Plasma protein signatures of adult asthma.

BACKGROUND: Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma. METHODS: Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with atopy (n = 207), asthma without atopy (n = 554), atopy without asthma (n = 147), compared to neither (n = 948)). RESULTS: Meta-analysis of 4860 proteins identified 115 significantly (FDR<0.05) associated with asthma. Multiple signaling pathways related to airway inflammation and pulmonary injury were enriched (FDR<0.05) among these proteins. A proteomic score generated using machine learning provided predictive value for asthma (AUC = 0.77, 95% CI = 0.75-0.79 in training set; AUC = 0.72, 95% CI = 0.69-0.75 in validation set). Twenty proteins are targeted by approved or investigational drugs for asthma or other conditions, suggesting potential drug repurposing. The combined asthma-atopy phenotype showed significant associations with 20 proteins, including five not identified in the overall asthma analysis. CONCLUSION: This first large-scale proteomics study identified over 100 plasma proteins associated with current asthma in adults. In addition to validating previous associations, we identified many novel proteins that could inform development of diagnostic biomarkers and therapeutic targets in asthma management.

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.

Cheiloscopy patterns in individuals with and without parafunctional oral habits: A cross-sectional observation pilot study.

PURPOSE: Lip prints are unique and have potential for use as a human identifier. The purpose of this study was to observe possible cheiloscopy differences of individuals with and without parafunctional oral habits such as smoking, vaping, playing a wind instrument or using an asthma inhaler. METHODS: This IRB approved blinded cross-sectional observation pilot study collected lip prints from 66 individuals, three of which were excluded. Participants cleansed their lips, then lipstick was applied to the vermillion zones of the upper and lower lips. Adhesive tape was applied to the lips and prints were transferred to white bond paper for viewing purposes. Each set of included lip prints was divided into quadrants and dichotomized into a group of those with an oral parafunctional habit or with no such habits. Each quadrant sample was then manually analysed and classed according to the gold standard Suzuki and Tsuchihashi system. RESULTS: A total of 252 dichotomized lip print quadrants (with habits n = 76, 30.2%, and without habits n = 176, 69.8%) were analysed. Type II patterns were the most common for examined quadrant samples; however, no statistically significant differences (Pearson's chi-squared test, p = 0.366) were observed between pattern classifications of samples with and without parafunctional oral habits. CONCLUSIONS: There is no statistically significant difference of lip print patterns between individuals with and without parafunctional oral habits. Further research on populational variations is needed for cheiloscopy to aid in human identifications.

Robust meta-analysis for large-scale genomic experiments based on an empirical approach.

BACKGROUND: Recent high-throughput technologies have opened avenues for simultaneous analyses of thousands of genes. With the availability of a multitude of public databases, one can easily access multiple genomic study results where each study comprises of significance testing results of thousands of genes. Researchers currently tend to combine this genomic information from these multiple studies in the form of a meta-analysis. As the number of genes involved is very large, the classical meta-analysis approaches need to be updated to acknowledge this large-scale aspect of the data. METHODS: In this article, we discuss how application of standard theoretical null distributional assumptions of the classical meta-analysis methods, such as Fisher's p-value combination and Stouffer's Z, can lead to incorrect significant testing results, and we propose a robust meta-analysis method that empirically modifies the individual test statistics and p-values before combining them. RESULTS: Our proposed meta-analysis method performs best in significance testing among several meta-analysis approaches, especially in presence of hidden confounders, as shown through a wide variety of simulation studies and real genomic data analysis. CONCLUSION: The proposed meta-analysis method produces superior meta-analysis results compared to the standard p-value combination approaches for large-scale simultaneous testing in genomic experiments. This is particularly useful in studies with large number of genes where the standard meta-analysis approaches can result in gross false discoveries due to the presence of unobserved confounding variables.

Mixture analysis of associations between exposure to low levels of multiple metals and semen quality and sperm DNA integrity.

