A Bayesian approach to differential edges with probabilistic interactions: applications in association and classification.

Motivation: Differential network (D-Net) analysis has attracted great attention in systems biology for its ability to identify genetic variations in response to different conditions. Current approaches either estimate the condition-specific networks separately followed by post-procedures to determine the differential edges or estimate the D-Net directly. Both types of analysis overlook the probabilistic inference and can only provide deterministic inference of the edges. Results: Here, we propose a Bayesian solution and translate the probabilistic estimation in the regression model to an inferential D-Net analysis for genetic association and classification studies. The proposed PRobabilistic Interaction for Differential Edges (PRIDE) focuses on inferring the D-Net with uncertainty so that the existence of the differential edges can be evaluated with probability and even prioritized if comparison among these edges is of interest. The performance of the proposed model is compared with state-of-the-art methods in simulations and is demonstrated in glioblastoma and breast cancer studies. The proposed PRIDE performs comparably to or outperforms most existing tools under deterministic evaluation criteria. Additionally, it offers the unique advantages, including prioritizing the differential edges with probabilities, highlighting the relative importance of hub nodes, and identifying potential sub-networks in a D-Net. Availability and implementation: All the data analyzed in this research can be downloaded at https://xenabrowser.net/datapages/. The R code for implementing PRIDE is available at https://github.com/YJGene0806/PRIDE_Code.

Performance and Operational Feasibility of Epstein-Barr Virus-Based Screening for Detection of Nasopharyngeal Carcinoma: Direct Comparison of Two Alternative Approaches.

PURPOSE: Two Epstein-Barr virus (EBV)-based testing approaches have shown promise for early detection of nasopharyngeal carcinoma (NPC). Neither has been independently validated nor their performance compared. We compared their diagnostic performance in an independent population. METHODS: We tested blood samples from 819 incident Taiwanese NPC cases (213 early-stage, American Joint Committee on Cancer version 7 stages I and II) diagnosed from 2010 to 2014 and from 1,768 controls from the same region, frequency matched to cases on age and sex. We compared an EBV antibody score using immunoglobulin A antibodies measured by enzyme-linked immunosorbent assay (EBV antibody score) and plasma EBV DNA load measured by real-time PCR followed by next-generation sequencing (NGS) among EBV DNA-positive individuals (EBV DNA algorithm). RESULTS: EBV antibodies and DNA load were measured for 2,522 (802 cases; 1,720 controls) and 2,542 (797 cases; 1,745 controls) individuals, respectively. Of the 898 individuals positive for plasma EBV DNA and therefore eligible for NGS, we selected 442 (49%) for NGS testing. The EBV antibody score had a sensitivity of 88.4% (95% CI, 86.1 to 90.6) and a specificity of 94.9% (95% CI, 93.8 to 96.0) for NPC. The EBV DNA algorithm yielded significantly higher sensitivity (93.2%; 95% CI, 91.3 to 94.9; P = 1.33 × 10-4) and specificity (98.1%; 95% CI, 97.3 to 98.8; P = 3.53 × 10-7). For early-stage NPC, the sensitivities were 87.1% (95% CI, 82.7 to 92.4) for the EBV antibody score and 87.0% (95% CI, 81.9 to 91.5) for the EBV DNA algorithm (P = .514). For regions with a NPC incidence of 20-100/100,000 person-years (eg, residents in southern China and Hong Kong), these two approaches yielded similar numbers needed to screen (EBV antibody score: 5,656-1,131; EBV DNA algorithm: 5,365-1,073); positive predictive values ranged from 0.4% to 1.7% and 1.0% to 4.7%, respectively. CONCLUSION: We demonstrated high sensitivity and specificity of EBV antibody and plasma EBV DNA for NPC detection, with slightly inferior performance of the EBV antibody score. Cost-effectiveness studies are needed to guide screening implementation.

Bayesian Approach to Disease Risk Evaluation Based on Air Pollution and Weather Conditions.

