PMID- 34728708
OWN - NLM
STAT- MEDLINE
DCOM- 20220124
LR  - 20230207
IS  - 2045-2322 (Electronic)
IS  - 2045-2322 (Linking)
VI  - 11
IP  - 1
DP  - 2021 Nov 2
TI  - Combining genetic risk score with artificial neural network to predict the 
      efficacy of folic acid therapy to hyperhomocysteinemia.
PG  - 21430
LID - 10.1038/s41598-021-00938-8 [doi]
LID - 21430
AB  - Artificial neural network (ANN) is the main tool to dig data and was inspired by 
      the human brain and nervous system. Several studies clarified its application in 
      medicine. However, none has applied ANN to predict the efficacy of folic acid 
      treatment to Hyperhomocysteinemia (HHcy). The efficacy has been proved to 
      associate with both genetic and environmental factors while previous studies just 
      focused on the latter one. The explained variance genetic risk score (EV-GRS) had 
      better power and could represent the effect of genetic architectures. Our aim was 
      to add EV-GRS into environmental factors to establish ANN to predict the efficacy 
      of folic acid therapy to HHcy. We performed the prospective cohort research 
      enrolling 638 HHcy patients. The multilayer perception algorithm was applied to 
      construct ANN. To evaluate the effect of ANN, we also established logistic 
      regression (LR) model to compare with ANN. According to our results, EV-GRS was 
      statistically associated with the efficacy no matter analyzed as a continuous 
      variable (OR = 3.301, 95%CI 1.954-5.576, P < 0.001) or category variable 
      (OR = 3.870, 95%CI 2.092-7.159, P < 0.001). In our ANN model, the accuracy was 
      84.78%, the Youden's index was 0.7073 and the AUC was 0.938. These indexes above 
      indicated higher power. When compared with LR, the AUC, accuracy, and Youden's 
      index of the ANN model (84.78%, 0.938, 0.7073) were all slightly higher than the 
      LR model (83.33% 0.910, 0.6687). Therefore, clinical application of the ANN model 
      may be able to better predict the folic acid efficacy to HHcy than the 
      traditional LR model. When testing two models in the validation set, we got the 
      same conclusion. This study appears to be the first one to establish the ANN 
      model which added EV-GRS into environmental factors to predict the efficacy of 
      folic acid to HHcy. This model would be able to offer clinicians a new method to 
      make decisions and individual therapeutic plans.
CI  - (c) 2021. The Author(s).
FAU - Chen, Xiaorui
AU  - Chen X
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China.
FAU - Huang, Xiaowen
AU  - Huang X
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China.
FAU - Jie, Diao
AU  - Jie D
AD  - The University of Glasgow, Glasgow, G12 8QQ, Scotland.
FAU - Zheng, Caifang
AU  - Zheng C
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China.
FAU - Wang, Xiliang
AU  - Wang X
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China.
FAU - Zhang, Bowen
AU  - Zhang B
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China.
FAU - Shao, Weihao
AU  - Shao W
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China.
FAU - Wang, Gaili
AU  - Wang G
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China.
FAU - Zhang, Weidong
AU  - Zhang W
AD  - Department of Epidemiology, School of Public Health, Zhengzhou University, 
      Zhengzhou, 450001, Henan, China. imooni@163.com.
LA  - eng
GR  - 132102310431/Science and Technology Department of Henan Province/
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20211102
PL  - England
TA  - Sci Rep
JT  - Scientific reports
JID - 101563288
RN  - 0 (Genetic Markers)
RN  - 935E97BOY8 (Folic Acid)
SB  - IM
MH  - Aged
MH  - *Algorithms
MH  - Female
MH  - Folic Acid/*therapeutic use
MH  - *Genetic Markers
MH  - *Genetic Predisposition to Disease
MH  - Humans
MH  - Hyperhomocysteinemia/*drug therapy/genetics/pathology
MH  - Male
MH  - *Neural Networks, Computer
MH  - Prospective Studies
MH  - Risk Factors
MH  - Treatment Outcome
PMC - PMC8563886
COIS- The authors declare no competing interests.
EDAT- 2021/11/04 06:00
MHDA- 2022/01/27 06:00
PMCR- 2021/11/02
CRDT- 2021/11/03 06:28
PHST- 2021/07/09 00:00 [received]
PHST- 2021/10/07 00:00 [accepted]
PHST- 2021/11/03 06:28 [entrez]
PHST- 2021/11/04 06:00 [pubmed]
PHST- 2022/01/27 06:00 [medline]
PHST- 2021/11/02 00:00 [pmc-release]
AID - 10.1038/s41598-021-00938-8 [pii]
AID - 938 [pii]
AID - 10.1038/s41598-021-00938-8 [doi]
PST - epublish
SO  - Sci Rep. 2021 Nov 2;11(1):21430. doi: 10.1038/s41598-021-00938-8.