Cohort Profile: Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS)

The prevalence of diabetes worldwide has been steadily increasing over the past 20 years. In 1997 it was estimated to be 124 million,1 in 2015 it was estimated to be 415 million among 20–70 year olds, and this is expected to rise to 642 million by 2040.2 In the UK, an estimated 4 million people have diabetes either diagnosed or undiagnosed.2 This represents a significant burden on health care resources,3 particularly given that type 2 diabetes (T2D) is associated with comorbidities including obesity,4 cardiovascular disease,5 chronic kidney disease6 and neuropathy.7 T2D is a complex disorder, caused by a combination of environmental and genetic factors.8 Before the first genome-wide association study (GWAS) was conducted for T2D in 2007,9 very few genetic loci were known to be involved with T2D. However, linkage and candidate-gene association studies have often failed to replicate findings through lack of power and inadequate knowledge of the underlying biological pathways.10,11 Diabetes Audit and Research in Tayside Scotland (DARTS) started in 1996 as a joint collaboration between the University of Dundee’s Department of Medicine and Medicines Monitoring Unit (MEMO), three Tayside Health Care Trusts (at Ninewells Hospital and Medical School, Perth Royal Infirmary and Stracathro Hospital) and a group of Tayside general practitioners (GPs) with a special interest in diabetes care.12 Initially supported by the Scottish Home and Health Department, the Wellcome Trust, the Robertson Trust and Tenovus Tayside, the aim of the study was to identify all patients with diabetes within the wider Tayside region, through electronic record linkage, in order to improve health care over and above that which was practical through existing general practice lists alone. In 1998, consenting patients within this electronic database were recruited to the Genetics of DARTS (GoDARTS) study and invited to provide a blood sample for DNA extraction, for research purposes. At the same time, they were invited to provide phenotypic data (clinical and lifestyle factors), through questionnaires and clinical examination. This resource was intended to help identify the relative contribution of specific genetic and environmental factors that are associated with disease onset, progression and response to treatment.10,11 Patients from the Tayside region of Scotland (n = 391 274 on 1 January 199612) were added to the DARTS register, for clinical purposes, through electronic record linkage on the basis of having diabetes mellitus according to primary and/or secondary care data sources. These included hospital diabetes clinics, mobile diabetes eye units, diabetes prescription databases, the Tayside regional biochemistry database and all diabetes-related hospital discharge records. This electronic record linkage technique has a sensitivity of 97% and is continually being updated, creating a longitudinal dataset of clinical data which is manually validated by a dedicated team of clinicians.12 Patients with T2D, which comprises around 90% of all diabetes cases, were invited to participate in the GoDARTS study either at diabetes or eye screening clinics or through their GP. For the pilot phase of the study (GoDARTS1), 2763 patients with T2D were recruited from December 1998 to October 2004. This phase was used to test recruitment processes and the ability to anonymously link patient clinical data from electronic records to the study, and was funded by Tenovus Tayside. As this was the primary aim of the pilot phase, only blood samples were taken at the point of recruitment and no baseline data were recorded. From October 2004 to May 2009, a second collection (GoDARTS2) was undertaken as part of the Wellcome Trust United Kingdom Type 2 Diabetes Case-Control Collection (WTCCC). A total of 16 146 people were recruited in this phase, including 7989 patients with T2D and 8157 matched healthy controls. We initially invited five matched non-diabetic controls per case from the corresponding GP practice; however, after initial success, this was reduced to two controls per case and on average one of the invited controls accepted. This incidentally included 1292 patients with T2D who had already been recruited in the GoDARTS1 phase. Baseline clinical and lifestyle measurements (Table 1) were recorded for all patients recruited in GoDARTS2. From October 2009 until 2015, an extension to the WTCCC project was granted (GoDARTS3), with 1342 patients with T2D being recruited during this time. Some of these participants had also been recruited to GoDARTS1 (n = 20), GoDARTS2 (n = 513) or both (n = 120), where baseline data did not exist or original DNA quality was poor (Figure 1). This gives a current total GoDARTS cohort of 18 306 participants, 10 149 of whom have T2D ( ∼ 44.8% of the DARTS study, representing the diabetic population in Tayside) and 8157 of whom were healthy controls at baseline. Summary of baseline data collected and comparison of response rates between cases and controls in GoDARTS n/a, not available. aBaseline data only available in participants recruited in GoDARTS3. bResponse rate calculated according to the number of positive responses to the main question. cResponse rate calculated according to the number of positive responses to present and/or past smoking status. A venn diagram showing the overlap in patient recruitment between GoDARTS1, GoDARTS2 and GoDARTS3. Currently the cohort is in the early stages of