cingulate regions on the brain, which are functionally consistent with frontal-executive and visuospatial deficits in DLB [157]. Across studies, sensitivity ranged from 65 to 85% and specificity from 85–87%, which appears less robust as a potential imaging marker compared with other methods.

6.5. Other PD Genes and Their Protein Products as Possible DLB Markers

Aside from α-syn and DJ-1, numerous other mutations have been associated with familial early-onset PD and possibly LBD (Table 1). Among these gene products are parkin (PARK 2), UCHL-1 (PARK 5), PINK1 (PTEN-induced putative kinase 1; PARK 6), and LRRK2/dardarin (PARK 8) [158]. Indeed, none of these mutations have yet been associated with prototypic LBD pathology, and it remains to be determined whether they actually represent LBDs or separate diseases with parkinsonian phenotype. Furthermore, no studies have addressed their role as biological markers of disease, but since both synucleins and DJ-1 are detected in CSF and peripheral fluids, it seems plausible that the protein products of other dominant genes in PD could be peripheral biomarker candidates for DLB and other LBD. Parkin, UCHL-1, and PINK1 genes, like DJ-1, all encode proteins important in neuroprotection in terms of maintaining protein homeostasis and preventing stress-related cellular damage, and mutations in these genes cause a loss of these critical functions. Leucine-rich repeat kinase 2 (LRRK2/dardarin), on the contrary, is linked with autosomal-dominant late-onset PD, and mutations result in a toxic gain of function.

LRRK2/dardarin is a kinase consisting of multiple functional domains, and recent evidence suggests that physiologically, its principal function may be to regulate neurite outgrowth. Expression in cultured neurons of several LRRK2 mutations associated with familial PD, such as G2019S, increased kinase activity and significantly reduced neurite outgrowth, whereas expression of a dominant-negative mutation, K1906M, markedly increased neurite length [159]. PD-associated mutations also generated tau-positive axonal inclusions in cultured neurons, suggesting that LRRK2 may be linked to abnormalities in tau. Indeed, expression of mutant G2019S LRRK2 in Drosophila caused activation of the Drosophila GSK-3β homolog and promoted tau hyperphosphorylation leading to microtubule fragmentation and dendritic pathology [160]. Similar tau hyperphosphorylation was also present in transgenic mice expressing G2019S LRRK2, and expression of both wild-type human LRRK2 and G2019S mutant LRRK2 caused abnormal dopaminergic transmission [161]. LRRK2 may also interact with α-syn, another dominantly inherited PD gene, to exert its effect. Lin et al. showed that overexpression of LRRK2 with A53T mutant α-syn in transgenic mice worsened neurodegeneration, while ablation of LRRK2 expression suppressed α-syn aggregation and pathology [162], and α-syn also activates GSK-3β in mice causing tau hyperphosphorylation [163], indicating that LRRK2, α-syn, and tau alterations may all be linked in the same pathway, perhaps with LRRK2 upstream of these events. Although early, evidence has indicated that LRRK2 is also a component of LB in PD and DLB brains [164], and that LRRK2 and α-syn interact in DLB brain and coimmunoprecipitate in cultured cells after oxidative stress challenge [165], suggesting that the LRRK2 may also be important in DLB pathogenesis. Interestingly, genome-wide association studies (GWASs) in a European cohort demonstrated that LRRK2, α-syn, and tau are loci associated with PD risk [166], but examination of tau in a Japanese GWAS cohort failed to identify it as a PD risk locus [167], showing a population difference with regard to this locus. Certainly, population differences might apply to all risk loci examined for PD and LBD, and it is important to determine whether the relationship among LRRK2, α-syn, and tau in PD, DLB, and other LBD is also influenced by population differences. These findings make LRRK2/dardarin an attractive candidate for examination as a potential biomarker, and if identified in CSF or peripheral fluids, they might be used with α-syn and tau as combined biomarkers.

Furthermore, emerging evidence is redefining the roles of PINK1 and parkin in PD pathogenesis. Because energy generation is critical for cellular function, mammalian cells are highly dependent on mitochondria [168]. Depolarization and morphological defects characterize damaged or impaired mitochondria which are targeted for removal through mitophagy, a highly specialized form of autophagy in which parkin and PINK1 play a crucial role (reviewed by Vives-Bauza and Przedborski) [169]. In this process, PINK1 cleavage is inhibited by the loss of mitochondrial membrane potential, causing its lengthening and the recruitment of cytosolic parkin [170, 171]. Voltage-dependent anion channel 1 and other outer mitochondrial membrane proteins are then ubiquitinated in a parkin-dependent manner, and this in turn recruits the binding of adapter proteins such as p62 and histone deacetylase 6 to initiate autophagosome assembly around the damaged mitochondrion and subsequent removal [169]. Of relevance to PD, mutant PINK1 and mutant parkin both cause motor dysfunction, dopaminergic loss, and abnormal mitochondrial morphology in Drosophila [172]. In this paradigm, loss of function PINK1 mutants are rescued by concurrent overexpression with wild-type parkin but not vice versa, indicating that parkin specifically acts downstream of PINK1. Also, parkin mutations have been shown to interfere with ubiquitination and the downstream steps in normal mitophagy [173]. Thus, PD, and possibly related dementias, might be a result, to some extent, of defective mitophagy due to loss of function in PINK1 and parkin such as found in autosomal dominant early-onset PD.

Although LRRK2, parkin, PINK1, and UCHL-1 have not yet been identified in peripheral fluids, PINK1 and parkin may be a promising candidates. Unexpectedly, both PINK1 and parkin, which are normally cytosolic or targeted to mitochondria, were localized extracellularly in AD and multiple sclerosis brain, and colocalized with amyloid plaques, reactive astrocytes, as well as amyloid-affected vessels [174, 175]. This suggests that both PINK1 and parkin are actively released from neurons and glia in response to injury and might be upregulated in CSF and peripheral fluids during neurodegeneration. Interestingly, given a role in mitophagy, they might also be a CSF or peripheral reflection of mitochondrial health and turnover. It remains to be seen whether these gene products can be detected in biological fluids such as CSF as potential biomarkers in PD and LBD.

7. Unbiased Methods in LBD Biomarker Discovery

7.1. Genomics in PD and LBDs

As detailed above, traditional methods for molecular biomarker determination have been derived from targeted analyses of candidate genes/mutations and corresponding proteins in brain and body fluids such as CSF and blood, with the subsequent exploration of mechanisms in cell culture and animal models. An emerging alternate approach has been to evaluate genomes and proteomes with regard to specific neurodegenerative diseases and their components in an unbiased manner to yield a number of potential pathogenetic, therapeutic, and biomarker targets for further validation. With regard to the genomic analysis of the LBDs, gene expression profiling has proved to be a promising tool. Scherzer et al., for instance, examined transgenic Drosophila expressing the human α-syn gene and performed temporal profiling of resultant gene expression [176]. They demonstrated a number of changes, including a downregulation of phospholipase A2 and other lipid genes, downregulation of several mitochondrial respiratory chain molecules, and alteration in membrane transport and energy genes such as voltage-gated calcium channel and lysosomal ATPase, suggesting that mitochondrial integrity might be affected by α-syn overexpression.

In Parkinson’s disease brain, RNA from populations of mesencephalic dopaminergic neurons with and without LB were isolated by immunolaser capture microdissection, amplified by polymerase chain reaction and expressed [177]. Interestingly, upregulation of the ubiquitin-specific protease 8 in LB-containing neurons indicated cellular damage and increased levels of ubiquitination in LB, whereas non-LB-bearing neurons showed increased expression of novel cytoprotective genes such as bullous pemphigoid antigen 1, an HSP-70-like gene (STCH) and Kelch-like 1. Although promising, further genomic profiling studies in DLB, PDD, and other LBD are needed to expand the range of novel gene targets for examination and validation.

7.2. Proteomic Profiling in PD and LBDs

As a complement to gene expression profiling and genomic methods, proteomic profiling has also assumed a greater importance in biomarker discovery for neurodegeneration with relevance to the LBD. Advances in methodologies such as 2-dimensional gel electrophoresis (2-D GE), liquid chromatography (LC), high-resolution mass spectrometry (MS), and quantitative proteomics allow analysis of static or condition-dependent protein structure and function associated with PD and LBD in a variety of sample types such as brain or body fluids (reviewed in Shi et al. 2009) [178]. In mice treated with MPTP, a specific mitochondrial toxin, isotope-coded affinity tag assay of brain tissue followed by MS analysis revealed 100 proteins with significantly altered levels including many mitochondrial and metabolic molecules, βAPP and DJ-1 [179].

