CoNVaDING: Single Exon Variation Detection in Targeted NGS Data

Performance evaluation of predictive models for detecting MMR gene mutations associated with Lynch syndrome in cancer patients in a Chinese cohort in Taiwan

Identifying Lynch syndrome significantly impacts cancer risk management, treatment, and prognosis. Validation of mutation risk predictive models for mismatch repair (MMR) genes is crucial for guiding genetic counseling and testing, particularly in the understudied Asian population. We evaluated the performance of four MMR mutation risk predictive models in a Chinese cohort of 604 patients with colorectal cancer (CRC), endometrial cancer (EC), or ovarian cancer (OC) in Taiwan. All patients underwent germline genetic testing and 36 (6.0%) carried a mutation in the MMR genes (MLH1, MSH2, MSH6, and PMS2). All models demonstrated good performance, with area under the receiver operating characteristic curves comparable to Western cohorts: PREMM5 0.80 (95% confidence interval [CI], 0.73-0.88), MMRPro 0.88 (95% CI, 0.82-0.94), MMRPredict 0.82 (95% CI, 0.74-0.90), and Myriad 0.76 (95% CI, 0.67-0.84). Notably, MMRPro exhibited exceptional performance across all subgroups regardless of family history (FH+ 0.88, FH- 0.83), cancer type (CRC 0.84, EC 0.85, OC 1.00), or sex (male 0.83, female 0.90). PREMM5 and MMRPredict had good accuracy in the FH+ subgroup (0.85 and 0.82, respectively) and in CRC patients (0.76 and 0.82, respectively). Using the ratio of observed and predicted mutation rates, MMRPro and PREMM5 had good overall fit, while MMRPredict and Myriad overestimated mutation rates. Risk threshold settings in different models led to different positive predictive values. We suggest a lower threshold (5%) for recommending genetic testing when using MMRPro, and a higher threshold (20%) when using PREMM5 and MMRPredict. Our findings have important implications for personalized mutation risk assessment and counseling on genetic testing.

Mismatch Repair (MMR) Gene Mutation Carriers Have Favorable Outcome in Colorectal and Endometrial Cancer: A Prospective Cohort Study

Germline (Lynch syndrome, LS) and somatic deficiencies of mismatch repair proteins (MMRd) are linked to colorectal and endometrial cancer; however, their prognostic impact in Asian populations remains unclear. This prospective cohort study aimed to determine the prevalence and outcome of germline and somatic MMRd in cancer patients suspected of LS. Patients with colorectal or endometrial cancer suspected of LS were enrolled and underwent gene sequencing for germline MMRd (gMMRd) and immunohistochemistry staining of MMR proteins in a subset of the pathological samples (pMMRd). Among the 451 enrolled patients, 36 patients were gMMRd (+). Compared with gMMRd (-) patients, the 10-year relapse-free survival in gMMRd (+) patients was significantly higher (100% vs. 77.9%; p = 0.006), whereas the 10-year overall survival was similar (100% vs. 90.9%; p = 0.12). Among the 102 gMMRd (-) patients with available pMMR status, 13.7% were pMMRd (+). The 5-year relapse-free survival was 62.9% in gMMRd (-) pMMRd (+) patients and 35.0% in gMMRd (-) pMMRd (-) patients, both lower than gMMRd (+) patients (100%; p < 0.001). This study showed that having LS confers a favorable outcome in colorectal and endometrial cancer patients and highlights the importance of germline genetic testing following the detection of somatic MMRd.

Optimised, Broad NGS Panel for Inherited Eye Diseases to Diagnose 1000 Patients in Poland

Advances in gene therapy and genome editing give hope that new treatments will soon be available for inherited eye diseases that together affect a significant proportion of the adult population. New solutions are needed to make genetic diagnosis fast and affordable. This is the first study of such a large group of patients with inherited retinal dystrophies (IRD) and inherited optic neuropathies (ION) in the Polish population. It is based on four years of diagnostic analysis using a broad, targeted NGS approach. The results include the most common pathogenic variants, as well as 91 novel causative variants, including frameshifts in the cumbersome RPGR ORF15 region. The high frequency of the ABCA4 complex haplotype p.(Leu541Pro;Ala1038Val) was confirmed. Additionally, a deletion of exons 22-24 in USH2A, probably specific to the Polish population, was uncovered as the most frequent copy number variation. The diagnostic yield of the broad NGS panel reached 64.3% and is comparable to the results reported for genetic studies of IRD and ION performed for other populations with more extensive WES or WGS methods. A combined approach to identify genetic causes of all known diseases manifesting in the posterior eye segment appears to be the optimal choice given the currently available treatment options and advanced clinical trials.

Carnitine palmitoyltransferase II (CPT II) deficiency responsible for refractory cardiac arrhythmias, acute multiorgan failure and early fatal outcome

BACKGROUND

Carnitine palmitoyltransferase II (CPT II) deficiency is a rare inborn error of mitochondrial fatty acid metabolism with autosomal recessive pattern of inheritance. Its phenotype is highly variable (neonatal, infantile, and adult onset) on the base of mutations of the CPT II gene. In affected subjects, long-chain acylcarnitines cannot be subdivided into carnitine and acyl-CoA, leading to their toxic accumulation in different organs. Neonatal form is the most severe, and all the reported patients died within a few days to 6 months after birth. Hereby, we report on a male late-preterm newborn who presented refractory cardiac arrhythmias and acute multiorgan (hepatic, renal, muscular) injury, leading to cerebral hemorrhage, hydrocephalus, cardiovascular failure and early (day 5 of life) to death. Subsequently, extended metabolic screening and target next generation sequencing (NGS) analysis allowed the CPT II deficiency diagnosis.

CASE PRESENTATION

The male proband was born at 36+ 4 weeks of gestation by spontaneous vaginal delivery. Parents were healthy and nonconsanguineous, although both coming from Nigeria. Family history was unremarkable. Apgar score was 9/9. At birth, anthropometric measures were as follows: weight 2850 g (47th centile, -0.07 standard deviations, SD), length 50 cm (81st centile, + 0.89 SD) and occipitofrontal circumference (OFC) 35 cm (87th centile, + 1.14 SD). On day 2 of life our newborn showed bradycardia (heart rate around 80 bpm) and hypotonia, and was then transferred to the Neonatal Intensive Care Unit (NICU). There, he subsequently manifested many episodes of ventricular tachycardia, which were treated with pharmacological (magnesium sulfate) and electrical cardioversion. Due to the critical conditions of the baby (hepatic, renal and cardiac dysfunctions) and to guarantee optimal management of the arrythmias, he was transferred to the Pediatric Cardiology Reference Center of our region (Sicily, Italy), where he died 2 days later. Thereafter, the carnitines profile evidenced by the extended metabolic screening resulted compatible with a fatty acid oxidation defect (increased levels of acylcarnitines C16 and C18, and low of C2); afterwards, the targeted next generation sequencing (NGS) analysis revealed the known c.680 C > T p. (Pro227Leu) homozygous missense mutation of the CPTII gene, for diagnosis of CPT II deficiency. Genetic investigations have been, then, extended to the baby's parents, who were identified as heterozygous carriers of the same variant. When we meet again the parents for genetic counseling, the mother was within the first trimester of her second pregnancy. Therefore, we offered to the couple and performed the prenatal target NGS analysis on chorionic villi sample, which did not detect any alterations, excluding thus the CPT II deficiency in their second child.

CONCLUSIONS

CPTII deficiency may be suspected in newborns showing cardiac arrhythmias, associated or not with hypertrophic cardiomyopathy, polycystic kidneys, brain malformations, hepatomegaly. Its diagnosis should be even more suspected and investigated in cases of increased plasmatic levels of creatine phosphokinase and acylcarnitines in addition to kidney, heart and liver dysfunctions, as occurred in the present patient. Accurate family history, extended metabolic screening, and multidisciplinary approach are necessary for diagnosis and adequate management of affected subjects. Next generation sequencing (NGS) techniques allow the identification of the CPTII gene mutation, essential to confirm the diagnosis before or after birth, as well as to calculate the recurrence risk for family members. Our report broads the knowledge of the genetic and molecular bases of such rare disease, improving its clinical characterization, and provides useful indications for the treatment of patients.

