Copy number variants calling from WES data through eXome hidden Markov model (XHMM) identifies additional 2.5% pathogenic genomic imbalances smaller than 30 kb undetected by array-CGH.

It has been estimated that Copy Number Variants (CNVs) account for 10%-20% of patients affected by Developmental Disorder (DD)/Intellectual Disability (ID). Although array comparative genomic hybridization (array-CGH) represents the gold-standard for the detection of genomic imbalances, common Agilent array-CGH 4 × 180 kb arrays fail to detect CNVs smaller than 30 kb. Whole Exome sequencing (WES) is becoming the reference application for the detection of gene variants and makes it possible also to infer genomic imbalances at single exon resolution. However, the contribution of small CNVs in DD/ID is still underinvestigated. We made use of the eXome Hidden Markov Model (XHMM) software, a tool utilized by the ExAC consortium, to detect CNVs from whole exome sequencing data, in a cohort of 200 unsolved DD/DI patients after array-CGH and WES-based single nucleotide/indel variant analyses. In five out of 200 patients (2.5%), we identified pathogenic CNV(s) smaller than 30 kb, ranging from one to six exons. They included two heterozygous deletions in TCF4 and STXBP1 and three homozygous deletions in PPT1, CLCN2, and PIGN. After reverse phenotyping, all variants were reported as causative. This study shows the interest in applying sequencing-based CNV detection, from available WES data, to reduce the diagnostic odyssey of additional patients unsolved DD/DI patients and compare the CNV-detection yield of Agilent array-CGH 4 × 180kb versus whole exome sequencing.

Exome sequencing allows detection of relevant pharmacogenetic variants in epileptic patients.

Beyond the identification of causal genetic variants in the diagnosis of Mendelian disorders, exome sequencing can detect numerous variants with potential relevance for clinical care. Clinical interventions can thus be conducted to improve future health outcomes for patients and their at-risk relatives, such as predicting late-onset genetic disorders accessible to prevention, treatment or identifying differential drug efficacy and safety. To evaluate the interest of such pharmacogenetic information, we designed an "in house" pipeline to determine the status of 122 PharmGKB (Pharmacogenomics Knowledgebase) variant-drug combinations in 31 genes. This pipeline was applied to a cohort of 90 epileptic patients who had previously an exome sequencing (ES) analysis, to determine the frequency of pharmacogenetic variants. We performed a retrospective analysis of drug plasma concentrations and treatment efficacy in patients bearing at least one relevant PharmGKB variant. For PharmGKB level 1A variants, CYP2C9 status for phenytoin prescription was the only relevant information. Nineteen patients were treated with phenytoin, among phenytoin-treated patients, none were poor metabolizers and four were intermediate metabolizers. While being treated with a standard protocol (10-23 mg/kg/30 min loading dose followed by 5 mg/kg/8 h maintenance dose), all identified intermediate metabolizers had toxic plasma concentrations (20 mg/L). In epileptic patients, pangenomic sequencing can provide information about common pharmacogenetic variants likely to be useful to guide therapeutic drug monitoring, and in the case of phenytoin, to prevent clinical toxicity caused by high plasma levels.

Experience and expectations of pharmacogenetic tests in France.

Although French genomic medicine is reaching a turning point in its history and the implementation of genome sequencing in routine is being implemented as part of the France Genomic Medicine 2025 Plan (FGMP), many questions about secondary data management remain to be addressed. In particular, the use of pharmacogenetic (PGx) information that can be extracted from genome data is a concern. We sought to analyze the opinion of French health professionals on their desire to have access to this information. For this purpose, we created a 22-item questionnaire on the experiences, attitudes, expectations, and knowledge of French physicians and pharmacists about PGx. We collected the responses in different groups and determined a knowledge score with the last 3 questions of the questionnaire. Then, we built a prediction model for this score and determined which factors may influence it. Half of the responders were physicians (158/311) and the other half were pharmacists (153/311), and the majority of them worked in a hospital (265/311). Almost two third (62.7%, 195/311) of the responders thought that pharmacogenetic data should be communicated with genomic results for the primary indication within the framework of FGMP, and 89.1% (277/311) of them that PGx tests could be an interesting tool to optimize patients' drug therapy in the future. Only 11.2% (35/311) of the responders reached the maximum knowledge score, while 25.4% (76/311) had already prescribed or recommended a PGx test. This study identified a need for training for French physicians and pharmacists in PGx, particularly given the interest of health professionals in it.

