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02.02.2019 | Original Paper

Integrated DNA methylation and gene expression profiling across multiple brain regions implicate novel genes in Alzheimer’s disease

verfasst von: Stephen A. Semick, Rahul A. Bharadwaj, Leonardo Collado-Torres, Ran Tao, Joo Heon Shin, Amy Deep-Soboslay, James R. Weiss, Daniel R. Weinberger, Thomas M. Hyde, Joel E. Kleinman, Andrew E. Jaffe, Venkata S. Mattay

Erschienen in: Acta Neuropathologica | Ausgabe 4/2019

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Abstract

Late-onset Alzheimer’s disease (AD) is a complex age-related neurodegenerative disorder that likely involves epigenetic factors. To better understand the epigenetic state associated with AD, we surveyed 420,852 DNA methylation (DNAm) sites from neurotypical controls (N = 49) and late-onset AD patients (N = 24) across four brain regions (hippocampus, entorhinal cortex, dorsolateral prefrontal cortex and cerebellum). We identified 858 sites with robust differential methylation collectively annotated to 772 possible genes (FDR < 5%, within 10 kb). These sites were overrepresented in AD genetic risk loci (p = 0.00655) and were enriched for changes during normal aging (p < 2.2 × 10⁻¹⁶), and nearby genes were enriched for processes related to cell-adhesion, immunity, and calcium homeostasis (FDR < 5%). To functionally validate these associations, we generated and analyzed corresponding transcriptome data to prioritize 130 genes within 10 kb of the differentially methylated sites. These 130 genes were differentially expressed between AD cases and controls and their expression was associated with nearby DNAm (p < 0.05). This integrated analysis implicates novel genes in Alzheimer’s disease, such as ANKRD30B. These results highlight DNAm differences in Alzheimer’s disease that have gene expression correlates, further implicating DNAm as an epigenetic mechanism underlying pathological molecular changes associated with AD. Furthermore, our framework illustrates the value of integrating epigenetic and transcriptomic data for understanding complex disease.

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Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc

Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD et al (2014) Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30:1363–1369. https://doi.org/10.1093/bioinformatics/btu049 CrossRefPubMedPubMedCentral

Bakulski KM, Dolinoy DC, Sartor MA, Paulson HL, Konen JR, Lieberman AP et al (2012) Genome-wide DNA methylation differences between late-onset Alzheimer’s disease and cognitively normal controls in human frontal cortex. J Alzheimers Dis 29:571–588. https://doi.org/10.3233/JAD-2012-111223 CrossRefPubMed

Bharadwaj R, Peter CJ, Jiang Y, Roussos P, Vogel-Ciernia A, Shen EY et al (2014) Conserved higher-order chromatin regulates NMDA receptor gene expression and cognition. Neuron 84:997–1008. https://doi.org/10.1016/j.neuron.2014.10.032 CrossRefPubMedPubMedCentral

Braak H, Braak E (1991) Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica 82(4):239–259CrossRefPubMed

Chouliaras L, Mastroeni D, Delvaux E, Grover A, Kenis G, Hof PR et al (2013) Consistent decrease in global DNA methylation and hydroxymethylation in the hippocampus of Alzheimer’s disease patients. Neurobiol Aging 34:2091–2099. https://doi.org/10.1016/j.neurobiolaging.2013.02.021 CrossRefPubMedPubMedCentral

Collado-Torres L, Burke EE, Peterson A, Shin JH, Straub RE, Rajpurohi A et al (2018) Regional heterogeneity in gene expression, regulation and coherence in hippocampus and dorsolateral prefrontal cortex across development and in schizophrenia. bioRxiv. https://doi.org/10.1101/426213 CrossRef

Conejero-Goldberg C, Hyde TM, Chen S, Herman MM, Kleinman JE, Davies P et al (2015) Cortical Transcriptional Profiles in APOE4 Carriers with Alzheimer's disease: patterns of protection and degeneration. J Alzheimers Dis 48(4):969–978CrossRefPubMed

Coppieters N, Dieriks BV, Lill C, Faull RL, Curtis MA, Dragunow M (2014) Global changes in DNA methylation and hydroxymethylation in Alzheimer’s disease human brain. Neurobiol Aging 35:1334–1344. https://doi.org/10.1016/j.neurobiolaging.2013.11.031 CrossRefPubMed

10.

Corder EH, Saunders AM, Strittmatter WJ, Schmechel DE, Gaskell PC, Small GW et al (1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261:921–923CrossRefPubMed

11.

