Abstract
Background
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.
Results
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.
Conclusions
TEX11, SPO11, and SYCP3 are involved in meiosis and spermatogenesis. We propose that further research in regarding these genes in detecting male infertility.
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Details
1 Universitas Riau, Master’s Program in Biomedical Sciences, Faculty of Medicine, Pekanbaru, Indonesia (GRID:grid.444161.2) (ISNI:0000 0000 8951 2213); Awal Bros Hospital, Tunas Bangsa IVF Clinic, Pekanbaru, Indonesia (GRID:grid.444161.2)
2 Universitas Riau, Master’s Program in Biomedical Sciences, Faculty of Medicine, Pekanbaru, Indonesia (GRID:grid.444161.2) (ISNI:0000 0000 8951 2213); Arifin Achmad General Hospital, Department of Medical Acupuncture, Pekanbaru, Indonesia (GRID:grid.444161.2)
3 National Research and Innovation Agency (BRIN), Research Center for Computing, Research Organization for Electronics and Informatics, Cibinong, Indonesia (GRID:grid.444161.2); University of Muhammadiyah Mataram, Department of Pharmacy, Faculty of Health Science, Mataram, Indonesia (GRID:grid.443798.5) (ISNI:0000 0001 0179 6061)
4 Universitas Riau, Graduate School in Biomedical Sciences, Faculty of Medicine, Pekanbaru, Indonesia (GRID:grid.444161.2) (ISNI:0000 0000 8951 2213); Universitas Riau, Department of Histology, Faculty of Medicine, Pekanbaru, Indonesia (GRID:grid.444161.2) (ISNI:0000 0000 8951 2213)
5 Universitas Riau, Department of Urology, Faculty of Medicine, Pekanbaru, Indonesia (GRID:grid.444161.2) (ISNI:0000 0000 8951 2213)
6 Universitas Ahmad Dahlan, Faculty of Pharmacy, Yogyakarta, Indonesia (GRID:grid.444626.6) (ISNI:0000 0000 9226 1101)
7 Universitas Riau, Department of Public Health and Community Medicine, Faculty of Medicine, Pekanbaru, Indonesia (GRID:grid.444161.2) (ISNI:0000 0000 8951 2213)