Basso et al. first examined the proteome of the substantia nigra from Parkinson’s disease brain and age-matched controls [180]. Using 2D GE and peptide fingerprinting, of the 44 expressed proteins, 9 proteins differed in PD versus controls, including oxidative and mitochondrial proteins such as peroxiredoxin II, mitochondrial complex III, calcium channel, and others. A subsequent study in PD brain showed decreased frontal cortex levels of mortalin, a novel mitochondrial chaperone protein with roles in energy generation [181]. In addition, LBs isolated by laser-capture microdissection, were analyzed by LC/MS and ultimately demonstrated 156 candidate proteins involved in ubiquitin-proteasome system and synaptic function, from which the heat shock cognate-71, a chaperone involved in neurodegenerative disease, was identified and validated as a candidate target [182]. Abdi and colleagues carried out proteomic evaluation of CSF from AD, PD, and DLB patients and normal control individuals, using chromatography, MS, and isobaric tagging for relative and absolute quantification (iTRAQ), identifying numerous candidate proteins related to PD and DLB, such as lipoproteins ApoC1 and ApoH [183]. Lastly, using surface-enhanced laser desorption/ionization-time of flight (SELDI-TOF) MS analysis of serum from DLB patients compared to AD, a combination of protein peaks provided the ability to separate DLB from non-DLB cases, with a sensitivity of 83.3% and a specificity of 95.8% [184]. Given promising findings, further exploration of the proteomics of the LBDs is warranted, and perhaps consideration should be given to determining whether combining various genomic and proteomic methods will be of value.

8. Conclusions

Over the last decade, tremendous advances have been made in understanding the pathogenetics of PD, PDD, and DLB, which has revealed not only the genetic basis of these disorders, but also related mechanisms common to all the LBD. In parallel, these discoveries have been a catalyst for translating and developing many of the involved proteins into promising biomarkers for disease. A common theme centers on genes that drive a complex network of synergistic and opposing cellular actions underlying pathogenesis. Aggregation of α-syn, the main constituent of intracellular LBs, results in toxic oligomers and protofibrils which not only act intracellularly, but also are actively and passively released into the extracellular environment causing damage to surrounding tissue. Proinflammatory cytokines such as interleukins are also produced which perpetuates the inflammatory cascade. On the contrary, DJ-1, PINK1, parkin, and perhaps others molecules are upregulated to oppose cellular protein misfolding and oxidative stress and maintain mitochondrial function, while autophagy mechanisms attempt to limit the toxic effect of synucleins and other toxins by lysosomal engulfment and digestion. Much of this is reminiscent of a relatively new concept applied to infectious diseases and mechanical tissue injury termed “damage-associated molecular patterning” (DAMP), which is an evolved system to recognize, contain, and repair damage to cells and tissues. It is characterized by the abnormal release of molecules normally confined and operating within healthy cells or from foreign pathogenic agents, that when released into the extracellular space activate receptors and pathways leading to inflammation and multiplying cellular damage (reviewed by Bianchi) [185]. In this regard, events in the pathogenesis of PD, DLB, and related disorders may represent a novel variation of the DAMP response, and in a sense, biological fluid markers are therefore a measurement of DAMP activity as it relates to neurodegeneration.

Despite progress in developing biological markers for PD, PDD, and DLB, clinical diagnosis of this spectrum of disorders remains challenging. The need for highly sensitive and specific biomarkers that accurately mirror the underlying pathogenetic features of these disorders demands not only that more advanced detection methods be devised and validated in large sample populations, but also that novel biomarker candidates be selected for evaluation based on rational selection from the multiple-associated gene-mechanism associations in the LBD. Gene products including β- and γ-synuclein, GBA, parkin, and PINK1 need to be examined in CSF, blood, and even urine to confirm their presence in biological fluids and threshold of detection. Alterations in the levels of these putative biomarker candidates in CSF and blood can provide further insight into the role these mechanisms may play in disease and also the ability of the potential biomarker to reflect resulting CNS changes. To better understand the relationship of gene mutations, mechanisms, and disease biomarkers in LBD, it would be of great interest to determine whether the levels of these putative biomarkers in CSF and peripheral fluids are altered in patients with known PD, DLB, and LBD mutations. It is likely that combinations of multiple peripheral biomarkers could be needed to monitor the various mechanistic aspects underlying the LBD, but the optimal combination has yet to be determined. Furthermore, both existing imaging modalities as well as novel imaging techniques to detect specific molecular biomarker targets will greatly complement peripheral biomarkers. New specific therapies for the LBD yet to be developed will probably target one or more of the multiple pathways described above, and indeed, this could determine which biomarker or combination of biomarkers would be appropriate as a therapeutic endpoint. Studies are also needed to establish which biomarkers will fulfill the criteria of minimum sensitivity and specificity for the LBD for consistent and reproducible diagnostic use in presymptomatic disease detection and also serve as robust tracking tools and endpoints in monitoring the efficacy of future LBD therapies.


This work was supported in part by a Grant-in-Aid for Science Research from the Ministry of Education, Culture, Sports, Science and Technology, Japan (to M. Hashimoto), by the Novartis Foundation for Gerontological Research (to M. Hashimoto), and by the following NIH Grants (to E. Masliah): AG18440, AG5131, AG022074, NS57096, and AG03197. The authors thank Dr. Michael Rafii, University of California, San Diego for his critical reading of their paper.


