BHAFT: Bayesian heredity-constrained accelerated failure time models for detecting gene-environment interactions in survival analysis.

In addition to considering the main effects, understanding gene-environment (G × E) interactions is imperative for determining the etiology of diseases and the factors that affect their prognosis. In the existing statistical framework for censored survival outcomes, there are several challenges in detecting G × E interactions, such as handling high-dimensional omics data, diverse environmental factors, and algorithmic complications in survival analysis. The effect heredity principle has widely been used in studies involving interaction identification because it incorporates the dependence of the main and interaction effects. However, Bayesian survival models that incorporate the assumption of this principle have not been developed. Therefore, we propose Bayesian heredity-constrained accelerated failure time (BHAFT) models for identifying main and interaction (M-I) effects with novel spike-and-slab or regularized horseshoe priors to incorporate the assumption of effect heredity principle. The R package rstan was used to fit the proposed models. Extensive simulations demonstrated that BHAFT models had outperformed other existing models in terms of signal identification, coefficient estimation, and prognosis prediction. Biologically plausible G × E interactions associated with the prognosis of lung adenocarcinoma were identified using our proposed model. Notably, BHAFT models incorporating the effect heredity principle could identify both main and interaction effects, which are highly useful in exploring G × E interactions in high-dimensional survival analysis. The code and data used in our paper are available at https://github.com/SunNa-bayesian/BHAFT.

Mediation analysis method review of high throughput data.

High-throughput technologies have made high-dimensional settings increasingly common, providing opportunities for the development of high-dimensional mediation methods. We aimed to provide useful guidance for researchers using high-dimensional mediation analysis and ideas for biostatisticians to develop it by summarizing and discussing recent advances in high-dimensional mediation analysis. The method still faces many challenges when extended single and multiple mediation analyses to high-dimensional settings. The development of high-dimensional mediation methods attempts to address these issues, such as screening true mediators, estimating mediation effects by variable selection, reducing the mediation dimension to resolve correlations between variables, and utilizing composite null hypothesis testing to test them. Although these problems regarding high-dimensional mediation have been solved to some extent, some challenges remain. First, the correlation between mediators are rarely considered when the variables are selected for mediation. Second, downscaling without incorporating prior biological knowledge makes the results difficult to interpret. In addition, a method of sensitivity analysis for the strict sequential ignorability assumption in high-dimensional mediation analysis is still lacking. An analyst needs to consider the applicability of each method when utilizing them, while a biostatistician could consider extensions and improvements in the methodology.

Visceral adiposity associated with incidence and development trajectory of cardiometabolic diseases: A prospective cohort study.

BACKGROUND AND AIMS: There is a lack of literature concerning the effects of visceral adipose on the development of first cardiometabolic disease (FCMD) and its subsequent progression to cardiometabolic multimorbidity (CMM) and mortality. METHODS AND RESULTS: 423,934 participants from the UK Biobank with different baseline disease conditions were included in the analysis. CMM was defined as the simultaneous presence of coronary heart disease, T2D, and stroke. Visceral adiposity was estimated by calculating the visceral adiposity index (VAI). Multistate models were used to assess the effect of visceral adiposity on the development of CMM. During a median follow-up of 13.5 years, 50,589 patients had at least one CMD, 6131 were diagnosed with CMM, whereas 24,634 patients died. We observed distinct roles of VAI with respect to different disease transitions of CMM. HRs (95 % CIs) of high VAI were 2.35 (2.29-2.42) and 1.64 (1.50-1.79) for transitions from healthy to FCMD and from FCMD to CMM, and 0.97 (0.93-1.02) for all-cause mortality risk from healthy, FCMD and CMM, respectively. CONCLUSIONS: Our study provides the first evidence that visceral adipose may contribute to the development of FCMD and CMM in healthy participants. However, visceral adipose may confer resistance to all-cause mortality in participants with existing CMD or CMM. A better understanding of the relationship between visceral adipose and CMM can focalize further investigations on patients with CMD with high levels of visceral fat and help take targeted preventive measures to reduce the medical burden on individual patients and society.

