Transcriptomic Analysis Under Drought and Salt Stress Provides Insight into Genes Putatively Involved in Ginsenoside Biosynthesis in Panax japonicus Meyer.

Panax japonicus Meyer, a perennial herb of the dicotyledonaceae family Araliaceae, is a rare folk traditional Chinese medicine, known as "the king of herbal medicine" in China. To understand the genes involved in secondary pathways under drought and salt stress, the transcriptomic analysis of P. japonicus is of vital importance. The transcriptome of underground rhizomes, stems, and leaves under drought and salt stress in P. japonicus were performed using the Illumina HiSeq platform. After de novo assembly of transcripts, expression profiling and identified differentially expressed genes (DEGs) were performed. Furthermore, putative functions of identified DEGs correlated with ginsenoside in P. japonicus were explored using Gene Ontology terms and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis. A total of 221,804 unigenes were obtained from the transcriptome of P. japonicus. The further analysis revealed that 10,839 unigenes were mapped to 91 KEGG pathways. Furthermore, a total of two metabolic pathways of P. japonicus in response to drought and salt stress related to triterpene saponin synthesis were screened. The sesquiterpene and triterpene metabolic pathways were annotated and finally putatively involved in ginsenoside content and correlation analysis of the expression of these genes were analyzed to identify four genes, ß-amyrin synthase, isoprene synthase, squalene epoxidase, and 1-deoxy-D-ketose-5-phosphate synthase, respectively. Our results paves the way for screening highly expressed genes and mining genes related to triterpenoid saponin synthesis. It also provides valuable references for the study of genes involved in ginsenoside biosynthesis and signal pathway of P. japonicus.

Associations of remnant cholesterol with cardiovascular and cancer mortality in a nationwide cohort.

The health significance of triglyceride-rich lipoproteins, also known as remnant cholesterol, has been increasingly recognized. However, evidence of their associations with cause-specific mortality in the general population was previously insufficient. To explore these associations and their heterogeneities across subgroups, a prospective cohort study was conducted including 3,403,414 community-based participants from ChinaHEART, an ongoing government-funded public health program throughout China, from November 2014 through December 2022. The study assessed mortality risk of all-cause mortality, cardiovascular disease (CVD) mortality (including mortality from ischemic heart diseases (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS), separately), and cancer mortality (including lung cancer, stomach cancer, and liver cancer, separately). During the 4-year follow-up, 23,646 individuals died from CVD (including 8807 from IHD, 3067 from IS, and 5190 from HS), and 20,318 from cancer (including 6208 from lung cancer, 3013 from liver cancer, and 2174 from stomach cancer). Compared with individuals with remnant cholesterol <17.9 mg/dL, multivariable-adjusted mortality hazard ratios (HRs) for individuals with remnant cholesterol ≥27.7 mg/dL were 1.03 (1.00-1.05) for all-cause mortality, 1.17 (1.12-1.21) for CVD (1.19 (1.12-1.27) for IHD mortality, and 1.22 (1.09-1.36) for IS mortality), and 0.90 (0.87-0.94) for all-cancer mortality (0.94 (0.87-1.02) for lung cancer, 0.59 (0.53-0.66) for liver cancer, and 0.73 (0.64-0.83) for stomach cancer). In summary, this study revealed a correlation between increased remnant cholesterol levels and an elevated risk of cardiovascular disease mortality, as well as a reduced risk of mortality for certain types of cancer.

Non-linear relationship between sleep duration and metabolic syndrome: A population-based study.

The aims of this study were to evaluate the prevalence of metabolic syndrome (MetS) and explore the association between sleep duration and MetS. This study enrolled 8 272 adults aged 18 years and older from 6 urban and 8 rural areas during 2013 to 2014in Henan China. Participants were interviewed about demographic characteristics, lifestyle factors and medical history, and physical measurements were performed. The relationships between sleep duration and MetS were evaluated and plotted by Restricted Cubic Spline Regression. The mean age was 51.5 years (SD 14.2) and 4 916 (59.4%) were female. The crude prevalence of MetS was 30.3% and the age-standardized rate was 23.6%. Men were more likely to have MetS than women (P = .01). MetS was positively associated with age, education, smoking, drinking, BMI and sleep duration, and seemed irrelevant to occupation and sedentary behavior. In terms of individual component of MetS, high blood pressure was the most prevalent component for both men and women, while the lowest prevalent was high triglycerides in men and for women was low high-density lipoprotein cholesterol (HDL-C). There was a U-shaped relationship between sleep duration and MetS and its components. Sleep duration <6 hours or >9 hours were associated with higher risk of MetS (OR from 1.10 to 2.15). The MetS was prevalent, and more than half of total adult population was suffering from high blood pressure. Sleep duration may be a determinant of metabolic health. Both short (<6 hours) and long sleep duration (>9 hours) was linked to an increased risk of MetS.

Body mass index had different effects on premenopausal and postmenopausal breast cancer risks: a dose-response meta-analysis with 3,318,796 subjects from 31 cohort studies.

