De Jager PL, Yang H-S, Bennett DA. Deconstructing and targeting the genomic architecture of human neurodegeneration. Nat Neurosci. 2018;21:1310–7.
Article
PubMed
CAS
Google Scholar
Pihlstrøm L, Wiethoff S, Houlden H. Chapter 22 - Genetics of neurodegenerative diseases: an overview. In: Kovacs GG, Alafuzoff I, editors. Handbook of Clinical Neurology. Volume 145: Elsevier; 2018. p. 309–23. https://doi.org/10.1016/b978-0-12-802395-2.00022-5.
Gan L, Cookson MR, Petrucelli L, La Spada AR. Converging pathways in neurodegeneration, from genetics to mechanisms. Nat Neurosci. 2018;21:1300–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Armstrong RA, Lantos PL, Cairns NJ. Overlap between neurodegenerative disorders. Neuropathology. 2005;25:111–24.
Article
PubMed
Google Scholar
Gratten J, Visscher PM. Genetic pleiotropy in complex traits and diseases: implications for genomic medicine. Genome Med. 2016;8:78.
Article
PubMed
PubMed Central
CAS
Google Scholar
Ibanez L, Farias FHG, Dube U, Mihindukulasuriya KA, Harari O. Polygenic risk scores in neurodegenerative diseases: a review. Curr Genet Med Rep. 2019;7:22–9.
Article
Google Scholar
Maier RM, Zhu Z, Lee SH, Trzaskowski M, Ruderfer DM, Stahl EA, Ripke S, Wray NR, Yang J, Visscher PM, Robinson MR. Improving genetic prediction by leveraging genetic correlations among human diseases and traits. Nat Commun. 2018;9:989.
Article
PubMed
PubMed Central
CAS
Google Scholar
Al-Chalabi A, Fang F, Hanby MF, Leigh PN, Shaw CE, Ye W, Rijsdijk F. An estimate of amyotrophic lateral sclerosis heritability using twin data. J Neurol Neurosurg Psychiatry. 2010;81:1324–6.
Article
CAS
PubMed
Google Scholar
Gatz M, Reynolds CA, Fratiglioni L, Johansson B, Mortimer JA, Berg S, Fiske A, Pedersen NL. Role of genes and environments for explaining Alzheimer disease. Arch Gen Psychiatry. 2006;63:168–74.
Article
PubMed
Google Scholar
Sullivan PF, Kendler KS, Neale MC. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry. 2003;60:1187–92.
Article
PubMed
Google Scholar
Wirdefeldt K, Gatz M, Reynolds CA, Prescott CA, Pedersen NL. Heritability of Parkinson disease in Swedish twins: a longitudinal study. Neurobiol Aging. 2011;32:1923.e1921–1923.e19238.
Article
Google Scholar
Cannon JR, Greenamyre JT. The role of environmental exposures in neurodegeneration and neurodegenerative diseases. Toxicol Sci. 2011;124:225–50.
Article
CAS
PubMed
PubMed Central
Google Scholar
De Jager PL, Srivastava G, Lunnon K, Burgess J, Schalkwyk LC, Yu L, Eaton ML, Keenan BT, Ernst J, McCabe C, et al. Alzheimer’s disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci. Nat Neurosci. 2014;17:1156–63.
Article
PubMed
PubMed Central
CAS
Google Scholar
Lunnon K, Smith R, Hannon E, De Jager PL, Srivastava G, Volta M, Troakes C, Al-Sarraj S, Burrage J, Macdonald R, et al. Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer’s disease. Nat Neurosci. 2014;17:1164–70.
Article
CAS
PubMed
PubMed Central
Google Scholar
Roubroeks JAY, Smith AR, Smith RG, Pishva E, Ibrahim Z, Sattlecker M, Hannon EJ, Kłoszewska I, Mecocci P, Soininen H, et al. An epigenome-wide association study of Alzheimer’s disease blood highlights robust DNA hypermethylation in the HOXB6 gene. Neurobiol Aging. 2020;95:26–45.
