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One hour post-load plasma glucose and 3 year risk of worsening fasting and 2 hour glucose tolerance in the RISC cohort

  • Melania MancoEmail author
  • Andrea Mari
  • John PetrieEmail author
  • Geltrude Mingrone
  • Beverley Balkau
  • for the EGIR-RISC study group
Open Access
Research Letter

Keywords

Diagnostic criteria Post-challenge glucose Post-load glucose Prediabetes Prediabetes phenotype Progression 

Abbreviations

BCGS

Beta cell glucose sensitivity

EGIR

European Group for the Study of Insulin Resistance

FPG

Fasting plasma glucose

IFG

Impaired fasting glucose

IGT

Impaired glucose tolerance

NGT

Normal glucose tolerance

OGIS

Oral glucose insulin sensitivity

1hPG

1 h post-load plasma glucose

2hPG

2 h post-load plasma glucose

RISC

Relationship between Insulin Sensitivity and Cardiovascular Risk

To the Editor: The 1 h post-load plasma glucose (1hPG) measurement has the potential to serve as a sensitive screening tool for identifying people who, despite having normal glucose tolerance (NGT), are at high-risk of developing type 2 diabetes over the next few years [1, 2]. Screening would be timely, as beta cells are still functional and lifestyle and drug interventions may be effective in delaying diabetes onset.

High 1hPG has been found to perform as well as the 2 h post-load plasma glucose (2hPG) measurement in predicting type 2 diabetes risk after median follow-up times of 9 and 13 years [3]. In a 33 year study, it was not only a better predictor of incident diabetes, but also of diabetes complications and mortality [4]. Robust evidence from the Botnia study and Malmö Prevention Project cohorts supports 1hPG as the best simple variable predicting incident type 2 diabetes, in comparison with other indices [1].

In a cross-sectional study, we previously described reduced euglycaemic clamp insulin sensitivity and impaired beta cell glucose sensitivity (BCGS) in people with NGT but with high 1hPG in 1205 healthy participants in the European Group for the Study of Insulin Resistance (EGIR) cohort: Relationship between Insulin Sensitivity and Cardiovascular Risk (RISC) [2]. There was a significant decreasing trend in insulin sensitivity from NGT with low 1hPG, to NGT with high 1hPG to impaired glucose tolerance (IGT: 2hPG: 7.8–11.1 mmol/l); BCGS was significantly higher in those with NGT and low 1hPG, in comparison with NGT and high 1hPG or IGT. This analysis of NGT included people without IGT and with a fasting plasma glucose (FPG) <6.1 mmol/l, the WHO definition of impaired fasting glucose (IFG) [2]. In our previous cross-sectional analysis of the baseline population, a 1hPG of 8.95 mmol/l was the ‘optimal’ cut-point (maximising [sensitivity + specificity]) associating 1hPG with prevalent IGT [2].

We now report 3 year longitudinal data from 797 participants with NGT at baseline, who had complete baseline and follow-up glucose data (see Table 1). Participants in the RISC study gave written informed consent. Ethics committee approval was obtained in each centre. The study was carried out in accordance with the Declaration of Helsinki as revised in 2008. The RISC Project Management Board approved the present analysis. In the present analysis, the definition of NGT was based on the ADA 2003 criteria (FPG <5.6 mmol/l and 2hPG <7.8 mmol/l, and not being treated for diabetes). The glucose tolerance status had worsened after 3 years for 183 people (23%): 40 had normal FPG but IGT; 117 had normal 2hPG but IFG (defined as FPG 5.6–6.9 mmol/l); 26 had both high FPG and 2hPG (including one case of diabetes diagnosed on the basis of FPG, and one on the basis of 2hPG). There was a higher percentage of progression to isolated IFG than to isolated IGT (15% vs 5%), with 3% showing progression on both FPG and 2hPG.
Table 1

Baseline characteristics and 3 year changes, according to baseline low or high 1hPG and 3 year progression to FPG ≥ 5.6 mmol/l and/or 2hPG ≥ 7.8 mmol/l

 

Low 1hPG <8.6 mmol/l (n = 620)

High 1hPG ≥8.6 mmol/l (n = 177)

 

Non-progressor

Progressor

p values

Non-progressor

Progressor

p values

 

n = 505 (81%)

n = 115 (19%)

Univariate

Adjusted

n = 109 (62%)

n = 68 (38%)

Univariate

Adjusted

At baseline

  Men (%)

37

45

0.1133

0.1243

48

68

0.0101

0.0152

  Age (years)

42 (36–49)

46 (39–54)

<0.0001

<0.0001

46 (38–51)

46 (40–54)

0.3933

0.2194

  BMI (kg/m2)

23.8 (21.8–26.2)

25.2 (23.4–27.8)

0.0001

0.0008

24.7 (23.2–27.1)

26.1 (23.5–28.6)

0.0383

0.0813

  Diabetes in family (%)

