Cohort Profile: Scottish Diabetes Research Network Type 1 Bioresource Study (SDRNT1BIO)

Type 1 diabetes mellitus (T1DM) affects approximately 0.4–0.5% of the population. A 70% increase in prevalent cases of T1DM in those aged under 15 years in Europe between 2005 and 2020 is predicted.1 T1DM continues to be associated with substantial mortality, with an estimated current period life expectancy differential of 11–13 years.2 The main chronic complications include cardiovascular disease (CVD), nephropathy, retinopathy and neuropathy. CVD risk continues to be increased 2–3-fold relative to the general population, and diabetic kidney disease remains a major determinant of early mortality in people with T1DM.3 As detailed in the strategic plans of the main diabetes research funders, research priorities include a better understanding of the determinants of T1DM and its complications including genetic determinants, improved methods for early detection of complications [www.diabetes.org.uk] and the development of sensitive biomarkers for complications [www.jdrf.org]. The availability of large prospective cohorts of patients, well characterized for complications, is pivotal to such research. Accordingly, we established the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) to facilitate a wide range of research including, but not limited to, the following. T1DM is partly genetically determined and more than 50 associated genetic loci have been identified, with the human leukocyte antigen (HLA) region on chromosome 6 having the major role.4 These discoveries yielded insights into the potential pathways causing diabetes, some of which are now being targeted by novel intervention therapies. However, more than 50 known genetic loci for T1DM do not explain all the known heritability, with estimates of missing heritability varying from 20% to 80%.5,6 Among several potential explanations for this ‘missing heritability’ are the existence of rare variants with large effects and the existence of additional, more common variants with effects too low to have been detected by sample sizes used so far. Existing genetic studies of T1DM have been based on around 12 000 cases, which is many times lower than sample sizes in meta-analyses of genome-wide association studies (GWAS) for type 2 diabetes mellitus (T2DM).4 Of note, almost all studies to date are in cohorts of childhood-onset T1DM, despite the fact that almost 50% of T1DM has its onset in adulthood. The largest study to date of older-onset T1DM was limited to evaluation of already known loci in 1212 autoantibody-positive adults with diabetes, in which subtle age of onset effects were found for some loci.7,8 Thus, additional discovery work to detect new T1DM loci is warranted, especially for those with older age of onset. We will conduct genome-wide association studies using the SDRNT1BIO cohort and a background population-representative control set of genotypes from Scotland. Many complications of diabetes are heritable (20–50% for retinopathy and nephropathy), justifying attempts to discover their genetic determinants.9 Few unequivocal replicable genetic associations have been found, so large-scale initiatives are under way although many have greater focus on T2DM than T1DM because of the greater prevalence and larger T2DM cohorts [www.imi-summit.eu]. The GENIE Consortium has focused on nephropathy in T1DM and a JDRF-funded consortium on the genetics of nephropathy in T1DM is currently under way.10 For many other phenotypes of relevance in T1DM, efforts to discover genetic determinants are sparse. For example, there are few genetic data on neuropathy,11 propensity to hypoglycaemia or diabetic ketoacidosis. Thus the GWAS data from the SDRNT1BIO will augment existing international efforts to understand the genetics of macro- and micro-vascular complications of diabetes and will provide novel GWAS studies of neglected traits. Several extremely productive prospective cohort studies of T1DM have yielded much of what we know about the pathogenesis and risk factors for complications and how these differ between T1DM and T2DM. These include the EURODIAB PCS (n = 2787),12 the Pittsburgh EDC (n = 658),13 the DCCT/EDIC (n = 1300),14 ORPS (n = 554)15 WESDR (n around 1000),16 CACTI (n around 656)17 and FinnDiane (n around 4500).18 However, the total sample size and number of incident cases of complications across these cohorts does not provide adequate power for discovery efforts. Larger cohort studies in T1DM, such as the Swedish National Diabetes Register, use regular reporting of risk factors from clinical sites and linkage to routine data but do not currently have any sample collection.19 To fully exploit new ‘omic methods for pathway and biomarker discovery, including lipidomics, metabolomics and genomics, and to develop more precise prediction algorithms for complications that incorporate new biomarkers, further large cohorts of T1DM patients are needed to supplement these existing excellent cohorts. With SDRNT1BIO, we decided to harness Scotland’s e-health care record system and the existence of a unique health care identifier across all records in Scotland, to enable the creation of a cohort in which extensive prospective routine data are automatically captured. The gold-standard biomarker of endogenous insulin production is C-peptide concentrations. Previously it was believed that those with T1DM have no residual insulin secretion. With the development of ultra-sensitive C-peptide assays, there is increasing realization that detectable levels of C-peptide are much more common in T1DM than previously thought.20–22 Exploring the genetic and