panelcn.MOPS: Copy-number detection in targeted NGS panel data for clinical diagnostics

Parkinson's Disease Gene Screening in Familial Cases from Central and South America

BACKGROUND

Parkinson's disease (PD) is the second most common neurodegenerative disease following Alzheimer's disease. Nearly 30 causative genes have been identified for PD and related disorders. However, most of these genes were identified in European-derived families, and little is known about their role in Latin American populations.

OBJECTIVES

Our goal was to assess the spectrum and frequency of pathogenic variants in known PD genes in familial PD patients from Latin America.

METHODS

We selected 335 PD patients with a family history of PD from the Latin American Research Consortium on the Genetics of PD. We capture-sequenced the coding regions of 26 genes related to neurodegenerative parkinsonism. Of the 335 PD patients, 324 had sufficient sequencing coverage to be analyzed.

RESULTS

We identified pathogenic variants in 41 individuals (12.7%) in FBXO7, GCH1, LRRK2, PARK7, PINK1, PLA2G6, PRKN, SNCA, and TARDBP, GBA1 risk variants in 25 individuals (7.7%), and variants of uncertain significance in another 24 individuals (7.4%) in ATP13A2, ATP1A3, DNAJC13, DNAJC6, GBA1, LRKK2, PINK1, VPS13C, and VPS35. Of the 70 unique variants identified, 19 were more frequent in Latin Americans than in any other population.

CONCLUSIONS

This is the first screening of known PD genes in a large cohort of patients with familial PD from Latin America. There were substantial differences in the spectrum of variants observed in comparison to previous findings from PD families of European origin. Our data provide further evidence that differences exist between the genetic architecture of PD in Latinos and European-derived populations. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Next-Generation Sequencing-Based Copy Number Variation Analysis in Chinese Patients with Primary Ciliary Dyskinesia Revealed Novel DNAH5 Copy Number Variations

Primary ciliary dyskinesia (PCD) is a rare disorder characterized by extensive genetic heterogeneity. However, in the genetic pathogenesis of PCD, copy number variation (CNV) has not received sufficient attention and has rarely been reported, especially in China. Next-generation sequencing (NGS) followed by targeted CNV analysis was used in patients highly suspected to have PCD with negative results in routine whole-exome sequencing (WES) analysis. Quantitative real-time polymerase chain reaction (qPCR) and Sanger sequencing were used to confirm these CNVs. To further characterize the ciliary phenotypes, high-speed video microscopy analysis (HSVA), transmission electron microscopy (TEM), and immunofluorescence (IF) analysis were used. Patient 1 (F1: II-1), a 0.6-year-old girl, came from a nonconsanguineous family-I. She presented with situs inversus totalis, neonatal respiratory distress, and sinusitis. The nasal nitric oxide level was markedly reduced. The respiratory cilia beat with reduced amplitude. TEM revealed shortened outer dynein arms (ODA) of cilia. chr5:13717907-13722661del spanning exons 71-72 was identified by NGS-based CNV analysis. Patient 2 (F2: IV-4), a 37-year-old man, and his eldest brother Patient 3 (F2: IV-2) came from a consanguineous family-II. Both had sinusitis, bronchiectasis and situs inversus totalis. The respiratory cilia of Patient 2 and Patient 3 were found to be uniformly immotile, with ODA defects. Two novel homozygous deletions chr5:13720087_13733030delinsGTTTTC and chr5:13649539_1 3707643del, spanning exons 69-71 and exons 77-79 were identified by NGS-based CNV analysis. Abnormalities in DNA copy number were confirmed by qPCR amplification. IF showed that the respiratory cilia of Patient 1 and Patient 2 were deficient in dynein axonemal heavy chain 5 (DNAH5) protein expression. This report identified three novel DNAH5 disease-associated variants by WES-based CNV analysis. Our study expands the genetic spectrum of PCD with DNAH5 in the Chinese population.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00130-0.

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Early Cancer Detection in Li-Fraumeni Syndrome with Cell-Free DNA

People with Li-Fraumeni syndrome (LFS) harbor a germline pathogenic variant in the TP53 tumor suppressor gene, face a near 100% lifetime risk of cancer, and routinely undergo intensive surveillance protocols. Liquid biopsy has become an attractive tool for a range of clinical applications, including early cancer detection. Here, we provide a proof-of-principle for a multimodal liquid biopsy assay that integrates a targeted gene panel, shallow whole-genome, and cell-free methylated DNA immunoprecipitation sequencing for the early detection of cancer in a longitudinal cohort of 89 LFS patients. Multimodal analysis increased our detection rate in patients with an active cancer diagnosis over uni-modal analysis and was able to detect cancer-associated signal(s) in carriers prior to diagnosis with conventional screening (positive predictive value = 67.6%, negative predictive value = 96.5%). Although adoption of liquid biopsy into current surveillance will require further clinical validation, this study provides a framework for individuals with LFS.

SIGNIFICANCE

By utilizing an integrated cell-free DNA approach, liquid biopsy shows earlier detection of cancer in patients with LFS compared with current clinical surveillance methods such as imaging. Liquid biopsy provides improved accessibility and sensitivity, complementing current clinical surveillance methods to provide better care for these patients. See related commentary by Latham et al., p. 23. This article is featured in Selected Articles from This Issue, p. 5.

BRACNAC: A BRCA1 and BRCA2 Copy Number Alteration Caller from Next-Generation Sequencing Data

Detecting copy number variations (CNVs) and alterations (CNAs) in the BRCA1 and BRCA2 genes is essential for testing patients for targeted therapy applicability. However, the available bioinformatics tools were initially designed for identifying CNVs/CNAs in whole-genome or -exome (WES) NGS data or targeted NGS data without adaptation to the BRCA1/2 genes. Most of these tools were tested on sample cohorts of limited size, with their use restricted to specific library preparation kits or sequencing platforms. We developed BRACNAC, a new tool for detecting CNVs and CNAs in the BRCA1 and BRCA2 genes in NGS data of different origin. The underlying mechanism of this tool involves various coverage normalization steps complemented by CNV probability evaluation. We estimated the sensitivity and specificity of our tool to be 100% and 94%, respectively, with an area under the curve (AUC) of 94%. The estimation was performed using the NGS data obtained from 213 ovarian and prostate cancer samples tested with in-house and commercially available library preparation kits and additionally using multiplex ligation-dependent probe amplification (MLPA) (12 CNV-positive samples). Using freely available WES and targeted NGS data from other research groups, we demonstrated that BRACNAC could also be used for these two types of data, with an AUC of up to 99.9%. In addition, we determined the limitations of the tool in terms of the minimum number of samples per NGS run (≥20 samples) and the minimum expected percentage of CNV-negative samples (≥80%). We expect that our findings will improve the efficacy of BRCA1/2 diagnostics. BRACNAC is freely available at the GitHub server.

