Devalina Junahar, Rinesia Dwiputri, Wirawan Adikusuma, Darmawi Darmawi, Afdal Afdal, Lalu Muhammad Irham, Suyanto Suyanto
{"title":"男性不育症的潜在生物标记特征:综合基因组分析","authors":"Devalina Junahar, Rinesia Dwiputri, Wirawan Adikusuma, Darmawi Darmawi, Afdal Afdal, Lalu Muhammad Irham, Suyanto Suyanto","doi":"10.1186/s43042-024-00512-7","DOIUrl":null,"url":null,"abstract":"Studies have attributed 50% of infertility cases to male infertility, 15% of which is caused by idiopathic genetic factors. Currently, no specific biomarkers have been revealed for male infertility. Furthermore, research on genetic factors causing male infertility is still limited. As with other multifactorial genetic disorders, numerous risk loci for male infertility have been identified by genome-wide association studies (GWAS), although their clinical significance remains uncertain. Therefore, we utilized an integrative bioinformatics-based approach to identify biomarkers for male infertility. Bioinformatics analysis was performed using Open Targets Platform, DisGeNet, and GWAS Catalog. After that, the STRING database and the Cytoscape program were used to analyze protein–protein interaction. CytoHubba was used to determine the most significant gene candidates. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to assess biological functions that correspond to the male infertility disease pathway. We identified 305 genes associated with male infertility and highlighted 10 biological risk genes as potential biomarkers for male infertility such as TEX11, SPO11, SYCP3, HORMAD1, STAG3, MSH4, SYCP2, SYCE1, RAD21L1, and AMH. Of all the genes, we took the top three genes, namely, TEX11, SPO11, and SYCP3 as the genes that have the most potential as biomarkers. TEX11, SPO11, and SYCP3 are involved in meiosis and spermatogenesis. We propose that further research in regarding these genes in detecting male infertility.","PeriodicalId":39112,"journal":{"name":"Egyptian Journal of Medical Human Genetics","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Potential biomarker signatures in male infertility: integrative genomic analysis\",\"authors\":\"Devalina Junahar, Rinesia Dwiputri, Wirawan Adikusuma, Darmawi Darmawi, Afdal Afdal, Lalu Muhammad Irham, Suyanto Suyanto\",\"doi\":\"10.1186/s43042-024-00512-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Studies have attributed 50% of infertility cases to male infertility, 15% of which is caused by idiopathic genetic factors. Currently, no specific biomarkers have been revealed for male infertility. Furthermore, research on genetic factors causing male infertility is still limited. As with other multifactorial genetic disorders, numerous risk loci for male infertility have been identified by genome-wide association studies (GWAS), although their clinical significance remains uncertain. Therefore, we utilized an integrative bioinformatics-based approach to identify biomarkers for male infertility. Bioinformatics analysis was performed using Open Targets Platform, DisGeNet, and GWAS Catalog. After that, the STRING database and the Cytoscape program were used to analyze protein–protein interaction. CytoHubba was used to determine the most significant gene candidates. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to assess biological functions that correspond to the male infertility disease pathway. We identified 305 genes associated with male infertility and highlighted 10 biological risk genes as potential biomarkers for male infertility such as TEX11, SPO11, SYCP3, HORMAD1, STAG3, MSH4, SYCP2, SYCE1, RAD21L1, and AMH. Of all the genes, we took the top three genes, namely, TEX11, SPO11, and SYCP3 as the genes that have the most potential as biomarkers. TEX11, SPO11, and SYCP3 are involved in meiosis and spermatogenesis. We propose that further research in regarding these genes in detecting male infertility.\",\"PeriodicalId\":39112,\"journal\":{\"name\":\"Egyptian Journal of Medical Human Genetics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Egyptian Journal of Medical Human Genetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s43042-024-00512-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Egyptian Journal of Medical Human Genetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s43042-024-00512-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Potential biomarker signatures in male infertility: integrative genomic analysis
Studies have attributed 50% of infertility cases to male infertility, 15% of which is caused by idiopathic genetic factors. Currently, no specific biomarkers have been revealed for male infertility. Furthermore, research on genetic factors causing male infertility is still limited. As with other multifactorial genetic disorders, numerous risk loci for male infertility have been identified by genome-wide association studies (GWAS), although their clinical significance remains uncertain. Therefore, we utilized an integrative bioinformatics-based approach to identify biomarkers for male infertility. Bioinformatics analysis was performed using Open Targets Platform, DisGeNet, and GWAS Catalog. After that, the STRING database and the Cytoscape program were used to analyze protein–protein interaction. CytoHubba was used to determine the most significant gene candidates. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to assess biological functions that correspond to the male infertility disease pathway. We identified 305 genes associated with male infertility and highlighted 10 biological risk genes as potential biomarkers for male infertility such as TEX11, SPO11, SYCP3, HORMAD1, STAG3, MSH4, SYCP2, SYCE1, RAD21L1, and AMH. Of all the genes, we took the top three genes, namely, TEX11, SPO11, and SYCP3 as the genes that have the most potential as biomarkers. TEX11, SPO11, and SYCP3 are involved in meiosis and spermatogenesis. We propose that further research in regarding these genes in detecting male infertility.