Functional genomics provide key insights to improve the diagnostic yield of hereditary ataxia

Improvements in functional genomic annotation have led to a critical mass of neurogenetic discoveries. This is exemplified in hereditary ataxia, a heterogeneous group of disorders characterised by incoordination from cerebellar dysfunction. Associated pathogenic variants in more than 300 genes have been described, leading to a detailed genetic classification partitioned by age-of-onset. Despite these advances, up to 75% of patients with ataxia remain molecularly undiagnosed even following whole genome sequencing, as exemplified in the 100,000 Genomes Project. This study aimed to understand whether we can improve our knowledge of the genetic architecture of hereditary ataxia by leveraging functional genomic annotations, and as a result, generate insights and strategies that raise the diagnostic yield. To achieve these aims, we used publicly-available multi-omics data to generate 294 genic features, capturing information relating to a gene's structure, genetic variation, tissue-specific, cell-type-specific and temporal expression, as well as protein products of a gene. We studied these features across genes typically causing childhood-onset, adult-onset or both types of disease first individually, then collectively. This led to the generation of testable hypotheses which we investigated using whole genome sequencing data from up to 2,182 individuals presenting with ataxia and 6,658 non-neurological probands recruited in the 100,000 Genomes Project. Using this approach, we demonstrated a high short tandem repeat (STR) density within childhood-onset genes suggesting that we may be missing pathogenic repeat expansions within this cohort. This was verified in both childhood- and adult-onset ataxia patients from the 100,000 Genomes Project who were unexpectedly found to have a trend for higher repeat sizes even at naturally-occurring STRs within known ataxia genes, implying a role for STRs in pathogenesis. Using unsupervised analysis, we found significant similarities in genomic annotation across the gene panels, which suggested adult- and childhood-onset patients should be screened using a common diagnostic gene set. We tested this within the 100,000 Genomes Project by assessing the burden of pathogenic variants among childhood-onset genes in adult-onset patients and vice versa. This demonstrated a significantly higher burden of rare, potentially pathogenic variants in conventional childhood-onset genes among individuals with adult-onset ataxia. Our analysis has implications for the current clinical practice in genetic testing for hereditary ataxia. We suggest that the diagnostic rate for hereditary ataxia could be increased by removing the age-of-onset partition, and through a modified screening for repeat expansions in naturally-occurring STRs within known ataxia-associated genes, in effect treating these regions as candidate pathogenic loci

Whole genome sequencing for the diagnosis of neurological repeat expansion disorders in the UK: a retrospective diagnostic accuracy and prospective clinical validation study

BACKGROUND: Repeat expansion disorders affect about 1 in 3000 individuals and are clinically heterogeneous diseases caused by expansions of short tandem DNA repeats. Genetic testing is often locus-specific, resulting in underdiagnosis of people who have atypical clinical presentations, especially in paediatric patients without a previous positive family history. Whole genome sequencing is increasingly used as a first-line test for other rare genetic disorders, and we aimed to assess its performance in the diagnosis of patients with neurological repeat expansion disorders. METHODS: We retrospectively assessed the diagnostic accuracy of whole genome sequencing to detect the most common repeat expansion loci associated with neurological outcomes (AR, ATN1, ATXN1, ATXN2, ATXN3, ATXN7, C9orf72, CACNA1A, DMPK, FMR1, FXN, HTT, and TBP) using samples obtained within the National Health Service in England from patients who were suspected of having neurological disorders; previous PCR test results were used as the reference standard. The clinical accuracy of whole genome sequencing to detect repeat expansions was prospectively examined in previously genetically tested and undiagnosed patients recruited in 2013-17 to the 100 000 Genomes Project in the UK, who were suspected of having a genetic neurological disorder (familial or early-onset forms of ataxia, neuropathy, spastic paraplegia, dementia, motor neuron disease, parkinsonian movement disorders, intellectual disability, or neuromuscular disorders). If a repeat expansion call was made using whole genome sequencing, PCR was used to confirm the result. FINDINGS: The diagnostic accuracy of whole genome sequencing to detect repeat expansions was evaluated against 793 PCR tests previously performed within the NHS from 404 patients. Whole genome sequencing correctly classified 215 of 221 expanded alleles and 1316 of 1321 non-expanded alleles, showing 97·3% sensitivity (95% CI 94·2-99·0) and 99·6% specificity (99·1-99·9) across the 13 disease-associated loci when compared with PCR test results. In samples from 11 631 patients in the 100 000 Genomes Project, whole genome sequencing identified 81 repeat expansions, which were also tested by PCR: 68 were confirmed as repeat expansions in the full pathogenic range, 11 were non-pathogenic intermediate expansions or premutations, and two were non-expanded repeats (16% false discovery rate). INTERPRETATION: In our study, whole genome sequencing for the detection of repeat expansions showed high sensitivity and specificity, and it led to identification of neurological repeat expansion disorders in previously undiagnosed patients. These findings support implementation of whole genome sequencing in clinical laboratories for diagnosis of patients who have a neurological presentation consistent with a repeat expansion disorder. FUNDING: Medical Research Council, Department of Health and Social Care, National Health Service England, National Institute for Health Research, and Illumina

Use of whole genome sequencing to determine genetic basis of suspected mitochondrial disorders: cohort study.

