Abstract
Numerous studies have elucidated the genetics of Parkinson’s disease; however, the aetiology of the majority of sporadic cases has not yet been resolved. We hypothesized that epigenetic variations could be associated with PD and evaluated the DNA methylation pattern in PD patients compared to brothers or twins without PD. The methylation of DNA from peripheral blood mononuclear cells of 62 discordant siblings including 24 monozygotic twins was characterized with Illumina DNA Methylation 450K bead arrays and subsequently validated in two independent cohorts: 221 PD vs. 227 healthy individuals (cohort 1) applying Illumina’s VeraCode and 472 PD patients vs. 487 controls (cohort 2) using pyrosequencing. We choose a delta beta of >15 % and selected 62 differentially methylated CpGs in 51 genes from the discordant siblings. Among them, three displayed multiple CpGs per gene: microRNA 886 (MIR886, 10 CpGs), phosphodiesterase 4D (PDE4D, 2 CpGs) and tripartite motif-containing 34 (TRIM34, 2 CpGs). PDE4D was confirmed in both cohorts (p value 2.44e−05). In addition, for biomarker construction, we used the penalized logistic regression model, resulting in a signature of eight CpGs with an AUC of 0.77. Our findings suggest that a distinct level of PD susceptibility stems from individual, epigenetic modifications of specific genes. We identified a signature of CpGs in blood cells that could separate control from disease with a reasonable discriminatory power, holding promise for future epigenetically based biomarker development.
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Abbreviations
- AUC:
-
Area under the curve
- CpG:
-
Cytosine and guanine separated by one phosphate
- GWAS:
-
Genome-wide association studies
- MPTP:
-
1-Methyl-4-phenyl-1,2,3,6-tetrahydro-pyridine
- MZ:
-
Monozygotic
- PD:
-
Parkinson’s disease
- PBMC:
-
Peripheral blood mononuclear cells
- ROC:
-
Receiver-operating characteristic
References
Sharma M, Ioannidis JP, Aasly JO, Annesi G, Brice A, Van Broeckhoven C (2012) Large-scale replication and heterogeneity in Parkinson disease genetic loci. Neurology 79:659–667
Nalls MA, Pankratz N, Lill CM et al (2014) Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease. Nat Genet 46:989–993
Wirdefeldt K, Gatz M, Reynolds CA, Prescott CA, Pedersen NL (2011) Heritability of Parkinson disease in Swedish twins: a longitudinal study. Neurobiol Aging 32:1923.e1–1923.e8
Christensen BC, Houseman EA, Marsit CJ et al (2009) Aging and environmental exposures alter tissue-specific DNA methylation dependent upon CpG island context. PLoS Genet 14:e1000602
Fraga MF, Esteller M (2007) Epigenetics and aging: the targets and the marks. Trends Genet 14:413–418
Portela A, Esteller M (2010) Epigenetic modifications and human disease. Nat Biotechnol 28:1057–1068
Fraga MF, Ballestar E, Paz MF et al (2005) Epigenetic differences arise during the lifetime of monozygotic twins. Proc Natl Acad Sci U S A 102:10604–10609
Bell JT, Spector TD (2012) DNA methylation sudies using twins: what are they telling us? Genome Biol 13:172
Bell JT, Saffery R (2012) The value of twins in epigenetic epidemiology. Int J Epidemiol 41:140–150
Champagne FA (2010) Early adversity and developmental outcomes: interaction between genetics, epigenetics, and social experiences across the life span. Perspect Psychol Sci 5:564–574
Jirtle RL, Skinner MK (2007) Environmental epigenomics and disease susceptibility. Nat Rev Genet 8:253–262
Tobi EW, Goeman JJ, Monajemi R, Gu H, Putter H, Zhang Y (2014) DNA methylation signatures link prenatal famine exposure to growth and metabolism. Nat Commun 5:5592
Hughes V (2014) Epigenetics: the sins of the father. Nature 507:22–24
Kaut O, Schmitt I, Wüllner U (2012) Genome-scale methylation analysis of Parkinson’s disease patients’ brains reveals DNA hypomethylation and increased mRNA expression of cytochrome P450 2E1. Neurogenetics 13:87–91
Touleimat N, Tost J (2012) Complete pipeline for Infinium ((R)) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation. Epigenomics 4:325–341
Price ME, Cotton AM, Lam LL, Farré P, Emberly E, Brown CJ, Robinson WP, Kobor MS (2013) Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array. Epigenetics Chromatin 6:4
Du P, Kibbe WA, Lin SM (2008) lumi: a pipeline for processing Illumina microarray. Bioinformatics 24:1547–1548
