A UK/Canada Collaboration on the genetics of long-term diabetes complications and their risk factors among people with type 1 diabetes

Lead Research Organisation: University of Edinburgh
Department Name: MRC Human Genetics Unit

Abstract

Over 100,000 Canadians and 380,000 in the UK overall have type 1 diabetes. People with type 1 diabetes require lifelong insulin injections to replace insulin synthesized by specialized cells in their pancreas that have died due to an immune process. Currently there are few treatments to prevent or delay the underlying destruction of insulin producing cells. However recent studies have shown that many people with type 1 diabetes do in fact still produce small amounts of insulin. This is important because these people have less severe diabetes: they require lower doses of insulin; have better control of their blood sugar levels; are at lower risk for the development of low blood sugar; and also importantly at lower risk for long-term complications of diabetes, including eye, kidney and heart diseases which are major health problems. However, we have little understanding of the factors that result in differences in insulin production capacity between people with type 1 diabetes. Genetics provides a unique opportunity to identify causal factors for important biomedical measures, such as varying insulin production in people with type 1 diabetes. We already conducted a pilot study where we identified genetic variations different locations in the genome that are related to insulin production and have shown that residual insulin production is very strongly genetically determined. However we showed that only a small percentage of the genetic contribution is from known genes so that there are important genes still to discover. Furthermore we showed that age at onset of diabetes is one determinant of residual insulin production but that the genes determining age at onset only capture a small percentage of the genetic determination of residual insulin production.
In this project we will use data and samples from ten different studies, with a total of ~12,200 people with type 1 diabetes, to allow us to identify the genetic factors that influence residual insulin production, age at onset and also glycaemic control separating those genes that influence these traits together from those that have specific effects on each trait. It is important to bring the collaboration together in order to maximise the size of the study to make it as powerful as possible and also to ensure standardised approach as that also increases the power for discovery. This would be the largest and most comprehensive study of this topic to date.
Identifying the genetic factors is the first step to understanding the mechanisms, which could ultimately be used to develop new approaches to help preserve insulin production in people with type 1 diabetes. The work will also lead to ways to identify which people with diabetes are most appropriate participants for which clinical trials which will accelerate drug development programmes. Since insulin production is also abnormal in many people with type 2 diabetes, which affects over 2 million Canadians and over 4 million in the UK overall, the discoveries about pancreatic cell function that we will make will also lead to important insights and accelerate development of new treatments for some people with type 2 diabetes.

Technical Summary

The aim of this collaborative project is to understand the genes and pathways underlying variation in residual beta-cell function as measured by C-peptide levels, age at diabetes onset and glycaemic control in type 1 diabetes (T1D). The purpose is to i) yield insights into the biology of beta-cell function, that will inform the development of new therapies to prevent or reverse T1D, ii) to enable stratification of those with diabetes with respect to predicted rate of C-peptide loss iii) to quantify the likely clinical impact of restoring beta cell function or of changing glycaemic control to a given level.
This collaboration will bring together leading researchers from Scotland and Canada; They will combine data from 12,200 people with T1D. The key steps will be: 1) To establish a common analysis plan for conducting genome-wide association studies (GWAS) of these inter-related phenotypes of C-peptide levels, age at onset and HbA1c trajectories. 2)To bring together the cohort specific GWAS results in a meta-analysis thus i)validating previous genotype-phenotype associations for these phenotypes ii)discovering new loci for these traits through a meta-analysis iii) enabling the construction of locus specific and genome wide genotypic scores 3)To use the genotype data in each cohort to compute locus-specific and genome-wide genotypic predictor scores for a range of other phenotypes of interest for which summary GWAS associations statistics are publicly available.4)To use the SNP associations and the genotypic scores to gain greater insight into biological pathways of relevance to beta cell biology and of the causal role of residual beta cell function in complications a number of approaches. 5)These SNP associations and genotypic scores will also be used to i) construct predictive models for C-peptide trajectories ii) quantify the likely impact of restoring beta cell function, or changing glycaemic control, on diabetic complications.

Planned Impact

The purpose of the proposed research is to identify the genetic determinants of some key characteristics that vary between people with a clinical diagnosis of type 1 diabetes. These characteristics to the extent of control of day-to-day blood glucose. Up until now, it has been considered that this has been largely reflecting the day-to-day clinical management of disease. We are now realising that there are inherent including genetic determinates of this control. The aspect of the research that we are trying to understand is why it is that some people with type 1 diabetes continue to have some preserved function of their pancreatic cells whilst others do not. We have already established that this is a strongly genetically determined, in part, trait and we will try to understand the genetic determinants of this here and what pathways those genetic determinants operate through. Accordingly, the key impact of our research will be on, first of all, a primary understanding of the mechanisms through which glycaemic control occurs in diabetes and through which the preservation of pancreatic function occurs. If we can understand the pathways leading to these traits then that leaves open the possibility of informing design of new molecules for intervening on these pathways, i.e. new drug development.
The long term impact of our work should be to contribute towards the development of therapeutics that may help to preserve pancreatic function in people with type 1 diabetes or to reverse its loss or even to prevent its loss in the first place.
Impacts of our work should be on the scientific community in a greater understanding of the pathogenesis of type 1 diabetes. Secondly, on the drug development industry in contributing important data on pathways enabling and fostering new molecule identification. Thirdly, on clinical understanding of variation in the clinical course of diabetes so that, for example, it may be possible to consider that some people with a heavy genetic load predisposing them to more brittle type of diabetes would have more intensive management. Fourthly, clinical trialists who might choose to use genotypic information for oversampling the most as risk persons into clinical trials and for estimating likely downstream benefits on complications of modifying beta cell function or glycaemic control. . Finally, and most importantly, the community of people with diabetes itself who will benefit from understanding that there are important genetic factors that they cannot control that may mean that they have less easy or more easy to control diabetes. People with diabetes should also benefit if and when therapeutics are developed that help to modulate the course of their disease that would be informed by the research described here. Of importance is that our understanding of both type 1 and type 2 diabetes should be progressed by this research so people with either type of diabetes may benefit.

