MicroRNA-138 is a potential regulator of memory performance in humans

Frontiers in Human Neuroscience

Volumn 8, Issue JULY, 2014, Pages

  Schröder, Julia ^a,b   Ansaloni, Sara ^a   Schilling, Marcel ^a,c   Liu, Tian ^a,d   Radke, Josefine ^b   Jaedicke, Marian ^a   Schjeide, Brit Maren M ^a   Mashychev, Andriy ^a   Tegeler, Christina ^b   Radbruch, Helena ^b   Papenberg, Goran ^d,e   Düzel, Sandra ^d   Demuth, Ilja ^b   Bucholtz, Nina ^b   Lindenberger, Ulman ^d   Li, Shu Chen ^d,f   Steinhagen Thiessen, Elisabeth ^b   Lill, Christina M ^a,g   Bertram, Lars ^a,h  

^a MAX PLANCK INSTITUTE FOR MOLECULAR GENETICS   (Germany)

^b CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^c MAX DELBRÜCK CENTER FOR MOLECULAR MEDICINE   (Germany)

^d MAX PLANCK INSTITUTE FOR HUMAN DEVELOPMENT   (Germany)

^e AGING RESEARCH CENTER   (Sweden)

^f DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^g UNIVERSITY MEDICAL CENTER MAINZ   (Germany)

^h IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

DCP1B; Episodic memory; Genome wide association study; GWAS; Hsa mir 138 5p; MicroRNA; Working memory

Indexed keywords

MICRORNA; MICRORNA 138; MICRORNA 138 1 3P; MICRORNA 138 5P; UNCLASSIFIED DRUG;

3' UNTRANSLATED REGION; ADULT; AGED; ALLELE; AMINO ACID SUBSTITUTION; ARTICLE; CONTROLLED STUDY; DCP1B GENE; EPISODIC MEMORY; FEMALE; FRONTAL CORTEX; GENE; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE INTERACTION; GENETIC ASSOCIATION; GENOTYPE; HIPPOCAMPUS; HUMAN; HUMAN CELL; HUMAN TISSUE; MALE; PROTEIN EXPRESSION; QUANTITATIVE TRAIT LOCUS; REGULATORY MECHANISM; RNA BINDING; RNA SEQUENCE; SINGLE NUCLEOTIDE POLYMORPHISM; UPREGULATION; VERY ELDERLY; WORKING MEMORY;

EID: 84904184099     PISSN: None     EISSN: 16625161     Source Type: Journal    
DOI: 10.3389/fnhum.2014.00501     Document Type: Article

References (35)

