Accelerated biological aging six decades after prenatal famine exposure.

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N=951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944-5, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

Evaluation of commonly used analysis strategies for epigenome- and transcriptome-wide association studies through replication of large-scale population studies.

BACKGROUND: A large number of analysis strategies are available for DNA methylation (DNAm) array and RNA-seq datasets, but it is unclear which strategies are best to use. We compare commonly used strategies and report how they influence results in large cohort studies. RESULTS: We tested the associations of DNAm and RNA expression with age, BMI, and smoking in four different cohorts (n = ~ 2900). By comparing strategies against the base model on the number and percentage of replicated CpGs for DNAm analyses or genes for RNA-seq analyses in a leave-one-out cohort replication approach, we find the choice of the normalization method and statistical test does not strongly influence the results for DNAm array data. However, adjusting for cell counts or hidden confounders substantially decreases the number of replicated CpGs for age and increases the number of replicated CpGs for BMI and smoking. For RNA-seq data, the choice of the normalization method, gene expression inclusion threshold, and statistical test does not strongly influence the results. Including five principal components or excluding correction of technical covariates or cell counts decreases the number of replicated genes. CONCLUSIONS: Results were not influenced by the normalization method or statistical test. However, the correction method for cell counts, technical covariates, principal components, and/or hidden confounders does influence the results.

Smoking is Associated to DNA Methylation in Atherosclerotic Carotid Lesions.

BACKGROUND: Tobacco smoking is a major risk factor for atherosclerotic disease and has been associated with DNA methylation (DNAm) changes in blood cells. However, whether smoking influences DNAm in the diseased vascular wall is unknown but may prove crucial in understanding the pathophysiology of atherosclerosis. In this study, we associated current tobacco smoking to epigenome-wide DNAm in atherosclerotic plaques from patients undergoing carotid endarterectomy. METHODS: DNAm at commonly methylated sites (cytosine-guanine nucleotide pairs separated by a phospho-group [CpGs]) was assessed in atherosclerotic plaque samples and peripheral blood samples from 485 carotid endarterectomy patients. We tested the association of current tobacco smoking with DNAm corrected for age and sex. To control for bias and inflation because of cellular heterogeneity, we applied a Bayesian method to estimate an empirical null distribution as implemented by the R package bacon. Replication of the smoking-associated methylated CpGs in atherosclerotic plaques was executed in the second sample of 190 carotid endarterectomy patients, and results were meta-analyzed using a fixed-effects model. RESULTS: Tobacco smoking was significantly associated to differential DNAm in atherosclerotic lesions of 4 CpGs (false discovery rate <0.05) mapped to 2 different genes ( AHRR, ITPK1) and 17 CpGs mapped to 8 genes and RNAs in blood. The strongest associations were found for CpGs mapped to the gene AHRR, a repressor of the aryl hydrocarbon receptor transcription factor involved in xenobiotic detoxification. One of these methylated CpGs were found to be regulated by local genetic variation. CONCLUSIONS: The risk factor tobacco smoking associates with DNAm at multiple loci in carotid atherosclerotic lesions. These observations support further investigation of the relationship between risk factors and epigenetic regulation in atherosclerotic disease.

SMCHD1 regulates a limited set of gene clusters on autosomal chromosomes.

BACKGROUND: Facioscapulohumeral muscular dystrophy (FSHD) is in most cases caused by a contraction of the D4Z4 macrosatellite repeat on chromosome 4 (FSHD1) or by mutations in the SMCHD1 or DNMT3B gene (FSHD2). Both situations result in the incomplete epigenetic repression of the D4Z4-encoded retrogene DUX4 in somatic cells, leading to the aberrant expression of DUX4 in the skeletal muscle. In mice, Smchd1 regulates chromatin repression at different loci, having a role in CpG methylation establishment and/or maintenance. METHODS: To investigate the global effects of harboring heterozygous SMCHD1 mutations on DNA methylation in humans, we combined 450k methylation analysis on mononuclear monocytes from female heterozygous SMCHD1 mutation carriers and unaffected controls with reduced representation bisulfite sequencing (RRBS) on FSHD2 and control myoblast cell lines. Candidate loci were then evaluated for SMCHD1 binding using ChIP-qPCR and expression was evaluated using RT-qPCR. RESULTS: We identified a limited number of clustered autosomal loci with CpG hypomethylation in SMCHD1 mutation carriers: the protocadherin (PCDH) cluster on chromosome 5, the transfer RNA (tRNA) and 5S rRNA clusters on chromosome 1, the HOXB and HOXD clusters on chromosomes 17 and 2, respectively, and the D4Z4 repeats on chromosomes 4 and 10. Furthermore, minor increases in RNA expression were seen in FSHD2 myoblasts for some of the PCDHß cluster isoforms, tRNA isoforms, and a HOXB isoform in comparison to controls, in addition to the previously reported effects on DUX4 expression. SMCHD1 was bound at DNAseI hypersensitivity sites known to regulate the PCDHß cluster and at the chromosome 1 tRNA cluster, with decreased binding in SMCHD1 mutation carriers at the PCDHß cluster sites. CONCLUSIONS: Our study is the first to investigate the global methylation effects in humans resulting from heterozygous mutations in SMCHD1. Our results suggest that SMCHD1 acts as a repressor on a limited set of autosomal gene clusters, as an observed reduction in methylation associates with a loss of SMCHD1 binding and increased expression for some of the loci.

