Association of healthy lifestyle behaviours with incident irritable bowel syndrome: a large population-based prospective cohort study.

OBJECTIVES: To evaluate the association between healthy lifestyle behaviours and the incidence of irritable bowel syndrome (IBS). DESIGN: Population-based prospective cohort study. SETTING: The UK Biobank. PARTICIPANTS: 64 268 adults aged 37 to 73 years who had no IBS diagnosis at baseline were enrolled between 2006 and 2010 and followed up to 2022. MAIN EXPOSURE: The five healthy lifestyle behaviours studied were never smoking, optimal sleep, high level of vigorous physical activity, high dietary quality and moderate alcohol intake. MAIN OUTCOME MEASURE: The incidence of IBS. RESULTS: During a mean follow-up of 12.6 years, 961 (1.5%) incident IBS cases were recorded. Among the 64 268 participants (mean age 55.9 years, 35 342 (55.0%) female, 7604 (11.8%) reported none of the five healthy lifestyle behaviours, 20 662 (32.1%) reported 1 behaviour, 21 901 (34.1%) reported 2 behaviours and 14 101 (21.9%) reported 3 to 5 behaviours at baseline. The multivariable adjusted hazard ratios associated with having 1, 2 and 3 to 5 behaviours for IBS incidence were 0.79 (95% confidence intervals 0.65 to 0.96), 0.64 (0.53 to 0.78) and 0.58 (0.46 to 0.72), respectively (P for trend <0.001). Never smoking (0.86, 0.76 to 0.98, P=0.02), high level of vigorous physical activity (0.83, 0.73 to 0.95, P=0.006) and optimal sleep (0.73, 0.60 to 0.88, P=0.001) demonstrated significant independent inverse associations with IBS incidence. No significant interactions were observed between these associations and age, sex, employment status, geographic location, gastrointestinal infection, endometriosis, family history of IBS or lifestyle behaviours. CONCLUSIONS: Adhering to a higher number of healthy lifestyle behaviours is significantly associated with a lower incidence of IBS in the general population. Our findings suggest the potential of lifestyle modifications as a primary prevention strategy for IBS.

Multi-omic analysis suggests tumor suppressor genes evolved specific promoter features to optimize cancer resistance.

Tumor suppressor genes (TSGs) exhibit distinct evolutionary features. We speculated that TSG promoters could have evolved specific features that facilitate their tumor-suppressing functions. We found that the promoter CpG dinucleotide frequencies of TSGs are significantly higher than that of non-cancer genes across vertebrate genomes, and positively correlated with gene expression across tissue types. The promoter CpG dinucleotide frequencies of all genes gradually increase with gene age, for which young TSGs have been subject to a stronger evolutionary pressure. Transcription-related features, namely chromatin accessibility, methylation and ZNF263-, SP1-, E2F4- and SP2-binding elements, are associated with gene expression. Moreover, higher promoter CpG dinucleotide frequencies and chromatin accessibility are positively associated with the ability of TSGs to resist downregulation during tumorigenesis. These results were successfully validated with independent datasets. In conclusion, TSGs evolved specific promoter features that optimized cancer resistance through achieving high expression in normal tissues and resistance to downregulation during tumorigenesis.

Characterizing superspreading potential of infectious disease: Decomposition of individual transmissibility.

In the context of infectious disease transmission, high heterogeneity in individual infectiousness indicates that a few index cases can generate large numbers of secondary cases, a phenomenon commonly known as superspreading. The potential of disease superspreading can be characterized by describing the distribution of secondary cases (of each seed case) as a negative binomial (NB) distribution with the dispersion parameter, k. Based on the feature of NB distribution, there must be a proportion of individuals with individual reproduction number of almost 0, which appears restricted and unrealistic. To overcome this limitation, we generalized the compound structure of a Poisson rate and included an additional parameter, and divided the reproduction number into independent and additive fixed and variable components. Then, the secondary cases followed a Delaporte distribution. We demonstrated that the Delaporte distribution was important for understanding the characteristics of disease transmission, which generated new insights distinct from the NB model. By using real-world dataset, the Delaporte distribution provides improvements in describing the distributions of COVID-19 and SARS cases compared to the NB distribution. The model selection yielded increasing statistical power with larger sample sizes as well as conservative type I error in detecting the improvement in fitting with the likelihood ratio (LR) test. Numerical simulation revealed that the control strategy-making process may benefit from monitoring the transmission characteristics under the Delaporte framework. Our findings highlighted that for the COVID-19 pandemic, population-wide interventions may control disease transmission on a general scale before recommending the high-risk-specific control strategies.

