Differential and correlation analyses of microarray gene expression data in the CEPH Utah families

Identification, replication and characterization of epigenetic remodelling in the aging genome: a cross population analysis

Aging is a complex biological process regulated by multiple cellular pathways and molecular mechanisms including epigenetics. Using genome-wide DNA methylation data measured in a large collection of Scottish old individuals, we performed discovery association analysis to identify age-methylated CpGs and replicated them in two independent Danish cohorts. The double-replicated CpGs were characterized by distribution over gene regions and location in relation to CpG islands. The replicated CpGs were further characterized by involvement in biological pathways to study their functional implications in aging. We identified 67,604 age-associated CpG sites reaching genome-wide significance of FWER <0.05, 86% demethylated with increasing age. Double-replication resulted in 5,168 CpGs (39% age-methylated and 61% age-demethylated) which were characterized by high concentration of age-methylated CpGs at 1stExon and TSS200 and a dominant pattern of age-demethylated CpGs at other gene regions, and by overwhelming age-related methylation in CpG islands and demethylation at shore/shelf and open sea. The differential distribution patterns over gene regions for methylated and demethylated CpGs both relate to reduced gene activity during aging. Pathway analysis showed that age-dependent methylations were especially involved in cellular signalling activities while demethylations particularly linked to functions of the extracellular matrix, all implicated in the aging process and age-related disease risk.

Identification of a T cell gene expression clock obtained by exploiting a MZ twin design

Many studies investigated age-related changes in gene expression of different tissues, with scarce agreement due to the high number of affecting factors. Similarly, no consensus has been reached on which genes change expression as a function of age and not because of environment. In this study we analysed gene expression of T lymphocytes from 27 healthy monozygotic twin couples, with ages ranging over whole adult lifespan (22 to 98 years). This unique experimental design allowed us to identify genes involved in normative aging, which expression changes independently from environmental factors. We obtained a transcriptomic signature with 125 genes, from which chronological age can be estimated. This signature has been tested in two datasets of same cell type hybridized over two different platforms, showing a significantly better performance compared to random signatures. Moreover, the same signature was applied on a dataset from a different cell type (human muscle). A lower performance was obtained, indicating the possibility that the signature is T cell-specific. As a whole our results suggest that this approach can be useful to identify age-modulated genes.

Twin methodology in epigenetic studies

Since the final decades of the last century, twin studies have made a remarkable contribution to the genetics of human complex traits and diseases. With the recent rapid development in modern biotechnology of high-throughput genetic and genomic analyses, twin modelling is expanding from analysis of diseases to molecular phenotypes in functional genomics especially in epigenetics, a thriving field of research that concerns the environmental regulation of gene expression through DNA methylation, histone modification, microRNA and long non-coding RNA expression, etc. The application of the twin method to molecular phenotypes offers new opportunities to study the genetic (nature) and environmental (nurture) contributions to epigenetic regulation of gene activity during developmental, ageing and disease processes. Besides the classical twin model, the case co-twin design using identical twins discordant for a trait or disease is becoming a popular and powerful design for epigenome-wide association study in linking environmental exposure to differential epigenetic regulation and to disease status while controlling for individual genetic make-up. It can be expected that novel uses of twin methods in epigenetic studies are going to help with efficiently unravelling the genetic and environmental basis of epigenomics in human complex diseases.

Twins for epigenetic studies of human aging and development

Most of the complex traits including aging phenotypes are caused by the interaction between genome and environmental conditions and the interface of epigenetics may be a central mechanism. Although modern technologies allow us high-throughput profiling of epigenetic patterns already at genome level, our understanding of genetic and environmental influences on the epigenetic processes remains limited. Twins are of special interest for genetic studies due to their genetic similarity and rearing-environment sharing. The classical twin design has made a great contribution in dissecting the genetic and environmental contributions to human diseases and complex traits. In the era of functional genomics, the valuable sample of twins is helping to bridge the gap between gene activity and the environments through epigenetic mechanisms unlimited by DNA sequence variations. We propose to extend the classical twin design to study the aging-related molecular epigenetic phenotypes and link them with environmental exposures especially early life events. Different study designs and application issues will be highlighted and novel approaches introduced with aim at making uses of twins in assessing the environmental impact on epigenetic changes during development and in the aging process.

