Place of concordance-discordance model in evaluating NGS performance.

INTRODUCTION: Ideally, evaluating NGS performance requires a gold standard; in its absence, concordance between replicates is often used as substitute standard. However, the appropriateness of the concordance-discordance criterion has been rarely evaluated. This study analyzes the relationship between the probability of discordance and the probability of error under different conditions. METHODS: This study used a conditional probability approach under conditional dependence then conditional independence between two sequencing results and compares the probabilities of discordance and error in different theoretical conditions of sensitivity, specificity, and correlation between replicates, then on real results of sequencing genome NA12878. The study examines also covariate effects on discordance and error using generalized additive models with smooth functions. RESULTS: With 99% sensitivity and 99.9% specificity under conditional independence, the probability of error for a positive concordant pair of calls is 0.1%. With additional hypotheses of 0.1% prevalence and 0.9 correlation between replicates, the probability of error for a positive concordant pair is 47.4%. With real data, the estimated sensitivity, specificity, and correlation between tests for variants are around 98.98%, 99.996%, and 93%, respectively, and the error rate for positive concordant calls approximates 2.5%. In covariate effect analyses, the effects' functional form are close between discordance and error models, though the parts of deviance explained by the covariates differ between discordance and error models. CONCLUSION: With conditional independence of two sequencing results, the concordance-discordance criterion seems acceptable as substitute standard. However, with high correlation, the criterion becomes questionable because a high percentage of false concordant results appears among concordant results.

Direct Comparative Analysis of a Pharmacogenomics Panel with PacBio Hifi® Long-Read and Illumina Short-Read Sequencing.

BACKGROUND: Pharmacogenetics (PGx) aims to determine genetic signatures that can be used in clinical settings to individualize treatment for each patient, including anti-cancer drugs, anti-psychotics, and painkillers. Taken together, a better understanding of the impacts of genetic variants on the corresponding protein function or expression permits the prediction of the pharmacological response: responders, non-responders, and those with adverse drug reactions (ADRs). OBJECTIVE: This work provides a comparison between innovative long-read sequencing (LRS) and short-read sequencing (SRS) techniques. METHODS AND MATERIALS: The gene panel captured using PacBio HiFi® sequencing was tested on thirteen clinical samples on GENTYANE's platform. SRS, using a comprehensive pharmacogenetics panel, was performed in routine settings at the Civil Hospitals of Lyon. We focused on complex regions analysis, including copy number variations (CNVs), structural variants, repeated regions, and phasing-haplotyping for three key pharmacogenes: CYP2D6, UGT1A1, and NAT2. RESULTS: Variants and the corresponding expected star (*) alleles were reported. Although only 38.4% concordance was found for haplotype determination and 61.5% for diplotype, this did not affect the metabolism scoring. A better accuracy of LRS was obtained for the detection of the CYP2D6*5 haplotype in the presence of the duplicated wild-type CYP2D6*2 form. A total concordance was performed for UGT1A1 TA repeat detection. Direct phasing using the LRS approach allowed us to correct certain NAT2 profiles. CONCLUSIONS: Combining an optimized variant-calling pipeline and with direct phasing analysis, LRS is a robust technique for PGx analysis that can minimize the risk of mis-haplotyping.

Performance comparisons between clustering models for reconstructing NGS results from technical replicates.

To improve the performance of individual DNA sequencing results, researchers often use replicates from the same individual and various statistical clustering models to reconstruct a high-performance callset. Here, three technical replicates of genome NA12878 were considered and five model types were compared (consensus, latent class, Gaussian mixture, Kamila-adapted k-means, and random forest) regarding four performance indicators: sensitivity, precision, accuracy, and F1-score. In comparison with no use of a combination model, i) the consensus model improved precision by 0.1%; ii) the latent class model brought 1% precision improvement (97%-98%) without compromising sensitivity (= 98.9%); iii) the Gaussian mixture model and random forest provided callsets with higher precisions (both >99%) but lower sensitivities; iv) Kamila increased precision (>99%) and kept a high sensitivity (98.8%); it showed the best overall performance. According to precision and F1-score indicators, the compared non-supervised clustering models that combine multiple callsets are able to improve sequencing performance vs. previously used supervised models. Among the models compared, the Gaussian mixture model and Kamila offered non-negligible precision and F1-score improvements. These models may be thus recommended for callset reconstruction (from either biological or technical replicates) for diagnostic or precision medicine purposes.

