Shuai Chen’s research while affiliated with First Affiliated Hospital of China Medical University and other places

Purpose This research focused on meticulously tracking and identifying adverse reactions associated with leuprorelin, a drug prescribed for conditions such as prostate cancer, endometriosis, uterine fibroids, and early-onset puberty. The main objective was to enhance patient safety and offer informed guidance on the appropriate use of this treatment. Methods From the first quarter of 2004 to the fourth quarter of 2023, a comprehensive analysis was conducted on a significant number of adverse event reports (AERs) from the FDA Adverse Event Reporting System (FAERS) database. Data mining with dismutation analysis was conducted to quantify signals associated with adverse events (AEs) related to leuprorelin, utilizing powerful algorithms such as ROR, PRR, BCPNN, and EBGM. Results A total of 102 positive reaction terms (PT) spanning 24 System Organ Classes (SOCs) were identified from an analysis of 60,709 reports associated with leuprorelin use. Notably, several previously unrecognized adverse reactions were uncovered, including Artificial Menopause, Ovarian Adhesion, Follicular Cystitis, Intercepted product preparation error, among others. These findings underscore the importance of exercising additional vigilance regarding the potential adverse effects of leuprorelin, such as Abscess Sterile, Injection site granuloma, Intercepted medication error, and Bulbospinal muscular atrophy congenital. Conclusions This research has successfully uncovered new and unforeseen signals associated with adverse drug reactions (ADRs) following leuprorelin administration. The study provides valuable insights into the intricate connection between ADRs and leuprorelin usage. The results underscore the crucial significance of continuous surveillance and meticulous monitoring to promptly identify and manage AEs, ultimately enhancing patient safety and well-being while undergoing leuprorelin therapy.

Background In recent years, with the continuous expansion of the application scope of Tranexamic acid (TXA), its usage has surged. Despite numerous studies demonstrating its powerful efficacy, concerns regarding its adverse reactions persist, necessitating comprehensive safety assessment. This study analyzed real-world data from the U.S. Food and Drug Administration to investigate TXA-related adverse events, aiming to elucidate its safety and optimize patient treatment. Methods The adverse drug event data concerning TXA from 2004 Q1 to 2023 Q3 were collected. Following data standardization, a variety of signal quantification techniques, including the reporting odds ratios, proportional reporting ratios, Bayesian confidence propagation neural network, and empirical Bayes geometric mean were used for analysis. Results After analyzing 16,692,026 adverse event reports, a total of 1,574 cases of adverse events related to TXA were identified, spanning 23 system organ classes and 307 preferred terms. In addition to the common thrombosis-related Vascular disorders (n = 386) and Cardiac disorders (n = 377), adverse reactions in the Nervous system disorders category were also observed (n = 785), including Myoclonus (n = 70), Status epilepticus (n = 43), and Myoclonic epilepsy (n = 17). Furthermore, this study uncovered adverse effects such as Renal cortical necrosis, Hepatic cyst rupture, and Vascular stent stenosis, which were not previously mentioned in the instructions. Although these occurred infrequently, they exhibited high signal strength. Both Retinal artery occlusion and Vascular stent thrombosis disorder were frequent and exhibited high signal strength as well. It is worth noting that 78 cases of adverse reactions were caused by confusion between incorrect product administration. Conclusion Our research suggests that TXA has some adverse reactions that are being overlooked. As a cornerstone medication in hemorrhage treatment, it’s crucial to monitor, identify, and address these adverse reactions effectively.

