De novo paradigm: the ultimate answer to the paradox in mental retardation?

Rare and undiagnosed diseases: From disease-causing gene identification to mechanism elucidation

Rare and undiagnosed diseases substantially decrease patient quality of life and have increasingly become a heavy burden on healthcare systems. Because of the challenges in disease-causing gene identification and mechanism elucidation, patients are often confronted with difficulty obtaining a precise diagnosis and treatment. Due to advances in sequencing and multiomics analysis approaches combined with patient-derived iPSC models and gene-editing platforms, substantial progress has been made in the diagnosis and treatment of rare and undiagnosed diseases. The aforementioned techniques also provide an operational basis for future precision medicine studies. In this review, we summarize recent progress in identifying disease-causing genes based on GWAS/WES/WGS-guided multiomics analysis approaches. In addition, we discuss recent advances in the elucidation of pathogenic mechanisms and treatment of diseases with state-of-the-art iPSC and organoid models, which are improved by cell maturation level and gene editing technology. The comprehensive strategies described above will generate a new paradigm of disease classification that will significantly promote the precision and efficiency of diagnosis and treatment for rare and undiagnosed diseases.

Identification of de novo germline mutations and causal genes for sporadic diseases using trio-based whole-exome/genome sequencing

Whole-genome or whole-exome sequencing (WGS/WES) of the affected proband together with normal parents (trio) is commonly adopted to identify de novo germline mutations (DNMs) underlying sporadic cases of various genetic disorders. However, our current knowledge of the occurrence and functional effects of DNMs remains limited and accurately identifying the disease-causing DNM from a group of irrelevant DNMs is complicated. Herein, we provide a general-purpose discussion of important issues related to pathogenic gene identification based on trio-based WGS/WES data. Specifically, the relevance of DNMs to human sporadic diseases, current knowledge of DNM biogenesis mechanisms, and common strategies or software tools used for DNM detection are reviewed, followed by a discussion of pathogenic gene prioritization. In addition, several key factors that may affect DNM identification accuracy and causal gene prioritization are reviewed. Based on recent major advances, this review both sheds light on how trio-based WGS/WES technologies can play a significant role in the identification of DNMs and causal genes for sporadic diseases, and also discusses existing challenges.

Genetic basis of intellectual disability

In the past decade, we have witnessed a flood of reports about mutations that cause or contribute to intellectual disability (ID). This rapid progress has been driven in large part by the implementation of chromosomal microarray analysis and next-generation sequencing methods. The findings have revealed extensive genetic heterogeneity for ID, as well as examples of a common genetic etiology for ID and other neurobehavioral/psychiatric phenotypes. Clinical diagnostic application of these new findings is already well under way, despite incomplete understanding of non-Mendelian transmission patterns that are sometimes observed.