Schizophrenia (SZ) is a devastating psychiatric illness with a complex etiology. While genetic sequence variation clearly contributes to SZ development, knowledge of DNA methylation patterns may provide complementary information. First, methylation studies may provide additional insights into disease processes. For example, as methylation may directly regulate gene expression and is mutable in postmitotic tissues, it provides functional information unobtainable by sequence alone and can account for clinical phenomena such as the dynamic course of illness including cycles of remissions and relapses. Second, the translational potential of methylation studies is profound. For example, pathogenic environmental events may leave methylation signatures in blood, traces of which can be preserved during cell division. As methylation marks can be measured cost-effectively in (histone-free) genomic DNA, they can potentially increase the predictive power of algorithms based on sequence variation. Two complications hamper inferences in methylation studies of SZ. First, there are many possible differences between SZ cases and controls that may affect the methylome including lifestyle differences, disease induced psychological stress, smoking and antipsychotic use. Rather than methylation affecting SZ susceptibility, the direction of effect could be reversed with the disease causing methylation changes. Second, the procurement of brain tissue is not possible in living patients. It is therefore important to study the methylome using a combination of blood samples, which can reveal useful biomarkers, and in brain tissue, which can help identify biologically relevant functions regulated by methylation. To address these complications we propose to study the methylomic profiles of SZ cases/controls in blood samples collected at birth. Because these samples were collected years prior to any SZ symptoms, it is logically impossible for SZ disease related confounders to cause the associations. Next, to generate causal hypotheses that can potentially be followed up with functional experiments, we integrate the pre SZ onset findings with methylation and transcription data from post SZ onset blood and brain samples using a logically rigorous analytical framework. As detailed knowledge is lacking about disease relevant methylation sites, we propose to assay all ~27 million CpGs in the human genome in all our samples. Successful completion of this proposal will identify biomarkers and functional methylation marks for SZ generally, and may specifically identify markers with potential to predict SZ risk. Such findings would be of considerable value for improving SZ treatment and care.

Public Health Relevance

DNA methylation studies offer great potential to improve the understanding of schizophrenia but the critical questions of whether associated methylation marks truly indicate disease risk, or if they reflect changes caused by the disease, or disease related confounders, remain to be investigated. Our goal is to disentangle these questions by studying the methylome in human samples collected pre- and post schizophrenia onset. The successful completion of the proposed work may identify biomarkers and functional methylation marks for SZ in general and may specifically identify markers with potential to predict SZ risk, which would be of tremendous value for improved SZ treatment and care.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH109525-02
Application #
9424683
Study Section
Behavioral Genetics and Epidemiology Study Section (BGES)
Program Officer
Koester, Susan E
Project Start
2017-02-06
Project End
2020-11-30
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Virginia Commonwealth University
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
105300446
City
Richmond
State
VA
Country
United States
Zip Code
23298
Aberg, Karolina A; Chan, Robin F; Shabalin, Andrey A et al. (2017) A MBD-seq protocol for large-scale methylome-wide studies with (very) low amounts of DNA. Epigenetics 12:743-750