DNA methyltransferase candidate polymorphisms, imprinting methylation, and birth outcome

Peer reviewedPublisher PD

Breast cancer risk and imprinting methylation in blood

Date of Acceptance: 17/08/2015 Acknowledgements This study was supported by the Breast Cancer Campaign (2008MayPR46) and Fraserburgh Moonlight Prowl Breast Cancer Charity. PH, GH and GWH acknowledge the support of the Scottish Government. We would like to thank Val Bain and Michela Donnarumma for help with the data and sample collection.Peer reviewedPublisher PD

Imprinting methylation predicts hippocampal volumes and hyperintensities and the change with age in later life.

Funder: Rural and Environment Science and Analytical Services Division; doi: http://dx.doi.org/10.13039/100011310Epigenetic imprinting is important for neurogenesis and brain function. Hippocampal volumes and brain hyperintensities in late life have been associated with early life circumstances. Epigenetic imprinting may underpin these associations. Methylation was measured at 982 sites in 13 imprinted locations in blood samples from a longitudinal cohort by bisulphite amplicon sequencing. Hippocampal volumes and hyperintensities were determined at age 64y and 72y using MRI. Hyperintensities were determined in white matter, grey matter and infratentorial regions. Permutation methods were used to adjust for multiple testing. At 64y, H19/IGF2 and NESPAS methylation predicted hippocampal volumes. PEG3 predicted hyperintensities in hippocampal grey matter, and white matter. GNASXL predicted grey matter hyperintensities. Changes with age were predicted for hippocampal volume (MEST1, KvDMR, L3MBTL, GNASXL), white matter (MEST1, PEG3) and hippocampal grey matter hyperintensities (MCTS2, GNASXL, NESPAS, L3MBTL, MCTS2, SNRPN, MEST1). Including childhood cognitive ability, years in education, or socioeconomic status as additional explanatory variables in regression analyses did not change the overall findings. Imprinting methylation in multiple genes predicts brain structures, and their change over time. These findings are potentially relevant to the development of novel tests of brain structure and function across the life-course, strategies to improve cognitive outcomes, and our understanding of early influences on brain development and function

Imprinting methylation in SNRPN and MEST1 in adult blood predicts cognitive ability.

Genomic imprinting is important for normal brain development and aberrant imprinting has been associated with impaired cognition. We studied the imprinting status in selected imprints (H19, IGF2, SNRPN, PEG3, MEST1, NESPAS, KvDMR, IG-DMR and ZAC1) by pyrosequencing in blood samples from longitudinal cohorts born in 1936 (n = 485) and 1921 (n = 223), and anterior hippocampus, posterior hippocampus, periventricular white matter, and thalamus from brains donated to the Aberdeen Brain Bank (n = 4). MEST1 imprint methylation was related to childhood cognitive ability score (-0.416 95% CI -0.792,-0.041; p = 0.030), with the strongest effect evident in males (-0.929 95% CI -1.531,-0.326; p = 0.003). SNRPN imprint methylation was also related to childhood cognitive ability (+0.335 95%CI 0.008,0.663; p = 0.045). A significant association was also observed for SNRPN methylation and adult crystallised cognitive ability (+0.262 95%CI 0.007,0.517; p = 0.044). Further testing of significant findings in a second cohort from the same region, but born in 1921, resulted in similar effect sizes and greater significance when the cohorts were combined (MEST1; -0.371 95% CI -0.677,-0.065; p = 0.017; SNRPN; +0.361 95% CI 0.079,0.643; p = 0.012). For SNRPN and MEST1 and four other imprints the methylation levels in blood and in the five brain regions were similar. Methylation of the paternally expressed, maternally methylated genes SNRPN and MEST1 in adult blood was associated with cognitive ability in childhood. This is consistent with the known importance of the SNRPN containing 15q11-q13 and the MEST1 containing 7q31-34 regions in cognitive function. These findings, and their sex specific nature in MEST1, point to new mechanisms through which complex phenotypes such as cognitive ability may be inherited. These mechanisms are potentially relevant to both the heritable and non-heritable components of cognitive ability. The process of epigenetic imprinting-within SNRPN and MEST1 in particular-and the factors that influence it, are worthy of further study in relation to the determinants of cognitive ability