Comprehensive Analysis of Clinically Relevant Copy Number Alterations (CNAs) Using a 523-Gene Next-Generation Sequencing Panel and NxClinical Software in Solid Tumors

Copy number alterations (CNAs) are significant in tumor initiation and progression. Identifying these aberrations is crucial for targeted therapies and personalized cancer diagnostics. Next-generation sequencing (NGS) methods present advantages in scalability and cost-effectiveness, surpassing limitations associated with reference assemblies and probe capacities in traditional laboratory approaches. This retrospective study evaluated CNAs in 50 FFPE tumor samples (breast cancer, ovarian carcinoma, pancreatic cancer, melanoma, and prostate carcinoma) using Illumina's TruSight Oncology 500 (TSO500) and the Affymetrix Oncoscan Molecular Inversion Probe (OS-MIP) (ThermoFisher Scientific, Waltham, MA, USA). NGS analysis with the NxClinical 6.2 software demonstrated a high sensitivity and specificity (100%) for CNA detection, with a complete concordance rate as compared to the OS-MIP. All 54 known CNAs were identified by NGS, with gains being the most prevalent (63%). Notable CNAs were observed in MYC (18%), TP53 (12%), BRAF (8%), PIK3CA, EGFR, and FGFR1 (6%) genes. The diagnostic parameters exhibited high accuracy, including a positive predictive value, negative predictive value, and overall diagnostic accuracy. This study underscores NxClinical as a reliable software for identifying clinically relevant gene alterations using NGS TSO500, offering valuable insights for personalized cancer treatment strategies based on CNA analysis.

Long-read genome sequencing identifies cryptic structural variants in congenital aniridia cases

BACKGROUND

Haploinsufficiency of the transcription factor PAX6 is the main cause of congenital aniridia, a genetic disorder characterized by iris and foveal hypoplasia. 11p13 microdeletions altering PAX6 or its downstream regulatory region (DRR) are present in about 25% of patients; however, only a few complex rearrangements have been described to date. Here, we performed nanopore-based whole-genome sequencing to assess the presence of cryptic structural variants (SVs) on the only two unsolved "PAX6-negative" cases from a cohort of 110 patients with congenital aniridia after unsuccessfully short-read sequencing approaches.

RESULTS

Long-read sequencing (LRS) unveiled balanced chromosomal rearrangements affecting the PAX6 locus at 11p13 in these two patients and allowed nucleotide-level breakpoint analysis. First, we identified a cryptic 4.9 Mb de novo inversion disrupting intron 7 of PAX6, further verified by targeted polymerase chain reaction amplification and sequencing and FISH-based cytogenetic analysis. Furthermore, LRS was decisive in correctly mapping a t(6;11) balanced translocation cytogenetically detected in a second proband with congenital aniridia and considered non-causal 15 years ago. LRS resolved that the breakpoint on chromosome 11 was indeed located at 11p13, disrupting the DNase I hypersensitive site 2 enhancer within the DRR of PAX6, 161 Kb from the causal gene. Patient-derived RNA expression analysis demonstrated PAX6 haploinsufficiency, thus supporting that the 11p13 breakpoint led to a positional effect by cleaving crucial enhancers for PAX6 transactivation. LRS analysis was also critical for mapping the exact breakpoint on chromosome 6 to the highly repetitive centromeric region at 6p11.1.

CONCLUSIONS

In both cases, the LRS-based identified SVs have been deemed the hidden pathogenic cause of congenital aniridia. Our study underscores the limitations of traditional short-read sequencing in uncovering pathogenic SVs affecting low-complexity regions of the genome and the value of LRS in providing insight into hidden sources of variation in rare genetic diseases.

Genotyping, characterization, and imputation of known and novel CYP2A6 structural variants using SNP array data

CYP2A6 metabolically inactivates nicotine. Faster CYP2A6 activity is associated with heavier smoking and higher lung cancer risk. The CYP2A6 gene is polymorphic, including functional structural variants (SV) such as gene deletions (CYP2A6*4), duplications (CYP2A6*1 × 2), and hybrids with the CYP2A7 pseudogene (CYP2A6*12, CYP2A6*34). SVs are challenging to genotype due to their complex genetic architecture. Our aims were to develop a reliable protocol for SV genotyping, functionally phenotype known and novel SVs, and investigate the feasibility of CYP2A6 SV imputation from SNP array data in two ancestry populations. European- (EUR; n = 935) and African- (AFR; n = 964) ancestry individuals from smoking cessation trials were genotyped for SNPs using an Illumina array and for CYP2A6 SVs using Taqman copy number (CN) assays. SV-specific PCR amplification and Sanger sequencing was used to characterize a novel SV. Individuals with SVs were phenotyped using the nicotine metabolite ratio, a biomarker of CYP2A6 activity. SV diplotype and SNP array data were integrated and phased to generate ancestry-specific SV reference panels. Leave-one-out cross-validation was used to investigate the feasibility of CYP2A6 SV imputation. A minimal protocol requiring three Taqman CN assays for CYP2A6 SV genotyping was developed and known SV associations with activity were replicated. The first domain swap CYP2A6-CYP2A7 hybrid SV, CYP2A6*53, was identified, sequenced, and associated with lower CYP2A6 activity. In both EURs and AFRs, most SV alleles were identified using imputation (>70% and >60%, respectively); importantly, false positive rates were <1%. These results confirm that CYP2A6 SV imputation can identify most SV alleles, including a novel SV.

Contribution of large genomic rearrangements in PALB2 to familial breast cancer: implications for genetic testing

BACKGROUND

PALB2 is the most important contributor to familial breast cancer after BRCA1 and BRCA2. Large genomic rearrangements (LGRs) in BRCA1 and BRCA2 are routinely assessed in clinical testing and are a significant contributor to the yield of actionable findings. In contrast, the contribution of LGRs in PALB2 has not been systematically studied.

METHODS

We performed targeted sequencing and real-time qPCR validation to identify LGRs in PALB2 in 5770 unrelated patients with familial breast cancer and 5741 cancer-free control women from the same Australian population.

RESULTS

Seven large deletions ranging in size from 0.96 kbp to 18.07 kbp involving PALB2 were identified in seven cases, while no LGRs were identified in any of the controls. Six LGRs were considered pathogenic as they included one or more exons of PALB2 and disrupted the WD40 domain at the C terminal end of the PALB2 protein while one LGR only involved a partial region of intron 10 and was considered a variant of unknown significance. Altogether, pathogenic LGRs identified in this study accounted for 10.3% (6 of 58) of the pathogenic PALB2 variants detected among the 5770 families with familial breast cancer.

CONCLUSIONS

Our data show that a clinically important proportion of PALB2 pathogenic mutations in Australian patients with familial breast cancer are LGRs. Such observations have provided strong support for inclusion of PALB2 LGRs in routine clinical genetic testing.

Case report: A gain-of-function of hamartin may lead to a distinct "inverse TSC1-hamartin" phenotype characterized by reduced cell growth

Mutations of TSC1 and TSC2 genes cause classical Tuberous Sclerosis Complex (TSC), a neurocutaneous disorder characterized by a tendency to develop hamartias, hamartomas, and other tumors. We herein report on a girl, now aged 5 years, who presented a previously unreported, distinct clinical phenotype consisting of primary microcephaly (head circumference = 40 cm, -5.6 standard deviations), brain anomalies including hypoplasia of the corpus callosum (with a residual draft of the genu), simplified parieto-temporal gyral pattern, colpocephaly with ectasia of the temporal ventricular horns, intellectual disability, and a general pattern of reduced growth (with weight and height < 3rd centiles). No classical features of TSC were recorded; the girl harbored a novel missense variant in TSC1 (c.611G > A). We hypothesize that her clinical phenotype could be related to a "gain-of-function" of the TSC1 protein product hamartin, causing an increase in the effects of the protein on inhibition of its intracellular targets (i.e., mTORC or RAC1 pathways), resulting in a distinct "inverse TSC1-hamartin" phenotype characterized by reduced growth of cells instead of the more classical predisposition to increased cell growth.

varAmpliCNV: analyzing variance of amplicons to detect CNVs in targeted NGS data

MOTIVATION

Computational identification of copy number variants (CNVs) in sequencing data is a challenging task. Existing CNV-detection methods account for various sources of variation and perform different normalization strategies. However, their applicability and predictions are restricted to specific enrichment protocols. Here, we introduce a novel tool named varAmpliCNV, specifically designed for CNV-detection in amplicon-based targeted resequencing data (Haloplex™ enrichment protocol) in the absence of matched controls. VarAmpliCNV utilizes principal component analysis (PCA) and/or metric dimensional scaling (MDS) to control variances of amplicon associated read counts enabling effective detection of CNV signals.