BACKGROUND: There is sufficient evidence supporting a relationship between increased body mass index (BMI) and an increased risk for breast cancer among postmenopausal women. However, most studies have found a decreased risk for premenopausal breast cancer. This study was conducted to find out the different effects of BMI on the risk of breast cancer among premenopausal and postmenopausal women, and explore the potential factors that influence the associations. METHODS: A dose-response meta-analysis with 3,318,796 participants from 31 articles was conducted. Cohort studies that included BMI and corresponding breast cancer risk were selected through various databases including PubMed, Medline, Web of Science, the China National Knowledge Infrastructure (CNKI) and Chinese Scientific Journals (VIP). Random effects models were used for analyzing the data. RESULTS: The summary relative risks (RRs) were 1.33 (95%CI: 1.20-1.48) and 0.94(95%CI: 0.80-1.11) among postmenopausal and premenopausal women, respectively. The dose-response meta-analysis indicated a positive non-linear association between BMI and breast cancer risk among postmenopausal women, and compared to the mean level of the normal BMI category (21.5 kg/m2) the RR in total postmenopausal women were1.03 (95% CI: 1.02-1.05) per 1 kg/m2 increment. However, no statistically significant association among total premenopausal women was detected. In subgroup analysis among European premenopausal women, the summary RR was 0.79(95%CI: 0.70-0.88). The non-linear relationship showed a negative non-linear association between BMI and breast cancer risk among European premenopausal women. When compared to the mean level of the normal BMI category, the RRs were 0.98 (95%CI: 0.96-1.00) per 1 kg/m2 increment, respectively. CONCLUSIONS: In line with previous studies BMI had different effects on pre-menopausal and postmenopausal breast cancer risk. However, contrary to previous studies, a high BMI was not associated with decreased risk in total pre-menopausal women. More research is needed to better understand these differences.

A risk-score model for predicting risk of type 2 diabetes mellitus in a rural Chinese adult population: A cohort study with a 6-year follow-up.

BACKGROUND: Several prediction tools have been developed to identify people with type 2 diabetes mellitus (T2DM) and to quantify the probability of developing T2DM. However, most of the risk models were constructed based on cross-sectional studies and tea-drinking was not included. METHODS: A total of 15 768 participants without known T2DM were followed up from 2007-2008 to 2013-2014; 12 654 were randomly assigned to the derivation dataset and 3114 to the validation dataset. We constructed a risk-score model for T2DM by using a Cox proportional-hazards model. Risk scores were calculated by multiplying ß by 10 in the derivation cohort and were verified in the validation dataset. The model's accuracy was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: Predictors for T2DM risk in the derivation dataset were drinking tea frequently, body mass index ≥28.0 kg/m2 , waist to height ratio ≥ 0.5, triglycerides level 1.70 to 2.25 and ≥2.26 mmol/L, and fasting plasma glucose 5.6 to 6.0 and ≥6.1 mmol/L. The corresponding scores were -2, 7, 7, 4, 6, 11, and 25, respectively. The sensitivity, specificity, and AUC (95% confidence interval) for this full model were 69.63%, 75.56%, and 0.791 (0.783-0.799), respectively. The ability of the non-invasive models to predict T2DM was not superior to that of the full model. With the validation dataset, the predictive performance was better for our full model than the Framingham risk-score model (AUC 0.731 vs 0.525, P < .001). CONCLUSIONS: Our risk-score model has fair efficacy for predicting 6-year risk of T2DM in a rural adult Chinese population.

[Relationship between uncoupling protein 1 gene promoter methylation and obesity in adult].

OBJECTIVE: To observe the relationship between the methylation status in promoter region of uncoupling protein 1( UCP1) gene and obesity. METHODS: A casecontrol study based on the hospital consisted 116 people was carried out, according to the body mass index( BMI), the subjects were divided into two groups, the overweight and obesity group with 50 samples( BMI≥24. 0) and the normal weight group with 66 samples( 18. 5≤BMI < 24), DNA samples were extracted from white blood cell and treated by hydrogen sulfite. Then mass spectrometry method was used to quantificationally detect the methylation level UCP1 gene promoter. The difference between the two groups was compared and the relationships between CpG sites and BMI were explored. RESULTS: Statistical analysis showed that the methylation differences between normal weight and overweight or obese group were not statistically significant, however, the CpG site UCP1-2_ Cp G_ 10. 11. 12. 13 had statistical significance in correlation coefficients with BMI according to multiple linear regression method( regression coefficient was 15. 370, P <0. 05). CONCLUSION: The UCP1 gene promoter methylation may be a factor for adult obesity.

[Detection for gene-based gene-gene interaction via kernel canonical correlation analysis].

OBJECTIVE: To detect the gene-based gene-gene interaction by kernel canonical correlation analysis. METHODS: Based on case-control study, statistical simulation studies were conducted to construct and test the KCCU statistic to evaluate gene-based gene-gene interaction of gene FTO and gene PRDMl6 by kernel canonical correlation analysis. RESULTS: The power of KCCU statistic was related to significant level, sample size, minor allele frequency, and it was higher when the gene-gene interaction increased. The power arrived 0.8 at the significant level of 0.05 when the minor allele frequency was higher than 0.05, the interaction odds ratio was higher than 1.5, and the sample size was greater than 5000. CONCLUSION: KCCU statistic is a valid and powerful statistical inference method for detecting gene-based gene-gene interaction in the large sample analysis with high interaction.