Precision Medicine in Type 2Diabetes: Clinical Markers ofInsulin Resistance Are AssociatedWithAlteredShort- andLong-termGlycemic Response to DPP-4Inhibitor TherapyDiabetes Care 2018;41:705–712 | https://doi.org/10.2337/dc17-1827

OBJECTIVE

A precision approach to type 2 diabetes therapy would aim to target treatmentaccording to patient characteristics. We examined if measures of insulin resistanceand secretion were associated with glycemic response to dipeptidyl peptidase4 (DPP-4) inhibitor therapy.

RESEARCH DESIGN AND METHODS

We evaluated whether markers of insulin resistance and insulin secretion wereassociated with 6-month glycemic response in a prospective study of noninsulin-treated participants starting DPP-4 inhibitor therapy (Predicting Response to IncretinBasedAgents [PRIBA] study; n = 254), with replication for routinely availablemarkersin U.K. electronic health care records (Clinical Practice Research Datalink [CPRD]; n =23,001). In CPRD, we evaluated associations between baseline markers and 3-yeardurability of response. To test the specificity of findings, we repeated analyses forglucagon-like peptide 1 (GLP-1) receptor agonists (PRIBA, n = 339; CPRD, n = 4,464).

RESULTS

In PRIBA, markers of higher insulin resistance (higher fasting C-peptide [P = 0.03],HOMA2 insulin resistance [P = 0.01], and triglycerides [P < 0.01]) were associatedwith reduced 6-month HbA1c response to DPP-4 inhibitors. In CPRD, higher triglycer-ides and BMI were associated with reduced HbA1c response (both P < 0.01). A sub-group defined by obesity (BMI ‡30 kg/m2) and high triglycerides (‡2.3 mmol/L) hadreduced 6-month response in both data sets (PRIBA HbA1c reduction 5.3 [95% CI 1.8,8.6] mmol/mol [0.5%] [obese and high triglycerides] vs. 11.3 [8.4, 14.1] mmol/mol[1.0%] [nonobese and normal triglycerides]; P = 0.01). In CPRD, the obese, high-triglycerides subgroup also had less durable response (hazard ratio 1.28 [1.16,1.41]; P < 0.001). There was no association between markers of insulin resistanceand response to GLP-1 receptor agonists.

CONCLUSIONS

Markers of higher insulin resistance are consistently associated with reduced glyce-mic response to DPP-4 inhibitors. This finding provides a starting point for theapplication of a precision diabetes approach to DPP-4 inhibitor therapy.

1Health Statistics Group, University of ExeterMedical School, Exeter, U.K.2National Institute for Health Research ExeterClinical Research Facility, University of ExeterMedical School, Exeter, U.K.3Blood Sciences, Royal Devon and Exeter Hospi-tal, Exeter, U.K.4Institute of Biomedical and Clinical Science, Uni-versity of Exeter Medical School, Exeter, U.K.5Institute of Cardiovascular and Medical Scien-ces, University of Glasgow, Glasgow, U.K.6Diabetes Trials Unit, Oxford Centre for Diabetes,Endocrinology and Metabolism, University ofOxford, Oxford, U.K.7Division of Molecular & Clinical Medicine, Nine-wells Hospital and Medical School, University ofDundee, Dundee, U.K.

Corresponding author: Angus G. Jones, angus.jones@exeter.ac.uk.

Received 31 August 2017 and accepted 28December 2017.

Clinical trial reg. no. NCT01503112, clinicaltrials.gov.

This article contains Supplementary Data onlineat http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc17-1827/-/DC1.

© 2018 by the American Diabetes Association.Readers may use this article as long as the workis properly cited, the use is educational and notfor profit, and the work is not altered. More infor-mation is available at http://www.diabetesjournals.org/content/license.

John M. Dennis,1 Beverley M. Shields,2

Anita V. Hill,2 Bridget A. Knight,2

Timothy J. McDonald,2,3

Lauren R. Rodgers,1 Michael N. Weedon,4

William E. Henley,1 Naveed Sattar,5

Rury R. Holman,6 Ewan R. Pearson,7

Andrew T. Hattersley,2 and

Angus G. Jones,2 on behalf of the

MASTERMIND Consortium

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Type 2 diabetes is a heterogeneous con-dition characterized by varying degrees ofreduced b-cell function and higher levelsof insulin resistance. Most of the 400 mil-lion patientsworldwidewill at somepointrequire glucose-lowering medication (1).Major international treatment guidelinesrecommend at least four oral treatmentoptions after initial metformin has failedto achieve control, with choice betweenthese informed predominantly bymethodof administration, overall side effect pro-file, and cost (2–5).Individual response to glucose-lowering