RESULTS

Performance of VarAmpliCNV was compared against three existing methods (ConVaDING, ONCOCNV and DECoN) on data of 167 samples run with an aortic aneurysm gene panel (n = 30), including 9 positive control samples. Additionally, we validated the performance on a large deafness gene panel (n = 145) run on 138 samples, containing 4 positive controls. VarAmpliCNV achieved higher sensitivity (100%) and specificity (99.78%) in comparison to competing methods. In addition, unsupervised clustering of CNV segments and visualization plots of amplicons spanning these regions are included as a downstream strategy to filter out false positives.

AVAILABILITY AND IMPLEMENTATION

The tool is freely available through galaxy toolshed and at: https://hub.docker.com/r/cmgantwerpen/varamplicnv. Supplementary Data File S1: https://tinyurl.com/2yzswyhh; Supplementary Data File S2: https://tinyurl.com/ycyf2fb4.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Scalable detection of technically challenging variants through modified next-generation sequencing

BACKGROUND

Some clinically important genetic variants are not easily evaluated with next-generation sequencing (NGS) methods due to technical challenges arising from high- similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.g., ARX polyalanine repeats, FMR1 AGG interruptions in CGG repeats, CFTR poly-T/TG repeats), and other complexities (e.g., MSH2 Boland inversions).

METHODS

We customized our NGS processes to detect the technically challenging variants mentioned above with adaptations including target enrichment and bioinformatic masking of similar sequences. Adaptations were validated with samples of known genotypes.

RESULTS

Our adaptations provided high-sensitivity and high-specificity detection for most of the variants and provided a high-sensitivity primary assay to be followed with orthogonal disambiguation for the others. The sensitivity of the NGS adaptations was 100% for all of the technically challenging variants. Specificity was 100% for those in PMS2, GBA1, SMN1/SMN2, and HBA1/HBA2, and for the MSH2 Boland inversion; 97.8%-100% for CYP21A2 variants; and 85.7% for ARX polyalanine repeats.

CONCLUSIONS

NGS assays can detect technically challenging variants when chemistries and bioinformatics are jointly refined. The adaptations described support a scalable, cost-effective path to identifying all clinically relevant variants within a single sample.

PEcnv: accurate and efficient detection of copy number variations of various lengths

Copy number variation (CNV) is a class of key biomarkers in many complex traits and diseases. Detecting CNV from sequencing data is a substantial bioinformatics problem and a standard requirement in clinical practice. Although many proposed CNV detection approaches exist, the core statistical model at their foundation is weakened by two critical computational issues: (i) identifying the optimal setting on the sliding window and (ii) correcting for bias and noise. We designed a statistical process model to overcome these limitations by calculating regional read depths via an exponentially weighted moving average strategy. A one-run detection of CNVs of various lengths is then achieved by a dynamic sliding window, whose size is self-adopted according to the weighted averages. We also designed a novel bias/noise reduction model, accompanied by the moving average, which can handle complicated patterns and extend training data. This model, called PEcnv, accurately detects CNVs ranging from kb-scale to chromosome-arm level. The model performance was validated with simulation samples and real samples. Comparative analysis showed that PEcnv outperforms current popular approaches. Notably, PEcnv provided considerable advantages in detecting small CNVs (1 kb–1 Mb) in panel sequencing data. Thus, PEcnv fills the gap left by existing methods focusing on large CNVs. PEcnv may have broad applications in clinical testing where panel sequencing is the dominant strategy. Availability and implementation: Source code is freely available at https://github.com/Sherwin-xjtu/PEcnv

ClearCNV: CNV calling from NGS panel data in the presence of ambiguity and noise

MOTIVATION

While the identification of small variants in panel sequencing data can be considered a solved problem, the identification of larger, multi-exon copy number variants (CNVs) still poses a considerable challenge. Thus, CNV calling has not been established in all laboratories performing panel sequencing. At the same time, such laboratories have accumulated large datasets and thus have the need to identify CNVs on their data to close the diagnostic gap.

RESULTS

In this article, we present our method clearCNV that addresses this need in two ways. First, it helps laboratories to properly assign datasets to enrichment kits. Based on homogeneous subsets of data, clearCNV identifies CNVs affecting the targeted regions. Using real-world datasets and validation, we show that our method is highly competitive with previous methods and preferable in terms of specificity.

AVAILABILITY AND IMPLEMENTATION

The software is available for free under a permissible license at https://github.com/bihealth/clear-cnv.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Algorithmic improvements for discovery of germline copy number variants in next-generation sequencing data

Background

Copy number variants (CNVs) play a significant role in human heredity and disease. However, sensitive and specific characterization of germline CNVs from NGS data has remained challenging, particularly for hybridization-capture data in which read counts are the primary source of copy number information.

Results

We describe two algorithmic adaptations that improve CNV detection accuracy in a Hidden Markov Model (HMM) context. First, we present a method for computing target- and copy number-specific emission distributions. Second, we demonstrate that the Pointwise Maximum a posteriori (PMAP) HMM decoding procedure yields improved sensitivity for small CNV calls compared to the more common Viterbi HMM decoder. We develop a prototype implementation, called Cobalt, and compare it to other CNV detection tools using sets of simulated and previously detected CNVs with sizes spanning a single exon to a full chromosome.

Conclusions

In both the simulation and previously detected CNV studies Cobalt shows similar sensitivity but significantly fewer false positive detections compared to other callers. Overall sensitivity is 80–90% for deletion CNVs spanning 1–4 targets and 90–100% for larger deletion events, while sensitivity is somewhat lower for small duplication CNVs.

Progress in Methods for Copy Number Variation Profiling

Copy number variations (CNVs) are the predominant class of structural genomic variations involved in the processes of evolutionary adaptation, genomic disorders, and disease progression. Compared with single-nucleotide variants, there have been challenges associated with the detection of CNVs owing to their diverse sizes. However, the field has seen significant progress in the past 20–30 years. This has been made possible due to the rapid development of molecular diagnostic methods which ensure a more detailed view of the genome structure, further complemented by recent advances in computational methods. Here, we review the major approaches that have been used to routinely detect CNVs, ranging from cytogenetics to the latest sequencing technologies, and then cover their specific features.

Low Detection Rates of Genetic FH in Cohort of Patients With Severe Hypercholesterolemia in the United Arabic Emirates

Background: Programs to screen for Familial hypercholesterolemia (FH) are conducted worldwide. In Western societies, these programs have been shown to be cost-effective with hit/detection rates of 1 in 217-250. Thus far, there is no published data on genetic FH in the Gulf region. Using United Arab Emirates as a proxy for the Gulf region, we assessed the prevalence of genetically confirmed FH in the Emirati population sample. Materials and Methods: We recruited 229 patients with LDL-C >95^th percentile and employed a customized next generation sequencing pipeline to screen canonical FH genes (LDLR, APOB, PCSK9, LDLRAP1). Results: Participants were characterized by mean total cholesterol and low-density lipoprotein cholesterol (LDL-c) of 6.3 ± 1.1 and 4.7 ± 1.1 mmol/L respectively. Ninety-six percent of the participants were using lipid-lowering medication with mean corrected LDL-c values of 10.0 ± 3.0 mmol/L 15 out of 229 participants were found to suffer from genetically confirmed FH. Carriers of causal genetic variants for FH had higher on-treatment LDL-c compared to those without causal variants (5.7 ± 1.5 vs 4.7 ± 1.0; p = 3.7E-04). The groups did not differ regarding high-density lipoprotein cholesterol, triglycerides, body mass index, blood pressure, glucose, and glycated haemoglobin. Conclusion: This study reveals a low 7% prevalence of genetic FH in Emiratis with marked hypercholesterolemia as determined by correcting LDL-c for the use of lipid-lowering treatment. The portfolio of mutations identified is, to a large extent, unique and includes gene duplications. Our findings warrant further studies into origins of hypercholesterolemia in these patients. This is further supported by the fact that these patients are also characterized by high prevalence of type 2 diabetes (42% in the current study cohort) which already puts them at an increased risk of atherosclerotic cardiovascular disease. These results may also be useful in public health initiatives for FH cascade screening programs in the UAE and maybe the Gulf region.

