Association between Serum Triglycerides and Prostate Specific Antigen (PSA) among U.S. Males: National Health and Nutrition Examination Survey (NHANES), 2003-2010

Association between vitamin B2 intake and prostate-specific antigen in American men: 2003-2010 National Health and Nutrition Examination Survey

BACKGROUND

Accumulating evidence suggests a pivotal role of vitamin B2 in the pathogenesis and progression of prostate cancer (PCa). Vitamin B2 intake has been postulated to modulate the screening rate for PCa by altering the concentration of prostate-specific antigen(PSA). However, the relationship between vitamin B2 and PSA remains indeterminate. Hence, we conducted a comprehensive evaluation of the association between vitamin B2 intake and PSA levels, utilizing data from the National Health and Nutrition Examination Survey (NHANES) database.

METHODS

From a pool of 20,371 participants in the NHANES survey conducted between 2003 and 2010, a cohort of 2,323 participants was selected for the present study. The male participants were classified into four distinct groups based on their levels of vitamin B2 intake. We employed a multiple linear regression model and a non-parametric regression method to investigate the relationship between vitamin B2 and PSA levels.

RESULTS

The study cohort comprised of 2,323 participants with a mean age of 54.95 years (± 11.73). Our findings revealed a statistically significant inverse correlation between vitamin B2 intake (mg) and PSA levels, with a reduction of 0.13 ng/ml PSA concentration for every unit increase in vitamin B2 intake. Furthermore, we employed a fully adjusted model to construct a smooth curve to explore the possible linear relationship between vitamin B2 intake and PSA concentration.

CONCLUSIONS

Our study in American men has unveiled a notable inverse association between vitamin B2 intake and PSA levels, potentially posing a challenge for the identification of asymptomatic prostate cancer. Specifically, our findings suggest that individuals with higher vitamin B2 intake may be at a greater risk of being diagnosed with advanced prostate cancer in the future, possibly indicating a detection bias. These results may offer a novel explanation for the observed positive correlation between vitamin B2 intake and prostate cancer.

Association between platelet‑to‑lymphocyte ratio and serum prostate specific antigen

There is evidence that the systemic inflammatory response may have an impact on prostate-specific antigen (PSA) levels. However, the relationship between the platelet-to-lymphocyte ratio (PLR) and PSA remains unclear. As a result, the relationship between PLR and PSA using the National Health and Nutrition Examination Survey (NHANES) database was examined. After the screening, 6,638 participants out of 52,186 in the NHANES survey conducted between 2001 to 2010 were suitable for the present study. The PLR was the independent variable in the present study, and PSA was the dependent variable. The selected subjects in the present study had an average age of 58.563±11.848 years. After controlling for covariates, the results showed that with every increase in PLR, the PSA concentration increased by 0.004 ng/ml (0.001, 0.007). This difference was statistically significant. Furthermore, a smoothing curve based on a fully adjusted model was created to investigate the possibility of a linear relationship between PLR and PSA concentration in men from USA. In men from USA, an independent and positive correlation between PLR and PSA was identified, which could potentially result in overdiagnosis of asymptomatic prostate cancer in populations with higher PLR levels.

Association of TyG index with prostate-specific antigen (PSA) in American men: results from NHANES, 2003-2010

BACKGROUND

In recent years, triglyceride-glucose index (TyG) was a new indicator of insulin resistance, and it has been widely reported that it may be associated with serum prostate-specific antigen (PSA) concentrations.

AIMS

We intended to investigate the possible connection between serum PSA concentration and the TyG index.

METHODS

This is a cross-sectional study of adults with complete data on TyG and serum PSA concentrations (ng/ml) from the NHANES, 2003-2010. The TyG index is obtained by the formula below: TyG = Ln [triglycerides (mg/dL) × fasting glucose(mg/dL)/2]. Multivariate regression analysis and subgroup analysis were used to examine the connection between the TyG index and serum PSA levels.