Paired Comparison of Routine Molecular Screening of Patient Samples with Advanced Non-Small Cell Lung Cancer in Circulating Cell-Free DNA Using Three Targeted Assays.

INTRODUCTION: Progressive advanced non-small cell lung cancer (NSCLC) accounts for about 80-85% of all lung cancers. Approximately 10-50% of patients with NSCLC harbor targetable activating mutations, such as in-frame deletions in Exon 19 (Ex19del) of EGFR. Currently, for patients with advanced NSCLC, testing for sensitizing mutations in EGFR is mandatory prior to the administration of tyrosine kinase inhibitors. PATIENTS AND METHODS: Plasma was collected from patients with NSCLC. We carried out targeted NGS using the Plasma-SeqSensei™ SOLID CANCER IVD kit on cfDNA (circulating free DNA). Clinical concordance for plasma detection of known oncogenic drivers was reported. In a subset of cases, validation was carried out using an orthogonal OncoBEAMTM EGFR V2 assay, as well as with our custom validated NGS assay. Somatic alterations were filtered, removing somatic mutations attributable to clonal hematopoiesis for our custom validated NGS assay. RESULTS: In the plasma samples, driver targetable mutations were studied, with a mutant allele frequency (MAF) ranging from 0.00% (negative detection) to 82.25%, using the targeted next-generation sequencing Plasma-SeqSensei™ SOLID CANCER IVD Kit. In comparison with the OncoBEAMTM EGFR V2 kit, the EGFR concordance is 89.16% (based on the common genomic regions). The sensitivity and specificity rates based on the genomic regions (EGFR exons 18, 19, 20, and 21) were 84.62% and 94.67%. Furthermore, the observed clinical genomic discordances were present in 25% of the samples: 5% in those linked to the lower of coverage of the OncoBEAMTM EGFR V2 kit, 7% in those induced by the sensitivity limit on the EGFR with the Plasma-SeqSensei™ SOLID CANCER IVD Kit, and 13% in the samples linked to the larger KRAS, PIK3CA, BRAF coverage of the Plasma-SeqSensei™ SOLID CANCER IVD kit. Most of these somatic alterations were cross validated in our orthogonal custom validated NGS assay, used in the routine management of patients. The concordance is 82.19% in the common genomic regions (EGFR exons 18, 19, 20, 21; KRAS exons 2, 3, 4; BRAF exons 11, 15; and PIK3CA exons 10, 21). The sensitivity and specificity rates were 89.38% and 76.12%, respectively. The 32% of genomic discordances were composed of 5% caused by the limit of coverage of the Plasma-SeqSensei™ SOLID CANCER IVD kit, 11% induced by the sensitivity limit of our custom validated NGS assay, and 16% linked to the additional oncodriver analysis, which is only covered by our custom validated NGS assay. CONCLUSIONS: The Plasma-SeqSensei™ SOLID CANCER IVD kit resulted in de novo detection of targetable oncogenic drivers and resistance alterations, with a high sensitivity and accuracy for low and high cfDNA inputs. Thus, this assay is a sensitive, robust, and accurate test.

A new 165-SNP low-density lipoprotein cholesterol polygenic risk score based on next generation sequencing outperforms previously published scores in routine diagnostics of familial hypercholesterolemia.

