Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials

Background: In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. We therefore aimed to identify genetic variants associated with glycaemic response to GLP-1 receptor agonist treatment. Methods: In this genome-wide analysis we included adults (aged ≥18 years) with type 2 diabetes treated with GLP-1 receptor agonists with baseline HbA1c of 7% or more (53 mmol/mol) from four prospective observational cohorts (DIRECT, PRIBA, PROMASTER, and GoDARTS) and two randomised clinical trials (HARMONY phase 3 and AWARD). The primary endpoint was HbA1c reduction at 6 months after starting GLP-1 receptor agonists. We evaluated variants in GLP1R, then did a genome-wide association study and gene-based burden tests. Findings: 4571 adults were included in our analysis, of these, 3339 (73%) were White European, 449 (10%) Hispanic, 312 (7%) American Indian or Alaskan Native, and 471 (10%) were other, and around 2140 (47%) of the participants were women. Variation in HbA1c reduction with GLP-1 receptor agonists treatment was associated with rs6923761G→A (Gly168Ser) in the GLP1R (0·08% [95% CI 0·04–0·12] or 0·9 mmol/mol lower reduction in HbA1c per serine, p=6·0 × 10−5) and low frequency variants in ARRB1 (optimal sequence kernel association test p=6·7 × 10−8), largely driven by rs140226575G→A (Thr370Met; 0·25% [SE 0·06] or 2·7 mmol/mol [SE 0·7] greater HbA1c reduction per methionine, p=5·2 × 10−6). A similar effect size for the ARRB1 Thr370Met was seen in Hispanic and American Indian or Alaska Native populations who have a higher frequency of this variant (6–11%) than in White European populations. Combining these two genes identified 4% of the population who had a 30% greater reduction in HbA1c than the 9% of the population with the worse response. Interpretation: This genome-wide pharmacogenomic study of GLP-1 receptor agonists provides novel biological and clinical insights. Clinically, when genotype is routinely available at the point of prescribing, individuals with ARRB1 variants might benefit from earlier initiation of GLP-1 receptor agonists. Funding: Innovative Medicines Initiative and the Wellcome Trus

Group-wise sufficient dimension reduction with principal fitted components

Sufficient dimension reduction methodologies in regressions of Y on a p-variate X aim at obtaining a reduction R(X) ∈ Rᵈ, d ≤ p, that retains all the regression information of Y in X. When the predictors fall naturally into a number of known groups or domains, it has been established that exploiting the grouping information often leads to more effective sufficient dimension reduction of the predictors. In this article, we consider group-wise sufficient dimension reduction based on principal fitted components, when the grouping information is unknown. Principal fitted components methodology is coupled with an agglomerative clustering procedure to identify a suitable grouping structure. Simulations and real data analysis demonstrate that the group-wise principal fitted components sufficient dimension reduction is superior to the standard principal fitted components and to general sufficient dimension reduction methods.Kofi P. Adragni, Elias Al-Najjar, Sean Martin, Sai K. Popuri, Andrew M. Rai

Statistical challenges of high-dimensional data

Modern applications of statistical theory and methods can involve extremely large datasets, often with huge numbers of measurements on each of a comparatively small number of experimental units. New methodology and accompanying theory have emerged in response: the goal of this Theme Issue is to illustrate a number of these recent developments. This overview article introduces the difficulties that arise with high-dimensional data in the context of the very familiar linear statistical model: we give a taste of what can nevertheless be achieved when the parameter vector of interest is sparse, that is, contains many zero elements. We describe other ways of identifying low-dimensional subspaces of the data space that contain all useful information. The topic of classification is then reviewed along with the problem of identifying, from within a very large set, the variables that help to classify observations. Brief mention is made of the visualization of high-dimensional data and ways to handle computational problems in Bayesian analysis are described. At appropriate points, reference is made to the other papers in the issue