Effect of self-regulating fatigue on health-related quality of life of middle-aged and elderly patients with recurrent stroke: a moderated sequential mediation model.

Although the association between self-regulation of fatigue and health-related quality of life (HRQoL) has been confirmed, the potential mechanism remains unclear. This study aimed to explore the role of health literacy, health behavior, and exercise frequency in the relationship among middle-aged and elderly patients with recurrent stroke. A cross-sectional survey was conducted. A total of 176 patients completed the survey, in which self-regulation of fatigue, HRQoL, health literacy and health behavior were measured by questionnaires. Based on Bootstrap analyses, a moderating sequential mediation model using PROCESS software was constructed with health literacy and health behavior as mediators and exercise frequency as the moderator. Of the participants, the mean age was 65.44 ± 12.43 years. Self-regulation of fatigue was found to affect HRQoL indirectly through two significant mediation pathways: (1) health literacy (ß=-0.11, 95%CI = -0.20, -0.03), which accounted for 28.79% of the total effect, and (2) health literacy and health behavior (ß=-0.02, 95%CI = -0.05, -0.00), which accounted for 4.80% of the total effect. Exercise frequency moderated the relationship between self-regulating fatigue and HRQoL. Specifically, the interaction term between self-regulating fatigue and exercise frequency significantly predicted HRQoL (ß = 0. 25, t = 2.55, p < 0.05). These findings highlight the role of health literacy and health behavior as sequential mediators of the relationship between self-regulating fatigue and HRQoL. Moreover, exercise frequency moderated the relationship between self-regulating fatigue and HRQoL. Encouraging patients with recurrent stroke to increase exercise frequency appropriately might improve HRQoL for patients with poor health literacy and health behavior.

Trends in cognitive function before and after stroke in China.

BACKGROUND: While cognitive impairment after stroke is common, cognitive trends before stroke are poorly understood, especially among the Chinese population who have a relatively high stroke burden. We aimed to model the trajectories of cognitive function before and after new-onset stroke among Chinese. METHODS: A total of 13,311 Chinese participants aged ≥ 45 years and without a history of stroke were assessed at baseline between June 2011 and March 2012 and in at least one cognitive test between 2013 (wave 2) and 2018 (wave 4). Cognitive function was assessed using a global cognition score, which included episodic memory, visuospatial abilities, and a 10-item Telephone Interview of Cognitive Status (TICS-10) test to reflect calculation, attention, and orientation abilities. RESULTS: During the 7-year follow-up, 610 (4.6%) participants experienced a first stroke. Both stroke and non-stroke groups showed declined cognitive function during follow-up. After adjustment for covariates, there was no significant difference in pre-stroke cognitive trajectories between stroke patients and stroke-free participants. The stroke group showed an acute decline in episodic memory (- 0.123 SD), visuospatial abilities (- 0.169 SD), and global cognition (- 0.135 SD) after stroke onset. In the years following stroke, the decline rate of the TICS-10 test was higher than the rate before stroke (- 0.045 SD/year). CONCLUSIONS: Chinese stroke patients had not experienced steeper declines in cognition before stroke compared with stroke-free individuals. Incident stroke was associated with acute declines in global cognition, episodic memory, visuospatial abilities, and accelerated declines in calculation, attention, and orientation abilities.

Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST.