BACKGROUND: Environmental factors such as meteorological conditions and air pollutants are recognized as important for human health, where mortality and morbidity of certain diseases may be related to abrupt climate change or air pollutant concentration. In the literature, environmental factors have been identified as risk factors for chronic diseases such as ischemic heart disease. However, the likelihood evaluation of the disease occurrence probability due to environmental factors is missing. METHOD: We defined people aged 51-90 years who were free from ischemic heart disease (ICD9: 410-414) in 1996-2002 as the susceptible group. A Bayesian conditional logistic regression model based on a case-crossover design was utilized to construct a risk information system and applied to data from three databases in Taiwan: air quality variables from the Environmental Protection Administration (EPA), meteorological parameters from the Central Weather Bureau (CWB), and subject information from the National Health Insurance Research Database (NHIRD). RESULTS: People living in different geographic regions in Taiwan were found to have different risk factors; thus, disease risk alert intervals varied in the three regions. CONCLUSIONS: Disease risk alert intervals can be a reference for weather bureaus to issue health warnings. With early warnings, susceptible groups can take measures to avoid exacerbation of disease when meteorological conditions and air pollution become hazardous to their health.

Probabilistic edge inference of gene networks with markov random field-based bayesian learning.

Current algorithms for gene regulatory network construction based on Gaussian graphical models focuses on the deterministic decision of whether an edge exists. Both the probabilistic inference of edge existence and the relative strength of edges are often overlooked, either because the computational algorithms cannot account for this uncertainty or because it is not straightforward in implementation. In this study, we combine the Bayesian Markov random field and the conditional autoregressive (CAR) model to tackle simultaneously these two tasks. The uncertainty of edge existence and the relative strength of edges can be measured and quantified based on a Bayesian model such as the CAR model and the spike-and-slab lasso prior. In addition, the strength of the edges can be utilized to prioritize the importance of the edges in a network graph. Simulations and a glioblastoma cancer study were carried out to assess the proposed model's performance and to compare it with existing methods when a binary decision is of interest. The proposed approach shows stable performance and may provide novel structures with biological insights.

Influence of parental behavior on myopigenic behaviors and risk of myopia: analysis of nationwide survey data in children aged 3 to 18 years.

BACKGROUND: Preventive parental behavior may play an important role in the outcomes of children's myopia. We investigated associations between parental behavior and children's myopia status and daily activities using data from the most recent myopia survey in Taiwan. METHODS: In total, 3845 children aged 3 to 18 years who completely responded to the questionnaire were included (total score ranging from 0 to 75). A score of ≥ 50 was considered to indicate beneficial parental behavior. Time allocation data for near-work activities, using electronic devices, and outdoor activities were collected using a separate self-reported questionnaire. Associations between beneficial parental behavior and children's myopia status and activity patterns were analyzed and stratified by school level. RESULTS: Beneficial parental behavior was positively associated with children's myopia in the overall samples [adj. odds ratio (OR): 1.31, 95% confidence interval (CI): 1.08-1.59, p = 0.006)] and at the elementary school level (adj. OR: 1.43, 95% CI: 1.11-1.83, p = 0.005). However, a negative association with high myopia was observed in the overall samples (adj. OR: 0.71, 95% CI: 0.50-0.99, p = 0.049) and high school level (adj. OR: 0.62, 95% CI: 0.41-0.92, p = 0.02). Beneficial parental behavior was associated with less time spent on near work (≥ 180 min/day) and electronic device use (≥ 60 min/day), but not with outdoor activities. CONCLUSION: In Taiwan, children's myopia is associated with higher rate of parents' beneficial behaviors, which suggests that regular vision surveillance is necessary to promote better parental behavior toward children's eye care. Certain parental practices may influence children's behavior pattern and reduce the risk of children's high myopia development in the long run.

Mitochondrial DNA methylation profiling of the human prefrontal cortex and nucleus accumbens: correlations with aging and drug use.