therapies in type 2 diabetes varies greatly.Identification of clinical phenotypic fea-tures or biomarkers robustly associatedwith glycemic response or other poten-tially beneficial effects (for example, re-duced weight gain or side effects for eachtherapy) may allow treatment of patientswith the agent that is most likely to beeffective for them, an approach known as“precision” or “stratified” medicine (6,7).Although much research has focused onidentifying genetic or novel biomarkerpredictors of response, precision diabetesismost likely to be cost effective and haveclinical impact using simple inexpensivebiomarkers or routinely available clinicalphenotypic features (8,9).Dipeptidyl peptidase 4 (DPP-4) inhibi-

tors are common (20% of U.S. and 27% ofU.K. second-line glucose-lowering pre-scriptions after metformin in 2013) (10,11),well-tolerated (12) oral therapy optionsrecommended in all clinical guidelines(2–5). Beyond baseline HbA1c and fastingglucose, it is unclear if other factors areassociated with glycemic response toDPP-4 inhibitors (13,14). A major mecha-nism of action of DPP-4 inhibitors is po-tentiation of b-cell insulin secretion. Weaimed to establish if measures of insulinsecretion and insulin resistance were asso-ciated with short-term glycemic responseand long-term durability of response inpatients with type 2 diabetes startingDPP-4 inhibitor therapy.

RESEARCH DESIGN AND METHODS

We assessed whether clinical featuresand biomarkers associated with insulinsecretion and insulin resistance were pre-dictive of short-term 6-month glycemicresponse in analysis of a prospectivestudy of patients starting DPP-4 inhibitortherapy as part of routine care (Predict-ing Response to Incretin Based Agents

[PRIBA] study). To validate our findings,we tested the consistency of associationsbetween routinely recorded factors asso-ciated with response in PRIBA in a retro-spective analysis of a much larger groupof patients from the U.K. Clinical Prac-tice Research Datalink (CPRD), evaluat-ing both 6-month glycemic responseand long-term durability of response to3 years.

Study Setting and Assessment

PRIBA Prospective Study

The PRIBA study was designed to test thehypothesis that thosewhohave low insulinsecretion, as measured by C-peptide, willhave poor glycemic response to incretin-based treatments (https://clinicaltrials.gov/ct2/show/NCT01503112),with asso-ciations between glycemic response andother clinical features, islet autoanti-bodies and HOMA2 estimates of b-cellfunction, and insulin sensitivity evaluatedin prespecified secondary analysis. Threehundred five participants due to startDPP-4 inhibitor therapy as part of theirusual care were recruited from primaryand secondary care across 17 National In-stitute for Health Research (NIHR) clinicalresearch network centers in the U.K. fromApril 2011 to October 2013 as previouslydescribed (15).

At baseline (immediately prior to start-ing therapy), we measured HbA1c, fastingglucose, clinical markers of insulin resis-tance and insulin secretion (fastingC-peptide and postmeal urine C-peptidecreatinine ratio [UCPCR] [16,17], BMI, tri-glycerides, HDL-cholesterol [HDL-c] [18],sex hormone–binding globulin [SHBG],GAD, and IA2 islet autoantibodies), andother clinical characteristics (age at ther-apy, sex, duration of diabetes, estimatedglomerular filtration rate [eGFR], ethnic-ity, LDL-cholesterol [LDL-c], and numberof diabetes therapies). We calculatedHOMA2-%B and HOMA2 estimates ofinsulin resistance (HOMA2-IR) from fast-ing glucose and C-peptide measures us-ing the HOMA2 calculator available fromhttp://www.dtu.ox.ac.uk/homacalculator/(19). Laboratory analysis was conductedas previously reported (15). Partici-pants were included in the analysis ifthey were not insulin treated and hadat least 3 months’ follow-up with .75%adherence to therapy and limited cotreat-ment change (see study profile in Supple-mentary Fig. 1A). Ethics approval wasgranted by the South West National

Research Ethics Committee, and all par-ticipants gave written informed consent.

Retrospective Analysis of U.K. Primary Care

Patients (CPRD Database)

CPRD is the world’s largest longitudinaldatabase of anonymized primary careelectronic health records (20). We in-cluded 23,001 noninsulin-treated patientswith type 2 diabetes with prescription re-cords of starting a DPP-4 inhibitor for thefirst time from June 2007 to September2016 and followed them up while they re-mainedonDPP-4 inhibitor therapywithoutthe addition or cessation of any other anti-hyperglycemic medication (see studyprofile in Supplementary Fig. 1B). We ex-tracted baseline routine clinical character-istics (age at therapy, duration of diabetes,sex, and BMI) and biomarkers (HbA1c, tri-glycerides, HDL-c, LDL-c, and eGFR), withbaseline defined as the most recent recordin the 3months prior to the drug start date.Ethics approval was granted by the CPRDIndependent Scientific Advisory Commit-tee (ISAC 13_177R).

