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Emerging Applications of Metabolomic and Genomic Profiling in Diabetic Clinical Medicine

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Emerging Applications of Metabolomic and Genomic Profiling in Diabetic Clinical Medicine Reviews/Commentaries/ADA Statements REVIEW Emerging Applications of Metabolomic and Genomic Profiling in Diabetic Clinical Medicine AINE M. MCKILLOP, PHD however, powerful methodologies are now PETER R. FLATT, PHD available for exploitation of novel quantita- tive and qualitative disease-related biomark- ers. Novel biomarkers are needed that are Clinical and epidemiological metabolomics provides a unique opportunity to look at genotype- independent of known clinical risk factors. phenotype relationships as well as the body’s responses to environmental and lifestyle factors. fl Fundamentally, metabolomics aims to Fundamentally, it provides information on the universal outcome of in uencing factors on monitor changes in products of metabo- disease states and has great potential in the early diagnosis, therapy monitoring, and understand- lism and provide valuable information on ing of the pathogenesis of disease. Diseases, such as diabetes, with a complex set of interactions fl between genetic and environmental factors, produce changes in the body’s biochemical profile, arangeofin uencing factors and gene- thereby providing potential markers for diagnosis and initiation of therapies. There is clearly related outcomes. Exploitation of genomic a need to discover new ways to aid diagnosis and assessment of glycemic status to help reduce technology in recent times has resulted in diabetes complications and improve the quality of life. Many factors, including peptides, proteins, many technical advances, and genomic metabolites, nucleic acids, and polymorphisms, have been proposed as putative biomarkers for analysis has now emerged as a valuable diabetes. Metabolomics is an approach used to identify and assess metabolic characteristics, changes, tool in predicting the body’s response to and phenotypes in response to influencing factors, such as environment, diet, lifestyle, and path- fi stimuli caused by disease or injury. Indeed, ophysiological states. The speci city and sensitivity using metabolomics to identify biomarkers of methodologies such as epigenetic profil- disease have become increasingly feasible because of advances in analytical and information tech- ing, sequencing technologies, microarrays, nologies. Likewise, the emergence of high-throughput genotyping technologies and genome-wide fi association studies has prompted the search for genetic markers of diabetes predisposition or sus- functional ngerprinting, and analysis of ceptibility. In this review, we consider the application of key metabolomic and genomic method- genomic alternations are all well-established ologies in diabetes and summarize the established, new, and emerging metabolomic and genomic methodologies in practice. Complementing biomarkers for the disease. We conclude by summarizing future insights into the search for im- these technologies with computational proved biomarkers for diabetes research and human diagnostics. methods/bioinformatics that integrate large – amounts of heterogeneous genetic and Diabetes Care 34:2624 2630, 2011 genomic information has helped provide meaningful results to aid our understanding iabetes is a rapidly increasing meta- accompanied by the characterization and of the complex changes of genes and macro- Dbolic disorder precipitated by complex quantification of small molecules. It can often molecules. There is now a clear need to dis- and poorly understood interactions be confused with the term metabonomics, cover novel and effective clinical biomarkers between multiple environmental and genetic which represents the global, dynamic met- using technologies that encompass an array factors. The consequences of diabetes are far abolic response of living systems to biolog- of different methodologies. Chromatogra- reaching, and disturbances in both the se- ical stimuli or genetic manipulation. Both phy, two-dimensional electrophoresis, cretion and action of insulin impact on the terms are closely affiliated with each other mass spectrometry, functional magnetic global regulation of metabolism, affecting the owing to the analytical and experimental resonance, positron emission tomography, composition of blood and other body fluids. technologies used in each field. The obser- and protein/gene sequencing are some Understanding of this process and identifi- vation of the characteristics and changes in examples being used to unravel the body’s cation of potential disease biomarkers have metabolism by metabolomics allow the re- complex biological systems. Sensitive and been greatly facilitated in recent years by the sulting data to be merged with data from the high-resolution techniques