Diagnostic genome sequencing improves diagnostic yield: a prospective single-centre study in 1000 patients with inherited eye diseases.

PURPOSE: Genome sequencing (GS) is expected to reduce the diagnostic gap in rare disease genetics. We aimed to evaluate a scalable framework for genome-based analyses 'beyond the exome' in regular care of patients with inherited retinal degeneration (IRD) or inherited optic neuropathy (ION). METHODS: PCR-free short-read GS was performed on 1000 consecutive probands with IRD/ION in routine diagnostics. Complementary whole-blood RNA-sequencing (RNA-seq) was done in a subset of 74 patients. An open-source bioinformatics analysis pipeline was optimised for structural variant (SV) calling and combined RNA/DNA variation interpretation. RESULTS: A definite genetic diagnosis was established in 57.4% of cases. For another 16.7%, variants of uncertain significance were identified in known IRD/ION genes, while the underlying genetic cause remained unresolved in 25.9%. SVs or alterations in non-coding genomic regions made up for 12.7% of the observed variants. The RNA-seq studies supported the classification of two unclear variants. CONCLUSION: GS is feasible in clinical practice and reliably identifies causal variants in a substantial proportion of individuals. GS extends the diagnostic yield to rare non-coding variants and enables precise determination of SVs. The added diagnostic value of RNA-seq is limited by low expression levels of the major IRD disease genes in blood.

Titin copy number variations associated with dominant inherited phenotypes.

BACKGROUND: Titinopathies are caused by mutations in the titin gene (TTN). Titin is the largest known human protein; its gene has the longest coding phase with 364 exons. Titinopathies are very complex neuromuscular pathologies due to the variable age of onset of symptoms, the great diversity of pathological and muscular impairment patterns (cardiac, skeletal muscle or mixed) and both autosomal dominant and recessive modes of transmission. Until now, only few CNVs in TTN have been reported without clear genotype-phenotype associations. METHODS: Our study includes eight families with dominant titinopathies. We performed next-generation sequencing or comparative genomic hybridisation array analyses and found CNVs in the TTN gene. We characterised these CNVs by RNA sequencing (RNAseq) analyses in six patients' muscles and performed genotype-phenotype inheritance association study by combining the clinical and biological data of these eight families. RESULTS: Seven deletion-type CNVs in the TTN gene were identified among these families. Genotype and RNAseq results showed that five deletions do not alter the reading frame and one is out-of-reading frame. The main phenotype identified was distal myopathy associated with contractures. The analysis of morphological, clinical and genetic data and imaging let us draw new genotype-phenotype associations of titinopathies. CONCLUSION: Identifying TTN CNVs will further increase diagnostic sensitivity in these complex neuromuscular pathologies. Our cohort of patients enabled us to identify new deletion-type CNVs in the TTN gene, with unexpected autosomal dominant transmission. This is valuable in establishing new genotype-phenotype associations of titinopathies, mainly distal myopathy in most of the patients.

An Integrated Transcriptomics and Genomics Approach Detects an X/Autosome Translocation in a Female with Duchenne Muscular Dystrophy.

Duchenne and Becker muscular dystrophies, caused by pathogenic variants in DMD, are the most common inherited neuromuscular conditions in childhood. These diseases follow an X-linked recessive inheritance pattern, and mainly males are affected. The most prevalent pathogenic variants in the DMD gene are copy number variants (CNVs), and most patients achieve their genetic diagnosis through Multiplex Ligation-dependent Probe Amplification (MLPA) or exome sequencing. Here, we investigated a female patient presenting with muscular dystrophy who remained genetically undiagnosed after MLPA and exome sequencing. RNA sequencing (RNAseq) from the patient's muscle biopsy identified an 85% reduction in DMD expression compared to 116 muscle samples included in the cohort. A de novo balanced translocation between chromosome 17 and the X chromosome (t(X;17)(p21.1;q23.2)) disrupting the DMD and BCAS3 genes was identified through trio whole genome sequencing (WGS). The combined analysis of RNAseq and WGS played a crucial role in the detection and characterisation of the disease-causing variant in this patient, who had been undiagnosed for over two decades. This case illustrates the diagnostic odyssey of female DMD patients with complex structural variants that are not detected by current panel or exome sequencing analysis.

Detection and Characterization of a De Novo Alu Retrotransposition Event Causing NKX2-1-Related Disorder.

