Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations

Array-based comparative genomic hybridization (aCGH) allows measuring DNA copy number at the whole genome scale. In cancer studies, one may be interested in identifying DNA copy number aberrations (CNAs) associated with certain clinicopathological characteristics such as cancer metastasis. We proposed to define test regions based on copy number pattern profiles across multiple samples, using either smoothed log2-ratio or discrete data of copy number gain/loss calls. Association test performed on the refined test regions instead of the probes has improved power due to reduced number of tests. We also compared three types of measurement of copy number levels, normalized log2-ratio, smoothed log2-ratio, and copy number gain or loss calls in statistical hypothesis testing. The relative strengths and weaknesses of the proposed method were demonstrated using both simulation studies and real data analysis of a liver cancer study

High-dimensional quantile mediation analysis with application to a birth cohort study of mother-newborn pairs

MOTIVATION: There has been substantial recent interest in developing methodology for high-dimensional mediation analysis. Yet, the majority of mediation statistical methods lean heavily on mean regression, which limits their ability to fully capture the complex mediating effects across the outcome distribution. To bridge this gap, we propose a novel approach for selecting and testing mediators throughout the full range of the outcome distribution spectrum. RESULTS: The proposed high-dimensional quantile mediation model provides a comprehensive insight into how potential mediators impact outcomes via their mediation pathways. This method\u27s efficacy is demonstrated through extensive simulations. The study presents a real-world data application examining the mediating effects of DNA methylation on the relationship between maternal smoking and offspring birthweight. AVAILABILITY AND IMPLEMENTATION: Our method offers a publicly available and user-friendly function qHIMA(), which can be accessed through the R package HIMA at https://CRAN.R-project.org/package=HIMA

HIMA2: High-dimensional mediation analysis and its application in epigenome-wide DNA methylation data

Mediation analysis plays a major role in identifying significant mediators in the pathway between environmental exposures and health outcomes. With advanced data collection technology for large-scale studies, there has been growing research interest in developing methodology for high-dimensional mediation analysis. In this paper we present HIMA2, an extension of the HIMA method (Zhang in Bioinformatics 32:3150-3154, 2016). First, the proposed HIMA2 reduces the dimension of mediators to a manageable level based on the sure independence screening (SIS) method (Fan in J R Stat Soc Ser B 70:849-911, 2008). Second, a de-biased Lasso procedure is implemented for estimating regression parameters. Third, we use a multiple-testing procedure to accurately control the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. We demonstrate its practical performance using Monte Carlo simulation studies and apply our method to identify DNA methylation markers which mediate the pathway from smoking to reduced lung function in the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Effects of airborne pollutants on mitochondrial DNA Methylation

Background: Mitochondria have small mitochondrial DNA (mtDNA) molecules independent from the nuclear DNA, a separate epigenetic machinery that generates mtDNA methylation, and are primary sources of oxidative-stress generation in response to exogenous environments. However, no study has yet investigated whether mitochondrial DNA methylation is sensitive to pro-oxidant environmental exposures. Methods: We sampled 40 male participants (20 high-, 20 low-exposure) from each of three studies on airborne pollutants, including investigations of steel workers exposed to metal-rich particulate matter (measured as PM1) in Brescia, Italy (Study 1); gas-station attendants exposed to air benzene in Milan, Italy (Study 2); and truck drivers exposed to traffic-derived Elemental Carbon (EC) in Beijing, China (Study 3). We have measured DNA methylation from buffy coats of the participants. We measured methylation by bisulfite-Pyrosequencing in three mtDNA regions, i.e., the transfer RNA phenylalanine (MT-TF), 12S ribosomal RNA (MT-RNR1) gene and “D-loop” control region. All analyses were adjusted for age and smoking. Results: In Study 1, participants with high metal-rich PM1 exposure showed higher MT-TF and MT-RNR1 methylation than low-exposed controls (difference = 1.41, P = 0.002); MT-TF and MT-RNR1 methylation was significantly associated with PM1 exposure (beta = 1.35, P = 0.025); and MT-RNR1 methylation was positively correlated with mtDNA copy number (r = 0.36; P = 0.02). D-loop methylation was not associated with PM1 exposure. We found no effects on mtDNA methylation from air benzene (Study 2) and traffic-derived EC exposure (Study 3). Conclusions: Mitochondrial MT-TF and MT-RNR1 DNA methylation was associated with metal-rich PM1 exposure and mtDNA copy number. Our results suggest that locus-specific mtDNA methylation is correlated to selected exposures and mtDNA damage. Larger studies are needed to validate our observations

