LXR signaling pathways link cholesterol metabolism with risk for prediabetes and diabetes.

BACKGROUNDPreclinical studies suggest that cholesterol accumulation leads to insulin resistance. We previously reported that alterations in a monocyte cholesterol metabolism transcriptional network (CMTN) - suggestive of cellular cholesterol accumulation - were cross-sectionally associated with obesity and type 2 diabetes (T2D). Here, we sought to determine whether the CMTN alterations independently predict incident prediabetes/T2D risk, and correlate with cellular cholesterol accumulation.METHODSMonocyte mRNA expression of 11 CMTN genes was quantified among 934 Multi-Ethnic Study of Atherosclerosis (MESA) participants free of prediabetes/T2D; cellular cholesterol was measured in a subset of 24 monocyte samples.RESULTSDuring a median 6-year follow-up, lower expression of 3 highly correlated LXR target genes - ABCG1 and ABCA1 (cholesterol efflux) and MYLIP (cholesterol uptake suppression) - and not other CMTN genes, was significantly associated with higher risk of incident prediabetes/T2D. Lower expression of the LXR target genes correlated with higher cellular cholesterol levels (e.g., 47% of variance in cellular total cholesterol explained by ABCG1 expression). Further, adding the LXR target genes to overweight/obesity and other known predictors significantly improved prediction of incident prediabetes/T2D.CONCLUSIONThese data suggest that the aberrant LXR/ABCG1-ABCA1-MYLIP pathway (LAAMP) is a major T2D risk factor and support a potential role for aberrant LAAMP and cellular cholesterol accumulation in diabetogenesis.FUNDINGThe MESA Epigenomics and Transcriptomics Studies were funded by NIH grants 1R01HL101250, 1RF1AG054474, R01HL126477, R01DK101921, and R01HL135009. This work was supported by funding from NIDDK R01DK103531 and NHLBI R01HL119962.

The association between aging-related monocyte transcriptional networks and comorbidity burden: the Multi-Ethnic Study of Atherosclerosis (MESA).

Translating our knowledge of the biological aging from animal models to humans may give rise to novel approaches of targeting multiple aging-related diseases simultaneously and increasing health span. Here, for the first time, we use transcriptomic signatures of monocytes to identify biological aging pathways underlying multiple aging-related diseases in humans. The ordinal logistic regression was used to cross-sectionally investigate transcriptomics of the comorbidity index in 1264 community-based Multi-Ethnic Study of Atherosclerosis (MESA) adults, 47% Caucasian, 32% Hispanic, 21% African American, and 51% female, aged 55-94 years. The comorbidity index was defined as the number of prevalent aging-related diseases including cardiovascular disease, type-2 diabetes, hypertension, cancer, dementia, chronic kidney disease, chronic obstructive pulmonary disease, and hip fracture. We identified 708 gene transcripts associated with the comorbidity index (FDR < 0.05) after adjusting for age, sex, ethnicity, and study site. In a weighted gene co-expression network analysis, as postulated, aging-related declines in apoptosis/autophagy (OR = 1.21 per SD increment, p = 0.0006) and ribosome/mitochondrion (OR = 0.90 per SD increment, p = 0.05) were positively associated with the comorbidity index. After adjusting for multiple comparisons, we identified 10 comorbidity-associated modules (FDR < 0.05), including the module of apoptosis/autophagy. There were three inter-correlated modules of these 10 involved in the complement subcomponent C1q, Fc gamma receptor I, and Fc gamma receptor III of the immune system, respectively. Aging-related upregulation of these three modules was positively associated with the comorbidity index. The odds of comorbidity increased with more of these modules acting together in a dose-response fashion. In conclusion, transcriptomic analysis of human immune cells may identify biomarker panels indicative of comprehensive biological mechanisms, especially immune signaling pathways, contributing to health aging.