Genetic diagnosis of familial hypercholesterolemia (FH) remains unexplained in 30 to 70% of patients after exclusion of monogenic disease. There is now a growing evidence that a polygenic burden significantly modulates LDL-cholesterol (LDL-c) concentrations. Several LDL-c polygenic risk scores (PRS) have been set up. However, the balance between their diagnosis performance and their practical use in routine practice is not clearly established. Consequently, we set up new PRS based on our routine panel for sequencing and compared their diagnostic performance with previously-published PRS. After a meta-analysis, four new PRS including 165 to 1633 SNP were setup using different softwares. They were established using two French control cohorts (MONA LISA n=1082 and FranceGenRef n=856). Then the explained LDL-c variance and the ability of each PRS to discriminate monogenic negative FH patients (M-) versus healthy controls were compared with 4 previously-described PRS in 785 unrelated FH patients. Between all PRS, the 165-SNP PRS developed with PLINK showed the best LDL-c explained variance (adjusted R²=0.19) and the best diagnosis abilities (AUROC=0.77, 95%CI=0.74-0.79): it significantly outperformed all the previously-published PRS (p<1 × 10-4). By using a cut-off at the 75th percentile, 61% of M- patients exhibited a polygenic hypercholesterolemia with the 165-SNP PRS versus 48% with the previously published 12-SNP PRS (p =3.3 × 10-6). These results were replicated using the UK biobank. This new 165-SNP PRS, usable in routine diagnosis, exhibits better diagnosis abilities for a polygenic hypercholesterolemia diagnosis. It would be a valuable tool to optimize referral for whole genome sequencing.

Familial transmission of chromoanagenesis leads to unpredictable unbalanced rearrangements through meiotic recombination.

Chromoanagenesis is a cellular mechanism that leads to complex chromosomal rearrangements (CCR) during a single catastrophic event. It may result in loss and/or gain of genetic material and may be responsible for various phenotypes. These rearrangements are usually sporadic. However, some familial cases have been reported. Here, we studied six families in whom an asymptomatic or paucisymptomatic parent transmitted a CCR to its offspring in an unbalanced manner. The rearrangements were characterized by karyotyping, fluorescent in situ hybridization, chromosomal microarray (CMA) and/or whole genome sequencing (WGS) in the carrier parents and offspring. We then hypothesized meiosis-pairing figures between normal and abnormal parental chromosomes that may have led to the formation of new unbalanced rearrangements through meiotic recombination. Our work indicates that chromoanagenesis might be associated with a normal phenotype and normal fertility, even in males, and that WGS may be the only way to identify these events when there is no imbalance. Subsequently, the CCR can be transmitted to the next generation in an unbalanced and unpredictable manner following meiotic recombination. Thereby, prenatal diagnosis using CMA should be proposed to these families to detect any pathogenic imbalances in the offspring.

Complete characterisation of two new large Xq28 duplications involving F8 using whole genome sequencing in patients without haemophilia A.

INTRODUCTION: Depending on the location of insertion of the gained region, F8 duplications can have variable clinical impacts from benign impact to severe haemophilia A phenotype. AIM: To characterize two large Xq28 duplications involving F8 incidentally detected by chromosome microarray analysis (CMA) in two patients presenting severe intellectual disability but no history of bleeding disorder. METHODS: Whole genome sequencing (WGS) was performed in order to characterize the two large Xq28 duplications at nucleotide level. RESULTS: In patient 1, a 60-73 kb gained region encompassing the exons 23-26 of F8 and SMIM9 was inserted at the int22h-2 locus following a non-homologous recombination between int22h-1 and int22h-2. We hypothesized that two independent events, micro-homology-mediated break-induced replication (MMBIR) and break-induced replication (BIR), could be involved in this rearrangement. In patient 2, the CMA found duplication from 101 to 116-kb long encompassing the exons 16-26 of F8 and SMIM9. The WGS analysis identified a more complex rearrangement with the presence of three genomic junctions. Due to the multiple micro-homologies observed at breakpoints, a replication-based mechanism such as fork stalling and template switching (FoSTeS) was greatly suspected. In both cases, these complex rearrangements preserved an intact copy of the F8. CONCLUSION: This study highlights the value of WGS to characterize the genomic junction at the nucleotide level and ultimately better describe the molecular mechanisms involved in Xq28 structural variations. It also emphasizes the importance of specifying the structure of the genomic gain in order to improve genotype-phenotype correlation and genetic counselling.

