Combining Exome and Transcriptome Data to Unravel the Genetic Basis of the Lissencephalies

NCT ID: NCT05185414

Last Updated: 2022-01-11

Study Results

Results pending

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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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

50 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-01-31

Study Completion Date

2025-09-30

Brief Summary

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Malformations of cortical development (MCD) are a heterogenous group of brain malformations including lissencephaly, heterotopia and polymicrogyria. The lissencephaly spectrum (including lissencephaly, pachygyria and subcortical band heterotopia) is a well-defined group of MCD with a strong monogenetic basis. Using current molecular techniques, a causative variant is detected in approximately 80% of individuals with lissencephaly. In a routine diagnostic setting, exome-based gene panels are most frequently used while whole exome sequencing (WES) and whole genome sequencing (WGS) are increasingly being implemented. Both techniques have their shortcomings including the detection of small copy number variants, the identification of pathogenic variants in non-coding regions as well as variant interpretation. The parallel use of quantitative RNA sequencing, measuring differences in RNA expression could be a possible solution for these shortcomings. The proposed research project will for the first time 1) evaluate the added value of WES/WGS combined with quantitative RNA sequencing for the identification of novel genes in individuals with lissencephaly, 2) identify the optimal sampling tissue for RNA sequencing in complex neurological phenotypes and 3) use RNA expression data to provide an evidence base for the current lissencephaly classification.

Detailed Description

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As mentioned before, lissencephalies have a strong monogenetic base in contrast to other brain malformations. Approximately 80% percent of the lissencephalies can be genetically diagnosed by standard WES or WGS.1 In the remaining 20% percent of unsolved cases quantitative RNA sequencing could make a considerable difference. By identifying RNA expression patterns in lissencephalies we will try to provide unsolved lissencephaly cases with a genetic diagnosis. A genetic diagnosis is im-portant in terms of predicting associated problems, follow-up, prognosis and in some cases family planning (e.g. pre-implantation genetic testing). This study will also investigate the additional diagnostic yield of RNA sequencing in lissencephalies and by extension in the MCD spectrum. And, if indicated, the feasibility of implementing RNA sequencing in the standard diagnostic work-up.

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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Classical Lissencephalies and Subcortical Band Heterotopias

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

PARALLEL

Diagnostic track: apply rna sequencing on lissencephaly patients without genetic diagnosis to establish diagnosis

Research track: apply rna sequencing on lissencephaly patient with an established genetic diagnosis to investigate additional diagnositc yield, suited sampling tissue and rna patterns
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

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.

Group Type OTHER

Venipuncture and skin biopsy for RNA extraction

Intervention Type DIAGNOSTIC_TEST

* 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.

Group Type OTHER

Venipuncture and skin biopsy for RNA extraction

Intervention Type DIAGNOSTIC_TEST

* 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)

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

Overall:

* 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

* No anomaly of the lissencephaly spectrum on MRI
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Marguerite - Marie Delacroix Foundation

UNKNOWN

Sponsor Role collaborator

Universitair Ziekenhuis Brussel

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

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

Site Status

Countries

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Belgium

Central Contacts

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Ellen RIJCKMANS, Dr

Role: CONTACT

+32476328726

Katrien STOUFFS, Prof Dr

Role: CONTACT

Facility Contacts

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Ellen RIJCKMANS, Dr

Role: primary

+32476328726

Katrien STOUFFS, Prof Dr

Role: backup

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.

Reference Type BACKGROUND
PMID: 29671837 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 30827497 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 32779696 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 33001864 (View on PubMed)

Other Identifiers

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TRANSC_LIS

Identifier Type: -

Identifier Source: org_study_id

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