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The genetics of glycaemic response to GLP-1 receptor agonists in Type 2 diabetes
Proposal
1843
Title of Proposed Research
The genetics of glycaemic response to GLP-1 receptor agonists in Type 2 diabetes
Lead Researcher
Ewan Pearson
Affiliation
University of DundeeDundee DD1 9SY
Funding Source
EU FP7 Innovative medicines Initiative. IMI-DIRECT (
http://www.direct-diabetes.org
).
Potential Conflicts of Interest
Honoraria from Lily, Novo Nordisk, Sanofi, AZ, BI. Paid industry consultancy with AstraZeneca, Grifols, Takeda, Sanofi and Roche.
Data Sharing Agreement Date
16 August 2017
Lay Summary
Approximately 387 million people between the ages of 20 and 79 live with diabetes worldwide, increasing to 642 million by 2040. Following initial lifestyle changes, there is a progressive need to add additional treatment to maintain the blood sugar as close to normal as possible. This usually involves initial treatment with tablets before moving on to injectable treatments such as insulin or a class of drugs called ‘GLP-1 Receptor agonists' or GLP-1RA.
Clinically, glycaemic response to GLP-1RAs is highly variable with some patients benefitting from marked response (assessed by HbA1c reduction and/or weight reduction) while others have disappointing lack of benefit. This is highlighted in the UK ABCD audit of exenatide and liraglutide, where nearly 30% of patients had weight loss (suggesting they were using the drug) but no HbA1c reduction with GLP-1RA treatment. The mechanism for this variability in response is poorly understood. There is a need to understand this variation to better target this effective treatment to the right patients.
How the research will add to medical science or improve patient care?
By understanding the mechanisms underlying this variation we will gain insight into the biological mechanism of action of GLP-1RAs or in biological differences in people's diabetes. Importantly, we will also potentially be able to identify subpopulations who, due to their genetics, are likely to respond well to GLP1-RA and thus should potentially be given these treatments early, or who will respond badly and who therefore should not be given these treatments as the harm is likely to outweigh the risks.
Given the high, and increasing, prevalence of T2DM and increasing use of expensive treatments such as GLP-1RAs if we can find a way to better target these treatments to those who will benefit the most, this will have major impact to patients, to payers and to society.
The aims and objectives of the research?
The overarching aim of this project is to identify clinical and genetic determinants of variation in therapeutic response to GLP-1RAs. Our objectives are:
1. To replicate an initial finding on genetic variants in the GLP-1 receptor
2. To undertake a combined analysis between our existing cohorts and the GSK trial data across all captured variants in the genome (Genome wide association study)
3. To undertake a gene-based rare variant analysis in relation to GLP-1RA response.
How will the research be conducted?
We will use the available clinical trial data on treatment with Albiglutide (GLP-1RA) to define response based upon the HbA1c reduction and weight at 6 months after initiation of treatment. We will explore how clinical parameters impact on this response (e.g. weight, age, sex) and then investigate how an individual's genetics impacts on this treatment response.
Interpretation and communication to patients/public
Results will be published and communicated to patients via patient organisations
Study Data Provided
[{ "PostingID": 1664, "Title": "GSK-GLP114179", "Description": "A Randomized, Open-Label, Parallel-Group, Multicenter Study to Determine the Efficacy and Safety of Albiglutide as Compared With Liraglutide in Subjects With Type 2 Diabetes Mellitus" },{ "PostingID": 2415, "Title": "GSK-GLP114130", "Description": "A Randomized, Double-Blind, Active-Controlled, Parallel-Group, Multicenter Study to Determine the Efficacy and Safety of Albiglutide as Compared With Sitagliptin in Subjects With Type 2 Diabetes Mellitus With Renal Impairment" },{ "PostingID": 2416, "Title": "GSK-GLP112753", "Description": "A Randomized, Double-Blind, Placebo and Active-Controlled, Parallel-Group, Multicenter Study to Determine the Efficacy and Safety of Albiglutide When Used in Combination With Metformin Compared With Metformin Plus Sitagliptin, Metformin Plus Glimepiride, and Metformin Plus Placebo in Subjects With Type 2 Diabetes Mellitus" },{ "PostingID": 3123, "Title": "GSK-GLP112754", "Description": "A randomized, open-label, parallel-group, multicenter study to determine the efficacy and long-term safety of albiglutide compared with insulin in subjects with type 2 diabetes mellitus." },{ "PostingID": 3124, "Title": "GSK-GLP112757", "Description": "A Randomized, Double-blind, Placebo and Active-Controlled, Parallel-group, Multicenter Study to Determine the Efficacy and Safety of Albiglutide Administered in Combination With Metformin and Glimepiride Compared With Metformin Plus Glimepiride and Placebo and with Metformin plus Glimepiride and Pioglitazone in Subjects With Type 2 Diabetes Mellitus" },{ "PostingID": 3126, "Title": "GSK-GLP112755", "Description": "A Randomized, Double-Blind, Placebo-Controlled, Parallel-Group, Multicenter Study to Determine the Efficacy and Safety of Albiglutide When Used in Combination With Pioglitazone With or Without Metformin in Subjects with Type 2 Diabetes Mellitus" },{ "PostingID": 3936, "Title": "GSK-GLP112756", "Description": "A Randomized, Double-Blind, Placebo-Controlled, Parallel-Group, Multicenter Study to Determine the Efficacy and Safety of Two Dose Levels of Albiglutide Compared With Placebo in Subjects With Type 2 Diabetes Mellitus" },{ "PostingID": 19799, "Title": "GSK-GLP116174", "Description": "A long term, randomised, double blind, placebo-controlled study to determine the effect of albiglutide, when added to standard blood glucose lowering therapies, on major cardiovascular events in patients with Type 2 diabetes mellitus" }]