  1. I. G. McKeith, D. Galasko, K. Kosaka et al., “Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop,” Neurology, vol. 47, no. 5, pp. 1113–1124, 1996. View at: Google Scholar
  2. A. R. Merdes, L. A. Hansen, D. V. Jeste et al., “Influence of Alzheimer pathology on clinical diagnostic accuracy in dementia with Lewy bodies,” Neurology, vol. 60, no. 10, pp. 1586–1590, 2003. View at: Google Scholar
  3. D. Weintraub, C. L. Comella, and S. Horn, “Parkinson's disease—Part 3: neuropsychiatric symptoms,” American Journal of Managed Care, vol. 14, no. 2, pp. S59–S69, 2008. View at: Google Scholar
  4. C. F. Lippa, J. E. Duda, M. Grossman et al., “DLB and PDD boundary issues: diagnosis, treatment, molecular pathology, and biomarkers,” Neurology, vol. 68, no. 11, pp. 812–819, 2007. View at: Publisher Site | Google Scholar
  5. C. F. Lippa, T. W. Smith, and E. Perry, “Dementia with Lewy bodies: choline acetyltransferase parallels nucleus basalis pathology,” Journal of Neural Transmission, vol. 106, no. 5–6, pp. 525–535, 1999. View at: Publisher Site | Google Scholar
  6. W. R. Markesbery, G. A. Jicha, H. Liu, and F. A. Schmitt, “Lewy body pathology in normal elderly subjects,” Journal of Neuropathology and Experimental Neurology, vol. 68, no. 7, pp. 816–822, 2009. View at: Publisher Site | Google Scholar
  7. G. A. Jicha, F. A. Schmitt, E. Abner et al., “Prodromal clinical manifestations of neuropathologically confirmed Lewy body disease,” Neurobiology of Aging, vol. 31, no. 10, pp. 1805–1813, 2010. View at: Publisher Site | Google Scholar
  8. C. R. Jack Jr., D. S. Knopman, W. J. Jagust et al., “Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade,” The Lancet Neurology, vol. 9, no. 1, pp. 119–128, 2010. View at: Publisher Site | Google Scholar
  9. B. Vellas, S. Andrieu, C. Sampaio, and G. Wilcock, “Disease-modifying trials in Alzheimer's disease: a European task force consensus,” The Lancet Neurology, vol. 6, no. 1, pp. 56–62, 2007. View at: Publisher Site | Google Scholar
  10. C. Haass and D. J. Selkoe, “Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid β-peptide,” Nature Reviews Molecular Cell Biology, vol. 8, no. 2, pp. 101–112, 2007. View at: Publisher Site | Google Scholar
  11. A. J. Harding and G. M. Halliday, “Cortical Lewy body pathology in the diagnosis of dementia,” Acta Neuropathologica, vol. 102, no. 4, pp. 355–363, 2001. View at: Google Scholar
  12. P. H. St George-Hyslop, “Molecular genetics of Alzheimer's disease,” Biological Psychiatry, vol. 47, no. 3, pp. 183–199, 2000. View at: Publisher Site | Google Scholar
  13. D. Selkoe and R. Kopan, “Notch and Presenilin: regulated intramembrane proteolysis links development and degeneration,” Annual Review of Neuroscience, vol. 26, pp. 565–597, 2003. View at: Publisher Site | Google Scholar
  14. H. Vanderstichele, E. Van Kerschaver, C. Hesse et al., “Standardization of measurement of β-amyloid((1-42)) in cerebrospinal fluid and plasma,” Amyloid, vol. 7, no. 4, pp. 245–258, 2000. View at: Google Scholar
  15. L. Parnetti, P. Tiraboschi, A. Lanari et al., “Cerebrospinal fluid biomarkers in Parkinson's disease with dementia and dementia with Lewy bodies,” Biological Psychiatry, vol. 64, no. 10, pp. 850–855, 2008. View at: Publisher Site | Google Scholar
  16. P. E. Spies, D. Slats, J. M. C. Sjögren et al., “The cerebrospinal fluid amyloid β42/40 ratio in the differentiation of alzheimer's disease from non-alzheimer's dementia,” Current Alzheimer Research, vol. 7, no. 5, pp. 470–476, 2010. View at: Publisher Site | Google Scholar
  17. W. E. Klunk, H. Engler, A. Nordberg et al., “Imaging brain amyloid in Alzheimer's disease with pittsburgh compound-B,” Annals of Neurology, vol. 55, no. 3, pp. 306–319, 2004. View at: Publisher Site | Google Scholar
  18. C. C. Rowe, S. Ng, U. Ackermann et al., “Imaging β-amyloid burden in aging and dementia,” Neurology, vol. 68, no. 20, pp. 1718–1725, 2007. View at: Publisher Site | Google Scholar
  19. S. N. Gomperts, D. M. Rentz, E. Moran et al., “Imaging amyloid deposition in Lewy body diseases,” Neurology, vol. 71, no. 12, pp. 903–910, 2008. View at: Publisher Site | Google Scholar
  20. M. Goedert, B. Ghetti, and M. G. Spillantini, “Tau gene mutations in frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP—17). Their relevance for understanding the neurogenerative process,” Annals of the New York Academy of Sciences, vol. 920, pp. 74–83, 2000. View at: Google Scholar
  21. D. G. Munoz, D. W. Dickson, C. Bergeron, I. R. A. Mackenzie, A. Delacourte, and V. Zhukareva, “The neuropathology and biochemistry of frontotemporal dementia,” Annals of Neurology, vol. 54, supplement 5, pp. S24–S28, 2003. View at: Publisher Site | Google Scholar
  22. G. Basurto-Islas, J. Luna-Muñoz, A. L. Guillozet-Bongaarts, L. I. Binder, R. Mena, and F. García-Sierra, “Accumulation of aspartic acid- and glutamic acid -cleaved tau in neurofibrillary tangles correlates with progression in Alzheimer disease,” Journal of Neuropathology and Experimental Neurology, vol. 67, no. 5, pp. 470–483, 2008. View at: Publisher Site | Google Scholar
  23. W. H. Stoothoff and G. V. W. Johnson, “Tau phosphorylation: physiological and pathological consequences,” Biochimica et Biophysica Acta, vol. 1739, no. 2–3, pp. 280–297, 2005. View at: Publisher Site | Google Scholar
  24. H. Arai, Y. I. Morikawa, M. Higuchi et al., “Cerebrospinal fluid tau levels in neurodegenerative diseases with distinct tau-related pathology,” Biochemical and Biophysical Research Communications, vol. 236, no. 2, pp. 262–264, 1997. View at: Publisher Site | Google Scholar
  25. L. Parnetti, A. Lanari, S. Amici, V. Gallai, E. Vanmechelen, and F. Hulstaert, “CSF phosphorylated tau is a possible marker for discriminating Alzheimer's disease from dementia with Lewy bodies. Phospho-Tau International Study Group,” Neurological Sciences, vol. 22, no. 1, pp. 77–78, 2001. View at: Publisher Site | Google Scholar
  26. S. Engelborghs, K. De Vreese, T. Van de Casteele et al., “Diagnostic performance of a CSF-biomarker panel in autopsy-confirmed dementia,” Neurobiology of Aging, vol. 29, no. 8, pp. 1143–1159, 2008. View at: Publisher Site | Google Scholar
  27. K. Buerger, R. Zinkowski, S. J. Teipel et al., “Differential diagnosis of Alzheimer disease with cerebrospinal fluid levels of tau protein phosphorylated at threonine 231,” Archives of Neurology, vol. 59, no. 8, pp. 1267–1272, 2002. View at: Publisher Site | Google Scholar
  28. D. de Jong, R. W. M. M. Jansen, Y. A. L. Pijnenburg et al., “CSF neurofilament proteins in the differential diagnosis of dementia,” Journal of Neurology, Neurosurgery and Psychiatry, vol. 78, no. 9, pp. 936–938, 2007. View at: Publisher Site | Google Scholar
  29. H. Hampel, K. Buerger, R. Zinkowski et al., “Measurement of phosphorylated tau epitopes in the differential diagnosis of Alzheimer disease: a comparative cerebrospinal fluid study,” Archives of General Psychiatry, vol. 61, no. 1, pp. 95–102, 2004. View at: Publisher Site | Google Scholar
  30. K. Koopman, N. Le Bastard, J. J. Martin, G. Nagels, P. P. De Deyn, and S. Engelborghs, “Improved discrimination of autopsy-confirmed Alzheimer's disease (AD) from non-AD dementias using CSF P-tau(181P),” Neurochemistry International, vol. 55, no. 4, pp. 214–218, 2009. View at: Publisher Site | Google Scholar
  31. J. M. George, H. Jin, W. S. Woods, and D. F. Clayton, “Characterization of a novel protein regulated during the critical period for song learning in the zebra finch,” Neuron, vol. 15, no. 2, pp. 361–372, 1995. View at: Publisher Site | Google Scholar
  32. M. A. Alim, M. S. Hossain, K. Arima et al., “Tubulin seeds α-synuclein fibril formation,” Journal of Biological Chemistry, vol. 277, no. 3, pp. 2112–2117, 2002. View at: Publisher Site | Google Scholar