Monocyte miRNAs Are Associated With Type 2 Diabetes.

miRNAs are small noncoding RNAs that may contribute to common diseases through epigenetic regulation of gene expression. Little is known regarding the role of miRNAs in type 2 diabetes (T2D). We performed miRNA sequencing and transcriptomic profiling of peripheral monocytes from the longitudinal Multi-Ethnic Study of Atherosclerosis (MESA) (N = 1,154). We examined associations between miRNAs and prevalent impaired fasting glucose and T2D and evaluated the T2D-associated miRNA effect on incident T2D. Of 774 detected miRNAs, 6 (miR-22-3p, miR-33a-5p, miR-181c-5p, miR-92b-3p, miR-222-3p, and miR-944) were associated with prevalent T2D. For five of the six miRNAs (all but miR-222-3p), our findings suggest a dose-response relationship with impaired fasting glucose and T2D. Two of the six miRNAs were associated with incident T2D (miR-92b-3p: hazard ratio [HR] 1.64, P = 1.30E-03; miR-222-3p: HR 1.97, P = 9.10E-03) in the highest versus lowest tertile of expression. Most of the T2D-associated miRNAs were also associated with HDL cholesterol concentrations. The genes targeted by these miRNAs belong to key nodes of a cholesterol metabolism transcriptomic network. Higher levels of miRNA expression expected to increase intracellular cholesterol accumulation in monocytes are linked to an increase in T2D risk.

Role of DNA methylation on the association between physical activity and cardiovascular diseases: results from the longitudinal multi-ethnic study of atherosclerosis (MESA) cohort.

BACKGROUND: The complexity of physical activity (PA) and DNA methylation interaction in the development of cardiovascular disease (CVD) is rarely simultaneously investigated in one study. We examined the role of DNA methylation on the association between PA and CVD. RESULTS: The Multi-Ethnic Study of Atherosclerosis (MESA) cohort Exam 5 data with 1065 participants free of CVD were used for final analysis. The quartile categorical total PA variable was created by activity intensity (METs/week). During a median follow-up of 4.0 years, 69 participants developed CVD. Illumina HumanMethylation450 BeadChip was used to provide genome-wide DNA methylation profiles in purified human monocytes (CD14+). We identified 23 candidate DNA methylation loci to be associated with both PA and CVD. We used the structural equation modeling (SEM) approach to test the complex relationships among multiple variables and the roles of mediators. Three of the 23 identified loci (corresponding to genes VPS13D, PIK3CD and VPS45) remained as significant mediators in the final SEM model along with other covariates. Bridged by the three genes, the 2nd PA quartile (ß = - 0.959; 95%CI: - 1.554 to - 0.449) and the 3rd PA quartile (ß = - 0.944; 95%CI: - 1.628 to - 0.413) showed the greatest inverse associations with CVD development, while the 4th PA quartile had a relatively weaker inverse association (ß = - 0.355; 95%CI: - 0.713 to - 0.124). CONCLUSIONS: The current study is among the first to simultaneously examine the relationships among PA, DNA methylation, and CVD in a large cohort with long-term exposure. We identified three DNA methylation loci bridged the association between PA and CVD. The function of the identified genes warrants further investigation in the pathogenesis of CVD.

Transcriptome prediction performance across machine learning models and diverse ancestries.

Transcriptome prediction methods such as PrediXcan and FUSION have become popular in complex trait mapping. Most transcriptome prediction models have been trained in European populations using methods that make parametric linear assumptions like the elastic net (EN). To potentially further optimize imputation performance of gene expression across global populations, we built transcriptome prediction models using both linear and non-linear machine learning (ML) algorithms and evaluated their performance in comparison to EN. We trained models using genotype and blood monocyte transcriptome data from the Multi-Ethnic Study of Atherosclerosis (MESA) comprising individuals of African, Hispanic, and European ancestries and tested them using genotype and whole-blood transcriptome data from the Modeling the Epidemiology Transition Study (METS) comprising individuals of African ancestries. We show that the prediction performance is highest when the training and the testing population share similar ancestries regardless of the prediction algorithm used. While EN generally outperformed random forest (RF), support vector regression (SVR), and K nearest neighbor (KNN), we found that RF outperformed EN for some genes, particularly between disparate ancestries, suggesting potential robustness and reduced variability of RF imputation performance across global populations. When applied to a high-density lipoprotein (HDL) phenotype, we show including RF prediction models in PrediXcan revealed potential gene associations missed by EN models. Therefore, by integrating other ML modeling into PrediXcan and diversifying our training populations to include more global ancestries, we may uncover new genes associated with complex traits.

