The association between toenail metals and extracellular MicroRNAs (ex-miRNAs) among the participants of the Normative Aging study (NAS).

BACKGROUND: Mechanistic studies of the effects of environmental risk factors have been exploring the potential role of microRNA(miRNAs) as a possible pathway to clinical disease. In this study we examine whether levels of toenail metals are associated with changes in extracellular miRNA(ex-miRNA) expression. METHODS: We used data derived from the Normative Aging Study from 1996 to 2014 to conduct our analyses. We looked at associations between measured toenail metals: arsenic, cadmium, lead, manganese, and mercury and 282 ex-miRNAs in this population using canonical correlation analyses (CCAs) and longitudinal median regression. We adjusted for covariates such as age, education, body mass index, drinking and smoking behaviors, diabetes, and where available, seafood consumption. The p-values obtained from regression analyses were corrected for multiple comparisons. Ex-miRNAs identified to be associated with toenail metal levels were further examined using pathway analyses. RESULTS: Our dataset included 937 observations from 589 men with an average age of 72.9 years at baseline. Both our correlation and regression analyses identified lead and cadmium as exposures most strongly associated with ex-miRNA expression. Numerous ex-miRNAs were identified as being associated with toenail metal levels. miR-27b-3p, in particular, was found to have high correlation with the first canonical dimension in the CCA and was significantly associated with cadmium in the regression analysis. Pathway analyses revealed messenger RNA (mRNA) targets for the ex-miRNAs that were associated with a number of clinical disorders including cancer, cardiovascular disease, and neurological disorders, etc. CONCLUSION: Toenail metals were associated with changes in ex-miRNA levels in both correlational and regression analyses. The ex-miRNAs identified can be linked to a variety of clinical disorders. Further studies are required to validate these findings.

Extracellular Vesicle-Encapsulated microRNAs as Novel Biomarkers of Lung Health.

Rationale: Early detection of respiratory diseases is critical to facilitate delivery of disease-modifying interventions. Extracellular vesicle-enriched microRNAs (EV-miRNAs) may represent reliable markers of early lung injury. Objectives: Evaluate associations of plasma EV-miRNAs with lung function. Methods: The prospective NAS (Normative Aging Study) collected plasma EV-miRNA measurements from 1996-2015 and spirometry every 3-5 years through 2019. Associations of EV-miRNAs with baseline lung function were modeled using linear regression. To complement the individual miRNA approach, unsupervised machine learning was used to identify clusters of participants with distinct EV-miRNA profiles. Associations of EV-miRNA profiles with multivariate latent longitudinal lung function trajectories were modeled using log binomial regression. Biological functions of significant EV-miRNAs were explored using pathway analyses. Results were replicated in an independent sample of NAS participants and in the HEALS (Health Effects of Arsenic Longitudinal Study). Measurements and Main Results: In the main cohort of 656 participants, 51 plasma EV-miRNAs were associated with baseline lung function (false discovery rate-adjusted P value < 0.05), 28 of which were replicated in the independent NAS sample and/or in the HEALS cohort. A subset of participants with distinct EV-miRNA expression patterns had increased risk of declining lung function over time, which was replicated in the independent NAS sample. Significant EV-miRNAs were shown in pathway analyses to target biological pathways that regulate respiratory cellular immunity, the lung inflammatory response, and airway structural integrity. Conclusions: Plasma EV-miRNAs may represent a robust biomarker of subclinical lung injury and may facilitate early identification and treatment of patients at risk of developing overt lung disease.

Cohort Network: A Knowledge Graph toward Data Dissemination and Knowledge-Driven Discovery for Cohort Studies.

Contemporary environmental health sciences draw on large-scale longitudinal studies to understand the impact of environmental exposures and behavior factors on the risk of disease and identify potential underlying mechanisms. In such studies, cohorts of individuals are assembled and followed up over time. Each cohort generates hundreds of publications, which are typically neither coherently organized nor summarized, hence limiting knowledge-driven dissemination. Hence, we propose a Cohort Network, a multilayer knowledge graph approach to extract exposures, outcomes, and their connections. We applied the Cohort Network on 121 peer-reviewed papers published over the past 10 years from the Veterans Affairs (VA) Normative Aging Study (NAS). The Cohort Network visualized connections between exposures and outcomes across different publications and identified key exposures and outcomes, such as air pollution, DNA methylation, and lung function. We demonstrated the utility of the Cohort Network for new hypothesis generation, e.g., identification of potential mediators of exposure-outcome associations. The Cohort Network can be used by investigators to summarize the cohort's research and facilitate knowledge-driven discovery and dissemination.

