Schizophrenia is a common, profoundly disabling disorder that carries a heavy burden for patients and families and is the subject of intensive genetic studies. The study of epigenetic variation is an essential complement to conventional genetic disease studies, since the phenotypic consequence of DNA sequence depends on its epigenetic context. Unlike sequence variation, epigenetic marks, i.e. chemical modifications of DNA and associated proteins, are affected by age and the environment, providing an important link between the genetic predisposition to disease and crucially important risks related to lifetime epigenetic exposures. The importance of epigenetic marks in cancer is well established, and the relevance to neuropsychiatric disease is now emerging. An epigenetic contribution to schizophrenia (SZ) is supported by important, but often ignored discordance among MZ twins, the effects of DNA methylation (DNAm) precursors on psychotic symptoms in SZ, and evidence for DNAm variation in SZ candidate genes. While genome-wide association studies are ongoing for SZ, no similar effort has yet been pursued to identify epigenetic changes, largely due to technology limitations. Here we propose to determine the potential epigenetic contribution to SZ by combining robust experimental and statistical genome-wide methods for DNAm analysis recently developed by the applicants, with three large and well-characterized Consortia focusing on the genetics of SZ (MGI, COGS, PAARTNERS) that have already carried out extensive genetic and phenotypic studies.
Our specific aims are: (1) Compare genome-wide methylation scan (GWMs) measures between SZ cases and controls using 1000 SZ cases / 1000 age/sex frequency matched control lymphocyte DNA as well as 140 SZ / 140 control brains; (2) Replicate GWM findings at 9,880 CpG sites in an independent sample of 2000 cases / 2000 controls from the NIMH Genetics Repository and fine-map the DNAm and examine expression patterns for the top 50 gene candidates; and (3) Integrate these epigenetic discoveries with the genetic data already being collected on these samples. These studies will provide the first comprehensive evaluation of the epigenetics of SZ and provide an unprecedented complement to SZ genetics data, allowing integration of genetic, environmental, and epigenetic effects on SZ. From an important treatment perspective, since epigenetic changes are potentially reversible, these studies may also lead to exciting new avenues for SZ therapy.

Public Health Relevance

Schizophrenia is a common, profoundly disabling disorder that carries a heavy burden for patients and families that is the subject of intensive genetic studies. The study of epigenetic variation, such as DNA methylation, is an essential complement to conventional genetic disease studies; unlike sequence variation, epigenetic marks are affected by age and the environment. This project will provide a comprehensive genome- wide approach to the epigenetics of SZ, bringing to bear state of the art experimental and statistical approaches to the analysis of DNA methylation on a sample set identified and assessed by an outstanding network of SZ phenotypic experts working together in a highly collaborative manner. ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01MH085270-01
Application #
7573981
Study Section
Special Emphasis Panel (ZRG1-HOP-T (04))
Program Officer
Koester, Susan E
Project Start
2008-09-30
Project End
2013-05-31
Budget Start
2008-09-30
Budget End
2009-05-31
Support Year
1
Fiscal Year
2008
Total Cost
$3,395,044
Indirect Cost
Name
Johns Hopkins University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Montano, Carolina; Taub, Margaret A; Jaffe, Andrew et al. (2016) Association of DNA Methylation Differences With Schizophrenia in an Epigenome-Wide Association Study. JAMA Psychiatry 73:506-14
MontaƱo, Carolina M; Irizarry, Rafael A; Kaufmann, Walter E et al. (2013) Measuring cell-type specific differential methylation in human brain tissue. Genome Biol 14:R94