Accurate detection of clinically relevant uniparental disomy from exome sequencing data

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Looking for Broken TAD Boundaries and Changes on DNA Interactions: Clinical Guide to 3D Chromatin Change Analysis in Complex Chromosomal Rearrangements and Chromothripsis

International audienceApparition of next-generation sequencing (NGS) was a breakthrough on knowledge of genome structure. Bioinformatic tools are a key point to analyze this huge amount of data from NGS and characterize the three-dimensional organization of chromosomes. This chapter describes usage of different browsers to explore publicly available online data and to search for possible 3D chromatin changes involved during complex chromosomal rearrangements as chromothripsis. Their pathogenic impact on clinical phenotype and gene misexpression can also be evaluated with annotated databases

Evaluating the Transition from Targeted to Exome Sequencing: A Guide for Clinical Laboratories

The transition from targeted to exome or genome sequencing in clinical contexts requires quality standards, such as targeted sequencing, in order to be fully adopted. However, no clear recommendations or methodology have emerged for evaluating this technological evolution. We developed a structured method based on four run-specific sequencing metrics and seven sample-specific sequencing metrics for evaluating the performance of exome sequencing strategies to replace targeted strategies. The indicators include quality metrics and coverage performance on gene panels and OMIM morbid genes. We applied this general strategy to three different exome kits and compared them with a myopathy-targeted sequencing method. After having achieved 80 million reads, all-tested exome kits generated data suitable for clinical diagnosis. However, significant differences in the coverage and PCR duplicates were observed between the kits. These are two main criteria to consider for the initial implementation with high-quality assurance. This study aims to assist molecular diagnostic laboratories in adopting and evaluating exome sequencing kits in a diagnostic context compared to the strategy used previously. A similar strategy could be used to implement whole-genome sequencing for diagnostic purposes

Predominance of BRCA2 mutation and estrogen receptor-positive breast cancer among BRCA1/2 mutation carriers.

International audience551 Background: PARP inhibitor (PARPi) agents can improve progression-free survival of patients with breast cancer (BC) who carry a germline BRCA1 or BRCA2 pathogenic or likely pathogenic variant (gBRCA1/2) in both the metastatic and adjuvant setting. Therefore, we need to redefine the criteria of women and tumor phenotype that should be tested for gBRCA1/2. Methods: We studied the relative distribution of gBRCA1 and gBRCA2 in unselected populations of women with BC and in unaffected individuals. We also analyzed the proportion of estrogen receptor (ER)-positive (ER+) tumors in unselected BC patients with gBRCA1/2.We performed a meta-analysis of studies of unselected BC that analyzed the relative contribution of gBRCA1 versus gBRCA2 and ER+ tumors among gBRCA1/2 carriers. We then performed a meta-analysis of gBRCA1/2 carriage in unaffected individuals, from genome-wide population studies, the gnomAD databank, and case–control studies. Results: The BRCA2 gene was involved in 54% of BC in unselected patients with gBRCA1/2 (n=108,699) and 59% of unaffected individuals (n=238,973) as compared with 38% of gBRCA1/2 family cohorts (n=29,700). The meta-analysis showed that 1.66% (95% CI 1.08-2.54) and 1.71% (95% CI 1.33-2.2) of unselected BC patients carried a gBRCA1 and gBRCA2, respectively. In unaffected individuals, the frequency of heterozygosity for gBRCA1 and gBRCA2 was estimated at 1/434 and 1/288, respectively. Nearly 0.5% of unaffected individuals in the studied populations carried a gBRCA1/2. Carriage of a gBRCA was 2.5% for patients with ER+ tumors (95% CI 1.5-4.1) and 5.7% (95% CI 5.1-6.2) for those with ER- tumors. Overall, 58% of breast tumors occurring in women carrying a gBRCA1/2 were ER+ (n=86,870). Conclusions: This meta-analysis showed that gBRCA2 carriage is predominant in unselected BC and in unaffected individuals. ER+ tumors among women with gBRCA1/2-related BC is predominant and has been underestimated. Because PARPi agents improve progression-free survival with ER+ gBRCA1/2 BC in both the adjuvant and metastatic setting, BC should be considered regardless of ER status for BRCA1/2 screening for therapeutic purposes