Publications

10 25 50
 
Description Collaboration on the risk factors and genetics of long-term diabetes complications among people with type 1 diabetes 
Organisation The Hospital for Sick Children (SickKids)
Department MICe Toronto
Country Canada 
Sector Academic/University 
PI Contribution This collaboration brings together the largest datasets and biobanks for the collection for residual beta-cell function, measured as c-peptide. Specifically, it will draw on the Scottish Diabetes Research Network T1BIO Resource (SDRNT1BIO), one of the largest available collections of samples and data of people with T1D, and on the landmark clinical trial, the DCCT/EDIC Study with its clinical follow up phase, along with 9 other smaller cohorts with a final sample size of 12,250. It involves conducting cohort specific GWAS, meta-analysis and bioinformatics analyses. The Collaboration is led by Paterson and Bull (Canada) and Colhoun and McKeigue (Scotland). Colhoun and McKeigue bring the largest collection of data into this collaboration and their expertise on Bayesian modelling.
Collaborator Contribution Paterson is a Senior Scientist in the Genetics and Genome Biology Program, and Co-director of the Statistical Analysis Facility of The Centre for Applied Genomics (TCAG; tcag.ca), both at the Research Institute of the Hospital for Sick Children, Toronto, Canada. He has expertise in the design and analysis of genetic studies. Bull is Senior Scientist in the Sinai Health System and Professor of Biostatistics, University of Toronto. She has developed innovative statistical methods such as resampling to address selection bias, regional regression test statistics for genetic association, and on-going development of joint models to integrate longitudinal risk factors and time-to-event outcomes with genetic variation.
Impact We have achieved our milestones regarding the GWAS meta-analysis and have drafted a publication that will be submitted shortly. We also presented an abstract on the results at ASHG 2022, titled "Multiple HLA haplotypes and a variant altering immunogenicity of minor histocompatibility antigen epitopes encoded by CTSH are associated with age at type 1 diabetes diagnosis". The functional analyses are underway and will be completed later this year. We have recently been granted a one year no cost extension to March 2024 to complete the remaining objectives.
Start Year 2020
 
Description Collaboration on the risk factors and genetics of long-term diabetes complications among people with type 1 diabetes 
Organisation University of Toronto
Country Canada 
Sector Academic/University 
PI Contribution This collaboration brings together the largest datasets and biobanks for the collection for residual beta-cell function, measured as c-peptide. Specifically, it will draw on the Scottish Diabetes Research Network T1BIO Resource (SDRNT1BIO), one of the largest available collections of samples and data of people with T1D, and on the landmark clinical trial, the DCCT/EDIC Study with its clinical follow up phase, along with 9 other smaller cohorts with a final sample size of 12,250. It involves conducting cohort specific GWAS, meta-analysis and bioinformatics analyses. The Collaboration is led by Paterson and Bull (Canada) and Colhoun and McKeigue (Scotland). Colhoun and McKeigue bring the largest collection of data into this collaboration and their expertise on Bayesian modelling.
Collaborator Contribution Paterson is a Senior Scientist in the Genetics and Genome Biology Program, and Co-director of the Statistical Analysis Facility of The Centre for Applied Genomics (TCAG; tcag.ca), both at the Research Institute of the Hospital for Sick Children, Toronto, Canada. He has expertise in the design and analysis of genetic studies. Bull is Senior Scientist in the Sinai Health System and Professor of Biostatistics, University of Toronto. She has developed innovative statistical methods such as resampling to address selection bias, regional regression test statistics for genetic association, and on-going development of joint models to integrate longitudinal risk factors and time-to-event outcomes with genetic variation.
Impact We have achieved our milestones regarding the GWAS meta-analysis and have drafted a publication that will be submitted shortly. We also presented an abstract on the results at ASHG 2022, titled "Multiple HLA haplotypes and a variant altering immunogenicity of minor histocompatibility antigen epitopes encoded by CTSH are associated with age at type 1 diabetes diagnosis". The functional analyses are underway and will be completed later this year. We have recently been granted a one year no cost extension to March 2024 to complete the remaining objectives.
Start Year 2020
 
Description Briefing with dabetes charity and patient representatives 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Patients, carers and/or patient groups
Results and Impact Event hosted by Juvenile Diabetes Research Foundation at which people with diabetes and donors met with my research team and we briefed them on the research work we do in diabetes includng the genetics work that s the subject of ths award
Year(s) Of Engagement Activity 2021