Genetic counselling and testing in congenital heart defects and hereditary thoracic aortic disease: Complex but essential
Bibliographic record
Abstract
Congenital heart disease (CHD), the most common type of birth defect, has a neonatal incidence of 0.8–1%. Surgical advances have improved the pooled survival of CHD to adulthood in up to 90%. However, mortality and morbidity in adults with CHD remain high.1 Poor cardiac prognosis due to heart failure or life-threatening arrhythmia may be complicated further by extracardiac features, which are present in about 20% of CHD patients (syndromic CHD). Along with the prevalence of adults with CHD, the demand for cardiogenetic testing is increasing. A genetic diagnosis may serve as a marker for long-term cardiac or extracardiac outcome, or can enhance recurrence risk prediction in offspring of adults with CHD.2 De Backer et al.3 raise awareness about genetic counselling and testing for adults with CHD and hereditary thoracic aortic disease (HTAD). This European Society of Cardiology (ESC) consensus document provides guidance to healthcare providers, dealing with these diseases, about the importance, the indication and the timing of genetic counselling. In addition, the authors introduce a diagnostic algorithm with the preferred methodology of genetic testing, and give an overview of diagnoses to consider when facing syndromic or non-syndromic CHD or HTAD. As stated by the authors, the bottleneck in genetic testing is shifting from variant detection to variant interpretation. Advanced genome-wide screening technologies for chromosomal, structural or single nucleotide variants, such as chromosomal microarray or whole exome/genome sequencing, expose the patient’s genome in the blink of an eye. However, huge challenges remain in translating the abundance of genetic variants per individual into clinically relevant findings. Standardised criteria have been introduced to categorise single nucleotide variants according to their pathogenicity, based on variant type (protein truncating vs. missense variant), on frequency in a reference population, on in silico variant effect prediction and on inheritance pattern.4 Rare, predicted damaging variants in known disease-related genes that occur de novo in sporadic patients (i.e. not inherited from the parents) or that segregate with the disease in familial cases are typically considered pathogenic. Genomic studies report (mainly de novo) pathogenic variants in up to 35% of patients with previously unexplained syndromic CHD5–7 and inherited pathogenic variants in up to 40% of selected families with multigenerational non-syndromic CHD.8 The same holds true for syndromic or familial thoracic aortic disease.9,10 These syndromic and familial CHD and HTAD subgroups involve Mendelian traits with relatively high penetrance, and therefore represent obvious target populations for genetic testing and usually allow straightforward counselling. The diagnostic yield of whole exome sequencing in sporadic non-syndromic (NS)-CHD and NS-HTAD, which represents the majority of the adult CHD and HTAD cohort, is much lower. Although monogenic causes for NS-CHD and NS-HTAD have been reported in up to 4%, the majority remains gene-elusive despite chromosomal microarray and whole exome sequencing, and is considered to arise from a complex interplay between genetic and environmental factors. The diagnostic odyssey in NS-CHD is hampered by genetic heterogeneity, with more than 25 known genes, each being held responsible for less than 0.1% of the total NS-CHD cohort. As a consequence, extensive NS-CHD populations should be tested genetically to reach a significant number of patients having a pathogenic variant in the same CHD gene, enabling gene-based outcome prediction. Genetic testing and counselling in NS-CHD is complicated further by reduced penetrance of pathogenic variants. This means that family members, who carry a pathogenic variant, can present with subtle heart disease or even with normal heart structure and function.6 Moreover, some patients with NS-CHD carry pathogenic variants in genes that typically cause a syndromic phenotype.6,7 Mechanisms underlying this cardiac and extracardiac phenotypic variability are poorly understood, and might involve the presence of additional genetic modifiers. In summary, genetic testing of adults with sporadic NS-CHD and NS-HTAD is complex, and comes with a high rate of variants of unknown significance. Even when a genetic diagnosis in these patients has been made, individualised counselling regarding cardiac outcome and recurrence risk can still be a minefield. Therefore, if genetic testing of sporadic NS-CHD and NS-HTAD is considered, pre and post-test counselling should be performed by trained clinical geneticists or genetic counsellors, as suggested by De Backer et al. and by others.11,12 Particularly when extracardiac features or developmental delay are present, referral to a clinical geneticist with expertise in syndromology is recommended. The complexity of counselling and the low diagnostic yield should not hold us back from performing genetic analyses in sporadic NS-CHD (at least for some CHD types) and sporadic NS-HTAD. As over time more mutation-positive patients and families will be identified, we will get a better grasp on penetrance, long-term cardiac prognosis, timing of (aortic) surgery,10 and the incidence of extracardiac features, related to particular genes or variants. Increased knowledge on the genetic aetiology of CHD and HTAD will derive from research projects, targeting the genomes of thousands of patients to identify novel genes, but should also come from diagnostic genetic labs, which should be encouraged to submit potentially damaging variants in known CHD or HTAD genes into highly curated open access patient databases, such as Clinvar (https://www.ncbi.nlm.nih.gov/clinvar/) (Figure 1). To enhance genotype–phenotype correlation, these databases should include detailed and standardised cardiac and extracardiac phenotypes, as well as results from extended familial segregation analysis of (likely) pathogenic variants. Cardiologists are pivotal in this collaborative effort to improve insight into the genetic aetiology of CHD and HTAD. They are front row to recognise, counsel or refer patients, who may benefit from a genetic diagnosis, and have the expertise to relate cardiovascular outcomes of CHD and HTAD patients to their mutational status. The ESC consensus document on genetic counselling and testing of adult CHD and HTAD will engage and guide cardiac care providers in facing these challenges. Sharing results of genomic research projects and diagnostic labs in curated databases is key to increase current knowledge and improve counselling regarding complex genetic disorders such as non-syndromic congenital heart disease and hereditary thoracic aortic disease. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The author(s) disclosed receipt of the following financial support: JB is supported by the Frans Van de Werf fund for clinical cardiovascular research and by a clinical research fund of UZ Leuven (KOOR). The author received no financial support for the research, authorship, and/or publication of this article.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".