Brian Thomas Joyce

Blood Epigenetic Age may Predict Cancer Incidence and Mortality

Biological measures of aging are important for understanding the health of an aging population, with epigenetics particularly promising. Previous studies found that tumor tissue is epigenetically older than its donors are chronologically. We examined whether blood Δage (the discrepancy between epigenetic and chronological ages) can predict cancer incidence or mortality, thus assessing its potential as a cancer biomarker. In a prospective cohort, Δage and its rate of change over time were calculated in 834 blood leukocyte samples collected from 442 participants free of cancer at blood draw. About 3–5 years before cancer onset or death, Δage was associated with cancer risks in a dose-responsive manner (P = 0.02) and a one-year increase in Δage was associated with cancer incidence (HR: 1.06, 95% CI: 1.02–1.10) and mortality (HR: 1.17, 95% CI: 1.07–1.28). Participants with smaller Δage and decelerated epigenetic aging over time had the lowest risks of cancer incidence (P = 0.003) and mortality (P = 0.02). Δage was associated with cancer incidence in a ‘J-shaped’ manner for subjects examined pre-2003, and with cancer mortality in a time-varying manner. We conclude that blood epigenetic age may mirror epigenetic abnormalities related to cancer development, potentially serving as a minimally invasive biomarker for cancer early detection.

Prospective changes in global DNA methylation and cancer incidence and mortality

Background:Methylation of repetitive elements Alu and LINE-1 in humans is considered a surrogate for global DNA methylation. Previous studies of blood-measured Alu/LINE-1 and cancer risk are inconsistent.Methods:We studied 1259 prospective methylation measurements from blood drawn 1–4 times from 583 participants from 1999 to 2012. We used Cox regression to evaluate time-dependent methylation as a biomarker for cancer risk and mortality, and linear regression to compare mean differences in methylation over time by cancer status and analyse associations between rate of methylation change and cancer.Results:Time-dependent LINE-1 methylation was associated with prostate cancer incidence (HR: 1.38, 95% CI: 1.01–1.88) and all-cancer mortality (HR: 1.41, 95% CI: 1.03–1.92). The first measurement of Alu methylation (HR: 1.39, 95% CI: 1.08–1.79) was associated with all-cancer mortality. Participants who ultimately developed cancer had lower mean LINE-1 methylation than cancer-free participants 10+ years pre-diagnosis (P<0.01). Rate of Alu methylation change was associated with all-cancer incidence (HR: 3.62, 95% CI: 1.09–12.10).Conclusions:Our results add longitudinal data on blood Alu and LINE-1 methylation and cancer, and potentially contribute to their use as early-detection biomarkers. Future larger studies are needed and should account for the interval between blood sample collection and cancer diagnosis.

Longitudinal Study of DNA Methylation of Inflammatory Genes and Cancer Risk

Background: Chronic inflammation plays a key role in cancer etiology. DNA methylation modification, one of the epigenetic mechanisms regulating gene expression, is considered a hallmark of cancer. Human and animal models have identified numerous links between DNA methylation and inflammatory biomarkers. Our objective was to prospectively and longitudinally examine associations between methylation of four inflammatory genes and cancer risk. Methods: We included 795 Normative Aging Study participants with blood drawn one to four times from 1999 to 2012 (median follow-up, 10.6 years). Promoter DNA methylation of IL6, ICAM-1, IFN, and TLR2 in blood leukocytes was measured using pyrosequencing at multiple CpG sites and averaged by gene for data analysis. We used Cox regression models to examine prospective associations of baseline and time-dependent methylation with cancer risk and compared mean methylation differences over time between cancer cases and cancer-free participants. Results: Baseline IFN hypermethylation was associated with all-cancer (HR, 1.49; P = 0.04) and prostate cancer incidence (HR, 1.69; P = 0.02). Baseline ICAM-1 and IL6 hypermethylation were associated with prostate cancer incidence (HR, 1.43; P = 0.02; HR, 0.70; P = 0.03, respectively). In our time-dependent analyses, IFN hypermethylation was associated with all-cancer (HR, 1.79; P = 0.007) and prostate cancer (HR, 1.57; P = 0.03) incidence; and ICAM-1 and IL6 hypermethylation were associated with prostate cancer incidence (HR, 1.39; P = 0.02; HR, 0.69; P = 0.03, respectively). We detected significant ICAM-1 hypermethylation in cancer cases (P = 0.0003) 10 to 13 years prediagnosis. Conclusion: Hypermethylation of IFN and ICAM-1 may play important roles in early carcinogenesis, particularly that of prostate cancer. Impact: These methylation changes could inform the development of early detection biomarkers and potential treatments of inflammation-related carcinogenesis. Cancer Epidemiol Biomarkers Prev; 24(10); 1531–8. ©2015 AACR.