BACKGROUND: Heterozygous NKX2-1 loss-of-function variants cause combinations of hyperkinetic movement disorders (MDs, particularly childhood-onset chorea), pulmonary dysfunction, and hypothyroidism. Mobile element insertions (MEIs) are potential disease-causing structural variants whose detection in routine diagnostics remains challenging. OBJECTIVE: To establish the molecular diagnosis of two first-degree relatives with clinically suspected NKX2-1-related disorder who had negative NKX2-1 Sanger (SS), whole-exome (WES), and whole-genome (WGS) sequencing. METHODS: The proband's WES was analyzed for MEIs. A candidate MEI in NKX2-1 underwent optimized SS after plasmid cloning. Functional studies exploring NKX2-1 haploinsufficiency at RNA and protein levels were performed. RESULTS: A 347-bp AluYa5 insertion with a 65-bp poly-A tail followed by a 16-bp duplication of the pre-insertion wild-type sequence in exon 3 of NKX2-1 (ENST00000354822.7:c.556_557insAlu541_556dup) segregated with the disease phenotype. CONCLUSIONS: We identified a de novo exonic AluYa5 insertion causing NKX2-1-related disorder in SS/WES/WGS-negative cases, suggesting that MEI analysis of short-read sequencing data or targeted long-read sequencing could unmask the molecular diagnosis of unsolved MD cases. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Combined loss of CDH1 and downstream regulatory sequences drive early-onset diffuse gastric cancer and increase penetrance of hereditary diffuse gastric cancer.

BACKGROUND: Germline CDH1 pathogenic or likely pathogenic variants cause hereditary diffuse gastric cancer (HDGC). Once a genetic cause is identified, stomachs' and breasts' surveillance and/or prophylactic surgery is offered to asymptomatic CDH1 carriers, which is life-saving. Herein, we characterized an inherited mechanism responsible for extremely early-onset gastric cancer and atypical HDGC high penetrance. METHODS: Whole-exome sequencing (WES) re-analysis was performed in an unsolved HDGC family. Accessible chromatin and CDH1 promoter interactors were evaluated in normal stomach by ATAC-seq and 4C-seq, and functional analysis was performed using CRISPR-Cas9, RNA-seq and pathway analysis. RESULTS: We identified a germline heterozygous 23 Kb CDH1-TANGO6 deletion in a family with eight diffuse gastric cancers, six before age 30. Atypical HDGC high penetrance and young cancer-onset argued towards a role for the deleted region downstream of CDH1, which we proved to present accessible chromatin, and CDH1 promoter interactors in normal stomach. CRISPR-Cas9 edited cells mimicking the CDH1-TANGO6 deletion display the strongest CDH1 mRNA downregulation, more impacted adhesion-associated, type-I interferon immune-associated and oncogenic signalling pathways, compared to wild-type or CDH1-deleted cells. This finding solved an 18-year family odyssey and engaged carrier family members in a cancer prevention pathway of care. CONCLUSION: In this work, we demonstrated that regulatory elements lying down-stream of CDH1 are part of a chromatin network that control CDH1 expression and influence cell transcriptome and associated signalling pathways, likely explaining high disease penetrance and very young cancer-onset. This study highlights the importance of incorporating scientific-technological updates and clinical guidelines in routine diagnosis, given their impact in timely genetic diagnosis and disease prevention.

Heterozygous UCHL1 loss-of-function variants cause a neurodegenerative disorder with spasticity, ataxia, neuropathy, and optic atrophy.

PURPOSE: Biallelic variants in UCHL1 have been associated with a progressive early-onset neurodegenerative disorder, autosomal recessive spastic paraplegia type 79. In this study, we investigated heterozygous UCHL1 variants on the basis of results from cohort-based burden analyses. METHODS: Gene-burden analyses were performed on exome and genome data of independent cohorts of patients with hereditary ataxia and spastic paraplegia from Germany and the United Kingdom in a total of 3169 patients and 33,141 controls. Clinical data of affected individuals and additional independent families were collected and evaluated. Patients' fibroblasts were used to perform mass spectrometry-based proteomics. RESULTS: UCHL1 was prioritized in both independent cohorts as a candidate gene for an autosomal dominant disorder. We identified a total of 34 cases from 18 unrelated families, carrying 13 heterozygous loss-of-function variants (15 families) and an inframe insertion (3 families). Affected individuals mainly presented with spasticity (24/31), ataxia (28/31), neuropathy (11/21), and optic atrophy (9/17). The mass spectrometry-based proteomics showed approximately 50% reduction of UCHL1 expression in patients' fibroblasts. CONCLUSION: Our bioinformatic analysis, in-depth clinical and genetic workup, and functional studies established haploinsufficiency of UCHL1 as a novel disease mechanism in spastic ataxia.

Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation.

Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants in coding or regulatory regions with complex diseases in large cohorts at genome-wide scale. However, rare variant association studies (RVAS) still lack power when cohorts are small to medium-sized and if genetic variation explains a small fraction of phenotypic variance. Here we present a novel Bayesian rare variant Association Test using Integrated Nested Laplace Approximation (BATI). Unlike existing RVAS tests, BATI allows integration of individual or variant-specific features as covariates, while efficiently performing inference based on full model estimation. We demonstrate that BATI outperforms established RVAS methods on realistic, semi-synthetic whole-exome sequencing cohorts, especially when using meaningful biological context, such as functional annotation. We show that BATI achieves power above 70% in scenarios in which competing tests fail to identify risk genes, e.g. when risk variants in sum explain less than 0.5% of phenotypic variance. We have integrated BATI, together with five existing RVAS tests in the 'Rare Variant Genome Wide Association Study' (rvGWAS) framework for data analyzed by whole-exome or whole genome sequencing. rvGWAS supports rare variant association for genes or any other biological unit such as promoters, while allowing the analysis of essential functionalities like quality control or filtering. Applying rvGWAS to a Chronic Lymphocytic Leukemia study we identified eight candidate predisposition genes, including EHMT2 and COPS7A.

New euchromatic variant dup(11)(p15.3p15.1) transmitted through two generations defined by low coverage whole genome sequencing.

We report on a 14-year old boy, his father, and his paternal uncle, all three carriers of a duplication of chromosomal region 11p15.3-p15.1. The aberration was transmitted by the grandmother, who is carrier of a balanced insertion 46,XX,ins(14;11)(q32.1;p15.3p15.1). In order to determine the precise molecular basis of this structural variant, we performed low-coverage whole genome sequencing on the boy's father. This approach allowed precise determination of the genomic breakpoints and revealed a duplication of 6.9 Mb, centromeric to the Beckwith-Wiedemann/Silver-Russell syndrome critical region in 11p15.5, that inserted in inverse orientation into 14q32.12 (according to HGVS nomenclature: NC_000014.8:g.92871000_92871001ins[NC_000011.9:g.12250642_19165928inv;T]). To our knowledge, this is the first report of a duplication of 11p15.3-p15.1 involving more than 40 genes and transmitted through two generations without apparent clinical effects.

Allele balance bias identifies systematic genotyping errors and false disease associations.

In recent years, next-generation sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors, and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the AB distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies. Availability: https://github.com/Francesc-Muyas/ABB.

Radiogenomics in head and neck cancer: correlation of radiomic heterogeneity and somatic mutations in TP53, FAT1 and KMT2D.

PURPOSE: Genetic tumour profiles and radiomic features can be used to complement clinical information in head and neck squamous cell carcinoma (HNSCC) patients. Radiogenomics imply the potential to investigate complementarity or interrelations of radiomic and genomic features, and prognostic factors might be determined. The aim of our study was to explore radiogenomics in HNSCC. METHODS: For 20 HNSCC patients treated with primary radiochemotherapy, next-generation sequencing (NGS) of tumour and corresponding normal tissue was performed. In total, 327 genes were investigated by panel sequencing. Radiomic features were extracted from computed tomography data. A hypothesis-driven approach was used for radiogenomic correlations of selected image-based heterogeneity features and well-known driver gene mutations in HNSCC. RESULTS: The most frequently mutated driver genes in our cohort were TP53 (involved in cell cycle control), FAT1 (Wnt signalling, cell-cell contacts, migration) and KMT2D (chromatin modification). Radiomic features of heterogeneity did not correlate significantly with somatic mutations in TP53 or KMT2D. However, somatic mutations in FAT1 and smaller primary tumour volumes were associated with reduced radiomic intra-tumour heterogeneity. CONCLUSION: The landscape of somatic variants in our cohort is well in line with previous reports. An association of somatic mutations in FAT1 with reduced radiomic tumour heterogeneity could potentially elucidate the previously described favourable outcomes of these patients. Larger studies are needed to validate this exploratory data in the future.

A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data.