Copy Number Variations (CNVs) Account for 10.8% of Pathogenic Variants in Patients Referred for Hereditary Cancer Testing

BACKGROUND/AIM

Germline copy number variation (CNV) is a type of genetic variant that predisposes significantly to inherited cancers. Today, next-generation sequencing (NGS) technologies have contributed to multi gene panel analysis in clinical practice.

MATERIALS AND METHODS

A total of 2,163 patients were screened for cancer susceptibility, using a solution-based capture method. A panel of 52 genes was used for targeted NGS. The capture-based approach enables computational analysis of CNVs from NGS data. We studied the performance of the CNV module of the commercial software suite SeqPilot (JSI Medical Systems) and of the non-commercial tool panelcn.MOPS. Additionally, we tested the performance of digital multiplex ligation-dependent probe amplification (digitalMLPA).

RESULTS

Pathogenic/likely pathogenic variants (P/LP) were identified in 464 samples (21.5%). CNV accounts for 10.8% (50/464) of pathogenic variants, referring to deletion/duplication of one or more exons of a gene. In patients with breast and ovarian cancer, CNVs accounted for 10.2% and 6.8% of pathogenic variants, respectively. In colorectal cancer patients, CNV accounted for 28.6% of pathogenic/likely pathogenic variants.

CONCLUSION

In silico CNV detection tools provide a viable and cost-effective method to identify CNVs from NGS experiments. CNVs constitute a substantial percentage of P/LP variants, since they represent up to one of every ten P/LP findings identified by NGS multigene analysis; therefore, their evaluation is highly recommended to improve the diagnostic yield of hereditary cancer analysis.

Copy Number Variation Discovery in South African Nguni-Sired and Bonsmara-Sired Crossbred Cattle

Crossbreeding forms part of Climate-Smart beef production and is one of the strategies to mitigate the effects of climate change. Two Nguni-sired and three Bonsmara-sired crossbred animals underwent whole genome sequencing. Following quality control and file preparation, the sequence data were investigated for genome-wide copy number variation (CNV) using the panelcn.MOPS tool. A total of 355 CNVs were identified in the crossbreds, of which 274 were unique in Bonsmara-sired crossbreds and 81 unique in the Nguni-sired crossbreds. Genes that differed in copy number in both crossbreds included genes related to growth (SCRN2, LOC109572916) and fertility-related factors (RPS28, LOC1098562432, LOC109570037). Genes that were present only in the Bonsmara-sired crossbreds included genes relating to lipid metabolism (MAF1), olfaction (LOC109569114), body size (HES7), immunity (LOC10957335, LOC109877039) and disease (DMBT1). Genes that were present only in the Nguni-sired crossbreds included genes relating to ketosis (HMBOX1) and amino acid transport (LOC109572916). Results of this study indicate that Nguni and Bonsmara cattle can be utilized in crossbreeding programs as they may enhance the presence of economically important traits associated with both breeds. This will produce crossbred animals that are good meat producers, grow faster, have high fertility, strong immunity and a better chance of producing in South Africa's harsh climate conditions. Ultimately, this study provides new genetic insights into the adaptability of Nguni and Bonsmara crossbred cattle.

Leigh Syndrome Spectrum: A Portuguese Population Cohort in an Evolutionary Genetic Era

Mitochondrial diseases are the most common inherited inborn error of metabolism resulting in deficient ATP generation, due to failure in homeostasis and proper bioenergetics. The most frequent mitochondrial disease manifestation in children is Leigh syndrome (LS), encompassing clinical, neuroradiological, biochemical, and molecular features. It typically affects infants but occurs anytime in life. Considering recent updates, LS clinical presentation has been stretched, and is now named LS spectrum (LSS), including classical LS and Leigh-like presentations. Apart from clinical diagnosis challenges, the molecular characterization also progressed from Sanger techniques to NGS (next-generation sequencing), encompassing analysis of nuclear (nDNA) and mitochondrial DNA (mtDNA). This upgrade resumed steps and favored diagnosis. Hereby, our paper presents molecular and clinical data on a Portuguese cohort of 40 positive cases of LSS. A total of 28 patients presented mutation in mtDNA and 12 in nDNA, with novel mutations identified in a heterogeneous group of genes. The present results contribute to the better knowledge of the molecular basis of LS and expand the clinical spectrum associated with this syndrome.

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.

The Scarface Score: Deciphering Response to DNA Damage Agents in High-Grade Serous Ovarian Cancer-A GEICO Study

Genomic Instability (GI) is a transversal phenomenon shared by several tumor types that provide both prognostic and predictive information. In the context of high-grade serous ovarian cancer (HGSOC), response to DNA-damaging agents such as platinum-based and poly(ADP-ribose) polymerase inhibitors (PARPi) has been closely linked to deficiencies in the DNA repair machinery by homologous recombination repair (HRR) and GI. In this study, we have developed the Scarface score, an integrative algorithm based on genomic and transcriptomic data obtained from the NGS analysis of a prospective GEICO cohort of 190 formalin-fixed paraffin-embedded (FFPE) tumor samples from patients diagnosed with HGSOC with a median follow up of 31.03 months (5.87-159.27 months). In the first step, three single-source models, including the SNP-based model (accuracy = 0.8077), analyzing 8 SNPs distributed along the genome; the GI-based model (accuracy = 0.9038) interrogating 28 parameters of GI; and the HTG-based model (accuracy = 0.8077), evaluating the expression of 7 genes related with tumor biology; were proved to predict response. Then, an ensemble model called the Scarface score was found to predict response to DNA-damaging agents with an accuracy of 0.9615 and a kappa index of 0.9128 (p < 0.0001). The Scarface Score approaches the routine establishment of GI in the clinical setting, enabling its incorporation as a predictive and prognostic tool in the management of HGSOC.

