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Genetic Factors in Developmental Disorders

Research uncovers genetic links to developmental disorders across diverse ancestry groups.

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Understanding genetic disorders is a complex and important area of research. Developmental disorders (DD) are a group of conditions that affect how a child grows and develops. Finding the genetic causes of these disorders can help in diagnosing and treating affected individuals. Recent advances in technology have made it easier to investigate these genetic causes. This text discusses how researchers are analyzing genetic information from many families to learn more about DDs.

Genetic Sequencing

Genetic sequencing is a method that allows scientists to read the DNA of individuals. High-throughput exome and genome sequencing have allowed for faster and more efficient analysis compared to traditional methods. Through these techniques, researchers can examine the genetic material of many patients at once, often leading to the identification of genetic variants linked to specific disorders. This is especially useful in understanding developmental disorders, where about 30-40% of patients can receive a genetic diagnosis.

Gene Discovery

Researchers have been able to discover multiple new genes associated with developmental disorders. By analyzing large groups of patients, scientists can use statistical methods to identify specific genetic changes that occur more frequently in individuals with these disorders. For example, a study that combined data from over 30,000 families found twenty-eight new genes likely responsible for DDs. This approach is more effective than older methods that often focused on small groups of patients, as it allows researchers to consider a wider range of genetic variations.

The Role of Ancestry

The genetic makeup of individuals can vary widely based on their ancestry. Studies have shown that the genetic causes of developmental disorders differ among various ancestry groups. This variation can be due in part to the level of consanguinity, which is the genetic relatedness of individuals within a population. For instance, researchers analyzed data from over 6,000 patients and found significant differences in the contribution of recessive genetic changes between European and Pakistani ancestry groups.

Research Findings

In a large study involving nearly 30,000 families, researchers combined genetic data from two major sources. By focusing on groups defined by their genetic ancestry, they aimed to identify the recessive genetic factors contributing to developmental disorders. About 20% of the participants came from non-European Ancestries. This research analyzed which genetic variants were associated with DDs and how these variants compared across different ancestry groups.

Participant Selection

The researchers looked at deidentified genetic data from multiple patient cohorts, ensuring that individuals included in the analysis had relevant medical histories. While there were some differences in reported clinical characteristics between the datasets, both groups had a variety of symptoms and similar levels of genetic mutations. This made it easier to combine the datasets for further analysis.

Attributable Fraction

The study estimated the contribution of recessive genetic variants to developmental disorders in different ancestry groups, looking closely at known disease-causing genes. The researchers calculated the "attributable fraction," which represents the percentage of patients who could potentially have their condition explained by genetic factors. Different ancestry groups showed varying attributable fractions, with some groups having a much higher percentage of potential genetic explanations compared to others.

Analyzing Genetic Variants

To analyze the recessive burden across different ancestry groups, the researchers compared the observed genetic changes to those expected based on known genetic frequencies. They used various classifications of genetic changes, including those that are likely to cause harm to the individual. The results indicated that the majority of the recessive genetic burden could be traced back to known disease-associated genes.

Known Genes and New Findings

Among the findings, a significant portion of the genetic burden in known disease-associated genes remained unexplained by current classifications of variants in genetic databases. For instance, many variants present in patients were not recorded as pathogenic, which suggests that there may be many more undiagnosed cases linked to known genes. The researchers identified several new genes with compelling evidence for being involved in developmental disorders, indicating the ongoing need for further investigation.

Challenges in Interpretation

Despite the advances in technology, interpreting genetic variants remains challenging. Many variants are categorized as "variants of uncertain significance," which complicates the diagnosis and treatment of patients. The study highlighted the need for better classification methods to distinguish between harmful variants and those that do not have significant effects. This is particularly important for improving genetic counseling and the overall diagnosis process.

Conclusion

This extensive research work sheds light on the complex nature of genetic contributions to developmental disorders. By combining data from different ancestry groups, the researchers were able to identify which genetic variants are more likely to cause these disorders. The findings underscore the importance of understanding genetic diversity and the role of known genes in diagnosing developmental conditions. As researchers continue to analyze vast amounts of genetic information, there is hope that they will find new ways to help affected individuals and families.

Future studies will need to focus on refining the interpretation of genetic variants and exploring the role of less common genes. This ensures that patients receive the most accurate diagnoses and appropriate care, which is essential as our understanding of genetic disorders evolves.

Original Source

Title: Federated analysis of the contribution of recessive coding variants to 29,745 developmental disorder patients from diverse populations

Abstract: Autosomal recessive (AR) coding variants are a well-known cause of rare disorders. We quantified the contribution of these variants to developmental disorders (DDs) in the largest and most ancestrally diverse sample to date, comprising 29,745 trios from the Deciphering Developmental Disorders (DDD) study and the genetic diagnostics company GeneDx, of whom 20.4% have genetically-inferred non-European ancestries. The estimated fraction of patients attributable to exome-wide AR coding variants ranged from [~]2% to [~]18% across genetically-inferred ancestry groups, and was significantly correlated with the average autozygosity (r=0.99, p=5x10-6). Established AR DD-associated (ARDD) genes explained 90% of the total AR coding burden, and this was not significantly different between probands with genetically-inferred European versus non-European ancestries. Approximately half the burden in these established genes was explained by variants not already reported as pathogenic in ClinVar. We estimated that [~]1% of undiagnosed patients in both cohorts were attributable to damaging biallelic genotypes involving missense variants in established ARDD genes, highlighting the challenge in interpreting these. By testing for gene-specific enrichment of damaging biallelic genotypes, we identified two novel ARDD genes passing Bonferroni correction, KBTBD2 (p=1x10-7) and CRELD1 (p=9x10-8). Several other novel or recently-reported candidate genes were identified at a more lenient 5% false-discovery rate, including ZDHHC16 and HECTD4. This study expands our understanding of the genetic architecture of DDs across diverse genetically-inferred ancestry groups and suggests that improving strategies for interpreting missense variants in known ARDD genes may allow us to diagnose more patients than discovering the remaining genes.

Authors: Hilary C Martin, V. K. Chundru, Z. Zhang, K. Walter, S. Lindsay, P. Danecek, R. Y. Eberhardt, E. J. Gardner, D. S. Malawsky, E. M. Wigdor, R. Torene, K. Retterer, C. F. Wright, K. McWalter, E. Sheridan, H. V. Firth, M. E. Hurles, K. E. Samocha, V. D. Ustach

Last Update: 2023-07-24 00:00:00

Language: English

Source URL: https://www.medrxiv.org/content/10.1101/2023.07.24.23293070

Source PDF: https://www.medrxiv.org/content/10.1101/2023.07.24.23293070.full.pdf

Licence: https://creativecommons.org/licenses/by/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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