Epigenomic Analysis of Sézary Syndrome Defines Patterns of Aberrant DNA Methylation and Identifies Diagnostic Markers.

Sézary syndrome (Sz) is a malignancy of skin-homing CD4(+) memory T cells that is clinically characterized by erythroderma, lymphadenopathy, and blood involvement. Distinction of Sz from erythroderma secondary to inflammatory skin diseases (erythrodermic inflammatory dermatosis [EID]) is often challenging. Recent studies identified recurrent mutations in epigenetic enzymes involved in DNA modification in Sz. Here we defined the DNA methylomes of purified CD4(+) T cells from patients with Sz, EID, and healthy control subjects. Sz showed extensive global DNA methylation alterations, with 7.8% of 473,921 interrogated autosomal CpG sites showing hypomethylation and 3.2% hypermethylation. Promoter CpG islands were markedly enriched for hypermethylation. The 126 genes with recurrent promoter hypermethylation in Sz included multiple candidate tumor suppressors that showed transcriptional repression, implicating aberrant methylation in the pathogenesis of Sz. Validation in an independent sample set showed promoter hypermethylation of CMTM2, C2orf40, G0S2, HSPB6, PROM1, and PAM in 94-100% of Sz samples but not in EID samples. Notably, promoter hypermethylation of a single gene, the chemokine-like factor CMTM2, was sufficient to accurately distinguish Sz from EID in all cases. This study shows that Sz is characterized by widespread yet distinct DNA methylation alterations, which can be used clinically as epigenetic diagnostic markers.

Developmental programming: State-of-the-science and future directions-Summary from a Pennington Biomedical symposium.

OBJECTIVE: On December 8-9, 2014, the Pennington Biomedical Research Center convened a scientific symposium to review the state-of-the-science and future directions for the study of developmental programming of obesity and chronic disease. The objectives of the symposium were to discuss: (i) past and current scientific advances in animal models, population-based cohort studies, and human clinical trials, (ii) the state-of-the-science of epigenetic-based research, and (iii) considerations for future studies. RESULTS: This symposium provided a comprehensive assessment of the state of the scientific field and identified research gaps and opportunities for future research in order to understand the mechanisms contributing to the developmental programming of health and disease. CONCLUSIONS: Identifying the mechanisms which cause or contribute to developmental programming of future generations will be invaluable to the scientific and medical community. The ability to intervene during critical periods of prenatal and early postnatal life to promote lifelong health is the ultimate goal. Considerations for future research including the use of animal models, the study design in human cohorts with considerations about the timing of the intrauterine exposure, and the resulting tissue-specific epigenetic signature were extensively discussed and are presented in this meeting summary.

Meta-analysis on blood transcriptomic studies identifies consistently coexpressed protein-protein interaction modules as robust markers of human aging.

The bodily decline that occurs with advancing age strongly impacts on the prospects for future health and life expectancy. Despite the profound role of age in disease etiology, knowledge about the molecular mechanisms driving the process of aging in humans is limited. Here, we used an integrative network-based approach for combining multiple large-scale expression studies in blood (2539 individuals) with protein-protein Interaction (PPI) data for the detection of consistently coexpressed PPI modules that may reflect key processes that change throughout the course of normative aging. Module detection followed by a meta-analysis on chronological age identified fifteen consistently coexpressed PPI modules associated with chronological age, including a highly significant module (P = 3.5 × 10(-38)) enriched for 'T-cell activation' marking age-associated shifts in lymphocyte blood cell counts (R(2) = 0.603; P = 1.9 × 10(-10)). Adjusting the analysis in the compendium for the 'T-cell activation' module showed five consistently coexpressed PPI modules that robustly associated with chronological age and included modules enriched for 'Translational elongation', 'Cytolysis' and 'DNA metabolic process'. In an independent study of 3535 individuals, four of five modules consistently associated with chronological age, underpinning the robustness of the approach. We found three of five modules to be significantly enriched with aging-related genes, as defined by the GenAge database, and association with prospective survival at high ages for one of the modules including ASF1A. The hereby-detected age-associated and consistently coexpressed PPI modules therefore may provide a molecular basis for future research into mechanisms underlying human aging.

