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Relationship: 904


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

N/A, Mitochondrial dysfunction 1 leads to Impaired, Proteostasis

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Inhibition of the mitochondrial complex I of nigro-striatal neurons leads to parkinsonian motor deficits adjacent Moderate Low Cataia Ives (send email) Open for citation & comment TFHA/WNT Endorsed
Mitochondrial complex inhibition leading to liver injury adjacent Not Specified Not Specified Arthur Author (send email) Under development: Not open for comment. Do not cite

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

In any cell type, including neurons, the protein homeostasis (proteostasis) plays a key role in cellular functions. There are two major systems involved in the removal of damaged cellular structures (e.g. defective mitochondria) and misfolded or damaged proteins, the ubiquitin-proteasome system (UPS) and the autophagy–lysosome pathway (ALP). These processes are highly energy demanding and highly susceptible to oxidative stress. Upon mitochondrial dysfunction UPS and ALP functions are compromised resulting in increased protein aggregation and impaired intracellular protein/organelles transport (e.g. Zaltieri et al., 2015; Song and Cortopassi, 2015; Fujita et al., 2014; Esteves et al., 2011; Sherer et al., 2002).

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help

The weight of evidence supporting the relationship between mitochondrial dysfunction and impaired proteostasis, including the impaired function of UPS and ALP that results in decreased protein degradation and increase protein aggregation is strong.

Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

The biological relationship between Mitochondrial dysfunction and Impaired proteostasis (unbalanced protein homeostasis) that involves dysregulation of proteins degradation (misfolded or damaged) as well as removal of cell organelles is partly understood. Under physiological conditions, mechanisms by which proteostasis is ensured include regulated protein translation, chaperone assisted protein folding and functional protein degradation pathways. Under oxidative stress, the proteostasis function becomes burdened with proteins modified by ROS (Powers et al., 2009; Zaltieri et al., 2015). These changed proteins can lead to further misfolding and aggregation of proteins (especially in non-dividing cells, like neurons). Particularly in DA cells, oxidative stress from dopamine metabolism and dopamine auto-oxidation may selectively increase their vulnerability to CI inhibitors (such as rotenone) and cause additional deregulation of protein degradation (Lotharius and Brundin, 2002; Esteves et al., 2011). As most oxidized proteins get degraded by UPS and ALP (McNaught and Jenner, 2001), mitochondrial dysfunction and subsequent deregulation of proteostasis play a pivotal role in the pathogenesis of PD (Dagda et al., 2013; Pan et al., 2008; Fornai et al., 2005; Sherer et al., 2002). It is also well documented that increased oxidative stress changes the protein degradation machinery and leads to a reduction of proteasome activity (Lin and Beal, 2006; Schapira, 2006).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help
  • The exact molecular link from mitochondrial dysfunction to disturbed proteostasis is not known. It is not clear which is the oxidative modification that drives the process.
  • The sequence of events taking place after inhibition of CI is not entirely clear (Zaltieri et al., 2015). Some studies suggest that induced oxidative stress leads to α-synuclein aggregation that triggers proteosomal dysfunction (Betarbet et al., 2006). Such order of events is suggested to take place in vivo (McNaught and Jenner, 2001). However, in other studies opposite sequence of events is proposed suggesting that first proteosomal dysfunction take place that leads to α-synuclein aggregation.

A vicious circle is observed here as α-synuclein aggregation potentiates proteosomal dysfunction and v/v. In this vicious cycle it is difficult to establish exact quantitative relationship of these two events.

