Zoektocht Naar Erfelijke MetaBole Aandoening (Dutch)/ Solve The Unsolved (English)

NCT ID: NCT06200142

Last Updated: 2024-01-10

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

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

334 participants

Study Classification

INTERVENTIONAL

Study Start Date

2019-12-10

Study Completion Date

2021-12-31

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The goal of this clinical trial is to integrate genomic (WES/WGS) and other -omics technologies in order to find the genetic causes, in 500 patients (children and adults) with an unexplained metabolic phenotype in whom standard care (genetic and metabolic evaluation) did not provide a diagnosis. The overall aim of this study is to diagnose patients with an unknown metabolic phenotype. In addition, we want to provide evidence that the combination of approaches and techniques used in this study will increase diagnostic yield compared to current separated approaches.

All participants will undergo a multi-omics(WES, WGS and metabolomics) approach to solve the unsolved genetic basis of their metabolic phenotype.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Rationale: Inborn Errors of Metabolism (IEM) are monogenic conditions in which the impairment of a biochemical pathway is intrinsic to the pathophysiology of the disease. Organ dysfunction results from intoxication and/or storage of metabolites, as well as a shortage of energy and building blocks. Rapid diagnosis of IEM enables initiation of targeted treatment (e.g. diet) slowing down or stopping the degenerative nature of the disease, resulting in significantly reduction of morbidity and mortality. A diagnosis also enables prognostication, access to community services and accurate genetic counselling for the patient and his/her family. Diagnosing IEM can be a major challenge, because of phenotypic heterogeneity and complex, expensive, diagnostic tests. Whole exome/ genome sequencing (WES/WGS) has revolutionized diagnostics of rare diseases and IEM, but still gives a negative or inconclusive result in \>50% of cases. Addition of other omics technologies (metabolomics, glycomics, lipidomics, epigenomics, transcriptomics, proteomics) with integrated bioinformatics increases diagnostic yield, as it may point to the defective pathway allowing scrutinizing genes in genomic data or vice versa: it generates evidence of the deleterious functional impact of a DNA variants of unknown significance (VUS). In this study we will unite our national expertises and apply a multi-omics approach to solve the unsolved genetic basis of patients with a metabolic phenotype on a larger scale.

Objective: Integrating genomic (WES/WGS) and other -omics technologies in order to find the genetic causes, in 500 patients (children and adults) with an unexplained metabolic phenotype in whom standard care (genetic and metabolic evaluation) did not provide a diagnosis.

Study design: A prospective, diagnostic (deep phenotyping, WES/WGS and pan-omics) multicenter cohort study.

Study population: (In)capacitated patients (all ages/both genders) with a clinical (and/or family) history and abnormal additional examination (physical (neurological)/ biochemical/ radiological/ genetic) suspicious for an IEM, without diagnosis.

Main study parameters/endpoints: 1) identification of a genetic variant and alignment with its biochemical and phenotypical abnormalities; 2) evaluating the diagnostic yield of combined WES/WGS and omics techniques Methods used: Patients with unexplained metabolic phenotypes are referred (on paper) and discussed by the ZOEMBA (Zoektocht naar Erfelijke MetaBole Aandoening) team. Clinical phenotyping, bioinformatic reanalysis of WES data and additional metabolomics will be performed in all participants. In case still no diagnosis is made, a tailormade diagnostic plan is made combining deep WES, WGS, glycomics, lipidomics, epigenomics, transcriptomics and/or proteomics leading to: a known IEM, a candidate variant or no diagnosis. In case of a variant, additional functional studies (enzymatic assays, targeted omics, CRISPR/CAS, cell lines) will be performed to confirm the effect of the genetic variant on protein function. When still no diagnosis is established, matchmaking (genetic/phenotypical) through international databases might lead to a diagnosis.

Nature and extent of the burden and risks associated with participation, benefit and group relatedness:

The study involves collection of clinical data, reanalysis of previously analysed genetic data, additional "omics" and functional testing. All participants will have between 1 and 3 clinical visits for this study (at the UMC of referral ) and a maximum of 2 telephone appointments with the arts-onderzoeker. Whenever possible study visits will be combined with regular hospital visits. Clinical data (clinical history, family history, physical examination, consultations, additional laboratory and/or radiological investigations) will be collected. A physical examination and blood and urine sampling will be performed in all participants at their first study visit. Any other already available biological samples (eg stored cell lines, dried blood spots, cerebrospinal fluid (CSF)) will be collected for re-analysis. For a selection of patients a skin biopsy will be performed at the 2nd clinical study visit for the use of functional studies. Potential burdens for participants are: the additional study visit(s), diagnostic procedures (e.g. blood, urine sampling and skin biopsy), as well as renewed (false) hope/uncertainty about finding a diagnosis. The potential benefit for all participants include: the opportunity to establish a diagnosis providing information on prognosis, (refinement of) management, genetic counselling with precise recurrence risk and option(s) for prenatal diagnosis.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Inherited Metabolic Disorders

