Identifying pleiotropic genes via the composite test amidst the complexity of polygenic traits.

Identifying the causal relationship between genotype and phenotype is essential to expanding our understanding of the gene regulatory network spanning the molecular level to perceptible traits. A pleiotropic gene can act as a central hub in the network, influencing multiple outcomes. Identifying such a gene involves testing under a composite null hypothesis where the gene is associated with, at most, one trait. Traditional methods such as meta-analyses of top-hit $P$-values and sequential testing of multiple traits have been proposed, but these methods fail to consider the background of genome-wide signals. Since Huang's composite test produces uniformly distributed $P$-values for genome-wide variants under the composite null, we propose a gene-level pleiotropy test that entails combining the aforementioned method with the aggregated Cauchy association test. A polygenic trait involves multiple genes with different functions to co-regulate mechanisms. We show that polygenicity should be considered when identifying pleiotropic genes; otherwise, the associations polygenic traits initiate will give rise to false positives. In this study, we constructed gene-trait functional modules using the results of the proposed pleiotropy tests. Our analysis suite was implemented as an R package PGCtest. We demonstrated the proposed method with an application study of the Taiwan Biobank database and identified functional modules comprising specific genes and their co-regulated traits.

SpliceAPP: an interactive web server to predict splicing errors arising from human mutations.

BACKGROUND: Splicing variants are a major class of pathogenic mutations, with their severity equivalent to nonsense mutations. However, redundant and degenerate splicing signals hinder functional assessments of sequence variations within introns, particularly at branch sites. We have established a massively parallel splicing assay to assess the impact on splicing of 11,191 disease-relevant variants. Based on the experimental results, we then applied regression-based methods to identify factors determining splicing decisions and their respective weights. RESULTS: Our statistical modeling is highly sensitive, accurately annotating the splicing defects of near-exon intronic variants, outperforming state-of-the-art predictive tools. We have incorporated the algorithm and branchpoint information into a web-based tool, SpliceAPP, to provide an interactive application. This user-friendly website allows users to upload any genetic variants with genome coordinates (e.g., chr15 74,687,208 A G), and the tool will output predictions for splicing error scores and evaluate the impact on nearby splice sites. Additionally, users can query branch site information within the region of interest. CONCLUSIONS: In summary, SpliceAPP represents a pioneering approach to screening pathogenic intronic variants, contributing to the development of precision medicine. It also facilitates the annotation of splicing motifs. SpliceAPP is freely accessible using the link https://bc.imb.sinica.edu.tw/SpliceAPP . Source code can be downloaded at https://github.com/hsinnan75/SpliceAPP .

Genome-wide multimediator analyses using the generalized Berk-Jones statistics with the composite test.

MOTIVATION: Mediation analysis is performed to evaluate the effects of a hypothetical causal mechanism that marks the progression from an exposure, through mediators, to an outcome. In the age of high-throughput technologies, it has become routine to assess numerous potential mechanisms at the genome or proteome scales. Alongside this, the necessity to address issues related to multiple testing has also arisen. In a sparse scenario where only a few genes or proteins are causally involved, conventional methods for assessing mediation effects lose statistical power because the composite null distribution behind this experiment cannot be attained. The power loss hence decreases the true mechanisms identified after multiple testing corrections. To fairly delineate a uniform distribution under the composite null, Huang (Genome-wide analyses of sparse mediation effects under composite null hypotheses. Ann Appl Stat 2019a;13:60-84; AoAS) proposed the composite test to provide adjusted P-values for single-mediator analyses. RESULTS: Our contribution is to extend the method to multimediator analyses, which are commonly encountered in genomic studies and also flexible to various biological interests. Using the generalized Berk-Jones statistics with the composite test, we proposed a multivariate approach that favors dense and diverse mediation effects, a decorrelation approach that favors sparse and consistent effects, and a hybrid approach that captures the edges of both approaches. Our analysis suite has been implemented as an R package MACtest. The utility is demonstrated by analyzing the lung adenocarcinoma datasets from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium. We further investigate the genes and networks whose expression may be regulated by smoking-induced epigenetic aberrations. AVAILABILITY AND IMPLEMENTATION: An R package MACtest is available on https://github.com/roqe/MACtest.

