Frontiers in Endocrinology最新文献

{"title":"Immune checkpoint inhibitor-associated diabetes mellitus: the case series report.","authors":"Yuhong Ma, Jing Xue, Qianwen Cheng, Hesheng Qian, Yingying Du","doi":"10.3389/fendo.2025.1589630","DOIUrl":"10.3389/fendo.2025.1589630","url":null,"abstract":"<p><p>This report aims to better define the rare adverse event of immune checkpoint inhibitor-associated diabetes mellitus(ICI-DM). We present 10 cases of patients including six of the patients had no prior history of diabetes, while four had varying degrees of pre-existing diabetes. Eight who received anti-PD-1 combination therapy, one who received anti-PD-1 monotherapy, and one who received dual anti-PD-1/CTLA-4 therapy. The mean time from initiation of immunotherapy to the onset of ICI-DM was 245.4 days (median, 149 days; range, 11 to 787 days). Diabetic ketoacidosis (DKA) occurred in 60% (6/10) of the patients, with a median fasting blood glucose level of 25.85 mmol/L (range, 14.76 to 38.23 mmol/L), and all had C-peptide levels below the normal range. Through a retrospective analysis of the clinical data of these 10 patients, we found that monitoring fasting blood glucose and HbA1c is crucial for patients undergoing or having undergone immunotherapy, as rapid pancreatic β-cell destruction can be observed in those who develop ICI-DM, potentially due to disruption of the PD-1/PD-L1 pathway.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1589630"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270864/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GLP-1 and GIP may play a role in long-term weight trajectories after gastric bypass.","authors":"Sara Andrade, Carolina B Lobato, Mariana Machado, Bolette Hartmann, Jens J Holst, Rui F Almeida, Mário Nora, Mariana P Monteiro, Marta Guimarães, Sofia S Pereira","doi":"10.3389/fendo.2025.1624001","DOIUrl":"10.3389/fendo.2025.1624001","url":null,"abstract":"<p><strong>Introduction: </strong>Suboptimal clinical responses to metabolic and bariatric surgery include insufficient weight loss (WL), weight regain (WR), and/or comorbidity remission failure or relapse. Gut hormones' role in WR and Type 2 diabetes (T2D) relapse is not fully established. So, our aim was to evaluate the hormone profiles of patients with long-term optimal and suboptimal response after gastric bypass (RYGB).</p><p><strong>Methods: </strong>This cross-sectional study included 43 individuals who underwent RYGB surgery over 10 years ago, divided into two groups: 23 participants with no T2D history but different WR trajectories (cohort 1), and 20 with prior T2D diagnosis and optimal WL (cohort 2), with post-RYGB T2D remission (n=10) or relapse (n=10).</p><p><strong>Results: </strong>Fasting and postprandial glucose, insulin, C-peptide, glucagon, GLP-1 and GIP levels were evaluated during a mixed-meal tolerance test. In cohort 1, fasting glucose, insulin, C-peptide, and glucagon, as well as the postprandial glucose and GIP levels, were significantly positively correlated with %WR. Additionally, postprandial GLP-1 and glucagon levels were negatively correlated with the %WR. In cohort 2, higher postprandial glucose and lower insulin were observed in participants with T2D relapse. No other significant differences were observed.</p><p><strong>Discussion: </strong>In sum, greater WR was associated with higher levels of postprandial glucose and GIP, along with lower GLP-1 and glucagon excursions. Whether these are cause or consequence of WR remains to be clarified. Additionally, GIP and GLP-1 profile of participants with T2D relapse did not differ from those with T2D remission.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1624001"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12271881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statin utilization and its predictors for the primary prevention of cardiovascular disease among type 2 diabetic patients in a resource-limited setting.","authors":"Feyisa Assefa Dhaba, Wubshet Abraham Alemu, Firaol Lamessa Kitila, Koricho Simie Tolla, Astarekew Alene, Zeru Seyoum Wendimagegn, Kedir Ali Getahun, Hassen Ahmed Yesuf, Surafel Mekasha Woldeyes","doi":"10.3389/fendo.2025.1472300","DOIUrl":"10.3389/fendo.2025.1472300","url":null,"abstract":"<p><strong>Background: </strong>Cardiovascular disease (CVD) is a major cause of mortality in patients with type 2 diabetes mellitus (T2DM). Statins are essential for the primary prevention of CVD in this high-risk group. Despite guideline recommendations, statin use remains suboptimal in clinical practice. Assessing statin utilization and identifying factors influencing their prescription are vital for enhancing evidence-based care, especially in resource-limited settings. Therefore, this study aimed to evaluate statin use and its predictors for primary CVD prevention among diabetic patients at Arsi Teaching and Referral Hospital in 2023.