BACKGROUND: Despite the brain's high demand for energy, research on its epigenetics focuses on nuclear methylation, and much of the mitochondrial DNA methylation remains seldom investigated. With a focus on the nucleus accumbens (NAcc) and the prefrontal cortex (PFC), we aimed to identify the mitochondrial methylation signatures for (1) distinguishing the two brain areas, (2) correlating with aging, and (3) reflecting the influence of illicit drugs on the brain. RESULT: We collected the brain tissue in the NAcc and the PFC from the deceased individuals without (n = 39) and with (n = 14) drug use and used whole-genome bisulfite sequencing to cover cytosine sites in the mitochondrial genome. We first detected differential methylations between the NAcc and the PFC in the nonusers group (P = 3.89 × 10-9). These function-related methylation differences diminished in the drug use group due to the selective alteration in the NAcc. Then, we found the correlation between the methylation levels and the chronological ages in the nonusers group (R2 = 0.34 in the NAcc and 0.37 in the PFC). The epigenetic clocks in illicit drug users, especially in the ketamine users, were accelerated in both brain regions by comparison with the nonusers. Finally, we summarized the effect of the illicit drugs on the methylation, which could significantly differentiate the drug users from the nonusers (AUC = 0.88 in the NAcc, AUC = 0.94 in the PFC). CONCLUSION: The mitochondrial methylations were different between different brain areas, generally accumulated with aging, and sensitive to the effects of illicit drugs. We believed this is the first report to elucidate comprehensively the importance of mitochondrial DNA methylation in human brain.

HYPERREFLECTIVE FOCI AS IMPORTANT PROGNOSTIC INDICATORS OF PROGRESSION OF RETINITIS PIGMENTOSA.

PURPOSE: To investigate the presence and clinical relevance of hyperreflective foci (HRFs) in retinitis pigmentosa. METHODS: Seventy seven retinitis pigmentosa cases were retrospectively reviewed. The 10-mm wide cross-line macular scans in optical coherence tomography were acquired. Hyperreflective foci were classified according to the location in optical coherence tomography: outer layers within the macula (HRF-outer-central), macular border beyond the central 3 mm (HRF-outer-perifoveal), and choroid (HRF-choroidal). The visual acuity at baseline, at 12 months, and other fundus characteristics were collected. RESULTS: The mean logMAR best-corrected visual acuity decreased from 0.59 ± 0.66 (20/78 in Snellen) to 0.74 ± 0.81 (20/106 in Snellen) in 1 year. Sixty-six (42.9%), 105 (68.2%), and 98 (63.6%) eyes were classified to HRF-outer-central, HRF-outer-perifoveal, and HRF-choroidal group, respectively. Hyperreflective foci were positively correlated with poorer vision, central macular thinning, and ellipsoid zone disruption (all P < 0.001). Worse vision was associated with older age, macular involvement, and the coexistence of two or three HRF groups (P = 0.014, 0.047, 0.019, <0.001, respectively). Hyperreflective foci developed more frequently in patients with thick choroid than in those with thin choroid. The coexistence of three HRF groups was correlated with quicker visual deterioration (P = 0.034). CONCLUSION: Hyperreflective foci are common in retinitis pigmentosa and can be a negative prognostic indicator of macular thickness and visual preservation. Thick choroid was associated with all groups of HRFs, especially HRF-choroidal.

The misuse of distributional assumptions in functional class scoring gene-set and pathway analysis.

Gene-set analysis (GSA) is a standard procedure for exploring potential biological functions of a group of genes. The development of its methodology has been an active research topic in recent decades. Many GSA methods, when newly proposed, rely on simulation studies to evaluate their performance with an implicit assumption that the multivariate expression values are normally distributed. This assumption is commonly adopted in GSAs, particularly those in the group of functional class scoring (FCS) methods. The validity of the normality assumption, however, has been disputed in several studies, yet no systematic analysis has been carried out to assess the effect of this distributional assumption. Our goal in this study is not to propose a new GSA method but to first examine if the multi-dimensional gene expression data in gene sets follow a multivariate normal (MVN) distribution. Six statistical methods in three categories of MVN tests were considered and applied to a total of 24 RNA data sets. These RNA values were collected from cancer patients as well as normal subjects, and the values were derived from microarray experiments, RNA sequencing, and single-cell RNA sequencing. Our first finding suggests that the MVN assumption is not always satisfied. This assumption does not hold true in many applications tested here. In the second part of this research, we evaluated the influence of non-normality on the statistical power of current FCS methods, both parametric and nonparametric ones. Specifically, the scenario of mixture distributions representing more than one population for the RNA values was considered. This second investigation demonstrates that the non-normality distribution of the RNA values causes a loss in the statistical power of these GSA tests, especially when subtypes exist. Among the FCS GSA tools examined here and among the scenarios studied in this research, the N-statistics outperform the others. Based on the results from these two investigations, we conclude that the assumption of MVN should be used with caution when evaluating new GSA tools, since this assumption cannot be guaranteed and violation may lead to spurious results, loss of power, and incorrect comparison between methods. If a newly proposed GSA tool is to be evaluated, we recommend the incorporation of a wide range of multivariate non-normal distributions or sampling from large databases if available.