Exposure to PM2.5 Metal Constituents and Liver Cancer Risk in REVEAL-HBV.

BACKGROUND: Ambient particulate matter is classified as a human Class 1 carcinogen, and recent studies found a positive relationship between fine particulate matter (PM2.5) and liver cancer. Nevertheless, little is known about which specific metal constituent contributes to the development of liver cancer. OBJECTIVE: To evaluate the association of long-term exposure to metal constituents in PM2.5 with the risk of liver cancer using a Taiwanese cohort study. METHODS: A total of 13,511 Taiwanese participants were recruited from the REVEAL-HBV in 1991-1992. Participants' long-term exposure to eight metal constituents (Ba, Cu, Mn, Sb, Zn, Pb, Ni, and Cd) in PM2.5 was based on ambient measurement in 2002-2006 followed by a land-use regression model for spatial interpolation. We ascertained newly developed liver cancer (ie, hepatocellular carcinoma [HCC]) through data linkage with the Taiwan Cancer Registry and national health death certification in 1991-2014. A Cox proportional hazards model was utilized to assess the association between exposure to PM2.5 metal component and HCC. RESULTS: We identified 322 newly developed HCC with a median follow-up of 23.1 years. Long-term exposure to PM2.5 Cu was positively associated with a risk of liver cancer. The adjusted hazard ratio (HR) was 1.13 (95% confidence interval [CI], 1.02-1.25; P = 0.023) with one unit increment on Cu normalized by PM2.5 mass concentration in the logarithmic scale. The PM2.5 Cu-HCC association remained statistically significant with adjustment for co-exposures to other metal constituents in PM2.5. CONCLUSION: Our findings suggest PM2.5 containing Cu may attribute to the association of PM2.5 exposure with liver cancer.

Causal mediation analyses for the natural course of hepatitis C: a prospective cohort study.

BackgroundHepatitis C virus (HCV) infection is a systemic disease. However, the relative contribution of intrahepatic and extrahepatic diseases to mediating HCV-induced mortality is unclear, albeit critical in resource allocation for reducing preventable deaths. To this end, this study comprehensively quantified the extent to which intrahepatic and extrahepatic diseases mediate HCV-induced mortality.MethodsA community-based cohort study with >25 years of follow-up was conducted in Taiwan. HCV infection was profiled by antibodies against HCV and HCV RNA in participants' serum samples. The cohort data were linked to Taiwan's National Health Insurance Research Database to determine the incidences of potential mediating diseases and mortality. We employed causal mediation analyses to estimate the mediation effects of HCV on mortality in relation to the incidences of 34 candidate diseases.ResultsIn 18,972 participants with 934 HCV infection, we observed that 54.1% of HCV-induced mortality was mediated by intrahepatic diseases, such as liver cirrhosis and liver cancer, and 45.9% of mortality was mediated by extrahepatic diseases. The major extrahepatic mediating diseases included septicemia (estimated proportion of HCV-induced mortality mediated through the disease: 25.2%), renal disease (16.7%), blood/immune diseases (12.2%), gallbladder diseases (9.7%), and endocrine diseases (9.6%). In women, hypertension (20.0%), metabolic syndrome (18.9%), and type 2 diabetes (17.0%) also mediated HCV-induced mortality. A dose-response relationship of HCV viral load was further demonstrated for the mediation effect.ConclusionBoth intrahepatic and extrahepatic manifestations mediated approximately a half of HCV-induced mortality. The mediation mechanisms are supported by a dose-response relationship of HCV viral load.

Model-based hypothesis tests for the causal mediation of semi-competing risks.

