Search

PurposeOsteoporosis is a complex bone disease influenced by numerous factors. Previous studies have found that some metabolites are related to bone mineral density (BMD). However, the associations between metabolites and BMD under the influence of genes and lifestyle have not been fully investigated.MethodsWe analyzed the effect of metabolites on BMD under the synergistic effect of genes and lifestyle, using the data of 797 participants aged 55–65 years from the Taizhou Imaging Study. The cumulative sum method was used to calculate the polygenic risk score of SNPs, and the healthful plant-based diet index was used to summarize food intake. The effect of metabolites on BMD changes under the influence of genes and lifestyle was analyzed through interaction analysis and mediation analysis.ResultsNineteen metabolites were found significantly different in the osteoporosis, osteopenia, and normal BMD groups. We found two high-density lipoprotein (HDL) subfractions were positively associated with osteopenia, and six very-low-density lipoprotein subfractions were negatively associated with osteopenia or osteoporosis, after adjusting for lifestyles and genetic factors. Tea drinking habits, alcohol consumption, smoking, and polygenic risk score changed BMD by affecting metabolites.ConclusionWith the increased level of HDL subfractions, the risk of bone loss in the population will increase; the risk of bone loss decreases with the increased level of very-low-density lipoprotein subfractions. Genetic factors and lifestyles can modify the effects of metabolites on BMD. Our results show evidence for the precise prevention of osteoporosis.

The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of potential drug target genes between SCC and AC is crucial for more effective treatment of these diseases, given the high toxicity of chemotherapy and resistance to administered medications. Herein we attempted to identify and rank differentially expressed genes (DEGs) in SCC vs. AC using ensemble feature selection methods. RNA-seq data from The Cancer Genome Atlas and the Fudan-Taizhou Institute of Health Sciences (China). Six feature filters algorithms were used to identify DEGs. We built robust predictive models for histological subtypes with the random forest (RF) classification algorithm. Pathway analysis also be performed to investigate the functional role of genes. 294 informative DEGs (87 of them are newly discovered) have been identified. The areas under receiver operator curve (AUC) were higher than 99.5% for all feature selection (FS) methods. Nine genes (i.e., ERBB3, ATP7B, ABCC3, GALNT14, CLDN18, GUCY2C, FGFR4, KCNQ5, and CACNA1B) may play a key role in the development of more directed anticancer therapy for SCC and AC patients. The first four of them are drug targets for chemotherapy and immunotherapy of esophageal cancer and involved in pharmacokinetics and pharmacodynamics pathways. Research identified novel DEGs in SCC and AC, and detected four potential drug targeted genes (ERBB3, ATP7B, ABCC3, and GALNT14) and five drug-related genes.

Background: We aimed to explore the relationship between lifestyle factors, cancer family history, and gastric cancer risk.Methods: We examined the association between lifestyle factors, cancer family history, and gastric cancer risk based on a population-based case-control study in Taixing, China, with 870 cases and 1928 controls. A lifestyle score was constructed considering body shape, smoking, alcohol drinking, tooth brushing habit, and food storage method. Unconditional logistic regression models were used to calculate odd ratios (ORs) and 95% confidence intervals (CIs).Results: Compared with participants with a lifestyle score of 0, subjects with a lifestyle score of 1 (OR 0.59, 95%CI 0.43–0.83), 2 (OR 0.42, 95%CI 0.30–0.59), 3 (OR 0.29, 95%CI 0.20–0.41), 4 (OR 0.20, 95%CI 0.13–0.32), or 5 (OR 0.10, 95%CI 0.04–0.22) had a lower risk of gastric cancer (P for trend < 0.001). Overall, 34% of gastric cancer cases (95%CI 27–41%) can be attributed to non-compliance with ≥3 healthy lifestyle. Family history of early-onset cancer is closely related to the occurrence of gastric cancer, with an OR ranging from 1.77 to 3.27. Regardless of family history, a good lifestyle is associated with a reduced risk of gastric cancer, with an OR value between 0.38 and 0.70.Conclusions: The early-onset cancer family history is closely related to the occurrence of gastric cancer and a good lifestyle is associated with a reduced risk of gastric cancer regardless of family history. Our results provide a basis for identifying and providing behavior guidance of high-risk groups of gastric cancer.