used in clinical upsurge in new technologies for comprehen- other “-omic” technologies. Genomic, meta- metabolomics, such as nuclear magnetic sive metabolic profiling, which are often bolomic, and proteomic state-of-the-art resonance, gas chromatography–mass collectively termed metabolomics. technologies are now used increasingly by spectrometry, and liquid chromatography– researchers to identify clinical methodolo- mass spectrometry, are sensitive and robust fi Metabolomic pro ling in clinical gies for the early diagnosis and monitoring and have the capacity to process large vol- medicine of human degenerative diseases such as di- umes of data from population studies (1,2). fi Metabolomics is de ned as the analyti- abetes. Classical risk factors still have an im- However, overinterpretation of data remains cal description of biological samples portant role to play in diabetes assessment; one of the key limitations to be overcome ccccccccccccccccccccccccccccccccccccccccccccccccc for successful exploitation of metabolomics From the SAAD Centre for Pharmacy and Diabetes, School of Biomedical Sciences, University of Ulster, and metabonomics. Coleraine, Northern Ireland, U.K. In this brief review, we consider recent Corresponding author: Aine M. McKillop, [email protected]. applications of metabolomic and related Received 3 May 2011 and accepted 6 September 2011. technologies in diabetes together with their DOI: 10.2337/dc11-0837 © 2011 by the American Diabetes Association. Readers may use this article as long as the work is properly use in relation to clinical diagnostics. Tech- cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/ nical details of the methodologies involved licenses/by-nc-nd/3.0/ for details. and their use in basic diabetes research have 2624 DIABETES CARE, VOLUME 34, DECEMBER 2011 care.diabetesjournals.org McKillop and Flatt Table 1dEstablished, new, and emerging metabolomic biomarkers for type 2 diabetes discover new markers, as illustrated in ges- tational diabetes mellitus, where there is a Predictor Abbreviation Reference no. drive to reconsider diagnostic criteria recog- nizing the possibility of adverse pregnancy Metabolic markers outcomes of milder levels of glucose intol- Insulin 7 and 8 erance than hitherto appreciated. Glucose 7 and 8 Metabolic markers of type 2 diabetes. g-Glutamyl transferase GGT 4 and 8 Whereas glucose and insulin are the most Alanine aminotransferase ALT 5 and 6 well-established biomarkers, there are many Ferritin FTH1 7 and 8 new and emerging biomarkers of diabetes Pancreatic polypeptide PP 9 (Table 1). Positive associations have been Fibronectin 10 reported between serum g-glutamyl trans- Fetuin A 11 ferase andincident type 2 diabetes (4). Path- Sex hormone–binding globulin SHBG 7 and 12 ophysiological mechanisms underlying Free testosterone 12 how serum g-glutamyl transferase relates Insulin-like growth factor I IGF-I 13 to type 2 diabetes risk have not been elu- Insulin receptor 8 cidated, but insulin resistance, oxidative Creatine kinase-MB CKMB 8 stress, and chronic low-grade systemic in- MR-Pro atrial natriuretic peptide MR_PRO_ANP 8 flammation may be involved. Alanine ami- NT-Pro B-type natriuretic peptide NT_PRO_BNP 8 notransferase (ALT) is elevated in some B-type natriuretic peptide BNP 8 patients with type 2 diabetes indepen- Biomarkers of glycemia dently of confounding factors such as Glycated hemoglobin HbA1c obesity (5,6), and evidence now indicates Fructosamine 14 that markers associated with fatty liver 1,5-Anhydroglucitol 1,5AG 15 may predict future development of type 2 Glycated albumin 16 diabetes. In most cases of nonalcoholic fatty Glycated insulin 17 liver disease, the hepatic component of Glycosylated amylin 18 metabolic syndrome, ALT is elevated, and Glycated LDL 19 studies have associated raised ALT with Markers of oxidative stress and nutrient status metabolic syndrome and type 2 diabetes (5). Glutathione GSH 20 A strong association has been found Advanced glycated end products receptor RAGE 24 between raised ferritin levels (below the Ascorbic acid Vitamin C 21 range indicative of clinical hemochroma- 25-Hydroxyvitamin D Vitamin D 22 tosis) and development of incident di- Homocysteine 8 abetes (7,8). Ferritin was associated with Branched-chain and aromatic amino acids Leu, Ile, Val, Tyr, Phe 23 diabetes independently of established risk Lipid-related markers factors (age, BMI, sex, family history, Leptin LEP 6 and 25 physical inactivity, and smoking), as Adiponectin ADIPOQ 6, 8, and 25 well as dietary factors and alcohol intake. Apolipoprotein B ApoB 8 The mechanism is thought to involve in- Apolipoprotein A ApoA 8 sulin resistance, free radical damage, and Endothelial and inflammatory markers accumulation of iron in hepatocytes. C-reactive protein CRP 6–8and26 Pancreatic polypeptide, believed to act Interleukin-18 IL-18 8 and 27
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