Association between sleep disordered breathing and epigenetic age acceleration: Evidence from the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Sleep disordered breathing (SDB) is a common disorder that results in oxidative stress and inflammation and is associated with multiple age-related health outcomes. Epigenetic age acceleration is a DNA methylation (DNAm)-based marker of fast biological aging. We examined the associations of SDB traits with epigenetic age acceleration. METHODS: A sample of 622 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) had blood DNAm measured and underwent Type 2 in-home polysomnography that assessed apnea-hypopnea index (AHI), percentage of sleep time with oxygen saturation lower than 90% (Per90), and arousal index. DNAm data provided measures of DNAm-Age acceleration and DNAm-PhenoAge acceleration. The association of each SDB trait with age acceleration was estimated using linear regression, controlling for covariates. In secondary analyses, we studied the associations of SDB traits with epigenetic age acceleration 2-10 years after sleep study in 530 individuals from the Framingham Heart Study (FHS). FINDINGS: In MESA, AHI was associated with greater DNAm-PhenoAge acceleration (ß = 0.03; 95% CI [0.001, 0.06]). Arousal index was associated with greater DNAm-Age acceleration (ß = 0.04; 95% CI [0.01, 0.07]). Both associations were stronger in women than men. In the secondary FHS analyses, Per90 was associated with greater DNAm-Age acceleration and this association was stronger in men. INTERPRETATION: More severe SDB was associated with epigenetic age acceleration in both cohorts. Future work should prospectively study short- and long-term effects of SDB, and whether treatment reduces epigenetic age acceleration among those individuals with SBD. FUNDING: National Institutes of Health.

Adrenocortical Challenge Response and Genomic Analyses in Scottish Terriers With Increased Alkaline Phosphate Activity.

Scottish terriers (ST) frequently have increased serum alkaline phosphatase (ALP) of the steroid isoform. Many of these also have high serum concentrations of adrenal sex steroids. The study's objective was to determine the cause of increased sex steroids in ST with increased ALP. Adrenal gland suppression and stimulation were compared by low dose dexamethasone (LDDS), human chorionic gonadotropin (HCG) and adrenocorticotropic hormone (ACTH) response tests. Resting plasma pituitary hormones were measured. Steroidogenesis-related mRNA expression was evaluated in six ST with increased ALP, eight dogs of other breeds with pituitary-dependent hyperadrenocorticism (HAC), and seven normal dogs. The genome-wide association of single nucleotide polymorphisms (SNP) with ALP activity was evaluated in 168 ST. ALP (reference interval 8-70 U/L) was high in all ST (1,054 U/L) and HAC (985 U/L) dogs. All HAC dogs and 2/8 ST had increased cortisol post-ACTH administration. All ST and 2/7 Normal dogs had increased sex steroids post-ACTH. ST and Normal dogs had similar post-challenge adrenal steroid profiles following LDDS and HCG. Surprisingly, mRNA of hydroxysteroid 17-beta dehydrogenase 2 (HSD17B2) was lower in ST and Normal dogs than HAC. HSD17B2 facilities metabolism of sex steroids. A SNP region was identified on chromosome 5 in proximity to HSD17B2 that correlated with increased serum ALP. ST in this study with increased ALP had a normal pituitary-adrenal axis in relationship to glucocorticoids and luteinizing hormone. We speculate the identified SNP and HSD17B2 gene may have a role in the pathogenesis of elevated sex steroids and ALP in ST.

Cross-species transcriptional analysis reveals conserved and host-specific neoplastic processes in mammalian glioma.

Glioma is a unique neoplastic disease that develops exclusively in the central nervous system (CNS) and rarely metastasizes to other tissues. This feature strongly implicates the tumor-host CNS microenvironment in gliomagenesis and tumor progression. We investigated the differences and similarities in glioma biology as conveyed by transcriptomic patterns across four mammalian hosts: rats, mice, dogs, and humans. Given the inherent intra-tumoral molecular heterogeneity of human glioma, we focused this study on tumors with upregulation of the platelet-derived growth factor signaling axis, a common and early alteration in human gliomagenesis. The results reveal core neoplastic alterations in mammalian glioma, as well as unique contributions of the tumor host to neoplastic processes. Notable differences were observed in gene expression patterns as well as related biological pathways and cell populations known to mediate key elements of glioma biology, including angiogenesis, immune evasion, and brain invasion. These data provide new insights regarding mammalian models of human glioma, and how these insights and models relate to our current understanding of the human disease.

Cell Cycle Model System for Advancing Cancer Biomarker Research.

