The clinical implementation of copy number detection in the age of next-generation sequencing

Validation of a targeted next-generation sequencing panel for pancreatic ductal adenocarcinomas

Pancreatic ductal adenocarcinoma (PDAC) is reported to be amongst the cancers with the lowest survival rate at 5 years. In the present study we aimed to validate a targeted next-generation sequencing (tNGS) panel to use in clinical routine, investigating genes important for PDAC diagnostic, prognostic and potential theragnostic aspect. In this NGS panel we also designed target regions to inquire about loss of heterozygosity (LOH) of chromosome 18 that has been described to be possibly linked to a worse disease progression. Copy number alteration has also been explored for a subset of genes. The last two methods are not commonly used for routine diagnostic with tNGS panels and we investigated their possible contribution to better characterize PDAC. A series of 140 formalin-fixed paraffin-embedded (FFPE) PDAC samples from 140 patients was characterized using this panel. Ninety-two % of patients showed alterations in at least one of the investigated genes (most frequent KRAS, TP53, SMAD4, CDKN2A and RNF43). Regarding LOH evaluation, we were able to detect chr18 LOH starting at 20% cell tumor percentage. The presence of LOH on chr18 is associated with a worse disease- and metastasis-free survival, in uni- and multivariate analyses. The present study validates the use of a tNGS panel for PDAC characterization, also evaluating chr18 LOH status for prognostic stratification.

Genetic Findings in Short Turkish Children Born to Consanguineous Parents

INTRODUCTION

The diagnostic yield of genetic analysis in the evaluation of children with short stature depends on associated clinical characteristics, but the additional effect of parental consanguinity has not been well documented.

METHODS

This observational case series of 42 short children from 34 consanguineous families was collected by six referral centres of paediatric endocrinology (inclusion criteria: short stature and parental consanguinity). In 18 patients (12 families, group 1), the clinical features suggested a specific genetic defect in the growth hormone (GH) insulin-like growth factor I (IGF-I) axis, and a candidate gene approach was used. In others (group 2), a hypothesis-free approach was chosen (gene panels, microarray analysis, and whole exome sequencing) and further subdivided into 11 patients with severe short stature (height <-3.5 standard deviation score [SDS]) and microcephaly (head circumference <-3.0 SDS) (group 2a), 10 patients with syndromic short stature (group 2b), and 3 patients with nonspecific isolated GH deficiency (group 2c).

RESULTS

In all 12 families from group 1, (likely) pathogenic variants were identified in GHR, IGFALS, GH1, and STAT5B. In 9/12 families from group 2a, variants were detected in PCNT, SMARCAL1, SRCAP, WDR4, and GHSR. In 5/9 families from group 2b, variants were found in TTC37, SCUBE3, NSD2, RABGAP1, and 17p13.3 microdeletions. In group 2c, no genetic cause was found. Homozygous, compound heterozygous, and heterozygous variants were found in 21, 1, and 4 patients, respectively.

CONCLUSION

Genetic testing in short children from consanguineous parents has a high diagnostic yield, especially in cases of severe GH deficiency or insensitivity, microcephaly, and syndromic short stature.

An Update Evolving View of Copy Number Variations in Autoimmune Diseases

Autoimmune diseases (AIDs) usually share possible common mechanisms, i.e., a defect in the immune tolerance exists due to diverse causes from central and peripheral tolerance mechanisms. Some genetic variations including copy number variations (CNVs) are known to link to several AIDs and are of importance in the susceptibility to AIDs and the potential therapeutic responses to medicines. As an important source of genetic variants, DNA CNVs have been shown to be very common in AIDs, implying these AIDs may possess possible common mechanisms. In addition, some CNVs are differently distributed in various diseases in different ethnic populations, suggesting that AIDs may have their own different phenotypes and different genetic and/or environmental backgrounds among diverse populations. Due to the continuous advancement in genotyping technology, such as high-throughput whole-genome sequencing method, more susceptible variants have been found. Moreover, further replication studies should be conducted to confirm the results of studies with different ethnic cohorts and independent populations. In this review, we aim to summarize the most relevant data that emerged in the past few decades on the relationship of CNVs and AIDs and gain some new insights into the issue.