Analyzing the causal mediation of semi-competing risks has become important in medical research. Semi-competing risks refers to a scenario wherein an intermediate event may be censored by a primary event but not vice versa. Causal mediation analyses decompose the effect of an exposure on the primary outcome into an indirect (mediation) effect: an effect mediated through a mediator, and a direct effect: an effect not through the mediator. Here we proposed a model-based testing procedure to examine the indirect effect of the exposure on the primary event through the intermediate event. Under the counterfactual outcome framework, we defined a causal mediation effect using counting process. To assess statistical evidence for the mediation effect, we proposed two tests: an intersection-union test (IUT) and a weighted log-rank test (WLR). The test statistic was developed from a semi-parametric estimator of the mediation effect using a Cox proportional hazards model for the primary event and a series of logistic regression models for the intermediate event. We built a connection between the IUT and WLR. Asymptotic properties of the two tests were derived, and the IUT was determined to be a size [Formula: see text] test and statistically more powerful than the WLR. In numerical simulations, both the model-based IUT and WLR can properly adjust for confounding covariates, and the Type I error rates of the proposed methods are well protected, with the IUT being more powerful than the WLR. Our methods demonstrate the strongly significant effects of hepatitis B or C on the risk of liver cancer mediated through liver cirrhosis incidence in a prospective cohort study. The proposed method is also applicable to surrogate endpoint analyses in clinical trials.

Inhibition of Viral Replication Reduces Transcriptionally Active Distinct Hepatitis B Virus Integrations With Implications on Host Gene Dysregulation.

BACKGROUND & AIMS: Hepatocellular carcinogenesis of hepatitis B virus (HBV) infection may arise from integration of viral DNA into the host genome. We aimed to gauge the effect of viral inhibition on transcriptionally active HBV-host integration events and explore the correlation of viral integrations with host gene dysregulation. METHODS: We leveraged data and biospecimens from an interventional trial, in which patients with HBV viremia above 2000 IU/mL and minimally raised serum liver enzyme were randomized to receive tenofovir disoproxil fumarate (TDF) or placebo for 3 years. Total RNA-sequencing was performed on paired liver biopsies taken before and after the 3-year intervention in 119 patients. Virus-host chimeric reads were captured to quantify the number of distinct viral integrations. Dysregulation of a host gene disrupted by viral integration was defined by aberrant expression >2 standard deviations away from samples without viral integration. RESULTS: The TDF (n = 64) and placebo groups (n = 55) were comparable at baseline. Expressed viral integrations were detected in all pre- and posttreatment samples. The number of distinct viral integrations significantly correlated with circulatory biomarkers indicative of viral activities including HBV DNA, RNA, and viral antigens (P < .0003 for all correlations). Moreover, TDF vs placebo achieved a significantly greater reduction in distinct viral integrations, with 3.28-fold and 1.81-fold decreases in the expressed integrations per million reads, respectively (analysis of covariance, P = .037). Besides, viral integrations significantly correlated with host gene dysregulation. CONCLUSION: Inhibition of viral replication reduces the number of transcriptionally active distinct HBV-host DNA integrations in patients with substantial viremia. Given the mutagenic potentials of viral integrations, such treatment effects should be considered in patient management.

Unified semicompeting risks analysis of hepatitis natural history through mediation modeling.

Natural history of hepatitis B or C is comprised of multiple milestones such as liver cirrhosis and liver cancer. To fully characterize its natural course, semicompeting risks represent a common problem where liver cirrhosis and liver cancer are both of interest, but only the former may be censored by the latter. Copula, frailty and multistate models serve as well-established analytics for semicompeting risks. Here, we cast the semicompeting risks in a mediation framework, with liver cirrhosis as a mediator and liver cancer as an outcome. We define the indirect and direct effects as the effects of an exposure on the liver cancer incidence mediated and not mediated through liver cirrhosis, respectively. With the estimands derived as conditional probabilities, we derive respective expressions under the copula, frailty, and multistate models. Next, we propose estimators based on nonparametric maximum likelihood or U-statistics and establish their asymptotic results. Numerical studies demonstrate that the efficiency of copula models leads to potential bias due to model misspecification. Moreover, the robustness of frailty models is accompanied by a loss in efficiency, and multistate models balance the efficiency and robustness. We demonstrate the utility of the proposed methods by a hepatitis study, showing that hepatitis B and C lead to a higher incidence of liver cancer by increasing liver cirrhosis incidence. Thus, mediation modeling provides a unified framework that accommodates various semicompeting risks models.