  • Whether α-synuclein is a substrate for proteasome remains controversial since both positive and negative data have been reported (Paxinou et al., 2001). Furthermore, polyubiquitination of α-synuclein, a prerequisite for 26S proteasomal degradation has yet to be reported (Stefanis et al., 2001). It is also not clear whether polyubiquitination of α-synuclein is necessary for its degradation. However, α-synuclein gets targeted by the UPS in the SHSY5Y neuroblastoma cell line. Phosphorylated α-synuclein gets targeted to mono- or di-ubiquitination in synucleinopathy brains (Hasegawa et al., 2002), but it is not clear if this modification can play any role in proteasomal degradation since monoubiquitination of proteins serves mainly as a signal for endocytosis or membrane trafficking.
  • On the contrary to the increased α-synuclein levels observed in the midbrain, decreased α-synuclein levels were found in the cerebellums of PD patients when compared to controls, suggesting an imbalance of α-synuclein levels in different parts of the brain (Westerlund et al., 2008).
  • Although mitochondrial alterations have been reported in PD patients (Ikawa et al., 2011) and disease models, it is not clear whether they represent a primary pathogenic mechanism. In particular, the critical interplay between mitochondrial dysfunction and oxidative stress, which has been widely reported in PD (Dias et al., 2013) and could constitute either a cause or a consequence of mitochondrial damage, hampers an effective comprehension of the above mentioned studies. Oxidative stress can constitute a bridge connecting mitochondrial dysfunction to the induction of α-synuclein misfolding, aggregation, and accumulation, but otherwise it may be also triggered by these latter events that in turn could induce mitochondrial alterations (Zhu and Chu, 2010; Dias et al., 2013).
  • It is still unclear whether the involvement of α-synuclein in chronic MPTP toxicity reflects a physiological function for α-synuclein that has been activated in the wrong context, or whether α-synuclein produces an accidental pathogenicity that contributes to MPTP toxicity but is unrelated to the normal function of α-synuclein (Fornai et al., 2005).
  • The inconsistent effects of MPP+ on autophagy (up or down regulation) are reported. It may be attributed to differences observed between immortalized cell lines and primary neurons, different timing or dose. While dysregulation of autophagy is always described, the direction is not clear. Further studies are required to clarify this issue.
  • MPTP administration does not induce Lewy body formation (in contrast to rotenone) characteristic of PD, even after repeated injections (Drolet et al., 2004; Dauer et al., 2002).
  • There is also controversy over whether the increase in autophagic markers is protective or, on the contrary, causative of neuronal death.
  • MPP+ may have effects apart from CI inhibition, e.g., on microtubules but it is still unclear whether this is a primary effect. Indeed, MPP+ binds to microtubules in PC12 cells and inhibits their polymerization and stability (Cappelletti et al., 1999; Cappelletti et al., 2001).
  • It is not clear whether microtubules disruption may be associated with α-synuclein aggregation since tubulin was shown to co-localize with α-synuclein in Lewy bodies. Furthermore, tubulin folding is dependent on ATP and GTP hydrolysis, and mitochondrial dysfunction with subsequent energy failure could trigger microtubules disruption. Cytoskeletal microtubule (MT) injury is likely to be responsible for altered rearrangement and movement of cell organelles, being a common feature of several neurodegenerative diseases including PD (Wade, 2009; Mattson et al., 1999).
  • It is not clear whether rotenone could cause microtubules depolymerization in vivo and in vitro (Brinkley et al., 1974) by binding to the colchicine site on tubulin heterodimers (Marshall et al., 1978). Ren and Feng (2007) found that microtubule depolymerization induced by rotenone caused vesicle accumulation in the soma and kills neurons.
Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