Intakes of magnesium, calcium and risk of fatty liver disease and prediabetes

Objective Obesity and insulin resistance play important roles in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). Mg intake is linked to a reduced risk of metabolic syndrome and insulin resistance; people with NAFLD or alcoholic liver disease are at high risk of Mg deficiency. The present study aimed to investigate whether Mg and Ca intakes were associated with risk of fatty liver disease and prediabetes by alcohol drinking status. Design We analysed the association between Ca or Mg intake and fatty liver disease, prediabetes or both prediabetes and fatty liver disease in cross-sectional analyses. Setting Third National Health and Nutrition Examination Survey (NHANES III) follow-up cohort of US adults. Subjects Nationally representative sample of US adults in NHANES (n 13 489). Results After adjusting for potential confounders, Mg intake was associated with approximately 30 % reduced odds of fatty liver disease and prediabetes, comparing the highest intake quartile v. the lowest. Mg intake may only be related to reduced odds of fatty liver disease and prediabetes in those whose Ca intake is less than 1200 mg/d. Mg intake may also only be associated with reduced odds of fatty liver disease among alcohol drinkers. Conclusions The study suggests that high intake of Mg may be associated with reduced risks of fatty liver disease and prediabetes. Further large studies, particularly prospective cohort studies, are warranted to confirm the findings

APOE ε4 Allele Modifies the Association of Lead Exposure with Age-related Cognitive Decline in Older Individuals

BACKGROUND: Continuing chronic and sporadic high-level of lead exposure in some regions in the U.S. has directed public attention to the effects of lead on human health. Long-term lead exposure has been associated with faster cognitive decline in older individuals; however, genetic susceptibility to lead-related cognitive decline during aging has been poorly studied. METHODS: We determined the interaction of APOE-epsilon variants and environmental lead exposure in relation to age-related cognitive decline. We measured tibia bone lead by K-shell-x-ray fluorescence, APOE-epsilon variants by multiplex PCR and global cognitive z-scores in 489 men from the VA-Normative Aging Study. To determine global cognitive z-scores we incorporated multiple cognitive assessments, including word list memory task, digit span backwards, verbal fluency test, sum of drawings, and pattern comparison task, which were assessed at multiple visits. We used linear mixed-effect models with random intercepts for individual and for cognitive test. RESULTS: An interquartile range (IQR:14.23μg/g) increase in tibia lead concentration was associated with a 0.06 (95% confidence interval [95%CI]: -0.11 to -0.01) lower global cognition z-score. In the presence of both ε4 alleles, one IQR increase in tibia lead was associated with 0.57 (95%CI: -0.97 to -0.16; p-value for interaction: 0.03) lower total cognition z-score. A borderline association was observed in presence of one ε4 allele (Estimate-effect per 1-IQR increase: -0.11, 95%CI: -0.22, 0.01) as well as lack of association in individuals without APOE ε4 allele. CONCLUSIONS: Our findings suggest that individuals carrying both ε4 alleles are more susceptible to lead impact on global cognitive decline during aging

Effects of Particulate Air Pollution on Blood Pressure in a Highly Exposed Population in Beijing, China: A Repeated-Measure Study

