Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomics
IntroductionAlthough significant progress has been made in the treatment and research of osteoporosis patients in recent years, the genetic mechanism of osteoporosis has not yet been fully elucidated.MethodsWe conducted a comprehensive analysis using 16S sequencing and UHPLC–MS/MS metabolomics data...
| الحاوية / القاعدة: | Frontiers in Medicine |
|---|---|
| المؤلفون الرئيسيون: | , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
Frontiers Media S.A.
2025-09-01
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1664359/full |
| _version_ | 1848780480745308160 |
|---|---|
| author | Yu Liu Yu Liu Yun Li Jiehua Li |
| author_facet | Yu Liu Yu Liu Yun Li Jiehua Li |
| author_sort | Yu Liu |
| collection | DOAJ |
| container_title | Frontiers in Medicine |
| description | IntroductionAlthough significant progress has been made in the treatment and research of osteoporosis patients in recent years, the genetic mechanism of osteoporosis has not yet been fully elucidated.MethodsWe conducted a comprehensive analysis using 16S sequencing and UHPLC–MS/MS metabolomics data to characterize the microbial composition and metabolic composition in the serum of osteoporosis patients.ResultsAt the phylum level, Proteobacteria are mainly present in Osteoporosis; In Normal, it is mainly Bacteroidota. At the genus level, Cupriavidus is the main species in Osteoporosis; In Normal, the main ones are Blautia, Bacteroides, Alcaligenes and Pseudomonas. Serum metabolomics revealed different metabolites (230 significantly differentially expressed metabolites) and lipid metabolism pathways (such as Glycerophospholipid metabolism) among the two groups. The combined serum microbiota and serum metabolomics datasets demonstrate a correlation reflecting the impact of microbiota on metabolic activity (p < 0.05).DiscussionOur research findings indicate that microbiota and metabolomics analysis provide important candidate biomarkers. The correlation between these serum microbiota and host metabolism is of great significance for optimizing early diagnosis and developing personalized treatment strategies. This study elucidates the relationship between serum microbiota and metabolites in osteoporosis. |
| format | Article |
| id | doaj-art-ccf62ca364e9484c82735a60629de8f3 |
| institution | Directory of Open Access Journals |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| spelling | doaj-art-ccf62ca364e9484c82735a60629de8f32025-09-24T05:40:35ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-09-011210.3389/fmed.2025.16643591664359Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomicsYu Liu0Yu Liu1Yun Li2Jiehua Li3Department of Geriatrics, The First Affiliated Hospital of Anhui Medical University, Hefei, ChinaDepartment of Geriatrics, The Third Affiliated Hospital of Anhui Medical University, Hefei, ChinaSchool of Biology and Pharmaceutical Engineering, Wuhan Polytechnic University, Wuhan, ChinaDepartment of Geriatrics, The First Affiliated Hospital of Anhui Medical University, Hefei, ChinaIntroductionAlthough significant progress has been made in the treatment and research of osteoporosis patients in recent years, the genetic mechanism of osteoporosis has not yet been fully elucidated.MethodsWe conducted a comprehensive analysis using 16S sequencing and UHPLC–MS/MS metabolomics data to characterize the microbial composition and metabolic composition in the serum of osteoporosis patients.ResultsAt the phylum level, Proteobacteria are mainly present in Osteoporosis; In Normal, it is mainly Bacteroidota. At the genus level, Cupriavidus is the main species in Osteoporosis; In Normal, the main ones are Blautia, Bacteroides, Alcaligenes and Pseudomonas. Serum metabolomics revealed different metabolites (230 significantly differentially expressed metabolites) and lipid metabolism pathways (such as Glycerophospholipid metabolism) among the two groups. The combined serum microbiota and serum metabolomics datasets demonstrate a correlation reflecting the impact of microbiota on metabolic activity (p < 0.05).DiscussionOur research findings indicate that microbiota and metabolomics analysis provide important candidate biomarkers. The correlation between these serum microbiota and host metabolism is of great significance for optimizing early diagnosis and developing personalized treatment strategies. This study elucidates the relationship between serum microbiota and metabolites in osteoporosis.https://www.frontiersin.org/articles/10.3389/fmed.2025.1664359/fullmetabolomicsmicrobiomeserumosteoporosisbiomarkers |
| spellingShingle | Yu Liu Yu Liu Yun Li Jiehua Li Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomics metabolomics microbiome serum osteoporosis biomarkers |
| title | Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomics |
| title_full | Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomics |
| title_fullStr | Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomics |
| title_full_unstemmed | Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomics |
| title_short | Integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16S rDNA sequencing and UHPLC/MS-based metabolomics |
| title_sort | integrative analysis of serum microorganisms and serum metabolomics in osteoporosis patients based on 16s rdna sequencing and uhplc ms based metabolomics |
| topic | metabolomics microbiome serum osteoporosis biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2025.1664359/full |
| work_keys_str_mv | AT yuliu integrativeanalysisofserummicroorganismsandserummetabolomicsinosteoporosispatientsbasedon16srdnasequencinganduhplcmsbasedmetabolomics AT yuliu integrativeanalysisofserummicroorganismsandserummetabolomicsinosteoporosispatientsbasedon16srdnasequencinganduhplcmsbasedmetabolomics AT yunli integrativeanalysisofserummicroorganismsandserummetabolomicsinosteoporosispatientsbasedon16srdnasequencinganduhplcmsbasedmetabolomics AT jiehuali integrativeanalysisofserummicroorganismsandserummetabolomicsinosteoporosispatientsbasedon16srdnasequencinganduhplcmsbasedmetabolomics |