Outcomes

Short-term Glycemic Response (PRIBA and

CPRD)

The primary outcome was the absolutechange from baseline in HbA1c 6 monthsafter starting therapy, adjusting for base-line HbA1c. When a 6-month HbA1c wasnot available or eligible in the PRIBA study(Supplementary Fig. 1A), weuseda3-monthHbA1cmeasure, aspreviously described (15).In CPRD, avalid6-monthHbA1cwas definedas the closest HbA1c to 6months after thedrug start date63months for patients onunchanged antihyperglycemic therapy.

Durability of Glycemic Response (CPRD)

In CPRD, in which long-term follow-updata were available, we assessed durabil-ity of response as the time to glycemicfailure up to 3 years in a complete caseanalysis of patients with baseline HbA1cbetween 53 and 97 mmol/mol (7–11%)and at least 3 months on DPP-4 inhibitortherapy (n = 15,616). Glycemic failure wasdefined as 1) two consecutive HbA1c

measurements .69 mmol/mol (8.5%)or 2) a single HbA1c measurement .69mmol/mol (8.5%) followed by the addi-tion of another antihyperglycemic ther-apy. To examine the sensitivity of resultsto this definition,we repeated theanalysisusingHbA1c thresholds of1) 53mmol/mol(7.5%) and 2) the baseline HbA1c levelspecific to each individual patient.

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Statistical Analysis

Short-term Response (PRIBA and CPRD)

We examined associations between eachstandardized marker of insulin resistanceand insulin secretion and 6-month HbA1cresponse in a series of linear regressionmodels adjusted for baseline HbA1c and,in PRIBA, cotherapy change (13,20). Non-normally distributed variables were log-transformed. We conducted a completecase analysis for each marker, includingall patients with valid data even if theyhad missing data for other markers. Toevaluate model fit, we examined normal-ity of residuals and linearity of associa-tions for continuous variables. In bothdata sets, we tested the independenceof initial associations for each marker ofinsulin resistance and insulin secretionwith 6-month response in further multi-variable analysis, controlling for baselineHbA1c and other routinely recorded char-acteristics: age at therapy, duration of di-abetes, sex, eGFR, LDL-c, ethnicity (CPRDonly: white, nonwhite, and missing), andcotherapy change (PRIBA only; CPRD pa-tients all on unchanged therapy).To further assess the robustness of find-

ings, we repeated the baseline adjustedanalysis of 6-month response for malesand females separately in both data setsand in PRIBA with additional adjustmentfor fasting glucose. In CPRD, we repeatedthe baseline adjusted analysis using 12-month response as the outcome in a dis-tinct cohort of patients with a 12-month(closest 63 months as for definition of 6-monthresponse)HbA1c record (n = 16,166).

Subgroup Analysis of Short-Term Response

(PRIBA and CPRD)

Based on the initial results, we definedthree patient subgroups by standard clin-ical cutoffs for obesity (BMI $30 kg/m2)and high triglycerides ($2.3 mmol/L)(21): group A, nonobese and normal tri-glycerides; group B, nonobese or normaltriglycerides; and group C, obese and hightriglycerides. We estimated the mean6-month HbA1c response for each sub-group using linear regression models ad-justed for baseline HbA1c and, in PRIBA,cotherapy change.We standardizedbase-line HbA1c to the mean PRIBA baselinelevel of 74 mmol/mol (8.9%) for all sub-groups in both data sets.

Durability of Response (CPRD)

For three subgroups defined by the sameBMI and triglyceride thresholds, we com-pared mean durability in response to

3 years after starting therapy using a flex-ible parametric time to failure survivalmodel. We included all patients with atleast 3 months on therapy after starting aDPP-4 inhibitor with valid baseline recordsof all covariates (baseline HbA1c, age attherapy, duration of diabetes, sex, andeGFR). The use of flexible parametricmodels allowed prediction of the proba-bility of therapy failure over 3 years aswell as hazard ratios (HRs) consistentwith Cox proportional hazards regression(22). We tested continuous variables fornonlinearity and evaluated proportionalhazards assumptions using Schoenfeldresiduals. To estimate the probability oftherapy failure for each subgroup, a pre-dicted survival curve was calculated foreach patient in the data set before theindividual survival curves for all patientswithin a subgroup were averaged (23).Each curve was standardized to the meanCPRD values of other clinical covariates(baseline HbA1c 72 mmol/mol [8.7%]; ageat therapy 64 years; duration of diabetes8 years; and eGFR 82 mL/min/1.73 m2).Point estimates for the failure probabilityat 3 years by subgroup were calculatedusing the same approach.