Performances of Targeted RNA Sequencing for the Analysis of Fusion Transcripts, Gene Mutation, and Expression in Hematological Malignancies.

RNA sequencing holds great promise to improve the diagnostic of hematological malignancies, because this technique enables to detect fusion transcripts, to look for somatic mutations in oncogenes, and to capture transcriptomic signatures of nosological entities. However, the analytical performances of targeted RNA sequencing have not been extensively described in diagnostic samples. Using a targeted panel of 1385 cancer-related genes in a series of 100 diagnosis samples and 8 controls, we detected all the already known fusion transcripts and also discovered unknown and/or unsuspected fusion transcripts in 12 samples. Regarding the analysis of transcriptomic profiles, we show that targeted RNA sequencing is performant to discriminate acute lymphoblastic leukemia entities driven by different oncogenic translocations. Additionally, we show that 86% of the mutations identified at the DNA level are also detectable at the messenger RNA (mRNA) level, except for nonsense mutations that are subjected to mRNA decay. We conclude that targeted RNA sequencing might improve the diagnosis of hematological malignancies. Standardization of the preanalytical steps and further refinements of the panel design and of the bioinformatical pipelines will be an important step towards its use in standard diagnostic procedures.

Whole Sequencing of Most Prevalent Dilated Cardiomyopathy-Causing Genes as a Molecular Strategy to Improve Molecular Diagnosis Efficiency?

Dilated cardiomyopathy (DCM) is the most common form of cardiomyopathy and one of the most common causes of heart failure. TTN-truncating variants represent the most common cause of DCM. Similarly, among other prevalent DCM-causing genes, truncating variants were also frequently detected in BAG3, DSP, FLNC, and LMNA. For these four genes, the current study aims to determine the prevalence of deep intronic pathogenic variants that could lead to splice defects. A next-generation sequencing (NGS) workflow based on whole gene sequencing of BAG3, DSP, FLNC, and LMNA of a cohort of 95 DCM patients, for whom no putatively causative point mutations were identified after NGS of a panel of 48 cardiomyopathy-causing genes, was thus performed. Our approach did not lead us to reconsider the molecular diagnosis of any patient of the cohort. This study suggests that deep splice mutations do not account for a significant proportion of DCM cases. In contrast with MYBPC3 in hypertrophic cardiomyopathy cases, NGS of BAG3, DSP, FLNC, and LMNA whole intronic sequences would not significantly improve the efficiency of molecular diagnosis of DCM probands.

Impact of interleukin-6 on drug transporters and permeability in the hCMEC/D3 blood-brain barrier model.

The blood-brain barrier (BBB) is a highly selective membrane composed predominantly of brain capillary endothelial cells expressing drug efflux transporters that prevent substrates from accessing the brain. Inflammation is associated with central nervous system diseases and can impair BBB permeability via several mechanisms, including altered transporter and cell junction expression. This can modify the brain's exposure to drugs. However, comprehensive genomic analysis of the impact of interleukin (IL)-6, which plays a key role in the inflammatory response, on the BBB is lacking. In the present study, we analyzed the effects of exposure of hCMEC/D3 cells to 20 ng/mL IL-6 for 72 h. We performed RNA sequencing and ABC transporter efflux assays. Physiologically based pharmacokinetics (PBPK) simulations were conducted to evaluate the potential impact of IL-6 on the digoxin pharmacokinetics profile and brain exposure by decreasing BBB ABCB1 efflux activity. Exposure of hCMEC/D3 cells to IL-6 triggered the deregulation of numerous genes involved in barrier permeability, such as cell junctions, focal adherens complex, and cell adhesion molecules. We observed mild modification of the mRNA expression and efflux activities of ABC transporters. PBPK simulation showed that, if we only consider the impact of IL-6 on ABCB1 transporter, the modification of the digoxin pharmacokinetics profile and brain exposure is slight. IL-6 slightly affected the gene expression levels and activities of ABC transporters on BBB cells, exhibiting a weaker effect than on hepatic cells. However, inflammation may cause other modifications, such as altered BBB permeability, that could modify drug pharmacokinetics.

