Application of Mendelian randomization in thyroid diseases: a review DOI Creative Commons
Zhonghui Li,

Ruohan Wang,

Lili Liu

et al.

Frontiers in Endocrinology, Journal Year: 2024, Volume and Issue: 15

Published: Dec. 19, 2024

Thyroid diseases are increasingly prevalent, posing significant challenges to patients' quality of life and placing substantial financial burdens on families society. Despite these impacts, the underlying pathophysiology many thyroid conditions remains poorly understood, complicating efforts in treatment, management, prevention. Observational studies can identify associations between exposure variables disease; however, they often struggle account for confounding factors reverse causation. Understanding disease occurrence, epidemiological trends, clinical diagnosis, prevention, treatment relies heavily robust etiological research. Mendelian randomization, a method grounded genetics epidemiology, has been widely employed studying etiology diseases, offering solution some challenges. This paper categorizes into dysfunction cancer, reviewing related randomization studies. It further provides novel perspectives approaches investigating mechanisms designing intervention strategies.

Language: Английский

Deciphering the therapeutic effects of Xiyanping injection: insights into pulmonary and gut microbiome modulation, SerpinB2/PAI-2 targeting, and alleviation of influenza a virus-induced lung injury DOI Creative Commons

Tengwen Liu,

Shuping Li,

Xuerui Wang

et al.

Virology Journal, Journal Year: 2025, Volume and Issue: 22(1)

Published: Jan. 28, 2025

Language: Английский

Citations

0
Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms DOI Creative Commons
Chun-Xia Huang,

Qiong Ma,

Xiao Zeng

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 29, 2025

Microorganisms are one of the most promising biomarkers for cancer, and relationship between microorganisms lung cancer occurrence development provides significant potential pulmonary nodule (PN) diagnosis from a microbiological perspective. This study aimed to analyze salivary microbiota features patients with PN assess as non-invasive biomarker. We collected saliva smples 153 40 controls. Using 16 S rRNA gene sequencing, differences in α- β-diversity community composition group controls were analyzed. Subsequently, specific microbial variables selected using six models trained on features. The evaluated metrics, such area under receiver operating characteristic curve (AUC), identify best-performing model. Furthermore, Bayesian optimization algorithm was used optimize this Finally, SHapley Additive exPlanations (SHAP) interpretability framework interpret output optimal model biomarkers. Significant observed Although predominant genera consistent groups, disparities their relative abundances. By leveraging random forest algorithm, ten identified incorporated into models, which effectively facilitated diagnosis. XGBoost demonstrated best performance. Further resulted Optimization-based (BOXGB) Based BOXGB model, an online microbiota-based prediction platform developed. Lastly, SHAP analysis suggested Defluviitaleaceae_UCG-011, Aggregatibacter, Oribacterium, Bacillus, Prevotalla proved biomarker, expanding clinical diagnostic approaches PN.

Language: Английский

Citations

0
Genetically Predicted Peripheral Immune Cells Mediate the Effect of Gut Microbiota on Influenza Susceptibility DOI Open Access
Shiqi Wang, Guosen Ou, Jialin Wu

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(14), P. 7706 - 7706

Published: July 14, 2024

The communication mechanism of the gut–lung axis has received increasing attention in recent years, particularly acute respiratory infectious diseases such as influenza. peripheral immune system serves a crucial bridge between gut and lungs, two organs that are not close proximity to each other. However, specific involving microbiota, cells, their anti-influenza effects lung remains be further elucidated. In this study, 731 species cells 211 different microbiota on influenza outcomes were analyzed using two-sample Mendelian randomization analysis. After identifying associated with outcomes, mediation analyses conducted determine mediating protective or injurious mediated by microbiota. 19 75 types identified being susceptibility. rigorous screening, 12 combinations for effects. Notably, down-regulation CD64 CD14- CD16- 21.10% 18.55% effect Alcaligenaceae Dorea against influenza, respectively. conclusion, focusing study genetically inferred risk factors. Furthermore, analysis was used proportion microbiota-mediated susceptibility This helps elucidate which affects from perspective regulation cells.

Language: Английский

Citations

2
Application of Mendelian randomization in thyroid diseases: a review DOI Creative Commons
Zhonghui Li,

Ruohan Wang,

Lili Liu

et al.

Frontiers in Endocrinology, Journal Year: 2024, Volume and Issue: 15

Published: Dec. 19, 2024

Thyroid diseases are increasingly prevalent, posing significant challenges to patients' quality of life and placing substantial financial burdens on families society. Despite these impacts, the underlying pathophysiology many thyroid conditions remains poorly understood, complicating efforts in treatment, management, prevention. Observational studies can identify associations between exposure variables disease; however, they often struggle account for confounding factors reverse causation. Understanding disease occurrence, epidemiological trends, clinical diagnosis, prevention, treatment relies heavily robust etiological research. Mendelian randomization, a method grounded genetics epidemiology, has been widely employed studying etiology diseases, offering solution some challenges. This paper categorizes into dysfunction cancer, reviewing related randomization studies. It further provides novel perspectives approaches investigating mechanisms designing intervention strategies.

Language: Английский

Citations

0