Replication Analysis With Glucagon-like

Peptide 1 Receptor Agonists (PRIBA and

CPRD)

To test the specificity of findings for DPP-4 inhibitors, we repeated the analyses ofshort-term response and durability of re-sponse for noninsulin-treated subjectsstarting glucagon-like peptide 1 (GLP-1) re-ceptor agonists, theother glucose-loweringdrug evaluated in PRIBA (PRIBA, n = 339;CPRD, n = 4,464). We have previously re-ported the PRIBA primary analysis of pre-dictors of glycemic response for the fullPRIBA GLP-1 receptor agonist cohort,which included an additional 209 insulin-treated participants (14). All data extrac-tion and analysis were conducted usingStata v14.0 (StataCorp, College Station, TX).

RESULTS

Patient Characteristics and Responseto DPP-4 Inhibitor TherapyBaseline characteristics and biomarkermeasures were similar for subjects start-ing DPP-4 inhibitors in both data sets(Table 1). In both cohorts, the majority ofpatients started sitagliptin. Two hundredfifty-four patients were included in PRIBAand 23,001 (for analysis of 6-month gly-cemic response) in CPRD (for study pro-files, see Supplementary Fig. 1). Mean

(SD) 6-month HbA1c change was 28.3(13.5)mmol/mol (20.7% [1.2%]) in PRIBAand 27.6 (15.1) mmol/mol (20.7%[1.4%]) in CPRD.

Higher Baseline Fasting C-Peptide andHOMA2-IR Are Associated WithReduced Glycemic Response to DPP-4InhibitorsIn the PRIBA cohort, mean HbA1c re-sponse was reduced by 1.67 mmol/molfor every 1 SD higher baseline fastingC-peptide (standardized b 1.67 [95% CI0.17, 3.17] mmol/mol/SD; P = 0.03) (Fig.1). We observed the same direction andsimilar size of effect for UCPCR (responsereduction per SD higher 1.65 [95%CI 20.07, 3.37] mmol/mol; P = 0.06).Higher baseline HOMA2-IR was also asso-ciated with reduced response (responsereduction per SD higher: 2.17 [95% CI0.62, 3.72]mmol/mol; P = 0.01), but therewas no evidence of an association be-tween b-cell function (HOMA2-%B) andresponse (response reductionperSDhigher0.16 [95% CI 21.49, 1.81] mmol/mol;P = 0.85). Islet autoantibody prevalencewas low (2.8% GAD or IA2 positive; re-sponse reduction for presence of autoanti-bodies: 5.6 [95%CI23.6, 14.7]mmol/mol;P = 0.23).

Other Markers of Insulin ResistanceAre Consistently Associated WithGlycemic Response to DPP-4 Inhibitorsin PRIBA and CPRDIn PRIBA, higher triglycerides was associ-ated with reduced glycemic response (re-sponse reduction per SD increase 2.54[95% CI 0.99, 4.08] mmol/mol; P , 0.001),with a consistent direction of associationfor higher BMI (response reduction perhigher BMI 0.96 [95% CI 20.54, 2.46]mmol/mol; P = 0.21) and lower SHBG (re-sponse reduction per SD higher SHBG21.19 [95% CI 22.81, 0.42] mmol/mol;P = 0.15) (Fig. 1 and Supplementary Table1). In CPRD, higher triglycerides and BMIwere associated with reduced HbA1c re-sponse (Fig. 1 and Supplementary Table1). HDL-c was not associated with re-sponse in either data set (P = 0.81 inPRIBA; P = 0.46 in CPRD).

Markers of Insulin Resistance AreAssociated With Glycemic Response toDPP-4 Inhibitors Independently ofOther Routine Clinical CharacteristicsResults were consistent when 1) stratifyingby sex (Supplementary Table 1), 2) con-trolling for baselineHbA1c, age at therapy,

care.diabetesjournals.org Dennis and Associates 707

sex, duration of diabetes, eGFR, LDL-c,ethnicity (CPRD only), and cotherapychange (PRIBA only) in multivariable analysis

of each data set (Supplementary Table 2),3) in PRIBA controlling for fasting glucose(Supplementary Table 3), and 4) in CPRD

with 12-month HbA1c response as theoutcome (Supplementary Table 4).