  33. M. A. Alim, Q. L. Ma, K. Takeda et al., “Demonstration of a role for α-synuclein as a functional microtubule-associated protein,” Journal of Alzheimer's Disease, vol. 6, no. 4, pp. 435–442, 2004. View at: Google Scholar
  34. N. M. Bonini and B. I. Giasson, “Snaring the function of α-synuclein,” Cell, vol. 123, no. 3, pp. 359–361, 2005. View at: Publisher Site | Google Scholar
  35. A. A. Cooper, A. D. Gitler, A. Cashikar et al., “α-synuclein blocks ER-Golgi traffic and Rab1 rescues neuron loss in Parkinson's models,” Science, vol. 313, no. 5785, pp. 324–328, 2006. View at: Publisher Site | Google Scholar
  36. G. Liu, C. Zhang, J. Yin et al., “α-synuclein is differentially expressed in mitochondria from different rat brain regions and dose-dependently down-regulates complex I activity,” Neuroscience Letters, vol. 454, no. 3, pp. 187–192, 2009. View at: Publisher Site | Google Scholar
  37. J. Madine, A. J. Doig, and D. A. Middleton, “A study of the regional effects of α-synuclein on the organization and stability of phospholipid bilayers,” Biochemistry, vol. 45, no. 18, pp. 5783–5792, 2006. View at: Publisher Site | Google Scholar
  38. M. Zhu, Z. J. Qin, D. Hu, L. A. Munishkina, and A. L. Fink, “α-synuclein can function as an antioxidant preventing oxidation of unsaturated lipid in vesicles,” Biochemistry, vol. 45, no. 26, pp. 8135–8142, 2006. View at: Publisher Site | Google Scholar
  39. O. M. A. El-Agnaf and G. B. Irvine, “Aggregation and neurotoxicity of α-synuclein and related peptides,” Biochemical Society Transactions, vol. 30, no. 4, pp. 559–565, 2002. View at: Publisher Site | Google Scholar
  40. H. I. Hurtig, J. Q. Trojanowski, J. Galvin et al., “Alpha-synuclein cortical Lewy bodies correlate with dementia in Parkinson's disease,” Neurology, vol. 54, no. 10, pp. 1916–1921, 2000. View at: Google Scholar
  41. M. G. Spillantini, R. A. Crowther, R. Jakes, M. Hasegawa, and M. Goedert, “α-synuclein in filamentous inclusions of Lewy bodies from Parkinson's disease and dementia with Lewy bodies,” Proceedings of the National Academy of Sciences of the United States of America, vol. 95, no. 11, pp. 6469–6473, 1998. View at: Publisher Site | Google Scholar
  42. M. Hashimoto, L. J. Hsu, A. Sisk et al., “Human recombinant NACP/α-synuclein is aggregated and fibrillated in vitro: relevance for Lewy body disease,” Brain Research, vol. 799, no. 2, pp. 301–306, 1998. View at: Publisher Site | Google Scholar
  43. M. H. Polymeropoulos, C. Lavedan, E. Leroy et al., “Mutation in the α-synuclein gene identified in families with Parkinson's disease,” Science, vol. 276, no. 5321, pp. 2045–2047, 1997. View at: Publisher Site | Google Scholar
  44. R. Krüger, W. Kuhn, T. Müller et al., “Ala30Pro mutation in the gene encoding α-synuclein in Parkinson's disease,” Nature Genetics, vol. 18, no. 2, pp. 106–108, 1998. View at: Google Scholar
  45. L. I. Golbe, G. Di Iorio, G. Sanges et al., “Clinical genetic analysis of Parkinson's disease in the Contursi kindred,” Annals of Neurology, vol. 40, no. 5, pp. 767–775, 1996. View at: Google Scholar
  46. K. Yamaguchi, E. J. Cochran, J. R. Murrell et al., “Abundant neuritic inclusions and microvacuolar changes in a case of diffuse Lewy body disease with the A53T mutation in the α-synuclein gene,” Acta Neuropathologica, vol. 110, no. 3, pp. 298–305, 2005. View at: Publisher Site | Google Scholar
  47. L. Morfis and D. J. Cordato, “Dementia with Lewy bodies in an elderly Greek male due to α-synuclein gene mutation,” Journal of Clinical Neuroscience, vol. 13, no. 9, pp. 942–944, 2006. View at: Publisher Site | Google Scholar
  48. J. J. Zarranz, J. Alegre, J. C. Gómez-Esteban et al., “The new mutation, E46K, of α-synuclein causes Parkinson and Lewy body dementia,” Annals of Neurology, vol. 55, no. 2, pp. 164–173, 2004. View at: Publisher Site | Google Scholar
  49. A. B. Singleton, M. Farrer, J. Johnson et al., “α-synuclein locus triplication causes Parkinson's disease,” Science, vol. 302, no. 5646, p. 841, 2003. View at: Publisher Site | Google Scholar
  50. J. Li, V. N. Uversky, and A. L. Fink, “Effect of familial Parkinson's disease point mutations A30P and A53T on the structural properties, aggregation, and fibrillation of human α-synuclein,” Biochemistry, vol. 40, no. 38, pp. 11604–11613, 2001. View at: Publisher Site | Google Scholar
  51. E. Tsika, M. Moysidou, J. Guo et al., “Distinct region-specific α-synuclein oligomers in A53T transgenic mice: implications for neurodegeneration,” Journal of Neuroscience, vol. 30, no. 9, pp. 3409–3418, 2010. View at: Publisher Site | Google Scholar
  52. R. A. Fredenburg, C. Rospigliosi, R. K. Meray et al., “The impact of the E46K mutation on the properties of α-synuclein in its monomelic and oligomeric states,” Biochemistry, vol. 46, no. 24, pp. 7107–7118, 2007. View at: Publisher Site | Google Scholar
  53. A. Iwai, E. Masliah, M. Yoshimoto et al., “The precursor protein of non-Aβ component of Alzheimer's disease amyloid is a presynaptic protein of the central nervous system,” Neuron, vol. 14, no. 2, pp. 467–475, 1995. View at: Google Scholar
  54. S. Nakajo, S. Shioda, Y. Nakai, and K. Nakaya, “Localization of phosphoneuroprotein 14 (PNP 14) and its mRNA expression in rat brain determined by immunocytochemistry and in situ hybridization,” Molecular Brain Research, vol. 27, no. 1, pp. 81–86, 1994. View at: Publisher Site | Google Scholar
  55. M. Hashimoto, E. Rockenstein, M. Mante, M. Mallory, and E. Masliah, “β-synuclein inhibits α-synuclein aggregation: a possible role as an anti-Parkinsonian factor,” Neuron, vol. 32, no. 2, pp. 213–223, 2001. View at: Publisher Site | Google Scholar
  56. H. Ohtake, P. Limprasert, Y. Fan et al., “β-synuclein gene alterations in dementia with Lewy bodies,” Neurology, vol. 63, no. 5, pp. 805–811, 2004. View at: Google Scholar
  57. M. Fujita, S. Sugama, K. Sekiyama et al., “A β-synuclein mutation linked to dementia produces neurodegeneration when expressed in mouse brain,” Nature Communications, vol. 1, no. 8, article 110, 2010. View at: Publisher Site | Google Scholar
  58. J. Wei, M. Fujita, M. Nakai et al., “Enhanced lysosomal pathology caused by β-synuclein mutants linked to dementia with Lewy bodies,” Journal of Biological Chemistry, vol. 282, no. 39, pp. 28904–28914, 2007. View at: Publisher Site | Google Scholar
  59. V. L. Buchman, H. J. Hunter, L. G. Pinon et al., “Persyn, a member of the synuclein family, has a distinct pattern of expression in the developing nervous system,” Journal of Neuroscience, vol. 18, no. 22, pp. 9335–9341, 1998. View at: Google Scholar
  60. M. Ahmad, S. Attoub, M. N. Singh, F. L. Martin, and O. M. A. El-Agnaf, “γ-synuclein and the progression of cancer,” Journal of the Federation of American Societies for Experimental Biology, vol. 21, no. 13, pp. 3419–3430, 2007. View at: Publisher Site | Google Scholar
  61. K. Nishioka, C. Wider, C. Vilariño-Güell et al., “Association of α-, β-, and γ-synuclein with diffuse Lewy body disease,” Archives of Neurology, vol. 67, no. 8, pp. 970–975, 2010. View at: Publisher Site | Google Scholar
  62. J. E. Galvin, K. Uryu, V. M. Y. Lee, and J. Q. Trojanowski, “Axon pathology in Parkinson's disease and Lewy body dementia hippocampus contains α-, β-, and γ-synuclein,” Proceedings of the National Academy of Sciences of the United States of America, vol. 96, no. 23, pp. 13450–13455, 1999. View at: Google Scholar
  63. N. Ninkina, O. Peters, S. Millership, H. Salem, H. van der Putten, and V. L. Buchman, “γ-synucleinopathy: neurodegeneration associated with overexpression of the mouse protein,” Human Molecular Genetics, vol. 18, no. 10, pp. 1779–1794, 2009. View at: Publisher Site | Google Scholar
  64. V. L. Buchman, J. Adu, L. G. P. Pinõn, N. N. Ninkina, and A. M. Davies, “Persyn, a member of the synuclein family, influences neurofilament network integrity,” Nature Neuroscience, vol. 1, no. 2, pp. 101–103, 1998. View at: Google Scholar