Whole-Gene Deletions of FZD4 Cause Familial Exudative Vitreoretinopathy

Familial exudative vitreoretinopathy (FEVR) is an inherited disorder characterized by abnormalities in the retinal vasculature. The FZD4 gene is associated with FEVR, but the prevalence and impact of FZD4 copy number variation (CNV) on FEVR patients are unknown. The aim of this study was to better understand the genetic features and clinical manifestations of patients with FZD4 CNVs. A total of 651 FEVR families were recruited. Families negative for mutations in FEVR-associated genes were selected for CNV analysis using SeqCNV. Semiquantitative multiplex polymerase chain reaction and multiplex ligation-dependent probe amplification were conducted to verify the CNVs. Four probands were found to carry whole-gene deletions of FZD4, accounting for 5% (4/80) of probands with FZD4 mutations and 0.6% (4/651) of all FEVR probands. The four probands exhibited similar phenotypes of unilateral retinal folds. FEVR in probands with CNVs was not more severe than in probands with FZD4 missense mutations (p = 1.000). Although this is the first report of FZD4 CNVs and the associated phenotypes, the interpretation of FZD4 CNVs should be emphasized when analyzing the next-generation sequencing data of FEVR patients because of their high prevalence.

Elucidation of the Genetic Cause in Dutch Limb Girdle Muscular Dystrophy Families: A 27-Year's Journey

BACKGROUND

A Dutch cohort of 105 carefully selected limb girdle muscular dystrophy (LGMD) patients from 68 families has been subject to genetic testing over the last 20 years. After subsequent targeted gene analysis around two thirds (45/68) of the families had received a genetic diagnosis in 2013.

OBJECTIVE

To describe the results of further genetic testing in the remaining undiagnosed limb girdle muscular dystrophy families in this cohort.

METHODS

In the families of the cohort for whom no genetic diagnosis was established (n = 23) further testing using Sanger sequencing, next generation sequencing with gene panel analysis or whole-exome sequencing was performed. In one case DNA analysis for facioscapulohumeral dystrophy type 1 was carried out.

RESULTS

In eight families no additional genetic tests could be performed. In 12 of the remaining 15 families in which additional testing could be performed a genetic diagnosis was established: two LGMDR1 calpain3-related families with CAPN3 mutations, one LGMDR2 dysferlin-related family with DYSF mutations, three sarcoglycanopathy families (LGMDR3-5 α-, β- and γ-sarcoglycan-related) with SGCA/SGCB/SGCG mutations, one LGMDR8 TRIM 32-related family with TRIM32 mutations, two LGMDR19 GMPPB-related families with GMPPB mutations, one family with MICU1-related myopathy, one family with FLNC-related myopathy and one family with facioscapulohumeral dystrophy type 1. At this moment a genetic diagnosis has been made in 57 of the 60 families of which DNA was available (95%).

CONCLUSION

A genetic diagnosis is obtained in 95% of the families of the original Dutch LGMD cohort of which DNA was available.

Identification of copy number variants by NGS-based NIPT at low sequencing depth

OBJECTIVE

To explore the clinical utility of detecting chromosome copy number variants (CNVs) in the fetus by noninvasive prenatal testing (NIPT) using the low-pass whole-genome sequencing.

METHODS

Eight hundred and seventy-three singleton pregnancies with chromosomal microarray analysis (CMA) available between January 2017 to December 2019 and stored enough plasma sample for NIPT testing were included in this study. The CMA results show that forty-eight pregnancies with CNVs and eight hundred and twenty-five pregnancies are normal. Each pregnancy's plasma sample was blindly tested with NIPT at a depth of 0.51-1.19x for CNVs detection. The performance of the NIPT method for CNVs detection compared with the CMA method is evaluated.

RESULTS

A total of fifty-two CNVs ranging from 0.1-47.3 Mb identified in forty-eight samples were identified by NIPT, of which thirty-four CNVs were consistent with CMA results. Additionally, eighteen CNVs were missed by NIPT. The overall sensitivity and specificity for the detection of CNVs were 65.38% (95% CI: 51.76%-76.89%) and 97.45% (95% CI: 96.12%-98.35%), respectively. However, for the detection of CNVs larger than 2 Mb and CNVs less than 2Mb, the sensitivities were 81.58% (95% CI: 66.27%-91.09%) and 21.43% (95% CI: 6.84%-48.32%), respectively.

CONCLUSION

Our study demonstrated that the NIPT might be an alternative method for screening CNVs comparable with other studies. However, CNVs less than 2Mb in length shows poor sensitivity by NIPT. Noninvasive CNVs detection based on the NIPT method still needs more clinical validation studies and technical improvement to achieve clinically acceptable accuracy.

Structural variation in the sequencing era

Identifying structural variation (SV) is essential for genome interpretation but has been historically difficult due to limitations inherent to available genome technologies. Detection methods that use ensemble algorithms and emerging sequencing technologies have enabled the discovery of thousands of SVs, uncovering information about their ubiquity, relationship to disease and possible effects on biological mechanisms. Given the variability in SV type and size, along with unique detection biases of emerging genomic platforms, multiplatform discovery is necessary to resolve the full spectrum of variation. Here, we review modern approaches for investigating SVs and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.