Monogenic Diabetes Misdiagnosed as Type 1
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: None AHT.
- Who it may be relevant to
- Registry conditions: Diabetes Mellitus, Type 1, Monogenic Diabetes, Neonatal Diabetes, Maturity-onset Diabetes in the Young (MODY). Basic parameters: 1 Day — 25 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Canada
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Accurate Diagnosis of Diabetes for Appropriate Management
Overview
The study has two aims: 1. To (1a) determine the frequency of monogenic diabetes misdiagnosed as type 1 diabetes (T1D) and (2) to define an algorithm for case selection. 2. To discover novel genes whose mutations cause monogenic diabetes misdiagnosed as T1D.
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.
1. 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. 2. 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.
Interventions
- Other None AHT
No further intervention planned for either group as part of the current study.
Primary outcome measures
- Proportion of monogenic diabetes among patients diagnosed as type 1 diabetes. [Time frame: 6 years]
- Proportion of patients carrying mutations in previously unstudied genes that meet statistical criteria of pathogenicity for monogenic diabetes. [Time frame: 7 years]
Secondary outcome measures (1)
- Risk-prediction score for monogenic diabetes mutation in antibody negative T1D patients [Time frame: 5 years]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Case-only
Study locations
Canada · 1 center
- The Montreal Children's Hospital — Montreal
Identifiers
NCT: NCT03988764 · ADDAM · Canscreen