Progress in understanding the complexity of a devastating disease such as cancer has underscored the need for developing comprehensive panels of molecular markers for early disease detection and precision medicine applications. The present study was conducted to assess whether a cohesive biological context can be assigned to protein markers derived from public data mining, and whether mass spectrometry can be utilized to screen for the co-expression of functionally related biomarkers to be recommended for further exploration in clinical context. Cell cycle arrest/release experiments of MCF7/SKBR3 breast cancer and MCF10 non-tumorigenic cells were used as a surrogate to support the production of proteins relevant to aberrant cell proliferation. Information downloaded from the scientific public domain was queried with bioinformatics tools to generate an initial list of 1038 cancer-associated proteins. Mass spectrometric analysis of cell extracts identified 352 proteins that could be matched to the public list. Differential expression, enrichment, and protein-protein interaction analysis of the proteomic data revealed several functionally-related clusters of relevance to cancer. The results demonstrate that public data derived from independent experiments can be used to inform biological research and support the development of molecular assays for probing the characteristics of a disease.

Blood monocyte transcriptome and epigenome analyses reveal loci associated with human atherosclerosis.

Little is known regarding the epigenetic basis of atherosclerosis. Here we present the CD14+ blood monocyte transcriptome and epigenome signatures associated with human atherosclerosis. The transcriptome signature includes transcription coactivator, ARID5B, which is known to form a chromatin derepressor complex with a histone H3K9Me2-specific demethylase and promote adipogenesis and smooth muscle development. ARID5B CpG (cg25953130) methylation is inversely associated with both ARID5B expression and atherosclerosis, consistent with this CpG residing in an ARID5B enhancer region, based on chromatin capture and histone marks data. Mediation analysis supports assumptions that ARID5B expression mediates effects of cg25953130 methylation and several cardiovascular disease risk factors on atherosclerotic burden. In lipopolysaccharide-stimulated human THP1 monocytes, ARID5B knockdown reduced expression of genes involved in atherosclerosis-related inflammatory and lipid metabolism pathways, and inhibited cell migration and phagocytosis. These data suggest that ARID5B expression, possibly regulated by an epigenetically controlled enhancer, promotes atherosclerosis by dysregulating immunometabolism towards a chronic inflammatory phenotype.The molecular mechanisms mediating the impact of environmental factors in atherosclerosis are unclear. Here, the authors examine CD14+ blood monocyte's transcriptome and epigenome signatures to find differential methylation and expression of ARID5B to be associated with human atherosclerosis.

Secondhand Tobacco Smoke Exposure Associations With DNA Methylation of the Aryl Hydrocarbon Receptor Repressor.

INTRODUCTION: Cigarette smoking is inversely associated with DNA methylation of the aryl hydrocarbon receptor repressor (AHRR; cg05575921). However, the association between secondhand tobacco smoke (SHS) exposure and AHRR methylation is unknown. METHODS: DNA methylation of AHRR cg05575921 in CD14+ monocyte samples, from 495 never-smokers and 411 former smokers (having quit smoking ≥15 years) from the Multi-Ethnic Study of Atherosclerosis (MESA), was cross-sectionally compared with concomitantly ascertained self-reported SHS exposure, urine cotinine concentrations, and estimates of air pollutants at participants' homes. Linear regression was used to test for associations, and covariates included age, sex, race, education, study site, and previous smoking exposure (smoking status, time since quitting, and pack-years). RESULTS: Recent indoor SHS exposure (hours per week) was inversely associated with cg05575921 methylation (ß ± SE = -0.009 ± 0.003, p = .007). The inverse effect direction was consistent (but did not reach significance) in the majority of stratified analyses (by smoking status, sex, and race). Categorical analysis revealed high levels of recent SHS exposure (≥10 hours per week) inversely associated with cg05575921 methylation (ß ± SE = -0.28 ± 0.09, p = .003), which remained significant (p < .05) in the majority of stratified analyses. cg05575921 methylation did not significantly (p < .05) associate with low to moderate levels of recent SHS exposure (1-9 hours per week), urine cotinine concentrations, years spent living with people smoking, years spent indoors (not at home) with people smoking, or estimated levels of air pollutants. CONCLUSIONS: High levels of recent indoor SHS exposure may be inversely associated with DNA methylation of AHRR in human monocytes. IMPLICATIONS: DNA methylation is a biochemical alteration that can occur in response to cigarette smoking; however, little is known about the effect of SHS on human DNA methylation. In the present study, we evaluated the association between SHS exposure and DNA methylation in human monocytes, at a site (AHRR cg05575921) known to have methylation inversely associated with current and former cigarette smoking compared to never smoking. Results from this study suggest high levels of recent SHS exposure inversely associate with DNA methylation of AHRR cg05575921 in monocytes from nonsmokers, albeit with weaker effects than active cigarette smoking.