Roubroeks JAY, Smith RG, van den Hove DLA, Lunnon K. Epigenetics and DNA methylomic profiling in Alzheimer’s disease and other neurodegenerative diseases. J Neurochem. 2017;143:158–70.
Article
CAS
PubMed
Google Scholar
Chuang Y-H, Paul KC, Bronstein JM, Bordelon Y, Horvath S, Ritz B. Parkinson’s disease is associated with DNA methylation levels in human blood and saliva. Genome Med. 2017;9:76.
Article
PubMed
PubMed Central
CAS
Google Scholar
Vallerga CL, Zhang F, Fowdar J, McRae AF, Qi T, Nabais MF, Zhang Q, Kassam I, Henders AK, Wallace L, et al. Analysis of DNA methylation associates the cystine–glutamate antiporter SLC7A11 with risk of Parkinson’s disease. Nat Commun. 2020;11:1238.
Article
CAS
PubMed
PubMed Central
Google Scholar
Figueroa-Romero C, Hur J, Bender DE, Delaney CE, Cataldo MD, Smith AL, Yung R, Ruden DM, Callaghan BC, Feldman EL. Identification of epigenetically altered genes in sporadic amyotrophic lateral sclerosis. PLoS One. 2012;7:e52672.
Article
CAS
PubMed
PubMed Central
Google Scholar
Nabais MF, Lin T, Benyamin B, Williams KL, Garton FC, Vinkhuyzen AAE, Zhang F, Vallerga CL, Restuadi R, Freydenzon A, et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. NPJ Genomic Med. 2020;5:10.
Article
CAS
Google Scholar
Hannon E, Dempster E, Viana J, Burrage J, Smith AR, Macdonald R, St Clair D, Mustard C, Breen G, Therman S, et al. An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation. Genome Biol. 2016;17:176.
Article
PubMed
PubMed Central
CAS
Google Scholar
Viana J, Hannon E, Dempster E, Pidsley R, Macdonald R, Knox O, Spiers H, Troakes C, Al-Saraj S, Turecki G, et al. Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions. Hum Mol Genet. 2017;26:210–25.
CAS
PubMed
Google Scholar
McCartney DL, Hillary RF, Stevenson AJ, Ritchie SJ, Walker RM, Zhang Q, Morris SW, Bermingham ML, Campbell A, Murray AD, et al. Epigenetic prediction of complex traits and death. Genome Biol. 2018;19:136.
Article
PubMed
PubMed Central
CAS
Google Scholar
Zhang F, Chen W, Zhu Z, Zhang Q, Nabais MF, Qi T, Deary IJ, Wray NR, Visscher PM, McRae AF, Yang J. OSCA: a tool for omic-data-based complex trait analysis. Genome Biol. 2019;20:107.
Article
PubMed
PubMed Central
Google Scholar
McLaughlin RL, Schijven D, van Rheenen W, van Eijk KR, O’Brien M, Kahn RS, Ophoff RA, Goris A, Bradley DG, Al-Chalabi A, et al. Genetic correlation between amyotrophic lateral sclerosis and schizophrenia. Nat Commun. 2017;8:14774.
Article
CAS
PubMed
PubMed Central
Google Scholar
Yap H-Y, Tee SZ-Y, Wong MM-T, Chow S-K, Peh S-C, Teow S-Y. Pathogenic role of immune cells in rheumatoid arthritis: implications in clinical treatment and biomarker development. Cells. 2018;7:161.
Article
CAS
PubMed Central
Google Scholar
Min JL, Hemani G, Davey Smith G, Relton C, Suderman M. Meffil: efficient normalization and analysis of very large DNA methylation datasets. Bioinformatics. 2018;34(23):3983–9.
Zhou W, Laird PW, Shen H. Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes. Nucleic Acids Res. 2017;45:e22.
