Cardiovascular disease biomarkers are associated with declining renal function in type 2 diabetes

Aims/hypothesis: We investigated whether biochemical cardiovascular risk factors and/or markers of subclinical cardiovascular disease were associated with the development of reduced renal function in people with type 2 diabetes. Methods: A cohort of 1066 Scottish men and women aged 60–74 years with type 2 diabetes from the Edinburgh Type 2 Diabetes Study were followed up for a median of 6.7 years. New-onset reduced renal function was defined as two eGFRs <60 ml−1 min−1 (1.73 m)−2 at least 3 months apart with a > 25% decline from baseline eGFR. Ankle brachial pressure index (ABI), N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT) were measured at baseline. Pulse wave velocity (PWV) and carotid intima media thickness were measured 1 year into follow-up. Data were analysed using Cox proportional hazards models. Results: A total of 119 participants developed reduced renal function during follow-up. ABI, PWV, NT-proBNP and hsTnT were all associated with onset of decline in renal function following adjustment for age and sex. These associations were attenuated after adjustment for additional diabetes renal disease risk factors (systolic BP, baseline eGFR, albumin:creatinine ratio and smoking pack-years), with the exception of hsTnT which remained independently associated (HR 1.51 [95% CI 1.22, 1.87]). Inclusion of hsTnT in a predictive model improved the continuous net reclassification index by 0.165 (0.008, 0.286). Conclusions/interpretation: Our findings demonstrate an association between hsTnT, a marker of subclinical cardiac ischaemia, and subsequent renal function decline. Further research is required to establish the predictive value of hsTnT and response to intervention

Higher baseline inflammatory marker levels predict greater cognitive decline in older people with type 2 diabetes:year 10 follow-up of the Edinburgh Type 2 Diabetes Study

AIMS/HYPOTHESIS: We aimed to determine the longitudinal association of circulating markers of systemic inflammation with subsequent long-term cognitive change in older people with type 2 diabetes. METHODS: The Edinburgh Type 2 Diabetes Study is a prospective cohort study of 1066 adults aged 60 to 75 years with type 2 diabetes. Baseline data included C-reactive protein, IL-6, TNF-α fibrinogen and neuropsychological testing on major cognitive domains. Cognitive testing was repeated after 10 years in 581 participants. A general cognitive ability score was derived from the battery of seven individual cognitive tests using principal component analysis. Linear regression was used to determine longitudinal associations between baseline inflammatory markers and cognitive outcomes at follow-up, with baseline cognitive test results included as covariables to model cognitive change over time. RESULTS: Following adjustment for age, sex and baseline general cognitive ability, higher baseline fibrinogen and IL-6 were associated with greater decline in general cognitive ability (standardised βs = −0.059, p=0.032 and −0.064, p=0.018, respectively). These associations lost statistical significance after adjustment for baseline vascular and diabetes-related covariables. When assessing associations with individual cognitive tests, higher IL-6 was associated with greater decline in tests of executive function and abstract reasoning (standardised βs = 0.095, p=0.006 and −0.127, p=0.001, respectively). Similarly, raised fibrinogen and C-reactive protein levels were associated with greater decline in processing speed (standardised βs = −0.115, p=0.001 and −0.111, p=0.001, respectively). These associations remained statistically significant after adjustment for the diabetes- and vascular-related risk factors. CONCLUSIONS/INTERPRETATION: Higher baseline levels of inflammatory markers, including plasma IL-6, fibrinogen and C-reactive protein, were associated with subsequent cognitive decline in older people with type 2 diabetes. At least some of this association appeared to be specific to certain cognitive domains and to be independent of vascular and diabetes-related risk factors. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-021-05634-w

Serum metabolomic profiles associated with subclinical and clinical cardiovascular phenotypes in people with type 2 diabetes

