BACKGROUND:Congenital heart disease (CHD) is the most common birth defect and a leading cause of infant mortality. CHD often has a genetic cause, and recent studies demonstrate the utility of genetic testing. In clinical practice, genetic testing continues to evolve, and the incorporation of rapid genome sequencing (rGS) in CHD is a recent development that requires evaluation. Although smaller studies demonstrate the value of rGS, they also highlight the burden of results interpretation.METHODS:We analyzed genetic testing in CHD at 2 time points, in 2018 and from 2022 to 2023, across a change in clinical testing guidelines from chromosome microarray to rGS.RESULTS:In an analysis of 421 hospitalized infants with CHD, genetic testing was performed in 77.7%, and the rate was consistent across time and in all patient subtypes analyzed. There was a significant shift in testing modalities, where in 2018, chromosome microarray was the most common test performed, with diagnostic results for CHD in 14.3%, whereas in 2022 to 2023, rGS was the most frequent test performed, with results diagnostic for CHD in 16.9%. In addition, rGS identified 44% more unique genetic diagnoses than chromosome microarray.CONCLUSIONS:This is the most extensive study to highlight the value of rGS in patients with CHD. These findings have important implications for CHD patient management.

BACKGROUND:Elevated lipoprotein(a) [Lp(a)] and familial hypercholesterolemia (FH) are common, underdiagnosed monogenic dyslipidemias that significantly increase cardiovascular risk. OBJECTIVE:We investigated whether standard clinical risk factors-low-density lipoprotein cholesterol (LDL-C), family history, and personal history of premature atherosclerotic cardiovascular disease (pASCVD)-can accurately distinguish these conditions. METHODS:We analyzed 378 lipid clinic patients receiving Lp(a) screening and FH genetic testing with multinomial logistic regression. RESULTS:we found that while higher LDL-C and younger age were associated with FH, personal/family histories of pASCVD failed to differentiate between FH, elevated Lp(a), or dual diagnoses. Genetic testing for FH and Lp(a) measurement revealed that 22.5% had FH, 35.7% had elevated Lp(a), and 12.7% had both. Despite statistical associations, predicted probabilities for each diagnosis overlapped considerably, and clinical risk factors commonly used in FH clinical diagnostic criteria would insufficiently distinguish these genetic disorders. CONCLUSIONS:Results demonstrate that clinical risk factors and scoring systems cannot reliably substitute diagnostic FH genetic testing and Lp(a) measurement-essential for accurate diagnosis and management for these high-risk disorders.

Abstract Background Congenital junctional ectopic tachycardia (cJET) is a rare, potentially life-threatening arrhythmia suspicious for a genetic basis, yet its molecular underpinnings remain incompletely defined. The POPDC2 gene, involved in cardiac pacemaking and membrane trafficking of interacting ion channels, has not previously been conclusively linked to human tachyarrhythmias. This study investigates a novel POPDC2 variant (p.Leu245Pro) identified in a family with autosomal dominant cJET. Methods Exome sequencing was performed to identify co-segregating variants in the affected family. Functional analysis of the POPDC2 p.Leu245Pro variant was conducted by molecular dynamics (MD) simulations, a membrane targeting assay, and a bimolecular fluorescence complementation assay. Additionally, the impact of the variant on Nav1.5 and TREK-1 currents was characterized in Xenopus oocytes. Results The p.Leu245Pro POPDC2 variant showed a destabilization of the POPDC1-POPDC2 dimer interface, resulting in impaired heterodimer formation and membrane localization. Electrophysiological studies in Xenopus oocytes demonstrated that the mutant protein significantly affected Nav1.5 and TREK-1 currents. These findings support a functional impact of the POPDC2 p.Leu245Pro variant relevant to cardiac conduction. Conclusions Our results provide the first functional evidence implicating POPDC2 in cJET and support its role as a novel candidate gene in tachyarrhythmic disease. This study enhances the understanding of genetic contributions to cJET and suggests further investigation of POPDC2 in other forms of supraventricular tachyarrhythmias.

