Development of oedema is associated with an improved glycaemic response in patients initiating thiazolidinediones: a MASTERMIND study

Abstracts of the 51st EASD Annual Meeting, Stockholm, Sweden, 14–18 September 2015This is the author accepted manuscript. The final version is available from Springer VerlagBackground and aims: Oedema is a common and serious side effect of thiazolidinedione therapy. A stratified medicines approach would aim to give thiazolidinediones to patients likely to have a good glycaemic response but to not develop oedema. We investigated whether oedema was associated with glycaemic response to thiazolidinedione therapy. Materials and methods: We retrospectively studied 11,459 patients initiating a thiazolidinedione from UK primary care data (Clinical Practice Research Datalink), and identified medical records of new oedema in the subsequent twelve months. Response was defined as change in HbA1c at twelve months and was adjusted for baseline HbA1c, baseline BMI, gender and compliance (medication possession ratio). In secondary analyses we restricted oedema classification to patients with concomitant weight gain. As a comparison the same analysis was performed in 13,089 patients initiating a sulfonylurea. Results: The 5% of patients with recorded oedema on thiazolidinediones had a mean (CI) 2.2 (1.1-3.2)mmol/mol greater fall in HbA1c (p3 kg (p< 0.001) and a 3.6 (1.8-5.4)mmol/mol greater fall when weight gain >5 kg (p3 kg (p=0.19). Conclusion: Patients with Type 2 diabetes who develop oedema on initiating thiazolidinediones have an improved glycaemic response, and more severe oedema may be associated with greater reductions in HbA1c. An association between oedema and glycaemic response was not observed in patients initiating sulfonylureas. This supports glycaemic lowering and fluid retention being mediated by a common pathway of thiazolidinedione drug action.Supported by: MRC grant MR-K005707-

Patients who develop oedema on initiating thiazolidinedione therapy have an improved glycaemic response: a MASTERMIND study

Special Issue: Abstracts of the Diabetes UK Professional Conference 2015, ExCeL London, 11–13 March 2015This is the author accepted manuscript. The final version is available from WileyBackground/aim: Oedema is a common and serious side effect ofthiazolidinedione therapy. A stratified medicine approach wouldaim to give thiazolidinediones to patients likely to have a goodglycaemic response but not to develop oedema. We investigatedwhether oedema was associated with glycaemic response tothiazolidinedione therapy.Methods: We studied 10,486 patients initiating a thiazolidinedionefrom Clinical Practice Research Datalink (CPRD), and identifiedmedical records of oedema in the subsequent 12 months. Responsewas defined as change in HbA1c at 12 months and was adjusted forbaseline HbA1c, baseline body mass index, gender and adherence(medication possession ratio). In secondary analyses we restrictedoedema classification to patients with concomitant weight gain. As acomparison the same analysis was performed in 13,089 patientsinitiating a sulfonylurea.Results: The 3% of patients with recorded oedema onthiazolidinediones had a mean (confidence interval) 3 (1.7–4.3)mmol/mol greater fall in HbA1c (p 3kg (p 8kg (p 3kg (p=0.19).Conclusion: Patients with Type 2 diabetes who develop oedemaon initiating thiazolidinediones have an improved glycaemicresponse, and more severe oedema is associated with greaterHbA1c reduction. This supports glycaemic lowering andfluid retention being mediated by a common pathway ofthiazolidinedione drug action

What to do with diabetes therapies when HbA1c lowering is inadequate:add, switch, or continue? A MASTERMIND study