PubMed
Google Scholar
Elliott HR, Tillin T, McArdle WL, Ho K, Duggirala A, Frayling TM, Davey Smith G, Hughes AD, Chaturvedi N, Relton CL. Differences in smoking associated DNA methylation patterns in South Asians and Europeans. Clin Epigenetics. 2014;6:4.
Article
PubMed
PubMed Central
CAS
Google Scholar
Tsaprouni LG, Yang T-P, Bell J, Dick KJ, Kanoni S, Nisbet J, Viñuela A, Grundberg E, Nelson CP, Meduri E, et al. Cigarette smoking reduces DNA methylation levels at multiple genomic loci but the effect is partially reversible upon cessation. Epigenetics. 2014;9:1382–96.
Article
PubMed
PubMed Central
Google Scholar
Zeilinger S, Kühnel B, Klopp N, Baurecht H, Kleinschmidt A, Gieger C, Weidinger S, Lattka E, Adamski J, Peters A, et al. Tobacco smoking leads to extensive genome-wide changes in DNA methylation. PLoS One. 2013;8:e63812.
Article
CAS
PubMed
PubMed Central
Google Scholar
de Leon J, Diaz FJ. A meta-analysis of worldwide studies demonstrates an association between schizophrenia and tobacco smoking behaviors. Schizophr Res. 2005;76:135–57.
Article
PubMed
Google Scholar
McClave AK, McKnight-Eily LR, Davis SP, Dube SR. Smoking characteristics of adults with selected lifetime mental illnesses: results from the 2007 National Health Interview Survey. Am J Public Health. 2010;100:2464–72.
Article
PubMed
PubMed Central
Google Scholar
de Bakker PIW, Ferreira MAR, Jia X, Neale BM, Raychaudhuri S, Voight BF. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum Mol Genet. 2008;17:R122–8.
Article
PubMed
PubMed Central
CAS
Google Scholar
Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–58.
Article
PubMed
Google Scholar
Qi T, Wu Y, Zeng J, Zhang F, Xue A, Jiang L, Zhu Z, Kemper K, Yengo L, Zheng Z, et al. Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nat Commun. 2018;9:2282.
Article
PubMed
PubMed Central
CAS
Google Scholar
McRae AF, Marioni RE, Shah S, Yang J, Powell JE, Harris SE, Gibson J, Henders AK, Bowdler L, Painter JN, et al. Identification of 55,000 replicated DNA methylation QTL. Sci Rep. 2018;8:17605.
Article
PubMed
PubMed Central
CAS
Google Scholar
Marioni RE, Harris SE, Zhang Q, McRae AF, Hagenaars SP, Hill WD, Davies G, Ritchie CW, Gale CR, Starr JM, et al. GWAS on family history of Alzheimer’s disease. Transl Psychiatry. 2018;8:99.
Article
PubMed
PubMed Central
Google Scholar
Nicolas A, Kenna KP, Renton AE, Ticozzi N, Faghri F, Chia R, Dominov JA, Kenna BJ, Nalls MA, Keagle P, et al. Genome-wide analyses identify KIF5A as a novel ALS gene. Neuron. 2018;97:1268–1283.e1266.
Article
CAS
PubMed
PubMed Central
Google Scholar
Nalls MA, Blauwendraat C, Vallerga CL, Heilbron K, Bandres-Ciga S, Chang D, Tan M, Kia DA, Noyce AJ, Xue 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. 2019;18:1091–102.
Article
CAS
PubMed
PubMed Central
Google Scholar
Shah S, Bonder Marc J, Marioni Riccardo E, Zhu Z, McRae Allan F, Zhernakova A, Harris Sarah E, Liewald D, Henders Anjali K, Mendelson Michael M, et al. Improving phenotypic prediction by combining genetic and epigenetic associations. Am J Hum Genet. 2015;97:75–85.