The Undiagnosed Rare Disease Clinic (URDC) of Indiana University, established in January 2020, is a multidisciplinary collaborative clinic that focuses on providing genetic diagnoses for patients and families dealing with the uncertainty of an undiagnosed rare disease and/or diagnostic odyssey. To identify rare disease-causing variants underlying the suspected undiagnosed genetic conditions in our patient cohort, the URDC team implemented the following procedure. After sequencing, each case was evaluated by a small multidisciplinary team using an individualized, multi-modal pipeline, incorporating a customized AI-based variant-prioritization system. Candidate genes and variants identified through this process were further assessed through targeted functional studies, including 3D structural modeling, RNA-seq and additional in vivo and in vitro assays. The patients enrolled in URDC were referred from both urban (80

OBJECTIVE:To evaluate the yield of prenatal genetic testing in infants with a confirmed genetic diagnosis. METHODS:We retrospectively reviewed records of infants with a genetic diagnosis who were evaluated using a standardized genetic consult and testing approach. The predicted yield of various prenatal genetic sceening and diagnostic tools in this cohort was determined and compared. RESULTS:Genome sequencing had the highest predicted diagnostic yield (96.9%), followed by CMA with reflex to exome sequencing (95.5%), exome sequencing alone (93.8%) and CMA alone (43.6%). ACOG-recommended NIPT and carrier screening could have detected 25.4% of diagnoses, while 55.3% were detectable through genome-wide NIPT and a large carrier screening panel. Genome-wide NIPT improved chromosomal abnormality detection by ∼30% compared with ACOG-recommended NIPT. A large commercial carrier screening panel detected 26.1% of single-gene conditions, versus 6.1% with the ACOG-recommended panel. Overall, 62% of single-gene conditions were undetectable with current screening tools. CONCLUSION:Prenatal ES or GS offers high diagnostic yields and a streamlined approach, suggesting that CMA may not be the most appropriate first-line test unless there is strong suspicion of a chromosomal diagnosis. Although prenatal genetic screening is valuable, its ability to identify rare genetic conditions remains limited. Our findings support revising the ACOG/ACMG guidelines to align with postnatal testing recommendations, particularly in high-risk pregnancies.

ABSTRACT Background Genetic causes of congenital heart disease (CHD) are often underrecognized, though precision phenotyping may improve screening for genetic disorders. We demonstrate how body region dysmorphology predicts genetic diagnoses associated with CHD. Methods We used a test‐negative case–control study of CHD infants undergoing standardized genetics evaluations. We investigated correlations between body region dysmorphology (BRD) and CHD classes and developed novel models for predicting genetic diagnoses, including cytogenetic/monogenic disorders identified by genetic testing. Results In 243/1008 patients with genetic diagnoses (24.1%), we found novel correlations between BRDs and CHD classes. Periorbital, maxilla/midface, ear, and mandible BRDs correlated with conotruncal CHD with genetic diagnoses (25.5%); left ventricular outflow tract CHD presented with few BRDs despite genetic diagnoses identified (18.5%). Septal and right ventricular outflow tract CHD had a wider spectrum of BRDs. Multivariable modeling identified multiple BRDs predicting genetic diagnoses, including of the face (OR = 2.57), forehead (OR = 2.55), neck (OR = 2.24), periorbital (OR = 1.57), and hands/feet (OR = 1.90) regions, after adjusting for extracardiac anomalies (OR = 3.65), CHD class (p = 0.02), and male sex (OR = 0.69). The BRD model had acceptable utility assessed by decision curve analysis. Face/forehead/neck BRDs predicted cytogenetic and monogenic diagnoses (ORs ranging 2.2–2.5), though BRDs of hands/feet associated with cytogenetic disorders (OR = 2.22). Males were less likely to have cytogenetic diagnoses compared to females (OR = 0.59), suggesting potential sex‐specific differences. Conclusions This is a novel investigation of body region dysmorphology patterns predictive of genetic diagnoses in CHD patients. Precision phenotyping can be an important part of care and allow clinicians to risk‐stratify young CHD patients suspected of having genetic disorders.

OBJECTIVE:Determine prenatal and neonatal factors that predict infantile outcomes in patients with congenital heart disease (CHD). STUDY DESIGN:Retrospective cohort of 415 neonates with CHD admitted to a neonatal intensive care unit (NICU). Statistical tests included Chi-square, Fisher's Exact, Kruskal-Wallis, and multivariable logistic regression. RESULTS:Cardiac lesion type was associated with mortality, length of stay, and enteral feeding tube support at discharge (EFTD) (p ≤ 0.01). A genetic diagnosis and an extra-cardiac congenital anomaly were associated with higher odds of respiratory support needs at discharge (RSND) [OR 2.8 (95% CI: 1.2, 6.5); 4.8 (1.9, 11.8)] and EFTD [5.5 (2.9, 10.8); 3.4 (2.4-9.7)]. Lower birth weight was associated with higher odds of RSND [0.5 (0.38, 0.66)], and lower gestational age with higher odds of EFTD [0.84 (0.75, 0.95)]. CONCLUSION:Several factors predicted adverse outcomes in infants with CHD, helping to identify high-risk cases for targeted care and improved parental guidance.