Poultry exposure and environmental protection against asthma in rural children.

BACKGROUND: Asthma is one of the most common chronic diseases in childhood, and the prevalence has been increasing over the past few decades. One of the most consistent epidemiological findings is that children living in a farming or rural environment are protected from development of asthma and allergies, but the protective factors in rural China are not clear. METHODS: A community-based, cross-sectional epidemiological study was performed in a total of 17,587 children aged 5-8 years, 3435 from Hong Kong (urban) and 14,152 from Conghua (rural county in southern China). Asthma and allergic symptoms as well as environmental exposures were ascertained by using a standardized and validated questionnaire. RESULTS: The prevalence of current wheeze was significantly lower in rural Conghua than that of urban Hong Kong (1.7% vs. 7.7%, p < 0.001). A lower rate of asthma ever was also reported in rural children compared with their urban counterparts (2.5% vs. 5.3%, p < 0.001). After adjusting for confounding factors, exposure to agricultural farming (adjusted odds ratio 0.74, 95% confidence interval: 0.56-0.97) and poultry (0.75, 0.59-0.96) were the most important factors associated with the asthma-protective effect in the rural area. Further propensity score-adjusted analysis indicated that such protection conferred by living in the rural environment was mainly attributable to poultry exposure. CONCLUSIONS: We confirmed that the prevalence of asthma and atopic disorders was significantly lower in rural children when compared with their urban peers. Exposure to poultry and agricultural farming are the most important factors associated with asthma protection in the rural area.

The non-pharmaceutical interventions may affect the advantage in transmission of mutated variants during epidemics: A conceptual model for COVID-19.

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that is difficult to be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in slowing or even containing the growth of the proportion of variants.

Shrinkage in serial intervals across transmission generations of COVID-19.

One of the key epidemiological characteristics that shape the transmission of coronavirus disease 2019 (COVID-19) is the serial interval (SI). Although SI is commonly considered following a probability distribution at a population scale, recent studies reported a slight shrinkage (or contraction) of the mean of effective SI across transmission generations or over time. Here, we develop a likelihood-based statistical inference framework with truncation to explore the change in SI across transmission generations after adjusting the impacts of case isolation. The COVID-19 contact tracing surveillance data in Hong Kong are used for exemplification. We find that for COVID-19, the mean of individual SI is likely to shrink with a factor at 0.72 per generation (95%CI: 0.54, 0.96) as the transmission generation increases, where a threshold may exist as the lower boundary of this shrinking process. We speculate that one of the probable explanations for the shrinkage in SI might be an outcome due to the competition among multiple candidate infectors within the same case cluster. Thus, the nonpharmaceutical interventive strategies are crucially important to block the transmission chains, and mitigate the COVID-19 epidemic.

Modelling the association between COVID-19 transmissibility and D614G substitution in SARS-CoV-2 spike protein: using the surveillance data in California as an example.

