Phenotypic and molecular characterisation of CDK13-related congenital heart defects, dysmorphic facial features and intellectual developmental disorders

Background: De novo missense variants in CDK13 have been described as the cause of syndromic congenital heart defects in seven individuals ascertained from a large congenital cardiovascular malformations cohort. We aimed to further define the phenotypic and molecular spectrum of this newly described disorder. Methods: To minimise ascertainment bias, we recruited nine additional individuals with CDK13 pathogenic variants from clinical and research exome laboratory sequencing cohorts. Each individual underwent dysmorphology exam and comprehensive medical history review. Results: We demonstrate greater than expected phenotypic heterogeneity, including 33% (3/9) of individuals without structural heart disease on echocardiogram. There was a high penetrance for a unique constellation of facial dysmorphism and global developmental delay, as well as less frequently seen renal and sacral anomalies. Two individuals had novel CDK13 variants (p.Asn842Asp, p.Lys734Glu), while the remaining seven unrelated individuals had a recurrent, previously published p.Asn842Ser variant. Summary of all variants published to date demonstrates apparent restriction of pathogenic variants to the protein kinase domain with clustering in the ATP and magnesium binding sites. Conclusions: Here we provide detailed phenotypic and molecular characterisation of individuals with pathogenic variants in CDK13 and propose management guidelines based upon the estimated prevalence of anomalies identified. Keywords: CDK13, CHDFIDD, De novo variant, Neurodevelopmental disorders, Agenesis of the corpus callosum, Hypertelorism, Developmental delay, Cyclin-dependent kinase, Undiagnosed Diseases Networ

Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities

Laboratory evaluation of patients with developmental delay/intellectual disability, congenital anomalies, and dysmorphic features has changed significantly in the last several years with the introduction of microarray technologies. Using these techniques, a patient’s genome can be examined for gains or losses of genetic material too small to be detected by standard G-banded chromosome studies. This increased resolution of microarray technology over conventional cytogenetic analysis allows for identification of chromosomal imbalances with greater precision, accuracy, and technical sensitivity. A variety of array-based platforms are now available for use in clinical practice, and utilization strategies are evolving. Thus, a review of the utility and limitations of these techniques and recommendations regarding present and future application in the clinical setting are presented in this study

Student perceptions of knowledge about genetics and personal genome testing.

a<p>The number (and percentage) of subjects who agreed or strongly agreed with each statement is reported.</p>b<p>Wilcoxon signed-rank test comparing pre- to post-course responses.</p>c<p>Mann-Whitney <i>U</i>-test comparing post-course responses between genotyped and non-genotyped groups.</p

Student reflection on genotyping offer and experience.

a<p>The number (and percentage) of subjects who agreed or strongly agreed with each statement is reported.</p>b<p>Mann-Whitney <i>U</i>-test comparing post-course responses between genotyped and non-genotyped groups.</p

Student attitudes toward personal genome testing.

a<p>For yes/no questions, the number (and percentage) of subjects responding yes is reported. For Likert items, the number (and percentage) of subjects who agreed or strongly agreed with the statement is reported.</p>b<p>McNemar's test for binary response questions and Wilcoxon signed-rank test for Likert-scale items comparing pre- to post-course responses.</p>c<p>Fisher's exact test for binary response questions and Mann-Whitney <i>U</i>-test for Likert-scale items comparing post-course responses between genotyped and non-genotyped groups.</p

Student scores assessing knowledge of genomics.

<p>Knowledge scores of non-genotyped students on the post-course survey compared to the pre-course survey improved by an average of 1% (46% to 47%), while genotyped students demonstrated an average 31% improvement (38% to 69%). Bar graphs show mean (±S.D.) percentage score on knowledge questions.</p