Familial aggregation and shared genetic loading for major psychiatric disorders and type 2 diabetes.

AIMS/HYPOTHESIS: Psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BPD), are highly comorbid with type 2 diabetes. However, the mechanisms underlying such comorbidity are understudied. This study explored the familial aggregation of common psychiatric disorders and type 2 diabetes by testing family history association, and investigated the shared genetic loading between them by testing the polygenic risk score (PRS) association. METHODS: A total of 105,184 participants were recruited from the Taiwan Biobank, and genome-wide genotyping data were available for 95,238 participants. The Psychiatric Genomics Consortium-derived PRS for SCZ, MDD and BPD was calculated. Logistic regression was used to estimate the OR with CIs between a family history of SCZ/MDD/BPD and a family history of type 2 diabetes, and between the PRS and the risk of type 2 diabetes. RESULTS: A family history of type 2 diabetes was associated with a family history of SCZ (OR 1.23, 95% CI 1.08, 1.40), MDD (OR 1.19, 95% CI 1.13, 1.26) and BPD (OR 1.26, 95% CI 1.15, 1.39). Compared with paternal type 2 diabetes, maternal type 2 diabetes was associated with a higher risk of a family history of SCZ. SCZ PRS was negatively associated with type 2 diabetes in women (OR 0.92, 95% CI 0.88, 0.97), but not in men; the effect of SCZ PRS reduced after adjusting for BMI. MDD PRS was positively associated with type 2 diabetes (OR 1.04, 95% CI 1.00, 1.07); the effect of MDD PRS reduced after adjusting for BMI or smoking. BPD PRS was not associated with type 2 diabetes. CONCLUSIONS/INTERPRETATION: The comorbidity of type 2 diabetes with psychiatric disorders may be explained by shared familial factors. The shared polygenic loading between MDD and type 2 diabetes implies not only pleiotropy but also a shared genetic aetiology for the mechanism behind the comorbidity. The negative correlation between polygenic loading for SCZ and type 2 diabetes implies the role of environmental factors.

Mediators linking obesity to childhood asthma.

BACKGROUND: Obesity and asthma are highly associated, but the mechanisms underlying the association remain unknown. We examined five mediators linking obesity with childhood asthma: (1) pulmonary function impairment, (2) airway inflammation, (3) physical fitness, (4) sleep-disordered breathing (SDB), and (5) early puberty. METHODS: A Mendelian randomization (MR) study with mediation analysis of data obtained from 5965 children as part of the Taiwan Children Health Study. Observational analysis, MR two-stage least-squares method, and MR sensitivity analysis were carried out to investigate each causal pathway. Prospective cohort analyses were used to strengthen the findings. RESULTS: The increased asthma risk associated with obesity was found to be mostly mediated through impaired pulmonary function, low physical fitness, and early puberty. In the MR analysis, body mass index was negatively associated with FEV1/FVC and physical fitness index (ß = -2.17 and -0.71; 95% CI, -3.92 to -0.42 and -1.30 to -0.13, respectively) and positively associated with early puberty (OR, 1.09; 95% CI, 1.02-1.17). High FEV1/FVC and physical fitness index reduced asthma risk (OR, 0.98 and 0.93; 95% CI, 0.97-0.99 and 0.88-0.98, respectively), whereas SDB and early puberty increased the risk of asthma (OR, 1.03 and 1.22; 95% CI, 1.01-1.05 and 1.05-1.42, respectively). Temporal causality was strengthened in prospective cohort analyses. The three main mediators were low physical fitness, impaired pulmonary function, and early puberty, with mediation proportions of 73.76%, 61.63%, and 27.66%, respectively. CONCLUSIONS: Interventions promoting physical fitness and pulmonary function might effectively reduce obesity-induced asthma risk.

