title: Metabolic signatures and risk of type 2 diabetes in a Chinese population: an untargeted metabolomics study using both LC-MS and GC-MS.
abstract: Metabolomics has provided new insight into diabetes risk assessment. In this study we characterised the human serum metabolic profiles of participants in the Singapore Chinese Health Study cohort to identify metabolic signatures associated with an increased risk of type 2 diabetes.
  
  
  
  In this nested case-control study, baseline serum metabolite profiles were measured using LC-MS and GC-MS during a 6-year follow-up of 197 individuals with type 2 diabetes but without a history of cardiovascular disease or cancer before diabetes diagnosis, and 197 healthy controls matched by age, sex and date of blood collection.
  
  
  
  A total of 51 differential metabolites were identified between cases and controls. Of these, 35 were significantly associated with diabetes risk in the multivariate analysis after false discovery rate adjustment, such as increased branched-chain amino acids (leucine, isoleucine and valine), non-esterified fatty acids (palmitic acid, stearic acid, oleic acid and linoleic acid) and lysophosphatidylinositol (LPI) species (16:1, 18:1, 18:2, 20:3, 20:4 and 22:6). A combination of six metabolites including proline, glycerol, aminomalonic acid, LPI (16:1), 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid and urea showed the potential to predict type 2 diabetes in at-risk individuals with high baseline HbA1c levels (≥6.5% [47.5 mmol/mol]) with an AUC of 0.935. Combined lysophosphatidylglycerol (LPG) (12:0) and LPI (16:1) also showed the potential to predict type 2 diabetes in individuals with normal baseline HbA1c levels (<6.5% [47.5 mmol/mol]; AUC = 0.781).
  
  
  
  Our findings show that branched-chain amino acids and NEFA are potent predictors of diabetes development in Chinese adults. Our results also indicate the potential of lysophospholipids for predicting diabetes.
authors: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore.
authors: Yonghai
authors: Y
authors: Lu
authors: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore.
authors: Yeli
authors: Y
authors: Wang
authors: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore.|NUS Environmental Research Institute, National University of Singapore, Singapore, Republic of Singapore.
authors: Choon-Nam
authors: CN
authors: Ong
authors: Department of General Medicine, Diabetes Centre, Khoo Teck Puat Hospital, Singapore, Republic of Singapore.
authors: Tavintharan
authors: T
authors: Subramaniam
authors: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore.
authors: Hyung Won
authors: HW
authors: Choi
authors: Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania, USA.|Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
authors: Jian-Min
authors: JM
authors: Yuan
authors: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore. woonpuay.koh@duke-nus.edu.sg.|Office of Clinical Sciences, Duke-NUS Medical School, 8 College Road Level 4, Singapore, 169857, Republic of Singapore. woonpuay.koh@duke-nus.edu.sg.
authors: Woon-Puay
authors: WP
authors: Koh
authors: Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, 430030, Hubei, People's Republic of China. panan@hust.edu.cn.|Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China. panan@hust.edu.cn.
authors: An
authors: A
authors: Pan
mesh_terms: D000597:Amino Acids, Branched-Chain / Q000097:blood; D044466:Asian People; D001786:Blood Glucose; D016022:Case-Control Studies; D002853:Chromatography, Liquid / Q000379:methods*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood*; D005230:Fatty Acids, Nonesterified / Q000097:blood; D005663:Furans; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D006442:Glycated Hemoglobin / Q000378:metabolism; D005990:Glycerol / Q000097:blood; D006801:Humans; D019787:Linoleic Acid / Q000097:blood; D008246:Lysophospholipids / Q000097:blood; D055432:Metabolomics / Q000379:methods*; D019301:Oleic Acid / Q000097:blood; D011392:Proline / Q000097:blood; D011422:Propionates; D014508:Urea / Q000097:blood
chemical_list: D000597:Amino Acids, Branched-Chain; D001786:Blood Glucose; D005230:Fatty Acids, Nonesterified; D005663:Furans; D006442:Glycated Hemoglobin; D005990:Glycerol; D019787:Linoleic Acid; D008246:Lysophospholipids; D019301:Oleic Acid; D011392:Proline; D011422:Propionates; D014508:Urea; C517652:hemoglobin A1c protein, human; C025449:lysophosphatidylinositol; C041693:3-carboxy-4-methyl-5-propyl-2-furanpropionic acid
keywords: Mass spectrometry; Metabolomics; Prospective study; Type 2 diabetes