Integrated Pathway-Based Approach Identifies Association between Genomic Regions at CTCF and CACNB2 and Schizophrenia

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Large-scale genetic studies of complex diseases such as schizophrenia have identified a variety of susceptibility loci. Since many of the respective variants have only a weak influence on disease risk, pathophysiological interpretation of the results is problematic. Investigation of the joint effects of multiple functionally related genes or pathways increases the power to detect disease related genes, and provides insights into the etiology of the disease in question. In the present study, an integrated hierarchical approach was applied to: (i) identify pathways associated with complex neuropsychiatric disease schizophrenia (ii) detect potentially affected genes in these pathways; and (iii) annotate the functional consequences of genetic markers in the affected genes or their regulatory regions. Two samples comprising >10,000 individuals of European ancestry as well as data from the Psychiatric Genomics Consortium schizophrenia study were examined. Pathways representing transcriptional regulation and gene expression, cell adhesion, apoptosis, and synapse organization showed significant association with schizophrenia. In particular, CTCF, CACNB2, and ARL5B, i.e. genes involved in chromatin modulation, calcium channel signaling and membrane transport, respectively, were highlighted as candidate genes for schizophrenia risk.

Vyšlo v časopise: Integrated Pathway-Based Approach Identifies Association between Genomic Regions at CTCF and CACNB2 and Schizophrenia. PLoS Genet 10(6): e32767. doi:10.1371/journal.pgen.1004345
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004345

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1. ManolioTA, BrooksLD, CollinsFS (2008) A HapMap harvest of insights into the genetics of common disease. J Clin Invest 118: 1590–1605.

2. HindorffLA, SethupathyP, JunkinsHA, RamosEM, MehtaJP, et al. (2009) Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci USA 106: 9362–9367.

3. JiaP, WangL, MeltzerHY, ZhaoZ (2010) Pathway-based analysis of GWAS datasets: effective but caution required. Int J Neuropsychopharmacol 14: 567–572.

4. HeroldC, MattheisenM, LacourA, VaitsiakhovichT, AngischM, et al. (2009) Integrated genome-wide pathway association analysis with INTERSNP. Hum Hered 73: 63–72.

5. WangK, LiM, HakonarsonH (2010) Analysing biological pathways in genome-wide association studies. Nat Rev Genet 11: 843–854.

6. RamananVK, ShenL, MooreJH, SaykinAJ (2012) Pathways analysis of genomic data: concepts, methods, and prospoects for future development. Trends in Genetics 28: 323–332.

7. TorkamaniA, TopolEJ, SchorkNJ (2008) Pathway analysis of seven common diseases assessed by genome-wide association. Genomics 92: 265–272.

8. AsklandK, ReadC, MooreJ (2009) Pathways-based analysis of whole-genome association study data in bipolar disorder reveal genes mediating ion channel activity and synaptic neurotransmission. Hum Genet 125: 63–79.

9. HolmansP, GreenEK, PahwaJS, FerreiraMA, PurcellSM, et al. (2009) Gene ontology analysis of GWA study datasets provides insights into the biology of bipolar disorder. Am J Hum Genet 85: 13–24.

10. O'DushlaineC, KennyE, HeronE, DonohoeG, GillM, et al. (2010) Molecular pathways involved in neuronal cell adhesion and membrane scaffolding contribute to schizophrenia and bipolar disorder susceptibility. Mol Psychiatry 16: 286–292.

11. WengL, MacciardiF, SubramanianA, GuffantiG, PotkinSG, et al. (2010) SNP-based pathway enrichment analysis for genome-wide association studies. BMC Bioinformatics 12: 99 doi:10.1186/1471-2105-12-99

12. JiaP, WangL, FanousAH, ChenX, KendlerKS, et al. (2012) A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia. J Med Genet 49: 96–103.

13. MaciejewskiH (2013) Gene set analysis methods: statistical models and methodological differences. Brief Bioinform doi: 10.1093/bib/bbt002

14. GoemanJJ, BühlmannP (2004) Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics 23: 980–987.

15. GoemanJJ, van de GeerSA, de KortF, van HouwelingenHC (2004) A global test for groups of genes: testing association with a clinical outcome. Bioinformatics 20: 93–99.

16. DeelenJ, UhHW, MonajemiR, van HeemstD, ThijssenPE, et al. (2013) Gene set analysis of GWAS data for human longevity highlights the relevance of the insulin/IGF-1 signaling and telomere maintenance pathways. Age 35: 235–249.