Adaptive Savitzky–Golay Filters for Analysis of Copy Number Variation Peaks from Whole-Exome Sequencing Data

Copy number variation (CNV) is a form of structural variation in the human genome that provides medical insight into complex human diseases; while whole-genome sequencing is becoming more affordable, whole-exome sequencing (WES) remains an important tool in clinical diagnostics. Because of its discontinuous nature and unique characteristics of sparse target-enrichment-based WES data, the analysis and detection of CNV peaks remain difficult tasks. The Savitzky–Golay (SG) smoothing is well known as a fast and efficient smoothing method. However, no study has documented the use of this technique for CNV peak detection. It is well known that the effectiveness of the classical SG filter depends on the proper selection of the window length and polynomial degree, which should correspond with the scale of the peak because, in the case of peaks with a high rate of change, the effectiveness of the filter could be restricted. Based on the Savitzky–Golay algorithm, this paper introduces a novel adaptive method to smooth irregular peak distributions. The proposed method ensures high-precision noise reduction by dynamically modifying the results of the prior smoothing to automatically adjust parameters. Our method offers an additional feature extraction technique based on density and Euclidean distance. In comparison to classical Savitzky–Golay filtering and other peer filtering methods, the performance evaluation demonstrates that adaptive Savitzky–Golay filtering performs better. According to experimental results, our method effectively detects CNV peaks across all genomic segments for both short and long tags, with minimal peak height fidelity values (i.e., low estimation bias). As a result, we clearly demonstrate how well the adaptive Savitzky–Golay filtering method works and how its use in the detection of CNV peaks can complement the existing techniques used in CNV peak analysis.

Genetic insights into childhood-onset schizophrenia: The yield of clinical exome sequencing

Childhood-onset schizophrenia (COS) is a rare form of schizophrenia with an onset prior to 13 years of age. Although genetic factors play a role in COS etiology, only a few causal variants have been reported to date. This study presents a diagnostic exome sequencing (ES) in 37 Israeli Jewish families with a proband diagnosed with COS. By implementing a trio/duo ES approach and applying a well-established diagnostic pipeline, we detected clinically significant variants in 7 probands (19 %). These single nucleotide variants and indels were mostly inherited. The implicated genes were ANKRD11, GRIA2, CHD2, CLCN3, CLTC, IGF1R and MICU1. In a secondary analysis that compared COS patients to 4721 healthy controls, we observed that patients had a significant enrichment of rare loss of function (LoF) variants in LoF intolerant genes associated with developmental diseases. Taken together, ES could be considered as a valuable tool in the genetic workup for COS patients.

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.

Array genotyping as diagnostic approach in medical genetics

Genotyping arrays are by far the most widely used genetic tests but are not generally utilized for diagnostic purposes in a medical context. In the present study, we examined the diagnostic value of a standard genotyping array (Illumina Global Screening Array) for a range of indications. Applications included stand-alone testing for specific variants (32 variants in 10 genes), first-tier array variant screening for monogenic conditions (10 different autosomal recessive metabolic diseases), and diagnostic workup for specific conditions caused by variants in multiple genes (suspected familial breast and ovarian cancer, and hypercholesterolemia). Our analyses showed a high analytical sensitivity and specificity of array-based analyses for validated and non-validated variants, and identified pitfalls that require attention. Ethical-legal assessment highlighted the need for a software solution that allows for individual indication-based consent and the reliable exclusion of non-consented results. Cost/time assessment revealed excellent performance of diagnostic array analyses, depending on indication, proband data, and array design. We have implemented some analyses in our diagnostic portfolio, but array optimization is required for the implementation of other indications.

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.

Acute to Subacute Atraumatic Entrapment Neuropathies in Patients With CMT1A: A Report of a Distinct Phenotypic Variant of CMT1A

Charcot-Marie-Tooth type 1A (CMT1A) is typically characterised as a childhood-onset, symmetrical, length-dependent polyneuropathy with a gradual progressive clinical course. Acute to subacute neurological deterioration in CMT1A is rare, and has been reported secondary to overlap pathologies including inflammatory neuropathy. We identified two patients with CMT1A who presented with acute to subacute, atraumatic, entrapment neuropathies as an initial symptom. A superimposed inflammatory neuropathy was excluded. Both patients had a diffuse demyelinating polyneuropathy, with markedly low motor nerve conduction velocities (<20 m/s). In both patients, we demonstrated symptomatic and asymptomatic partial conduction blocks at multiple entrapment sites. Nerve ultrasound findings in our patients demonstrated marked diffuse nerve enlargement, more pronounced at non-entrapment sites compared to entrapment sites. We discuss ways to distinguish this condition from its other differentials. We propose pathophysiological mechanisms underlying this condition. We propose that CMT1A with acute to subacute, atraumatic, entrapment neuropathies to be a distinct phenotypic variant of CMT1A.

Phase 2 Trial (POLA Study) of Lurbinectedin plus Olaparib in Patients with Advanced Solid Tumors: Results of Efficacy, Tolerability, and the Translational Study

We hypothesized that the combination of olaparib and lurbinectedin maximizes DNA damage, thus increasing its efficacy. The POLA phase 1 trial established the recommended phase 2 dose of lurbinectedin as being 1.5 mg (day 1) and that of olaparib as being 250 mg/12 h (days 1-5) for a 21-day cycle. In phase 2, we explore the efficacy of the combination in terms of clinical response and its correlation with mutations in the HRR genes and the genomic instability (GI) parameters. Results: A total of 73 patients with high-grade ovarian (n = 46), endometrial (n = 26), and triple-negative breast cancer (n = 1) were treated with lurbinectedin and olaparib. Most patients (62%) received ≥3 lines of prior therapy. The overall response rate (ORR) and disease control rate (DCR) were 9.6% and 72.6%, respectively. The median progression-free survival (PFS) was 4.54 months (95% CI 3.0-5.2). Twelve (16.4%) patients were considered long-term responders (LTR), with a median PFS of 13.3 months. No clinical benefit was observed for cases with HRR gene mutation. In ovarian LTRs, although a direct association with GI and a total loss of heterozygosity (LOH) events was observed, the association did not reach statistical significance (p = 0.055). Globally, the total number of LOHs might be associated with the ORR (p =0.074). The most common grade 3-4 toxicities were anemia and thrombocytopenia, in 6 (8.2%) and 3 (4.1%) patients, respectively. Conclusion: The POLA study provides evidence that the administration of lurbinectedin and olaparib is feasible and tolerable, with a DCR of 72.6%. Different GI parameters showed associations with better responses.

Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort

Renal cell carcinoma (RCC) is among the 10 most common cancer entities and can be categorised into distinct subtypes by differential expression of Krebs cycle genes. We investigated the predictive value of several targeted metabolites with regards to tumour stages and patient survival in an unselected cohort of 420 RCCs. Unsupervised hierarchical clustering of metabolite ratios identified two main clusters separated by α-ketoglutarate (α-KG) levels and sub-clusters with differential levels of the oncometabolite 2-hydroxyglutarate (2HG). Sub-clusters characterised by high 2HG were enriched in higher tumour stages, suggesting metabolite profiles might be suitable predictors of tumour stage or survival. Bootstrap forest models based on single metabolite signatures showed that lactate, 2HG, citrate, aspartate, asparagine, and glutamine better predicted the cancer-specific survival (CSS) of clear cell RCC patients, whereas succinate and α-ketoglutarate were better CSS predictors for papillary RCC patients. Additionally, this assay identifies rare cases of tumours with SDHx mutations, which are caused predominantly by germline mutations and which predispose to development of different neoplasms. Hence, analysis of selected metabolites should be further evaluated for potential utility in liquid biopsies, which can be obtained using less invasive methods and potentially facilitate disease monitoring for both patients and caregivers.

isoCNV: in silico optimization of copy number variant detection from targeted or exome sequencing data

Background

Accurate copy number variant (CNV) detection is especially challenging for both targeted sequencing (TS) and whole‐exome sequencing (WES) data. To maximize the performance, the parameters of the CNV calling algorithms should be optimized for each specific dataset. This requires obtaining validated CNV information using either multiplex ligation-dependent probe amplification (MLPA) or array comparative genomic hybridization (aCGH). They are gold standard but time-consuming and costly approaches.

Results

We present isoCNV which optimizes the parameters of DECoN algorithm using only NGS data. The parameter optimization process is performed using an in silico CNV validated dataset obtained from the overlapping calls of three algorithms: CNVkit, panelcn.MOPS and DECoN. We evaluated the performance of our tool and showed that increases the sensitivity in both TS and WES real datasets.

Conclusions

isoCNV provides an easy-to-use pipeline to optimize DECoN that allows the detection of analysis-ready CNV from a set of DNA alignments obtained under the same conditions. It increases the sensitivity of DECoN without the need for orthogonal methods. isoCNV is available at https://gitlab.com/sequentiateampublic/isocnv.

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.

Low-level mosaicism in tuberous sclerosis complex in four unrelated patients: Comparison of clinical characteristics and diagnostic pathways

Tuberous sclerosis complex (TSC) is an autosomal dominant neurocutaneous syndrome caused by either TSC1 or TSC2 gene mutations. About 15% of TSC patients remain without genetic diagnosis by conventional analysis despite clinical evidence. It is important to identify somatic mosaics, as therapeutic options are now available in patients with TSC1 or TSC2 mutations. Here, we describe the clinical and genetic characteristics of four male TSC patients with low‐level mosaicism. Patients presented at ages between 9 months and 32 years. Clinical manifestations varied considerably and included brain lesions in all four patients, cardiac rhabdomyomas in two young patients, skin involvement in two patients, and retinal hamartomas and renal angiomyolipomas in three patients. One patient presented with epileptic seizures and psychomotor delay. Low levels of mosaicism for TSC1 or TSC2 mutation were found in different tissue samples employing next generation sequencing and multiple ligation‐dependent probe amplification. The five disease‐associated variants, including one second‐hit mutation, include three truncating mutations and one deletion in TSC2, and one truncating mutation in TSC1. Sanger sequencing, allele‐specific oligonucleotide PCR (ASO‐PCR), and droplet digital PCR were used to confirm and quantify the disclosed mutations. Genetic identification of low‐level mosaicism for TSC remains challenging but is important for optimal surveillance and management.

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.

Genetic Characterization of Cancer of Unknown Primary Using Liquid Biopsy Approaches

Cancers of unknown primary (CUPs) comprise a heterogeneous group of rare metastatic tumors whose primary site cannot be identified after extensive clinical-pathological investigations. CUP patients are generally treated with empirical chemotherapy and have dismal prognosis. As recently reported, CUP genome presents potentially druggable alterations for which targeted therapies could be proposed. The paucity of tumor tissue, as well as the difficult DNA testing and the lack of dedicated panels for target gene sequencing are further relevant limitations. Here, we propose that circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) could be used to identify actionable mutations in CUP patients. Blood was longitudinally collected from two CUP patients. CTCs were isolated with CELLSEARCH® and DEPArrayTM NxT and Parsortix systems, immunophenotypically characterized and used for single-cell genomic characterization with Ampli1TM kits. Circulating cell-free DNA (ccfDNA), purified from plasma at different time points, was tested for tumor mutations with a CUP-dedicated, 92-gene custom panel using SureSelect Target Enrichment technology. In parallel, FFPE tumor tissue was analyzed with three different assays: FoundationOne CDx assay, DEPArray LibPrep and OncoSeek Panel, and the SureSelect custom panel. These approaches identified the same mutations, when the gene was covered by the panel, with the exception of an insertion in APC gene. which was detected by OncoSeek and SureSelect panels but not FoundationOne. FGFR2 and CCNE1 gene amplifications were detected in single CTCs, tumor tissue, and ccfDNAs in one patient. A somatic variant in ARID1A gene (p.R1276∗) was detected in the tumor tissue and ccfDNAs. The alterations were validated by Droplet Digital PCR in all ccfDNA samples collected during tumor evolution. CTCs from a second patient presented a pattern of recurrent amplifications in ASPM and SEPT9 genes and loss of FANCC. The 92-gene custom panel identified 16 non-synonymous somatic alterations in ccfDNA, including a deletion (I1485Rfs∗19) and a somatic mutation (p. A1487V) in ARID1A gene and a point mutation in FGFR2 gene (p.G384R). Our results support the feasibility of non-invasive liquid biopsy testing in CUP cases, either using ctDNA or CTCs, to identify CUP genetic alterations with broad NGS panels covering the most frequently mutated genes.

