The diagnostic yield of whole exome sequencing as a first approach in consanguineous Omani renal ciliopathy syndrome patients [version 2; peer review: 2 approved]
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ABSTRACT:
SUBMITTER: Al Alawi I
PROVIDER: S-EPMC8290205 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Ciliopathies are a group of rare disorders characterized by a high genetic and phenotypic variability, which complicates their molecular diagnosis. Hence the need to use the latest powerful approaches to faster identify the genetic defect in these patients. We applied whole exome sequencing to six consanguineous families clinically diagnosed with ciliopathy-like disease, and for which mutations in predominant Bardet-Biedl syndrome (BBS) genes had previously been excluded. Our strategy, based on first applying several filters to ciliary variants and using many of the bioinformatics tools available, allowed us to identify causal mutations in BBS2, ALMS1 and CRB1 genes in four families, thus confirming the molecular diagnosis of ciliopathy. In the remaining two families, after first rejecting the presence of pathogenic variants in common cilia-related genes, we adopted a new filtering strategy combined with prioritisation tools to rank the final candidate genes for each case. Thus, we propose CORO2B, LMO7 and ZNF17 as novel candidate ciliary genes, but further functional studies will be needed to confirm their role. Our data show the usefulness of this strategy to diagnose patients with unclear phenotypes, and therefore the success of applying such technologies to achieve a rapid and reliable molecular diagnosis, improving genetic counselling for these patients. In addition, the described pipeline also highlights the common pitfalls associated to the large volume of data we have to face and the difficulty of assigning a functional role to these changes, hence the importance of designing the most appropriate strategy according to each case.
| S-EPMC5553726 | biostudies-literature
Project description:Dilated cardiomyopathy (DCM) is a heritable, genetically heterogeneous disorder characterized by progressive heart failure. DCM typically remains clinically silent until adulthood, yet symptomatic disease can develop in childhood. We sought to identify the genetic basis of pediatric DCM in 15 sporadic and three affected-siblings cases, comprised of 21 affected children (mean age, five years) whose parents had normal echocardiograms (mean age, 39 years). Twelve underwent cardiac transplantation and five died with severe heart failure. Parent-offspring whole exome sequencing (WES) data were filtered for rare, deleterious, de novo and recessive variants. In prior work, we reported de novo mutations in TNNT2 and RRAGC and compound heterozygous mutations in ALMS1 and TAF1A among four cases in our cohort. Here, de novo mutations in established DCM genes-RBM20, LMNA, TNNT2, and PRDM16-were identified among five additional cases. The RBM20 mutation was previously reported in familial DCM. An identical unreported LMNA mutation was identified in two unrelated cases, both harboring gene-specific defects in cardiomyocyte nuclear morphology. Collectively, WES had a 50% diagnostic yield in our cohort, providing an explanation for pediatric heart failure and enabling informed family planning. Research is ongoing to discover novel DCM genes among the remaining families.
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Project description:Cohort studies collect, generate and distribute data over long periods of time – often over the lifecourse of their participants. It is common for these studies to host a list of publications (which can number many thousands) on their website to demonstrate the impact of the study and facilitate the search of existing research to which the study data has contributed. The ability to search and explore these publication lists varies greatly between studies. We believe a lack of rich search and exploration functionality of study publications is a barrier to entry for new or prospective users of a study’s data, since it may be difficult to find and evaluate previous work in a given area. These lists of publications are also typically manually curated, resulting in a lack of rich metadata to analyse, making bibliometric analysis difficult. We present here a software pipeline that aggregates metadata from a variety of third-party providers to power a web based search and exploration tool for lists of publications. Alongside core publication metadata (i.e. author lists, keywords etc.), we include geocoding of first authors and citation counts in our pipeline. This allows a characterisation of a study as a whole based on common locations of authors, frequency of keywords, citation profile etc. This enriched publications metadata can be useful for generating study impact metrics and web-based graphics for public dissemination. In addition, the pipeline produces a research data set for bibliometric analysis or social studies of science. We use a previously published list of publications from a cohort study as an exemplar input data set to show the output and utility of the pipeline here.
| S-EPMC8108552 | biostudies-literature
Project description:Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.