Background Previous investigations have demonstrated a correlation between the composition of gut microbiota and the development of thyroid cancer (TC). Nonetheless, there was no consensus on the causal effect of gut microbiota composition on TC risk. Therefore, the present study aimed to perform a bidirectional two-sample Mendelian randomization (MR) analysis to explore potential causal associations between gut microbiota and TC risk. Methods Utilizing data from the MiBioGen consortium’s genome-wide association studies (GWAS) meta-analysis involving a sample size of 18,340, we identified instrumental variables for 211 gut microbiota taxa. The summary statistics for TC was from relevant large-scale GWAS conducted by the FinnGen consortium. In the first stage, the Inverse-variance weighted (IVW) method was used as the primary estimate method, and the stability of estimations was tested by a battery of sensitivity analyses. In the second stage, a reverse MR analysis was applied to determine whether reverse causality existed. Results According to the IVW method, we identified 9 genetically predicted gut microbiota that were causally correlated with TC risk. Among them, we observed a positive causal effect of Family Christensenellaceae (OR = 1.664, 95% CI: 1.103–2.511, P = 0.015), Family Victivallaceae (OR = 1.268, 95% CI: 1.009–1.594, P = 0.042), Genus Methanobrevibacter (OR = 1.505, 95% CI: 1.049–2.159, P = 0.027), Genus Ruminococcus2 (OR = 1.846, 95% CI: 1.261–2.704, P = 0.002), Genus Subdoligranulum (OR = 1.907, 95% CI: 1.165–3.121, P = 0.010), Phylum Verrucomicrobia (OR = 1.309, 95% CI: 1.027–1.668, P = 0.029) on TC risk, while Class Betaproteobacteria (OR = 0.522, 95% CI: 0.310–0.879, P = 0.015), Family Family XI (OR = 0.753, 95% CI: 0.577–0.983, P = 0.037), Genus Sutterella (OR = 0.596, 95% CI: 0.381–0.933, P = 0.024) might be correlated with a decreased risk of TC. Subsequently, various sensitivity analyses indicated no heterogeneity, directional pleiotropy or outliers. In addition, reverse analysis demonstrated a negative causal effect of TC risk on the abundance of the gut microbiota (Genus Ruminococcus2, OR = 0.947, 95% CI: 0.907–0.989, P = 0.014). Conclusion Genetic evidence suggested that bidirectional causal associations of specific bacteria taxa and the risk of TC, highlighting the association of the “gut-thyroid” axis. Further exploration of the potential microbiota-related mechanisms might have profound implications for public health in terms of the early prevention and treatment of TC.

The Homeostatic Model Assessment for Triglyceride Glucose Index (TyG) and its related indices, including triglyceride glucose-waist circumference (TyG-WC), triglyceride glucose-waist-to-height ratio (TyG-WHtR) and triglyceride glucose-body mass index (TyG-BMI), has emerged as a practical tool for assessing insulin resistance in metabolic disorders. However, limited studies have explored the connection between TyG, TyG-related indices and osteoporosis. This population-based study, utilizing data from the National Health and Nutrition Examination Survey 2011–2018, involved 5456 participants. Through weighted multivariate linear regression and smoothed curve fitting, a significant positive correlation was found between TyG, TyG-related indices and total bone mineral density (BMD) after adjusting for covariates [β = 0.0124, 95% CI (0.0006, 0.0242), P = 0.0390; β = 0.0004, 95% CI (0.0003, 0.0004), P < 0.0001; β = 0.0116, 95% CI (0.0076, 0.0156), P < 0.0001; β = 0.0001, 95% CI (0.0001, 0.0001), P < 0.0001]. In subgroup analysis, race stratification significantly affected the relationship between TyG and total BMD. Additionally, gender and race were both significant for TyG-related indices. Non-linear relationships and threshold effects with inflection points at 9.106, 193.9265, 4.065, and 667.5304 (TyG, TyG-BMI, TyG-WHtR, TyG-WC) were identified. Saturation phenomena were observed between TyG-BMI, TyG-WC and total BMD with saturation thresholds at 314.177 and 1022.0428. These findings contributed to understanding the association between TyG, TyG-related indices and total BMD, offering insights for osteoporosis prevention and treatment.

Background Cancer remains one of the leading causes of mortality worldwide. Diet can impact inflammation and consequently affect cancer outcomes. The Dietary Inflammatory Index (DII) can serve as a tool to assess the inflammatory potential of cancer survivors' diets and further predict their survival. Objectives To investigate the relationship between the DII and the survival of cancer survivors in National Health and Nutrition Examination Survey (NHANES). Methods An overall sample of 2359 U.S. cancer survivors from the 2005–2014 cohorts of the NHANES were studied. The DII scores were calculated using 28 dietary components and the mortality status was ascertained until December 31, 2015. Based on the multiple analyses, the relationship between DII and all-cause mortality was examined. Results The weighted mean age at baseline was 65.17 ± 14.46 years, 53.16 % were female and 71.30 % were non-Hispanic white. The average DII was 1.51 ± 1.97. After accounting for multiple covariates, positive associations were observed (P < 0.01). Based on Kaplan-Meier survival curves, their significant relationship remains same and the survival probability was decreased among the groups of anti-inflammatory diets (DII < 0) versus pro-inflammatory diets (DII ≥ 0) significantly (Log rank test; P = 0.03). Further analyses were conducted on subgroups and the results are still robust. Conclusions An elevated DII was associated with a rising mortality rate among cancer survivors. DII might serve as a potential inflammatory predictor of cancer mortality prognosis, as well as guide nutritional care and even clinical treatment of cancer survivors.