1. Abecasis, G. R., Altshuler, D., Auton, A., Brooks, L. D., Durbin, R. M., Gibbs, R. A., et al. (2010). A map of human genome variation from population-scale sequencing. Nature 467, 1061-1073. doi: 10.1038/nature09534
2. Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., et al. (2010). A method and server for predicting damaging missense mutations. Nat. Methods 7, 248-249. doi: 10.1038/nmeth0410-248
3. Behm-Ansmant, I., Rehwinkel, J., Doerks, T., Stark, A., Bork, P., and Izaurralde, E. (2006). mRNA degradation by miRNAs and GW182 requires both CCR4:NOT deadenylase and DCP1:DCP2 decapping complexes. Genes Dev. 20, 1885-1898. doi: 10.1101/gad.1424106
4. Bertram, L., Böckenhoff, A., Demuth, I., Düzel, S., Eckardt, R., Li, S. C., et al. (2013). Cohort profile: The Berlin Aging Study II (BASE-II). Int. J. Epidemiol. 43, 703-712. doi: 10.1093/ije/dyt018
5. Betel, D., Koppal, A., Agius, P., Sander, C., and Leslie, C. (2010). Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol. 11:R90. doi: 10.1186/gb-2010-11-8-r90
6. ENCODE Project Consortium., Bernstein, B. E., Birney, E., Dunham, I., Green, E. D., Gunter, C., et al. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74. doi: 10.1038/nature11247
7. Fillenbaum, G. G., van Belle, G., Morris, J. C., Mohs, R. C., Mirra, S. S., Davis, P. C., et al. (2008). Consortium to Establish a Registry for Alzheimer's Disease (CERAD): The first twenty years. Alzheimers Dement. 4, 96-109. doi: 10.1016/j.jalz.2007.08.005
8. Goldberg Hermo, X., Lemos Giráldez, S., and Fañanás Saura, L. (2014). A systematic review of the complex organization of human cognitive domains and their heritability. Psicothema 26, 1-9. doi: 10.7334/psicothema2012.210
9. Griffiths-Jones, S., Grocock, R. J., van Dongen, S., Bateman, A., and Enright, A. J. (2006). miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 34, D140-D144. doi: 10.1093/nar/gkj112
10. Helwak, A., Kudla, G., Dudnakova, T., and Tollervey, D. (2013). Mapping the human miRNA Interactome by CLASH reveals frequent noncanonical binding. Cell 153, 654-665. doi: 10.1016/j.cell.2013.03.043
11. Kraft, P. (2008). Curses-winner's and otherwise-in genetic epidemiology. Epidemiology 19, 649-651; discussion 657-658. doi: 10.1097/EDE.0b013e318181b865
12. Kulkarni, M., Ozgur, S., and Stoecklin, G. (2010). On track with P-bodies. Biochem. Soc. Trans. 38(Pt 1), 242-251. doi: 10.1042/BST0380242
13. Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., et al. (2007). A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129, 1401-1414. doi: 10.1016/j.cell.2007.04.040
14. Lappalainen, T., Sammeth, M., Friedländer, M. R., 't Hoen, P. A., Monlong, J., Rivas, M. A., et al. (2013). Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501, 506-511. doi: 10.1038/nature12531
15. Li, S. C., Papenberg, G., Nagel, I. E., Preuschhof, C., Schröder, J., Nietfeld, W., et al. (2013). Aging magnifies the effects of dopamine transporter and D2 receptor genes on backward serial memory. Neurobiol. Aging 34, 358. e1-358. e10. doi: 10.1016/j.neurobiolaging.2012.08.001
16. Lill, C. M., Schilling, M., Ansaloni, S., Schröder, J., Jaedicke, M., Luessi, F., et al. (2014). Assessment of microRNA-related SNP effects in the 3′ untranslated region of the IL22RA2 risk locus in multiple sclerosis. Neurogenetics 15, 129-134. doi: 10.1007/s10048-014-0396-y
17. Lindenberger, U., Nagel, I. E., Chicherio, C., Li, S. C., Heekeren, H. R., and Bäckman, L. (2008). Age-related decline in brain resources modulates genetic effects on cognitive functioning. Front. Neurosci. 2:2. doi: 10.3389/neuro.01.039.2008
18. Liu, T., Li, S. C., Papenberg, G., Schröder, J., Roehr, J. T., Nietfeld, W., et al. (in press). No association between CTNNBL1 and episodic memory performance. Transl. Psychiatry.
19. Marchini, J., and Howie, B. (2010). Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11, 499-511. doi: 10.1038/nrg2796
20. McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P., et al. (2008). Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet. 9, 356-369. doi: 10.1038/nrg2344
21. McClearn, G. E., Johansson, B., Berg, S., Pedersen, N. L., Ahern, F., Petrill, S. A., et al. (1997). Substantial genetic influence on cognitive abilities in twins 80 or more years old. Science 276, 1560-1563. doi: 10.1126/science.276.5318.1560
22. Milnik, A., Heck, A., Vogler, C., Heinze, H. J., de Quervain, D. J., and Papassotiropoulos, A. (2012). Association ofKIBRA with episodic and working memory: a meta-analysis. Am. J. Med. Genet. B Neuropsychiatr. Genet. 159B, 958-969. doi: 10.1002/ajmg.b.32101
23. Miska, E. A., Alvarez-Saavedra, E., Townsend, M., Yoshii, A., Šestan, N., Rakic, P., et al. (2004). Microarray analysis of microRNA expression in the developing mammalian brain. Genome Biol. 5:R68. doi: 10.1186/gb-2004-5-9-r68
24. Morris, J. C., Heyman, A., Mohs, R. C., Hughes, J. P., van Belle, G., Fillenbaum, G., et al. (1989). The Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer's disease. Neurology 39, 1159-1165. doi: 10.1212/WNL.39.9.1159
25. Papassotiropoulos, A., and de Quervain, D. J. (2011). Genetics of human episodic memory: dealing with complexity. Trends Cogn. Sci. 15, 381-387. doi: 10.1016/j.tics.2011.07.005
26. Papassotiropoulos, A., Stephan, D. A., Huentelman, M. J., Hoerndli, F. J., Craig, D. W., Pearson, J. V., et al. (2006). Common Kibra alleles are associated with human memory performance. Science 314, 475-478. doi: 10.1126/science.1129837
27. Papenberg, G., Li, S. C., Nagel, I. E., Nietfeld, W., Schjeide, B. M., Schröder, J., et al. (2014). Dopamine and glutamate receptor genes interactively influence episodic memory in old age. Neurobiol. Aging 35, 1213. e3-1213. e8. doi: 10.1016/j.neurobiolaging.2013.11.014
28. Peterson, S. M., Thompson, J. A., Ufkin, M. L., Sathyanarayana, P., Liaw, L., and Congdon, C. B. (2014). Common features of microRNA target prediction tools. Front. Genet. 5:23. doi: 10.3389/fgene.2014.00023
29. Salmena, L., Poliseno, L., Tay, Y., Kats, L., and Pandolfi, P. P. (2011). A ceRNA hypothesis: The Rosetta Stone of a hidden RNA language? Cell 146, 353-358. doi: 10.1016/j.cell.2011.07.014
30. Satoh, J. (2012). Molecular network of microRNA targets in Alzheimer's disease brains. Exp. Neurol. 235, 436-446. doi: 10.1016/j.expneurol.2011.09.003
31. Schilling, M. (2011). In Silico Assessment of the Effects of Single Nucleotide Polymorphisms on miRNA-mRNA Interactions. Bachelor's thesis. Department of Mathematics and Computer Science-FU Berlin, Berlin.
32. Schilling, M. (2013). The Role of DNA Sequence Variants Predicted to Alter miRNA-mRNA Interactions in Disease Pathogenesis. Master's thesis. Department of Mathematics and Computer Science-FU Berlin, Berlin.
33. Schratt, G. (2009). microRNAs at the synapse. Nat. Rev. Neurosci. 10, 842-849. doi: 10.1038/nrn2763
34. Siegel, G., Obernosterer, G., Fiore, R., Oehmen, M., Bicker, S., Christensen, M., et al. (2009). A functional screen implicates microRNA-138-dependent regulation of the depalmitoylation enzyme APT1 in dendritic spine morphogenesis. Nat. Cell Biol. 11, 705-716. doi: 10.1038/ncb1876
35. Welter, D., MacArthur, J., Morales, J., Burdett, T., Hall, P., Junkins, H., et al. (2014). The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 42, D1001-D1006. doi: 10.1093/nar/gkt1229