Mendelian randomization study of urolithiasis: exploration of risk factors using human blood metabolites.

BACKGROUND: Urolithiasis is a highly prevalent global disease closely associated with metabolic factors; however, the causal relationship between blood metabolites and urolithiasis remains poorly understood. METHOD: In our study, we employed a bi-directional two-sample Mendelian randomization (MR) analysis to investigate the causal associations between urolithiasis and metabolites. The random-effects inverse-variance weighted (IVW) estimation method was utilized as the primary approach, complemented by several other estimators including MR-Egger, weighted median, colocalization and MR-PRESSO. Furthermore, the study included replication and meta-analysis. Finally, we conducted metabolic pathway analysis to elucidate potential metabolic pathways. RESULTS: After conducting multiple tests for correction, glycerol might contribute to the urolithiasis and dehydroisoandrosterone sulfate (DHEA-S) might inhibit this process. Furthermore, several blood metabolites had shown potential associations with a causal relationship. Among the protective metabolites were lipids (dehydroisoandrosterone sulfate and 1-stearoylglycerol (1-monostearin)), amino acids (isobutyrylcarnitine and 2-aminobutyrate), a keto acid (acetoacetate) and a carbohydrate (mannose). The risk metabolites included lipids (1-palmitoylglycerophosphoethanolamine, glycerol and cortisone), a carbohydrate (erythronate), a peptide (pro-hydroxy-pro) and a fatty acid (eicosenoate). In reverse MR analysis, urolithiasis demonstrated a statistically significant causal relationship with butyrylcarnitine, 3-methyl-2-oxobutyrate, scyllo-inositol, leucylleucine and leucylalanine. However, it was worth noting that none of the blood metabolites exhibited statistical significance after multiple corrections. Additionally, we identified one metabolic pathway associated with urolithiasis. CONCLUSION: The results we obtained demonstrate the causal relevance between two metabolites and urolithiasis, as well as identify one metabolic pathway potentially associated with its development. Given the high prevalence of urolithiasis, further investigations are encouraged to elucidate the mechanisms of these metabolites and explore novel therapeutic strategies.

Time-dependent analysis of erectile dysfunction in kidney transplant recipients: insights from four distinct time periods.

BACKGROUND AND INTENTION: Erectile dysfunction (ED) is an underappreciated clinical condition in men. This study aims to compare the dynamic changes in the distribution of ED among male kidney transplant recipients (mKTRs) in four epochs: end-stage renal disease period (ESRDp), early post-transplant period (EPTP), pre-COVID-19, and post-COVID-19. METHODS: General information was gathered through interviews, follow-ups, and medical records. The International Index of Erectile Function Questionnaire-5 was used to assess erectile function. The Mann-Whitney U test and chi-square test were used to analyze differences in ED strength. Univariate and logistic regression analyses were conducted to identify risk factors for ED. RESULTS: The database contains 230 mKTRs. In the ESRDp, 17.0% had normal erectile function, 53.5% had mild ED, 18.3% had moderate ED, and 11.3% had severe ED. In the EPTP, the distribution was 38.2% normal, 42.6% mild, 10.8% moderate, and 8.2% severe. In the pre-COVID-19 period, it was 34.3%, 47.3%, 10.4%, and 7.8%, and in the post-COVID-19 period, it was 23.0%, 45.6%, 21.3%, and 10.0%. Overall, erectile function improved after kidney transplant (KT). However, post-COVID-19, the proportion of erectile function significantly decreased compared to EPTP and pre-COVID-19 periods. Risk factors for post-pandemic ED included degree, Generalized Anxiexy Disorder-7, kidney donor type, postoperative time, hypertension and hemoglobin concentration. CONCLUSION: KT improves erectile function in mKTRs within 5 years, but post-SARS-CoV-2 viral infection, ED worsens due to altered risk factors. These findings inform future research for comprehensive ED prevention and management strategies in this population.

The association between shift work, shift work sleep disorders and premature ejaculation in male workers.