BACKGROUND: The COVID-19 pandemic poses a serious threat to global health, and pathogenic mutations are a major challenge to disease control. We developed a statistical framework to explore the association between molecular-level mutation activity of SARS-CoV-2 and population-level disease transmissibility of COVID-19. METHODS: We estimated the instantaneous transmissibility of COVID-19 by using the time-varying reproduction number (Rt). The mutation activity in SARS-CoV-2 is quantified empirically depending on (i) the prevalence of emerged amino acid substitutions and (ii) the frequency of these substitutions in the whole sequence. Using the likelihood-based approach, a statistical framework is developed to examine the association between mutation activity and Rt. We adopted the COVID-19 surveillance data in California as an example for demonstration. RESULTS: We found a significant positive association between population-level COVID-19 transmissibility and the D614G substitution on the SARS-CoV-2 spike protein. We estimate that a per 0.01 increase in the prevalence of glycine (G) on codon 614 is positively associated with a 0.49% (95% CI: 0.39 to 0.59) increase in Rt, which explains 61% of the Rt variation after accounting for the control measures. We remark that the modeling framework can be extended to study other infectious pathogens. CONCLUSIONS: Our findings show a link between the molecular-level mutation activity of SARS-CoV-2 and population-level transmission of COVID-19 to provide further evidence for a positive association between the D614G substitution and Rt. Future studies exploring the mechanism between SARS-CoV-2 mutations and COVID-19 infectivity are warranted.

Inferencing superspreading potential using zero-truncated negative binomial model: exemplification with COVID-19.

BACKGROUND: In infectious disease transmission dynamics, the high heterogeneity in individual infectiousness indicates that few index cases generate large numbers of secondary cases, which is commonly known as superspreading events. The heterogeneity in transmission can be measured by describing the distribution of the number of secondary cases as a negative binomial (NB) distribution with dispersion parameter, k. However, such inference framework usually neglects the under-ascertainment of sporadic cases, which are those without known epidemiological link and considered as independent clusters of size one, and this may potentially bias the estimates. METHODS: In this study, we adopt a zero-truncated likelihood-based framework to estimate k. We evaluate the estimation performance by using stochastic simulations, and compare it with the baseline non-truncated version. We exemplify the analytical framework with three contact tracing datasets of COVID-19. RESULTS: We demonstrate that the estimation bias exists when the under-ascertainment of index cases with 0 secondary case occurs, and the zero-truncated inference overcomes this problem and yields a less biased estimator of k. We find that the k of COVID-19 is inferred at 0.32 (95%CI: 0.15, 0.64), which appears slightly smaller than many previous estimates. We provide the simulation codes applying the inference framework in this study. CONCLUSIONS: The zero-truncated framework is recommended for less biased transmission heterogeneity estimates. These findings highlight the importance of individual-specific case management strategies to mitigate COVID-19 pandemic by lowering the transmission risks of potential super-spreaders with priority.

Attach importance of the bootstrap t test against Student's t test in clinical epidemiology: a demonstrative comparison using COVID-19 as an example.

Student's t test is valid for statistical inference under the normality assumption or asymptotically. By contrast, although the bootstrap t test was proposed in 1993, it is seldom adopted in medical research. We aim to demonstrate that the bootstrap t test outperforms Student's t test under normality in data. Using random data samples from normal distributions, we evaluated the testing performance, in terms of true-positive rate (TPR) and false-positive rate and diagnostic abilities, in terms of the area under the curve (AUC), of the bootstrap t test and Student's t test. We explore the AUC of both tests with varying sample size and coefficient of variation. We compare the testing outcomes using the COVID-19 serial interval (SI) data in Shenzhen and Hong Kong, China, for demonstration. With fixed TPR, the bootstrap t test maintained the equivalent accuracy in TPR, but significantly improved the true-negative rate from the Student's t test. With varying TPR, the diagnostic ability of bootstrap t test outperformed or equivalently performed as Student's t test in terms of the AUC. The equivalent performances are possible but rarely occur in practice. We find that the bootstrap t test outperforms by successfully detecting the difference in COVID-19 SI, which is defined as the time interval between consecutive transmission generations, due to sex and non-pharmaceutical interventions against the Student's t test. We demonstrated that the bootstrap t test outperforms Student's t test, and it is recommended to replace Student's t test in medical data analysis regardless of sample size.