This is the author accepted manuscript. The final version is available from BioMed Central via the DOI in this record.Background: It is unclear what to do when people with type 2 diabetes have had no or a limited glycemic response to a recently introduced medication. Intra-individual HbA1c variability can obscure true response. Some guidelines suggest stopping apparently ineffective therapy, but no studies have addressed this issue. Methods: In a retrospective cohort analysis using the UK Clinical Practice Research Datalink (CPRD), we assessed the outcome of 55,530 patients with type 2 diabetes starting their second or third non-insulin glucose lowering medication, with a baseline HbA1c >58mmol/mol (7.5%). For those with no HbA1c improvement or a limited response at 6 months (HbA1c fall <5.5mmol/mol [0.5%]) we compared HbA1c 12 months later in those who continued their treatment unchanged, switched to new treatment, or added new treatment. Results: An increase or a limited reduction in HbA1c was common, occurring in 21.9% (12,168/55,230), who had a mean HbA1c increase of 2.5mmol/mol (0.2%). After this limited response, continuing therapy was more frequent (n=9,308; 74%) than switching (n=1,177; 9%) or adding (n=2,163; 17%). Twelve months later, in those who switched medication HbA1c fell (-6.8mmol/mol [-0.6%], 95%CI -7.7, -6.0) only slightly more than those who continued unchanged (-5.1 mmol/mol [-0.5%], 95%CI -5.5, -4.8). Adding another new therapy was associated with a substantially better reduction (-12.4mmol/mol [-1.1%], 95%CI -13.1, -11.7). Propensity score matched subgroups demonstrated similar results. Conclusions: Where glucose lowering therapy does not appear effective on initial HbA1c testing, changing agents does not improve glycemic control. The initial agent should be continued with another therapy added.Medical Research Council (MRC)National Institute for Health Research (NIHR

Type 2 Diabetes, Metabolic traits and Risk of Heart Failure:a Mendelian Randomization study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Are the new drugs better? Changing UK prescribing of Type 2 diabetes medications and effects on HbA1c and weight, 2010 to 2016

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Aim: The availability of new glucose‐lowering drugs has changed UK National Institute of Clinical Excellence Type 2 diabetes guidelines, but there has been little evaluation of real‐world use of these drugs, or of the population‐level impact of their use. We examined changes in UK prescribing for patients starting second‐ and third‐line medications, and population‐level trends in glycaemic response and weight change. Methods: We extracted incident second‐ and third‐line oral prescription records for patients with Type 2 diabetes in the UK‐representative Clinical Practice Research Datalink, 2010 to 2016 (n = 68,902). Each year we calculated the proportion of each drug prescribed as the percentage of the total prescribed. We estimated annual mean six‐month HbA1c response and weight change using linear regression, standardised for clinical characteristics. Results: Use of Dipeptidyl peptidase‐4 (DPP4) inhibitors has increased markedly to overtake sulfonylureas as the most commonly prescribed second‐line drug in 2016 (43% vs 34% of total prescriptions compared with 18% v 59% in 2010). Use of sodium‐glucose co‐transporter‐2 (SGLT2) inhibitors has increased rapidly to 14% of second‐line and 27% of third‐line prescriptions in 2016. Mean HbA1c response at six months was stable over time (2016: 13.5 (95% confidence interval 12.8, 14.1) mmol/mol vs 2010: 13.9 (13.6;14.2) mmol/mol, p = 0.21). We found mean weight loss at six months in 2016, in contrast to 2010 where there was mean weight gain (2016: −1.2 (−0.9; −1.5) kg vs 2010: +0.4 (+0.3; +0.5) kg, p < 0.001). Conclusion: The pattern of drug prescribing to manage patients with Type 2 diabetes has changed rapidly in the United Kingdom. Increasing use of DPP4 inhibitors and SGLT2 inhibitors has not resulted in improved glycaemic control but has improved the body weight of patients starting second‐ and third‐line therapy. Acknowledgement: This abstract is submitted on behalf of the MASTERMIND consortium

Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Adherence to oral glucose-lowering therapies and associations with 1-year HbA_1c:A retrospective cohort analysis in a large primary care database

