PMID- 37955008
OWN - NLM
STAT- MEDLINE
DCOM- 20231114
LR  - 20231116
IS  - 1664-2392 (Print)
IS  - 1664-2392 (Electronic)
IS  - 1664-2392 (Linking)
VI  - 14
DP  - 2023
TI  - An early prediction model for type 2 diabetes mellitus based on genetic variants 
      and nongenetic risk factors in a Han Chinese cohort.
PG  - 1279450
LID - 10.3389/fendo.2023.1279450 [doi]
LID - 1279450
AB  - AIMS: We aimed to construct a prediction model of type 2 diabetes mellitus (T2DM) 
      in a Han Chinese cohort using a genetic risk score (GRS) and a nongenetic risk 
      score (NGRS). METHODS: A total of 297 Han Chinese subjects who were free from 
      type 2 diabetes mellitus were selected from the Tianjin Medical University 
      Chronic Disease Cohort for a prospective cohort study. Clinical characteristics 
      were collected at baseline and subsequently tracked for a duration of 9 years. 
      Genome-wide association studies (GWASs) were performed for T2DM-related 
      phenotypes. The GRS was constructed using 13 T2DM-related quantitative trait 
      single nucleotide polymorphisms (SNPs) loci derived from GWASs, and NGRS was 
      calculated from 4 biochemical indicators of independent risk that screened by 
      multifactorial Cox regressions. RESULTS: We found that HOMA-IR, uric acid, and 
      low HDL were independent risk factors for T2DM (HR >1; P<0.05), and the NGRS 
      model was created using these three nongenetic risk factors, with an area under 
      the ROC curve (AUC) of 0.678; high fasting glucose (FPG >5 mmol/L) was a key risk 
      factor for T2DM (HR = 7.174, P< 0.001), and its addition to the NGRS model caused 
      a significant improvement in AUC (from 0.678 to 0.764). By adding 13 SNPs 
      associated with T2DM to the GRS prediction model, the AUC increased to 0.892. The 
      final combined prediction model was created by taking the arithmetic sum of the 
      two models, which had an AUC of 0.908, a sensitivity of 0.845, and a specificity 
      of 0.839. CONCLUSIONS: We constructed a comprehensive prediction model for type 2 
      diabetes out of a Han Chinese cohort. Along with independent risk factors, GRS is 
      a crucial element to predicting the risk of type 2 diabetes mellitus.
CI  - Copyright (c) 2023 Li, Ye, Jiao, Wang, Zhang, Chen, Zhang, Feng, Wang, Chen, Gao, 
      Wei and Li.
FAU - Li, Jinjin
AU  - Li J
AD  - Department of Genetics, College of Basic Medical Sciences, Tianjin Medical 
      University, Tianjin, China.
AD  - NHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of 
      Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of 
      Endocrinology, Tianjin Medical University, Tianjin, China.
FAU - Ye, Qun
AU  - Ye Q
AD  - Department of Genetics, College of Basic Medical Sciences, Tianjin Medical 
      University, Tianjin, China.
FAU - Jiao, Hongxiao
AU  - Jiao H
AD  - Department of Genetics, College of Basic Medical Sciences, Tianjin Medical 
      University, Tianjin, China.
AD  - Center of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
FAU - Wang, Wanyao
AU  - Wang W
AD  - Department of Genetics, College of Basic Medical Sciences, Tianjin Medical 
      University, Tianjin, China.
FAU - Zhang, Kai
AU  - Zhang K
AD  - Geriatric Medicine, Tianjin General Hospital of Tianjin Medical University, 
      Tianjin, China.
FAU - Chen, Chen
AU  - Chen C
AD  - Geriatric Medicine, Tianjin General Hospital of Tianjin Medical University, 
      Tianjin, China.
FAU - Zhang, Yuan
AU  - Zhang Y
AD  - Department of Genetics, College of Basic Medical Sciences, Tianjin Medical 
      University, Tianjin, China.
FAU - Feng, Shuzhi
AU  - Feng S
AD  - Geriatric Medicine, Tianjin General Hospital of Tianjin Medical University, 
      Tianjin, China.
FAU - Wang, Ximo
AU  - Wang X
AD  - Tianjin Nankai Hospital, Tianjin, China.
FAU - Chen, Yubao
AU  - Chen Y
AD  - Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences, 
      Beijing, China.
FAU - Gao, Huailin
AU  - Gao H
AD  - Hebei Yiling Hospital, Shijiazhuang, Hebei, China.
FAU - Wei, Fengjiang
AU  - Wei F
AD  - Department of Genetics, College of Basic Medical Sciences, Tianjin Medical 
      University, Tianjin, China.
FAU - Li, Wei-Dong
AU  - Li WD
AD  - Department of Genetics, College of Basic Medical Sciences, Tianjin Medical 
      University, Tianjin, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20231025
PL  - Switzerland
TA  - Front Endocrinol (Lausanne)
JT  - Frontiers in endocrinology
JID - 101555782
SB  - IM
MH  - Humans
MH  - *Diabetes Mellitus, Type 2/epidemiology/genetics
MH  - Genome-Wide Association Study
MH  - Prospective Studies
MH  - East Asian People
MH  - Risk Factors
PMC - PMC10634500
OTO - NOTNLM
OT  - Han Chinese
OT  - cohort study
OT  - genetic risk factors
OT  - genome-wide association study
OT  - prediction model
OT  - type 2 diabetes mellitus
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2023/11/13 06:42
MHDA- 2023/11/14 06:43
PMCR- 2023/01/01
CRDT- 2023/11/13 04:44
PHST- 2023/08/18 00:00 [received]
PHST- 2023/09/25 00:00 [accepted]
PHST- 2023/11/14 06:43 [medline]
PHST- 2023/11/13 06:42 [pubmed]
PHST- 2023/11/13 04:44 [entrez]
PHST- 2023/01/01 00:00 [pmc-release]
AID - 10.3389/fendo.2023.1279450 [doi]
PST - epublish
SO  - Front Endocrinol (Lausanne). 2023 Oct 25;14:1279450. doi: 
      10.3389/fendo.2023.1279450. eCollection 2023.