ArticleAmerican journal of translational research2023
Up-regulated and hypomethylated genes are causative factors and diagnostic markers of osteoporosis.
Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDue to the lack of sensitive diagnostic biomarkers for osteoporosis (OP), there is an urgent need to identify and uncover biomarkers associated with the disease in order to facilitate early clinical diagnosis and effective intervention strategies.
methodsGEO2R was employed to conduct a screening of differentially expressed genes (DEGs) within the transcriptome sequencing data obtained from blood samples of OP patients within the GSE163849 dataset. Subsequently, we conducted expression confirmation of the identified DEGs using an additional dataset, GSE35959. To further explore Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, MicroRNA (miRNA) interactions, and drug predictions, we employed the DAVID, miRTarBase, and DrugBank databases. For validation purposes, clinical OP samples paired with normal controls were collected from the Pakistani population. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was employed to assess the expression levels of DEGs and miRNA, while targeted bisulfite sequencing (bisulfite-seq) analysis was used to investigate methylation patterns. DNA and RNA from clinical OP and normal control samples were extracted using appropriate methods.
resultsOut of total identified 269 DEGs, EGFR (epidermal growth factor receptor), HMOX1 (heme oxygenase-1), PGR (progesterone receptor), CXCL10 (C-X-C motif chemokine ligand 10), CCL5 (C-C motif chemokine ligand 5), and IL12B (interleukin 12B) were prioritized as top DEGs in OP patients. Expression validation of these genes on additional Gene Expression Omnibus (GEO) dataset and Pakistani OP patients revealed consistent significant up-regulation of these genes in OP patients. Receiver operating characteristic (ROC) analysis demonstrated that these DEGs displayed considerable diagnostic accuracy for detecting OP. Targeted bisulfite-seq analysis further revealed that EGFR, HMOX1, PGR, CXCL10, CCL5, and IL12B were hypomethylated in OP patients. Moreover, has-miR-27a-5p, a common expression regulator of the EGFR, HMOX1, PGR, CXCL10, CCL5, and IL12B was also significantly down-regulated in OP patients.
conclusionThe DEGs that have been identified hold significant potential for the future development of diagnostic and treatment approaches for OP in preclinical and clinical applications.
Indexed as
Identifiers
37969207PMC10641362W4388737083What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.