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RNA Sequencing: A New Hope for Genetic Disorders

RNA sequencing sheds light on genetic disorders, enhancing diagnosis and treatment possibilities.

Huayun Hou, Kyoko E. Yuki, Gregory Costain, Anna Szuto, Sierra Barnes, Arun K. Ramani, Alper Celik, Michael Braga, Meagan Gloven-Brown, Dimitri J. Stavropoulos, Sarah Bowdin, Ronald D Cohn, Roberto Mendoza-Londono, Stephen W. Scherer, Michael Brudno, Christian R. Marshall, M. Stephen Meyn, Adam Shlien, James J. Dowling, Michael D. Wilson, Lianna Kyriakopoulou

― 6 min read


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Genetic Disorders occur when there is a change in a person's DNA that impacts their health. These changes, known as genetic variants, can lead to various conditions, some of which can be quite serious. Diagnosing these disorders can be challenging, as not every genetic variant leads to an obvious condition. Many people with suspected genetic disorders remain undiagnosed, leaving them and their families with unanswered questions.

Exome and Genome Sequencing

In recent years, technologies like exome and genome sequencing have become essential tools in identifying genetic variants. Exome sequencing focuses on the parts of the DNA that code for proteins, while genome sequencing looks at the entire DNA sequence. These methods have improved our ability to find genetic causes for many disorders. However, even with these advancements, over half of individuals with genetic issues still do not receive a clear diagnosis. This is partly because we don’t fully understand what many genetic changes do in the body.

The Potential of RNA Sequencing

To help with diagnoses, RNA sequencing (RNA-seq) has emerged. This technique looks at the RNA produced by genes, shedding light on how genetic changes might affect gene activity and protein production. RNA-seq can uncover important changes in Gene Expression and Splicing, which are vital for diagnosing genetic disorders. Splicing is the process by which certain parts of the gene are included or excluded in the final RNA product. Significant changes in splicing can lead to disorders, much like a recipe being mishandled can ruin a dish.

Success Stories and Diagnostic Rates

Several studies have shown that RNA-seq can improve diagnostic rates in people with rare diseases. For example, researchers found that RNA-seq conducted on muscle biopsies helped diagnose around 35% of individuals with neuromuscular disorders. In another instance, RNA-seq using skin cells provided a diagnosis for about 10-16% of individuals with mitochondrial diseases.

Moreover, there was a study where RNA-seq of blood samples increased the diagnostic rate by 7.5% in a diverse group of patients with suspected rare diseases. These results suggest that RNA-seq can be a powerful addition to the toolkit for diagnosing genetic disorders.

The Study Design

In a recent investigation, researchers aimed to see how RNA-seq could help clarify genetic diagnoses obtained from genome sequencing. They collected blood samples from children with suspected genetic disorders and conducted RNA-seq to analyze the RNA content. This study was conducted at a leading children's hospital, where many families sought answers for their children's genetic conditions.

The children participating in the study had various complex symptoms, including developmental delays, seizures, and congenital abnormalities. Many had already undergone standard genetic testing without conclusive results.

Sample Collection and Processing

The researchers gathered samples from a well-defined group of children. They ensured that each participant had a thorough medical history and that their symptoms were accurately recorded. The samples went through careful processing to extract RNA, which involved using specialized kits to ensure the quality of the data obtained.

The RNA was then prepared for sequencing. This is akin to preparing ingredients for a big family dinner – the better you prepare, the better the meal will turn out! The researchers took great care in creating the RNA libraries to minimize variability and ensure reliable results.

Analyzing the Results

After sequencing the RNA from each sample, the researchers used a set of computational tools to analyze the data. They looked at gene expression levels and splicing patterns, aiming to identify any unusual changes that could point to a genetic disorder.

The analysis involved comparing the RNA data from each sample against a reference dataset to spot differences. This process is similar to checking your outfit with a fashion guide to see if it matches or clashes.

Key Findings in Diagnosed Cases

For the cases with already identified genetic variants, the RNA sequencing revealed additional insights. In many instances, the variants affected how genes were expressed or spliced. In plain terms, the genetic changes were not just present; they were having a real impact on the body.

Some patients showed reduced expression of key genes associated with their conditions. Others had unexpected splicing events, indicating that the usual process of forming RNA was disrupted. These revelations provided essential information that could confirm or refine the initial diagnoses the children had been given.