The ubiquitin proteasome system is highly conserved in eukaryotes, from yeast to human. Ubiquitin is a small (8.5 kDa) regulatory protein that has been found in almost all tissues of eukaryotic organisms. For instance, drosophila has been used as PD model to study the role of ubiquitin in α-synuclein induced-toxicity (Lee et al., 2009). Human and yeast ubiquitin share 96% sequence identity. Neither ubiquitin nor the ubiquitination machinery are known to exist in prokaryotes. Autophagy is ubiquitous in eukaryotic cells and is the major mechanism involved in the clearance of oxidatively or otherwise damaged/worn-out macromolecules and organelles (Esteves et al., 2011). Due to the high degree of conservation, most of the knowledge on autophagy proteins in vertebrates is derived from studies in yeast (Klionsky et al., 2007). Autophagy is seen in all eukaryotic systems, including fungi, plants, slime mold, nematodes, fruit flies and insects, rodents (i.e., laboratory mice and rats), and humans. It is a fundamental and phylogenetically conserved self-degradation process that is characterized by the formation of double-layered vesicles (autophagosomes) around intracellular cargo for delivery to lysosomes and proteolytic degradation.


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Alvarez-Erviti L, Rodriguez-Oroz MC, Cooper JM et al. 2010. Chaperone-mediated autophagy markers in Parkinson disease brains. Arch Neurol. 67:1464–1472.

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Betarbet R, Canet-Aviles RM, Sherer TB, Mastroberardino PG, McLendon C, Kim JH, et al. 2006. Intersecting pathways to neurodegeneration in Parkinson’s disease: effects of the pesticide rotenone on DJ-1, α-synuclein, and the ubiquitin–proteasome system. Neurobiol Dis. 22:404–20.

Betarbet R., Sherer T.B., Greenamyre J.T. Ubiquitin-proteasome system and Parkinson's diseases. Exp. Neurol., 191 (Suppl.) (2005), pp. S17–S27

Betarbet R, Sherer TB, MacKenzie G, Garcia-Osuna M, Panov AV, Greenamyre JT. 2000. Chronic systemic pesticide exposure reproduces features of Parkinson’s disease. Nat Neurosci. 3:1301–6.

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Cannon JR, Tapias V, Na HM, Honick AS, Drolet RE, and Greenamyre JT. 2009. “A highly reproducible rotenone model of Parkinson’s disease”. Neurobiology of Disease. 34(2) 279–290.

Cappelletti G, Maggioni MG, Maci R. 1999. Influence of MPP+ on the state of tubulin polymerisation in NGF-differentiated PC12 cells. J Neurosci Res. 56(1):28-35.

Cappelletti G, Pedrotti B, Maggioni MG, Maci R. 2001. Microtubule assembly is directly affected by MPP(+)in vitro. Cell Biol Int.25(10):981-4.

Chang DT, Honick AS, Reynolds IJ. 2006. Mitochondrial trafficking to synapses in cultured primary cortical neurons. J Neurosci. 26: 7035–7045.

Chen L, Jin J, Davis J, Zhou Y, Wang Y, Liu J, Lockhart PJ, Zhang J. 2007. Oligomeric α-synuclein inhibits tubulin polymerization. Biochem Biophys Res Commun. 356: 548–553.

Chen Y, McMillan-Ward E, Kong J, Israels SJ, Gibson SB. 2007. Mitochondrial electron-transport-chain inhibitors of complexes I and II induce autophagic cell death mediated by reactive oxygen species. J. Cell Sci. 120:4155–4166.

Cherra SJ,Kulich SM, Uechi G, Balasubramani M, Mountzouris J, Day BW, Chu CT. 2010. Regulation of the autophagy protein LC3 by phosphorylation. J. Cell Biol. 190:533–539.

Chiba Y., S. Takei, N. Kawamura, Y. Kawaguchi, K. Sasaki, S. Hasegawa-Ishii, A. Furukawa, M. Hosokawa, A. Shimada. Immunohistochemical localization of aggresomal proteins in glial cytoplasmic inclusions in multiple system atrophy. Neuropathol. Appl. Neurobiol., 38 (2012), pp. 559–571.

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Chu Y, Dodiya H, Aebischer P, Olanow CW, Kordower JH. 2009. Alterations in lysosomal and proteasomal markers in Parkinson’s disease: relationship to α-synuclein inclusions. Neurobiol Dis. 35(3):385-98.

