Exome reanalysis and proteomic profiling identified TRIP4 as a novel cause of cerebellar hypoplasia and spinal muscular atrophy (PCH1)

TRIP4 is one of the subunits of the transcriptional coregulator ASC-1, a ribonucleoprotein complex that participates in transcriptional coactivation and RNA processing events. Recessive variants in the TRIP4 gene have been associated with spinal muscular atrophy with bone fractures as well as a severe form of congenital muscular dystrophy. Here we present the diagnostic journey of a patient with cerebellar hypoplasia and spinal muscular atrophy (PCH1) and congenital bone fractures. Initial exome sequencing analysis revealed no candidate variants. Reanalysis of the exome data by inclusion in the Solve-RD project resulted in the identification of a homozygous stop-gain variant in the TRIP4 gene, previously reported as disease-causing. This highlights the importance of analysis reiteration and improved and updated bioinformatic pipelines. Proteomic profile of the patient’s fibroblasts showed altered RNA-processing and impaired exosome activity supporting the pathogenicity of the detected variant. In addition, we identified a novel genetic form of PCH1, further strengthening the link of this characteristic phenotype with altered RNA metabolism

A MT-TL1 variant identified by whole exome sequencing in an individual with intellectual disability, epilepsy, and spastic tetraparesis

Funder: The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257Abstract: The genetic etiology of intellectual disability remains elusive in almost half of all affected individuals. Within the Solve-RD consortium, systematic re-analysis of whole exome sequencing (WES) data from unresolved cases with (syndromic) intellectual disability (n = 1,472 probands) was performed. This re-analysis included variant calling of mitochondrial DNA (mtDNA) variants, although mtDNA is not specifically targeted in WES. We identified a functionally relevant mtDNA variant in MT-TL1 (NC_012920.1:m.3291T > C; NC_012920.1:n.62T > C), at a heteroplasmy level of 22% in whole blood, in a 23-year-old male with severe intellectual disability, epilepsy, episodic headaches with emesis, spastic tetraparesis, brain abnormalities, and feeding difficulties. Targeted validation in blood and urine supported pathogenicity, with heteroplasmy levels of 23% and 58% in index, and 4% and 17% in mother, respectively. Interestingly, not all phenotypic features observed in the index have been previously linked to this MT-TL1 variant, suggesting either broadening of the m.3291T > C-associated phenotype, or presence of a co-occurring disorder. Hence, our case highlights the importance of underappreciated mtDNA variants identifiable from WES data, especially for cases with atypical mitochondrial phenotypes and their relatives in the maternal line

Exome reanalysis and proteomic profiling identified TRIP4 as a novel cause of cerebellar hypoplasia and spinal muscular atrophy (PCH1)

Abstract: TRIP4 is one of the subunits of the transcriptional coregulator ASC-1, a ribonucleoprotein complex that participates in transcriptional coactivation and RNA processing events. Recessive variants in the TRIP4 gene have been associated with spinal muscular atrophy with bone fractures as well as a severe form of congenital muscular dystrophy. Here we present the diagnostic journey of a patient with cerebellar hypoplasia and spinal muscular atrophy (PCH1) and congenital bone fractures. Initial exome sequencing analysis revealed no candidate variants. Reanalysis of the exome data by inclusion in the Solve-RD project resulted in the identification of a homozygous stop-gain variant in the TRIP4 gene, previously reported as disease-causing. This highlights the importance of analysis reiteration and improved and updated bioinformatic pipelines. Proteomic profile of the patient’s fibroblasts showed altered RNA-processing and impaired exosome activity supporting the pathogenicity of the detected variant. In addition, we identified a novel genetic form of PCH1, further strengthening the link of this characteristic phenotype with altered RNA metabolism

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

Solving unsolved rare neurological diseases-a Solve-RD viewpoint.

Funder: Durch Princess Beatrix Muscle Fund Durch Speeren voor Spieren Muscle FundFunder: University of Tübingen Medical Faculty PATE programFunder: European Reference Network for Rare Neurological Diseases | 739510Funder: European Joint Program on Rare Diseases (EJP-RD COFUND-EJP) | 44140962

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

De novo mutations in children born after medical assisted reproduction

STUDY QUESTION: Are there more de novo mutations (DNMs) present in the genomes of children born through medical assisted reproduction (MAR) compared to spontaneously conceived children? SUMMARY ANSWER: In this pilot study, no statistically significant difference was observed in the number of DNMs observed in the genomes of MAR children versus spontaneously conceived children. WHAT IS KNOWN ALREADY: DNMs are known to play a major role in sporadic disorders with reduced fitness such as severe developmental disorders, including intellectual disability and epilepsy. Advanced paternal age is known to place offspring at increased disease risk, amongst others by increasing the number of DNMs in their genome. There are very few studies reporting on the effect of MAR on the number of DNMs in the offspring, especially when male infertility is known to be affecting the potential fathers. With delayed parenthood an ongoing epidemiological trend in the 21st century, there are more children born from fathers of advanced age and more children born through MAR every day. STUDY DESIGN, SIZE, DURATION: This observational pilot study was conducted from January 2015 to March 2019 in the tertiary care centre at Radboud University Medical Center. We included a total of 53 children and their respective parents, forming 49 trios (mother, father and child) and two quartets (mother, father and two siblings). One group of children was born after spontaneous conception (n = 18); a second group of children born after IVF (n = 17) and a third group of children born after ICSI combined with testicular sperm extraction (ICSI-TESE) (n = 18). In this pilot study, we also subdivided each group by paternal age, resulting in a subgroup of children born to younger fathers (45 years of age at conception). PARTICIPANTS/MATERIALS, SETTING, METHODS: Whole-genome sequencing (WGS) was performed on all parent-offspring trios to identify DNMs. For 34 of 53 trios/quartets, WGS was performed twice to independently detect and validate the presence of DNMs. Quality of WGS-based DNM calling was independently assessed by targeted Sanger sequencing. MAIN RESULTS AND THE ROLE OF CHANCE: No significant differences were observed in the number of DNMs per child for the different methods of conception, independent of parental age at conception (multi-factorial ANOVA, f(2) = 0.17, P-value = 0.85). As expected, a clear paternal age effect was observed after adjusting for method of conception and maternal age at conception (multiple regression model, t = 5.636, P-value = 8.97 × 10-7), with on average 71 DNMs in the genomes of children born to young fathers (45 years of age). LIMITATIONS, REASONS FOR CAUTION: This is a pilot study and other small-scale studies have recently reported contrasting results. Larger unbiased studies are required to confirm or falsify these results. WIDER IMPLICATIONS OF THE FINDINGS: This pilot study did not show an effect for the method of conception on the number of DNMs per genome in offspring. Given the role that DNMs play in disease risk, this negative result is good news for IVF and ICSI-TESE born children, if replicated in a larger cohort. STUDY FUNDING/COMPETING INTEREST(S): This research was funded by the Netherlands Organisation for Scientific Research (918-15-667) and by an Investigator Award in Science from the Wellcome Trust (209451). The authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A