Synthesis and Pharmacological Characterization of C4_β‑Amide-Substituted 2‑Aminobicyclo[3.1.0]­hexane-2,6-dicarboxylates. Identification of (1<i>S,</i>2<i>S,</i>4<i>S,</i>5<i>R,</i>6<i>S</i>)‑2-Amino-4-[(3-methoxybenzoyl)­amino]­bicyclo[3.1.0]­hexane-2,6-dicarboxylic Acid (LY2794193), a Highly Potent and Selective mGlu₃ Receptor Agonist

Multiple therapeutic opportunities have been suggested for compounds capable of selective activation of metabotropic glutamate 3 (mGlu₃) receptors, but small molecule tools are lacking. As part of our ongoing efforts to identify potent, selective, and systemically bioavailable agonists for mGlu₂ and mGlu₃ receptor subtypes, a series of C4_β-N-linked variants of (1<i>S</i>,2<i>S</i>,5<i>R</i>,6<i>S</i>)-2-amino-bicyclo­[3.1.0]­hexane-2,6-dicarboxylic acid <b>1</b> (LY354740) were prepared and evaluated for both mGlu₂ and mGlu₃ receptor binding affinity and functional cellular responses. From this investigation we identified (1<i>S</i>,2<i>S</i>,4<i>S</i>,5<i>R</i>,6<i>S</i>)-2-amino-4-[(3-methoxybenzoyl)­amino]­bicyclo­[3.1.0]­hexane-2,6-dicarboxylic acid <b>8p</b> (LY2794193), a molecule that demonstrates remarkable mGlu₃ receptor selectivity. Crystallization of <b>8p</b> with the amino terminal domain of hmGlu₃ revealed critical binding interactions for this ligand with residues adjacent to the glutamate binding site, while pharmacokinetic assessment of <b>8p</b> combined with its effect in an mGlu₂ receptor-dependent behavioral model provides estimates for doses of this compound that would be expected to selectively engage and activate central mGlu₃ receptors in vivo

Synthesis and Pharmacological Characterization of C4_β‑Amide-Substituted 2‑Aminobicyclo[3.1.0]­hexane-2,6-dicarboxylates. Identification of (1<i>S,</i>2<i>S,</i>4<i>S,</i>5<i>R,</i>6<i>S</i>)‑2-Amino-4-[(3-methoxybenzoyl)­amino]­bicyclo[3.1.0]­hexane-2,6-dicarboxylic Acid (LY2794193), a Highly Potent and Selective mGlu₃ Receptor Agonist

Multiple therapeutic opportunities have been suggested for compounds capable of selective activation of metabotropic glutamate 3 (mGlu₃) receptors, but small molecule tools are lacking. As part of our ongoing efforts to identify potent, selective, and systemically bioavailable agonists for mGlu₂ and mGlu₃ receptor subtypes, a series of C4_β-N-linked variants of (1<i>S</i>,2<i>S</i>,5<i>R</i>,6<i>S</i>)-2-amino-bicyclo­[3.1.0]­hexane-2,6-dicarboxylic acid <b>1</b> (LY354740) were prepared and evaluated for both mGlu₂ and mGlu₃ receptor binding affinity and functional cellular responses. From this investigation we identified (1<i>S</i>,2<i>S</i>,4<i>S</i>,5<i>R</i>,6<i>S</i>)-2-amino-4-[(3-methoxybenzoyl)­amino]­bicyclo­[3.1.0]­hexane-2,6-dicarboxylic acid <b>8p</b> (LY2794193), a molecule that demonstrates remarkable mGlu₃ receptor selectivity. Crystallization of <b>8p</b> with the amino terminal domain of hmGlu₃ revealed critical binding interactions for this ligand with residues adjacent to the glutamate binding site, while pharmacokinetic assessment of <b>8p</b> combined with its effect in an mGlu₂ receptor-dependent behavioral model provides estimates for doses of this compound that would be expected to selectively engage and activate central mGlu₃ receptors in vivo