A diabetes-predictive amino acid score and future cardiovascular disease

Magnusson, Martin; Lewis, Gregory D.; Ericson, Ulrika; Orho‐Melander, Marju; Hedblad, Bo; Engström, Gunnar; Östling, Gerd; Clish, Clary B.; Wang, Thomas J.; Gerszten, Robert E.; Melander, Olle

doi:10.1093/eurheartj/ehs424

Cited by 241 publications

(213 citation statements)

References 30 publications

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“…For each diet, we examined the direction of change in the concentrations of the metabolites that have been shown to predict the risk of type 2 diabetes (31,32,(38)(39)(40)(41)(42). We annotated each metabolite by whether the change by diet was in the direction that increased or decreased risk of disease.…”

Section: Disease Riskmentioning

confidence: 99%

“…Multiple metabolites that have been linked to risk of type 2 diabetes (31,32,(38)(39)(40)(41)(42) showed strong or moderate associations with diet, including amino acids (isoleucine, leucine, valine, tyrosine, serine and glutamine), lipids (C18:2 lysophosphatidylethanolamine (LPE), C22:6 LPE, C56:9 TAG, C58:10 TAG, and C60:12 TAG), and others (2-aminoadipate, betaine, and C3 carnitine) as depicted in Supplemental Figures 5 and 6. The concordance between the metabolite profile that predicts type 2 diabetes risk and the dietassociated changes varied across classes of metabolites.…”

Section: Effect Of Diet On Metabolites That Predict Disease Riskmentioning

confidence: 99%

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Metabolomic profiles as reliable biomarkers of dietary composition

Esko¹,

Hirschhorn

Feldman

et al. 2017

The American Journal of Clinical Nutrition

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Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects. Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol. Design: Twenty-one adults with a high body mass index (in kg/m 2 ; mean 6 SD: 34.4 6 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons. Results: Of 333 metabolites, we identified 152 whose concentrations differed for $1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (.95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors. Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.Am J Clin Nutr 2017;105:547-54.

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Section: Disease Riskmentioning

confidence: 99%

Section: Effect Of Diet On Metabolites That Predict Disease Riskmentioning

confidence: 99%

Metabolomic profiles as reliable biomarkers of dietary composition

Esko¹,

Hirschhorn

Feldman

et al. 2017

The American Journal of Clinical Nutrition

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“…106 The 3 amino acids most strongly associated with diabetes mellitus (isoleucine, tyrosine, and phenylalanine) were subsequently shown to predict incident atherosclerotic cardiovascular disease (MI or stroke), carotid intima-media thickness and plaques, and exerciseinduced myocardial ischemia. 107 These findings highlight a potential key role of amino acid metabolism in early diabetes mellitus development, and they point to a potential link between type 2 diabetes mellitus and susceptibility to atherosclerotic cardiovascular disease.…”

Section: Musunuru Et Al Expressed Genome In Cardiovascular Diseases Amentioning

confidence: 82%

The Expressed Genome in Cardiovascular Diseases and Stroke: Refinement, Diagnosis, and Prediction: A Scientific Statement From the American Heart Association