Davies MN, Volta M, Pidsley R, Lunnon K, Dixit A, Lovestone S et al (2012) Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol 13:R43. https://doi.org/10.1186/gb-2012-13-6-r43 CrossRefPubMedPubMedCentral

12.

De Jager PL, Srivastava G, Lunnon K, Burgess J, Schalkwyk LC, Yu L et al (2014) Alzheimer’s disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci. Nat Neurosci 17:1156–1163. https://doi.org/10.1038/nn.3786 CrossRefPubMedPubMedCentral

13.

Farrer LA, Cupples LA, Haines JL, Hyman B, Kukull WA, Mayeux R et al (1997) Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA 278:1349–1356CrossRefPubMed

14.

Fleminger S (2003) Head injury as a risk factor for Alzheimer's disease: the evidence 10 years on; a partial replication. J Neurol Neurosurg Psychiatry 74(7):857–862CrossRefPubMedPubMedCentral

15.

Gasparoni G, Bultmann S, Lutsik P, Kraus TFJ, Sordon S, Vlcek J et al (2018) DNA methylation analysis on purified neurons and glia dissects age and Alzheimer’s disease-specific changes in the human cortex. Epigenet Chromatin 11:41. https://doi.org/10.1186/s13072-018-0211-3 CrossRef

16.

Gjoneska E, Pfenning AR, Mathys H, Quon G, Kundaje A, Tsai LH et al (2015) Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease. Nature 518:365–369. https://doi.org/10.1038/nature14252 CrossRefPubMedPubMedCentral

17.

Graff J, Rei D, Guan JS, Wang WY, Seo J, Hennig KM et al (2012) An epigenetic blockade of cognitive functions in the neurodegenerating brain. Nature 483:222–226. https://doi.org/10.1038/nature10849 CrossRefPubMedPubMedCentral

18.

Guintivano J, Aryee MJ, Kaminsky ZA (2013) A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression. Epigenetics 8:290–302. https://doi.org/10.4161/epi.23924 CrossRefPubMedPubMedCentral

19.

Gutierrez-Arcelus M, Ongen H, Lappalainen T, Montgomery SB, Buil A, Yurovsky A et al (2015) Tissue-specific effects of genetic and epigenetic variation on gene regulation and splicing. PLoS Genet 11:e1004958. https://doi.org/10.1371/journal.pgen.1004958 CrossRefPubMedPubMedCentral

20.

Hasin Y, Seldin M, Lusis A (2017) Multi-omics approaches to disease. Genome Biol 18:83. https://doi.org/10.1186/s13059-017-1215-1 CrossRefPubMedPubMedCentral

21.

Horvath S (2013) DNA methylation age of human tissues and cell types. Genome Biol 14:R115. https://doi.org/10.1186/gb-2013-14-10-r115 CrossRefPubMedPubMedCentral

22.

Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH et al (2012) DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinform 13:86. https://doi.org/10.1186/1471-2105-13-86 CrossRef

23.

Hyman BT, Trojanowski JQ (1997) Consensus recommendations for the postmortem diagnosis of Alzheimer disease from the National Institute on Aging and the Reagan Institute Working Group on diagnostic criteria for the neuropathological assessment of Alzheimer disease. J Neuropathol Exp Neurol 56(10):1095–1097CrossRefPubMed

24.

Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P et al (2009) The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat Genet 41:178–186. https://doi.org/10.1038/ng.298 CrossRefPubMedPubMedCentral

25.

Jaffe AE, Irizarry RA (2014) Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol 15:R31. https://doi.org/10.1186/gb-2014-15-2-r31 CrossRefPubMedPubMedCentral

26.

Jaffe AE, Murakami P, Lee H, Leek JT, Fallin MD, Feinberg AP et al (2012) Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. Int J Epidemiol 41:200–209. https://doi.org/10.1093/ije/dyr238 CrossRefPubMedPubMedCentral

27.

Jager D, Stockert E, Gure AO, Scanlan MJ, Karbach J, Jager E et al (2001) Identification of a tissue-specific putative transcription factor in breast tissue by serological screening of a breast cancer library. Cancer Res 61:2055–2061PubMed

28.

Jansen I, Kiddle SJ, Posthuma D. Genetic meta-analysis identifies 9 novel loci and functional pathways for Alzheimer’s disease risk. Nature Genet. https://doi.org/10.17863/CAM.35461

29.