Biallelic variants in VPS50 cause a neurodevelopmental disorder with neonatal cholestasis

Golgi-associated retrograde protein (GARP) and endosome-associated recycling protein (EARP) complexes are membrane-tethering heterotetramers located at the trans-Golgi network and recycling endosomes, respectively. GARP and EARP share the three subunits VPS51, VPS52, and VPS53, while VPS50 is unique to EARP and VPS54 to GARP. Retrograde transport of endosomal cargos to the TGN is mediated by GARP and endocytic recycling by EARP. Here we report two unrelated individuals with homozygous variants in VPS50, a splice variant (c.1978-1G>T) and an in-frame deletion (p.Thr608del). Both patients had severe developmental delay, postnatal microcephaly, corpus callosum hypoplasia, seizures and irritability, transient neonatal cholestasis, and failure to thrive. Light and transmission electron microscopy of liver from one revealed absence of gamma-glutamyltransferase at bile canaliculi, with mislocalization to basolateral membranes, and abnormal tight junctions. Using patient-derived fibroblasts, we identified reduced VPS50 protein accompanied by reduced levels of VPS52 and VPS53. While transferrin-receptor internalization rate was normal in cells of both patients, recycling of the receptor to the plasma membrane was significantly delayed. These data underscore the importance of VPS50 and/or the EARP complex in endocytic recycling and suggest an additional function in establishing cell polarity and trafficking between basolateral and apical membranes in hepatocytes. Individuals with biallelic hypomorphic variants in VPS50, VPS51 or VPS53 show an overarching neurodegenerative disorder with severe developmental delay, intellectual disability, microcephaly, early-onset epilepsy, and variable atrophy of the cerebellum, cerebrum, and/or brainstem. The term "GARP/EARP deficiency" designates disorders in such individuals.

Clinical Utility of Functional RNA Analysis for the Reclassification of Splicing Gene Variants in Hereditary Cancer

BACKGROUND

Classification of splicing variants (SVs) in genes associated with hereditary cancer is often challenging. The aim of this study was to investigate the occurrence of SVs in hereditary cancer genes and the clinical utility of RNA analysis.

MATERIAL AND METHODS

1518 individuals were tested for cancer predisposition, using a Next Generation Sequencing (NGS) panel of 36 genes. Splicing variant analysis was performed using RT-PCR and Sanger Sequencing.

RESULTS

In total, 34 different SVs were identified, 53% of which were classified as pathogenic or likely pathogenic. The remaining 16 variants were initially classified as Variant of Uncertain Significance (VUS). RNA analysis was performed for 3 novel variants.

CONCLUSION

The RNA analysis assisted in the reclassification of 20% of splicing variants from VUS to pathogenic. RNA analysis is essential in the case of uncharacterized splicing variants, for proper classification and personalized management of these patients.

Bioinformatic strategies for the analysis of genomic aberrations detected by targeted NGS panels with clinical application

Molecular profiling of tumor samples has acquired importance in cancer research, but currently also plays an important role in the clinical management of cancer patients. Rapid identification of genomic aberrations improves diagnosis, prognosis and effective therapy selection. This can be attributed mainly to the development of next-generation sequencing (NGS) methods, especially targeted DNA panels. Such panels enable a relatively inexpensive and rapid analysis of various aberrations with clinical impact specific to particular diagnoses. In this review, we discuss the experimental approaches and bioinformatic strategies available for the development of an NGS panel for a reliable analysis of selected biomarkers. Compliance with defined analytical steps is crucial to ensure accurate and reproducible results. In addition, a careful validation procedure has to be performed before the application of NGS targeted assays in routine clinical practice. With more focus on bioinformatics, we emphasize the need for thorough pipeline validation and management in relation to the particular experimental setting as an integral part of the NGS method establishment. A robust and reproducible bioinformatic analysis running on powerful machines is essential for proper detection of genomic variants in clinical settings since distinguishing between experimental noise and real biological variants is fundamental. This review summarizes state-of-the-art bioinformatic solutions for careful detection of the SNV/Indels and CNVs for targeted sequencing resulting in translation of sequencing data into clinically relevant information. Finally, we share our experience with the development of a custom targeted NGS panel for an integrated analysis of biomarkers in lymphoproliferative disorders.

CNV_IFTV: An Isolation Forest and Total Variation-Based Detection of CNVs from Short-Read Sequencing Data

Accurate detection of copy number variations (CNVs) from short-read sequencing data is challenging due to the uneven distribution of reads and the unbalanced amplitudes of gains and losses. The direct use of read depths to measure CNVs tends to limit performance. Thus, robust computational approaches equipped with appropriate statistics are required to detect CNV regions and boundaries. This study proposes a new method called CNV_IFTV to address this need. CNV_IFTV assigns an anomaly score to each genome bin through a collection of isolation trees. The trees are trained based on isolation forest algorithm through conducting subsampling from measured read depths. With the anomaly scores, CNV_IFTV uses a total variation model to smooth adjacent bins, leading to a denoised score profile. Finally, a statistical model is established to test the denoised scores for calling CNVs. CNV_IFTV is tested on both simulated and real data in comparison to several peer methods. The results indicate that the proposed method outperforms the peer methods. CNV_IFTV is a reliable tool for detecting CNVs from short-read sequencing data even for low-level coverage and tumor purity. The detection results on tumor samples can aid to evaluate known cancer genes and to predict target drugs for disease diagnosis.

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.

Long-Range PCR-Based NGS Applications to Diagnose Mendelian Retinal Diseases

The purpose of this study was to develop a flexible, cost-efficient, next-generation sequencing (NGS) protocol for genetic testing. Long-range polymerase chain reaction (PCR) amplicons of up to 20 kb in size were designed to amplify entire genomic regions for a panel (n = 35) of inherited retinal disease (IRD)-associated loci. Amplicons were pooled and sequenced by NGS. The analysis was applied to 227 probands diagnosed with IRD: (A) 108 previously molecularly diagnosed, (B) 94 without previous genetic testing, and (C) 25 undiagnosed after whole-exome sequencing (WES). The method was validated with 100% sensitivity on cohort A. Long-range PCR-based sequencing revealed likely causative variant(s) in 51% and 24% of proband from cohorts B and C, respectively. Breakpoints of 3 copy number variants (CNVs) could be characterized. Long-range PCR libraries spike-in extended coverage of WES. Read phasing confirmed compound heterozygosity in 5 probands. The proposed sequencing protocol provided deep coverage of the entire gene, including intronic and promoter regions. Our method can be used (i) as a first-tier assay to reduce genetic testing costs, (ii) to elucidate missing heritability cases, (iii) to characterize breakpoints of CNVs at nucleotide resolution, (iv) to extend WES data to non-coding regions by spiking-in long-range PCR libraries, and (v) to help with phasing of candidate variants.