Intermediate and long-term exposure to air pollution and temperature and the extracellular microRNA profile of participants in the normative aging study (NAS).

BACKGROUND: The molecular effects of intermediate and long-term exposure to air pollution and temperature, such as those on extracellular microRNA (ex-miRNA) are not well understood but may have clinical consequences. OBJECTIVES: To assess the association between exposure to ambient air pollution and temperature and ex-miRNA profiles. METHODS: Our study population consisted of 734 participants in the Normative Aging Study (NAS) between 1999 and 2015. We used high-resolution models to estimate four-week, eight-week, twelve-week, six-month, and one-year moving averages of PM2.5, O3, NO2, and ambient temperature based on geo-coded residential addresses. The outcome of interest was the extracellular microRNA (ex-miRNA) profile of each participant over time. We used a longitudinal quantile regression approach to estimate the association between the exposures and each ex-miRNA. Results were corrected for multiple comparisons and ex-miRNAs that were still significantly associated with the exposures were further analyzed using KEGG pathway analysis and Ingenuity Pathway Analysis. RESULTS: We found 151 significant associations between levels of PM2.5, O3, NO2, and ambient temperature and 82 unique ex-miRNAs across multiple quantiles. Most of the significant results were associations with intermediate-term exposure to O3, long-term exposure to PM2.5, and both intermediate and long-term exposure to ambient temperature. The exposures were most often associated with the 75th and 90th percentile of the outcomes. Pathway analyses of significant ex-miRNAs revealed their involvement in biological pathways involving cell function and communication as well as clinical diseases such as cardiovascular disease, respiratory disease, and neurological disease. CONCLUSION: Our results show that intermediate and long-term exposure to all our exposures of interest were associated with changes in the ex-miRNA profile of study participants. Further studies on environmental risk factors and ex-miRNAs are warranted.

Pulmonary Function and Blood DNA Methylation: A Multiancestry Epigenome-Wide Association Meta-analysis.

Rationale: Methylation integrates factors present at birth and modifiable across the lifespan that can influence pulmonary function. Studies are limited in scope and replication. Objectives: To conduct large-scale epigenome-wide meta-analyses of blood DNA methylation and pulmonary function. Methods: Twelve cohorts analyzed associations of methylation at cytosine-phosphate-guanine probes (CpGs), using Illumina 450K or EPIC/850K arrays, with FEV1, FVC, and FEV1/FVC. We performed multiancestry epigenome-wide meta-analyses (total of 17,503 individuals; 14,761 European, 2,549 African, and 193 Hispanic/Latino ancestries) and interpreted results using integrative epigenomics. Measurements and Main Results: We identified 1,267 CpGs (1,042 genes) differentially methylated (false discovery rate, <0.025) in relation to FEV1, FVC, or FEV1/FVC, including 1,240 novel and 73 also related to chronic obstructive pulmonary disease (1,787 cases). We found 294 CpGs unique to European or African ancestry and 395 CpGs unique to never or ever smokers. The majority of significant CpGs correlated with nearby gene expression in blood. Findings were enriched in key regulatory elements for gene function, including accessible chromatin elements, in both blood and lung. Sixty-nine implicated genes are targets of investigational or approved drugs. One example novel gene highlighted by integrative epigenomic and druggable target analysis is TNFRSF4. Mendelian randomization and colocalization analyses suggest that epigenome-wide association study signals capture causal regulatory genomic loci. Conclusions: We identified numerous novel loci differentially methylated in relation to pulmonary function; few were detected in large genome-wide association studies. Integrative analyses highlight functional relevance and potential therapeutic targets. This comprehensive discovery of potentially modifiable, novel lung function loci expands knowledge gained from genetic studies, providing insights into lung pathogenesis.

Metabolomic differences in lung function metrics: evidence from two cohorts.

