Evidence map›Paper›PMID 32959501›Full record

ArticleMolecular genetics & genomic medicine2020

Identification of common differentially expressed genes in Turner (45,X) and Klinefelter (47,XXY) syndromes using bioinformatics analysis.

María Carolina Manotas, Juan Camilo Calderón, Liliana López-Kleine, Fernando Suárez-Obando, Olga M Moreno, Adriana Rojas

Open access · goldAbstract read
In one paragraph

Article in Molecular genetics & genomic medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 17% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Non-mosaic Klinefelter syndrome with high sperm count: rewriting the textbooks.Journal of assisted reproduction and genetics · 2025
    Article
  4. Article
  5. Article
  6. A Review of Recent Developments in Turner Syndrome Research.Journal of cardiovascular development and disease · 2021
    Review
  7. Observational
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

María Carolina ManotasInstitute of Human Genetics. Faculty of Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia.ORCID 0000-0002-4900-4948
Juan Camilo CalderónDepartment of Statistics, Faculty of Science, Universidad Nacional de Colombia, Ciudad Universitaria, Bogotá, Colombia.ORCID 0000-0002-3433-272X
Liliana López-KleineDepartment of Statistics, Faculty of Science, Universidad Nacional de Colombia, Ciudad Universitaria, Bogotá, Colombia.ORCID 0000-0001-9325-9529
Fernando Suárez-ObandoInstitute of Human Genetics. Faculty of Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia.ORCID 0000-0003-1005-2210
Olga M MorenoInstitute of Human Genetics. Faculty of Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia.ORCID 0000-0002-0826-6191
Adriana RojasInstitute of Human Genetics. Faculty of Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia.ORCID 0000-0001-8528-4433
Pontificia Universidad Javeriana · COUniversidad Nacional de Colombia · CO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnalysis of patients with chromosomal abnormalities, including Turner syndrome and Klinefelter syndrome, has highlighted the importance of X-linked gene dosage as a contributing factor for disease susceptibility. Escape from X-inactivation and X-linked imprinting can result in transcriptional differences between normal men and women as well as in patients with sex chromosome abnormalities.

objectiveTo identify differentially expressed genes among patients with Turner (45,X) and Klinefelter (46,XXY) syndrome using bioinformatics analysis. METHODOLOGY: Two gene expression data sets of Turner (45,X) and Klinefelter syndrome (47,XXY) were obtained from the Gene Omnibus Expression (GEO) database of the National Center for Biotechnology Information (NCBI). Statistical analysis was performed using R Bioconductor libraries. Differentially expressed genes (DEGs) were determined using significance analysis of microarray (SAM). The functional annotation of the DEGs was performed with DAVID v6.8 (The Database for Annotation, Visualization, and Integrated Discovery).

resultsThere are no genes over-expressed simultaneously in both diseases. However, when crossing the list of under-expressed genes for 45,X cells and the list of over-expressed genes for 47,XXY cells, there are 16 common genes: SLC25A6, AKAP17A, ASMTL, KDM5C, KDM6A, ATRX, CSF2RA, DHRSX, CD99, ZBED1, EIF1AX, MVB12B, SMC1A, P2RY8, DOCK7, DDX3X, eight of which are involved in the regulation of gene expression by epigenetic mechanisms, regulation of splicing processes and protein synthesis.

conclusionOf the 16 identified as under-expressed in 45,X cells and over-expressed in 47,XXY cells, 14 are located in X chromosome and 2 in autosomal chromosome; 8 of these genes are involved in the regulation of gene expression: 5 genes are related to epigenetic mechanisms, 2 in regulation of splicing processes, and 1 in the protein synthesis process. Our results are limited by it being the product of a bioinformatic analysis from mRNA isolated from whole blood, this makes necessary further exploration of the relationships between these genes and Turner syndrome and Klinefelter syndrome in the future.

Indexed as

TranscriptomeChromatin Assembly and DisassemblyDNA MethylationEpigenesis, GeneticGene Expression ProfilingGenetic LociHumansKlinefelter SyndromeRNA SplicingTurner SyndromeUp-Regulation

Identifiers

PMID32959501
PMCPMC7667333
OpenAlexW3087169375

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.