17. PedrosoI, BreenG (2011) Gene Set Analysis and Network Analysis for Genome-Wide Association Studies. Cold Spring Harb Protoc doi:10.1101/pdb.top065581

18. BoyleA, HongE, HariharanM, ChengY, SchaubM, et al. (2012) Annotation of functional variation in personal genomes using RegulomeDB. Genome Res 22: 1790–1797.

19. JiaP, WangL, MeltzerHY, ZhaoZ (2010) Common variants conferring risk of schizophrenia: a pathway analysis of GWAS data. Schizophr Res 122: 38–42.

20. LeeYH, KimJH, SongGG (2013) Pathway analysis of a genome-wide association study in schizophrenia. Gene 525: 107–115.

21. ChenLS, HutterCM, PotterJD, LiuY, PrenticeRL, et al. (2010) Insights into Colon Cancer Etiology via a Regularized Approach to Gene Set Analysis of GWAS Data. Am J Hum Genet 86: 860–871.

22. WangK, LiM, BucanM (2007) Pathway-Based Approaches for Analysis of Genomewide Association Studies. Am J Hum Genet 81: 1278–1283.

23. HolmansP, GreenEK, PahwaJS, FerreiraMA, PurcellSM, et al. (2009) Gene ontology analysis of GWA study datasets provides insights into the biology of bipolar disorder. Am J Hum Genet 85: 13–24.

24. BuraeiZ, YangJ (2013) Structure and function of the β subunit of voltage-gated Ca(2+) channels. Biochim Biophys Acta 1828: 1530–1540.

25. Cross-Disorder Group of the Psychiatric Genomics Consortium (2010) SmollerJW, CraddockN, KendlerK, LeePH, et al. (2010) Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381: 1371–1379. Erratum in: Lancet 381: 1360.

26. LeeMT, ChenCH, LeeCS, ChenCC, ChongMY, et al. (2011) Genome-wide association study of bipolar I disorder in the Han Chinese population. Mol Psychiatry 16: 548–556.

27. KobayashiT, YamadaY, FukaoM, TsutsuuraM, TohseN (2007) Regulation of Cav1.2 current: interaction with intracellular molecules. J Pharmacol Sci 103: 347–353.

28. Psychiatric GWAS Consortium Bipolar Disorder Working Group (2013) Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet 43: 977–983.

29. FerreiraMA, O'DonovanMC, MengYA, JonesIR, RuderferMD, et al. (2008) Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet 40: 1056–1058.

30. Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (2011) RipkeS, SandersAR, KendlerKS, LevinsonDF, et al. (2011) Genome-wide association study identifies five new schizophrenia loci. Nat Gen 43: 969–976.

31. GreenEK, GrozevaD, JonesI, JonesL, KirovG, et al. (2010) The bipolar disorder risk allele at CACNA1C also confers risk of recurrent major depression and of schizophrenia. Mol Psychiatry 15: 1016–1022.

32. HoughtonFJ, BellinghamSA, HillAF, BourgesD, AngDK, et al. (2012) Arl5b is a Golgi-localised small G protein involved in the regulation of retrograde transport. Exp Cell Res 318: 464–477.

33. TayaS, ShinodaT, TsuboiD, AsakiJ, NagaiK, et al. (2007) DISC1 regulates the transport of the NUDEL/LIS1/14-3-3epsilon complex through kinesin-1. J Neurosci 27: 15–26.

34. GuoY, MonahanK, WuH, GertzJ, VarleyKE, et al. (2012) CTCF/cohesin-mediated DNA looping is required for protocadherin α promoter choice. Proc Natl Acad Sci U S A 109: 21081–21086.

35. MonahanK, RudnickND, KehayovaPD, PauliF, NewberryKM, et al. (2012) Role of CCCTC binding factor (CTCF) and cohesin in the generation of single-cell diversity of protocadherin-α gene expression. Proc Natl Acad Sci U S A 109: 9125–9130.

36. PhillipsJE, CorcesVG (2009) CTCF: master weaver of the genome. Cell 137: 1194–1211.

37. HirayamaT, TarusawaE, YoshimuraY, GaljartN, YagiT (2012) CTCF is required for neural development and stochastic expression of clustered Pcdh genes in neurons. Cell Rep 2: 345–357.

38. KirovG, GeorgievaL, WilliamsN, NikolovI, NortonN, et al. (2003) Variation in the protocadherin gamma A gene cluster. Genomics 82: 433–440.

39. GregórioSP, SalletPC, DoKA, LinE, GattazWF, Dias-NetoE (2009) Polymorphisms in genes involved in neurodevelopment may be associated with altered brain morphology in schizophrenia: preliminary evidence. Psychiatry Res 165: 1–9.

