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.

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.

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.

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.

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.

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.

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.

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.

Exploring the importance of cancer pathways by meta-analysis of differential protein expression networks in three different cancers.

BACKGROUND: It is believed that all cancers occur due to the mutation or change in one or more genes. In order to investigate the significance of the biological pathways which are interrupted by these genetic mutations, we pursue an integrated analysis using multiple cancer datasets released by the International Cancer Genome Consortium (ICGC). This dataset consists of expression profiles for genes/proteins of patients receiving treatment, for three types of cancer - Head and Neck Squamous Cell Carcinoma (HNSC), Lung Adenocarcinoma (LUAD) and Kidney Renal Clear Cell Carcinoma (KIRC). We consider pathway analysis to identify all the biological pathways which are active among the patients and investigate the roles of the significant pathways using a differential network analysis of the protein expression datasets for the three cancers separately. We then integrate the pathway based results of all the three cancers which provide a more comprehensive picture of the three cancers. RESULTS: From our analysis of the protein expression data, overall, RAS and PI3K signaling pathways appear to play the most significant roles in the three cancers - Head and Neck Squamous Cell Carcinoma (HNSC), Lung Adenocarcinoma (LUAD) and Kidney Renal Clear Cell Carcinoma (KIRC). CONCLUSION: This analysis suggests that the RAS and PI3K signaling pathways are the two most important pathways in all the three cancers and should be investigated further for their potential roles in cancers. REVIEWERS: This article was reviewed by Joaquin Dopazo and Samiran Ghosh.

Differences in protein-protein association networks for lung adenocarcinoma: A retrospective study.

Various methods to determine the connectivity scores between groups of proteins associated with lung adenocarcinoma are examined. Proteins act together to perform a wide range of functions within biological processes. Hence, identification of key proteins and their interactions within protein networks can provide invaluable information on disease mechanisms. Differential network analysis provides a means of identifying differences in the interactions among proteins between two networks. We use connectivity scores based on the method of partial least squares to quantify the strength of the interactions between each pair of proteins. These scores are then used to perform permutation-based statistical tests. This examines if there are significant differences between the network connectivity scores for individual proteins or classes of proteins. The expression data from a study on lung adenocarcinoma is used in this study. Connectivity scores are computed for a group of 109 subjects who were in the complete remission and as well as for a group of 51 subjects whose cancer had progressed. The distributions of the connectivity scores are similar for the two networks yet subtle but statistically significant differences have been identified and their impact discussed.