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s/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/J-IGT13.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-78.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-636.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-359.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-465.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-976.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-297.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-28.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/140706-151.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/140706-50.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-72.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-758.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-696.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/J-IGT10.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/20191222_3P35.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/3B118.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-247.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-256-2.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/3M13.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-138.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-639.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-577.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/O-IGT15-F.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/0227-478.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/20191222_3N14.raw.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343/FILES/RAW_FILES/1201-468.raw.zipprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS2343<p>For instrumental analysis, an aliquot of standard stock solution was prepared by mixing BA standards for a final concentration of 5 µM each. A series of standard calibration solutions were diluted with desalted serum (depleted of BAs using activated charcoal) for the calibration curve. The calibration curve and the corresponding regression coefficients were obtained by internal standard adjustment.</p>MetaboLightsPublicLiquid Chromatography MS -Liquid Chromatography MS - negative - reverse phase<p>A Waters ACQUITY UPLC system equipped with a binary solvent delivery manager and a sample manager (Waters, Milford, MA) was used throughout the study. All chromatographic separations were performed with an ACQUITY BEH C18 column (1.7 μm, 100 mm x 2.1 mm internal dimensions) (Waters Corp., Milford, MA). The mobile phase consisted of water with 0.01% formic acid (mobile phase A) and acetonitrile/methanol with 0.01% formic acid (9/1, v/v, mobile phase B). The flow rate was 0.45 ml/min with the following mobile phase gradient: 0−0.5 min (5% B), 0.5−1 min (5−20% B), 1−2 min (20−25% B), 2−5.5 min (25% B), 5.5−6 min (25−30% B), 6−8 min (30% B), and 8−9 min (30−35% B), 9−17 min (35−65% B), 17−18 min (65−99% B), 18−19 min (99% B), 19−19.1 min (99−5% B), 19−20 min (5% B). The column was maintained at 45 °C and the injection volume for all samples was 5 µl.</p>Hyocholic acid species as novel biomarkers for metabolic disorders. 10.1038/s41467-021-21744-w. PMID:33674561Shanghai Sixth People's HospitalXiaojiao Zhengblood serumfecesmass spectrometry<p>For sample pretreatment, an aliquot of 50 µl serum sample was mixed with 300 µl acetonitrile-methanol (8:2 v/v) containing 6 internal standards (IS) (D4-GCA, D4-GDCA, D4-CA, D4-UDCA, D4-LCA, and D4-GCDCA, 50 nM for each). The mixture was allowed to stand at 20 °C for 30 min, and was then centrifuged at 13,000 x g at 4 °C for 30 min. An aliquot of 300 µl of supernatant was transferred to another tube and then vacuum-dried. A 25 µl volume of acetonitrile-methanol (9/1, v/v) containing 0.01% formic acid was added, and the sample was re-vortexed at 1,500 x g, 10 °C for 10 min followed by addition of 25 µl water containing 0.01% formic acid. The sample was vortexed again at 1,500 x g, 10 °C for 10 min, and then centrifuged at 13,000 x g, 4 °C for 15 min. The supernatant was used for ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS) analysis. For fecal samples, 10 mg of dried samples were accurately weighed and homogenized with 200 µl of a mixture of methanol and water (1:1, v/v) (containing 6 IS: D4-GCA, D4-GDCA, D4-CA, D4-UDCA, D4-LCA, and D4-GCDCA, 50 nM for each) for 5 min. After centrifugation at 13,000 x g for 15 min, the supernatant was transferred to a 1.5 ml tube. The residue was reconstituted with 200 µl of a mixture of acetonitrile-methanol (8:2, v/v) (containing 6 IS: D4-GCA, D4-GDCA, D4-CA, D4-UDCA, D4-LCA, and D4-GCDCA, 50 nM for each) for 5 min. After centrifugation at 13,000 x g for 15 min, the supernatant was added to the same tube. Each combined supernatant was centrifuged at 13,000 x g for 10 min and then, a 60 µl aliquot of the supernatant of each sample was used for UPLC-MS analysis.