Article
CAS
PubMed
PubMed Central
Google Scholar
Kunkle BW, Grenier-Boley B, Sims R, Bis JC, Damotte V, Naj AC, Boland A, Vronskaya M, van der Lee SJ, Amlie-Wolf A, et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat Genet. 2019;51:414–30.
Article
CAS
PubMed
PubMed Central
Google Scholar
Jansen R, Hottenga J-J, Nivard MG, Abdellaoui A, Laport B, de Geus EJ, Wright FA, Penninx BWJH, Boomsma DI. Conditional eQTL analysis reveals allelic heterogeneity of gene expression. Hum Mol Genet. 2017;26:1444–51.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bonder MJ, Luijk R, Zhernakova DV, Moed M, Deelen P, Vermaat M, van Iterson M, van Dijk F, van Galen M, Bot J, et al. Disease variants alter transcription factor levels and methylation of their binding sites. Nat Genet. 2017;49:131–8.
Article
CAS
PubMed
Google Scholar
Ng B, White CC, Klein H-U, Sieberts SK, McCabe C, Patrick E, Xu J, Yu L, Gaiteri C, Bennett DA, et al. An xQTL map integrates the genetic architecture of the human brain’s transcriptome and epigenome. Nat Neurosci. 2017;20:1418–26.
Article
CAS
PubMed
PubMed Central
Google Scholar
Carrasquillo MM, Allen M, Reddy JS, Hoffman GE, Dang KK, Calley J, Ebert PJ, Eddy J, Wang X, Greenwood AK, Mostafavi S, CommonMind Consortium (CMC), The AMP-AD Consortium, Omberg L, Peters MA, Logsdon BA, De Jager PL, Ertekin-Taner N, Mangravite LM. Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions. Sci Data. 2020;7(1):340. https://doi.org/10.1038/s41597-020-00642-8.
Teschendorff AE, Breeze CE, Zheng SC, Beck S. A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies. BMC Bioinformatics. 2017;18:105.
Article
PubMed
PubMed Central
CAS
Google Scholar
Zhang Q, Vallerga CL, Walker RM, et al. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Med. 2019;11:54. https://doi.org/10.1186/s13073-019-0667-1.
Barker ED, Cecil CAM, Walton E, Houtepen LC, O’Connor TG, Danese A, Jaffee SR, Jensen SKG, Pariante C, McArdle W, et al. Inflammation-related epigenetic risk and child and adolescent mental health: a prospective study from pregnancy to middle adolescence. Dev Psychopathol. 2018;30:1145–56.
Article
PubMed
PubMed Central
Google Scholar
Ligthart S, Marzi C, Aslibekyan S, Mendelson MM, Conneely KN, Tanaka T, Colicino E, Waite LL, Joehanes R, Guan W, et al. DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. Genome Biol. 2016;17:255.
Article
PubMed
PubMed Central
CAS
Google Scholar
Buhl AM, Jurlander J, Geisler CH, Pedersen LB, Andersen MK, Josefsson P, Petersen JH, Leffers H. CLLU1 expression levels predict time to initiation of therapy and overall survival in chronic lymphocytic leukemia. Eur J Haematol. 2006;76:455–64.
Article
CAS
PubMed
Google Scholar
Glad CAM, Andersson-Assarsson JC, Berglund P, Bergthorsdottir R, Ragnarsson O, Johannsson G. Reduced DNA methylation and psychopathology following endogenous hypercortisolism - a genome-wide study. Sci Rep. 2017;7:44445.
Article
CAS
PubMed
PubMed Central
Google Scholar
Blair LJ, Nordhues BA, Hill SE, Scaglione KM, O’Leary JC III, Fontaine SN, Breydo L, Zhang B, Li P, Wang L, et al. Accelerated neurodegeneration through chaperone-mediated oligomerization of tau. J Clin Invest. 2013;123:4158–69.
