Integration of pathologic characteristics, genetic risk and lifestyle exposure for colorectal cancer survival assessment.

The development of an effective survival prediction tool is key for reducing colorectal cancer mortality. Here, we apply a three-stage study to devise a polygenic prognostic score (PPS) for stratifying colorectal cancer overall survival. Leveraging two cohorts of 3703 patients, we first perform a genome-wide survival association analysis to develop eight candidate PPSs. Further using an independent cohort with 470 patients, we identify the 287 variants-derived PPS (i.e., PPS287) achieving an optimal prediction performance [hazard ratio (HR) per SD = 1.99, P = 1.76 × 10-8], accompanied by additional tests in two external cohorts, with HRs per SD of 1.90 (P = 3.21 × 10-14; 543 patients) and 1.80 (P = 1.11 × 10-9; 713 patients). Notably, the detrimental impact of pathologic characteristics and genetic risk could be attenuated by a healthy lifestyle, yielding a 7.62% improvement in the 5-year overall survival rate. Therefore, our findings demonstrate the integrated contribution of pathologic characteristics, germline variants, and lifestyle exposure to the prognosis of colorectal cancer patients.

Development, validation, and evaluation of a risk assessment tool for personalized screening of gastric cancer in Chinese populations.

BACKGROUND: Effective risk prediction models are lacking for personalized endoscopic screening of gastric cancer (GC). We aimed to develop, validate, and evaluate a questionnaire-based GC risk assessment tool for risk prediction and stratification in the Chinese population. METHODS: In this three-stage multicenter study, we first selected eligible variables by Cox regression models and constructed a GC risk score (GCRS) based on regression coefficients in 416,343 subjects (aged 40-75 years) from the China Kadoorie Biobank (CKB, development cohort). In the same age range, we validated the GCRS effectiveness in 13,982 subjects from another independent Changzhou cohort (validation cohort) as well as in 5348 subjects from an endoscopy screening program in Yangzhou. Finally, we categorized participants into low (bottom 20%), intermediate (20-80%), and high risk (top 20%) groups by the GCRS distribution in the development cohort. RESULTS: The GCRS using 11 questionnaire-based variables demonstrated a Harrell's C-index of 0.754 (95% CI, 0.745-0.762) and 0.736 (95% CI, 0.710-0.761) in the two cohorts, respectively. In the validation cohort, the 10-year risk was 0.34%, 1.05%, and 4.32% for individuals with a low (≤ 13.6), intermediate (13.7~30.6), and high (≥ 30.7) GCRS, respectively. In the endoscopic screening program, the detection rate of GC varied from 0.00% in low-GCRS individuals, 0.27% with intermediate GCRS, to 2.59% with high GCRS. A proportion of 81.6% of all GC cases was identified from the high-GCRS group, which represented 28.9% of all the screened participants. CONCLUSIONS: The GCRS can be an effective risk assessment tool for tailored endoscopic screening of GC in China. Risk Evaluation for Stomach Cancer by Yourself (RESCUE), an online tool was developed to aid the use of GCRS.

Maternal mortality ratio in Jiangsu Province, China: recent trends and associated factors.

BACKGROUND: In recent years, births to older mothers and multiparous mothers have increased rapidly with the change of birth policy in China. And mothers of advanced age are more likely to have maternal complications and poor birth outcomes. We aimed to estimate the recent trends and underlying risk factors of maternal mortality. METHODS: In this systematic assessment, we used data from the National Maternal and Child Health Routine Reporting System (2013-2018), Jiangsu Provincial Maternal Mortality Surveillance System (2017-2018), the Integrated National Mortality Surveillance System (2018), City Statistical Yearbooks (2018), City Health Statistical Yearbooks (2018). The factors associated with maternal mortality ratio (MMR) were explored using the stepwise regression analysis and cluster analysis. RESULTS: The MMR maintained at low levels between 2013 and 2016 and there was a slight increase in maternal mortality after 2016 in Jiangsu province. With the implementation of the China's universal two child policies, the percentage of multiparous mothers ascended from 34.2% (95% confidence interval (CI) = 34.1-34.3%) in 2013 to 51.4% (95% CI = 51.3-51.6%) in 2018 (beta = 3.88, P < 0.001). Consistently, the percentage of advanced maternal age (≥ 35) increased from 8.4% (95% CI = 8.4-8.5%) in 2013 to 10.4% (95% CI = 10.3-10.4%) in 2018 (beta = 0.50, P = 0.012). And we found that the percentage of multiparous mothers and advanced maternal age among maternal deaths were higher than all pregnant women (P < 0.001). In the stepwise regression analysis, four risk factors were significantly associated with maternal mortality ratio (primary industry of gross domestic product (GDP), rate of delivery in maternal and child health hospital, rate of cesarean section and rate of low birth weight). As the results derived from cluster analysis, the relatively developed regions had lower preventable maternal mortality ratio (43.5% (95% CI = 31.2-56.7%) vs. 62.6% (95% CI = 52.3-72.0%), P = 0.027). CONCLUSIONS: Since the universal two child policy has been associated with changes in health related birth characteristics: women giving birth have been more likely to be multiparous, and more likely to be aged 35 and over. This somewhat magnifies the impact of differences in economic development and obstetric services on MMR. The findings based on prefecture level data suggest that interventions must target economic development, the health system and maternal risk factors in synergy. These approaches will be of great benefit to control or diminish environmental factors associated with preventable deaths and will effectively reduce MMR and narrow the gap among the different regions.