OBJECTIVE: Shift work and Shift Work Sleep Disorder (SWSD) are known to affect the secretion of several neurotransmitters and hormones associated with premature ejaculation (PE). However, their specific influence on the regulation of male ejaculation remains unclear. This study explores the relationship between shift work, SWSD, and PE. METHODS: From April to October 2023, a cross-sectional survey was conducted across five regions of China to explore the work schedules, sleep quality, and sexual function of male workers. Participants' sleep quality was evaluated using a validated SWSD questionnaire, and their erectile function and ejaculatory control were assessed with the International Inventory of Erectile Function (IIEF-5) scores and Premature Ejaculation Diagnostic Tool (PEDT) scores, respectively. Univariate and multivariate linear regression analyses were employed to identify risk factors associated with PE. Confounders were controlled using multiple regression models, and clinical prediction models were developed to predict PE onset and assess the contribution of risk factors. RESULTS: The study included 1239 eligible participants, comprising 840 non-shift workers and 399 shift workers (148 with SWSD and 251 without SWSD). Compared to non-shift working males, those involved in shift work (ß 1.58, 95% CI 0.75 - 2.42, p < 0.001) and those suffering from SWSD (ß 2.86, 95% CI 1.86 - 3.85, p < 0.001) they had significantly higher PEDT scores. Additionally, we identified daily sleep of less than six hours, depression, anxiety, diabetes, hyperlipidemia, frequent alcohol consumption (more than twice a week), and erectile dysfunction as risk factors for PE. The predictive model for PE demonstrated commendable efficacy. CONCLUSION: Both shift work and SWSD significantly increase the risk of premature ejaculation, with the risk magnifying in tandem with the duration of shift work. This study reveals the potential impact of shift work and SWSD on PE and provides new theoretical foundations for the risk assessment and prevention of this condition.

Anemia and testosterone deficiency risk: insights from NHANES data analysis and a Mendelian randomization analysis.

BACKGROUND: Previous research has shown that testosterone deficiency (TD) increases the risk of anemia, but it is unclear whether anemia affects testosterone levels. This study investigated the influence of anemia on testosterone levels. METHODS: Utilizing data from six NHANES cycles, including demographic, testosterone levels, and hemoglobin concentrations, we employed multivariable-adjusted logistic regression to investigate the relationship between anemia and testosterone levels. Moreover, a two-sample Mendelian randomization (MR) study employing genome-wide association study (GWAS) data examined the causal relationship. Kaplan-Meier survival estimation was used to compared the overall survival (OS) of anemic and nonanemic patients with low testosterone and normal testosterone levels. RESULTS: The inclusion of 21,786 participants (2318 with anemia and19,468 without anemia) revealed that nonanemic patients exhibited higher testosterone levels than did anemic patients (ß = 22.616, 95% CI: 3.873-41.359, p = 0.01807). MR analysis confirmed anemia as a cause of TD (OR = 1.045, 95% CI: 1.020-1.071, p < 0.001). Anemic males with low testosterone had reduced OS compared to those with normal levels (p < 0.001). CONCLUSIONS: Anemia emerged as a potential risk factor for TD, highlighting a bidirectional relationship between these conditions. Additional prospective investigations are essential for the validation and reinforcement of our findings.

Is There a Two-Way Risk between Decreased Testosterone Levels and the Progression and Prognosis of Chronic Kidney Disease? A Cohort Study Based on the National Health and Nutrition Examination Survey Database.

