Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-22T19:00:57.087Z Has data issue: false hasContentIssue false
  • English
  • Français

Genome-wide DNA methylation in 1-year-old infants of mothers with major depressive disorder

Published online by Cambridge University Press:  30 September 2016

Dante Cicchetti ,
Susan Hetzel ,
Fred A. Rogosch ,
Elizabeth D. Handley  and
Sheree L. Toth
Dante Cicchetti*
Affiliation:
University of Minnesota Institute of Child Development University of Rochester Mt. Hope Family Center
Susan Hetzel
Affiliation:
University of Minnesota Institute of Child Development
Fred A. Rogosch
Affiliation:
University of Rochester Mt. Hope Family Center
Elizabeth D. Handley
Affiliation:
University of Rochester Mt. Hope Family Center
Sheree L. Toth
Affiliation:
University of Rochester Mt. Hope Family Center
*
Address correspondence and reprint requests to: Dante Cicchetti, Institute of Child Development, University of Minnesota, 51 East River Road, Minneapolis, MN 55455; E-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

A genome-wide methylation study was conducted among a sample of 114 infants (M age = 13.2 months, SD = 1.08) of low-income urban women with (n = 73) and without (n = 41) major depressive disorder. The Illumina HumanMethylation450 BeadChip array with a GenomeStudio Methylation Module and Illumina Custom model were used to conduct differential methylation analyses. Using the 5.0 × 10–7p value, 2,119 loci were found to be significantly different between infants of depressed and nondepressed mothers. Infants of depressed mothers had greater methylation at low methylation sites (0%–29%) compared to infants of nondepressed mothers. At high levels of methylation (70%–100%), the infants of depressed mothers were predominantly hypomethylated. The mean difference in methylation between the infants of depressed and infants of nondepressed mothers was 5.23%. Disease by biomarker analyses were also conducted using GeneGo MetaCore Software. The results indicated significant cancer-related differences in biomarker networks such as prostatic neoplasms, ovarian and breast neoplasms, and colonic neoplasms. The results of a process networks analysis indicated significant differences in process networks associated with neuronal development and central nervous system functioning, as well as cardiac development between infants of depressed and nondepressed mothers. These findings indicate that early in development, infants of mothers with major depressive disorder evince epigenetic differences relative to infants of well mothers that suggest risk for later adverse health outcomes.