Background Nonischemic dilated cardiomyopathy (DCM) can result from pathogenic variants in genes affecting myocardial structure and function. FKTN and LMNA mutations may involve both cardiac and skeletal muscle, consistent with limb-girdle muscular dystrophy (LGMD), with cardiac disease sometimes preceding neuromuscular symptoms. Case Summary We report on 2 adults presenting with advanced DCM requiring heart transplantation, who were later diagnosed with LGMD. A 22-year-old woman had biallelic FKTN variants, and a 37-year-old man carried a heterozygous LMNA pathogenic variant. Both had elevated creatine kinase prior to proximal muscle weakness. Muscle biopsy and genetic testing confirmed dystrophic processes. Discussion These cases demonstrate that genetically mediated DCM may initially present as isolated cardiac disease. Early genetic testing can guide transplant planning, long-term care, and family counseling.

BACKGROUND:Genetic disorders are prevalent in patients with congenital heart disease (CHD), but genetic evaluations are underutilized and nonstandardized. We sought to quantify a dysmorphology score and develop phenotype-based prediction models for genetic diagnoses in CHD. METHODS:We used a test-negative case-control study of inpatient infants (<1 year) with CHD undergoing standardized genetic evaluations. We quantified a novel dysmorphology score and combined it with other clinical variables used in multivariable logistic regression models to predict genetic diagnoses identified by genetic testing. RESULTS:Of 1008 patients, 24.1% (243/1008) had genetic diagnoses identified. About half of the cohort were either nondysmorphic or mildly dysmorphic with dysmorphology scores ≤2. There were higher dysmorphology scores according to CHD class (P=0.0007), extracardiac anomaly-positive status (P<0.0001), female sex (P=0.05), and genetic diagnosis identified (P<0.0001). Multivariable logistic regression models quantified this effect further: each +1 increase in the dysmorphology score was associated with a 17% to 20% increased risk of genetic diagnoses (odds ratios, 1.17-1.20, P<0.0001). Extracardiac anomaly-positive status remained a stronger predictor of genetic diagnoses (odds ratios, 2.81-3.39). Nonetheless, about 10% of the cohort were minimally dysmorphic (dysmorphology scores ≤2), had isolated CHD, and were found to have genetic diagnoses, indicating that dysmorphology-based screening can be used to risk-stratify but not exclude genetic diagnoses. CONCLUSIONS:The dysmorphology score is a novel screen for patients with CHD at high risk of having genetic diagnoses identified by genetic testing, including disorders not easily recognized by clinicians. We used these results to develop predicted probability plots for genetic diagnoses in patients with CHD.

Retention is a challenge that every health organization faces in an evolving and competitive market, including those in hospital settings. Some healthcare professions have identified factors that influence their employees to either stay or leave, which has led to the development and implementation of targeted strategies to increase job satisfaction and retention. Prior to this study, only factors associated with leaving have been identified in the genetic counseling profession. Despite the growing number of genetic counselors in the field, a shortage of patient‐facing genetic counselors is expected by 2030. Therefore, this study explored three topics among patient‐facing genetic counselors: (1) intent to stay in their current position, (2) top factors that influence this decision, (3) whether these factors differ by generational age, and (4) whether these factors differ by work setting. Genetic counselors who were in a patient‐facing position for ≥6 months, board‐certified, and working in the United States or Canada were eligible for study participation. Of the 520 respondents, the majority (84.6%) intend to stay in their current position. The top factors selected for staying were flexibility (58.9%), colleagues (56.4%), salary (52.0%), autonomy (48.1%), location (47.5%), and specialty (44.0%). Generation X was more likely to choose autonomy and less likely to choose location in their top five factors for staying compared to other generations. Individuals working in industry were more likely to choose flexibility and autonomy ; those in academic centers were more likely to choose colleagues ; those in non‐hospital clinics were more likely to choose salary ; and those in non‐academic health centers were more likely to choose location compared to other work settings. Based on our results, clinical leadership should allocate resources to strategies that increase flexibility, foster a collaborative environment, and promote autonomy within the workplace to increase retention and prevent the predicted shortage of patient‐facing genetic counselors.