In Vivo Characterization of the Toxicological Properties of DPhP, One of the Main Degradation Products of Aryl Phosphate Esters.

BACKGROUND: Aryl phosphate esters (APEs) are widely used and commonly present in the environment. Health hazards associated with these compounds remain largely unknown and the effects of diphenyl phosphate (DPhP), one of their most frequent derivatives, are poorly characterized. OBJECTIVE: Our aim was to investigate whether DPhP per se may represent a more relevant marker of exposure to APEs than direct assessment of their concentration and determine its potential deleterious biological effects in chronically exposed mice. METHODS: Conventional animals (FVB mice) were acutely or chronically exposed to relevant doses of DPhP or to triphenyl phosphate (TPhP), one of its main precursors. Both molecules were measured in blood and other tissues by liquid chromatography-mass spectrometry (LC-MS). Effects of chronic DPhP exposure were addressed through liver multi-omics analysis to determine the corresponding metabolic profile. Deep statistical exploration was performed to extract correlated information, guiding further physiological analyses. RESULTS: Multi-omics analysis confirmed the existence of biological effects of DPhP, even at a very low dose of 0.1mg/mL in drinking water. Chemical structural homology and pathway mapping demonstrated a clear reduction of the fatty acid catabolic processes centered on acylcarnitine and mitochondrial ß-oxidation in mice exposed to DPhP in comparison with those treated with vehicle. An interesting finding was that in mice exposed to DPhP, mRNA, expression of genes involved in lipid catabolic processes and regulated by peroxisome proliferator-activated receptor alpha (PPARα) was lower than that in vehicle-treated mice. Immunohistochemistry analysis showed a specific down-regulation of HMGCS2, a kernel target gene of PPARα. Overall, DPhP absorption disrupted body weight-gain processes. CONCLUSIONS: Our results suggest that in mice, the effects of chronic exposure to DPhP, even at a low dose, are not negligible. Fatty acid metabolism in the liver is essential for controlling fast and feast periods, with adverse consequences on the overall physiology. Therefore, the impact of DPhP on circulating fat, cardiovascular pathologies and metabolic disease incidence deserves, in light of our results, further investigations. https://doi.org/10.1289/EHP6826.

PCSK9 post-transcriptional regulation: Role of a 3'UTR microRNA-binding site variant in linkage disequilibrium with c.1420G.

BACKGROUND AND AIMS: Proprotein convertase subtilisin/kexin type 9 (PCSK9) plays a crucial role in cholesterol homeostasis. A common variant, the G allele in position c.1420 (c.1420G), has been associated with a decrease of both plasma PCSK9 and LDL-cholesterol concentrations. However, the functional effect of this variant is currently not well understood. We hypothesized that it could be explained by functional variants in linkage disequilibrium (LD), more specifically, by variants located in the PCSK9 3' UTR as targets for miR regulation of PCSK9 expression. METHODS: Variations in LD with c.1420G were studied in 1029 patients followed for dyslipidaemia. In silico studies identified potential miRNA binding sites induced by PCSK9 3'UTR variants in LD with c.1420G. Their functionality was studied with a luciferase reporter assay in HuH-7 cells and confirmed by cotransfection of anti-miRNAs. RESULTS: The c.*571C and c.*234T variants located in the PCSK9 3'UTR were found in tight LD with c.1420G (D' = 0.962; LOD = 163.06). The haplotype carrying c.*571C showed a 6.7% decrease in luciferase activity (p = 0.003). Inhibition of hsa-miR-1228-3p and hsa-miR-143-5p counteracted their effect on the haplotype carrying c.*571C allele, suggesting that PCSK9 expression was decreased by the endogenous binding of hsa-miR-1228-3p and hsa-miR-143-5p on its 3'UTR. CONCLUSIONS: This post-transcriptional regulation might contribute towards the association between plasma PCSK9 levels and c.1420G. Such regulation of PCSK9 expression may open new perspectives for the treatment of hypercholesterolemia and atherosclerosis cardiovascular diseases.

Chromosomal instability in the prediction of pituitary neuroendocrine tumors prognosis.