PURPOSE: The causal relationship between the incidence and prognosis of chronic kidney disease (CKD) and serum testosterone levels in patients is not yet fully understood. This study aims to use the National Health and Nutrition Examination Survey (NHANES), a large-scale nationally representative sample, to investigate the relationship between CKD and testosterone. MATERIALS AND METHODS: This study included six NHANES cycles for linear regression analysis, verified by multiple imputation methods. Stratified analysis and subgroup analysis were used to demonstrate the stability of CKD's effect on testosterone. Furthermore, we used Kaplan-Meier plots and log-rank tests to evaluate differences in survival rates between CKD male patients with low and normal levels of testosterone. RESULTS: From a total of 71,163 subjects, the cohort selected 28,663 eligible participants. Results showed that CKD patients had testosterone levels 28.423 ng/mL (24.762, 32.083) lower than non-CKD patients. The results of multiple imputations (ß=27.700, 95% confidence interval: 23.427, 31.974) were consistent with those of linear regression analysis, and the numerical match was good. Stratified regression analysis, and subgroup analysis results showed that CKD had a significant impact on testosterone at different dimensions. Kaplan-Meier plots showed significantly reduced survival rates in low testosterone CKD male patients (p<0.0001). CONCLUSIONS: The results of this big data analysis suggest that there may be a two-way risk between low levels of testosterone and CKD. The testosterone levels of CKD patients were significantly lower than those of the non-CKD population, and CKD patients with low testosterone levels had poorer prognoses. These results suggest that correcting testosterone levels in a timely manner can have preventive and therapeutic effects on the progression of CKD.

Ae index is an independent predictor of kidney stone recurrence in overweight and obese patients.

BACKGROUND: Finding some convenient and economical indicators to initially screen overweight and obese patients at high risk of kidney stone recurrence can help them prevent stone recurrence with lower medical cost. The purpose of this article is to determine the clinical value of Ae index (Apo B × 1000/eGFR) as an independent predictor for kidney stone recurrence in overweight and obese populations. METHODS: We queried the electronic medical records of patients with kidney stone operated at our hospital from March 2016 to March 2022, and selected BMI ≥ 25 kg/m2 as the study population and divided the patients into stone recurrence group and non-recurrence group. Relevant parameters of routine blood and biochemical test, glycated serum protein (GSP), and history of hypertension and hyperglycemia were collected. Then the Chi-square test, independent samples t-test or Wilcoxon rank-sum test were used to calculate the differences between the two groups of data. Next, we performed univariate and multivariate logistic regression analysis to screen out the most significant variables Apo B and eGFR, and then we calculated the Ae index using the formula Apo B × 1000/eGFR, and analyzed the relationship between Ae index and kidney stone recurrence. RESULTS: Univariate analysis found that Apo B (OR:8.376,95%CI:3.093-22.680), Creatinine (OR:1.012,95%CI:1.003-1.021), Cystatin C(OR:2.747,95%CI:1.369-5.508), LDL-C (OR:1.588,95%CI:1.182-2.134), TC (OR:1.543,95%CI:1.198-1.988) were positively associated, eGFR (OR:0.980,95%CI:0.970-0.991) was negatively associated with kidney stone recurrence. And multivariate logistic regression analysis suggested that Apo B (OR:11.028, 95%CI:3.917-31.047) and eGFR (OR:0.976, 95%CI:0.965-0.988) were the most significant factors. Then we calculated Ae index and analyzed it, the sensitivity was 74.26% and the specificity was 60.00%, higher than either individual variable. Its smoothed curve revealed a non-linear relationship between them with the inflection point of 9.16. And the OR on the left side of the inflection point was 1.574 (95% CI: 1.228-2.018), whereas the OR on the right side of the inflection point was 1.088 (95% CI: 1.007-1.177). CONCLUSIONS: Ae index is an easily calculated and obtained index that has some predictive value for kidney stone recurrence in overweight and obese patients, which is of interest.

A Novel Cuprotosis-Related Gene FDX1 Signature for Overall Survival Prediction in Clear Cell Renal Cell Carcinoma Patients.