BACKGROUND: Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. RESULTS: We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. CONCLUSION: We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

Structural variant calling and clinical interpretation in 6224 unsolved rare disease exomes.

Structural variants (SVs), including large deletions, duplications, inversions, translocations, and more complex events have the potential to disrupt gene function resulting in rare disease. Nevertheless, current pipelines and clinical decision support systems for exome sequencing (ES) tend to focus on small alterations such as single nucleotide variants (SNVs) and insertions-deletions shorter than 50 base pairs (indels). Additionally, detection and interpretation of large copy-number variants (CNVs) are frequently performed. However, detection of other types of SVs in ES data is hampered by the difficulty of identifying breakpoints in off-target (intergenic or intronic) regions, which makes robust identification of SVs challenging. In this paper, we demonstrate the utility of SV calling in ES resulting in a diagnostic yield of 0.4% (23 out of 5825 probands) for a large cohort of unsolved patients collected by the Solve-RD consortium. Remarkably, 8 out of 23 pathogenic SV were not found by comprehensive read-depth-based CNV analysis, resulting in a 0.13% increased diagnostic value.

Genomes in clinical care.

In the era of precision medicine, genome sequencing (GS) has become more affordable and the importance of genomics and multi-omics in clinical care is increasingly being recognized. However, how to scale and effectively implement GS on an institutional level remains a challenge for many. Here, we present Genome First and Ge-Med, two clinical implementation studies focused on identifying the key pillars and processes that are required to make routine GS and predictive genomics a reality in the clinical setting. We describe our experience and lessons learned for a variety of topics including test logistics, patient care processes, data reporting, and infrastructure. Our model of providing clinical care and comprehensive genomic analysis from a single source may be used by other centers with a similar structure to facilitate the implementation of omics-based personalized health concepts in medicine.

Phenotype-driven genomics enhance diagnosis in children with unresolved neuromuscular diseases.

Establishing a molecular diagnosis remains challenging in half of individuals with childhood-onset neuromuscular diseases (NMDs) despite exome sequencing. This study evaluates the diagnostic utility of combining genomic approaches in undiagnosed NMD patients. We performed deep phenotyping of 58 individuals with unsolved childhood-onset NMDs that have previously undergone inconclusive exome studies. Genomic approaches included trio genome sequencing and RNASeq. Genetic diagnoses were reached in 23 out of 58 individuals (40%). Twenty-one individuals carried causal single nucleotide variants (SNVs) or small insertions and deletions, while 2 carried pathogenic structural variants (SVs). Genomic sequencing identified pathogenic variants in coding regions or at the splice site in 17 out of 21 resolved cases, while RNA sequencing was additionally required for the diagnosis of 4 cases. Reasons for previous diagnostic failures included low coverage in exonic regions harboring the second pathogenic variant and involvement of genes that were not yet linked to human diseases at the time of the first NGS analysis. In summary, our systematic genetic analysis, integrating deep phenotyping, trio genome sequencing and RNASeq, proved effective in diagnosing unsolved childhood-onset NMDs. This approach holds promise for similar cohorts, offering potential improvements in diagnostic rates and clinical management of individuals with NMDs.

Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses.

We report the results of a comprehensive copy number variant (CNV) reanalysis of 9171 exome sequencing datasets from 5757 families affected by a rare disease (RD). The data reanalysed was extremely heterogeneous, having been generated using 28 different enrichment kits by 42 different research groups across Europe partnering in the Solve-RD project. Each research group had previously undertaken their own analysis of the data but failed to identify disease-causing variants. We applied three CNV calling algorithms to maximise sensitivity, and rare CNVs overlapping genes of interest, provided by four partner European Reference Networks, were taken forward for interpretation by clinical experts. This reanalysis has resulted in a molecular diagnosis being provided to 51 families in this sample, with ClinCNV performing the best of the three algorithms. We also identified partially explanatory pathogenic CNVs in a further 34 individuals. This work illustrates the value of reanalysing ES cold cases for CNVs.

Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples.

Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES.

Unravelling undiagnosed rare disease cases by HiFi long-read genome sequencing.