Chen YA, Lemire M, Choufani S, Butcher DT, Grafodatskaya D, Zanke BW, Gallinger S, Hudson TJ, Weksberg R (2013) Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics 8:203–209
Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, Kelsey KT (2012) DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. doi:10.1186/1471-2105-13-86
Zaykin DV (2011) Optimally weighted Z-test is a powerful method for combining probabilities in meta-analysis. J Evol Biol 24:1836–1841
Maxx P, Horowitz J, Timothy Greenamyre J (2010) Mitochondrial iron metabolism and its role in neurodegeneration. J Alzheimers Dis 20(Suppl 2):S551–S568
Rusconi L, Salvatoni L, Giudici L, Bertani I, Kilstrup-Nielsen C, Broccoli V (2008) CDKL5 expression is modulated during neuronal development and its subcellular distribution is tightly regulated by the C-terminal tail. J Biol Chem 283:30101–30111
Imai Y, Soda M, Hatakeyama S, Akagi T, Hashikawa T, Nakayama KI, Takahashi R (2002) CHIP is associated with Parkin, a gene responsible for familial Parkinson’s disease, and enhances its ubiquitin ligase activity. Mol Cell 10:55–67
Du P, Zhang X, Huang CC, Jafari N, Kibbe WA, Hou L, Lin SM (2010) Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics 11:587
Friedman J, Hastie T, Tibshirani R (2010) Regularization paths for generalized linear models via coordinate descent. J Stat Softw 33:1–22
Cedervall P, Aulabaugh A, Geoghegan KF, McLellan TJ, Pandit J (2015) Engineered stabilization and structural analysis of the autoinhibited conformation of PDE4. Proc Natl Acad Sci U S A 112:E1414–E1422
Yang L, Calingasan NY, Lorenzo BJ, Beal MF (2008) Attenuation of MPTP neurotoxicity by rolipram, a specific inhibitor of phosphodiesterase IV. Exp Neurol 211:311–314
Bate C, Williams A (2015) cAMP-inhibits cytoplasmic phospholipase A and protects neurons against amyloid-β-induced synapse damage. Biology (Basel) 4:591–606
Hernán MA, Takkouche B, Caamaño-Isorna F, Gestal-Otero JJ (2002) A meta-analysis of coffee drinking, cigarette smoking, and the risk of Parkinson’s disease. Ann Neurol 52:276–284
Lin MK, Farrer MJ (2014) Genetics and genomics of Parkinson’s disease. Genome Med 6:48
Coupland KG, Mellick GD, Silburn PA et al (2014) DNA methylation of the MAPT gene in Parkinson’s disease cohorts and modulation by vitamin E in vitro. Mov Disord 29:1606–1614
Ricciardi S, Ungaro F, Hambrock M (2012) CDKL5 ensures excitatory synapse stability by reinforcing NGL-1-PSD95 interaction in the postsynaptic compartment and is impaired in patient iPSC-derived neurons. Nat Cell Biol 14:911–923
Zhu YC, Li D, Wang L, Lu B, Zheng J, Zhao SL, Zeng R, Xiong ZQ (2013) Palmitoylation-dependent CDKL5-PSD-95 interaction regulates synaptic targeting of CDKL5 and dendritic spine development. Proc Natl Acad Sci U S A 110:9118–9123
Mari F, Azimonti S, Bertani I et al (2005) CDKL5 belongs to the same molecular pathway of MeCP2 and it is responsible for the early-onset seizure variant of Rett syndrome. Hum. Mol Genet 14:1935–1946
Imai Y, Soda M, Inoue H, Hattori N, Mizuno Y, Takahashi R (2001) An unfolded putative transmembrane polypeptide, which can lead to endoplasmic reticulum stress, is a substrate of Parkin. Cell 105:891–902
Murakami T, Shoji M, Imai Y, Inoue H, Kawarabayashi T, Matsubara E, Harigaya Y, Sasaki A, Takahashi R, Abe K (2004) Pael-R is accumulated in Lewy bodies of Parkinson’s disease. Ann Neurol 55:439–442
Meyer RC, Giddens MM, Schaefer SA, Hall RA (2013) GPR37 and GPR37L1 are receptors for the neuroprotective and glioprotective factors prosaptide and prosaposin. Proc Natl Acad Sci U S A 110:9529–9534
Rakyan VK, Down TA, Balding DJ, Beck S (2011) Epigenome-wide association studies for common human diseases. Nat Rev Genet 12:529–541
Wüllner U, Klockgether T (2003) Inflammation in Parkinson’s disease. J Neurol 250 Suppl 1:I35–138
Chao Y, Wong, SC, Tan, EK (2014) Evidence of inflammatory system involvement in Parkinson’s disease. Biomed Res Int: 308654. Review
Vivekanantham S, Shah S, Dewji R, Dewji A, Khatri C, Ologunde R (2015) Neuroinflammation in Parkinson’s disease: role in neurodegeneration and tissue repair. Int J Neurosci 125:717–725