| S-EPMC8114187 | biostudies-literature
Project description:Mounting evidence indicates that worldwide, innovation systems are increasing unsustainable. Equally, concerns about inequities in the science and innovation process, and in access to its benefits, continue. Against a backdrop of growing health, economic and scientific challenges global stakeholders are urgently seeking to spur innovation and maximize the just distribution of benefits for all. Open Science collaboration (OS) - comprising a variety of approaches to increase open, public, and rapid mobilization of scientific knowledge - is seen to be one of the most promising ways forward. Yet, many decision-makers hesitate to construct policy to support the adoption and implementation of OS without access to substantive, clear and reliable evidence. In October 2017, international thought-leaders gathered at an Open Science Leadership Forum in the Washington DC offices of the Bill and Melinda Gates Foundation to share their views on what successful Open Science looks like. Delegates from developed and developing nations, national governments, science agencies and funding bodies, philanthropy, researchers, patient organizations and the biotechnology, pharma and artificial intelligence (AI) industries discussed the outcomes that would rally them to invest in OS, as well as wider issues of policy and implementation. This first of two reports, summarizes delegates' views on what they believe OS will deliver in terms of research, innovation and social impact in the life sciences. Through open and collaborative process over the next months, we will translate these success outcomes into a toolkit of quantitative and qualitative indicators to assess when, where and how open science collaborations best advance research, innovation and social benefit. Ultimately, this work aims to develop and openly share tools to allow stakeholders to evaluate and re-invent their innovation ecosystems, to maximize value for the global public and patients, and address long-standing questions about the mechanics of innovation.
| S-EPMC7839829 | biostudies-literature
Project description:Whole-exome sequencing (WES) is an effective approach to identify the susceptibility of genetic variants of autism spectrum disorder (ASD). The Israel Ministry of Health supports WES as an adjunct tool for ASD diagnosis, despite its unclear diagnostic yield and cost effectiveness. To address this knowledge gap, we applied WES to a population-based sample of 182 Bedouin and Jewish children with ASD from southern Israel, and assessed its yield in a gene panel of 205 genes robustly associated with ASD. We then compared the incremental cost-effectiveness ratios (ICERs) for an ASD diagnosis by WES, chromosomal microarray analysis (CMA), and CMA + WES. Overall, 32 ASD candidate variants were detected in 28 children, corresponding to an overall WES diagnostic yield of 15.4%. Interestingly, the diagnostic yield was significantly higher for the Bedouin children than for the Jewish children, i.e., 27.6% vs. 11.1% (p = 0.036). The most cost-effective means for genetic testing was the CMA alone, followed closely by the CMA + WES strategy (ICER = USD 117 and USD 124.8 per child). Yet, WES alone could become more cost effective than the other two approaches if there was to be a 25% increase in its yield or a 50% decrease in its cost. These findings suggest that WES should be recommended to facilitate ASD diagnosis in Israel, especially for highly consanguineous populations, such as the Bedouin.
| S-EPMC8774872 | biostudies-literature
Project description:The pathogen exposure history of an individual is recorded in their T-cell repertoire and can be accessed through the study of T-cell receptors (TCRs) if the tools to identify them were available. For each T-cell, the TCR loci undergoes genetic rearrangement that creates a unique DNA sequence. In theory these unique sequences can be used as biomarkers for tracking T-cell responses and cataloging immunological history. We developed the immune Cell Analysis Tool (iCAT), an R software package that analyzes TCR sequencing data from exposed (positive) and unexposed (negative) samples to identify TCR sequences statistically associated with positive samples. The presence and absence of associated sequences in samples trains a classifier to diagnose pathogen-specific exposure. We demonstrate the high accuracy of iCAT by testing on three TCR sequencing datasets. First, iCAT successfully diagnosed smallpox vaccinated versus naïve samples in an independent cohort of mice with 95% accuracy. Second, iCAT displayed 100% accuracy classifying naïve and monkeypox vaccinated mice. Finally, we demonstrate the use of iCAT on human samples before and after exposure to SARS-CoV-2, the virus behind the COVID-19 global pandemic. We were able to correctly classify the exposed samples with perfect accuracy. These experimental results show that iCAT capitalizes on the power of TCR sequencing to simplify infection diagnostics. iCAT provides the option of a graphical, user-friendly interface on top of usual R interface allowing it to reach a wider audience.