Hypothesis test for causal mediation of time-to-event mediator and outcome.

Hepatitis B has been a well-documented risk factor of liver cancer and mortality. To what extent hepatitis B affects mortality through increasing liver cancer incidence is of research interest and remains to be studied. We formulate the research question as a hypothesis testing problem of causal mediation where both the mediator and the outcome are time-to-event variables. The problem is closely related to semicompeting risks because time to the intermediate event may be censored by an occurrence of the outcome. We propose two hypothesis testing methods: a weighted log-rank test (WLR) and an intersection-union test (IUT). A test statistic of the WLR is constructed by adapting a nonparametric estimator of the mediation effect; however, the test may be conservative regarding its Type I Error rate. To address this, we further propose the IUT, the test statistic of which is constructed under the composite null hypothesis. Asymptotic properties of the two tests are studied, showing that the IUT is a size α test with better statistical power than the WLR. The theoretical properties are supported by extensive simulation studies under finite samples. Applying the proposed methods to the motivating hepatitis study, both WLR and IUT provided strong evidence that hepatitis B had a significant mediation effect on mortality via liver cancer incidence.

Application of Risk Scores for Hepatocellular Carcinoma in Patients with Chronic Hepatitis B: Current Status and Future Perspective.

Accurate risk prediction for hepatocellular carcinoma (HCC) among patients with chronic hepatitis B (CHB) may guide treatment strategies including initiation of antiviral therapy and also inform implementation of HCC surveillance. There have been 26 risk scores developed to predict HCC in CHB patients with (n = 14) or without (n = 12) receiving antiviral treatment; all of them invariably include age in the scoring formula. Virological biomarkers of replicative activities (i.e., hepatitis B virus DNA level or hepatitis B envelope antigen status) are frequently included in the scores derived from patients with untreated CHB, whereas measurements that gauge severity of liver fibrosis and/or reserve of hepatic function (i.e., cirrhosis diagnosis, liver stiffness measurement, platelet count, or albumin) are essential components in the scores developed from treated patients. External validation is a prerequisite for clinical application but not yet performed for all scores. For the future, higher predictive accuracy may be achieved with machine learning based on more comprehensive data.

Epidemiology of Virus Infection and Human Cancer.

Seven viruses including the Epstein-Barr virus (EBV), hepatitis B virus (HBV), hepatitis C virus (HCV), Kaposi's sarcoma herpes virus (KSHV), human immunodeficiency virus, type-1 (HIV-1), human T cell lymphotrophic virus, type-1 (HTLV-1), and human papillomavirus (HPV) have been classified as Group 1 human carcinogens by the International Agency for Research on Cancer (IARC). The conclusions are based on the findings of epidemiological and mechanistic studies. EBV, HPV, HTLV-1, and KSHV are direct carcinogens; HBV and HCV are indirect carcinogens through chronic inflammation; and HIV-1 is an indirect carcinogen through immune suppression. Some viruses may cause more than one cancer, while some cancers may be caused by more than one virus. However, only a proportion of persons infected by these oncogenic viruses will develop specific cancers. A series of studies have been carried out to assess the viral, host, and environmental cofactors of EBV-associated nasopharyngeal carcinoma, HBV/HCV-associated hepatocellular carcinoma, and HPV-associated cervical carcinoma. Persistent infection, high viral load, and viral genotype are important risk predictors of these virus-caused cancers. Risk calculators incorporating host and viral risk predictors have been developed for the prediction of long-term risk of hepatocellular carcinoma, nasopharyngeal carcinoma and cervical cancer. These risk calculators are useful for the triage and clinical management of infected patients. Both clinical trials and national programs of immunization, antiviral therapy and screening have demonstrated a significant reduction in the incidence of cancers caused by HBV, HCV, and HPV. Future research on gene-gene and gene-environment interactions of oncogenic viruses and the human host using large-scale longitudinal studies with serial measurements of biosignatures are in urgent need.