DECoN: A Detection and Visualization Tool for Exonic Copy Number Variants

Detection of copy number variants from targeted sequencing, including whole-exome sequencing, can be particularly difficult since the break points of the CNV are not always captured. Here we describe DECoN, a software tool which uses changes in read depth to identify CNVs that affect whole exons. It is optimized for clinical use and allows for interactive visualization of CNVs identified.

VarGenius-HZD Allows Accurate Detection of Rare Homozygous or Hemizygous Deletions in Targeted Sequencing Leveraging Breadth of Coverage

Homozygous deletions (HDs) may be the cause of rare diseases and cancer, and their discovery in targeted sequencing is a challenging task. Different tools have been developed to disentangle HD discovery but a sensitive caller is still lacking. We present VarGenius-HZD, a sensitive and scalable algorithm that leverages breadth-of-coverage for the detection of rare homozygous and hemizygous single-exon deletions (HDs). To assess its effectiveness, we detected both real and synthetic rare HDs in fifty exomes from the 1000 Genomes Project obtaining higher sensitivity in comparison with state-of-the-art algorithms that each missed at least one event. We then applied our tool on targeted sequencing data from patients with Inherited Retinal Dystrophies and solved five cases that still lacked a genetic diagnosis. We provide VarGenius-HZD either stand-alone or integrated within our recently developed software, enabling the automated selection of samples using the internal database. Hence, it could be extremely useful for both diagnostic and research purposes.

Implementation of fetal clinical exome sequencing: Comparing prospective and retrospective cohorts

PURPOSE

We compared the diagnostic yield of fetal clinical exome sequencing (fCES) in prospective and retrospective cohorts of pregnancies presenting with anomalies detected using ultrasound. We evaluated factors that led to a higher diagnostic efficiency, such as phenotypic category, clinical characterization, and variant analysis strategy.

METHODS

fCES was performed for 303 fetuses (183 ongoing and 120 ended pregnancies, in which chromosomal abnormalities had been excluded) using a trio/duo-based approach and a multistep variant analysis strategy.

RESULTS

fCES identified the underlying genetic cause in 13% (24/183) of prospective and 29% (35/120) of retrospective cases. In both cohorts, recessive heterozygous compound genotypes were not rare, and trio and simplex variant analysis strategies were complementary to achieve the highest possible diagnostic rate. Limited prenatal phenotypic information led to interpretation challenges. In 2 prospective cases, in-depth analysis allowed expansion of the spectrum of prenatal presentations for genetic syndromes associated with the SLC17A5 and CHAMP1 genes.

CONCLUSION

fCES is diagnostically efficient in fetuses presenting with cerebral, skeletal, urinary, or multiple anomalies. The comparison between the 2 cohorts highlights the importance of providing detailed phenotypic information for better interpretation and prenatal reporting of genetic variants.

CNV-MEANN: A Neural Network and Mind Evolutionary Algorithm-Based Detection of Copy Number Variations From Next-Generation Sequencing Data

Copy number variation (CNV), is defined as repetitions or deletions of genomic segments of 1 Kb to 5 Mb, and is a major trigger for human disease. The high-throughput and low-cost characteristics of next-generation sequencing technology provide the possibility of the detection of CNVs in the whole genome, and also greatly improve the clinical practicability of next-generation sequencing (NGS) testing. However, current methods for the detection of CNVs are easily affected by sequencing and mapping errors, and uneven distribution of reads. In this paper, we propose an improved approach, CNV-MEANN, for the detection of CNVs, involving changing the structure of the neural network used in the MFCNV method. This method has three differences relative to the MFCNV method: (1) it utilizes a new feature, mapping quality, to replace two features in MFCNV, (2) it considers the influence of the loss categories of CNV on disease prediction, and refines the output structure, and (3) it uses a mind evolutionary algorithm to optimize the backpropagation (neural network) neural network model, and calculates individual scores for each genome bin to predict CNVs. Using both simulated and real datasets, we tested the performance of CNV-MEANN and compared its performance with those of seven widely used CNV detection methods. Experimental results demonstrated that the CNV-MEANN approach outperformed other methods with respect to sensitivity, precision, and F1-score. The proposed method was able to detect many CNVs that other approaches could not, and it reduced the boundary bias. CNV-MEANN is expected to be an effective method for the analysis of changes in CNVs in the genome.

A Local Outlier Factor-Based Detection of Copy Number Variations From NGS Data

Copy number variation (CNV) is a major type of genomic structural variations that play an important role in human disorders. Next generation sequencing (NGS) has fueled the advancement in algorithm design to detect CNVs at base-pair resolution. However, accurate detection of CNVs of low amplitudes remains a challenging task. This paper proposes a new computational method, CNV-LOF, to identify CNVs of full-range amplitudes from NGS data. CNV-LOF is distinctly different from traditional methods, which mainly consider aberrations from a global perspective and rely on some assumed distribution of NGS read depths. In contrast, CNV-LOF takes a local view on the read depths and assigns an outlier factor to each genome segment. With the outlier factor profile, CNV-LOF uses a boxplot procedure to declare CNVs without the reliance of any distribution assumptions. Simulation experiments indicate that CNV-LOF outperforms five existing methods with respect to F1-measure, sensitivity, and precision. CNV-LOF is further validated on real sequencing samples, yielding highly consistent results with peer methods. CNV-LOF is able to detect CNVs of low and moderate amplitudes where the other existing methods fail, and it is expected to become a routine approach for the discovery of novel CNVs on whole sequencing genome.

Detecting copy number variation in next generation sequencing data from diagnostic gene panels

Background

Detection of copy number variation (CNV) in genes associated with disease is important in genetic diagnostics, and next generation sequencing (NGS) technology provides data that can be used for CNV detection. However, CNV detection based on NGS data is in general not often used in diagnostic labs as the data analysis is challenging, especially with data from targeted gene panels. Wet lab methods like MLPA (MRC Holland) are widely used, but are expensive, time consuming and have gene-specific limitations. Our aim has been to develop a bioinformatic tool for CNV detection from NGS data in medical genetic diagnostic samples.

Results

Our computational pipeline for detection of CNVs in NGS data from targeted gene panels utilizes coverage depth of the captured regions and calculates a copy number ratio score for each region. This is computed by comparing the mean coverage of the sample with the mean coverage of the same region in other samples, defined as a pool. The pipeline selects pools for comparison dynamically from previously sequenced samples, using the pool with an average coverage depth that is nearest to the one of the samples. A sliding window-based approach is used to analyze each region, where length of sliding window and sliding distance can be chosen dynamically to increase or decrease the resolution. This helps in detecting CNVs in small or partial exons. With this pipeline we have correctly identified the CNVs in 36 positive control samples, with sensitivity of 100% and specificity of 91%. We have detected whole gene level deletion/duplication, single/multi exonic level deletion/duplication, partial exonic deletion and mosaic deletion. Since its implementation in mid-2018 it has proven its diagnostic value with more than 45 CNV findings in routine tests.

Conclusions

With this pipeline as part of our diagnostic practices it is now possible to detect partial, single or multi-exonic, and intragenic CNVs in all genes in our target panel. This has helped our diagnostic lab to expand the portfolio of genes where we offer CNV detection, which previously was limited by the availability of MLPA kits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01059-x.

Molecular Diagnosis of Pompe Disease in the Genomic Era: Correlation with Acid Alpha-Glucosidase Activity in Dried Blood Spots

Measurement of alpha-glucosidase activity on dried blood spots has been the main method to screen for Pompe disease, but a paradigm shift has been observed in recent years with the incorporation of gene panels and exome sequencing in molecular diagnostic laboratories. An 89-gene panel has been available to Canadian physicians since 2017 and was analyzed in 2030 patients with a suspected muscle disease. Acid alpha-glucosidase activity was measured in parallel in dried blood spots from 1430 patients. Pompe disease was diagnosed in 14 patients, representing 0.69% of our cohort. In 7 other patients, low enzyme activities overlapping those of Pompe disease cases were attributable to the presence of pseudodeficiency alleles. Only two other patients had enzymatic activity in the Pompe disease range, and a single heterozygous pathogenic variant was identified. It is possible that a second variant could have been missed; we suggest that RNA analysis should be considered in such cases. With gene panel testing increasingly being performed as a first-tier analysis of patients with suspected muscle disorders, our study supports the relevance of performing reflex enzymatic activity assay in selected patients, such as those with a single GAA variant identified and those in whom the observed genotype is of uncertain clinical significance.

