Lysine pathway metabolites and the risk of type 2 diabetes and cardiovascular disease in the PREDIMED study: results from two case-cohort studies

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Abstract

Background

The pandemic of cardiovascular disease (CVD) and type 2 diabetes (T2D) requires the identification of new predictor biomarkers. Biomarkers potentially modifiable with lifestyle changes deserve a special interest. Our aims were to analyze: (a) The associations of lysine, 2-aminoadipic acid (2-AAA) or pipecolic acid with the risk of T2D or CVD in the PREDIMED trial; (b) the effect of the dietary intervention on 1-year changes in these metabolites, and (c) whether the Mediterranean diet (MedDiet) interventions can modify the effects of these metabolites on CVD or T2D risk.

Methods

Two unstratified case-cohort studies nested within the PREDIMED trial were used. For CVD analyses, we selected 696 non-cases and 221 incident CVD cases; for T2D, we included 610 non-cases and 243 type 2 diabetes incident cases. Metabolites were quantified using liquid chromatography–tandem mass spectrometry, at baseline and after 1-year of intervention.

Results

In weighted Cox regression models, we found that baseline lysine (HR _{+1 SD increase} = 1.26; 95% CI 1.06–1.51) and 2-AAA (HR _{+1 SD increase} = 1.28; 95% CI 1.05–1.55) were both associated with a higher risk of T2D, but not with CVD. A significant interaction (p = 0.032) between baseline lysine and T2D on the risk of CVD was observed: subjects with prevalent T2D and high levels of lysine exhibited the highest risk of CVD. The intervention with MedDiet did not have a significant effect on 1-year changes of the metabolites.

Conclusions

Our results provide an independent prospective replication of the association of 2-AAA with future risk of T2D. We show an association of lysine with subsequent CVD risk, which is apparently diabetes-dependent. No evidence of effects of MedDiet intervention on lysine, 2-AAA or pipecolic acid changes was found.

Trial registration ISRCTN35739639; registration date: 05/10/2005; recruitment start date 01/10/2003

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Most cited references 18

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Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis

Marta Guasch-Ferré, Adela Hruby, Estefanía Toledo … (2016)

OBJECTIVE To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite. RESULTS We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24–1.48]; I 2 = 9.5%), 36% for leucine (1.36 [1.17–1.58]; I 2 = 37.4%), 35% for valine (1.35 [1.19–1.53]; I 2 = 45.8%), 36% for tyrosine (1.36 [1.19–1.55]; I 2 = 51.6%), and 26% for phenylalanine (1.26 [1.10–1.44]; I 2 = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81–0.96] and 0.85 [0.82–0.89], respectively; both I 2 = 0.0%). CONCLUSIONS In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.

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Cohort profile: design and methods of the PREDIMED study.

Miguel Martínez-González, Dolores Corella, Jordi Salas-Salvadó … (2012)

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2-Aminoadipic acid is a biomarker for diabetes risk.

NIKOLAOS PSYCHOGIOS, Anh D. Ngo, Robert Gerszten … (2013)

Improvements in metabolite-profiling techniques are providing increased breadth of coverage of the human metabolome and may highlight biomarkers and pathways in common diseases such as diabetes. Using a metabolomics platform that analyzes intermediary organic acids, purines, pyrimidines, and other compounds, we performed a nested case-control study of 188 individuals who developed diabetes and 188 propensity-matched controls from 2,422 normoglycemic participants followed for 12 years in the Framingham Heart Study. The metabolite 2-aminoadipic acid (2-AAA) was most strongly associated with the risk of developing diabetes. Individuals with 2-AAA concentrations in the top quartile had greater than a 4-fold risk of developing diabetes. Levels of 2-AAA were not well correlated with other metabolite biomarkers of diabetes, such as branched chain amino acids and aromatic amino acids, suggesting they report on a distinct pathophysiological pathway. In experimental studies, administration of 2-AAA lowered fasting plasma glucose levels in mice fed both standard chow and high-fat diets. Further, 2-AAA treatment enhanced insulin secretion from a pancreatic β cell line as well as murine and human islets. These data highlight a metabolite not previously associated with diabetes risk that is increased up to 12 years before the onset of overt disease. Our findings suggest that 2-AAA is a marker of diabetes risk and a potential modulator of glucose homeostasis in humans.