Genetic testing strategies used to determine the etiology of congenital heart disease/defects (CHD/CHDs) vary between and within institutions, leading to potentially missed diagnostic opportunities. There has been little investigation comparing the diagnostic utility of gene panels among more comprehensive strategies used in the genetic evaluation of patients with CHD. In this descriptive study, we investigated the diagnostic yields of different genetic testing strategies in a real‐world cohort of 263 patients with CHDs with genetic diagnoses. We counterfactually determined the diagnostic yield of a virtual gene panel designed for this study. We compared the diagnostic yield of the gene panel to other testing strategies, including chromosomal microarray (CMA), CMA + the gene panel, and genome sequencing. We assessed diagnostic yield differences according to clinical presentations to determine if phenotypes can inform optimal testing strategies. The virtual gene panel would have identified 51.3% of genetic disorders in this cohort, and 25.9% of genetic disorders would have remained undetected; another 22.8% may have needed additional testing to fully characterize the diagnoses. A combined approach of the virtual gene panel and CMA increased the diagnostic yield compared with panel‐only testing or CMA alone (87.8% vs. 51.3% and 63.1%, respectively). The gene panel plus CMA would have increased the diagnostic yield by 24%–35% compared with CMA or panel testing alone in patients with extracardiac anomalies, 19%–41% in syndromic patients, and 0%–70% across CHD classifications. This combined approach also eliminated the potential need for follow‐up testing; however, genome sequencing had a higher diagnostic yield across all clinical presentations (99.6%). CHD gene panels and CMA used individually or in combination are suboptimal first‐line testing strategies, missing up to 36.5% of genetic disorders in our sample. Given the wide spectrum of phenotypes and genetic etiologies, our results support consideration of standardized genome sequencing for patients with CHDs.

BACKGROUND:Genetic disorders are pervasive in neonatal intensive care unit (NICU) populations, and the superiority of genomic testing to rapidly identify genetic diagnoses is established, yet patients remain untested and undiagnosed. METHODS:In this single-center 19-month cohort study, outcomes before and after implementation of a clinical guideline standardizing genomic testing were evaluated in 2169 patients in the NICU (pre: 692, 31.9%; post: 1477, 68.1%). Primary outcomes were qualifying for and receipt of any genetic services and a diagnosis. Secondary outcomes included admission length and hospital charges. RESULTS:The frequency of qualifying for genetic services across racial and birth weight (BW) categories differed: 643 (44.3%; 95% CI 41.8-46.9) white vs 155 (32.3%; 95% CI 28.1-36.5) Black, P < .001; and 584 (49.1%; 95% CI 46.3-52.0) normal vs 78 (23.2%; 95% CI 18.7-27.7) very and extremely low BW, P < .001. When adjusting for these differences, all populations experienced increases in genetics consultations, 177 (25.6%; 95% CI 22.3-28.8) vs 461 (31.2%; 95% CI 28.9-33.6), P = .007; completion of genomic testing, 62 (9.0%; 95% CI 6.8-11.1) vs 363 (24.6%; 95% CI 22.4-26.8), P < .001; and confirmed genetic diagnoses, 57 (8.2%; 95% CI 6.2-10.3) vs 172 (11.6%; 95% CI 10.0-13.3), P = .02. Patients receiving genomic testing experienced decreases in admission length, 46 vs 24 days, P = .008; and hospital charges, $561 536.00 vs $354 627.00, P = .03; regardless of testing outcome. CONCLUSIONS:A significant number of patients in the NICU required genomic testing. However, differences existed across race and BW categories in qualifying for genomic services. Standardizing genomic care equitability improved access to testing and genetic disorder detection and lowered the use of health care resources.