Standard Clinical Criteria of Obesityand High Triglycerides Can IdentifyPatients Likely to Have MarkedlyReduced Glycemic Response to DPP-4InhibitorsHigher triglycerides were associated withreduced glycemic response independentlyof BMI in both data sets, and higher BMIwas associated with reduced response in-dependently of triglycerides in CPRD (Sup-plementary Table 5). To examine thepotential clinical implication of this finding,we compared mean baseline HbA1c ad-justed response in three patient subgroupsdefinedby standard clinical cutoffs for obe-sity (BMI $30 kg/m2) and high triglycer-ides ($2.3mmol/L) (subgroupA:nonobeseand normal triglycerides; subgroup B: non-obese or normal triglycerides; and subgroupC: obese and high triglycerides).

In PRIBA, we found mean 6-monthbaseline HbA1c standardized glycemic re-sponse was halved for the obese and hightriglycerides subgroup (subgroup C 25.2[95% CI 21.8, 28.6] mmol/mol [20.5%(95% CI20.2,20.8)]) compared with thenonobese and normal triglycerides sub-group (subgroup A 211.3 [95% CI 28.4,214.1] mmol/mol [21.0% (95% CI20.8,21.3)]) and was significantly reducedcompared with intermediate subgroup B(29.9 [95% CI 27.6, 212.2] mmol/mol[20.9% (95% CI 20.7, 21.1)]) (Fig. 2A).Direction of effect was replicated in CPRD,albeit with smaller differences in mean re-sponse between subgroups (subgroup Amean baseline adjusted HbA1c response210.3 [95% CI 29.8, 210.7] mmol/mol

Table 1—Subject baseline characteristics

PRIBA (n = 254) CPRD (n = 23,001)

CharacteristicsBaseline HbA1c (mmol/mol) 74 (12) 72 (15)Baseline HbA1c (%) 8.9 (1.1) 8.7 (1.3)Age at therapy start (years) 63 (10) 64 (11)Age at diagnosis (years) 54 (10) 56 (10)Male sex, % 63 61Duration of diabetes (years) 9 (6) 8 (5)BMI 32 (29–37); 33 (6) 32 (28–36); 33 (6)Ethnicity, %White 97 45Nonwhite 3 6Missing 0 49

BiomarkersTriglycerides (mmol/L) 1.7 (1.2–2.4); 1.8 (0.9)* 1.8 (1.3–2.6); 1.9 (1.0)*HDL-c (mmol/L) 1.1 (0.9–1.3); 1.1 (0.3)* 1.1 (0.9–1.3); 1.1 (0.3)*LDL-c (mmol/L) 1.9 (1.5–2.3); 1.9 (0.8)* 2.1 (1.6–2.6); 2.0 (0.8)*SHBG (nmol/L) 27 (19–41); 27 (16)* NAFasting C-peptide (pmol/L) 1,150 (820–1,460); 1,090 (480)* NAHOMA2-%B 54 (37–73); 51 (27)* NAHOMA2-IR 3.1 (2.3–4.2); 3.1 (1.5)* NAUCPCR (nmol/mmol) 3.4 (2.0–5.0); 3.0 (2.3)* NAeGFR (mL/min/1.73 m2) 85 (70–98); 85 (24) 82 (66–97); 82 (23)GAD or IA2 positive, % 3 NA

TherapyNumber of concomitant therapies

at therapy start, % of total0 3 61 35 512 57 423+ 5 2

DPP-4 type, % of totalSitagliptin 87 72Alogliptin 0 2Linagliptin 4 10Saxagliptin 6 12Vildagliptin 2 4

Data are median (interquartile range) or mean (SD) unless otherwise specified. NA, notavailable. *Log-transformed.

Figure 1—DPP-4 inhibitors: associations betweenmarkers of insulin resistance and HbA1c response at 6months. Circles (black, PRIBA in A; white, CPRD inB) denote the mean HbA1c change (mmol/mol) at 6 months per 1 SD higher baseline value of each marker. Error bars denote 95% CI.

708 Insulin Resistance and Response to DPP-4 Inhibitors Diabetes Care Volume 41, April 2018

[20.9% (95% CI 20.9, 21.0)]; subgroupB 28.8 (95% CI 28.5, 29.1) mmol/mol[20.8% (95% CI 20.8, 20.8)]; and sub-group C27.5 (95% CI27.0, 27.9) mmol/mol [20.7%(95%CI20.6,20.7)]) (Fig. 2B).