Solve-RD is a pan-European rare disease (RD) research program that aims to identify disease-causing genetic variants in previously undiagnosed RD families. We utilised 10-fold coverage HiFi long-read sequencing (LRS) for detecting causative structural variants (SVs), single nucleotide variants (SNVs), insertion-deletions (InDels), and short tandem repeat (STR) expansions in extensively studied RD families without clear molecular diagnoses. Our cohort includes 293 individuals from 114 genetically undiagnosed RD families selected by European Rare Disease Network (ERN) experts. Of these, 21 families were affected by so-called 'unsolvable' syndromes for which genetic causes remain unknown, and 93 families with at least one individual affected by a rare neurological, neuromuscular, or epilepsy disorder without genetic diagnosis despite extensive prior testing. Clinical interpretation and orthogonal validation of variants in known disease genes yielded thirteen novel genetic diagnoses due to de novo and rare inherited SNVs, InDels, SVs, and STR expansions. In an additional four families, we identified a candidate disease-causing SV affecting several genes including an MCF2 / FGF13 fusion and PSMA3 deletion. However, no common genetic cause was identified in any of the 'unsolvable' syndromes. Taken together, we found (likely) disease-causing genetic variants in 13.0% of previously unsolved families and additional candidate disease-causing SVs in another 4.3% of these families. In conclusion, our results demonstrate the added value of HiFi long-read genome sequencing in undiagnosed rare diseases.

Clinical trio genome sequencing facilitates the interpretation of variants in cancer predisposition genes in paediatric tumour patients.

The prevalence of pathogenic and likely pathogenic (P/LP) variants in genes associated with cancer predisposition syndromes (CPS) is estimated to be 8-18% for paediatric cancer patients. In more than half of the carriers, the family history is unsuspicious for CPS. Therefore, broad genetic testing could identify germline predisposition in additional children with cancer resulting in important implications for themselves and their families. We thus evaluated clinical trio genome sequencing (TGS) in a cohort of 72 paediatric patients with solid cancers other than retinoblastoma or CNS-tumours. The most prevalent cancer types were sarcoma (n = 26), neuroblastoma (n = 15), and nephroblastoma (n = 10). Overall, P/LP variants in CPS genes were identified in 18.1% of patients (13/72) and P/LP variants in autosomal-dominant CPS genes in 9.7% (7/72). Genetic evaluation would have been recommended for the majority of patients with P/LP variants according to the Jongmans criteria. Four patients (5.6%, 4/72) carried P/LP variants in autosomal-dominant genes known to be associated with their tumour type. With the immediate information on variant inheritance, TGS facilitated the identification of a de novo P/LP in NF1, a gonadosomatic mosaic in WT1 and two pathogenic variants in one patient (DICER1 and PALB2). TGS allows a more detailed characterization of structural variants with base-pair resolution of breakpoints which can be relevant for the interpretation of copy number variants. Altogether, TGS allows comprehensive identification of children with a CPS and supports the individualised clinical management of index patients and high-risk relatives.

UV-radiation and MC1R germline mutations are risk factors for the development of conventional and spitzoid melanomas in children and adolescents.

BACKGROUND: Genomic characterisation has led to an improved understanding of adult melanoma. However, the aetiology of melanoma in children is still unclear and identifying the correct diagnosis and therapeutic strategies remains challenging. METHODS: Exome sequencing of matched tumour-normal pairs from 26 paediatric patients was performed to study the mutational spectrum of melanomas. The cohort was grouped into different categories: spitzoid melanoma (SM), conventional melanoma (CM), and other melanomas (OT). FINDINGS: In all patients with CM (n = 10) germline variants associated with melanoma were found in low to moderate melanoma risk genes: in 8 patients MC1R variants, in 2 patients variants in MITF, PTEN and BRCA2. Somatic BRAF mutations were detected in 60% of CMs, homozygous deletions of CDKN2A in 20%, TERTp mutations in 30%. In the SM group (n = 12), 5 patients carried at least one MC1R variant; somatic BRAF mutations were detected in 8.3%, fusions in 25% of the cases. No SM showed a homozygous CDKN2A deletion nor a TERTp mutation. In 81.8% of the CM/SM cases the UV damage signatures SBS7 and/or DBS1 were detected. The patient with melanoma arising in giant congenital nevus (CNM) demonstrated the characteristic NRAS Q61K mutation. INTERPRETATION: UV-radiation and MC1R germline variants are risk factors in the development of conventional and spitzoid paediatric melanomas. Paediatric CMs share genomic similarities with adult CMs while the SMs differ genetically from the CM group. Consistent genetic characterization of all paediatric melanomas will potentially lead to better subtype differentiation, treatment, and prevention in the future. FUNDING: Found in Acknowledgement.