Kaup AR, Nettiksimmons J, Harris TB, Sink KM, Satterfield S, Metti AL et al (2015) Cognitive resilience to apolipoprotein E epsilon4: contributing factors in black and white older adults. JAMA Neurol 72:340–348. https://doi.org/10.1001/jamaneurol.2014.3978 CrossRefPubMedPubMedCentral

30.

Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12:357–360. https://doi.org/10.1038/nmeth.3317 CrossRefPubMedPubMedCentral

31.

Klein HU, Bennett DA, De Jager PL (2016) The epigenome in Alzheimer’s disease: current state and approaches for a new path to gene discovery and understanding disease mechanism. Acta Neuropathol 132:503–514. https://doi.org/10.1007/s00401-016-1612-7 CrossRefPubMedPubMedCentral

32.

Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C et al (2013) Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat Genet 45:1452–1458. https://doi.org/10.1038/ng.2802 CrossRefPubMedPubMedCentral

33.

Lawrence M, Huber W, Pages H, Aboyoun P, Carlson M, Gentleman R et al (2013) Software for computing and annotating genomic ranges. PLoS Comput Biol 9:e1003118. https://doi.org/10.1371/journal.pcbi.1003118 CrossRefPubMedPubMedCentral

34.

Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930. https://doi.org/10.1093/bioinformatics/btt656 CrossRefPubMed

35.

Lim AS, Kowgier M, Yu L, Buchman AS, Bennett DA (2013) Sleep fragmentation and the risk of incident Alzheimer’s disease and cognitive decline in older persons. Sleep 36:1027–1032. https://doi.org/10.5665/sleep.2802 CrossRefPubMedPubMedCentral

36.

Lindsay J, Laurin D, Verreault R, Hebert R, Helliwell B, Hill GB et al (2002) Risk factors for Alzheimer’s disease: a prospective analysis from the Canadian Study of Health and Aging. Am J Epidemiol 156:445–453CrossRefPubMed

37.

Lipska BK, Deep-Soboslay A, Weickert CS, Hyde TM, Martin CE, Herman MM et al (2006) Critical factors in gene expression in postmortem human brain: focus on studies in schizophrenia. Biol Psychiatry 60:650–658. https://doi.org/10.1016/j.biopsych.2006.06.019 CrossRefPubMed

38.

Liu CC, Liu CC, Kanekiyo T, Xu H, Bu G (2013) Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol 9:106–118. https://doi.org/10.1038/nrneurol.2012.263 CrossRefPubMedPubMedCentral

39.

Liu G, Jiang Y, Wang P, Feng R, Jiang N, Chen X et al (2012) Cell adhesion molecules contribute to Alzheimer’s disease: multiple pathway analyses of two genome-wide association studies. J Neurochem 120:190–198. https://doi.org/10.1111/j.1471-4159.2011.07547.x CrossRefPubMed

40.

Lunnon K, Smith R, Hannon E, De Jager PL, Srivastava G, Volta M et al (2014) Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer’s disease. Nat Neurosci 17:1164–1170. https://doi.org/10.1038/nn.3782 CrossRefPubMedPubMedCentral

41.

Magi S, Castaldo P, Macri ML, Maiolino M, Matteucci A, Bastioli G et al (2016) Intracellular calcium dysregulation: implications for Alzheimer’s disease. Biomed Res Int 2016:6701324. https://doi.org/10.1155/2016/6701324 CrossRefPubMedPubMedCentral

42.

Marioni RE, Harris SE, Zhang Q, McRae AF, Hagenaars SP, Hill WD et al (2018) GWAS on family history of Alzheimer’s disease. Transl Psychiatry 8:99. https://doi.org/10.1038/s41398-018-0150-6 CrossRefPubMedPubMedCentral

43.

Marzi SJ, Leung SK, Ribarska T, Hannon E, Smith AR, Pishva E et al (2018) A histone acetylome-wide association study of Alzheimer’s disease identifies disease-associated H3K27ac differences in the entorhinal cortex. Nat Neurosci 21:1618–1627. https://doi.org/10.1038/s41593-018-0253-7 CrossRefPubMed

44.

Mastroeni D, McKee A, Grover A, Rogers J, Coleman PD (2009) Epigenetic differences in cortical neurons from a pair of monozygotic twins discordant for Alzheimer’s disease. PLoS One 4:e6617. https://doi.org/10.1371/journal.pone.0006617 CrossRefPubMedPubMedCentral

45.