NGS and phenotypic ontology-based approaches increase the diagnostic yield in syndromic retinal diseases

Syndromic retinal diseases (SRDs) are a group of complex inherited systemic disorders, with challenging molecular underpinnings and clinical management. Our main goal is to improve clinical and molecular SRDs diagnosis, by applying a structured phenotypic ontology and next-generation sequencing (NGS)-based pipelines. A prospective and retrospective cohort study was performed on 100 probands with an a priori diagnosis of non-Usher SRDs, using available clinical data, including Human Phenotype Ontology annotation, and further classification into seven clinical categories (ciliopathies, specific syndromes and five others). Retrospective molecular diagnosis was assessed using different molecular and bioinformatic methods depending on availability. Subsequently, uncharacterized probands were prospectively screened using other NGS approaches to extend the number of analyzed genes. After phenotypic classification, ciliopathies were the most common SRD (35%). A global characterization rate of 52% was obtained, with six cases incompletely characterized for a gene that partially explained the phenotype. An improved characterization rate was achieved addressing prospective cases (83%) and well-recognizable syndrome (62%) subgroups. The 27% of the fully characterized cases were reclassified into a different clinical category after identification of the disease-causing gene. Clinical-exome sequencing is the most appropriate first-tier approach for prospective cases, whereas whole-exome sequencing and bioinformatic reanalysis increases the diagnosis of uncharacterized retrospective cases to 45%, mostly those with unspecific symptoms. Our study describes a comprehensive approach to SRDs in daily clinical practice and the importance of thorough clinical assessment and selection of the most appropriate molecular test to be used to solve these complex cases and elucidate novel associations.

PRDX1 gene-related epi-cblC disease is a common type of inborn error of cobalamin metabolism with mono- or bi-allelic MMACHC epimutations

Background

The role of epigenetics in inborn errors of metabolism (IEMs) is poorly investigated. Epigenetic changes can contribute to clinical heterogeneity of affected patients but could also be underestimated determining factors in the occurrence of IEMs. An epigenetic cause of IEMs has been recently described for the autosomal recessive methylmalonic aciduria and homocystinuria, cblC type (cblC disease), and it has been named epi-cblC. Epi-cblC has been reported in association with compound heterozygosity for a genetic variant and an epimutation at the MMACHC locus, which is secondary to a splicing variant (c.515-1G > T or c.515-2A > T) at the adjacent PRDX1 gene. Both these variants cause aberrant antisense transcription and cis-hypermethylation of the MMACHC gene promotor with subsequent silencing. Until now, only nine epi-cblC patients have been reported.

Methods

We report clinical/biochemical assessment, MMACHC/PRDX1 gene sequencing and genome-wide DNA methylation profiling in 11 cblC patients who had an inconclusive MMACHC gene testing. We also compare clinical phenotype of epi-cblC patients with that of canonical cblC patients.

Results

All patients turned out to have the epi-cblC disease. One patient had a bi-allelic MMACHC epimutation due to the homozygous PRDX1:c.515-1G > T variant transmitted by both parents. We found that the bi-allelic epimutation produces the complete silencing of MMACHC in the patient’s fibroblasts. The remaining ten patients had a mono-allelic MMACHC epimutation, due to the heterozygous PRDX1:c.515-1G > T, in association with a mono-allelic MMACHC genetic variant. Epi-cblC disease has accounted for about 13% of cblC cases diagnosed by newborn screening in the Tuscany and Umbria regions since November 2001. Comparative analysis showed that clinical phenotype of epi-cblC patients is similar to that of canonical cblC patients.

Conclusions

We provide evidence that epi-cblC is an underestimated cause of inborn errors of cobalamin metabolism and describe the first instance of epi-cblC due to a bi-allelic MMACHC epimutation. MMACHC epimutation/PRDX1 mutation analyses should be part of routine genetic testing for all patients presenting with a metabolic phenotype that combines methylmalonic aciduria and homocystinuria.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01117-2.

CIRCNV: Detection of CNVs Based on a Circular Profile of Read Depth from Sequencing Data

Simple Summary

In this study, we propose a copy number variation (CNV) detection method called CIRCNV, which is based on a circular profile of the read depth from sequencing data. The proposed method is an extended version of our previously developed method CNV-LOF. The main difference of CIRCNV from CNV-LOF lies in its two new features: (1) it transfers the read depth profile from a line shape to a circular shape via a polar coordinate transformation to generate a meaningful two-dimensional dataset for CNV analysis and promote fairness between the ends and middle part of the genome, and (2) it performs two rounds of CNV declaration via estimating tumor purity and recovering the truth circular RD profile. We test and evaluate the performance of CIRCNV via conducting simulation studies and real sequencing tumor sample applications. The experimental results show that CIRCNV outperforms peer methods with respect to sensitivity, precision, and the F1-score. The experiments prove that the proposed method is a reliable and effective tool in the field of variation analysis of tumor genomes.

Abstract

Copy number variation (CNV) is a common type of structural variation in the human genome. Accurate detection of CNVs from tumor genomes can provide crucial information for the study of tumor genesis and cancer precision diagnosis. However, the contamination of normal genomes in tumor genomes and the crude profiles of the read depth make such a task difficult. In this paper, we propose an alternative approach, called CIRCNV, for the detection of CNVs from sequencing data. CIRCNV is an extension of our previously developed method CNV-LOF, which uses local outlier factors to predict CNVs. Comparatively, CIRCNV can be performed on individual tumor samples and has the following two new features: (1) it transfers the read depth profile from a line shape to a circular shape via a polar coordinate transformation, in order to improve the efficiency of the read depth (RD) profile for the detection of CNVs; and (2) it performs a second round of CNV declaration based on the truth circular RD profile, which is recovered by estimating tumor purity. We test and validate the performance of CIRCNV based on simulation and real sequencing data and perform comparisons with several peer methods. The results demonstrate that CIRCNV can obtain superior performance in terms of sensitivity and precision. We expect that our proposed method will be a supplement to existing methods and become a routine tool in the field of variation analysis of tumor genomes.

Copy Number Variant Detection with Low-Coverage Whole-Genome Sequencing Represents a Viable Alternative to the Conventional Array-CGH

Copy number variations (CNVs) represent a type of structural variant involving alterations in the number of copies of specific regions of DNA that can either be deleted or duplicated. CNVs contribute substantially to normal population variability, however, abnormal CNVs cause numerous genetic disorders. At present, several methods for CNV detection are applied, ranging from the conventional cytogenetic analysis, through microarray-based methods (aCGH), to next-generation sequencing (NGS). In this paper, we present GenomeScreen, an NGS-based CNV detection method for low-coverage, whole-genome sequencing. We determined the theoretical limits of its accuracy and obtained confirmation in an extensive in silico study and in real patient samples with known genotypes. In theory, at least 6 M uniquely mapped reads are required to detect a CNV with the length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in silico analysis required at least 8 M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has mean resolution of 200 kb. GenomeScreen and aCGH both detected 59 deviations, while GenomeScreen furthermore detected 134 other (usually) smaller variations. When compared to aCGH, overall performance of the proposed GenemoScreen tool is comparable or superior in terms of accuracy, turn-around time, and cost-effectiveness, thus providing reasonable benefits, particularly in a prenatal diagnosis setting.

Diagnostic yield of targeted next generation sequencing in 2002 Dutch cardiomyopathy patients

BACKGROUND

Next-generation sequencing (NGS) is increasingly used for clinical evaluation of cardiomyopathy patients as it allows for simultaneous screening of multiple cardiomyopathy-associated genes. Adding copy number variant (CNV) analysis of NGS data is not routine yet and may contribute to the diagnostic yield.

