Beyond genotype: serotonin transporter epigenetic modification predicts human brain function.
paper
Cited
Public
- Authors
- Nikolova, Yuliya S; Koenen, Karestan C; Galea, Sandro; Wang, Chiou-Miin; Seney, Marianne L; Sibille, Etienne; Williamson, Douglas E; Hariri, Ahmad R
- Year
- 2014
- Journal
- Nature neuroscience
- PMID
- 25086606
- DOI
- 10.1038/nn.3778
- PMCID
- PMC4146649
We examined epigenetic regulation in regards to behaviorally and clinically relevant human brain function. Specifically, we found that increased promoter methylation of the serotonin transporter gene predicted increased threat-related amygdala reactivity and decreased mRNA expression in postmortem amygdala tissue. These patterns were independent of functional genetic variation in the same region. Furthermore, the association with amygdala reactivity was replicated in a second cohort and was robust to both sampling methods and age.
Effects of SLC6A4 promoter methylation on amygdala reactivity. Statistical parametric map illustrating mean bilateral threatβrelated amygdala reactivity across all participants in the (a) Discovery cohort (left: Γ = β24, y = β8, z = β16, t = 10.29, p = 2.0095 Γ 10β14, kE = 180; right: Γ = 30, y = β4, z = β20, t = 11.13, p < 0.00001, kE = 203) and (c) Replication cohort (left: Γ = β20, y = β4, z = β18, t = 11.29, p < 0.00001, kE = 197; right: Γ = 20, y = β4, z = β16, t = 11.80, p = 1.29 Γ 10β13, kE = 205). Activation clusters are overlaid onto canonical structural brain images in the coronal plane (Y = β2). Average percent SLC6A4 proximal promoter methylation was positively correlated with reactivity of the left amygdala in both the Discovery (b) and Replication cohort (d).a.u.= arbitrary units.*p < 0.05
Effects of SLC6A4 promoter methylation on gene expression. There was a negative correlation between percent methylation at CpG 14 and SLC6A4 mRNA levels in amygdala tissue. Y-axis units are expressed as arbitrary signal (2-dCT Γ 10,000), square root transformed to normalize the distribution of the variable.
| # | Section | Preview |
|---|---|---|
| 20 | Methods β DNA Methylation Analyses by Quantitative Bisulfite Pyrosequencing β Replication and postmortem cohorts | Control analyses conducted by EpigenDx only in the Discovery cohort used additional methylationβ¦ |
| 21 | Methods β Self-Report Measures | To assess recent life stress we administered a modified version of the Life Events Scale forβ¦ |
| 22 | Methods β Statistical Analysis β Statistical analysis of methylation data | Percent methylation was computed as the ratio of methylation cytosines over the sum of allβ¦ |
| 23 | Methods β Statistical Analysis β Statistical analysis of methylation data | No single nucleotide polymorphisms (SNPs) resulting in CpG site gain or loss were identified withinβ¦ |
| 24 | Methods β Statistical Analysis β Statistical analysis of methylation data | Linear regression models, as implemented in IBM SPSS Statistics 20.0 (Chicago, IL), were used toβ¦ |
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