GoDARTS4, the fourth phase of the study. In this phase, recruitment is continuing through a number of initiatives including the Scottish Health Research Register (SHARE)/Scottish Diabetes Research Network (SDRN), the Genetics of SHARE (GoSHARE) and GoDARTS-Scotland. SHARE/SDRN is a register of patients in Scotland who want to participate in medical research and have provided consent for their electronic medical records to be used for research purposes [http://www.share-sdrn.org]. GoSHARE is a parallel project which additionally aims to get permission to collect spare blood from people attending for routine clinical tests at hospital or GP clinics, that would otherwise to go to waste after the necessary tests had been performed [http://www.goshare.org.uk/]. Since the aim is to involve everyone who is resident in the Tayside area, this will inevitably include people with T2D, and they will contribute to the GoDARTS study. GoDARTS Scotland is a sub-study specifically recruiting people who have been diagnosed with T2D in the past 2 years in order to study response to therapies, including metformin. At the point of recruitment, all participants in GoDARTS provide, by invitation, informed consent for their data to be used for research purposes and explicit consent for use in collaboration with industry. This includes allowing their baseline data to be linked anonymously to individual patient medical records including laboratory data, hospital admissions and Scottish Care Information – Diabetes (SCI-Diabetes) data. SCI-Diabetes is a shared electronic patient record which can be accessed by health professionals and researchers to aid the treatment of diabetes patients in Scotland. In this way, longitudinal data can be accessed relating to routine diabetes management, for example glycosylated haemoglobin (HbA1c), fasting insulin and fasting glucose, as well as previous patient diagnoses including diabetic complications. Furthermore, ∼ 95% of patients have consented to being contacted for future studies, aiding research beyond T2D. As patients attend a baseline clinic at recruitment, initial measurements are cross-sectional. However, the use of electronic record linkage, which automatically updates patient details and grants access to NHS data as far back as 1987, makes GoDARTS a longitudinal cohort. This is made possible through the use of the community health index (CHI) number, which is a unique numerical identifier issued to each patient on first registration with a GP or admission to a hospital in Scotland. Around 96% of the UK population are estimated to be registered with a GP.13 The CHI is a 10-digit number consisting of six digits corresponding to the patient’s date of birth (DDMMYY), two digits randomly generated, one digit corresponding to the patients gender (odd for males, even for females) and one check digit. The CHI number links to live databases which are constantly being updated, such as the Scottish Morbidity Record (SMR) providing data on primary and secondary diagnoses for patients discharged from hospital since 1980, the Tayside echocardiography database providing data on all echocardiograms performed at Ninewells Hospital since 1994, the General Registrar’s Office providing mortality data since 1998, the biochemistry database listing all assays performed since 1981 and a database containing all prescriptions dispensed since 1989. This allows identification of an up-to-date record of every individual’s health care processes and outcomes and linkage of corresponding datasets. An anonymization process converts the CHI into a study pro-CHI, to protect the identities and confidentiality of individuals while retaining the ability to link patient data across multiple datasets. For GoDARTS1, only blood samples were taken for DNA extraction as this was a pilot phase used to test the ability to link electronic health records anonymously to genetic data. For GoDARTS2 and GoDARTS3, participants completed a lifestyle questionnaire and consented to baseline measurements being recorded at recruitment (Table 1). In addition, during GoDARTS3 urine samples ( ∼ 80% of recruits) were taken for proteomic and metabolomics analysis and RNA ( ∼ 30% of recruits) was extracted from blood samples. The lifestyle questionnaire contains items relating to smoking history (present and past status, along with amount and age started where applicable), as well as level of physical activities in three common locations (work/education, travel and home life) over three different time periods in life (recently, past 10 years and youth). In addition, women were asked about their menopausal history. Baseline observations were recorded and included height, weight and waist measurements, as well as heart rate and blood pressure. The patient’s recruitment information was recorded including ethnicity, screening location, confirmation of T2D and medication history, as well as family history of diabetes and whether the patient had previously participated in GoDARTS. As baseline data were only recorded for participants recruited in GoDARTS2 and GoDARTS3, there are 1451 participants who were only involved in GoDARTS1 (Figure 1) and do not have these data. Furthermore, there are 17 healthy control participants from GoDARTS2 who are missing baseline data, meaning that a total of 16 838 patients have these available, including 8698 cases and 8140 controls. As well as phenotypic data, genetic data are available for 8564 T2D cases (Figure 2) and 4586 controls (Figure 3) after quality