Obesity and High Triglycerides AreAssociated With Less DurableGlycemic Response to DPP-4 InhibitorsOver 3 YearsA total of 15,616 patients were followedup in this analysis for a mean time of 1.5

years. Over the 3-year study period, 3,514(23%) patients had glycemic failure (con-firmed HbA1c$69mmol/mol [8.5%]). Weobserved an increased relative risk of gly-cemic failure (reflecting a less durable re-sponse) in the same obesity- and hightriglycerides–defined subgroups, stan-dardizing for other clinical characteristics(HRs for glycemic failure: subgroup C,obese and high triglycerides vs. subgroupA, nonobese and normal triglycerides,1.28 [95% CI 1.16, 1.41], P , 0.001;

subgroup B, obese or high triglyceridesvs. subgroup A, 1.17 [95% CI 1.08, 1.27],P , 0.001; and subgroup C vs. subgroupB, 1.09 [95% CI 1.01, 1.18], P = 0.04)(Supplementary Table 6). Consistent rela-tive differences between subgroups wereobserved at HbA1c failure thresholds of7.5% and the baseline HbA1c specific toeach individual patient (SupplementaryTables 7 and 8). These results translatedinto significant differences between sub-groups in the absolute probability of gly-cemic failure at 3 years (subgroup C:obese and high triglycerides, 39% [95%CI 37, 42]; subgroup B: obese or high tri-glycerides, 37% [95% CI 35, 38]; andsubgroup A: nonobese and normal trigly-cerides, 32% [95%CI 31, 34]) (Supplemen-tary Fig. 2).

There Is No Evidence of an AssociationBetween Markers of Insulin Resistanceand Glycemic Response to GLP-1Receptor AgonistsWe found no evidence of an associationbetween any marker of insulin resistanceand 6-month glycemic response to GLP-1receptor agonists in PRIBA (n = 339) orCPRD (n = 4,464) in continuous analysis(Fig. 3 and Supplementary Tables 8 and9). There was also no evidence for a dif-ference in response to GLP-1 receptoragonists across the obesity- and triglycer-ide-defined subgroups (all subgroup com-parisons, P. 0.40) (Supplementary Table10 and Supplementary Fig. 3), althoughthere were few subjects in the nonobese,normal triglyceride subgroup startingGLP-1 receptor agonist therapy in bothdata sets (PRIBA, 2% and CPRD, 5%). Sim-ilarly, in CPRD, we found no evidence ofan association between durability of gly-cemic response and BMI (HR per unit in-crease 1.01 [95% CI 1.00, 1.02]; P = 0.29)or triglyceride levels (HR per unit increase0.99 [95% CI 0.95, 1.04]; P = 0.80)(Supplementary Table 11) or of a differ-ence in durability of response acrossobesity- and triglyceride-defined sub-groups (Supplementary Table 12 andSupplementary Fig. 4).

CONCLUSIONS

Our results show that markers of higherinsulin resistance are consistently as-sociated with reduced glycemic responseto DPP-4 inhibitor therapy. In our U.K.-representative cohort, 22% of patientswere obese with high triglycerides ($2.3mmol/L), and these patients had both

Figure 2—DPP-4 inhibitors: predictedmeanabsoluteHbA1c change frombaseline at 6months in PRIBA(A) and CPRD (B) across subgroups defined by the presence or absence of obesity (BMI$30 kg/m2)and high triglycerides (TRGS) ($2.3 mmol/L): subgroup A, nonobese and normal triglycerides; sub-groupB, nonobese or normal triglycerides; and subgroupC, obese andhigh triglycerides. BaselineHbA1c isstandardized to the mean PRIBA baseline level of 74 mmol/mol (8.9%) for all subgroups. Error barsdenote 95% CI.

care.diabetesjournals.org Dennis and Associates 709

markedly reduced short-term glycemicresponse and shorter durability of re-sponse on DPP-4 inhibitor treatment.With GLP-1 receptor agonists, we foundno evidence of an association betweenmarkers of insulin response and either6-month glycemic response or durabilityof response to 3 years. Findings were ro-bustly demonstrated in a prospectivestudy and validated in real-world dataand provide a starting point for the appli-cation of a precision diabetes approachwith DPP-4 inhibitor therapy.Strengths of this study include that we

have shown consistent findings acrossseveral clinical features and markers ofinsulin resistance in a prospective studyand large data set of electronic healthcare records. We have shown that find-ings are robust with adjustment forbaseline HbA1c (13,24) and potential con-founders and by definition of glycemicresponse, with similar associations forshort-term (6- and 12-month) and long-term (3-year durability) glycemic out-comes. Our study is the first to identifycharacteristics associated with durabilityof response toDPP-4 inhibitor therapy, anarea in which evidence is limited (25).Limitations of this study include that