Background: Ferredoxin 1 (FDX1) is a newly discovered gene regulating cuprotosis. However, the effect of FDX1 expression on clear renal cell carcinoma (ccRCC) is unknown. Methods: Gene expression profiles and clinical data of ccRCC patients were downloaded from the Cancer Genome Atlas (TCGA) database. The differences in FDX1 expression between ccRCC and nonneoplastic tissues adjacent to cancer were analyzed by R software. The results were validated by GEO data, quantitative real-time polymerase chain reaction (qRT-PCR), western blotting (WB), and immunohistochemistry (IHC). Chi-square test was used to analyze the clinical pathological parameters. Kaplan-Meier survival analysis and Cox proportional hazard regression model selection were used to evaluate the effect of FDX1 expression on overall survival. Protein interaction networks were used to analyze other proteins that interact with FDX1. Signal pathway analysis was performed for possible FDX1 enrichment using GSEA and ssGSEA algorithms. Pan-cancer analysis of FDX1 was carried out through TCGA database. Results: The FDX1 expression in nontumor tissues was significantly higher than that in ccRCC, and the expression difference was verified by GEO data, qRT-PCR, WB, and IHC. The high expression of FDX1 was significantly related to the well overall survival rate (P < 0.05). The chi-square test showed that the high expression of FDX1 was related to gender, TNM stage, T stage, lymph node metastasis, and pathological grade. Additionally, the FDX1 expression level was different in groups classified based on pathological grade, gender, TNM stage, T stage, lymph node metastasis, and distant metastasis (P < 0.05). The multivariate analysis revealed the high expression of FDX1 as an important independent predictor for overall survival. STRING database results showed that LIAS and LIPT1 may interact with FDX1 in the PPI network, which are also involved in the regulation of cuprotosis. The GSEA and ssGSEA results showed that the FDX1 was enriched in the anticancer pathway. The FDX1 high expression is associated with better prognosis in many cancers, as revealed by pan-cancer analysis. Conclusion: FDX1 may play a role in the progression of ccRCC as a tumor suppressor gene. It can be used as a potential prognostic indicator and therapeutic target of ccRCC. However, the cuprotosis regulatory role in the development of ccRCC needs to be further verified.

A Statistical Prediction Model for Survival After Kidney Transplantation from Deceased Donors.

BACKGROUND In an environment of limited kidney donation resources, patient recovery and survival after kidney transplantation (KT) are highly important. We used pre-operative data of kidney recipients to build a statistical model for predicting survivability after kidney transplantation. MATERIAL AND METHODS A dataset was constructed from a pool of patients who received a first KT in our hospital. For allogeneic transplantation, all donated kidneys were collected from deceased donors. Logistic regression analysis was used to change continuous variables into dichotomous ones through the creation of appropriate cut-off values. A regression model based on the least absolute shrinkage and selection operator (LASSO) algorithm was used for dimensionality reduction, feature selection, and survivability prediction. We used receiver operating characteristic (ROC) analysis, calibration, and decision curve analysis (DCA) to evaluate the performance and clinical impact of the proposed model. Finally, a 10-fold cross-validation scheme was implemented to verify the model robustness. RESULTS We identified 22 potential variables from which 30 features were selected as survivability predictors. The model established based on the LASSO regression algorithm had shown discrimination with an area under curve (AUC) value of 0.690 (95% confidence interval: 0.557-0.823) and good calibration result. DCA demonstrated clinical applicability of the prognostic model when the intervention progressed to the possibility threshold of 2%. An average AUC value of 0.691 was obtained on the validation data. CONCLUSIONS Our results suggest that the proposed model can predict the mortality risk for patients after kidney transplants and could help kidney specialists choose kidney recipients with better prognosis.

Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor.

