A Comparative Cross-Platform Analysis to Identify Potential Biomarker Genes for Evaluation of Teratozoospermia and Azoospermia
Male infertility is a global public health concern. Teratozoospermia is a qualitative anomaly of spermatozoa morphology, contributing significantly to male infertility, whereas azoospermia is the complete absence of spermatozoa in the ejaculate. Thus, there is a serious need for unveiling the common...
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| Veröffentlicht in: | Genes 2022-09, Vol.13 (10), p.1721 |
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| creator | Das, Suchismita Guha, Pokhraj Nath, Monika Das, Sandipan Sen, Surojit Sahu, Jagajjit Kopanska, Marta Dutta, Sulagna Jamal, Qazi Mohammad Sajid Kesari, Kavindra Kumar Sengupta, Pallav Slama, Petr Roychoudhury, Shubhadeep |
| description | Male infertility is a global public health concern. Teratozoospermia is a qualitative anomaly of spermatozoa morphology, contributing significantly to male infertility, whereas azoospermia is the complete absence of spermatozoa in the ejaculate. Thus, there is a serious need for unveiling the common origin and/or connection between both of these diseases, if any. This study aims to identify common potential biomarker genes of these two diseases via an in silico approach using a meta-analysis of microarray data. In this study, a differential expression analysis of genes was performed on four publicly available RNA microarray datasets, two each from teratozoospermia (GSE6872 and GSE6967) and azoospermia (GSE145467 and GSE25518). From the analysis, 118 DEGs were found to be common to teratozoospermia and azoospermia, and, interestingly, sperm autoantigenic protein 17 (
) was found to possess the highest fold change value among all the DEGs (9.471), while coiled-coil domain-containing 90B (
) and coiled-coil domain-containing 91 (
) genes were found to be common among three of analyses, i.e., Network Analyst, ExAtlas, and GEO2R. This observation indicates that
and
genes might have significant roles to play as potential biomarkers for teratozoospermia and azoospermia. Thus, our study opens a new window of research in this area and can provide an important theoretical basis for the diagnosis and treatment of both these diseases. |
| doi_str_mv | 10.3390/genes13101721 |
| format | Article |
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) was found to possess the highest fold change value among all the DEGs (9.471), while coiled-coil domain-containing 90B (
) and coiled-coil domain-containing 91 (
) genes were found to be common among three of analyses, i.e., Network Analyst, ExAtlas, and GEO2R. This observation indicates that
and
genes might have significant roles to play as potential biomarkers for teratozoospermia and azoospermia. Thus, our study opens a new window of research in this area and can provide an important theoretical basis for the diagnosis and treatment of both these diseases.</description><identifier>ISSN: 2073-4425</identifier><identifier>EISSN: 2073-4425</identifier><identifier>DOI: 10.3390/genes13101721</identifier><identifier>PMID: 36292606</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Azoospermia - diagnosis ; Azoospermia - genetics ; Biological markers ; Biomarkers ; Datasets ; DNA microarrays ; Epigenetics ; Evaluation ; Gene expression ; Genetic aspects ; Humans ; Identification and classification ; Infertility ; Infertility, Male ; Infertility, Male - genetics ; Kinases ; Male ; Males ; Meta-analysis ; Protein folding ; Proteins ; Public health ; RNA ; Semen - metabolism ; Software ; Sperm ; Spermatogenesis ; Statistical power ; Teratozoospermia - genetics ; Teratozoospermia - metabolism ; Testes ; Variance analysis</subject><ispartof>Genes, 2022-09, Vol.13 (10), p.1721</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c438t-5ff9eca2a9a28b7223f653db98f2a94c69af0b2a059daaead17d21881d264d873</cites><orcidid>0000-0001-5525-708X ; 0000-0002-2926-7281 ; 0000-0001-7468-5696 ; 0000-0003-4174-1852 ; 0000-0003-3936-0698 ; 0000-0003-0570-259X ; 0000-0003-3622-9555 ; 0000-0002-7893-5282 ; 0000-0002-1928-5048</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9602071/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9602071/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,882,27905,27906,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36292606$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Das, Suchismita</creatorcontrib><creatorcontrib>Guha, Pokhraj</creatorcontrib><creatorcontrib>Nath, Monika</creatorcontrib><creatorcontrib>Das, Sandipan</creatorcontrib><creatorcontrib>Sen, Surojit</creatorcontrib><creatorcontrib>Sahu, Jagajjit</creatorcontrib><creatorcontrib>Kopanska, Marta</creatorcontrib><creatorcontrib>Dutta, Sulagna</creatorcontrib><creatorcontrib>Jamal, Qazi Mohammad Sajid</creatorcontrib><creatorcontrib>Kesari, Kavindra Kumar</creatorcontrib><creatorcontrib>Sengupta, Pallav</creatorcontrib><creatorcontrib>Slama, Petr</creatorcontrib><creatorcontrib>Roychoudhury, Shubhadeep</creatorcontrib><title>A Comparative Cross-Platform Analysis to Identify Potential Biomarker Genes for Evaluation of Teratozoospermia and Azoospermia</title><title>Genes</title><addtitle>Genes (Basel)</addtitle><description>Male infertility is a global public health concern. Teratozoospermia is a qualitative anomaly of spermatozoa morphology, contributing significantly to male infertility, whereas azoospermia is the complete absence of spermatozoa in the ejaculate. Thus, there is a serious need for unveiling the common origin and/or connection between both of these diseases, if any. This study aims to identify common potential biomarker genes of these two diseases via an in silico approach using a meta-analysis of microarray data. In this study, a differential expression analysis of genes was performed on four publicly available RNA microarray datasets, two each from teratozoospermia (GSE6872 and GSE6967) and azoospermia (GSE145467 and GSE25518). From the analysis, 118 DEGs were found to be common to teratozoospermia and azoospermia, and, interestingly, sperm autoantigenic protein 17 (
) was found to possess the highest fold change value among all the DEGs (9.471), while coiled-coil domain-containing 90B (
) and coiled-coil domain-containing 91 (
) genes were found to be common among three of analyses, i.e., Network Analyst, ExAtlas, and GEO2R. This observation indicates that
and
genes might have significant roles to play as potential biomarkers for teratozoospermia and azoospermia. Thus, our study opens a new window of research in this area and can provide an important theoretical basis for the diagnosis and treatment of both these diseases.</description><subject>Azoospermia - diagnosis</subject><subject>Azoospermia - genetics</subject><subject>Biological markers</subject><subject>Biomarkers</subject><subject>Datasets</subject><subject>DNA microarrays</subject><subject>Epigenetics</subject><subject>Evaluation</subject><subject>Gene expression</subject><subject>Genetic aspects</subject><subject>Humans</subject><subject>Identification and classification</subject><subject>Infertility</subject><subject>Infertility, Male</subject><subject>Infertility, Male - genetics</subject><subject>Kinases</subject><subject>Male</subject><subject>Males</subject><subject>Meta-analysis</subject><subject>Protein folding</subject><subject>Proteins</subject><subject>Public health</subject><subject>RNA</subject><subject>Semen - metabolism</subject><subject>Software</subject><subject>Sperm</subject><subject>Spermatogenesis</subject><subject>Statistical power</subject><subject>Teratozoospermia - genetics</subject><subject>Teratozoospermia - metabolism</subject><subject>Testes</subject><subject>Variance analysis</subject><issn>2073-4425</issn><issn>2073-4425</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNptkk1LJDEQhsOirKIevS6BPbfmqzudi9AOrgqCHvQcajrJbLS7M5v0DIyH_e2m8XPA5JBK5a2HqlQhdEzJCeeKnC7sYBPllFDJ6A-0z4jkhRCs3Pli76GjlB5JXoIwQsqfaI9XTLGKVPvof4NnoV9ChNGvLZ7FkFJx18HoQuxxM0C3ST7hMeBrY4fRuw2-C-NkQYfPfeghPtmIL6dEcI7BF2voVhkWBhwcvrcZHJ5DSEsbew8YBoObz_sh2nXQJXv0dh6ghz8X97Or4ub28nrW3BSt4PVYlM4p2wIDBayeS8a4q0pu5qp22SfaSoEjcwakVAbAgqHSMFrX1LBKmFryA3T2yl2u5r01bS4gQqeX0ecCNjqA19svg_-rF2GtVZX_TNIM-P0GiOHfyqZRP4ZVzN-TNJOsFrIulfpULaCz2g8uZFjb-9TqRopSMi7FxDr5RpW3sb1vw2Cdz_6tgOI1oJ3aE637SJwSPQ2C3hqErP_1tdoP9Xvb-QucdLDY</recordid><startdate>20220925</startdate><enddate>20220925</enddate><creator>Das, Suchismita</creator><creator>Guha, Pokhraj</creator><creator>Nath, Monika</creator><creator>Das, Sandipan</creator><creator>Sen, Surojit</creator><creator>Sahu, Jagajjit</creator><creator>Kopanska, Marta</creator><creator>Dutta, Sulagna</creator><creator>Jamal, Qazi Mohammad Sajid</creator><creator>Kesari, Kavindra Kumar</creator><creator>Sengupta, Pallav</creator><creator>Slama, Petr</creator><creator>Roychoudhury, Shubhadeep</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-5525-708X</orcidid><orcidid>https://orcid.org/0000-0002-2926-7281</orcidid><orcidid>https://orcid.org/0000-0001-7468-5696</orcidid><orcidid>https://orcid.org/0000-0003-4174-1852</orcidid><orcidid>https://orcid.org/0000-0003-3936-0698</orcidid><orcidid>https://orcid.org/0000-0003-0570-259X</orcidid><orcidid>https://orcid.org/0000-0003-3622-9555</orcidid><orcidid>https://orcid.org/0000-0002-7893-5282</orcidid><orcidid>https://orcid.org/0000-0002-1928-5048</orcidid></search><sort><creationdate>20220925</creationdate><title>A Comparative Cross-Platform Analysis to Identify Potential Biomarker Genes for Evaluation of Teratozoospermia and Azoospermia</title><author>Das, Suchismita ; Guha, Pokhraj ; Nath, Monika ; Das, Sandipan ; Sen, Surojit ; Sahu, Jagajjit ; Kopanska, Marta ; Dutta, Sulagna ; Jamal, Qazi Mohammad Sajid ; Kesari, Kavindra Kumar ; Sengupta, Pallav ; Slama, Petr ; Roychoudhury, Shubhadeep</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-5ff9eca2a9a28b7223f653db98f2a94c69af0b2a059daaead17d21881d264d873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Azoospermia - diagnosis</topic><topic>Azoospermia - genetics</topic><topic>Biological markers</topic><topic>Biomarkers</topic><topic>Datasets</topic><topic>DNA microarrays</topic><topic>Epigenetics</topic><topic>Evaluation</topic><topic>Gene expression</topic><topic>Genetic aspects</topic><topic>Humans</topic><topic>Identification and classification</topic><topic>Infertility</topic><topic>Infertility, Male</topic><topic>Infertility, Male - genetics</topic><topic>Kinases</topic><topic>Male</topic><topic>Males</topic><topic>Meta-analysis</topic><topic>Protein folding</topic><topic>Proteins</topic><topic>Public health</topic><topic>RNA</topic><topic>Semen - metabolism</topic><topic>Software</topic><topic>Sperm</topic><topic>Spermatogenesis</topic><topic>Statistical power</topic><topic>Teratozoospermia - genetics</topic><topic>Teratozoospermia - metabolism</topic><topic>Testes</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Das, Suchismita</creatorcontrib><creatorcontrib>Guha, Pokhraj</creatorcontrib><creatorcontrib>Nath, Monika</creatorcontrib><creatorcontrib>Das, Sandipan</creatorcontrib><creatorcontrib>Sen, Surojit</creatorcontrib><creatorcontrib>Sahu, Jagajjit</creatorcontrib><creatorcontrib>Kopanska, Marta</creatorcontrib><creatorcontrib>Dutta, Sulagna</creatorcontrib><creatorcontrib>Jamal, Qazi Mohammad Sajid</creatorcontrib><creatorcontrib>Kesari, Kavindra