40. MatsuzakaY, OkamotoK, MabuchiT, IizukiM, OzawaA, et al. (2004) Identification, expression analysis amd polymorphism of a novel RLTPR gene encoding a RGD motif, tropomodulin domain and proline/leucine-rich regions. Gene 343: 291–304.

41. D'SouzaSE, GinsbergMH, PlowEF (1991) Arginyl-glycyl-aspartic acid (RGD): a cell adhesion motif. Trens Biochem Sci 16: 246–250.

42. JamadarS, PowersNR, MedaSA, GelernterJ, GruenJR (2011) Genetic influences of cortical gray matter in language-related regions in healthy controls and schizophrenia. Schizophr Res 129: 141–148.

43. LiT, ZengZ, ZhaoQ, WangT, HuangK, et al. (2012) FoxP2 is significantly associated with schizophrenia and major depression in the Chinese Han Population. World J Biol Psychiatry 14: 146–150.

44. WalkerRM, HillAE, NewmanAC, HamiltonG, TorranceHS, et al. (2012) The DISC1 promoter: characterization and regulation by FOXP2. Hum Mol Genet 21: 2862–2872.

45. NakataniK, SakaueH, ThompsonDA, WeigelRJ, RothRA (1999) Identification of a human Akt3 (protein kinase B gamma) which contains the regulatory serine phosphorylation site. Biochem Biophys Res Commun 257: 906–910.

46. DiezH, GarridoJJ, WandosellF (2012) Specific roles of Akt iso forms in apoptosis and axon growth regulation in neurons. PLoS ONE 7: e32715 doi:10.1371/journal.pone.0032715

47. PoduriA, EvronyGD, CaiX, ElhosaryPC, BeroukhimR, LehtinenMK (2012) Somatic activation of AKT3 causes hemispheric developmental brain malformations. Neuron 74: 41–48.

48. RietschelM, MattheisenM, DegenhardtF (2012) Genetic Risk and Outcome in Psychosis (GROUP Investigators) (2012) MühleisenTW, et al. (2012) Association between genetic variation in a region on chromosome 11 and schizophrenia in large samples from Europe. Mol Psychiatry 17: 906–917.

49. PriebeL, DegenhardtF, StrohmaierJ, BreuerR, HermsS, et al. (2013) Copy Number Variants in German Patients with Schizophrenia. PLoS ONE 8 (7) e64035.

50. ShiJ, LevinsonDF, DuanJ, SandersAR, ZhengY, et al. (2009) Common variants on chromosome 6p22.1 are associated with schizophrenia. Nature 460: 753–757.

51. PurcellS, NealeB, Todd-BrownK, ThomasL, FerreiraMAR, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81: 559–575.

52. VeyrierasJB, KudaravalliS, KimSY, DermitzakisET, GiladY, et al. (2008) High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genet 2008; 4: e1000214.

53. SubramanianA, TamayoP, MoothaVK, MukherjeeS, EbertBL, et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102: 15545–15550.

54. The Gene Ontology Consortium Gene ontology: tool for the unification of biology. Nat Genet 25: 25–29.

55. KanehisaM, GotoS (2010) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 28: 27–30.

56. KanehisaM, GotoS, SatoY, FurumichiM, TanabeM (2012) KEGG for integration and interpretation of large-scale molecular datasets. Nucleic Acids Res 40: D109–D114.

57. BenjaminiY, HochbergY (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Stat Methodol 57: 289–300.

58. GoemanJJ, MansmannU (2008) Multiple testing on the directed acyclic graph of gene ontology. Bioinformatics 24: 537–544.

59. BørglumAD, DemontisD, GroveJ, PallesenJ, HollegaardMV, et al. (2013) Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci. Mol Psychiatry 2013 doi: 10.1038/mp.2013.2

60. 1000 Genomes Project Consortium (2010) AbecasisGR, AltshulerD, AutonA, BrooksLD, et al. (2010) A map of human genome variation from population-scale sequencing. Nature 467: 1061–1073.

61. JohnsonA, HandsakerR, PulitS, NizzariM, O'DonnellC, et al. (2008) SNAP: A web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24: 2938–2939.

62. AdzhubeiIA, SchmidtS, PeshkinL, RamenskyVE, GerasimovaA, et al. (2010) A method and server for predicting damaging missense mutations. Nat Meth 7: 248–249.

63. KumarP, HenikoffS, NgPC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4: 1073–1081.