Subgrouping time-dependent prescribing patterns of first-onset major depressive episodes by psychotropics dissection.

BACKGROUND: Subgrouping patients with major depressive disorder is a promising solution for the issue of heterogeneity. However, the link between available subtypes and distinct pathological mechanisms is weak and yields disappointing results in clinical application. AIM: To develop a novel approach for classification of patients with time-dependent prescription patterns at first onset in real-world settings. METHODS: Drug-naive patients experiencing their first major depressive episode (n = 105) participated in this study. Psychotropic agents prescribed in the first 24 mo following disease onset were recorded monthly and categorized as antidepressants, augmentation agents, and hypnosedatives. Monthly cumulative doses of agents in each category were converted into relevant equivalents. Four parameters were used to summarize the time-dependent prescription patterns for each psychotropic load: Stability, amount, frequency, and the time trend of monthly prescriptions. A K-means cluster analysis was used to derive subgroups of participants based on these input parameters of psychotropic agents across 24 mo. Clinical validity of the resulting data-driven clusters was compared using relevant severity indicators. RESULTS: Four distinct clusters were derived from K-means analysis, which matches experts' consent: "Short-term antidepressants use", "long-term antidepressants use", "long-term antidepressants and sedatives use", and "long-term antidepressants, sedatives, and augmentation use". At the first 2 years of disease course, the four clusters differed on the number of antidepressants used at adequate dosage and duration, frequency of outpatient service use, and number of psychiatric admissions. After the first 2 years following disease onset, depression severity was differed in the four subgroups. CONCLUSION: Our findings suggested a new approach to optimize the subgrouping of patients with major depressive disorder, which may assist future etiological and treatment response studies.

An Integrative Co-localization (INCO) Analysis for SNV and CNV Genomic Features With an Application to Taiwan Biobank Data.

Genomic studies have been a major approach to elucidating disease etiology and to exploring potential targets for treatments of many complex diseases. Statistical analyses in these studies often face the challenges of multiplicity, weak signals, and the nature of dependence among genetic markers. This situation becomes even more complicated when multi-omics data are available. To integrate the data from different platforms, various integrative analyses have been adopted, ranging from the direct union or intersection operation on sets derived from different single-platform analysis to complex hierarchical multi-level models. The former ignores the biological relationship between molecules while the latter can be hard to interpret. We propose in this study an integrative approach that combines both single nucleotide variants (SNVs) and copy number variations (CNVs) in the same genomic unit to co-localize the concurrent effect and to deal with the sparsity due to rare variants. This approach is illustrated with simulation studies to evaluate its performance and is applied to low-density lipoprotein cholesterol and triglyceride measurements from Taiwan Biobank. The results show that the proposed method can more effectively detect the collective effect from both SNVs and CNVs compared to traditional methods. For the biobank analysis, the identified genetic regions including the gene VNN2 could be novel and deserve further investigation.

Rare variants discovery by extensive whole-genome sequencing of the Han Chinese population in Taiwan: Applications to cardiovascular medicine.

Introduction: A population-specific genomic reference is important for research and clinical practice, yet it remains unavailable for Han Chinese (HC) in Taiwan. Objectives: We report the first whole genome sequencing (WGS) database of HC (1000 Taiwanese genome (1KTW-WGS)) and demonstrate several applications to cardiovascular medicine. Methods: Whole genomes of 997 HC were sequenced to at least 30X depth. A total of 20,117 relatively healthy HC individuals were genotyped using a customized Axiom GWAS array. We performed a genome-wide genotype imputation technique using IMPUTE2. Results: We identified 26.7 million single-nucleotide variants (SNVs) and 4.2 million insertions-deletions. Of the SNVs, 16.1% were novel relative to dbSNP (build 152), and 34.2% were novel relative to gnomAD. A total of 18,450 healthy HC individuals were genotyped using a customized Genome-Wide Association Study (GWAS) array. We identified hypertension-associated variants and developed a hypertension prediction model based on the correlation between the WGS data and GWAS data (combined clinical and genetic models, AUC 0.887), and also identified 3 novel hyperlipidemia-associated variants. Each individual carried an average of 16.42 (SD = 3.72) disease-causing variants. Additionally, we established an online SCN5A (an important cardiac gene) database that can be used to explore racial differences. Finally, pharmacogenetics studies identified HC population-specific SNVs in genes (CYP2C9 and VKORC1) involved in drug metabolism and blood clotting. Conclusion: This research demonstrates the benefits of constructing a population-specific genomic reference database for precision medicine.