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Crews L, Spencer B, Desplats P, Patrick C, Paulino A, Rockenstein E, Hansen L, Adame A, Galasko D, Masliah E. 2010. Selective molecular alterations in the autophagy pathway in patients with Lewy body disease and in models of α-synucleinopathy. PLoS One 19;5(2):e9313.

Dadakhujaev S, Noh HS, Jung EJ, Cha JY, Baek SM, Ha JH, Kim DR. 2010. Autophagy protects the rotenone-induced cell death in α-synuclein overexpressing SH-SY5Y cells. Neurosci. Lett. 472:47–52.

Dagda RK, Banerjee TD and Janda E. 2013. How Parkinsonian Toxins Dysregulate the Autophagy Machinery. Int. J. Mol. Sci. 14:22163-22189.

Danzer KM, Haasen D, Karow AR, Moussaud S, Habeck M, Giese A, Kretzschmar H, Hengerer B, Kostka M. 2007. Different species of α-synuclein oligomers induce calcium influx and seeding. The Journal of Neuroscience, 27(34):9220–9232.

Dauer W, Kholodilov N, Vila M, Trillat AC, Goodchild R, Larsen KE, Staal R, Tieu K, Schmitz Y, Yuan CA, Rocha M, Jackson-Lewis V, Hersch S, Sulzer D, Przedborski S, Burke R, Hen R. 2002. Resistance of alpha -synuclein null mice to the parkinsonian neurotoxin MPTP. Proc Natl Acad Sci U S A. 99(22):14524-9.

Domingues AF, Arduíno DM, Esteves AR, Swerdlow RH, Oliveira CR, Cardoso SM. Mitochondria and ubiquitin-proteasomal system interplay: relevance to Parkinson's disease. Free Radic Biol Med. 2008 Sep 15;45(6):820-5.

De Vos KJ, Grierson AJ, Ackerley S, and Miller CCJ. 2008. Role of axonal transport in neurodegenerative diseases, Annual Review of Neuroscience. 31:151–173.

De Vos KJ, Chapman AL, Tennant ME, Manser C, Tudor EL, Lau KF, Brownlees J, Ackerley S, Shaw PJ, McLoughlin DM, Shaw CE, Leigh PN, Miller CC, Grierson AJ. 2007. Familial amyotrophic lateral sclerosis-linked SOD1 mutants perturb fast axonal transport to reduce axonal mitochondria content”. Human Molecular Genetics. 16(22):2720–2728.

Dehay B, Bove J, Rodriguez-Muela N, Perier C, Recasens A, Boya P, Vila M. 2010. Pathogenic lysosomal depletion in Parkinson’s disease. J. Neurosci. 30:12535–12544.

Dias V, Junn E, and Mouradian MM. 2013. The role of oxidative stress in parkinson’s disease. Journal of Parkinson’s Disease. 3(4):461–491.

Drolet RE, Cannon JR, Montero L, and Greenamyre JT. 2009. Chronic rotenone exposure reproduces Parkinson’s disease gastrointestinal neuropathology. Neurobiology of Disease. 36(1):96–102.

Drolet RE, Behrouz B, Lookingland KJ, Goudreau JL, 2004. Mice lacking α-synuclein have an attenuated loss of striatal dopamine following prolonged chronic MPTP administration. Neurotoxicology. 25(5):761-9.

Duka T, Rusnak M, Drolet RE, Duka V, Wersinger C, Goudreau JL, and Sidhu A. 2006. α-synuclein induces hyperphosphorylation of Tau in the MPTP model of parkinsonism. FASEB J. 20, 2302–2312.

Esposito A, Dohm CP, Kermer P, Bähr M, Wouters FS. 2007. α-synuclein and its disease-related mutants interact differentially with the microtubule protein tau and associate with the actin cytoskeleton. Neurobiol Dis 26:521–531.