RATIONALE: The biochemical mechanisms underlying lung function are incompletely understood. OBJECTIVES: To identify and validate the plasma metabolome of lung function using two independent adult cohorts: discovery-the European Prospective Investigation into Cancer-Norfolk (EPIC-Norfolk, n=10 460) and validation-the VA Normative Aging Study (NAS) metabolomic cohort (n=437). METHODS: We ran linear regression models for 693 metabolites to identify associations with forced expiratory volume in one second (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC), in EPIC-Norfolk then validated significant findings in NAS. Significance in EPIC-Norfolk was denoted using an effective number of tests threshold of 95%; a metabolite was considered validated in NAS if the direction of effect was consistent and p<0.05. MEASUREMENTS AND MAIN RESULTS: Of 156 metabolites that associated with FEV1 in EPIC-Norfolk after adjustment for age, sex, body mass index, height, smoking and asthma status, 34 (21.8%) validated in NAS, including several metabolites involved in oxidative stress. When restricting the discovery sample to men only, a similar percentage, 18 of 79 significant metabolites (22.8%) were validated. A smaller number of metabolites were validated for FEV1/FVC, 6 of 65 (9.2%) when including all EPIC-Norfolk as the discovery population, and 2 of 34 (5.9%) when restricting to men. These metabolites were characterised by involvement in respiratory track secretants. Interestingly, no metabolites were validated for both FEV1 and FEV1/FVC. CONCLUSIONS: The validation of metabolites associated with respiratory function can help to better understand mechanisms of lung health and may assist the development of biomarkers.

Associations between solar and geomagnetic activity and peripheral white blood cells in the Normative Aging Study.

It has been hypothesized that solar and geomagnetic activity can affect the function of the autonomic nervous system (ANS) and melatonin secretion, both of which may influence immune response. We investigated the association between solar geomagnetic activity and white blood cell counts in the Normative Aging Study (NAS) Cohort between 2000 and 2013. Linear mixed effects models with moving day averages ranging from 0 to 28 days were used to evaluate the effects of solar activity measures, interplanetary magnetic field (IMF), and sunspot number (SSN), and a measure of geomagnetic activity, K Index (K), on total white blood cell (WBC), neutrophil, monocytes, lymphocyte, eosinophil, and basophil concentrations. After adjusting for demographic and health-related factors, there were consistently significant associations between IMF, SSN, and Kp index, with reductions in total WBC, neutrophils, and basophil counts. These associations were stronger with longer moving averages. The associations were similar after adjusting for ambient air particulate pollution and particle radioactivity. Our findings suggest that periods of increased solar and geomagnetic activity result in lower WBC, neutrophil, and basophil counts that may contribute to mil mild immune suppression.

Gaseous air pollutants and DNA methylation in a methylome-wide association study of an ethnically and environmentally diverse population of U.S. adults.

Epigenetic mechanisms may underlie air pollution-health outcome associations. We estimated gaseous air pollutant-DNA methylation (DNAm) associations using twelve subpopulations within Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) cohorts (n = 8397; mean age 61.3 years; 83% female; 46% African-American, 46% European-American, 8% Hispanic/Latino). We used geocoded participant address-specific mean ambient carbon monoxide (CO), nitrogen oxides (NO2; NOx), ozone (O3), and sulfur dioxide (SO2) concentrations estimated over the 2-, 7-, 28-, and 365-day periods before collection of blood samples used to generate Illumina 450 k array leukocyte DNAm measurements. We estimated methylome-wide, subpopulation- and race/ethnicity-stratified pollutant-DNAm associations in multi-level, linear mixed-effects models adjusted for sociodemographic, behavioral, meteorological, and technical covariates. We combined stratum-specific estimates in inverse variance-weighted meta-analyses and characterized significant associations (false discovery rate; FDR<0.05) at Cytosine-phosphate-Guanine (CpG) sites without among-strata heterogeneity (PCochran's Q > 0.05). We attempted replication in the Cooperative Health Research in Region of Augsburg (KORA) study and Normative Aging Study (NAS). We observed a -0.3 (95% CI: -0.4, -0.2) unit decrease in percent DNAm per interquartile range (IQR, 7.3 ppb) increase in 28-day mean NO2 concentration at cg01885635 (chromosome 3; regulatory region 290 bp upstream from ZNF621; FDR = 0.03). At intragenic sites cg21849932 (chromosome 20; LIME1; intron 3) and cg05353869 (chromosome 11; KLHL35; exon 2), we observed a -0.3 (95% CI: -0.4, -0.2) unit decrease (FDR = 0.04) and a 1.2 (95% CI: 0.7, 1.7) unit increase (FDR = 0.04), respectively, in percent DNAm per IQR (17.6 ppb) increase in 7-day mean ozone concentration. Results were not fully replicated in KORA and NAS. We identified three CpG sites potentially susceptible to gaseous air pollution-induced DNAm changes near genes relevant for cardiovascular and lung disease. Further harmonized investigations with a range of gaseous pollutants and averaging durations are needed to determine the effect of gaseous air pollutants on DNA methylation and ultimately gene expression.