OBJECTIVES

Determine the diagnostic yield of our targeted NGS gene panel in routine clinical diagnostics of Dutch cardiomyopathy patients and explore the impact of exon CNVs on diagnostic yield.

METHODS

Patients (N = 2002) referred for clinical genetic analysis underwent diagnostic testing of 55-61 genes associated with cardiomyopathies. Samples were analyzed and evaluated for single nucleotide variants (SNVs), indels and CNVs. CNVs identified in the NGS data and suspected of being pathogenic based on type, size and location were confirmed by additional molecular tests.

RESULTS

A (likely) pathogenic (L)P variant was detected in 22.7% of patients, including 3 with CNVs and 25 where a variant was identified in a gene currently not associated with the patient's cardiomyopathy subtype. Only 15 out of 2002 patients (0.8%) were found to carry two (L)P variants.

CONCLUSION

The yield of routine clinical diagnostics of cardiomyopathies was relatively low when compared to literature. This is likely due to the fact that our study reports the outcome of patients in daily routine diagnostics, therefore also including patients not fully fulfilling (subtype specific) cardiomyopathy criteria. This may also explain why (L)P variants were identified in genes not associated with the reported subtype. The added value of CNV analysis was shown to be limited but not negligible.

Clinical Value of EGFR Copy Number Gain Determined by Amplicon-Based Targeted Next Generation Sequencing in Patients with EGFR-Mutated NSCLC

BACKGROUND

The clinical relevance of epidermal growth factor receptor (EGFR) copy number gain in patients with EGFR mutated advanced non-small cell lung cancer on first-line tyrosine kinase inhibitor treatment has not been fully elucidated.

OBJECTIVE

We aimed to estimate EGFR copy number gain using amplicon-based next generation sequencing data and explored its prognostic value.

PATIENTS AND METHODS

Next generation sequencing data were obtained for 1566 patients with non-small cell lung cancer. EGFR copy number gain was defined based on an increase in EGFR read counts relative to internal reference amplicons and normal controls in combination with a modified z-score ≥ 3.5. Clinical follow-up data were available for 60 patients treated with first-line EGFR-tyrosine kinase inhibitors.

RESULTS

Specificity and sensitivity of next generation sequencing-based EGFR copy number estimations were above 90%. EGFR copy number gain was observed in 27.9% of EGFR mutant cases and in 7.4% of EGFR wild-type cases. EGFR gain was not associated with progression-free survival but showed a significant effect on overall survival with an adjusted hazard ratio of 3.14 (95% confidence interval 1.46-6.78, p = 0.003). Besides EGFR copy number gain, osimertinib in second or subsequent lines of treatment and the presence of T790M at relapse revealed significant effects in a multivariate analysis with adjusted hazard ratio of 0.43 (95% confidence interval 0.20-0.91, p = 0.028) and 0.24 (95% confidence interval 0.1-0.59, p = 0.001), respectively.

CONCLUSIONS

Pre-treatment EGFR copy number gain determined by amplicon-based next generation sequencing data predicts worse overall survival in EGFR-mutated patients treated with first-line EGFR-tyrosine kinase inhibitors. T790M at relapse and subsequent treatment with osimertinib predict longer overall survival.

Prioritizing variants of uncertain significance for reclassification using a rule-based algorithm in inherited retinal dystrophies

Inherited retinal dystrophies (IRD) are a highly heterogeneous group of rare diseases with a molecular diagnostic rate of >50%. Reclassification of variants of uncertain significance (VUS) poses a challenge for IRD diagnosis. We collected 668 IRD cases analyzed by our geneticists using two different clinical exome-sequencing tests. We identified 114 unsolved cases pending reclassification of 125 VUS and studied their genomic, functional, and laboratory-specific features, comparing them to pathogenic and likely pathogenic variants from the same cohort (N = 390). While the clinical exome used did not show differences in diagnostic rate, the more IRD-experienced geneticist reported more VUS (p = 4.07e-04). Significantly fewer VUS were reported in recessive cases (p = 2.14e-04) compared to other inheritance patterns, and of all the genes analyzed, ABCA4 and IMPG2 had the lowest and highest VUS frequencies, respectively (p = 3.89e-04, p = 6.93e-03). Moreover, few frameshift and stop-gain variants were found to be informed VUS (p = 6.73e-08 and p = 2.93e-06). Last, we applied five pathogenicity predictors and found there is a significant proof of deleteriousness when all score for pathogenicity in missense variants. Altogether, these results provided input for a set of rules that correctly reclassified ~70% of VUS as pathogenic in validation datasets. Disease- and setting-specific features influence VUS reporting. Comparison with pathogenic and likely pathogenic variants can prioritize VUS more likely to be reclassified as causal.

Clinical utility of genetic testing in early-onset kidney disease: seven genes are the main players

BACKGROUND

Inherited kidney diseases are one of the leading causes of chronic kidney disease (CKD) that manifests before the age of 30 years. Precise clinical diagnosis of early-onset CKD is complicated due to the high phenotypic overlap, but genetic testing is a powerful diagnostic tool. We aimed to develop a genetic testing strategy to maximize the diagnostic yield for patients presenting with early-onset CKD and to determine the prevalence of the main causative genes.

METHODS

We performed genetic testing of 460 patients with early-onset CKD of suspected monogenic cause using next-generation sequencing of a custom-designed kidney disease gene panel in addition to targeted screening for c.428dupC MUC1.

RESULTS

We achieved a global diagnostic yield of 65% (300/460), which varied depending on the clinical diagnostic group: 77% in cystic kidney diseases, 76% in tubulopathies, 67% in autosomal dominant tubulointerstitial kidney disease, 61% in glomerulopathies, and 38% in congenital anomalies of the kidney and urinary tract. Among the 300 genetically diagnosed patients, the clinical diagnosis was confirmed in 77%, a specific diagnosis within a clinical diagnostic group was identified in 15%, and 7% of cases were reclassified. Of the 64 causative genes identified in our cohort, seven (COL4A3, COL4A4, COL4A5, HNF1B, PKD1, PKD2, and PKHD1) accounted for 66% (198/300) of the genetically diagnosed patients.

CONCLUSIONS

Two-thirds of patients with early-onset CKD in this cohort had a genetic cause. Just seven genes were responsible for the majority of diagnoses. Establishing a genetic diagnosis is crucial to define the precise etiology of CKD, which allows accurate genetic counseling and improved patient management.

Identification of New Genes Involved in Germline Predisposition to Early-Onset Gastric Cancer

The genetic cause for several families with gastric cancer (GC) aggregation is unclear, with marked relevance in early-onset patients. We aimed to identify new candidate genes involved in GC germline predisposition. Whole-exome sequencing (WES) of germline samples was performed in 20 early-onset GC patients without previous germline mutation identified. WES was also performed in nine tumor samples to analyze the somatic profile using SigProfilerExtractor tool. Sequencing germline data were filtered to select those variants with plausible pathogenicity, rare frequency and previously involved in cancer. Then, a manual filtering was performed to prioritize genes according to current knowledge and function. These genetic variants were prevalidated with Integrative Genomics Viewer 2.8.2 (IGV). Subsequently, a further selection step was carried out according to function and information obtained from tumor samples. After IGV and selection step, 58 genetic variants in 52 different candidate genes were validated by Sanger sequencing. Among them, APC, FAT4, CTNND1 and TLR2 seem to be the most promising genes because of their role in hereditary cancer syndromes, tumor suppression, cell adhesion and Helicobacter pylori recognition, respectively. These encouraging results represent the open door to the identification of new genes involved in GC germline predisposition.

Update on next generation sequencing of pharmacokinetics-related genes: Development of the PKseq panel, a platform for amplicon sequencing of drug-metabolizing enzyme and drug transporter genes

Genetic variation in pharmacokinetics (PK)-related genes encoding drug metabolizing enzymes or drug transporters is one of the most practical pharmacogenetic biomarkers for the prediction or explanation of an individual's response to drugs. Many pharmacogenomic variations are identified using targeted, whole-exome, and whole-genome sequencing, and the number of known novel variations and alleles in PK-related genes is increasing. The high homology of sequences among PK-related genes is suspected to lead to potential read misalignment and genotyping errors when short-read sequencing was performed. Therefore, highly efficient and accurate next generation sequencing (NGS) platforms for the sequencing of PK-related genes are needed. We have developed PKseq, a targeted sequencing panel based on multiplex PCR, which targets the coding regions of 37 drug transporters, 30 cytochrome P450 isoforms, 10 UDP-glucuronosyltransferases, 5 flavin-containing monooxygenases, 4 glutathione S-transferases, 4 sulfotransferases, and 10 other genes. In this review, we describe the current NGS platforms for the sequencing of PK-related genes. The NGS platforms, including the PKseq panel, will be useful not only for the identification of all the variants of PK-related genes associated with adverse drug reactions and drug efficacy, but also for clinical sequencing to achieve pharmacogenomics-based stratified medicine.