| S-EPMC8276190 | biostudies-literature
Project description:A dysregulated host immune response significantly contributes to morbidity and mortality in tuberculous meningitis (TBM). Effective host directed therapies (HDTs) are critical to improve survival and clinical outcomes. Currently only one HDT, dexamethasone, is proven to improve mortality. However, there is no evidence dexamethasone reduces morbidity, how it reduces mortality is uncertain, and it has no proven benefit in HIV co-infected individuals. Further research on these aspects of its use, as well as alternative HDTs such as aspirin, thalidomide and other immunomodulatory drugs is needed. Based on new knowledge from pathogenesis studies, repurposed therapeutics which act upon small molecule drug targets may also have a role in TBM. Here we review existing literature investigating HDTs in TBM, and propose new rationale for the use of novel and repurposed drugs. We also discuss host variable responses and evidence to support a personalised approach to HDTs in TBM.
| S-EPMC8792876 | biostudies-literature
Project description:Importance:Whole-exome sequencing (WES) has the potential to reveal tumor and germline mutations of clinical relevance, but the diagnostic yield for pediatric patients with solid tumors is unknown. Objective:To characterize the diagnostic yield of combined tumor and germline WES for children with solid tumors. Design:Unselected children with newly diagnosed and previously untreated central nervous system (CNS) and non-CNS solid tumors were prospectively enrolled in the BASIC3 study at a large academic children's hospital during a 23-month period from August 2012 through June 2014. Blood and tumor samples underwent WES in a certified clinical laboratory with genetic results categorized on the basis of perceived clinical relevance and entered in the electronic health record. Main Outcomes and Measures:Clinical categorization of somatic mutations; frequencies of deleterious germline mutations related to patient phenotype and incidental medically-actionable mutations. Results:Of the first 150 participants (80 boys and 70 girls, mean age, 7.4 years), tumor samples adequate for WES were available from 121 patients (81%). Somatic mutations of established clinical utility (category I) were reported in 4 (3%) of 121 patients, with mutations of potential utility (category II) detected in an additional 29 (24%) of 121 patients. CTNNB1 was the gene most frequently mutated, with recurrent mutations in KIT, TSC2, and MAPK pathway genes (BRAF, KRAS, and NRAS) also identified. Mutations in consensus cancer genes (category III) were found in an additional 24 (20%) of 121 tumors. Fewer than half of somatic mutations identified were in genes known to be recurrently mutated in the tumor type tested. Diagnostic germline findings related to patient phenotype were discovered in 15 (10%) of 150 cases: 13 pathogenic or likely pathogenic dominant mutations in adult and pediatric cancer susceptibility genes (including 2 each in TP53, VHL, and BRCA1), 1 recessive liver disorder with hepatocellular carcinoma (TJP2), and 1 renal diagnosis (CLCN5). Incidental findings were reported in 8 (5%) of 150 patients. Most patients harbored germline uncertain variants in cancer genes (98%), pharmacogenetic variants (89%), and recessive carrier mutations (85%). Conclusions and Relevance:Tumor and germline WES revealed mutations in a broad spectrum of genes previously implicated in both adult and pediatric cancers. Combined reporting of tumor and germline WES identified diagnostic and/or potentially actionable findings in nearly 40% of newly diagnosed pediatric patients with solid tumors.
| S-EPMC5471125 | biostudies-literature
Project description:IntroductionThe aim of this retrospective cohort study was to determine the potential diagnostic yield of prenatal whole exome sequencing in fetuses with structural anomalies on expert ultrasound scans and normal chromosomal microarray results.Material and methodsIn the period 2013-2016, 391 pregnant women with fetal ultrasound anomalies who received normal chromosomal microarray results, were referred for additional genetic counseling and opted for additional molecular testing pre- and/or postnatally. Most of the couples received only a targeted molecular test and in 159 cases (40.7%) whole exome sequencing (broad gene panels or open exome) was performed. The results of these molecular tests were evaluated retrospectively, regardless of the time of the genetic diagnosis (prenatal or postnatal).ResultsIn 76 of 391 fetuses (19.4%, 95% CI 15.8%-23.6%) molecular testing provided a genetic diagnosis with identification of (likely) pathogenic variants. In the majority of cases (91.1%, 73/76) the (likely) pathogenic variant would be detected by prenatal whole exome sequencing analysis.ConclusionsOur retrospective cohort study shows that prenatal whole exome sequencing, if offered by a clinical geneticist, in addition to chromosomal microarray, would notably increase the diagnostic yield in fetuses with ultrasound anomalies and would allow early diagnosis of a genetic disorder irrespective of the (incomplete) fetal phenotype.
| S-EPMC8247008 | biostudies-literature