Article
CAS
PubMed
PubMed Central
Google Scholar
Jinwal UK, Koren J 3rd, Borysov SI, Schmid AB, Abisambra JF, Blair LJ, Johnson AG, Jones JR, Shults CL, O’Leary JC 3rd, et al. The Hsp90 cochaperone, FKBP51, increases Tau stability and polymerizes microtubules. J Neurosci. 2010;30:591–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zannas AS, Jia M, Hafner K, Baumert J, Wiechmann T, Pape JC, Arloth J, Ködel M, Martinelli S, Roitman M, et al. Epigenetic upregulation of FKBP5 by aging and stress contributes to NF-κB–driven inflammation and cardiovascular risk. Proc Natl Acad Sci. 2019;116:11370.
Article
CAS
PubMed
PubMed Central
Google Scholar
Houseman E, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, Kelsey KT. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bionformatics. 2012;13:86. https://doi.org/10.1186/1471-2105-13-86.
Michels KB, Binder AM, Dedeurwaerder S, Epstein CB, Greally JM, Gut I, Houseman EA, Izzi B, Kelsey KT, Meissner A, et al. Recommendations for the design and analysis of epigenome-wide association studies. Nat Methods. 2013;10:949.
Article
CAS
PubMed
Google Scholar
Boerkoel CF, Takashima H, Stankiewicz P, Garcia CA, Leber SM, Rhee-Morris L, Lupski JR. Periaxin mutations cause recessive Dejerine-Sottas neuropathy. Am J Hum Genet. 2001;68:325–33.
Article
CAS
PubMed
Google Scholar
Guilbot AL, Williams A, Ravisé N, Verny C, Brice A, Sherman DL, Brophy PJ, LeGuern E, Vr D, Bareil C, et al. A mutation in periaxin is responsible for CMT4F, an autosomal recessive form of Charcot–Marie–Tooth disease. Hum Mol Genet. 2001;10:415–22.
Article
CAS
PubMed
Google Scholar
Hung C-W, Chen Y-C, Hsieh W-L, Chiou S-H, Kao C-L. Ageing and neurodegenerative diseases. Ageing Res Rev. 2010;9:S36–46.
Article
PubMed
Google Scholar
Amor S, Puentes F, Baker D, van der Valk P. Inflammation in neurodegenerative diseases. Immunology. 2010;129:154–69.
Article
CAS
PubMed
PubMed Central
Google Scholar
McCombe PA, Henderson RD. The role of immune and inflammatory mechanisms in ALS. Curr Mol Med. 2011;11:246–54.
Article
CAS
PubMed
PubMed Central
Google Scholar
Braun PR, Han S, Hing B, Nagahama Y, Gaul LN, Heinzman JT, Grossbach AJ, Close L, Dlouhy BJ, Howard MA, et al. Genome-wide DNA methylation comparison between live human brain and peripheral tissues within individuals. Transl Psychiatry. 2019;9:47.
Article
PubMed
PubMed Central
CAS
Google Scholar
Hannon E, Lunnon K, Schalkwyk L, Mill J. Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes. Epigenetics. 2015;10:1024–32.
Article
PubMed
PubMed Central
Google Scholar
Hannon E, Mansell G, Burrage J, Kepa A, Best-Lane J, Rose A, Heck S, Moffitt T, Caspi A, Arseneault L, Mill J. Assessing the co-variability of DNA methylation across peripheral cells and tissues: implications for the interpretation of findings in epigenetic epidemiology. bioRxiv. 2020; 2020.2005.2021.107730.
Brooks BR, Miller RG, Swash M, Munsat TL. El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Other Motor Neuron Disord. 2000;1:293–9.
Article
CAS
PubMed
Google Scholar
Sachdev PS, Lammel A, Trollor JN, Lee T, Wright MJ, Ames D, Wen W, Martin NG, Brodaty H, Schofield PR. A comprehensive neuropsychiatric study of elderly twins: the older Australian twins study. Twin Res Hum Genet. 2009;12:573–82.
Article
PubMed
Google Scholar
Project Min EALSSC. Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis. Eur J Hum Genet. 2018;26:1537–46.