21

23

0.6402

0.6938

28

36

0.2360

0.3143

  Smoker (%)

25

25

0.9938

0.4434

36

33

0.6851

0.8395

  FPG (mmol/l)

4.9 (4.6–5.1)

5.2 (4.9–5.4)

<0.0001

<0.0001

5.1 (4.8–5.3)

5.2 (5.1–5.4)

0.0025

0.0154

  2hPG (mmol/l)

5.0 (4.3–5.8)

5.7 (4.8–6.3)

<0.0001

<0.0001

6.1 (5.3–6.9)

6.4 (5.7–7.0)

0.1748

0.0724

  LDL-cholesterol (mmol/l)

2.8 (2.2–3.3)

2.9 (2.5–3.4)

0.0576

0.8499

2.9 (2.4–3.3)

3.1 (2.6–3.6)

0.0496

0.1773

  HDL-cholesterol (mmol/l)

1.5 (1.2–1.7)

1.3 (1.1–1.6)

0.0134

0.0563

1.4 (1.1–1.6)

1.3 (1.1–1.5)

0.1311

0.9096

  Triacylglycerol (mmol/l)a

0.83 (0.62–1.14)

0.93 (0.68–1.21)

0.0941

0.9211

0.91 (0.70–1.15)

1.12 (0.78–1.66)

0.0066

0.1038

  Systolic BP (mmHg)

115 (107–124)

119 (110–127)

0.0119

0.8486

119 (110–125)

122 (114–130)

0.0363

0.2529

  Diastolic BP (mmHg)

73 (67–79)

75 (70–79)

0.0792

0.6799

75 (69–80)

77 (73–82)

0.0473

0.2378

  Basal insulin secretion (pmol min−1 m−2)a

61 (49–78)

69 (54–92)

0.0029

0.0597

65 (48–91)

86 (68–100)

0.0005

0.0044

  Total insulin secretion (nmol/m2)

36 (28–43)

39 (33–47)

0.0056

0.0623

44 (34–55)

46 (39–55)

0.1279

0.2629

  BCGS (pmol min−1 m−2 mmol−1 l)a

133 (100–187)

134 (99–176)

0.7585

0.9362

90 (66–112)

86 (69–103)

0.9380

0.9380

  Clamp insulin sensitivity (μmol min−1 kgFFM−1 nmol−1 l)a

143 (111–194)

134 (99–181)

0.1298

0.8733

133 (90–171)

95 (75–138)

0.0016

0.0481

  OGIS (ml min−1 kgFFM−1)a

12.7 (11.1–14.5)

11.6 (10.2–12.9)

<0.0001

0.0001

10.5 (9.6–11.9)

9.9 (8.7–11.2)

0.0278

0.6382

Per cent change over 3 years

  BMI

1.0 (−2.1–4.9)

2.0 (−1.8–4.8)

0.7289

0.2461

1.5 (−2.3–3.7)

1.4 (0.1–5.1)

0.3518

0.3541

  Basal insulin secretiona

−0.5 (−18–20)

14 (−5–38)

0.0092

0.0114

4.5 (−14–24)

11 (−5.8–32)

0.1049

0.0728

  Total insulin secretiona

4.8 (−10–24)

15 (−3–39)

0.0050

0.0550

−5.3 (−22–12)

12 (−10–27))

0.1110

0.2288

  BCGSa

−8.7 (−37–35)

−15 (−34–12)

0.3274

0.1556

24 (−3.7–74)

−2.4 (−21–48)

0.0302

0.0600

  OGIS

−2.7 (−12–6.9)

−14 (−22–−4.5)

<0.0001

<0.0001

7.7 (−6.9–20)

−13 (−18–−3.5)

<0.0001

<0.0001

Data are median (quartile 1–quartile 3) or % for both baseline variables and per cent change over 3 years variables

Progressors were participants who presented with FPG ≥5.6 mmol/l, or 2hPG ≥7.8 mmol/l or both conditions after 3 years of follow-up

p values used logistic regression, unadjusted and adjusted for sex, age and BMI

aLogarithms, base e, were used in the logistic regression analyses

FFM, fat-free mass

In the population currently being studied over 3 years of follow-up, as described in Table 1, the ‘optimal’ cut-point associated with a worsening glucose status was 7.6 mmol/l, corresponding to 306 (38%) of our NGT population. After adjusting for sex, age and BMI, the corresponding cut-point was 6.2 mmol/l, corresponding to 526 (66%) of our population. These frequencies of people at risk of diabetes are probably too high for these cut-points to be used in practice. A petition has been published proposing a 1hPG of 8.6 mmol/l be used as a cut-point for diagnosing IGT, based on a number of large population based studies [5]; this cut-point identified 177 (22%) in our population.