The continuing evolution of the genetic counseling profession necessitates an ongoing reflection on the perceived validity and role of our research in the larger systems we operate in. Despite our need for an analytically inclined professional culture and decision-making process, many genetic counselors may not have the training or support needed to ensure such rigor. In this special issue of the Journal of Genetic Counseling, authors were tasked with providing methodological foundations for genetic counselors navigating various phases of research, to improve the quality of our research output and to incorporate our findings into decision-making in healthcare and non-healthcare settings. In this manuscript, we describe various statistical approaches in lay terms and provide resources for genetic counselors new and seasoned alike. We hope to ease some of the trepidation in applying statistical approaches to genetic counseling research and provide resources to increase the analytical confidence of our workforce. This can increase the validity of the analyses and findings disseminated within and beyond our profession. First, we review some history and foundations of statistical practices that inform study design, sampling, data collection, analysis, and interpretation. Next, we highlight how different study designs inform the choice of data analysis and provide resources for statistical strategy choice. Finally, we provide resources on how to interpret statistical test results, recommend best practices, and highlight common but avoidable misconceptions in statistical interpretation. We hope this review provides a framework for novices in quantitative methodology and provides the language needed to collaborate with analytical/statistical colleagues.

BACKGROUND:Lipoprotein(a) [Lp(a)] is a common heritable causal cardiovascular risk factor, and understanding how patients use Lp(a) status for family screening is imperative. No studies to date have focused on the patient's perspective of their experiences. OBJECTIVE:To understand the experiences of people with elevated Lp(a), we investigated the factors that influence decision regret, optimism, anxiety, and family screening. METHODS:Participants with self-reported elevated Lp(a) completed an online survey assessing their experiences living with elevated Lp(a), including demographics, clinical and family history, barriers to testing, and, among the parent sub-cohort, the decision to test children's Lp(a). RESULTS:Among 1001 participants with completed surveys, most had no decision regret (70.7%) and minimal anxiety (71.7%) related to their elevated Lp(a). Almost half of participants (47.4%) experienced barriers to Lp(a) testing. Almost all participants (92.9%) reported they shared their Lp(a) results with their family. In a subgroup analysis of parents of children <18 years (n = 399), we investigated influences on the decision to test their children's Lp(a). Significant influences included age, optimism with current clinical care, and an interaction between decision regret and being clinically diagnosed with familial hypercholesterolemia (FH). Higher decision regret was associated with a lower probability of testing their children's Lp(a) for participants without a clinical diagnosis of FH. CONCLUSION:We report novel experiences of people with elevated Lp(a), including levels of Lp(a)-specific anxiety, optimism, and decision regret regarding testing. Our results provide impetus for future research aimed at improving Lp(a) testing access, clinician education, and providing support to patients and families.

Background:Contemporary guidelines recommend genetic counseling for potentially inherited cardiomyopathies, channelopathies, aortopathies, and dyslipidemias, but few, small, studies characterize cardiovascular genetic counseling (CVGC) outcomes impeding efforts to improve CVGC service delivery. We aimed to 1) quantify psychosocial CVGC outcomes, 2) identify clinical, demographic, and service delivery characteristics associated with extent of benefit from CVGC, and 3) determine how outcomes are associated with patient-reported quality of the genetic counselor (GC):patient alliance. Methods:890 adults attending a first outpatient CVGC appointment at eight United States and Canadian medical centers completed questionnaires assessing empowerment (Genetic Counseling Outcome Scale [GCOS-24]), worry (modified Cancer Worry Scale [CWS]), cardiac anxiety (Cardiac Anxiety Questionnaire [CAQ]), and GC:patient alliance (Working Alliance Inventory-patient [WAI-SR]) prior to and up to 4 weeks post-CVGC, but before results of genetic tests ordered were returned to decouple CVGC and genetic test result impact. Results:Following CVGC, empowerment increased (GCOS-24 change: +5.94±11.6, p<0.001), worry decreased (CWS change: -0.40±3.55, p=0.002), and cardiac fear decreased (CAQ fear subscale change: -0.034±0.46, p=0.033) with no change in whole-scale CAQ (0.013±0.34, p=0.29). In linear regression, worry decreased most in patients with less formal education (p=0.0021), with an arrhythmia indication (p=0.013), and who were at-risk family members (p=0.016) while strength of the GC:patient alliance had no impact. In contrast, the GC:patient alliance was strongly positively associated with change in empowerment (p<0.001). Conclusions:This observational, multicenter, multiprovider study provides foundational evidence that CVGC is associated with increased empowerment and decreased worry in adults attending outpatient CVGC and suggests opportunities for optimizing CVGC services.