Metabolomic signatures of the short-term exposure to air pollution and temperature.

BACKGROUND: Short-term exposures to air pollution and temperature have been reported to be associated with inflammation and oxidative stress. However, mechanistic understanding of the affected metabolic pathways is still lacking and literature on the short-term exposure of air-pollution on the metabolome is limited. OBJECTIVES: We aimed to determine changes in the plasma metabolome and associated metabolic pathways related to short-term exposure to outdoor air pollution and temperature. METHODS: We performed mass-spectrometry based untargeted metabolomic profiling of plasma samples from a large and well-characterized cohort of men (Normative Aging Study) to identify metabolic pathways associated with short-term exposure to PM2.5, NO2, O3, and temperature (one, seven-, and thirty-day average of address-specific predicted estimates). We used multivariable linear mixed-effect regression and independent component analysis (ICA) while simultaneously adjusting for all exposures and correcting for multiple testing. RESULTS: Overall, 456 white men provided 648 blood samples, in which 1158 metabolites were quantified, between 2000 and 2016. Average age and body mass index were 75.0 years and 27.7 kg/m2, respectively. Only 3% were current smokers. In the adjusted models, NO2, and temperature showed statistically significant associations with several metabolites (19 metabolites for NO2 and 5 metabolites for temperature). We identified six metabolic pathways (sphingolipid, butanoate, pyrimidine, glycolysis/gluconeogenesis, propanoate, and pyruvate metabolisms) perturbed with short-term exposure to air pollution and temperature. These pathways were involved in inflammation and oxidative stress, immunity, and nucleic acid damage and repair. CONCLUSIONS: This is the first study to report an untargeted metabolomic signature of temperature exposure, the largest to report an untargeted metabolomic signature of air pollution, and the first to use ICA. We identified several significant plasma metabolites and metabolic pathways associated with short-term exposure to air pollution and temperature; using an untargeted approach. Those pathways were involved in inflammation and oxidative stress, immunity, and nucleic acid damage and repair. These results need to be confirmed by future research.

Metabolomic signatures of the long-term exposure to air pollution and temperature.

BACKGROUND: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood. OBJECTIVES: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature. METHODS: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM2.5, NO2, O3, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures. RESULTS: Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m2. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM2.5, 15 metabolites with NO2, and 6 metabolites with temperature) while no metabolites were associated with O3. One out of five ICA factors (factor 2) was significantly associated with PM2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM2.5 and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair. CONCLUSIONS: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM2.5, NO2 and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.

Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation.

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p < 1.6 × 10-3). The replicated methylation sites are heritable (h2 > 30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

The Role of Ambient Particle Radioactivity in Inflammation and Endothelial Function in an Elderly Cohort.

BACKGROUND: The mechanisms by which exposure to particulate matter might increase risk of cardiovascular morbidity and mortality are not fully known. However, few existing studies have investigated the potential role of particle radioactivity. Naturally occurring radionuclides attach to particulate matter and continue to release ionizing radiation after inhalation and deposition in the lungs. We hypothesize that exposure to particle radioactivity increases biomarkers of inflammation. METHODS: Our repeated-measures study included 752 men in the greater Boston area. We estimated regional particle radioactivity as a daily spatial average of gross beta concentrations from five monitors in the study area. We used linear mixed-effects regression models to estimate short- and medium-term associations between particle radioactivity and biomarkers of inflammation and endothelial dysfunction, with and without adjustment for additional particulate air pollutants. RESULTS: We observed associations between particle radioactivity on C-reactive protein (CRP), intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1), but no associations with fibrinogen. An interquartile range width increase in mean 7-day particle radioactivity (1.2 × 10 Bq/m) was associated with a 4.9% increase in CRP (95% CI = 0.077, 9.9), a 2.8% increase in ICAM-1 (95% CI = 1.4, 4.2), and a 4.3% increase in VCAM-1 (95% CI = 2.5, 6.1). The main effects of particle radioactivity remained similar after adjustment in most cases. We also obtained similar effect estimates in a sensitivity analysis applying a robust causal model. CONCLUSION: Regional particle radioactivity is positively associated with inflammatory biomarkers, indicating a potential pathway for radiation-induced cardiovascular effects.

Individual species and cumulative mixture relationships of 24-hour urine metal concentrations with DNA methylation age variables in older men.