BACKGROUND: Atherosclerotic cardiovascular diseases (CVD) is the leading cause of death in diabetes, but the full range of biomarkers reflecting atherosclerotic burden and CVD risk in people with diabetes is unknown. Metabolomics may help identify novel biomarkers potentially involved in development of atherosclerosis. We investigated the serum metabolomic profile of subclinical atherosclerosis, measured using ankle brachial index (ABI), in people with type 2 diabetes, compared with the profile for symptomatic CVD in the same population. METHODS: The Edinburgh Type 2 Diabetes Study is a cohort of 1,066 individuals with type 2 diabetes. ABI was measured at baseline, years 4 and 10, with cardiovascular events assessed at baseline and during 10 years of follow-up. A panel of 228 metabolites was measured at baseline using nuclear magnetic resonance spectrometry, and their association with both ABI and prevalent CVD was explored using univariate regression models and least absolute shrinkage and selection operator (LASSO). Metabolites associated with baseline ABI were further explored for association with follow-up ABI and incident CVD. RESULTS: Mean (standard deviation, SD) ABI at baseline was 0.97 (0.18, N = 1025), and prevalence of CVD was 35.0%. During 10-year follow-up, mean (SD) change in ABI was + 0.006 (0.178, n = 436), and 257 CVD events occurred. Lactate, glycerol, creatinine and glycoprotein acetyls levels were associated with baseline ABI in both univariate regression [βs (95% confidence interval, CI) ranged from − 0.025 (− 0.036, − 0.015) to − 0.023 (− 0.034, − 0.013), all p < 0.0002] and LASSO analysis. The associations remained nominally significant after adjustment for major vascular risk factors. In prospective analyses, lactate was nominally associated with ABI measured at years 4 and 10 after adjustment for baseline ABI. The four ABI-associated metabolites were all positively associated with prevalent CVD [odds ratios (ORs) ranged from 1.29 (1.13, 1.47) to 1.49 (1.29, 1.74), all p < 0.0002], and they were also positively associated with incident CVD [ORs (95% CI) ranged from 1.19 (1.02, 1.39) to 1.35 (1.17, 1.56), all p < 0.05]. CONCLUSIONS: Serum metabolites relating to glycolysis, fluid balance and inflammation were independently associated with both a marker of subclinical atherosclerosis and with symptomatic CVD in people with type 2 diabetes. Additional investigation is warranted to determine their roles as possible etiological and/or predictive biomarkers for atherosclerotic CVD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12933-022-01493-w

Serum ferritin and incident cardiometabolic diseases in Scottish adults

BACKGROUND: Iron stores, estimated as ferritin levels, and type 2 diabetes (T2D) have been associated previously, while findings regarding coronary heart disease (CHD) and cerebrovascular disease (CEVD) are still inconclusive. No study has focused on simultaneous evaluation of associations between iron stores and the above cardiometabolic diseases (CMD) in the same population. We aim to evaluate the association between serum ferritin and risk of T2D, CHD and CEVD in Scottish population over a wide range of ferritin levels. METHODS: Longitudinal study in 6,497 participants of the 1995 and 1998 Scottish health surveys, who were followed-up until 2011. Cox regression models were conducted adjusting for age, sex/menopausal status, fibrinogen, GGT levels, smoking, alcohol consumption, total cholesterol, HDL-cholesterol, blood pressure, and BMI. Ferritin was used as continuous (sex/menopausal status-specific Z score) and categorical variable (sex/menopausal status-specific quartiles, quintiles and sextiles). RESULTS: During follow-up, 4.9% of the participants developed T2D, 5.3% CHD, and 2.3% CEVD. By using ferritin quartiles, serum ferritin was positively associated with T2D, CHD and CEVD but only the association with T2D remained after adjustment for covariates [Quartile 4 v. 1: adjusted HR 95% CI 1.59 (1.10–2.34); P = 0.006]. When ferritin sextiles were used (6 v. 1), the ferritin-CEVD association became slightly stronger and significant [adjusted HR 95% CI 2.08 (1.09–3.94); P = 0.024]. CONCLUSIONS: Iron stores relate differently to each CMD. Serum ferritin levels were positively and independently associated with incident T2D, and with incident CEVD if higher cut-off points for high ferritin levels were considered. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12933-022-01450-7

The UK Longitudinal Linkage Collaboration: A trusted research environment for the longitudinal research community