Statistical Analysis Plan
(1) We will first analyse the clinical and genetic determinants of GLP-1RA response by meta-analysing across all albiglutide treatment intervention arms. We will develop a common clinical model, based upon our previous data this is likely to be: HbA1c reduction ~ baseline HbA1c + age + diabetes duration + BMI (+SNP)We will include SNPs individually and together in the model, and will undertake meta-analysis of the model derived betas for the SNPs. As the trials differ in inclusion criteria, and background medication we anticipate using a random effects meta-analysis.(2) We will then take any significant variants identified in (1) forward to evaluate the gene*treatment interaction in the four placebo controlled trials using a random effects meta-analysis of the gene*treatment interaction from each trial. We will also assess the impact of variants identified in (1) in the other available trials e.g. comparing against sitagliptin, pioglitazone, lispro insulin, glargine insulin.(3) We will then examine the effects of variants identified in (1) on the secondary endpoints outlined. Again where combining across placebo controlled trials a random effects meta-analysis of the gene*treatment interaction will be undertaken.(4) In an exploratory analysis we will undertake investigation of genetic variants that alter weight change, pulse and blood pressure change, and change in amylase and lipase in response to Albiglutide intervention. We will follow steps (1) and (2) but with HbA1c reduction replaced by these secondary outcomes.We will undertake steps 1 to 4 for five candidate genetic variants; then undertake GWAS and a gene burden test. For the candidate snp replication a p value of <0.01 will be considered statistically significant. For GWAS and gene burden test, accepted p-value thresholds of p<5x10-8 and p<2x10-6 will be used respectively. PowerFor analysis (1) there are ~2100 indviduals in whom albuglutide treatment is given. Of these we anticipate ~1400 having genetic information.For the candidate (replication SNPs), assuming we are testing 5 independent SNPs, assuming a standard deviation in treatment response of 1%, and MAF of 35% we will have 80% power to detect a difference between genotypes of 0.15%, assuming an additive model and alpha of 0.01.For the GWAS meta-analysis we will have a total n of ~ 2500. This will give us 80% power to detect a variant with an allelic impact of 0.21%, assuming an alpha of 5*10-8.Time to event analysisWe will use cox proportional hazards models of the intention to treat cohort. Our primary analysis will be on the albiglutide intervention group only as power is limited for a formal genotype*treatment interaction. We will follow up any signals identified in the albiglutide arm, in the control arm, and more formally using a test for interaction. For GWAS we will adjust for ethnicity by including the first 3 principal components. For variants that show a large variation in minor allele frequency by ethnic group we will undertake stratified and ethnic specific subgroup analyses. For continuous measures, such as weight, HbA1c, pulse rate and SBP, we will use mixed model for repeated measurements, with treatment group, genotype and genotype*treatment as fixed effects, with individuals having random intercept and slopes. We will evaluate statistically significant results by replication in independent trials and observational data sets, where response is defined as the change from baseline at ~6 months.Significance level.Where we are using SNPs well validated to impact on HbA1c reduction we will use a p-value threshold of 0.05 for the albiglutide treatment arm.For genome wide analyses we will use a p-value for the interaction term of p<5*10-8 as significant. For rare variant burden tests we will use a gene-based p-value for the interaction of p<1*10-6PowerThe primary endpoint occurred in 338 (7%) of 4731 patients at an event rate of 4·57 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an event rate of 5·87 events per 100 person-years in the placebo group (HR 0·78, 95% CI 0·68-0·90).Our primary analysis will be on the ~4187 with DNA treated with Albiglutide. For the common variants in GLP-1R, with MAF of 32%, we will have 80% power, alpha 0.05 to detect a relative risk of 1.4 in variant carriers. This equates to an endpoint occurring in 6% of wildtype individuals and 8% GLP-1R variant carriers. A gene*treatment interaction for this variant (n=8374) will have 62% power to detect an interaction effect of this size.
Publication Citation
Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials Adem Y Dawed, Andrea Mari, Andrew Brown, Timothy J McDonald, Lin Li, Shuaicheng Wang, et al. The Lancet Diabetes and Endocrinology January, 2023
DOI:
https://doi.org/10.1016/S2213-8587
(22)00340-0
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