The objective of this study was to assess the association of exposure to metal mixtures with semen quality and sperm DNA integrity of coke oven workers (n = 96). Urinary six metals (cadmium, lead, arsenic, zinc, selenium, and copper) were quantified using inductively coupled-mass spectrometry. Semen quality parameters included sperm concentration, sperm concentration, sperm motility, sperm morphology, and sperm viability. Sperm DNA fragmentation and 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodGuo) adducts served as biomarkers for assessing sperm DNA integrity. Bayesian kernel machine regression with the hierarchical variable selection process was used for analyzing both individual and joint effects of the metal mixture on the outcomes of semen samples, while adjusting for age, smoking, alcohol consumption, job length, and body mass index. The metal mixture was associated with reduced sperm concentration, motility, viability, and normal morphology. It was novel that a dose-response relationship was observed between exposure of the metal mixture and semen quality. Among the metals tested, cadmium had a reverse relationship with sperm motility, viability, and normal morphology, and a non-linear relationship with sperm viability and sperm motility. The metal mixture and individual metals were not associated with sperm DNA fragmentation and 8-oxodGuo. In conclusion, exposure to metal mixtures and cadmium may exert an association with semen quality and had no association with sperm DNA breakages.

Interaction between Genetic Risk Scores for reduced pulmonary function and smoking, asthma and endotoxin.

RATIONALE: Genome-wide association studies (GWASs) have identified numerous loci associated with lower pulmonary function. Pulmonary function is strongly related to smoking and has also been associated with asthma and dust endotoxin. At the individual SNP level, genome-wide analyses of pulmonary function have not identified appreciable evidence for gene by environment interactions. Genetic Risk Scores (GRSs) may enhance power to identify gene-environment interactions, but studies are few. METHODS: We analysed 2844 individuals of European ancestry with 1000 Genomes imputed GWAS data from a case-control study of adult asthma nested within a US agricultural cohort. Pulmonary function traits were FEV1, FVC and FEV1/FVC. Using data from a recent large meta-analysis of GWAS, we constructed a weighted GRS for each trait by combining the top (p value<5×10-9) genetic variants, after clumping based on distance (±250 kb) and linkage disequilibrium (r2=0.5). We used linear regression, adjusting for relevant covariates, to estimate associations of each trait with its GRS and to assess interactions. RESULTS: Each trait was highly significantly associated with its GRS (all three p values<8.9×10-8). The inverse association of the GRS with FEV1/FVC was stronger for current smokers (pinteraction=0.017) or former smokers (pinteraction=0.064) when compared with never smokers and among asthmatics compared with non-asthmatics (pinteraction=0.053). No significant interactions were observed between any GRS and house dust endotoxin. CONCLUSIONS: Evaluation of interactions using GRSs supports a greater impact of increased genetic susceptibility on reduced pulmonary function in the presence of smoking or asthma.

Epigenome-wide association study of DNA methylation and adult asthma in the Agricultural Lung Health Study.

Epigenome-wide studies of methylation in children support a role for epigenetic mechanisms in asthma; however, studies in adults are rare and few have examined non-atopic asthma. We conducted the largest epigenome-wide association study (EWAS) of blood DNA methylation in adults in relation to non-atopic and atopic asthma.We measured DNA methylation in blood using the Illumina MethylationEPIC array among 2286 participants in a case-control study of current adult asthma nested within a United States agricultural cohort. Atopy was defined by serum specific immunoglobulin E (IgE). Participants were categorised as atopy without asthma (n=185), non-atopic asthma (n=673), atopic asthma (n=271), or a reference group of neither atopy nor asthma (n=1157). Analyses were conducted using logistic regression.No associations were observed with atopy without asthma. Numerous cytosine-phosphate-guanine (CpG) sites were differentially methylated in non-atopic asthma (eight at family-wise error rate (FWER) p<9×10-8, 524 at false discovery rate (FDR) less than 0.05) and implicated 382 novel genes. More CpG sites were identified in atopic asthma (181 at FWER, 1086 at FDR) and implicated 569 novel genes. 104 FDR CpG sites overlapped. 35% of CpG sites in non-atopic asthma and 91% in atopic asthma replicated in studies of whole blood, eosinophils, airway epithelium, or nasal epithelium. Implicated genes were enriched in pathways related to the nervous system or inflammation.We identified numerous, distinct differentially methylated CpG sites in non-atopic and atopic asthma. Many CpG sites from blood replicated in asthma-relevant tissues. These circulating biomarkers reflect risk and sequelae of disease, as well as implicate novel genes associated with non-atopic and atopic asthma.