Age-associated gene expression in normal breast tissue mirrors qualitative age-at-incidence patterns for breast cancer

BACKGROUND

Age is the strongest breast cancer risk factor, with overall breast cancer risk increasing steadily beginning at approximately 30 years of age. However, while breast cancer risk is lower among younger women, young women's breast cancer may be more aggressive. Although, several genomic and epidemiologic studies have shown higher prevalence of aggressive, estrogen-receptor negative breast cancer in younger women, the age-related gene expression that predisposes to these tumors is poorly understood. Characterizing age-related patterns of gene expression in normal breast tissues may provide insights on etiology of distinct breast cancer subtypes that arise from these tissues.

METHODS

To identify age-related changes in normal breast tissue, 96 tissue specimens from patients with reduction mammoplasty, ages 14 to 70 years, were assayed by gene expression microarray.

RESULTS

Significant associations between gene expression levels and age were identified for 802 probes (481 increased, 321 decreased with increasing age). Enriched functions included "aging of cells," "shape change," and "chemotaxis," and enriched pathways included Wnt/beta-catenin signaling, Ephrin receptor signaling, and JAK/Stat signaling. Applying the age-associated genes to publicly available tumor datasets, the age-associated pathways defined two groups of tumors with distinct survival.

CONCLUSION

The hazard rates of young-like tumors mirrored that of high-grade tumors in the Surveillance, Epidemiology, and End Results Program, providing a biologic link between normal aging and age-related tumor aggressiveness.

IMPACT

These data show that studies of normal tissue gene expression can yield important insights about the pathways and biologic pressures that are relevant during tumor etiology and progression.

A growth curve model with fractional polynomials for analysing incomplete time-course data in microarray gene expression studies

Identifying the various gene expression response patterns is a challenging issue in expression microarray time-course experiments. Due to heterogeneity in the regulatory reaction among thousands of genes tested, it is impossible to manually characterize a parametric form for each of the time-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human in vivo irritated epidermis data with missing observations to investigate time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model selection and significant gene identification strategies that can be applied in microarray-based time-course gene expression experiments with missing observations.

Peripheral blood gene expression profiles in metabolic syndrome, coronary artery disease and type 2 diabetes

To determine if individuals with metabolic disorders possess unique gene expression profiles, we compared transcript levels in peripheral blood from patients with coronary artery disease, type 2 diabetes and their precursor state, metabolic syndrome to those of control subjects and subjects with rheumatoid arthritis. The gene expression profile of each metabolic state was distinguishable from controls and correlated with other metabolic states more than with rheumatoid arthritis. Of note, subjects in the metabolic cohorts over-expressed gene sets that participate in the innate immune response. Genes involved in activation of the pro-inflammatory transcription factor, NF-κB, were over-expressed in coronary artery disease while genes differentially expressed in type 2 diabetes play key roles in T cell activation and signaling. RT-PCR validation confirmed microarray results. Furthermore, several genes differentially expressed in human metabolic disorders have been previously shown to participate in inflammatory responses in murine models of obesity and Type 2 diabetes. Taken together, these data demonstrate that peripheral blood from individuals with metabolic disorders display overlapping and non-overlapping patterns of gene expression indicative of unique, underlying immune processes.

Ranking analysis of correlation coefficients in gene expressions

Development of statistical methods has become very necessary for large-scale correlation analysis in the current "omic" data. We propose ranking analysis of correlation coefficients (RAC) based on transforming correlation matrix into correlation vector and conducting a "locally ranking" strategy that significantly reduces computational complexity and load. RAC gives estimation of null correlation distribution and an estimator of false discovery rate (FDR) for finding gene pairs of being correlated in expressions obtained by comparison between the ranked observed correlation coefficients and the ranked estimated ones at a given threshold level. The simulated and real data show that the estimated null correlation distribution is exactly the same with the true one and the FDR estimator works well in various scenarios. By applying our RAC, in the null dataset, no gene pairs were found but, in the human cancer dataset, 837 gene pairs were found to have positively correlated expression variations at FDR≤5%. RAC performs well in multiple conditions (classes), each with 3 or more replicate observations.

Genetics and beyond--the transcriptome of human monocytes and disease susceptibility

Background

Variability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes.