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Author and article information

Contributors

Miguel A. Martínez-González: +34 948425600 806463 , mamartinez@unav.es

Journal

Journal ID (nlm-ta): Cardiovasc Diabetol

Journal ID (iso-abbrev): Cardiovasc Diabetol

Title: Cardiovascular Diabetology

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2840

Publication date (Electronic): 13 November 2019

Publication date PMC-release: 13 November 2019

Publication date Collection: 2019

Volume: 18

Electronic Location Identifier: 151

Affiliations

[1 ]ISNI 0000000419370271, GRID grid.5924.a, Department of Preventive Medicine and Public Health, , University of Navarra, ; Pamplona, Spain

[2 ]IdiSNA, Navarra Institute for Health Research, Pamplona, Spain

[3 ]ISNI 0000 0000 9314 1427, GRID grid.413448.e, CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, ; Madrid, Spain

[4 ]GRID grid.66859.34, Broad Institute of MIT and Harvard University, ; Cambridge, USA

[5 ]Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Spain

[6 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Epidemiology, , Harvard T.H. Chan School of Public Health, ; Boston, USA

[7 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Biostatistics, , Harvard T.H. Chan School of Public Health, ; Boston, USA

[8 ]ISNI 0000 0001 2284 9230, GRID grid.410367.7, Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d’Investigació Sanitària Pere Virgili, , Rovira i Virgili University, ; Reus, Spain

[9 ]ISNI 0000 0001 2173 938X, GRID grid.5338.d, Department of Preventive Medicine, , University of Valencia, ; Valencia, Spain

[10 ]ISNI 0000 0004 1937 0247, GRID grid.5841.8, Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biomediques August Pi Sunyer (IDI- BAPS), Hospital Clinic, , University of Barcelona, ; Barcelona, Spain

[11 ]GRID grid.10403.36, Department of Internal Medicine, , Institut d’Investigacions Biomediques August Pi Sunyer (IDI-BAPS), ; Barcelona, Spain

[12 ]ISNI 0000 0001 2298 7828, GRID grid.10215.37, Department of Preventive Medicine, , University of Malaga, ; Malaga, Spain

[13 ]ISNI 0000 0004 1767 8811, GRID grid.411142.3, Cardiovascular and Nutrition Research Group, , Institut de Recerca Hospital del Mar (IMIM), ; Barcelona, Spain

[14 ]Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain

[15 ]ISNI 0000 0004 1796 5984, GRID grid.411164.7, Instituto de Investigación Sanitaria de Palma (IdISPa), , University Hospital of Son Espases, ; Palma de Mallorca, Spain

[16 ]Department of Cardiology, University Hospital of Alava, Vitoria, Spain

[17 ]ISNI 0000 0004 1769 9380, GRID grid.4521.2, Research Institute of Biomedical and Health Sciences, , University of Las Palmas de Gran Canaria, ; Las Palmas, Spain

[18 ]ISNI 0000 0004 0378 8294, GRID grid.62560.37, Channing Division for Network Medicine, Department of Medicine, , Brigham and Women’s Hospital and Harvard Medical School, ; Boston, USA

Article

Publisher ID: 958

DOI: 10.1186/s12933-019-0958-2

PMC ID: 6852717

PubMed ID: 31722714

SO-VID: 93d316ba-428c-4d29-b9aa-23f196839055

License:

Open AccessThis 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 21 August 2019

Date accepted : 28 October 2019

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000050, National Heart, Lung, and Blood Institute;

Award ID: HL118264

Award ID: 2R01HL118264

Award Recipient : Frank B. Hu

Funded by: FundRef http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;

Award ID: R01DK102896

Award Recipient : Frank B. Hu

Funded by: FundRef http://dx.doi.org/10.13039/501100004587, Instituto de Salud Carlos III;

Award ID: RD06/0045

Award ID: RTIC G03/140

Award Recipient : Ramon Estruch Miguel A. Martínez-González

Funded by: FundRef http://dx.doi.org/10.13039/501100006318, Universidad Carlos III de Madrid;

Award ID: CB06/03

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: biomarkers,metabolites,cardiovascular disease,type 2 diabetes,dietary intervention

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: biomarkers, metabolites, cardiovascular disease, type 2 diabetes, dietary intervention

Lysine pathway metabolites and the risk of type 2 diabetes and cardiovascular disease in the PREDIMED study: results from two case-cohort studies

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Results

Conclusions

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Journal of the ASEAN Federation of Endocrine Societies

Most cited references 18

Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis

Cohort profile: design and methods of the PREDIMED study.

2-Aminoadipic acid is a biomarker for diabetes risk.

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