Mastroeni D, Sekar S, Nolz J, Delvaux E, Lunnon K, Mill J et al (2017) ANK1 is up-regulated in laser captured microglia in Alzheimer’s brain; the importance of addressing cellular heterogeneity. PLoS One 12:e0177814. https://doi.org/10.1371/journal.pone.0177814 CrossRefPubMedPubMedCentral

46.

Miller JA, Guillozet-Bongaarts A, Gibbons LE, Postupna N, Renz A, Beller AE et al (2017) Neuropathological and transcriptomic characteristics of the aged brain. Elife. https://doi.org/10.7554/elife.31126 CrossRefPubMedPubMedCentral

47.

Montano CM, Irizarry RA, Kaufmann WE, Talbot K, Gur RE, Feinberg AP et al (2013) Measuring cell-type specific differential methylation in human brain tissue. Genome Biol 14:R94. https://doi.org/10.1186/gb-2013-14-8-r94 CrossRefPubMedPubMedCentral

48.

Mostafavi S, Gaiteri C, Sullivan SE, White CC, Tasaki S, Xu J et al (2018) A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer’s disease. Nat Neurosci 21:811–819. https://doi.org/10.1038/s41593-018-0154-9 CrossRefPubMedPubMedCentral

49.

Nativio R, Donahue G, Berson A, Lan Y, Amlie-Wolf A, Tuzer F et al (2018) Dysregulation of the epigenetic landscape of normal aging in Alzheimer’s disease. Nat Neurosci 21:497–505. https://doi.org/10.1038/s41593-018-0101-9 CrossRefPubMedPubMedCentral

50.

Ng B, White CC, Klein HU, Sieberts SK, McCabe C, Patrick E et al (2017) An xQTL map integrates the genetic architecture of the human brain’s transcriptome and epigenome. Nat Neurosci 20:1418–1426. https://doi.org/10.1038/nn.4632 CrossRefPubMedPubMedCentral

51.

Patel H, Dobson RJB, Newhouse SJ (2018) Meta-analysis of Alzheimer’s disease brain transcriptomic data. bioRxiv. https://doi.org/10.1101/480459 CrossRef

52.

Price AJ, Collado-Torres L, Ivanov NA, Xia W, Burke EE, Shin JH et al (2018) Divergent neuronal DNA methylation patterns across human cortical development: critical periods and a unique role of CpH methylation. bioRxiv. https://doi.org/10.1101/428391 CrossRef

53.

Radak Z, Hart N, Sarga L, Koltai E, Atalay M, Ohno H et al (2010) Exercise plays a preventive role against Alzheimer’s disease. J Alzheimers Dis 20:777–783. https://doi.org/10.3233/JAD-2010-091531 CrossRefPubMed

54.

Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W et al (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43:e47. https://doi.org/10.1093/nar/gkv007 CrossRefPubMedPubMedCentral

55.

Rizzardi LF, Hickey PF, DiBlasi VR, Tryggvadóttir R, Callahan CM, Idrizi A et al (2019) Neuronal brain-region-specific DNA methylation and chromatin accessibility are associated with neuropsychiatric trait heritability. Nature Neurosci 22(2):307–316CrossRefPubMed

56.

Sanchez-Mut JV, Aso E, Heyn H, Matsuda T, Bock C, Ferrer I et al (2014) Promoter hypermethylation of the phosphatase DUSP22 mediates PKA-dependent TAU phosphorylation and CREB activation in Alzheimer’s disease. Hippocampus 24:363–368. https://doi.org/10.1002/hipo.22245 CrossRefPubMedPubMedCentral

57.

Sanchez-Mut JV, Aso E, Panayotis N, Lott I, Dierssen M, Rabano A et al (2013) DNA methylation map of mouse and human brain identifies target genes in Alzheimer’s disease. Brain 136:3018–3027. https://doi.org/10.1093/brain/awt237 CrossRefPubMedPubMedCentral

58.

Sanchez-Mut JV, Graff J (2015) Epigenetic alterations in Alzheimer’s disease. Front Behav Neurosci 9:347. https://doi.org/10.3389/fnbeh.2015.00347 CrossRefPubMedPubMedCentral

59.

Sanchez-Mut JV, Heyn H, Silva BA, Dixsaut L, Garcia-Esparcia P, Vidal E et al (2018) PM20D1 is a quantitative trait locus associated with Alzheimer’s disease. Nat Med 24:598–603. https://doi.org/10.1038/s41591-018-0013-y CrossRefPubMed

60.

