Transcriptome Alterations in Myotonic Dystrophy Frontal Cortex

Otero, Brittney A.; Poukalov, Kiril; Hildebrandt, Ryan P.; Thornton, Charles A.; Jinnai, Kenji; Fujimura, Harutoshi; Kimura, Takashi; Hagerman, Katharine A.; Sampson, Jacinda B.; Day, John W.; Wang, Eric T.

doi:10.1101/2020.09.09.284505

Cited by 2 publications

(1 citation statement)

References 64 publications

(75 reference statements)

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“…OGM has also been applied to other areas of paediatrics to improve the diagnostic yield including neurodevelopmental paediatrics 29 , mytonic dystrophy 30 , disorders of sex development 31 , and with the potential for widespread application for prenatal diagnostic testing 32 . Given the extended capabilities of OGM, many undiagnosed conditions in paediatrics will be elucidated using this new technique and other future developments as we enter an era of next generation cytogenetics 27 .…”

Section: Disease Reclassification and Predicting Future Disease In Ch...mentioning

confidence: 99%

Precision diagnostics in children

Dimitri¹

2023

Camb. prisms Precis. med.

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Medical practice is transforming from a reactive to a pro-active and preventive discipline that is underpinned by precision medicine. The advances in technologies in such fields as genomics, proteomics, metabolomics, transcriptomics and artificial intelligence have resulted in a paradigm shift in our understanding of specific diseases in childhood, greatly enhanced by our ability to combine data from changes within cells to the impact of environmental and population changes. Diseases in children have been reclassified as we understand more about their genomic origin and their evolution. Genomic discoveries, additional 'Omics' data and advances such as optical genome mapping have driven rapid improvements in the precision and speed of diagnoses of diseases in children, and are now being incorporated into newborn screening, have improved targeted therapies in childhood, and have supported the development of predictive biomarkers to assess therapeutic impact and determine prognosis in congenital and acquired diseases of childhood.New medical device technologies are facilitating data capture at a population level to support higher diagnostic accuracy and tailored therapies in children according to predicted population outcome, and digital ecosystems now tailor therapies and provide support for their specific needs. By capturing biological and environmental data as early as possible in childhood, we can understand factors that predict disease or maintain health, and track changes across a more extensive longitudinal path. Data from multiple health and external sources over long time periods starting from birth or even in the in-utero environment will provide further clarity about how to sustain health and prevent or predict disease. In this respect, we will not only use data to diagnose disease, but precision diagnostics will aid the 'diagnosis of good health'. The principle of 'start early and gain more' will thus underpin the value of applying a personalised medicine approach early in life.

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Section: Disease Reclassification and Predicting Future Disease In Ch...mentioning

confidence: 99%

Precision diagnostics in children

Dimitri¹

2023

Camb. prisms Precis. med.

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Clinical improvement of DM1 patients reflected by reversal of disease-induced gene expression in blood

Cruchten

As²,

Glennon³

et al. 2022

BMC Med

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Background Myotonic dystrophy type 1 (DM1) is an incurable multisystem disease caused by a CTG-repeat expansion in the DM1 protein kinase (DMPK) gene. The OPTIMISTIC clinical trial demonstrated positive and heterogenous effects of cognitive behavioral therapy (CBT) on the capacity for activity and social participations in DM1 patients. Through a process of reverse engineering, this study aims to identify druggable molecular biomarkers associated with the clinical improvement in the OPTIMISTIC cohort. Methods Based on full blood samples collected during OPTIMISTIC, we performed paired mRNA sequencing for 27 patients before and after the CBT intervention. Linear mixed effect models were used to identify biomarkers associated with the disease-causing CTG expansion and the mean clinical improvement across all clinical outcome measures. Results We identified 608 genes for which their expression was significantly associated with the CTG-repeat expansion, as well as 1176 genes significantly associated with the average clinical response towards the intervention. Remarkably, all 97 genes associated with both returned to more normal levels in patients who benefited the most from CBT. This main finding has been replicated based on an external dataset of mRNA data of DM1 patients and controls, singling these genes out as candidate biomarkers for therapy response. Among these candidate genes were DNAJB12, HDAC5, and TRIM8, each belonging to a protein family that is being studied in the context of neurological disorders or muscular dystrophies. Across the different gene sets, gene pathway enrichment analysis revealed disease-relevant impaired signaling in, among others, insulin-, metabolism-, and immune-related pathways. Furthermore, evidence for shared dysregulations with another neuromuscular disease, Duchenne muscular dystrophy, was found, suggesting a partial overlap in blood-based gene dysregulation. Conclusions DM1-relevant disease signatures can be identified on a molecular level in peripheral blood, opening new avenues for drug discovery and therapy efficacy assessments.

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Transcriptome Alterations in Myotonic Dystrophy Frontal Cortex

Cited by 2 publications

References 64 publications

Precision diagnostics in children

Precision diagnostics in children

Clinical improvement of DM1 patients reflected by reversal of disease-induced gene expression in blood

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