Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen
Abstract PCOS is a widespread disease that primarily caused in-pregnancy in pregnant-age women. Normoandrogen (NA) and Hyperandrogen (HA) PCOS are distinct subtypes of PCOS, while bio-markers and expression patterns for NA PCOS and HA PCOS have not been disclosed. We performed microarray analysis on...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2024-02-01
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| Series: | Journal of Ovarian Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13048-024-01361-z |
| _version_ | 1797273614511243264 |
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| author | Wensu Liu Tianyu Tang Jianwei Feng Chunyu Wang Lin Lin Shengli Wang Kai Zeng Renlong Zou Zeyu Yang Yue Zhao |
| author_facet | Wensu Liu Tianyu Tang Jianwei Feng Chunyu Wang Lin Lin Shengli Wang Kai Zeng Renlong Zou Zeyu Yang Yue Zhao |
| author_sort | Wensu Liu |
| collection | DOAJ |
| description | Abstract PCOS is a widespread disease that primarily caused in-pregnancy in pregnant-age women. Normoandrogen (NA) and Hyperandrogen (HA) PCOS are distinct subtypes of PCOS, while bio-markers and expression patterns for NA PCOS and HA PCOS have not been disclosed. We performed microarray analysis on granusola cells from NA PCOS, HA PCOS and normal tissue from 12 individuals. Afterwards, microarray data were processed and specific genes for NA PCOS and HA PCOS were identified. Further functional analysis selected IL6R and CD274 as new NA PCOS functional markers, and meanwhile selected CASR as new HA PCOS functional marker. IL6R, CD274 and CASR were afterwards experimentally validated on mRNA and protein level. Subsequent causal relationship analysis based on Apriori Rules Algorithm and co-occurrence methods identified classification markers for NA PCOS and HA PCOS. According to classification markers, downloaded transcriptome datasets were merged with our microarray data. Based on merged data, causal knowledge graph was constructed for NA PCOS or HA PCOS and female infertility on NA PCOS and HA PCOS. Gene-drug interaction analysis was then performed and drugs for HA PCOS and NA PCOS were predicted. Our work was among the first to indicate the NA PCOS and HA PCOS functional and classification markers and using markers to construct knowledge graphs and afterwards predict drugs for NA PCOS and HA PCOS based on transcriptome data. Thus, our study possessed biological and clinical value on further understanding the inner mechanism on the difference between NA PCOS and HA PCOS. |
| first_indexed | 2024-03-07T14:46:55Z |
| format | Article |
| id | doaj.art-a74172285c3044278609b18931270b4e |
| institution | Directory Open Access Journal |
| issn | 1757-2215 |
| language | English |
| last_indexed | 2024-03-07T14:46:55Z |
| publishDate | 2024-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Ovarian Research |
| spelling | doaj.art-a74172285c3044278609b18931270b4e2024-03-05T19:58:05ZengBMCJournal of Ovarian Research1757-22152024-02-0117111810.1186/s13048-024-01361-zKnowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogenWensu Liu0Tianyu Tang1Jianwei Feng2Chunyu Wang3Lin Lin4Shengli Wang5Kai Zeng6Renlong Zou7Zeyu Yang8Yue Zhao9Health Sciences Institute, China Medical UniversityDepartment of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical UniversityDepartment of Ultrasound, Shengjing Hospital of China Medical UniversityDepartment of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical UniversityDepartment of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical UniversityDepartment of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical UniversityDepartment of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical UniversityDepartment of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical UniversityDepartment of Ultrasound, Shengjing Hospital of China Medical UniversityDepartment of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical UniversityAbstract PCOS is a widespread disease that primarily caused in-pregnancy in pregnant-age women. Normoandrogen (NA) and Hyperandrogen (HA) PCOS are distinct subtypes of PCOS, while bio-markers and expression patterns for NA PCOS and HA PCOS have not been disclosed. We performed microarray analysis on granusola cells from NA PCOS, HA PCOS and normal tissue from 12 individuals. Afterwards, microarray data were processed and specific genes for NA PCOS and HA PCOS were identified. Further functional analysis selected IL6R and CD274 as new NA PCOS functional markers, and meanwhile selected CASR as new HA PCOS functional marker. IL6R, CD274 and CASR were afterwards experimentally validated on mRNA and protein level. Subsequent causal relationship analysis based on Apriori Rules Algorithm and co-occurrence methods identified classification markers for NA PCOS and HA PCOS. According to classification markers, downloaded transcriptome datasets were merged with our microarray data. Based on merged data, causal knowledge graph was constructed for NA PCOS or HA PCOS and female infertility on NA PCOS and HA PCOS. Gene-drug interaction analysis was then performed and drugs for HA PCOS and NA PCOS were predicted. Our work was among the first to indicate the NA PCOS and HA PCOS functional and classification markers and using markers to construct knowledge graphs and afterwards predict drugs for NA PCOS and HA PCOS based on transcriptome data. Thus, our study possessed biological and clinical value on further understanding the inner mechanism on the difference between NA PCOS and HA PCOS.https://doi.org/10.1186/s13048-024-01361-zPolycystic ovary syndromeHyperandrogenic polycystic ovary syndromeNormoandrogenic polycystic ovary syndromeKnowledge graphDrug-gene interaction |
| spellingShingle | Wensu Liu Tianyu Tang Jianwei Feng Chunyu Wang Lin Lin Shengli Wang Kai Zeng Renlong Zou Zeyu Yang Yue Zhao Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen Journal of Ovarian Research Polycystic ovary syndrome Hyperandrogenic polycystic ovary syndrome Normoandrogenic polycystic ovary syndrome Knowledge graph Drug-gene interaction |
| title | Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen |
| title_full | Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen |
| title_fullStr | Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen |
| title_full_unstemmed | Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen |
| title_short | Knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen |
| title_sort | knowledge graph construction based on granulosa cells transcriptome from polycystic ovary syndrome with normoandrogen and hyperandrogen |
| topic | Polycystic ovary syndrome Hyperandrogenic polycystic ovary syndrome Normoandrogenic polycystic ovary syndrome Knowledge graph Drug-gene interaction |
| url | https://doi.org/10.1186/s13048-024-01361-z |
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