Objective To explore the correlation and dose-response relationship between blood lipid parameters and the risk of thyroid nodules (TNs) in euthyroid women, providing references for disease prevention. Methods A case-control study was conducted, including 1 412 euthyroid women (701 in the case group and 711 in the control group). Crude and multivariable logistic regression models were used to assess the association between blood lipid parameters and the risk of TNs, and restricted cubic spline regression was applied to explore the dose-response relationship. Results Compared with women in the lowest quartile of serum triglyceride (TG; Q1, TG≤0.92 mmol/L), the risk of TNs was 45% (OR＝1.45, 95%CI 1.06-1.98) higher for those in Q2 (TG 0.93-1.24 mmol/L), 101% (OR＝2.01, 95%CI 1.47-2.77) higher for those in Q3 (TG 1.25-1.81 mmol/L), and 67% (OR＝1.67, 95%CI 1.19-2.33) higher for those in Q4 (TG>1.81 mmol/L) after adjusting for age, body mass index (BMI) and education. For each unit increase in log₁₀TG, the risk increased by 98% (OR＝1.98, 95%CI 1.14-3.45). Moreover, the correlation remained statistically significant even after further adjustment for thyroglobulin antibody (TGAb), thyroid peroxidase antibody (TPOAb) and urinary iodine (OR＝1.75, 95%CI 1.00-3.06, P＜0.05). However, correlations of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) with the risk of TNs were not statistically significant. Restricted cubic spline regression analysis further demonstrated the non-linear dose-response relationship of TG levels with the risk of TNs. Specifically, the risk of TNs increased in a monotonic manner at lower TG concentrations (＜1.23 mmol/L), but appeared to plateau or even slightly decrease at higher levels of TG (≥1.23 mmol/L). Conclusions Among euthyroid women, higher serum TG level is associated with risk of TNs, and this correlation is non-linear.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective:To conduct clinical analysis and genetic variant detection in patients with congenital hypothyroidism, and to explore the role of paired box 8(PAX8) gene variants in the pathogenic mechanism of congenital hypothyroidism, thereby providing insights for its diagnosis and management.Methods:This study was a retrospective analysis based on previously collected clinical and genetic data. Clinical information from 763 children with congenital hypothyroidism and some of their family members was collected between 2014 and 2025. Peripheral blood samples were obtained for genomic DNA extraction. Next-generation sequencing was performed to detect pathogenic variants in the patients. The identified pathogenic PAX8 variants were confirmed by Sanger sequencing and pedigree analysis. Functional analysis of the variant was then performed using bioinformatics tools.Results:Five PAX8 variants were identified among 763 children with congenital hypothyroidism. One proband was identified through neonatal screening and subsequently confirmed to have congenital hypothyroidism. Thyroid ultrasound revealed a small thyroid gland. A heterozygous missense variant in the PAX8 gene, NM_003466.3: c.91C>T: p.R31C, was identified in this proband, resulting in the substitution of arginine with cysteine at Codon 31 of the PAX8 protein. Sanger sequencing confirmed that this was a de novo variant, as it was absent in the proband′s parents. Multiple bioinformatic programs consistently predicted the variant to be deleterious. According to the American College of Medical Genetics and Genomics(ACMG) guidelines, the variant was classified as pathogenic. Conclusions:A de novo PAX8 variant, p. R31C, was identified in a patient with congenital hypothyroidism. This variant is located within the paired domain of the PAX8 protein and may impair the protein′s function by disrupting its binding to DNA.

Objective:To conduct clinical analysis and genetic variant detection in patients with congenital hypothyroidism, and to explore the role of paired box 8(PAX8) gene variants in the pathogenic mechanism of congenital hypothyroidism, thereby providing insights for its diagnosis and management.Methods:This study was a retrospective analysis based on previously collected clinical and genetic data. Clinical information from 763 children with congenital hypothyroidism and some of their family members was collected between 2014 and 2025. Peripheral blood samples were obtained for genomic DNA extraction. Next-generation sequencing was performed to detect pathogenic variants in the patients. The identified pathogenic PAX8 variants were confirmed by Sanger sequencing and pedigree analysis. Functional analysis of the variant was then performed using bioinformatics tools.Results:Five PAX8 variants were identified among 763 children with congenital hypothyroidism. One proband was identified through neonatal screening and subsequently confirmed to have congenital hypothyroidism. Thyroid ultrasound revealed a small thyroid gland. A heterozygous missense variant in the PAX8 gene, NM_003466.3: c.91C>T: p.R31C, was identified in this proband, resulting in the substitution of arginine with cysteine at Codon 31 of the PAX8 protein. Sanger sequencing confirmed that this was a de novo variant, as it was absent in the proband′s parents. Multiple bioinformatic programs consistently predicted the variant to be deleterious. According to the American College of Medical Genetics and Genomics(ACMG) guidelines, the variant was classified as pathogenic. Conclusions:A de novo PAX8 variant, p. R31C, was identified in a patient with congenital hypothyroidism. This variant is located within the paired domain of the PAX8 protein and may impair the protein′s function by disrupting its binding to DNA.