Real-time quantification of the transmission advantage associated with a single mutation in pathogen genomes: a case study on the D614G substitution of SARS-CoV-2.

BACKGROUND: The COVID-19 pandemic poses serious threats to global health, and the emerging mutation in SARS-CoV-2 genomes, e.g., the D614G substitution, is one of the major challenges of disease control. Characterizing the role of the mutation activities is of importance to understand how the evolution of pathogen shapes the epidemiological outcomes at population scale. METHODS: We developed a statistical framework to reconstruct variant-specific reproduction numbers and estimate transmission advantage associated with the mutation activities marked by single substitution empirically. Using likelihood-based approach, the model is exemplified with the COVID-19 surveillance data from January 1 to June 30, 2020 in California, USA. We explore the potential of this framework to generate early warning signals for detecting transmission advantage on a real-time basis. RESULTS: The modelling framework in this study links together the mutation activity at molecular scale and COVID-19 transmissibility at population scale. We find a significant transmission advantage of COVID-19 associated with the D614G substitution, which increases the infectivity by 54% (95%CI: 36, 72). For the early alarming potentials, the analytical framework is demonstrated to detect this transmission advantage, before the mutation reaches dominance, on a real-time basis. CONCLUSIONS: We reported an evidence of transmission advantage associated with D614G substitution, and highlighted the real-time estimating potentials of modelling framework.

Low dispersion in the infectiousness of COVID-19 cases implies difficulty in control.

The individual infectiousness of coronavirus disease 2019 (COVID-19), quantified by the number of secondary cases of a typical index case, is conventionally modelled by a negative-binomial (NB) distribution. Based on patient data of 9120 confirmed cases in China, we calculated the variation of the individual infectiousness, i.e., the dispersion parameter k of the NB distribution, at 0.70 (95% confidence interval: 0.59, 0.98). This suggests that the dispersion in the individual infectiousness is probably low, thus COVID-19 infection is relatively easy to sustain in the population and more challenging to control. Instead of focusing on the much fewer super spreading events, we also need to focus on almost every case to effectively reduce transmission.

Epidemiological Parameters of COVID-19: Case Series Study.

BACKGROUND: The estimates of several key epidemiological parameters of the COVID-19 pandemic are often based on small sample sizes or are inaccurate for various reasons. OBJECTIVE: The aim of this study is to obtain more robust estimates of the incubation period, serial interval, frequency of presymptomatic transmission, and basic reproduction number (R0) of COVID-19 based on a large case series. METHODS: We systematically retrieved and screened 20,658 reports of laboratory-confirmed COVID-19 cases released by the health authorities of China, Japan, and Singapore. In addition, 9942 publications were retrieved from PubMed and China National Knowledge Infrastructure (CNKI) through April 8, 2020. To be eligible, a report had to contain individual data that allowed for accurate estimation of at least one parameter. Widely used models such as gamma distributions were fitted to the data sets and the results with the best-fitting values were presented. RESULTS: In total, 1591 cases were included for the final analysis. The mean incubation period (n=687) and mean serial interval (n=1015 pairs) were estimated to be 7.04 (SD 4.27) days and 6.49 (SD 4.90) days, respectively. In 40 cases (5.82%), the incubation period was longer than 14 days. In 32 infector-infectee pairs (3.15%), infectees' symptom onsets occurred before those of infectors. Presymptomatic transmission occurred in 129 of 296 infector-infectee pairs (43.58%). R0 was estimated to be 1.85 (95% CI 1.37-2.60). CONCLUSIONS: This study provides robust estimates of several epidemiological parameters of COVID-19. The findings support the current practice of 14-day quarantine of persons with potential exposure, but also suggest the need for additional measures. Presymptomatic transmission together with the asymptomatic transmission reported by previous studies highlight the importance of adequate testing, strict quarantine, and social distancing.

Global cytokine/chemokine profile identifies potential progression prediction indicators in hand-foot-and-mouth disease patients with Enterovirus A71 infections.