DNA Methylation of the Aryl Hydrocarbon Receptor Repressor Associations With Cigarette Smoking and Subclinical Atherosclerosis.

BACKGROUND: Tobacco smoke contains numerous agonists of the aryl hydrocarbon receptor (AhR) pathway, and activation of the AhR pathway was shown to promote atherosclerosis in mice. Intriguingly, cigarette smoking is most strongly and robustly associated with DNA modifications to an AhR pathway gene, the AhR repressor (AHRR). We hypothesized that altered AHRR methylation in monocytes, a cell type sensitive to cigarette smoking and involved in atherogenesis, may be a part of the biological link between cigarette smoking and atherosclerosis. METHODS AND RESULTS: DNA methylation profiles of AHRR in monocytes (542 CpG sites ± 150 kb of AHRR, using Illumina 450K array) were integrated with smoking habits and ultrasound-measured carotid plaque scores from 1256 participants of the Multi-Ethnic Study of Atherosclerosis (MESA). Methylation of cg05575921 significantly associated (P=6.1 × 10(-134)) with smoking status (current versus never). Novel associations between cg05575921 methylation and carotid plaque scores (P=3.1 × 10(-10)) were identified, which remained significant in current and former smokers even after adjusting for self-reported smoking habits, urinary cotinine, and well-known cardiovascular disease risk factors. This association replicated in an independent cohort using hepatic DNA (n=141). Functionally, cg05575921 was located in a predicted gene expression regulatory element (enhancer) and had methylation correlated with AHRR mRNA profiles (P=1.4 × 10(-17)) obtained from RNA sequencing conducted on a subset (n=373) of the samples. CONCLUSIONS: These findings suggest that AHRR methylation may be functionally related to AHRR expression in monocytes and represents a potential biomarker of subclinical atherosclerosis in smokers.

Alterations of a Cellular Cholesterol Metabolism Network Are a Molecular Feature of Obesity-Related Type 2 Diabetes and Cardiovascular Disease.

Obesity is linked to type 2 diabetes (T2D) and cardiovascular diseases; however, the underlying molecular mechanisms remain unclear. We aimed to identify obesity-associated molecular features that may contribute to obesity-related diseases. Using circulating monocytes from 1,264 Multi-Ethnic Study of Atherosclerosis (MESA) participants, we quantified the transcriptome and epigenome. We discovered that alterations in a network of coexpressed cholesterol metabolism genes are a signature feature of obesity and inflammatory stress. This network included 11 BMI-associated genes related to sterol uptake (↑LDLR, ↓MYLIP), synthesis (↑SCD, FADS1, HMGCS1, FDFT1, SQLE, CYP51A1, SC4MOL), and efflux (↓ABCA1, ABCG1), producing a molecular profile expected to increase intracellular cholesterol. Importantly, these alterations were associated with T2D and coronary artery calcium (CAC), independent from cardiometabolic factors, including serum lipid profiles. This network mediated the associations between obesity and T2D/CAC. Several genes in the network harbored C-phosphorus-G dinucleotides (e.g., ABCG1/cg06500161), which overlapped Encyclopedia of DNA Elements (ENCODE)-annotated regulatory regions and had methylation profiles that mediated the associations between BMI/inflammation and expression of their cognate genes. Taken together with several lines of previous experimental evidence, these data suggest that alterations of the cholesterol metabolism gene network represent a molecular link between obesity/inflammation and T2D/CAC.

Transcriptomic profiles of aging in purified human immune cells.