</p>Homo sapienshttps://www.ebi.ac.uk/metabolights/MTBLS2343Shouli Wang.Weiping Jia.Yuqian Bao.Kun Ge.Guoxiang Xie.Yijun You.Junliang Kuang.Cheng Hu.Haoyong Yu.Miao Jiang.Zhangchi Ning.Yike Guo.Aihua Zhao.Cynthia Rajani.Shuiping Zhou.Xiaohui Ma.Xiaojiao Zheng.Aiping Lu.Xiaojing Ma.Mengci Li.Yitao Li.Jieyi Wang.Tianlu Chen.Jian Zhou.Wei Jia.<p>The BA profile raw data acquired using UPLC-MS were processed and quantified using TargetLynx software (Waters Corp., Milford, MA). Manual checking and corrections were carried out in order to ensure data quality.</p>CohortPatient groupjoyzheng99@sjtu.edu.cn<p><strong>Human study 1, cross-sectional study 1 (Cohort1):</strong></p><p>This is a nested case-control study, performed within the SHOS<strong>[1]</strong>, which was designed to investigate the occurrence and development of the metabolic syndrome and its related diseases. Beginning in 2009, the SHOS recruited participants from four communities in Shanghai, China. The participants that were selected satisfied the criteria for overweight/obese and diabetes (see the paper associated with this study for the full exclusion criteria). According to these criteria, a total of 1,107 subjects with fasting serum samples were selected prior to bile acid (BA) analysis. This cohort included 585 HL (329 men and 256 women), 419 HO (229 men and 190 women) and 103 OD (52 men and 51 women) participants. We further selected 103 subjects from each group with matched age, sex and BMI as a matched cohort.</p><p><br></p><p><strong>Human study 2, cross-sectional study 2 (Cohort2):</strong></p><p>A group of 91 subjects including 26 healthy controls (9 men and 17 women), 30 individuals with pre-diabetes (10 men and 20 women) and 35 patients with diabetes (16 men and 19 women) were recruited for this study. The exclusion criteria were the same as in human study 1. Fasting sera and fecal samples of 91 participants were collected and stored for later analysis.</p><p><br></p><p><strong>Human study 3, Gastric bypass surgery intervention study (Cohort3):</strong></p><p>A total of 38 patients with obesity and diabetes who received RYGB surgery were enrolled in the study<strong>[2]</strong>. Any patient with a history of open abdominal surgery, a serious disease (such as heart or lung insufficiency) that was incompatible with surgery, an acute T2DM complication, severe alcohol or drug dependency, a mental disorder, type 1 diabetes, secondary diabetes, an unstable psychiatric illness, or who was at a relatively high surgical risk (such as a patient with an active ulcer) was excluded. The fasting serum specimens of these subjects were collected and stored for future analysis before (baseline) and 1, 3, 6, and 12 months after the surgery.</p><p><br></p><p><strong>Human study 4, a 10-year longitudinal study (Cohort4):</strong></p><p>A group of 132 subjects (36 men and 96 women) were selected from the Shanghai Diabetes Study, which was intended to assess the prevalence of diabetes and diabetes-associated metabolic disorders in urban Shanghai<strong>[3]</strong>. All 132 subjects were metabolically healthy at baseline (the year 2000-2001). 10 years later (year 2010-2011), 86 participants (26 men and 60 women) became metabolically unhealthy (future metabolically unhealthy) and 46 participants (10 men and 36 women) remained healthy (future metabolically healthy). Fasting serum samples of the 132 participants at baseline were collected and stored for future analysis. </p><p><br></p><p><strong>Human study 5, a 5-year longitudinal study&nbsp;(Cohort5):</strong></p><p>A group of 207 subjects (117 men and 90 women) were selected from the physical examination centers in Beijing. All 207 subjects were metabolically healthy at baseline (the year 2011). 5 years later (the year 2016), 90 participants (60 men and 30 women) became metabolically unhealthy (future metabolically unhealthy) and 117 participants (57 men and 60 women) remained healthy (future metabolically healthy). Fasting serum samples of the 207 participants at baseline were collected and stored for future analysis.