PMID- 30004843
OWN - NLM
STAT- MEDLINE
DCOM- 20190304
LR  - 20190304
IS  - 1557-8100 (Electronic)
IS  - 1536-2310 (Linking)
VI  - 22
IP  - 7
DP  - 2018 Jul
TI  - Type 2 Diabetes Mellitus: Integrative Analysis of Multiomics Data for Biomarker 
      Discovery.
PG  - 514-523
LID - 10.1089/omi.2018.0053 [doi]
AB  - Increased fasting plasma glucose (FPG) is an independent risk factor for type 2 
      diabetes mellitus (T2DM). The development of systems biology technologies for 
      integration of multiomics data is crucial for predicting increased FPG levels. In 
      this case-control study, immunoglobulin (Ig) G glycosylation profiling and 
      genome-wide association analyses were performed on 511 participants, and among 
      them 76 had increased FPG (aged 47.6 +/- 6.14 years), and 435 had decreased or 
      fluctuant FPG (aged 47.9 +/- 6.08 years). We identified nine single nucleotide 
      polymorphisms (SNPs) in five genes (RPL7AP27, SNX30, SLC39A12, BACE2, and IGFL2) 
      that were significantly associated with increased FPG (odds ratios 1.937-2.393). 
      Moreover, of the 24 glycan peaks (GPs), GPs 3, 8, and 11 presented positive 
      trends with increased FPG levels, whereas GPs 4 and 14 presented negative trends. 
      A significant improvement of predictive power was observed when adding 24 IgG GPs 
      to 9 SNPs with the area under the curve increased from 0.75 to 0.81. This report 
      shows that the combination of candidate SNPs with IgG glycomics offers biomarker 
      potentials for T2DM. The substantial predictive power obtained from integrating 
      genomics and glycomics biomarkers suggests the feasibility of applying such 
      multiomics strategies to enable predictive, preventive, and personalized medicine 
      for T2DM.
FAU - Ge, Siqi
AU  - Ge S
AD  - 1 Beijing Key Laboratory of Clinical Epidemiology, Department of Epidemiology and 
      Health Statistics, School of Public Health, Capital Medical University , Beijing, 
      China .
AD  - 2 Department of Public Health, School of Medical and Health Sciences, Edith Cowan 
      University , Perth, Australia .
FAU - Wang, Youxin
AU  - Wang Y
AD  - 1 Beijing Key Laboratory of Clinical Epidemiology, Department of Epidemiology and 
      Health Statistics, School of Public Health, Capital Medical University , Beijing, 
      China .
AD  - 2 Department of Public Health, School of Medical and Health Sciences, Edith Cowan 
      University , Perth, Australia .
FAU - Song, Manshu
AU  - Song M
AD  - 1 Beijing Key Laboratory of Clinical Epidemiology, Department of Epidemiology and 
      Health Statistics, School of Public Health, Capital Medical University , Beijing, 
      China .
AD  - 2 Department of Public Health, School of Medical and Health Sciences, Edith Cowan 
      University , Perth, Australia .
FAU - Li, Xingang
AU  - Li X
AD  - 2 Department of Public Health, School of Medical and Health Sciences, Edith Cowan 
      University , Perth, Australia .
FAU - Yu, Xinwei
AU  - Yu X
AD  - 1 Beijing Key Laboratory of Clinical Epidemiology, Department of Epidemiology and 
      Health Statistics, School of Public Health, Capital Medical University , Beijing, 
      China .
AD  - 2 Department of Public Health, School of Medical and Health Sciences, Edith Cowan 
      University , Perth, Australia .
FAU - Wang, Hao
AU  - Wang H
AD  - 1 Beijing Key Laboratory of Clinical Epidemiology, Department of Epidemiology and 
      Health Statistics, School of Public Health, Capital Medical University , Beijing, 
      China .
AD  - 2 Department of Public Health, School of Medical and Health Sciences, Edith Cowan 
      University , Perth, Australia .
FAU - Wang, Jing
AU  - Wang J
AD  - 3 Department of Pathophysiology, Peking Union Medical College , China Academy of 
      Medical Sciences, Beijing, China .
FAU - Zeng, Qiang
AU  - Zeng Q
AD  - 4 Department of International Inpatient, Institute of Health Management , Chinese 
      PLA General Hospital, Beijing, China .
FAU - Wang, Wei
AU  - Wang W
AD  - 1 Beijing Key Laboratory of Clinical Epidemiology, Department of Epidemiology and 
      Health Statistics, School of Public Health, Capital Medical University , Beijing, 
      China .
AD  - 2 Department of Public Health, School of Medical and Health Sciences, Edith Cowan 
      University , Perth, Australia .
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - OMICS
JT  - Omics : a journal of integrative biology
JID - 101131135
RN  - 0 (Biomarkers)
RN  - 0 (Blood Glucose)
RN  - 0 (Immunoglobulin G)
SB  - IM
MH  - Adult
MH  - Aged
MH  - Biomarkers/*metabolism
MH  - Blood Glucose/metabolism
MH  - Case-Control Studies
MH  - Diabetes Mellitus, Type 2/genetics/*metabolism
MH  - Female
MH  - Humans
MH  - Immunoglobulin G/metabolism
MH  - Male
MH  - Middle Aged
MH  - Polymorphism, Single Nucleotide/genetics
OTO - NOTNLM
OT  - IgG glycosylation
OT  - T2DM
OT  - biomarker discovery
OT  - genome-wide association study
OT  - multiomics
OT  - predictive models
EDAT- 2018/07/14 06:00
MHDA- 2019/03/05 06:00
CRDT- 2018/07/14 06:00
PHST- 2018/07/14 06:00 [entrez]
PHST- 2018/07/14 06:00 [pubmed]
PHST- 2019/03/05 06:00 [medline]
AID - 10.1089/omi.2018.0053 [doi]
PST - ppublish
SO  - OMICS. 2018 Jul;22(7):514-523. doi: 10.1089/omi.2018.0053.