The DOI matches its Crossref record; 247 of the 247 references it cites were found in a registry or an index.
Dysregulated Lipid Metabolism and Its Role in α-Synucleinopathy in Parkinson’s Disease
Open accessAbstract
Parkinson’s disease (PD) is the second most common neurodegenerative disease, the main pathological hallmark of which is the accumulation of α-synuclein (α-syn) and the formation of filamentous aggregates called Lewy bodies in the brainstem, limbic system, and cortical areas. Lipidomics is a newly emerging field which can provide fresh insights and new answers that will enhance our capacity for early diagnosis, tracking disease progression, predicting critical endpoints, and identifying risk in pre-symptomatic persons. In recent years, lipids have been implicated in many aspects of PD pathology. Biophysical and lipidomic studies have demonstrated that α-syn binds preferentially not only to specific lipid families but also to specific molecular species and that these lipid-protein complexes enhance its interaction with synaptic membranes, influence its oligomerization and aggregation, and interfere with the catalytic activity of cytoplasmic lipid enzymes and lysosomal lipases, thereby affecting lipid metabolism. The genetic link between aberrant lipid metabolism and PD is even more direct, with mutations in GBA and SMPD1 enhancing PD risk in humans and loss of GALC function increasing α-syn aggregation and accumulation in experimental murine models. Moreover, a number of lipidomic studies have reported PD-specific lipid alterations in both patient brains and plasma, including alterations in the lipid composition of lipid rafts in the frontal cortex. A further aspect of lipid dysregulation promoting PD pathogenesis is oxidative stress and inflammation, with proinflammatory lipid mediators such as platelet activating factors (PAFs) playing key roles in arbitrating the progressive neurodegeneration seen in PD linked to α-syn intracellular trafficking. Lastly, there are a number of genetic risk factors of PD which are involved in normal lipid metabolism and function. Genes such as PLA2G6 and SCARB2, which are involved in glycerophospholipid and sphingolipid metabolism either directly or indirectly are associated with risk of PD. This review seeks to describe these facets of metabolic lipid dysregulation as they relate to PD pathology and potential pathomechanisms involved in disease progression, while highlighting incongruous findings and gaps in knowledge that necessitate further research.
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Wislet‐Gendebien, S., Visanji, N. P., Whitehead, S. N., Marsilio, D., Hou, W., Figeys, D., Fraser, P. E., Bennett, S. A. L., & Tandon, A. (2008) · BMC Neuroscience · doi:10.1186/1471-2202-9-92 · Cited by 26
Self-citationRetractedStaging of brain pathology related to sporadic Parkinson’s disease
Braak, H., Tredici, K. D., Rüb, U., de Vos, R. A. I., Jansen Steur, E. N. H., & Braak, E. (2003) · Neurobiology of Aging · doi:10.1016/s0197-4580(02)00065-9 · Cited by 10,777
Bernheimer, H., Birkmayer, W., Hornykiewicz, O., Jellinger, K., & Seitelberger, F. (1973) · Journal of the Neurological Sciences · doi:10.1016/0022-510x(73)90175-5 · Cited by 2,651
Oxidative stress and neurodegeneration: where are we now?
Halliwell, B. (2006) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2006.03907.x · Cited by 2,614
Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030
Dorsey, E. R., Constantinescu, R., Thompson, J. P., Biglan, K. M., Holloway, R. G., Kieburtz, K., Marshall, F. J., Ravina, B. M., Schifitto, G., Siderowf, A., et al. (2007) · Neurology · doi:10.1212/01.wnl.0000247740.47667.03 · Cited by 2,472
Structure and Function of Sphingolipid- and Cholesterol-rich Membrane Rafts
Brown, D. A., & London, E. (2000) · Journal of Biological Chemistry · doi:10.1074/jbc.r000005200 · Cited by 2,344
α-Synuclein is phosphorylated in synucleinopathy lesions
Fujiwara, H., Hasegawa, M., Dohmae, N., Kawashima, A., Masliah, E., Goldberg, M. S., Shen, J., Takio, K., & Iwatsubo, T. (2002) · Nature Cell Biology · doi:10.1038/ncb748 · Cited by 2,132
Oxidative stress in Parkinson's disease
Jenner, P. (2003) · Annals of Neurology · doi:10.1002/ana.10483 · Cited by 2,053
Neuroinflammation in Parkinson’s disease: A target for neuroprotection?
Hirsch, E. C., & Hunot, S. (2009) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70062-6 · Cited by 1,984
International Parkinson's Disease Genomics Consortium (IPDGC), Nalls, M. A., Parkinson's Study Group (PSG) Parkinson's Research: The Organized GENetics Initiative (PROGENI), 23andMe, GenePD, NeuroGenetics Research Consortium (NGRC), Hussman Institute of Human Genomics (HIHG), Investigator, T. A. J. D., (CHARGE), C. F. H. A. A. R. I. G. E., North American Brain Expression Consortium (NABEC), et al. (2014) · Nature Genetics · doi:10.1038/ng.3043 · Cited by 1,895
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Ageing as a risk factor for neurodegenerative disease
Hou, Y., Dan, X., Babbar, M., Wei, Y., Hasselbalch, S. G., Croteau, D. L., & Bohr, V. A. (2019) · Nature Reviews Neurology · doi:10.1038/s41582-019-0244-7 · Cited by 3,310
Brain lipidomics: From functional landscape to clinical significance
Yoon, J. H., Seo, Y., Jo, Y. S., Lee, S., Cho, E., Cazenave-Gassiot, A., Shin, Y.-S., Moon, M. H., An, H. J., Wenk, M. R., et al. (2022) · Science Advances · doi:10.1126/sciadv.adc9317 · Cited by 324
Lipid droplets in the nervous system
Ralhan, I., Chang, C.-L., Lippincott-Schwartz, J., & Ioannou, M. S. (2021) · Journal of Cell Biology · doi:10.1083/jcb.202102136 · Cited by 281
Probiotic Bacillus subtilis protects against α-synuclein aggregation in C. elegans
Goya, M. E., Xue, F., Sampedro-Torres-Quevedo, C., Arnaouteli, S., Riquelme-Dominguez, L., Romanowski, A., Brydon, J., Ball, K. L., Stanley-Wall, N. R., & Doitsidou, M. (2020) · Cell Reports · doi:10.1016/j.celrep.2019.12.078 · Cited by 205
Ruiz-Pozo, V. A., Tamayo-Trujillo, R., Cadena-Ullauri, S., Frias-Toral, E., Guevara-Ramírez, P., Paz-Cruz, E., Chapela, S., Montalván, M., Morales-López, T., Simancas-Racines, D., et al. (2023) · Nutrients · doi:10.3390/nu15163585 · Cited by 63
Metadata
- Authors
- Alecu, I., & Bennett, S. A. L.
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2019-04-11
- Volume
- 13
- Pages
- 328-328
- ISSN
- 1662-453X (ISSN-L)
- OpenAlex
- W2938730938
- Cited by
- 258
- References
- 247
- FWCI
- 15.29
- Type
- journal article
- Language
- en
- Open access
- gold
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