</p><p><strong>Methods: </strong>A hospital-based cross-sectional study was carried out among 351 diabetic patients at Arsi Teaching and Referral Hospital (ARTH) between February and September 2022. Participants were selected using a systematic random sampling method. Data were collected through a pretested, interviewer-administered structured questionnaire and a checklist. Trained nurses from the diabetic clinic conducted data collection. The collected data were initially entered into Epi Data version 7.2, then exported to SPSS version 26 (IBM, USA) for analysis. The association between statin use and potential predictors was examined using odds ratios (ORs) with 95% confidence intervals (CIs). Variables with a p-value below 0.05 in the multivariable logistic regression were considered statistically significant.</p><p><strong>Results: </strong>The prevalence of statin utilization for the primary prevention of CVD among type 2 diabetic patients on follow-up at Asella Teaching Hospital was 189 [(53.8%, 95% CI: 48.6%, 59.0%)]. The most commonly prescribed statin was atorvastatin, followed by simvastatin. The probability of statin use was greater in participants with hypertension [AOR=4.8, 95% CI (2.0-11.5)], dyslipidemia [AOR=10.5, 95% CI (2.0-11.5)], and uncontrolled glycemic control [AOR=8.0,95% CI (3.8-17.7)].</p><p><strong>Conclusions: </strong>Suboptimal statin utilization (53.8%) for primary CVD prevention in type 2 diabetes was observed, with utilization heavily influenced by comorbidities. Urgent quality improvement initiatives are needed to ensure statin access aligns with guideline recommendations for patients with hypertension, dyslipidemia, and poor glycemic control in the study area.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1472300"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeting the brain-gut-prostate axis in chronic prostatitis: mechanisms and therapeutics.","authors":"Shiwei Song, Chunlei Zhang, Bin Zhang, Jinlong Yin, Chang Yu, Xuanrong Wang, Qing Wang, Fulin Ma, Changfeng Yang, Dehui Chang","doi":"10.3389/fendo.2025.1628094","DOIUrl":"10.3389/fendo.2025.1628094","url":null,"abstract":"<p><p>Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS), a refractory urinary system disorder, is closely associated with dysregulation of the brain-gut-prostate axis. Emerging evidence highlights the pivotal role of gut microbiota dysbiosis and its bidirectional interactions with the neuroimmune system in CP/CPPS pathogenesis. This systematic review integrates perspectives from microbiomics, neuroimmunology, and metabolomics to propose a theoretical framework of the brain-gut-prostate axis and multi-dimensional therapeutic strategies targeting this axis. By transcending conventional localized anti-inflammatory approaches, these strategies aim to address clinical resistance and phenotypic heterogeneity. Mechanistic insights into microbiota-derived metabolites (e.g., short-chain fatty acids, SCFAs), neuroendocrine signaling (e.g., thyrotropin-releasing hormone, TRH), and immune crosstalk (e.g., Th17/Treg imbalance) are explored, alongside innovative therapies such as microbiome modulation, neural interventions, and immune regulation. This holistic paradigm not only provides new mechanistic insights but also offers promising avenues for personalized management and translational research in CP/CPPS, potentially overcoming current therapeutic bottlenecks.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1628094"},"PeriodicalIF":4.6,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270845/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of personalized continuous care in wound care of patients with diabetic foot ulcers.","authors":"Yan Mi, Jing Wang","doi":"10.3389/fendo.2025.1612047","DOIUrl":"10.3389/fendo.2025.1612047","url":null,"abstract":"<p><strong>Background: </strong>Diabetic foot ulcers (DFUs), a common complication of diabetes, are often accompanied by delayed wound healing, pain, psychological distress, and sleep disturbances.</p><p><strong>Objective: </strong>To evaluate the effectiveness of personalized continuous care (PCC) compared to routine care in improving wound healing, symptom severity, and psychological/sleep outcomes in DFU patients.