  65. O. M. El-Agnaf, S. A. Salem, K. E. Paleologou et al., “Alpha-synuclein implicated in Parkinson's disease is present in extracellular biological fluids, including human plasma,” Journal of the Federation of American Societies for Experimental Biology, vol. 17, no. 13, pp. 1945–1947, 2003. View at: Google Scholar
  66. H. J. Lee, S. Patel, and S. J. Lee, “Intravesicular localization and exocytosis of α-synuclein and its aggregates,” Journal of Neuroscience, vol. 25, no. 25, pp. 6016–6024, 2005. View at: Publisher Site | Google Scholar
  67. P. Desplats, H. J. Lee, E. J. Bae et al., “Inclusion formation and neuronal cell death through neuron-to-neuron transmission of α-synuclein,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 31, pp. 13010–13015, 2009. View at: Publisher Site | Google Scholar
  68. J. Y. Sung, S. M. Park, C. H. Lee et al., “Proteolytic cleavage of extracellular secreted α-synuclein via matrix metalloproteinases,” Journal of Biological Chemistry, vol. 280, no. 26, pp. 25216–25224, 2005. View at: Publisher Site | Google Scholar
  69. R. Borghi, R. Marchese, A. Negro et al., “Full length α-synuclein is present in cerebrospinal fluid from Parkinson's disease and normal subjects,” Neuroscience Letters, vol. 287, no. 1, pp. 65–67, 2000. View at: Publisher Site | Google Scholar
  70. B. Mollenhauer, V. Cullen, I. Kahn et al., “Direct quantification of CSF α-synuclein by ELISA and first cross-sectional study in patients with neurodegeneration,” Experimental Neurology, vol. 213, no. 2, pp. 315–325, 2008. View at: Publisher Site | Google Scholar
  71. E. B. Mukaetova-Ladinska, J. Milne, A. Andras et al., “Alpha- and gamma-synuclein proteins are present in cerebrospinal fluid and are increased in aged subjects with neurodegenerative and vascular changes,” Dementia and Geriatric Cognitive Disorders, vol. 26, no. 1, pp. 32–42, 2008. View at: Publisher Site | Google Scholar
  72. Z. Hong, M. Shi, K. A. Chung et al., “DJ-1 and α-synuclein in human cerebrospinal fluid as biomarkers of Parkinson's disease,” Brain, vol. 133, no. 3, pp. 713–726, 2010. View at: Publisher Site | Google Scholar
  73. C. Ballard, E. L. Jones, E. Londos, L. Minthon, P. Francis, and D. Aarsland, “α-synuclein antibodies recognize a protein present at lower levels in the CSF of patients with dementia with Lewy bodies,” International Psychogeriatrics, vol. 22, no. 2, pp. 321–327, 2010. View at: Publisher Site | Google Scholar
  74. T. Tokuda, M. M. Qureshi, M. T. Ardah et al., “Detection of elevated levels of α-synuclein oligomers in CSF from patients with Parkinson disease,” Neurology, vol. 75, no. 20, pp. 1766–1772, 2010. View at: Publisher Site | Google Scholar
  75. Q. X. Li, S. S. Mok, K. M. Laughton et al., “Plasma α-synuclein is decreased in subjects with Parkinson's disease,” Experimental Neurology, vol. 204, no. 2, pp. 583–588, 2007. View at: Publisher Site | Google Scholar
  76. O. M. A. El-Agnaf, S. A. Salem, K. E. Paleologou et al., “Detection of oligomeric forms of α-synuclein protein in human plasma as a potential biomarker for Parkinson's disease,” Journal of the Federation of American Societies for Experimental Biology, vol. 20, no. 3, pp. 419–425, 2006. View at: Publisher Site | Google Scholar
  77. A. W. Michell, L. M. Luheshi, and R. A. Barker, “Skin and platelet α-synuclein as peripheral biomarkers of Parkinson's disease,” Neuroscience Letters, vol. 381, no. 3, pp. 294–298, 2005. View at: Publisher Site | Google Scholar
  78. R. Barbour, K. Kling, J. P. Anderson et al., “Red blood cells are the major source of alpha-synuclein in blood,” Neurodegenerative Diseases, vol. 5, no. 2, pp. 55–59, 2008. View at: Publisher Site | Google Scholar
  79. D. Nagakubo, T. Taira, H. Kitaura et al., “DJ-1, a novel oncogene which transforms mouse NIH3T3 cells in cooperation with ras,” Biochemical and Biophysical Research Communications, vol. 231, no. 2, pp. 509–513, 1997. View at: Publisher Site | Google Scholar
  80. S. Shendelman, A. Jonason, C. Martinat, T. Leete, and A. Abeliovich, “DJ-1 Is a redox-dependent molecular chaperone that inhibits α-synuclein aggregate formation,” Public Library of Science, Biology, vol. 2, no. 11, article e362, 2004. View at: Publisher Site | Google Scholar
  81. K. Takahashi, T. Taira, T. Niki, C. Seino, S. M. M. Iguchi-Ariga, and H. Ariga, “DJ-1 positively regulates the androgen receptor by impairing the binding of PIASx α to the receptor,” Journal of Biological Chemistry, vol. 276, no. 40, pp. 37556–37563, 2001. View at: Publisher Site | Google Scholar
  82. Y. Shinbo, T. Niki, T. Taira et al., “Proper SUMO-1 conjugation is essential to DJ-1 to exert its full activities,” Cell Death and Differentiation, vol. 13, no. 1, pp. 96–108, 2006. View at: Publisher Site | Google Scholar
  83. R. H. Kim, P. D. Smith, H. Aleyasin et al., “Hypersensitivity of DJ-1-deficient mice to 1-methyl-4-phenyl-1,2,3,6- tetrahydropyrindine (MPTP) and oxidative stress,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 14, pp. 5215–5220, 2005. View at: Publisher Site | Google Scholar
  84. M. Meulener, A. J. Whitworth, C. E. Armstrong-Gold et al., “Drosophila DJ-1 mutants are selectively sensitive to environmental toxins associated with Parkinson's disease,” Current Biology, vol. 15, no. 17, pp. 1572–1577, 2005. View at: Publisher Site | Google Scholar
  85. V. Bonifati, P. Rizzu, M. J. van Baren et al., “Mutations in the DJ-1 gene associated with autosomal recessive early-onset parkinsonism,” Science, vol. 299, no. 5604, pp. 256–259, 2003. View at: Publisher Site | Google Scholar
  86. D. J. Moore, L. Zhang, T. M. Dawson, and V. L. Dawson, “A missense mutation (L166P) in DJ-1, linked to familial Parkinson's disease, confers reduced protein stability and impairs homo-oligomerization,” Journal of Neurochemistry, vol. 87, no. 6, pp. 1558–1567, 2003. View at: Google Scholar
  87. D. W. Miller, R. Ahmad, S. Hague et al., “L166P mutant DJ-1, causative for recessive Parkinson's disease, is degraded through the ubiquitin-proteasome system,” Journal of Biological Chemistry, vol. 278, no. 38, pp. 36588–36595, 2003. View at: Publisher Site | Google Scholar
  88. A. Arias Vásquez, K. Sleegers, M. C. J. Dekker et al., “A deletion in DJ-1 and the risk of dementia—a population-based survey,” Neuroscience Letters, vol. 372, no. 3, pp. 196–199, 2004. View at: Publisher Site | Google Scholar
  89. C. M. Morris, K. K. O'Brien, A. M. Gibson, J. A. Hardy, and A. B. Singleton, “Polymorphism in the human DJ-1 gene is not associated with sporadic dementia with Lewy bodies or Parkinson's disease,” Neuroscience Letters, vol. 352, no. 2, pp. 151–153, 2003. View at: Publisher Site | Google Scholar
  90. P. Rizzu, D. A. Hinkle, V. Zhukareva et al., “DJ-1 colocalizes with tau inclusions: a link between parkinsonism and dementia,” Annals of Neurology, vol. 55, no. 1, pp. 113–118, 2004. View at: Publisher Site | Google Scholar
  91. Y. Wang, J. S. Chandran, H. Cai, and M. P. Mattson, “DJ-1 is essential for long-term depression at hippocampal CA1 synapses,” NeuroMolecular Medicine, vol. 10, no. 1, pp. 40–45, 2008. View at: Publisher Site | Google Scholar
  92. M. Waragai, J. Wei, M. Fujita et al., “Increased level of DJ-1 in the cerebrospinal fluids of sporadic Parkinson's disease,” Biochemical and Biophysical Research Communications, vol. 345, no. 3, pp. 967–972, 2006. View at: Publisher Site | Google Scholar
  93. M. Waragai, M. Nakai, J. Wei et al., “Plasma levels of DJ-1 as a possible marker for progression of sporadic Parkinson's disease,” Neuroscience Letters, vol. 425, no. 1, pp. 18–22, 2007. View at: Publisher Site | Google Scholar
  94. L. Allard, P. R. Burkhard, P. Lescuyer et al., “PARK7 and nucleoside diphosphate kinase A as plasma markers for the early diagnosis of stroke,” Clinical Chemistry, vol. 51, no. 11, pp. 2043–2051, 2005. View at: Publisher Site | Google Scholar