Causal mediation of semicompeting risks.

The semi-competing risks problem arises when one is interested in the effect of an exposure or treatment on both intermediate (e.g., having cancer) and primary events (e.g., death) where the intermediate event may be censored by the primary event, but not vice versa. Here we propose a nonparametric approach casting the semi-competing risks problem in the framework of causal mediation modeling. We set up a mediation model with the intermediate and primary events, respectively as the mediator and the outcome, and define an indirect effect as the effect of the exposure on the primary event mediated by the intermediate event and a direct effect as that not mediated by the intermediate event. A nonparametric estimator with time-varying weights is proposed for direct and indirect effects where the counting process at time t of the primary event N2n1(t) and its compensator An1(t) are both defined conditional on the status of the intermediate event right before t, N1(t-)=n1 . We show that N2n1(t)-An1(t) is a zero-mean martingale. Based on this, we further establish theoretical properties for the proposed estimators. Simulation studies are presented to illustrate the finite sample performance of the proposed method. Its advantage in causal interpretation over existing methods is also demonstrated in a hepatitis study.

Association Between Traffic Count and Cardiovascular Mortality: A Prospective Cohort Study in Taiwan.

BACKGROUND: Exposure to traffic-related pollution is positively associated with cardiovascular diseases (CVD), but little is known about how different sources of traffic pollution (eg, gasoline-powered cars, diesel-engine vehicles) contribute to CVD. Therefore, we evaluated the association between exposure to different types of engine exhaust and CVD mortality. METHODS: We recruited 12,098 participants from REVEAL-HBV cohort in Taiwan. The CVD mortality in 2000-2014 was ascertained by the Taiwan Death Certificates. Traffic pollution sources (2005-2013) were based on information provided by the Directorate General of Highway in 2005. Exposure to PM2.5 was based on a land-use regression model. We applied Cox proportional hazard models to assess the association of traffic vehicle exposure and CVD mortality. A causal mediation analysis was applied to evaluate the mediation effect of PM2.5 on the relationship between traffic and CVD mortality. RESULTS: A total of 382 CVD mortalities were identified from 2000 to 2014. We found participants exposed to higher volumes of small car and truck exhausts had an increased CVD mortality. The adjusted hazard ratio (HR) was 1.10 for small cars (95% confidence interval [CI], 0.94-1.27; P-value = 0.23) and 1.24 for truck (95% CI, 1.03-1.51; P-value = 0.03) per one unit increment of the logarithm scale. The findings were still robust with further adjustment for different types of vehicles. A causal mediation analysis revealed PM2.5 had an over 60% mediation effect on traffic-CVD association. CONCLUSIONS: Exposure to exhaust from trucks or gasoline-powered cars is positively associated with CVD mortality, and air pollution may play a role in this association.

Estimating the causal effect of embryo transfer day on clinical in vitro fertilization outcomes using propensity score matching.