Epigenome-wide meta-analysis of DNA methylation and childhood asthma.

BACKGROUND: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. OBJECTIVE: We sought to identify differential DNA methylation in newborns and children related to childhood asthma. METHODS: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. RESULTS: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. CONCLUSION: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.

Improving protein identification from tandem mass spectrometry data by one-step methods and integrating data from other platforms.

MOTIVATION: Many approaches have been proposed for the protein identification problem based on tandem mass spectrometry (MS/MS) data. In these experiments, proteins are digested into peptides and the resulting peptide mixture is subjected to mass spectrometry. Some interesting putative peptide features (peaks) are selected from the mass spectra. Following that, the precursor ions undergo fragmentation and are analyzed by MS/MS. The process of identification of peptides from the mass spectra and the constituent proteins in the sample is called protein identification from MS/MS data. There are many two-step protein identification procedures, reviewed in the literature, which first attempt to identify the peptides in a separate process and then use these results to infer the proteins. However, in recent years, there have been attempts to provide a one-step solution to protein identification, which simultaneously identifies the proteins and the peptides in the sample. RESULTS: In this review, we briefly introduce the most popular two-step protein identification procedure, PeptideProphet coupled with ProteinProphet. Following that, we describe the difficulties with two-step procedures and review some recently introduced one-step protein/peptide identification procedures that do not suffer from these issues. The focus of this review is on one-step procedures that are based on statistical likelihood-based models, but some discussion of other one-step procedures is also included. We report comparative performances of one-step and two-step methods, which support the overall superiorities of one-step procedures. We also cover some recent efforts to improve protein identification by incorporating other molecular data along with MS/MS data.

A novel statistical approach for identification of the master regulator transcription factor.

BACKGROUND: Transcription factors are known to play key roles in carcinogenesis and therefore, are gaining popularity as potential therapeutic targets in drug development. A 'master regulator' transcription factor often appears to control most of the regulatory activities of the other transcription factors and the associated genes. This 'master regulator' transcription factor is at the top of the hierarchy of the transcriptomic regulation. Therefore, it is important to identify and target the master regulator transcription factor for proper understanding of the associated disease process and identifying the best therapeutic option. METHODS: We present a novel two-step computational approach for identification of master regulator transcription factor in a genome. At the first step of our method we test whether there exists any master regulator transcription factor in the system. We evaluate the concordance of two ranked lists of transcription factors using a statistical measure. In case the concordance measure is statistically significant, we conclude that there is a master regulator. At the second step, our method identifies the master regulator transcription factor, if there exists one. RESULTS: In the simulation scenario, our method performs reasonably well in validating the existence of a master regulator when the number of subjects in each treatment group is reasonably large. In application to two real datasets, our method ensures the existence of master regulators and identifies biologically meaningful master regulators. An R code for implementing our method in a sample test data can be found in http://www.somnathdatta.org/software . CONCLUSION: We have developed a screening method of identifying the 'master regulator' transcription factor just using only the gene expression data. Understanding the regulatory structure and finding the master regulator help narrowing the search space for identifying biomarkers for complex diseases such as cancer. In addition to identifying the master regulator our method provides an overview of the regulatory structure of the transcription factors which control the global gene expression profiles and consequently the cell functioning.

Allied Dental Students' Perceived Knowledge, Confidence, and Attitudes Regarding Disaster Victim Identification Topics.