</p><p><br></p><p><strong>Criteria for lean, overweight/obesity, pre-diabetes, diabetes, metabolically healthy and unhealthy status:</strong></p><p>Individuals with BMI &lt; 25 kg/m^2 were considered lean and those with BMI ≥ 25 were classified as overweight/obese. Individuals with 6.1 mmol/l ≤ fasting blood glucose &lt; 7.0 mmol/l or 7.8 mmol/l ≤ oral glucose tolerance test (OGTT) (2 h) &lt; 11.1 mmol/l were classified as pre-diabetic. Subjects with fasting blood glucose ≥ 7.0 mmol/l and/or OGTT (2 h) ≥ 11.1 mmol/l were classified as diabetic. Subjects were considered 'metabolically healthy' if they met all of the following criteria: fasting blood glucose &lt; 6.1 mmol/l, OGTT (2 h) &lt; 7.8 mmol/l and no previous history of diabetes; systolic blood pressure (SP)/diastolic blood pressure (DP) &lt; 140/90 mmHg and no previous history of high blood pressure; fasting plasma TG&lt; 1.7 mmol/l and fasting plasma high-density lipoprotein-cholesterol (HDL) ≥ 0.9 mmol/l (men) or ≥ 1.0 mmol/l (women), and no previous history of high cholesterol (total cholesterol (TC) &lt; 5.18 mmol/l); no history of cardiovascular or endocrine disease<strong>[4]</strong>. Those who failed to meet all criteria above were classified as 'metabolically unhealthy'. </p><p><br></p><p><strong>Clinical measurements and sample collection:</strong></p><p>All human samples were collected, stored and measured following the standard operating protocol of the hospital. Participants were given a standard 75-g OGTT after an overnight fast of more than 8 h. Venous blood samples were drawn at 0 (fasting), 30, 60 and 120 min. Fasting and postprandial plasma glucose and insulin levels, fasting serum lipid profiles (TC, TG, HDL-c, LDL-c), blood pressure (SP and DP), waist circumference, BMI, liver and kidney function tests were determined as previously described<strong>[4][5]</strong>. The blood samples were centrifuged for plasma or serum collection, and then divided into aliquots and delivered on dry ice to the study laboratory. Fecal samples from the recruited subjects were collected in the sterile feces containers (Cat 80.9924.014, SARSTEDT). Each sample was either frozen immediately at -80 °C or briefly stored in personal -20 °C freezers before transport to the laboratory within 24 h. All samples were stored in a -80 °C freezer until analysis.</p><p><br></p><p><strong>Refs:</strong></p><p><strong>[1]</strong> Bao Y, Ma X, Yang R, Wang F, Hao Y, Dou J, He H, Jia W. Inverse relationship between serum osteocalcin levels and visceral fat area in Chinese men. J Clin Endocrinol Metab. 2013 Jan;98(1):345-51. doi:10.1210/jc.2012-2906. PMID:23162093.</p><p><strong>[2]</strong> Yu H, Ni Y, Bao Y, Zhang P, Zhao A, Chen T, Xie G, Tu Y, Zhang L, Su M, Wei L, Jia W, Jia W. Chenodeoxycholic Acid as a Potential Prognostic Marker for Roux-en-Y Gastric Bypass in Chinese Obese Patients. J Clin Endocrinol Metab. 2015 Nov;100(11):4222-30. doi:10.1210/jc.2015-2884. PMID:26425885.</p><p><strong>[3]</strong> Jia WP, Pang C, Chen L, Bao YQ, Lu JX, Lu HJ, Tang JL, Wu YM, Zuo YH, Jiang SY, Xiang KS. Epidemiological characteristics of diabetes mellitus and impaired glucose regulation in a Chinese adult population: the Shanghai Diabetes Studies, a cross-sectional 3-year follow-up study in Shanghai urban communities. Diabetologia. 2007 Feb;50(2):286-92. doi:10.1007/s00125-006-0503-1. PMID:17180353.</p><p><strong>[4]</strong> Ni Y, Zhao L, Yu H, Ma X, Bao Y, Rajani C, Loo LW, Shvetsov YB, Yu H, Chen T, Zhang Y, Wang C, Hu C, Su M, Xie G, Zhao A, Jia W, Jia W. Circulating Unsaturated Fatty Acids Delineate the Metabolic Status of Obese Individuals. EBioMedicine. 2015 Sep 6;2(10):1513-22. doi:10.1016/j.ebiom.2015.09.004. PMID:26629547.</p><p><strong>[5]</strong>&nbsp;Gu Y, Zhao A, Huang F, Zhang Y, Liu J, Wang C, Jia W, Xie G, Jia W. Very low carbohydrate diet significantly alters the serum metabolic profiles in obese subjects. J Proteome Res. 2013 Dec 6;12(12):5801-11. doi:10.1021/pr4008199. PMID:24224694.