immunological differences between those with and without detectable C-peptide might yield possible mechanisms for preserving beta cell function and preventing or even reversing T1DM; this is another question being addressed by the SDRNT1BIO.23 Another aspect of diabetes stratification is the improved detection of maturity-onset diabetes of the young (MODY) among those misdiagnosed as having T1DM. Diagnosis of MODY remains difficult and at present it is estimated only around 25% of all cases of MODY are correctly diagnosed.24 The data collected on family history, genotype, C-peptide and auto-antibody status, along with sequencing of potential cases, will allow us to compare the yield of cases from various detection algorithms. The environmental determinants of T1DM remain largely unknown (putative factors include infection, e.g. congenital rubella, caesarean section, older maternal age, Vitamin D deficiency).25 Although prospective cohort studies with data pre-dating onset of diabetes are an ideal design for examining such factors, they are challenging with a disease of relatively low incidence such as T1DM. Nonetheless, the SDRNT1BIO can yield useful information on the role of environment, for example by examining how the pattern of potential risk factors varies with genotype or auto-antibody phenotype. Accordingly we have collected some lifestyle, environment and pre-diagnosis data. For T1DM complications, the SDRNT1BIO and linked e-health record data are being used to explore socioeconomic differentials and the impact of health care activities on complications. The SDRNT1BIO was established with joint funding from the Scottish Chief Scientist Office and Diabetes UK. The study activities, including protocol development and recruitment of participants, were overseen by a Study Steering Committee including a patient representative, the study funders, and lead diabetes consultants from participating Scottish Health Boards. All data and (baseline and prospective) are held at the co-ordinating centre at the University of Edinburgh, UK. Eligibility criteria are summarized in Table 1. We aimed to recruit a representative sample of all adults aged 16 years and older with a clinical diagnosis of T1DM or with monogenic diabetes (i.e. MODY) or with a diagnosis of latent autoimmune disease of adulthood. Inclusion and exclusion criteria for participation in SDRNT1BIO cohort Inclusion and exclusion criteria for participation in SDRNT1BIO cohort The SDRNT1BIO cohort was established using a cross-sectional design for the study fieldwork, with recruitment primarily focused on 10 of 14 NHS Board regions in Scotland (Table 2). The Boards not targeted were excluded because of the envisaged high cost per participant recruited, given the remote geographical location and low population density (i.e. the Shetland, Orkney and Western Islands and Scottish Borders). Health boards in order of contribution to Scotland-wide population with T1DM SE, standard error. Health boards in order of contribution to Scotland-wide population with T1DM SE, standard error. The sampling frame used was the comprehensive SCI-Diabetes electronic health care record in which > 99% of patients with diagnosed diabetes are estimated to be registered. This estimate is based on the fact that 99.5% of general practices nationally are electronically queried nightly for all records with diagnostic codes for diabetes. Diagnostic coding levels are very high for adults because they are required before practices can receive payments under the general practice United Kingdom pay-for-performance programme. Validation against other datasets, such as hospital admissions with diabetes codes, are consistent with this > 99% estimate of coverage.26 Recruitment was primarily undertaken at diabetes outpatient clinics, with some additional recruitment in renal units since end-stage renal disease patients have lower attendance at diabetes clinics. GP-based clinics were included at a few sites of high population density, though at present very few people with T1DM in Scotland are managed solely in primary care. At participating clinics we systematically evaluated each clinic list for the subsequent week, and as many eligible patients as could be seen on the day were invited to take part, on the day or at a subsequent clinic visit. There was sufficient research nurse time for 78% (7593/9731) of all attending eligible patients to be invited, and of these 80.7% (6127/7593) participated. No financial incentive for participation was offered with the exception of travel expenses if a visit outside a routine clinic visit was needed. Table 3A and B shows the distribution of some key characteristics among the SDRNT1BIO recruits compared with the national population from SCI-Diabetes. As shown, the participants are similar to the national population in almost all characteristics. With regard to socioeconomic status, 16% of SDRNT1BIO participants are resident in areas with the most deprived quintile of Scottish Index of Multiple Deprivation (SIMD) scores (a residential area based measure of deprivation) compared with 20% of the total national T1DM population (Table 3B).27 As shown in Table 3B, although we sampled from renal clinics to ensure capture of those with end stage renal disease, the prevalence of dialysis was 1.2% vs 1.5% nationally and slightly fewer were albuminuric (11%) compared with the national prevalence (19%). Comparison of SDRNT1BIO participants with national Scottish population with type 1 diabetes (continuous variables) S, standard deviation; y, years; MDRD, Modification of Diet in Renal Disease; eGFR, 186 x (creatinine in