Methodology/Principal Findings

To get better insight into the overall variability of gene expression, we assessed the transcriptome of circulating monocytes, a key cell involved in immunity-related diseases and atherosclerosis, in 1,490 unrelated individuals and investigated its association with >675,000 SNPs and 10 common cardiovascular risk factors. Out of 12,808 expressed genes, 2,745 expression quantitative trait loci were detected (P<5.78×10⁻¹²), most of them (90%) being cis-modulated. Extensive analyses showed that associations identified by genome-wide association studies of lipids, body mass index or blood pressure were rarely compatible with a mediation by monocyte expression level at the locus. At a study-wide level (P<3.9×10⁻⁷), 1,662 expression traits (13.0%) were significantly associated with at least one risk factor. Genome-wide interaction analyses suggested that genetic variability and risk factors mostly acted additively on gene expression. Because of the structure of correlation among expression traits, the variability of risk factors could be characterized by a limited set of independent gene expressions which may have biological and clinical relevance. For example expression traits associated with cigarette smoking were more strongly associated with carotid atherosclerosis than smoking itself.

Conclusions/Significance

This study demonstrates that the monocyte transcriptome is a potent integrator of genetic and non-genetic influences of relevance for disease pathophysiology and risk assessment.

Dissecting complex phenotypes using the genomics of twins

Genetics in the post-genomic period is shifting from structural to functional genetics or genomics. Meanwhile, the use of twins is largely expanding from traditional heritability estimation for disease phenotypes to the study of both diseases and various molecular phenotypes, such as the regulatory phenotypes in functional genomics concerning gene expression and regulation, by engaging both classical twin design and marker-based gene mapping techniques in genetic epidemiology. New research designs have been proposed for making novel uses of twins in studying the molecular basis in the epigenetics of human diseases. Besides, twins not only serve as ideal samples for disease gene mapping using conventional genetic markers but also represent an excellent model for associating DNA copy number variations, a structural genetic marker, with human diseases. It is believed that, with the rapid development in biotechniques and new advances in bioinformatics, the unique samples of twins will make new contributions to our understanding of the nature and nurture in complex disease development and in human health. This paper aims at summarizing the new uses of twins in current genetic studies and suggesting novel proposes together with useful design and analytical strategies.

Monosomy for the X chromosome

Dosage compensation serves to equalize X chromosome gene expression in mammalian males and females and involves extensive silencing of the 2nd X chromosome in females. If dosage compensation mechanisms completely suppressed the 2nd X chromosome, then actual physical loss of this "eXtra" chromosome should have few consequences. However, X monosomy has major effects upon normal development, fertility and longevity in humans and some other species. This article reviews observations and arguments attempting to explain the phenotypic effects of X monosomy in humans and other mammals in terms of X chromosome gene dosage.

Activation of host wound responses in breast cancer microenvironment

PURPOSE

Cancer progression is mediated by processes that are also important in wound repair. As a result, cancers have been conceptualized as overhealing wounds or "wounds that do not heal," and gene expression signatures reflective of wound repair have shown value as predictors of breast cancer survival. Despite the widespread acknowledgment of commonalities between host responses to wounds and host responses to cancer, the gene expression responses of normal tissue adjacent to cancers have not been well characterized.

EXPERIMENTAL DESIGN

Using RNA extracted from histologically normal breast tissue from 107 patients, including 60 reduction mammoplasty patients and 47 cancer patients, we measured whole genome expression profiles and identified a gene expression signature that is induced in response to breast cancer.

RESULTS

This signature represents an in vivo "wound response" signature that is differentially expressed in the normal tissue of breast cancer patients compared with those without disease and is highly accurate (at least 92% sensitivity and 98% specificity) in distinguishing diseased and nondiseased. The in vivo wound response signature is highly prognostic of breast cancer survival, and there is a strong association between the groups identified by this signature and those identified using serum-treated fibroblasts and other microenvironment-derived or microenvironment-related signatures.

CONCLUSIONS

The prevalence of the wound response signature in histologically normal tissue adjacent to breast cancer suggests that microenvironment response is an important variable in breast cancer progression and may be an important target for clinical interventions.

Transcriptional (dys)regulation and aging in Caenorhabditis elegans

New work could link laboratory-defined longevity pathways to the process of normal aging.

A circuit of transcription factors has been discovered in Caenorhabditis elegans that could provide a link between laboratory-defined intracellular 'longevity pathways', gene dysregulation and the process of normal aging.