BACKGROUND: The prediction model of intravenous immunoglobulin (IVIG) resistance in Kawasaki disease can calculate the probability of IVIG resistance and provide a basis for clinical decision-making. We aim to assess the quality of these models developed in the children with Kawasaki disease. METHODS: Studies of prediction models for IVIG-resistant Kawasaki disease were identified through searches in the PubMed, Web of Science, and Embase databases. Two investigators independently performed literature screening, data extraction, quality evaluation, and discrepancies were settled by a statistician. The checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) was used for data extraction, and the prediction models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST). RESULTS: Seventeen studies meeting the selection criteria were included in the qualitative analysis. The top three predictors were neutrophil measurements (peripheral neutrophil count and neutrophil %), serum albumin level, and C-reactive protein (CRP) level. The reported area under the curve (AUC) values for the developed models ranged from 0.672 (95% confidence interval [CI]: 0.631-0.712) to 0.891 (95% CI: 0.837-0.945); The studies showed a high risk of bias (ROB) for modeling techniques, yielding a high overall ROB. CONCLUSION: IVIG resistance models for Kawasaki disease showed high ROB. An emphasis on improving their quality can provide high-quality evidence for clinical practice. IMPACT STATEMENT: This study systematically evaluated the risk of bias (ROB) of existing prediction models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease to provide guidance for future model development meeting clinical expectations. This is the first study to systematically evaluate the ROB of IVIG resistance in Kawasaki disease by using PROBAST. ROB may reduce model performance in different populations. Future prediction models should account for this problem, and PROBAST can help improve the methodological quality and applicability of prediction model development.

Association between coffee and incident heart failure: A prospective cohort study from the UK Biobank.

BACKGROUND AND AIMS: The relationship between coffee consumption and heart failure (HF) incidence is inconclusive. This study aimed to explore the association between time-varying coffee consumption and incident HF using a longitudinal study design. METHODS AND RESULTS: Data were obtained from the UK Biobank, comprising 497,503 adults (age, 56.5 ± 8.1 years; 54.6% women) who were free from HF at baseline in 2006-2010. The median follow-up time for the HF incidence was 11.9 years. Marginal structural models (MSM) were employed to adjust for potential time-varying confounders and account for bias caused by loss of follow-up. Furthermore, we used a restricted cubic spline to test and describe the nonlinear relationship between coffee consumption and HF risk. At baseline, 70.5% of participants reported drinking ≥1 cups/d coffee and 2.7% participants developed HF. After adjusting for potential confounders, we identified a nonlinear J-shaped association between coffee consumption and HF risk (P < 0.001). Compared with drinking coffee <1 cups/d, 1-2 cups/d (HR = 0.878; 95% CI: 0.838-0.920), 3-4 cups/d (HR = 0.920; 95% CI: 0.869-0.974) may be associated with a reduced risk of HF, while >6 cups/d (HR = 1.209; 95% CI: 1.056-1.385) may be associated with a higher risk of HF. However, sensitive analyses stratified by gender and smoking status indicated that >6 cups/d does not significantly increase the risk of HF. Additionally, the type of coffee was found to significant impact on the incidence of HF (P < 0.05). CONCLUSION: In this large cohort of UK adults, moderate coffee consumption may reduce risk of HF incidence.

Association between the visceral adiposity index and risks of all-cause and cause-specific mortalities in a large cohort: Findings from the UK biobank.

BACKGROUND AND AIMS: The visceral adiposity index (VAI) has been recently established as a measure of visceral fat distribution and is shown to be associated with a wide range of adverse health events. However, the precise associations between the VAI score and all-cause and cause-specific mortalities in the general population remain undetermined. METHODS AND RESULTS: In this large-scale prospective epidemiological study, 357,457 participants (aged 38-73 years) were selected from the UK Biobank. We used Cox competing risk regression models to estimate the association between the VAI score and all-cause, cardiovascular disease (CVD), cancer, and other mortalities. The VAI score was significantly correlated with an increased risk of all-cause mortality (hazard ratio [HR], 1.200; 95% confidence interval [CI], 1.148-1.255; P < 0.0001), cancer mortality (HR, 1.224; 95% CI, 1.150-1.303; P < 0.0001), CVD mortality (HR, 1.459; 95% CI, 1.148-1.255; P < 0.0001), and other mortalities (HR, 1.200; 95% CI, 1.148-1.255; P < 0.0001) after adjusting for a series of confounders. In addition, the subgroup analyses showed that HRs were significantly higher in participants who were male, aged below 65 years, and body mass index less than 25. CONCLUSION: In summary, VAI was positively associated with an increased risk of all-cause and cause-specific mortalities in a nationwide, well-characterised population identified in a UK Biobank. The VAI score might be a complementary traditional predictive indicator for evaluating the risk of adverse health events in the population of Western adults aged 38 years and older.

