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

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

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

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

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

Concomitant epigenetic targeting of LSD1 and HDAC synergistically induces mitochondrial apoptosis in rhabdomyosarcoma cells

The lysine-specific demethylase 1 (LSD1) is overexpressed in several cancers including rhabdomyosarcoma (RMS). However, little is yet known about whether or not LSD1 may serve as therapeutic target in RMS. We therefore investigated the potential of LSD1 inhibitors alone or in combination with other epigenetic modifiers such as histone deacetylase (HDAC) inhibitors. Here, we identify a synergistic interaction of LSD1 inhibitors (i.e., GSK690, Ex917) and HDAC inhibitors (i.e., JNJ-26481585, SAHA) to induce cell death in RMS cells. By comparison, LSD1 inhibitors as single agents exhibit little cytotoxicity against RMS cells. Mechanistically, GSK690 acts in concert with JNJ-26481585 to upregulate mRNA levels of the proapoptotic BH3-only proteins BMF, PUMA, BIM and NOXA. This increase in mRNA levels is accompanied by a corresponding upregulation of BMF, PUMA, BIM and NOXA protein levels. Importantly, individual knockdown of either BMF, BIM or NOXA significantly reduces GSK690/JNJ-26481585-mediated cell death. Similarly, genetic silencing of BAK significantly rescues cell death upon GSK690/JNJ-26481585 cotreatment. Also, overexpression of antiapoptotic BCL-2 or MCL-1 significantly protects RMS cells from GSK690/JNJ-26481585-induced cell death. Furthermore, GSK690 acts in concert with JNJ-26481585 to increase activation of caspase-9 and -3. Consistently, addition of the pan-caspase inhibitor N-benzyloxycarbonyl-Val-Ala-Asp-fluoromethylketone (zVAD.fmk) significantly reduces GSK690/JNJ-26481585-mediated cell death. In conclusion, concomitant LSD1 and HDAC inhibition synergistically induces cell death in RMS cells by shifting the ratio of pro- and antiapoptotic BCL-2 proteins in favor of apoptosis, thereby engaging the intrinsic apoptotic pathway. This indicates that combined treatment with LSD1 and HDAC inhibitors is a promising new therapeutic approach in RMS

Next-generation sequencing reveals a novel role of lysine-specific demethylase 1 in adhesion of rhabdomyosarcoma cells

Lysine-specific demethylase 1 (LSD1), a histone lysine demethylase with the main specificity for H3K4me2, has been shown to be overexpressed in rhabdomyosarcoma (RMS) tumor samples. However, its role in RMS biology is not yet well understood. Here, we identified a new role of LSD1 in regulating adhesion of RMS cells. Genetic knockdown of LSD1 profoundly suppressed clonogenic growth in a panel of RMS cell lines, whereas LSD1 proved to be largely dispensable for regulating cell death and short-term survival. Combined RNA and ChIP-sequencing performed to analyze RNA expression and histone methylation at promoter regions revealed a gene set enrichment for adhesion-associated terms upon LSD1 knockdown. Consistently, LSD1 knockdown significantly reduced adhesion to untreated surfaces. Importantly, precoating of the plates with the adhesives collagen I or fibronectin rescued this reduced adhesion of LSD1 knockdown cells back to levels of control cells. Using KEGG pathway analysis, we identified 17 differentially expressed genes (DEGs) in LSD1 knockdown cells related to adhesion processes, which were validated by qRT-PCR. Combining RNA and ChIP-sequencing results revealed that, within this set of genes, SPP1, C3AR1, ITGA10 and SERPINE1 also exhibited increased H3K4me2 levels at their promoter regions in LSD1 knockdown compared to control cells. Indeed, LSD1 ChIP experiments confirmed enrichment of LSD1 at their promoter regions, suggesting a direct transcriptional regulation by LSD1. By identifying a new role of LSD1 in the modulation of cell adhesion and clonogenic growth of RMS cells, these findings highlight the importance of LSD1 in RMS

Dual-energy CT in sacral fragility fractures: defining a cut-off Hounsfield unit value for the presence of traumatic bone marrow edema in patients with osteoporosis

Background Demographic change entails an increasing incidence of fragility fractures. Dual-energy CT (DECT) with virtual non-calcium (VNCa) reconstructions has been introduced as a promising diagnostic method for evaluating bone microarchitecture and marrow simultaneously. This study aims to define the most accurate cut-off value in Hounsfield units (HU) for discriminating the presence and absence of bone marrow edema (BME) in sacral fragility fractures. Methods Forty-six patients (40 women, 6 men; 79.7 ± 9.2 years) with suspected fragility fractures of the sacrum underwent both DECT (90 kVp / 150 kVp with tin prefiltration) and MRI. Nine regions-of-interest were placed in each sacrum on DECT-VNCa images. The resulting 414 HU measurements were stratified into “edema” (n = 80) and “no edema” groups (n = 334) based on reference BME detection in T2-weighted MRI sequences. Area under the receiver operating characteristic curve was calculated to determine the desired cut-off value and an associated conspicuity range for edema detection. Results The mean density within the “edema” group of measurements (+ 3.1 ± 8.3 HU) was substantially higher compared to the “no edema” group (-51.7 ± 21.8 HU; p < 0.010). Analysis in DECT-VNCa images suggested a cut-off value of -12.9 HU that enabled sensitivity and specificity of 100% for BME detection compared to MRI. A range of HU values between -14.0 and + 20.0 is considered indicative of BME in the sacrum. Conclusions Quantitative analysis of DECT-VNCa with a cut-off of -12.9 HU allows for excellent diagnostic accuracy in the assessment of sacral fragility fractures with associated BME. A diagnostic “one-stop-shop” approach without additional MRI is feasible