Type
Regular Articles
Information
Development and Psychopathology , Volume 28 , Special Issue 4pt2: Epigenetics: Development, Psychopathology, Resilience, and Preventive Intervention , November 2016 , pp. 1413 - 1419
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.Google Scholar
Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck Depression Inventory—II. San Antonio, TX: Psychological Corporation.Google Scholar
Braithwaite, E. C., Kundakovic, M., Ramchandani, P. G., Murphy, S. E., & Champagne, F. A. (2015). Maternal prenatal depressive symptoms predict infant NR3C1 1F and BDNF IV DNA methylation. Epigenetics, 10, 408–417.Google Scholar
Cicchetti, D., & Aber, J. L. (1986). Early precursors to later depression: An organizational perspective. In Lipsitt, L. & Rovee-Collier, C. (Eds.), Advances in infancy (Vol. 4, pp. 87–137). Norwood, NJ: Ablex.Google Scholar
Cicchetti, D., Rogosch, F. A., Toth, S. L., & Spagnola, M. (1997). Affect, cognition, and the emergence of self-knowledge in the toddler offspring of depressed mothers. Journal of Experimental Child Psychology, 67, 338–362.Google Scholar
Cicchetti, D., & Schneider-Rosen, K. (1986). An organizational approach to childhood depression. In Rutter, M., Izard, C., & Read, P. (Eds.), Depression in young people: Clinical and developmental perspectives (pp. 71–134). New York: Guilford Press.Google Scholar
Cicchetti, D., & Toth, S. L. (1995). Developmental psychopathology and disorders of affect. In Cicchetti, D. & Cohen, D. J. (Eds.), Developmental psychopathology: Risk, disorder, and adaptation (Vol. 2, pp. 369–420). New York: Wiley.Google Scholar
Cicchetti, D., & Toth, S. L. (1998). The development of depression in children and adolescents. American Psychologist, 53, 221–241.Google Scholar
Cole, P. M., Luby, J., & Sullivan, M. W. (2008). Emotions and the development of childhood depression: Bridging the gap. Child Development Perspectives, 2, 141–148.CrossRefGoogle ScholarPubMed
Cummings, E. M., & Cicchetti, D. (1990). Toward a transactional model of relations between attachment and depression. In M. T. Greenberg, D. Cicchetti, & E. M. Cummings (Eds.), Attachment in the preschool years, (pp. 339–372). Chicago: University of Chicago Press.Google Scholar
Davidson, R. J., & Fox, N. A. (1982). Asymmetrical brain activity discriminates between positive versus affective stimuli in human infants. Science, 218, 1235–1237.Google Scholar
Dozois, D. J., Dobson, K. S., & Ahnberg, J. L. (1998). A psychometric evaluation of the Beck Depression Inventory—II. Psychological Assessment, 10, 83–89.CrossRefGoogle Scholar
Field, T., & Diego, M. (2008). Maternal depression effects of infant frontal EEG asymmetry. International Journal of Neuroscience, 118, 1081–1108.CrossRefGoogle ScholarPubMed
Goodman, S. H., & Gotlib, I. H. (1999). Risk for psychopathology in the children of depressed mothers: A developmental model for understanding mechanisms of transmission. Psychological Review, 106, 458–490.Google Scholar
Oberlander, T. F., Weinberg, J., Papsdorf, M., Grunau, R., Misri, S., & Devlin, A. M. (2008). Prenatal exposure to maternal depression, neonatal methylation of human glucocorticoid receptor gene (NR3 C1) and infant cortisol stress responses. Epigenetics, 3, 97–106.CrossRefGoogle Scholar
Radke-Yarrow, M., Cummings, E. M., Kuczynski, L., & Chapman, M. (1985). Patterns of attachment in two- and three-year-olds in normal families and families with parental depression. Child Development, 56, 884–893.CrossRefGoogle ScholarPubMed
Radloff, L. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.Google Scholar
Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews. Genetics, 12, 529–541.CrossRefGoogle ScholarPubMed
Robins, L., Cottler, L., Bucholz, K., & Compton, W. (1995). Diagnostic Interview Schedule for DSM-IV. St. Louis, MO: Washington University.Google Scholar
Robins, L., Helzer, J., Croughan, J., & Ratcliff, K. (1981). The NIMH Diagnostic Interview Schedule: Its history, characteristics, and validity. Archives of General Psychiatry, 38, 381–389.Google Scholar
Robins, L. W., Helzer, J. E., Ratcliff, K. S., & Seyfried, W. (1982). Validity of the Diagnostic Interview Schedule, Version II: DSM-III diagnoses. Psychological Medicine, 12, 855–865.Google Scholar
Storch, E. A., Roberti, J. W., & Roth, D. A. (2004). Factor structure, concurrent validity, and internal consistency of the Beck Depression Inventory—Second Edition in a sample of college students. Depression and Anxiety, 19, 187–189.Google Scholar
Szyf, M., & Bick, J. (2013). DNA methylation: A mechanism for embedding early life experiences in the genome. Child Development, 84, 49–57.Google Scholar
Toth, S. L., Rogosch, F. A., Manly, J. T., & Cicchetti, D. (2006). The efficacy of toddler–parent psychotherapy to reorganize attachment in the young offspring of mothers with major depressive disorder. Journal of Consulting & Clinical Psychology, 74, 1006–1016.Google Scholar
Yang, B. Z. Y., Zhang, H., Ge, W., Weder, N., Douglas-Palumberi, H., Perepletchikova, F., et al. (2013). Child abuse and epigenetic mechanisms of disease risk. American Journal of Preventive Medicine, 44, 101–107.Google Scholar