we were only able to partially replicateour results from the PRIBA study cohort,as measures such as C-peptide were notavailable in our replication data set. Oureffect size for triglycerides is notablysmaller in our replication data set. It ispossible this relates to differences in tri-glyceride measurement (we were unableto confirm if measured triglycerides werefasted in these real-world data), to

increased error in electronic health carerecords in comparison with the prospec-tive study (26), or to the effect of statisti-cal chance in the smaller data set. Theonly long-term follow-up data we had toevaluate durability of glycemic responsewas from the routine primary care dataset CPRD; further evaluation in a trial set-ting with greater follow-up than PRIBAwould be of considerable interest. An ad-ditional important limitation is that thisstudy has examined response to onlytwo of the available therapies. Evidenceis limited for other therapies, although aprevious study found no evidence of a re-lationship between clinical insulin re-sistance or dyslipidemia markers andglycemic responsewith the sodium–glucosecotransporter 2 inhibitor dapagliflozin(27). High BMI and triglycerides haveboth been shown to be associated withmodest increases in the rate of diabetesprogression (28). Although this is unlikelyto be relevant to our finding for 6-monthglycemic response, this could influenceour findings for treatment durability,and replication looking at other compari-son therapies is therefore particularly im-portant in this context. Although we haveonly examined relatively crude measuresof insulin resistance, for clinical practicewe consider it very unlikely that more com-plex measures would ever be feasible (29).

Existing studies of the association be-tween insulin resistance and short-termglycemic response to DPP-4 inhibitorshave not shown consistent findings andare constrained by methodological andreporting limitations, as recently reviewedby Bihan et al. (13). Meta-regression of

study-level data has suggested reducedglycemic response in patients with higherBMI in one study (30), but no relationshipin another analysis (31). These studiesshould be interpreted with some cau-tion due to risk of ecological bias (32,33).A number of individual clinical trials ofDPP-4 inhibitors have commented onconsistency of glucose response acrosssubgroups defined by baseline BMI orinsulin resistance; reduced glycemic re-sponse with high HOMA2-IR was reportedin two of seven studies and reduced re-sponse with high BMI in 6 of 36 studies,as reviewed in Bihan et al. (13). No studiesreported an opposite direction of effect.These reports are very limited, with thevastmajority providing no statistical com-parison or details of what analysis wasundertaken. An important issue for anal-ysis of this nature is accounting for theinfluence of baseline HbA1c, the strongestpredictor of glycemic response, whichmay confound true associations, espe-cially as baseline HbA1c and insulin re-sistance are positively correlated (24,34,35). There are limited data examiningthe relationship between triglyceridesand response to DPP-4 inhibitors; how-ever, one study stratified patients bybaseline triglycerides (,/.1.7 mmol/L)and found the odds of achieving anHbA1c target of 53 mmol/mol (7%) weredoubled in the low-triglyceride subgroup(odds ratio 2.2 [95% CI 1.0, 4.7]; P = 0.04)(36).

Although it is plausible that our findingof reduced glycemic response in thosewith high BMI or high triglycerides di-rectly relates to insulin resistance through

Figure 3—GLP-1 receptor agonists: associations betweenmarkers of insulin resistance and HbA1c response at 6 months. Circles (black, PRIBA in A; white,CPRD in B) denote the mean HbA1c change (mmol/mol) at 6 months per 1 SD higher baseline value of each marker. Error bars denote 95% CI.

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reduced effect of drug-potentiated insu-lin secretion, this effect is not apparent inother drugs with effects on insulin secre-tion; for example, there is no relationshipbetween obesity and response to sulfo-nylurea therapy or GLP-1 receptor ago-nists (15,37). An alternative explanationwould be a direct effect of lipotoxicity,or indirect associations with other (un-measured) factors important to DPP-4 in-hibitor response. A direct mechanism forlipotoxicity in reducing response to incretin-based therapy has been previously sug-gested, with expression of GLP-1 receptorsdiminished in islets exposed to elevatedfatty acid levels in animal models andb-cell response to GLP-1 restored follow-ing fatty acid reduction with fibrate phar-macotherapy; however, this mechanismwould not explain the lack of an associa-tion between these features and GLP-1receptor agonist response (38). It hasalso been shown that GLP-1 response isblunted in obese insulin-resistant pa-tients with high liver fat and also bluntedin patients with high fasting triglycerides(39,40); therefore, impaired GLP-1 secre-tion in obese insulin-resistant individualsrepresents a potential indirect mecha-nism that could also account for the lackof a similar relationship for injected GLP-1receptor agonist therapy. Although thelack of association for HDL-c may be con-sidered unexpected, we note HDL-c has amuch weaker relationship with insulin re-sistance than either triglycerides or fast-ing insulin/C-peptide, which may explainthis finding (18).Our findings have potential implica-

