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Epigenome-wide association study of peripheral immune cell populations in Parkinson’s disease – npj Parkinson’s Disease


  • Tan, E. K. et al. Parkinson disease and the immune system—associations, mechanisms and therapeutics. Nat. Rev. Neurol. 16, 303–318 (2020).

    Article 
    PubMed 

    Google Scholar
     

  • Zhu, B., Yin, D., Zhao, H. & Zhang, L. The immunology of Parkinson’s disease. Semin. Immunopathol. 44, 659–672 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vijiaratnam, N., Simuni, T., Bandmann, O., Morris, H. R. & Foltynie, T. Progress towards therapies for disease modification in Parkinson’s disease. Lancet Neurol. 20, 559–572 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • McGeer, P. L., Itagaki, S., Akiyama, H. & McGeer, E. G. Rate of cell death in parkinsonism indicates active neuropathological process. Ann. Neurol. 24, 574–576 (1988).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Galiano-Landeira, J., Torra, A., Vila, M. & Bove, J. CD8 T cell nigral infiltration precedes synucleinopathy in early stages of Parkinson’s disease. Brain 143, 3717–3733 (2020).

    Article 
    PubMed 

    Google Scholar
     

  • Sulzer, D. et al. T cells from patients with Parkinson’s disease recognize alpha-synuclein peptides. Nature 546, 656–661 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Scott, K. M., Kouli, A., Yeoh, S. L., Clatworthy, M. R. & Williams-Gray, C. H. A systematic review and meta-analysis of alpha synuclein auto-antibodies in Parkinson’s disease. Front. Neurol. 9, 815 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hamza, T. H. et al. Common genetic variation in the HLA region is associated with late-onset sporadic Parkinson’s disease. Nat. Genet. 42, 781–785 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Nalls, M. A. et al. Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet Neurol. 18, 1091–1102 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Raj, T. et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344, 519–523 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Gagliano, S. A. et al. Genomics implicates adaptive and innate immunity in Alzheimer’s and Parkinson’s diseases. Ann. Clin. Transl. Neurol. 3, 924–933 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lu, Q. et al. Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease. PLoS Genet. 13, e1006933 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Andersen, M. S. et al. Heritability enrichment implicates microglia in Parkinson’s disease pathogenesis. Ann. Neurol. 89, 942–951 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tansey, K. E., Cameron, D. & Hill, M. J. Genetic risk for Alzheimer’s disease is concentrated in specific macrophage and microglial transcriptional networks. Genome Med. 10, 14 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Navarro, E. et al. Dysregulation of mitochondrial and proteolysosomal genes in Parkinson’s disease myeloid cells. Nat. Aging 1, 850–863 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cavalli, G. & Heard, E. Advances in epigenetics link genetics to the environment and disease. Nature 571, 489–499 (2019).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Hwang, J. Y., Aromolaran, K. A. & Zukin, R. S. The emerging field of epigenetics in neurodegeneration and neuroprotection. Nat. Rev. Neurosci. 18, 347–361 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Song, H. et al. Epigenetic modification in Parkinson’s disease. Front. Cell Dev. Biol. 11, 1123621 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pavlou, M. A. S. & Outeiro, T. F. Epigenetics in Parkinson’s disease. Adv. Exp. Med. Biol. 978, 363–390 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Kaut, O. et al. Epigenome-wide analysis of DNA methylation in Parkinson’s disease cortex. Life 12, 502 (2022).