Metabolic Syndromes as Important Comorbidities in Patients of Inherited Retinal Degenerations: Experiences from the Nationwide Health Database and a Large Hospital-Based Cohort.

This study aimed to evaluate the medical and socioeconomic impacts of IRDs using the nationwide health database and a large hospital-based cohort. This retrospective cross-sectional cohort study used data from the nationwide National Health Insurance Research Database (NHIRD). All patients with IRD from January 2012 to December 2016 were selected from the NHIRD and matched with the general population at a ratio of 1:4. All variables, including comorbidities, medications, service utilization, and medical costs, within 1 year from the date of the IRD diagnosis, were analyzed. Disability data were retrieved from the Taiwan Inherited retinal degeneration Project (TIP), a medical center-based database. A total of 4447 and 17,788 subjects from the nationwide database were included in the IRD and control groups, respectively. The Charlson comorbidity index score was higher in the IRD group (0.74:0.52, p < 0.001). Yearly visits to the ophthalmology clinic were more frequent in the IRD group (6.80:1.06, p < 0.001), particularly to tertiary medical centers (p < 0.001). The IRD group showed greater odds ratios (OR) for metabolic syndrome-related comorbidities, including hypertension (OR = 1.18, 95% confidence interval (CI) 1.10 to 1.26) and diabetes (OR = 1.32, 95% CI 1.21 to 1.45), and double the average yearly medical cost (2104.3 vs. 1084.6 USD, p < 0.001) and ten times the yearly ophthalmology cost (369.1 vs. 36.1 USD, p < 0.001). The average disability level was 54.17% for all subjects. This study revealed the large medical and socioeconomic impacts of IRD on not only patients with IRD, but also their family members and the whole society.

Evolution of the Prevalence of Myopia among Taiwanese Schoolchildren: A Review of Survey Data from 1983 through 2017.

PURPOSE: The aim of this study was to evaluate the changes in the prevalence of myopia in Taiwanese schoolchildren over the past few decades and to analyze the risk factors for myopia. DESIGN: Analysis of 8 consecutive population-based myopia surveys conducted from 1983 through 2017. PARTICIPANTS: An average of 8917 (5019-11 656) schoolchildren 3 to 18 years of age were selected using stratified systematic cluster sampling or by probability proportional to size sampling. METHODS: All participants underwent complete ophthalmic evaluations. Three drops of 0.5% tropicamide were used to obtain the cycloplegic refractive status of each participant. Questionnaires were used to acquire participant data from the 1995, 2005, 2010, and 2016 surveys. MAIN OUTCOME MEASURES: Prevalence of myopia (spherical equivalence of ≤-0.25 diopter [D]) and high myopia (≤-6.0 D) was assessed. Multivariate analyses of risk factors were conducted. RESULTS: The prevalence of myopia among all age groups increased steadily. From 1983 through 2017, the weighted prevalence increased from 5.37% (95% confidence interval [CI], 3.50%-7.23%) to 25.41% (95% CI, 21.27%-29.55%) for 7-year-olds (P = 0.001 for trend) and from 30.66% (95% CI, 26.89%-34.43%) to 76.67% (95% CI, 72.94%-80.40%) for 12-year-olds (P = 0.001 for trend). The prevalence of high myopia also increased from 1.39% (95% CI, 0.43%-2.35%) to 4.26% (95% CI, 3.35%-5.17%) for 12-year-olds (P = 0.008 for trend) and from 4.37% (95% CI, 2.91%-5.82%) to 15.36% (95% CI, 13.78%-16.94%) for 15-year-olds (P = 0.039 for trend). In both the 2005 and 2016 survey samples, children who spent less than 180 minutes daily on near-work activities showed significantly lower risks for myopia developing (<60 minutes: odds ratio [OR], 0.48 and 0.56; 60-180 minutes: OR, 0.69 and 0.67). In the 2016 survey, spending more than 60 minutes daily on electronic devices was associated significantly with both myopia and high myopia (OR, 2.43 and 2.31). CONCLUSIONS: The prevalence of myopia among schoolchildren increased rapidly from 1983 through 2017 in Taiwan. The major risk factors are older age and time spent on near-work activities. Use of electronic devices increased the amount of time spent on near-work and may increase the risk of developing myopia.