BACKGROUND: Globally, toxic metal exposures are a well-recognized risk factor for many adverse health outcomes. DNA methylation-based measures of biological aging are predictive of disease, but have poorly understood relationships with metal exposures. OBJECTIVE: We performed a pilot study examining the relationships of 24-h urine metal concentrations with three novel DNA methylation-based measures of biological aging: DNAmAge, GrimAge, and PhenoAge. METHODS: We utilized a previously established urine panel of five common metals [arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg)] found in a subset of the elderly US Veterans Affairs Normative Aging Study cohort (N = 48). The measures of DNA methylation-based biological age were calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. Bayesian Kernel Machine Regression (BKMR) was used to determine metals most important to the aging outcomes and the relationship of the cumulative metal mixture with the outcomes. Individual relationships of important metals with the biological aging outcomes were modeled using fully-adjusted linear models controlling for chronological age, renal function, and lifestyle/environmental factors. RESULTS: Mn was selected as important to PhenoAge. A 1 ng/mL increase in urine Mn was associated with a 9.93-year increase in PhenoAge (95%CI: 1.24, 18.61, p = 0.03). The cumulative urine metal mixture was associated with increases in PhenoAge. Compared to a model where each metal in the mixture is set to its 50th percentile value, every one-unit increase of the cumulative mixture with each metal at its 70th percentile was associated with a 2.53-year increase in PhenoAge (95%CI: 0.10, 4.96, P<0.05). CONCLUSION: Our results add novel evidence that metals detected in urine are associated with increases in biological aging and suggest that these DNA methylation-based measures may be useful for identifying individuals at-risk for diseases related to toxic metal exposures. Further research is necessary to confirm these findings more broadly.

Metabolomic signatures of lead exposure in the VA Normative Aging Study.

BACKGROUND: Lead (Pb) is widespread and exposure to this non-essential heavy metal can cause multiple negative health effects; however the mechanisms underlying these effects remain incompletely understood. OBJECTIVES: To identify plasma metabolomic signatures of Pb exposure, as measured in blood and toenails. METHODS: In a subset of men from the VA Normative Aging Study, mass-spectrometry based plasma metabolomic profiling was performed. Pb levels were measured in blood samples and toenail clippings collected concurrently. Multivariable linear regression models, smoothing splines and Pathway analyses were employed to identify metabolites associated with Pb exposure. RESULTS: In 399 men, 858 metabolites were measured and passed QC, of which 154 (17.9%) were significantly associated with blood Pb (p < 0.05). Eleven of these passed stringent correction for multiple testing, including pro-hydroxy-pro (ß(95%CI): 1.52 (0.93,2.12), p = 7.18x10-7), N-acetylglycine (ß(95%CI): 1.44 (0.85,2.02), p = 1.12x10-6), tartarate (ß(95%CI): 0.68 (0.35,1.00), p = 4.84x10-5), vanillylmandelate (ß(95%CI): 1.05 (0.47,1.63), p = 4.44x10-7), and lysine (ß(95%CI): 1.88 (-2.8,-0.95), p = 9.10x10-5). A subset of 48 men had a second blood sample collected a mean of 6.1 years after their first. Three of the top eleven metabolites were also significant in this second blood sample. Furthermore, we identified 70 plasma metabolites associated with Pb as measured in toenails. Twenty-three plasma metabolites were significantly associated with both blood and toenail measures, while others appeared to be specific to the biosample in which Pb was measured. For example, benzanoate metabolism appeared to be of importance with the longer-term exposure assessed by toenails. DISCUSSION: Pb exposure is responsible for 0.6% of the global burden of disease and metabolomics is particularly well-suited to explore its pathogenic mechanisms. In this study, we identified metabolites and metabolomic pathways associated with Pb exposure that suggest that Pb exposure acts through oxidative stress and immune dysfunction. These findings help us to better understand the biology of this important public health burden.

Meta-analysis of epigenome-wide association studies of cognitive abilities.