OBJECTIVE: To determine whether whole genome sequencing can be used to define the molecular basis of suspected mitochondrial disease. DESIGN: Cohort study. SETTING: National Health Service, England, including secondary and tertiary care. PARTICIPANTS: 345 patients with suspected mitochondrial disorders recruited to the 100 000 Genomes Project in England between 2015 and 2018. INTERVENTION: Short read whole genome sequencing was performed. Nuclear variants were prioritised on the basis of gene panels chosen according to phenotypes, ClinVar pathogenic/likely pathogenic variants, and the top 10 prioritised variants from Exomiser. Mitochondrial DNA variants were called using an in-house pipeline and compared with a list of pathogenic variants. Copy number variants and short tandem repeats for 13 neurological disorders were also analysed. American College of Medical Genetics guidelines were followed for classification of variants. MAIN OUTCOME MEASURE: Definite or probable genetic diagnosis. RESULTS: A definite or probable genetic diagnosis was identified in 98/319 (31%) families, with an additional 6 (2%) possible diagnoses. Fourteen of the diagnoses (4% of the 319 families) explained only part of the clinical features. A total of 95 different genes were implicated. Of 104 families given a diagnosis, 39 (38%) had a mitochondrial diagnosis and 65 (63%) had a non-mitochondrial diagnosis. CONCLUSION: Whole genome sequencing is a useful diagnostic test in patients with suspected mitochondrial disorders, yielding a diagnosis in a further 31% after exclusion of common causes. Most diagnoses were non-mitochondrial disorders and included developmental disorders with intellectual disability, epileptic encephalopathies, other metabolic disorders, cardiomyopathies, and leukodystrophies. These would have been missed if a targeted approach was taken, and some have specific treatments

Use of whole genome sequencing to determine genetic basis of suspected mitochondrial disorders: cohort study

Funder: University of Cambridge; FundRef: http://dx.doi.org/10.13039/501100000735Funder: Alzheimer's Society; FundRef: http://dx.doi.org/10.13039/501100000320Funder: Leverhulme Trust; FundRef: http://dx.doi.org/10.13039/501100000275Funder: National Institute for Health Research; FundRef: http://dx.doi.org/10.13039/501100000272Funder: Department of Health; FundRef: http://dx.doi.org/10.13039/501100000276Funder: Evelyn Trust; FundRef: http://dx.doi.org/10.13039/501100004282Funder: Wellcome Trust; FundRef: http://dx.doi.org/10.13039/100004440Funder: Medical Research Council; FundRef: http://dx.doi.org/10.13039/501100000265Abstract: Objective: To determine whether whole genome sequencing can be used to define the molecular basis of suspected mitochondrial disease. Design: Cohort study. Setting: National Health Service, England, including secondary and tertiary care. Participants: 345 patients with suspected mitochondrial disorders recruited to the 100 000 Genomes Project in England between 2015 and 2018. Intervention: Short read whole genome sequencing was performed. Nuclear variants were prioritised on the basis of gene panels chosen according to phenotypes, ClinVar pathogenic/likely pathogenic variants, and the top 10 prioritised variants from Exomiser. Mitochondrial DNA variants were called using an in-house pipeline and compared with a list of pathogenic variants. Copy number variants and short tandem repeats for 13 neurological disorders were also analysed. American College of Medical Genetics guidelines were followed for classification of variants. Main outcome measure: Definite or probable genetic diagnosis. Results: A definite or probable genetic diagnosis was identified in 98/319 (31%) families, with an additional 6 (2%) possible diagnoses. Fourteen of the diagnoses (4% of the 319 families) explained only part of the clinical features. A total of 95 different genes were implicated. Of 104 families given a diagnosis, 39 (38%) had a mitochondrial diagnosis and 65 (63%) had a non-mitochondrial diagnosis. Conclusion: Whole genome sequencing is a useful diagnostic test in patients with suspected mitochondrial disorders, yielding a diagnosis in a further 31% after exclusion of common causes. Most diagnoses were non-mitochondrial disorders and included developmental disorders with intellectual disability, epileptic encephalopathies, other metabolic disorders, cardiomyopathies, and leukodystrophies. These would have been missed if a targeted approach was taken, and some have specific treatments

Number of paraaortic lymph node dissections as a prognostic factor in locally advanced cervical cancer