Orimo A, Tominaga N, Yoshimura K, Yamauchi Y, Nomura M, Sato M, Nogi Y, Suzuki M, Suzuki H, Ikeda K, Inoue S, Muramatsu M (2000) Molecular cloning of ring finger protein 21 (RNF21)/interferon-responsive finger protein (ifp1), which possesses two RING-B box-coiled coil domains in tandem. Genomics 69:143–149
Rajsbaum R, Versteeg GA, Schmid S et al (2014) Unanchored K48-linked polyubiquitin synthesized by the E3-ubiquitin ligase TRIM6 stimulates the interferon-IKKε kinase-mediated antiviral response. Immunity 40:880–895
Candel S, Sepulcre MP, Espín-Palazón R, Tyrkalska SD, de Oliveira S, Meseguer J, Mulero V (2015) Md1 and Rp105 regulate innate immunity and viral resistance in zebrafish. Dev Comp Immunol 50:155–165
Chen H, Jacobs E, Schwarzschild MA, McCullough ML, Calle EE, Thun M, Ascherio A (2005) Nonsteroidal antiinflammatory drug use and the risk for Parkinson’s disease. Ann Neurol 58:963–967
Eyal A, Szargel R, Avraham E, Liani E, Haskin J, Rott R, Engelender S (2006) Synphilin-1A: an aggregation-prone isoform of synphilin-1 that causes neuronal death and is present in aggregates from alpha-synucleinopathy patients. Proc Natl Acad Sci U S A 103:5917–5922
Kaminsky ZA, Tang T, Wang SC, Ptak C, Oh GH, Wong AH (2009) DNA methylation profiles in monozygotic and dizygotic twins. Nat Genet 41:240–245
Mahishi LH, Hart RP, Lynch DR, Ratan RR (2012) miR-886-3p levels are elevated in Friedreich ataxia. J Neurosci 32:9369–9373
Masliah E, Dumaop W, Galasko D, Desplats P (2013) Distinctive patterns of DNA methylation associated with Parkinson disease: identification of concordant epigenetic changes in brain and peripheral blood leukocytes. Epigenetics 8:1030–1038
Davies MN, Volta M, Pidsley R (2012) Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol 13:R43
Acknowledgments
We would like to thank all of the participants, PD patients and twins for their voluntary contribution to this research project. We would also like to thank the staff of the Department of Twin Research (DTR) of the King’s College in London for their help and support in undertaking this project, with special thanks to Victoria Vazquez. The Wellcome Trust provides core support for DTR. This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking [Aetionomy [grant number 115568]), the BMBF/ANR through the EpiPD (Epigenomics of Parkinson’s disease) project, under the auspices of the bilateral Epigenomics of Common and Age-related Diseases Programme (grant no. 01KU1403B to UW and ANR-13-EPIG-0003-05 to JT) and the ParkinsonFonds (research grant to OK). The excellent technical work of Anne Hanke, Hassan Khazneh and Sabine Proske-Schmitz is gratefully acknowledged.
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The experiments were undertaken with the understanding and written consent of each subject. The study conforms to the World Medical Association Declaration of Helsinki. The Ethics Committee of the Medical Faculty of the University of Bonn approved this study (No. 51/00, 6 July 2000).
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The authors declare that they have no conflict of interest.
Authors’ contributions
OK conceived the study, collected MZ twin probes, participated in pyrosequencing, performed statistical analysis and interpretation of data and wrote the manuscript.
IS participated in the sequence alignment, designed primers and performed pyrosequencing.
JT performed statistical analysis and provided figures.
FB performed statistical analysis.
YL performed statistical analysis.
PH participated in the sequence alignment and helped to draft the manuscript.
SW collected the data and probes and performed the VeraCode array.
MR participated in the study design and helped to draft the manuscript.
VV collected MZ twin probes, contributed to data interpretation and helped to draft the manuscript.
HF performed statistical analysis and provided figures.
UW conceived the study, contributed to data interpretation and wrote the manuscript.
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Kaut, O., Schmitt, I., Tost, J. et al. Epigenome-wide DNA methylation analysis in siblings and monozygotic twins discordant for sporadic Parkinson’s disease revealed different epigenetic patterns in peripheral blood mononuclear cells. Neurogenetics 18, 7–22 (2017). https://doi.org/10.1007/s10048-016-0497-x
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DOI: https://doi.org/10.1007/s10048-016-0497-x