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Background: The plasma amino acid profile can be a useful indicator in clinical settings because it changes in response to various metabolic alternations. However, the association between the plasma amino acid profile and body fat accumulation has not been evaluated in humans. Objective: This study aimed to relate plasma amino acids to visceral fat accumulation in humans because excess visceral fat raises the odds ratio of developing metabolic syndrome. Design: A total of 1,449 subjects (985 males and 464 females) who had undergone a comprehensive health screening were enrolled in this study. The visceral fat area (VFA) was determined in each subject using CT imaging. Subjects were then divided into two groups according to VFA: high-VFA ( 100 cm, n=867) and low-VFA (<100 cm, n=582). The plasma amino acid profile was analyzed together with other metabolic valuables and then compared between the two groups using uniand multivariate analyses. Results: As the degree of visceral fat accumulation increased, plasma concentrations of several amino acids changed significantly. Glu, Val, Leu, Ile, Tyr, Ala, Phe, Pro, Lys, Orn, Trp, Met, His and alpha-aminobutyric acid (ABA) levels were significantly higher in the high-VFA group compared to the low-VFA group, whereas the levels of Gly, Ser, Gln and Asn were significantly lower. To evaluate the potential of using amino acids as an indicator of VFA, a discriminant analysis was conducted with the multivariate logistic regression analysis “AminoIndex”, and the ROC curve was calculated. The resulting “AminoIndex” exhibited an area under the ROC curve of 0.81 (95% confidence interval; 0.78 to 0.83), with higher sensitivity and specificity by 80% and 65%, respectively. Conclusions: The plasma amino acid profile changes depending on visceral fat content and can be used as a marker for diagnosing elevated visceral obesity in humans. Introduction Recent progress in metabolomics has enables the high throughput measurement of diverse amino acids 1-3 and has shown the new possibility of using amino acid analysis of biological samples as a biomarker discovery tool by generating diagnostic indices through systematic multivariate regression models. Published studies have shown that amino acids in biological fluids change in response to metabolic alternations during the courses of various diseases, such as renal failure, cancer, atherosclerosis, and insulin resistance. The balance between branched amino acids (Leu, Val and Ile; BCAA) and aromatic amino acids (Phe and Tyr; AAA) is known as Fischer’s ratio and is one of a few classical indicators used to monitor hepatic encephalopathy. Recently, a novel multivariate logistic regression model of plasma free amino acids (“AminoIndex) was reported for the discrimination of various disease states in rat models of type-1 and type-2 diabetes and the progression of liver fibrosis in chronic hepatitis C in humans. Furthermore, the usefulness of amino acid profiles in various tissues in combination with other “-omics” datasets has been reported for investigating metabolic and regulatory networks in animals . Recent studies have suggested that there may be an association between plasma amino acid levels and obesity in both animals and humans. For instance, elevated plasma BCAAs and glutamate were observed in obese rodents 14, 15 and humans. The plasma ratio of Trp/large neutral amino acids was also lower in obese subjects . Furthermore, a reduction in the levels of Gly, Trp, Thr, His, taurine, citrulline and cystine has been reported in obese subjects. These studies strongly indicate that the volume of adipose tissue or its dysfunctions could affect amino acid metabolism and the levels of amino acids in peripheral circulation. However, the relationship between plasma amino acid levels and fat content, particularly in a specific body fat deposit, has not been evaluated in humans. Visceral obesity has been reported to represent a clinical intermediate phenotype reflecting the relative incapability of subcutaneous adipose tissue to act as a protective energy depot, leading to ectopic fat deposition in visceral adipose, skeletal muscle, liver, heart and other tissues . Thus, visceral obesity may be both a marker of a dysmetabolic state and a cause of metabolic syndrome. Waist circumference and bioelectrical impedance have been reported to be better markers of visceral fat accumulation than body mass index. However, these approaches are insufficient to diagnose visceral obesity. Although both computed tomography (CT) and magnetic resonance imaging (MRI) achieve a reliable prediction of visceral fat , such highcost and low-throughput measurements are unsuitable for primary diagnosis. In this study, we first determined the plasma amino acid profile of human subjects who underwent CT scans for estimation of visceral fat area (VFA). Next, each plasma amino acid level was compared between lowand high-VFA groups to assess its discriminant power. Finally, a discriminant analysis with