Abstract
Childhood traumatization (CT) is associated with the development of several neuropsychiatric disorders in later life. Experimental data in animals and observational data in humans revealed evidence for biological alterations in response to CT that may contribute to its long-term consequences. This includes epigenetic changes in miRNA levels that contribute to complex alterations of gene expression. We investigated the association between CT and 121 miRNAs in a target sample of N = 150 subjects from the general population and patients from the Department of Psychiatry. We hypothesized that CT exhibits a long-term effect on miRNA plasma levels. We supported our findings using bioinformatics tools and databases. Among the 121 miRNAs 22 were nominally significantly associated with CT and four of them (let-7g-5p, miR-103a-3p, miR-107, and miR-142-3p) also after correction for multiple testing; most of them were previously associated with Alzheimer’s disease (AD) or depression. Pathway analyses of target genes identified significant pathways involved in neurodevelopment, inflammation and intracellular transduction signaling. In an independent general population sample (N = 587) three of the four miRNAs were replicated. Extended analyses in the general population sample only (N = 687) showed associations of the four miRNAs with gender, memory, and brain volumes. We gained increasing evidence for a link between CT, depression and AD through miRNA alterations. We hypothesize that depression and AD not only share environmental factors like CT but also biological factors like altered miRNA levels. This miRNA pattern could serve as mediating factor on the biological path from CT to adult neuropsychiatric disorders.
Similar content being viewed by others
Log in or create a free account to read this content
Gain free access to this article, as well as selected content from this journal and more on nature.com
or
References
Carr CP, Martins CMS, Stingel AM, Lemgruber VB, Juruena MF. The role of early life stress in adult psychiatric disorders: a systematic review according to childhood trauma subtypes. J Nerv Ment Dis. 2013;201:1007–20. https://doi.org/10.1097/NMD.0000000000000049
van der Auwera S, Peyrot WJ, Milaneschi Y, Hertel J, Baune B, Breen G, et al. Genome-wide gene-environment interaction in depression: A systematic evaluation of candidate genes: the childhood trauma working-group of PGC-MDD. Am J Med Genet B Neuropsychiatr Genet. 2018;177:40–9. https://doi.org/10.1002/ajmg.b.32593
Grabe HJ, Wittfeld K, van der Auwera S, Janowitz D, Hegenscheid K, Habes M, et al. Effect of the interaction between childhood abuse and rs1360780 of the FKBP5 gene on gray matter volume in a general population sample. Hum Brain Mapp. 2016;37:1602–13. https://doi.org/10.1002/hbm.23123
Gapp K, Jawaid A, Sarkies P, Bohacek J, Pelczar P, Prados J, et al. Implication of sperm RNAs in transgenerational inheritance of the effects of early trauma in mice. Nat Neurosci. 2014;17:667–9. https://doi.org/10.1038/nn.3695
Ramo-Fernández L, Schneider A, Wilker S, Kolassa I-T. Epigenetic alterations associated with war trauma and childhood maltreatment. Behav Sci Law. 2015;33:701–21. https://doi.org/10.1002/bsl.2200
Cattane N, Mora C, Lopizzo N, Borsini A, Maj C, Pedrini L, et al. Identification of a miRNAs signature associated with exposure to stress early in life and enhanced vulnerability for schizophrenia: new insights for the key role of miR-125b-1-3p in neurodevelopmental processes. Schizophr Res. 2018. https://doi.org/10.1016/j.schres.2018.07.030
Camkurt MA, Güneş S, Coşkun S, Fındıklı E. Peripheral signatures of psychiatric disorders: MicroRNAs. Clin Psychopharmacol Neurosci. 2017;15:313–9. https://doi.org/10.9758/cpn.2017.15.4.313
Place RF, Li L-C, Pookot D, Noonan EJ, Dahiya R. MicroRNA-373 induces expression of genes with complementary promoter sequences. Proc Natl Acad Sci USA. 2008;105:1608–13. https://doi.org/10.1073/pnas.0707594105