</p><p><strong>Methods: </strong>A retrospective cohort study of 60 DFU patients (2021-2024) compared PCC (n=30) with routine care (n=30). Outcomes assessed included wound area reduction, granulation tissue coverage, symptom scores (ulceration, necrosis, pain), and validated psychological (SDS, SAS) and sleep (AIS) scales.</p><p><strong>Results: </strong>The PCC group showed superior wound healing (40.51% <i>vs</i>. 27.43% area reduction; 61.66% <i>vs</i>. 46.32% granulation coverage, p<0.05), lower symptom scores (ulceration: 3.18 ± 0.45 <i>vs</i>. 4.46 ± 0.6; pain: 2.01 ± 0.29 <i>vs</i>. 3.45 ± 0.58, p<0.01), and improved psychological (SDS: 32.1 ± 3.88 <i>vs</i>. 44.87 ± 4.05; SAS: 30.36 ± 3.77 <i>vs</i>. 43.25 ± 4.56, p<0.001) and sleep outcomes (AIS: 8.23 ± 0.6 <i>vs</i>. 11.33 ± 0.94, p<0.001).</p><p><strong>Conclusion: </strong>PCC enhances DFU wound healing, alleviates symptoms, and improves psychological well-being and sleep quality, supporting its integration routine clinical practice.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1612047"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Logistic regression analysis of pregnancy outcome and EFI score of infertile patients with ovarian endometriosis cyst after staged oral administration of traditional Chinese medicine.","authors":"Yali Bo, Shaochan Peng, Jiawen Su, Dunmin Ye","doi":"10.3389/fendo.2025.1624925","DOIUrl":"10.3389/fendo.2025.1624925","url":null,"abstract":"<p><strong>Background: </strong>Ovarian endometriosis cysts are associated with infertility, and recent research increasingly focuses on improving pregnancy outcomes. Traditional Chinese medicine (TCM) has long been used for gynecological issues, yet the impact of staged TCM administration on pregnancy outcomes and Endometriosis Fertility Index (EFI) scores in infertile patients remains underexplored.</p><p><strong>Objective: </strong>This study aims to evaluate the effects of staged TCM administration on pregnancy outcomes and EFI scores in patients with ovarian endometriosis cysts.</p><p><strong>Method: </strong>A retrospective analysis of 150 infertile patients treated with staged TCM administration was conducted. Patients received Formula I before ovulation and Formula II post-ovulation, with the cohort split into pregnancy (n=91) and non-pregnancy groups (n=49). All patients underwent laparoscopic surgery prior to TCM treatment. Logistic regression and ROC analysis were used to assess pregnancy predictors.</p><p><strong>Results: </strong>Significant differences in age, infertility type, infertility duration, r-AFS stage, cyst diameter, and EFI score (P<0.05) were found. Age, secondary infertility, infertility duration (≥3 years), advanced r-AFS stage, cyst diameter (≥3cm), and EFI score (<7) were key risk factors. The EFI score's AUC for predicting pregnancy was 0.731 (95%CI, 0.617-0.844), with 72.58% sensitivity and 75.83% specificity. No significant difference in follow-up duration was observed between the groups.</p><p><strong>Conclusion: </strong>Age, secondary infertility, infertility duration (≥ 3 years), r-AFS stage (stages III and IV), cyst diameter (≥ 3cm), and EFI score (< 7) were identified as risk factors for infertility in patients with ovarian endometriosis following a two-phase staged oral administration of traditional Chinese medicine. Among these factors, the EFI score can serve as a crucial evaluation index for postoperative pregnancy, assessing the likelihood of pregnancy and predicting patient prognosis.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1624925"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270884/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective analysis of metabolic syndrome and inflammation in aortic aneurysm risk: UK Biobank study.","authors":"Xinyi Liu, Hao Liu, Suwei Chen, Chen Gong, Yipeng Ge, Zhiyu Qiao, Chengnan Li, Junming Zhu","doi":"10.3389/fendo.2025.1612975","DOIUrl":"10.3389/fendo.2025.1612975","url":null,"abstract":"<p><strong>Context/objectives: </strong>Metabolic syndrome (MetS) is associated with various diseases, yet its connection with aortic aneurysm (AA) is not well understood. The role of chronic inflammation as a mediator in this relationship also remains unclear. This study explores the combined effects of MetS and inflammation on AA risk.