Disruption of chromatin organisation causes MEF2C gene overexpression in intellectual disability: a case report

BACKGROUND: Balanced structural variants are mostly described in disease with gene disruption or subtle rearrangement at breakpoints. CASE PRESENTATION: Here we report a patient with mild intellectual deficiency who carries a de novo balanced translocation t(3;5). Breakpoints were fully explored by microarray, Array Painting and Sanger sequencing. No gene disruption was found but the chromosome 5 breakpoint was localized 228-kb upstream of the MEF2C gene. The predicted Topologically Associated Domains analysis shows that it contains only the MEF2C gene and a long non-coding RNA LINC01226. RNA studies looking for MEF2C gene expression revealed an overexpression of MEF2C in the lymphoblastoid cell line of the patient. CONCLUSIONS: Pathogenicity of MEF2C overexpression is still unclear as only four patients with mild intellectual deficiency carrying 5q14.3 microduplications containing MEF2C are described in the literature. The microduplications in these individuals also contain other genes expressed in the brain. The patient presented the same phenotype as 5q14.3 microduplication patients. We report the first case of a balanced translocation leading to an overexpression of MEF2C similar to a functional duplication.status: publishe

Predominance of BRCA2 Mutation and Estrogen Receptor Positivity in Unselected Breast Cancer with BRCA1 or BRCA2 Mutation

International audienceBackground: Poly(ADP-ribose) polymerase 1 inhibitor (PARPi) agents can improve progression-free survival of patients with breast cancer who carry a germline BRCA1 or BRCA2 pathogenic or likely pathogenic variant (gBRCA) in both the metastatic and adjuvant setting. Therefore, we need to reassess the frequency of gBRCA1 and gBRCA2 in order to redefine the criteria for women and tumor phenotype that should be tested. Objective: We studied the relative distribution of gBRCA1 and gBRCA2 in unselected populations of women with breast cancer and in unaffected individuals. We also analyzed the proportion of estrogen receptor (ER)-positive (ER+) tumors in unselected breast cancer patients with gBRCA. Design: We performed a meta-analysis of studies of unselected breast cancer that analyzed the relative contribution of gBRCA1 versus gBRCA2 among unselected breast cancer cases in gBRCA carriers. We then performed a meta-analysis of gBRCA carriage in unaffected individuals from genome-wide population studies, the gnomAD databank, and case–control studies. Results: The BRCA2 gene was involved in 54% of breast cancer cases in unselected patients with gBRCA (n = 108,699) and 60% of unaffected individuals (n = 238,973) as compared with 38% of the largest gBRCA family cohort (n = 29,700). The meta-analysis showed that 1.66% (95% CI 1.08–2.54) and 1.71% (95% CI 1.33–2.2) of unselected breast cancer patients carried gBRCA1 and gBRCA2, respectively. In a population of unaffected individuals, the frequency of heterozygosity for gBRCA1 and gBRCA2 was estimated at 1/434 and 1/288, respectively. Nearly 0.5% of unaffected individuals in the studied populations carried a gBRCA. Carriage of a gBRCA was 2.5% for patients with ER+ tumors (95% CI 1.5–4.1) and 5.7% (95% CI 5.1–6.2) for those with ER- tumors. Overall, 58% of breast tumors occurring in women carrying a gBRCA were ER+ (n = 86,870). Conclusions: This meta-analysis showed that gBRCA2 carriage is predominant in unselected breast cancer patients and unaffected individuals. ER+ tumors among women with gBRCA-related breast cancer are predominant and have been underestimated. Because PARPi agents improve progression-free survival with ER+ gBRCA breast cancer in most clinical trials, breast cancer should be considered, regardless of ER status, for BRCA1/2 screening for therapeutic purposes

Disruption of chromatin organisation causes MEF2C gene overexpression in intellectual disability: a case report