Background Recent observational studies and clinical trials demonstrated an association between gut microbiota and musculoskeletal (MSK) diseases. Nonetheless, whether the gut microbiota composition has a causal effect on the risk of MSK diseases remains unclear. Methods Based on large-scale genome-wide association studies (GWAS), we performed a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between gut microbiota and six MSK diseases, namely osteoporosis (OP), fracture, sarcopenia, low back pain (LBP), rheumatoid arthritis (RA), and ankylosing spondylitis (AS). Instrumental variables for 211 gut microbiota taxa were obtained from the largest available GWAS meta-analysis (n = 18,340) conducted by the MiBioGen consortium. And the summary-level data for six MSK diseases were derived from published GWAS. The inverse-variance weighted (IVW) method was conducted as a primary analysis to estimate the causal effect, and the robustness of the results was tested via sensitivity analyses using multiple methods. The Bonferroni-corrected test was used to determine the strength of the causal relationship between gut microbiota and various MSK diseases. Finally, a reverse MR analysis was applied to evaluate reverse causality. Results According to the IVW method, we found 57 suggestive causal relationships and 3 significant causal relationships between gut microbiota and MSK diseases. Among them, Genus Bifidobacterium (β: 0.035, 95% CI: 0.013–0.058, p = 0.0002) was associated with increased left handgrip strength, Genus Oxalobacter (OR: 1.151, 95% CI: 1.065–1.245, p = 0.0003) was correlated with an increased risk of LBP, and Family Oxalobacteraceae (OR: 0.792, 95% CI: 0.698–0.899, p = 0.0003) was linked with a decreased risk of RA. Subsequently, sensitivity analyses revealed no heterogeneity, directional pleiotropy, or outliers for the causal effect of specific gut microbiota on MSK diseases (p > 0.05). Reverse MR analysis showed fracture may result in a higher abundance of Family Bacteroidales (p = 0.030) and sarcopenia may lead to a higher abundance of Genus Sellimonas (p = 0.032). Conclusion Genetic evidence suggested a causal relationship between specific bacteria taxa and six MSK diseases, which highlights the association of the “gut-bone/muscle” axis. Further exploration of the potential microbiota-related mechanisms of bone and muscle metabolism might provide novel insights into the prevention and treatment of MSK diseases.

Background Recent studies have reported that the gut microbiota is essential for preventing and delaying the progression of osteoporosis. Nonetheless, the causal relationship between the gut microbiota and the risk of osteoporosis has not been fully revealed. Methods A two-sample Mendelian randomization (MR) analysis based on a large-scale genome-wide association study (GWAS) was conducted to investigate the causal relationship between the gut microbiota and bone mineral density (BMD). Instrumental variables for 211 gut microbiota taxa were obtained from the available GWAS meta-analysis (n = 18,340) conducted by the MiBioGen consortium. The summary-level data for BMD were from the Genetic Factors for Osteoporosis (GEFOS) Consortium, which involved a total of 32,735 individuals of European ancestry. The inverse variance-weighted (IVW) method was performed as a primary analysis to estimate the causal effect, and the robustness of the results was tested via sensitivity analyses by using multiple methods. Finally, a reverse MR analysis was applied to evaluate reverse causality. Results According to the IVW method, we found that nine, six, and eight genetically predicted gut microbiota were associated with lumbar spine (LS) BMD, forearm (FA) BMD, and femoral neck (FN) BMD, respectively. Among them, the higher genetically predicted Genus Prevotella9 level was correlated with increased LS-BMD [β = 0.125, 95% confidence interval (CI): 0.050–0.200, P = 0.001] and FA-BMD (β = 0.129, 95% CI: 0.007–0.251, P = 0.039). The higher level of genetically predicted Family Prevotellaceae was associated with increased FA-BMD (β = 0.154, 95% CI: 0.020–0.288, P = 0.025) and FN-BMD (β = 0.080, 95% CI: 0.015–0.145, P = 0.016). Consistent directional effects for all analyses were observed in both the MR-Egger and weighted median methods. Subsequently, sensitivity analyses revealed no heterogeneity, directional pleiotropy, or outliers for the causal effect of specific gut microbiota on BMD (P > 0.05). In reverse MR analysis, there was no evidence of reverse causality between LS-BMD, FA-BMD, and FN-BMD and gut microbiota (P > 0.05). Conclusion Genetic evidence suggested a causal relationship between the gut microbiota and BMD and identified specific bacterial taxa that regulate bone mass variation. Further exploration of the potential microbiota-related mechanisms of bone metabolism might provide new approaches for the prevention and treatment of osteoporosis.