Cognitive functions are important correlates of health outcomes across the life-course. Individual differences in cognitive functions are partly heritable. Epigenetic modifications, such as DNA methylation, are susceptible to both genetic and environmental factors and may provide insights into individual differences in cognitive functions. Epigenome-wide meta-analyses for blood-based DNA methylation levels at ~420,000 CpG sites were performed for seven measures of cognitive functioning using data from 11 cohorts. CpGs that passed a Bonferroni correction, adjusting for the number of CpGs and cognitive tests, were assessed for: longitudinal change; being under genetic control (methylation QTLs); and associations with brain health (structural MRI), brain methylation and Alzheimer's disease pathology. Across the seven measures of cognitive functioning (meta-analysis n range: 2557-6809), there were epigenome-wide significant (P < 1.7 × 10-8) associations for global cognitive function (cg21450381, P = 1.6 × 10-8), and phonemic verbal fluency (cg12507869, P = 2.5 × 10-9). The CpGs are located in an intergenic region on chromosome 12 and the INPP5A gene on chromosome 10, respectively. Both probes have moderate correlations (~0.4) with brain methylation in Brodmann area 20 (ventral temporal cortex). Neither probe showed evidence of longitudinal change in late-life or associations with white matter brain MRI measures in one cohort with these data. A methylation QTL analysis suggested that rs113565688 was a cis methylation QTL for cg12507869 (P = 5 × 10-5 and 4 × 10-13 in two lookup cohorts). We demonstrate a link between blood-based DNA methylation and measures of phonemic verbal fluency and global cognitive ability. Further research is warranted to understand the mechanisms linking genomic regulatory changes with cognitive function to health and disease.

Testing for the indirect effect under the null for genome-wide mediation analyses.

Mediation analysis helps researchers assess whether part or all of an exposure's effect on an outcome is due to an intermediate variable. The indirect effect can help in designing interventions on the mediator as opposed to the exposure and better understanding the outcome's mechanisms. Mediation analysis has seen increased use in genome-wide epidemiological studies to test for an exposure of interest being mediated through a genomic measure such as gene expression or DNA methylation (DNAm). Testing for the indirect effect is challenged by the fact that the null hypothesis is composite. We examined the performance of commonly used mediation testing methods for the indirect effect in genome-wide mediation studies. When there is no association between the exposure and the mediator and no association between the mediator and the outcome, we show that these common tests are overly conservative. This is a case that will arise frequently in genome-wide mediation studies. Caution is hence needed when applying the commonly used mediation tests in genome-wide mediation studies. We evaluated the performance of these methods using simulation studies, and performed an epigenome-wide mediation association study in the Normative Aging Study, analyzing DNAm as a mediator of the effect of pack-years on FEV1 .

Improving estimation and prediction in linear regression incorporating external information from an established reduced model.

We consider a situation where there is rich historical data available for the coefficients and their standard errors in a linear regression model describing the association between a continuous outcome variable Y and a set of predicting factors X, from a large study. We would like to use this summary information for improving inference in an expanded model of interest, Y given X,B. The additional variable B is a new biomarker, measured on a small number of subjects in a new dataset. We formulate the problem in an inferential framework where the historical information is translated in terms of nonlinear constraints on the parameter space and propose both frequentist and Bayes solutions to this problem. We show that a Bayesian transformation approach proposed by Gunn and Dunson is a simple and effective computational method to conduct approximate Bayesian inference for this constrained parameter problem. The simulation results comparing these methods indicate that historical information on E(Y|X) can improve the efficiency of estimation and enhance the predictive power in the regression model of interest E(Y|X,B). We illustrate our methodology by enhancing a published prediction model for bone lead levels in terms of blood lead and other covariates, with a new biomarker defined through a genetic risk score.

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

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).

Lung function association with outdoor temperature and relative humidity and its interaction with air pollution in the elderly.

While the effects of weather variability on cardio-respiratory mortality are well described, research examining the effects on morbidity, especially for vulnerable populations, is warranted. We investigated the associations between lung function and outdoor temperature (T in Celsius degrees (°C)) and relative humidity (RH), in a cohort of elderly men, the Normative Aging Study. Our study included 1103 participants whose forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and weather exposures were assessed one to five times during the period 1995-2011 (i.e. 3162 observations). Temperature and relative humidity were measured at one location 4 h to 7 days before lung function tests. We used linear mixed-effects models to examine the associations with outdoor T and RH. A 5-degree increase in the 3-day moving average T was associated with a significant 0.7% decrease (95%CI: -1.24, -0.20) in FVC and a 5% increase in the 7-day moving average RH was associated with a significant 0.2% decrease (95%CI: -0.40, -0.02) in FVC and FEV1. The associations with T were greater when combined with higher exposures of black carbon with a 1.6% decrease (95%CI -2.2; -0.9) in FVC and a 1% decrease (95%CI -1.7; -0.4) in FEV1. The relationships between T and RH and lung function were linear. No synergistic effect of T and RH was found. Heat and lung function are two predictors of mortality. Our findings suggest that increases in temperature and relative humidity are related to decreases in lung function, and such observations might be amplified by high black carbon levels.