Performance of In Silico Prediction Tools for the Detection of Germline Copy Number Variations in Cancer Predisposition Genes in 4208 Female Index Patients with Familial Breast and Ovarian Cancer

Simple Summary

The identification of germline copy number variants (CNVs) by targeted nextgeneration sequencing frequently relies on in silico prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools in 17 cancer predisposition genes in a large series of 4208 female index patients with familial breast and/or ovarian cancer. We identified 77 CNVs in 76 out of 4208 patients; six CNVs were missed by at least one of the prediction tools. Experimental verification of in silico predicted CNVs is required due to high frequencies of false positive predictions. For female index patients with familial breast and/or ovarian cancer, CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further cancer predisposition genes.

Abstract

The identification of germline copy number variants (CNVs) by targeted next-generation sequencing (NGS) frequently relies on in silico CNV prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools, including one commercial (Sophia Genetics DDM) and three non-commercial tools (ExomeDepth, GATK gCNV, panelcn.MOPS) in 17 cancer predisposition genes in 4208 female index patients with familial breast and/or ovarian cancer (BC/OC). CNV predictions were verified via multiplex ligation-dependent probe amplification. We identified 77 CNVs in 76 out of 4208 patients (1.81%); 33 CNVs were identified in genes other than BRCA1/2, mostly in ATM, CHEK2, and RAD51C and less frequently in BARD1, MLH1, MSH2, PALB2, PMS2, RAD51D, and TP53. The Sophia Genetics DDM software showed the highest sensitivity; six CNVs were missed by at least one of the non-commercial tools. The positive predictive values ranged from 5.9% (74/1249) for panelcn.MOPS to 79.1% (72/91) for ExomeDepth. Verification of in silico predicted CNVs is required due to high frequencies of false positive predictions, particularly affecting target regions at the extremes of the GC content or target length distributions. CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further BC/OC predisposition genes.

Targeted Genetic Analysis in a Chinese Cohort of 208 Patients Related to Familial Hypercholesterolemia

AIM

Familial hypercholesterolemia (FH) is the most commonly encountered genetic condition that predisposes individuals to severe autosomal dominant lipid metabolism dysfunction. Although more than 75% of the European population has been scrutinized for FH-causing mutations, the genetic diagnosis proportion among Chinese people remains very low (less than 0.5%). The aim of this study was to identify genetic mutations and help make a precise diagnosis in Chinese FH patients.

METHODS

We designed a gene panel containing 20 genes responsible for FH and tested 208 unrelated Chinese possible/probable or definite FH probands. In addition, we called LDLR copy number variation (CNVs) with the panel data by panelcn.MOPS, and multiple ligation-dependent probe amplification (MLPA) was used to search for CNVs in LDLR, APOB, and PCSK9.

RESULTS

A total of 79 probands (38.0%) tested positive for a (likely) pathogenic mutation, most of which were LDLR mutations, and three LDLR CNVs called from the panel data were all successfully confirmed by MLPA analysis. In total, 48 different mutations were identified, including 45 LDLR mutations, 1 APOB mutation, 1 ABCG5 mutation, and 1 APOE mutation. Among them, the five most frequent mutations (LDLR c.1879G＞A, c.1747C＞T, c.313＋1G＞A, c.400T＞C, and APOB c.10579C＞T) were detected. Moreover, we also found that patients with LDLR variants of CNVs and splicing and nonsense had increased low-density lipoprotein cholesterol levels when compared with those who carried missense variants.

CONCLUSIONS

The spectrum of FH-causing mutations in the Chinese population is refined and expanded. Analyses of FH causal genes have been a great help in clinical diagnosis and have deep implications in disease treatment. These data can serve as a considerable dataset for next-generation sequencing analysis of the Chinese population with FH and contribute to the genetic diagnosis and counseling of FH patients.

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.

RKDOSCNV: A Local Kernel Density-Based Approach to the Detection of Copy Number Variations by Using Next-Generation Sequencing Data

Copy number variations (CNVs) are significant causes of many human cancers and genetic diseases. The detection of CNVs has become a common method by which to analyze human diseases using next-generation sequencing (NGS) data. However, effective detection of insignificant CNVs is still a challenging task. In this study, we propose a new detection method, RKDOSCNV, to meet the need. RKDOSCNV uses kernel density estimation method to evaluate the local kernel density distribution of each read depth segment (RDS) based on an expanded nearest neighbor (k-nearest neighbors, reverse nearest neighbors, and shared nearest neighbors of each RDS) data set, and assigns a relative kernel density outlier score (RKDOS) for each RDS. According to the RKDOS profile, RKDOSCNV predicts the candidate CNVs by choosing a reasonable threshold, which it uses split read approach to correct the boundaries of candidate CNVs. The performance of RKDOSCNV is assessed by comparing it with several current popular methods via experiments with simulated and real data at different tumor purity levels. The experimental results verify that the performance of RKDOSCNV is superior to that of several other methods. In summary, RKDOSCNV is a simple and effective method for the detection of CNVs from whole genome sequencing (WGS) data, especially for samples with low tumor purity.

Analysis of Heterozygous PRKN Variants and Copy-Number Variations in Parkinson's Disease

BACKGROUND

Biallelic PRKN mutation carriers with Parkinson's disease (PD) typically have an earlier disease onset, slow disease progression, and, often, different neuropathology compared to sporadic PD patients. However, the role of heterozygous PRKN variants in the risk of PD is controversial.

OBJECTIVES

Our aim was to examine the association between heterozygous PRKN variants, including single-nucleotide variants and copy-number variations (CNVs), and PD.