Article
CAS
Google Scholar
Huisman MHB, de Jong SW, van Doormaal PTC, Weinreich SS, Schelhaas HJ, van der Kooi AJ, de Visser M, Veldink JH, van den Berg LH. Population based epidemiology of amyotrophic lateral sclerosis using capture–recapture methodology. J Neurol Neurosurg Psychiatry. 2011;82:1165.
Article
PubMed
Google Scholar
Costello S, Cockburn M, Bronstein J, Zhang X, Ritz B. Parkinson’s disease and residential exposure to maneb and paraquat from agricultural applications in the central valley of California. Am J Epidemiol. 2009;169:919–26.
Article
PubMed
PubMed Central
Google Scholar
Horvath S, Ritz BR. Increased epigenetic age and granulocyte counts in the blood of Parkinson’s disease patients. Aging (Albany NY). 2015;7:1130–42.
Article
CAS
Google Scholar
Ellis KA, Bush AI, Darby D, De Fazio D, Foster J, Hudson P, Lautenschlager NT, Lenzo N, Martins RN, Maruff P, et al. The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer’s disease. Int Psychogeriatr. 2009;21:672–87.
Article
PubMed
Google Scholar
Petersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, Jack CR Jr, Jagust WJ, Shaw LM, Toga AW, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology. 2010;74:201–9 http://adni.loni.usc.edu/data-samples/access-data/.
Article
PubMed
PubMed Central
Google Scholar
Lovestone S, Francis P, Kloszewska I, Mecocci P, Simmons A, Soininen H, Spenger C, Tsolaki M, Vellas B, Wahlund L-O, et al. AddNeuroMed—the European collaboration for the discovery of novel biomarkers for Alzheimer’s disease. Ann N Y Acad Sci. 2009;1180:36–46.
Article
CAS
PubMed
Google Scholar
Lovestone S, Francis P, Strandgaard K. Biomarkers for disease modification trials--the innovative medicines initiative and AddNeuroMed. J Nutr Health Aging. 2007;11(4):359–61.
CAS
PubMed
Google Scholar
McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease. Neurology. 1984;34:939.
Article
CAS
PubMed
Google Scholar
Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999;56:303–8.
Article
CAS
PubMed
Google Scholar
Furney SJ, Simmons A, Breen G, Pedroso I, Lunnon K, Proitsi P, Hodges A, Powell J, Wahlund LO, Kloszewska I, et al. Genome-wide association with MRI atrophy measures as a quantitative trait locus for Alzheimer’s disease. Mol Psychiatry. 2011;16:1130–8.
Article
CAS
PubMed
Google Scholar
Datta SR, McQuillin A, Rizig M, Blaveri E, Thirumalai S, Kalsi G, Lawrence J, Bass NJ, Puri V, Choudhury K, et al. A threonine to isoleucine missense mutation in the pericentriolar material 1 gene is strongly associated with schizophrenia. Mol Psychiatry. 2008;15:615.
Article
PubMed
CAS
Google Scholar
The International Schizophrenia C, Stone JL, O’Donovan MC, Gurling H, Kirov GK, Blackwood DHR, Corvin A, Craddock NJ, Gill M, Hultman CM, et al. Rare chromosomal deletions and duplications increase risk of schizophrenia. Nature. 2008;455:237.
Article
CAS
Google Scholar
Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, Reinius L, Acevedo N, Taub M, Ronninger M, et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol. 2013;31:142.
Article
CAS
PubMed
PubMed Central
Google Scholar
Padyukov L, Silva C, Stolt P, Alfredsson L, Klareskog L. A gene–environment interaction between smoking and shared epitope genes in HLA–DR provides a high risk of seropositive rheumatoid arthritis. Arthritis Rheum. 2004;50:3085–92.
Article
CAS
PubMed
Google Scholar
Deary IJ, Gow AJ, Pattie A, Starr JM. Cohort profile: the Lothian Birth Cohorts of 1921 and 1936. Int J Epidemiol. 2011;41:1576–84.