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

NA

Intervention Model

SINGLE_GROUP

(In)capacitated patients (all ages/both genders) with a clinical (and/or family) history and abnormal additional examination (physical (neurological)/ biochemical/ radiological/ genetic) suspicious for an IEM, without diagnosis.
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

The unsolved

(In)capacitated patients (all ages/both genders) with a clinical (and/or family) history and abnormal additional examination (physical (neurological)/ biochemical/ radiological/ genetic) suspicious for an IEM, without diagnosis.

Group Type EXPERIMENTAL

Untargeted metabolomics

Intervention Type DIAGNOSTIC_TEST

Untargeted metabolomics in bloodspots and in plasma

WES and WGS

Intervention Type GENETIC

WES reanalysis and WGS analysis

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Untargeted metabolomics

Untargeted metabolomics in bloodspots and in plasma

Intervention Type DIAGNOSTIC_TEST

WES and WGS

WES reanalysis and WGS analysis

Intervention Type GENETIC

Other Intervention Names

Discover alternative or legacy names that may be used to describe the listed interventions across different sources.

Genomics

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

Patients with an unexplained metabolic phenotype defined as: neurological symptoms and/or abnormalities on (physical) examination suggestive of an inborn error of metabolism (energy deficiency, intoxication type or storage type):

Energy deficiency: neurological (repeated rhabdomyolysis, verified exercise intolerance, neuropathy, myopathy, ataxia), ophthalmological (retinitis pigmentosa (RP)), otological (hearing loss, deafness), endocrine (hypoparathyroidism, hypoglycemia) Intoxication: neurological (encephalopathy, regression, movement disorder, psychiatric symptoms), ophthalmological (lens luxation), organic (liver and kidney function abnormalities) Storage: neurological (regression, psychiatric symptoms), ophthalmological (cataract/corneal clouding), skin (angiokeratomas), blood (cytopenias), organic (hepatosplenomegaly, cardiac hypertrophy, skeletal abnormalities, short stature, coarse facial features, umbilical/inguinal hernia)

AND / OR one or more of the following suggesting a deficient metabolic pathway or process:

* abnormal metabolites in body fluids (CSF, urine, blood)
* functional studies at a biochemical/cellular level indicative of a metabolic deficiency (e.g. respiratory chain complex analysis)
* organ dysfunction (e.g. liver or kidney failure)
* an abnormal clinical function test (protein loading test, fasting test, meal test, validated exercise test, non-ischaemic underarm test)
* abnormalities on imaging (neuro-imaging (including spectroscopy); X-rays (dysostoses or other bone abnormalities); ultrasound (enlarged liver/spleen))
* a VUS (variant of unknown significance) in a gene involved in metabolism

AND no diagnosis despite extensive clinical, metabolic and genetic investigations

* SNP-array/array-CGH: inconclusive results
* metabolic screening according to up to date clinical protocols: inconclusive results
* WES (open or gene panel): no class 4 or 5 variants in a known (OMIM annotated) disease related gene that can fully explain the phenotype of the patient

Exclusion Criteria

A patient will be excluded from participation in this study if:

* after discussion by the ZOEMBA team (see Methods) he/she is suspected to have:

* a genetic condition for which there is a simpler and more cost-effective test available for diagnosis
* a complex genetic disorder (caused by a combination of multiple genes and/or environmental influences)
* a condition that is thought to be caused by factors that are non-genetic, such as infection, injury or toxic exposure
* he/she is unable to follow the study protocol (e.g. additional blood samples)
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Stichting Metakids

UNKNOWN

Sponsor Role collaborator

Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Clara van Karnebeek

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Clara DM van Karnebeek, Professor

Role: PRINCIPAL_INVESTIGATOR

Amsterdam UMC and United for Metabolic Diseases (UMD)

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Amsterdam UMC

Amsterdam, , Netherlands

Site Status

Countries

Review the countries where the study has at least one active or historical site.

Netherlands

Provided Documents

Download supplemental materials such as informed consent forms, study protocols, or participant manuals.

Document Type: Study Protocol

View Document

Related Links

Access external resources that provide additional context or updates about the study.

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

ZOEMBA

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.

Genetic Diagnosis in Inborn Errors of Metabolism
NCT06376279 ENROLLING_BY_INVITATION
Rare and Undiagnosed Disease Research Biorepository
NCT04703179 ENROLLING_BY_INVITATION