Risk assessment models for genetic risk predictors of lung cancer using two-stage replication for Asian and European populations.

In the past ten years, great successes have been accumulated by taking advantage of both candidate-gene studies and genome-wide association studies. However, limited studies were available to systematically evaluate the genetic effects for lung cancer risk with large-scale and different ethnic populations. We systematically reviewed relevant literatures and filtered out 241 important genetic variants identified in 124 articles. A two-stage case-control study within specific subgroups was performed to assess the effects [Training set: 2,331 cases vs. 3,077 controls (Chinese population); testing set: 1,937 cases vs. 1,984 controls (European population)]. Variable selection and model development were used LASSO penalized regression and genetic risk score (GRS) system. Further change in area under the receiver operator characteristic curves (AUC) made by the epidemiologic model with and without GRS was used to compare predictions. It kept 38 genetic variants in our study and the ratios of lung cancer risk for subjects in the upper quartile GRS was three times higher compared to that in the low quartile (odds ratio: 4.64, 95% CI: 3.87-5.56). In addition, we found that adding genetic predictors to smoking risk factor-only model improved lung cancer predictive value greatly: AUC, 0.610 versus 0.697 (P < 0.001). Similar performance was derived in European population and the combined two data sets. Our findings suggested that genetic predictors could improve the predictive ability of risk model for lung cancer and highlighted the application among different populations, indicating that the lung cancer risk assessment model will be a promising tool for high risk population screening and prediction.

A fast algorithm for Bayesian multi-locus model in genome-wide association studies.

Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data. Here, we propose a fast algorithm of Bayesian adaptive lasso using variational inference (BAL-VI). Extensive simulations and real data analysis indicate that our model outperforms the well-known Bayesian lasso and Bayesian adaptive lasso models in accuracy and speed. BAL-VI can complete a simultaneous analysis of a lung cancer GWAS data with ~3400 subjects and ~570,000 SNPs in about half a day.

Comprehensive assessment showed no associations of variants at the SLC10A1 locus with susceptibility to persistent HBV infection among Southern Chinese.

The sodium taurocholate cotransporting polypeptide (NTCP) encoded by SLC10A1 was recently demonstrated to be a functional receptor for hepatitis B virus (HBV). The role of SLC10A1 polymorphisms, particularly the Ser267Phe variant (rs2296651) in exon 4, has been frequently investigated in regard to risk of persistent HBV infection. However, these investigations have generated conflicting results. To examine whether common genetic variation at the SLC10A1 locus is associated with risk of persistent HBV infection, haplotype-tagging and imputed single nucleotide polymorphisms (SNPs) were assessed in two case-control sample sets, totally including 2,550 cases (persistently HBV infected subjects, PIs) and 2,124 controls (spontaneously recovered subjects, SRs) of Southern Chinese ancestry. To test whether rare or subpolymorphic SLC10A1 variants are associated with disease risk, the gene's exons in 244 cases were sequenced. Overall, we found neither SNPs nor haplotypes of SLC10A1 showed significant association in the two sample sets. Furthermore, no significant associations of rare variants or copy number variation covering SLC10A1 were observed. Finally, expression quantitative trait locus analyses revealed that SNPs potentially affecting SLC10A1 expression also showed no significant associations. We conclude that genetic variation at the SLC10A1 locus is not likely a major risk factor of persistent HBV infection among Southern Chinese.

[Forest resources in Qungyuan County of Liaoning, Northeast China: the structure and optimal spatial allocation].

By using RS/GIS techniques and the method of multiple objective grey situation decision, and in considering the forest economic benefits (biomass and stand productivity) and ecological benefits (water and soil conservation) , an optimal spatial allocation of the present forest types in Qingyuan County of Liaoning, Northeast China was approached in this study. After the optimization of spatial allocation, the structural proportions of different forest types in Qingyuan County changed obviously, with the area of coniferous forests reduced from 43% to 23% , the area of broadleaved forests reduced from 51% to 31% , the area of mixed coniferous-broadleaf forests increased from 3% to 43% , and the area of shrubs remained unchanged. As compared with the results before optimization, the biomass, stand productivity, and water conservation function of the forest ecosystem in Qingyuan County after optimization increased by 0.6%, 2.1% , and 31.7%, respectively, and the soil conservation function remained unchanged. It could be concluded that after the optimization of spatial allocation, the forest ecosystem of Qingyuan County could maintain its soil conservation function, and, at the time of keeping higher timber production, fully exert waler conservation function, realizing the maximization of the economic and ecological benefits of the forest ecosystem.