  95. S. Koide-Yoshida, T. Niki, M. Ueda et al., “DJ-1 degrades transthyretin and an inactive form of DJ-1 is secreted in familial amyloidotic polyneuropathy,” International Journal of Molecular Medicine, vol. 19, no. 6, pp. 885–893, 2007. View at: Google Scholar
  96. H. Liu, M. Wang, M. Li et al., “Expression and role of DJ-1 in leukemia,” Biochemical and Biophysical Research Communications, vol. 375, no. 3, pp. 477–483, 2008. View at: Publisher Site | Google Scholar
  97. J. Choi, M. C. Sullards, J. A. Olzmann et al., “Oxidative damage of DJ-1 is linked to sporadic Parkinson and Alzheimer diseases,” Journal of Biological Chemistry, vol. 281, no. 16, pp. 10816–10824, 2006. View at: Publisher Site | Google Scholar
  98. E. Sidransky, “Gaucher disease: complexity in a "simple" disorder,” Molecular Genetics and Metabolism, vol. 83, no. 1–2, pp. 6–15, 2004. View at: Publisher Site | Google Scholar
  99. O. Goker-Alpan, R. Schiffmann, M. E. LaMarca, R. L. Nussbaum, A. McInerney-Leo, and E. Sidransky, “Parkinsonism among Gaucher disease carriers,” Journal of Medical Genetics, vol. 41, no. 12, pp. 937–940, 2004. View at: Publisher Site | Google Scholar
  100. A. Halperin, D. Elstein, and A. Zimran, “Increased incidence of Parkinson disease among relatives of patients with Gaucher disease,” Blood Cells, Molecules, and Diseases, vol. 36, no. 3, pp. 426–428, 2006. View at: Publisher Site | Google Scholar
  101. J. Aharon-Peretz, S. Badarny, H. Rosenbaum, and R. Gershoni-Baruch, “Mutations in the glucocerebrosidase gene and Parkinson disease: phenotype-genotype correlation,” Neurology, vol. 65, no. 9, pp. 1460–1461, 2005. View at: Publisher Site | Google Scholar
  102. J. Aharon-Peretz, H. Rosenbaum, and R. Gershoni-Baruch, “Mutations in the glucocerebrosidase gene and Parkinson's disease in Ashkenazi Jews,” The New England Journal of Medicine, vol. 351, no. 19, pp. 1972–1977, 2004. View at: Publisher Site | Google Scholar
  103. A. Lwin, E. Orvisky, O. Goker-Alpan, M. E. LaMarca, and E. Sidransky, “Glucocerebrosidase mutations in subjects with parkinsonism,” Molecular Genetics and Metabolism, vol. 81, no. 1, pp. 70–73, 2004. View at: Publisher Site | Google Scholar
  104. Z. Gan-Or, N. Giladi, U. Rozovski et al., “Genotype-phenotype correlations between GBA mutations and Parkinson disease risk and onset,” Neurology, vol. 70, no. 24, pp. 2277–2283, 2008. View at: Publisher Site | Google Scholar
  105. E. Sidransky, M. A. Nalls, J. O. Aasly et al., “Multicenter analysis of glucocerebrosidase mutations in Parkinson's disease,” The New England Journal of Medicine, vol. 361, no. 17, pp. 1651–1661, 2009. View at: Publisher Site | Google Scholar
  106. J. Neumann, J. Bras, E. Deas et al., “Glucocerebrosidase mutations in clinical and pathologically proven Parkinson's disease,” Brain, vol. 132, no. 7, pp. 1783–1794, 2009. View at: Publisher Site | Google Scholar
  107. Z. Gan-Or, N. Giladi, and A. Orr-Urtreger, “Differential phenotype in Parkinson's disease patients with severe versus mild GBA mutations,” Brain, vol. 132, no. 10, article e125, 2009. View at: Publisher Site | Google Scholar
  108. L. N. Clark, L. A. Kartsaklis, R. W. Gilbert et al., “Association of glucocerebrosidase mutations with dementia with Lewy bodies,” Archives of Neurology, vol. 66, no. 5, pp. 578–583, 2009. View at: Publisher Site | Google Scholar
  109. O. Goker-Alpan, B. I. Giasson, M. J. Eblan et al., “Glucocerebrosidase mutations are an important risk factor for Lewy body disorders,” Neurology, vol. 67, no. 5, pp. 908–910, 2006. View at: Publisher Site | Google Scholar
  110. L. Alvarez-Erviti, M. C. Rodriguez-Oroz, J. M. Cooper et al., “Chaperone-mediated autophagy markers in Parkinson disease brains,” Archives of Neurology, vol. 67, no. 12, pp. 1464–1472, 2010. View at: Publisher Site | Google Scholar
  111. A. M. Cuervo, L. Stafanis, R. Fredenburg, P. T. Lansbury, and D. Sulzer, “Impaired degradation of mutant α-synuclein by chaperone-mediated autophagy,” Science, vol. 305, no. 5688, pp. 1292–1295, 2004. View at: Publisher Site | Google Scholar
  112. S. K. Mak, A. L. McCormack, A. B. Manning-Bog, A. M. Cuervo, and D. A. Di Monte, “Lysosomal degradation of α-synuclein in vivo,” Journal of Biological Chemistry, vol. 285, no. 18, pp. 13621–13629, 2010. View at: Publisher Site | Google Scholar
  113. K. Hruska, O. Goker-Alpan, and E. Sidransky, “Gaucher disease and the synucleinopathies,” Journal of Biomedicine and Biotechnology, vol. 2006, no. 3, Article ID 78549, 2006. View at: Publisher Site | Google Scholar
  114. K. Wong, E. Sidransky, A. Verma et al., “Neuropathology provides clues to the pathophysiology of Gaucher disease,” Molecular Genetics and Metabolism, vol. 82, no. 3, pp. 192–207, 2004. View at: Publisher Site | Google Scholar
  115. I. Ron, D. Rapaport, and M. Horowitz, “Interaction between parkin and mutant glucocerebrosidase variants: a possible link between Parkinson disease and Gaucher disease,” Human Molecular Genetics, vol. 19, no. 19, pp. 3771–3781, 2010. View at: Publisher Site | Google Scholar
  116. M. Migita, H. Hamada, J. Fujimura, A. Watanabe, T. Shimada, and Y. Fukunaga, “Glucocerebrosidase level in the cerebrospinal fluid during enzyme replacement therapy—unsuccessful treatment of the neurological abnormality in type 2 Gaucher disease,” European Journal of Pediatrics, vol. 162, no. 7–8, pp. 524–525, 2003. View at: Publisher Site | Google Scholar
  117. C. Balducci, L. Pierguidi, E. Persichetti et al., “Lysosomal hydrolases in cerebrospinal fluid from subjects with Parkinson's disease,” Movement Disorders, vol. 22, no. 10, pp. 1481–1484, 2007. View at: Publisher Site | Google Scholar
  118. L. Parnetti, C. Balducci, L. Pierguidi et al., “Cerebrospinal fluid β-glucocerebrosidase activity is reduced in dementia with Lewy Bodies,” Neurobiology of Disease, vol. 34, no. 3, pp. 484–486, 2009. View at: Publisher Site | Google Scholar
  119. G. J. Ho, R. Drego, E. Hakimian, and E. Masliah, “Mechanisms of cell signaling and inflammation in Alzheimer's disease,” Current Drug Targets—Inflammation and Allergy, vol. 4, no. 2, pp. 247–256, 2005. View at: Publisher Site | Google Scholar
  120. K. M. Mattila, J. O. Rinne, T. Lehtimäki, M. Röyttä, J. P. Ahonen, and M. Hurme, “Association of an interleukin 1B gene polymorphism (-511) with Parkinson's disease in Finnish patients,” Journal of Medical Genetics, vol. 39, no. 6, pp. 400–402, 2002. View at: Google Scholar
  121. A. D. Wahner, J. S. Sinsheimer, J. M. Bronstein, and B. Ritz, “Inflammatory cytokine gene polymorphisms and increased risk of Parkinson disease,” Archives of Neurology, vol. 64, no. 6, pp. 836–840, 2007. View at: Publisher Site | Google Scholar
  122. M. Nishimura, I. Mizuta, E. Mizuta, S. Yamasaki, M. Ohta, and S. Kuno, “Influence of interleukin-1β gene polymorphisms on age-at-onset of sporadic Parkinson's disease,” Neuroscience Letters, vol. 284, no. 1–2, pp. 73–76, 2000. View at: Publisher Site | Google Scholar
  123. X. Su, K. A. Maguire-Zeiss, R. Giuliano, L. Prifti, K. Venkatesh, and H. J. Federoff, “Synuclein activates microglia in a model of Parkinson's disease,” Neurobiology of Aging, vol. 29, no. 11, pp. 1690–1701, 2008. View at: Publisher Site | Google Scholar
  124. D. Blum-Degena, T. Müller, W. Kuhn, M. Gerlach, H. Przuntek, and P. Riederer, “Interleukin-1β and interleukin-6 are elevated in the cerebrospinal fluid of Alzheimer's and de novo Parkinson's disease patients,” Neuroscience Letters, vol. 202, no. 1–2, pp. 17–20, 1995. View at: Publisher Site | Google Scholar
  125. T. Müller, D. Blum-Degen, H. Przuntek, and W. Kuhn, “Interleukin-6 levels in cerebrospinal fluid inversely correlate to severity of Parkinson's disease,” Acta Neurologica Scandinavica, vol. 98, no. 2, pp. 142–144, 1998. View at: Google Scholar
