Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes - PubMed (original) (raw)

Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes

Eilis Hannon et al. Epigenetics. 2015.

Abstract

Given the tissue-specific nature of epigenetic processes, the assessment of disease-relevant tissue is an important consideration for epigenome-wide association studies (EWAS). Little is known about whether easily accessible tissues, such as whole blood, can be used to address questions about interindividual epigenomic variation in inaccessible tissues, such as the brain. We quantified DNA methylation in matched DNA samples isolated from whole blood and 4 brain regions (prefrontal cortex, entorhinal cortex, superior temporal gyrus, and cerebellum) from 122 individuals. We explored co-variation between tissues and the extent to which methylomic variation in blood is predictive of interindividual variation identified in the brain. For the majority of DNA methylation sites, interindividual variation in whole blood is not a strong predictor of interindividual variation in the brain, although the relationship with cortical regions is stronger than with the cerebellum. Variation at a subset of probes is strongly correlated across tissues, even in instances when the actual level of DNA methylation is significantly different between them. A substantial proportion of this co-variation, however, is likely to result from genetic influences. Our data suggest that for the majority of the genome, a blood-based EWAS for disorders where brain is presumed to be the primary tissue of interest will give limited information relating to underlying pathological processes. These results do not, however, discount the utility of using a blood-based EWAS to identify biomarkers of disease phenotypes manifest in the brain. We have generated a searchable database for the interpretation of data from blood-based EWAS analyses ( http://epigenetics.essex.ac.uk/bloodbrain/).

Keywords: DNA methylation; Illumina 450K array; blood; brain; cerebellum; cortex; epigenetic epidemiology.

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Figures

Figure 1.

Figure 1.

Variation in DNA methylation in whole blood is correlated with variation in the brain for a small proportion of probes. (A) The proportion of sites (y-axis) for which tissue (black), sex (red), or individual (green) explain a given percentage of DNA methylation variance (x-axis). (B) to (E) Histograms showing the distribution of correlation coefficients between DNA methylation in whole blood and the 4 brain regions (PFC, EC, STG and CER). For all 4 brain regions the distribution of correlation coefficients is significantly skewed to the right, with stronger correlations seen between whole blood and cortical regions than between whole blood and cerebellum.

Figure 2.

Figure 2.

Variation in DNA methylation in whole blood as a predictor of variation in the brain. Shown is the proportion of sites (y-axis) for which variation in blood explains a certain of percentage of DNA methylation variance (x-axis) in the PFC (black), EC (red), STG (green), and CER (blue) from the same individuals.

Figure 3.

Figure 3.

DNA methylation in whole blood significantly co-varies with that in the brain at some genomic loci. An example output of our online database (

http://epigenetics.essex.ac.uk/bloodbrain/

) for blood-brain correla-tions at cg26039926. Shown is a boxplot of the distribution of DNA methylation values across all individuals split by tissue and four scatterplots demonstrating the relationship between DNA methylation in whole blood and four brain regions (PFC, EC, STG, CER). At this probe there is a highly significant correlation between individual variation in whole blood and that observed in all four brain regions.

Figure 4.

Figure 4.

Sites at which interindividual variation correlates between whole blood and brain are enriched in specific genic features. Bar charts plotting the percentage of sites annotated to particular genic feature categories and CpG Island annotations for the full set of “blood variable” sites, in addition to the subset of sites characterized by the highest correlation (r2 > 50%) between blood and brain. Fisher's exact tests were used to test for either over or underrepresentation for each type of feature and are presented in Table S2.

Figure 5.

Figure 5.

EWAS analyses of brain phenotypes using whole blood DNA may potentially miss disease associated variation and interrogate DNA methylation sites that are not actually variable in the brain. Venn diagrams showing the overlap of DNA methylation sites that are (A) variable in whole blood but not variable in the cortex (STG) or cerebellum and (B) variable in the cortex (STG) and cerebellum but not in whole blood.

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