Trends and projections of the global burden of thyroid cancer from 1990 to 2030.

Background: We aimed to explore the burden of thyroid cancer worldwide from 1990 to 2019 and to project its future trends from 2020 to 2030. Methods: Based on annual data on thyroid cancer cases from 1990 to 2019 available in the Global Burden of Disease (GBD) database, we calculated the age-standardised incidence, death, and disability-adjusted life year (DALY) rates for thyroid cancer. We used the estimated annual percentage change (EPAC) to quantify the temporal trends in these age-standardised rates from 1990 to 2019 and applied generalised additive models to project the disease burden from 2020 to 2030. Results: The global age-standardised incidence rate (ASIR) of thyroid cancer increased from 1990 to 2019, with a higher overall disease burden in women than in men at both study time points. The male-to-female ratios for the ASIR increased from 0.41 in 1990 to 0.51 in 2019, while the ratio for the age-standardised death rate (ASDR) increased from 0.60 to 0.82. The models predicted the United Arab Emirates would have the fastest rising trend in both the ASIR (estimated annual percentage changes (EAPC) = 4.19) and age-standardised DALY rate (EAPC = 4.36) in 2020-30, while Saint Kitts and Nevis will have the fastest rising trend in the ASDR (EAPC = 2.29). Meanwhile, the growth trends for the ASDR and age-standardised DALY rate are projected to increase across countries in this period. A correlation analysis of the global burden of thyroid cancer between 1990-2019 and 2020-30 showed a significant positive correlation between the increase in the ASIR and socio-demographic index (SDI) in low-SDI and low-middle-SDI countries. Conclusions: The global burden of thyroid cancer is increasing, especially in the female population and in low-middle-SDI regions, underscoring a need to target them for effective prevention, diagnosis, and treatment.

Identification of functional lncRNAs based on competing endogenous RNA network in osteoblast differentiation.

Adult human mesenchymal stem cells have the potential to differentiate into osteoblast, which plays crucial roles in bone regeneration and repair. Some transcriptional factors (TFs), such as BMP-2 and RUNX2, have been demonstrated to control the differentiation processes. It is important to discover more key regulators in osteoblast differentiation. Recently, some studies found long noncoding RNAs (lncRNAs) participating in osteoblast differentiation, such as MALAT1, DANCR, and ANCR. In this study, we performed a network-based computational analysis to investigate the lncRNA-messenger RNA (mRNA) crosstalks via integrating microRNA (miRNA)-RNA interactions, gene coexpression, and protein-protein interactions. First, multiple topology analyses were performed to osteoblast-differentiation-related lncRNA-mRNA network (ODLMN). Several lncRNAs with central topology structures were identified as key regulators. Results showed that these lncRNAs participated in osteoblast differentiation via phosphoinositide 3-kinase (PI3K), mitogen-activated protein kinase, and Ras signals. Previous studies have demonstrated that lncRNAs exert functions by involving in close modules. Second, after performing module searching in ODLMN, two functional modules were identified, which played crucial roles through involving in PI3K/protein kinase B, cyclic adenosine 3',5'-monophosphate, and hypoxia-inducible factor 1 pathways. Third, a subset of core lncRNA-TF crosstalks that might form feedback loops to control the biological processes in osteoblast differentiation was identified. These core lncRNA-TF feedback loops showed more TF binding affinity than other lncRNAs. All these results can help us to uncover the molecular mechanism and provide new targets for bone regeneration and repair.

A P53-related microRNA model for predicting the prognosis of hepatocellular carcinoma patients.

Studies have shown that microRNAs (miRNAs) play a vital role in tumor progression and patients' prognosis. Therefore, we aimed to construct a miRNA model for forecasting the survival of hepatocellular carcinoma (HCC) patients. The gene expression data of 433 patients with HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus public databases were remined by survival analysis and receptor manipulation characteristic curve (ROC). A prognostic model including six miRNAs (hsa-mir-26a-1-3p, hsa-mir-188-5p, hsa-mir-212-5p, hsa-mir-149-5p, hsa-mir-105-5p, and hsa-mir-132-5p) were constructed in the training dataset (TCGA, n = 333). HCC patients were stratified into a high-risk group and a low-risk group with significantly different survival (median: 2.75 vs. 8.93 years, log-rank test p < .001). Then we proved its performance of stratification in another independent dataset (GSE116182, median: 2.55 vs 6.96 years, log-rank test p = .008). Cox regression analysis showed that the prognostic model was an independent prognostic indicator for HCC patients. Then time-dependent ROC analyses were performed to test the prognostic ability of the model with that of TNM staging, we found the model had a better performance, especially at 5 years (AUC = 0.76). Functional prediction showed that the genes targeted by the six prognostic miRNAs in the prognostic model were highly expressed in the P53-related pathway. In conclusion, we constructed a prognostic miRNA model that could indicate the survival of HCC patients.

Gender-Specific Association of ATP2B1 Variants with Susceptibility to Essential Hypertension in the Han Chinese Population.

Previous genome-wide association studies (GWASs) found that several ATP2B1 variants are associated with essential hypertension (EHT). But the "genome-wide significant" ATP2B1 SNPs (rs2681472, rs2681492, rs17249754, and rs1105378) are in strong linkage disequilibrium (LD) and are located in the same LD block in Chinese populations. We asked whether there are other SNPs within the ATP2B1 gene associated with susceptibility to EHT in the Han Chinese population. Therefore, we performed a case-control study to investigate the association of seven tagSNPs within the ATP2B1 gene and EHT in the Han Chinese population, and we then analyzed the interaction among different SNPs and nongenetic risk factors for EHT. A total of 902 essential hypertensive cases and 902 normotensive controls were involved in the study. All 7 tagSNPs within the ATP2B1 gene were retrieved from HapMap, and genotyping was performed using the Tm-shift genotyping method. Chi-squared test, logistic regression, and propensity score analysis showed that rs17249754 was associated with EHT, particularly in females. The MDR analysis demonstrated that the interaction of rs2070759, rs17249754, TC, TG, and BMI increased the susceptibility to hypertension. Crossover analysis and stratified analysis indicated that BMI has a major effect on the development of hypertension, while ATP2B1 variants have a minor effect.