Article
PubMed
Google Scholar
Taylor AM, Pattie A, Deary IJ. Cohort profile update: the Lothian Birth Cohorts of 1921 and 1936. Int J Epidemiol. 2018;47:1042–1042r https://www.lothianbirthcohort.ed.ac.uk/content/collaboration.
Article
PubMed
PubMed Central
Google Scholar
Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE, Gibson J, Henders AK, Redmond P, Cox SR, et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 2015;16:25.
Article
PubMed
PubMed Central
CAS
Google Scholar
Shah S, McRae AF, Marioni RE, Harris SE, Gibson J, Henders AK, Redmond P, Cox SR, Pattie A, Corley J, et al. Genetic and environmental exposures constrain epigenetic drift over the human life course. Genome Res. 2014;24:1725–33.
Article
CAS
PubMed
PubMed Central
Google Scholar
Fortin J-P, Labbe A, Lemire M, Zanke BW, Hudson TJ, Fertig EJ, Greenwood CMT, Hansen KD. Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biol. 2014;15:503.
Article
PubMed
PubMed Central
CAS
Google Scholar
Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 2014;15:R31.
Article
PubMed
PubMed Central
Google Scholar
Kang HM, Sul JH, Service SK, Zaitlen NA, Kong S-Y, Freimer NB, Sabatti C, Eskin E. Variance component model to account for sample structure in genome-wide association studies. Nat Genet. 2010;42:348.
Article
CAS
PubMed
PubMed Central
Google Scholar
Yang J, Zaitlen NA, Goddard ME, Visscher PM, Price AL. Advantages and pitfalls in the application of mixed-model association methods. Nat Genet. 2014;46:100–6.
Article
PubMed
PubMed Central
CAS
Google Scholar
Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics (Oxford, England). 2010;26:2190–1.
Article
CAS
Google Scholar
Venables WN, Ripley BD. Modern Applied Statistics with S. 4th ed. New York: Springer; 2002.
Book
Google Scholar
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, Müller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bionformatics. 2011;12:77. https://doi.org/10.1186/1471-2105-12-77.
Nabais MF. Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders. Github. 2020. https://doi.org/10.5281/zenodo.4287177.
Gratten J: Epigenome analysis of Parkinson’s disease and control samples from the System Genomics Parkinson’s disease (SGPD) consortium. GSE145361. Gene Expression Omnibus. 2020. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE145361.
Ritz B, Horvath S: Genome wide DNA methylation study of Parkinson’s disease in whole blood samples. GSE111629. Gene Expression Omnibus. 2018. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111629.
Veldink JH: ProjectMine. European Genome-phenome Archive. 2020. https://www.ebi.ac.uk/ega/dacs/EGAC00001000703.
Nabais MF, Laws SM, Wray NR, Henders AK, Wallace L, McRae AF: Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders. GSE153712. Gene Expression Omnibus. 2020. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE153712.
Lunnon K, Roubroeks JAY: An epigenome-wide association study of Alzheimer’s disease blood highlights robust DNA hypermethylation in the HOXB6 gene. GSE144858. Gene Expression Omnibus. 2020. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE144858.
Hannon E, Dempster E, Viana J, Burrage J, Smith AR, Macdonald R, St. Clair D, Mustard C, Breen G, Therman S, et al: An integrated genetic-epigenetic analysis of schizophrenia: Evidence for co-localization of genetic associations and differential DNA methylation. GSE84727. Gene Expression Omnibus. 2016. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84727.
Hannon E, Dempster E, Viana J, Burrage J, Smith AR, Macdonald R, St. Clair D, Mustard C, Breen G, Therman S, et al: An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation. GSE80417. Gene Expression Omnibus. 2016. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80417.
Liu Y, AP F: Differential DNA methylation in rheumatoid arthritis. GSE42861. Gene Expression Omnibus. 2013. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse42861.