Traffic-derived particulate matter exposure and histone H3 modification: A repeated measures study

Background: Airborne particulate matter (PM) may induce epigenetic changes that potentially lead to chronic diseases. Histone modifications regulate gene expression by influencing chromatin structure that can change gene expression status. We evaluated whether traffic‐derived PM exposure is associated with four types of environmentally inducible global histone H3 modifications. Methods: The Beijing Truck Driver Air Pollution Study included 60 truck drivers and 60 office workers examined twice, 1–2 weeks apart, for ambient PM10 (both day‐of and 14‐day average exposures), personal PM2.5, black carbon (BC), and elemental components (potassium, sulfur, iron, silicon, aluminum, zinc, calcium, and titanium). For both PM10 measures, we obtained hourly ambient PM10 data for the study period from the Beijing Municipal Environmental Bureaus 27 representatively distributed monitoring stations. We then calculated a 24 h average for each examination day and a moving average of ambient PM10 measured in the 14 days prior to each examination. Examinations measured global levels of H3 lysine 9 acetylation (H3K9ac), H3 lysine 9 tri‐methylation (H3K9me3), H3 lysine 27 tri‐methylation (H3K27me3), and H3 lysine 36 tri‐methylation (H3K36me3) in blood leukocytes collected after work. We used adjusted linear mixed‐effect models to examine percent changes in histone modifications per each &mgr;g/m3 increase in PM exposure. Results: In all participants each &mgr;g/m3 increase in 14‐day average ambient PM10 exposure was associated with lower H3K27me3 (&bgr;=−1.1%, 95% CI: −1.6, −0.6) and H3K36me3 levels (&bgr;=−0.8%, 95% CI: −1.4, −0.1). Occupation‐stratified analyses showed associations between BC and both H3K9ac and H3K36me3 that were stronger in office workers (&bgr;=4.6%, 95% CI: 0.9, 8.4; and &bgr;=4.1%, 95% CI: 1.3; 7.0 respectively) than in truck drivers (&bgr;=0.1%, 95% CI: −1.3, 1.5; and &bgr;=0.9%, 95% CI: −0.9, 2.7, respectively; both pinteraction <0.05). Sex‐stratified analyses showed associations between examination‐day PM10 and H3K9ac, and between BC and H3K9me3, were stronger in women (&bgr;=10.7%, 95% CI: 5.4, 16.2; and &bgr;=7.5%, 95% CI: 1.2, 14.2, respectively) than in men (&bgr;=1.4%, 95% CI: −0.9, 3.7; and &bgr;=0.9%, 95% CI: −0.9, 2.7, respectively; both pinteraction <0.05). We observed no associations between personal PM2.5 or elemental components and histone modifications. Conclusions: Our results suggest a possible role of global histone H3 modifications in effects of traffic‐derived PM exposures, particularly BC exposure. Future studies should assess the roles of these modifications in human diseases and as potential mediators of air pollution‐induced disease, in particular BC exposure. HighlightsWe assessed effects of PM exposures on histone H3 modification in human leukocyte.Traffic‐derived PM may induce short‐term changes in histone H3 modifications.Occupation and sex may modify effects of PM exposures on histone H3 modifications.

Blood pressure and expression of microRNAs in whole blood

Background Blood pressure (BP) is a complex, multifactorial clinical outcome driven by genetic susceptibility, behavioral choices, and environmental factors. Many molecular mechanisms have been proposed for the pathophysiology of high BP even as its prevalence continues to grow worldwide, increasing morbidity and marking it as a major public health concern. To address this, we evaluated miRNA profiling in blood leukocytes as potential biomarkers of BP and BP-related risk factors. Methods The Beijing Truck Driver Air Pollution Study included 60 truck drivers and 60 office workers examined in 2008. On two days separated by 1–2 weeks, we examined three BP measures: systolic, diastolic, and mean arterial pressure measured at both pre- and post-work exams for blood NanoString nCounter miRNA profiles. We used covariate-adjusted linear mixed-effect models to examine associations between BP and increased miRNA expression in both pooled and risk factor-stratified analyses. Results Overall 43 miRNAs were associated with pre-work BP (FDR<0.05). In stratified analyses different but overlapping groups of miRNAs were associated with pre-work BP in truck drivers, high-BMI participants, and usual alcohol drinkers (FDR<0.05). Only four miRNAs were associated with post-work BP (FDR<0.05), in ever smokers. Conclusion Our results suggest that many miRNAs were significantly associated with BP in subgroups exposed to known hypertension risk factors. These findings shed light on the underlying molecular mechanisms of BP, and may assist with the development of a miRNA panel for early detection of hypertension.