RESULTS

Multiple regression analysis of the weighted linear model showed that individuals with a higher TyG index had lower PSA levels. Subgroup analyses and interaction tests showed no apparent dependence on age, race/ethnicity, BMI, household income ratio, education level, and marital status on this negative association (all interactions p > 0.05).

CONCLUSIONS

TyG index is related to lower serum PSA concentrations in adult men from the USA. Further comprehensive prospective studies are needed to confirm our findings.

Machine learning algorithms identify hypokalaemia risk in people with hypertension in the United States National Health and Nutrition Examination Survey 1999-2018

BACKGROUND

Hypokalaemia is a side-effect of diuretics. We aimed to use machine learning to identify features predicting hypokalaemia risk in hypertensive patients.

METHODS

Participants with hypertension in the United States National Health and Nutrition Examination Survey 1999-2018 were included for analysis. To select the most suitable algorithm, we tested and evaluated five machine learning algorithms commonly employed in epidemiological studies: Logistic Regression, k-Nearest Neighbor, Random Forest, Recursive Partitioning and Regression Trees, and eXtreme Gradient Boosting. These algorithms were accessed using a set of 38 screened features. We then selected the key hypokalaemia-associated features in the hypertension group and their cardiovascular diseases (CVD) subgroup using the SHapley Additive exPlanations (SHAP) values. Using SHAP values, the key features and their impact pattern on hypokalaemia risk were determined.

RESULTS

A total of 25,326 hypertensive participants were included for analysis, of whom 4,511 had known CVD. The Random Forest algorithm had the highest AUROC (hypertension dataset: 0.73 [95%CI, 0.71-0.76]; CVD subgroup: 0.72 [95%CI, 0.66-0.78]). Moreover, the nomogram based on the top twelve key features screened by random forest retained good performance: age, sex, race, poverty income ratio, body mass index, systolic and diastolic blood pressure, non-potassium-sparing diuretics use and duration, renin-angiotensin blockers use and duration, and CVD history in hypertension dataset; while in CVD subgroup, the additional key features were comorbid diabetes, education level, smoking status, and use of bronchodilators.

CONCLUSION

Our predictive model based on the random forest algorithm performed best among the tested and evaluated five algorithms. Hypokalaemia-associated key features have been identified in hypertensive patients and the subgroup with CVD. These findings from machine learning facilitate the development of artificial intelligence to highlight hypokalaemia risk in hypertension patients.

Comprehensive analysis between volatile organic compound (VOC) exposure and female sex hormones: a cross-sectional study from NHANES 2013-2016

There is growing evidence suggesting that exposure to volatile organic compounds (VOCs) can pose significant health risks, including interference with the function of the reproductive system. However, there has been a lack of research focused on the impact of common environmental VOCs on the levels of sex hormones in the general female population. In this study, we conducted a cross-sectional analysis utilizing the database of the National Health and Nutrition Examination Survey (NHANES, 2013-2016). A total of 2633 participants were included in this study. The Pearson correlation model revealed the potential of co-exposure or co-toxicity between benzene and 2,5-dimethylfuran. According to GLM models, we discovered a significant positive association between blood levels of 2,5-dimethylfuran and benzene with testosterone levels in women. Subgroup analysis further identified that the women with underweight and healthy weight might be the high-risk subgroup. Bayesian kernel machine regression (BKMR) was applied to further assess the univariate and bivariate exposure-response relationships between multiple VOCs. Our research systemically formulated the possible relationship between exposure to VOCs and female sex hormones, indicating the role of VOCs as a risk factor for endocrine disruption, especially benzene and 2,5-dimethylfuran. These findings have important implications for public health and call for further investigation.

Association between body mass index and hemoglobin A1c with serum prostate-specific antigen level: A retrospective cohort study

OBJECTIVES

To assess the association between body mass index (BMI) and hemoglobin A1c (HbA1c) with serum prostate-specific antigen (PSA) level.