Objectives Our Trusted Research Environment (TRE) provides a centralised infrastructure to pool Longitudinal Population Studies’ (LPS) data and systematically link participants’ routine health, administrative and environmental records. All data are held in a centralised research resource which is now certified by UK Statistics Authority as meeting the Digital Economy Act standard. Approach We have created an unprecedented infrastructure integrating data from interdisciplinary and pan-UK LPS linked to participants’ NHS England records with delegated access responsibilities. Integrated and curated data are made available for pooled analysis within a functionally anonymous DEA and ISO 27001 accredited TRE. We developed a bespoke governance and data curation framework with LPS data managers and Public/participant contributors. New data pipelines are being built with partners at ADRUK and the Office of National Statistics to link non-health records. Our design supports long-term sustainability, linkage accuracy and the ability to link data at both an individual and household level. Results This organisation is a collaboration of >24 LPS with ~280,000 participants. Participants' data are linked to NHS records and geo-coded environmental exposures. This resource is now accessible for public benefit research for bona fide UK researchers. Administrative data including tax, work and pensions, and education are being added to the resource. This data flow is enabled by: (1) a model where TTP processes participant identifiers for many different data owners; (2) creation of a novel longitudinal data pipeline, enabling linkage, data extraction and update of records over time; (3) an access framework where Linked Data Access Panel considers applications on behalf of data owners (e.g., the NHS), with review by a Public Panel and distributing applications to LPS for approval of appropriate data use. Conclusion Our organisation provides a strategic research-ready platform for longitudinal research. We are extending linkages of LPS participants to previously inaccessible datasets. The research resource is positioned to allow researchers to investigate cross-cutting themes such as understanding health and social inequalities, health-social-environmental interactions, and managing the COVID-19 recovery

UK Longitudinal Linkage Collaboration – and the challenges in creating a new Longitudinal Populations Studies linked data resource.

Objectives The UK Longitudinal Linkage Collaboration (UK LLC) is a new, unprecedented infrastructure enabling research into the COVID-19 pandemic. The UK LLC integrates data from >20 UK longitudinal studies with systematically linked health, administrative and environmental records to facilitate cross-disciplinary COVID-19 research for accredited UK based researchers. Approach Bringing together all of the key components that form the UK LLC was a huge challenge that may have only been possible in the midst of the pandemic. First, we collaborated with the Longitudinal Population Studies (LPS) to create and agree how data linkage, data provision and applications to access the UK LLC would work. In parallel, public contributors helped to create fair processing materials. Finally, we worked closely with NHS Digital and other key national data providers to organise approvals for all studies to be linked, and for the UK LLC to have delegated decision-making for research applications. Results We faced a myriad of challenges creating the UK LLC including: • Short timeframe and short-term funding structure – initial funding for six months with an 18-month extension. • Working across >20 different LPS and four nations with different structures for access, consent and data provision. • Lack of capacity at various points in the data pipeline due to the volume of COVID-19 research required and underway across the involved organisations. • Data processing complexities – split data method means no one can see the entire process therefore catching linkage errors requires working across four different organisations. • With such complex data flows it is challenging to find the balance with communications about data to the public – being accurate about what we are doing, but expressing the complexity in lay terms. Conclusion Creating the UK LLC required collaboration with LPS, data providers and researchers. An iterative approach to creating the data application and data provision pipelines was crucial in developing these processes. The UK LLC was built quickly, from initial funding in October 2020 to provisioning data to researchers in December 2021

Comparison of non-traditional biomarkers, and combinations of biomarkers, for vascular risk prediction in people with type 2 diabetes: The Edinburgh Type 2 Diabetes Study

We aimed at comparing the impact of multiple non-traditional biomarkers (ankle brachial pressure index (ABI), N-terminal pro-brain natriuretic peptide (NT-proBNP), high sensitivity cardiac troponin (hs-cTnT), gamma-glutamyl transpeptidase (GGT) and four markers of systemic inflammation), both individually and in combination, on cardiovascular risk prediction, over and above traditional risk factors incorporated in the QRISK2 score, in older people with type 2 diabetes. We conducted a prospective study of 1066 men and women aged 60-75 years with type 2 diabetes mellitus, living in Lothian, Scotland. After 8 years, 205 cardiovascular events occurred. Higher levels of hs-cTNT and NT-proBNP and lower ABI at baseline were associated with increased risk of CV events, independently of traditional risk factors (basic model). The C statistic of 0.722 (95% CI 0.681, 0.763) for the basic model increased on addition of individual biomarkers, most markedly for hs-cTnT (0.732; 0.690, 0.774)). Models including different combinations of biomarkers had even greater C statistics, with the highest for ABI, hs-cTnT and GGT combined (0.740; 0.699, 0.781). Individually, hs-cTnT appeared to be the most promising biomarker in terms of improving vascular risk prediction in people with type 2 diabetes, over and above traditional risk factors incorporated in the QRISK2 score. Combining several non-traditional biomarkers added further predictive value, and this approach merits further investigation when developing cost effective risk prediction tools for use in clinical practice