BACKGROUND: For women undergoing in vitro fertilization (IVF), the clinical benefit of embryo transfer at the blastocyst stage (Day 5) versus cleavage stage (Day 3) remains controversial. The purpose of this study is to compare the implantation rate, clinical pregnancy rate and odds of live birth of Day 3 and Day 5 embryo transfer, and more importantly, to address the issue that patients were chosen to receive either transfer protocol due to their underlying clinical characteristics, i.e., confounding by indication. METHODS: We conducted a retrospective cohort study of 9,090 IVF cycles collected by Lee Women's Hospital in Taichung, Taiwan from 1998 to 2014. We utilized the method of propensity score matching to mimic a randomized controlled trial (RCT) where each patient with Day 5 transfer was matched by another patient with Day 3 transfer with respect to other clinical characteristics. Implantation rate, clinical pregnancy rate, and odds of live birth were compared for women underwent Day 5 transfer and Day 3 transfer to estimate the causal effects. We further investigated the causal effects in subgroups by stratifying age and anti-Mullerian hormone (AMH). RESULTS: Our analyses uncovered an evidence of a significant difference in implantation rate (p=0.04) favoring Day 5 transfer, and showed that Day 3 and Day 5 transfers made no difference in both odds of live birth (p=0.27) and clinical pregnancy rate (p=0.11). With the increase of gestational age, the trend toward non-significance of embryo transfer day in our result appeared to be consistent for subgroups stratified by age and AMH, while all analyses stratified by age and AMH were not statistically significant. CONCLUSIONS: We conclude that for women without strong indications for Day 3 or Day 5 transfer, there is a small significant difference in implantation rate in favor of Day 5 transfer. However, the two protocols have indistinguishable outcomes on odds of live birth and clinical pregnancy rate.

Leveraging cell-specific differentially methylated regions to identify leukocyte infiltration in adipose tissue.

Obesity is understood to be an inflammatory condition characterized in part by changes in resident immune cell populations in adipose tissue. However, much of this knowledge has been obtained through experimental animal models. Epigenetic mechanisms, such as DNA methylation may be useful tools for characterizing the changes in immune cell populations in human subjects. In this study, we introduce a simple and intuitive method for assessing cellular infiltration by blood into other heterogeneous, admixed tissues such as adipose tissue, and apply this approach in a large human cohort study. Associations between higher leukocyte infiltration, measured by evaluating a distance measure between the methylation signatures of leukocytes and adipose tissue, and increasing body mass index (BMI) or android fat mass (AFM) were identified and validated in independent replication samples for CD4 (pBMI = 0.009, pAFM = 0.020), monocytes (pBMI = 0.001, pAFM = 4.3 × 10-4 ), and dendritic cells (pBMI = 0.571, pAFM = 0.012). Patterns of depletion with increasing adiposity were observed for plasma B (pBMI = 0.430, pAFM = 0.004) and immature B (pBMI = 0.022, pAFM = 0.042) cells. CD4, dendritic, monocytes, immature B, and plasma B cells may be important agents in the inflammatory process. Finally, the method used to assess leukocyte infiltration in this study is straightforwardly extended to other cell types and tissues in which infiltration might be of interest.

High Level of Hepatitis B Core-Related Antigen Associated With Increased Risk of Hepatocellular Carcinoma in Patients With Chronic HBV Infection of Intermediate Viral Load.

BACKGROUND & AIMS: Chronic hepatitis B virus (HBV) infection is a risk factor for hepatocellular carcinoma (HCC). Serum levels of HB core-related antigen (HBcrAg) have been associated with active replication of HBV. We investigated whether HBcrAg levels are associated with development of HCC, especially in patients who do not require antiviral treatment. METHODS: We collected data from 2666 adults positive for hepatitis B surface antigen (HBsAg), infected with HBV genotypes B or C, and without liver cirrhosis, who had long-term follow-up at the National Taiwan University Hospital from 1985 through 2000. None of the patients received antiviral treatment during the follow-up. Baseline levels of HBV DNA, HBsAg, and HBcrAg were determined retrospectively and participants were followed for a mean of 15.95 years. The primary end point was an association between serum level of HBcrAg and HCC development. RESULTS: HCC developed in 209 patients in the cohort (incidence rate, 4.91 cases/1000 person-years). We found a positive association between baseline level of HBcrAg and HCC development; HBcrAg level was an independent risk factor in multivariable analysis. In the subgroup of hepatitis B e antigen-negative patients with HBV DNA levels from 2000 to 19,999 IU/mL (intermediate viral load [IVL]) and normal levels of alanine aminotransferase, HBcrAg levels of 10 KU/mL or more identified patients at increased risk of HCC (hazard ratio, 6.29; confidence interval, 2.27-17.48). Patients with an IVL and a high level of HBcrAg had a risk for HCC that did not differ significantly from that of patients with a high viral load (≥20,000 IU/mL). Patients with an IVL but a low level of HBcrAg had a low risk of HCC, with an annual incidence rate of 0.10% (95% confidence interval, 0.04%-0.24%). CONCLUSIONS: In a long-term follow-up study of 2666 patients with chronic HBV infection (genotypes B or C), level of HBcrAg is an independent risk factor of HCC. Moreover, HBcrAg level of 10 KU/mL identifies patients with an IVL who are at high risk for HCC.