The purpose of this study was to analyze the impact of copy number variations (CNV) on sporadic pituitary neuroendocrine tumors (PitNETs) prognosis, to identify specific prognosis markers according to the known clinico-pathological classification. CGH array analysis was performed on 195 fresh-frozen PitNETs (56 gonadotroph, 11 immunonegative, 56 somatotroph, 39 lactotroph and 33 corticotroph), with 5 years post-surgery follow-up (124 recurrences), classified according to the five-tiered grading classification (invasion, Ki-67, mitotic index and p53 positivity). Effect of alterations on recurrence was studied using logistic regression models. Transcriptomic analysis of 32 lactotroph tumors was performed. The quantity of CNV was dependent on tumor type: higher in lactotroph (median(min-max) = 38% (0-97) of probes) compared to corticotroph (11% (0-77)), somatotroph (5% (0-99)), gonadotroph (0% (0-10)) and immunonegative tumors (0% (0-17). It was not predictive of recurrence in the whole cohort. In lactotroph tumors, genome instability, especially quantity of gains, significantly predicted recurrence independently of invasion and proliferation (p-value = 0.02, OR = 1.2). However, no specific CNV was found as a prognostic marker. Transcriptomic analysis of the genes included in the CNV and associated with prognosis didn't show significantly overrepresented pathway. In somatotroph and corticotroph tumors, USP8 and GNAS mutations were not associated with genome disruption or recurrence respectively. To conclude, CGH array analysis showed genome instability was dependent on PitNET type. Lactotroph tumors were highly altered and the quantity of altered genome was associated with poorer prognosis though the mechanism is unclear, whereas gonadotroph and immunonegative tumors showed the same 'quiet' profile, leaving the mechanism underlying tumorigenesis open to question.

Development of a new expanded next-generation sequencing panel for genetic diseases involved in dyslipidemia.

The aim of this study was to provide an efficient tool: reliable, able to increase the molecular diagnosis performance, to facilitate the detection of copy number variants (CNV), to assess genetic risk scores (wGRS) and to offer the opportunity to explore candidate genes. Custom SeqCap EZ libraries, NextSeq500 sequencing and a homemade pipeline enable the analysis of 311 dyslipidemia-related genes. In the training group (48 DNA from patients with a well-established molecular diagnosis), this next-generation sequencing (NGS) workflow showed an analytical sensitivity >99% (n = 532 variants) without any false negative including a partial deletion of one exon. In the prospective group, from 25 DNA from patients without prior molecular analyses, 18 rare variants were identified in the first intention panel genes, allowing the diagnosis of monogenic dyslipidemia in 11 patients. In six other patients, the analysis of minor genes and wGRS determination provided a hypothesis to explain the dyslipidemia. Remaining data from the whole NGS workflow identified four patients with potentially deleterious variants. This NGS process gives a major opportunity to accede to an enhanced understanding of the genetic of dyslipidemia by simultaneous assessment of multiple genetic determinants.

Comparison of Nucleic Acid Extraction Methods for a Viral Metagenomics Analysis of Respiratory Viruses.

Viral metagenomics next-generation sequencing (mNGS) is increasingly being used to characterize the human virome. The impact of viral nucleic extraction on virome profiling has been poorly studied. Here, we aimed to compare the sensitivity and sample and reagent contamination of three extraction methods used for viral mNGS: two automated platforms (eMAG; MagNA Pure 24, MP24) and the manual QIAamp Viral RNA Mini Kit (QIAamp). Clinical respiratory samples (positive for Respiratory Syncytial Virus or Herpes Simplex Virus), one mock sample (including five viruses isolated from respiratory samples), and a no-template control (NTC) were extracted and processed through an mNGS workflow. QIAamp yielded a lower proportion of viral reads for both clinical and mock samples. The sample cross-contamination was higher when using MP24, with up to 36.09% of the viral reads mapping to mock viruses in the NTC (vs. 1.53% and 1.45% for eMAG and QIAamp, respectively). The highest number of viral reads mapping to bacteriophages in the NTC was found with QIAamp, suggesting reagent contamination. Our results highlight the importance of the extraction method choice for accurate virome characterization.