Purpose Disaster victim identification (DVI) service requires knowledge, confidence, and an attitude (KCA) of readiness. The purpose of this study was to assess allied dental students' perceived KCA regarding DVI skills and topics.Methods A convenience sample of senior dental hygiene students (n=27) and senior dental assistant students (n=14) were recruited by email then presented mismatched simulated antemortem (AM) and postmortem (PM) bitewing radiographs and asked to indicate correct matches. Collectively, participants made 205 radiographic matches and indicated 205 degrees of certainty binarily as "positive" or "possible" (one per match). Participants also completed a researcher designed pretest/posttest electronic survey with seven 3-point Likert-scale items with answer options of "slightly", "moderately", or "extremely" regarding self-perceived knowledge. Statistical analyses were conducted with R software using an α=0.05 significance level.Results A total of n=41 students participated, yielding a response rate of 85.4%. A one-sided linear trend test revealed statistically significant increases of perceived confidence in knowledge from pretest to posttest regarding forensic odontologists' role in DVI (p<0.0001), DVI applications for mass fatality incidents (MFI) (p<0.0001), role of dental radiology in DVI (p<0.0001), and dental morphology applications for DVI (p<0.0001). Participants indicated moderate or extreme confidence in personal clinical skillsets to assist forensic odontologists with DVI. A one-sided Fisher's exact test revealed a statistically significant (p<0.05) positive association between expressed degree of certainty (confidence) and correct radiographic matches. A one-sided linear trend test revealed statistically significant (p<0.0001) improvements in attitude regarding participants' perceived importance for their respective professions to volunteer in DVI.Conclusion Participants of this study reported significant improvements of self-perceived KCA regarding DVI skills and topics. These characteristics may encourage allied dental professionals to pursue further DVI educational opportunities and future service when support is needed for MFI.

Populational Variations of Cheiloscopy Patterns: A cross-sectional observation pilot study.

Purpose Lip prints are unique and have potential for use as a human identifier. The purpose of this study was to observe possible cheiloscopy differences of individuals with and without parafunctional oral habits such as smoking, vaping, playing a wind instrument or using an asthma inhaler.Methods This IRB approved blinded cross-sectional observation pilot study collected lip prints from sixty-six individuals, three of which were excluded. Participants cleansed their lips, then lipstick was applied to the vermillion zones of the upper and lower lips. Adhesive tape was applied to the lips and prints were transferred to white bond paper for viewing purposes. Each set of included lip prints was divided into quadrants and dichotomized into a group of those with an oral parafunctional habit or with no such habits. Each quadrant sample was then manually analyzed and classed according to the gold standard Suzuki and Tsuchihashi system.Results A total of 252 dichotomized lip print quadrants (with habits n=76, 30.2%, and without habits n=176, 69.8%) were analyzed. Type II patterns were the most common for examined quadrant samples; however, no statistically significant differences (Pearson's chi-squared test, p=0.366) were observed between pattern classifications of samples with and without parafunctional oral habits.Conclusion There is no statistically significant difference of lip print patterns between individuals with and without parafunctional oral habits. Further research on populational variations is needed for cheiloscopy to aid in human identifications.

Mixture analysis on associations between semen quality and sperm DNA integrity and occupational exposure to polycyclic aromatic hydrocarbons.

The objective of this study was to assess relationships between exposure to PAHs at occupational levels and outcomes of human semen quality and sperm DNA integrity. Personal breathing zone air samples were collected to quantify exposure of 16 targeted PAHs to coke-oven workers at a steel company in southern Taiwan. Semen quality, including concentration, motility, morphology, and viability, were assessed. Sperm DNA fragmentation, 8-oxodGuo, bulky PAH adducts, and benzo[a]pyrene diol epoxide-DNA adducts served as biomarkers for assessment of sperm DNA integrity. The Bayesian Kernel Machine Regression modeling was employed to estimate mixture effects of the PAH mixture on the outcomes of semen quality and sperm DNA integrity and to identify individual compounds of PAH mixtures associated with the mixture effects. Exposure to the PAH mixture was inversely associated with sperm viability, while benzo(b)fluoranthene (B[b]F) was identified as the main predictor for sperm viability. Exposure to the PAH mixture also exhibited a positive trend with sperm DNA fragmentation. B[b]F and benzo(a)anthracene (B[a]A) were identified as individual PAH compounds associated with increased sperm DNA fragmentation.

Dental Hygiene and Dental Assistant Students' Simulated DVI Radiographic Match Accuracy: A pilot study.