Prediction of genome-wide DNA methylation in repetitive elements

Abstract DNA methylation in repetitive elements (RE) suppresses their mobility and maintains genomic stability, and decreases in it are frequently observed in tumor and/or surrogate tissues. Averaging methylation across RE in genome is widely used to quantify global methylation. However, methylation may vary in specific RE and play diverse roles in disease development, thus averaging methylation across RE may lose significant biological information. The ambiguous mapping of short reads by and high cost of current bisulfite sequencing platforms make them impractical for quantifying locus-specific RE methylation. Although microarray-based approaches (particularly Illuminas Infinium methylation arrays) provide cost-effective and robust genome-wide methylation quantification, the number of interrogated CpGs in RE remains limited. We report a random forest-based algorithm (and corresponding R package, REMP) that can accurately predict genome-wide locus-specific RE methylation based on Infinium array profiling data. We validated its prediction performance using alternative sequencing and microarray data. Testing its clinical utility with The Cancer Genome Atlas data demonstrated that our algorithm offers more comprehensively extended locus-specific RE methylation information that can be readily applied to large human studies in a cost-effective manner. Our work has the potential to improve our understanding of the role of global methylation in human diseases, especially cancer.

Intervention thresholds: a conceptual frame for advance care planning choices

BackgroundAdvance care planning (ACP) provides for decisions in the event of decisional incapacity. Determining ahead of time what a person may want is challenging and limits the utility of ACP. We present empirical evidence for a new approach to ACP: the individual’s “intervention threshold.” The intervention threshold is intuitively understood by clinicians and lay people, but has not been thoroughly described, measured, or analyzed.MethodsUsing a mixed-methods approach to address the concept of the intervention thresholds, we recruited 52 subjects from a population of chronically ill outpatients for structured telephone interviews assessing knowledge, attitudes, and prior ACP activities. Respondents were presented with 11 interventions for each of four medical scenarios. For each scenario, they were asked whether they would accept each intervention. Data was evaluated by descriptive statistics and chi-squared statistics.ResultsComplete data were obtained from 52 patients, mean age of 64.5, 34.6% of whom were male. Only 17.3% reported prior ACP discussion with a physician. Rates of accepting and refusing interventions varied by scenario (p < 0.0001) and intervention intensity (p < 0.0001).ConclusionsThese data provide evidence that people display transitions between wanting or not wanting interventions based on scenarios. Further research is needed to determine effective ways to identify, measure, and represent the components of an individual’s intervention threshold in order to facilitate informed decision making during future incapacity.

Regularized estimation in sparse high-dimensional multivariate regression, with application to a DNA methylation study

Abstract In this article, we consider variable selection for correlated high dimensional DNA methylation markers as multivariate outcomes. A novel weighted square-root LASSO procedure is proposed to estimate the regression coefficient matrix. A key feature of this method is tuning-insensitivity, which greatly simplifies the computation by obviating cross validation for penalty parameter selection. A precision matrix obtained via the constrained ℓ1 minimization method is used to account for the within-subject correlation among multivariate outcomes. Oracle inequalities of the regularized estimators are derived. The performance of our proposed method is illustrated via extensive simulation studies. We apply our method to study the relation between smoking and high dimensional DNA methylation markers in the Normative Aging Study (NAS).

MicroRNA Expression in Ethnic Specific Early Stage Breast Cancer: An Integration and Comparative Analysis

Breast cancer (BC) has a higher incidence in young Lebanese woman as compared to the West. We assessed the microRNA (miRNA) microarray profile of tissues derived from Lebanese patients with early BC and performed mRNA-miRNA integration analysis. 173 miRNAs were significantly dysregulated in 45 BC versus 17 normal adjacent breast tissues, including 74 with a fold change more than two of which 17 were never reported before in cancer. Integration analysis of mRNA-miRNA microarray data revealed a potential role of 51 dysregulated miRNA regulating 719 tumor suppressive or oncogenic mRNA associated with increased proliferation and decreased migration and invasion. We then performed a comparative miRNA microarray profile analysis of BC tissue between these 45 Lebanese and 197 matched American BC patients. Notably, Lebanese BC patients had 21 exclusively dysregulated miRNA (e.g. miR-31, 362-3p, and 663) and 4 miRNA with different expression manner compared to American patients (e.g. miR-1288-star and 324-3p). Some of these differences could reflect variation in patient age at diagnosis or ethnic variation affecting miRNA epigenetic regulation or sequence of miRNA precursors. Our data provide a basis for genetic/epigenetic investigations to explore the role of miRNA in early stage BC in young women, including ethnic specific differences.

Ultra-high dimensional variable selection with application to normative aging study: DNA methylation and metabolic syndrome

BackgroundMetabolic syndrome has become a major public health challenge worldwide. The association between metabolic syndrome and DNA methylation is of great research interest.ResultsWe constructed a binomial model to investigate the association between a metabolic syndrome index and DNA methylation in the Normative Aging Study. We applied the Iterative Sure Independence Screening (ISIS) method with elastic net penalty to DNA methylation levels at 484,548 CpG markers from 659 human subjects, and demonstrated that the screening step in ISIS can significantly improve the performance of the elastic net.ConclusionThe proposed method identifies four CpGs which can be mapped to two biologically relevant and functional genes. Identification of significant CpG markers may potentially have practical implications for disease prevention and treatment.