Background: Recent advances in genetics have provided insights into important inherited causes of Parkinson’s disease (PD), but the underlying biological mechanisms are still incompletely understood. Gene expression studies have pointed toward the dysregulation of neuroinflammation, mitochondrial function, and protein degradation pathways. Objective: We aimed to identify groups of dysregulated genes in PD. Methods: In order to increase statistical power and control for potential confounders, we re-analyzed transcriptomic data from PD patients and model systems, integrating additional genomic data using a systems biology approach. Using weighted gene co-expression network analysis, we partitioned genes into co-expressed modules. Results: One co-expression module, M13, had an expression trajectory that was highly correlated with PD, was not characterized by any specific cell type markers, and was enriched in PD genes identified by genome-wide association studies. Genes within M13 seemed to be related to global microRNA biogenesis, and DICER1 and AGO3 were highly connected within the module. The NUCKS1 gene, previously identified as part of the PARK16 locus, was also a hub gene within M13. Conclusion: These results suggest that microRNA processing and function may play a role in the pathogenesis of PD, and thus may represent a useful target for future drug development.

1.
Kumaran R, Cookson MR: Pathways to -Parkinsonism Redux: Convergent pathobiological mechanisms in genetics of Parkinson’s disease. Hum Mol Genet 2015; 24(R1):R32–R44.
2.
Pickrell AM, Youle RJ: The Roles of PINK1, Parkin, and Mitochondrial Fidelity in Parkinson’s Disease. Neuron 2015; 85: 257–273.
3.
Soreq L, Ben-Shaul Y, Israel Z, Bergman H, Soreq H: Meta-analysis of genetic and environmental Parkinson’s disease models reveals a common role of mitochondrial protection pathways. Neurobiol Dis 2012; 45: 1018–1030.
4.
Zheng B, Liao Z, Locascio JJ, Lesniak KA, Roderick SS, Watt ML, Eklund AC, Zhang-James Y, Kim PD, Hauser MA, Grünblatt E, Moran LB, Mandel SA, Riederer P, Miller RM, Federoff HJ, Wüllner U, Papapetropoulos S, Youdim MB, Cantuti-Castelvetri I, Young AB, Vance JM, Davis RL, Hedreen JC, Adler CH, Beach TG, Graeber MB, Middleton FA, Rochet J-C, Scherzer CR: PGC-1α, a potential therapeutic target for early intervention in Parkinson’s disease. Sci Transl Med 2010; 2: 52ra73.
5.
Riley BE, Gardai SJ, Emig-Agius D, Bessarabova M, Ivliev AE, Schüle B, Alexander J, Wallace W, Halliday GM, Langston JW, Braxton S, Yednock T, Shaler T, Johnston JA: Systems-based analyses of brain regions functionally impacted in Parkinson’s disease reveals underlying causal mechanisms. PLoS One 2014; 9:e102909.
6.
Lesnick TG, Papapetropoulos S, Mash DC, Ffrench-Mullen J, Shehadeh L, de Andrade M, Henley JR, Rocca WA, Ahlskog JE, Maraganore DM: A genomic pathway approach to a complex disease: axon guidance and -Parkinson disease. PLoS Genet 2007; 3:e98.
7.
Zhang Y, James M, Middleton FA, Davis RL: Transcriptional analysis of multiple brain regions in Parkinson’s disease supports the involvement of specific protein processing, energy metabolism, and signaling pathways, and suggests novel disease mechanisms. Am J Med Genet B Neuropsychiatr Genet 2005; 137B: 5–16.
8.
Dijkstra AA, Ingrassia A, de Menezes RX, van Kesteren RE, Rozemuller AJ, Heutink P, van de Berg WD: Evidence for immune response, axonal dysfunction and reduced endocytosis in the substantia nigra in early stage -Parkinson’s disease. PLoS One 2015; 10:e0128651.
9.
Rhinn H, Qiang L, Yamashita T, Rhee D, Zolin A, Vanti W, Abeliovich A: Alternative α-synuclein transcript usage as a convergent mechanism in Parkinson’s disease pathology. Nat Commun 2012; 3: 1084.
10.
Langfelder P, Horvath S: WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics 2008; 9: 559.
11.
Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensinger A, Bernard A, Boe AF, Boguski MS, Brockway KS, Byrnes EJ, Chen L, Chen L, Chen TM, Chin MC, Chong J, Crook BE, Czaplinska A, Dang CN, Datta S, Dee NR, Desaki AL, Desta T, Diep E, Dolbeare TA, Donelan MJ, Dong HW, Dougherty JG, Duncan BJ, Ebbert AJ, Eichele G, Estin LK, Faber C, Facer BA, Fields R, Fischer SR, Fliss TP, Frensley C, Gates SN, Glattfelder KJ, Halverson KR, Hart MR, Hohmann JG, Howell MP, Jeung DP, Johnson RA, Karr PT, Kawal R, Kidney JM, Knapik RH, Kuan CL, Lake JH, Laramee AR, Larsen KD, Lau C, Lemon TA, Liang AJ, Liu Y, Luong LT, Michaels J, Morgan JJ, Morgan RJ, Mortrud MT, Mosqueda NF, Ng LL, Ng R, Orta GJ, Overly CC, Pak TH, Parry SE, Pathak SD, Pearson OC, Puchalski RB, Riley ZL, Rockett HR, Rowland SA, Royall JJ, Ruiz MJ, Sarno NR, Schaffnit K, Shapovalova NV, Sivisay T, Slaughterbeck CR, Smith SC, Smith KA, Smith BI, Sodt AJ, Stewart NN, Stumpf KR, Sunkin SM, Sutram M, Tam A, Teemer CD, Thaller C, Thompson CL, Varnam LR, Visel A, Whitlock RM, Wohnoutka PE, Wolkey CK, Wong VY, Wood M, Yaylaoglu MB, Young RC, Youngstrom BL, Yuan XF, Zhang B, Zwingman TA, Jones AR: Genome-wide atlas of gene expression in the adult mouse brain. Nature 2007; 445: 168–176.