Human Intelligence and Polymorphisms in the DNA Methyltransferase Genes Involved in Epigenetic Marking

Epigenetic mechanisms have been implicated in syndromes associated with mental impairment but little is known about the role of epigenetics in determining the normal variation in human intelligence. We measured polymorphisms in four DNA methyltransferases (DNMT1, DNMT3A, DNMT3B and DNMT3L) involved in epigenetic marking and related these to childhood and adult general intelligence in a population (n = 1542) consisting of two Scottish cohorts born in 1936 and residing in Lothian (n = 1075) or Aberdeen (n = 467). All subjects had taken the same test of intelligence at age 11yrs. The Lothian cohort took the test again at age 70yrs. The minor T allele of DNMT3L SNP 11330C>T (rs7354779) allele was associated with a higher standardised childhood intelligence score; greatest effect in the dominant analysis but also significant in the additive model (coefficient = 1.40additive; 95%CI 0.22,2.59; p = 0.020 and 1.99dominant; 95%CI 0.55,3.43; p = 0.007). The DNMT3L C allele was associated with an increased risk of being below average intelligence (OR 1.25additive; 95%CI 1.05,1.51; p = 0.011 and OR 1.37dominant; 95%CI 1.11,1.68; p = 0.003), and being in the lowest 40th (padditive = 0.009; pdominant = 0.002) and lowest 30th (padditive = 0.004; pdominant = 0.002) centiles for intelligence. After Bonferroni correction for the number variants tested the link between DNMT3L 11330C>T and childhood intelligence remained significant by linear regression and centile analysis; only the additive regression model was borderline significant. Adult intelligence was similarly linked to the DNMT3L variant but this analysis was limited by the numbers studied and nature of the test and the association was not significant after Bonferroni correction. We believe that the role of epigenetics in the normal variation in human intelligence merits further study and that this novel finding should be tested in other cohorts

Continuous birth outcomes and their relationship to DNMT variants in mothers and babies.

1<p>Variants specified in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068896#pone-0068896-t001" target="_blank">Table 1</a>. Linear regression analysis based on all three genotype frequencies (homozygote minor frequency>heterozygote>homozygote common) adjusted for baby sex, and gestational age ² or baby sex alone ³.</p>*<p><i>p</i><0.05,</p>**<p><i>p</i><0.01,</p>***<p><i>p</i><0.001.</p

Categorical birth outcomes and their relationship to DNMT variants in babies.

1<p>Variants specified in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068896#pone-0068896-t001" target="_blank">Table 1</a>. Logistic regression analysis based on all three genotype frequencies (homozygote minor frequency>heterozygote>homozygote common). The standardised birth weight is already adjusted for gestational age and baby sex ²; the risk of requiring neonatal treatment was adjusted for gestational age, baby sex and baby weight ³.</p>*<p><i>p</i><0.05,</p>**<p><i>p</i><0.01,</p>***<p><i>p</i><0.001.</p

Proportion of babies in lowest standardised birth weight decile and the proportion requiring neonatal treatment by baby DNMT3L genotype.

<p>Raw data unadjusted for any other variable. Error bars represent 95% confidence intervals.</p

Continuous birth outcomes and their relationship to to LINE1, PEG3, SNRPN and IGF2 methylation in cord blood.

<p>Linear regression analysis of DNA methylation on birth parameters. Analyses were adjusted for baby sex, and gestational age ¹ or baby sex alone ².</p>*<p><i>p</i><0.05,</p>**<p><i>p</i><0.01,</p>***<p><i>p</i><0.001.</p

DNMT genotypes and allele frequencies in mothers and babies.

<p>Genotype frequencies are shown with the percentages in brackets. Allele frequencies are expressed as proportions. All genotypes were in Hardy-Weinberg equilibrium (Chi-squared test).</p