Translational Diagnostics: An In-House Pipeline to Validate Genetic Variants in Children with Undiagnosed and Rare Diseases

Integrating non-mammalian model organisms in the diagnosis of rare genetic diseases in humans

Next-generation sequencing technology has rapidly accelerated the discovery of genetic variants of interest in individuals with rare diseases. However, showing that these variants are causative of the disease in question is complex and may require functional studies. Use of non-mammalian model organisms - mainly fruitflies (Drosophila melanogaster), nematode worms (Caenorhabditis elegans) and zebrafish (Danio rerio) - enables the rapid and cost-effective assessment of the effects of gene variants, which can then be validated in mammalian model organisms such as mice and in human cells. By probing mechanisms of gene action and identifying interacting genes and proteins in vivo, recent studies in these non-mammalian model organisms have facilitated the diagnosis of numerous genetic diseases and have enabled the screening and identification of therapeutic options for patients. Studies in non-mammalian model organisms have also shown that the biological processes underlying rare diseases can provide insight into more common mechanisms of disease and the biological functions of genes. Here, we discuss the opportunities afforded by non-mammalian model organisms, focusing on flies, worms and fish, and provide examples of their use in the diagnosis of rare genetic diseases.

The best of both worlds: Blending cutting-edge research with clinical processes for a productive exome clinic

Genomic medicine has been transformed by next-generation sequencing (NGS), inclusive of exome sequencing (ES) and genome sequencing (GS). Currently, ES is offered widely in clinical settings, with a less prevalent alternative model consisting of hybrid programs that incorporate research ES along with clinical patient workflows. We were among the earliest to implement a hybrid ES clinic, have provided diagnoses to 45% of probands, and have identified several novel candidate genes. Our program is enabled by a cost-effective investment by the health system and is unique in encompassing all the processes that have been variably included in other hybrid/clinical programs. These include careful patient selection, utilization of a phenotype-agnostic bioinformatics pipeline followed by manual curation of variants and phenotype integration by clinicians, close collaborations between the clinicians and the bioinformatician, pursuit of interesting variants, communication of results to patients in categories that are predicated upon the certainty of a diagnosis, and tracking changes in results over time and the underlying mechanisms for such changes. Due to its effectiveness, scalability to GS and its resource efficiency, specific elements of our paradigm can be incorporated into existing clinical settings, or the entire hybrid model can be implemented within health systems that have genomic medicine programs, to provide NGS in a scientifically rigorous, yet pragmatic setting.

CRISPR/Cas9-based functional genomics strategy to decipher the pathogenicity of genetic variants in inherited metabolic disorders

The determination of the functional impact of variants of uncertain significance (VUS) is one of the major bottlenecks in the diagnostic workflow of inherited genetic diseases. To face this problem, we set up a CRISPR/Cas9-based strategy for knock-in cellular model generation, focusing on inherited metabolic disorders (IMDs). We selected variants in seven IMD-associated genes, including seven reported disease-causing variants and four benign/likely benign variants. Overall, 11 knock-in cell models were generated via homology-directed repair in HAP1 haploid cells using CRISPR/Cas9. The functional impact of the variants was determined by analyzing the characteristic biochemical alterations of each disorder. Functional studies performed in knock-in cell models showed that our approach accurately distinguished the functional effect of pathogenic from non-pathogenic variants in a reliable manner in a wide range of IMDs. Our study provides a generic approach to assess the functional impact of genetic variants to improve IMD diagnosis and this tool could emerge as a promising alternative to invasive tests, such as muscular or skin biopsies. Although the study has been performed only in IMDs, this strategy is generic and could be applied to other genetic disorders.

The Increasing Impact of Translational Research in the Molecular Diagnostics of Neuromuscular Diseases

The diagnosis of neuromuscular diseases (NMDs) has been progressively evolving from the grouping of clinical symptoms and signs towards the molecular definition. Optimal clinical, biochemical, electrophysiological, electrophysiological, and histopathological characterization is very helpful to achieve molecular diagnosis, which is essential for establishing prognosis, treatment and genetic counselling. Currently, the genetic approach includes both the gene-targeted analysis in specific clinically recognizable diseases, as well as genomic analysis based on next-generation sequencing, analyzing either the clinical exome/genome or the whole exome or genome. However, as of today, there are still many patients in whom the causative genetic variant cannot be definitely established and variants of uncertain significance are often found. In this review, we address these drawbacks by incorporating two additional biological omics approaches into the molecular diagnostic process of NMDs. First, functional genomics by introducing experimental cell and molecular biology to analyze and validate the variant for its biological effect in an in-house translational diagnostic program, and second, incorporating a multi-omics approach including RNA-seq, metabolomics, and proteomics in the molecular diagnosis of neuromuscular disease. Both translational diagnostics programs and omics are being implemented as part of the diagnostic process in academic centers and referral hospitals and, therefore, an increase in the proportion of neuromuscular patients with a molecular diagnosis is expected. This improvement in the process and diagnostic performance of patients will allow solving aspects of their health problems in a precise way and will allow them and their families to take a step forward in their lives.

PLXNA2 and LRRC40 as candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disability with high heritability yet the genetic etiology remains elusive. Therefore, it is necessary to elucidate new genotype-phenotype relationships for ASD to improve both the etiological knowledge and diagnosis. In this work, a copy-number variant and whole-exome sequencing analysis were performed in an ASD patient with a complex neurobehavioral phenotype with epilepsy and attention deficit hyperactivity disorder. We identified rare recessive single nucleotide variants in the two genes, PLXNA2 encoding Plexin A2 that participates in neurodevelopment, and LRRC40, which encodes Leucine-rich repeat containing protein 40, a protein of unknown function. PLXNA2 showed the heterozygous missense variants c.614G>A (p.Arg205Gln) and c.4904G>A (p.Arg1635Gln) while LRRC40 presented the homozygous missense variant c.1461G>T (p.Leu487Phe). In silico analysis predicted that these variants could be pathogenic. We studied PLXNA2 and LRRC40 mRNA and proteins in fibroblasts from the patient and controls. We observed a significant PlxnA2 subcellular delocalization and very low levels of LRRC40 in the patient. Moreover, we found a novel interaction between PlxnA2 and LRRC40 suggesting that participate in a common neural pathway. This interaction was significant decreased in the patient's fibroblasts. In conclusion, our results identified PLXNA2 and LRRC40 genes as candidates in ASD providing novel clues for the pathogenesis. Further attention to these genes is warranted in genetic studies of patients with neurodevelopmental disorders, particularly ASD. LAY SUMMARY: Genomics is improving the knowledge and diagnosis of patients with autism spectrum disorder (ASD) yet the genetic etiology remains elusive. Here, using genomic analysis together with experimental functional studies, we identified in an ASD complex patient the PLXNA2 and LRRC40 recessive genes as ASD candidates. Furthermore, we found that the proteins of these genes interact in a common neural network. Therefore, more attention to these genes is warranted in genetic studies of patients with neurodevelopmental disorders, particularly ASD.