BACKGROUND: Delayed graft function (DGF) is a major complication of kidney transplantation (KT), especially in patients receiving donor of decease (DD) KT. Therefore, the kidney donor pool is rare worldwide, it is critical to evaluate the risk coefficient of DGF using preoperative data of donors and recipients and provide a reference for clinical decision-making and resource allocation. METHOD AND ANALYSIS: A total of 238 DD recipients were performed in our center. Finally, 211 patients were included. The clinical database was divided into 34 clinical blood indicators (CBIs) and 6 demographics indexes (DIs). CBIs and DIs were screened for variables with P<0.05 and demonstrated the best cut-off value using multivariable logistics regression. The selected CBIs were passed through the least absolute shrinkage and selection operator (LASSO) to obtain the predictive factors and synthesized into a Riskscore, forming a nomogram with the selected DIs. We used receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) to verify the discrimination and clinical effects of this nomogram. Finally, 10-fold cross-validation was conducted internally to show the effect of the model. RESULTS: The 34 CBIs of the database finally screened out 12 predictors, which were synthesized into Riskscore. The 6 DIs selected 3 variables. Riskscore and 3 DIswere constructed into a nomogram, and the ROC of the nomogram has an AUC value of 0.725. Calibration and DCA showed excellent verification effects on the nomogram. The 10-fold crossover internal validation also demonstrated the model's excellent discrepancy. CONCLUSION: The nomogram has an excellent ability to predict DGF and provides an essential reference for decision-making and resource allocation in a clinical setting.

Analysis of Risk Factors for Carbapenem-Resistant Klebsiella pneumoniae Infection and Its Effect on the Outcome of Early Infection After Kidney Transplantation.

Background: Infections remain a major cause of morbidity and mortality in kidney transplant (KT) recipients. This study was performed to identify the overall prevalence of early infections, prevalence of carbapenem-resistant Klebsiella pneumoniae (CRKP) infection after KT, one-year postoperative mortality in patients with early infections and risk factors for CRKP infections. Methods: We conducted a retrospective study of all patients who received KT in our hospital between January 2017 and December 2019. We evaluated the demographic, clinical, infection characteristics and the one-year postoperative outcomes. Results: Among the 419 patients who received KT between January 2017 and December 2019, 150 patients had at least one infection within 90 days after KT. The total prevalence of early infections was 36.1% (150/415), the prevalence of early CRKP infections was 10.4% (43/415), and the one-year postoperative mortality was 15.3% (23/150) in patients with early infections. The risk factors independently related to one-year postoperative mortality were mechanical ventilation (MV) > 48 h (Odds ratio (OR)= 13.879, 95%Confidence interval (CI): 2.265~85.035; P=0.004) and CRKP infection (OR=6.751, 95% CI: 1.051~43.369; P =0.044). MV> 48 h was independently related to CRKP infection (OR=3.719, 95% CI: 1.024~13.504; P=0.046). Kaplan-Meier survival curves showed that the one-year survival rate of patients infected with CRKP in the early postoperative stage was significantly lower than that of uninfected patients. Conclusions: In general, the prevalence of early infections after KT is high, and CRKP infection is closely correlated with poor prognosis. The effective prevention and treatment of CRKP infection is an important way to improve the one-year survival rate after KT.

Kidney transplantation improve semen quality in patients with dialysis: A systematic review and meta-analysis.

Kidney transplantation has been considered as the most effective therapy for patients with end-stage renal disease. However, less attention was attached to infertility. The present meta-analysis was conducted to compare the semen quality between patients with dialysis and patients after kidney transplantation. An extensive search in MEDLINE, PubMed and Web of Science was conducted from inception to March 2021. The data extracted for meta-analysis included sample size and characteristics, main reported outcomes like semen quality and hormone levels. For the semen quality and hormone levels, the standardized mean difference (SMD) and 95% confidential interval (CI) were calculated to evaluate the effect size. Finally, 5 studies were included in meta-analysis. Kidney transplantation could improve the sperm density of patients undergoing dialysis (SMD 1.58 [0.02, 3.15]). Additionally, the sperm motility was also improved after the kidney transplantation (SMD 3.26 [0.73, 5.79]). The sperm density of kidney transplantation patients was lower than that in healthy subjects (SMD -0.75 [-1.42, -0.07]), same as the sperm motility (SMD -0.50 [-0.80, -0.20]). Our meta-analysis suggests kidney transplantation could improve semen quality of patients with ESRD, including sperm density and sperm motility. Of note, semen quality of renal transplantation recipient still is inferior to healthy subjects.