Malan-Müller S, Hemmings SMJ, Seedat S. Big effects of small RNAs: a review of microRNAs in anxiety. Mol Neurobiol. 2013;47:726–39. https://doi.org/10.1007/s12035-012-8374-6
Kumari A, Singh P, Baghel MS, Thakur MK. Social isolation mediated anxiety like behavior is associated with enhanced expression and regulation of BDNF in the female mouse brain. Physiol Behav. 2016;158:34–42. https://doi.org/10.1016/j.physbeh.2016.02.032
Dickson DA, Paulus JK, Mensah V, Lem J, Saavedra-Rodriguez L, Gentry A, et al. Reduced levels of miRNAs 449 and 34 in sperm of mice and men exposed to early life stress. Transl Psychiatry. 2018;8:101. https://doi.org/10.1038/s41398-018-0146-2
Völzke H, Alte D, Schmidt CO, Radke D, Lorbeer R, Friedrich N, et al. Cohort profile: the study of health in Pomerania. Int J Epidemiol. 2011;40:294–307. https://doi.org/10.1093/ije/dyp394
Grabe HJ, Assel H, Bahls T, Dörr M, Endlich K, Endlich N, et al. Cohort profile: Greifswald approach to individualized medicine (GANI_MED). J Transl Med. 2014;12:144. https://doi.org/10.1186/1479-5876-12-144
Hawley CJ, Gale TM, Smith PSJ, Jain S, Farag A, Kondan R, et al. Equations for converting scores between depression scales (MÅDRS, SRS, PHQ-9 and BDI-II): good statistical, but weak idiographic, validity. Hum Psychopharmacol. 2013;28:544–51. https://doi.org/10.1002/hup.2341
Bernstein DP, Stein JA, Newcomb MD, Walker E, Pogge D, Ahluvalia T, et al. Development and validation of a brief screening version of the Childhood Trauma Questionnaire. Child Abus Negl. 2003;27:169–90.
Grabe HJ, Schulz A, Schmidt CO, Appel K, Driessen M, Wingenfeld K, et al. Ein Screeninginstrument für Missbrauch und Vernachlässigung in der Kindheit: der Childhood Trauma Screener (CTS). Psychiatr Prax. 2012;39:109–15. https://doi.org/10.1055/s-0031-1298984
Oswald WD, Fleischmann UM. Psychometrics in aging and dementia: advances in geropsychological assessments. Arch Gerontol Geriatr. 1985;4:299–309.
Ameling S, Kacprowski T, Chilukoti RK, Malsch C, Liebscher V, Suhre K, et al. Associations of circulating plasma microRNAs with age, body mass index and sex in a population-based study. BMC Med Genom. 2015;8:61. https://doi.org/10.1186/s12920-015-0136-7
StataCorp. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP; 2015.
Vlachos IS, Zagganas K, Paraskevopoulou MD, Georgakilas G, Karagkouni D, Vergoulis T, et al. DIANA-miRPathv3.0: deciphering microRNA function with experimental support. Nucleic Acids Res. 2015;43:W460–6. https://doi.org/10.1093/nar/gkv403
Wang X. Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies. Bioinformatics. 2016;32:1316–22. https://doi.org/10.1093/bioinformatics/btw002
Hamberg M, Backes C, Fehlmann T, Hart M, Meder B, Meese E, et al. MiRTargetLink–miRNAs, genes and interaction networks. Int J Mol Sci. 2016;17:564. https://doi.org/10.3390/ijms17040564
Vlachos IS, Paraskevopoulou MD, Karagkouni D, Georgakilas G, Vergoulis T, Kanellos I, et al. DIANA-TarBasev7.0: indexing more than half a million experimentally supported miRNA:mRNA interactions. Nucleic Acids Res. 2015;43:D153–9. https://doi.org/10.1093/nar/gku1215
Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45:D362–8. https://doi.org/10.1093/nar/gkw937
Ludwig N, Leidinger P, Becker K, Backes C, Fehlmann T, Pallasch C, et al. Distribution of miRNA expression across human tissues. Nucleic Acids Res. 2016;44:3865–77. https://doi.org/10.1093/nar/gkw116
Mendes-Silva AP, Pereira KS, Tolentino-Araujo GT, Nicolau EdS, Silva-Ferreira CM, Teixeira AL, et al. Shared biologic pathways between Alzheimer disease and major depression: a systematic review of MicroRNA expression studies. Am J Geriatr Psychiatry. 2016;24:903–12. https://doi.org/10.1016/j.jagp.2016.07.017
Chen J, Qi Y, Liu C-F, Lu J-M, Shi J, Shi Y. MicroRNA expression data analysis to identify key miRNAs associated with Alzheimer’s disease. J Gene Med. 2018;20:e3014. https://doi.org/10.1002/jgm.3014
Chang W-S, Wang Y-H, Zhu X-T, Wu C-J. Genome-wide profiling of miRNA and mRNA expression in Alzheimer’s disease. Med Sci Monit. 2017;23:2721–31.
