Purpose: The increased adoption of genomic strategies in the clinic makes it imperative for diagnostic laboratories to improve the efficiency of variant interpretation. Clinical exome sequencing (CES) is becoming a valuable diagnostic tool, capable of meeting the diagnostic demand imposed by the vast array of different rare monogenic disorders. We have assessed a clinician-led and phenotype-based approach for virtual gene panel generation for analysis of targeted CES in patients with rare disease in a single institution.
Methods: Retrospective survey of 400 consecutive cases presumed by clinicians to have rare monogenic disorders, referred on singleton basis for targeted CES. We evaluated diagnostic yield and variant workload to characterise the usefulness of a clinician-led approach for generation of virtual gene panels that can incorporate up to three different phenotype-driven gene selection methods.
Results: Abnormalities of the nervous system (54.5%), including intellectual disability, head and neck (19%), skeletal system (16%), ear (15%) and eye (15%) were the most common clinical features reported in referrals. Combined phenotype-driven strategies for virtual gene panel generation were used in 57% of cases. On average, 7.3 variants (median=5) per case were retained for clinical interpretation. The overall diagnostic rate of proband-only CES using personalised phenotype-driven virtual gene panels was 24%.
Conclusions: Our results show that personalised virtual gene panels are a cost-effective approach for variant analysis of CES, maintaining diagnostic yield and optimising the use of resources for clinical genomic sequencing in the clinic.
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http://dx.doi.org/10.1136/jmedgenet-2020-107303 | DOI Listing |
Bioorg Chem
December 2024
Department of Natural Products & Medicinal Chemistry, CSIR-Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500007, Telangana, India; Academy of Scientific & Innovative Research (AcSIR), Ghaziabad 201002, India. Electronic address:
Cyclin-dependent kinases, CDK7 and CDK9 play critical roles in cancer by regulating transcriptional processes essential for cell proliferation and survival. Their dysregulation leads to aberrant gene expression, promoting oncogenic pathways and contributing to tumor growth and progression. This study aimed to identify a new chemotype for CDK7/9 inhibitors using a structure-based virtual screening approach.
View Article and Find Full Text PDFThe 18th International Zebrafish Conference (IZFC2024) took place from August 17 to 21, 2024, at Miyako Messe in Kyoto, Japan. This conference attracted 641 researchers from around the world along with 83 virtual participants, making it the largest gathering since the COVID-19 pandemic. The event featured two keynote lectures, three award lectures, 36 plenary talks, 90 oral presentations, and 374 poster presentations.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
January 2025
Astellas Pharma Inc., Northbrook, Illinois, USA.
The antitumor efficacy of an intratumoral injection of a genetically engineered oncolytic vaccinia virus carrying human IL-7 and murine IL-12 genes (hIL-7/mIL-12-VV) was demonstrated in CT26.WT-bearing mice. In the CT26.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in available cohorts. We introduce "genome-wide association neural networks (GWANN)" a novel approach that uses neural networks (NNs) to perform a gene-level association study with family history of Alzheimer's disease (AD). In UK Biobank, we defined cases (n = 42 110) as those with AD or family history of AD and sampled an equal number of controls.
View Article and Find Full Text PDFPharmaceuticals (Basel)
December 2024
School of Medicine, Shanghai University, Shanghai 200444, China.
Background/objectives: Breast cancer is the second most common malignancy worldwide and poses a significant threat to women's health. However, the prognostic biomarkers and therapeutic targets of breast cancer are unclear. A prognostic model can help in identifying biomarkers and targets for breast cancer.
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