  • Young, J. I. et al. Genome-wide brain DNA methylation analysis suggests epigenetic reprogramming in Parkinson disease. Neurol. Genet. 5, e342 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Masliah, E., Dumaop, W., Galasko, D. & Desplats, P. Distinctive patterns of DNA methylation associated with Parkinson disease: identification of concordant epigenetic changes in brain and peripheral blood leukocytes. Epigenetics 8, 1030–1038 (2013).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pihlstrom, L. et al. Epigenome-wide association study of human frontal cortex identifies differential methylation in Lewy body pathology. Nat. Commun. 13, 4932 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Marshall, L. L. et al. Epigenomic analysis of Parkinson’s disease neurons identifies Tet2 loss as neuroprotective. Nat. Neurosci. 23, 1203–1214 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Kochmanski, J., Kuhn, N. C. & Bernstein, A. I. Parkinson’s disease-associated, sex-specific changes in DNA methylation at PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2beta), and NR4A2 (NURR1) in cortical neurons. NPJ Parkinsons Dis. 8, 120 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Moore, K., McKnight, A. J., Craig, D. & O’Neill, F. Epigenome-wide association study for Parkinson’s disease. Neuromol. Med 16, 845–855 (2014).

    Article 
    CAS 

    Google Scholar
     

  • Chuang, Y. H. et al. Parkinson’s disease is associated with DNA methylation levels in human blood and saliva. Genome Med. 9, 76 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Henderson-Smith, A. et al. DNA methylation changes associated with Parkinson’s disease progression: outcomes from the first longitudinal genome-wide methylation analysis in blood. Epigenetics 14, 365–382 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Paul, K. C. et al. Immune system disruptions implicated in whole blood epigenome-wide association study of depression among Parkinson’s disease patients. Brain Behav. Immun. Health 26, 100530 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vallerga, C. L. et al. Analysis of DNA methylation associates the cystine-glutamate antiporter SLC7A11 with risk of Parkinson’s disease. Nat. Commun. 11, 1238 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Postuma, R. B. et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov. Disord. 30, 1591–1601 (2015).

    Article 
    PubMed 

    Google Scholar
     

  • Graw, S., Henn, R., Thompson, J. A. & Koestler, D. C. pwrEWAS: a user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS). BMC Bioinforma. 20, 218 (2019).

    Article 

    Google Scholar
     

  • Breheny, P., Stromberg, A. & Lambert, J. P-value histograms: inference and diagnostics. High Throughput 7, 23 (2018).

  • Zhang, L. et al. Sex-specific DNA methylation differences in Alzheimer’s disease pathology. Acta Neuropathol. Commun. 9, 77 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Castro de Moura, M. et al. Epigenome-wide association study of COVID-19 severity with respiratory failure. EBioMedicine 66, 103339 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bradic, M. et al. DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome. J. Transl. Med. 20, 526 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Gaunt, T. R. et al. Systematic identification of genetic influences on methylation across the human life course. Genome Biol. 17, 61 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Campagna, M. P. et al. Epigenome-wide association studies: current knowledge, strategies and recommendations. Clin. Epigenet. 13, 214 (2021).

    Article 
    CAS 

    Google Scholar
     

  • Li, Y. I., Wong, G., Humphrey, J. & Raj, T. Prioritizing Parkinson’s disease genes using population-scale transcriptomic data. Nat. Commun. 10, 994 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Schmitt, I. et al. L-dopa increases alpha-synuclein DNA methylation in Parkinson’s disease patients in vivo and in vitro. Mov. Disord. 30, 1794–1801 (2015).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Gu, C. et al. The IFN-gamma-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma. Front. Oncol. 12, 955979 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Sui, J. et al. Integrated analysis of long non-coding RNAassociated ceRNA network reveals potential lncRNA biomarkers in human lung adenocarcinoma. Int. J. Oncol. 49, 2023–2036 (2016).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Humayun, A. & Fornace, A. J. Jr. GADD45 in stress signaling, cell cycle control, and apoptosis. Adv. Exp. Med. Biol. 1360, 1–22 (2022).