Objective:The degree of involvement of extraocular muscles varies across different regions of retrobulbar tissue in patients with thyroid eye disease, but the mechanism is unclear. This study aims to explore the relationship between differential expression of thyroid-stimulating hormone receptor(TSHR) in different parts of the extraocular muscles and the varying degrees of muscle involvement.Methods:The medial, lateral, superior, and inferior rectus muscle were separated from the retrobulbar tissue of rats, and the expression level of TSHR in four extraocular muscles was detected by immunofluorescence and qPCR. Extraocular muscle tissue of patients with strabismus was collected to detect the expression of TSHR and the cell types expressed by fluorescence.Results:The results of qPCR showed that the expression of TSHR in the medial rectus muscle was significantly higher than that in the lateral, superior, and inferior rectus muscle(medial rectus vs lateral rectus, P=0.012; medial rectus vs superior rectus, P=0.015; medial rectus vs inferior rectus, P=0.013), but there was no difference in insulin-like growth factor 1(IGF-1R) expression. Immunofluorescence showed that TSHR was co-expressed with PAX7, a molecular marker of muscle satellite cells, and the expression level in the medial rectus muscle of rats and humans was significantly higher than those in the other three extraocular muscles. Conclusion:The high specific expression of TSHR in the satellite cells of the medial rectus muscle may be the reason why the medial rectus muscle is most susceptible to involvement in thyroid eye disease.

Objective:To detect the prevalence of mosaic loss of chromosome Y in adult men in ten study areas in China, describe the epidemiological distribution of mosaic loss of chromosome Y (mLOY) carriers and assess its prospective association with lung cancer.Methods:Based on the data from baseline survey, genetic analysis and follow-up (as of December 31, 2018) from China Kadoorie Biobank, we used Mosaic Chromosomal Alterations pipeline to detect mLOY carriers in 10 areas in China and described the epidemiological characteristics of mLOY carriers in adult men, including age, area distribution, lifestyle and disease history. We used multivariate logistic regression model to identify the potential relevant factor of mLOY. Cox proportional hazard regression model was fitted to assess the prospective association of mLOY with lung cancer. Stratification analysis were conducted to evaluate the potential modification effects of smoking and age. We also conducted mediation analysis to assess the mediating effect of mLOY in the association between smoking and lung cancer.Results:A total of 42 859 adult men were included in our analysis, in whom 2 458 mLOY carriers were detected (5.7%). The detection rate increased with age ( P<0.05). The detection rate was higher in urban area (7.3%±0.2%) than that in rural area (4.7%±0.1%). The results of logistic regression analysis indicated that smoking might be a risk factor for the detection of mLOY ( OR=1.49, 95% CI:1.36-1.64). After follow-up for average 11.1 years, 1 041 lung cancer cases were observed. The prospective analysis showed that mLOY carriers had an increased risk for lung cancer by 24% compared with non-mLOY carriers ( HR=1.24, 95% CI:1.01-1.52) and expanded mLOY carriers (mLOY cell proportion ≥10%) had an increased risk for lung cancer by 50% ( HR=1.50, 95% CI:1.13-2.00). Stratification analysis showed no modification effects of smoking and age in the association between mLOY and lung cancer (interaction P>0.05). Mediation analysis showed that mLOY could be a mediating factor in the association between smoking and lung cancer, the estimated effect was 0.09 (0.01-0.17). Conclusions:There were significant differences in the detection rate of mLOY in adult men with different social-economic characteristics and lifestyles in ten areas in China. Besides, mLOY carriers, especially expanded mLOY carriers, had increased risk for lung cancer and mLOY might be a mediating factor in the association between smoking and lung cancer.

Objective·To establish a transgenic zebrafish line Tg(amh:mCherry)for studying gonadal development and related diseases,and to trace and analyze the developmental process of zebrafish gonads.Methods·A recombinant transgenic expression vector pTol2-amh-mCherry was constructed by using the upstream promoter sequence of the zebrafish anti-Müllerian hormone(amh)gene coding region and the gene coding sequence of the red fluorescent protein,and was validated by using Sanger sequencing.The recombinant transgenic expression vector and mRNA of Tol2 transposase were co-microinjected into zebrafish embryos,and fluorescent zebrafish were selected by using fluorescence microscope to screen for a stable inherited transgenic zebrafish line Tg(amh:mCherry).In situ hybridization was used to detect whether the location of the fluorescence signals was consistent with the location of endogenous expression of amh.The red fluorescence of transgenic zebrafish from generation F3 was observed by fluorescence microscopy,and the process of gonadal development was tracked and analyzed.Results·The recombinant transgenic expression vector pTol2-amh-mCherry was successfully constructed,and a stable inherited F3 generation transgenic zebrafish line Tg(amh:mCherry)was successfully established.The results of in situ hybridization showed that the location of the red fluorescence signals in the transgenic zebrafish Tg(amh:mCherry)was consistent with the location of endogenous expression of amh.Through observation and analysis of the fluorescence of transgenic zebrafish from F3 generation,five developmental patterns of zebrafish gonads were found.Conclusion·The successful construction of Tg(amh:mCherry)transgenic zebrafish line facilitates the tracer analysis of zebrafish gonadal development,which provides a better experimental model for the study of gonad-related diseases.