Purpose Allied dental health care professionals have served on disaster victim identification (DVI) teams; however, the literature is void of statistical measures regarding transferable skills and disaster preparedness. The purpose of this study was to assess second year dental hygiene and dental assistant students' match accuracy for simulated DVI radiographs and compare the match accuracy between the student groups.Methods Five patient cases were chosen at random to retrospectively collect sets of digital bitewing radiographs from two time periods. The five retrospectively selected sets of images served as simulated antemortem (AM) and postmortem (PM) radiographs. A convenience sample of second year dental hygiene and dental assistant students from two institutions (n=48) were invited to participate in this IRB-exempt descriptive observational study. The previously selected AM and PM images were randomly mismatched, and participants were asked to visually compare the image sets and indicate the matches using a drag and drop feature in an electronic survey instrument. Descriptive statistics were used to analyze the data; the significance level was set at α=0.05.Results A total of 41 dental hygiene and dental assistant students agreed to participate for a response rate of 85.4%. Eighty-five percent of the participants accurately matched five out of five sets while the remaining 15% accurately matched three out of five sets. A one-sample binomial proportion test revealed that 80% of the participants were able to match at least four out of five sets (p<0.001). Dental hygiene students demonstrated increased matching performance as compared to dental assisting students (p=0.013).Conclusion Both dental hygiene and dental assistant students demonstrated transferable DVI skills to accurately match simulated AM and PM radiographs. Future research is needed in a larger sample to develop and assess best practices of DVI training to build on existing skills for allied dental health care professionals.

Mixture Analysis of Associations between Occupational Exposure to Polycyclic Aromatic Hydrocarbons and Sperm Oxidative DNA Damage.

OBJECTIVE: This study aimed to determine (i) associations between levels of the polycyclic aromatic hydrocarbon (PAH) mixture with 16 targeted PAH compounds in the personal breathing zone area and sperm oxidative DNA damage, (ii) associations between levels of individual PAH compounds and sperm oxidative DNA damage, (iii) oxidative stress as the mode of action for the genotoxic effects on sperm, and (iv) any dose-response relationship between exposure to the PAH mixture and/or individual PAH compounds and sperm oxidative DNA damage. METHODS: Sixteen targeted PAH compounds in the personal breathing zone area of 38 coke-oven workers and 24 control subjects were quantified using gas chromatography-mass spectrometry. Sperm oxidative damage and status were evaluated by measuring levels of sperm 7,8-dihydro-8-oxoguanie (8-oxodGuo), seminal malondialdehyde (MDA) and seminal reactive oxygen species (ROS). Bayesian kernel machine regression with hierarchical variable selection process was employed to determine associations of the PAH mixture and the biomarkers of sperm oxidative damage. A novel grouping approach needed for the hierarchical variable selection process was developed based on PAH bay region and molecular weight. RESULTS: The PAH mixture exhibited a positive trend with increased sperm 8-oxodGuo levels at their lower percentiles (25th-50th). The exposure of the PAH mixture was associated with increased MDA levels in sperm. Bay and bay-like regions of the PAH mixture were the most important group for estimating the associations between the PAH mixture and sperm oxidative stress status. Benzo[a]anthracene was the main individual PAH compound that was associated with increased MDA levels. CONCLUSION: Sperm oxidative DNA damage induced by occupational exposure to the PAH mixture had a suggestive association with increased MDA levels in coke-oven workers. Finally, the study identified that the individual PAH compound, benzo[a]anthracene, was the primary driver for the suggestive association between the PAH mixture and sperm oxidative damage.

Early-life farm exposures and eczema among adults in the Agricultural Lung Health Study.

Background: Several studies conducted in Europe have suggested a protective association between early-life farming exposures and childhood eczema or atopic dermatitis; few studies have examined associations in adults. Objectives: To investigate associations between early-life exposures and eczema among 3217 adult farmers and farm spouses (mean age 62.8 years) in a case-control study nested within an US agricultural cohort. Methods: We used sampling-weighted logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for associations between early-life exposures and self-reported doctor-diagnosed eczema (273 cases) and polytomous logistic regression to estimate ORs (95%CIs) for a 4-level outcome combining information on eczema and atopy (specific IgE≥0.35). Additionally, we explored genetic and gene-environment associations with eczema. Results: Although early-life farming exposures were not associated with eczema overall, several early-life exposures were associated with a reduced risk of having both eczema and atopy. Notably, results suggest stronger protective associations among individuals with both eczema and atopy than among those with either atopy alone or eczema alone. For example, ORs (95%CIs) for having a mother who did farm work while pregnant were 1.01 (0.60-1.69) for eczema alone and 0.80 (0.65-0.99) for atopy alone, but 0.54 (0.33-0.80) for having both eczema and atopy. A genetic risk score based on previously identified atopic dermatitis variants was strongly positively associated with eczema, and interaction testing suggested protective effects of several early-life farming exposures only in individuals at lower genetic risk. Conclusions: In utero and childhood farming exposures are associated with decreased odds of having eczema with atopy in adults.