Esteves AR, Arduíno DM, Silva DF, Oliveira CR, Cardoso SM. 2011. Mitochondrial Dysfunction: The Road to Alpha-Synuclein Oligomerization in PD. Parkinsons Dis. 2011:693761.

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Filomeni G, Graziani I, de Zio D, Dini L, Centonze D., Rotilio G, Ciriolo MR. 2012. Neuroprotection of kaempferol by autophagy in models of rotenone-mediated acute toxicity: Possible implications for Parkinson’s disease. Neurobiol. Aging. 33:767–785.

Follett J, Darlow B, Wong MB, Goodwin J, and Pountney DL. 2013. Potassium depolarization and raised calcium induces α-synuclein aggregates.. Neurotoxicity Research. 23(4)378–392.

Fornai F, Schlüter OM, Lenzi P, Gesi M, Ruffoli R, Ferrucci M, Lazzeri G, Busceti CL, Pontarelli F, Battaglia G, Pellegrini A, Nicoletti F, Ruggieri S, Paparelli A, Südhof TC. 2005. Parkinson-like syndrome induced by continuous MPTP infusion: Convergent roles of the ubiquitinproteasome system and _α-synuclein. PNAS. 102: 3413–3418.

Fujita KA, Ostaszewski M, Matsuoka Y, Ghosh S, Glaab E, Trefois C, Crespo I, Perumal TM, Jurkowski W, Antony PM, Diederich N, Buttini M, Kodama A, Satagopam VP, Eifes S, Del Sol A, Schneider R, Kitano H, Balling R. 2014. Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map. Mol Neurobiol. 49:88–102. Giasson BI, Forman MS, Higuchi M, Golbe LI, Graves CL, Kotzbauer PT, Trojanowski JQ, Lee VM. 2003. Initiation and synergistic fibrillization of tau and α-synuclein. Science. 300:636–640.

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Haskin J, Szargel R, Shani V, Mekies LN, Rott R, Lim GG, Lim KL, Bandopadhyay R, Wolosker H, Engelender S. AF-6 is a positive modulator of the PINK1/parkin pathway and is deficient in Parkinson's disease. Hum Mol Genet. 2013 May 15;22(10):2083-96.

Höglinger GU, Carrard G, Michel PP, Medja F, Lombès A, Ruberg M, Friguet B, Hirsch EC. 2003. Dysfunction of mitochondrial complex I and the proteasome: interactions between two biochemical deficits in a cellular model of Parkinson’s disease. J. Neurochem. 86, 1297–1307.

Ikawa M, Okazawa H, Kudo T, Kuriyama M, Fujibayashi Y, Yoneda M. 2011. “Evaluation of striatal oxidative stress in patients with Parkinson’s disease using [62Cu]ATSM PET” Nuclear Medicine and Biology. 38(7)945–951.

Jiang H, Cheng D, Liu W, Peng J, Feng J. 2010. Protein kinase C inhibits autophagy and phosphorylates LC3. Biochem. Biophys. Res. Commun.395:471–476.

Kawaguchi Y., J.J. Kovacs, A. McLaurin, J.M. Vance, A. Ito, T.P. Yao. The deacetylase HDAC6 regulates aggresome formation and cell viability in response to misfolded protein stress. Cell, 115 (2003), pp. 727–738.

Kim I, Rodriguez-Enriquez S, and Lemasters JJ. 2007. Selective degradation of mitochondria by mitophagy. Archives of Biochemistry and Biophysics. 462(2)245–253.

Lee HJ, Khoshaghideh F, Lee F, and Lee SJ. 2006. Impairment of microtubule-dependent trafficking by overexpression of α-synuclein. European Journal of Neuroscience. 24(11)3153–3162.

Lee HJ, Shin SY, Choi C, Lee YH, Lee SJ. 2002. Formation and removal of α-synuclein aggregates in cells exposed to mitochondrial inhibitors. J Biol Chem. 277:5411–5417.

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