RESUMEN
Existing traditional Chinese medicine (TCM)-related databases are still insufficient in data standardization, integrity and precision, and need to be updated urgently. Herein, an Encyclopedia of Traditional Chinese Medicine version 2.0 (ETCM v2.0, http://www.tcmip.cn/ETCM2/front/#/) was constructed as the latest curated database hosting 48,442 TCM formulas recorded by ancient Chinese medical books, 9872 Chinese patent drugs, 2079 Chinese medicinal materials and 38,298 ingredients. To facilitate the mechanistic research and new drug discovery, we improved the target identification method based on a two-dimensional ligand similarity search module, which provides the confirmed and/or potential targets of each ingredient, as well as their binding activities. Importantly, five TCM formulas/Chinese patent drugs/herbs/ingredients with the highest Jaccard similarity scores to the submitted drugs are offered in ETCM v2.0, which may be of significance to identify prescriptions/herbs/ingredients with similar clinical efficacy, to summarize the rules of prescription use, and to find alternative drugs for endangered Chinese medicinal materials. Moreover, ETCM v2.0 provides an enhanced JavaScript-based network visualization tool for creating, modifying and exploring multi-scale biological networks. ETCM v2.0 may be a major data warehouse for the quality marker identification of TCMs, the TCM-derived drug discovery and repurposing, and the pharmacological mechanism investigation of TCMs against various human diseases.
RESUMEN
The aims of this study are to estimate the contributions of genetic factors to the variation of tea drinking and cigarette smoking, to examine the roles of genetic factors in their correlation and further to investigate underlying causation between them. We included 11 625 male twin pairs from the Chinese National Twin Registry (CNTR). Bivariate genetic modelling was fitted to explore the genetic influences on tea drinking, cigarette smoking and their correlation. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was further used to explore the causal relationship between them. We found that genetic factors explained 17% and 23% of the variation in tea drinking and cigarette smoking, respectively. A low phenotypic association between them was reported (rph = 0.21, 95% confidence interval [CI]: [0.19, 0.24]), which was partly attributed to common genetic factors (rA = 0.45, 95% CI [0.19, 1.00]). In the ICE FALCON analysis with current smoking as the exposure, tea drinking was associated with his own (ßself = 0.39, 95% CI [0.23, 0.55]) and his co-twin's smoking status (ßco-twin = 0.25, 95% CI [0.10, 0.41]). Their association attenuated with borderline significance conditioning on his own smoking status (p = 0.045), indicating a suggestive causal effect of smoking status on tea drinking. On the contrary, when we used tea drinking as the predictor, we found familial confounding between them only. In conclusion, both tea drinking and cigarette smoking were influenced by genetic factors, and their correlation was partly explained by common genetic factors. In addition, our finding suggests that familial confounders account for the relationship between tea drinking and cigarette smoking. And current smoking might have a causal effect on weekly tea drinking, but not vice versa.