Tenofovir Versus Entecavir for Hepatocellular Carcinoma Prevention in an International Consortium of Chronic Hepatitis B.

INTRODUCTION: It is unclear whether entecavir (ETV) and tenofovir disoproxil fumarate (TDF) differ in their effectiveness for preventing hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). METHODS: This retrospective cohort study analyzed an international consortium that encompassed 19 centers from 6 countries or regions composed of previously untreated CHB patients then treated with either ETV or TDF monotherapy. Those who developed HCC before antiviral treatment or within 1 year of therapy were excluded. The association between antiviral regimen and HCC risk was evaluated using competing-risk survival regression. We also applied propensity score matching (PSM) to 1:1 balance the 2 treatment cohorts. A total of 5,537 patients were eligible (n = 4,837 received ETV and n = 700 received TDF) and observed for HCC occurrence until December 23, 2018. Before PSM, the TDF cohort was significantly younger and had generally less advanced diseases. RESULTS: In the unadjusted analysis, TDF was associated with a lower risk of HCC (subdistribution hazard ratio [SHR], 0.45; 95% confidence interval [CI], 0.26-0.79; P = 0.005). The multivariable analysis, however, found that the association between TDF and HCC no longer existed (SHR, 0.81; 95% CI, 0.42-1.56; P = 0.52) after adjustment for age, sex, country, albumin, platelet, α-fetoprotein, cirrhosis, and diabetes mellitus. Furthermore, the PSM analysis (n = 1,040) found no between-cohort differences in HCC incidences (P = 0.51) and no association between regimens (TDF or ETV) and HCC risk in the multivariable-adjusted analysis (adjusted SHR, 0.89; 95% CI, 0.41-1.92; P = 0.77). DISCUSSION: TDF and ETV did not significantly differ in the prevention of HCC in patients with CHB.

The causal role of elevated uric acid and waist circumference on the risk of metabolic syndrome components.

BACKGROUND/OBJECTIVES: Hyperuricemia has been found to cluster with multiple components of metabolic syndrome (MetS). It is unclear whether hyperuricemia is a downstream result of MetS or may play an upstream role in MetS development. Using the Mendelian randomization (MR) method, we examined the causal relationship between elevated uric acid and the various components of MetS with waist circumference as a positive control. SUBJECTS/METHODS: Data from 10k participants of Taiwan Biobank was used to carry out MR analysis with uric acid risk score (wGRS) and waist circumference wGRS as instrumental variables and components of MetS as the outcomes. RESULTS: We found that genetically increased serum uric acid corresponds to a significant increment of triglyceride (ß = 0.065, p < 0.0001), systolic blood pressure (ß = 1.047, p = 0.0005), diastolic blood pressure (ß = 0.857, p < 0.0001), and mean arterial pressure (ß = 0.920, p < 0.0001), but a significant reduction of high-density lipoprotein cholesterol (ß = -0.020, p = 0.0014). Uric acid wGRS was not associated with fasting serum glucose, HbA1C, waist circumference, or BMI. On the other hand, waist circumference was causally associated with all the components of MetS including uric acid. CONCLUSIONS: Our MR investigation shows that uric acid increment may augment the risk of MetS through increasing blood pressure and triglyceride levels and lowering HDL-C value but not through accumulating fat or hyperglycemia. High waist circumference may be a causal agent for all the components of MetS including hyperuricemia.