Association of a Reproducible Epigenetic Risk Profile for Schizophrenia With Brain Methylation and Function.

Publication date: Feb 12, 2020

Schizophrenia is a severe mental disorder in which epigenetic mechanisms may contribute to illness risk. Epigenetic profiles can be derived from blood cells, but to our knowledge, it is unknown whether these predict established brain alterations associated with schizophrenia.

To identify an epigenetic signature (quantified as polymethylation score [PMS]) of schizophrenia using machine learning applied to genome-wide blood DNA-methylation data; evaluate whether differences in blood-derived PMS are mirrored in data from postmortem brain samples; test whether the PMS is associated with alterations of dorsolateral prefrontal cortex hippocampal (DLPFC-HC) connectivity during working memory in healthy controls (HC); explore the association between interactions between polygenic and epigenetic risk with DLPFC-HC connectivity; and test the specificity of the signature compared with other serious psychiatric disorders.

In this case-control study conducted from 2008 to 2018 in sites in Germany, the United Kingdom, the United States, and Australia, blood DNA-methylation data from 2230 whole-blood samples from 6 independent cohorts comprising HC (1238 [55.5%]) and participants with schizophrenia (803 [36.0%]), bipolar disorder (39 [1.7%]), major depressive disorder 35 [1.6%]), and autism (27 [1.2%]), and first-degree relatives of all patient groups (88 [3.9%]) were analyzed. DNA-methylation data were further explored from 244 postmortem DLPFC samples from 136 HC and 108 patients with schizophrenia. Neuroimaging and genome-wide association data were available for 393 HC. The latter data was used to calculate a polygenic risk score (PRS) for schizophrenia. The data were analyzed in 2019.

The accuracy of schizophrenia control classification based on machine learning using epigenetic data; association of schizophrenia PMS scores with DLPFC-HC connectivity; and association of the interaction between PRS and PMS with DLPFC-HC connectivity.

This study included 7488 participants (4395 men [58.7%]), of whom 3158 (2230 men [70.6%]) received a diagnosis of schizophrenia. The PMS signature was associated with schizophrenia across 3 independent data sets (area under the curve [AUC] from 0.69 to 0.78; P value from 0.049 to 1.24?x?10-7) and data from postmortem DLPFC samples (AUC?=?0.63; P?=?1.42?x?10-4), but not with major depressive disorder (AUC?=?0.51; P?=?.16), autism (AUC?=?0.53; P?=?.66), or bipolar disorder (AUC?=?0.58; P?=?.21). Pathways contributing most to the classification included synaptic processes. Healthy controls with schizophrenia-like PMS showed significantly altered DLPFC-HC connectivity (validation methylation/magnetic resonance imaging, t?

Chen, J., Zang, Z., Braun, U., Schwarz, K., Harneit, A., Kremer, T., Ma, R., Schweiger, J., Moessnang, C., Geiger, L., Cao, H., Degenhardt, F., N”othen, M.M., Tost, H., Meyer-Lindenberg, A., and Schwarz, E. Association of a Reproducible Epigenetic Risk Profile for Schizophrenia With Brain Methylation and Function. 21009. 2020 JAMA Psychiatry.

Concepts Keywords
AUC Illness
Australia Autism
Autism Major depressive disorder
Bipolar Disorder Participants schizophrenia
Blood Bipolar disorder
Brain Branches of biology
Dorsolateral Prefrontal Cortex Epigenetics
Epigenetic Psychiatry
Genome Schizophrenia
Germany DNA
Hippocampal Cerebral cortex
Magnetic Resonance Imaging Dorsolateral prefrontal cortex
Major Depressive Disorder DNA methylation
Mental Disorder Epigenetics of schizophrenia
Methylation Behavioral epigenetics
Neuroimaging Magnetic resonance imaging
Psychiatric Disorders
United Kingdom
United States
Working Memory


Type Source Name
disease MESH Schizophrenia
pathway REACTOME Methylation
disease MESH severe mental disorder
disease MESH bipolar disorder
disease MESH major depressive disorder
disease MESH autism
disease MESH men
disease MESH diagnosis

Original Article

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