BACKGROUND: Transcriptomic studies hold great potential towards understanding the human aging process. Previous transcriptomic studies have identified many genes with age-associated expression levels; however, small samples sizes and mixed cell types often make these results difficult to interpret. RESULTS: Using transcriptomic profiles in CD14+ monocytes from 1,264 participants of the Multi-Ethnic Study of Atherosclerosis (aged 55-94 years), we identified 2,704 genes differentially expressed with chronological age (false discovery rate, FDR ≤ 0.001). We further identified six networks of co-expressed genes that included prominent genes from three pathways: protein synthesis (particularly mitochondrial ribosomal genes), oxidative phosphorylation, and autophagy, with expression patterns suggesting these pathways decline with age. Expression of several chromatin remodeler and transcriptional modifier genes strongly correlated with expression of oxidative phosphorylation and ribosomal protein synthesis genes. 17% of genes with age-associated expression harbored CpG sites whose degree of methylation significantly mediated the relationship between age and gene expression (p < 0.05). Lastly, 15 genes with age-associated expression were also associated (FDR ≤ 0.01) with pulse pressure independent of chronological age. Comparing transcriptomic profiles of CD14+ monocytes to CD4+ T cells from a subset (n = 423) of the population, we identified 30 age-associated (FDR < 0.01) genes in common, while larger sets of differentially expressed genes were unique to either T cells (188 genes) or monocytes (383 genes). At the pathway level, a decline in ribosomal protein synthesis machinery gene expression with age was detectable in both cell types. CONCLUSIONS: An overall decline in expression of ribosomal protein synthesis genes with age was detected in CD14+ monocytes and CD4+ T cells, demonstrating that some patterns of aging are likely shared between different cell types. Our findings also support cell-specific effects of age on gene expression, illustrating the importance of using purified cell samples for future transcriptomic studies. Longitudinal work is required to establish the relationship between identified age-associated genes/pathways and aging-related diseases.

Penalized multimarker vs. single-marker regression methods for genome-wide association studies of quantitative traits.

The data from genome-wide association studies (GWAS) in humans are still predominantly analyzed using single-marker association methods. As an alternative to single-marker analysis (SMA), all or subsets of markers can be tested simultaneously. This approach requires a form of penalized regression (PR) as the number of SNPs is much larger than the sample size. Here we review PR methods in the context of GWAS, extend them to perform penalty parameter and SNP selection by false discovery rate (FDR) control, and assess their performance in comparison with SMA. PR methods were compared with SMA, using realistically simulated GWAS data with a continuous phenotype and real data. Based on these comparisons our analytic FDR criterion may currently be the best approach to SNP selection using PR for GWAS. We found that PR with FDR control provides substantially more power than SMA with genome-wide type-I error control but somewhat less power than SMA with Benjamini-Hochberg FDR control (SMA-BH). PR with FDR-based penalty parameter selection controlled the FDR somewhat conservatively while SMA-BH may not achieve FDR control in all situations. Differences among PR methods seem quite small when the focus is on SNP selection with FDR control. Incorporating linkage disequilibrium into the penalization by adapting penalties developed for covariates measured on graphs can improve power but also generate more false positives or wider regions for follow-up. We recommend the elastic net with a mixing weight for the Lasso penalty near 0.5 as the best method.

Age-related variations in the methylome associated with gene expression in human monocytes and T cells.

Age-related variations in DNA methylation have been reported; however, the functional relevance of these differentially methylated sites (age-dMS) are unclear. Here we report potentially functional age-dMS, defined as age- and cis-gene expression-associated methylation sites (age-eMS), identified by integrating genome-wide CpG methylation and gene expression profiles collected ex vivo from circulating T cells (227 CD4+ samples) and monocytes (1,264 CD14+ samples, age range: 55-94 years). None of the age-eMS detected in 227 T-cell samples are detectable in 1,264 monocyte samples, in contrast to the majority of age-dMS detected in T cells that replicated in monocytes. Age-eMS tend to be hypomethylated with older age, located in predicted enhancers and preferentially linked to expression of antigen processing and presentation genes. These results identify and characterize potentially functional age-related methylation in human T cells and monocytes, and provide novel insights into the role age-dMS may have in the aging process.

Methylomics of gene expression in human monocytes.