Huang F, Long Z, Chen Z, Li J, Hu Z, Qiu R, et al. Investigation of gene regulatory networks associated with autism spectrum disorder based on MiRNA expression in China. PLoS ONE. 2015;10:e0129052. https://doi.org/10.1371/journal.pone.0129052
Daimiel-Ruiz L, Klett-Mingo M, Konstantinidou V, Micó V, Aranda JF, García B, et al. Dietary lipids modulate the expression of miR-107, an miRNA that regulates the circadian system. Mol Nutr Food Res. 2015;59:552–65. https://doi.org/10.1002/mnfr.201400616
Scarr E, Craig JM, Cairns MJ, Seo MS, Galati JC, Beveridge NJ, et al. Decreased cortical muscarinic M1 receptors in schizophrenia are associated with changes in gene promoter methylation, mRNA and gene targeting microRNA. Transl Psychiatry. 2013;3:e230. https://doi.org/10.1038/tp.2013.3
Yılmaz ŞG, Erdal ME, Özge AA, Sungur MA. Can peripheral MicroRNA expression data serve as epigenomic (Upstream) biomarkers of Alzheimer’s disease? OMICS. 2016;20:456–61. https://doi.org/10.1089/omi.2016.0099
Gao B, Hao S, Tian W, Jiang Y, Zhang S, Guo L et al. MicroRNA-107 is downregulated and having tumor suppressive effect in breast cancer by negatively regulating brain-derived neurotrophic factor. J Gene Med. 2017. https://doi.org/10.1002/jgm.2932
Kumar P, Dezso Z, MacKenzie C, Oestreicher J, Agoulnik S, Byrne M, et al. Circulating miRNA biomarkers for Alzheimer’s disease. PLoS ONE. 2013;8:e69807 https://doi.org/10.1371/journal.pone.0069807
Ono M, Devilly GJ, Shum DHK. A meta-analytic review of overgeneral memory: the role of trauma history, mood, and the presence of posttraumatic stress disorder. Psychol Trauma. 2016;8:157–64. https://doi.org/10.1037/tra0000027
Cassiers LLM, Sabbe BGC, Schmaal L, Veltman DJ, Penninx BWJH, van den Eede F. Structural and functional brain abnormalities associated with exposure to different childhood trauma subtypes: a systematic review of neuroimaging findings. Front Psychiatry. 2018;9:329. https://doi.org/10.3389/fpsyt.2018.00329
Radford K, Delbaere K, Draper B, Mack HA, Daylight G, Cumming R, et al. Childhood stress and adversity is associated with late-life dementia in aboriginal Australians. Am J Geriatr Psychiatry. 2017;25:1097–106. https://doi.org/10.1016/j.jagp.2017.05.008
Derkow K, Rössling R, Schipke C, Krüger C, Bauer J, Fähling M, et al. Distinct expression of the neurotoxic microRNA family let-7 in the cerebrospinal fluid of patients with Alzheimer’s disease. PLoS ONE. 2018;13:e0200602. https://doi.org/10.1371/journal.pone.0200602
Hu Y-S, Xin J, Hu Y, Zhang L, Wang J. Analyzing the genes related to Alzheimer’s disease via a network and pathway-based approach. Alzheimers Res Ther. 2017;9:29. https://doi.org/10.1186/s13195-017-0252-z
Daugherty D, Goldberg J, Fischer W, Dargusch R, Maher P, Schubert D. A novel Alzheimer’s disease drug candidate targeting inflammation and fatty acid metabolism. Alzheimers Res Ther. 2017;9:50. https://doi.org/10.1186/s13195-017-0277-3
Estrada LD, Oliveira-Cruz L, Cabrera D. Transforming growth factor beta type I role in neurodegeneration: implications for Alzheimer´s disease. Curr Protein Pept Sci. 2018;19:1180–8. https://doi.org/10.2174/1389203719666171129094937
Deming Y, Dumitrescu L, Barnes LL, Thambisetty M, Kunkle B, Gifford KA, et al. Sex-specific genetic predictors of Alzheimer’s disease biomarkers. Acta Neuropathol. 2018. https://doi.org/10.1007/s00401-018-1881-4
Gusareva ES, Twizere J-C, Sleegers K, Dourlen P, Abisambra JF, Meier S, et al. Male-specific epistasis between WWC1 and TLN2 genes is associated with Alzheimer’s disease. Neurobiol Aging. 2018. https://doi.org/10.1016/j.neurobiolaging.2018.08.001
van der Auwera S, Terock J, Teumer A, Schomerus G, Homuth G, Grabe HJ. Gender effects for the interaction of dopamine related genetic variants in BDNF and COMT on memory performance. Pharmacopsychiatry; under review.