In the present analysis, the percentage of people whose glucose status progressed according to 1hPG (electronic supplementary material [ESM] Fig. 1) showed a linear relation—the higher the 1hPG, the higher the percentage that progressed—but there is no clear threshold for defining a cut-point. However, comparing people with a 1hPG ≥8.6 mmol/l with those below this cut-point, the OR of progression was 2.74 (95% CI 1.90, 3.95); after adjusting the logistic regression for sex, age and BMI the OR was 2.19 (1.49, 3.20) and this remained statistically significant after adjusting for either FPG or 2hPG. The 1hPG associated with progressing according to either FPG or 2hPG, or both, had a C statistic of 0.67, and this was not significantly different from those of FPG (0.71) or 2hPG (0.65), using the DeLong test, in keeping with previous studies [2, 3].

In the current group of 797 participants we present, as medians (interquartile range) or %, the metabolic features of individuals with NGT whose glucose status progressed (‘progressors’) vs those who did not (‘non-progressors’) according to 1hPG (< and ≥8.6 mmol/l) at baseline (Table 1). Comparisons between progressors and non-progressors were made by logistic regression, unadjusted, and adjusted for sex, age and BMI. In progressors from both NGT groups, after adjusting for sex, age and BMI, a higher baseline FPG was the only common statistically significant risk factor; however in the low 1hPG group, progressors were older, the 2hPG was higher and the oral glucose insulin sensitivity (OGIS) index [6] was lower in progressors than non-progressors; for the high 1hPG group, basal insulin secretion was higher and the clamp measure of insulin sensitivity lower in progressors than in non-progressors, indicating the importance of these two factors. Over three years of follow-up, the OGIS index decreased more in progressors in both 1hPG groups, while in the low 1hPG group, basal insulin secretion increased more in progressors (Table 1). The sample sizes in our data are not large, particularly for the high 1hPG group; we can note that over three years the BCGS decreased more in progressors than in non-progressors in the high 1hPG group (p = 0.0600).

More people progressed in relation to an increase in FPG than in 2hPG, 143 (18%) vs 66 (8%) (with 26 of these progressing in relation to both), so the metabolic features described in the paragraph above for progressors reflect more the metabolic impairment of participants who developed isolated IFG rather than isolated IGT or combined IFG and IGT; indeed we observed a higher clamp insulin sensitivity for isolated IFG than for isolated IGT, in both 1hPG groups (ESM Tables 1 and 2). In the low 1hPG group, comparing people who progressed to isolated IFG or isolated IGT over three years, basal insulin secretion increased more, total insulin secretion less and OGIS decreased less in those who progressed to isolated IFG; with the small sample sizes in the high 1hPG group, no statistically significant differences were seen, but changes were in the same direction (ESM Tables 1 and 2).

These new data from the RISC study further support the notion that high 1hPG is associated with an increased risk of IGT, and also of IFG, and it represents an intermediate risk category between IFG and IGT, supporting the case to rehabilitate the 1hPG test for use in the prediction of type 2 diabetes risk.

The RISC study provides insight on mechanisms involved in the deterioration of glucose homeostasis in individuals at risk of type 2 diabetes. The balance between insulin secretion and insulin sensitivity is central along the progression pathway to overt diabetes in a continuum of risk. Data from other cohort studies with similar measures are now required to validate our results.

Notes

Contribution statement

MM and BB designed the study, performed the analysis, interpreted the data and drafted the letter. AM contributed to data analysis, data interpretation and revised the manuscript for important intellectual content. BB, GM and JP contributed to data acquisition. GM and JP revised the draft for important intellectual content. All authors approved the final manuscript to be published. MM and BB are the guarantors of this work.

Funding

The RISC study received the European Union Grant QLG1-CT-2001-01252 and AstraZeneca, Sweden provided additional finances. Merck, France supported the European Group for the study of Insulin Resistance (EGIR). There has been no funding for the analysis or writing of this article. The study sponsors were not involved in the study design, collection, analysis and interpretation of data, the writing of this report nor in the decision to submit for publication.

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Supplementary material

125_2018_4798_MOESM1_ESM.pdf (232 kb)
ESM (PDF 231 kb)

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Copyright information

© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Melania Manco
    • 1
    Email author
  • Andrea Mari
    • 2
  • John Petrie
    • 3
    Email author
  • Geltrude Mingrone
    • 4
    • 5
  • Beverley Balkau
    • 6
  • for the EGIR-RISC study group
  1. 1.Research Area for Multifactorial Diseases and Complex PhenotypesBambino Gesù Children’s HospitalRomeItaly
  2. 2.CNR Institute of NeurosciencePaduaItaly
  3. 3.Institute of Cardiovascular and Medical Sciences, BHF Glasgow Cardiovascular Research CentreUniversity of GlasgowGlasgowUK
  4. 4.Department of Internal Medicine, IRCCS Policlinico Universitario A. GemelliCatholic University of Sacred HeartRomeItaly
  5. 5.Department of DiabetesKing’s College LondonLondonUK
  6. 6.CESP Centre for Research in Epidemiology and Population HealthUniv Paris-Saclay, Univ Paris SudVillejuifFrance

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