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

December 29, 2023 updated by: Clara van Karnebeek, Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)

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.

Study Overview

Detailed Description

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.

Study Type

Interventional

Enrollment (Actual)

334

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

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)

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: 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.
Untargeted metabolomics in bloodspots and in plasma
WES reanalysis and WGS analysis
Other Names:
  • Genomics

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Diagnostic yield
Time Frame: 3 years
Number of patients diagnosed
3 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Collaborators

Investigators

  • Principal Investigator: Clara DM van Karnebeek, Professor, Amsterdam UMC and United for Metabolic Diseases (UMD)

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 10, 2019

Primary Completion (Actual)

December 31, 2021

Study Completion (Actual)

December 31, 2021

Study Registration Dates

First Submitted

December 29, 2023

First Submitted That Met QC Criteria

December 29, 2023

First Posted (Actual)

January 10, 2024

Study Record Updates

Last Update Posted (Actual)

January 10, 2024

Last Update Submitted That Met QC Criteria

December 29, 2023

Last Verified

December 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • ZOEMBA

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

To make data Findable (according to FAIR principles), data will be shared internationally with other authorized researchers through the existing, well-managed, secure, large-scale, controlled-access web-based, repository of the RD-Connect platform (https://platform.rd-connect.eu/).

IPD Sharing Time Frame

3 years

IPD Sharing Access Criteria

RD-connect access

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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