2-Aminoadipic acid is a biomarker for diabetes risk Wang, Thomas J.; Ngo, Debby; Psychogios, Nikolaos; Dejam, Andre; Larson, Martin G.; Vasan, Ramachandran S.; Ghorbani, Anahita; O'Sullivan, John; Cheng, Susan; Rhee, Eugene P.; Sinha, Sumita; McCabe, Elizabeth; Fox, Caroline S.; O'Donnell, Christopher J.; Ho, Jennifer E.; Florez, Jose C.; Magnusson, Martin; Pierce, Kerry A.; Souza, Amanda L.; Yu, Yi; Carter, Christian; Light, Peter E.; Melander, Olle; Clish, Clary B.; Gerszten, Robert E. Published in: Journal of Clinical Investigation DOI: 10.1172/JCI64801 Published: 2013-01-01

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Citation for published version (APA): Wang, T. J., Ngo, D., Psychogios, N., Dejam, A., Larson, M. G., Vasan, R. S., ... Gerszten, R. E. (2013). 2Aminoadipic acid is a biomarker for diabetes risk. Journal of Clinical Investigation, 123(10), 4309-4317. DOI: 10.1172/JCI64801

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Research article

2-Aminoadipic acid is a biomarker for diabetes risk Thomas J. Wang,1,2,3,4 Debby Ngo,1,5 Nikolaos Psychogios,1 Andre Dejam,1 Martin G. Larson,3,6 Ramachandran S. Vasan,3,7 Anahita Ghorbani,2,3 John O’Sullivan,1 Susan Cheng,3,8 Eugene P. Rhee,1,9,10 Sumita Sinha,1 Elizabeth McCabe,11 Caroline S. Fox,3,12,13 Christopher J. O’Donnell,2,3,13 Jennifer E. Ho,3,7 Jose C. Florez,10,14,15 Martin Magnusson,16,17 Kerry A. Pierce,10 Amanda L. Souza,10 Yi Yu,18 Christian Carter,18 Peter E. Light,18 Olle Melander,17,19 Clary B. Clish,10 and Robert E. Gerszten1,2,10 1Cardiovascular

Research Center and 2Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. Heart Study of the National Heart, Lung and Blood Institute and Boston University School of Medicine, Framingham, Massachusetts, USA. 4Division of Cardiovascular Medicine, Vanderbilt University, Nashville, Tennessee, USA. 5Pulmonary Division, Harvard Medical School, Boston, Massachusetts, USA. 6Department of Mathematics and Statistics and 7Preventive Medicine Section, Department of Medicine, Boston University, Boston, Massachusetts, USA. 8Cardiovascular Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA. 9Renal Division, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. 10Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. 11School of Public Health, Boston University, Boston, Massachusetts, USA. 12Division of Endocrinology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA. 13National Heart, Lung and Blood Institute Division of Intramural Research, Bethesda, Maryland, USA. 14Diabetes Unit and 15Center for Human Genetic Research, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. 16Department of Cardiology, Skåne University Hospital, Malmö, Sweden. 17Department of Clinical Sciences, Lund University, Malmö, Sweden. 18Alberta Diabetes Institute, Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada. 19Center of Emergency Medicine, Skåne University Hospital, Malmö, Sweden. 3Framingham

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. Introduction The burden of type 2 diabetes mellitus (T2DM) is increasing, with an estimated 366 million cases worldwide. Given the availability of proven interventions for delaying or preventing diabetes, early identification of individuals at risk is a public health priority (1–4). Emerging technologies have enhanced the feasibility of acquiring detailed profiles of a human’s metabolic status (metabolite profiling, or metabolomics) (5–9). These techniques, which allow the assessment of large numbers of metabolites that are substrates and products in metabolic pathways, have the potential to identify biochemical changes before the onset of overt clinical disease. Ongoing improvements in metabolomics technologies now provide sufficient sample throughput to make studies of epidemiological cohorts more feasible (6–9). In an initial “proof-of-principle” Authorship note: Thomas J. Wang, Debby Ngo, and Nikolaos Psychogios are co–first authors. Conflict of interest: R.E. Gerszten, R.S. Vasan, M.G. Larson, and T.J. Wang are named as coinventors on a patent application relating to amino acid predictors of diabetes. J.C. Florez has received consulting honoraria from Novartis, Lilly, and Pfizer. P.E. Light has received consulting honoraria from Merck. Citation for this article: J Clin Invest. 2013;123(10):4309–4317. doi:10.1172/JCI64801.

study, we found that branched chain and aromatic amino acid concentrations had a significant association with future T2DM in individuals with normal glucose tolerance (8). We recently developed a liquid chromatography–tandem mass spectrometry (LC-MS/MS) method capable of profiling 70 intermediary organic acids, purines, pyrimidines, and other compounds that had not been assayed previously in our population-based studies (8, 9). Using this method, we sought to identify new metabolite biomarkers of diabetes risk in 2 large, epidemiologic cohorts with more than a decade of followup. We then studied the functional effects of the strongest metabolite predictor in cell-based and animal studies. Results 2-AAA predicts future diabetes in the Framingham Heart Study. Baseline clinical characteristics are shown in Table 1. Cases and controls were similar with respect to age, sex, BMI, and fasting glucose. From a screen of 70 metabolites, 2-aminoadipic acid (2-AAA) had the strongest association with future diabetes (P = 0.0009, with a higher fasting concentration in the cases). Results for all metabolites profiled are shown in Supplemental Table 1 (supplemental material available online with this article; doi:10.1172/JCI64801DS1).