control. Samples have been genotyped across five platforms. GWAS data have been obtained for 7857 T2D cases and 1108 controls, using the Affymetrix Genome-Wide Human SNP Array 6.0 and the Illumina HumanOmniExpress. The Affymetrix GWAS chip contains 932 979 single nucleotide polymorphisms (SNPs), and the Illumina GWAS chip contains 731 296. This has allowed for imputation of additional and missing genotypes by SHAPEIT14 and IMPUTE215 using the 1000 Genomes reference panel.16 In addition, 707 T2D cases and 3478 controls have been genotyped using custom genotyping arrays from Illumina. These include the Immunochip, Cardio-Metabochip (Metabochip) and Human Exome array. The Immunochip contains 196 524 genetic markers from loci that have previously been associated with at least one of 13 autoimmune diseases, including T1D,17 and the Metabochip contains 196 725 SNPs from loci that have prior evidence of association with T2D, coronary artery disease/myocardial infarction and 21 related traits.18 The specific criteria by which markers on the Cardio-Metabochip and the Immunochip have been chosen makes these platforms a cost-effective means of replicating and fine-mapping known loci and discovering novel loci by virtue of overlapping biological mechanisms between the related traits. The Human Exome Array contains 247 870 genetic markers from across the exome, allowing for studies to focus on identifying protein-altering variants.19 A venn diagram showing the overlap of T2D cases genotyped between different platforms. Overall, 8564 cases out of a possible 10 149 have been genotyped on at least one platform, with 7857 having genome-wide data. A venn diagram showing the overlap of controls genotyped between different platforms. Overall, 4586 controls out of a possible 8157 have been genotyped on at least one platform, with 1108 having genome-wide data. Baseline clinical and demographic statistics are summarized in Table 2. Overall, 53.33% of the cohort are male, which is similar to the proportion represented in DARTS (52.83%), with the proportion being higher in cases (56.38%) compared with controls (50.08%). The majority of the cohort are Caucasian (99.70%) and the median age at recruitment was higher in cases (67 years) compared with controls (60 years). This observation is also apparent when the cases and controls are further dichotomized into males (66 vs 62 years) and females (68 vs 58 years). The cohort contains data on a number of continuous traits known to be associated with T2D. For example, median body mass index (BMI) (30.6 vs 26.6 kg/m2), resting heart rate (1st = 73 vs 68 bpm), creatinine (89 vs 87 µmol/l) and triglyceride (1.880 vs 1.315 mmol/l) levels were all higher in cases compared with controls. Furthermore, there was a higher proportion of past smokers among those with T2D (63.14% vs 53.56%). Comparison between cases and controls in baseline measurements Median values given for all continuous data. As of 2014, mortality data have shown that the number of deaths at 9 years after recruitment was 2587 out of 10 149among the cases and the Kaplan–Meier survival probability is 70.0%, whereas among the controls the number of deaths was 851 out of 8157 and the Kaplan–Meier survival probability is 88.2% (Figure 4). Control group mortality data do not go beyond this, as recruitment of controls did not begin until GoDARTS2 (approximately 7 years after the start of GoDARTS1); however, the number of deaths after 16 years among the cases was 2941 (out of 10 149) with a Kaplan–Meier survival probability of 53.5%. A Kaplan-Meier plot comparing survival rate since baseline recruitment in cases and controls. According to SCI-Diabetes data, the number of people initially recruited as controls at baseline, but who went on to develop diabetes, is 650 (out of 8157) and the Kaplan–Meier cumulative incidence probability is 8.3% (Figure 5). Also captured were self-reported physical activity data, and these can be seen to successfully stratify the effect of the fat mass and obesity-associated protein gene (FTO) risk allele, rs9939609, where the genetic association with BMI is largely attenuated in active individuals, as has been observed in large meta-analyses (Figure 6). A Kaplan-Meier cumulative incidence plot of diabetes in the GoDARTS baseline controls group. A plot showing that increased physical activity successfully stratifies the association of the obesity risk allele rs9939609 in with studies have been using GoDARTS either as the primary study cohort or as part of a or The is a of studies, in all of which GoDARTS has been A and up-to-date of studies can be at GoDARTS in the with first study being in At this time candidate-gene studies were and these were particularly in replicating at the which had previously been associated with a of including T2D. In two and in were shown to have on body with the associated with BMI and the associated with higher This provided an for previous between this gene and findings were with to T2D and with analysis the effect of with these in to the risk effect of In addition, was shown to have an effect to with to and weight in studies similar in the related with and an association at with reduced In the GoDARTS study part of the UK T2D collection which the main cohort for the This involved studies traits including and in to T2D. of the first studies using the an association in the gene with This effect was observed from age 7 years and related study at the gene with BMI and obesity among GoDARTS was involved in the the identification