METHODS

We fully sequenced PRKN in 2809 PD patients and 3629 healthy controls, including 1965 late-onset (63.97 ± 7.79 years, 63% men) and 553 early-onset PD patients (43.33 ± 6.59 years, 68% men). PRKN was sequenced using targeted next-generation sequencing with molecular inversion probes. CNVs were identified using a combination of multiplex ligation-dependent probe amplification and ExomeDepth. To examine whether rare heterozygous single-nucleotide variants and CNVs in PRKN are associated with PD risk and onset, we used optimized sequence kernel association tests and regression models.

RESULTS

We did not find any associations between all types of PRKN variants and risk of PD. Pathogenic and likely-pathogenic heterozygous single-nucleotide variants and CNVs were less common among PD patients (1.52%) than among controls (1.8%, false discovery rate-corrected P = 0.55). No associations with age at onset and in stratified analyses were found.

CONCLUSIONS

Heterozygous single-nucleotide variants and CNVs in PRKN are not associated with PD. Molecular inversion probes allow for rapid and cost-effective detection of all types of PRKN variants, which may be useful for pretrial screening and for clinical and basic science studies targeting specifically PRKN patients. © 2020 International Parkinson and Movement Disorder Society.

CONDEL: Detecting Copy Number Variation and Genotyping Deletion Zygosity from Single Tumor Samples Using Sequence Data

Characterizing copy number variations (CNVs) from sequenced genomes is a both feasible and cost-effective way to search for driver genes in cancer diagnosis. A number of existing algorithms for CNV detection only explored part of the features underlying sequence data and copy number structures, resulting in limited performance. Here, we describe CONDEL, a method for detecting CNVs from single tumor samples using high-throughput sequence data. CONDEL utilizes a novel statistic in combination with a peel-off scheme to assess the statistical significance of genome bins, and adopts a Bayesian approach to infer copy number gains, losses, and deletion zygosity based on statistical mixture models. We compare CONDEL to six peer methods on a large number of simulation datasets, showing improved performance in terms of true positive and false positive rates, and further validate CONDEL on three real datasets derived from the 1000 Genomes Project and the EGA archive. CONDEL obtained higher consistent results in comparison with other three single sample-based methods, and exclusively identified a number of CNVs that were previously associated with cancers. We conclude that CONDEL is a powerful tool for detecting copy number variations on single tumor samples even if these are sequenced at low-coverage.

Complex Characterization of Germline Large Genomic Rearrangements of the BRCA1 and BRCA2 Genes in High-Risk Breast Cancer Patients-Novel Variants from a Large National Center

Large genomic rearrangements (LGRs) affecting one or more exons of BRCA1 and BRCA2 constitute a significant part of the mutation spectrum of these genes. Since 2004, the National Institute of Oncology, Hungary, has been involved in screening for LGRs of breast or ovarian cancer families enrolled for genetic testing. LGRs were detected by multiplex ligation probe amplification method, or next-generation sequencing. Where it was possible, transcript-level characterization of LGRs was performed. Phenotype data were collected and analyzed too. Altogether 28 different types of LGRs in 51 probands were detected. Sixteen LGRs were novel. Forty-nine cases were deletions or duplications in BRCA1 and two affected BRCA2. Rearrangements accounted for 10% of the BRCA1 mutations. Three exon copy gains, two complex rearrangements, and 23 exon losses were characterized by exact breakpoint determinations. The inferred mechanisms for LGR formation were mainly end-joining repairs utilizing short direct homologies. Comparing phenotype features of the LGR-carriers to that of the non-LGR BRCA1 mutation carriers, revealed no significant differences. Our study is the largest comprehensive report of LGRs of BRCA1/2 in familial breast and ovarian cancer patients in the Middle and Eastern European region. Our data add novel insights to genetic interpretation associated to the LGRs.

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 .

Co-existence of ABCB11 and DCDC2 disease: Infantile cholestasis requires both next-generation sequencing and clinical-histopathologic correlation

A boy exhibiting conjugated hyperbilirubinemia from birth, with elevated serum gamma-glutamyl transpeptidase activity (GGT), developed liver failure unusually early (7mo); GGT concomitantly normalized. ABCB4 disease was suspected, but no ABCB4 lesion was found. The boy was instead homozygous for ABCB11 variant c.1213 T>C (p.(Cys405Arg)), which is predicted to affect protein function. Both ABCB4 and ABCB11 were normally expressed in the explanted liver, with intralobular cholestasis; however, large-duct sclerosing cholangiopathy and ductal-plate malformation also were present. The primary-cilium constituent doublecortin domain containing 2 (DCDC2) was not expressed. Co-existence of ABCB11 disease and DCDC2 disease was proposed. Further testing identified homozygosity for the canonical-receptor splice-site variant c.294-2A>G (p.?) in DCDC2. Our report emphasizes the need to integrate clinical, histological, and genetic data in patients with neonatal cholestasis.

CSGALNACT1-congenital disorder of glycosylation: A mild skeletal dysplasia with advanced bone age

Congenital disorders of glycosylation (CDGs) comprise a large number of inherited metabolic defects that affect the biosynthesis and attachment of glycans. CDGs manifest as a broad spectrum of disease, most often including neurodevelopmental and skeletal abnormalities and skin laxity. Two patients with biallelic CSGALNACT1 variants and a mild skeletal dysplasia have been described previously. We investigated two unrelated patients presenting with short stature with advanced bone age, facial dysmorphism, and mild language delay, in whom trio-exome sequencing identified novel biallelic CSGALNACT1 variants: compound heterozygosity for c.1294G>T (p.Asp432Tyr) and the deletion of exon 4 that includes the start codon in one patient, and homozygosity for c.791A>G (p.Asn264Ser) in the other patient. CSGALNACT1 encodes CSGalNAcT-1, a key enzyme in the biosynthesis of sulfated glycosaminoglycans chondroitin and dermatan sulfate. Biochemical studies demonstrated significantly reduced CSGalNAcT-1 activity of the novel missense variants, as reported previously for the p.Pro384Arg variant. Altered levels of chondroitin, dermatan, and heparan sulfate moieties were observed in patients' fibroblasts compared to controls. Our data indicate that biallelic loss-of-function mutations in CSGALNACT1 disturb glycosaminoglycan synthesis and cause a mild skeletal dysplasia with advanced bone age, CSGALNACT1-CDG.