The role of depression and physical activity in the association of between sleep quality, and duration with and health-related quality of life among the elderly: a UK Biobank cross-sectional study.

BACKGROUND: Although studies have shown that sleep quality (duration) is associated with health-related quality of life (HRQoL), most of these studies have been small-sized and targeted at young and middle-aged adults. In addition, few studies have explored the path mechanism of sleep disorders leading to impaired HRQoL. OBJECTIVES: This study aimed to determine the association between sleep quality and duration and HRQoL among the elderly in the United Kingdom, assess whether depression mediated the association, and explore the role of physical activity (PA) in the path association. METHODS: Data were extracted from the baseline survey of the UK Biobank, a large prospective cohort study enrolling more than 500,000 participants, of which 52,551 older adults (aged ≥60 years) were included in the study. HRQoL was assessed using the European Quality of Life-5 Dimensions. Tobit and multivariate logistic regression models were used to determine the association between sleep quality and duration and HRQoL. The mediating and moderated mediation models were estimated using the PROCESS macro and MEDCURVE macro. RESULTS: The Tobit model showed that the elderly with short or long sleep duration (ß = - 0.062, 95% confidence interval [CI] = - 0.071 to - 0.053; ß = - 0.072, 95% CI = - 0.086 to - 0.058) had worse HRQoL after adjusting potential covariates. In the logistic regression models, we found an inverted U-shaped association between sleep duration and HRQoL. Moreover, a significant positive association was observed between sleep quality and HRQoL (all P < 0.05). The results also revealed that depression mediated the association between sleep disorders and HRQoL (sleep quality: ß = 0.008, 95% CI = 0.007-0.010; sleep duration: θ = 0.001 [mean], 95% CI = 0.001-0.002). Furthermore, PA moderated all paths among sleep quality and duration, depression, and HRQoL, and greater effects were observed in the elderly with lower PA levels. CONCLUSIONS: The findings show that poor sleep quality and duration were independently associated with worse HRQoL among the elderly in the United Kingdom. Furthermore, PA buffers the mediating effect of depression and adverse effects of sleep disorders on HRQoL. It is essential to properly increase PA and provide early intervention for depression in the elderly with sleep disorders to improve their HRQoL.

Associations of ultra-processed food consumption with cardiovascular disease and all-cause mortality: UK Biobank.

BACKGROUND: This study aimed to investigate the associations between ultra-processed food (UPF) consumption and the risk of cardiovascular disease and all-cause mortality in the UK Biobank Cohort. METHODS: This observational prospective study evaluated 60 298 participants aged 40 years or older. We used the NOVA classification system to identify and categorize UPF. The associations among UPF consumption, cardiovascular disease (CVD) incidence and all-cause mortality were estimated using multivariable Cox proportional hazards models. Dose-response analysis of UPF consumption and CVD incidence and mortality was performed using a restricted cubic spline. RESULTS: After a median follow-up of 10.9 years, 6048 participants (10.0%) experienced CVD events, and 5327 (8.8%) and 1503 (2.5%) experienced coronary heart and cerebrovascular diseases, respectively. There were 2590 (4.3%) deaths, of which 384 (0.6%) deaths were caused by CVD. A higher intake of UPF was associated with a higher risk of CVD and all-cause mortality (all P < 0.001). A higher intake of UPF was associated with a higher risk of CVD [hazard ratio (HR) = 1.17, 95% confidence interval (CI): 1.09-1.26], coronary heart disease (HR = 1.16, 95% CI: 1.07-1.25), cerebrovascular disease (HR = 1.30, 95% CI: 1.13-1.50) and all-cause mortality (HR = 1.22, 95% CI: 1.09-1.36). The association of UPF consumption with a range of CVD incidents and all-cause mortality was monotonic (all P for non-linearity > 0.30). CONCLUSIONS: A higher proportion of UPF consumption was associated with CVD and all-cause mortality. Thus, actions to limit UPF consumption should be incorporated into the CVD and all-cause mortality prevention recommendations.

