Combining Exome and Transcriptome Data to Unravel the Genetic Basis of the Lissencephalies
NCT ID: NCT05185414
Last Updated: 2022-01-11
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
50 participants
INTERVENTIONAL
2022-01-31
2025-09-30
Brief Summary
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Detailed Description
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High efficiency in identifying new pathogenic variants and novel gene annotation can be expected because of the strong monogenetic base. These novel variants and gene annotation are indispensable for better understanding the origin and pathophysiology of the lissencephaly spectrum and neuronal migration.
The functional impact of newly discovered genes can be further investigated by the innovative CRISPR-Cas9 method. This gene-editing technique allows researchers to create knock-out or even knock-in genes, as an opportunity to investigate novel annotated genes and their functional consequences. Although it is beyond the scope of this study, it is an interesting item for future joined research projects, within our research group or in collaboration with others. During this study, also genetically diagnosed lissencephaly cases will be subjected to RNA sequencing. The current classifi-cation of lissencephalies is based on pathogenic variants and biological pathways. Alterations in RNA-expression pattern could possibly shine a new light on this classification.
This study will also evaluate which sampling tissues are most suited for RNA extraction and sequencing. Considerations to make include the targeted quality of the extracted RNA and differences in tissue-specific gene expression. Mouth swaps, although non-invasive, are not suited for RNA extraction because of the natural oral flora with multiple viruses and bacteria (exogenous genetic material). Fibroblast-derived RNA is considered to be of good quality, but a skin biopsy is required and considered relatively invasive. Whole blood is obtained by minimal invasive techniques, but gene expression may be of poorer quality compared to fibroblasts.
The first part of the study is performed in a diagnostic setting in unsolved lissencephaly cases. Fibroblasts will be obtained by skin biopsy (punch). RNA seq data will be extracted from fibroblasts and blood. This RNA seq data will be analyzed in search for new pathogenic variants. When new pathogenic variants are identified in the RNA seq data, existing WES data will be reanalyzed. If neces-sary, subsequent WGS will be performed. When a genetic diagnosis is obtained, RNA seq and WES/WGS data will be transferred to the research part of the study.
A second part of the study is performed in a research setting. Lissencephaly patients with a genetic diagnosis will be proposed to donate a skin biopsy and . RNA seq data will be extracted from fibroblasts and blood as in the diagnostic track. In the RNA seq data two items will be observed. Firstly, has RNA seq data extracted from fibroblasts a major advantage over RNA seq data extracted from blood in terms of variant detection? Secondly, can RNA patterns be identified in common affected pathways?
Conditions
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Study Design
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NON_RANDOMIZED
PARALLEL
Research track: apply rna sequencing on lissencephaly patient with an established genetic diagnosis to investigate additional diagnositc yield, suited sampling tissue and rna patterns
DIAGNOSTIC
NONE
Study Groups
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RNA sequencing in genetically solved lissencephaly cases
RNA expression patterns in lissencephalies. RNA sequencing will be applied to the genetically solved lissencephaly cases. The acquired information on RNA expression patterns will be implemented in unsolved lissencephaly cases.
Venipuncture and skin biopsy for RNA extraction
* Blood sampling (standard venipuncture)
* Skin biopsy (fibroblasts)
RNA sequencing in genetically unsolved lissencephaly cases
Obtain a genetic diagnosis in unsolved lissencephaly cases by implementation of RNA expression patterns obtained in arm 1.
Venipuncture and skin biopsy for RNA extraction
* Blood sampling (standard venipuncture)
* Skin biopsy (fibroblasts)
Interventions
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Venipuncture and skin biopsy for RNA extraction
* Blood sampling (standard venipuncture)
* Skin biopsy (fibroblasts)
Eligibility Criteria
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Inclusion Criteria
* anomaly on MRI of the lissencephaly spectrum (lissencephaly, pachygyria, subcortical band heterotopia
Diagnostic track:
* No established genetic diagnosis by conventional WES/WGS
Research track:
* An established genetic diagnosis by conventinal WES/WGS
Exclusion Criteria
ALL
No
Sponsors
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Marguerite - Marie Delacroix Foundation
UNKNOWN
Universitair Ziekenhuis Brussel
OTHER
Responsible Party
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Principal Investigators
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Ellen RIJCKMANS, Dr
Role: PRINCIPAL_INVESTIGATOR
UZ Brussel - Vrije Universiteit Brussel
Locations
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UZ Brussel
Jette, Brussels Capital, Belgium
Countries
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Central Contacts
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Facility Contacts
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References
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Di Donato N, Timms AE, Aldinger KA, Mirzaa GM, Bennett JT, Collins S, Olds C, Mei D, Chiari S, Carvill G, Myers CT, Riviere JB, Zaki MS; University of Washington Center for Mendelian Genomics; Gleeson JG, Rump A, Conti V, Parrini E, Ross ME, Ledbetter DH, Guerrini R, Dobyns WB. Analysis of 17 genes detects mutations in 81% of 811 patients with lissencephaly. Genet Med. 2018 Nov;20(11):1354-1364. doi: 10.1038/gim.2018.8. Epub 2018 Apr 19.
Gonorazky HD, Naumenko S, Ramani AK, Nelakuditi V, Mashouri P, Wang P, Kao D, Ohri K, Viththiyapaskaran S, Tarnopolsky MA, Mathews KD, Moore SA, Osorio AN, Villanova D, Kemaladewi DU, Cohn RD, Brudno M, Dowling JJ. Expanding the Boundaries of RNA Sequencing as a Diagnostic Tool for Rare Mendelian Disease. Am J Hum Genet. 2019 Mar 7;104(3):466-483. doi: 10.1016/j.ajhg.2019.01.012. Epub 2019 Feb 28.
Severino M, Geraldo AF, Utz N, Tortora D, Pogledic I, Klonowski W, Triulzi F, Arrigoni F, Mankad K, Leventer RJ, Mancini GMS, Barkovich JA, Lequin MH, Rossi A. Definitions and classification of malformations of cortical development: practical guidelines. Brain. 2020 Oct 1;143(10):2874-2894. doi: 10.1093/brain/awaa174.
Murdock DR, Dai H, Burrage LC, Rosenfeld JA, Ketkar S, Muller MF, Yepez VA, Gagneur J, Liu P, Chen S, Jain M, Zapata G, Bacino CA, Chao HT, Moretti P, Craigen WJ, Hanchard NA; Undiagnosed Diseases Network; Lee B. Transcriptome-directed analysis for Mendelian disease diagnosis overcomes limitations of conventional genomic testing. J Clin Invest. 2021 Jan 4;131(1):e141500. doi: 10.1172/JCI141500.
Other Identifiers
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TRANSC_LIS
Identifier Type: -
Identifier Source: org_study_id
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