    Article 
    PubMed 

    Google Scholar
     

  • Gao, Y. et al. The emerging role of Rab GTPases in the pathogenesis of Parkinson’s disease. Mov. Disord. 33, 196–207 (2018).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Waschbusch, D. et al. LRRK2 transport is regulated by its novel interacting partner Rab32. PLoS ONE 9, e111632 (2014).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • McGrath, E., Waschbusch, D., Baker, B. M. & Khan, A. R. LRRK2 binds to the Rab32 subfamily in a GTP-dependent manner via its armadillo domain. Small GTPases 12, 133–146 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Zimprich, A. et al. Mutations in LRRK2 cause autosomal-dominant parkinsonism with pleomorphic pathology. Neuron 44, 601–607 (2004).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Paisan-Ruiz, C. et al. Cloning of the gene containing mutations that cause PARK8-linked Parkinson’s disease. Neuron 44, 595–600 (2004).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Langston, R. G. et al. Association of a common genetic variant with Parkinson’s disease is mediated by microglia. Sci. Transl. Med. 14, eabp8869 (2022).

  • Kim, C. et al. LRRK2 mediates microglial neurotoxicity via NFATc2 in rodent models of synucleinopathies. Sci. Transl. Med. 12, eaay0399 (2020).

  • Xu, E. et al. Pathological alpha-synuclein recruits LRRK2 expressing pro-inflammatory monocytes to the brain. Mol. Neurodegener. 17, 7 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Stevens, C. H. et al. Reduced T helper and B lymphocytes in Parkinson’s disease. J. Neuroimmunol. 252, 95–99 (2012).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Horvath, S. & Ritz, B. R. Increased epigenetic age and granulocyte counts in the blood of Parkinson’s disease patients. Aging 7, 1130–1142 (2015).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hannon, E., Weedon, M., Bray, N., O’Donovan, M. & Mill, J. Pleiotropic effects of trait-associated genetic variation on DNA methylation: utility for refining GWAS loci. Am. J. Hum. Genet. 100, 954–959 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tsalenchuk, M., Gentleman, S. M. & Marzi, S. J. Linking environmental risk factors with epigenetic mechanisms in Parkinson’s disease. NPJ Parkinsons Dis. 9, 123 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Aryee, M. J. et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30, 1363–1369 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pidsley, R. et al. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genomics 14, 293 (2013).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Fortin, J. P. et al. Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biol. 15, 503 (2014).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chen, Y. A. et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics 8, 203–209 (2013).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chen, J. et al. CpGFilter: model-based CpG probe filtering with replicates for epigenome-wide association studies. Bioinformatics 32, 469–471 (2016).

    Article 
    PubMed 

    Google Scholar
     

  • Piehler, A. P., Grimholt, R. M., Ovstebo, R. & Berg, J. P. Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes. BMC Immunol. 11, 21 (2010).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Maess, M. B., Sendelbach, S. & Lorkowski, S. Selection of reliable reference genes during THP-1 monocyte differentiation into macrophages. BMC Mol. Biol. 11, 90 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Schmittgen, T. D. & Livak, K. J. Analyzing real-time PCR data by the comparative C(T) method. Nat. Protoc. 3, 1101–1108 (2008).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Leek, J. T., Johnson, W. E., Parker, H. S., Jaffe, A. E. & Storey, J. D. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28, 882–883 (2012).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Leek, J. T. Asymptotic conditional singular value decomposition for high-dimensional genomic data. Biometrics 67, 344–352 (2011).

    Article 
    PubMed 

    Google Scholar
     

  • Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Mansell, G. et al. Guidance for DNA methylation studies: statistical insights from the Illumina EPIC array. BMC Genomics 20, 366 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Peters, T. J. et al. De novo identification of differentially methylated regions in the human genome. Epigenet. Chromatin 8, 6 (2015).

    Article 

    Google Scholar
     

  • Phipson, B., Maksimovic, J. & Oshlack, A. missMethyl: an R package for analyzing data from Illumina’s HumanMethylation450 platform. Bioinformatics 32, 286–288 (2016).

    Article 
    CAS 
    PubMed 

    Google Scholar
     



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