Bidirectional association between depression and multimorbidity in middle-aged and elderly Chinese adults: a longitudinal cohort study.

BACKGROUND: Few studies have investigated the bidirectional association between depression and multimorbidity from a longitudinal perspective. We aimed to explore the bidirectional relationship between depression and multimorbidity in a middle-aged and elderly Chinese population. METHODS: Participants aged 45 years and older from the China Health and Retirement Longitudinal Study (CHARLS) were included. Depression was measured with a 10-item version of the Center for Epidemiological Studies Depression Scale (CESD-10). In stage I, we assessed the association of baseline depression with follow-up multimorbidity. In stage II, we examined whether multimorbidity increases the risk of depression. Logistic regression models were used to estimate the odds ratios (ORs) and confidence intervals (CIs). The ORs were then converted to risk ratios (RRs) using a proposed formula. RESULTS: A total of 7056 subjects without multimorbidity and 7587 subjects without depression at baseline were included in stage I and stage II. In stage I, the adjusted RRs (95% CIs) of depressed participants developing one disease, two diseases, three diseases, and ≥4 diseases were 1.15 (0.96-1.35), 1.64 (1.36-1.99), 1.84 (1.44-2.35) and 2.42 (1.75-3.34), respectively. In stage II, compared with individuals without any disease, the adjusted RRs (95% CIs) of developing depression for individuals carrying one disease, two diseases, three diseases, and ≥4 diseases were 1.08 (0.96-1.22), 1.39 (1.22-1.57), 1.46 (1.23-1.70) and 1.62 (1.34-1.93), respectively. CONCLUSIONS: Baseline depression increases the risk of future multimorbidity, and multimorbidity also contributes to an increased risk of incident depression in middle-aged and elderly Chinese adults.

Perioperative dexmedetomidine and 5-year survival in patients undergoing cardiac surgery.

BACKGROUND: Dexmedetomidine sedation has been associated with favourable outcomes after surgery. We aimed to assess whether perioperative dexmedetomidine use is associated with improved survival after cardiac surgery. METHODS: This retrospective cohort study included 2068 patients undergoing on-pump coronary artery bypass grafting and/or valve surgery. Among them, 1029 patients received dexmedetomidine, and 1039 patients did not. Intravenous dexmedetomidine infusion of 0.007 µg kg-1 min-1 was initiated before or immediately after cardiopulmonary bypass and lasted for < 24 h. The primary outcome was 5-year survival after cardiac surgery. The propensity scores matching (PSM), inverse probability of treatment weighting (IPTW), and overlap weighting approaches were used to minimise bias. Survival analyses were performed with Cox proportional-hazard models. RESULTS: The median age was 63 yr old and the male to female ratio was 71:29 in both groups. Baseline covariates were balanced between groups after adjustment using PSM, IPTW, or overlap weighting. Patients receiving dexmedetomidine in cardiac surgical procedures had higher survival during postoperative 5 yr in unadjusted analysis (hazard ratio [HR]=0.63; 95% confidence interval [CI], 0.51-0.78; P<0.001), and after adjustment with PSM (HR=0.63; 95% CI, 0.45-0.89; P=0.009), IPTW (HR=0.70; 95% CI, 0.51-0.95; P=0.023), or overlap weighting (HR=0.67; 95% CI, 0.51-0.89; P=0.006). The 5-yr mortality rate after cardiac surgery was 13% and 20% in the dexmedetomidine and non-dexmedetomidine groups, respectively (PSM adjusted odds ratio=0.61; 95% CI, 0.42-0.89; P=0.010). CONCLUSION: Perioperative dexmedetomidine infusion was associated with improved 5-yr survival in patients undergoing cardiac surgery.

Longitudinal Follow-Up Studies on the Bidirectional Association between ADL/IADL Disability and Multimorbidity: Results from Two National Sample Cohorts of Middle-Aged and Elderly Adults.

