<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Yan Q</submitter><funding>the Jiangsu Province Science and Technology support Plan</funding><funding>the Nature Science Foundation of China</funding><pagination>582S-591S</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8804785</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>13(2_suppl)</volume><pubmed_abstract>&lt;h4>Objective&lt;/h4>To find out the pathways and key genes and to reveal disc degeneration pathogenesis based on bioinformatic analyses.&lt;h4>Design&lt;/h4>The GSE70362 dataset was downloaded from the GEO (Gene Expression Omnibus) database. Differentially expressed genes (DEGs) between the patients having disc degeneration and healthy controls were screened by Limma package in R language. Critical genes were identified by adopting gene ontologies (GOs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks.&lt;h4>Results&lt;/h4>We identified 112 DEGs, including 60 genes which were upregulated and 52 that were downregulated. Analyses, such as GO and KEGG demonstrated that the DEGs got enriched in 4 biological processes and 2 signaling pathways, mainly re</pubmed_abstract><journal>Cartilage</journal><pubmed_title>Bioinformatics-Based Research on Key Genes and Pathways of Intervertebral Disc Degeneration.</pubmed_title><pmcid>PMC8804785</pmcid><funding_grant_id>BE2019669</funding_grant_id><funding_grant_id>81672220</funding_grant_id><pubmed_authors>Yang H</pubmed_authors><pubmed_authors>Zou J</pubmed_authors><pubmed_authors>Yan Q</pubmed_authors><pubmed_authors>Wu C</pubmed_authors><pubmed_authors>Ge J</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors><pubmed_authors>Yu H</pubmed_authors><pubmed_authors>Xiao Q</pubmed_authors></additional><is_claimable>false</is_claimable><name>Bioinformatics-Based Research on Key Genes and Pathways of Intervertebral Disc Degeneration.</name><description>&lt;h4>Objective&lt;/h4>To find out the pathways and key genes and to reveal disc degeneration pathogenesis based on bioinformatic analyses.&lt;h4>Design&lt;/h4>The GSE70362 dataset was downloaded from the GEO (Gene Expression Omnibus) database. Differentially expressed genes (DEGs) between the patients having disc degeneration and healthy controls were screened by Limma package in R language. Critical genes were identified by adopting gene ontologies (GOs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks.&lt;h4>Results&lt;/h4>We identified 112 DEGs, including 60 genes which were upregulated and 52 that were downregulated. Analyses, such as GO and KEGG demonstrated that the DEGs got enriched in 4 biological processes and 2 signaling pathways, mainly re</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Dec</publication><modification>2025-04-19T10:51:06.375Z</modification><creation>2025-04-19T10:51:06.375Z</creation></dates><accession>S-EPMC8804785</accession><cross_references><pubmed>33233925</pubmed><doi>10.1177/1947603520973247</doi></cross_references></HashMap>