Screening of CNVs using NGS data improves mutation detection yield and decreases costs in genetic testing for hereditary cancer

INTRODUCTION

Germline CNVs are important contributors to hereditary cancer. In genetic diagnostics, multiplex ligation-dependent probe amplification (MLPA) is commonly used to identify them. However, MLPA is time-consuming and expensive if applied to many genes, hence many routine laboratories test only a subset of genes of interest.

METHODS AND RESULTS

We evaluated a next-generation sequencing (NGS)-based CNV detection tool (DECoN) as first-tier screening to decrease costs and turnaround time and expand CNV analysis to all genes of clinical interest in our diagnostics routine. We used DECoN in a retrospective cohort of 1860 patients where a limited number of genes were previously analysed by MLPA, and in a prospective cohort of 2041 patients, without MLPA analysis. In the retrospective cohort, 6 new CNVs were identified and confirmed by MLPA. In the prospective cohort, 19 CNVs were identified and confirmed by MLPA, 8 of these would have been lost in our previous MLPA-restricted detection strategy. Also, the number of genes tested by MLPA across all samples decreased by 93.0% in the prospective cohort.

CONCLUSION

Including an in silico germline NGS CNV detection tool improved our genetic diagnostics strategy in hereditary cancer, both increasing the number of CNVs detected and reducing turnaround time and costs.

Novel TMEM98, MFRP, PRSS56 variants in a large United States high hyperopia and nanophthalmos cohort

Nanophthalmos is a rare condition defined by a small, structurally normal eye with resultant high hyperopia. While six genes have been implicated in this hereditary condition (MFRP, PRSS56, MYRF, TMEM98, CRB1,VMD2/BEST1), the relative contribution of these to nanophthalmos or to less severe high hyperopia (≥ + 5.50 spherical equivalent) has not been fully elucidated. We collected probands and families (n = 56) with high hyperopia or nanophthalmos (≤ 21.0 mm axial length). Of 53 families that passed quality control, plausible genetic diagnoses were identified in 10/53 (18.8%) by high-throughput panel or pooled exome sequencing. These include 1 TMEM98 family (1.9%), 5 MFRP families (9.4%), and 4 PRSS56 families (7.5%), with 4 additional families having single allelic hits in MFRP or PRSS56 (7.5%). A novel deleterious TMEM98 variant (NM_015544.3, c.602G>C, p.(Arg201Pro)) segregated with disease in 4 affected members of a family. Multiple novel missense and frameshift variants in MFRP and PRSS56 were identified. PRSS56 families were more likely to have choroidal folds than other solved families, while MFRP families were more likely to have retinal degeneration. Together, this study defines the prevalence of nanophthalmos gene variants in high hyperopia and nanophthalmos and indicates that a large fraction of cases remain outside of single gene coding sequences.

Digestive involvement in a severe form of Snyder-Robinson syndrome: Possible expansion of the phenotype

Snyder-Robinson syndrome (OMIM #309583) is a rare X-linked condition, caused by mutation in the SMS gene (MIM *300105), characterized by a wide spectrum of clinical signs including developmental delay, epilepsy, asthenic habitus, dysmorphism, osteopenia, and renal or genital anomalies. Here we describe two maternal half-brothers who both presented with severe neurodevelopmental delay, seizures, hearing loss, facial dysmorphism, renal and ophthalmologic anomalies, failure to thrive and premature death. A novel p.(Gly203Asp) variant was found at the hemizygous state in the two boys, and an elevated Spermidine/Spermine ratio confirmed the diagnosis of Snyder-Robinson syndrome. One of the brothers presented with gastrointestinal symptoms, with jejunal stenosis, enteral feeding intolerance, failure to thrive due to a dysfunctional gastrointestinal system, cholestasis and exocrine pancreatic insufficiency. Although more studies will be needed to understand its mechanisms, this observation lends further support to the possibility of severe digestive involvement in Snyder Robinson syndrome.

appMAGI: A complete laboratory information management system for clinical diagnostics

Background:

The increasing demand for genetic testing for clinical diagnosis and research challenges genetic laboratory capacity to track an increasing number of patient samples through all steps of analysis, from sample collection to report generation. This task is usually performed with the help of a laboratory information management system (LIMS), software that makes it possible to collect, store and retrieve laboratory and sample data. To date there are no open-source options that can manage the entire analytical flow of a genetic laboratory. appMAGI seeks to include all the management aspects of a clinical diagnostic laboratory, making it simpler to process many samples while maintaining the high security and quality standards required in clinical diagnostic practice.

Methods:

appMAGI is written in python using Django. It is a web application that does not require local installation, making development, updates and maintenance a much easier task. appMAGI runs on the Ubuntu server and uses SQLite as engine database.

Results:

In this work we describe an innovative LIMS called appMAGI designed to support all aspects of a clinical diagnostic laboratory. appMAGI can track samples throughout the diagnostic workflow and NGS analysis by virtue of a customizable bioinformatics pipeline. It can handle sample non-compliance, manage laboratory stocks, help generate reports and provide insights into sample data by means of special tools.

Conclusions:

appMAGI is a LIMS endowed with all the features required to manage thousands of samples. Allowing efficient management of patient samples from sample collection to diagnostic report generation. (www.actabiomedica.it)

Detection of somatic TP53 mutations and 17p deletions in patients with chronic lymphocytic leukemia: a review of the current methods

Chronic lymphocytic leukemia is the most common hematologic malignancy among adults in Western countries. Several studies show that somatic mutations in the TP53 gene are present in up to 50% of patients with relapsed or refractory chronic lymphocytic leukemia. This study aims to review and compare the methods used to detect somatic TP53 mutations and/or 17p deletions and analyze their importance in the chronic lymphocytic leukemia diagnosis and follow-up. In chronic lymphocytic leukemia patients with refractory or recurrent disease, the probability of clonal expansion of cells with the TP53 mutation and/or 17p deletion is very high. The studies assessed showed several methodologies able to detect these changes. For the 17p deletion, the chromosome G-banding (karyotype) and interphase fluorescence in situ hybridization are the most sensitive. For somatic mutations involving the TP53 gene, moderate or high-coverage read next-generation sequencing and Sanger sequencing are the most recommended ones. The TP53 gene mutations represent a strong adverse prognostic factor for patient survival and treatment resistance in chronic lymphocytic leukemia. Patients carrying low-proportion TP53 mutation (less than 20–25% of all alleles) remain a challenge to these tests. Thus, for any of the methods employed, it is essential that the laboratory conduct its analytical validation, documenting its accuracy, precision and sensitivity/limit of detection.

Evaluation of CNV detection tools for NGS panel data in genetic diagnostics

Although germline copy-number variants (CNVs) are the genetic cause of multiple hereditary diseases, detecting them from targeted next-generation sequencing data (NGS) remains a challenge. Existing tools perform well for large CNVs but struggle with single and multi-exon alterations. The aim of this work is to evaluate CNV calling tools working on gene panel NGS data and their suitability as a screening step before orthogonal confirmation in genetic diagnostics strategies. Five tools (DECoN, CoNVaDING, panelcn.MOPS, ExomeDepth, and CODEX2) were tested against four genetic diagnostics datasets (two in-house and two external) for a total of 495 samples with 231 single and multi-exon validated CNVs. The evaluation was performed using the default and sensitivity-optimized parameters. Results showed that most tools were highly sensitive and specific, but the performance was dataset dependant. When evaluating them in our diagnostics scenario, DECoN and panelcn.MOPS detected all CNVs with the exception of one mosaic CNV missed by DECoN. However, DECoN outperformed panelcn.MOPS specificity achieving values greater than 0.90 when using the optimized parameters. In our in-house datasets, DECoN and panelcn.MOPS showed the highest performance for CNV screening before orthogonal confirmation. Benchmarking and optimization code is freely available at https://github.com/TranslationalBioinformaticsIGTP/CNVbenchmarkeR .