</p><p><strong>Methods: </strong>Data from 312,505 UK Biobank participants were analyzed to assess the relationship between MetS and AA. Cox proportional hazards regression models evaluated the association, while restricted cubic splines, mediation analyses, interaction assessments, and joint analyses explored the impact of inflammatory indicators, including the low-grade chronic inflammation (INFLA) score.</p><p><strong>Results: </strong>Over a mean follow-up of 14.6 years, 2,382 participants developed AA. MetS was associated with a higher AA risk (HR: 1.27; 95% CI: 1.16-1.39) in fully adjusted models. Each additional MetS component increased AA risk by 16%. Inflammatory markers, including the INFLA score, significantly mediated this relationship. Joint analyses revealed a stronger association in MetS patients with high INFLA scores (HR: 1.68; 95% CI: 1.45-1.95).</p><p><strong>Conclusion: </strong>MetS and its components notably elevate AA risk, with inflammation playing a key mediating role. These findings underscore the importance of targeted prevention strategies, particularly for MetS populations with high chronic inflammation.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1612975"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270853/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BCAA metabolism: the Achilles' heel of ovarian cancer, polycystic ovary syndrome, and premature ovarian failure.","authors":"Tian Zeng, Yitong Liu, Xing Tang, Runshu Fu, Qing Gao, Wenchao Zhou, Jiawen Fang, Juan Zhang, Juan Zou, Yukun Li","doi":"10.3389/fendo.2025.1579477","DOIUrl":"10.3389/fendo.2025.1579477","url":null,"abstract":"<p><p>Branched-chain amino acids (BCAAs), including valine, leucine and isoleucine, are essential nutrient signals that influence mammalian animal metabolism. Many enzymes are involved in the metabolism of BCAAs, such as branched-chain amino acid transaminases (BCATs), branched-chain α-keto acid dehydrogenase (BCKDH), and BCKDH kinase (BCKDK). The aberrant expression of enzymes involved in BCAA metabolism and an imbalance in BCAA amino acid intake can lead to disordered metabolism. Aberrant BCAA metabolism can lead to several diseases, such as human ovarian disease, including ovarian cancer (OC), polycystic ovary syndrome (PCOS), and premature ovarian failure (POF), which are common gynaecological diseases. The overexpression of BCATs is found in OC, which promotes BCAA catalysis to provide a large amount of energy for tumorigenesis. However, BCKDK is overexpressed in epithelial ovarian cancer (EOC), which promotes proliferation and migration via MEK-ERK. In addition, several studies have reported that high levels of BCAAs are increased in the plasma of PCOS and POF patients. This review focuses on the role of BCAA metabolism and potential management methods for OC, PCOS and POF.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1579477"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270879/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of estimated glucose disposal rate with chronic kidney disease: comparative analysis against traditional insulin resistance indices.","authors":"Yuanxin Liu, Mingda Liu, Yuyin Jiang, Siyuan Cui, Wei Tang","doi":"10.3389/fendo.2025.1507735","DOIUrl":"10.3389/fendo.2025.1507735","url":null,"abstract":"<p><strong>Background: </strong>Chronic kidney disease (CKD) is a widespread condition, marked by significant morbidity and mortality rates, particularly in individuals with comorbidities such as diabetes and hypertension. While insulin resistance (IR) has been linked to CKD, the traditional methods used to measure IR have inherent limitations. This necessitates the exploration of alternative indicators that can more accurately reflect the relationship between IR and CKD.</p><p><strong>Methods: </strong>This study employed a cross-sectional design, utilizing data extracted from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2013 to 2018. The study sample comprised 7423 participants. Comprehensive demographic, anthropometric, and laboratory data were collected and analyzed. The estimated glucose disposal rate (eGDR), along with established measures of insulin resistance such as HOMA-IR, QUICKI, and the TyG, TyG-BMI, and TyG-WC indices were computed. The relationships between these indices and CKD indicators, specifically the eGFR and UACR, were assessed using a combination of linear and logistic regression models. Additionally, the performance of these indices was evaluated using receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>Elevated levels of the eGDR were significantly correlated with improved kidney function and a reduced prevalence of chronic kidney disease (CKD) and