selected amino acids was examined with the multivariate logistic regression analysis “AminoIndex” and an additional assessment was made with ROC curve analysis. Subjects and Methods Subjects A total of 1,449 subjects (985 males and 464 females) who had undergone comprehensive health screening tests between January 2008 and June 2009 at the Center for Multiphasic Health Testing and Services, Mitsui Memorial Hospital, and the Kameda Medical Center Makuhari were enrolled. Subjects were divided into two groups according to visceral fat area (VFA) volumes calculated from CT images: highVFA ( 100 cm, n=867) and low-VFA (<100 cm, n=582). These VFA areas were chosen because previous studies have reported that the mean number of metabolic risk factors in Japanese subjects with VFA 100 cm is significantly higher than in those with VFA<100 cm, irrespective of BMI. Subjects were provided with no medical treatments before examination and blood sampling. The protocol was approved by the Ethical Committees of Mitsui Memorial Hospital and Kameda Medical Center Makuhari. In Japan, regular health check-ups for employees are legally mandated; thus, the majority of the subjects enrolled in the study did not have serious health problems. In addition, most or all of the costs of the health screenings are paid by the company for which the individual works or by each individual. In addition, there are several options to choose from in the health screening program. The option chosen is up to each individual, not to the physicians or the company for which the individual works. Therefore, the study population was thought to not be enriched for any particular disease condition. Analyses of metabolic parameters Blood samples were taken from the subjects after an overnight fast. Serum levels of total cholesterol (TC), HDL-cholesterol (HDL-C), and triglycerides (TG) were determined enzymatically. Plasma glucose was measured by the hexokinase method, and hemoglobin A1c (HbA1c) was determined using the latex agglutination immunoassay. Systolic and diastolic blood pressures were measured twice on the same day, and the mean value was used in the analysis. BMI was calculated as weight in kilograms divided by height in meters squared. Measurement of abdominal fat area by CT scan Subcutaneous and visceral fat areas visualized on a CT scan at the level of the umbilicus were measured using Fat Scan software (N2 System Co., Osaka, Japan). All CT scans were performed in the supine posture using a CT scanner (SOMATOM Sensation Cardiac 64, Siemens, Germany). The VFA was defined as the intraperitoneal fat bound by the parietal peritoneum or transversalis fascia, excluding the vertebral column and paraspinal muscles. The SFA was defined as the fat superficial to the abdominal and back muscles. A region of interest drawn around the external margin of the dermis was used to calculate the total abdominal fat (TAF) area. The SFA was obtained by subtracting the VFA from the TAF. Plasma amino acid profiling Blood samples (5 ml) were taken from forearm veins after an overnight fast in collection tubes containing EDTA-2Na (Terumo, Tokyo, Japan) and immediately cooled on ice. Plasma was obtained by centrifugation at 3000 rpm for 15 min at 4°C and stored at −80°C until analysis. Before analysis, a 50 L portion of the plasma sample was added to 50 L of the internal standard solution and 100 L of acetonitrile, and the solution was mixed with a vortex-mixer as described previously . After mixing, the precipitate was removed by centrifugation at 15,000 rpm for 10 min at 4°C and the supernatant was used for further analysis. Plasma amino acid analysis was carried out with HPLC-ESI-MS following derivatization. A MSQ Plus LC/MS system (Thermo Fischer Scientific, Waltham, MA, USA) equipped with an electrospray ionization source was used in the positive ionization mode for selected ion monitoring (SIM). Xcalibur (TM) version 1.4 SR1 software was used for data collection and processing. The HPLC separation system consisted of an L-2100 (pump), L-2200 (autosampler), and L-2300 (column oven) (Hitachi High-Technologies Corporation, Tokyo, Japan). A Wakosil-II 3C8-100HG column (100 mm × 2.1 mm, 3 m) (Wako Pure Chemical Industries, Osaka, Japan) was used for the separation. The mobile phase consisted of eluent A (25 mM ammonium formate in water) and eluent B (water:acetonitrile=40:60). In this study, twenty-four compounds were measured as described previously : alanine (Ala), alphaaminobutyric acid (ABA), arginine (Arg), asparagine (Asn), citrulline (Cit), glutamic acid (Glu), glutamine (Gln), glycine (Gly), histidine (His), isoleucine (Ile), leucine (Leu), lysine (Lys), methionine (Met), ornithine (Orn), phenylalanine (Phe), proline (Pro), serine (Ser), threonine (Thr), tryptophan (Trp), tyrosine (Tyr), and valine (Val). Statistical analysis A Welch t-test was used to analyze differences in demographic variables, biochemical variables, and the plasm

Plasma amino acid profile is altered by visceral fat accumulation and is a predictor of visceral obesity in humans