DNA methylation is one of several epigenetic mechanisms that contribute to the regulation of gene expression; however, the extent to which methylation of CpG dinucleotides correlates with gene expression at the genome-wide level is still largely unknown. Using purified primary monocytes from subjects in a large community-based cohort (n = 1264), we characterized methylation (>485 000 CpG sites) and mRNA expression (>48K transcripts) and carried out genome-wide association analyses of 8370 expression phenotypes. We identified 11 203 potential cis-acting CpG loci whose degree of methylation was associated with gene expression (eMS) at a false discovery rate threshold of 0.001. Most of the associations were consistent in effect size and direction of effect across sex and three ethnicities. Contrary to expectation, these eMS were not predominately enriched in promoter regions, or CpG islands, but rather in the 3' UTR, gene bodies, CpG shores or 'offshore' sites, and both positive and negative correlations between methylation and expression were observed across all locations. eMS were enriched for regions predicted to be regulatory by ENCODE (Encyclopedia of DNA Elements) data in multiple cell types, particularly enhancers. One of the strongest association signals detected (P < 2.2 × 10(-308)) was a methylation probe (cg17005068) in the promoter/enhancer region of the glutathione S-transferase theta 1 gene (GSTT1, encoding the detoxification enzyme) with GSTT1 mRNA expression. Our study provides a detailed description of the epigenetic architecture in human monocytes and its relationship to gene expression. These data may help prioritize interrogation of biologically relevant methylation loci and provide new insights into the epigenetic basis of human health and diseases.

Simulating systems genetics data with SysGenSIM.

SUMMARY: SysGenSIM is a software package to simulate Systems Genetics (SG) experiments in model organisms, for the purpose of evaluating and comparing statistical and computational methods and their implementations for analyses of SG data [e.g. methods for expression quantitative trait loci (eQTL) mapping and network inference]. SysGenSIM allows the user to select a variety of network topologies, genetic and kinetic parameters to simulate SG data ( genotyping, gene expression and phenotyping) with large gene networks with thousands of nodes. The software is encoded in MATLAB, and a user-friendly graphical user interface is provided. AVAILABILITY: The open-source software code and user manual can be downloaded at: http://sysgensim.sourceforge.net/ CONTACT: alf@crs4.it.

Sporadic breast cancer patients' germline DNA exhibit an AT-rich microsatellite signature.

Using a custom CGH-like oligonucleotide array to measure the global microsatellite content in the genomes of 72 cancer, cancer-free, and high risk patient and cell line samples (56 germline DNA and 16 in tumor or tumor cell line DNA) we found a unique, reproducible, and statistically significant pattern of 18 motif-specific microsatellite families (out of 962 possible 1-6 mer repeats) in breast cancer patient germline and tumor DNA, but not in germline DNA of cancer-free volunteer controls or in breast cancer patients with BRCA1/2 mutations. These high-similarity A/T rich repetitive motifs were also more pronounced in the germlines and tumors of colon cancer tumor patients (3/6 samples) and microsatellite unstable colon cancer cell lines; however, germline DNA of sporadic breast cancer patients exhibited the largest global content shift for those motifs with extreme AT/GC ratios. These results indicate that global microsatellite variability is complex, suggest the existence of a previously unknown genomic destabilization mechanism in breast cancer patients' germline DNA, and warrant further testing of such microsatellite variability as a predictor of future breast cancer development.

Nonparametric Bayesian variable selection with applications to multiple quantitative trait loci mapping with epistasis and gene-environment interaction.

The joint action of multiple genes is an important source of variation for complex traits and human diseases. However, mapping genes with epistatic effects and gene-environment interactions is a difficult problem because of relatively small sample sizes and very large parameter spaces for quantitative trait locus models that include such interactions. Here we present a nonparametric Bayesian method to map multiple quantitative trait loci (QTL) by considering epistatic and gene-environment interactions. The proposed method is not restricted to pairwise interactions among genes, as is typically done in parametric QTL analysis. Rather than modeling each main and interaction term explicitly, our nonparametric Bayesian method measures the importance of each QTL, irrespective of whether it is mostly due to a main effect or due to some interaction effect(s), via an unspecified function of the genotypes at all candidate QTL. A Gaussian process prior is assigned to this unknown function. In addition to the candidate QTL, nongenetic factors and covariates, such as age, gender, and environmental conditions, can also be included in the unspecified function. The importance of each genetic factor (QTL) and each nongenetic factor/covariate included in the function is estimated by a single hyperparameter, which enters the covariance function and captures any main or interaction effect associated with a given factor/covariate. An initial evaluation of the performance of the proposed method is obtained via analysis of simulated and real data.