Dataset Information

The Needle in the Haystack-Searching for Genetic and Epigenetic Differences in Monozygotic Twins Discordant for Tetralogy of Fallot.

ABSTRACT: Congenital heart defects (CHDs) are the most common birth defect in human with an incidence of almost 1% of all live births. Most cases have a multifactorial origin with both genetics and the environment playing a role in its development and progression. Adding an epigenetic component to this aspect is exemplified by monozygotic twins which share the same genetic background but have a different disease status. As a result, the interplay between the genetic, epigenetic and the environmental conditions might contribute to the etiology and phenotype. To date, the underlying causes of the majority of CHDs remain poorly understood. In this study, we performed genome-wide high-throughput sequencing to examine the genetic, structural genomic and epigenetic differences of two identical twin pairs discordant for Tetralogy of Fallot (TOF), representing the most common cyanotic form of CHDs. Our results show the almost identical genetic and structural genomic identity of the twins. In contrast, several epigenetic alterations could be observed given by DNA methylation changes in regulatory regions of known cardiac-relevant genes. Overall, this study provides first insights into the impact of genetic and especially epigenetic factors underlying monozygotic twins discordant for CHD like TOF.

SUBMITTER: Grunert M

PROVIDER: S-EPMC7761217 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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The Needle in the Haystack-Searching for Genetic and Epigenetic Differences in Monozygotic Twins Discordant for Tetralogy of Fallot.

Grunert Marcel M Appelt Sandra S Grossfeld Paul P Sperling Silke R SR

Journal of cardiovascular development and disease 20201202 4

Congenital heart defects (CHDs) are the most common birth defect in human with an incidence of almost 1% of all live births. Most cases have a multifactorial origin with both genetics and the environment playing a role in its development and progression. Adding an epigenetic component to this aspect is exemplified by monozygotic twins which share the same genetic background but have a different disease status. As a result, the interplay between the genetic, epigenetic and the environmental condi ...[more]

PMID: 33276527

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Project description:Although monozygotic (MZ) twins share the majority of their genetic makeup, they can be phenotypically discordant on several traits and diseases. DNA methylation is an epigenetic mechanism that can be influenced by genetic, environmental and stochastic events and may have an important impact on individual variability. In this study we explored epigenetic differences in peripheral blood samples in three MZ twin studies on major depressive disorder (MDD). Epigenetic data for twin pairs were collected as part of a previous study using 8.1-K-CpG microarrays tagging DNA modification in white blood cells from MZ twins discordant for MDD. Data originated from three geographical regions: UK, Australia and the Netherlands. Ninety-seven MZ pairs (194 individuals) discordant for MDD were included. Different methods to address non independently-and-identically distributed (non-i.i.d.) data were evaluated. Machine-learning methods with feature selection centered on support vector machine and random forest were used to build a classifier to predict cases and controls based on epivariations. The most informative variants were mapped to genes and carried forward for network analysis. A mixture approach using principal component analysis (PCA) and Bayes methods allowed to combine the three studies and to leverage the increased predictive power provided by the larger sample. A machine-learning algorithm with feature reduction classified affected from non-affected twins above chance levels in an independent training-testing design. Network analysis revealed gene networks centered on the PPAR-γ (NR1C3) and C-MYC gene hubs interacting through the AP-1 (c-Jun) transcription factor. PPAR-γ (NR1C3) is a drug target for pioglitazone, which has been shown to reduce depression symptoms in patients with MDD. Using a data-driven approach we were able to overcome challenges of non-i.i.d. data when combining epigenetic studies from MZ twins discordant for MDD. Individually, the studies yielded negative results but when combined classification of the disease state from blood epigenome alone was possible. Network analysis revealed genes and gene networks that support the inflammation hypothesis of MDD.

Dataset Information

The Needle in the Haystack-Searching for Genetic and Epigenetic Differences in Monozygotic Twins Discordant for Tetralogy of Fallot.

Publications

The Needle in the Haystack-Searching for Genetic and Epigenetic Differences in Monozygotic Twins Discordant for Tetralogy of Fallot.

Similar Datasets

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