Application of Metabolomics to Diagnosis of Insulin Resistance

Milburn, Michael V.; Lawton, Kay A.

doi:10.1146/annurev-med-061511-134747

Cited by 54 publications

(47 citation statements)

References 38 publications

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“…Metabolites represent an intermediate biological process that bridges gene function, nongenetic factors, and phenotypic end points (13,14). Numerous studies have shown that metabolic phenotypes can provide novel insights into gene function, mechanisms of disease pathogenesis, and biomarkers for disease diagnosis and prognosis (13,(15)(16)(17)(18)(19)(20)(21). MS, in combination with liquid chromatography (LC) and GC, has become the main platform for metabolomic analysis.…”

Section: Liningmentioning

confidence: 99%

Plasma metabolomic profiles enhance precision medicine for volunteers of normal health

Guo

Milburn

Ryals

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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168

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Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broadspectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care.metabolomics | whole-exome sequencing | functional phenotyping | gene penetrance | disease assessment T he rapid progression of next generation sequencing (NGS) technology in recent years has significantly reduced the cost and time required to query a patient's genome accurately. The ability to comprehensively survey genetic variations and their associations with diseases is currently central to personalized medicine and can potentially transform clinical diagnosis and disease management. Indeed, whole-genome sequencing and whole-exome sequencing (WES) have been used successfully to investigate both common and rare diseases (1-7), as well as to provide guidance for drug treatment (8). Despite these successes, significant limitations remain on applying NGS in clinical settings for patient care (9-11). One of the key challenges is the proper interpretation of NGS data. It is known that human exome sequencing identifies ∼10,000 nonsynonymous single-nucleotide variants (12). The computational algorithms and databases for predicting and prioritizing functional pathogenic variants are not yet fully effective. More importantly, the impact of nongenetic factors, such ...

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Section: Liningmentioning

confidence: 99%

Plasma metabolomic profiles enhance precision medicine for volunteers of normal health

Guo

Milburn

Ryals

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

168

144

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“…Metabolomic studies in metabolic diseases 31 have been used to identify novel biomarkers that associate with IR 23,32,33 and predict T2DM. [34][35][36] The three metabolites used in the test have a number of potential roles in metabolic pathways relevant to insulin action, insulin secretion, or β-cell function.…”

Section: Metabolite Biomarkers Of Insulin Resistancementioning

confidence: 99%

A Novel Fasting Blood Test for Insulin Resistance and Prediabetes

Cobb

Gall

Adam

et al. 2013

J Diabetes Sci Technol

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Background: Insulin resistance (IR) can precede the dysglycemic states of prediabetes and type 2 diabetes mellitus (T2DM) by a number of years and is an early marker of risk for metabolic and cardiovascular disease. There is an unmet need for a simple method to measure IR that can be used for routine screening, prospective study, risk assessment, and therapeutic monitoring. We have reported several metabolites whose fasting plasma levels correlated with insulin sensitivity. These metabolites were used in the development of a novel test for IR and prediabetes. Methods: Data from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study were used in an iterative process of algorithm development to define the best combination of metabolites for predicting the M value derived from the hyperinsulinemic euglycemic clamp, the gold standard measure of IR. Subjects were divided into a training set and a test set for algorithm development and validation. The resulting calculated M score, MQ, was utilized to predict IR and the risk of progressing from normal glucose tolerance to impaired glucose tolerance (IGT) over a 3 year period. Results: MQ correlated with actual M values, with an r value of 0.66. In addition, the test detects IR and predicts 3 year IGT progression with areas under the curve of 0.79 and 0.70, respectively, outperforming other simple measures such as fasting insulin, fasting glucose, homeostatic model assessment of IR, or body mass index. Conclusions: The result, Quantose™, is a simple test for IR based on a single fasting blood sample and may have value as an early indicator of risk for the development of prediabetes and T2DM.

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“…Most reported elevated plasma levels of branched-chain amino acids (BCAA; leucine, isoleucine, valine) in obese children, adolescents, and adults compared with their lean counterparts (1,5,18,29,32,33,50,58), and weight loss was associated with lower BCAA levels (39). Circulating alanine, phenylalanine, tyrosine, glutamate/ glutamine, aspartate/asparagine, and arginine have also been shown to be increased in obese individuals (33).…”

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confidence: 99%

Alterations of plasma metabolite profiles related to adipose tissue distribution and cardiometabolic risk

Boulet

Chevrier

Grenier-Larouche

et al. 2015

American Journal of Physiology-Endocrinology and Metabolism

117

106

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profiling of obese individuals revealed altered concentrations of many metabolites, especially branched-chain amino acids (BCAA), possibly linked to altered adipose tissue BCAA catabolism. We tested the hypothesis that some features of this metabolite signature relate closely to visceral obesity and concomitant alterations in cardiometabolic risk factors. We also postulated that alterations in BCAA-catabolizing enzymes are predominant in visceral adipose tissue. Fifty-nine women (BMI 20 -41 kg/m 2 ) undergoing gynecologic surgery were recruited and characterized for overall and regional adiposity, blood metabolite levels using targeted metabolomics, and cardiometabolic risk factors. Adipose samples (visceral and subcutaneous) were obtained and used for gene expression and Western blot analyses. Obese women had significantly higher circulating BCAA and kynurenine/tryptophan (Kyn/Trp) ratio than lean or overweight women (P Ͻ 0.01). Principal component analysis confirmed that factors related to AA and the Kyn/Trp ratio were positively associated with BMI, fat mass, visceral or subcutaneous adipose tissue area, and subcutaneous adipocyte size (P Յ 0.05). AA-related factor was positively associated with HOMA-IR (P Յ 0.01). Factors reflecting glycerophospholipids and sphingolipids levels were mostly associated with altered blood lipid concentrations (P Յ 0.05). Glutamate level was the strongest independent predictor of visceral adipose tissue area (r ϭ 0.46, P Ͻ 0.001). Obese women had lower expression and protein levels of BCAA-catabolizing enzymes in visceral adipose tissue than overweight or lean women (P Յ 0.05). We conclude that among metabolites altered in obesity plasma concentrations of BCAA and the Kyn/Trp ratio are closely related to increased adiposity. Alterations in expression and protein levels of BCAA-catabolizing enzymes are predominant in visceral adipose tissue.

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Application of Metabolomics to Diagnosis of Insulin Resistance

Cited by 54 publications

References 38 publications

Plasma metabolomic profiles enhance precision medicine for volunteers of normal health

Plasma metabolomic profiles enhance precision medicine for volunteers of normal health

A Novel Fasting Blood Test for Insulin Resistance and Prediabetes

Alterations of plasma metabolite profiles related to adipose tissue distribution and cardiometabolic risk

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