Association test using Copy Number Profile Curves (CONCUR) enhances power in rare copy number variant analysis.

Copy number variants (CNVs) are the gain or loss of DNA segments in the genome that can vary in dosage and length. CNVs comprise a large proportion of variation in human genomes and impact health conditions. To detect rare CNV associations, kernel-based methods have been shown to be a powerful tool due to their flexibility in modeling the aggregate CNV effects, their ability to capture effects from different CNV features, and their accommodation of effect heterogeneity. To perform a kernel association test, a CNV locus needs to be defined so that locus-specific effects can be retained during aggregation. However, CNV loci are arbitrarily defined and different locus definitions can lead to different performance depending on the underlying effect patterns. In this work, we develop a new kernel-based test called CONCUR (i.e., copy number profile curve-based association test) that is free from a definition of locus and evaluates CNV-phenotype associations by comparing individuals' copy number profiles across the genomic regions. CONCUR is built on the proposed concepts of "copy number profile curves" to describe the CNV profile of an individual, and the "common area under the curve (cAUC) kernel" to model the multi-feature CNV effects. The proposed method captures the effects of CNV dosage and length, accounts for the numerical nature of copy numbers, and accommodates between- and within-locus etiological heterogeneity without the need to define artificial CNV loci as required in current kernel methods. In a variety of simulation settings, CONCUR shows comparable or improved power over existing approaches. Real data analyses suggest that CONCUR is well powered to detect CNV effects in the Swedish Schizophrenia Study and the Taiwan Biobank.

Network hub-node prioritization of gene regulation with intra-network association.

BACKGROUND: To identify and prioritize the influential hub genes in a gene-set or biological pathway, most analyses rely on calculation of marginal effects or tests of statistical significance. These procedures may be inappropriate since hub nodes are common connection points and therefore may interact with other nodes more often than non-hub nodes do. Such dependence among gene nodes can be conjectured based on the topology of the pathway network or the correlation between them. RESULTS: Here we develop a pathway activity score incorporating the marginal (local) effects of gene nodes as well as intra-network affinity measures. This score summarizes the expression levels in a gene-set/pathway for each sample, with weights on local and network information, respectively. The score is next used to examine the impact of each node through a leave-one-out evaluation. To illustrate the procedure, two cancer studies, one involving RNA-Seq from breast cancer patients with high-grade ductal carcinoma in situ and one microarray expression data from ovarian cancer patients, are used to assess the performance of the procedure, and to compare with existing methods, both ones that do and do not take into consideration correlation and network information. The hub nodes identified by the proposed procedure in the two cancer studies are known influential genes; some have been included in standard treatments and some are currently considered in clinical trials for target therapy. The results from simulation studies show that when marginal effects are mild or weak, the proposed procedure can still identify causal nodes, whereas methods relying only on marginal effect size cannot. CONCLUSIONS: The NetworkHub procedure proposed in this research can effectively utilize the network information in combination with local effects derived from marker values, and provide a useful and complementary list of recommendations for prioritizing causal hubs.

Cigarette smoking increases the risk of nasopharyngeal carcinoma through the elevated level of IgA antibody against Epstein-Barr virus capsid antigen: A mediation analysis.