JOURNAL ARTICLEOBJECTIVE: The impact of taking oral glucose-lowering medicines intermittently, rather than as recommended, is unclear. We conducted a retrospective cohort study using community-acquired U.K. clinical data (Clinical Practice Research Database [CPRD] and GoDARTS database) to examine the prevalence of nonadherence to treatment for type 2 diabetes and investigate its potential impact on HbA1c reduction stratified by type of glucose-lowering medication. RESEARCH DESIGN AND METHODS: Data were extracted for patients treated between 2004 and 2014 who were newly-prescribed metformin, sulfonylurea, thiazolidinedione, or dipeptidyl peptidase-4 inhibitors and who continued to obtain prescriptions over 1 year. Cohorts were defined by prescribed medication type, and good adherence was defined as a medication possession ratio ≥0.8. Linear regression was used to determine potential associations between adherence and 1-year baseline-adjusted HbA1c reduction. RESULTS: In CPRD and GoDARTS, 13% and 15% of patients, respectively, were nonadherent. Proportions of nonadherent patients varied by the oral glucose-lowering treatment prescribed (range 8.6% [thiazolidinedione] to 18.8% [metformin]). Nonadherent, compared with adherent, patients had a smaller HbA1c reduction (0.4% [4.4mmmol/mol] and 0.46% [5.0 mmol/mol] for CPRD and GoDARTs, respectively). Difference in HbA1c response for adherent compared with nonadherent patients varied by drug (range 0.38% [4.1 mmol/mol] to 0.75% [8.2 mmol/mol] lower in adherent group). Decreasing levels of adherence were consistently associated with a smaller reduction in HbA1c. CONCLUSIONS: Reduced medication adherence for commonly used glucose-lowering therapies among patients persisting with treatment is associated with smaller HbA1c reductions compared with those taking treatment as recommended. Differences observed in HbA1c responses to glucose-lowering treatments may be explained in part by their intermittent use.A.J.F. and R.R.H. are National Institute for Health Research (NIHR) Senior Investigators and receive additional support from the Oxford NIHR Biomedical Research Centre. M.N.W. was supported by a Wellcome Trust Institutional Strategic Support Award (WT097835MF). E.R.P. holds a Wellcome Trust New Investigator award. The MASTERMIND consortium is funded by the U.K. Medical Research Council MR-K005707-1. The funder of the trial had no role in study design, data collection, data analysis, data interpretation, or writing of the report

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance

Background and aims The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance. Methods and results A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29–4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28–4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03–6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01–3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16–2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09–5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46–4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02). Conclusion We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance

A Quantum Natural Language Processing Approach to Musical Intelligence

There has been tremendous progress in Artificial Intelligence (AI) for music, in particular for musical composition and access to large databases for commercialisation through the Internet. We are interested in further advancing this field, focusing on composition. In contrast to current black-box AI methods, we are championing an interpretable compositional outlook on generative music systems. In particular, we are importing methods from the Distributional Compositional Categorical (DisCoCat) modelling framework for Natural Language Processing (NLP), motivated by musical grammars. Quantum computing is a nascent technology, which is very likely to impact the music industry in time to come. Thus, we are pioneering a Quantum Natural Language Processing (QNLP) approach to develop a new generation of intelligent musical systems. This work follows from previous experimental implementations of DisCoCat linguistic models on quantum hardware. In this chapter, we present Quanthoven, the first proof-of-concept ever built, which (a) demonstrates that it is possible to program a quantum computer to learn to classify music that conveys different meanings and (b) illustrates how such a capability might be leveraged to develop a system to compose meaningful pieces of music. After a discussion about our current understanding of music as a communication medium and its relationship to natural language, the chapter focuses on the techniques developed to (a) encode musical compositions as quantum circuits, and (b) design a quantum classifier. The chapter ends with demonstrations of compositions created with the system.Comment: Pre-publication draft of a chapter to appear in Quantum Computer Music, E. R. Miranda (Ed.

Best practice guidelines for the molecular genetic diagnosis of maturity-onset diabetes of the young

Member of the EMQN MODY group: Gisela GasparAIMS/HYPOTHESIS: Mutations in the GCK and HNF1A genes are the most common cause of the monogenic forms of diabetes known as 'maturity-onset diabetes of the young'. GCK encodes the glucokinase enzyme, which acts as the pancreatic glucose sensor, and mutations result in stable, mild fasting hyperglycaemia. A progressive insulin secretory defect is seen in patients with mutations in the HNF1A and HNF4A genes encoding the transcription factors hepatocyte nuclear factor-1 alpha and -4 alpha. A molecular genetic diagnosis often changes management, since patients with GCK mutations rarely require pharmacological treatment and HNF1A/4A mutation carriers are sensitive to sulfonylureas. These monogenic forms of diabetes are often misdiagnosed as type 1 or 2 diabetes. Best practice guidelines for genetic testing were developed to guide testing and reporting of results