International audienceBACKGROUND:Balanced structural variants are mostly described in disease with gene disruption or subtle rearrangement at breakpoints.CASE PRESENTATION:Here we report a patient with mild intellectual deficiency who carries a de novo balanced translocation t(3;5). Breakpoints were fully explored by microarray, Array Painting and Sanger sequencing. No gene disruption was found but the chromosome 5 breakpoint was localized 228-kb upstream of the MEF2C gene. The predicted Topologically Associated Domains analysis shows that it contains only the MEF2C gene and a long non-coding RNA LINC01226. RNA studies looking for MEF2C gene expression revealed an overexpression of MEF2C in the lymphoblastoid cell line of the patient.CONCLUSIONS:Pathogenicity of MEF2C overexpression is still unclear as only four patients with mild intellectual deficiency carrying 5q14.3 microduplications containing MEF2C are described in the literature. The microduplications in these individuals also contain other genes expressed in the brain. The patient presented the same phenotype as 5q14.3 microduplication patients. We report the first case of a balanced translocation leading to an overexpression of MEF2C similar to a functional duplication

Next generation phenotyping for diagnosis and phenotype–genotype correlations in Kabuki syndrome

Abstract The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photographs and distinguish KS1 (KS type 1, KMT2D-related) from KS2 (KS type 2, KDM6A-related). We included retrospectively and prospectively, from 1998 to 2023, all frontal and lateral pictures of patients with a molecular confirmation of KS. After automatic preprocessing, we extracted geometric and textural features. After incorporation of age, gender, and ethnicity, we used XGboost (eXtreme Gradient Boosting), a supervised machine learning classifier. The model was tested on an independent validation set. Finally, we compared the performances of our model with DeepGestalt (Face2Gene). The study included 1448 frontal and lateral facial photographs from 6 centers, corresponding to 634 patients (527 controls, 107 KS); 82 (78%) of KS patients had a variation in the KMT2D gene (KS1) and 23 (22%) in the KDM6A gene (KS2). We were able to distinguish KS from controls in the independent validation group with an accuracy of 95.8% (78.9–99.9%, p < 0.001) and distinguish KS1 from KS2 with an empirical Area Under the Curve (AUC) of 0.805 (0.729–0.880, p < 0.001). We report an automatic detection model for KS with high performances (AUC 0.993 and accuracy 95.8%). We were able to distinguish patients with KS1 from KS2, with an AUC of 0.805. These results outperform the current commercial AI-based solutions and expert clinicians

A Reliable Targeted Next-Generation Sequencing Strategy for Diagnosis of Myopathies and Muscular Dystrophies, Especially for the Giant Titin and Nebulin Genes

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Using deep-neural-network-driven facial recognition to identify distinct Kabuki syndrome 1 and 2 gestalt

International audienceKabuki syndrome (KS) is a rare genetic disorder caused by mutations in two major genes, KMT2D and KDM6A, that are responsible for Kabuki syndrome 1 (KS1, OMIM147920) and Kabuki syndrome 2 (KS2, OMIM300867), respectively. We lack a description of clinical signs to distinguish KS1 and KS2. We used facial morphology analysis to detect any facial morphological differences between the two KS types. We used a facial-recognition algorithm to explore any facial morphologic differences between the two types of KS. We compared several image series of KS1 and KS2 individuals, then compared images of those of Caucasian origin only (12 individuals for each gene) because this was the main ethnicity in this series. We also collected 32 images from the literature to amass a large series. We externally validated results obtained by the algorithm with evaluations by trained clinical geneticists using the same set of pictures. Use of the algorithm revealed a statistically significant difference between each group for our series of images, demonstrating a different facial morphotype between KS1 and KS2 individuals (mean area under the receiver operating characteristic curve = 0.85 [p = 0.027] between KS1 and KS2). The algorithm was better at discriminating between the two types of KS with images from our series than those from the literature (p = 0.0007). Clinical geneticists trained to distinguished KS1 and KS2 significantly recognised a unique facial morphotype, which validated algorithm findings (p = 1.6e-11). Our deep-neural-network-driven facial-recognition algorithm can reveal specific composite gestalt images for KS1 and KS2 individuals