BACKGROUND AND OBJECTIVES: Few studies have investigated the bidirectional relationship between disability and multimorbidity, which are common conditions among the older population. Based on the data from the China Health and Retirement Longitudinal Study (CHARLS) and the Survey of Health, Ageing and Retirement in Europe (SHARE), we aimed to investigate the bidirectional relationship between disability and multimorbidity. METHODS: The activities of daily living (ADLs) and the instrumental activities of daily living (IADLs) scales were used to measure disability. In stage I, we used multinomial logistic regression to assess the longitudinal association between ADL/IADL disability and follow-up multimorbidity. In stage II, binary logistic regression was used to evaluate the multimorbidity effect on future disability. RESULTS: Compared with those free of disability, people with disability possessed ascending risks for developing an increasing number of diseases. For ADL disability, the odds ratio (OR) (95% confidence interval [CI]) values of developing ≥4 diseases were 4.10 (2.58, 6.51) and 6.59 (4.54, 9.56) in CHARLS and SHARE; for IADL disability, the OR (95% CI) values were 2.55 (1.69, 3.84) and 4.85 (3.51, 6.70) in CHARLS and SHARE. Meanwhile, the number of diseases at baseline was associated, in a dose-response manner, with future disability. Compared with those without chronic diseases, participants carrying ≥4 diseases had OR (95% CI) values of 4.82 (3.73, 6.21)/4.66 (3.65, 5.95) in CHARLS and 3.19 (2.59, 3.94)/3.28 (2.71, 3.98) in SHARE for developing ADL/IADL disability. CONCLUSION: The consistent findings across 2 national longitudinal studies supported a strong bidirectional association between disability and multimorbidity among middle-aged and elderly adults. Thus, tailored interventions should be taken to prevent the mutual development of disability and multimorbidity.

Estimation of losses of quality-adjusted life expectancy attributed to the combination of cognitive impairment and multimorbidity among Chinese adults aged 45 years and older.

OBJECTIVES: This study aims to estimate the losses of quality-adjusted life expectancy (QALE) due to the joint effects of cognitive impairment and multimorbidity, and to further confirm additional losses attributable to this interaction among middle-aged and elderly Chinese people. METHODS: The National Cause of Death Monitoring Data were linked with the China Health and Retirement Longitudinal Study (CHARLS). A mapping and assignment method was used to estimate health utility values, which were further used to calculate QALE. Losses of QALE were measured by comparing the differences between subgroups. All the losses of QALE were displayed at two levels: the individual and population levels. RESULTS: At age 45, the individual-level and population-level losses of QALE attributed to the combination of cognitive impairment and multimorbidity were 7.61 (95% CI: 5.68, 9.57) years and 4.30 (95% CI: 3.43, 5.20) years, respectively. The losses for cognitive impairment alone were 3.10 (95% CI: 2.29, 3.95) years and 1.71 (95% CI: 1.32, 2.13) years at the two levels. Similarly, the losses for multimorbidity alone were 3.53 (95% CI: 2.53, 4.56) years and 1.91 (95% CI: 1.24, 2.63) years at the two levels. Additional losses due to the interaction of cognitive impairment and multimorbidity were indicated by the 0.98 years of the individual-level gap and 0.67 years of the population-level gap. CONCLUSION: Among middle-aged and elderly Chinese people, cognitive impairment and multimorbidity resulted in substantial losses of QALE, and additional QALE losses were seen due to their interaction at both individual and population levels.

Gsslasso Cox: a Bayesian hierarchical model for predicting survival and detecting associated genes by incorporating pathway information.

