Diabetes, Gestational, Diabetes Mellitus, Type 2
Conditions
Keywords
Precision medicine, Personalized medicine, Genetics
Brief summary
The aim of TRANSLATE is to implement genetic information directly into patient care to improve diagnosis and treatment of non-autoimmune diabetes. This project is the first large-scale implementation of systematic genetic testing within a common, non-communicable, chronic disease in Denmark, and will spearhead efforts to advance personalized medicine in Denmark. The project will contribute to establishing technology, workflow, and evidence on how to implement and communicate actionable genetic information to clinicians and patients in a generalized format. These developments are pivotal for personalized medicine to reach broader clinical application.
Detailed description
The TRANSLATE project is an integrative project with multifaceted goals, that can be broken down into two main columns. The foundation for both columns is the WGS analysis in a clinical diagnostic setting in order to guide patient treatment. Patients are not randomized and the inclusion and exclusion criteria are deliberately broad and minimal, respectively. The first column is the clinical development project, which seeks to complete a novel diagnostic process. This column will develop new pipelines and uncover barriers and challenges associated with gene-based precision medicine to facilitate sustainable implementation of gene-based precision medicine beyond the TRANSLATE project. During the project, we wish to focus on potential barriers against a broad application of gene-based precision medicine in a common disease. These may include: * Challenges pertaining to the selection of variants that are deemed clinically actionable, automation of genetic interpretation/translation, and the feasibility of large-scale precision medicine implementation * Ethical concerns of patients, clinicians, and other technicians with regard to the application and utility of genetic information * Validity and limitations of current computational pipelines for variant calling including the calling of structural variants and aggregate genetic tools * Challenges regarding the interoperability of IT systems and databases nationally in Denmark, specifically how central databases can be linked to clinical end-users * How implementation of genetic analyses affects clinical decision-making and/or clinical trajectories, both qualitatively and quantitatively The second column is a register-based research project in which we will utilize data from the patients to advance gene-based precision medicine. In this column we will both address how to establish comprehensive research infrastructure, as well as answer specific research questions. We will address how to combine and harmonize genetic data with other Danish registry sources. We will use the newly established methodologies to focus on the following research areas with respect to patient stratification, clinical trajectories, complication development, and other clinically relevant outcomes: * Polygenic risk scores * Machine learning algorithms * Combined polygenic and monogenic traits * Non-coding variation * Structural variation, specifically exon deletions and duplications, which have previously been shown as a cause of monogenic diabetes
Interventions
OTHERWhole genome sequencing
Each participant will have WGS performed in order to report on clinically actionable genetic variation in diabetes.
Sponsors
Steno Diabetes Center Copenhagen
BGI Europe
Intomics A/S
Rigshospitalet, Denmark
Danish National Genome Center
Nordsjaellands Hospital
Herlev Hospital
Hvidovre University Hospital
University of Copenhagen
Study design
Observational model
OTHER
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Any case of non-T1D defined as debut \>30 years of age, OR debut \<30 years of age AND negative autoantibodies * Any case of diabetes diagnosed in pregnancy (obstetric departments)
Exclusion criteria
* Age \<18 years * Inability to provide informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Selection of clinically actionable genetic variation in diabetes | Until final patient inclusion (May 2025) + 2 years (May 2027) | Using mixed methods such as gene burden investigations, workgroups, interviews, etc. challenges related to the selection of clinically actionable genetic variants and automation of interpretation/translation will be delineated. |
| Ethical concerns regarding the application and utility of genetic information | Until final patient inclusion (May 2025) + 2 years (May 2027) | The project will address how patients, clinicians, technicians etc. shape their understanding of the utility and challenges associated with gene-based precision medicine using ethnographic methods such as field observations and semi-structured interviews. |
| Validity and limitations of current computational pipelines | Until final patient inclusion (May 2025) + 2 years (May 2027) | By comparing computational and analytical methods, the project will investigate the validity and limitations of different computational pipelines. This includes handling of single nucleotide variants, as well as structural variation. |
| Interoperability of IT systems and databases | Until final patient inclusion (May 2025) + 2 years (May 2027) | The project will address the flow of data to and from clinical end-users, through centralized databases, both with respect to how the data flow is perceived by users and potential challenges, and how interoperability can be improved to enhance clinical utility. The project will also address how to harmonize data from different sources. |
| Impact on clinical decision-making and clinical trajectories | Until final patient inclusion (May 2025) + 2 years (May 2027) | Using mixed methods such as mapping of clinical trajectories through clinical registries and qualitative methods such as interviews, workgroups, etc., the project will investigate how implementation of gene-based precision diabetes impacts clinical decision making. |
Countries
Denmark
Outcome results
None listed