Integrating protein-protein interaction networks with gene-gene co-expression networks improves gene signatures for classifying breast cancer metastasis.

Multiple studies have illustrated that gene expression profiling of primary breast cancers throughout the final stages of tumor development can provide valuable markers for risk prediction of metastasis and disease sub typing. However, the identification of a biologically interpretable and universally shared set of markers proved to be difficult. Here, we propose a method for de novo grouping of genes by dissecting the protein-protein interaction network into disjoint sub networks using pair wise gene expression correlation measures. We show that the obtained sub networks are functionally coherent and are consistently identified when applied on a compendium composed of six different breast cancer studies. Application of the proposed method using different integration approaches underlines the robustness of the identified sub network related to cell cycle and identifies putative new sub network markers for metastasis related to cell-cell adhesion, the proteasome complex and JUN-FOS signalling. Although gene selection with the proposed method does not directly improve upon previously reported cross study classification performances, it shows great promises for applications in data integration and result interpretation.

Evidence of genetic effects on blood lead concentration.

BACKGROUND: Lead is an environmental pollutant that causes acute and chronic toxicity. Surveys have related mean blood lead concentrations to exogenous sources, including industrial activity, use of lead-based paints, or traffic density. However, there has been little investigation of individual differences in lead absorption, distribution, or toxicity, or of genetic causes of such variation. OBJECTIVES: We assessed the genetic contribution to variation in blood lead concentration in adults and conducted a preliminary search for genes producing such variation. METHODS: Erythrocyte lead concentration was measured by inductively coupled plasma mass spectrometry in venous blood samples from 2,926 Australian adult male and female twins. Mean lead concentrations were compared by place of residence, social class and education, and by the subjects' age, sex, alcohol intake, smoking habits, iron status, and HFE genotype. RESULTS: After adjustment for these covariates, there was strong evidence of genetic effects but not for shared environmental effects persisting into adult life. Linkage analysis showed suggestive evidence (logarithm of odds = 2.63, genome-wide p = 0.170) for a quantitative trait locus affecting blood lead values on chromosome 3 with the linkage peak close to SLC4A7, a gene whose product affects lead transport. CONCLUSIONS: We conclude that genetic variation plays a significant role in determining lead absorption, lead distribution within the body, or both.

Efficacy and toxicity of methotrexate in early rheumatoid arthritis are associated with single-nucleotide polymorphisms in genes coding for folate pathway enzymes.

OBJECTIVE: To determine associations of methotrexate (MTX) efficacy and toxicity with single-nucleotide polymorphisms (SNPs) in genes coding for folate pathway enzymes in patients with early rheumatoid arthritis (RA). METHODS: Patients (n=205) with active RA received MTX at an initial dosage of 7.5 mg/week, which was increased to 15 mg/week and combined with folic acid (1 mg/day) after 4 weeks. If the Disease Activity Score in 44 joints (DAS44) was >2.4 at 3 months, MTX was increased to 25 mg/week. MTX efficacy was evaluated at 3 and 6 months and compared for genotypes in 3 analyses: patients with and without good response (DAS441.2), and patients with and without moderate improvement (DeltaDAS44>0.6). The association between MTX-related adverse drug events (ADEs) and genotype was evaluated by comparing genotypes between patients with and without ADEs, specifically pneumonitis, gastrointestinal ADEs, skin and mucosal ADEs, and elevated liver enzyme levels. The following SNPs were analyzed: methylenetetrahydrofolate reductase (MTHFR) 677C>T, MTHFR 1298A>C, dihydrofolate reductase (DHFR) -473G>A, DHFR 35289G>A, and reduced folate carrier 80G>A. In case of significant differences, odds ratios (ORs) were calculated. RESULTS: At 6 months, MTHFR 1298AA was associated with good improvement relative to 1298C (OR 2.3, 95% confidence interval [95% CI] 1.18-4.41), which increased with increased copies of the MTHFR 677CC haplotype. In contrast, MTHFR 1298C allele carriers developed more ADEs (OR 2.5, 95% CI 1.32-4.72). CONCLUSION: Patients with MTHFR 1298AA and MTHFR 677CC showed greater clinical improvement with MTX, whereas only the MTHFR 1298C allele was associated with toxicity. In the future, MTHFR genotypes may help determine which patients will benefit most from MTX treatment.