  126. M. Mogi, M. Harada, P. Riederer, H. Narabayashi, K. Fujita, and T. Nagatsu, “Tumor necrosis factor-α (TNF-α) increases both in the brain and in the cerebrospinal fluid from parkinsonian patients,” Neuroscience Letters, vol. 165, no. 1–2, pp. 208–210, 1994. View at: Publisher Site | Google Scholar
  127. H. Chen, E. J. O'Reilly, M. A. Schwarzschild, and A. Ascherio, “Peripheral inflammatory biomarkers and risk of Parkinson's disease,” American Journal of Epidemiology, vol. 167, no. 1, pp. 90–95, 2008. View at: Publisher Site | Google Scholar
  128. E. Gómez-Tortosa, I. Gonzalo, S. Fanjul et al., “Cerebrospinal fluid markers in dementia with Lewy bodies compared with Alzheimer disease,” Archives of Neurology, vol. 60, no. 9, pp. 1218–1222, 2003. View at: Publisher Site | Google Scholar
  129. Q. Liu, F. Xie, S. L. Siedlak et al., “Neurofilament proteins in neurodegenerative diseases,” Cellular and Molecular Life Sciences, vol. 61, no. 24, pp. 3057–3075, 2004. View at: Publisher Site | Google Scholar
  130. C. Lavedan, S. Buchholtz, R. L. Nussbaum, R. L. Albin, and M. H. Polymeropoulos, “A mutation in the human neurofilament M gene in Parkinson's disease that suggests a role for the cytoskeleton in neuronal degeneration,” Neuroscience Letters, vol. 322, no. 1, pp. 57–61, 2002. View at: Publisher Site | Google Scholar
  131. M. L. Schmidt, J. Murray, V. M. Y. Lee, W. D. Hill, A. Wertkin, and J. Q. Trojanowski, “Epitope map of neurofilament protein domains in cortical and peripheral nervous system Lewy bodies,” American Journal of Pathology, vol. 139, no. 1, pp. 53–65, 1991. View at: Google Scholar
  132. B. Holmberg, L. Rosengren, J. E. Karlsson, and B. Johnels, “Increased cerebrospinal fluid levels of neurofilament protein in progressive supranuclear palsy and multiple-system atrophy compared with Parkinson's disease,” Movement Disorders, vol. 13, no. 1, pp. 70–77, 1998. View at: Publisher Site | Google Scholar
  133. H. Tohgi, T. Abe, K. Hashiguchi, M. Saheki, and S. Takahashi, “Remarkable reduction in acetylcholine concentration in the cerebrospinal fluid from patients with Alzheimer type dementia,” Neuroscience Letters, vol. 177, no. 1–2, pp. 139–142, 1994. View at: Publisher Site | Google Scholar
  134. M. J. Welch, C. H. Markham, and D. J. Jenden, “Acetylcholine and choline in cerebrospinal fluid of patients with Parkinson's disease and Huntington's chorea,” Journal of Neurology Neurosurgery and Psychiatry, vol. 39, no. 4, pp. 367–374, 1976. View at: Google Scholar
  135. H. Shimada, S. Hirano, H. Shinotoh et al., “Mapping of brain acetylcholinesterase alterations in Lewy body disease by PET,” Neurology, vol. 73, no. 4, pp. 273–278, 2009. View at: Publisher Site | Google Scholar
  136. G. Lunardi, S. Galati, D. Tropepi et al., “Correlation between changes in CSF dopamine turnover and development of dyskinesia in Parkinson's disease,” Parkinsonism and Related Disorders, vol. 15, no. 5, pp. 383–389, 2009. View at: Publisher Site | Google Scholar
  137. K. Kanemaru and H. Yamanouchi, “Assessment of CSF homovanillic acid levels distinguishes dementia with Lewy bodies from Alzheimer's disease,” Journal of Neurology, vol. 249, no. 8, pp. 1125–1126, 2002. View at: Publisher Site | Google Scholar
  138. X. S. Hu, N. Okamura, H. Arai et al., “18F-fluorodopa PET study of striatal dopamine uptake in the diagnosis of dementia with Lewy bodies,” Neurology, vol. 55, no. 10, pp. 1575–1577, 2000. View at: Google Scholar
  139. Z. Walker, E. Jaros, R. W. H. Walker et al., “Dementia with Lewy bodies: a comparison of clinical diagnosis, FP-CIT single photon emission computed tomography imaging and autopsy,” Journal of Neurology, Neurosurgery and Psychiatry, vol. 78, no. 11, pp. 1176–1181, 2007. View at: Publisher Site | Google Scholar
  140. J. T. O'Brien, S. Colloby, J. Fenwick et al., “Dopamine transporter loss visualized with FP-CIT SPECT in the differential diagnosis of dementia with Lewy bodies,” Archives of Neurology, vol. 61, no. 6, pp. 919–925, 2004. View at: Publisher Site | Google Scholar
  141. I. McKeith, J. O'Brien, Z. Walker et al., “Sensitivity and specificity of dopamine transporter imaging with I-FP-CIT SPECT in dementia with Lewy bodies: a phase III, multicentre study,” The Lancet Neurology, vol. 6, no. 4, pp. 305–313, 2007. View at: Publisher Site | Google Scholar
  142. F. Roselli, N. M. Pisciotta, R. Perneczky et al., “Severity of neuropsychiatric symptoms and dopamine transporter levels in dementia with Lewy bodies: a 123I-FP-CIT SPECT study,” Movement Disorders, vol. 24, no. 14, pp. 2097–2103, 2009. View at: Publisher Site | Google Scholar
  143. M. Yoshita, J. Taki, and M. Yamada, “A clinical role for [(123)I]MIBG myocardial scintigraphy in the distinction between dementia of the Alzheimer's-type and dementia with Lewy bodies,” Journal of Neurology Neurosurgery and Psychiatry, vol. 71, no. 5, pp. 583–588, 2001. View at: Publisher Site | Google Scholar
  144. K. Wada-Isoe, M. Kitayama, K. Nakaso, and K. Nakashima, “Diagnostic markers for diagnosing dementia with Lewy bodies: CSF and MIBG cardiac scintigraphy study,” Journal of the Neurological Sciences, vol. 260, no. 1–2, pp. 33–37, 2007. View at: Publisher Site | Google Scholar
  145. H. Watanabe, T. Ieda, T. Katayama et al., “Cardiac (123)I-meta-iodobenzylguanidine (MIBG) uptake in dementia with Lewy bodies: comparison with Alzheimer's disease,” Journal of Neurology Neurosurgery and Psychiatry, vol. 70, no. 6, pp. 781–783, 2001. View at: Publisher Site | Google Scholar
  146. M. Yoshita, J. Taki, K. Yokoyama et al., “Value of 123I-MIBG radioactivity in the differential diagnosis of DLB from AD,” Neurology, vol. 66, no. 12, pp. 1850–1854, 2006. View at: Publisher Site | Google Scholar
  147. H. Hanyu, S. Shimizu, K. Hirao et al., “Comparative value of brain perfusion SPECT and [(123)I]MIBG myocardial scintigraphy in distinguishing between dementia with Lewy bodies and Alzheimer's disease,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 33, no. 3, pp. 248–253, 2006. View at: Publisher Site | Google Scholar
  148. M. Estorch, V. Camacho, P. Paredes et al., “Cardiac (123)I-metaiodobenzylguanidine imaging allows early identification of dementia with Lewy bodies during life,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 35, no. 9, pp. 1636–1641, 2008. View at: Publisher Site | Google Scholar
  149. S. Kobayashi, M. Tateno, H. Morii, K. Utsumi, and T. Saito, “Decreased cardiac MIBG uptake, its correlation with clinical symptoms in dementia with Lewy bodies,” Psychiatry Research, vol. 174, no. 1, pp. 76–80, 2009. View at: Publisher Site | Google Scholar
  150. R. Watson, A. M. Blamire, and J. T. O'Brien, “Magnetic resonance imaging in Lewy body dementias,” Dementia and Geriatric Cognitive Disorders, vol. 28, no. 6, pp. 493–506, 2009. View at: Publisher Site | Google Scholar
  151. E. J. Burton, I. G. McKeith, D. J. Burn, E. D. Williams, and J. T. O'Brien, “Cerebral atrophy in Parkinson's disease with and without dementia: a comparison with Alzheimer's disease, dementia with Lewy bodies and controls,” Brain, vol. 127, no. 4, pp. 791–800, 2004. View at: Publisher Site | Google Scholar
  152. J. T. O'Brien, S. Paling, R. Barber et al., “Progressive brain atrophy on serial MRI in dementia with Lewy bodies, AD, and vascular dementia,” Neurology, vol. 56, no. 10, pp. 1386–1388, 2001. View at: Google Scholar
  153. E. J. Burton, I. G. McKeith, D. J. Burn, and J. T. O'Brien, “Brain atrophy rates in Parkinson's disease with and without dementia using serial magnetic resonance imaging,” Movement Disorders, vol. 20, no. 12, pp. 1571–1576, 2005. View at: Publisher Site | Google Scholar
  154. F. Sabattoli, M. Boccardi, S. Galluzzi, A. Treves, P. M. Thompson, and G. B. Frisoni, “Hippocampal shape differences in dementia with Lewy bodies,” NeuroImage, vol. 41, no. 3, pp. 699–705, 2008. View at: Publisher Site | Google Scholar