mmol/l/88.4)−1.154 x (age−0.203) x 0.742 (if female) x (1.210 if Black). Comparison of SDRNT1BIO participants with national Scottish population with type 1 diabetes (continuous variables) S, standard deviation; y, years; MDRD, Modification of Diet in Renal Disease; eGFR, 186 x (creatinine in mmol/l/88.4)−1.154 x (age−0.203) x 0.742 (if female) x (1.210 if Black). Comparison of SDRNT1BIO participants with national Scottish population with type 1 diabetes (categorical variables) SE, standard error of mean; ACR, urine albumin to creatinine ratio; y, years; N/A, not applicable. Comparison of SDRNT1BIO participants with national Scottish population with type 1 diabetes (categorical variables) SE, standard error of mean; ACR, urine albumin to creatinine ratio; y, years; N/A, not applicable. Baseline data collection took place between 1 December 2010 and 29 November 2013 inclusive, and comprised a single study visit of approximately 30 minutes. Informed consent was documented for all participants. Participants were asked to complete a self-report questionnaire, and had clinical measures and a blood sample taken. Additionally, patients were asked to provide a urine sample at the study visit and were provided a sample tube to post back a second urine sample later. Table 4 summarizes the items collected. Summary of SDRNT1BIO baseline measures (2011–13) Demographic characteristics • Date of birth • Sex • Ethnicity • Location when diabetes diagnosed Family history of diabetes Diabetes & clinical history • Date of diagnosis • Other health conditions including specific questions on coeliac, rheumatoid and other autoimmune conditions Glucose and insulin management • Start of insulin therapy and current regimen • Date insulin injections started • Current insulin dose • Carbohydrate counting/exchange • Glucose self-monitoring Diabetes acute crises • Ketoacidosis • Hypoglycaemia History of diabetes complications • Kidney dialysis/transplant • Laser therapy to back of the eye • Amputation • Complications affecting legs and/or feet • Diabetic neuropathy diagnosis • Michigan neuropathy scale • Hospital Anxiety and Depression Scale (HADS) – 14 items Lifestyle Alcohol units per week Smoking habits (cigarettes/cigars/pipes) • Current smoker, ex-smoker, non-smoker • times a day • started to • • of • and blood (n = with a • blood in blood in urine sample (n = with a urine (n = with or more Demographic characteristics • Date of birth • Sex • Ethnicity • Location when diabetes diagnosed Family history of diabetes Diabetes & clinical history • Date of diagnosis • Other health conditions including specific questions on coeliac, rheumatoid and other autoimmune conditions Glucose and insulin management • Start of insulin therapy and current regimen • Date insulin injections started • Current insulin dose • Carbohydrate counting/exchange • Glucose self-monitoring Diabetes acute crises • Ketoacidosis • Hypoglycaemia History of diabetes complications • Kidney dialysis/transplant • Laser therapy to back of the eye • Amputation • Complications affecting legs and/or feet • Diabetic neuropathy diagnosis • Michigan neuropathy scale • Hospital Anxiety and Depression Scale (HADS) – 14 items Lifestyle Alcohol units per week Smoking habits (cigarettes/cigars/pipes) • Current smoker, ex-smoker, non-smoker • times a day • started to • • of • and blood (n = with a • blood in blood in urine sample (n = with a urine (n = with or more Summary of SDRNT1BIO baseline measures (2011–13) Demographic characteristics • Date of birth • Sex • Ethnicity • Location when diabetes diagnosed Family history of diabetes Diabetes & clinical history • Date of diagnosis • Other health conditions including specific questions on coeliac, rheumatoid and other autoimmune conditions Glucose and insulin management • Start of insulin therapy and current regimen • Date insulin injections started • Current insulin dose • Carbohydrate counting/exchange • Glucose self-monitoring Diabetes acute crises • Ketoacidosis • Hypoglycaemia History of diabetes complications • Kidney dialysis/transplant • Laser therapy to back of the eye • Amputation • Complications affecting legs and/or feet • Diabetic neuropathy diagnosis • Michigan neuropathy scale • Hospital Anxiety and Depression Scale (HADS) – 14 items Lifestyle Alcohol units per week Smoking habits (cigarettes/cigars/pipes) • Current smoker, ex-smoker, non-smoker • times a day • started to • • of • and blood (n = with a • blood in blood in urine sample (n = with a urine (n = with or more Demographic characteristics • Date of birth • Sex • Ethnicity • Location when diabetes diagnosed Family history of diabetes Diabetes & clinical history • Date of diagnosis • Other health conditions including specific questions on coeliac, rheumatoid and other autoimmune conditions Glucose and insulin management • Start of insulin therapy and current regimen • Date insulin injections started • Current insulin dose • Carbohydrate counting/exchange • Glucose self-monitoring Diabetes acute crises • Ketoacidosis • Hypoglycaemia History of diabetes complications • Kidney dialysis/transplant • Laser therapy to back of the eye • Amputation • Complications affecting legs and/or feet • Diabetic neuropathy diagnosis • Michigan neuropathy scale • Hospital Anxiety and Depression Scale (HADS) – 14 items Lifestyle Alcohol units per week Smoking habits (cigarettes/cigars/pipes) • Current smoker, ex-smoker, non-smoker • times a day • started to • • of • and blood (n = with a • blood in blood in urine sample (n = with a urine (n = with or more were used these were We included the questions from the the Hospital Anxiety and Depression and the used