BACKGROUND: Group structures among genes encoded in functional relationships or biological pathways are valuable and unique features in large-scale molecular data for survival analysis. However, most of previous approaches for molecular data analysis ignore such group structures. It is desirable to develop powerful analytic methods for incorporating valuable pathway information for predicting disease survival outcomes and detecting associated genes. RESULTS: We here propose a Bayesian hierarchical Cox survival model, called the group spike-and-slab lasso Cox (gsslasso Cox), for predicting disease survival outcomes and detecting associated genes by incorporating group structures of biological pathways. Our hierarchical model employs a novel prior on the coefficients of genes, i.e., the group spike-and-slab double-exponential distribution, to integrate group structures and to adaptively shrink the effects of genes. We have developed a fast and stable deterministic algorithm to fit the proposed models. We performed extensive simulation studies to assess the model fitting properties and the prognostic performance of the proposed method, and also applied our method to analyze three cancer data sets. CONCLUSIONS: Both the theoretical and empirical studies show that the proposed method can induce weaker shrinkage on predictors in an active pathway, thereby incorporating the biological similarity of genes within a same pathway into the hierarchical modeling. Compared with several existing methods, the proposed method can more accurately estimate gene effects and can better predict survival outcomes. For the three cancer data sets, the results show that the proposed method generates more powerful models for survival prediction and detecting associated genes. The method has been implemented in a freely available R package BhGLM at https://github.com/nyiuab/BhGLM .

Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information.

Motivation: Large-scale molecular data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, standard approaches for omics data analysis ignore the group structure among genes encoded in functional relationships or pathway information. Results: We propose new Bayesian hierarchical generalized linear models, called group spike-and-slab lasso GLMs, for predicting disease outcomes and detecting associated genes by incorporating large-scale molecular data and group structures. The proposed model employs a mixture double-exponential prior for coefficients that induces self-adaptive shrinkage amount on different coefficients. The group information is incorporated into the model by setting group-specific parameters. We have developed a fast and stable deterministic algorithm to fit the proposed hierarchal GLMs, which can perform variable selection within groups. We assess the performance of the proposed method on several simulated scenarios, by varying the overlap among groups, group size, number of non-null groups, and the correlation within group. Compared with existing methods, the proposed method provides not only more accurate estimates of the parameters but also better prediction. We further demonstrate the application of the proposed procedure on three cancer datasets by utilizing pathway structures of genes. Our results show that the proposed method generates powerful models for predicting disease outcomes and detecting associated genes. Availability and implementation: The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Contact: nyi@uab.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Exposure to Chinese famine in early life modifies the association between hyperglycaemia and cardiovascular disease.

BACKGROUND AND AIMS: The Great Leap Forward Famine during 1959-1961 was the world's largest famine, and its adverse long-term effects might be more apparent in the coming decade with ageing of the exposed populations. The aim of this study was to examine whether the Chinese Famine modified the effect of hyperglycaemia on cardiovascular disease (CVD). METHODS AND RESULTS: We used data of 4337 adults born between 1952 and 1964 collected from the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression was used to estimate the odds ratios (ORs) and confidence intervals (CIs) between hyperglycaemia and CVD. The prevalence of CVD showed significant difference among different famine exposure cohorts (P = 0.0156). After multivariable adjustment, the ORs (95% CIs) were as follows: 1.46 (0.94, 2.26) for late childhood, 1.76 (1.06, 2.90) for mid childhood, 1.40 (0.86, 2.27) for early childhood, 2.55 (1.30, 5.02) for the foetal cohort and 1.10 (0.63, 1.95) for the non-exposed cohort. There was a significant interaction between hyperglycaemia and famine exposure for CVD (P = 0.0374). In addition, the subgroup analyses showed that the effect of hyperglycaemia on CVD in the foetal exposure cohort was significantly higher than those in any of the other famine-exposed cohorts, especially in those who lived in rural areas (OR: 4.67, 95% CI: 1.70-12.84), those who lived in severe famine areas (OR: 5.01, 95% CI: 1.22-20.66) and those who were men (OR: 3.66, 95% CI: 1.01-13.33). CONCLUSION: Exposure to the Chinese Famine, especially during the foetal stage of life, aggravated the association between hyperglycaemia and CVD.

The spike-and-slab lasso Cox model for survival prediction and associated genes detection.