</p>Metabolomicsultra-performance liquid chromatography-mass spectrometryuntargeted metabolitesPrimary Health Carediabetes mellitushyocholic acidgastric bypassultra-performance liquid chromatography-mass spectrometryuntargeted metabolitesPrimary Health Carediabetes mellitushyocholic acidgastric bypass<p>The mass spectrometer was a Waters XEVO TQ instrument with an ESI source (Waters Corp., Milford, MA). The entire UPLC−MS system was controlled by MassLynx 4.1 software. The mass spectrometer was operated in negative ion mode with a 2.5 kV capillary voltage. The source and desolvation gas temperature were 150 and 450 °C, respectively. The data were collected with a multiple reaction monitor (MRM), and the cone and collision energy for each BA used the optimized settings from QuanOptimize application manager (Waters Corp., Milford, MA).</p>taurodeoxycholic acidtaurocholic acid3-ketocholic acid7-ketolithocholic acidglycocholic acidUrsocholic acidCholic acid7-ketodeoxycholic acidtaurohyocholic acidDehydrocholic acidHyodeoxycholic acidDeoxycholic acidglycohyodeoxycholic acidtaurochenodeoxycholic acidtauroursodeoxycholic acidursodeoxycholic acidHyocholic acidGlycolithocholic acidglycochenodeoxycholic acidglycodeoxycholic acidtaurohyodeoxycholic acidglycoursodeoxycholic acidChenodeoxycholic acidglycohyocholic acidHyocholic acid (HCA) is a major bile acid (BA) species in the BA pool of pigs, a species known for its exceptional resistance to spontaneous development of diabetic phenotypes. HCA and its derivatives are also present in human blood and urine. We investigate whether human HCA profiles can predict the development of metabolic disorders. We find in the first cohort (n = 1107) that both obesity and diabetes are associated with lower serum concentrations of HCA species. A separate cohort study (n = 91) validates this finding and further reveals that individuals with pre-diabetes are associated with lower levels of HCA species in feces. Serum HCA levels increase in the patients after gastric bypass surgery (n = 38) and can predict the remission of diabetes two years after surgery. The results are replicated in two independent, prospective cohorts (n = 132 and n = 207), where serum HCA species are found to be strong predictors for metabolic disorders in 5 and 10 years, respectively. These findings underscore the association of HCA species with diabetes, and demonstrate the feasibility of using HCA profiles to assess the future risk of developing metabolic abnormalities.Hyocholic acid species as novel biomarkers for metabolic disorders.Zheng Xiaojiao X, Chen Tianlu T, Zhao Aihua A, Ning Zhangchi Z, Kuang Junliang J, Wang Shouli S, You Yijun Y, Bao Yuqian Y, Ma Xiaojing X, Yu Haoyong H, Zhou Jian J, Jiang Miao M, Li Mengci M, Wang Jieyi J, Ma Xiaohui X, Zhou Shuiping S, Li Yitao Y, Ge Kun K, Rajani Cynthia C, Xie Guoxiang G, Hu Cheng C, Guo Yike Y, Guo Yike Y, Lu Aiping A, Jia Weiping W, Jia Wei WfalseHyocholic acid species as novel biomarkers for metabolic disordersHyocholic acid (HCA) is a major bile acid (BA) species in the BA pool of pigs, a species known for its exceptional resistance to spontaneous development of diabetic phenotypes. HCA and its derivatives are also present in human blood and urine. We investigate whether human HCA profiles can predict the development of metabolic disorders. We find in the first cohort (n = 1107) that both obesity and diabetes are associated with lower serum concentrations of HCA species. A separate cohort study (n = 91) validates this finding and further reveals that individuals with pre-diabetes are associated with lower levels of HCA species in feces. Serum HCA levels increase in the patients after gastric bypass surgery (n = 38) and can predict the remission of diabetes two years after surgery. The results are replicated in two independent, prospective cohorts (n = 132 and n = 207), where serum HCA species are found to be strong predictors for metabolic disorders in 5 and 10 years, respectively. These findings underscore the association of HCA species with diabetes, and demonstrate the feasibility of using HCA profiles to assess the future risk of developing metabolic abnormalities.2021-10-062020-12-24MTBLS2343MTBLC81244MTBLC52023MTBLC133176MTBLC166732MTBLC52022MTBLC139138MTBLC16359MTBLC17687MTBLC28865MTBLC16755MTBLC36274MTBLC16525MTBLC28834MTBLC27471MTBLC9410MTBLC9907MTBLC89929MTBLC80774MTBLC37998MTBLC88108MTBLC16390MTBLC82679MTBLC81240MTBLC3145933674561CHEBI:81244CHEBI:52023CHEBI:133176CHEBI:166732CHEBI:52022CHEBI:139138CHEBI:16359CHEBI:17687CHEBI:28865CHEBI:16755CHEBI:36274CHEBI:16525CHEBI:28834CHEBI:27471CHEBI:9410CHEBI:9907CHEBI:89929CHEBI:80774CHEBI:37998CHEBI:88108CHEBI:16390CHEBI:82679CHEBI:81240CHEBI:31459