Prognostic assessment of apoptotic gene polymorphisms in non-small cell lung cancer in Chinese.

Apoptosis plays a key role in inhibiting tumor growth, progression and resistance to anti-tumor therapy. We hypothesized that genetic variants in apoptotic genes may affect the prognosis of lung cancer. To test this hypothesis, we selected 38 potentially functional single nucleotide polymorphisms (SNPs) from 12 genes (BAX, BCL2, BID, CASP3, CASP6, CASP7, CASP8, CASP9, CASP10, FAS, FASLG and MCL1) involved in apoptosis to assess their prognostic significance in lung cancer in a Chinese case cohort with 568 non-small cell lung cancer (NSCLC) patients. Thirty-five SNPs passing quality control underwent association analyses, 11 of which were shown to be significantly associated with NSCLC survival (P < 0.05). After Cox stepwise regression analyses, 3 SNPs were independently associated with the outcome of NSCLC (BID rs8190315: P = 0.003; CASP9 rs4645981: P = 0.007 and FAS rs1800682: P = 0.016). A favorable survival of NSCLC was significantly associated with the genotypes of BID rs8190315 AG/GG (adjusted HR = 0.65, 95% CI: 0.49-0.88), CASP9 rs4645981 AA (HR = 0.22, 95% CI: 0.07-0.69) and FAS rs1800682 GG (adjusted HR = 0.67, 95% CI: 0.46-0.97). Time-dependent receptor operation curve (ROC) analysis revealed that the area under curve (AUC) at year 5 was significantly increased from 0.762 to 0.819 after adding the risk score of these 3 SNPs to the clinical risk score. The remaining 32 SNPs were not significantly associated with NSCLC prognosis after adjustment for these 3 SNPs. These findings indicate that BID rs8190315, CASP9 rs4645981 and FAS rs1800682 polymorphisms in the apoptotic pathway may be involved in the prognosis of NSCLC in the Chinese population.

Breast cancer risk assessment with five independent genetic variants and two risk factors in Chinese women.

INTRODUCTION: Recently, several genome-wide association studies (GWAS) have identified novel single nucleotide polymorphisms (SNPs) associated with breast cancer risk. However, most of the studies were conducted among Caucasians and only one from Chinese. METHODS: In the current study, we first tested whether 15 SNPs identified by previous GWAS were also breast cancer marker SNPs in this Chinese population. Then, we grouped the marker SNPs, and modeled them with clinical risk factors, to see the usage of these factors in breast cancer risk assessment. Two methods (risk factors counting and odds ratio (OR) weighted risk scoring) were used to evaluate the cumulative effects of the five significant SNPs and two clinical risk factors (age at menarche and age at first live birth). RESULTS: Five SNPs located at 2q35, 3p24, 6q22, 6q25 and 10q26 were consistently associated with breast cancer risk in both testing set (878 cases and 900 controls) and validation set (914 cases and 967 controls) samples. Overall, all of the five SNPs contributed to breast cancer susceptibility in a dominant genetic model (2q35, rs13387042: adjusted OR = 1.26, P = 0.006; 3q24.1, rs2307032: adjusted OR = 1.24, P = 0.005; 6q22.33, rs2180341: adjusted OR = 1.22, P = 0.006; 6q25.1, rs2046210: adjusted OR = 1.51, P = 2.40 × 10-8; 10q26.13, rs2981582: adjusted OR = 1.31, P = 1.96 × 10-4). Risk score analyses (area under the curve (AUC): 0.649, 95% confidence interval (CI): 0.631 to 0.667; sensitivity = 62.60%, specificity = 57.05%) presented better discrimination than that by risk factors counting (AUC: 0.637, 95% CI: 0.619 to 0.655; sensitivity = 62.16%, specificity = 60.03%) (P < 0.0001). Absolute risk was then calculated by the modified Gail model and an AUC of 0.658 (95% CI = 0.640 to 0.676) (sensitivity = 61.98%, specificity = 60.26%) was obtained for the combination of five marker SNPs, age at menarche and age at first live birth. CONCLUSIONS: This study shows that five GWAS identified variants were also consistently validated in this Chinese population and combining these genetic variants with other risk factors can improve the risk predictive ability of breast cancer. However, more breast cancer associated risk variants should be incorporated to optimize the risk assessment.