Kumar</creatorcontrib><creatorcontrib>Sengupta, Pallav</creatorcontrib><creatorcontrib>Slama, Petr</creatorcontrib><creatorcontrib>Roychoudhury, Shubhadeep</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Genes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Das, Suchismita</au><au>Guha, Pokhraj</au><au>Nath, Monika</au><au>Das, Sandipan</au><au>Sen, Surojit</au><au>Sahu, Jagajjit</au><au>Kopanska, Marta</au><au>Dutta, Sulagna</au><au>Jamal, Qazi Mohammad Sajid</au><au>Kesari, Kavindra Kumar</au><au>Sengupta, Pallav</au><au>Slama, Petr</au><au>Roychoudhury, Shubhadeep</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Comparative Cross-Platform Analysis to Identify Potential Biomarker Genes for Evaluation of Teratozoospermia and Azoospermia</atitle><jtitle>Genes</jtitle><addtitle>Genes (Basel)</addtitle><date>2022-09-25</date><risdate>2022</risdate><volume>13</volume><issue>10</issue><spage>1721</spage><pages>1721-</pages><issn>2073-4425</issn><eissn>2073-4425</eissn><abstract>Male infertility is a global public health concern. Teratozoospermia is a qualitative anomaly of spermatozoa morphology, contributing significantly to male infertility, whereas azoospermia is the complete absence of spermatozoa in the ejaculate. Thus, there is a serious need for unveiling the common origin and/or connection between both of these diseases, if any. This study aims to identify common potential biomarker genes of these two diseases via an in silico approach using a meta-analysis of microarray data. In this study, a differential expression analysis of genes was performed on four publicly available RNA microarray datasets, two each from teratozoospermia (GSE6872 and GSE6967) and azoospermia (GSE145467 and GSE25518). From the analysis, 118 DEGs were found to be common to teratozoospermia and azoospermia, and, interestingly, sperm autoantigenic protein 17 (
) was found to possess the highest fold change value among all the DEGs (9.471), while coiled-coil domain-containing 90B (
) and coiled-coil domain-containing 91 (
) genes were found to be common among three of analyses, i.e., Network Analyst, ExAtlas, and GEO2R. This observation indicates that
and
genes might have significant roles to play as potential biomarkers for teratozoospermia and azoospermia. Thus, our study opens a new window of research in this area and can provide an important theoretical basis for the diagnosis and treatment of both these diseases.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>36292606</pmid><doi>10.3390/genes13101721</doi><orcidid>https://orcid.org/0000-0001-5525-708X</orcidid><orcidid>https://orcid.org/0000-0002-2926-7281</orcidid><orcidid>https://orcid.org/0000-0001-7468-5696</orcidid><orcidid>https://orcid.org/0000-0003-4174-1852</orcidid><orcidid>https://orcid.org/0000-0003-3936-0698</orcidid><orcidid>https://orcid.org/0000-0003-0570-259X</orcidid><orcidid>https://orcid.org/0000-0003-3622-9555</orcidid><orcidid>https://orcid.org/0000-0002-7893-5282</orcidid><orcidid>https://orcid.org/0000-0002-1928-5048</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Genes, 2022-09, Vol.13 (10), p.1721 |
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| source | MEDLINE; PubMed Central Open Access; MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals; PubMed Central |
| subjects | Azoospermia - diagnosis Azoospermia - genetics Biological markers Biomarkers Datasets DNA microarrays Epigenetics Evaluation Gene expression Genetic aspects Humans Identification and classification Infertility Infertility, Male Infertility, Male - genetics Kinases Male Males Meta-analysis Protein folding Proteins Public health RNA Semen - metabolism Software Sperm Spermatogenesis Statistical power Teratozoospermia - genetics Teratozoospermia - metabolism Testes Variance analysis |
| title | A Comparative Cross-Platform Analysis to Identify Potential Biomarker Genes for Evaluation of Teratozoospermia and Azoospermia |
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