albuminuria. The correlation coefficients (R²) demonstrated that eGDR had a stronger association with the estimated glomerular filtration rate (eGFR) at R²=0.1379 and with the urinary albumin-to-creatinine ratio (UACR) at R²=0.0816, compared to the traditional measures of insulin resistance. eGDR also declined progressively across worsening CKD stages (p for trend< 0.001), highlighting a dose-response relationship. Logistic regression analysis further revealed that higher eGDR levels were associated with a decreased risk of developing CKD and proteinuria. Additionally, the ROC curve analysis indicated that eGDR exhibited the highest predictive accuracy for CKD, with an area under the curve (AUC) of 0.75, and for proteinuria, with an area under the curve (AUC) of 0.68.</p><p><strong>Conclusion: </strong>The eGDR has emerged as a reliable and practical marker of insulin resistance associated with CKD indicators, demonstrating stronger associations with eGFR and UACR compared to traditional measures like HOMA-IR, QUICKI, TyG, TyG-BMI and TyG-WC. The simplicity of calculating eGDR enhances its utility as a valuable tool for the early detection and management of CKD, potentially improving clinical outcomes.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1507735"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12272229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Life's Essential 8 and heavy metal exposure to determine infertility risk in American women: a machine learning prediction model based on the SHAP method.","authors":"Xiaoqing Gu, Qianbing Li, Xiangfei Wang","doi":"10.3389/fendo.2025.1586828","DOIUrl":"10.3389/fendo.2025.1586828","url":null,"abstract":"<p><strong>Background: </strong>Fertility status is a marker of future health, and female infertility has been shown to be an important medical and social problem. Life's Essential 8 (\"LE8\") is a comprehensive cardiovascular health assessment proposed by the American Heart Association. The assessment indicators include 4 health behaviors (diet, physical activity, nicotine exposure, and sleep health) and 4 health factors (body mass index, blood lipids, blood glucose, and blood pressure). LE8 and heavy metal exposure have both been shown to be associated with infertility. However, the association between LE8 and heavy metal exposure and female infertility has not been investigated. The aim of this study was to develop a machine learning prediction model for LE8 and heavy metal exposure and the risk of female infertility in the United States.</p><p><strong>Methods: </strong>The National Health and Nutrition Examination Survey (\"NHANES\") is a nationally representative program conducted by the National Center for Health Statistics to assess the health and nutritional status of the U.S. population. For this study, 873 women between the ages of 20 and 45 were selected from the 2013-2018 NHANES dataset. The association between LE8 and heavy metal exposure and risk of infertility was assessed using logistic regression analysis and six machine learning models (Decision Tree, GBDT, AdaBoost, LGBM, Logistic Regression, Random Forest), and the SHAP algorithm was used to explain the model's decision process.</p><p><strong>Results: </strong>Of the six machine learning models, the LGBM model has the best predictive performance, with an AUROC of 0.964 on the test set. SHAP analysis showed that LE8, body mass index (\"BMI\"), diet, Cadmium (\"Cd\"), Cesium (\"Cs\"), Molybdenum (\"Mo\"), Antimony (\"Sb\"), Tin (\"Sn\"), education level and pregnancy history were significantly associated with the risk of female infertility. Cd, BMI and LE8 are the variables that contribute most to the prediction of infertility risk. Among them, BMI and LE8 have a negative predictive effect on female infertility in the model, while Cd has a positive contribution to the prediction of female infertility. Further analysis showed that there was a significant interaction between heavy metals and LE8, which may have a synergistic effect on the risk of female infertility.</p><p><strong>Conclusions: </strong>This study used LE8 and heavy metal exposure to create a machine learning model that predicts the risk of female infertility. The model identified ten key factors. The model demonstrated high predictive accuracy and good clinical interpretability. In the future, LE8 and heavy metal exposure can be used to screen for female infertility early on.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1586828"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}