Background: Osteoarthritis (OA) and sarcopenia are common musculoskeletal disorders in the aged population, and a growing body of evidence indicated that they mutually influence one another. Nevertheless, there was still substantial controversy and uncertainty about the causal relationship between sarcopenia and OA. We explored the complex association between sarcopenia-related traits and OA using cross-sectional analysis and Mendelian randomization (MR). Methods: The cross-sectional study used the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. Weighted multivariable-adjusted logistic regression and subgroup analyses were used to evaluate the correlation between sarcopenia, grip, appendicular lean mass (ALM) and the risk of OA. Then, we further performed MR analysis to examine the causal effect of sarcopenia-related traits (grip strength, ALM) on OA. Instrumental variables for grip strength and ALM were from the UK Biobank, and the summary-level data for OA was derived from the Genetics of Osteoarthritis (GO) Consortium GWAS (n = 826,690). Results: In this cross-sectional analysis, we observed that sarcopenia, grip were significantly linked with the risk of OA (OR 1.607, 95% CI 1.233-2.094, P < 0.001), (OR 0.972, 95% CI 0.964-0.979, P < 0.001). According to subgroup analyses stratified by gender, body mass index (BMI), and age, the significant positive relationship between sarcopenia and OA remained in males, females, the age (46-59 years) group, and the BMI (18.5-24.9 kg/m2) group (P < 0.05). Furthermore, MR analysis and sensitivity analyses showed causal associations between right grip, left grip and KOA (OR 0.668; 95% CI 0.509 to 0.877; P = 0.004), (OR 0.786; 95% CI 0.608 to 0.915; P = 0.042). Consistent directional effects for all analyses were observed in both the MR-Egger and weighted median methods. Subsequently, sensitivity analyses revealed no heterogeneity, directional pleiotropy or outliers for the causal effect of grip strength on KOA (P > 0.05). Conclusions: Our research provided evidence that sarcopenia is correlated with an increased risk of OA, and there was a protective impact of genetically predicted grip strength on OA. These findings needed to be verified in further prospective cohort studies with a large sample size.

Introduction: There is evidence that individual antioxidants may increase bone mineral density (BMD) in patients with low BMD. However, the association between overall dietary antioxidant intake and BMD is unclear. The objective of this study was to examine how overall dietary antioxidant intake is related to BMD. Materials and methods: A total of 14,069 people participated in the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2010. Dietary Antioxidant Index (DAI) was calculated from the intake of vitamins A, C, E, zinc, selenium, and magnesium, which indicates a nutritional tool to assess the overall antioxidant properties of the diet. The correlation between the Composite Dietary Antioxidant Index (CDAI) and BMD was examined using multivariate logistic regression models. In addition to fitting smoothing curves, we fitted generalized additive models as well. Furthermore, to ensure data stability and avoid confounding factors, subgroup analysis was also conducted on gender and body mass index (BMI). Results: A significant association was demonstrated by the study between CDAI and total spine BMD (β = 0.001, 95% CI 0-0.001, P = 0.00039). And just like that, CDAI was positively correlated with femoral neck (β = 0.003, 95% CI 0.003-0.004, P < 0.00001) and trochanter (β = 0.004, 95% CI 0.003-0.004, P < 0.00001). In the gender subgroup analysis, CDAI maintained a strong positive correlation with femoral neck and trochanter BMD in males and females. Nevertheless, the link with total spine BMD was only observed in males. In addition, in the subgroup analysis stratified by BMI, CDAI showed a significantly positive relation to BMD of the femoral neck and trochanter in each group. However, the significant relationship between CDAI and BMD of the total spine was only maintained when BMI was above 30 kg/m2. Conclusion: This study found that CDAI correlated positively with femoral neck, trochanter, and total spine BMD. This suggests that intake of a diet rich in antioxidants can reduce the risk of low bone mass and osteoporosis.