OBJECTIVE: New clinical indicators are urgently needed for predicting the progression and complications of hand-foot-and-mouth disease (HFMD) caused by EV-A71 infections. MATERIALS AND METHODS: Serum specimens from 132 EV-A71 HFMD patients and 73 health children were collected during 2012-2014 in Shenzhen, China. The specific cytokines/chemokines were detected with a 274-human cytokine antibody array, followed by a 38-inflammation cytokine array, and further validated by ELISA. RESULTS: Cytokines varied in different severity of EV-A71 HFMD patients. The ROC curve analysis revealed 5 serum cytokines with high sensitivity and specificity in predicting the disease progression. Eotaxin, IL-8 and IP-10 have showed high AUC values (0.90-0.95) for discrimination between the health controls and the patient group. The three cytokines showed high sensitivity (80-91%) and specificity (88-95%). MMP-8 had a high sensitivity and specificity to predict mild HFMD (100%, 100%). IL-1b and leptin discriminated the severe/critical group from the mild group (79% and 69% in sensitivity, 73% and 63% in specificity). CONCLUSIONS: Eotaxin, IP-10 and IL-8 could be potential indicators for predicting HFMD progression with EV-A71 infection. MMP-8 is a specific indicator for mild infection, while IL-1b and leptin display potential for predicting the severity and criticality.

A novel susceptibility locus in MST1 and gene-gene interaction network for Crohn's disease in the Chinese population.

The incidence of Crohn's disease is increasing in many Asian countries, but considerable differences in genetic susceptibility have been reported between Western and Asian populations. This study aimed to fine-map 23 previously reported Crohn's disease genes and identify their interactions in the Chinese population by Illumina-based targeted capture sequencing. Our results showed that the genetic polymorphism A>G at rs144982232 in MST1 showed the most significant association (P = 1.78 × 10-5 ; odds ratio = 4.87). JAK2 rs1159782 (T>C) was also strongly associated with Crohn's disease (P = 2.34 × 10-4 ; odds ratio = 3.72). Gene-gene interaction analysis revealed significant interactions between MST1 and other susceptibility genes, including NOD2, MUC19 and ATG16L1 in contributing to Crohn's disease risk. Main genetic associations and gene-gene interactions were verified using ImmunoChip data set. In conclusion, a novel susceptibility locus in MST1 was identified. Our analysis suggests that MST1 might interact with key susceptibility genes involved in autophagy and bacterial recognition. These findings provide insight into the genetic architecture of Crohn's disease in Chinese and may partially explain the disparity of genetic signals in Crohn's disease susceptibility across different ethnic populations by highlighting the contribution of gene-gene interactions.

Clostridium difficile toxin B induces autophagic cell death in colonocytes.

Toxin B (TcdB) is a major pathogenic factor of Clostridum difficile. However, the mechanism by which TcdB exerts its cytotoxic action in host cells is still not completely known. Herein, we report for the first time that TcdB induced autophagic cell death in cultured human colonocytes. The induction of autophagy was demonstrated by the increased levels of LC3-II, formation of LC3+ autophagosomes, accumulation of acidic vesicular organelles and reduced levels of the autophagic substrate p62/SQSTM1. TcdB-induced autophagy was also accompanied by the repression of phosphoinositide 3-kinase (PI3K)/Akt/mechanistic target of rapamycin (mTOR) complex 1 activity. Functionally, pharmacological inhibition of autophagy by wortmannin or chloroquine or knockdown of autophagy-related genes Beclin 1, Atg5 and Atg7 attenuated TcdB-induced cell death in colonocytes. Genetic ablation of Atg5, a gene required for autophagosome formation, also mitigated the cytotoxic effect of TcdB. In conclusion, our study demonstrated that autophagy serves as a pro-death mechanism mediating the cytotoxic action of TcdB in colonocytes. This discovery suggested that blockade of autophagy might be a novel therapeutic strategy for C. difficile infection.