Sequence variations of ACVRL1 play a critical role in hepatic vascular malformations in hereditary hemorrhagic telangiectasia.

BACKGROUND: Hereditary Hemorrhagic Telangiectasia (HHT) is an autosomal dominant disorder characterized by multiple telangiectases and caused by germline disease-causing variants in the ENG (HHT1), ACVRL1 (HHT2) and, to a lesser extent MADH4 and GDF2, which encode proteins involved in the TGF-ß/BMP9 signaling pathway. Common visceral complications of HHT are caused by pulmonary, cerebral, or hepatic arteriovenous malformations (HAVMs). There is large intrafamilial variability in the severity of visceral involvement, suggesting a role for modifier genes. The objective of the present study was to investigate the potential role of ENG, ACVRL1, and of other candidate genes belonging to the same biological pathway in the development of HAVMs. METHODS: We selected 354 patients from the French HHT patient database who had one disease causing variant in either ENG or ACVRL1 and who underwent hepatic exploration. We first compared the distribution of the different types of variants with the occurrence of HAVMs. Then, we genotyped 51 Tag-SNPs from the Hap Map database located in 8 genes that encode proteins belonging to the TGF-ß/BMP9 pathway (ACVRL1, ENG, GDF2, MADH4, SMAD1, SMAD5, TGFB1, TGFBR1), as well as in two additional candidate genes (PTPN14 and ADAM17). We addressed the question of a possible genetic association with the occurrence of HAVMs. RESULTS: The proportion of patients with germline ACVRL1 variants and the proportion of women were significantly higher in HHT patients with HAVMs. In the HHT2 group, HAVMs were more frequent in patients with truncating variants. Six SNPs (3 in ACVRL1, 1 in ENG, 1 in SMAD5, and 1 in ADAM17) were significantly associated with HAVMs. After correction for multiple testing, only one remained significantly associated (rs2277383). CONCLUSIONS: In this large association study, we confirmed the strong relationship between ACVRL1 and the development of HAVMs. Common polymorphisms of ACVRL1 may also play a role in the development of HAVMs, as a modifying factor, independently of the disease-causing variants.

Genome sequencing in cytogenetics: Comparison of short-read and linked-read approaches for germline structural variant detection and characterization.

BACKGROUND: Structural variants (SVs) include copy number variants (CNVs) and apparently balanced chromosomal rearrangements (ABCRs). Genome sequencing (GS) enables SV detection at base-pair resolution, but the use of short-read sequencing is limited by repetitive sequences, and long-read approaches are not yet validated for diagnosis. Recently, 10X Genomics proposed Chromium, a technology providing linked-reads to reconstruct long DNA fragments and which could represent a good alternative. No study has compared short-read to linked-read technologies to detect SVs in a constitutional diagnostic setting yet. The aim of this work was to determine whether the 10X Genomics technology enables better detection and comprehension of SVs than short-read WGS. METHODS: We included 13 patients carrying various SVs. Whole genome analyses were performed using paired-end HiSeq X sequencing with (linked-read strategy) or without (short-read strategy) Chromium library preparation. Two different bioinformatic pipelines were used: Variants are called using BreakDancer for short-read strategy and LongRanger for long-read strategy. Variant interpretations were first blinded. RESULTS: The short-read strategy allowed diagnosis of known SV in 10/13 patients. After unblinding, the linked-read strategy identified 10/13 SVs, including one (patient 7) missed by the short-read strategy. CONCLUSION: In conclusion, regarding the results of this study, 10X Genomics solution did not improve the detection and characterization of SV.

Comparison of crossover and parallel-group designs for the identification of a binary predictive biomarker of the treatment effect.