METHODS

A retrospective cohort study was carried out at King Faisal Specialist Hospital and Research Centre in Riyadh, Saudi Arabia, from January 2016 to December 2021. Data were collected from the medical records of patients who visited the family medicine clinics, including demographics, smoking status, BMI value, index PSA level, testosterone level, digital rectal exam findings, prostate biopsy status, fasting blood glucose (FBG), HbA1c, diabetes duration, chronic comorbidities (namely, hypertension, dyslipidemia, or chronic kidney disease), and medication history.

RESULTS

The mean PSA level was 1.89±4.02 ng/dL and mean HbA1c was 6.59±2.69%. Of the participants, 41.8% were overweight, 54.3% were non-diabetics, and 85.3% were nonsmokers. Only 11 (1.6%) participants had undergone a prostate biopsy after taking a PSA test. There was a positive correlation between PSA level and age, a negative correlation between PSA level and BMI, and no correlation between PSA level and HbA1c or FBG.

CONCLUSION

Prostate-specific antigen levels were higher in older people and those with low BMIs. No correlations were found between PSA levels and HbA1c or FBG, even after adjusting for other variables. Moreover, no correlations were found between PSA levels and other comorbidities such as dyslipidemia, chronic kidney disease, and hypertension.

The association between dietary selenium intake and Hashimoto's thyroiditis among US adults: National Health and Nutrition Examination Survey (NHANES), 2007-2012

BACKGROUND

Selenium has been shown to influence the pathological processes and physiological functions of thyroid. Although growing evidence has shown that selenium can improve the treatment of Hashimoto's thyroiditis (HT), there is a need to evaluate the association between dietary selenium intake and HT in a large cross-sectional study. This study explored the association between dietary selenium intake and HT based on the National Health reand Nutrition Examination Survey (NHANES) database (2007-2012).

METHODS

A total of 8756 of 30,442 participants were included in the study. Dietary selenium intake was the independent variable, while HT was the dependent variable. In addition, the relative importance of the selected variables was determined using the XGBoost model. A smooth curve was constructed based on the fully adjusted model to investigate the potential linear relationship between dietary selenium intake and HT. Smooth curves were also constructed to explore the linear/non-linear relationship between dietary selenium intake and thyroid peroxidase antibody (TPOAb)/ thyroglobulin antibody (TgAb).

RESULTS

The mean age of the enrolled participants was 44.35 years (± 20.92). The risk of HT was significantly reduced by a 35% per-unit increase in dietary selenium intake after fully adjusting for covariates according to the model (log2-transformed data; OR 0.65; 95% CI 0.51, 0.83). The XGBoost model revealed that dietary selenium intake was the most important variable associated with Hashimoto's thyroiditis. Dietary selenium intake (Log2-transformed) was negatively correlated with TPOAb levels [- 16.42 (- 22.18, - 10.65), P < 0.0001], while a non-linear relationship was observed between dietary selenium intake and TgAb with an inflection point of 6.58 (95.67 μg, Log2-transformed).

CONCLUSION

Dietary selenium intake is independently and inversely associated with HT risk. Moreover, dietary selenium intake is negatively correlated with TPOAb levels and non-linearly correlated with TGAb levels. Therefore, dietary selenium intake may be a safe and low-cost alternative for the prevention and treatment of HT.

Prostate-Specific Antigen Monitoring Using Nano Zinc(II) Metal-Organic Framework-Based Optical Biosensor

BACKGROUND

The prostate-specific antigen (PSA) is an important cancer biomarker that is commonly utilized in the diagnosis of prostate cancer. The development of a PSA determination technique that is rapid, simple, and inexpensive, in addition to highly accurate, sensitive, and selective, remains a formidable obstacle.

