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Integrated Analysis of Gene Expression Differences in Twins Discordant for Disease and Binary Phenotypes.

ABSTRACT: While both genes and environment contribute to phenotype, deciphering environmental contributions to phenotype is a challenge. Furthermore, elucidating how different phenotypes may share similar environmental etiologies also is challenging. One way to identify environmental influences is through a discordant monozygotic (MZ) twin study design. Here, we assessed differential gene expression in MZ discordant twin pairs (affected vs. non-affected) for seven phenotypes, including chronic fatigue syndrome, obesity, ulcerative colitis, major depressive disorder, intermittent allergic rhinitis, physical activity, and intelligence quotient, comparing the spectrum of genes differentially expressed across seven phenotypes individually. Second, we performed meta-analysis for each gene to identify commonalities and differences in gene expression signatures between the seven phenotypes. In our integrative analyses, we found that there may be a common gene expression signature (with small effect sizes) across the phenotypes; however, differences between phenotypes with respect to differentially expressed genes were more prominently featured. Therefore, defining common environmentally induced pathways in phenotypes remains elusive. We make our work accessible by providing a new database (DiscTwinExprDB: http://apps.chiragjpgroup.org/disctwinexprdb/ ) for investigators to study non-genotypic influence on gene expression.

SUBMITTER: Tangirala S

PROVIDER: S-EPMC5758574 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Integrated Analysis of Gene Expression Differences in Twins Discordant for Disease and Binary Phenotypes.

Tangirala Sivateja S Patel Chirag J CJ

Scientific reports 20180108 1

While both genes and environment contribute to phenotype, deciphering environmental contributions to phenotype is a challenge. Furthermore, elucidating how different phenotypes may share similar environmental etiologies also is challenging. One way to identify environmental influences is through a discordant monozygotic (MZ) twin study design. Here, we assessed differential gene expression in MZ discordant twin pairs (affected vs. non-affected) for seven phenotypes, including chronic fatigue syn ...[more]

PMID: 29311748

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Project description:Body mass index (BMI) discordant monozygotic (MZ) twins allow an examination of the causes and consequences of adiposity in a genetically controlled design. Few studies have examined longitudinal BMI discordance in MZ pairs.The aim of this work was to study the development over time of BMI discordance in adolescent and adult MZ twin pairs and to examine lifestyle, metabolic, inflammatory and gene expression differences associated with concurrent and long-term BMI discordance in MZ pairs.BMI data from 2775 MZ twin pairs, collected in eight longitudinal surveys and a biobank project between 1991 and 2011, were analyzed to characterize longitudinal discordance. Lifestyle characteristics were compared within discordant pairs (?BMI?3?kg?m(-2)) and biomarkers (lipids, glucose, insulin, C-reactive protein, fibrinogen, interleukin (IL)-6, tumor necrosis factor-? and soluble IL-6 receptor and liver enzymes aspartate aminotransferase, alanine aminotransferase and gamma glutamyl transferase) and gene expression were compared in peripheral blood from discordant pairs who participated in the Netherlands Twin Register biobank project.The prevalence of discordance ranged from 3.2% in 1991 (mean age=17, s.d.=2.4) to 17.4% (N=202 pairs) in 2009 (mean age=35, s.d.=15) and was 16.5% (N=174) among pairs participating in the biobank project (mean age=35, s.d.=12). Of the 699 MZ pairs with BMI data from 3 to 5 time points, 17 pairs (2.4%) were long-term discordant (at all available time points; mean follow-up range=6.4 years). Concurrently discordant pairs showed significant differences in self-ratings of which twin eats most (P=2.3 × 10(-13)) but not in leisure time exercise activity (P=0.28) and smoking (P>0.05). Ten out of the 14 biomarkers showed significantly more unfavorable levels in the heavier of twin of the discordant pairs (P-values <0.001); most of these biomarker differences were largest in longitudinally discordant pairs. No significant gene expression differences were identified, although high ranking genes were enriched for Gene Ontology terms highlighting metabolic gene regulation and inflammation pathways.BMI discordance is uncommon in adolescent identical pairs but increases with higher pair-mean of BMI at older ages, although long-term BMI discordance is rare. In discordant pairs, the heavier twin had a more unfavorable blood biomarker profile than the genetically matched leaner twin, in support of causal effects of obesity.

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.

Project description:BackgroundMoyamoya disease (MMD) is characterized by progressive stenosis of intracranial arteries in the circle of Willis with unknown etiology even after the identification of a Moyamoya susceptible gene, RNF213. Recently, differences in epigenetic regulations have been investigated by a case-control study in MMD. Here, we employed a disease discordant monozygotic twin-based study design to unmask potential confounders.MethodsCirculating genome-wide microRNA (miRNome) profiling was performed in MMD-discordant monozygotic twins, non-twin-MMD patients, and non-MMD healthy volunteers by microarray followed by qPCRvalidation, using blood samples. Differential plasma-microRNAs were further quantified in endothelial cells differentiated from iPS cell lines (iPSECs) derived from another independent non-twin cohort. Lastly, their target gene expression in the iPSECs was analyzed.ResultsMicroarray detected 309 plasma-microRNAs in MMD-discordant monozygotic twins that were also detected in the non-twin cohort. Principal component analysis of the plasma-microRNA expression level demonstrated distinct 2 groups separated by MMD and healthy control in the twin- and non-twin cohorts. Of these, differential upregulations of hsa-miR-6722-3p/- 328-3p were validated in the plasma of MMD (absolute log2 expression fold change (logFC) > 0.26 for the twin cohort; absolute logFC > 0.26, p < 0.05, and q < 0.15 for the non-twin cohort). In MMD derived iPSECs, hsa-miR-6722-3p/- 328-3p showed a trend of up-regulation with a 3.0- or higher expression fold change. Bioinformatics analysis revealed that 41 target genes of miR-6722-3p/- 328-3p were significantly down-regulated in MMD derived iPSECs and were involved in STAT3, IGF-1-, and PTEN-signaling, suggesting a potential microRNA-gene expression interaction between circulating plasma and endothelial cells.ConclusionsOur MMD-discordant monozygotic twin-based study confirmed a novel circulating microRNA signature in MMD as a potential diagnostic biomarker minimally confounded by genetic heterogeneity. The novel circulating microRNA signature can contribute for the future functional microRNA analysis to find new diagnostic and therapeutic target of MMD.

Dataset Information

Integrated Analysis of Gene Expression Differences in Twins Discordant for Disease and Binary Phenotypes.

Publications

Integrated Analysis of Gene Expression Differences in Twins Discordant for Disease and Binary Phenotypes.

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