Frequent Genetic Mismatch between Vaccine Strains and Circulating Seasonal Influenza Viruses, Hong Kong, China, 1996-2012.

The World Health Organization selects influenza vaccine compositions biannually to cater to peaks in temperate regions. In tropical and subtropical regions, where influenza seasonality varies and epidemics can occur year-round, the choice of vaccine remains uncertain. Our 17-year molecular epidemiologic survey showed that most influenza A(H3N2) (9/11) and B (6/7) vaccine strains had circulated in East Asia >1 year before inclusion into vaccines. Northern Hemisphere vaccine strains and circulating strains in East Asia were closely matched in 7 (20.6%) of 34 seasons for H3N2 and 5 (14.7%) of 34 seasons for B. Southern Hemisphere vaccines also had a low probability of matching (H3N2, 14.7%; B, 11.1%). Strain drift among seasons was common (H3N2, 41.2%; B, 35.3%), and biannual vaccination strategy (Northern Hemisphere vaccines in November followed by Southern Hemisphere vaccines in May) did not improve matching. East Asia is an important contributor to influenza surveillance but often has mismatch between vaccine and contemporarily circulating strains.

Oncogenes without a Neighboring Tumor-Suppressor Gene Are More Prone to Amplification.

Focal copy number gains or losses are important genomic hallmarks of cancer. The genomic distribution of oncogenes and tumor-suppressor genes (TSG) in relation to focal copy number aberrations is unclear. Our analysis revealed that the mean distance of TSGs from oncogenes was significantly shorter than that of noncancer genes, suggesting that oncogenes and TSGs tend to be in close physical proximity in the human genome. Such relationship was conserved in mouse and drosophila. Pan-cancer analysis using data from The Cancer Genome Atlas indicated that oncogenes without a nearby TSG are more prone to amplification. In conclusion, our study provides evidence for the nonrandom distribution of oncogenes and TSGs across different species. Our data also support that the existence of a neighboring TSG can suppress amplification of an oncogene, shedding new light on a previously unappreciated protective mechanism of TSGs.

Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges.

Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships.

The involvement of regulatory non-coding RNAs in sepsis: a systematic review.

BACKGROUND: Sepsis coincides with altered gene expression in different tissues. Accumulating evidence has suggested that microRNAs, long non-coding RNAs, and circular RNAs are important molecules involved in the crosstalk with various pathways pertinent to innate immunity, mitochondrial functions, and apoptosis. METHODS: We searched articles indexed in PubMed (MEDLINE), EMBASE and Europe PubMed Central databases using the Medical Subject Heading (MeSH) or Title/Abstract words ("microRNA", "long non-coding RNA", "circular RNA", "sepsis" and/or "septic shock") from inception to Sep 2016. Studies investigating the role of host-derived microRNA, long non-coding RNA, and circular RNA in the pathogenesis of and as biomarkers or therapeutics in sepsis were included. Data were extracted in terms of the role of non-coding RNAs in pathogenesis, and their applicability for use as biomarkers or therapeutics in sepsis. Two independent researchers assessed the quality of studies using a modified guideline from the Systematic Review Center for Laboratory animal Experimentation (SYRCLE), a tool based on the Cochrane Collaboration Risk of Bias tool. RESULTS: Observational studies revealed dysregulation of non-coding RNAs in septic patients. Experimental studies confirmed their crosstalk with JNK/NF-κB and other cellular pathways pertinent to innate immunity, mitochondrial function, and apoptosis. Of the included studies, the SYRCLE scores ranged from 3 to 7 (average score of 4.55). This suggests a moderate risk of bias. Of the 10 articles investigating non-coding RNAs as biomarkers, none of them included a validation cohort. Selective reporting of sensitivity, specificity, and receiver operating curve was common. CONCLUSIONS: Although non-coding RNAs appear to be good candidates as biomarkers and therapeutics for sepsis, their differential expression across tissues complicated the process. Further investigation on organ-specific delivery of these regulatory molecules may be useful.