METHODS

In this study, we developed a practical biosensor based on Zn(II) metal-organic framework nanoparticles (Zn-MOFs-NPs). Many spectroscopic and microanalytical tools are used to determine the structure, morphology, and physicochemical properties of the prepared MOF.

RESULTS

According to the results, Zn-MOFs-NPs are sensitive to PSA, selective to an extremely greater extent, and stable in terms of chemical composition. Furthermore, the Zn-MOFs-NPs did not exhibit any interferences from other common analytes that might cause interference. The detection limit for PSA was calculated and was 0.145 fg/mL throughout a wide linear concentration range (0.1 fg/mL-20 pg/mL).

CONCLUSIONS

Zn-MOFs-NPs were successfully used as a growing biosensor for the monitoring and measurement of PSA in biological real samples.

Assessing volatile organic compounds exposure and prostate-specific antigen: National Health and Nutrition Examination Survey, 2001–2010

Background

Volatile organic compounds (VOCs) are a large group of chemicals widely used in people's daily routines. Increasing evidence revealed the VOCs' accumulating toxicity. However, the VOCs toxicity in male prostate has not been reported previously. Thus, we comprehensively evaluated the association between VOCs and prostate-specific antigen (PSA).

Methods

A total of 2016 subjects were included in our study from the National Health and Nutrition Examination Survey with VOCs, PSA, and other variables among U.S. average population. We constructed XGBoost Algorithm Model, Regression Model, and Generalized linear Model (GAM) to analyze the potential association. Stratified analysis was used to identify high-risk populations.

Results

XGBoost Algorithm model identified blood chloroform as the most critical variable in the PSA concentration. Regression analysis suggested that blood chloroform was a positive association with PSA, which showed that environmental chloroform exposure is an independent risk factor that may cause prostate gland changes [β, (95% CI), P = 0.007, (0.003, 0.011), 0.00019]. GAM observed the linear relationship between blood chloroform and PSA concentration. Meanwhile, blood chloroform linear correlated with water chloroform in the lower dose range, indicating that the absorption of water may be the primary origin of chloroform. Stratified associations analysis identified the high-risk group on the chloroform exposures.

Conclusion

This study revealed that blood chloroform was positively and independently associated with total PSA level, suggesting that long-term environmental chloroform exposure may cause changes in the prostate gland.

Multiple statistical models reveal specific volatile organic compounds affect sex hormones in American adult male: NHANES 2013-2016

BACKGROUND

Some VOCs are identified as endocrine-disrupting chemicals (EDCs), interfering with the effect of sex hormones. However, no studies focused on the common spectrum of environmental VOCs exposure affecting sex hormones in the average male population.

OBJECTIVES

We aimed to explore the association between VOCs and sex hormones in American adult males using multiple statistical models.

METHODS

The generalized linear (GLM), eXtreme Gradient Boosting (XGBoost), weighted quantile sum (WQS), Bayesian kernel machine regression (BKMR) and stratified models were used to evaluate the associations between Specific Volatile Organic Compounds and sex hormones in American adult male from NHANES 2013-2016.

RESULTS

Pearson correlation model revealed the potential co-exposure pattern among VOCs. XGBoost algorithm models and the WQS model suggested the relative importance of VOCs. BKMR models reveal that co-exposure to the VOCs was associated with increased Testosterone (TT), Estradiol (E₂), SHBG and decreased TT/E₂. GLM models revealed specific VOC exposure as an independent risk factor causing male sex hormones disorders. Stratified analysis identified the high-risk group on the VOCs exposures. We found Blood 2,5-Dimethylfuran in VOCs was the most significant effect on sex hormones in male. Testosterone increased by 213.594 (ng/dL) (124.552, 302.636) and estradiol increased by 7.229 (pg/mL) for each additional unit of blood 2,5-Dimethylfuran (ng/mL).

CONCLUSION

This study is an academic illustration of the association between VOCs exposure and sex hormones, suggesting that exposure to VOCs might be associated with sex hormone metabolic disorder in American adult males.