Abstract

During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; however, many cases remain undiagnosed after applying standard diagnostic sequencing techniques. This review discusses various methods to improve the molecular diagnostic rates in these genomic cold cases. We discuss extended analysis methods to consider, non-Mendelian inheritance models, mosaicism, dual/multiple diagnoses, periodic re-analysis, artificial intelligence tools, and deep phenotyping, in addition to integrating various omics methods to improve variant prioritization. Last, novel genomic technologies, including long-read sequencing, artificial long-read sequencing, and optical genome mapping are discussed. In conclusion, a more comprehensive molecular analysis and a timely re-analysis of unsolved cases are imperative to improve diagnostic rates. In addition, our current understanding of the human genome is still limited due to restrictions in technologies. Novel technologies are now available that improve upon some of these limitations and can capture all human genomic variation more accurately. Last, we recommend a more routine implementation of high molecular weight DNA extraction methods that is coherent with the ability to use and/or optimally benefit from these novel genomic methods.

Highlights

  • Etiological diagnosis in pediatric neurological disorders (NDs) and neurodevelopmental disorders (NDDs) is imperative for disease management, counseling, prognosis, treatment, prevention, and quality of life

  • DNA next-generation sequencing (NGS) technology has dramatically improved over the past decades, large parts of the human genome are not interrogated by the current short-read NGS methods used in both diagnostics and novel gene discovery

  • This review discusses various methods to increase the diagnostic findings in genomic cold cases with a pediatric neurological condition, i.e., cases which remain unsolved after standard short-read sequencing methods

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Summary

Introduction

Etiological diagnosis in pediatric neurological disorders (NDs) and neurodevelopmental disorders (NDDs) is imperative for disease management, counseling, prognosis, treatment, prevention, and quality of life. Over the past decade, targeted next-generation gene panels and exome sequencing have emerged as cost-effective ways of identifying the disease-associated variants in Mendelian disorders, including pediatric NDs [1]. Parent-offspring trio sequencing has been proven to be especially effective It allows for a more efficient variant filtering (based on fitting inheritance models), and it is useful in the context of de novo variant discovery. Targeted next-generation sequencing, exome sequencing, and genome sequencing can be effective in identifying causal genetic variation in NDs, many cases remain unsolved [2,3]. DNA next-generation sequencing (NGS) technology has dramatically improved over the past decades, large parts of the human genome are not interrogated by the current short-read NGS methods used in both diagnostics and novel gene discovery. This review discusses various methods to increase the diagnostic findings in genomic cold cases with a pediatric neurological condition, i.e., cases which remain unsolved after standard short-read sequencing methods

Extended Analysis of Existing Data
Non-Mendelian Inheritance Models
Dual/Multiple Diagnoses
Mosaicism
Theof different levels in of mosaicism in diseases
Periodic Data Re-Analysis
Artificial Intelligence (AI) Applications
Transcriptomics
Epigenomics
Proteomics
Metabolomics
Public Recourses and Bioinformatic Predictions
Deep Phenotyping
Novel DNA Sequencing and Mapping Technologies
Long-Read Sequencing (LRS)
Artificial Long-Read Sequencing (Alrs)
Optical Genome Mapping (OGM)
Integrating Different Data Types
Findings
Conclusions and Future Directions
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