  155. M. J. Firbank, A. M. Blamire, M. S. Krishnan et al., “Diffusion tensor imaging in dementia with Lewy bodies and Alzheimer's disease,” Psychiatry Research, vol. 155, no. 2, pp. 135–145, 2007. View at: Publisher Site | Google Scholar
  156. K. Lobotesis, J. D. Fenwick, A. Phipps et al., “Occipital hypoperfusion on SPECT in dementia with Lewy bodies but not AD,” Neurology, vol. 56, no. 5, pp. 643–649, 2001. View at: Google Scholar
  157. S. J. Colloby, J. D. Fenwick, D. E. Williams et al., “A comparison of (99m)Tc-HMPAO SPET changes in dementia with Lewy bodies and Alzheimer's disease using statistical parametric mapping,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 29, no. 5, pp. 615–622, 2002. View at: Publisher Site | Google Scholar
  158. J. Hardy, P. Lewis, T. Revesz, A. Lees, and C. Paisan-Ruiz, “The genetics of Parkinson's syndromes: a critical review,” Current Opinion in Genetics and Development, vol. 19, no. 3, pp. 254–265, 2009. View at: Publisher Site | Google Scholar
  159. D. MacLeod, J. Dowman, R. Hammond, T. Leete, K. Inoue, and A. Abeliovich, “The familial parkinsonism gene LRRK2 regulates neurite process morphology,” Neuron, vol. 52, no. 4, pp. 587–593, 2006. View at: Publisher Site | Google Scholar
  160. C. H. Lin, P. I. Tsai, R. M. Wu, and C. T. Chien, “LRRK2 G2019S mutation induces dendrite degeneration through mislocalization and phosphorylation of tau by recruiting autoactivated GSK3β,” Journal of Neuroscience, vol. 30, no. 39, pp. 13138–13149, 2010. View at: Publisher Site | Google Scholar
  161. H. L. Melrose, J. C. Dächsel, B. Behrouz et al., “Impaired dopaminergic neurotransmission and microtubule-associated protein tau alterations in human LRRK2 transgenic mice,” Neurobiology of Disease, vol. 40, no. 3, pp. 503–517, 2010. View at: Publisher Site | Google Scholar
  162. X. Lin, L. Parisiadou, X. L. Gu et al., “Leucine-rich repeat kinase 2 regulates the progression of neuropathology induced by Parkinson's-disease-related mutant α-synuclein,” Neuron, vol. 64, no. 6, pp. 807–827, 2009. View at: Publisher Site | Google Scholar
  163. T. Duka, V. Duka, J. N. Joyce, and A. Sidhu, “α-synuclein contributes to GSK-3β-catalyzed tau phosphorylation in Parkinson's disease models,” Journal of the Federation of American Societies for Experimental Biology, vol. 23, no. 9, pp. 2820–2830, 2009. View at: Publisher Site | Google Scholar
  164. X. Zhu, A. Babar, S. L. Siedlak et al., “LRRK2 in Parkinson's disease and dementia with Lewy bodies,” Molecular Neurodegeneration, vol. 1, no. 17, 2006. View at: Publisher Site | Google Scholar
  165. H. Qing, Y. Zhang, Y. Deng, E. G. McGeer, and P. L. McGeer, “Lrrk2 interaction with α-synuclein in diffuse Lewy body disease,” Biochemical and Biophysical Research Communications, vol. 390, no. 4, pp. 1229–1234, 2009. View at: Publisher Site | Google Scholar
  166. J. Simón-Sánchez, C. Schulte, J. M. Bras et al., “Genome-wide association study reveals genetic risk underlying Parkinson's disease,” Nature Genetics, vol. 41, no. 12, pp. 1308–1312, 2009. View at: Publisher Site | Google Scholar
  167. W. Satake, Y. Nakabayashi, I. Mizuta et al., “Genome-wide association study identifies common variants at four loci as genetic risk factors for Parkinson's disease,” Nature Genetics, vol. 41, no. 12, pp. 1303–1307, 2009. View at: Publisher Site | Google Scholar
  168. S. DiMauro and E. A. Schon, “Mitochondrial respiratory-chain diseases,” The New England Journal of Medicine, vol. 348, no. 26, pp. 2656–2668, 2003. View at: Publisher Site | Google Scholar
  169. C. Vives-Bauza and S. Przedborski, “Mitophagy: the latest problem for Parkinson's disease,” Trends in Molecular Medicine, vol. 17, no. 3, pp. 158–165, 2011. View at: Publisher Site | Google Scholar
  170. N. Matsuda, S. Sato, K. Shiba et al., “PINK1 stabilized by mitochondrial depolarization recruits Parkin to damaged mitochondria and activates latent Parkin for mitophagy,” Journal of Cell Biology, vol. 189, no. 2, pp. 211–221, 2010. View at: Publisher Site | Google Scholar
  171. D. P. Narendra, S. M. Jin, A. Tanaka et al., “PINK1 is selectively stabilized on impaired mitochondria to activate Parkin,” Public Library of Science, Biology, vol. 8, no. 1, Article ID e1000298., 2010. View at: Publisher Site | Google Scholar
  172. J. Park, S. B. Lee, S. Lee et al., “Mitochondrial dysfunction in Drosophila PINK1 mutants is complemented by parkin,” Nature, vol. 441, no. 7097, pp. 1157–1161, 2006. View at: Publisher Site | Google Scholar
  173. J. Y. Lee, Y. Nagano, J. P. Taylor, K. L. Lim, and T. P. Yao, “Disease-causing mutations in parkin impair mitochondrial ubiquitination, aggregation, and HDAC6-dependent mitophagy,” Journal of Cell Biology, vol. 189, no. 4, pp. 671–679, 2010. View at: Publisher Site | Google Scholar
  174. M. M. M. Wilhelmus, S. M. A. Van Der Pol, Q. Jansen et al., “Association of Parkinson disease-related protein PINK1 with Alzheimer disease and multiple sclerosis brain lesions,” Free Radical Biology and Medicine, vol. 50, no. 3, pp. 469–476, 2011. View at: Publisher Site | Google Scholar
  175. M. E. Witte, J. G. J. M. Bol, W. H. Gerritsen et al., “Parkinson's disease-associated parkin colocalizes with Alzheimer's disease and multiple sclerosis brain lesions,” Neurobiology of Disease, vol. 36, no. 3, pp. 445–452, 2009. View at: Publisher Site | Google Scholar
  176. C. R. Scherzer, R. V. Jensen, S. R. Gullans, and M. B. Feany, “Gene expression changes presage neurodegeneration in a Drosophila model of Parkinson's disease,” Human Molecular Genetics, vol. 12, no. 19, pp. 2457–2466, 2003. View at: Publisher Site | Google Scholar
  177. L. Lu, F. Neff, D. Alvarez-Fischer et al., “Gene expression profiling of Lewy body-bearing neurons in Parkinson's disease,” Experimental Neurology, vol. 195, no. 1, pp. 27–39, 2005. View at: Publisher Site | Google Scholar
  178. M. Shi, W. M. Caudle, and J. Zhang, “Biomarker discovery in neurodegenerative diseases: a proteomic approach,” Neurobiology of Disease, vol. 35, no. 2, pp. 157–164, 2009. View at: Publisher Site | Google Scholar
  179. J. Jin, G. E. Meredith, L. Chen et al., “Quantitative proteomic analysis of mitochondrial proteins: relevance to Lewy body formation and Parkinson's disease,” Molecular Brain Research, vol. 134, no. 1, pp. 119–138, 2005. View at: Publisher Site | Google Scholar
  180. M. Basso, S. Giraudo, D. Corpillo, B. Bergamasco, L. Lopiano, and M. Fasano, “Proteome analysis of human substantia nigra in Parkinson's disease,” Proteomics, vol. 4, no. 12, pp. 3943–3952, 2004. View at: Publisher Site | Google Scholar
  181. M. Shi, J. Jin, Y. Wang et al., “Mortalin: a protein associated with progression of Parkinson disease?” Journal of Neuropathology and Experimental Neurology, vol. 67, no. 2, pp. 117–124, 2008. View at: Publisher Site | Google Scholar
  182. J. B. Leverenz, I. Umar, Q. Wang et al., “Proteomic identification of novel proteins in cortical Lewy bodies,” Brain Pathology, vol. 17, no. 2, pp. 139–145, 2007. View at: Publisher Site | Google Scholar
  183. F. Abdi, J. F. Quinn, J. Jankovic et al., “Detection of biomarkers with a multiplex quantitative proteomic platform in cerebrospinal fluid of patients with neurodegenerative disorders,” Journal of Alzheimer's Disease, vol. 9, no. 3, pp. 293–348, 2006. View at: Google Scholar
  184. K. Wada-Isoe, K. Michio, K. Imamura et al., “Serum proteomic profiling of dementia with Lewy bodies: diagnostic potential of SELDI-TOF MS analysis,” Journal of Neural Transmission, vol. 114, no. 12, pp. 1579–1583, 2007. View at: Publisher Site | Google Scholar
  185. M. E. Bianchi, “DAMPs, PAMPs and alarmins: all we need to know about danger,” Journal of Leukocyte Biology, vol. 81, no. 1, pp. 1–5, 2007. View at: Publisher Site | Google Scholar

Copyright © 2011 Gilbert J. Ho et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

More related articles

2009 Views | 593 Downloads | 3 Citations
 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.