Sanchez-Mut JV, Heyn H, Vidal E, Moran S, Sayols S, Delgado-Morales R et al (2016) Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns. Transl Psychiatry 6:e718. https://doi.org/10.1038/tp.2015.214 CrossRefPubMedPubMedCentral

61.

Scarmeas N, Stern Y, Tang MX, Mayeux R, Luchsinger JA (2006) Mediterranean diet and risk for Alzheimer’s disease. Ann Neurol 59:912–921. https://doi.org/10.1002/ana.20854 CrossRefPubMedPubMedCentral

62.

Smith AR, Mill J, Smith RG, Lunnon K (2016) Elucidating novel dysfunctional pathways in Alzheimer's disease by integrating loci identified in genetic and epigenetic studies. Neuroepigenetics 6:32–50CrossRef

63.

Smith AR, Smith RG, Burrage J, Troakes C, Al-Sarraj S, Kalaria RN et al (2018) A cross-brain regions study of ANK1 DNA methylation in different neurodegenerative diseases. Neurobiol Aging 74:70–76. https://doi.org/10.1016/j.neurobiolaging.2018.09.024 CrossRefPubMed

64.

Smith AR, Smith RG, Condliffe D, Hannon E, Schalkwyk L, Mill J et al (2016) Increased DNA methylation near TREM2 is consistently seen in the superior temporal gyrus in Alzheimer’s disease brain. Neurobiol Aging 47:35–40. https://doi.org/10.1016/j.neurobiolaging.2016.07.008 CrossRefPubMedPubMedCentral

65.

Smith RG, Hannon E, De Jager PL, Chibnik L, Lott SJ, Condliffe D et al (2018) Elevated DNA methylation across a 48-kb region spanning the HOXA gene cluster is associated with Alzheimer’s disease neuropathology. Alzheimers Dement. https://doi.org/10.1016/j.jalz.2018.01.017 CrossRefPubMedPubMedCentral

66.

Watson CT, Roussos P, Garg P, Ho DJ, Azam N, Katsel PL et al (2016) Genome-wide DNA methylation profiling in the superior temporal gyrus reveals epigenetic signatures associated with Alzheimer’s disease. Genome Med 8:5. https://doi.org/10.1186/s13073-015-0258-8 CrossRefPubMedPubMedCentral

67.

Won H, de la Torre-Ubieta L, Stein JL, Parikshak NN, Huang J, Opland CK et al (2016) Chromosome conformation elucidates regulatory relationships in developing human brain. Nature 538:523–527. https://doi.org/10.1038/nature19847 CrossRefPubMedPubMedCentral

68.

Yamamoto T, Hirano A (1986) A comparative study of modified Bielschowsky, Bodian and thioflavin S stains on Alzheimer's neurofibrillary tangles. Neuropathol Appl Neurobiol 12(1):3–9CrossRefPubMed

69.

Yu L, Chibnik LB, Srivastava GP, Pochet N, Yang J, Xu J et al (2015) Association of brain DNA methylation in SORL1, ABCA7, HLA-DRB5, SLC24A4, and BIN1 with pathological diagnosis of Alzheimer disease. JAMA Neurol 72:15–24. https://doi.org/10.1001/jamaneurol.2014.3049 CrossRefPubMedPubMedCentral

70.

Zhang B, Gaiteri C, Bodea LG, Wang Z, McElwee J, Podtelezhnikov AA et al (2013) Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer’s disease. Cell 153:707–720. https://doi.org/10.1016/j.cell.2013.03.030 CrossRefPubMedPubMedCentral

Titel: Integrated DNA methylation and gene expression profiling across multiple brain regions implicate novel genes in Alzheimer’s disease
verfasst von: Stephen A. Semick
Rahul A. Bharadwaj
Leonardo Collado-Torres
Ran Tao
Joo Heon Shin
Amy Deep-Soboslay
James R. Weiss
Daniel R. Weinberger
Thomas M. Hyde
Joel E. Kleinman
Andrew E. Jaffe
Venkata S. Mattay
Publikationsdatum: 02.02.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Acta Neuropathologica / Ausgabe 4/2019
Print ISSN: 0001-6322
Elektronische ISSN: 1432-0533
DOI: https://doi.org/10.1007/s00401-019-01966-5

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Integrated DNA methylation and gene expression profiling across multiple brain regions implicate novel genes in Alzheimer’s disease

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