Michigan crises were based on of diabetic and in the 12 and included a measure of For we blood of using the or which was by the and were using the existing and of each were using the or and were using a protocol based on by the Scottish Diabetes Research from participants were at the end of each and The time between sampling and at was and the and range were 2 15 30 to 10 were on to the was and A key in the cohort was to harness the potential of data linkage to routine electronic health care records as a to participants. linkage is in Scotland because the health care records of all patients have a unique health care the Health Index This is at birth for those into Scotland, on with a general care is at the of so almost all with a general All SDRNT1BIO participants were for such linkage and their data have been linked to capture and prospective SCI-Diabetes which data on 99% of patients with diabetes in Scotland and key clinical for diabetes care including primary retinopathy and from and urine are being from a Scotland wide from NHS the Scottish Renal which data on all those in of renal therapy in Scotland since routine data from outpatient attendance hospital and day birth including mortality and Scottish data study day participation To have been with data to the end of for the and and to end 2013 for the with a further linkage The prospective data are with for the Participants are to have if at 1 has without any or or if they have been at their general practice without there or in Scotland. the end of it was possible to that participants were already of those not had no because of At participants were invited to consent for to which as we have not this Participants were invited to consent for having blood and from any clinical to which of participants We have established a for such blood capture for the participants in of the health boards and to this collection nationally as of the To date we for SDRNT1BIO participants. The studies using the of the are now under but we useful set of information from the data. of T1DM has in with more use of insulin blood and we the of insulin management and management among the SDRNT1BIO participants, and associations with and socioeconomic was using the based on at time of into measures of insulin and management were insulin 4 or 4 injections a day or using blood 4 or 4 a and or were at times but were using a (Table were blood at times and were using or had lower than of 4 vs use vs 4 vs and vs All measures by per increase in quintile were for for for and for = for (Table All measures and were associated with lower (Table was lower in those in the more beta per quintile = for age and beta on for We that patient aimed at as in national diabetes to by and Glucose management measures by age and shown are and standard error for and for the other Glucose management measures by age and shown are and standard error for and for the other of management measures to the Scottish Index of Multiple Deprivation are for age and for all of management measures to the Scottish Index of Multiple Deprivation are for age and for all in by management measures = standard error. in by management measures = standard error. The main of the SDRNT1BIO cohort its large the comprehensive and prospective capture of a wide range of health the large set of that the cohort is being its of the national population with T1DM; the high of consent to the high of consent to blood and the low cost of the work given the of data collected. are only a have as of funding to date for and to and for The study was in with the in the of and was by the Research Committee are held under the of the are by the National and for Health and NHS and Scottish Renal The SDRNT1BIO was established to research We to the between use and the data and of linked data. All data are held in an with the study identifier to patient held and to are held on a only to place on the with have undertaken an data A data for for include having a the and power to the question in the the question is already being using the the is a in a research and is being are not but can be to have measures if these are and if the question the unique characteristics of the cohort (i.e. be in a extensive studies be by for but can be as To date have been used for and genome-wide have been used for the of and for The of these are have been used for of These studies with in the Scotland and the of the UK. the study in the place for in a The SDRNT1BIO is of the largest and most comprehensive of from people with type 1 diabetes (T1DM) in and has been shown to be representative of the national population with T1DM. aged 16 years or with T1DM, were from across Scotland between 1 December 2010 and 29 November with a high of consent to include baseline of blood and capture of patients to blood Baseline data of diabetes diagnosis and history of complications and e.g. and from e.g. and blood linkage to routine electronic health care records has and prospective data capture across a number of health care in primary renal outpatient and The SDRNT1BIO has been SDRNT1BIO was established to research are from the study This work was by the Chief Scientist Office and Diabetes and contribution from Scottish Diabetes Research Network to facilitate NHS Scotland, Edinburgh, Diabetes NHS Diabetic University Diabetes Research & & Diabetic and Hospital & and Diabetes University of and Diabetes University of of research and and of and for and for research from and of and of for and research from and The other no of We to the and from the NHS health boards across Scotland for this research study in their We to the participants took the time to in the