Further delineation of putative ACTB loss-of-function variants: A 4-patient series

ACTB encodes β‐cytoplasmic actin, an essential component of the cytoskeleton. Based on chromosome 7p22.1 deletions that include the ACTB locus and on rare truncating ACTB variants, a phenotype resulting from ACTB haploinsufficiency was recently proposed. We report putative ACTB loss‐of‐function variants in four patients. To the best of our knowledge, we report the first 7p22.1 microdeletion confined to ACTB and the second ACTB frameshifting mutation that predicts mRNA decay. A de‐novo ACTB p.(Gly302Ala) mutation affects β‐cytoplasmic actin distribution. All four patients share a facial gestalt that is distinct from that of individuals with dominant‐negative ACTB variants in Baraitser‐Winter cerebrofrontofacial syndrome. Two of our patients had strikingly thin and sparse scalp hair. One patient had sagittal craniosynostosis and hypospadias. All three affected male children have attention deficits and mild global developmental delay. Mild intellectual disability was present in only one patient. Heterozygous ACTB deletion can allow for normal psychomotor function.

Copy number variation profiling in pharmacogenes using panel-based exome resequencing and correlation to human liver expression

Structural variants including copy number variations (CNV) have gained widespread attention, especially in pharmacogenomics but for several genes functional relevance and clinical evidence are still lacking. Detection of CNVs in next-generation sequencing data is challenging but offers widespread applications. We developed a cohort-based CNV detection workflow to extract CNVs from read counts of targeted NGS of 340 genes involved in absorption, distribution, metabolism and excretion (ADME) of drugs. We applied our method to 150 human liver tissue samples and correlated identified CNVs to mRNA expression levels. In total, we identified 445 deletions (73%) and 167 duplications (27%) in 36 pharmacogenes including all well-known CNVs of CYPs, GSTs, SULTs, UGTs, numerous described rare CNVs of CYP2E1, SLC16A3 or UGT2B15 as well as novel observations, e.g., for SLC22A12, SLC22A17 and GPS2 (G Protein Pathway Suppressor 2). We were able to fine-map complex CNVs of CYP2A6 and CYP2D6 with exon resolution. Correlation analysis confirmed known expression patterns for common CNVs and suggested an influence on expression variability for some rare CNVs. Our straightforward CNV detection workflow can be easily applied to any NGS coverage data and helped to analyze CNVs in an ADME-NGS panel of 340 pharmacogenes to improve genotype-phenotype correlations.

Using R and Bioconductor in Clinical Genomics and Transcriptomics

Bioinformatics pipelines are essential in the analysis of genomic and transcriptomic data generated by next-generation sequencing (NGS). Recent guidelines emphasize the need for rigorous validation and assessment of robustness, reproducibility, and quality of NGS analytic pipelines intended for clinical use. Software tools written in the R statistical language and, in particular, the set of tools available in the Bioconductor repository are widely used in research bioinformatics; and these frameworks offer several advantages for use in clinical bioinformatics, including the breath of available tools, modular nature of software packages, ease of installation, enforcement of interoperability, version control, and short learning curve. This review provides an introduction to R and Bioconductor software, its advantages and limitations for clinical bioinformatics, and illustrative examples of tools that can be used in various steps of NGS analysis.

Optimizing Genetic Workup in Pheochromocytoma and Paraganglioma by Integrating Diagnostic and Research Approaches

Pheochromocytomas and paragangliomas (PPGL) are rare neuroendocrine tumors with a strong hereditary background and a large genetic heterogeneity. Identification of the underlying genetic cause is crucial for the management of patients and their families as it aids differentiation between hereditary and sporadic cases. To improve diagnostics and clinical management we tailored an enrichment based comprehensive multi-gene next generation sequencing panel applicable to both analyses of tumor tissue and blood samples. We applied this panel to tumor samples and compared its performance to our current routine diagnostic approach. Routine diagnostic sequencing of 11 PPGL susceptibility genes was applied to blood samples of 65 unselected PPGL patients at a single center in Dresden, Germany. Predisposing germline mutations were identified in 19 (29.2%) patients. Analyses of 28 PPGL tumor tissues using the dedicated PPGL panel revealed pathogenic or likely pathogenic variants in known PPGL susceptibility genes in 21 (75%) cases, including mutations in IDH2, ATRX and HRAS. These mutations suggest sporadic tumor development. Our results imply a diagnostic benefit from extended molecular tumor testing of PPGLs and consequent improvement of patient management. The approach is promising for determination of prognostic biomarkers that support therapeutic decision-making.

Analysis of hereditary cancer syndromes by using a panel of genes: novel and multiple pathogenic mutations

BACKGROUND

Hereditary cancer predisposition syndromes are responsible for approximately 5-10% of all diagnosed cancer cases. In the past, single-gene analysis of specific high risk genes was used for the determination of the genetic cause of cancer heritability in certain families. The application of Next Generation Sequencing (NGS) technology has facilitated multigene panel analysis and is widely used in clinical practice, for the identification of individuals with cancer predisposing gene variants. The purpose of this study was to investigate the extent and nature of variants in genes implicated in hereditary cancer predisposition in individuals referred for testing in our laboratory.

METHODS

In total, 1197 individuals from Greece, Romania and Turkey were referred to our laboratory for genetic testing in the past 4 years. The majority of referrals included individuals with personal of family history of breast and/or ovarian cancer. The analysis of genes involved in hereditary cancer predisposition was performed using a NGS approach. Genomic DNA was enriched for targeted regions of 36 genes and sequencing was carried out using the Illumina NGS technology. The presence of large genomic rearrangements (LGRs) was investigated by computational analysis and Multiplex Ligation-dependent Probe Amplification (MLPA).

RESULTS

A pathogenic variant was identified in 264 of 1197 individuals (22.1%) analyzed while a variant of uncertain significance (VUS) was identified in 34.8% of cases. Clinically significant variants were identified in 29 of the 36 genes analyzed. Concerning the mutation distribution among individuals with positive findings, 43.6% were located in the BRCA1/2 genes whereas 21.6, 19.9, and 15.0% in other high, moderate and low risk genes respectively. Notably, 25 of the 264 positive individuals (9.5%) carried clinically significant variants in two different genes and 6.1% had a LGR.

CONCLUSIONS

In our cohort, analysis of all the genes in the panel allowed the identification of 4.3 and 8.1% additional pathogenic variants in other high or moderate/low risk genes, respectively, enabling personalized management decisions for these individuals and supporting the clinical significance of multigene panel analysis in hereditary cancer predisposition.