PMID- 22023374
OWN - NLM
STAT- MEDLINE
DCOM- 20120614
LR  - 20221207
IS  - 1557-8593 (Electronic)
IS  - 1520-9156 (Print)
IS  - 1520-9156 (Linking)
VI  - 14
IP  - 3
DP  - 2012 Mar
TI  - Application of back propagation artificial neural network on genetic variants in 
      adiponectin ADIPOQ, peroxisome proliferator-activated receptor-gamma, and retinoid X 
      receptor-alpha genes and type 2 diabetes risk in a Chinese Han population.
PG  - 293-300
LID - 10.1089/dia.2011.0071 [doi]
AB  - AIMS: Our study was designed to explore the applied characteristics of the back 
      propagation artificial neural network (BPANN) on studying the genetic variants in 
      adipnectin ADIPOQ, peroxisome proliferator-activated receptor (PPAR)-gamma, and 
      retinoid X receptor-alpha (RXR-alpha) genes and type 2 diabetes mellitus (T2DM) risks in 
      a Chinese Han population. SUBJECTS AND METHODS: We used BPANN as the fitting 
      model based on data gathered from T2DM patients (n=913) and normal controls 
      (n=1,001). The mean impact value (MIV) for each input variables were calculated, 
      and the sequence of the factors according to their absolute MIVs was sorted. 
      RESULTS: The results from BPANN were compared with multiple logistic regression 
      analysis, and the generalized multifactor dimensionality reduction (GMDR) method 
      was used to calculate the joint effects of ADIPOQ, PPAR-gamma, and RXR-alpha genes. By 
      BPANN analysis, the sequence according to the importance of the T2DM risk factors 
      was in the order of serum adiponectin level, rs3856806, rs7649121, hypertension, 
      rs3821799, rs17827276, rs12495941, rs4240711, age, rs16861194, waist 
      circumference, rs2241767, rs2920502, rs1063539, alcohol drinking, smoking, 
      hyperlipoproteinemia, gender, rs3132291, T2DM family history, rs4842194, 
      rs822394, rs1801282, rs1045570, rs16861205, rs6537944, body mass index, rs266729, 
      and rs1801282. However, compared with multiple logistic regression analysis, only 
      11 factors were statistically significant. After overweight and obesity were 
      taken as environment adjustment factors into the analysis, model A2 B4 C5 C6 C8 
      (rs3856806, rs4240711, rs7649121, rs3821799, rs12495941) was the best model 
      (coefficient of variation consistency=10/10, P=0.0107) in the GMDR method. 
      CONCLUSIONS: These results suggested the interactions of ADIPOQ, PPAR-gamma, and 
      RXR-alpha genes might play a role in susceptibility to T2DM. BPANN could be used to 
      analyze the risk factors of diseases and provide more complicated relationships 
      between inputs and outputs.
FAU - Shi, Hui
AU  - Shi H
AD  - Department of Epidemiology and Biostatistics, School of Public Health, Nanjing 
      Medical University, Nanjing, Jiangsu, China.
FAU - Lu, Ying
AU  - Lu Y
FAU - Du, Juan
AU  - Du J
FAU - Du, Wencong
AU  - Du W
FAU - Ye, Xinhua
AU  - Ye X
FAU - Yu, Xiaofang
AU  - Yu X
FAU - Ma, Jianhua
AU  - Ma J
FAU - Cheng, Jinluo
AU  - Cheng J
FAU - Gao, Yanqin
AU  - Gao Y
FAU - Cao, Yuanyuan
AU  - Cao Y
FAU - Zhou, Ling
AU  - Zhou L
FAU - Li, Qian
AU  - Li Q
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20111024
PL  - United States
TA  - Diabetes Technol Ther
JT  - Diabetes technology & therapeutics
JID - 100889084
RN  - 0 (ADIPOQ protein, human)
RN  - 0 (Adiponectin)
RN  - 0 (PPAR gamma)
RN  - 0 (Retinoid X Receptor alpha)
SB  - IM
MH  - Adiponectin/*genetics
MH  - Asian People/*genetics
MH  - China/epidemiology
MH  - Diabetes Mellitus, Type 2/epidemiology/*genetics
MH  - Female
MH  - Genetic Predisposition to Disease
MH  - Genetic Variation
MH  - Genotype
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - *Neural Networks, Computer
MH  - PPAR gamma/*genetics
MH  - Retinoid X Receptor alpha/*genetics
MH  - Risk Assessment
MH  - Risk Factors
PMC - PMC3284696
EDAT- 2011/10/26 06:00
MHDA- 2012/06/15 06:00
PMCR- 2013/03/01
CRDT- 2011/10/26 06:00
PHST- 2011/10/26 06:00 [entrez]
PHST- 2011/10/26 06:00 [pubmed]
PHST- 2012/06/15 06:00 [medline]
PHST- 2013/03/01 00:00 [pmc-release]
AID - 10.1089/dia.2011.0071 [pii]
AID - 10.1089/dia.2011.0071 [doi]
PST - ppublish
SO  - Diabetes Technol Ther. 2012 Mar;14(3):293-300. doi: 10.1089/dia.2011.0071. Epub 
      2011 Oct 24.