Phenotype based prediction of exome sequencing outcome using machine learning for neurodevelopmental disorders

Reverse Phenotyping after Whole-Exome Sequencing in Children with Developmental Delay/Intellectual Disability-An Exception or a Necessity?

This study delves into the diagnostic yield of whole-exome sequencing (WES) in pediatric patients presenting with developmental delay/intellectual disability (DD/ID), while also exploring the utility of Reverse Phenotyping (RP) in refining diagnoses. A cohort of 100 pediatric patients underwent WES, yielding a diagnosis in 66% of cases. Notably, RP played a significant role in cases with negative prior genetic testing, underscoring its significance in complex diagnostic scenarios. The study revealed a spectrum of genetic conditions contributing to DD/ID, illustrating the heterogeneity of etiological factors. Despite challenges, WES demonstrated effectiveness, particularly in cases with metabolic abnormalities. Reverse phenotyping was indicated in half of the patients with positive WES findings. Neural network models exhibited moderate-to-exceptional predictive abilities for aiding in patient selection for WES and RP. These findings emphasize the importance of employing comprehensive genetic approaches and RP in unraveling the genetic underpinnings of DD/ID, thereby facilitating personalized management and genetic counseling for affected individuals and families. This research contributes insights into the genetic landscape of DD/ID, enhancing our understanding and guiding clinical practice in this particular field of clinical genetics.

Reanalysis of whole-exome sequencing (WES) data of children with neurodevelopmental disorders in a standard patient care context

This study aims to inform future genetic reanalysis management by evaluating the yield of whole-exome sequencing (WES) reanalysis in standard patient care in the Netherlands. Single-center data of 159 patients with a neurodevelopmental disorder (NDD), in which WES analysis and reanalysis were performed between January 1, 2014, and December 31, 2021, was retrospectively collected. Patients were included if they were under the age of 18 years at initial analysis and if this initial analysis did not result in a diagnosis. Demographic, phenotypic, and genotypic characteristics of patients were collected and analyzed. The primary outcomes of our study were (i) diagnostic yield at reanalysis, (ii) reasons for detecting a new possibly causal variant at reanalysis, (iii) unsolicited findings, and (iv) factors associated with positive result of reanalysis. In addition, we conducted a questionnaire study amongst the 7 genetic department in the Netherlands creating an overview of used techniques, yield, and organization of WES reanalysis. The single-center data show that in most cases, WES reanalysis was initiated by the clinical geneticist (65%) or treating physician (30%). The mean time between initial WES analysis and reanalysis was 3.7 years. A new (likely) pathogenic variant or VUS with a clear link to the phenotype was found in 20 initially negative cases, resulting in a diagnostic yield of 12.6%. In 75% of these patients, the diagnosis had clinical consequences, as for example, a screening plan for associated signs and symptoms could be devised. Most (32%) of the (likely) causal variants identified at WES reanalysis were discovered due to a newly described gene-disease association. In addition to the 12.6% diagnostic yield based on new diagnoses, reclassification of a variant of uncertain significance found at initial analysis led to a definite diagnosis in three patients. Diagnostic yield was higher in patients with dysmorphic features compared to patients without clear dysmorphic features (yield 27% vs. 6%; p = 0.001).

CONCLUSIONS

Our results show that WES reanalysis in patients with NDD in standard patient care leads to a substantial increase in genetic diagnoses. In the majority of newly diagnosed patients, the diagnosis had clinical consequences. Knowledge about the clinical impact of WES reanalysis, clinical characteristics associated with higher yield, and the yield per year after a negative WES in larger clinical cohorts is warranted to inform guidelines for genetic reanalysis. These guidelines will be of great value for pediatricians, pediatric rehabilitation specialists, and pediatric neurologists in daily care of patients with NDD.

WHAT IS KNOWN

• Whole exome sequencing can cost-effectively identify a genetic cause of intellectual disability in about 30-40% of patients. • WES reanalysis in a research setting can lead to a definitive diagnosis in 10-20% of previously exome negative cases.

WHAT IS NEW

• WES reanalysis in standard patient care resulted in a diagnostic yield of 13% in previously exome negative children with NDD. • The presence of dysmorphic features is associated with an increased diagnostic yield of WES reanalysis.

Bi-allelic variants in the ESAM tight-junction gene cause a neurodevelopmental disorder associated with fetal intracranial hemorrhage

The blood-brain barrier (BBB) is an essential gatekeeper for the central nervous system and incidence of neurodevelopmental disorders (NDDs) is higher in infants with a history of intracerebral hemorrhage (ICH). We discovered a rare disease trait in thirteen individuals, including four fetuses, from eight unrelated families associated with homozygous loss-of-function variant alleles of ESAM which encodes an endothelial cell adhesion molecule. The c.115del (p.Arg39Glyfs∗33) variant, identified in six individuals from four independent families of Southeastern Anatolia, severely impaired the in vitro tubulogenic process of endothelial colony-forming cells, recapitulating previous evidence in null mice, and caused lack of ESAM expression in the capillary endothelial cells of damaged brain. Affected individuals with bi-allelic ESAM variants showed profound global developmental delay/unspecified intellectual disability, epilepsy, absent or severely delayed speech, varying degrees of spasticity, ventriculomegaly, and ICH/cerebral calcifications, the latter being also observed in the fetuses. Phenotypic traits observed in individuals with bi-allelic ESAM variants overlap very closely with other known conditions characterized by endothelial dysfunction due to mutation of genes encoding tight junction molecules. Our findings emphasize the role of brain endothelial dysfunction in NDDs and contribute to the expansion of an emerging group of diseases that we propose to rename as "tightjunctionopathies."

Application and research progress of machine learning in the diagnosis and treatment of neurodevelopmental disorders in children

The prevalence of neurodevelopment disorders (NDDs) among children has been on the rise. This has affected the health and social life of children. This condition has also imposed a huge economic burden on families and health care systems. Currently, it is difficult to perform early diagnosis of NDDs, which results in delayed intervention. For this reason, patients with NDDs have a prognosis. In recent years, machine learning (ML) technology, which integrates artificial intelligence technology and medicine, has been applied in the early detection and prediction of diseases based on data mining. This paper reviews the progress made in the application of ML in the diagnosis and treatment of NDDs in children based on supervised and unsupervised learning tools. The data reviewed here provide new perspectives on early diagnosis and treatment of NDDs.