of for type 2 diabetes, including the first of and and risk for and also the original of the association of the gene with candidate-gene studies have also been conducted to effect in T2D, as by the identification of the traits have also been with 10 novel loci associated with fasting fasting and associated with levels after In to GWAS of traits and T2D GoDARTS has the use of electronic medical records for the study of This was initially used to study response to and As part of the GoDARTS as a cohort for the GWAS of response to and The analysis a novel association of response to at a including the which provided to the of of this the GoDARTS cohort was the main cohort for a large Genetics study that a in to be associated with response to in GoDARTS include response to and and to and of the GoDARTS study to the Tayside echocardiography database has allowed the identification of genetic associated with as well as the association of both ( and ( levels with risk of heart From around the focus of studies has from genome-wide analysis to of these genotyping with the This has been in the and fine-mapping of loci in and cardiovascular In 17 novel T2D have been and a further genetic have and to identify the has been seen in coronary artery with loci being and traits have also been with loci being with fasting fasting glucose, and that has been used is and studies using the Illumina Exome This has been used to within the protein region of the which are to of the missing in common to their protein-altering polymorphisms in these are to be and the biological can be study Exome chip genotyping in GoDARTS to the in and are associated with triglyceride levels and reduced risk of coronary artery disease in have a effect on risk and reduced related to and have successfully a large chip study has that not a large in T2D In GoDARTS has been used in studies to the between a and This has been used to a for and to out a effect between and in In addition, and have been in studies have been and a of disease can be in Table Summary of using the GoDARTS cohort coronary artery T2D, type 2 The main of GoDARTS large 10 149 participants with T2D ( ∼ of people with T2D in Tayside) and 8157 the of genetic and phenotypic the ability to link patient genetic and baseline data to routine electronic medical and the existing consent for use of these for research and for future for possible research the for recruitment by for future has allowed further studies to of these is an project that will be participants for and related to identify possible risk factors As a the GoDARTS cohort is in longitudinal phenotypic data, such as and In the linkage of the study to individual electronic medical which are constantly updated, means the cohort is not by that can longitudinal This linkage is made possible through the use of the CHI number which allows patient data to The of a large of clinical and demographic data allows a large of diabetes-related to be on both genome-wide and and also a means to control for common such as age and blood pressure. The large number of samples recruited at baseline T2D cases and the power with which to identify genetic to both as a cohort and as part of Furthermore, RNA has been collected from patient blood which will gene studies to be conducted in the A of the GoDARTS cohort is the missing baseline data of GoDARTS1 patients who were not recruited in GoDARTS1 or 2. This is to GoDARTS1 being a pilot phase of the study, and baseline data were not collected at this However, linkage is possible for these samples. Patients were also not recruited at the point of which in the of disease on the samples the lifestyle questionnaire that was to As this was by the physical smoking and menopausal history are to information about this cohort can be at to the dataset is available to researchers worldwide and access with the general of the are by the details on the and collaboration process can be at in a GoDARTS was in 1998 in order study the type 2 diabetes (T2D) diabetes and patient response to The study is a of the Diabetes Audit and Research in Tayside Scotland study, which was to identify all patients within the Tayside with diabetes, through electronic record linkage, to provide care over and above existing As of 2014, the study has 18 306 participants of whom 10 149 have T2D and 8157 are controls. Baseline data are available for 16 838 cases and 8140 and 8564 T2D cases and 4586 controls have genetic data. Baseline data collection includes a lifestyle questionnaire containing items on physical smoking history, and menopausal history for In addition, clinical observations were recorded and blood and urine samples were Baseline data are linked to existing NHS providing mortality and data by electronic record linkage to has been provided by ∼ 95% of participants to be possible in future Information on collaboration and data access can be at A of GoDARTS can be at The Wellcome Trust United Kingdom Type 2 Diabetes Control Collection was funded by the Wellcome Trust and as part of the has from the Wellcome Trust to develop the GoDARTS cohort. a and are of the which is funded by the and are supported by this and are supported by We are to all the participants in this study, the general the Scottish of Care for their help in recruiting the participants and to the which includes and laboratory research and The study with the of We the of the Health University of for and the data and NHS Tayside, the original data of

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