As part of its mission to support the Turner Syndrome (TS) community, the Turner Syndrome Foundation (TSF) spreads awareness of this chromosomal condition. With increased awareness, researchers will have the knowledge to develop new perspectives about TS. As a result, doctors will be able diagnose and treat the patients with TS early enough to help them achieve their full potential. This post examines a new gene-analysis study using bioinformatics to learn how to better diagnose and treat TS.
Purpose of the Bioinformatics Study
A 2020 study conducted in Shanghai, China, used bioinformatic, statistical analysis and data mining techniques to reveal gene patterns that cause TS. The goal was to increase understanding of what causes TS’s challenges. The hope is to develop new insights for how to treat and diagnose TS.
To learn more about the bolded terms related to this study, please refer to the glossary section below.
Researchers from the Shanghai Jiao Tong University School of Medicine’s Ninth People Hospital’s Endocrinology Department included:
- Hao Wang
- Hui Zhu
- Wenjiao Zhu
- Yue Xu
- Nan Wang
- Bing Han
Huaidong Song, from the same hospital’s Research Center for Clinical Medicine, also contributed to the study.
Scope of the Study
The experiment studied 36 biological women. Twenty-six had TS with a missing X chromosome, with most inheriting their remaining X chromosomes from their mother. The other 10 women had all 46 chromosomes.
This work was funded by a grant from the National Natural Science Foundation of China.
How the Study Was Conducted
This study used the following process:
- The researchers took cells from the 36 subjects.
- The research team used public microarray analysis data from Clara M. Cheng and her team from the Eunice Kennedy Shriver National Institute of Child Health and Human Development in Bethesda, Maryland to compare their chromosome patterns with the cell samples’ patterns.
- Gene Expression Omnibus 2R, an online analysis tool, helped with these comparisons.
- Online software known as DAVID Bioinformatics Resources 6.8 then delved deeper into the gene patterns with gene-tissue analysis.
- PPI Network Analysis software then analyzed the genes‘ proteins and their interactions to see how genes cause TS’s challenges.
Results Using Microarray Analysis
Microarray analysis helped the researchers make interesting discoveries, including:
- Analysis of the 36 women’s cells identified 42 genes that had increased expression and 91 genes with decreased expression.
- In Cheng’s public data, 279 genes had increased expression, and 234 genes had decreased expression.
- When combining these two datasets, the researchers discovered 85 genes that had differential expression. It was mostly decreased expression (60 vs. 25).
- Of these 85 genes, 15 were on the X chromosome, involved in controlling crucial cell functions.
- For example, three of the X chromosome‘s less-expressed genes were linked to the immune system’s functioning.
Results of Gene-Tissue Analysis
DAVID gene-tissue analysis helped the researchers make an intriguing discovery. Most of the differentially expressed genes affected the immune system. This is important since as mentioned, some of the X chromosome’s genes are immune-related. As a result, missing an X chromosome could affect the chances of a woman with TS having autoimmune health challenges.
Results of PPI Network Analysis of Gene Proteins
In addition, PPI network analysis of gene proteins helped the researchers make other fascinating revelations, which included:
- MYL9 and MYLF genes, which have proteins connected to skeletal and muscle movement, had differential expression. MYL9’s myosin-light-chain protein controls skeletal and smooth muscles in areas like the heart. MYLPF’s regulatory-light-chain-protein controls striated muscle in the skeleton and heart. This suggests that both may contribute to the heart muscles’ and skeletal system’s functioning. This creates crucial links between these genes and health risks for TS patients, such as aortic coarctation.
- The SHOX gene, which helps the skeleton function, was identified as a differentially expressed gene. The researchers linked it to short stature, which affects many individuals with TS.
- IGFBP2, a gene which helps bones and cartilage protein grow, also had differential expression. Thus, the researchers connected it to bone health challenges that affect patients with TS.
- PPI network analysis also identified two groups of abnormal protein interaction. They consisted of eight genes, with CDC27 and CD99 noted as especially important, since they affect the immune system.
Limitations in the study’s data included the subjects’:
- health conditions, and
- medications used.
Since the information was obtained from a public database, the above factors could not be determined. Therefore, direct links between these factors and gene patterns related to TS could not be made.
The researchers disclosed that they had no conflicts of interest. They suggested that research should continue exploring the relationship between the genes identified in this study and TS.
Importance for the TS Community
This study revealed some of the genes responsible for TS. It also described how these genes may be responsible for challenges faced by many TS patients. This study could help set an essential foundation for possible TS treatments that target the genes.
Supporting the TS community and advocating for TS awareness will help increase opportunities for projects like these. Additionally, it will also help individuals with TS overcome their various health challenges.
If you would like to help promote TS awareness, you can:
- shop for items that help spread TS awareness,
- advocate for increased accommodations and care for the TS community,
- sign TSF’s petition to help advocate for the TS community and for more TS awareness days,
- donate to and/or volunteer to help TSF and its mission,
- organize a fundraiser for TSF’s causes.
- spread TS awareness,
- join TSF’s professional membership to learn how to help the TS community get the medical services they need and support them,
- join TSF’s education committee, check out TSF’s resources to learn more about TS and how to support students with TS, and/or
- participate in TS research or collaborate with TSF for your research project in support of the TS community.
- Aortic coarctation: a birth defect in which a part of the aorta is narrower than usual; can require surgery if the narrowing is severe
- Autoimmune: the body’s reaction against its own immune system; in cases of immune system overactivity, the body attacks and damages its own tissues
- Bioinformatics: the science of collecting and analyzing complex biological data, such as genetic codes
- Cartilage: tissue that’s tough, linked together, and has no blood or nerves running through it
- Chromosome: DNA packages found in the cells’ centers, or nuclei
- DAVID Bioinformatics Resources: a collection of software tools that aims to provide functional interpretation of large lists of genes derived from genomic studies
- Differential expression: DNA sections in genes being used more (increased) or less (decreased) than normal
- DNA: the building blocks of cells, which controls parts of the body and is made of chemicals, sugars, and phosphates
- Expression: DNA sections being used for cell function
- Gene: sections of DNA within chromosomes that control the body’s cells
- Gene-tissue analysis: a technique used to understand how genes affect how body tissue function
- Microarray analysis: a technique used to analyze gene expression
- PPI Network Analysis: a method used to analyze how gene protein chains and their interactions with each other affect the body
- Proteins: chemical-compounds made of amino-acid molecule chains that are found within genes and affect cell function
- Smooth Muscles:long, top-shaped muscles that are found in organs like the digestive system and heart
- Striated muscles: band-shaped muscles that are found in organs such as the skeleton (think Twizzlers)
- Tissue: cell groups that collaborate to help an organ function
- X Chromosome: a type of chromosome that usually exists in pairs in each cell in females. Women with TS have only one X, one incomplete X, or a combination of both.
Takeaways & Action Steps
- Researchers from Shanghai wanted to expand TS treatments by conducting this bioinformatic analysis study.
- They identified some genes whose differential expression causes challenges for patients with TS, such as short stature and aortic coarctation.
- This study has helped lay the foundation for therapies targeting the genes identified.
- If this article has motivated you to help TSF’s cause, there are a variety of ways you can spread awareness and advocate for the TS community. A few include educating others about TS, joining our professional membership, and signing out Petition for Patient Care.
Written by Ruchika Srivastava, TSF volunteer blog writer and editor. Edited by Prabhat Sharma, TSF volunteer blog editor, and Susan Herman, TSF volunteer lead blog editor.
© Turner Syndrome Foundation, 2021