Musunuru¹,

Ingelsson²,

Fornage³

et al. 2017

Circ Cardiovasc Genet

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Abstract-There have been major advances in our knowledge of the contribution of DNA sequence variations to cardiovascular disease and stroke. However, the inner workings of the body reflect the complex interplay of factors beyond the DNA sequence, including epigenetic modifications, RNA transcripts, proteins, and metabolites, which together can be considered the "expressed genome." The emergence of high-throughput technologies, including epigenomics, transcriptomics, proteomics, and metabolomics, is now making it possible to address the contributions of the expressed genome to cardiovascular disorders. This statement describes how the expressed genome can currently and, in the future, potentially be used to diagnose diseases and to predict who will develop diseases such as coronary artery disease, stroke, heart failure, and arrhythmias. (Circ Cardiovasc Genet. 2017;10:e000037. DOI: 10.1161/HCG.0000000000000037.)Key Words: AHA Scientific Statements ◼ cardiovascular diseases ◼ DNA ◼ epigenomics ◼ genome ◼ metabolomics ◼ proteomics ◼ strokeThe American Heart Association makes every effort to avoid any actual or potential conflicts of interest that may arise as a result of an outside relationship or a personal, professional, or business interest of a member of the writing panel. Specifically, all members of the writing group are required to complete and submit a Disclosure Questionnaire showing all such relationships that might be perceived as real or potential conflicts of interest.This statement was approved by the American Heart Association Science Advisory and Coordinating Committee on March 13, 2017, and the American Heart Association Executive Committee on April 17, 2017. A copy of the document is available at http://professional.heart.org/statements by using either "Search for Guidelines & Statements" or the "Browse by Topic" area. To purchase additional reprints, call 843-216-2533 or e-mail kelle.ramsay@ wolterskluwer.com.The American Heart Association requests that this document be cited as follows: Expert peer review of AHA Scientific Statements is conducted by the AHA Office of Science Operations. For more on AHA statements and guidelines development, visit http://professional.heart.org/statements. Select the "Guidelines & Statements" drop-down menu, then click "Publication Development."Permissions: Multiple copies, modification, alteration, enhancement, and/or distribution of this document are not permitted without the express permission of the American Heart Association. Instructions for obtaining permission are located at http://www.heart.org/HEARTORG/General/CopyrightPermission-Guidelines_UCM_300404_Article.jsp. A link to the "Copyright Permissions Request Form" appears on the right side of the page. I n no small part as a result of the completion of the Human Genome Project, considerable effort has been invested over the past few decades in understanding the contribution of genetics to the risk of cardiovascular diseases and stroke. Genomewide association studies, candidate gene sequencing studies, a...

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“…A previous study reported the integration of metabolite levels of bio fluids and other biochemical information (e.g., glucose and HbA1c) could better reflect T2DM risk than a single established risk factor [29,[39][40][41][42][43][44][45][46]. Determination of the levels of several amino acid and other metabolites that showed a marked change after metformin treatment could significantly improve drug response prediction and serve as markers for the diagnosis of T2DM.…”

Section: Discussionmentioning

confidence: 99%

“…Several studies suggested that higher plasma amino acid level profile could reflect hyperglycemia odds and incidence of type 2 diabetes mellitus hazards assessment [29,[43][44][45]. Phenylalanine and tyrosine could be a strong predictor of diabetes [46], further theses AAAs are future biomarkers of long-term impaired insulin sensitivity.…”

Section: Discussionmentioning

confidence: 99%

Mechanism by which Metformin Influence Metabolic Changes in Human: A Systematic-Review

Park¹,

Kim²,

Shin³

2016

J Diabetes Metab

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Metformin is the most widely used oral antihyperglycemic agent for the improvement of type 2 diabetes mellitus (T2DM). In patients with T2DM, metformin increases insulin sensitivity and reduces glucose production. In this systematic review, we identified and compared metabolic changes induced by metformin administration.We searched articles published within the past 5 years on Pubmed.gov by using the keywords "metformin and metabolomics." No restrictions were placed on the languages, species, or gender during the selection of articles. From the 29 identified articles, we excluded non-human in vivo or in vitro studies, studies in cancer patients, and studies in which the focus was not on variation in the levels of metabolites after administration of medication such as pharmacogenetic studies. Finally, we selected 8 articles and compared their results.In the selected study results, a treatment with metformin and a combination of metformin and other anti-diabetic agents decreased the levels of phenylalanine, tyrosine, lysine, and glutamate to 5.58 ± 2.23%, 11.50 ± 2.12%, 25.28 ± 27.90%, and 35.49 ± 26.18% (mean ± SD), respectively, but increased the levels of alanine to 16.00% in 3 months-5 years of follow-up after metformin treatment compared to the control. The levels of total cholesterol and low-density lipoprotein (LDL) cholesterol (5.28%) decreased, whereas those of high-density lipoprotein (HDL) cholesterol increased by 34.65% in 18-30 months of follow-up after administration of metformin.Metformin administration in human alters the blood concentration of phenylalanine, tyrosine, glutamate and lysine. Further confirmatory studies are required to understand how these metabolites related to the drug mechanism and also drug response, and to develop the biomarkers for predicting metformin response in humans.

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A diabetes-predictive amino acid score and future cardiovascular disease

Abstract: This study identifies branched-chain and aromatic amino acids as novel markers of CVD development and as an early link between diabetes and CVD susceptibility.

Cited by 241 publications

References 30 publications

Metabolomic profiles as reliable biomarkers of dietary composition

Metabolomic profiles as reliable biomarkers of dietary composition

The Expressed Genome in Cardiovascular Diseases and Stroke: Refinement, Diagnosis, and Prediction: A Scientific Statement From the American Heart Association

Mechanism by which Metformin Influence Metabolic Changes in Human: A Systematic-Review

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