The Journal of Clinical Investigation   http://www.jci.org   Volume 123   Number 10   October 2013

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research article Table 1 Baseline characteristics Cases (n = 188) Clinical characteristics

Matched controls (n = 188)

FHS Additional random cohort (n = 1,561)

Age (yr) 56 ± 9 57 ± 8 Women 43% 43% 30.5 ± 5.0 30.0 ± 5.5 BMI (kg/m2) Waist circumference (cm) 102 ± 12 100 ± 14 Hypertension 53% 53% Parental history of diabetesA 32% 18% Physical activity index 36 ± 6 35 ± 7 Total caloric intake (kcal) 1,988 ± 658 1,863 ± 601 Total protein intake (g) 82 ± 27 77 ± 27 Lysine intake (g) 6 ± 2 6 ± 2 Fasting glucose (mg/dl) 105 ± 9 105 ± 9

55 ± 10 54% 26.7 ± 4.4 91 ± 13 30% 19% 35 ± 6 1,854 ± 611 77 ± 27 5 ± 2 93 ± 9

Whole cohort (n = 1,937)

MDC Cases Matched controls (n = 162) (n = 162)

55±10 58 ± 6 58 ± 6 52% 55% 55% 27.4 ± 4.8 28.2 ± 4.8 28.5 ± 4.9 93 ± 14 91 ± 14 91 ± 16 34% 77% 74% 20% 7% 2% 35 ±6 – – 1,868 ± 616 – – 77 ± 27 – – 6 ± 2 – – 96 ± 10 97 ± 8 97 ± 7

Values are mean ± SD or percentage. AParental history information missing in 57 participants in Framingham sample.

Conditional logistic regression models were performed adjusting for age, sex, BMI, and fasting glucose (Table 2). Each SD increment in log marker was associated with a 60% increased odds of future diabetes (P = 0.002). Individuals in the top quartile of plasma 2-AAA concentration had a 4-fold higher odds of developing diabetes over the 12-year follow-up period compared with those in the lowest quartile (adjusted odds ratio 4.49, 95% CI, 1.86 to 10.89). Results were similar after further adjustment for parental history of diabetes, total caloric intake, and dietary protein, fat, or carbohydrates (data not shown). There was no interaction between follow-up year and the case-control difference for 2-AAA (P > 0.10), suggesting a stable association with new-onset diabetes during the follow-up period. The association with 2-AAA was similar in analyses restricted to diabetes cases diagnosed 8 or more years after the baseline examination. In this analysis, the odds ratio for individuals in the highest quartile of 2-AAA was 4.16 (95% CI, 1.26–13.8). 2-AAA is associated with insulin resistance and β cell function. Results for biochemical measures of insulin resistance and β cell function are shown in Supplemental Table 2. Fasting concentrations of 2-AAA

were moderately correlated with fasting insulin (age- and sexadjusted partial correlation, r = 0.25; P < 0.001), homeostasis model assessment of insulin resistance (HOMA-IR) (r = 0.24; P < 0.001), homeostasis model assessment of β cell function (HOMA-B) (r = 0.25, P < 0.001), and 2-hour glucose during oral glucose tolerance testing (r = 0.14; P = 0.006). Baseline concentrations of 2-AAA and hemoglobin A1c (HbA1c) were not significantly correlated (r = 0.05; P = 0.37), consistent with the nondiabetic status of all individuals at baseline. The association of 2-AAA levels and incident diabetes was unchanged even after adjusting for these measures of insulin resistance and β cell function (Table 3). There were also no significant associations between 2-AAA and dietary intake of fat, protein, carbohydrates, or lysine assessed using a food frequency questionnaire (ref. 10 and data not shown). Replication of the results. We performed replication studies in the Malmö Diet and Cancer Study (MDC). As in the Framingham Heart Study (FHS), concentrations of 2-AAA were significantly higher in cases compared with matched controls (P = 0.004; pooled P < 0.0001). There was a 57% increased odds

Table 2 2-AAA and the risk of future diabetes Model 2-AAA

FHS (188 cases, 188 controls) 12-year follow-up

MDC (162 cases, 162 controls) 13-year follow-up

Combined sample (350 cases, 350 controls)

As continuous variable Per SD increment P value

1.60 (1.19–2.16) 1.57 (1.15–2.14) 1.59 (1.28–1.97) 0.002 0.004