tions for clinical practice, as both BMIand triglycerides are routinely availableat no additional cost. Stratification oftreatment based on these criteria maytherefore be cost effective even withthe more modest differences in treat-ment effect seen in our replication co-hort. Although our own and previousresearch suggests these findings may bespecific to DPP-4 inhibitors, further workexamining the relationship betweenthese and other factors and response tocomparator drugs is needed. Our studydesign, emphasizing the importance ofreplication across data sets, provides anexemplar for such future analyses. In ad-dition, although simple categorization bysubgroupmay provide a starting point forprediction of therapy response in type 2diabetes, we anticipate a more sophis-ticated precision diabetes approach

combining features into a multivariableresponse calculator will have greatestclinical utility, and this is an importantarea for future research (8,41).

In conclusion, our study shows simplemarkers of higher insulin resistance areconsistently associated with reduced gly-cemic response to DPP-4 inhibitor therapy.This finding was robustly demonstratedin a prospective study, was validated inreal-world data, and provides a startingpoint for the application of a precision di-abetes approach to DPP-4 inhibitor ther-apy in type 2 diabetes.

Acknowledgments.The authors thank the staffof the NIHR Exeter Clinical Research Facility andNIHR Diabetes Research Network for assistancewith conducting the study. The authors alsothank the members of the PRIBA study group(see Supplementary Data for participating centersand members) and all cohort participants.Funding. The PRIBA study was funded by a Na-tional Institute for Health Research (U.K.) DoctoralResearch Fellowship (DRF-2010-03-72 to A.G.J.)and supported by the NIHR Clinical Research Net-work. TheMASTERMINDConsortium is supportedby the Medical Research Council (U.K.) (MR/N00633X/1). B.M.S., A.V.H., B.A.K., and A.T.H.are supported by the NIHR Exeter Clinical ResearchFacility. T.J.M. is an NIHR Chief Scientist OfficeClinical Senior Lecturer. N.S. acknowledges supportby InnovativeMedicines InitiativeJointUndertakingunder grant agreement 115372, the resources ofwhich comprise financial contributions from theEuropeanUnion’s Seventh FrameworkProgramme(FP7/2007–2013) and EFPIA (European FederationofPharmaceutical IndustriesandAssociations) com-panies’ in-kind contribution. R.R.H. and A.T.H. areNIHR Senior Investigators. E.R.P. is a WellcomeTrust New Investigator (102820/Z/13/Z). A.T.H.is a Wellcome Trust Senior Investigator. A.G.J. issupported by an NIHR Clinician Scientist award.The views expressed are those of the authors

and not necessarily those of the National HealthService, NIHR, or Department of Health. Thefunders had no role in any part of the study or inany decision about publication.Duality of Interest.W.E.H. declares a grant fromQuintiles. E.R.P. declares personal fees from EliLilly andCompany,NovoNordisk, andAstraZeneca.N.S. declares personal fees from Boehringer Ingel-heim, Eli Lilly and Company, Novo Nordisk, andJanssen and a grant from AstraZeneca. R.R.H. de-clares research funding from Bayer, AstraZeneca,and Merck Sharp & Dohme and honoraria fromAmgen, Bayer, Elcelyx, Janssen, Intarcia Therapeu-tics, Merck Sharp & Dohme, Novartis, Novo Nor-disk, and Servier. No other potential conflicts ofinterest relevant to this article were reported.Author Contributions. J.M.D. and A.G.J. de-signed the study and drafted the article. B.M.S.,L.R.R., and M.N.W. extracted the CPRD data.A.V.H., B.A.K., T.J.M., and A.G.J. researched thedata (PRIBA study). J.M.D., B.M.S., and A.G.J.analyzed the data with assistance from W.E.H.W.E.H., N.S., R.R.H., E.R.P., andA.T.H. discussed andcontributed to study design and provided support

for the analysis and interpretation of results. Allauthors critically revised the article and approvedthefinalversion.A.G.J. is theguarantorof thisworkand, as such, had full access toall of the data in thestudy and takes responsibility for the integrity ofthe data and the accuracy of the data analysis.Prior Presentation. Parts of this study werepresented in abstract form at the Diabetes UKProfessional Conference, Manchester, U.K., 8–10 March 2017.

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