BACKGROUND: The study aims are to evaluate the associations between nasopharyngeal carcinoma (NPC) risk and cigarette smoking and to explore the effects of cigarette smoking on Epstein-Barr virus (EBV) infection for NPC risk. METHODS: 1235 male NPC cases and 1262 hospital-based male controls matched to cases were recruited across six collaborative hospitals between 2010 and 2014. Using a standardized questionnaire, information on cigarette smoking and other potential risk factors for NPC was obtained. Blood was collected and used for anti-EBV VCA IgA and anti-EBV EA-EBNA1 IgA testing using standard methods. Unconditional logistic regression analysis was used to estimate odds ratio (OR) with 95% confidence interval (CI) for each risk factor after adjusting for confounders. RESULTS: 63.6% of cases and 44.0% of controls reported ever smoking cigarettes. After full adjustment, current smokers had a significant 1.60-fold (95% CI = 1.30-1.97) and former smokers a borderline significant 1.27-fold (95% CI = 1.00-1.60) increased NPC risk compared to never smokers. NPC risk increased with increasing duration, intensity, and pack-years of cigarette smoking but not with age at smoking initiation. Among controls, anti-EBV VCA IgA seropositivity rate was higher in current smokers than never smokers (14.0% vs 8.4%; OR = 1.82; 95% CI = 1.19-2.79). Mediation analyses showed that more than 90% of the cigarette smoking effect on NPC risk is mediated through anti-EBV VCA IgA. CONCLUSION: This study confirms the association between long-term cigarette smoking and NPC and demonstrates that current smoking is associated with seropositivity of anti-EBV VCA IgA antibodies.

Evaluation of Rare and Common Variants from Suspected Familial or Sporadic Nasopharyngeal Carcinoma (NPC) Susceptibility Genes in Sporadic NPC.

BACKGROUND: Genetic susceptibility is associated with nasopharyngeal carcinoma (NPC). We previously identified rare variants potentially involved in familial NPC and common variants significantly associated with sporadic NPC. METHODS: We conducted targeted gene sequencing of 20 genes [16 identified from the study of multiplex families, three identified from a pooled analysis of NPC genome-wide association study (GWAS), and one identified from both studies] among 819 NPC cases and 938 controls from two case-control studies in Taiwan (independent from previous studies). A targeted, multiplex PCR primer panel was designed using the custom Ion AmpliSeq Designer v4.2 targeting the regions of the selected genes. Gene-based and single-variant tests were conducted. RESULTS: We found that NPC was associated with combined common and rare variants in CDKN2A/2B (P = 1.3 × 10-4), BRD2 (P = 1.6 × 10-3), TNFRSF19 (P = 4.0 × 10-3), and CLPTM1L/TERT (P = 5.4 × 10-3). Such associations were likely driven by common variants within these genes, based on gene-based analyses evaluating common variants and rare variants separately (e.g., for common variants of CDKN2A/2B, P = 4.6 × 10-4; for rare variants, P = 0.04). We also observed a suggestive association with rare variants in HNRNPU (P = 3.8 × 10-3) for NPC risk. In addition, we validated four previously reported NPC risk-associated SNPs. CONCLUSIONS: Our findings confirm previously reported associated variants and suggest that some common variants in genes previously linked to familial NPC are associated with the development of sporadic NPC. IMPACT: NPC-associated genes, including CLPTM1L/TERT, BRD2, and HNRNPU, suggest a role for telomere length maintenance in NPC etiology.

Globally temporal transitions of blood lead levels of preschool children across countries of different categories of Human Development Index.

In the past decades, efforts to eliminate lead from gasoline, paint and drinking water around the world have substantially reduced human blood lead levels. This study was therefore aimed at examining the global temporal trends in the blood lead levels of preschool children by the category of UN Human Development Index (HDI). In total, 103 blood lead records were retrieved from 51 articles searched from PubMed and Google Scholar, with study subjects aged up to 8years old. Collected preschool children blood lead levels were plotted chronologically by HDI category and their reciprocals were used in regression analysis against calendar year to establish their temporal transition trends in the past decades. Results show that the modes of blood lead level of the preschool children were reduced from 4-6µg/dL to 0.8-1.5µg/dL, from 6-15µg/dL to 3-6µg/dL and from 12-16 to 5-6µg/dL for the very high HDI countries, the high HDI countries and the medium/low HDI countries, respectively. The highest correlation coefficient, 0.849, between the reciprocal of blood lead level and the calendar year was found for the very high HDI countries. Based on the regression lines, the predicted preschool children mean blood lead levels in the year of 2030 are 0.74µg/dL, 2.21µg/dL and 2.86µg/dL, respectively, for the very high HDI countries, the high HDI countries and the medium/low HDI countries. Persistent differences in blood lead level prevailed among countries of different HDI category, suggesting the effects of disparities and inequalities, at the state level, on preschool children blood lead levels. Further action is warranted to reduce the already low environmental lead exposure to eliminate the developmental burden of lead on children through (1) identification of individual local factors for lead exposure and (2) averting health disparity and inequalities at the state level.