MET-dependent solid tumours - molecular diagnosis and targeted therapy

Attempts to develop MET-targeted therapies have historically focused on MET-expressing cancers, with limited success. Thus, MET expression in the absence of a genomic marker of MET dependence is a poor predictor of benefit from MET-targeted therapy. However, owing to the development of more sensitive methods of detecting genomic alterations, high-level MET amplification and activating MET mutations or fusions are all now known to be drivers of oncogenesis. MET mutations include those affecting the kinase or extracellular domains and those that result in exon 14 skipping. The activity of MET tyrosine kinase inhibitors varies by MET alteration category. The likelihood of benefit from MET-targeted therapies increases with increasing levels of MET amplification, although no consensus exists on the optimal diagnostic cut-off point for MET copy number gains identified using fluorescence in situ hybridization and, in particular, next-generation sequencing. Several agents targeting exon 14 skipping alterations are currently in clinical development, with promising data available from early-phase trials. By contrast, the therapeutic implications of MET fusions remain underexplored. Here we summarize and evaluate the utility of various diagnostic techniques and the roles of different classes of MET-targeted therapies in cancers with MET amplification, mutation and fusion, and MET overexpression.

Molecular diagnosis of muscular diseases in outpatient clinics: A Canadian perspective

Objective

To evaluate the diagnostic yield of an 89-gene panel in a large cohort of patients with suspected muscle disorders and to compare the diagnostic yield of gene panel and exome sequencing approaches.

Methods

We tested 1,236 patients from outpatient clinics across Canada using a gene panel and performed exome sequencing for 46 other patients with sequential analysis of 89 genes followed by all mendelian genes. Sequencing and analysis were performed in patients with muscle weakness or symptoms suggestive of a muscle disorder and showing at least 1 supporting clinical laboratory.

Results

We identified a molecular diagnosis in 187 (15.1%) of the 1,236 patients tested with the 89-gene panel. Diagnoses were distributed across 40 different genes, but 6 (DMD, RYR1, CAPN3, PYGM, DYSF, and FKRP) explained about half of all cases. Cardiac anomalies, positive family history, age <60 years, and creatine kinase >1,000 IU/L were all associated with increased diagnostic yield. Exome sequencing identified a diagnosis in 10 (21.7%) of the 46 patients tested. Among these, 3 were attributed to genes not included in the 89-gene panel. Despite differences in median coverage, only 1 of the 187 diagnoses that were identified on gene panel in the 1,236 patients could have been potentially missed if exome sequencing had been performed instead.

Conclusions

Our study supports the use of gene panel testing in patients with suspected muscle disorders from outpatient clinics. It also shows that exome sequencing has a low risk of missing diagnoses compared with gene panel, while potentially increasing the diagnostic yield of patients with muscle disorders.

Genomic testing in myeloid malignancy

Clinical genetic testing in the myeloid malignancies is undergoing a rapid transition from the era of cytogenetics and single-gene testing to an era dominated by next-generation sequencing (NGS). This transition promises to better reveal the genetic alterations underlying disease, but there are distinct risks and benefits associated with different NGS testing platforms. NGS offers the potential benefit of being able to survey alterations across a wider set of genes, but analytic and clinical challenges associated with incidental findings, germ line variation, turnaround time, and limits of detection must be addressed. Additionally, transcriptome-based testing may offer several distinct benefits beyond traditional DNA-based methods. In addition to testing at disease diagnosis, research indicates potential benefits of genetic testing both prior to disease onset and at remission. In this review, we discuss the transition from the era of cytogenetics and single-gene tests to the era of NGS panels and genome-wide sequencing-highlighting both the potential and drawbacks of these novel technologies.

Novel homozygous OSGEP gene pathogenic variants in two unrelated patients with Galloway-Mowat syndrome: case report and review of the literature

Background

Galloway-Mowat syndrome (GAMOS) is a rare autosomal recessive disorder characterized by early-onset nephrotic syndrome and microcephaly with brain anomalies. WDR73 pathogenic variants were described as the first genetic cause of GAMOS and, very recently, four novel causative genes, OSGEP, LAGE3, TP53RK, and TPRKB, have been identified.

Case presentation

We present the clinical and genetic characteristics of two unrelated infants with clinical suspicion of GAMOS who were born from consanguineous parents. Both patients showed a similar clinical presentation, with early-onset nephrotic syndrome, microcephaly, brain atrophy, developmental delay, axial hypotonia, and early fatality. We identified two novel likely disease-causing variants in the OSGEP gene. These two cases, in conjunction with the findings of a literature review, indicate that OSGEP pathogenic variants are associated with an earlier onset of nephrotic syndrome and shorter life expectancy than WDR73 pathogenic variants.

Conclusions

Our findings expand the spectrum of pathogenic variants in the OSGEP gene and, taken in conjunction with the results of the literature review, suggest that the OSGEP gene should be considered the main known monogenic cause of GAMOS. Early genetic diagnosis of GAMOS is of paramount importance for genetic counseling and family planning.

Genomic Landscape of Sporadic Retinitis Pigmentosa: Findings from 877 Spanish Cases

PURPOSE

We aimed to unravel the molecular basis of sporadic retinitis pigmentosa (sRP) in the largest cohort reported to date.

DESIGN

Case series.

PARTICIPANTS

A cohort of 877 unrelated Spanish sporadic cases with a clinical diagnosis of retinitis pigmentosa (RP) and negative family history.

METHODS

The cohort was studied by classic genotyping or targeted next-generation sequencing (NGS). Multiplex ligation-dependent probe amplification (MLPA) and array-based comparative genomic hybridization were performed to confirm copy number variations detected by NGS. Quantitative fluorescent polymerase chain reaction was assessed in sRP cases carrying de novo variants to confirm paternity.

MAIN OUTCOME MEASURES

The study of the sRP cohort showed a high proportion of causal autosomal dominant (AD) and X-linked (XL) variants, most of them being de novo.

RESULTS

Causative variants were identified in 38% of the patients studied, segregating recessively in 84.5% of the solved cases. Biallelic variants detected in only 6 different autosomal recessive genes explained 50% of the cases characterized. Causal AD and XL variants were found in 7.6% and 7.9% of cases, respectively. Remarkably, 20 de novo variants were confirmed after trio analysis, explaining 6% of the cases. In addition, 17% of the solved sRP cases were reclassified to a different retinopathy phenotype.

CONCLUSIONS

This study highlights the clinical utility of NGS testing for sRP cases, expands the mutational spectrum, and provides accurate prevalence of mutated genes. Our findings evidence the underestimated role of de novo variants in the etiology of RP, emphasizing the importance of segregation analysis as well as comprehensive screening of genes carrying XL and AD variants in sporadic cases. Such in-depth study is essential for accurate family counseling and future enrollment in gene therapy-based treatments.

Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel

PURPOSE

To provide a validated method to confidently identify exon-containing copy-number variants (CNVs), with a low false discovery rate (FDR), in targeted sequencing data from a clinical laboratory with particular focus on single-exon CNVs.

METHODS

DNA sequence coverage data are normalized within each sample and subsequently exonic CNVs are identified in a batch of samples, when the target log₂ ratio of the sample to the batch median exceeds defined thresholds. The quality of exonic CNV calls is assessed by C-scores (Z-like scores) using thresholds derived from gold standard samples and simulation studies. We integrate an ExonQC threshold to lower FDR and compare performance with alternate software (VisCap).

RESULTS

Thirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. We demonstrated FDR reduction in validation, simulation, and 10,926 eMERGESeq samples without sensitivity loss. Sixty-four multiexon and 29 single-exon CNVs with high C-scores were assessed by Multiplex Ligation-dependent Probe Amplification (MLPA).

CONCLUSION

Atlas-CNV is validated as a method to identify exonic CNVs in targeted sequencing data generated in the clinical laboratory. The ExonQC and C-score assignment can reduce FDR (identification of targets with high variance) and improve calling accuracy of single-exon CNVs respectively. We propose guidelines and criteria to identify high confidence single-exon CNVs.