Opioid medication use and blood DNA methylation: epigenome-wide association meta-analysis.

Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate <0.05) was observed at six CpGs annotated to the following genes: KIAA0226, CPLX2, TDRP, RNF38, TTC23 and GPR179. Integrative epigenomic analyses linked implicated loci to regulatory elements in blood and/or brain. Additionally, 74 CpGs were differentially methylated in males or females. Methylation at significant CpGs correlated with gene expression in blood and/or brain. Conclusion: This study identified DNA methylation related to opioid medication use in general populations. The results could inform the development of blood methylation biomarkers of opioid use.

Bayesian Hierarchical Model for Protein Identifications.

In proteomics, identification of proteins from complex mixtures of proteins extracted from biological samples is an important problem. Among the experimental technologies, Mass-Spectrometry (MS) is the most popular one. Protein identification from MS data typically relies on a "two-step" procedure of identifying the peptide first followed by the separate protein identification procedure next. In this setup, the interdependence of peptides and proteins are neglected resulting in relatively inaccurate protein identification. In this article, we propose a Markov chain Monte Carlo (MCMC) based Bayesian hierarchical model, a first of its kind in protein identification, which integrates the two steps and performs joint analysis of proteins and peptides using posterior probabilities. We remove the assumption of independence of proteins by using clustering group priors to the proteins based on the assumption that proteins sharing the same biological pathway are likely to be present or absent together and are correlated. The complete conditionals of the proposed joint model being tractable, we propose and implement a Gibbs sampling scheme for full posterior inference that provides the estimation and statistical uncertainties of all relevant parameters. The model has better operational characteristics compared to two existing "one-step" procedures on a range of simulation settings as well as on two well-studied datasets.

Comparison of smoking-related DNA methylation between newborns from prenatal exposure and adults from personal smoking.

Aim: Cigarette smoking influences DNA methylation genome wide, in newborns from pregnancy exposure and in adults from personal smoking. Whether a unique methylation signature exists for in utero exposure in newborns is unknown. Materials & methods: We separately meta-analyzed newborn blood DNA methylation (assessed using Illumina450k Beadchip), in relation to sustained maternal smoking during pregnancy (9 cohorts, 5648 newborns, 897 exposed) and adult blood methylation and personal smoking (16 cohorts, 15907 participants, 2433 current smokers). Results & conclusion: Comparing meta-analyses, we identified numerous signatures specific to newborns along with many shared between newborns and adults. Unique smoking-associated genes in newborns were enriched in xenobiotic metabolism pathways. Our findings may provide insights into specific health impacts of prenatal exposure on offspring.

EAMA: Empirically adjusted meta-analysis for large-scale simultaneous hypothesis testing in genomic experiments.

Recent developments in high throughput genomic assays have opened up the possibility of testing hundreds and thousands of genes simultaneously. However, adhering to the regular statistical assumptions regarding the null distributions of test statistics in such large-scale multiple testing frameworks has the potential of leading to incorrect significance testing results and biased inference. This problem gets worse when one combines results from different independent genomic experiments with a possibility of ending up with gross false discoveries of significant genes. In this article, we develop a meta-analysis method of combining p-values from different independent experiments involving large-scale multiple testing frameworks, through empirical adjustments of the individual test statistics and p-values. Even though, it is based on various existing ideas, this specific combination is novel and potentially useful. Through simulation studies and real genomic datasets we show that our method outperforms the standard meta-analysis approach of significance testing in terms of accurately identifying the truly significant set of genes.