Discovering Potential Candidate Genes

In addition to confirming existing diagnoses, RNA-seq helped identify potential candidate genes in children who had not received a diagnosis from earlier testing. Of the participants still in search of answers, the researchers found promising candidate genes linked to their clinical symptoms in several cases.

This was like finding a missing puzzle piece that could finally complete the picture of their health. Although not every child received a definitive answer, the ability to highlight potential genetic causes provides a valuable direction for future testing.

Technical Challenges and Considerations

Despite the promising findings, the study also highlighted challenges in using RNA-seq in clinical settings. One major issue is that blood may not always be the best tissue for detecting certain genetic changes, especially if the disorder primarily affects other tissues. This could lead to missed or inaccurate results, similar to trying to measure the aroma of a dish from a distance – you may not get the full picture!

Moreover, the analysis of RNA data can be complicated, and subtle differences in results can occur based on the methods used. The researchers emphasized the importance of having well-matched control groups and consistent processing techniques to mitigate these issues.

Implications for Future Research

The findings from this research underscore the potential of RNA-seq in advancing our understanding of genetic disorders. By combining RNA-seq with traditional genomic analyses, healthcare providers may increase diagnostic rates and offer more precise information about genetic variants' effects.

This could lead to more tailored treatments for individuals with genetic disorders, much like customizing a dish to suit someone's specific taste. The study also highlighted the need for more pediatric RNA-seq data to help refine the understanding of how genetic changes affect health.

Conclusion

RNA sequencing has shown great promise as an effective tool in diagnosing genetic disorders. By providing detailed insights into gene expression and splicing, RNA-seq can complement traditional genomic testing and help clarify uncertainties.

While challenges still exist, such as tissue selection and data analysis, the potential benefits of incorporating RNA-seq into clinical practice are compelling. It offers hope to families seeking answers for their loved ones, as the science of genetics continues to evolve.

The road ahead may be tricky, but with tools like RNA sequencing, the journey toward understanding genetic disorders is becoming clearer. Just remember, every twist and turn on this path contributes to the overall story of each child’s health journey.

Original Source

Title: Assessing the diagnostic impact of blood transcriptome profiling in a pediatric cohort previously assessed by genome sequencing

Abstract: Despite advances in diagnostic testing and genome sequencing, the majority of individuals with rare genetic disorders remain undiagnosed. As a complement to genome sequencing, transcriptional profiling can provide insight into the functional consequences of DNA variants on RNA transcript expression and structure. Here we assessed the utility of blood derived RNA-seq in a well-studied, but still mostly undiagnosed, cohort of individuals who enrolled in the SickKids Genome Clinic study. This cohort was established to benchmark the ability of genome sequencing technologies to diagnose genetic diseases and has been subjected to multiple analyses. We used RNA-seq to profile whole blood RNA expression from all probands for whom a blood sample was available (n=134). Our RNA-centric analysis included differential gene expression, alternative splicing, and allele specific expression. In one third of the diagnosed individuals (20/61), RNA-seq provided additional evidence supporting the pathogenicity of the variant found by prior DNA-based analyses. In 2/61 cases, RNA-seq changed the GS-derived genetic diagnosis (EPG5 to LZTR1 in an individual with a Noonan syndrome-like disorder) and discovered an additional relevant gene (CEP120 in addition to SON in an individual with ZTTK syndrome). In [~]7% (5/73) of the undiagnosed participants, RNA-seq provided at least one plausible, potentially diagnostic candidate gene. This study illustrates the benefits and limitations of using whole-blood RNA profiling to support existing molecular diagnoses and reveal candidate molecular mechanisms underlying undiagnosed genetic disease.

Authors: Huayun Hou, Kyoko E. Yuki, Gregory Costain, Anna Szuto, Sierra Barnes, Arun K. Ramani, Alper Celik, Michael Braga, Meagan Gloven-Brown, Dimitri J. Stavropoulos, Sarah Bowdin, Ronald D Cohn, Roberto Mendoza-Londono, Stephen W. Scherer, Michael Brudno, Christian R. Marshall, M. Stephen Meyn, Adam Shlien, James J. Dowling, Michael D. Wilson, Lianna Kyriakopoulou

Last Update: 2024-12-05 00:00:00

Language: English

Source URL: https://www.medrxiv.org/content/10.1101/2024.12.03.24317221

Source PDF: https://www.medrxiv.org/content/10.1101/2024.12.03.24317221.full.pdf

Licence: https://creativecommons.org/licenses/by-nc/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to medrxiv for use of its open access interoperability.

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