Background: Particulate Matter (PM) exposure is critical in Beijing due to high population density and rapid increase in vehicular traffic. PM effects on blood pressure (BP) have been investigated as a mechanism mediating cardiovascular risks, but results are still inconsistent. The purpose of our study is to determine the effects of ambient and personal PM exposure on BP. Methods: Before the 2008 Olympic Games (June 15-July 27), we examined 60 truck drivers and 60 office workers on two days, 1-2 weeks apart (n = 240). We obtained standardized measures of post-work BP. Exposure assessment included personal $PM_{2.5}$ and Elemental Carbon (EC, a tracer of traffic particles) measured using portable monitors during work hours; and ambient $PM_{10}$ averaged over 1-8 days pre-examination. We examined associations of exposures (exposure group, personal $PM_{2.5}/EC$, ambient $PM_{10}$) with BP controlling for multiple covariates. Results: Mean personal $PM_{2.5}$ was $94.6 μg/m^3$ (SD = 64.9) in office workers and 126.8 (SD = 68.8) in truck drivers (p-value 0.14). Personal $PM_{2.5}$ and EC during work hours were not associated with increased BP. Conclusions: Our results indicate delayed effects of ambient $PM_{10}$ on BP. Lack of associations with exposure groups and personal $PM_{2.5}/EC$ indicates that PM effects are related to background levels of pollution in Beijing, and not specifically to work-related exposure

PGS: a tool for association study of high-dimensional microRNA expression data with repeated measures

Motivation: MicroRNAs (miRNAs) are short single-stranded non-coding molecules that usually function as negative regulators to silence or suppress gene expression. Due to interested in the dynamic nature of the miRNA and reduced microarray and sequencing costs, a growing number of researchers are now measuring high-dimensional miRNAs expression data using repeated or multiple measures in which each individual has more than one sample collected and measured over time. However, the commonly used site-by-site multiple testing may impair the value of repeated or multiple measures data by ignoring the inherent dependent structure, which lead to problems including underpowered results after multiple comparison correction using false discovery rate (FDR) estimation and less biologically meaningful results. Hence, new methods are needed to tackle these issues. Results: We propose a penalized regression model incorporating grid search method (PGS), for analyzing association study of high-dimensional microRNA expression data with repeated measures. The development of this analytical framework was motivated by a real-world miRNA dataset. Comparisons between PGS and the site-by-site testing revealed that PGS provided smaller phenotype prediction errors and higher enrichment of phenotype-related biological pathways than the site-by-site testing. Simulation study showed that PGS provided more accurate estimates and higher sensitivity than site-by-site testing with comparable specificities. Availability: R source code for PGS algorithm, implementation example, and simulation study are available for download at https://github.com/feizhe/PGS

Maternal OGTT Glucose Levels at 26–30 Gestational Weeks with Offspring Growth and Development in Early Infancy

Aims. We aim to evaluate the association of maternal gestational oral glucose tolerance test (OGTT) glucose concentrations with anthropometry in the offspring from birth to 12 months in Tianjin, China. Methods:. A total of 27,157 pregnant women underwent OGTT during 26–30 weeks gestation, and their children had body weight/length measured from birth to 12 months old. Results:. Maternal OGTT glucose concentrations at 26–30 gestational weeks were positively associated with Z-scores for birth length-for-gestational age and birth weight-for-length. Compared with infants born to mothers with normal glucose tolerance, infants born to mothers with gestational diabetes mellitus (impaired glucose tolerance/new diabetes) had higher mean values of Z-scores for birth length-for-gestational age (0.07/0.23; normal group −0.08) and birth weight-for-length (0.27/0.57; normal group −0.001), smaller changes in mean values of Z-scores for length-for-age (0.75/0.62; normal group 0.94) and weight-for-length (0.18/−0.17; normal group 0.37) from birth to month 3, and bigger changes in mean values in Z-scores for weight-for-length (0.07/0.12; normal group 0.02) from month 9 to 12. Conclusions:. Abnormal maternal glucose tolerance during pregnancy was associated with higher birth weight and birth length, less weight and length gain in the first 3 months of life, and more weight gain in the months 9–12 of life