Hommers L, Raab A, Bohl A, Weber H, Scholz C-J, Erhardt A. et al. MicroRNA hsa-miR-4717-5p regulates RGS2 and may be a risk factor for anxiety-related traits. Am J Med Genet B Neuropsychiatr Genet. 2015;168B:296–306. https://doi.org/10.1002/ajmg.b.3231
Grasso M, Piscopo P, Confaloni A, Denti MA. Circulating miRNAs as biomarkers for neurodegenerative disorders. Molecules. 2014;19:6891–910. https://doi.org/10.3390/molecules19056891
Mandelli L, Petrelli C, Serretti A. The role of specific early trauma in adult depression: a meta-analysis of published literature. Child trauma adult Depress Eur Psychiatry. 2015;30:665–80. https://doi.org/10.1016/j.eurpsy.2015.04.007
Diniz BS, Butters MA, Albert SM, Dew MA, Reynolds CF. Late-life depression and risk of vascular dementia and Alzheimer’s disease: systematic review and meta-analysis of community-based cohort studies. Br J Psychiatry. 2013;202:329–35. https://doi.org/10.1192/bjp.bp.112.118307
Ye Q, Bai F, Zhang Z. Shared genetic risk factors for late-life depression and Alzheimer’s disease. J Alzheimers Dis. 2016;52:1–15. https://doi.org/10.3233/JAD-151129
Goldberg LR, Gould TJ. Multigenerational and transgenerational effects of paternal exposure to drugs of abuse on behavioral and neural function. Eur J Neurosci. 2018. https://doi.org/10.1111/ejn.14060
Funding
The authors thank Anja Wiechert and Ulrike Lissner for excellent support during sample preparation. SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. The Greifswald Approach to Individualized Medicine (GANI_MED) was funded by the Federal Ministry of Education and Research Grant no. 03IS2061A and the German Research Foundation Grant no. GR 1912/5-1. SV was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (Integrament; grant no. 01ZX1614E). HJG has received travel grants and speakers honoraria from Fresenius Medical Care and Janssen Cilag. He has received research funding from the German Research Foundation, the German Federal Ministry of Education and Research (BMBF), the DAMP Foundation, Fresenius Medical Care, the EU “Joint Program Neurodegenerative Disorders” (JPND: 01ED1615), and the European Social Fund (ESF). All other authors state that they have nothing to disclose. All authors declare no competing interests.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
About this article
Cite this article
Van der Auwera, S., Ameling, S., Wittfeld, K. et al. Association of childhood traumatization and neuropsychiatric outcomes with altered plasma micro RNA-levels. Neuropsychopharmacol. 44, 2030–2037 (2019). https://doi.org/10.1038/s41386-019-0460-2
Received:
Revised:
Accepted:
Published:
Version of record:
Issue date:
DOI: https://doi.org/10.1038/s41386-019-0460-2
This article is cited by
-
A multi-omic approach implicates novel protein dysregulation in post-traumatic stress disorder
Genome Medicine (2025)
-
Regulation of Zbp1 by miR-99b-5p in microglia controls the development of schizophrenia-like symptoms in mice
The EMBO Journal (2024)
-
MiR-10a, miR-15a, let-7a, and let-7g expression as stress-relevant biomarkers to assess acute or chronic psychological stress and mental health in human capillary blood
Molecular Biology Reports (2023)
-
Identification of Peripheral Blood miRNA Biomarkers in First-Episode Drug-Free Schizophrenia Patients Using Bioinformatics Strategy
Molecular Neurobiology (2022)
-
Repeated sampling facilitates within- and between-subject modeling of the human sperm transcriptome to identify dynamic and stress-responsive sncRNAs
Scientific Reports (2020)