Background Lymph node (LN) metastases are the most important prognostic factor in locally advanced cervical cancer. Paraaortic lymphadenectomy is the only method able to confirm the presence of metastasis and thereby help to determine the most adequate treatment approach. There is no standard regarding the minimal number of LNs that should be removed in paraaortic lymphadenectomy. Women with undiagnosed positive paraaortic LNs (false negatives) due to a low LN count do not receive extended-field radiation therapy, which may lead to worse survival outcomes. The aim of this study is to confirm LN metastases as poor prognosis and to assess whether in cases of locally advanced CC with negative paraaortic LN status, the number of paraaortic LN laparoscopically removed carries a prognostic value. Methods We analyzed 78 patients with locally advanced cervical cancer that underwent complete paraaortic lymphadenectomy. Results Fifteen (19.2%) women had paraaortic LN metastases. The mean number of LN extracted was 11.1 (SD 7.5). Patients with paraaortic LN metastases presented a worse overall survival (127.1 months [95% CI 111.7-142.4] vs. 59.6 months [95% CI 31.2-87.9]; p < 0.01). Nevertheless, there were no differences regarding disease-free survival. There were no prognostic differences according to the number of LNs resected in patients with negative lymphadenectomy. Conclusions Patients with locally advanced cervical cancer and paraaortic LN metastases present worse survival. In women with negative paraaortic LN, the number of LNs removed does not imply shorter survival. Resumen Antecedentes Las metástasis linfáticas son el factor pronóstico más importante en el cáncer de cérvix localmente avanzado. La linfadenectomía paraaórtica es el único método capaz de confirmar la presencia de metástasis y, por lo tanto, ayudar a determinar el enfoque de tratamiento más adecuado. No existe una norma con respecto al número mínimo de ganglios que deben resecarse en la linfadenectomía paraaórtica. Las mujeres con ganglios paraaórticos positivos no diagnosticados (falsos negativos) debido a un bajo recuento no reciben radioterapia de campo extendido, lo que puede conducir a peores resultados de supervivencia. El objetivo de este estudio es confirmar las metástasis ganglionares como principal factor pronóstico y evaluar si, en los casos de cáncer de cérvix localmente avanzado sin metástasis ganglionares paraaórticas, el número de ganglios extraídos por laparoscopia tiene un valor pronóstico. Métodos Se analizaron 78 pacientes con cáncer cervical localmente avanzado que se sometieron a una linfadenectomía paraaórtica completa. Resultados Quince (19,2%) mujeres tuvieron metástasis ganglionares paraaórticas. El número medio de ganglios extraído fue de 11,1 (DE 7,5). Las pacientes con metástasis paraaórticas presentaron una peor supervivencia global (127,1 meses [IC del 95%: 111,7-142,4] frente a 59,6 meses [IC del 95%: 31,2 a 87,9]; p < 0,01). Sin embargo, no hubo diferencias en cuanto a la supervivencia libre de enfermedad. No hubo diferencias pronósticas según el número de ganglios resecados en pacientes con linfadenectomía negativa. Conclusiones Las pacientes con cáncer cervical localmente avanzado y metástasis paraaórticas presentan peor supervivencia. En las mujeres con linfadenectomía paraaórtica negativa, el número de ganglios extraídos no implica una supervivencia peor

REViewer: haplotype-resolved visualization of read alignments in and around tandem repeats

Background Expansions of short tandem repeats are the cause of many neurogenetic disorders including familial amyotrophic lateral sclerosis, Huntington disease, and many others. Multiple methods have been recently developed that can identify repeat expansions in whole genome or exome sequencing data. Despite the widely recognized need for visual assessment of variant calls in clinical settings, current computational tools lack the ability to produce such visualizations for repeat expansions. Expanded repeats are difficult to visualize because they correspond to large insertions relative to the reference genome and involve many misaligning and ambiguously aligning reads. Results We implemented REViewer, a computational method for visualization of sequencing data in genomic regions containing long repeat expansions and FlipBook, a companion image viewer designed for manual curation of large collections of REViewer images. To generate a read pileup, REViewer reconstructs local haplotype sequences and distributes reads to these haplotypes in a way that is most consistent with the fragment lengths and evenness of read coverage. To create appropriate training materials for onboarding new users, we performed a concordance study involving 12 scientists involved in short tandem repeat research. We used the results of this study to create a user guide that describes the basic principles of using REViewer as well as a guide to the typical features of read pileups that correspond to low confidence repeat genotype calls. Additionally, we demonstrated that REViewer can be used to annotate clinically relevant repeat interruptions by comparing visual assessment results of 44 FMR1 repeat alleles with the results of triplet repeat primed PCR. For 38 of these alleles, the results of visual assessment were consistent with triplet repeat primed PCR. Conclusions Read pileup plots generated by REViewer offer an intuitive way to visualize sequencing data in regions containing long repeat expansions. Laboratories can use REViewer and FlipBook to assess the quality of repeat genotype calls as well as to visually detect interruptions or other imperfections in the repeat sequence and the surrounding flanking regions. REViewer and FlipBook are available under open-source licenses at https://github.com/illumina/REViewer and https://github.com/broadinstitute/flipbook respectively.Medicine, Faculty ofMedical Genetics, Department ofReviewedFacultyResearche

PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels

I ndividual genomes contain millions of genetic variants. When considering which variants may be causative for a given rare genetic disease, applying filtering criteria (such as allele frequency, predicted variant consequence, familial segregation and mode of inheritance) decreases this number to hundreds of variants. However, such a number remains labor intensive for a diagnostic genetic testing laboratory to interpret as part of routine service for each patient or family. A list of genes with evidence of disease causation in the condition being assessed aids in prioritizing and ranking the variants. This prioritization decreases the number of candidates that laboratories or clinical geneticists must assess to identify the likely causative variants for clinical reporting. Established lists of genes with clear evidence of disease causation (referred to herein as virtual gene panels) are therefore a highly effective tool in variant prioritization.M. Caulfield was funded by the National Institute for Health Research (NIHR) as part of the portfolio of translational research of the NIHR Biomedical Research Center at Barts and The London School of Medicine and Dentistry. He is supported as an NIHR senior investigator, and this work was funded by the MRC eMedLab award. This research was made possible through access to the data and findings generated by the 100,000 Genomes Project. The 100,000 Genomes Project is managed by Genomics England Limited (a wholly owned company of the Department of Health). The 100,000 Genomes Project is funded by the NIHR and NHSE. The Wellcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructur

A New Overgrowth Syndrome is due to Mutations in RNF125

Overgrowth syndromes (OGS) are a group of disorders in which all parameters of growth and physical development are above the mean for age and sex. We evaluated a series of 270 families from the Spanish Overgrowth Syndrome Registry with no known OGS. We identified one de novo deletion and three missense mutations in RNF125 in six patients from four families with overgrowth, macrocephaly, intellectual disability, mild hydrocephaly, hypoglycemia, and inflammatory diseases resembling Sjögren syndrome. RNF125 encodes an E3 ubiquitin ligase and is a novel gene of OGS. Our studies of the RNF125 pathway point to upregulation of RIG-I-IPS1-MDA5 and/or disruption of the PI3K-AKT and interferon signaling pathways as the putative final effectors.Fil: Tenorio, Jair. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Mansilla, Alicia. Instituto Cajal. Madrid; EspañaFil: Valencia, María. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Martínez Glez, Víctor. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Romanelli, Valeria. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; EspañaFil: Arias, Pedro. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Castrejón, Nerea. Hospital San Juan de Dios. Barcelona; EspañaFil: Poletta, Fernando Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. CEMIC-CONICET. Centro de Educaciones Médicas e Investigaciones Clínicas ; ArgentinaFil: Guillén Navarro, Encarna. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Hospital Virgen de la Arrixaca. Murcia; EspañaFil: Gordo, Gema. Universidad Autónoma de Madrid; EspañaFil: Mansilla, Elena. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: García Santiago, Fé. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: González Casado, Isabel. Hospital Universitario La Paz. Madrid; EspañaFil: Vallespín, Elena. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Palomares, María. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Mori, María A.. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Santos Simarro, Fernando. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: García Miñaur, Sixto. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Fernández, Luis. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Mena, Rocío. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Benito Sanz, Sara. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: del Pozo, Ángela. Hospital Universitario La Paz. Madrid; EspañaFil: Silla, Juan Carlos. Hospital Universitario La Paz. Madrid; EspañaFil: Ibañez, Kristina. Hospital Universitario La Paz. Madrid; EspañaFil: López Granados, Eduardo. Hospital Universitario La Paz. Madrid; EspañaFil: Martín Trujillo, Alex. Cancer Epigenetics and Biology Program. Barcelona; EspañaFil: Montaner, David. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Centro de Investigación Príncipe Felipe. Valencia; EspañaFil: The SOGRI Consortium. Hospital Universitario La Paz. Madrid; EspañaFil: Heath, Karen E. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Hospital Universitario La Paz. Madrid; EspañaFil: Campos Barros, Ángel. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Hospital Universitario La Paz. Madrid; EspañaFil: Dopazo, Joaquín. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Centro de Investigación Príncipe Felipe. Valencia; EspañaFil: Nevado, Julián. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Hospital Universitario La Paz. Madrid; EspañaFil: Monk, David. Cancer Epigenetics and Biology Program. Barcelona; EspañaFil: Ruiz Pérez, Víctor. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; EspañaFil: Lapunzina, Pablo. Centro de Investigación Biomédica en Red de Enfermedades Raras. Madrid; España. Universidad Autónoma de Madrid; Españ