Introduction: The NKX2.5 gene is an important cardiac developmental transcription factor, and variants in this gene are most commonly associated with CHD. However, there is an increased need to recognise associations with conduction disease and potentially dangerous ventricular arrhythmias. There is an increased risk of arrhythmia and sudden cardiac death in patients with NKX2.5 variants, an association with relatively less attention in the literature. Methods: We created a family pedigree and reconstructed familial relationships involving numerous relatives with CHD, conduction disease, and ventricular non-compaction following the sudden death of one family member. Two informative but distantly related family members had genetic testing to determine the cause of arrhythmias via arrhythmia/cardiomyopathy gene testing, and we identified obligate genetic-positive relatives based on family relationships and Mendelian inheritance pattern. Results: We identified a novel pathogenic variant in the NKX2.5 gene (c.437C > A; p. Ser146*), and segregation analysis allowed us to link family cardiac phenotypes including CHD, conduction disease, left ventricular non-compaction, and ventricular arrhythmias/sudden cardiac death. Conclusions: We report a novel NKX2.5 gene variant linking a spectrum of familial heart disease, and we also encourage recognition of the association between NKX2.5 gene and potentially dangerous ventricular arrhythmias, which will inform clinical risk stratification, screening, and management.

Heterozygous missense variants and in-frame indels in SMC3 are a cause of Cornelia de Lange syndrome (CdLS), marked by intellectual disability, growth deficiency, and dysmorphism, via an apparent dominant-negative mechanism. However, the spectrum of manifestations associated with SMC3 loss-of-function variants has not been reported, leading to hypotheses of alternative phenotypes or even developmental lethality. We used matchmaking servers, patient registries, and other resources to identify individuals with heterozygous, predicted loss-of-function (pLoF) variants in SMC3, and analyzed population databases to characterize mutational intolerance in this gene. Here, we show that SMC3 behaves as an archetypal haploinsufficient gene: it is highly constrained against pLoF variants, strongly depleted for missense variants, and pLoF variants are associated with a range of developmental phenotypes. Among 14 individuals with SMC3 pLoF variants, phenotypes were variable but coalesced on low growth parameters, developmental delay/intellectual disability, and dysmorphism, reminiscent of atypical CdLS. Comparisons to individuals with SMC3 missense/in-frame indel variants demonstrated an overall milder presentation in pLoF carriers. Furthermore, several individuals harboring pLoF variants in SMC3 were nonpenetrant for growth, developmental, and/or dysmorphic features, and some had alternative symptomatologies with rational biological links to SMC3. Analyses of tumor and model system transcriptomic data and epigenetic data in a subset of cases suggest that SMC3 pLoF variants reduce SMC3 expression but do not strongly support clustering with functional genomic signatures of typical CdLS. Our finding of substantial population-scale LoF intolerance in concert with variable growth and developmental features in subjects with SMC3 pLoF variants expands the scope of cohesinopathies, informs on their allelic architecture, and suggests the existence of additional clearly LoF-constrained genes whose disease links will be confirmed only by multi-layered genomic data paired with careful phenotyping.

ABSTRACT Background Dysmorphology evaluation is important for congenital heart disease (CHD) assessment, but there are no prior investigations quantifying the screening performance compared to standardized genetics evaluations. We investigated this through systematic dysmorphology assessment in CHD patients with standardized genetic testing in primarily pediatric patients with CHD. Methods Dysmorphology evaluations preceding genetic testing results allowed us to test for associations between dysmorphic status and genetic diagnoses while adjusting for extracardiac anomalies (ECAs). We use a test‐negative case–control design on a pediatric inpatient CHD cohort for our study. Results Of 568 patients, nearly 96% of patients completed genetic testing, primarily chromosome microarray (CMA) ± exome sequencing‐based genetic testing (493/568, 86.8%). Overall, 115 patients (20.2%) were found to have genetic diagnoses, and dysmorphic patients had doubled risk of genetic diagnoses, after ECA adjustment (OR = 2.10, p = 0.0030). We found that 7.9% (14/178) of ECA−/nondysmorphic patients had genetic diagnoses, which increased to 13.5% (26/192) in the ECA−/dysmorphic patients. Nearly 43% of ECA+/dysmorphic patients had genetic diagnoses (63/147). The positive predictive value of dysmorphic status was only 26.3%, and the negative predictive value of nondysmorphic status was 88.7%. Conclusions Dysmorphology‐based prediction of genetic disorders is limited because of diagnoses found in apparently isolated CHD. Our findings represent one of the only assessments of phenotype‐based screening for genetic disorders in CHD and should inform clinical genetics evaluation practices for pediatric CHD.