A second look at exome sequencing data: detecting mobile elements insertion in a rare disease cohort.

About 0.3% of all variants are due to de novo mobile element insertions (MEIs). The massive development of next-generation sequencing has made it possible to identify MEIs on a large scale. We analyzed exome sequencing (ES) data from 3232 individuals (2410 probands) with developmental and/or neurological abnormalities, with MELT, a tool designed to identify MEIs. The results were filtered by frequency, impacted region and gene function. Following phenotype comparison, two candidates were identified in two unrelated probands. The first mobile element (ME) was found in a patient referred for poikilodermia. A homozygous insertion was identified in the FERMT1 gene involved in Kindler syndrome. RNA study confirmed its pathological impact on splicing. The second ME was a de novo Alu insertion in the GRIN2B gene involved in intellectual disability, and detected in a patient with a developmental disorder. The frequency of de novo exonic MEIs in our study is concordant with previous studies on ES data. This project, which aimed to identify pathological MEIs in the coding sequence of genes, confirms that including detection of MEs in the ES pipeline can increase the diagnostic rate. This work provides additional evidence that ES could be used alone as a diagnostic exam.

Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders.

Purpose: Multi-omics offer worthwhile and increasingly accessible technologies to diagnostic laboratories seeking potential second-tier strategies to help patients with unresolved rare diseases, especially patients clinically diagnosed with a rare OMIM (Online Mendelian Inheritance in Man) disease. However, no consensus exists regarding the optimal diagnostic care pathway to adopt after negative results with standard approaches. Methods: In 15 unsolved individuals clinically diagnosed with recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach using several novel omics technologies to establish a molecular diagnosis. Inclusion criteria included a clinical autosomal recessive disease diagnosis and single heterozygous pathogenic variant in the gene of interest identified by first-line analysis (60%-9/15) or a clinical diagnosis of an X-linked recessive or autosomal dominant disease with no causative variant identified (40%-6/15). We performed a multi-step analysis involving short-read genome sequencing (srGS) and complementary approaches such as mRNA sequencing (mRNA-seq), long-read genome sequencing (lrG), or optical genome mapping (oGM) selected according to the outcome of the GS analysis. Results: SrGS alone or in combination with additional genomic and/or transcriptomic technologies allowed us to resolve 87% of individuals by identifying single nucleotide variants/indels missed by first-line targeted tests, identifying variants affecting transcription, or structural variants sometimes requiring lrGS or oGM for their characterization. Conclusion: Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we detail our experience of the implementation of genomics and transcriptomics technologies in a pilot cohort of previously investigated patients with a typical clinical diagnosis without molecular etiology.

Detection of the novel allele, HLA-A*32:165, in a French individual by next-generation sequencing.

The HLA-A*32:165 allele has one non-synonymous nucleotide change from HLA-A*32:01:01 at nucleotide 242 in exon 2.

Detection of relevant pharmacogenetic information through exome sequencing in oncology.

Background: Germline sequencing of individual genomes can detect alleles responsible for adverse drug reactions (ADRs) in relation to chemotherapy, targeted agents, antiemetics or pain treatment. Materials & methods: To evaluate the interest of such pharmacogenetic information, the authors retrospectively analyzed genes known to have an impact on cancer therapy in a cohort of 445 solid cancers patients. Results: Six patients treated with 5-fluorouracil carrying one DPYD variant classified as 1A showed decreased drug mean clearance (p = 0.01). Regarding CYP2D6, all patients (n = 5) with predicted CYP2D6 poor or ultra-rapid metabolizer status experienced adverse drug reactions related to opioid therapy. Conclusion: Genomic germline sequencing performed for theragnostic issues in patients with a solid tumor, can provide relevant information about common pharmacogenetic alleles.