MOTIVATION: Large-scale molecular profiling data have offered extraordinary opportunities to improve survival prediction of cancers and other diseases and to detect disease associated genes. However, there are considerable challenges in analyzing large-scale molecular data. RESULTS: We propose new Bayesian hierarchical Cox proportional hazards models, called the spike-and-slab lasso Cox, for predicting survival outcomes and detecting associated genes. We also develop an efficient algorithm to fit the proposed models by incorporating Expectation-Maximization steps into the extremely fast cyclic coordinate descent algorithm. The performance of the proposed method is assessed via extensive simulations and compared with the lasso Cox regression. We demonstrate the proposed procedure on two cancer datasets with censored survival outcomes and thousands of molecular features. Our analyses suggest that the proposed procedure can generate powerful prognostic models for predicting cancer survival and can detect associated genes. AVAILABILITY AND IMPLEMENTATION: The methods have been implemented in a freely available R package BhGLM ( http://www.ssg.uab.edu/bhglm/ ). CONTACT: nyi@uab.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metabolomic characterization of hypertension and dyslipidemia.

BACKGROUND: Hypertension and dyslipidemia are two main risk factors for cardiovascular diseases (CVD). Moreover, their coexistence predisposes individuals to a considerably increased risk of CVD. However, the regulatory mechanisms involved in hypertension and dyslipidemia as well as their interactions are incompletely understood. OBJECTIVES: The aims of our study were to identify metabolic biomarkers and pathways for hypertension and dyslipidemia, and compare the metabolic patterns between hypertension and dyslipidemia. METHODS: In this study, we performed metabolomic investigations into hypertension and dyslipidemia based on a "healthy" UK population. Metabolomic data from the Husermet project were acquired by gas chromatography-mass spectrometry and ultra-performance liquid chromatography-mass spectrometry. Both univariate and multivariate statistical methods were used to facilitate biomarker selection and pathway analysis. RESULTS: Serum metabolic signatures between individuals with and without hypertension or dyslipidemia exhibited considerable differences. Using rigorous selection criteria, 26 and 46 metabolites were identified as potential biomarkers of hypertension and dyslipidemia respectively. These metabolites, mainly involved in fatty acid metabolism, glycerophospholipid metabolism, alanine, aspartate and glutamate metabolism, are implicated in insulin resistance, vascular remodeling, macrophage activation and oxidised LDL formation. Remarkably, hypertension and dyslipidemia exhibit both common and distinct metabolic patterns, revealing their independent and synergetic biological implications. CONCLUSION: This study identified valuable biomarkers and pathways for hypertension and dyslipidemia, and revealed common and different metabolic patterns between hypertension and dyslipidemia. The information provided in this study could shed new light on the pathologic mechanisms and offer potential intervention targets for hypertension and dyslipidemia as well as their related diseases.

Tea consumption is associated with cognitive impairment in older Chinese adults.

OBJECTIVE: To explore the association between tea consumption and cognitive impairment (CoI). METHODS: 4579 adults (≥60 years) from the Weitang Geratric Diseases Study were assessed for characteristics of tea consumption and cognitive function by administering questionnaires and the Abbreviated Mental Test (AMT), respectively. We divided the subjects into normal cognitive function group (AMT score ≥8) and CoI group (AMT score ≤7).   The association between tea consumption and risk of CoI was determined by logistic regression models. RESULTS: The least-squared means of the AMT scores for the subjects who seldom consumed tea were less favorable than those who habitually consumed tea. An inverse association was found between tea consumption (of any type) and prevalence of CoI (odds ratio = 0.74, 95% confidence interval = 0.57-0.98, P = 0.032). Interestingly, the protective correlation of tea was more obvious in never smokers (odds ratio = 0.63), but vanished in current/former smokers (odds ratio = 1.10). In never smokers, frequency of tea consumption was significantly associated with CoI (P for trend = 0.010). CONCLUSION: Habitual tea consumption is suggested to be associated with a decreased risk of CoI among elders in Suzhou, and a higher frequency of tea consumption was associated with a lower prevalence of CoI among never smokers.