- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03988764
Monogenic Diabetes Misdiagnosed as Type 1 (ADDAM)
Accurate Diagnosis of Diabetes for Appropriate Management
The study has two aims:
- To (1a) determine the frequency of monogenic diabetes misdiagnosed as type 1 diabetes (T1D) and (2) to define an algorithm for case selection.
- To discover novel genes whose mutations cause monogenic diabetes misdiagnosed as T1D.
Study Overview
Status
Detailed Description
Aim 1. The investigators will recruit 5,000 cases diagnosed as T1D under the age of 25, from 17 participating clinics across Canada. All cases will be tested for four antibodies (against proinsulin, GAD65, islet antigen 2 (IA-2), and ZnT8). Cases negative for all four will be exome-sequenced.
- Variant annotation will be focused on known monogenic diabetes genes. Variants rated as pathogenic, likely pathogenic or of unknown significance whose zygosity fits the genetic model, will be confirmed in a clinically certified laboratory and communicated to the treating health care team. End-point is the frequency of such variants compared to their frequency in control, non-T1D exomes.
- The following variables will be examined for the ability to predict monogenic diabetes: Negativity for all autoantibodies tested, family history, polygenic T1D risk score, age of onset, sex, glycosylated hemoglobin (HbA1c), insulin dose, and presence of syndromic features. Predictors will be analyzed by multiple regression and results subjected to jackknife (leave-one-out) validation. Machine-learning techniques may be used.
Aim 2. Variants outside known genes in non-diagnostic exomes will be annotated and examined under autosomal dominant, recessive, X-linked and mitochondrial inheritance models. Corresponding frequency cutoffs will be 0.0005, 0.01, 0.001 and 0.0005 (if heteroplasmy >70%). Formal mutation-burden analysis will be based on depth-adjusted data from the Genome Aggregation Database (gnomAD). Genes mutated in more than one unrelated proband will be examined by a statistical approach taking into account the presence of a large number of phenocopies (Akawi et al., Nat Genet. 2015;47:1363-1369). Genes that achieve statistical significance will be tested in additional cohorts with international collaborations.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Constantin Polychronakos, MD
- Phone Number: 22866 5144124400
- Email: constantin.polychronakos@mcgill.ca
Study Contact Backup
- Name: Luc Marchand, MSc
- Phone Number: 22623 5144124400
- Email: luc.marchand@gmail.com
Study Locations
-
-
Quebec
-
Montreal, Quebec, Canada, H4A 3J1
- Recruiting
- The Montreal Children's Hospital
-
Contact:
- Angeliki Makri, MD
- Phone Number: 22623 514-934-1934
- Email: angeliki.makri@mail.mcgill.ca
-
Contact:
- Constantin Polychronakos, MD
- Phone Number: 22623 514-934-1934
- Email: constantin.polychronakos@mcgill.ca
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Diagnosis of diabetes under the age of 25 as either type 1 or undetermined type.
Exclusion Criteria:
- Existing T1D autoantibody testing with a positive result
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
---|
Antibody-negative
Patient has been found negative for at least three T1D antibodies. The investigators will proceed with whole exome sequencing |
Antibody-positive
Patient has been found to be positive for at least one T1D autoantibody. No further studies will be performed as part of the main study. |
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Proportion of monogenic diabetes among patients diagnosed as type 1 diabetes.
Time Frame: 6 years
|
The exomes of all patients negative for four T1D autoantibodies will be sequenced and pathogenic variants in genes known to cause monogenic diabetes will be called and annotated.
The frequency of genes carrying such variants among these patients will be compared to control exomes from public databases.
|
6 years
|
Proportion of patients carrying mutations in previously unstudied genes that meet statistical criteria of pathogenicity for monogenic diabetes.
Time Frame: 7 years
|
Exomes not found to carry a mutation (per outcome 1) will be analyzed to discover pathogenic variants in novel genes.
Genes mutated in more than one unrelated probands will be statistically evaluated to see if variants in these gene occur more frequently than in control exomes.
The number of probands that is needed to fulfill this criterion will depend on the gene's tolerance to protein-altering mutations.
|
7 years
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Risk-prediction score for monogenic diabetes mutation in antibody negative T1D patients
Time Frame: 5 years
|
Composit score with a statistically significant ROC curve for predicting monogenic diabetes in individuals previously diagnosed as T1D.
It will be based on age of onset, T1D polygenic risk score.
The risk score will aim to predict monogenic diabetes in cases with clinical T1D diagnosis and known to be antibody negative.
The scale will be calculated as follows: From the exome sequencing, the investigators will be able to determine genotype at the three most important loci determining risk for autoimmune T1D (HLA, INS and PTPN22).The composite risk score, along with family history, age of onset, HbA1c+4*insulin dose/kg (as proxy for residual beta cell function) will be subjected to logistic regression for an overall risk.
The ROC curve will be used to select a point likely to capture most cases unlikely to have autoimmune T1D, sacrificing specificity to maximize sensitivity.
Data will be validated with jackknife cross-validation.
|
5 years
|
Collaborators and Investigators
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Pathologic Processes
- Glucose Metabolism Disorders
- Metabolic Diseases
- Nervous System Diseases
- Immune System Diseases
- Autoimmune Diseases
- Kidney Diseases
- Urologic Diseases
- Eye Diseases
- Neurologic Manifestations
- Endocrine System Diseases
- Disease
- Congenital Abnormalities
- Genetic Diseases, Inborn
- Otorhinolaryngologic Diseases
- Neurodegenerative Diseases
- Ear Diseases
- Eye Diseases, Hereditary
- Heredodegenerative Disorders, Nervous System
- Optic Nerve Diseases
- Cranial Nerve Diseases
- Sensation Disorders
- Optic Atrophies, Hereditary
- Optic Atrophy
- Pituitary Diseases
- Abnormalities, Multiple
- Hearing Disorders
- Vision Disorders
- Deaf-Blind Disorders
- Blindness
- Hearing Loss
- Deafness
- Diabetes Insipidus
- Female Urogenital Diseases
- Female Urogenital Diseases and Pregnancy Complications
- Urogenital Diseases
- Male Urogenital Diseases
- Diabetes Mellitus
- Diabetes Mellitus, Type 2
- Syndrome
- Diabetes Mellitus, Type 1
- Wolfram Syndrome
Other Study ID Numbers
- ADDAM
- Canscreen (Other Identifier: Research Ethics Board, MUHC)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ANALYTIC_CODE
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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