Developmental Biology - Genetic Disorders|
Linking 28 Genes to Developmental Disorders
Researchers estimate another 1,000 genes are still to be found that can be linked to developmental disorders...
Research into causes of developmental disorders has identified 285 genes linked to such conditions, including 28 newly-associated genes. Published 14 October 2020, in Nature, the study by researchers located at the Wellcome Sanger Institute, Radboud University Medical Center, OPKO Health's GeneDx, along with other collaborators — will enable diagnoses for around 500 families living with children with these rare conditions.
Researchers collated healthcare and research data from health records where identifying personal details were removed, to create the largest available genetic resource for developmental disorders.
Analysis of the data estimates around 1,000 genes linked to such disorders still remain to be discovered. Finding them all will require ten times the amount of data currently available, which will only be possible with more open access to healthcare records.
Globally, around 400,000 babies are born every year with new and spontaneous DNA changes - known as de novo mutations. De novo mutations are not carried by either parent, but interfere with their child's development. These developmental disorders can lead to conditions such as intellectual disability, epilepsy, autism or heart defects.
De novo mutations in genes that create proteins are well-established causes of developmental disorders, and can take place in the sperm or egg, and are subsequently passed to the child. But, to date many genes linked to these disorders remain unknown.
Although every person is born with around 60 de novo mutations on average, the vast majority do not lead to health problems.
Ongoing initiatives, such as the Deciphering Developmental Disorders (DDD) study, have discovered associated genes by looking for patterns in genomes of people with these disorders. But as many conditions are extremely rare, statistical analysis to locate these genes requires large volumes of anonymised patient data which has not always been easily accessible.
For this study, researchers analysed 31,058 exome sequence 'trios'. Each trio includes sequences from the child and each parent.
The sample was created by combining existing research and clinical datasets from the Wellcome Sanger Institute, Radboud University Medical Center and GeneDx.
The scale of the dataset greatly increased the statistical power available to search for previously undiscovered mutations. The authors then used an improved statistical test to determine whether individuals in the study had more mutations in the same gene than they would expect to occur by chance.
"From previous studies we know certain genes and types of mutation are more strongly linked to developmental disorders, allowing us to narrow our search. Combined with a much larger dataset, we were able to identify 28 novel genes associated with developmental disorders."
Kaitlin Samocha PhD, the Wellcome Sanger Institute and first author on the paper.
"Caring for a child with a developmental disorder can be extremely challenging for a family, particularly when the child's doctors don't know what is causing their condition and is unable to make a diagnosis. A diagnosis can help families access support networks, inform treatment for their child and understand the risk for any further children they might have."
Helen Firth PhD, Consultant Clinical Geneticist at Addenbrooke's Hospital.
The study also applied statistical modelling to the data to estimate that approximately 1,000 more development disorder-associated genes remain undiscovered. Around 60 per cent of children born with a disorder do not have a diagnosis. The authors estimate around 50 per cent of these children will have a mutation in one of these unknown genes.
"This study has really shown the benefits of access to healthcare data, not least to the approximately 500 families living with a developmental disorder who had not been able to get a diagnosis until now. But our findings also estimate that we require ten times as much data to be able to identify all the genes linked to developmental disorders. As such, greater access to anonymised patient data is crucial to our understanding of these conditions and our ability to help the families living with them."
Matthew Hurles PhD, the Wellcome Sanger Institute and lead author of the study.
"As a global leader in clinical exome sequencing and rare disease diagnostics, GeneDx is committed to helping end the diagnostic odyssey not only through diagnostic testing but through collaborative research projects like this one. By combining data and efforts across institutions, we are able to provide more patients and families with answers."
Kyle Retterer, Senior Vice President, Chief Technology Officer, and lead author of the study from GeneDx.
De novo mutations in protein-coding genes are a well-established cause of developmental disorders1. However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations1, 2. Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent–offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders.
Joanna Kaplanis, Kaitlin E. Samocha, Laurens Wiel, Zhancheng Zhang, Kevin J. Arvai, Ruth Y. Eberhardt, Giuseppe Gallone, Stefan H. Lelieveld, Hilary C. Martin, Jeremy F. McRae, Patrick J. Short, Rebecca I. Torene, Elke de Boer, Petr Danecek, Eugene J. Gardner, Ni Huang, Jenny Lord, Iñigo Martincorena, Rolph Pfundt, Margot R. F. Reijnders, Alison Yeung, Helger G. Yntema, Deciphering Developmental Disorders Study, Lisenka E. L. M. Vissers, Jane Juusola, Caroline F. Wright, Han G. Brunner, Helen V. Firth, David R. FitzPatrick, Jeffrey C. Barrett, Matthew E. Hurles, Christian Gilissen and Kyle Retterer
The authors thank the families and their clinicians for their participation and engagement, and our colleagues who assisted in the generation and processing of data. Inclusion of RadboudUMC data was in part supported by the Solve-RD project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 779257. This work was in part financially supported by grants from the Netherlands Organization for Scientific Research (917-17-353 to C.G.). The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003). This study makes use of DECIPHER, which is funded by the Wellcome Trust. The full acknowledgements can be found at www.ddduk.org/access.html. The DDD study authors acknowledges the work of R. Kelsell. Finally, we acknowledge the contribution of an esteemed DDD clinical collaborator, M. Bitner-Glindicz, who died during the course of the study.
About Greenwood Genetic Center
The Greenwood Genetic Center (GGC), founded in 1974, is a nonprofit organization advancing the field of medical genetics and caring for families impacted by genetic disease and birth defects. At its home campus in Greenwood, South Carolina, a talented team of physicians and scientists provides clinical genetic services, diagnostic laboratory testing, educational programs and resources, and research in the field of medical genetics. GGC's faculty and staff are committed to the goal of developing preventive and curative therapies for the individuals and families they serve. GGC extends its reach as a resource to all residents of South Carolina with satellite offices in Charleston, Columbia, Florence, and Greenville. For more information about GGC please visit http://www.ggc.org.
The authors would like to thank Brian Kwan for his early contributions and help generating the gnptab-KO line. This work was supported by an R01 to RS from the NIHGMS GM086524, grants to HFS from the National MPS Society and the ISMRD, as well as a grant to RS by the Yash Ghandi Foundation. We would also like to thank Matthew Bogyo (Stanford University) for contributing the BMV109 and BMV157 probes used in this study. We would like to thank Koichi Kawakami and Yoshiko Takahashi (National Institute of Genetics, Japan) for providing the TOL2 transgenesis constructs (MTA K2019-055) (68). Additionally, we are grateful to Andrei Alexandrov (Clemson Center for Human Genetics) for his expert assistance with FAC sorting of zebrafish cells. We would also like to acknowledge that much of the zebrafish work related to this study was performed on animals raised in the Hazel and Bill Allin Aquaculture Facility housed at the Greenwood Genetic Center. We thank the staff of the facility for their excellent animal care and husbandry.
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Oct 20 2020 Fetal Timeline Maternal Timeline News
Analysis of the data estimates around 1,000 genes linked to developmental
disorders remain to be discovered. CREDIT Public Domain.