12.
Alexa A, Rahnenführer J, Lengauer T: Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics 2006; 22: 1600–1607.
13.
ZhangY, Chen K, Sloan SA, Bennett ML, Scholze AR, O’Keeffe S, Phatnani HP, Guarnieri P, Caneda C, Ruderisch N, Deng S, Liddelow SA, Zhang C, Daneman R, Maniatis T, Barres BA, Wu JQ: An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J Neurosci 2014; 34: 11929–11947.
14.
Langfelder P, Mischel PS, Horvath S: When is hub gene selection better than standard meta-analysis? PLoS One 2013; 8:e61505.
15.
Satake W, Nakabayashi Y, Mizuta I, Hirota Y, Ito C, Kubo M, Kawaguchi T, Tsunoda T, Watanabe M, Takeda A, Tomiyama H, Nakashima K, Hasegawa K, Obata F, Yoshikawa T, Kawakami H, Sakoda S, Yamamoto M, Hattori N, Murata M, Nakamura Y, Toda T: Genome-wide association study identifies common variants at four loci as genetic risk factors for Parkinson’s disease. Nat Genet 2009; 41: 1303–1307.
16.
Grundt K, Haga IV, Aleporou-Marinou V, Drosos Y, Wanvik B, Østvold AC: Characterisation of the NUCKS gene on human chromosome 1q32.1 and the presence of a homologous gene in different species. Biochem Biophys Res Commun 2004; 323: 796–801.
17.
Kim J, Inoue K, Ishii J, Vanti WB, Voronov SV, Murchison E, Hannon G, Abeliovich A: A MicroRNA feedback circuit in midbrain dopamine neurons. Science 2007; 317: 1220–1224.
18.
Junn E, Lee KW, Jeong BS, Chan TW, Im JY, Mouradian MM: Repression of alpha-synuclein expression and toxicity by microRNA-7. Proc Natl Acad Sci U S A 2009; 106: 13052–13057.
19.
Doxakis E: Post-transcriptional regulation of alpha-synuclein expression by mir-7 and mir-153. J Biol Chem 2010; 285: 12726–12734.
20.
Wang G, van der Walt JM, Mayhew G, Li YJ, Züchner S, Scott WK, Martin ER, Vance JM: Variation in the miRNA-433 binding site of FGF20 confers risk for Parkinson disease by overexpression of alpha-synuclein. Am J Hum Genet 2008; 82: 283–289.
21.
Miñones-Moyano E, Porta S, Escaramís G, -Rabionet R, Iraola S, Kagerbauer B, Espinosa-Parrilla Y, Ferrer I, Estivill X, Martí E: -MicroRNA profiling of Parkinson’s disease brains identifies early downregulation of miR-34b/c which modulate mitochondrial function. Hum Mol Genet 2011; 20: 3067–3078.
22.
Kim W, Lee Y, McKenna ND, Yi M, Simunovic F, Wang Y, Kong B, Rooney RJ, Seo H, Stephens RM, Sonntag KC: miR-126 contributes to Parkinson’s disease by dysregulating the insulin-like growth factor/phosphoinositide 3-kinase signaling. Neurobiol Aging 2014; 35: 1712–1721.
23.
Thome AD, Harms AS, Volpicelli-Daley LA, Standaert DG: MicroRNA-155 regulates alpha-synuclein-induced inflammatory responses in models of Parkinson disease. J Neurosci 2016; 36: 2383–2390.
24.
Giraldez AJ, Cinalli RM, Glasner ME, Enright AJ, Thomson JM, Baskerville S, Hammond SM, Bartel DP, Schier AF: MicroRNAs Regulate Brain Morphogenesis in Zebrafish. Science 2005; 308: 833–838.
25.
Sempere LF, Freemantle S, Pitha-Rowe I, Moss E, Dmitrovsky E, Ambros V: Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 2004; 5:R13.
26.
Heman-Ackah SM, Hallegger M, Rao MS, Wood MJ: RISC in PD: the impact of -microRNAs in Parkinson’s disease cellular and molecular pathogenesis. Front Mol Neurosci 2013; 6.
27.
WinterJ, Jung S, Keller S, Gregory RI, Diederichs S: Many roads to maturity: microRNA biogenesis pathways and their regulation. Nat Cell Biol 2009; 11: 228–234.
28.
Gehrke S, Imai Y, Sokol N, Lu B: Pathogenic LRRK2 negatively regulates microRNA-mediated translational repression. Nature 2010; 466: 637–641.
29.
Butcher NJ, Kiehl TR, Hazrati LN, et al: Association between early-onset parkinson disease and 22q11.2 deletion syndrome: Identification of a novel genetic form of parkinson disease and its clinical implications. JAMA Neurol 2013; 70: 1359–1366.
Copyright / Drug Dosage / Disclaimer
Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.
You do not currently have access to this content.