Pros and cons of crossover design are well known for estimating the treatment effect compared to parallel-group design, but remain unclear for identifying and estimating an interaction between a potential biomarker and the treatment effect. Such 'predictive' biomarkers, or 'effect modifiers', help to predict the response to specific treatments. The purpose of this report was to better characterize the advantages and disadvantages of crossover versus parallel-group design to identify predictive biomarkers. The treatment effect, the effect of a binary biomarker and their interaction were modelled using a linear model. The intra-subject correlation in the crossover design was taken into account through an intra-class correlation coefficient. The variance-covariance matrix of the parameters was derived and compared. For both trial designs, the variance of the parameter estimating an interaction between the treatment effect and a potential predictive biomarker corresponds to the variance of the parameter estimating the treatment effect, multiplied by the inverse of the frequency of the candidate biomarker. The ratio of the variance of the interaction parameter in the crossover to the variance estimated in the parallel-group design depends on the complement of the intra-class correlation coefficient. When planning a clinical trial including a search for candidate biomarker, the frequency of the candidate biomarker helps design the sample size, and the intra-subject correlation of the outcome should be taken into account for choosing between parallel-group and crossover designs.

Whole MYBPC3 NGS sequencing as a molecular strategy to improve the efficiency of molecular diagnosis of patients with hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most common heritable cardiomyopathy, historically believed to affect 1 of 500 people. MYBPC3 pathogenic variations are the most frequent cause of familial HCM and more than 90% of them introduce a premature termination codon. The current study aims to determine the prevalence of deep intronic MYBPC3 pathogenic variations that could lead to splice mutations. To improve molecular diagnosis, a next-generation sequencing (NGS) workflow based on whole MYBPC3 sequencing of a cohort of 93 HCM patients, for whom no putatively causative point mutations were identified after NGS sequencing of a panel of 48 cardiomyopathy-causing genes, was performed. Our approach led us to reconsider the molecular diagnosis of six patients of the cohort (6.5%). These HCM probands were carriers of either a new large MYBPC3 rearrangement or splice intronic variations (five cases). Four pathogenic intronic variations, including three novel ones, were detected. Among them, the prevalence of one of them (NM_000256.3:c.1927+ 600 C>T) was estimated at about 0.35% by the screening of 1,040 unrelated HCM individuals. This study suggests that deep MYBPC3 splice mutations account for a significant proportion of HCM cases (6.5% of this cohort). Consequently, NGS sequencing of MYBPC3 intronic sequences have to be performed systematically.

Contribution of rare and predicted pathogenic gene variants to childhood-onset lupus: a large, genetic panel analysis of British and French cohorts.

BACKGROUND: Systemic lupus erythematosus (SLE) is a rare immunological disorder and genetic factors are considered important in its causation. Monogenic lupus has been associated with around 30 genotypes in humans and 60 in mice, while genome-wide association studies have identified more than 90 risk loci. We aimed to analyse the contribution of rare and predicted pathogenic gene variants in a population of unselected cases of childhood-onset SLE. METHODS: For this genetic panel analysis we designed a next-generation sequencing panel comprising 147 genes, including all known lupus-causing genes in humans, and potentially lupus-causing genes identified through GWAS and animal models. We screened 117 probands fulfilling American College of Rheumatology (ACR) criteria for SLE, ascertained through British and French cohorts of childhood-onset SLE, and compared these data with those of 791 ethnically matched controls from the 1000 Genomes Project and 574 controls from the FREX Consortium. FINDINGS: After filtering, mendelian genotypes were confirmed in eight probands, involving variants in C1QA, C1QC, C2, DNASE1L3, and IKZF1. Seven additional patients carried heterozygous variants in complement or type I interferon-associated autosomal recessive genes, with decreased concentrations of the encoded proteins C3 and C9 recorded in two patients. Rare variants that were predicted to be damaging were significantly enriched in the childhood-onset SLE cohort compared with controls; 25% of SLE probands versus 5% of controls were identified to harbour at least one rare, predicted damaging variant (p=2·98 × 10-11). Inborn errors of immunity were estimated to account for 7% of cases of childhood-onset SLE, with defects in innate immunity representing the main monogenic contribution. INTERPRETATION: An accumulation of rare variants that are predicted to be damaging in SLE-associated genes might contribute to disease expression and clinical heterogeneity. FUNDING: European Research Council.